WorldWideScience

Sample records for maximum entropy modelling

  1. Nonsymmetric entropy and maximum nonsymmetric entropy principle

    International Nuclear Information System (INIS)

    Liu Chengshi

    2009-01-01

    Under the frame of a statistical model, the concept of nonsymmetric entropy which generalizes the concepts of Boltzmann's entropy and Shannon's entropy, is defined. Maximum nonsymmetric entropy principle is proved. Some important distribution laws such as power law, can be derived from this principle naturally. Especially, nonsymmetric entropy is more convenient than other entropy such as Tsallis's entropy in deriving power laws.

  2. Maximum entropy models of ecosystem functioning

    International Nuclear Information System (INIS)

    Bertram, Jason

    2014-01-01

    Using organism-level traits to deduce community-level relationships is a fundamental problem in theoretical ecology. This problem parallels the physical one of using particle properties to deduce macroscopic thermodynamic laws, which was successfully achieved with the development of statistical physics. Drawing on this parallel, theoretical ecologists from Lotka onwards have attempted to construct statistical mechanistic theories of ecosystem functioning. Jaynes’ broader interpretation of statistical mechanics, which hinges on the entropy maximisation algorithm (MaxEnt), is of central importance here because the classical foundations of statistical physics do not have clear ecological analogues (e.g. phase space, dynamical invariants). However, models based on the information theoretic interpretation of MaxEnt are difficult to interpret ecologically. Here I give a broad discussion of statistical mechanical models of ecosystem functioning and the application of MaxEnt in these models. Emphasising the sample frequency interpretation of MaxEnt, I show that MaxEnt can be used to construct models of ecosystem functioning which are statistical mechanical in the traditional sense using a savanna plant ecology model as an example

  3. Maximum entropy models of ecosystem functioning

    Energy Technology Data Exchange (ETDEWEB)

    Bertram, Jason, E-mail: jason.bertram@anu.edu.au [Research School of Biology, The Australian National University, Canberra ACT 0200 (Australia)

    2014-12-05

    Using organism-level traits to deduce community-level relationships is a fundamental problem in theoretical ecology. This problem parallels the physical one of using particle properties to deduce macroscopic thermodynamic laws, which was successfully achieved with the development of statistical physics. Drawing on this parallel, theoretical ecologists from Lotka onwards have attempted to construct statistical mechanistic theories of ecosystem functioning. Jaynes’ broader interpretation of statistical mechanics, which hinges on the entropy maximisation algorithm (MaxEnt), is of central importance here because the classical foundations of statistical physics do not have clear ecological analogues (e.g. phase space, dynamical invariants). However, models based on the information theoretic interpretation of MaxEnt are difficult to interpret ecologically. Here I give a broad discussion of statistical mechanical models of ecosystem functioning and the application of MaxEnt in these models. Emphasising the sample frequency interpretation of MaxEnt, I show that MaxEnt can be used to construct models of ecosystem functioning which are statistical mechanical in the traditional sense using a savanna plant ecology model as an example.

  4. Modeling multisite streamflow dependence with maximum entropy copula

    Science.gov (United States)

    Hao, Z.; Singh, V. P.

    2013-10-01

    Synthetic streamflows at different sites in a river basin are needed for planning, operation, and management of water resources projects. Modeling the temporal and spatial dependence structure of monthly streamflow at different sites is generally required. In this study, the maximum entropy copula method is proposed for multisite monthly streamflow simulation, in which the temporal and spatial dependence structure is imposed as constraints to derive the maximum entropy copula. The monthly streamflows at different sites are then generated by sampling from the conditional distribution. A case study for the generation of monthly streamflow at three sites in the Colorado River basin illustrates the application of the proposed method. Simulated streamflow from the maximum entropy copula is in satisfactory agreement with observed streamflow.

  5. Stimulus-dependent maximum entropy models of neural population codes.

    Directory of Open Access Journals (Sweden)

    Einat Granot-Atedgi

    Full Text Available Neural populations encode information about their stimulus in a collective fashion, by joint activity patterns of spiking and silence. A full account of this mapping from stimulus to neural activity is given by the conditional probability distribution over neural codewords given the sensory input. For large populations, direct sampling of these distributions is impossible, and so we must rely on constructing appropriate models. We show here that in a population of 100 retinal ganglion cells in the salamander retina responding to temporal white-noise stimuli, dependencies between cells play an important encoding role. We introduce the stimulus-dependent maximum entropy (SDME model-a minimal extension of the canonical linear-nonlinear model of a single neuron, to a pairwise-coupled neural population. We find that the SDME model gives a more accurate account of single cell responses and in particular significantly outperforms uncoupled models in reproducing the distributions of population codewords emitted in response to a stimulus. We show how the SDME model, in conjunction with static maximum entropy models of population vocabulary, can be used to estimate information-theoretic quantities like average surprise and information transmission in a neural population.

  6. Maximum entropy principle and hydrodynamic models in statistical mechanics

    International Nuclear Information System (INIS)

    Trovato, M.; Reggiani, L.

    2012-01-01

    This review presents the state of the art of the maximum entropy principle (MEP) in its classical and quantum (QMEP) formulation. Within the classical MEP we overview a general theory able to provide, in a dynamical context, the macroscopic relevant variables for carrier transport in the presence of electric fields of arbitrary strength. For the macroscopic variables the linearized maximum entropy approach is developed including full-band effects within a total energy scheme. Under spatially homogeneous conditions, we construct a closed set of hydrodynamic equations for the small-signal (dynamic) response of the macroscopic variables. The coupling between the driving field and the energy dissipation is analyzed quantitatively by using an arbitrary number of moments of the distribution function. Analogously, the theoretical approach is applied to many one-dimensional n + nn + submicron Si structures by using different band structure models, different doping profiles, different applied biases and is validated by comparing numerical calculations with ensemble Monte Carlo simulations and with available experimental data. Within the quantum MEP we introduce a quantum entropy functional of the reduced density matrix, the principle of quantum maximum entropy is then asserted as fundamental principle of quantum statistical mechanics. Accordingly, we have developed a comprehensive theoretical formalism to construct rigorously a closed quantum hydrodynamic transport within a Wigner function approach. The theory is formulated both in thermodynamic equilibrium and nonequilibrium conditions, and the quantum contributions are obtained by only assuming that the Lagrange multipliers can be expanded in powers of ħ 2 , being ħ the reduced Planck constant. In particular, by using an arbitrary number of moments, we prove that: i) on a macroscopic scale all nonlocal effects, compatible with the uncertainty principle, are imputable to high-order spatial derivatives both of the

  7. Credal Networks under Maximum Entropy

    OpenAIRE

    Lukasiewicz, Thomas

    2013-01-01

    We apply the principle of maximum entropy to select a unique joint probability distribution from the set of all joint probability distributions specified by a credal network. In detail, we start by showing that the unique joint distribution of a Bayesian tree coincides with the maximum entropy model of its conditional distributions. This result, however, does not hold anymore for general Bayesian networks. We thus present a new kind of maximum entropy models, which are computed sequentially. ...

  8. Maximum Entropy Fundamentals

    Directory of Open Access Journals (Sweden)

    F. Topsøe

    2001-09-01

    Full Text Available Abstract: In its modern formulation, the Maximum Entropy Principle was promoted by E.T. Jaynes, starting in the mid-fifties. The principle dictates that one should look for a distribution, consistent with available information, which maximizes the entropy. However, this principle focuses only on distributions and it appears advantageous to bring information theoretical thinking more prominently into play by also focusing on the "observer" and on coding. This view was brought forward by the second named author in the late seventies and is the view we will follow-up on here. It leads to the consideration of a certain game, the Code Length Game and, via standard game theoretical thinking, to a principle of Game Theoretical Equilibrium. This principle is more basic than the Maximum Entropy Principle in the sense that the search for one type of optimal strategies in the Code Length Game translates directly into the search for distributions with maximum entropy. In the present paper we offer a self-contained and comprehensive treatment of fundamentals of both principles mentioned, based on a study of the Code Length Game. Though new concepts and results are presented, the reading should be instructional and accessible to a rather wide audience, at least if certain mathematical details are left aside at a rst reading. The most frequently studied instance of entropy maximization pertains to the Mean Energy Model which involves a moment constraint related to a given function, here taken to represent "energy". This type of application is very well known from the literature with hundreds of applications pertaining to several different elds and will also here serve as important illustration of the theory. But our approach reaches further, especially regarding the study of continuity properties of the entropy function, and this leads to new results which allow a discussion of models with so-called entropy loss. These results have tempted us to speculate over

  9. A Hybrid Physical and Maximum-Entropy Landslide Susceptibility Model

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    Jerry Davis

    2015-06-01

    Full Text Available The clear need for accurate landslide susceptibility mapping has led to multiple approaches. Physical models are easily interpreted and have high predictive capabilities but rely on spatially explicit and accurate parameterization, which is commonly not possible. Statistical methods can include other factors influencing slope stability such as distance to roads, but rely on good landslide inventories. The maximum entropy (MaxEnt model has been widely and successfully used in species distribution mapping, because data on absence are often uncertain. Similarly, knowledge about the absence of landslides is often limited due to mapping scale or methodology. In this paper a hybrid approach is described that combines the physically-based landslide susceptibility model “Stability INdex MAPping” (SINMAP with MaxEnt. This method is tested in a coastal watershed in Pacifica, CA, USA, with a well-documented landslide history including 3 inventories of 154 scars on 1941 imagery, 142 in 1975, and 253 in 1983. Results indicate that SINMAP alone overestimated susceptibility due to insufficient data on root cohesion. Models were compared using SINMAP stability index (SI or slope alone, and SI or slope in combination with other environmental factors: curvature, a 50-m trail buffer, vegetation, and geology. For 1941 and 1975, using slope alone was similar to using SI alone; however in 1983 SI alone creates an Areas Under the receiver operator Curve (AUC of 0.785, compared with 0.749 for slope alone. In maximum-entropy models created using all environmental factors, the stability index (SI from SINMAP represented the greatest contributions in all three years (1941: 48.1%; 1975: 35.3; and 1983: 48%, with AUC of 0.795, 0822, and 0.859, respectively; however; using slope instead of SI created similar overall AUC values, likely due to the combined effect with plan curvature indicating focused hydrologic inputs and vegetation identifying the effect of root cohesion

  10. Maximum Quantum Entropy Method

    OpenAIRE

    Sim, Jae-Hoon; Han, Myung Joon

    2018-01-01

    Maximum entropy method for analytic continuation is extended by introducing quantum relative entropy. This new method is formulated in terms of matrix-valued functions and therefore invariant under arbitrary unitary transformation of input matrix. As a result, the continuation of off-diagonal elements becomes straightforward. Without introducing any further ambiguity, the Bayesian probabilistic interpretation is maintained just as in the conventional maximum entropy method. The applications o...

  11. On the maximum-entropy/autoregressive modeling of time series

    Science.gov (United States)

    Chao, B. F.

    1984-01-01

    The autoregressive (AR) model of a random process is interpreted in the light of the Prony's relation which relates a complex conjugate pair of poles of the AR process in the z-plane (or the z domain) on the one hand, to the complex frequency of one complex harmonic function in the time domain on the other. Thus the AR model of a time series is one that models the time series as a linear combination of complex harmonic functions, which include pure sinusoids and real exponentials as special cases. An AR model is completely determined by its z-domain pole configuration. The maximum-entropy/autogressive (ME/AR) spectrum, defined on the unit circle of the z-plane (or the frequency domain), is nothing but a convenient, but ambiguous visual representation. It is asserted that the position and shape of a spectral peak is determined by the corresponding complex frequency, and the height of the spectral peak contains little information about the complex amplitude of the complex harmonic functions.

  12. Maximum entropy methods

    International Nuclear Information System (INIS)

    Ponman, T.J.

    1984-01-01

    For some years now two different expressions have been in use for maximum entropy image restoration and there has been some controversy over which one is appropriate for a given problem. Here two further entropies are presented and it is argued that there is no single correct algorithm. The properties of the four different methods are compared using simple 1D simulations with a view to showing how they can be used together to gain as much information as possible about the original object. (orig.)

  13. Maximum entropy production: Can it be used to constrain conceptual hydrological models?

    Science.gov (United States)

    M.C. Westhoff; E. Zehe

    2013-01-01

    In recent years, optimality principles have been proposed to constrain hydrological models. The principle of maximum entropy production (MEP) is one of the proposed principles and is subject of this study. It states that a steady state system is organized in such a way that entropy production is maximized. Although successful applications have been reported in...

  14. Introduction to maximum entropy

    International Nuclear Information System (INIS)

    Sivia, D.S.

    1988-01-01

    The maximum entropy (MaxEnt) principle has been successfully used in image reconstruction in a wide variety of fields. We review the need for such methods in data analysis and show, by use of a very simple example, why MaxEnt is to be preferred over other regularizing functions. This leads to a more general interpretation of the MaxEnt method, and its use is illustrated with several different examples. Practical difficulties with non-linear problems still remain, this being highlighted by the notorious phase problem in crystallography. We conclude with an example from neutron scattering, using data from a filter difference spectrometer to contrast MaxEnt with a conventional deconvolution. 12 refs., 8 figs., 1 tab

  15. Introduction to maximum entropy

    International Nuclear Information System (INIS)

    Sivia, D.S.

    1989-01-01

    The maximum entropy (MaxEnt) principle has been successfully used in image reconstruction in a wide variety of fields. The author reviews the need for such methods in data analysis and shows, by use of a very simple example, why MaxEnt is to be preferred over other regularizing functions. This leads to a more general interpretation of the MaxEnt method, and its use is illustrated with several different examples. Practical difficulties with non-linear problems still remain, this being highlighted by the notorious phase problem in crystallography. He concludes with an example from neutron scattering, using data from a filter difference spectrometer to contrast MaxEnt with a conventional deconvolution. 12 refs., 8 figs., 1 tab

  16. On Maximum Entropy and Inference

    Directory of Open Access Journals (Sweden)

    Luigi Gresele

    2017-11-01

    Full Text Available Maximum entropy is a powerful concept that entails a sharp separation between relevant and irrelevant variables. It is typically invoked in inference, once an assumption is made on what the relevant variables are, in order to estimate a model from data, that affords predictions on all other (dependent variables. Conversely, maximum entropy can be invoked to retrieve the relevant variables (sufficient statistics directly from the data, once a model is identified by Bayesian model selection. We explore this approach in the case of spin models with interactions of arbitrary order, and we discuss how relevant interactions can be inferred. In this perspective, the dimensionality of the inference problem is not set by the number of parameters in the model, but by the frequency distribution of the data. We illustrate the method showing its ability to recover the correct model in a few prototype cases and discuss its application on a real dataset.

  17. Maximum Entropy Discrimination Poisson Regression for Software Reliability Modeling.

    Science.gov (United States)

    Chatzis, Sotirios P; Andreou, Andreas S

    2015-11-01

    Reliably predicting software defects is one of the most significant tasks in software engineering. Two of the major components of modern software reliability modeling approaches are: 1) extraction of salient features for software system representation, based on appropriately designed software metrics and 2) development of intricate regression models for count data, to allow effective software reliability data modeling and prediction. Surprisingly, research in the latter frontier of count data regression modeling has been rather limited. More specifically, a lack of simple and efficient algorithms for posterior computation has made the Bayesian approaches appear unattractive, and thus underdeveloped in the context of software reliability modeling. In this paper, we try to address these issues by introducing a novel Bayesian regression model for count data, based on the concept of max-margin data modeling, effected in the context of a fully Bayesian model treatment with simple and efficient posterior distribution updates. Our novel approach yields a more discriminative learning technique, making more effective use of our training data during model inference. In addition, it allows of better handling uncertainty in the modeled data, which can be a significant problem when the training data are limited. We derive elegant inference algorithms for our model under the mean-field paradigm and exhibit its effectiveness using the publicly available benchmark data sets.

  18. Using maximum entropy modeling to identify and prioritize red spruce forest habitat in West Virginia

    Science.gov (United States)

    Nathan R. Beane; James S. Rentch; Thomas M. Schuler

    2013-01-01

    Red spruce forests in West Virginia are found in island-like distributions at high elevations and provide essential habitat for the endangered Cheat Mountain salamander and the recently delisted Virginia northern flying squirrel. Therefore, it is important to identify restoration priorities of red spruce forests. Maximum entropy modeling was used to identify areas of...

  19. Feasible Histories, Maximum Entropy

    International Nuclear Information System (INIS)

    Pitowsky, I.

    1999-01-01

    We consider the broadest possible consistency condition for a family of histories, which extends all previous proposals. A family that satisfies this condition is called feasible. On each feasible family of histories we choose a probability measure by maximizing entropy, while keeping the probabilities of commuting histories to their quantum mechanical values. This procedure is justified by the assumption that decoherence increases entropy. Finally, a criterion for identifying the nearly classical families is proposed

  20. Maximum entropy tokamak configurations

    International Nuclear Information System (INIS)

    Minardi, E.

    1989-01-01

    The new entropy concept for the collective magnetic equilibria is applied to the description of the states of a tokamak subject to ohmic and auxiliary heating. The condition for the existence of steady state plasma states with vanishing entropy production implies, on one hand, the resilience of specific current density profiles and, on the other, severe restrictions on the scaling of the confinement time with power and current. These restrictions are consistent with Goldston scaling and with the existence of a heat pinch. (author)

  1. Bistability, non-ergodicity, and inhibition in pairwise maximum-entropy models.

    Science.gov (United States)

    Rostami, Vahid; Porta Mana, PierGianLuca; Grün, Sonja; Helias, Moritz

    2017-10-01

    Pairwise maximum-entropy models have been used in neuroscience to predict the activity of neuronal populations, given only the time-averaged correlations of the neuron activities. This paper provides evidence that the pairwise model, applied to experimental recordings, would produce a bimodal distribution for the population-averaged activity, and for some population sizes the second mode would peak at high activities, that experimentally would be equivalent to 90% of the neuron population active within time-windows of few milliseconds. Several problems are connected with this bimodality: 1. The presence of the high-activity mode is unrealistic in view of observed neuronal activity and on neurobiological grounds. 2. Boltzmann learning becomes non-ergodic, hence the pairwise maximum-entropy distribution cannot be found: in fact, Boltzmann learning would produce an incorrect distribution; similarly, common variants of mean-field approximations also produce an incorrect distribution. 3. The Glauber dynamics associated with the model is unrealistically bistable and cannot be used to generate realistic surrogate data. This bimodality problem is first demonstrated for an experimental dataset from 159 neurons in the motor cortex of macaque monkey. Evidence is then provided that this problem affects typical neural recordings of population sizes of a couple of hundreds or more neurons. The cause of the bimodality problem is identified as the inability of standard maximum-entropy distributions with a uniform reference measure to model neuronal inhibition. To eliminate this problem a modified maximum-entropy model is presented, which reflects a basic effect of inhibition in the form of a simple but non-uniform reference measure. This model does not lead to unrealistic bimodalities, can be found with Boltzmann learning, and has an associated Glauber dynamics which incorporates a minimal asymmetric inhibition.

  2. Inferring Pairwise Interactions from Biological Data Using Maximum-Entropy Probability Models.

    Directory of Open Access Journals (Sweden)

    Richard R Stein

    2015-07-01

    Full Text Available Maximum entropy-based inference methods have been successfully used to infer direct interactions from biological datasets such as gene expression data or sequence ensembles. Here, we review undirected pairwise maximum-entropy probability models in two categories of data types, those with continuous and categorical random variables. As a concrete example, we present recently developed inference methods from the field of protein contact prediction and show that a basic set of assumptions leads to similar solution strategies for inferring the model parameters in both variable types. These parameters reflect interactive couplings between observables, which can be used to predict global properties of the biological system. Such methods are applicable to the important problems of protein 3-D structure prediction and association of gene-gene networks, and they enable potential applications to the analysis of gene alteration patterns and to protein design.

  3. The simplest maximum entropy model for collective behavior in a neural network

    International Nuclear Information System (INIS)

    Tkačik, Gašper; Marre, Olivier; Mora, Thierry; Amodei, Dario; Bialek, William; Berry II, Michael J

    2013-01-01

    Recent work emphasizes that the maximum entropy principle provides a bridge between statistical mechanics models for collective behavior in neural networks and experiments on networks of real neurons. Most of this work has focused on capturing the measured correlations among pairs of neurons. Here we suggest an alternative, constructing models that are consistent with the distribution of global network activity, i.e. the probability that K out of N cells in the network generate action potentials in the same small time bin. The inverse problem that we need to solve in constructing the model is analytically tractable, and provides a natural ‘thermodynamics’ for the network in the limit of large N. We analyze the responses of neurons in a small patch of the retina to naturalistic stimuli, and find that the implied thermodynamics is very close to an unusual critical point, in which the entropy (in proper units) is exactly equal to the energy. (paper)

  4. Maximum Entropy in Drug Discovery

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    Chih-Yuan Tseng

    2014-07-01

    Full Text Available Drug discovery applies multidisciplinary approaches either experimentally, computationally or both ways to identify lead compounds to treat various diseases. While conventional approaches have yielded many US Food and Drug Administration (FDA-approved drugs, researchers continue investigating and designing better approaches to increase the success rate in the discovery process. In this article, we provide an overview of the current strategies and point out where and how the method of maximum entropy has been introduced in this area. The maximum entropy principle has its root in thermodynamics, yet since Jaynes’ pioneering work in the 1950s, the maximum entropy principle has not only been used as a physics law, but also as a reasoning tool that allows us to process information in hand with the least bias. Its applicability in various disciplines has been abundantly demonstrated. We give several examples of applications of maximum entropy in different stages of drug discovery. Finally, we discuss a promising new direction in drug discovery that is likely to hinge on the ways of utilizing maximum entropy.

  5. Modelling streambank erosion potential using maximum entropy in a central Appalachian watershed

    Directory of Open Access Journals (Sweden)

    J. Pitchford

    2015-03-01

    Full Text Available We used maximum entropy to model streambank erosion potential (SEP in a central Appalachian watershed to help prioritize sites for management. Model development included measuring erosion rates, application of a quantitative approach to locate Target Eroding Areas (TEAs, and creation of maps of boundary conditions. We successfully constructed a probability distribution of TEAs using the program Maxent. All model evaluation procedures indicated that the model was an excellent predictor, and that the major environmental variables controlling these processes were streambank slope, soil characteristics, bank position, and underlying geology. A classification scheme with low, moderate, and high levels of SEP derived from logistic model output was able to differentiate sites with low erosion potential from sites with moderate and high erosion potential. A major application of this type of modelling framework is to address uncertainty in stream restoration planning, ultimately helping to bridge the gap between restoration science and practice.

  6. Maximum entropy beam diagnostic tomography

    International Nuclear Information System (INIS)

    Mottershead, C.T.

    1985-01-01

    This paper reviews the formalism of maximum entropy beam diagnostic tomography as applied to the Fusion Materials Irradiation Test (FMIT) prototype accelerator. The same formalism has also been used with streak camera data to produce an ultrahigh speed movie of the beam profile of the Experimental Test Accelerator (ETA) at Livermore. 11 refs., 4 figs

  7. Maximum entropy beam diagnostic tomography

    International Nuclear Information System (INIS)

    Mottershead, C.T.

    1985-01-01

    This paper reviews the formalism of maximum entropy beam diagnostic tomography as applied to the Fusion Materials Irradiation Test (FMIT) prototype accelerator. The same formalism has also been used with streak camera data to produce an ultrahigh speed movie of the beam profile of the Experimental Test Accelerator (ETA) at Livermore

  8. How fast can we learn maximum entropy models of neural populations?

    Energy Technology Data Exchange (ETDEWEB)

    Ganmor, Elad; Schneidman, Elad [Department of Neuroscience, Weizmann Institute of Science, Rehovot 76100 (Israel); Segev, Ronen, E-mail: elad.ganmor@weizmann.ac.i, E-mail: elad.schneidman@weizmann.ac.i [Department of Life Sciences and Zlotowski Center for Neuroscience, Ben-Gurion University of the Negev, Beer-Sheva 84105 (Israel)

    2009-12-01

    Most of our knowledge about how the brain encodes information comes from recordings of single neurons. However, computations in the brain are carried out by large groups of neurons. Modelling the joint activity of many interacting elements is computationally hard because of the large number of possible activity patterns and limited experimental data. Recently it was shown in several different neural systems that maximum entropy pairwise models, which rely only on firing rates and pairwise correlations of neurons, are excellent models for the distribution of activity patterns of neural populations, and in particular, their responses to natural stimuli. Using simultaneous recordings of large groups of neurons in the vertebrate retina responding to naturalistic stimuli, we show here that the relevant statistics required for finding the pairwise model can be accurately estimated within seconds. Furthermore, while higher order statistics may, in theory, improve model accuracy, they are, in practice, harmful for times of up to 20 minutes due to sampling noise. Finally, we demonstrate that trading accuracy for entropy may actually improve model performance when data is limited, and suggest an optimization method that automatically adjusts model constraints in order to achieve good performance.

  9. How fast can we learn maximum entropy models of neural populations?

    International Nuclear Information System (INIS)

    Ganmor, Elad; Schneidman, Elad; Segev, Ronen

    2009-01-01

    Most of our knowledge about how the brain encodes information comes from recordings of single neurons. However, computations in the brain are carried out by large groups of neurons. Modelling the joint activity of many interacting elements is computationally hard because of the large number of possible activity patterns and limited experimental data. Recently it was shown in several different neural systems that maximum entropy pairwise models, which rely only on firing rates and pairwise correlations of neurons, are excellent models for the distribution of activity patterns of neural populations, and in particular, their responses to natural stimuli. Using simultaneous recordings of large groups of neurons in the vertebrate retina responding to naturalistic stimuli, we show here that the relevant statistics required for finding the pairwise model can be accurately estimated within seconds. Furthermore, while higher order statistics may, in theory, improve model accuracy, they are, in practice, harmful for times of up to 20 minutes due to sampling noise. Finally, we demonstrate that trading accuracy for entropy may actually improve model performance when data is limited, and suggest an optimization method that automatically adjusts model constraints in order to achieve good performance.

  10. Density estimation by maximum quantum entropy

    International Nuclear Information System (INIS)

    Silver, R.N.; Wallstrom, T.; Martz, H.F.

    1993-01-01

    A new Bayesian method for non-parametric density estimation is proposed, based on a mathematical analogy to quantum statistical physics. The mathematical procedure is related to maximum entropy methods for inverse problems and image reconstruction. The information divergence enforces global smoothing toward default models, convexity, positivity, extensivity and normalization. The novel feature is the replacement of classical entropy by quantum entropy, so that local smoothing is enforced by constraints on differential operators. The linear response of the estimate is proportional to the covariance. The hyperparameters are estimated by type-II maximum likelihood (evidence). The method is demonstrated on textbook data sets

  11. Modeling of the Maximum Entropy Problem as an Optimal Control Problem and its Application to Pdf Estimation of Electricity Price

    Directory of Open Access Journals (Sweden)

    M. E. Haji Abadi

    2013-09-01

    Full Text Available In this paper, the continuous optimal control theory is used to model and solve the maximum entropy problem for a continuous random variable. The maximum entropy principle provides a method to obtain least-biased probability density function (Pdf estimation. In this paper, to find a closed form solution for the maximum entropy problem with any number of moment constraints, the entropy is considered as a functional measure and the moment constraints are considered as the state equations. Therefore, the Pdf estimation problem can be reformulated as the optimal control problem. Finally, the proposed method is applied to estimate the Pdf of the hourly electricity prices of New England and Ontario electricity markets. Obtained results show the efficiency of the proposed method.

  12. Online Robot Dead Reckoning Localization Using Maximum Relative Entropy Optimization With Model Constraints

    International Nuclear Information System (INIS)

    Urniezius, Renaldas

    2011-01-01

    The principle of Maximum relative Entropy optimization was analyzed for dead reckoning localization of a rigid body when observation data of two attached accelerometers was collected. Model constraints were derived from the relationships between the sensors. The experiment's results confirmed that accelerometers each axis' noise can be successfully filtered utilizing dependency between channels and the dependency between time series data. Dependency between channels was used for a priori calculation, and a posteriori distribution was derived utilizing dependency between time series data. There was revisited data of autocalibration experiment by removing the initial assumption that instantaneous rotation axis of a rigid body was known. Performance results confirmed that such an approach could be used for online dead reckoning localization.

  13. Topics in Bayesian statistics and maximum entropy

    International Nuclear Information System (INIS)

    Mutihac, R.; Cicuttin, A.; Cerdeira, A.; Stanciulescu, C.

    1998-12-01

    Notions of Bayesian decision theory and maximum entropy methods are reviewed with particular emphasis on probabilistic inference and Bayesian modeling. The axiomatic approach is considered as the best justification of Bayesian analysis and maximum entropy principle applied in natural sciences. Particular emphasis is put on solving the inverse problem in digital image restoration and Bayesian modeling of neural networks. Further topics addressed briefly include language modeling, neutron scattering, multiuser detection and channel equalization in digital communications, genetic information, and Bayesian court decision-making. (author)

  14. Maximum entropy principal for transportation

    International Nuclear Information System (INIS)

    Bilich, F.; Da Silva, R.

    2008-01-01

    In this work we deal with modeling of the transportation phenomenon for use in the transportation planning process and policy-impact studies. The model developed is based on the dependence concept, i.e., the notion that the probability of a trip starting at origin i is dependent on the probability of a trip ending at destination j given that the factors (such as travel time, cost, etc.) which affect travel between origin i and destination j assume some specific values. The derivation of the solution of the model employs the maximum entropy principle combining a priori multinomial distribution with a trip utility concept. This model is utilized to forecast trip distributions under a variety of policy changes and scenarios. The dependence coefficients are obtained from a regression equation where the functional form is derived based on conditional probability and perception of factors from experimental psychology. The dependence coefficients encode all the information that was previously encoded in the form of constraints. In addition, the dependence coefficients encode information that cannot be expressed in the form of constraints for practical reasons, namely, computational tractability. The equivalence between the standard formulation (i.e., objective function with constraints) and the dependence formulation (i.e., without constraints) is demonstrated. The parameters of the dependence-based trip-distribution model are estimated, and the model is also validated using commercial air travel data in the U.S. In addition, policy impact analyses (such as allowance of supersonic flights inside the U.S. and user surcharge at noise-impacted airports) on air travel are performed.

  15. [Prediction of potential geographic distribution of Lyme disease in Qinghai province with Maximum Entropy model].

    Science.gov (United States)

    Zhang, Lin; Hou, Xuexia; Liu, Huixin; Liu, Wei; Wan, Kanglin; Hao, Qin

    2016-01-01

    To predict the potential geographic distribution of Lyme disease in Qinghai by using Maximum Entropy model (MaxEnt). The sero-diagnosis data of Lyme disease in 6 counties (Huzhu, Zeku, Tongde, Datong, Qilian and Xunhua) and the environmental and anthropogenic data including altitude, human footprint, normalized difference vegetation index (NDVI) and temperature in Qinghai province since 1990 were collected. By using the data of Huzhu Zeku and Tongde, the prediction of potential distribution of Lyme disease in Qinghai was conducted with MaxEnt. The prediction results were compared with the human sero-prevalence of Lyme disease in Datong, Qilian and Xunhua counties in Qinghai. Three hot spots of Lyme disease were predicted in Qinghai, which were all in the east forest areas. Furthermore, the NDVI showed the most important role in the model prediction, followed by human footprint. Datong, Qilian and Xunhua counties were all in eastern Qinghai. Xunhua was in hot spot areaⅡ, Datong was close to the north of hot spot area Ⅲ, while Qilian with lowest sero-prevalence of Lyme disease was not in the hot spot areas. The data were well modeled in MaxEnt (Area Under Curve=0.980). The actual distribution of Lyme disease in Qinghai was in consistent with the results of the model prediction. MaxEnt could be used in predicting the potential distribution patterns of Lyme disease. The distribution of vegetation and the range and intensity of human activity might be related with Lyme disease distribution.

  16. Zipf's law, power laws and maximum entropy

    International Nuclear Information System (INIS)

    Visser, Matt

    2013-01-01

    Zipf's law, and power laws in general, have attracted and continue to attract considerable attention in a wide variety of disciplines—from astronomy to demographics to software structure to economics to linguistics to zoology, and even warfare. A recent model of random group formation (RGF) attempts a general explanation of such phenomena based on Jaynes' notion of maximum entropy applied to a particular choice of cost function. In the present paper I argue that the specific cost function used in the RGF model is in fact unnecessarily complicated, and that power laws can be obtained in a much simpler way by applying maximum entropy ideas directly to the Shannon entropy subject only to a single constraint: that the average of the logarithm of the observable quantity is specified. (paper)

  17. Receiver function estimated by maximum entropy deconvolution

    Institute of Scientific and Technical Information of China (English)

    吴庆举; 田小波; 张乃铃; 李卫平; 曾融生

    2003-01-01

    Maximum entropy deconvolution is presented to estimate receiver function, with the maximum entropy as the rule to determine auto-correlation and cross-correlation functions. The Toeplitz equation and Levinson algorithm are used to calculate the iterative formula of error-predicting filter, and receiver function is then estimated. During extrapolation, reflective coefficient is always less than 1, which keeps maximum entropy deconvolution stable. The maximum entropy of the data outside window increases the resolution of receiver function. Both synthetic and real seismograms show that maximum entropy deconvolution is an effective method to measure receiver function in time-domain.

  18. Predicting the distribution of the Asian tapir in Peninsular Malaysia using maximum entropy modeling.

    Science.gov (United States)

    Clements, Gopalasamy Reuben; Rayan, D Mark; Aziz, Sheema Abdul; Kawanishi, Kae; Traeholt, Carl; Magintan, David; Yazi, Muhammad Fadlli Abdul; Tingley, Reid

    2012-12-01

    In 2008, the IUCN threat status of the Asian tapir (Tapirus indicus) was reclassified from 'vulnerable' to 'endangered'. The latest distribution map from the IUCN Red List suggests that the tapirs' native range is becoming increasingly fragmented in Peninsular Malaysia, but distribution data collected by local researchers suggest a more extensive geographical range. Here, we compile a database of 1261 tapir occurrence records within Peninsular Malaysia, and demonstrate that this species, indeed, has a much broader geographical range than the IUCN range map suggests. However, extreme spatial and temporal bias in these records limits their utility for conservation planning. Therefore, we used maximum entropy (MaxEnt) modeling to elucidate the potential extent of the Asian tapir's occurrence in Peninsular Malaysia while accounting for bias in existing distribution data. Our MaxEnt model predicted that the Asian tapir has a wider geographic range than our fine-scale data and the IUCN range map both suggest. Approximately 37% of Peninsular Malaysia contains potentially suitable tapir habitats. Our results justify a revision to the Asian tapir's extent of occurrence in the IUCN Red List. Furthermore, our modeling demonstrated that selectively logged forests encompass 45% of potentially suitable tapir habitats, underscoring the importance of these habitats for the conservation of this species in Peninsular Malaysia. © 2012 Wiley Publishing Asia Pty Ltd, ISZS and IOZ/CAS.

  19. Predictive modeling and mapping of Malayan Sun Bear (Helarctos malayanus) distribution using maximum entropy.

    Science.gov (United States)

    Nazeri, Mona; Jusoff, Kamaruzaman; Madani, Nima; Mahmud, Ahmad Rodzi; Bahman, Abdul Rani; Kumar, Lalit

    2012-01-01

    One of the available tools for mapping the geographical distribution and potential suitable habitats is species distribution models. These techniques are very helpful for finding poorly known distributions of species in poorly sampled areas, such as the tropics. Maximum Entropy (MaxEnt) is a recently developed modeling method that can be successfully calibrated using a relatively small number of records. In this research, the MaxEnt model was applied to describe the distribution and identify the key factors shaping the potential distribution of the vulnerable Malayan Sun Bear (Helarctos malayanus) in one of the main remaining habitats in Peninsular Malaysia. MaxEnt results showed that even though Malaysian sun bear habitat is tied with tropical evergreen forests, it lives in a marginal threshold of bio-climatic variables. On the other hand, current protected area networks within Peninsular Malaysia do not cover most of the sun bears potential suitable habitats. Assuming that the predicted suitability map covers sun bears actual distribution, future climate change, forest degradation and illegal hunting could potentially severely affect the sun bear's population.

  20. Predictive modeling and mapping of Malayan Sun Bear (Helarctos malayanus distribution using maximum entropy.

    Directory of Open Access Journals (Sweden)

    Mona Nazeri

    Full Text Available One of the available tools for mapping the geographical distribution and potential suitable habitats is species distribution models. These techniques are very helpful for finding poorly known distributions of species in poorly sampled areas, such as the tropics. Maximum Entropy (MaxEnt is a recently developed modeling method that can be successfully calibrated using a relatively small number of records. In this research, the MaxEnt model was applied to describe the distribution and identify the key factors shaping the potential distribution of the vulnerable Malayan Sun Bear (Helarctos malayanus in one of the main remaining habitats in Peninsular Malaysia. MaxEnt results showed that even though Malaysian sun bear habitat is tied with tropical evergreen forests, it lives in a marginal threshold of bio-climatic variables. On the other hand, current protected area networks within Peninsular Malaysia do not cover most of the sun bears potential suitable habitats. Assuming that the predicted suitability map covers sun bears actual distribution, future climate change, forest degradation and illegal hunting could potentially severely affect the sun bear's population.

  1. Maximum-Entropy Models of Sequenced Immune Repertoires Predict Antigen-Antibody Affinity.

    Directory of Open Access Journals (Sweden)

    Lorenzo Asti

    2016-04-01

    Full Text Available The immune system has developed a number of distinct complex mechanisms to shape and control the antibody repertoire. One of these mechanisms, the affinity maturation process, works in an evolutionary-like fashion: after binding to a foreign molecule, the antibody-producing B-cells exhibit a high-frequency mutation rate in the genome region that codes for the antibody active site. Eventually, cells that produce antibodies with higher affinity for their cognate antigen are selected and clonally expanded. Here, we propose a new statistical approach based on maximum entropy modeling in which a scoring function related to the binding affinity of antibodies against a specific antigen is inferred from a sample of sequences of the immune repertoire of an individual. We use our inference strategy to infer a statistical model on a data set obtained by sequencing a fairly large portion of the immune repertoire of an HIV-1 infected patient. The Pearson correlation coefficient between our scoring function and the IC50 neutralization titer measured on 30 different antibodies of known sequence is as high as 0.77 (p-value 10-6, outperforming other sequence- and structure-based models.

  2. A Novel Maximum Entropy Markov Model for Human Facial Expression Recognition.

    Directory of Open Access Journals (Sweden)

    Muhammad Hameed Siddiqi

    Full Text Available Research in video based FER systems has exploded in the past decade. However, most of the previous methods work well when they are trained and tested on the same dataset. Illumination settings, image resolution, camera angle, and physical characteristics of the people differ from one dataset to another. Considering a single dataset keeps the variance, which results from differences, to a minimum. Having a robust FER system, which can work across several datasets, is thus highly desirable. The aim of this work is to design, implement, and validate such a system using different datasets. In this regard, the major contribution is made at the recognition module which uses the maximum entropy Markov model (MEMM for expression recognition. In this model, the states of the human expressions are modeled as the states of an MEMM, by considering the video-sensor observations as the observations of MEMM. A modified Viterbi is utilized to generate the most probable expression state sequence based on such observations. Lastly, an algorithm is designed which predicts the expression state from the generated state sequence. Performance is compared against several existing state-of-the-art FER systems on six publicly available datasets. A weighted average accuracy of 97% is achieved across all datasets.

  3. Using maximum entropy modeling for optimal selection of sampling sites for monitoring networks

    Science.gov (United States)

    Stohlgren, Thomas J.; Kumar, Sunil; Barnett, David T.; Evangelista, Paul H.

    2011-01-01

    Environmental monitoring programs must efficiently describe state shifts. We propose using maximum entropy modeling to select dissimilar sampling sites to capture environmental variability at low cost, and demonstrate a specific application: sample site selection for the Central Plains domain (453,490 km2) of the National Ecological Observatory Network (NEON). We relied on four environmental factors: mean annual temperature and precipitation, elevation, and vegetation type. A “sample site” was defined as a 20 km × 20 km area (equal to NEON’s airborne observation platform [AOP] footprint), within which each 1 km2 cell was evaluated for each environmental factor. After each model run, the most environmentally dissimilar site was selected from all potential sample sites. The iterative selection of eight sites captured approximately 80% of the environmental envelope of the domain, an improvement over stratified random sampling and simple random designs for sample site selection. This approach can be widely used for cost-efficient selection of survey and monitoring sites.

  4. Application of Bayesian Maximum Entropy Filter in parameter calibration of groundwater flow model in PingTung Plain

    Science.gov (United States)

    Cheung, Shao-Yong; Lee, Chieh-Han; Yu, Hwa-Lung

    2017-04-01

    Due to the limited hydrogeological observation data and high levels of uncertainty within, parameter estimation of the groundwater model has been an important issue. There are many methods of parameter estimation, for example, Kalman filter provides a real-time calibration of parameters through measurement of groundwater monitoring wells, related methods such as Extended Kalman Filter and Ensemble Kalman Filter are widely applied in groundwater research. However, Kalman Filter method is limited to linearity. This study propose a novel method, Bayesian Maximum Entropy Filtering, which provides a method that can considers the uncertainty of data in parameter estimation. With this two methods, we can estimate parameter by given hard data (certain) and soft data (uncertain) in the same time. In this study, we use Python and QGIS in groundwater model (MODFLOW) and development of Extended Kalman Filter and Bayesian Maximum Entropy Filtering in Python in parameter estimation. This method may provide a conventional filtering method and also consider the uncertainty of data. This study was conducted through numerical model experiment to explore, combine Bayesian maximum entropy filter and a hypothesis for the architecture of MODFLOW groundwater model numerical estimation. Through the virtual observation wells to simulate and observe the groundwater model periodically. The result showed that considering the uncertainty of data, the Bayesian maximum entropy filter will provide an ideal result of real-time parameters estimation.

  5. A subjective supply–demand model: the maximum Boltzmann/Shannon entropy solution

    International Nuclear Information System (INIS)

    Piotrowski, Edward W; Sładkowski, Jan

    2009-01-01

    The present authors have put forward a projective geometry model of rational trading. The expected (mean) value of the time that is necessary to strike a deal and the profit strongly depend on the strategies adopted. A frequent trader often prefers maximal profit intensity to the maximization of profit resulting from a separate transaction because the gross profit/income is the adopted/recommended benchmark. To investigate activities that have different periods of duration we define, following the queuing theory, the profit intensity as a measure of this economic category. The profit intensity in repeated trading has a unique property of attaining its maximum at a fixed point regardless of the shape of demand curves for a wide class of probability distributions of random reverse transactions (i.e. closing of the position). These conclusions remain valid for an analogous model based on supply analysis. This type of market game is often considered in research aiming at finding an algorithm that maximizes profit of a trader who negotiates prices with the Rest of the World (a collective opponent), possessing a definite and objective supply profile. Such idealization neglects the sometimes important influence of an individual trader on the demand/supply profile of the Rest of the World and in extreme cases questions the very idea of demand/supply profile. Therefore we put forward a trading model in which the demand/supply profile of the Rest of the World induces the (rational) trader to (subjectively) presume that he/she lacks (almost) all knowledge concerning the market but his/her average frequency of trade. This point of view introduces maximum entropy principles into the model and broadens the range of economic phenomena that can be perceived as a sort of thermodynamical system. As a consequence, the profit intensity has a fixed point with an astonishing connection with Fibonacci classical works and looking for the quickest algorithm for obtaining the extremum of a

  6. A subjective supply-demand model: the maximum Boltzmann/Shannon entropy solution

    Science.gov (United States)

    Piotrowski, Edward W.; Sładkowski, Jan

    2009-03-01

    The present authors have put forward a projective geometry model of rational trading. The expected (mean) value of the time that is necessary to strike a deal and the profit strongly depend on the strategies adopted. A frequent trader often prefers maximal profit intensity to the maximization of profit resulting from a separate transaction because the gross profit/income is the adopted/recommended benchmark. To investigate activities that have different periods of duration we define, following the queuing theory, the profit intensity as a measure of this economic category. The profit intensity in repeated trading has a unique property of attaining its maximum at a fixed point regardless of the shape of demand curves for a wide class of probability distributions of random reverse transactions (i.e. closing of the position). These conclusions remain valid for an analogous model based on supply analysis. This type of market game is often considered in research aiming at finding an algorithm that maximizes profit of a trader who negotiates prices with the Rest of the World (a collective opponent), possessing a definite and objective supply profile. Such idealization neglects the sometimes important influence of an individual trader on the demand/supply profile of the Rest of the World and in extreme cases questions the very idea of demand/supply profile. Therefore we put forward a trading model in which the demand/supply profile of the Rest of the World induces the (rational) trader to (subjectively) presume that he/she lacks (almost) all knowledge concerning the market but his/her average frequency of trade. This point of view introduces maximum entropy principles into the model and broadens the range of economic phenomena that can be perceived as a sort of thermodynamical system. As a consequence, the profit intensity has a fixed point with an astonishing connection with Fibonacci classical works and looking for the quickest algorithm for obtaining the extremum of a

  7. Maximum Entropy Production Modeling of Evapotranspiration Partitioning on Heterogeneous Terrain and Canopy Cover: advantages and limitations.

    Science.gov (United States)

    Gutierrez-Jurado, H. A.; Guan, H.; Wang, J.; Wang, H.; Bras, R. L.; Simmons, C. T.

    2015-12-01

    Quantification of evapotranspiration (ET) and its partition over regions of heterogeneous topography and canopy poses a challenge using traditional approaches. In this study, we report the results of a novel field experiment design guided by the Maximum Entropy Production model of ET (MEP-ET), formulated for estimating evaporation and transpiration from homogeneous soil and canopy. A catchment with complex terrain and patchy vegetation in South Australia was instrumented to measure temperature, humidity and net radiation at soil and canopy surfaces. Performance of the MEP-ET model to quantify transpiration and soil evaporation was evaluated during wet and dry conditions with independently and directly measured transpiration from sapflow and soil evaporation using the Bowen Ratio Energy Balance (BREB). MEP-ET transpiration shows remarkable agreement with that obtained through sapflow measurements during wet conditions, but consistently overestimates the flux during dry periods. However, an additional term introduced to the original MEP-ET model accounting for higher stomatal regulation during dry spells, based on differences between leaf and air vapor pressure deficits and temperatures, significantly improves the model performance. On the other hand, MEP-ET soil evaporation is in good agreement with that from BREB regardless of moisture conditions. The experimental design allows a plot and tree scale quantification of evaporation and transpiration respectively. This study confirms for the first time that the MEP-ET originally developed for homogeneous open bare soil and closed canopy can be used for modeling ET over heterogeneous land surfaces. Furthermore, we show that with the addition of an empirical function simulating the plants ability to regulate transpiration, and based on the same measurements of temperature and humidity, the method can produce reliable estimates of ET during both wet and dry conditions without compromising its parsimony.

  8. Maximum entropy PDF projection: A review

    Science.gov (United States)

    Baggenstoss, Paul M.

    2017-06-01

    We review maximum entropy (MaxEnt) PDF projection, a method with wide potential applications in statistical inference. The method constructs a sampling distribution for a high-dimensional vector x based on knowing the sampling distribution p(z) of a lower-dimensional feature z = T (x). Under mild conditions, the distribution p(x) having highest possible entropy among all distributions consistent with p(z) may be readily found. Furthermore, the MaxEnt p(x) may be sampled, making the approach useful in Monte Carlo methods. We review the theorem and present a case study in model order selection and classification for handwritten character recognition.

  9. Quantile-based Bayesian maximum entropy approach for spatiotemporal modeling of ambient air quality levels.

    Science.gov (United States)

    Yu, Hwa-Lung; Wang, Chih-Hsin

    2013-02-05

    Understanding the daily changes in ambient air quality concentrations is important to the assessing human exposure and environmental health. However, the fine temporal scales (e.g., hourly) involved in this assessment often lead to high variability in air quality concentrations. This is because of the complex short-term physical and chemical mechanisms among the pollutants. Consequently, high heterogeneity is usually present in not only the averaged pollution levels, but also the intraday variance levels of the daily observations of ambient concentration across space and time. This characteristic decreases the estimation performance of common techniques. This study proposes a novel quantile-based Bayesian maximum entropy (QBME) method to account for the nonstationary and nonhomogeneous characteristics of ambient air pollution dynamics. The QBME method characterizes the spatiotemporal dependence among the ambient air quality levels based on their location-specific quantiles and accounts for spatiotemporal variations using a local weighted smoothing technique. The epistemic framework of the QBME method can allow researchers to further consider the uncertainty of space-time observations. This study presents the spatiotemporal modeling of daily CO and PM10 concentrations across Taiwan from 1998 to 2009 using the QBME method. Results show that the QBME method can effectively improve estimation accuracy in terms of lower mean absolute errors and standard deviations over space and time, especially for pollutants with strong nonhomogeneous variances across space. In addition, the epistemic framework can allow researchers to assimilate the site-specific secondary information where the observations are absent because of the common preferential sampling issues of environmental data. The proposed QBME method provides a practical and powerful framework for the spatiotemporal modeling of ambient pollutants.

  10. Maximum-entropy description of animal movement.

    Science.gov (United States)

    Fleming, Chris H; Subaşı, Yiğit; Calabrese, Justin M

    2015-03-01

    We introduce a class of maximum-entropy states that naturally includes within it all of the major continuous-time stochastic processes that have been applied to animal movement, including Brownian motion, Ornstein-Uhlenbeck motion, integrated Ornstein-Uhlenbeck motion, a recently discovered hybrid of the previous models, and a new model that describes central-place foraging. We are also able to predict a further hierarchy of new models that will emerge as data quality improves to better resolve the underlying continuity of animal movement. Finally, we also show that Langevin equations must obey a fluctuation-dissipation theorem to generate processes that fall from this class of maximum-entropy distributions when the constraints are purely kinematic.

  11. Maximum entropy and Bayesian methods

    International Nuclear Information System (INIS)

    Smith, C.R.; Erickson, G.J.; Neudorfer, P.O.

    1992-01-01

    Bayesian probability theory and Maximum Entropy methods are at the core of a new view of scientific inference. These 'new' ideas, along with the revolution in computational methods afforded by modern computers allow astronomers, electrical engineers, image processors of any type, NMR chemists and physicists, and anyone at all who has to deal with incomplete and noisy data, to take advantage of methods that, in the past, have been applied only in some areas of theoretical physics. The title workshops have been the focus of a group of researchers from many different fields, and this diversity is evident in this book. There are tutorial and theoretical papers, and applications in a very wide variety of fields. Almost any instance of dealing with incomplete and noisy data can be usefully treated by these methods, and many areas of theoretical research are being enhanced by the thoughtful application of Bayes' theorem. Contributions contained in this volume present a state-of-the-art overview that will be influential and useful for many years to come

  12. Maximum entropy analysis of liquid diffraction data

    International Nuclear Information System (INIS)

    Root, J.H.; Egelstaff, P.A.; Nickel, B.G.

    1986-01-01

    A maximum entropy method for reducing truncation effects in the inverse Fourier transform of structure factor, S(q), to pair correlation function, g(r), is described. The advantages and limitations of the method are explored with the PY hard sphere structure factor as model input data. An example using real data on liquid chlorine, is then presented. It is seen that spurious structure is greatly reduced in comparison to traditional Fourier transform methods. (author)

  13. Maximum entropy analysis of EGRET data

    DEFF Research Database (Denmark)

    Pohl, M.; Strong, A.W.

    1997-01-01

    EGRET data are usually analysed on the basis of the Maximum-Likelihood method \\cite{ma96} in a search for point sources in excess to a model for the background radiation (e.g. \\cite{hu97}). This method depends strongly on the quality of the background model, and thus may have high systematic unce...... uncertainties in region of strong and uncertain background like the Galactic Center region. Here we show images of such regions obtained by the quantified Maximum-Entropy method. We also discuss a possible further use of MEM in the analysis of problematic regions of the sky....

  14. Two-dimensional maximum entropy image restoration

    International Nuclear Information System (INIS)

    Brolley, J.E.; Lazarus, R.B.; Suydam, B.R.; Trussell, H.J.

    1977-07-01

    An optical check problem was constructed to test P LOG P maximum entropy restoration of an extremely distorted image. Useful recovery of the original image was obtained. Comparison with maximum a posteriori restoration is made. 7 figures

  15. Dynamical maximum entropy approach to flocking.

    Science.gov (United States)

    Cavagna, Andrea; Giardina, Irene; Ginelli, Francesco; Mora, Thierry; Piovani, Duccio; Tavarone, Raffaele; Walczak, Aleksandra M

    2014-04-01

    We derive a new method to infer from data the out-of-equilibrium alignment dynamics of collectively moving animal groups, by considering the maximum entropy model distribution consistent with temporal and spatial correlations of flight direction. When bird neighborhoods evolve rapidly, this dynamical inference correctly learns the parameters of the model, while a static one relying only on the spatial correlations fails. When neighbors change slowly and the detailed balance is satisfied, we recover the static procedure. We demonstrate the validity of the method on simulated data. The approach is applicable to other systems of active matter.

  16. The two-box model of climate: limitations and applications to planetary habitability and maximum entropy production studies.

    Science.gov (United States)

    Lorenz, Ralph D

    2010-05-12

    The 'two-box model' of planetary climate is discussed. This model has been used to demonstrate consistency of the equator-pole temperature gradient on Earth, Mars and Titan with what would be predicted from a principle of maximum entropy production (MEP). While useful for exposition and for generating first-order estimates of planetary heat transports, it has too low a resolution to investigate climate systems with strong feedbacks. A two-box MEP model agrees well with the observed day : night temperature contrast observed on the extrasolar planet HD 189733b.

  17. Maximum entropy method in momentum density reconstruction

    International Nuclear Information System (INIS)

    Dobrzynski, L.; Holas, A.

    1997-01-01

    The Maximum Entropy Method (MEM) is applied to the reconstruction of the 3-dimensional electron momentum density distributions observed through the set of Compton profiles measured along various crystallographic directions. It is shown that the reconstruction of electron momentum density may be reliably carried out with the aid of simple iterative algorithm suggested originally by Collins. A number of distributions has been simulated in order to check the performance of MEM. It is shown that MEM can be recommended as a model-free approach. (author). 13 refs, 1 fig

  18. Maximum Entropy: Clearing up Mysteries

    Directory of Open Access Journals (Sweden)

    Marian Grendár

    2001-04-01

    Full Text Available Abstract: There are several mystifications and a couple of mysteries pertinent to MaxEnt. The mystifications, pitfalls and traps are set up mainly by an unfortunate formulation of Jaynes' die problem, the cause célèbre of MaxEnt. After discussing the mystifications a new formulation of the problem is proposed. Then we turn to the mysteries. An answer to the recurring question 'Just what are we accomplishing when we maximize entropy?' [8], based on MaxProb rationale of MaxEnt [6], is recalled. A brief view on the other mystery: 'What is the relation between MaxEnt and the Bayesian method?' [9], in light of the MaxProb rationale of MaxEnt suggests that there is not and cannot be a conflict between MaxEnt and Bayes Theorem.

  19. Assessing suitable area for Acacia dealbata Mill. in the Ceira River Basin (Central Portugal based on maximum entropy modelling approach

    Directory of Open Access Journals (Sweden)

    Jorge Pereira

    2015-12-01

    Full Text Available Biological invasion by exotic organisms became a key issue, a concern associated to the deep impacts on several domains described as resultant from such processes. A better understanding of the processes, the identification of more susceptible areas, and the definition of preventive or mitigation measures are identified as critical for the purpose of reducing associated impacts. The use of species distribution modeling might help on the purpose of identifying areas that are more susceptible to invasion. This paper aims to present preliminary results on assessing the susceptibility to invasion by the exotic species Acacia dealbata Mill. in the Ceira river basin. The results are based on the maximum entropy modeling approach, considered one of the correlative modelling techniques with better predictive performance. Models which validation is based on independent data sets present better performance, an evaluation based on the AUC of ROC accuracy measure.

  20. Weak scale from the maximum entropy principle

    Science.gov (United States)

    Hamada, Yuta; Kawai, Hikaru; Kawana, Kiyoharu

    2015-03-01

    The theory of the multiverse and wormholes suggests that the parameters of the Standard Model (SM) are fixed in such a way that the radiation of the S3 universe at the final stage S_rad becomes maximum, which we call the maximum entropy principle. Although it is difficult to confirm this principle generally, for a few parameters of the SM, we can check whether S_rad actually becomes maximum at the observed values. In this paper, we regard S_rad at the final stage as a function of the weak scale (the Higgs expectation value) vh, and show that it becomes maximum around vh = {{O}} (300 GeV) when the dimensionless couplings in the SM, i.e., the Higgs self-coupling, the gauge couplings, and the Yukawa couplings are fixed. Roughly speaking, we find that the weak scale is given by vh ˜ T_{BBN}2 / (M_{pl}ye5), where ye is the Yukawa coupling of electron, T_BBN is the temperature at which the Big Bang nucleosynthesis starts, and M_pl is the Planck mass.

  1. Deep-sea benthic megafaunal habitat suitability modelling: A global-scale maximum entropy model for xenophyophores

    Science.gov (United States)

    Ashford, Oliver S.; Davies, Andrew J.; Jones, Daniel O. B.

    2014-12-01

    Xenophyophores are a group of exclusively deep-sea agglutinating rhizarian protozoans, at least some of which are foraminifera. They are an important constituent of the deep-sea megafauna that are sometimes found in sufficient abundance to act as a significant source of habitat structure for meiofaunal and macrofaunal organisms. This study utilised maximum entropy modelling (Maxent) and a high-resolution environmental database to explore the environmental factors controlling the presence of Xenophyophorea and two frequently sampled xenophyophore species that are taxonomically stable: Syringammina fragilissima and Stannophyllum zonarium. These factors were also used to predict the global distribution of each taxon. Areas of high habitat suitability for xenophyophores were highlighted throughout the world's oceans, including in a large number of areas yet to be suitably sampled, but the Northeast and Southeast Atlantic Ocean, Gulf of Mexico and Caribbean Sea, the Red Sea and deep-water regions of the Malay Archipelago represented particular hotspots. The two species investigated showed more specific habitat requirements when compared to the model encompassing all xenophyophore records, perhaps in part due to the smaller number and relatively more clustered nature of the presence records available for modelling at present. The environmental variables depth, oxygen parameters, nitrate concentration, carbon-chemistry parameters and temperature were of greatest importance in determining xenophyophore distributions, but, somewhat surprisingly, hydrodynamic parameters were consistently shown to have low importance, possibly due to the paucity of well-resolved global hydrodynamic datasets. The results of this study (and others of a similar type) have the potential to guide further sample collection, environmental policy, and spatial planning of marine protected areas and industrial activities that impact the seafloor, particularly those that overlap with aggregations of

  2. Information Entropy Production of Maximum Entropy Markov Chains from Spike Trains

    Science.gov (United States)

    Cofré, Rodrigo; Maldonado, Cesar

    2018-01-01

    We consider the maximum entropy Markov chain inference approach to characterize the collective statistics of neuronal spike trains, focusing on the statistical properties of the inferred model. We review large deviations techniques useful in this context to describe properties of accuracy and convergence in terms of sampling size. We use these results to study the statistical fluctuation of correlations, distinguishability and irreversibility of maximum entropy Markov chains. We illustrate these applications using simple examples where the large deviation rate function is explicitly obtained for maximum entropy models of relevance in this field.

  3. Combining Experiments and Simulations Using the Maximum Entropy Principle

    DEFF Research Database (Denmark)

    Boomsma, Wouter; Ferkinghoff-Borg, Jesper; Lindorff-Larsen, Kresten

    2014-01-01

    are not in quantitative agreement with experimental data. The principle of maximum entropy is a general procedure for constructing probability distributions in the light of new data, making it a natural tool in cases when an initial model provides results that are at odds with experiments. The number of maximum entropy...... in the context of a simple example, after which we proceed with a real-world application in the field of molecular simulations, where the maximum entropy procedure has recently provided new insight. Given the limited accuracy of force fields, macromolecular simulations sometimes produce results....... Three very recent papers have explored this problem using the maximum entropy approach, providing both new theoretical and practical insights to the problem. We highlight each of these contributions in turn and conclude with a discussion on remaining challenges....

  4. The maximum-entropy method in superspace

    Czech Academy of Sciences Publication Activity Database

    van Smaalen, S.; Palatinus, Lukáš; Schneider, M.

    2003-01-01

    Roč. 59, - (2003), s. 459-469 ISSN 0108-7673 Grant - others:DFG(DE) XX Institutional research plan: CEZ:AV0Z1010914 Keywords : maximum-entropy method, * aperiodic crystals * electron density Subject RIV: BM - Solid Matter Physics ; Magnetism Impact factor: 1.558, year: 2003

  5. Objective Bayesianism and the Maximum Entropy Principle

    Directory of Open Access Journals (Sweden)

    Jon Williamson

    2013-09-01

    Full Text Available Objective Bayesian epistemology invokes three norms: the strengths of our beliefs should be probabilities; they should be calibrated to our evidence of physical probabilities; and they should otherwise equivocate sufficiently between the basic propositions that we can express. The three norms are sometimes explicated by appealing to the maximum entropy principle, which says that a belief function should be a probability function, from all those that are calibrated to evidence, that has maximum entropy. However, the three norms of objective Bayesianism are usually justified in different ways. In this paper, we show that the three norms can all be subsumed under a single justification in terms of minimising worst-case expected loss. This, in turn, is equivalent to maximising a generalised notion of entropy. We suggest that requiring language invariance, in addition to minimising worst-case expected loss, motivates maximisation of standard entropy as opposed to maximisation of other instances of generalised entropy. Our argument also provides a qualified justification for updating degrees of belief by Bayesian conditionalisation. However, conditional probabilities play a less central part in the objective Bayesian account than they do under the subjective view of Bayesianism, leading to a reduced role for Bayes’ Theorem.

  6. Maximum entropy decomposition of quadrupole mass spectra

    International Nuclear Information System (INIS)

    Toussaint, U. von; Dose, V.; Golan, A.

    2004-01-01

    We present an information-theoretic method called generalized maximum entropy (GME) for decomposing mass spectra of gas mixtures from noisy measurements. In this GME approach to the noisy, underdetermined inverse problem, the joint entropies of concentration, cracking, and noise probabilities are maximized subject to the measured data. This provides a robust estimation for the unknown cracking patterns and the concentrations of the contributing molecules. The method is applied to mass spectroscopic data of hydrocarbons, and the estimates are compared with those received from a Bayesian approach. We show that the GME method is efficient and is computationally fast

  7. The maximum entropy production and maximum Shannon information entropy in enzyme kinetics

    Science.gov (United States)

    Dobovišek, Andrej; Markovič, Rene; Brumen, Milan; Fajmut, Aleš

    2018-04-01

    We demonstrate that the maximum entropy production principle (MEPP) serves as a physical selection principle for the description of the most probable non-equilibrium steady states in simple enzymatic reactions. A theoretical approach is developed, which enables maximization of the density of entropy production with respect to the enzyme rate constants for the enzyme reaction in a steady state. Mass and Gibbs free energy conservations are considered as optimization constraints. In such a way computed optimal enzyme rate constants in a steady state yield also the most uniform probability distribution of the enzyme states. This accounts for the maximal Shannon information entropy. By means of the stability analysis it is also demonstrated that maximal density of entropy production in that enzyme reaction requires flexible enzyme structure, which enables rapid transitions between different enzyme states. These results are supported by an example, in which density of entropy production and Shannon information entropy are numerically maximized for the enzyme Glucose Isomerase.

  8. Bayesian maximum entropy integration of ozone observations and model predictions: an application for attainment demonstration in North Carolina.

    Science.gov (United States)

    de Nazelle, Audrey; Arunachalam, Saravanan; Serre, Marc L

    2010-08-01

    States in the USA are required to demonstrate future compliance of criteria air pollutant standards by using both air quality monitors and model outputs. In the case of ozone, the demonstration tests aim at relying heavily on measured values, due to their perceived objectivity and enforceable quality. Weight given to numerical models is diminished by integrating them in the calculations only in a relative sense. For unmonitored locations, the EPA has suggested the use of a spatial interpolation technique to assign current values. We demonstrate that this approach may lead to erroneous assignments of nonattainment and may make it difficult for States to establish future compliance. We propose a method that combines different sources of information to map air pollution, using the Bayesian Maximum Entropy (BME) Framework. The approach gives precedence to measured values and integrates modeled data as a function of model performance. We demonstrate this approach in North Carolina, using the State's ozone monitoring network in combination with outputs from the Multiscale Air Quality Simulation Platform (MAQSIP) modeling system. We show that the BME data integration approach, compared to a spatial interpolation of measured data, improves the accuracy and the precision of ozone estimations across the state.

  9. Maximum entropy production rate in quantum thermodynamics

    Energy Technology Data Exchange (ETDEWEB)

    Beretta, Gian Paolo, E-mail: beretta@ing.unibs.i [Universita di Brescia, via Branze 38, 25123 Brescia (Italy)

    2010-06-01

    In the framework of the recent quest for well-behaved nonlinear extensions of the traditional Schroedinger-von Neumann unitary dynamics that could provide fundamental explanations of recent experimental evidence of loss of quantum coherence at the microscopic level, a recent paper [Gheorghiu-Svirschevski 2001 Phys. Rev. A 63 054102] reproposes the nonlinear equation of motion proposed by the present author [see Beretta G P 1987 Found. Phys. 17 365 and references therein] for quantum (thermo)dynamics of a single isolated indivisible constituent system, such as a single particle, qubit, qudit, spin or atomic system, or a Bose-Einstein or Fermi-Dirac field. As already proved, such nonlinear dynamics entails a fundamental unifying microscopic proof and extension of Onsager's reciprocity and Callen's fluctuation-dissipation relations to all nonequilibrium states, close and far from thermodynamic equilibrium. In this paper we propose a brief but self-contained review of the main results already proved, including the explicit geometrical construction of the equation of motion from the steepest-entropy-ascent ansatz and its exact mathematical and conceptual equivalence with the maximal-entropy-generation variational-principle formulation presented in Gheorghiu-Svirschevski S 2001 Phys. Rev. A 63 022105. Moreover, we show how it can be extended to the case of a composite system to obtain the general form of the equation of motion, consistent with the demanding requirements of strong separability and of compatibility with general thermodynamics principles. The irreversible term in the equation of motion describes the spontaneous attraction of the state operator in the direction of steepest entropy ascent, thus implementing the maximum entropy production principle in quantum theory. The time rate at which the path of steepest entropy ascent is followed has so far been left unspecified. As a step towards the identification of such rate, here we propose a possible

  10. Pareto versus lognormal: a maximum entropy test.

    Science.gov (United States)

    Bee, Marco; Riccaboni, Massimo; Schiavo, Stefano

    2011-08-01

    It is commonly found that distributions that seem to be lognormal over a broad range change to a power-law (Pareto) distribution for the last few percentiles. The distributions of many physical, natural, and social events (earthquake size, species abundance, income and wealth, as well as file, city, and firm sizes) display this structure. We present a test for the occurrence of power-law tails in statistical distributions based on maximum entropy. This methodology allows one to identify the true data-generating processes even in the case when it is neither lognormal nor Pareto. The maximum entropy approach is then compared with other widely used methods and applied to different levels of aggregation of complex systems. Our results provide support for the theory that distributions with lognormal body and Pareto tail can be generated as mixtures of lognormally distributed units.

  11. Maximum entropy perception-action space: a Bayesian model of eye movement selection

    OpenAIRE

    Colas , Francis; Bessière , Pierre; Girard , Benoît

    2010-01-01

    International audience; In this article, we investigate the issue of the selection of eye movements in a free-eye Multiple Object Tracking task. We propose a Bayesian model of retinotopic maps with a complex logarithmic mapping. This model is structured in two parts: a representation of the visual scene, and a decision model based on the representation. We compare different decision models based on different features of the representation and we show that taking into account uncertainty helps...

  12. Automatic maximum entropy spectral reconstruction in NMR

    International Nuclear Information System (INIS)

    Mobli, Mehdi; Maciejewski, Mark W.; Gryk, Michael R.; Hoch, Jeffrey C.

    2007-01-01

    Developments in superconducting magnets, cryogenic probes, isotope labeling strategies, and sophisticated pulse sequences together have enabled the application, in principle, of high-resolution NMR spectroscopy to biomolecular systems approaching 1 megadalton. In practice, however, conventional approaches to NMR that utilize the fast Fourier transform, which require data collected at uniform time intervals, result in prohibitively lengthy data collection times in order to achieve the full resolution afforded by high field magnets. A variety of approaches that involve nonuniform sampling have been proposed, each utilizing a non-Fourier method of spectrum analysis. A very general non-Fourier method that is capable of utilizing data collected using any of the proposed nonuniform sampling strategies is maximum entropy reconstruction. A limiting factor in the adoption of maximum entropy reconstruction in NMR has been the need to specify non-intuitive parameters. Here we describe a fully automated system for maximum entropy reconstruction that requires no user-specified parameters. A web-accessible script generator provides the user interface to the system

  13. Automatically quantifying the scientific quality and sensationalism of news records mentioning pandemics: validating a maximum entropy machine-learning model.

    Science.gov (United States)

    Hoffman, Steven J; Justicz, Victoria

    2016-07-01

    To develop and validate a method for automatically quantifying the scientific quality and sensationalism of individual news records. After retrieving 163,433 news records mentioning the Severe Acute Respiratory Syndrome (SARS) and H1N1 pandemics, a maximum entropy model for inductive machine learning was used to identify relationships among 500 randomly sampled news records that correlated with systematic human assessments of their scientific quality and sensationalism. These relationships were then computationally applied to automatically classify 10,000 additional randomly sampled news records. The model was validated by randomly sampling 200 records and comparing human assessments of them to the computer assessments. The computer model correctly assessed the relevance of 86% of news records, the quality of 65% of records, and the sensationalism of 73% of records, as compared to human assessments. Overall, the scientific quality of SARS and H1N1 news media coverage had potentially important shortcomings, but coverage was not too sensationalizing. Coverage slightly improved between the two pandemics. Automated methods can evaluate news records faster, cheaper, and possibly better than humans. The specific procedure implemented in this study can at the very least identify subsets of news records that are far more likely to have particular scientific and discursive qualities. Copyright © 2016 Elsevier Inc. All rights reserved.

  14. A Maximum Entropy Method for a Robust Portfolio Problem

    Directory of Open Access Journals (Sweden)

    Yingying Xu

    2014-06-01

    Full Text Available We propose a continuous maximum entropy method to investigate the robustoptimal portfolio selection problem for the market with transaction costs and dividends.This robust model aims to maximize the worst-case portfolio return in the case that allof asset returns lie within some prescribed intervals. A numerical optimal solution tothe problem is obtained by using a continuous maximum entropy method. Furthermore,some numerical experiments indicate that the robust model in this paper can result in betterportfolio performance than a classical mean-variance model.

  15. A maximum entropy model for predicting wild boar distribution in Spain

    Directory of Open Access Journals (Sweden)

    Jaime Bosch

    2014-09-01

    Full Text Available Wild boar (Sus scrofa populations in many areas of the Palearctic including the Iberian Peninsula have grown continuously over the last century. This increase has led to numerous different types of conflicts due to the damage these mammals can cause to agriculture, the problems they create in the conservation of natural areas, and the threat they pose to animal health. In the context of both wildlife management and the design of health programs for disease control, it is essential to know how wild boar are distributed on a large spatial scale. Given that the quantifying of the distribution of wild species using census techniques is virtually impossible in the case of large-scale studies, modeling techniques have thus to be used instead to estimate animals’ distributions, densities, and abundances. In this study, the potential distribution of wild boar in Spain was predicted by integrating data of presence and environmental variables into a MaxEnt approach. We built and tested models using 100 bootstrapped replicates. For each replicate or simulation, presence data was divided into two subsets that were used for model fitting (60% of the data and cross-validation (40% of the data. The final model was found to be accurate with an area under the receiver operating characteristic curve (AUC value of 0.79. Six explanatory variables for predicting wild boar distribution were identified on the basis of the percentage of their contribution to the model. The model exhibited a high degree of predictive accuracy, which has been confirmed by its agreement with satellite images and field surveys.

  16. Maximum entropy modeling of invasive plants in the forests of Cumberland Plateau and Mountain Region

    Science.gov (United States)

    Dawn Lemke; Philip Hulme; Jennifer Brown; Wubishet. Tadesse

    2011-01-01

    As anthropogenic influences on the landscape change the composition of 'natural' areas, it is important that we apply spatial technology in active management to mitigate human impact. This research explores the integration of geographic information systems (GIS) and remote sensing with statistical analysis to assist in modeling the distribution of invasive...

  17. Choosing between Higher Moment Maximum Entropy Models and Its Application to Homogeneous Point Processes with Random Effects

    Directory of Open Access Journals (Sweden)

    Lotfi Khribi

    2017-12-01

    Full Text Available In the Bayesian framework, the usual choice of prior in the prediction of homogeneous Poisson processes with random effects is the gamma one. Here, we propose the use of higher order maximum entropy priors. Their advantage is illustrated in a simulation study and the choice of the best order is established by two goodness-of-fit criteria: Kullback–Leibler divergence and a discrepancy measure. This procedure is illustrated on a warranty data set from the automobile industry.

  18. Predicting Changes in Macrophyte Community Structure from Functional Traits in a Freshwater Lake: A Test of Maximum Entropy Model

    Science.gov (United States)

    Fu, Hui; Zhong, Jiayou; Yuan, Guixiang; Guo, Chunjing; Lou, Qian; Zhang, Wei; Xu, Jun; Ni, Leyi; Xie, Ping; Cao, Te

    2015-01-01

    Trait-based approaches have been widely applied to investigate how community dynamics respond to environmental gradients. In this study, we applied a series of maximum entropy (maxent) models incorporating functional traits to unravel the processes governing macrophyte community structure along water depth gradient in a freshwater lake. We sampled 42 plots and 1513 individual plants, and measured 16 functional traits and abundance of 17 macrophyte species. Study results showed that maxent model can be highly robust (99.8%) in predicting the species relative abundance of macrophytes with observed community-weighted mean (CWM) traits as the constraints, while relative low (about 30%) with CWM traits fitted from water depth gradient as the constraints. The measured traits showed notably distinct importance in predicting species abundances, with lowest for perennial growth form and highest for leaf dry mass content. For tuber and leaf nitrogen content, there were significant shifts in their effects on species relative abundance from positive in shallow water to negative in deep water. This result suggests that macrophyte species with tuber organ and greater leaf nitrogen content would become more abundant in shallow water, but would become less abundant in deep water. Our study highlights how functional traits distributed across gradients provide a robust path towards predictive community ecology. PMID:26167856

  19. Human Brain Networks: Spiking Neuron Models, Multistability, Synchronization, Thermodynamics, Maximum Entropy Production, and Anesthetic Cascade Mechanisms

    Directory of Open Access Journals (Sweden)

    Wassim M. Haddad

    2014-07-01

    Full Text Available Advances in neuroscience have been closely linked to mathematical modeling beginning with the integrate-and-fire model of Lapicque and proceeding through the modeling of the action potential by Hodgkin and Huxley to the current era. The fundamental building block of the central nervous system, the neuron, may be thought of as a dynamic element that is “excitable”, and can generate a pulse or spike whenever the electrochemical potential across the cell membrane of the neuron exceeds a threshold. A key application of nonlinear dynamical systems theory to the neurosciences is to study phenomena of the central nervous system that exhibit nearly discontinuous transitions between macroscopic states. A very challenging and clinically important problem exhibiting this phenomenon is the induction of general anesthesia. In any specific patient, the transition from consciousness to unconsciousness as the concentration of anesthetic drugs increases is very sharp, resembling a thermodynamic phase transition. This paper focuses on multistability theory for continuous and discontinuous dynamical systems having a set of multiple isolated equilibria and/or a continuum of equilibria. Multistability is the property whereby the solutions of a dynamical system can alternate between two or more mutually exclusive Lyapunov stable and convergent equilibrium states under asymptotically slowly changing inputs or system parameters. In this paper, we extend the theory of multistability to continuous, discontinuous, and stochastic nonlinear dynamical systems. In particular, Lyapunov-based tests for multistability and synchronization of dynamical systems with continuously differentiable and absolutely continuous flows are established. The results are then applied to excitatory and inhibitory biological neuronal networks to explain the underlying mechanism of action for anesthesia and consciousness from a multistable dynamical system perspective, thereby providing a

  20. Maximum-Entropy Models of Sequenced Immune Repertoires Predict Antigen-Antibody Affinity

    DEFF Research Database (Denmark)

    Asti, Lorenzo; Uguzzoni, Guido; Marcatili, Paolo

    2016-01-01

    The immune system has developed a number of distinct complex mechanisms to shape and control the antibody repertoire. One of these mechanisms, the affinity maturation process, works in an evolutionary-like fashion: after binding to a foreign molecule, the antibody-producing B-cells exhibit a high...... of an HIV-1 infected patient. The Pearson correlation coefficient between our scoring function and the IC50 neutralization titer measured on 30 different antibodies of known sequence is as high as 0.77 (p-value 10-6), outperforming other sequence- and structure-based models....

  1. Predicting the current and future potential distributions of lymphatic filariasis in Africa using maximum entropy ecological niche modelling.

    Directory of Open Access Journals (Sweden)

    Hannah Slater

    Full Text Available Modelling the spatial distributions of human parasite species is crucial to understanding the environmental determinants of infection as well as for guiding the planning of control programmes. Here, we use ecological niche modelling to map the current potential distribution of the macroparasitic disease, lymphatic filariasis (LF, in Africa, and to estimate how future changes in climate and population could affect its spread and burden across the continent. We used 508 community-specific infection presence data collated from the published literature in conjunction with five predictive environmental/climatic and demographic variables, and a maximum entropy niche modelling method to construct the first ecological niche maps describing potential distribution and burden of LF in Africa. We also ran the best-fit model against climate projections made by the HADCM3 and CCCMA models for 2050 under A2a and B2a scenarios to simulate the likely distribution of LF under future climate and population changes. We predict a broad geographic distribution of LF in Africa extending from the west to the east across the middle region of the continent, with high probabilities of occurrence in the Western Africa compared to large areas of medium probability interspersed with smaller areas of high probability in Central and Eastern Africa and in Madagascar. We uncovered complex relationships between predictor ecological niche variables and the probability of LF occurrence. We show for the first time that predicted climate change and population growth will expand both the range and risk of LF infection (and ultimately disease in an endemic region. We estimate that populations at risk to LF may range from 543 and 804 million currently, and that this could rise to between 1.65 to 1.86 billion in the future depending on the climate scenario used and thresholds applied to signify infection presence.

  2. Maximum entropy deconvolution of low count nuclear medicine images

    International Nuclear Information System (INIS)

    McGrath, D.M.

    1998-12-01

    Maximum entropy is applied to the problem of deconvolving nuclear medicine images, with special consideration for very low count data. The physics of the formation of scintigraphic images is described, illustrating the phenomena which degrade planar estimates of the tracer distribution. Various techniques which are used to restore these images are reviewed, outlining the relative merits of each. The development and theoretical justification of maximum entropy as an image processing technique is discussed. Maximum entropy is then applied to the problem of planar deconvolution, highlighting the question of the choice of error parameters for low count data. A novel iterative version of the algorithm is suggested which allows the errors to be estimated from the predicted Poisson mean values. This method is shown to produce the exact results predicted by combining Poisson statistics and a Bayesian interpretation of the maximum entropy approach. A facility for total count preservation has also been incorporated, leading to improved quantification. In order to evaluate this iterative maximum entropy technique, two comparable methods, Wiener filtering and a novel Bayesian maximum likelihood expectation maximisation technique, were implemented. The comparison of results obtained indicated that this maximum entropy approach may produce equivalent or better measures of image quality than the compared methods, depending upon the accuracy of the system model used. The novel Bayesian maximum likelihood expectation maximisation technique was shown to be preferable over many existing maximum a posteriori methods due to its simplicity of implementation. A single parameter is required to define the Bayesian prior, which suppresses noise in the solution and may reduce the processing time substantially. Finally, maximum entropy deconvolution was applied as a pre-processing step in single photon emission computed tomography reconstruction of low count data. Higher contrast results were

  3. A spatiotemporal dengue fever early warning model accounting for nonlinear associations with meteorological factors: a Bayesian maximum entropy approach

    Science.gov (United States)

    Lee, Chieh-Han; Yu, Hwa-Lung; Chien, Lung-Chang

    2014-05-01

    Dengue fever has been identified as one of the most widespread vector-borne diseases in tropical and sub-tropical. In the last decade, dengue is an emerging infectious disease epidemic in Taiwan especially in the southern area where have annually high incidences. For the purpose of disease prevention and control, an early warning system is urgently needed. Previous studies have showed significant relationships between climate variables, in particular, rainfall and temperature, and the temporal epidemic patterns of dengue cases. However, the transmission of the dengue fever is a complex interactive process that mostly understated the composite space-time effects of dengue fever. This study proposes developing a one-week ahead warning system of dengue fever epidemics in the southern Taiwan that considered nonlinear associations between weekly dengue cases and meteorological factors across space and time. The early warning system based on an integration of distributed lag nonlinear model (DLNM) and stochastic Bayesian Maximum Entropy (BME) analysis. The study identified the most significant meteorological measures including weekly minimum temperature and maximum 24-hour rainfall with continuous 15-week lagged time to dengue cases variation under condition of uncertainty. Subsequently, the combination of nonlinear lagged effects of climate variables and space-time dependence function is implemented via a Bayesian framework to predict dengue fever occurrences in the southern Taiwan during 2012. The result shows the early warning system is useful for providing potential outbreak spatio-temporal prediction of dengue fever distribution. In conclusion, the proposed approach can provide a practical disease control tool for environmental regulators seeking more effective strategies for dengue fever prevention.

  4. Maximum entropy reconstruction of spin densities involving non uniform prior

    International Nuclear Information System (INIS)

    Schweizer, J.; Ressouche, E.; Papoular, R.J.; Zheludev, A.I.

    1997-01-01

    Diffraction experiments give microscopic information on structures in crystals. A method which uses the concept of maximum of entropy (MaxEnt), appears to be a formidable improvement in the treatment of diffraction data. This method is based on a bayesian approach: among all the maps compatible with the experimental data, it selects that one which has the highest prior (intrinsic) probability. Considering that all the points of the map are equally probable, this probability (flat prior) is expressed via the Boltzman entropy of the distribution. This method has been used for the reconstruction of charge densities from X-ray data, for maps of nuclear densities from unpolarized neutron data as well as for distributions of spin density. The density maps obtained by this method, as compared to those resulting from the usual inverse Fourier transformation, are tremendously improved. In particular, any substantial deviation from the background is really contained in the data, as it costs entropy compared to a map that would ignore such features. However, in most of the cases, before the measurements are performed, some knowledge exists about the distribution which is investigated. It can range from the simple information of the type of scattering electrons to an elaborate theoretical model. In these cases, the uniform prior which considers all the different pixels as equally likely, is too weak a requirement and has to be replaced. In a rigorous bayesian analysis, Skilling has shown that prior knowledge can be encoded into the Maximum Entropy formalism through a model m(rvec r), via a new definition for the entropy given in this paper. In the absence of any data, the maximum of the entropy functional is reached for ρ(rvec r) = m(rvec r). Any substantial departure from the model, observed in the final map, is really contained in the data as, with the new definition, it costs entropy. This paper presents illustrations of model testing

  5. Neutron spectra unfolding with maximum entropy and maximum likelihood

    International Nuclear Information System (INIS)

    Itoh, Shikoh; Tsunoda, Toshiharu

    1989-01-01

    A new unfolding theory has been established on the basis of the maximum entropy principle and the maximum likelihood method. This theory correctly embodies the Poisson statistics of neutron detection, and always brings a positive solution over the whole energy range. Moreover, the theory unifies both problems of overdetermined and of underdetermined. For the latter, the ambiguity in assigning a prior probability, i.e. the initial guess in the Bayesian sense, has become extinct by virtue of the principle. An approximate expression of the covariance matrix for the resultant spectra is also presented. An efficient algorithm to solve the nonlinear system, which appears in the present study, has been established. Results of computer simulation showed the effectiveness of the present theory. (author)

  6. Mapping the Global Potential Geographical Distribution of Black Locust (Robinia Pseudoacacia L. Using Herbarium Data and a Maximum Entropy Model

    Directory of Open Access Journals (Sweden)

    Guoqing Li

    2014-11-01

    Full Text Available Black locust (Robinia pseudoacacia L. is a tree species of high economic and ecological value, but is also considered to be highly invasive. Understanding the global potential distribution and ecological characteristics of this species is a prerequisite for its practical exploitation as a resource. Here, a maximum entropy modeling (MaxEnt was used to simulate the potential distribution of this species around the world, and the dominant climatic factors affecting its distribution were selected by using a jackknife test and the regularized gain change during each iteration of the training algorithm. The results show that the MaxEnt model performs better than random, with an average test AUC value of 0.9165 (±0.0088. The coldness index, annual mean temperature and warmth index were the most important climatic factors affecting the species distribution, explaining 65.79% of the variability in the geographical distribution. Species response curves showed unimodal relationships with the annual mean temperature and warmth index, whereas there was a linear relationship with the coldness index. The dominant climatic conditions in the core of the black locust distribution are a coldness index of −9.8 °C–0 °C, an annual mean temperature of 5.8 °C–14.5 °C, a warmth index of 66 °C–168 °C and an annual precipitation of 508–1867 mm. The potential distribution of black locust is located mainly in the United States, the United Kingdom, Germany, France, the Netherlands, Belgium, Italy, Switzerland, Australia, New Zealand, China, Japan, South Korea, South Africa, Chile and Argentina. The predictive map of black locust, climatic thresholds and species response curves can provide globally applicable guidelines and valuable information for policymakers and planners involved in the introduction, planting and invasion control of this species around the world.

  7. Binary versus non-binary information in real time series: empirical results and maximum-entropy matrix models

    Science.gov (United States)

    Almog, Assaf; Garlaschelli, Diego

    2014-09-01

    The dynamics of complex systems, from financial markets to the brain, can be monitored in terms of multiple time series of activity of the constituent units, such as stocks or neurons, respectively. While the main focus of time series analysis is on the magnitude of temporal increments, a significant piece of information is encoded into the binary projection (i.e. the sign) of such increments. In this paper we provide further evidence of this by showing strong nonlinear relations between binary and non-binary properties of financial time series. These relations are a novel quantification of the fact that extreme price increments occur more often when most stocks move in the same direction. We then introduce an information-theoretic approach to the analysis of the binary signature of single and multiple time series. Through the definition of maximum-entropy ensembles of binary matrices and their mapping to spin models in statistical physics, we quantify the information encoded into the simplest binary properties of real time series and identify the most informative property given a set of measurements. Our formalism is able to accurately replicate, and mathematically characterize, the observed binary/non-binary relations. We also obtain a phase diagram allowing us to identify, based only on the instantaneous aggregate return of a set of multiple time series, a regime where the so-called ‘market mode’ has an optimal interpretation in terms of collective (endogenous) effects, a regime where it is parsimoniously explained by pure noise, and a regime where it can be regarded as a combination of endogenous and exogenous factors. Our approach allows us to connect spin models, simple stochastic processes, and ensembles of time series inferred from partial information.

  8. Binary versus non-binary information in real time series: empirical results and maximum-entropy matrix models

    International Nuclear Information System (INIS)

    Almog, Assaf; Garlaschelli, Diego

    2014-01-01

    The dynamics of complex systems, from financial markets to the brain, can be monitored in terms of multiple time series of activity of the constituent units, such as stocks or neurons, respectively. While the main focus of time series analysis is on the magnitude of temporal increments, a significant piece of information is encoded into the binary projection (i.e. the sign) of such increments. In this paper we provide further evidence of this by showing strong nonlinear relations between binary and non-binary properties of financial time series. These relations are a novel quantification of the fact that extreme price increments occur more often when most stocks move in the same direction. We then introduce an information-theoretic approach to the analysis of the binary signature of single and multiple time series. Through the definition of maximum-entropy ensembles of binary matrices and their mapping to spin models in statistical physics, we quantify the information encoded into the simplest binary properties of real time series and identify the most informative property given a set of measurements. Our formalism is able to accurately replicate, and mathematically characterize, the observed binary/non-binary relations. We also obtain a phase diagram allowing us to identify, based only on the instantaneous aggregate return of a set of multiple time series, a regime where the so-called ‘market mode’ has an optimal interpretation in terms of collective (endogenous) effects, a regime where it is parsimoniously explained by pure noise, and a regime where it can be regarded as a combination of endogenous and exogenous factors. Our approach allows us to connect spin models, simple stochastic processes, and ensembles of time series inferred from partial information. (paper)

  9. Mapping distribution of Rastrelliger kanagurta in the exclusive economic zone (EEZ) of Malaysia using maximum entropy modeling approach

    Science.gov (United States)

    Yusop, Syazwani Mohd; Mustapha, Muzzneena Ahmad

    2018-04-01

    The coupling of fishing locations for R. kanagurta obtained from SEAFDEC and multi-sensor satellite imageries of oceanographic variables; sea surface temperature (SST), sea surface height (SSH) and chl-a concentration (chl-a) were utilized to evaluate the performance of maximum entropy (MaxEnt) models for R. kanagurta fishing ground for prediction. Besides, this study was conducted to identify the relative percentage contribution of each environmental variable considered in order to describe the effects of the oceanographic factors on the species distribution in the study area. The potential fishing grounds during intermonsoon periods; April and October 2008-2009 were simulated separately and covered the near-coast of Kelantan, Terengganu, Pahang and Johor. The oceanographic conditions differed between regions by the inherent seasonal variability. The seasonal and spatial extents of potential fishing grounds were largely explained by chl-a concentration (0.21-0.99 mg/m3 in April and 0.28-1.00 mg/m3 in October), SSH (77.37-85.90 cm in April and 107.60-108.97 cm in October) and SST (30.43-33.70 °C in April and 30.48-30.97 °C in October). The constructed models were applicable and therefore they were suitable for predicting the potential fishing zones of R. kanagurta in EEZ. The results from this study revealed MaxEnt's potential for predicting the spatial distribution of R. kanagurta and highlighted the use of multispectral satellite images for describing the seasonal potential fishing grounds.

  10. Rumor Identification with Maximum Entropy in MicroNet

    Directory of Open Access Journals (Sweden)

    Suisheng Yu

    2017-01-01

    Full Text Available The widely used applications of Microblog, WeChat, and other social networking platforms (that we call MicroNet shorten the period of information dissemination and expand the range of information dissemination, which allows rumors to cause greater harm and have more influence. A hot topic in the information dissemination field is how to identify and block rumors. Based on the maximum entropy model, this paper constructs the recognition mechanism of rumor information in the micronetwork environment. First, based on the information entropy theory, we obtained the characteristics of rumor information using the maximum entropy model. Next, we optimized the original classifier training set and the feature function to divide the information into rumors and nonrumors. Finally, the experimental simulation results show that the rumor identification results using this method are better than the original classifier and other related classification methods.

  11. Maximum-entropy clustering algorithm and its global convergence analysis

    Institute of Scientific and Technical Information of China (English)

    2001-01-01

    Constructing a batch of differentiable entropy functions touniformly approximate an objective function by means of the maximum-entropy principle, a new clustering algorithm, called maximum-entropy clustering algorithm, is proposed based on optimization theory. This algorithm is a soft generalization of the hard C-means algorithm and possesses global convergence. Its relations with other clustering algorithms are discussed.

  12. Maximum Entropy Estimation of Transition Probabilities of Reversible Markov Chains

    Directory of Open Access Journals (Sweden)

    Erik Van der Straeten

    2009-11-01

    Full Text Available In this paper, we develop a general theory for the estimation of the transition probabilities of reversible Markov chains using the maximum entropy principle. A broad range of physical models can be studied within this approach. We use one-dimensional classical spin systems to illustrate the theoretical ideas. The examples studied in this paper are: the Ising model, the Potts model and the Blume-Emery-Griffiths model.

  13. Stochastic modeling and control system designs of the NASA/MSFC Ground Facility for large space structures: The maximum entropy/optimal projection approach

    Science.gov (United States)

    Hsia, Wei-Shen

    1986-01-01

    In the Control Systems Division of the Systems Dynamics Laboratory of the NASA/MSFC, a Ground Facility (GF), in which the dynamics and control system concepts being considered for Large Space Structures (LSS) applications can be verified, was designed and built. One of the important aspects of the GF is to design an analytical model which will be as close to experimental data as possible so that a feasible control law can be generated. Using Hyland's Maximum Entropy/Optimal Projection Approach, a procedure was developed in which the maximum entropy principle is used for stochastic modeling and the optimal projection technique is used for a reduced-order dynamic compensator design for a high-order plant.

  14. Information Entropy Production of Maximum Entropy Markov Chains from Spike Trains

    Directory of Open Access Journals (Sweden)

    Rodrigo Cofré

    2018-01-01

    Full Text Available The spiking activity of neuronal networks follows laws that are not time-reversal symmetric; the notion of pre-synaptic and post-synaptic neurons, stimulus correlations and noise correlations have a clear time order. Therefore, a biologically realistic statistical model for the spiking activity should be able to capture some degree of time irreversibility. We use the thermodynamic formalism to build a framework in the context maximum entropy models to quantify the degree of time irreversibility, providing an explicit formula for the information entropy production of the inferred maximum entropy Markov chain. We provide examples to illustrate our results and discuss the importance of time irreversibility for modeling the spike train statistics.

  15. MAXIMUM-LIKELIHOOD-ESTIMATION OF THE ENTROPY OF AN ATTRACTOR

    NARCIS (Netherlands)

    SCHOUTEN, JC; TAKENS, F; VANDENBLEEK, CM

    In this paper, a maximum-likelihood estimate of the (Kolmogorov) entropy of an attractor is proposed that can be obtained directly from a time series. Also, the relative standard deviation of the entropy estimate is derived; it is dependent on the entropy and on the number of samples used in the

  16. Microscopic model for the non-linear fluctuating hydrodynamic of 4 He superfluid helium deduced by maximum entropy method

    International Nuclear Information System (INIS)

    Alvarez R, J.T.

    1998-01-01

    This thesis presents a microscopic model for the non-linear fluctuating hydrodynamic of superfluid helium ( 4 He), model developed by means of the Maximum Entropy Method (Maxent). In the chapter 1, it is demonstrated the necessity to developing a microscopic model for the fluctuating hydrodynamic of the superfluid helium, starting from to show a brief overview of the theories and experiments developed in order to explain the behavior of the superfluid helium. On the other hand, it is presented the Morozov heuristic method for the construction of the non-linear hydrodynamic fluctuating of simple fluid. Method that will be generalized for the construction of the non-linear fluctuating hydrodynamic of the superfluid helium. Besides, it is presented a brief summary of the content of the thesis. In the chapter 2, it is reproduced the construction of a Generalized Fokker-Planck equation, (GFP), for a distribution function associated with the coarse grained variables. Function defined with aid of a nonequilibrium statistical operator ρhut FP that is evaluated as Wigneris function through ρ CG obtained by Maxent. Later this equation of GFP is reduced to a non-linear local FP equation from considering a slow and Markov process in the coarse grained variables. In this equation appears a matrix D mn defined with a nonequilibrium coarse grained statistical operator ρhut CG , matrix elements are used in the construction of the non-linear fluctuating hydrodynamics equations of the superfluid helium. In the chapter 3, the Lagrange multipliers are evaluated for to determine ρhut CG by means of the local equilibrium statistical operator ρhut l -tilde with the hypothesis that the system presents small fluctuations. Also are determined the currents associated with the coarse grained variables and furthermore are evaluated the matrix elements D mn but with aid of a quasi equilibrium statistical operator ρhut qe instead of the local equilibrium operator ρhut l -tilde. Matrix

  17. Mammographic image restoration using maximum entropy deconvolution

    International Nuclear Information System (INIS)

    Jannetta, A; Jackson, J C; Kotre, C J; Birch, I P; Robson, K J; Padgett, R

    2004-01-01

    An image restoration approach based on a Bayesian maximum entropy method (MEM) has been applied to a radiological image deconvolution problem, that of reduction of geometric blurring in magnification mammography. The aim of the work is to demonstrate an improvement in image spatial resolution in realistic noisy radiological images with no associated penalty in terms of reduction in the signal-to-noise ratio perceived by the observer. Images of the TORMAM mammographic image quality phantom were recorded using the standard magnification settings of 1.8 magnification/fine focus and also at 1.8 magnification/broad focus and 3.0 magnification/fine focus; the latter two arrangements would normally give rise to unacceptable geometric blurring. Measured point-spread functions were used in conjunction with the MEM image processing to de-blur these images. The results are presented as comparative images of phantom test features and as observer scores for the raw and processed images. Visualization of high resolution features and the total image scores for the test phantom were improved by the application of the MEM processing. It is argued that this successful demonstration of image de-blurring in noisy radiological images offers the possibility of weakening the link between focal spot size and geometric blurring in radiology, thus opening up new approaches to system optimization

  18. Bayesian interpretation of Generalized empirical likelihood by maximum entropy

    OpenAIRE

    Rochet , Paul

    2011-01-01

    We study a parametric estimation problem related to moment condition models. As an alternative to the generalized empirical likelihood (GEL) and the generalized method of moments (GMM), a Bayesian approach to the problem can be adopted, extending the MEM procedure to parametric moment conditions. We show in particular that a large number of GEL estimators can be interpreted as a maximum entropy solution. Moreover, we provide a more general field of applications by proving the method to be rob...

  19. Maximum-Entropy Inference with a Programmable Annealer

    Science.gov (United States)

    Chancellor, Nicholas; Szoke, Szilard; Vinci, Walter; Aeppli, Gabriel; Warburton, Paul A.

    2016-03-01

    Optimisation problems typically involve finding the ground state (i.e. the minimum energy configuration) of a cost function with respect to many variables. If the variables are corrupted by noise then this maximises the likelihood that the solution is correct. The maximum entropy solution on the other hand takes the form of a Boltzmann distribution over the ground and excited states of the cost function to correct for noise. Here we use a programmable annealer for the information decoding problem which we simulate as a random Ising model in a field. We show experimentally that finite temperature maximum entropy decoding can give slightly better bit-error-rates than the maximum likelihood approach, confirming that useful information can be extracted from the excited states of the annealer. Furthermore we introduce a bit-by-bit analytical method which is agnostic to the specific application and use it to show that the annealer samples from a highly Boltzmann-like distribution. Machines of this kind are therefore candidates for use in a variety of machine learning applications which exploit maximum entropy inference, including language processing and image recognition.

  20. Application of maximum entropy to neutron tunneling spectroscopy

    International Nuclear Information System (INIS)

    Mukhopadhyay, R.; Silver, R.N.

    1990-01-01

    We demonstrate the maximum entropy method for the deconvolution of high resolution tunneling data acquired with a quasielastic spectrometer. Given a precise characterization of the instrument resolution function, a maximum entropy analysis of lutidine data obtained with the IRIS spectrometer at ISIS results in an effective factor of three improvement in resolution. 7 refs., 4 figs

  1. Maximum Entropy and Theory Construction: A Reply to Favretti

    Directory of Open Access Journals (Sweden)

    John Harte

    2018-04-01

    Full Text Available In the maximum entropy theory of ecology (METE, the form of a function describing the distribution of abundances over species and metabolic rates over individuals in an ecosystem is inferred using the maximum entropy inference procedure. Favretti shows that an alternative maximum entropy model exists that assumes the same prior knowledge and makes predictions that differ from METE’s. He shows that both cannot be correct and asserts that his is the correct one because it can be derived from a classic microstate-counting calculation. I clarify here exactly what the core entities and definitions are for METE, and discuss the relevance of two critical issues raised by Favretti: the existence of a counting procedure for microstates and the choices of definition of the core elements of a theory. I emphasize that a theorist controls how the core entities of his or her theory are defined, and that nature is the final arbiter of the validity of a theory.

  2. A Maximum Entropy Approach to Loss Distribution Analysis

    Directory of Open Access Journals (Sweden)

    Marco Bee

    2013-03-01

    Full Text Available In this paper we propose an approach to the estimation and simulation of loss distributions based on Maximum Entropy (ME, a non-parametric technique that maximizes the Shannon entropy of the data under moment constraints. Special cases of the ME density correspond to standard distributions; therefore, this methodology is very general as it nests most classical parametric approaches. Sampling the ME distribution is essential in many contexts, such as loss models constructed via compound distributions. Given the difficulties in carrying out exact simulation,we propose an innovative algorithm, obtained by means of an extension of Adaptive Importance Sampling (AIS, for the approximate simulation of the ME distribution. Several numerical experiments confirm that the AIS-based simulation technique works well, and an application to insurance data gives further insights in the usefulness of the method for modelling, estimating and simulating loss distributions.

  3. Twenty-five years of maximum-entropy principle

    Science.gov (United States)

    Kapur, J. N.

    1983-04-01

    The strengths and weaknesses of the maximum entropy principle (MEP) are examined and some challenging problems that remain outstanding at the end of the first quarter century of the principle are discussed. The original formalism of the MEP is presented and its relationship to statistical mechanics is set forth. The use of MEP for characterizing statistical distributions, in statistical inference, nonlinear spectral analysis, transportation models, population density models, models for brand-switching in marketing and vote-switching in elections is discussed. Its application to finance, insurance, image reconstruction, pattern recognition, operations research and engineering, biology and medicine, and nonparametric density estimation is considered.

  4. Maximum entropy reconstructions for crystallographic imaging; Cristallographie et reconstruction d`images par maximum d`entropie

    Energy Technology Data Exchange (ETDEWEB)

    Papoular, R

    1997-07-01

    The Fourier Transform is of central importance to Crystallography since it allows the visualization in real space of tridimensional scattering densities pertaining to physical systems from diffraction data (powder or single-crystal diffraction, using x-rays, neutrons, electrons or else). In turn, this visualization makes it possible to model and parametrize these systems, the crystal structures of which are eventually refined by Least-Squares techniques (e.g., the Rietveld method in the case of Powder Diffraction). The Maximum Entropy Method (sometimes called MEM or MaxEnt) is a general imaging technique, related to solving ill-conditioned inverse problems. It is ideally suited for tackling undetermined systems of linear questions (for which the number of variables is much larger than the number of equations). It is already being applied successfully in Astronomy, Radioastronomy and Medical Imaging. The advantages of using MAXIMUM Entropy over conventional Fourier and `difference Fourier` syntheses stem from the following facts: MaxEnt takes the experimental error bars into account; MaxEnt incorporate Prior Knowledge (e.g., the positivity of the scattering density in some instances); MaxEnt allows density reconstructions from incompletely phased data, as well as from overlapping Bragg reflections; MaxEnt substantially reduces truncation errors to which conventional experimental Fourier reconstructions are usually prone. The principles of Maximum Entropy imaging as applied to Crystallography are first presented. The method is then illustrated by a detailed example specific to Neutron Diffraction: the search for proton in solids. (author). 17 refs.

  5. Spatiotemporal modeling of PM2.5 concentrations at the national scale combining land use regression and Bayesian maximum entropy in China.

    Science.gov (United States)

    Chen, Li; Gao, Shuang; Zhang, Hui; Sun, Yanling; Ma, Zhenxing; Vedal, Sverre; Mao, Jian; Bai, Zhipeng

    2018-05-03

    Concentrations of particulate matter with aerodynamic diameter Bayesian Maximum Entropy (BME) interpolation of the LUR space-time residuals were developed to estimate the PM 2.5 concentrations on a national scale in China. This hybrid model could potentially provide more valid predictions than a commonly-used LUR model. The LUR/BME model had good performance characteristics, with R 2  = 0.82 and root mean square error (RMSE) of 4.6 μg/m 3 . Prediction errors of the LUR/BME model were reduced by incorporating soft data accounting for data uncertainty, with the R 2 increasing by 6%. The performance of LUR/BME is better than OK/BME. The LUR/BME model is the most accurate fine spatial scale PM 2.5 model developed to date for China. Copyright © 2018. Published by Elsevier Ltd.

  6. Three faces of entropy for complex systems: Information, thermodynamics, and the maximum entropy principle

    Science.gov (United States)

    Thurner, Stefan; Corominas-Murtra, Bernat; Hanel, Rudolf

    2017-09-01

    There are at least three distinct ways to conceptualize entropy: entropy as an extensive thermodynamic quantity of physical systems (Clausius, Boltzmann, Gibbs), entropy as a measure for information production of ergodic sources (Shannon), and entropy as a means for statistical inference on multinomial processes (Jaynes maximum entropy principle). Even though these notions represent fundamentally different concepts, the functional form of the entropy for thermodynamic systems in equilibrium, for ergodic sources in information theory, and for independent sampling processes in statistical systems, is degenerate, H (p ) =-∑ipilogpi . For many complex systems, which are typically history-dependent, nonergodic, and nonmultinomial, this is no longer the case. Here we show that for such processes, the three entropy concepts lead to different functional forms of entropy, which we will refer to as SEXT for extensive entropy, SIT for the source information rate in information theory, and SMEP for the entropy functional that appears in the so-called maximum entropy principle, which characterizes the most likely observable distribution functions of a system. We explicitly compute these three entropy functionals for three concrete examples: for Pólya urn processes, which are simple self-reinforcing processes, for sample-space-reducing (SSR) processes, which are simple history dependent processes that are associated with power-law statistics, and finally for multinomial mixture processes.

  7. Stationary neutrino radiation transport by maximum entropy closure

    International Nuclear Information System (INIS)

    Bludman, S.A.

    1994-11-01

    The authors obtain the angular distributions that maximize the entropy functional for Maxwell-Boltzmann (classical), Bose-Einstein, and Fermi-Dirac radiation. In the low and high occupancy limits, the maximum entropy closure is bounded by previously known variable Eddington factors that depend only on the flux. For intermediate occupancy, the maximum entropy closure depends on both the occupation density and the flux. The Fermi-Dirac maximum entropy variable Eddington factor shows a scale invariance, which leads to a simple, exact analytic closure for fermions. This two-dimensional variable Eddington factor gives results that agree well with exact (Monte Carlo) neutrino transport calculations out of a collapse residue during early phases of hydrostatic neutron star formation

  8. Maximum and minimum entropy states yielding local continuity bounds

    Science.gov (United States)

    Hanson, Eric P.; Datta, Nilanjana

    2018-04-01

    Given an arbitrary quantum state (σ), we obtain an explicit construction of a state ρɛ * ( σ ) [respectively, ρ * , ɛ ( σ ) ] which has the maximum (respectively, minimum) entropy among all states which lie in a specified neighborhood (ɛ-ball) of σ. Computing the entropy of these states leads to a local strengthening of the continuity bound of the von Neumann entropy, i.e., the Audenaert-Fannes inequality. Our bound is local in the sense that it depends on the spectrum of σ. The states ρɛ * ( σ ) and ρ * , ɛ (σ) depend only on the geometry of the ɛ-ball and are in fact optimizers for a larger class of entropies. These include the Rényi entropy and the minimum- and maximum-entropies, providing explicit formulas for certain smoothed quantities. This allows us to obtain local continuity bounds for these quantities as well. In obtaining this bound, we first derive a more general result which may be of independent interest, namely, a necessary and sufficient condition under which a state maximizes a concave and Gâteaux-differentiable function in an ɛ-ball around a given state σ. Examples of such a function include the von Neumann entropy and the conditional entropy of bipartite states. Our proofs employ tools from the theory of convex optimization under non-differentiable constraints, in particular Fermat's rule, and majorization theory.

  9. How multiplicity determines entropy and the derivation of the maximum entropy principle for complex systems.

    Science.gov (United States)

    Hanel, Rudolf; Thurner, Stefan; Gell-Mann, Murray

    2014-05-13

    The maximum entropy principle (MEP) is a method for obtaining the most likely distribution functions of observables from statistical systems by maximizing entropy under constraints. The MEP has found hundreds of applications in ergodic and Markovian systems in statistical mechanics, information theory, and statistics. For several decades there has been an ongoing controversy over whether the notion of the maximum entropy principle can be extended in a meaningful way to nonextensive, nonergodic, and complex statistical systems and processes. In this paper we start by reviewing how Boltzmann-Gibbs-Shannon entropy is related to multiplicities of independent random processes. We then show how the relaxation of independence naturally leads to the most general entropies that are compatible with the first three Shannon-Khinchin axioms, the (c,d)-entropies. We demonstrate that the MEP is a perfectly consistent concept for nonergodic and complex statistical systems if their relative entropy can be factored into a generalized multiplicity and a constraint term. The problem of finding such a factorization reduces to finding an appropriate representation of relative entropy in a linear basis. In a particular example we show that path-dependent random processes with memory naturally require specific generalized entropies. The example is to our knowledge the first exact derivation of a generalized entropy from the microscopic properties of a path-dependent random process.

  10. Tail Risk Constraints and Maximum Entropy

    Directory of Open Access Journals (Sweden)

    Donald Geman

    2015-06-01

    Full Text Available Portfolio selection in the financial literature has essentially been analyzed under two central assumptions: full knowledge of the joint probability distribution of the returns of the securities that will comprise the target portfolio; and investors’ preferences are expressed through a utility function. In the real world, operators build portfolios under risk constraints which are expressed both by their clients and regulators and which bear on the maximal loss that may be generated over a given time period at a given confidence level (the so-called Value at Risk of the position. Interestingly, in the finance literature, a serious discussion of how much or little is known from a probabilistic standpoint about the multi-dimensional density of the assets’ returns seems to be of limited relevance. Our approach in contrast is to highlight these issues and then adopt throughout a framework of entropy maximization to represent the real world ignorance of the “true” probability distributions, both univariate and multivariate, of traded securities’ returns. In this setting, we identify the optimal portfolio under a number of downside risk constraints. Two interesting results are exhibited: (i the left- tail constraints are sufficiently powerful to override all other considerations in the conventional theory; (ii the “barbell portfolio” (maximal certainty/ low risk in one set of holdings, maximal uncertainty in another, which is quite familiar to traders, naturally emerges in our construction.

  11. The Maximum Entropy Principle and the Modern Portfolio Theory

    Directory of Open Access Journals (Sweden)

    Ailton Cassetari

    2003-12-01

    Full Text Available In this work, a capital allocation methodology base don the Principle of Maximum Entropy was developed. The Shannons entropy is used as a measure, concerning the Modern Portfolio Theory, are also discuted. Particularly, the methodology is tested making a systematic comparison to: 1 the mean-variance (Markovitz approach and 2 the mean VaR approach (capital allocations based on the Value at Risk concept. In principle, such confrontations show the plausibility and effectiveness of the developed method.

  12. Predicting the Outcome of NBA Playoffs Based on the Maximum Entropy Principle

    OpenAIRE

    Ge Cheng; Zhenyu Zhang; Moses Ntanda Kyebambe; Nasser Kimbugwe

    2016-01-01

    Predicting the outcome of National Basketball Association (NBA) matches poses a challenging problem of interest to the research community as well as the general public. In this article, we formalize the problem of predicting NBA game results as a classification problem and apply the principle of Maximum Entropy to construct an NBA Maximum Entropy (NBAME) model that fits to discrete statistics for NBA games, and then predict the outcomes of NBA playoffs using the model. Our results reveal that...

  13. Discontinuity of maximum entropy inference and quantum phase transitions

    International Nuclear Information System (INIS)

    Chen, Jianxin; Ji, Zhengfeng; Yu, Nengkun; Zeng, Bei; Li, Chi-Kwong; Poon, Yiu-Tung; Shen, Yi; Zhou, Duanlu

    2015-01-01

    In this paper, we discuss the connection between two genuinely quantum phenomena—the discontinuity of quantum maximum entropy inference and quantum phase transitions at zero temperature. It is shown that the discontinuity of the maximum entropy inference of local observable measurements signals the non-local type of transitions, where local density matrices of the ground state change smoothly at the transition point. We then propose to use the quantum conditional mutual information of the ground state as an indicator to detect the discontinuity and the non-local type of quantum phase transitions in the thermodynamic limit. (paper)

  14. On an Objective Basis for the Maximum Entropy Principle

    Directory of Open Access Journals (Sweden)

    David J. Miller

    2015-01-01

    Full Text Available In this letter, we elaborate on some of the issues raised by a recent paper by Neapolitan and Jiang concerning the maximum entropy (ME principle and alternative principles for estimating probabilities consistent with known, measured constraint information. We argue that the ME solution for the “problematic” example introduced by Neapolitan and Jiang has stronger objective basis, rooted in results from information theory, than their alternative proposed solution. We also raise some technical concerns about the Bayesian analysis in their work, which was used to independently support their alternative to the ME solution. The letter concludes by noting some open problems involving maximum entropy statistical inference.

  15. Applications of the maximum entropy principle in nuclear physics

    International Nuclear Information System (INIS)

    Froehner, F.H.

    1990-01-01

    Soon after the advent of information theory the principle of maximum entropy was recognized as furnishing the missing rationale for the familiar rules of classical thermodynamics. More recently it has also been applied successfully in nuclear physics. As an elementary example we derive a physically meaningful macroscopic description of the spectrum of neutrons emitted in nuclear fission, and compare the well known result with accurate data on 252 Cf. A second example, derivation of an expression for resonance-averaged cross sections for nuclear reactions like scattering or fission, is less trivial. Entropy maximization, constrained by given transmission coefficients, yields probability distributions for the R- and S-matrix elements, from which average cross sections can be calculated. If constrained only by the range of the spectrum of compound-nuclear levels it produces the Gaussian Orthogonal Ensemble (GOE) of Hamiltonian matrices that again yields expressions for average cross sections. Both avenues give practically the same numbers in spite of the quite different cross section formulae. These results were employed in a new model-aided evaluation of the 238 U neutron cross sections in the unresolved resonance region. (orig.) [de

  16. Bayesian Reliability Estimation for Deteriorating Systems with Limited Samples Using the Maximum Entropy Approach

    OpenAIRE

    Xiao, Ning-Cong; Li, Yan-Feng; Wang, Zhonglai; Peng, Weiwen; Huang, Hong-Zhong

    2013-01-01

    In this paper the combinations of maximum entropy method and Bayesian inference for reliability assessment of deteriorating system is proposed. Due to various uncertainties, less data and incomplete information, system parameters usually cannot be determined precisely. These uncertainty parameters can be modeled by fuzzy sets theory and the Bayesian inference which have been proved to be useful for deteriorating systems under small sample sizes. The maximum entropy approach can be used to cal...

  17. Maximum Entropy, Word-Frequency, Chinese Characters, and Multiple Meanings

    Science.gov (United States)

    Yan, Xiaoyong; Minnhagen, Petter

    2015-01-01

    The word-frequency distribution of a text written by an author is well accounted for by a maximum entropy distribution, the RGF (random group formation)-prediction. The RGF-distribution is completely determined by the a priori values of the total number of words in the text (M), the number of distinct words (N) and the number of repetitions of the most common word (kmax). It is here shown that this maximum entropy prediction also describes a text written in Chinese characters. In particular it is shown that although the same Chinese text written in words and Chinese characters have quite differently shaped distributions, they are nevertheless both well predicted by their respective three a priori characteristic values. It is pointed out that this is analogous to the change in the shape of the distribution when translating a given text to another language. Another consequence of the RGF-prediction is that taking a part of a long text will change the input parameters (M, N, kmax) and consequently also the shape of the frequency distribution. This is explicitly confirmed for texts written in Chinese characters. Since the RGF-prediction has no system-specific information beyond the three a priori values (M, N, kmax), any specific language characteristic has to be sought in systematic deviations from the RGF-prediction and the measured frequencies. One such systematic deviation is identified and, through a statistical information theoretical argument and an extended RGF-model, it is proposed that this deviation is caused by multiple meanings of Chinese characters. The effect is stronger for Chinese characters than for Chinese words. The relation between Zipf’s law, the Simon-model for texts and the present results are discussed. PMID:25955175

  18. Image coding based on maximum entropy partitioning for identifying ...

    Indian Academy of Sciences (India)

    A new coding scheme based on maximum entropy partitioning is proposed in our work, particularly to identify the improbable intensities related to different emotions. The improbable intensities when used as a mask decode the facial expression correctly, providing an effectiveplatform for future emotion categorization ...

  19. Gamma-ray spectra deconvolution by maximum-entropy methods

    International Nuclear Information System (INIS)

    Los Arcos, J.M.

    1996-01-01

    A maximum-entropy method which includes the response of detectors and the statistical fluctuations of spectra is described and applied to the deconvolution of γ-ray spectra. Resolution enhancement of 25% can be reached for experimental peaks and up to 50% for simulated ones, while the intensities are conserved within 1-2%. (orig.)

  20. The constraint rule of the maximum entropy principle

    NARCIS (Netherlands)

    Uffink, J.

    1995-01-01

    The principle of maximum entropy is a method for assigning values to probability distributions on the basis of partial information. In usual formulations of this and related methods of inference one assumes that this partial information takes the form of a constraint on allowed probability

  1. Applications of the Maximum Entropy Method in superspace

    Czech Academy of Sciences Publication Activity Database

    van Smaalen, S.; Palatinus, Lukáš

    2004-01-01

    Roč. 305, - (2004), s. 57-62 ISSN 0015-0193 Grant - others:DFG and FCI(DE) XX Institutional research plan: CEZ:AV0Z1010914 Keywords : Maximum Entropy Method * modulated structures * charge density Subject RIV: BM - Solid Matter Physics ; Magnetism Impact factor: 0.517, year: 2004

  2. Maximum entropy estimation via Gauss-LP quadratures

    NARCIS (Netherlands)

    Thély, Maxime; Sutter, Tobias; Mohajerin Esfahani, P.; Lygeros, John; Dochain, Denis; Henrion, Didier; Peaucelle, Dimitri

    2017-01-01

    We present an approximation method to a class of parametric integration problems that naturally appear when solving the dual of the maximum entropy estimation problem. Our method builds up on a recent generalization of Gauss quadratures via an infinite-dimensional linear program, and utilizes a

  3. On the maximum entropy distributions of inherently positive nuclear data

    Energy Technology Data Exchange (ETDEWEB)

    Taavitsainen, A., E-mail: aapo.taavitsainen@gmail.com; Vanhanen, R.

    2017-05-11

    The multivariate log-normal distribution is used by many authors and statistical uncertainty propagation programs for inherently positive quantities. Sometimes it is claimed that the log-normal distribution results from the maximum entropy principle, if only means, covariances and inherent positiveness of quantities are known or assumed to be known. In this article we show that this is not true. Assuming a constant prior distribution, the maximum entropy distribution is in fact a truncated multivariate normal distribution – whenever it exists. However, its practical application to multidimensional cases is hindered by lack of a method to compute its location and scale parameters from means and covariances. Therefore, regardless of its theoretical disadvantage, use of other distributions seems to be a practical necessity. - Highlights: • Statistical uncertainty propagation requires a sampling distribution. • The objective distribution of inherently positive quantities is determined. • The objectivity is based on the maximum entropy principle. • The maximum entropy distribution is the truncated normal distribution. • Applicability of log-normal or normal distribution approximation is limited.

  4. Current opinion about maximum entropy methods in Moessbauer spectroscopy

    International Nuclear Information System (INIS)

    Szymanski, K

    2009-01-01

    Current opinion about Maximum Entropy Methods in Moessbauer Spectroscopy is presented. The most important advantage offered by the method is the correct data processing under circumstances of incomplete information. Disadvantage is the sophisticated algorithm and its application to the specific problems.

  5. Combining Experiments and Simulations Using the Maximum Entropy Principle

    DEFF Research Database (Denmark)

    Boomsma, Wouter; Ferkinghoff-Borg, Jesper; Lindorff-Larsen, Kresten

    2014-01-01

    in the context of a simple example, after which we proceed with a real-world application in the field of molecular simulations, where the maximum entropy procedure has recently provided new insight. Given the limited accuracy of force fields, macromolecular simulations sometimes produce results...

  6. Learning maximum entropy models from finite-size data sets: A fast data-driven algorithm allows sampling from the posterior distribution.

    Science.gov (United States)

    Ferrari, Ulisse

    2016-08-01

    Maximum entropy models provide the least constrained probability distributions that reproduce statistical properties of experimental datasets. In this work we characterize the learning dynamics that maximizes the log-likelihood in the case of large but finite datasets. We first show how the steepest descent dynamics is not optimal as it is slowed down by the inhomogeneous curvature of the model parameters' space. We then provide a way for rectifying this space which relies only on dataset properties and does not require large computational efforts. We conclude by solving the long-time limit of the parameters' dynamics including the randomness generated by the systematic use of Gibbs sampling. In this stochastic framework, rather than converging to a fixed point, the dynamics reaches a stationary distribution, which for the rectified dynamics reproduces the posterior distribution of the parameters. We sum up all these insights in a "rectified" data-driven algorithm that is fast and by sampling from the parameters' posterior avoids both under- and overfitting along all the directions of the parameters' space. Through the learning of pairwise Ising models from the recording of a large population of retina neurons, we show how our algorithm outperforms the steepest descent method.

  7. An adaptive meshfree method for phase-field models of biomembranes. Part I: Approximation with maximum-entropy basis functions

    OpenAIRE

    Rosolen, A.; Peco, C.; Arroyo, M.

    2013-01-01

    We present an adaptive meshfree method to approximate phase-field models of biomembranes. In such models, the Helfrich curvature elastic energy, the surface area, and the enclosed volume of a vesicle are written as functionals of a continuous phase-field, which describes the interface in a smeared manner. Such functionals involve up to second-order spatial derivatives of the phase-field, leading to fourth-order Euler–Lagrange partial differential equations (PDE). The solutions develop sharp i...

  8. Spatiotemporal modeling of ozone levels in Quebec (Canada): a comparison of kriging, land-use regression (LUR), and combined Bayesian maximum entropy-LUR approaches.

    Science.gov (United States)

    Adam-Poupart, Ariane; Brand, Allan; Fournier, Michel; Jerrett, Michael; Smargiassi, Audrey

    2014-09-01

    Ambient air ozone (O3) is a pulmonary irritant that has been associated with respiratory health effects including increased lung inflammation and permeability, airway hyperreactivity, respiratory symptoms, and decreased lung function. Estimation of O3 exposure is a complex task because the pollutant exhibits complex spatiotemporal patterns. To refine the quality of exposure estimation, various spatiotemporal methods have been developed worldwide. We sought to compare the accuracy of three spatiotemporal models to predict summer ground-level O3 in Quebec, Canada. We developed a land-use mixed-effects regression (LUR) model based on readily available data (air quality and meteorological monitoring data, road networks information, latitude), a Bayesian maximum entropy (BME) model incorporating both O3 monitoring station data and the land-use mixed model outputs (BME-LUR), and a kriging method model based only on available O3 monitoring station data (BME kriging). We performed leave-one-station-out cross-validation and visually assessed the predictive capability of each model by examining the mean temporal and spatial distributions of the average estimated errors. The BME-LUR was the best predictive model (R2 = 0.653) with the lowest root mean-square error (RMSE ;7.06 ppb), followed by the LUR model (R2 = 0.466, RMSE = 8.747) and the BME kriging model (R2 = 0.414, RMSE = 9.164). Our findings suggest that errors of estimation in the interpolation of O3 concentrations with BME can be greatly reduced by incorporating outputs from a LUR model developed with readily available data.

  9. MAXIMUM PRINCIPLE FOR SUBSONIC FLOW WITH VARIABLE ENTROPY

    Directory of Open Access Journals (Sweden)

    B. Sizykh Grigory

    2017-01-01

    Full Text Available Maximum principle for subsonic flow is fair for stationary irrotational subsonic gas flows. According to this prin- ciple, if the value of the velocity is not constant everywhere, then its maximum is achieved on the boundary and only on the boundary of the considered domain. This property is used when designing form of an aircraft with a maximum critical val- ue of the Mach number: it is believed that if the local Mach number is less than unit in the incoming flow and on the body surface, then the Mach number is less then unit in all points of flow. The known proof of maximum principle for subsonic flow is based on the assumption that in the whole considered area of the flow the pressure is a function of density. For the ideal and perfect gas (the role of diffusion is negligible, and the Mendeleev-Clapeyron law is fulfilled, the pressure is a function of density if entropy is constant in the entire considered area of the flow. Shows an example of a stationary sub- sonic irrotational flow, in which the entropy has different values on different stream lines, and the pressure is not a function of density. The application of the maximum principle for subsonic flow with respect to such a flow would be unreasonable. This example shows the relevance of the question about the place of the points of maximum value of the velocity, if the entropy is not a constant. To clarify the regularities of the location of these points, was performed the analysis of the com- plete Euler equations (without any simplifying assumptions in 3-D case. The new proof of the maximum principle for sub- sonic flow was proposed. This proof does not rely on the assumption that the pressure is a function of density. Thus, it is shown that the maximum principle for subsonic flow is true for stationary subsonic irrotational flows of ideal perfect gas with variable entropy.

  10. A maximum-entropy model

    Indian Academy of Sciences (India)

    problem is important from an experimental point of view, because absorption is always present. ... equal-a-priori probabilities is expressed mathematically by the invariant measure on the matrix space ... the interval between zero and one.

  11. Development of an Anisotropic Geological-Based Land Use Regression and Bayesian Maximum Entropy Model for Estimating Groundwater Radon across Northing Carolina

    Science.gov (United States)

    Messier, K. P.; Serre, M. L.

    2015-12-01

    Radon (222Rn) is a naturally occurring chemically inert, colorless, and odorless radioactive gas produced from the decay of uranium (238U), which is ubiquitous in rocks and soils worldwide. Exposure to 222Rn is likely the second leading cause of lung cancer after cigarette smoking via inhalation; however, exposure through untreated groundwater is also a contributing factor to both inhalation and ingestion routes. A land use regression (LUR) model for groundwater 222Rn with anisotropic geological and 238U based explanatory variables is developed, which helps elucidate the factors contributing to elevated 222Rn across North Carolina. Geological and uranium based variables are constructed in elliptical buffers surrounding each observation such that they capture the lateral geometric anisotropy present in groundwater 222Rn. Moreover, geological features are defined at three different geological spatial scales to allow the model to distinguish between large area and small area effects of geology on groundwater 222Rn. The LUR is also integrated into the Bayesian Maximum Entropy (BME) geostatistical framework to increase accuracy and produce a point-level LUR-BME model of groundwater 222Rn across North Carolina including prediction uncertainty. The LUR-BME model of groundwater 222Rn results in a leave-one out cross-validation of 0.46 (Pearson correlation coefficient= 0.68), effectively predicting within the spatial covariance range. Modeled results of 222Rn concentrations show variability among Intrusive Felsic geological formations likely due to average bedrock 238U defined on the basis of overlying stream-sediment 238U concentrations that is a widely distributed consistently analyzed point-source data.

  12. Precise charge density studies by maximum entropy method

    CERN Document Server

    Takata, M

    2003-01-01

    For the production research and development of nanomaterials, their structural information is indispensable. Recently, a sophisticated analytical method, which is based on information theory, the Maximum Entropy Method (MEM) using synchrotron radiation powder data, has been successfully applied to determine precise charge densities of metallofullerenes and nanochannel microporous compounds. The results revealed various endohedral natures of metallofullerenes and one-dimensional array formation of adsorbed gas molecules in nanochannel microporous compounds. The concept of MEM analysis was also described briefly. (author)

  13. PNNL: A Supervised Maximum Entropy Approach to Word Sense Disambiguation

    Energy Technology Data Exchange (ETDEWEB)

    Tratz, Stephen C.; Sanfilippo, Antonio P.; Gregory, Michelle L.; Chappell, Alan R.; Posse, Christian; Whitney, Paul D.

    2007-06-23

    In this paper, we described the PNNL Word Sense Disambiguation system as applied to the English All-Word task in Se-mEval 2007. We use a supervised learning approach, employing a large number of features and using Information Gain for dimension reduction. Our Maximum Entropy approach combined with a rich set of features produced results that are significantly better than baseline and are the highest F-score for the fined-grained English All-Words subtask.

  14. The maximum entropy method of moments and Bayesian probability theory

    Science.gov (United States)

    Bretthorst, G. Larry

    2013-08-01

    The problem of density estimation occurs in many disciplines. For example, in MRI it is often necessary to classify the types of tissues in an image. To perform this classification one must first identify the characteristics of the tissues to be classified. These characteristics might be the intensity of a T1 weighted image and in MRI many other types of characteristic weightings (classifiers) may be generated. In a given tissue type there is no single intensity that characterizes the tissue, rather there is a distribution of intensities. Often this distributions can be characterized by a Gaussian, but just as often it is much more complicated. Either way, estimating the distribution of intensities is an inference problem. In the case of a Gaussian distribution, one must estimate the mean and standard deviation. However, in the Non-Gaussian case the shape of the density function itself must be inferred. Three common techniques for estimating density functions are binned histograms [1, 2], kernel density estimation [3, 4], and the maximum entropy method of moments [5, 6]. In the introduction, the maximum entropy method of moments will be reviewed. Some of its problems and conditions under which it fails will be discussed. Then in later sections, the functional form of the maximum entropy method of moments probability distribution will be incorporated into Bayesian probability theory. It will be shown that Bayesian probability theory solves all of the problems with the maximum entropy method of moments. One gets posterior probabilities for the Lagrange multipliers, and, finally, one can put error bars on the resulting estimated density function.

  15. ON A GENERALIZATION OF THE MAXIMUM ENTROPY THEOREM OF BURG

    Directory of Open Access Journals (Sweden)

    JOSÉ MARCANO

    2017-01-01

    Full Text Available In this article we introduce some matrix manipulations that allow us to obtain a version of the original Christoffel-Darboux formula, which is of interest in many applications of linear algebra. Using these developments matrix and Jensen’s inequality, we obtain the main result of this proposal, which is the generalization of the maximum entropy theorem of Burg for multivariate processes.

  16. Application of the maximum entropy method to dynamical fermion simulations

    Science.gov (United States)

    Clowser, Jonathan

    This thesis presents results for spectral functions extracted from imaginary-time correlation functions obtained from Monte Carlo simulations using the Maximum Entropy Method (MEM). The advantages this method are (i) no a priori assumptions or parametrisations of the spectral function are needed, (ii) a unique solution exists and (iii) the statistical significance of the resulting image can be quantitatively analysed. The Gross Neveu model in d = 3 spacetime dimensions (GNM3) is a particularly interesting model to study with the MEM because at T = 0 it has a broken phase with a rich spectrum of mesonic bound states and a symmetric phase where there are resonances. Results for the elementary fermion, the Goldstone boson (pion), the sigma, the massive pseudoscalar meson and the symmetric phase resonances are presented. UKQCD Nf = 2 dynamical QCD data is also studied with MEM. Results are compared to those found from the quenched approximation, where the effects of quark loops in the QCD vacuum are neglected, to search for sea-quark effects in the extracted spectral functions. Information has been extract from the difficult axial spatial and scalar as well as the pseudoscalar, vector and axial temporal channels. An estimate for the non-singlet scalar mass in the chiral limit is given which is in agreement with the experimental value of Mao = 985 MeV.

  17. On the Five-Moment Hamburger Maximum Entropy Reconstruction

    Science.gov (United States)

    Summy, D. P.; Pullin, D. I.

    2018-05-01

    We consider the Maximum Entropy Reconstruction (MER) as a solution to the five-moment truncated Hamburger moment problem in one dimension. In the case of five monomial moment constraints, the probability density function (PDF) of the MER takes the form of the exponential of a quartic polynomial. This implies a possible bimodal structure in regions of moment space. An analytical model is developed for the MER PDF applicable near a known singular line in a centered, two-component, third- and fourth-order moment (μ _3 , μ _4 ) space, consistent with the general problem of five moments. The model consists of the superposition of a perturbed, centered Gaussian PDF and a small-amplitude packet of PDF-density, called the outlying moment packet (OMP), sitting far from the mean. Asymptotic solutions are obtained which predict the shape of the perturbed Gaussian and both the amplitude and position on the real line of the OMP. The asymptotic solutions show that the presence of the OMP gives rise to an MER solution that is singular along a line in (μ _3 , μ _4 ) space emanating from, but not including, the point representing a standard normal distribution, or thermodynamic equilibrium. We use this analysis of the OMP to develop a numerical regularization of the MER, creating a procedure we call the Hybrid MER (HMER). Compared with the MER, the HMER is a significant improvement in terms of robustness and efficiency while preserving accuracy in its prediction of other important distribution features, such as higher order moments.

  18. Using Maximum Entropy to Find Patterns in Genomes

    Science.gov (United States)

    Liu, Sophia; Hockenberry, Adam; Lancichinetti, Andrea; Jewett, Michael; Amaral, Luis

    The existence of over- and under-represented sequence motifs in genomes provides evidence of selective evolutionary pressures on biological mechanisms such as transcription, translation, ligand-substrate binding, and host immunity. To accurately identify motifs and other genome-scale patterns of interest, it is essential to be able to generate accurate null models that are appropriate for the sequences under study. There are currently no tools available that allow users to create random coding sequences with specified amino acid composition and GC content. Using the principle of maximum entropy, we developed a method that generates unbiased random sequences with pre-specified amino acid and GC content. Our method is the simplest way to obtain maximally unbiased random sequences that are subject to GC usage and primary amino acid sequence constraints. This approach can also be easily be expanded to create unbiased random sequences that incorporate more complicated constraints such as individual nucleotide usage or even di-nucleotide frequencies. The ability to generate correctly specified null models will allow researchers to accurately identify sequence motifs which will lead to a better understanding of biological processes. National Institute of General Medical Science, Northwestern University Presidential Fellowship, National Science Foundation, David and Lucile Packard Foundation, Camille Dreyfus Teacher Scholar Award.

  19. Maximum entropy reconstruction of the configurational density of states from microcanonical simulations

    International Nuclear Information System (INIS)

    Davis, Sergio

    2013-01-01

    In this work we develop a method for inferring the underlying configurational density of states of a molecular system by combining information from several microcanonical molecular dynamics or Monte Carlo simulations at different energies. This method is based on Jaynes' Maximum Entropy formalism (MaxEnt) for Bayesian statistical inference under known expectation values. We present results of its application to measure thermodynamic entropy and free energy differences in embedded-atom models of metals.

  20. Application of the maximum entropy method to profile analysis

    International Nuclear Information System (INIS)

    Armstrong, N.; Kalceff, W.; Cline, J.P.

    1999-01-01

    Full text: A maximum entropy (MaxEnt) method for analysing crystallite size- and strain-induced x-ray profile broadening is presented. This method treats the problems of determining the specimen profile, crystallite size distribution, and strain distribution in a general way by considering them as inverse problems. A common difficulty faced by many experimenters is their inability to determine a well-conditioned solution of the integral equation, which preserves the positivity of the profile or distribution. We show that the MaxEnt method overcomes this problem, while also enabling a priori information, in the form of a model, to be introduced into it. Additionally, we demonstrate that the method is fully quantitative, in that uncertainties in the solution profile or solution distribution can be determined and used in subsequent calculations, including mean particle sizes and rms strain. An outline of the MaxEnt method is presented for the specific problems of determining the specimen profile and crystallite or strain distributions for the correspondingly broadened profiles. This approach offers an alternative to standard methods such as those of Williamson-Hall and Warren-Averbach. An application of the MaxEnt method is demonstrated in the analysis of alumina size-broadened diffraction data (from NIST, Gaithersburg). It is used to determine the specimen profile and column-length distribution of the scattering domains. Finally, these results are compared with the corresponding Williamson-Hall and Warren-Averbach analyses. Copyright (1999) Australian X-ray Analytical Association Inc

  1. Maximum entropy method approach to the θ term

    International Nuclear Information System (INIS)

    Imachi, Masahiro; Shinno, Yasuhiko; Yoneyama, Hiroshi

    2004-01-01

    In Monte Carlo simulations of lattice field theory with a θ term, one confronts the complex weight problem, or the sign problem. This is circumvented by performing the Fourier transform of the topological charge distribution P(Q). This procedure, however, causes flattening phenomenon of the free energy f(θ), which makes study of the phase structure unfeasible. In order to treat this problem, we apply the maximum entropy method (MEM) to a Gaussian form of P(Q), which serves as a good example to test whether the MEM can be applied effectively to the θ term. We study the case with flattering as well as that without flattening. In the latter case, the results of the MEM agree with those obtained from the direct application of the Fourier transform. For the former, the MEM gives a smoother f(θ) than that of the Fourier transform. Among various default models investigated, the images which yield the least error do not show flattening, although some others cannot be excluded given the uncertainly related to statistical error. (author)

  2. Gravitational entropies in LTB dust models

    International Nuclear Information System (INIS)

    Sussman, Roberto A; Larena, Julien

    2014-01-01

    We consider generic Lemaître–Tolman–Bondi (LTB) dust models to probe the gravitational entropy proposals of Clifton, Ellis and Tavakol (CET) and of Hosoya and Buchert (HB). We also consider a variant of the HB proposal based on a suitable quasi-local scalar weighted average. We show that the conditions for entropy growth for all proposals are directly related to a negative correlation of similar fluctuations of the energy density and Hubble scalar. While this correlation is evaluated locally for the CET proposal, it must be evaluated in a non-local domain dependent manner for the two HB proposals. By looking at the fulfilment of these conditions at the relevant asymptotic limits we are able to provide a well grounded qualitative description of the full time evolution and radial asymptotic scaling of the three entropies in generic models. The following rigorous analytic results are obtained for the three proposals: (i) entropy grows when the density growing mode is dominant, (ii) all ever-expanding hyperbolic models reach a stable terminal equilibrium characterized by an inhomogeneous entropy maximum in their late time evolution; (iii) regions with decaying modes and collapsing elliptic models exhibit unstable equilibria associated with an entropy minimum (iv) near singularities the CET entropy diverges while the HB entropies converge; (v) the CET entropy converges for all models in the radial asymptotic range, whereas the HB entropies only converge for models asymptotic to a Friedmann–Lemaître–Robertson–Walker background. The fact that different independent proposals yield fairly similar conditions for entropy production, time evolution and radial scaling in generic LTB models seems to suggest that their common notion of a ‘gravitational entropy’ may be a theoretically robust concept applicable to more general spacetimes. (paper)

  3. Bayesian Reliability Estimation for Deteriorating Systems with Limited Samples Using the Maximum Entropy Approach

    Directory of Open Access Journals (Sweden)

    Ning-Cong Xiao

    2013-12-01

    Full Text Available In this paper the combinations of maximum entropy method and Bayesian inference for reliability assessment of deteriorating system is proposed. Due to various uncertainties, less data and incomplete information, system parameters usually cannot be determined precisely. These uncertainty parameters can be modeled by fuzzy sets theory and the Bayesian inference which have been proved to be useful for deteriorating systems under small sample sizes. The maximum entropy approach can be used to calculate the maximum entropy density function of uncertainty parameters more accurately for it does not need any additional information and assumptions. Finally, two optimization models are presented which can be used to determine the lower and upper bounds of systems probability of failure under vague environment conditions. Two numerical examples are investigated to demonstrate the proposed method.

  4. Application of the maximum entropy production principle to electrical systems

    International Nuclear Information System (INIS)

    Christen, Thomas

    2006-01-01

    For a simple class of electrical systems, the principle of the maximum entropy production rate (MaxEP) is discussed. First, we compare the MaxEP principle and the principle of the minimum entropy production rate and illustrate the superiority of the MaxEP principle for the example of two parallel constant resistors. Secondly, we show that the Steenbeck principle for the electric arc as well as the ohmic contact behaviour of space-charge limited conductors follow from the MaxEP principle. In line with work by Dewar, the investigations seem to suggest that the MaxEP principle can also be applied to systems far from equilibrium, provided appropriate information is available that enters the constraints of the optimization problem. Finally, we apply the MaxEP principle to a mesoscopic system and show that the universal conductance quantum, e 2 /h, of a one-dimensional ballistic conductor can be estimated

  5. Ergodicity, Maximum Entropy Production, and Steepest Entropy Ascent in the Proofs of Onsager's Reciprocal Relations

    Science.gov (United States)

    Benfenati, Francesco; Beretta, Gian Paolo

    2018-04-01

    We show that to prove the Onsager relations using the microscopic time reversibility one necessarily has to make an ergodic hypothesis, or a hypothesis closely linked to that. This is true in all the proofs of the Onsager relations in the literature: from the original proof by Onsager, to more advanced proofs in the context of linear response theory and the theory of Markov processes, to the proof in the context of the kinetic theory of gases. The only three proofs that do not require any kind of ergodic hypothesis are based on additional hypotheses on the macroscopic evolution: Ziegler's maximum entropy production principle (MEPP), the principle of time reversal invariance of the entropy production, or the steepest entropy ascent principle (SEAP).

  6. Maximum-entropy networks pattern detection, network reconstruction and graph combinatorics

    CERN Document Server

    Squartini, Tiziano

    2017-01-01

    This book is an introduction to maximum-entropy models of random graphs with given topological properties and their applications. Its original contribution is the reformulation of many seemingly different problems in the study of both real networks and graph theory within the unified framework of maximum entropy. Particular emphasis is put on the detection of structural patterns in real networks, on the reconstruction of the properties of networks from partial information, and on the enumeration and sampling of graphs with given properties.  After a first introductory chapter explaining the motivation, focus, aim and message of the book, chapter 2 introduces the formal construction of maximum-entropy ensembles of graphs with local topological constraints. Chapter 3 focuses on the problem of pattern detection in real networks and provides a powerful way to disentangle nontrivial higher-order structural features from those that can be traced back to simpler local constraints. Chapter 4 focuses on the problem o...

  7. Maximum entropy technique in the doublet structure analysis

    International Nuclear Information System (INIS)

    Belashev, B.Z.; Panebrattsev, Yu.A.; Shakhaliev, Eh.I.; Soroko, L.M.

    1998-01-01

    The Maximum Entropy Technique (MENT) for solution of the inverse problems is explained. The effective computer program for resolution of the nonlinear equations system encountered in the MENT has been developed and tested. The possibilities of the MENT have been demonstrated on the example of the MENT in the doublet structure analysis of noisy experimental data. The comparison of the MENT results with results of the Fourier algorithm technique without regularization is presented. The tolerant noise level is equal to 30% for MENT and only 0.1% for the Fourier algorithm

  8. Hydrodynamic Relaxation of an Electron Plasma to a Near-Maximum Entropy State

    International Nuclear Information System (INIS)

    Rodgers, D. J.; Servidio, S.; Matthaeus, W. H.; Mitchell, T. B.; Aziz, T.; Montgomery, D. C.

    2009-01-01

    Dynamical relaxation of a pure electron plasma in a Malmberg-Penning trap is studied, comparing experiments, numerical simulations and statistical theories of weakly dissipative two-dimensional (2D) turbulence. Simulations confirm that the dynamics are approximated well by a 2D hydrodynamic model. Statistical analysis favors a theoretical picture of relaxation to a near-maximum entropy state with constrained energy, circulation, and angular momentum. This provides evidence that 2D electron fluid relaxation in a turbulent regime is governed by principles of maximum entropy.

  9. The mechanics of granitoid systems and maximum entropy production rates.

    Science.gov (United States)

    Hobbs, Bruce E; Ord, Alison

    2010-01-13

    A model for the formation of granitoid systems is developed involving melt production spatially below a rising isotherm that defines melt initiation. Production of the melt volumes necessary to form granitoid complexes within 10(4)-10(7) years demands control of the isotherm velocity by melt advection. This velocity is one control on the melt flux generated spatially just above the melt isotherm, which is the control valve for the behaviour of the complete granitoid system. Melt transport occurs in conduits initiated as sheets or tubes comprising melt inclusions arising from Gurson-Tvergaard constitutive behaviour. Such conduits appear as leucosomes parallel to lineations and foliations, and ductile and brittle dykes. The melt flux generated at the melt isotherm controls the position of the melt solidus isotherm and hence the physical height of the Transport/Emplacement Zone. A conduit width-selection process, driven by changes in melt viscosity and constitutive behaviour, operates within the Transport Zone to progressively increase the width of apertures upwards. Melt can also be driven horizontally by gradients in topography; these horizontal fluxes can be similar in magnitude to vertical fluxes. Fluxes induced by deformation can compete with both buoyancy and topographic-driven flow over all length scales and results locally in transient 'ponds' of melt. Pluton emplacement is controlled by the transition in constitutive behaviour of the melt/magma from elastic-viscous at high temperatures to elastic-plastic-viscous approaching the melt solidus enabling finite thickness plutons to develop. The system involves coupled feedback processes that grow at the expense of heat supplied to the system and compete with melt advection. The result is that limits are placed on the size and time scale of the system. Optimal characteristics of the system coincide with a state of maximum entropy production rate. This journal is © 2010 The Royal Society

  10. Robust optimum design with maximum entropy method; Saidai entropy ho mochiita robust sei saitekika sekkeiho

    Energy Technology Data Exchange (ETDEWEB)

    Kawaguchi, K; Egashira, Y; Watanabe, G [Mazda Motor Corp., Hiroshima (Japan)

    1997-10-01

    Vehicle and unit performance change according to not only external causes represented by the environment such as temperature or weather, but also internal causes which are dispersion of component characteristics and manufacturing processes or aged deteriorations. We developed the design method to estimate thus performance distributions with maximum entropy method and to calculate specifications with high performance robustness using Fuzzy theory. This paper describes the details of these methods and examples applied to power window system. 3 refs., 7 figs., 4 tabs.

  11. Maximum Entropy Closure of Balance Equations for Miniband Semiconductor Superlattices

    Directory of Open Access Journals (Sweden)

    Luis L. Bonilla

    2016-07-01

    Full Text Available Charge transport in nanosized electronic systems is described by semiclassical or quantum kinetic equations that are often costly to solve numerically and difficult to reduce systematically to macroscopic balance equations for densities, currents, temperatures and other moments of macroscopic variables. The maximum entropy principle can be used to close the system of equations for the moments but its accuracy or range of validity are not always clear. In this paper, we compare numerical solutions of balance equations for nonlinear electron transport in semiconductor superlattices. The equations have been obtained from Boltzmann–Poisson kinetic equations very far from equilibrium for strong fields, either by the maximum entropy principle or by a systematic Chapman–Enskog perturbation procedure. Both approaches produce the same current-voltage characteristic curve for uniform fields. When the superlattices are DC voltage biased in a region where there are stable time periodic solutions corresponding to recycling and motion of electric field pulses, the differences between the numerical solutions produced by numerically solving both types of balance equations are smaller than the expansion parameter used in the perturbation procedure. These results and possible new research venues are discussed.

  12. Maximum entropy networks are more controllable than preferential attachment networks

    International Nuclear Information System (INIS)

    Hou, Lvlin; Small, Michael; Lao, Songyang

    2014-01-01

    A maximum entropy (ME) method to generate typical scale-free networks has been recently introduced. We investigate the controllability of ME networks and Barabási–Albert preferential attachment networks. Our experimental results show that ME networks are significantly more easily controlled than BA networks of the same size and the same degree distribution. Moreover, the control profiles are used to provide insight into control properties of both classes of network. We identify and classify the driver nodes and analyze the connectivity of their neighbors. We find that driver nodes in ME networks have fewer mutual neighbors and that their neighbors have lower average degree. We conclude that the properties of the neighbors of driver node sensitively affect the network controllability. Hence, subtle and important structural differences exist between BA networks and typical scale-free networks of the same degree distribution. - Highlights: • The controllability of maximum entropy (ME) and Barabási–Albert (BA) networks is investigated. • ME networks are significantly more easily controlled than BA networks of the same degree distribution. • The properties of the neighbors of driver node sensitively affect the network controllability. • Subtle and important structural differences exist between BA networks and typical scale-free networks

  13. The Structure of the Class of Maximum Tsallis–Havrda–Chavát Entropy Copulas

    Directory of Open Access Journals (Sweden)

    Jesús E. García

    2016-07-01

    Full Text Available A maximum entropy copula is the copula associated with the joint distribution, with prescribed marginal distributions on [ 0 , 1 ] , which maximizes the Tsallis–Havrda–Chavát entropy with q = 2 . We find necessary and sufficient conditions for each maximum entropy copula to be a copula in the class introduced in Rodríguez-Lallena and Úbeda-Flores (2004, and we also show that each copula in that class is a maximum entropy copula.

  14. Jarzynski equality in the context of maximum path entropy

    Science.gov (United States)

    González, Diego; Davis, Sergio

    2017-06-01

    In the global framework of finding an axiomatic derivation of nonequilibrium Statistical Mechanics from fundamental principles, such as the maximum path entropy - also known as Maximum Caliber principle -, this work proposes an alternative derivation of the well-known Jarzynski equality, a nonequilibrium identity of great importance today due to its applications to irreversible processes: biological systems (protein folding), mechanical systems, among others. This equality relates the free energy differences between two equilibrium thermodynamic states with the work performed when going between those states, through an average over a path ensemble. In this work the analysis of Jarzynski's equality will be performed using the formalism of inference over path space. This derivation highlights the wide generality of Jarzynski's original result, which could even be used in non-thermodynamical settings such as social systems, financial and ecological systems.

  15. Predicting the Outcome of NBA Playoffs Based on the Maximum Entropy Principle

    Directory of Open Access Journals (Sweden)

    Ge Cheng

    2016-12-01

    Full Text Available Predicting the outcome of National Basketball Association (NBA matches poses a challenging problem of interest to the research community as well as the general public. In this article, we formalize the problem of predicting NBA game results as a classification problem and apply the principle of Maximum Entropy to construct an NBA Maximum Entropy (NBAME model that fits to discrete statistics for NBA games, and then predict the outcomes of NBA playoffs using the model. Our results reveal that the model is able to predict the winning team with 74.4% accuracy, outperforming other classical machine learning algorithms that could only afford a maximum prediction accuracy of 70.6% in the experiments that we performed.

  16. LensEnt2: Maximum-entropy weak lens reconstruction

    Science.gov (United States)

    Marshall, P. J.; Hobson, M. P.; Gull, S. F.; Bridle, S. L.

    2013-08-01

    LensEnt2 is a maximum entropy reconstructor of weak lensing mass maps. The method takes each galaxy shape as an independent estimator of the reduced shear field and incorporates an intrinsic smoothness, determined by Bayesian methods, into the reconstruction. The uncertainties from both the intrinsic distribution of galaxy shapes and galaxy shape estimation are carried through to the final mass reconstruction, and the mass within arbitrarily shaped apertures are calculated with corresponding uncertainties. The input is a galaxy ellipticity catalog with each measured galaxy shape treated as a noisy tracer of the reduced shear field, which is inferred on a fine pixel grid assuming positivity, and smoothness on scales of w arcsec where w is an input parameter. The ICF width w can be chosen by computing the evidence for it.

  17. Venus atmosphere profile from a maximum entropy principle

    Directory of Open Access Journals (Sweden)

    L. N. Epele

    2007-10-01

    Full Text Available The variational method with constraints recently developed by Verkley and Gerkema to describe maximum-entropy atmospheric profiles is generalized to ideal gases but with temperature-dependent specific heats. In so doing, an extended and non standard potential temperature is introduced that is well suited for tackling the problem under consideration. This new formalism is successfully applied to the atmosphere of Venus. Three well defined regions emerge in this atmosphere up to a height of 100 km from the surface: the lowest one up to about 35 km is adiabatic, a transition layer located at the height of the cloud deck and finally a third region which is practically isothermal.

  18. LIBOR troubles: Anomalous movements detection based on maximum entropy

    Science.gov (United States)

    Bariviera, Aurelio F.; Martín, María T.; Plastino, Angelo; Vampa, Victoria

    2016-05-01

    According to the definition of the London Interbank Offered Rate (LIBOR), contributing banks should give fair estimates of their own borrowing costs in the interbank market. Between 2007 and 2009, several banks made inappropriate submissions of LIBOR, sometimes motivated by profit-seeking from their trading positions. In 2012, several newspapers' articles began to cast doubt on LIBOR integrity, leading surveillance authorities to conduct investigations on banks' behavior. Such procedures resulted in severe fines imposed to involved banks, who recognized their financial inappropriate conduct. In this paper, we uncover such unfair behavior by using a forecasting method based on the Maximum Entropy principle. Our results are robust against changes in parameter settings and could be of great help for market surveillance.

  19. Maximum Entropy and Probability Kinematics Constrained by Conditionals

    Directory of Open Access Journals (Sweden)

    Stefan Lukits

    2015-03-01

    Full Text Available Two open questions of inductive reasoning are solved: (1 does the principle of maximum entropy (PME give a solution to the obverse Majerník problem; and (2 isWagner correct when he claims that Jeffrey’s updating principle (JUP contradicts PME? Majerník shows that PME provides unique and plausible marginal probabilities, given conditional probabilities. The obverse problem posed here is whether PME also provides such conditional probabilities, given certain marginal probabilities. The theorem developed to solve the obverse Majerník problem demonstrates that in the special case introduced by Wagner PME does not contradict JUP, but elegantly generalizes it and offers a more integrated approach to probability updating.

  20. A maximum entropy reconstruction technique for tomographic particle image velocimetry

    International Nuclear Information System (INIS)

    Bilsky, A V; Lozhkin, V A; Markovich, D M; Tokarev, M P

    2013-01-01

    This paper studies a novel approach for reducing tomographic PIV computational complexity. The proposed approach is an algebraic reconstruction technique, termed MENT (maximum entropy). This technique computes the three-dimensional light intensity distribution several times faster than SMART, using at least ten times less memory. Additionally, the reconstruction quality remains nearly the same as with SMART. This paper presents the theoretical computation performance comparison for MENT, SMART and MART, followed by validation using synthetic particle images. Both the theoretical assessment and validation of synthetic images demonstrate significant computational time reduction. The data processing accuracy of MENT was compared to that of SMART in a slot jet experiment. A comparison of the average velocity profiles shows a high level of agreement between the results obtained with MENT and those obtained with SMART. (paper)

  1. Tsallis distribution as a standard maximum entropy solution with 'tail' constraint

    International Nuclear Information System (INIS)

    Bercher, J.-F.

    2008-01-01

    We show that Tsallis' distributions can be derived from the standard (Shannon) maximum entropy setting, by incorporating a constraint on the divergence between the distribution and another distribution imagined as its tail. In this setting, we find an underlying entropy which is the Renyi entropy. Furthermore, escort distributions and generalized means appear as a direct consequence of the construction. Finally, the 'maximum entropy tail distribution' is identified as a Generalized Pareto Distribution

  2. Comparison Between Bayesian and Maximum Entropy Analyses of Flow Networks†

    Directory of Open Access Journals (Sweden)

    Steven H. Waldrip

    2017-02-01

    Full Text Available We compare the application of Bayesian inference and the maximum entropy (MaxEnt method for the analysis of flow networks, such as water, electrical and transport networks. The two methods have the advantage of allowing a probabilistic prediction of flow rates and other variables, when there is insufficient information to obtain a deterministic solution, and also allow the effects of uncertainty to be included. Both methods of inference update a prior to a posterior probability density function (pdf by the inclusion of new information, in the form of data or constraints. The MaxEnt method maximises an entropy function subject to constraints, using the method of Lagrange multipliers,to give the posterior, while the Bayesian method finds its posterior by multiplying the prior with likelihood functions incorporating the measured data. In this study, we examine MaxEnt using soft constraints, either included in the prior or as probabilistic constraints, in addition to standard moment constraints. We show that when the prior is Gaussian,both Bayesian inference and the MaxEnt method with soft prior constraints give the same posterior means, but their covariances are different. In the Bayesian method, the interactions between variables are applied through the likelihood function, using second or higher-order cross-terms within the posterior pdf. In contrast, the MaxEnt method incorporates interactions between variables using Lagrange multipliers, avoiding second-order correlation terms in the posterior covariance. The MaxEnt method with soft prior constraints, therefore, has a numerical advantage over Bayesian inference, in that the covariance terms are avoided in its integrations. The second MaxEnt method with soft probabilistic constraints is shown to give posterior means of similar, but not identical, structure to the other two methods, due to its different formulation.

  3. Application of Maximum Entropy Distribution to the Statistical Properties of Wave Groups

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    The new distributions of the statistics of wave groups based on the maximum entropy principle are presented. The maximum entropy distributions appear to be superior to conventional distributions when applied to a limited amount of information. Its applications to the wave group properties show the effectiveness of the maximum entropy distribution. FFT filtering method is employed to obtain the wave envelope fast and efficiently. Comparisons of both the maximum entropy distribution and the distribution of Longuet-Higgins (1984) with the laboratory wind-wave data show that the former gives a better fit.

  4. The Data-Constrained Generalized Maximum Entropy Estimator of the GLM: Asymptotic Theory and Inference

    Directory of Open Access Journals (Sweden)

    Nicholas Scott Cardell

    2013-05-01

    Full Text Available Maximum entropy methods of parameter estimation are appealing because they impose no additional structure on the data, other than that explicitly assumed by the analyst. In this paper we prove that the data constrained GME estimator of the general linear model is consistent and asymptotically normal. The approach we take in establishing the asymptotic properties concomitantly identifies a new computationally efficient method for calculating GME estimates. Formulae are developed to compute asymptotic variances and to perform Wald, likelihood ratio, and Lagrangian multiplier statistical tests on model parameters. Monte Carlo simulations are provided to assess the performance of the GME estimator in both large and small sample situations. Furthermore, we extend our results to maximum cross-entropy estimators and indicate a variant of the GME estimator that is unbiased. Finally, we discuss the relationship of GME estimators to Bayesian estimators, pointing out the conditions under which an unbiased GME estimator would be efficient.

  5. The Kalman Filter Revisited Using Maximum Relative Entropy

    Directory of Open Access Journals (Sweden)

    Adom Giffin

    2014-02-01

    Full Text Available In 1960, Rudolf E. Kalman created what is known as the Kalman filter, which is a way to estimate unknown variables from noisy measurements. The algorithm follows the logic that if the previous state of the system is known, it could be used as the best guess for the current state. This information is first applied a priori to any measurement by using it in the underlying dynamics of the system. Second, measurements of the unknown variables are taken. These two pieces of information are taken into account to determine the current state of the system. Bayesian inference is specifically designed to accommodate the problem of updating what we think of the world based on partial or uncertain information. In this paper, we present a derivation of the general Bayesian filter, then adapt it for Markov systems. A simple example is shown for pedagogical purposes. We also show that by using the Kalman assumptions or “constraints”, we can arrive at the Kalman filter using the method of maximum (relative entropy (MrE, which goes beyond Bayesian methods. Finally, we derive a generalized, nonlinear filter using MrE, where the original Kalman Filter is a special case. We further show that the variable relationship can be any function, and thus, approximations, such as the extended Kalman filter, the unscented Kalman filter and other Kalman variants are special cases as well.

  6. Image Segmentation using a Refined Comprehensive Learning Particle Swarm Optimizer for Maximum Tsallis Entropy Thresholding

    OpenAIRE

    L. Jubair Ahmed; A. Ebenezer Jeyakumar

    2013-01-01

    Thresholding is one of the most important techniques for performing image segmentation. In this paper to compute optimum thresholds for Maximum Tsallis entropy thresholding (MTET) model, a new hybrid algorithm is proposed by integrating the Comprehensive Learning Particle Swarm Optimizer (CPSO) with the Powell’s Conjugate Gradient (PCG) method. Here the CPSO will act as the main optimizer for searching the near-optimal thresholds while the PCG method will be used to fine tune the best solutio...

  7. Multifield stochastic particle production: beyond a maximum entropy ansatz

    Energy Technology Data Exchange (ETDEWEB)

    Amin, Mustafa A.; Garcia, Marcos A.G.; Xie, Hong-Yi; Wen, Osmond, E-mail: mustafa.a.amin@gmail.com, E-mail: marcos.garcia@rice.edu, E-mail: hxie39@wisc.edu, E-mail: ow4@rice.edu [Physics and Astronomy Department, Rice University, 6100 Main Street, Houston, TX 77005 (United States)

    2017-09-01

    We explore non-adiabatic particle production for N {sub f} coupled scalar fields in a time-dependent background with stochastically varying effective masses, cross-couplings and intervals between interactions. Under the assumption of weak scattering per interaction, we provide a framework for calculating the typical particle production rates after a large number of interactions. After setting up the framework, for analytic tractability, we consider interactions (effective masses and cross couplings) characterized by series of Dirac-delta functions in time with amplitudes and locations drawn from different distributions. Without assuming that the fields are statistically equivalent, we present closed form results (up to quadratures) for the asymptotic particle production rates for the N {sub f}=1 and N {sub f}=2 cases. We also present results for the general N {sub f} >2 case, but with more restrictive assumptions. We find agreement between our analytic results and direct numerical calculations of the total occupation number of the produced particles, with departures that can be explained in terms of violation of our assumptions. We elucidate the precise connection between the maximum entropy ansatz (MEA) used in Amin and Baumann (2015) and the underlying statistical distribution of the self and cross couplings. We provide and justify a simple to use (MEA-inspired) expression for the particle production rate, which agrees with our more detailed treatment when the parameters characterizing the effective mass and cross-couplings between fields are all comparable to each other. However, deviations are seen when some parameters differ significantly from others. We show that such deviations become negligible for a broad range of parameters when N {sub f}>> 1.

  8. Spectrum unfolding in X-ray spectrometry using the maximum entropy method

    International Nuclear Information System (INIS)

    Fernandez, Jorge E.; Scot, Viviana; Di Giulio, Eugenio

    2014-01-01

    The solution of the unfolding problem is an ever-present issue in X-ray spectrometry. The maximum entropy technique solves this problem by taking advantage of some known a priori physical information and by ensuring an outcome with only positive values. This method is implemented in MAXED (MAXimum Entropy Deconvolution), a software code contained in the package UMG (Unfolding with MAXED and GRAVEL) developed at PTB and distributed by NEA Data Bank. This package contains also the code GRAVEL (used to estimate the precision of the solution). This article introduces the new code UMESTRAT (Unfolding Maximum Entropy STRATegy) which applies a semi-automatic strategy to solve the unfolding problem by using a suitable combination of MAXED and GRAVEL for applications in X-ray spectrometry. Some examples of the use of UMESTRAT are shown, demonstrating its capability to remove detector artifacts from the measured spectrum consistently with the model used for the detector response function (DRF). - Highlights: ► A new strategy to solve the unfolding problem in X-ray spectrometry is presented. ► The presented strategy uses a suitable combination of the codes MAXED and GRAVEL. ► The applied strategy provides additional information on the Detector Response Function. ► The code UMESTRAT is developed to apply this new strategy in a semi-automatic mode

  9. Maximizing entropy of image models for 2-D constrained coding

    DEFF Research Database (Denmark)

    Forchhammer, Søren; Danieli, Matteo; Burini, Nino

    2010-01-01

    This paper considers estimating and maximizing the entropy of two-dimensional (2-D) fields with application to 2-D constrained coding. We consider Markov random fields (MRF), which have a non-causal description, and the special case of Pickard random fields (PRF). The PRF are 2-D causal finite...... context models, which define stationary probability distributions on finite rectangles and thus allow for calculation of the entropy. We consider two binary constraints and revisit the hard square constraint given by forbidding neighboring 1s and provide novel results for the constraint that no uniform 2...... £ 2 squares contains all 0s or all 1s. The maximum values of the entropy for the constraints are estimated and binary PRF satisfying the constraint are characterized and optimized w.r.t. the entropy. The maximum binary PRF entropy is 0.839 bits/symbol for the no uniform squares constraint. The entropy...

  10. Exact Maximum-Entropy Estimation with Feynman Diagrams

    Science.gov (United States)

    Netser Zernik, Amitai; Schlank, Tomer M.; Tessler, Ran J.

    2018-02-01

    A longstanding open problem in statistics is finding an explicit expression for the probability measure which maximizes entropy with respect to given constraints. In this paper a solution to this problem is found, using perturbative Feynman calculus. The explicit expression is given as a sum over weighted trees.

  11. Network Inference and Maximum Entropy Estimation on Information Diagrams

    Czech Academy of Sciences Publication Activity Database

    Martin, E.A.; Hlinka, J.; Meinke, A.; Děchtěrenko, Filip; Tintěra, J.; Oliver, I.; Davidsen, J.

    2017-01-01

    Roč. 7, č. 1 (2017), s. 1-15, č. článku 7062. ISSN 2045-2322 R&D Projects: GA ČR GA13-23940S Institutional support: RVO:68081740 Keywords : complex networks * mutual information * entropy maximization * fMRI Subject RIV: AN - Psychology OBOR OECD: Cognitive sciences Impact factor: 4.259, year: 2016

  12. Principle of maximum entropy for reliability analysis in the design of machine components

    Science.gov (United States)

    Zhang, Yimin

    2018-03-01

    We studied the reliability of machine components with parameters that follow an arbitrary statistical distribution using the principle of maximum entropy (PME). We used PME to select the statistical distribution that best fits the available information. We also established a probability density function (PDF) and a failure probability model for the parameters of mechanical components using the concept of entropy and the PME. We obtained the first four moments of the state function for reliability analysis and design. Furthermore, we attained an estimate of the PDF with the fewest human bias factors using the PME. This function was used to calculate the reliability of the machine components, including a connecting rod, a vehicle half-shaft, a front axle, a rear axle housing, and a leaf spring, which have parameters that typically follow a non-normal distribution. Simulations were conducted for comparison. This study provides a design methodology for the reliability of mechanical components for practical engineering projects.

  13. Empirical study on entropy models of cellular manufacturing systems

    Institute of Scientific and Technical Information of China (English)

    Zhifeng Zhang; Renbin Xiao

    2009-01-01

    From the theoretical point of view,the states of manufacturing resources can be monitored and assessed through the amount of information needed to describe their technological structure and operational state.The amount of information needed to describe cellular manufacturing systems is investigated by two measures:the structural entropy and the operational entropy.Based on the Shannon entropy,the models of the structural entropy and the operational entropy of cellular manufacturing systems are developed,and the cognizance of the states of manufacturing resources is also illustrated.Scheduling is introduced to measure the entropy models of cellular manufacturing systems,and the feasible concepts of maximum schedule horizon and schedule adherence are advanced to quantitatively evaluate the effectiveness of schedules.Finally,an example is used to demonstrate the validity of the proposed methodology.

  14. Power spectrum of the geomagnetic field by the maximum entropy method

    International Nuclear Information System (INIS)

    Kantor, I.J.; Trivedi, N.B.

    1980-01-01

    Monthly mean values of Vassouras (state of Rio de Janeiro) geomagnetic field are analyzed us the maximum entropy method. The method is described and compared with other methods of spectral analysis, and its advantages and disadvantages are presented. (Author) [pt

  15. Unification of field theory and maximum entropy methods for learning probability densities

    OpenAIRE

    Kinney, Justin B.

    2014-01-01

    The need to estimate smooth probability distributions (a.k.a. probability densities) from finite sampled data is ubiquitous in science. Many approaches to this problem have been described, but none is yet regarded as providing a definitive solution. Maximum entropy estimation and Bayesian field theory are two such approaches. Both have origins in statistical physics, but the relationship between them has remained unclear. Here I unify these two methods by showing that every maximum entropy de...

  16. Network Inference and Maximum Entropy Estimation on Information Diagrams

    Czech Academy of Sciences Publication Activity Database

    Martin, E.A.; Hlinka, Jaroslav; Meinke, A.; Děchtěrenko, Filip; Tintěra, J.; Oliver, I.; Davidsen, J.

    2017-01-01

    Roč. 7, č. 1 (2017), č. článku 7062. ISSN 2045-2322 R&D Projects: GA ČR GA13-23940S; GA MZd(CZ) NV15-29835A Grant - others:GA MŠk(CZ) LO1611 Institutional support: RVO:67985807 Keywords : complex networks * mutual information * entropy maximization * fMRI Subject RIV: BD - Theory of Information OBOR OECD: Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8) Impact factor: 4.259, year: 2016

  17. A Research on Maximum Symbolic Entropy from Intrinsic Mode Function and Its Application in Fault Diagnosis

    Directory of Open Access Journals (Sweden)

    Zhuofei Xu

    2017-01-01

    Full Text Available Empirical mode decomposition (EMD is a self-adaptive analysis method for nonlinear and nonstationary signals. It has been widely applied to machinery fault diagnosis and structural damage detection. A novel feature, maximum symbolic entropy of intrinsic mode function based on EMD, is proposed to enhance the ability of recognition of EMD in this paper. First, a signal is decomposed into a collection of intrinsic mode functions (IMFs based on the local characteristic time scale of the signal, and then IMFs are transformed into a serious of symbolic sequence with different parameters. Second, it can be found that the entropies of symbolic IMFs are quite different. However, there is always a maximum value for a certain symbolic IMF. Third, take the maximum symbolic entropy as features to describe IMFs from a signal. Finally, the proposed features are applied to evaluate the effect of maximum symbolic entropy in fault diagnosis of rolling bearing, and then the maximum symbolic entropy is compared with other standard time analysis features in a contrast experiment. Although maximum symbolic entropy is only a time domain feature, it can reveal the signal characteristic information accurately. It can also be used in other fields related to EMD method.

  18. Unification of field theory and maximum entropy methods for learning probability densities

    Science.gov (United States)

    Kinney, Justin B.

    2015-09-01

    The need to estimate smooth probability distributions (a.k.a. probability densities) from finite sampled data is ubiquitous in science. Many approaches to this problem have been described, but none is yet regarded as providing a definitive solution. Maximum entropy estimation and Bayesian field theory are two such approaches. Both have origins in statistical physics, but the relationship between them has remained unclear. Here I unify these two methods by showing that every maximum entropy density estimate can be recovered in the infinite smoothness limit of an appropriate Bayesian field theory. I also show that Bayesian field theory estimation can be performed without imposing any boundary conditions on candidate densities, and that the infinite smoothness limit of these theories recovers the most common types of maximum entropy estimates. Bayesian field theory thus provides a natural test of the maximum entropy null hypothesis and, furthermore, returns an alternative (lower entropy) density estimate when the maximum entropy hypothesis is falsified. The computations necessary for this approach can be performed rapidly for one-dimensional data, and software for doing this is provided.

  19. Unification of field theory and maximum entropy methods for learning probability densities.

    Science.gov (United States)

    Kinney, Justin B

    2015-09-01

    The need to estimate smooth probability distributions (a.k.a. probability densities) from finite sampled data is ubiquitous in science. Many approaches to this problem have been described, but none is yet regarded as providing a definitive solution. Maximum entropy estimation and Bayesian field theory are two such approaches. Both have origins in statistical physics, but the relationship between them has remained unclear. Here I unify these two methods by showing that every maximum entropy density estimate can be recovered in the infinite smoothness limit of an appropriate Bayesian field theory. I also show that Bayesian field theory estimation can be performed without imposing any boundary conditions on candidate densities, and that the infinite smoothness limit of these theories recovers the most common types of maximum entropy estimates. Bayesian field theory thus provides a natural test of the maximum entropy null hypothesis and, furthermore, returns an alternative (lower entropy) density estimate when the maximum entropy hypothesis is falsified. The computations necessary for this approach can be performed rapidly for one-dimensional data, and software for doing this is provided.

  20. Estimation of typhoon rainfall in GaoPing River: A Multivariate Maximum Entropy Method

    Science.gov (United States)

    Pei-Jui, Wu; Hwa-Lung, Yu

    2016-04-01

    The heavy rainfall from typhoons is the main factor of the natural disaster in Taiwan, which causes the significant loss of human lives and properties. Statistically average 3.5 typhoons invade Taiwan every year, and the serious typhoon, Morakot in 2009, impacted Taiwan in recorded history. Because the duration, path and intensity of typhoon, also affect the temporal and spatial rainfall type in specific region , finding the characteristics of the typhoon rainfall type is advantageous when we try to estimate the quantity of rainfall. This study developed a rainfall prediction model and can be divided three parts. First, using the EEOF(extended empirical orthogonal function) to classify the typhoon events, and decompose the standard rainfall type of all stations of each typhoon event into the EOF and PC(principal component). So we can classify the typhoon events which vary similarly in temporally and spatially as the similar typhoon types. Next, according to the classification above, we construct the PDF(probability density function) in different space and time by means of using the multivariate maximum entropy from the first to forth moment statistically. Therefore, we can get the probability of each stations of each time. Final we use the BME(Bayesian Maximum Entropy method) to construct the typhoon rainfall prediction model , and to estimate the rainfall for the case of GaoPing river which located in south of Taiwan.This study could be useful for typhoon rainfall predictions in future and suitable to government for the typhoon disaster prevention .

  1. Combined analysis of steady state and transient transport by the maximum entropy method

    Energy Technology Data Exchange (ETDEWEB)

    Giannone, L.; Stroth, U; Koellermeyer, J [Association Euratom-Max-Planck-Institut fuer Plasmaphysik, Garching (Germany); and others

    1996-04-01

    A new maximum entropy approach has been applied to analyse three types of transient transport experiments. For sawtooth propagation experiments in the ASDEX Upgrade and ECRH power modulation and power-switching experiments in the Wendelstein 7-AS Stellarator, either the time evolution of the temperature perturbation or the phase and amplitude of the modulated temperature perturbation are used as non-linear constraints to the {chi}{sub e} profile to be fitted. Simultaneously, the constraints given by the equilibrium temperature profile for steady-state power balance are fitted. In the maximum entropy formulation, the flattest {chi}{sub e} profile consistent with the constraints is found. It was found that {chi}{sub e} determined from sawtooth propagation was greater than the power balance value by a factor of five in the ASDEX Upgrade. From power modulation experiments, employing the measurements of four modulation frequencies simultaneously, the power deposition profile as well as the {chi}{sub e} profile could be determined. A comparison of the predictions of a time-independent {chi}{sub e} model and a power-dependent {chi}{sub e} model is made. The power-switching experiments show that the {chi}{sub e} profile must change within a millisecond to a new value consistent with the power balance value at the new input power. Neither power deposition broadening due to suprathermal electrons nor temperature or gradient dependences of {chi}{sub e} can explain this observation. (author).

  2. Vertical and horizontal processes in the global atmosphere and the maximum entropy production conjecture

    Directory of Open Access Journals (Sweden)

    S. Pascale

    2012-01-01

    Full Text Available The objective of this paper is to reconsider the Maximum Entropy Production conjecture (MEP in the context of a very simple two-dimensional zonal-vertical climate model able to represent the total material entropy production due at the same time to both horizontal and vertical heat fluxes. MEP is applied first to a simple four-box model of climate which accounts for both horizontal and vertical material heat fluxes. It is shown that, under condition of fixed insolation, a MEP solution is found with reasonably realistic temperature and heat fluxes, thus generalising results from independent two-box horizontal or vertical models. It is also shown that the meridional and the vertical entropy production terms are independently involved in the maximisation and thus MEP can be applied to each subsystem with fixed boundary conditions. We then extend the four-box model by increasing its resolution, and compare it with GCM output. A MEP solution is found which is fairly realistic as far as the horizontal large scale organisation of the climate is concerned whereas the vertical structure looks to be unrealistic and presents seriously unstable features. This study suggest that the thermal meridional structure of the atmosphere is predicted fairly well by MEP once the insolation is given but the vertical structure of the atmosphere cannot be predicted satisfactorily by MEP unless constraints are imposed to represent the determination of longwave absorption by water vapour and clouds as a function of the state of the climate. Furthermore an order-of-magnitude estimate of contributions to the material entropy production due to horizontal and vertical processes within the climate system is provided by using two different methods. In both cases we found that approximately 40 mW m−2 K−1 of material entropy production is due to vertical heat transport and 5–7 mW m−2 K−1 to horizontal heat transport.

  3. Estimation of Lithological Classification in Taipei Basin: A Bayesian Maximum Entropy Method

    Science.gov (United States)

    Wu, Meng-Ting; Lin, Yuan-Chien; Yu, Hwa-Lung

    2015-04-01

    In environmental or other scientific applications, we must have a certain understanding of geological lithological composition. Because of restrictions of real conditions, only limited amount of data can be acquired. To find out the lithological distribution in the study area, many spatial statistical methods used to estimate the lithological composition on unsampled points or grids. This study applied the Bayesian Maximum Entropy (BME method), which is an emerging method of the geological spatiotemporal statistics field. The BME method can identify the spatiotemporal correlation of the data, and combine not only the hard data but the soft data to improve estimation. The data of lithological classification is discrete categorical data. Therefore, this research applied Categorical BME to establish a complete three-dimensional Lithological estimation model. Apply the limited hard data from the cores and the soft data generated from the geological dating data and the virtual wells to estimate the three-dimensional lithological classification in Taipei Basin. Keywords: Categorical Bayesian Maximum Entropy method, Lithological Classification, Hydrogeological Setting

  4. Analysis of neutron reflectivity data: maximum entropy, Bayesian spectral analysis and speckle holography

    International Nuclear Information System (INIS)

    Sivia, D.S.; Hamilton, W.A.; Smith, G.S.

    1991-01-01

    The analysis of neutron reflectivity data to obtain nuclear scattering length density profiles is akin to the notorious phaseless Fourier problem, well known in many fields such as crystallography. Current methods of analysis culminate in the refinement of a few parameters of a functional model, and are often preceded by a long and laborious process of trial and error. We start by discussing the use of maximum entropy for obtained 'free-form' solutions of the density profile, as an alternative to the trial and error phase when a functional model is not available. Next we consider a Bayesian spectral analysis approach, which is appropriate for optimising the parameters of a simple (but adequate) type of model when the number of parameters is not known. Finally, we suggest a novel experimental procedure, the analogue of astronomical speckle holography, designed to alleviate the ambiguity problems inherent in traditional reflectivity measurements. (orig.)

  5. Spatio-temporal spike train analysis for large scale networks using the maximum entropy principle and Monte Carlo method

    International Nuclear Information System (INIS)

    Nasser, Hassan; Cessac, Bruno; Marre, Olivier

    2013-01-01

    Understanding the dynamics of neural networks is a major challenge in experimental neuroscience. For that purpose, a modelling of the recorded activity that reproduces the main statistics of the data is required. In the first part, we present a review on recent results dealing with spike train statistics analysis using maximum entropy models (MaxEnt). Most of these studies have focused on modelling synchronous spike patterns, leaving aside the temporal dynamics of the neural activity. However, the maximum entropy principle can be generalized to the temporal case, leading to Markovian models where memory effects and time correlations in the dynamics are properly taken into account. In the second part, we present a new method based on Monte Carlo sampling which is suited for the fitting of large-scale spatio-temporal MaxEnt models. The formalism and the tools presented here will be essential to fit MaxEnt spatio-temporal models to large neural ensembles. (paper)

  6. A Two-Stage Maximum Entropy Prior of Location Parameter with a Stochastic Multivariate Interval Constraint and Its Properties

    Directory of Open Access Journals (Sweden)

    Hea-Jung Kim

    2016-05-01

    Full Text Available This paper proposes a two-stage maximum entropy prior to elicit uncertainty regarding a multivariate interval constraint of the location parameter of a scale mixture of normal model. Using Shannon’s entropy, this study demonstrates how the prior, obtained by using two stages of a prior hierarchy, appropriately accounts for the information regarding the stochastic constraint and suggests an objective measure of the degree of belief in the stochastic constraint. The study also verifies that the proposed prior plays the role of bridging the gap between the canonical maximum entropy prior of the parameter with no interval constraint and that with a certain multivariate interval constraint. It is shown that the two-stage maximum entropy prior belongs to the family of rectangle screened normal distributions that is conjugate for samples from a normal distribution. Some properties of the prior density, useful for developing a Bayesian inference of the parameter with the stochastic constraint, are provided. We also propose a hierarchical constrained scale mixture of normal model (HCSMN, which uses the prior density to estimate the constrained location parameter of a scale mixture of normal model and demonstrates the scope of its applicability.

  7. Maximum entropy approach to statistical inference for an ocean acoustic waveguide.

    Science.gov (United States)

    Knobles, D P; Sagers, J D; Koch, R A

    2012-02-01

    A conditional probability distribution suitable for estimating the statistical properties of ocean seabed parameter values inferred from acoustic measurements is derived from a maximum entropy principle. The specification of the expectation value for an error function constrains the maximization of an entropy functional. This constraint determines the sensitivity factor (β) to the error function of the resulting probability distribution, which is a canonical form that provides a conservative estimate of the uncertainty of the parameter values. From the conditional distribution, marginal distributions for individual parameters can be determined from integration over the other parameters. The approach is an alternative to obtaining the posterior probability distribution without an intermediary determination of the likelihood function followed by an application of Bayes' rule. In this paper the expectation value that specifies the constraint is determined from the values of the error function for the model solutions obtained from a sparse number of data samples. The method is applied to ocean acoustic measurements taken on the New Jersey continental shelf. The marginal probability distribution for the values of the sound speed ratio at the surface of the seabed and the source levels of a towed source are examined for different geoacoustic model representations. © 2012 Acoustical Society of America

  8. A Bayes-Maximum Entropy method for multi-sensor data fusion

    Energy Technology Data Exchange (ETDEWEB)

    Beckerman, M.

    1991-01-01

    In this paper we introduce a Bayes-Maximum Entropy formalism for multi-sensor data fusion, and present an application of this methodology to the fusion of ultrasound and visual sensor data as acquired by a mobile robot. In our approach the principle of maximum entropy is applied to the construction of priors and likelihoods from the data. Distances between ultrasound and visual points of interest in a dual representation are used to define Gibbs likelihood distributions. Both one- and two-dimensional likelihoods are presented, and cast into a form which makes explicit their dependence upon the mean. The Bayesian posterior distributions are used to test a null hypothesis, and Maximum Entropy Maps used for navigation are updated using the resulting information from the dual representation. 14 refs., 9 figs.

  9. Spatial data modelling and maximum entropy theory

    Czech Academy of Sciences Publication Activity Database

    Klimešová, Dana; Ocelíková, E.

    2005-01-01

    Roč. 51, č. 2 (2005), s. 80-83 ISSN 0139-570X Institutional research plan: CEZ:AV0Z10750506 Keywords : spatial data classification * distribution function * error distribution Subject RIV: BD - Theory of Information

  10. Entropy - Some Cosmological Questions Answered by Model of Expansive Nondecelerative Universe

    Directory of Open Access Journals (Sweden)

    Miroslav Sukenik

    2003-01-01

    Full Text Available Abstract: The paper summarizes the background of Expansive Nondecelerative Universe model and its potential to offer answers to some open cosmological questions related to entropy. Three problems are faced in more detail, namely that of Hawkings phenomenon of black holes evaporation, maximum entropy of the Universe during its evolution, and time evolution of specific entropy.

  11. Maximum entropy based reconstruction of soft X ray emissivity profiles in W7-AS

    International Nuclear Information System (INIS)

    Ertl, K.; Linden, W. von der; Dose, V.; Weller, A.

    1996-01-01

    The reconstruction of 2-D emissivity profiles from soft X ray tomography measurements constitutes a highly underdetermined and ill-posed inversion problem, because of the restricted viewing access, the number of chords and the increased noise level in most plasma devices. An unbiased and consistent probabilistic approach within the framework of Bayesian inference is provided by the maximum entropy method, which is independent of model assumptions, but allows any prior knowledge available to be incorporated. The formalism is applied to the reconstruction of emissivity profiles in an NBI heated plasma discharge to determine the dependence of the Shafranov shift on β, the reduction of which was a particular objective in designing the advanced W7-AS stellarator. (author). 40 refs, 7 figs

  12. Study on Droplet Size and Velocity Distributions of a Pressure Swirl Atomizer Based on the Maximum Entropy Formalism

    Directory of Open Access Journals (Sweden)

    Kai Yan

    2015-01-01

    Full Text Available A predictive model for droplet size and velocity distributions of a pressure swirl atomizer has been proposed based on the maximum entropy formalism (MEF. The constraint conditions of the MEF model include the conservation laws of mass, momentum, and energy. The effects of liquid swirling strength, Weber number, gas-to-liquid axial velocity ratio and gas-to-liquid density ratio on the droplet size and velocity distributions of a pressure swirl atomizer are investigated. Results show that model based on maximum entropy formalism works well to predict droplet size and velocity distributions under different spray conditions. Liquid swirling strength, Weber number, gas-to-liquid axial velocity ratio and gas-to-liquid density ratio have different effects on droplet size and velocity distributions of a pressure swirl atomizer.

  13. Maximum non-extensive entropy block bootstrap for non-stationary processes

    Czech Academy of Sciences Publication Activity Database

    Bergamelli, M.; Novotný, Jan; Urga, G.

    2015-01-01

    Roč. 91, 1/2 (2015), s. 115-139 ISSN 0001-771X R&D Projects: GA ČR(CZ) GA14-27047S Institutional support: RVO:67985998 Keywords : maximum entropy * bootstrap * Monte Carlo simulations Subject RIV: AH - Economics

  14. Bayesian Maximum Entropy prediction of soil categories using a traditional soil map as soft information.

    NARCIS (Netherlands)

    Brus, D.J.; Bogaert, P.; Heuvelink, G.B.M.

    2008-01-01

    Bayesian Maximum Entropy was used to estimate the probabilities of occurrence of soil categories in the Netherlands, and to simulate realizations from the associated multi-point pdf. Besides the hard observations (H) of the categories at 8369 locations, the soil map of the Netherlands 1:50 000 was

  15. Critical Analysis of Non-Nuclear Electron-Density Maxima and the Maximum Entropy Method

    NARCIS (Netherlands)

    de Vries, R.Y.; Briels, Willem J.; Feil, D.; Feil, D.

    1996-01-01

    Experimental evidence for the existence of non-nuclear maxima in charge densities is questioned. It is shown that the non-nuclear maxima reported for silicon are artifacts of the maximum entropy method that was used to analyze the x-ray diffraction data. This method can be improved by the use of

  16. Deconvolution in the presence of noise using the Maximum Entropy Principle

    International Nuclear Information System (INIS)

    Steenstrup, S.

    1984-01-01

    The main problem in deconvolution in the presence of noise is the nonuniqueness. This problem is overcome by the application of the Maximum Entropy Principle. The way the noise enters in the formulation of the problem is examined in some detail and the final equations are derived such that the necessary assumptions becomes explicit. Examples using X-ray diffraction data are shown. (orig.)

  17. Uncertainty estimation of the self-thinning process by Maximum-Entropy Principle

    Science.gov (United States)

    Shoufan Fang; George Z. Gertner

    2000-01-01

    When available information is scarce, the Maximum-Entropy Principle can estimate the distributions of parameters. In our case study, we estimated the distributions of the parameters of the forest self-thinning process based on literature information, and we derived the conditional distribution functions and estimated the 95 percent confidence interval (CI) of the self-...

  18. Comparison of tomography reconstruction by maximum entropy and filtered retro projection

    International Nuclear Information System (INIS)

    Abdala, F.J.P.; Simpson, D.M.; Roberty, N.C.

    1992-01-01

    The tomographic reconstruction with few projections is studied, comparing the maximum entropy method with filtered retro projection. Simulations with and without the presence of noise and also with the presence of an object of high density inside of the skull are showed. (C.G.C.)

  19. Structure of incommensurate ammonium tetrafluoroberyllate studied by structure refinements and the maximum entropy method

    Czech Academy of Sciences Publication Activity Database

    Palatinus, Lukáš; Amami, M.; van Smaalen, S.

    2004-01-01

    Roč. 60, - (2004), s. 127-137 ISSN 0108-7681 Grant - others:DFG(DE) XX Institutional research plan: CEZ:AV0Z1010914 Keywords : incommensurate modulation * superspace * maximum entropy method Subject RIV: BM - Solid Matter Physics ; Magnetism Impact factor: 5.418, year: 2004

  20. Incommensurate modulations made visible by the Maximum Entropy Method in superspace

    Czech Academy of Sciences Publication Activity Database

    Palatinus, Lukáš; van Smaalen, S.

    2004-01-01

    Roč. 219, - (2004), s. 719-729 ISSN 0044-2968 Grant - others:DFG(DE) XX Institutional research plan: CEZ:AV0Z1010914 Keywords : Maximum Entropy Method * modulated structures * charge density Subject RIV: BM - Solid Matter Physics ; Magnetism Impact factor: 1.390, year: 2004

  1. The prior-derived F constraints in the maximum-entropy method

    Czech Academy of Sciences Publication Activity Database

    Palatinus, Lukáš; van Smaalen, S.

    2005-01-01

    Roč. 61, - (2005), s. 363-372 ISSN 0108-7673 Institutional research plan: CEZ:AV0Z10100521 Keywords : charge density * maximum-entropy method * sodium nitrite Subject RIV: BM - Solid Matter Physics ; Magnetism Impact factor: 1.791, year: 2005

  2. The generalized F constraint in the maximum-entropy method - a study on simulated data

    Czech Academy of Sciences Publication Activity Database

    Palatinus, Lukáš; van Smaalen, S.

    2002-01-01

    Roč. 58, - (2002), s. 559-567 ISSN 0108-7673 Grant - others:DFG(DE) XX Institutional research plan: CEZ:AV0Z1010914 Keywords : maximum-entropy method * electron density * oxalic acid Subject RIV: BM - Solid Matter Physics ; Magnetism Impact factor: 1.417, year: 2002

  3. Can the maximum entropy principle be explained as a consistency requirement?

    NARCIS (Netherlands)

    Uffink, J.

    1997-01-01

    The principle of maximum entropy is a general method to assign values to probability distributions on the basis of partial information. This principle, introduced by Jaynes in 1957, forms an extension of the classical principle of insufficient reason. It has been further generalized, both in

  4. Application of the Maximum Entropy Method to Risk Analysis of Mergers and Acquisitions

    Science.gov (United States)

    Xie, Jigang; Song, Wenyun

    The maximum entropy (ME) method can be used to analyze the risk of mergers and acquisitions when only pre-acquisition information is available. A practical example of the risk analysis of China listed firms’ mergers and acquisitions is provided to testify the feasibility and practicality of the method.

  5. Separation of Stochastic and Deterministic Information from Seismological Time Series with Nonlinear Dynamics and Maximum Entropy Methods

    International Nuclear Information System (INIS)

    Gutierrez, Rafael M.; Useche, Gina M.; Buitrago, Elias

    2007-01-01

    We present a procedure developed to detect stochastic and deterministic information contained in empirical time series, useful to characterize and make models of different aspects of complex phenomena represented by such data. This procedure is applied to a seismological time series to obtain new information to study and understand geological phenomena. We use concepts and methods from nonlinear dynamics and maximum entropy. The mentioned method allows an optimal analysis of the available information

  6. Least squares autoregressive (maximum entropy) spectral estimation for Fourier spectroscopy and its application to the electron cyclotron emission from plasma

    International Nuclear Information System (INIS)

    Iwama, N.; Inoue, A.; Tsukishima, T.; Sato, M.; Kawahata, K.

    1981-07-01

    A new procedure for the maximum entropy spectral estimation is studied for the purpose of data processing in Fourier transform spectroscopy. The autoregressive model fitting is examined under a least squares criterion based on the Yule-Walker equations. An AIC-like criterion is suggested for selecting the model order. The principal advantage of the new procedure lies in the enhanced frequency resolution particularly for small values of the maximum optical path-difference of the interferogram. The usefulness of the procedure is ascertained by some numerical simulations and further by experiments with respect to a highly coherent submillimeter wave and the electron cyclotron emission from a stellarator plasma. (author)

  7. Conditional maximum-entropy method for selecting prior distributions in Bayesian statistics

    Science.gov (United States)

    Abe, Sumiyoshi

    2014-11-01

    The conditional maximum-entropy method (abbreviated here as C-MaxEnt) is formulated for selecting prior probability distributions in Bayesian statistics for parameter estimation. This method is inspired by a statistical-mechanical approach to systems governed by dynamics with largely separated time scales and is based on three key concepts: conjugate pairs of variables, dimensionless integration measures with coarse-graining factors and partial maximization of the joint entropy. The method enables one to calculate a prior purely from a likelihood in a simple way. It is shown, in particular, how it not only yields Jeffreys's rules but also reveals new structures hidden behind them.

  8. Application of maximum entropy to statistical inference for inversion of data from a single track segment.

    Science.gov (United States)

    Stotts, Steven A; Koch, Robert A

    2017-08-01

    In this paper an approach is presented to estimate the constraint required to apply maximum entropy (ME) for statistical inference with underwater acoustic data from a single track segment. Previous algorithms for estimating the ME constraint require multiple source track segments to determine the constraint. The approach is relevant for addressing model mismatch effects, i.e., inaccuracies in parameter values determined from inversions because the propagation model does not account for all acoustic processes that contribute to the measured data. One effect of model mismatch is that the lowest cost inversion solution may be well outside a relatively well-known parameter value's uncertainty interval (prior), e.g., source speed from track reconstruction or towed source levels. The approach requires, for some particular parameter value, the ME constraint to produce an inferred uncertainty interval that encompasses the prior. Motivating this approach is the hypothesis that the proposed constraint determination procedure would produce a posterior probability density that accounts for the effect of model mismatch on inferred values of other inversion parameters for which the priors might be quite broad. Applications to both measured and simulated data are presented for model mismatch that produces minimum cost solutions either inside or outside some priors.

  9. A Maximum Entropy Approach to Assess Debonding in Honeycomb aluminum Plates

    Directory of Open Access Journals (Sweden)

    Viviana Meruane

    2014-05-01

    Full Text Available Honeycomb sandwich structures are used in a wide variety of applications. Nevertheless, due to manufacturing defects or impact loads, these structures can be subject to imperfect bonding or debonding between the skin and the honeycomb core. The presence of debonding reduces the bending stiffness of the composite panel, which causes detectable changes in its vibration characteristics. This article presents a new supervised learning algorithm to identify debonded regions in aluminum honeycomb panels. The algorithm uses a linear approximation method handled by a statistical inference model based on the maximum-entropy principle. The merits of this new approach are twofold: training is avoided and data is processed in a period of time that is comparable to the one of neural networks. The honeycomb panels are modeled with finite elements using a simplified three-layer shell model. The adhesive layer between the skin and core is modeled using linear springs, the rigidities of which are reduced in debonded sectors. The algorithm is validated using experimental data of an aluminum honeycomb panel under different damage scenarios.

  10. Entanglement entropy in top-down models

    Energy Technology Data Exchange (ETDEWEB)

    Jones, Peter A.R.; Taylor, Marika [Mathematical Sciences and STAG Research Centre, University of Southampton,Highfield, Southampton, SO17 1BJ (United Kingdom)

    2016-08-26

    We explore holographic entanglement entropy in ten-dimensional supergravity solutions. It has been proposed that entanglement entropy can be computed in such top-down models using minimal surfaces which asymptotically wrap the compact part of the geometry. We show explicitly in a wide range of examples that the holographic entanglement entropy thus computed agrees with the entanglement entropy computed using the Ryu-Takayanagi formula from the lower-dimensional Einstein metric obtained from reduction over the compact space. Our examples include not only consistent truncations but also cases in which no consistent truncation exists and Kaluza-Klein holography is used to identify the lower-dimensional Einstein metric. We then give a general proof, based on the Lewkowycz-Maldacena approach, of the top-down entanglement entropy formula.

  11. Entanglement entropy in top-down models

    International Nuclear Information System (INIS)

    Jones, Peter A.R.; Taylor, Marika

    2016-01-01

    We explore holographic entanglement entropy in ten-dimensional supergravity solutions. It has been proposed that entanglement entropy can be computed in such top-down models using minimal surfaces which asymptotically wrap the compact part of the geometry. We show explicitly in a wide range of examples that the holographic entanglement entropy thus computed agrees with the entanglement entropy computed using the Ryu-Takayanagi formula from the lower-dimensional Einstein metric obtained from reduction over the compact space. Our examples include not only consistent truncations but also cases in which no consistent truncation exists and Kaluza-Klein holography is used to identify the lower-dimensional Einstein metric. We then give a general proof, based on the Lewkowycz-Maldacena approach, of the top-down entanglement entropy formula.

  12. Nonequilibrium thermodynamics and maximum entropy production in the Earth system: applications and implications.

    Science.gov (United States)

    Kleidon, Axel

    2009-06-01

    The Earth system is maintained in a unique state far from thermodynamic equilibrium, as, for instance, reflected in the high concentration of reactive oxygen in the atmosphere. The myriad of processes that transform energy, that result in the motion of mass in the atmosphere, in oceans, and on land, processes that drive the global water, carbon, and other biogeochemical cycles, all have in common that they are irreversible in their nature. Entropy production is a general consequence of these processes and measures their degree of irreversibility. The proposed principle of maximum entropy production (MEP) states that systems are driven to steady states in which they produce entropy at the maximum possible rate given the prevailing constraints. In this review, the basics of nonequilibrium thermodynamics are described, as well as how these apply to Earth system processes. Applications of the MEP principle are discussed, ranging from the strength of the atmospheric circulation, the hydrological cycle, and biogeochemical cycles to the role that life plays in these processes. Nonequilibrium thermodynamics and the MEP principle have potentially wide-ranging implications for our understanding of Earth system functioning, how it has evolved in the past, and why it is habitable. Entropy production allows us to quantify an objective direction of Earth system change (closer to vs further away from thermodynamic equilibrium, or, equivalently, towards a state of MEP). When a maximum in entropy production is reached, MEP implies that the Earth system reacts to perturbations primarily with negative feedbacks. In conclusion, this nonequilibrium thermodynamic view of the Earth system shows great promise to establish a holistic description of the Earth as one system. This perspective is likely to allow us to better understand and predict its function as one entity, how it has evolved in the past, and how it is modified by human activities in the future.

  13. Reinterpreting maximum entropy in ecology: a null hypothesis constrained by ecological mechanism.

    Science.gov (United States)

    O'Dwyer, James P; Rominger, Andrew; Xiao, Xiao

    2017-07-01

    Simplified mechanistic models in ecology have been criticised for the fact that a good fit to data does not imply the mechanism is true: pattern does not equal process. In parallel, the maximum entropy principle (MaxEnt) has been applied in ecology to make predictions constrained by just a handful of state variables, like total abundance or species richness. But an outstanding question remains: what principle tells us which state variables to constrain? Here we attempt to solve both problems simultaneously, by translating a given set of mechanisms into the state variables to be used in MaxEnt, and then using this MaxEnt theory as a null model against which to compare mechanistic predictions. In particular, we identify the sufficient statistics needed to parametrise a given mechanistic model from data and use them as MaxEnt constraints. Our approach isolates exactly what mechanism is telling us over and above the state variables alone. © 2017 John Wiley & Sons Ltd/CNRS.

  14. Short-time maximum entropy method analysis of molecular dynamics simulation: Unimolecular decomposition of formic acid

    Science.gov (United States)

    Takahashi, Osamu; Nomura, Tetsuo; Tabayashi, Kiyohiko; Yamasaki, Katsuyoshi

    2008-07-01

    We performed spectral analysis by using the maximum entropy method instead of the traditional Fourier transform technique to investigate the short-time behavior in molecular systems, such as the energy transfer between vibrational modes and chemical reactions. This procedure was applied to direct ab initio molecular dynamics calculations for the decomposition of formic acid. More reactive trajectories of dehydrolation than those of decarboxylation were obtained for Z-formic acid, which was consistent with the prediction of previous theoretical and experimental studies. Short-time maximum entropy method analyses were performed for typical reactive and non-reactive trajectories. Spectrograms of a reactive trajectory were obtained; these clearly showed the reactant, transient, and product regions, especially for the dehydrolation path.

  15. Derivation of some new distributions in statistical mechanics using maximum entropy approach

    Directory of Open Access Journals (Sweden)

    Ray Amritansu

    2014-01-01

    Full Text Available The maximum entropy principle has been earlier used to derive the Bose Einstein(B.E., Fermi Dirac(F.D. & Intermediate Statistics(I.S. distribution of statistical mechanics. The central idea of these distributions is to predict the distribution of the microstates, which are the particle of the system, on the basis of the knowledge of some macroscopic data. The latter information is specified in the form of some simple moment constraints. One distribution differs from the other in the way in which the constraints are specified. In the present paper, we have derived some new distributions similar to B.E., F.D. distributions of statistical mechanics by using maximum entropy principle. Some proofs of B.E. & F.D. distributions are shown, and at the end some new results are discussed.

  16. On the maximum-entropy method for kinetic equation of radiation, particle and gas

    International Nuclear Information System (INIS)

    El-Wakil, S.A.; Madkour, M.A.; Degheidy, A.R.; Machali, H.M.

    1995-01-01

    The maximum-entropy approach is used to calculate some problems in radiative transfer and reactor physics such as the escape probability, the emergent and transmitted intensities for a finite slab as well as the emergent intensity for a semi-infinite medium. Also, it is employed to solve problems involving spherical geometry, such as luminosity (the total energy emitted by a sphere), neutron capture probability and the albedo problem. The technique is also employed in the kinetic theory of gases to calculate the Poiseuille flow and thermal creep of a rarefied gas between two plates. Numerical calculations are achieved and compared with the published data. The comparisons demonstrate that the maximum-entropy results are good in agreement with the exact ones. (orig.)

  17. Comments on a derivation and application of the 'maximum entropy production' principle

    International Nuclear Information System (INIS)

    Grinstein, G; Linsker, R

    2007-01-01

    We show that (1) an error invalidates the derivation (Dewar 2005 J. Phys. A: Math. Gen. 38 L371) of the maximum entropy production (MaxEP) principle for systems far from equilibrium, for which the constitutive relations are nonlinear; and (2) the claim (Dewar 2003 J. Phys. A: Math. Gen. 36 631) that the phenomenon of 'self-organized criticality' is a consequence of MaxEP for slowly driven systems is unjustified. (comment)

  18. Hydrodynamic equations for electrons in graphene obtained from the maximum entropy principle

    Energy Technology Data Exchange (ETDEWEB)

    Barletti, Luigi, E-mail: luigi.barletti@unifi.it [Dipartimento di Matematica e Informatica “Ulisse Dini”, Università degli Studi di Firenze, Viale Morgagni 67/A, 50134 Firenze (Italy)

    2014-08-15

    The maximum entropy principle is applied to the formal derivation of isothermal, Euler-like equations for semiclassical fermions (electrons and holes) in graphene. After proving general mathematical properties of the equations so obtained, their asymptotic form corresponding to significant physical regimes is investigated. In particular, the diffusive regime, the Maxwell-Boltzmann regime (high temperature), the collimation regime and the degenerate gas limit (vanishing temperature) are considered.

  19. Reconstruction of the electron momentum density distribution by the maximum entropy method

    International Nuclear Information System (INIS)

    Dobrzynski, L.

    1996-01-01

    The application of the Maximum Entropy Algorithm to the analysis of the Compton profiles is discussed. It is shown that the reconstruction of electron momentum density may be reliably carried out. However, there are a number of technical problems which have to be overcome in order to produce trustworthy results. In particular one needs the experimental Compton profiles measured for many directions, and to have efficient computational resources. The use of various cross-checks is recommended. (orig.)

  20. Use of the maximum entropy method in X-ray astronomy

    International Nuclear Information System (INIS)

    Willingale, R.

    1981-01-01

    An algorithm used to apply the maximum entropy method in X-ray astronomy is described. It is easy to programme on a digital computer and fast enough to allow processing of two-dimensional images. The method gives good noise suppression without loss of instrumental resolution and has been successfully applied to several data analysis problems in X-ray astronomy. The restoration of a high-resolution image from the Einstein Observatory demonstrates the use of the algorithm. (author)

  1. A parallel implementation of a maximum entropy reconstruction algorithm for PET images in a visual language

    International Nuclear Information System (INIS)

    Bastiens, K.; Lemahieu, I.

    1994-01-01

    The application of a maximum entropy reconstruction algorithm to PET images requires a lot of computing resources. A parallel implementation could seriously reduce the execution time. However, programming a parallel application is still a non trivial task, needing specialized people. In this paper a programming environment based on a visual programming language is used for a parallel implementation of the reconstruction algorithm. This programming environment allows less experienced programmers to use the performance of multiprocessor systems. (authors)

  2. A parallel implementation of a maximum entropy reconstruction algorithm for PET images in a visual language

    Energy Technology Data Exchange (ETDEWEB)

    Bastiens, K; Lemahieu, I [University of Ghent - ELIS Department, St. Pietersnieuwstraat 41, B-9000 Ghent (Belgium)

    1994-12-31

    The application of a maximum entropy reconstruction algorithm to PET images requires a lot of computing resources. A parallel implementation could seriously reduce the execution time. However, programming a parallel application is still a non trivial task, needing specialized people. In this paper a programming environment based on a visual programming language is used for a parallel implementation of the reconstruction algorithm. This programming environment allows less experienced programmers to use the performance of multiprocessor systems. (authors). 8 refs, 3 figs, 1 tab.

  3. Maximum entropy restoration of laser fusion target x-ray photographs

    International Nuclear Information System (INIS)

    Brolley, J.E.; Lazarus, R.B.; Suydam, B.R.

    1976-01-01

    Maximum entropy principles were used to analyze the microdensitometer traces of a laser-fusion target photograph. The object is a glowing laser-fusion target microsphere 0.95 cm from a pinhole of radius 2 x 10 -4 cm, the image is 7.2 cm from the pinhole and the photon wavelength is likely to be 6.2 x 10 -8 cm. Some computational aspects of the problem are also considered

  4. Maximum Entropy Method in Moessbauer Spectroscopy - a Problem of Magnetic Texture

    International Nuclear Information System (INIS)

    Satula, D.; Szymanski, K.; Dobrzynski, L.

    2011-01-01

    A reconstruction of the three dimensional distribution of the hyperfine magnetic field, isomer shift and texture parameter z from the Moessbauer spectra by the maximum entropy method is presented. The method was tested on the simulated spectrum consisting of two Gaussian hyperfine field distributions with different values of the texture parameters. It is shown that proper prior has to be chosen in order to arrive at the physically meaningful results. (authors)

  5. Lattice Field Theory with the Sign Problem and the Maximum Entropy Method

    Directory of Open Access Journals (Sweden)

    Masahiro Imachi

    2007-02-01

    Full Text Available Although numerical simulation in lattice field theory is one of the most effective tools to study non-perturbative properties of field theories, it faces serious obstacles coming from the sign problem in some theories such as finite density QCD and lattice field theory with the θ term. We reconsider this problem from the point of view of the maximum entropy method.

  6. An entropy approach for evaluating the maximum information content achievable by an urban rainfall network

    Directory of Open Access Journals (Sweden)

    E. Ridolfi

    2011-07-01

    Full Text Available Hydrological models are the basis of operational flood-forecasting systems. The accuracy of these models is strongly dependent on the quality and quantity of the input information represented by rainfall height. Finer space-time rainfall resolution results in more accurate hazard forecasting. In this framework, an optimum raingauge network is essential in predicting flood events.

    This paper develops an entropy-based approach to evaluate the maximum information content achievable by a rainfall network for different sampling time intervals. The procedure is based on the determination of the coefficients of transferred and nontransferred information and on the relative isoinformation contours.

    The nontransferred information value achieved by the whole network is strictly dependent on the sampling time intervals considered. An empirical curve is defined, to assess the objective of the research: the nontransferred information value is plotted versus the associated sampling time on a semi-log scale. The curve has a linear trend.

    In this paper, the methodology is applied to the high-density raingauge network of the urban area of Rome.

  7. Estimation of Fine Particulate Matter in Taipei Using Landuse Regression and Bayesian Maximum Entropy Methods

    Directory of Open Access Journals (Sweden)

    Yi-Ming Kuo

    2011-06-01

    Full Text Available Fine airborne particulate matter (PM2.5 has adverse effects on human health. Assessing the long-term effects of PM2.5 exposure on human health and ecology is often limited by a lack of reliable PM2.5 measurements. In Taipei, PM2.5 levels were not systematically measured until August, 2005. Due to the popularity of geographic information systems (GIS, the landuse regression method has been widely used in the spatial estimation of PM concentrations. This method accounts for the potential contributing factors of the local environment, such as traffic volume. Geostatistical methods, on other hand, account for the spatiotemporal dependence among the observations of ambient pollutants. This study assesses the performance of the landuse regression model for the spatiotemporal estimation of PM2.5 in the Taipei area. Specifically, this study integrates the landuse regression model with the geostatistical approach within the framework of the Bayesian maximum entropy (BME method. The resulting epistemic framework can assimilate knowledge bases including: (a empirical-based spatial trends of PM concentration based on landuse regression, (b the spatio-temporal dependence among PM observation information, and (c site-specific PM observations. The proposed approach performs the spatiotemporal estimation of PM2.5 levels in the Taipei area (Taiwan from 2005–2007.

  8. Estimation of fine particulate matter in Taipei using landuse regression and bayesian maximum entropy methods.

    Science.gov (United States)

    Yu, Hwa-Lung; Wang, Chih-Hsih; Liu, Ming-Che; Kuo, Yi-Ming

    2011-06-01

    Fine airborne particulate matter (PM2.5) has adverse effects on human health. Assessing the long-term effects of PM2.5 exposure on human health and ecology is often limited by a lack of reliable PM2.5 measurements. In Taipei, PM2.5 levels were not systematically measured until August, 2005. Due to the popularity of geographic information systems (GIS), the landuse regression method has been widely used in the spatial estimation of PM concentrations. This method accounts for the potential contributing factors of the local environment, such as traffic volume. Geostatistical methods, on other hand, account for the spatiotemporal dependence among the observations of ambient pollutants. This study assesses the performance of the landuse regression model for the spatiotemporal estimation of PM2.5 in the Taipei area. Specifically, this study integrates the landuse regression model with the geostatistical approach within the framework of the Bayesian maximum entropy (BME) method. The resulting epistemic framework can assimilate knowledge bases including: (a) empirical-based spatial trends of PM concentration based on landuse regression, (b) the spatio-temporal dependence among PM observation information, and (c) site-specific PM observations. The proposed approach performs the spatiotemporal estimation of PM2.5 levels in the Taipei area (Taiwan) from 2005-2007.

  9. Identification of Watershed-scale Critical Source Areas Using Bayesian Maximum Entropy Spatiotemporal Analysis

    Science.gov (United States)

    Roostaee, M.; Deng, Z.

    2017-12-01

    The states' environmental agencies are required by The Clean Water Act to assess all waterbodies and evaluate potential sources of impairments. Spatial and temporal distributions of water quality parameters are critical in identifying Critical Source Areas (CSAs). However, due to limitations in monetary resources and a large number of waterbodies, available monitoring stations are typically sparse with intermittent periods of data collection. Hence, scarcity of water quality data is a major obstacle in addressing sources of pollution through management strategies. In this study spatiotemporal Bayesian Maximum Entropy method (BME) is employed to model the inherent temporal and spatial variability of measured water quality indicators such as Dissolved Oxygen (DO) concentration for Turkey Creek Watershed. Turkey Creek is located in northern Louisiana and has been listed in 303(d) list for DO impairment since 2014 in Louisiana Water Quality Inventory Reports due to agricultural practices. BME method is proved to provide more accurate estimates than the methods of purely spatial analysis by incorporating space/time distribution and uncertainty in available measured soft and hard data. This model would be used to estimate DO concentration at unmonitored locations and times and subsequently identifying CSAs. The USDA's crop-specific land cover data layers of the watershed were then used to determine those practices/changes that led to low DO concentration in identified CSAs. Primary results revealed that cultivation of corn and soybean as well as urban runoff are main contributing sources in low dissolved oxygen in Turkey Creek Watershed.

  10. Mixed memory, (non) Hurst effect, and maximum entropy of rainfall in the tropical Andes

    Science.gov (United States)

    Poveda, Germán

    2011-02-01

    Diverse linear and nonlinear statistical parameters of rainfall under aggregation in time and the kind of temporal memory are investigated. Data sets from the Andes of Colombia at different resolutions (15 min and 1-h), and record lengths (21 months and 8-40 years) are used. A mixture of two timescales is found in the autocorrelation and autoinformation functions, with short-term memory holding for time lags less than 15-30 min, and long-term memory onwards. Consistently, rainfall variance exhibits different temporal scaling regimes separated at 15-30 min and 24 h. Tests for the Hurst effect evidence the frailty of the R/ S approach in discerning the kind of memory in high resolution rainfall, whereas rigorous statistical tests for short-memory processes do reject the existence of the Hurst effect. Rainfall information entropy grows as a power law of aggregation time, S( T) ˜ Tβ with = 0.51, up to a timescale, TMaxEnt (70-202 h), at which entropy saturates, with β = 0 onwards. Maximum entropy is reached through a dynamic Generalized Pareto distribution, consistently with the maximum information-entropy principle for heavy-tailed random variables, and with its asymptotically infinitely divisible property. The dynamics towards the limit distribution is quantified. Tsallis q-entropies also exhibit power laws with T, such that Sq( T) ˜ Tβ( q) , with β( q) ⩽ 0 for q ⩽ 0, and β( q) ≃ 0.5 for q ⩾ 1. No clear patterns are found in the geographic distribution within and among the statistical parameters studied, confirming the strong variability of tropical Andean rainfall.

  11. Merging daily sea surface temperature data from multiple satellites using a Bayesian maximum entropy method

    Science.gov (United States)

    Tang, Shaolei; Yang, Xiaofeng; Dong, Di; Li, Ziwei

    2015-12-01

    Sea surface temperature (SST) is an important variable for understanding interactions between the ocean and the atmosphere. SST fusion is crucial for acquiring SST products of high spatial resolution and coverage. This study introduces a Bayesian maximum entropy (BME) method for blending daily SSTs from multiple satellite sensors. A new spatiotemporal covariance model of an SST field is built to integrate not only single-day SSTs but also time-adjacent SSTs. In addition, AVHRR 30-year SST climatology data are introduced as soft data at the estimation points to improve the accuracy of blended results within the BME framework. The merged SSTs, with a spatial resolution of 4 km and a temporal resolution of 24 hours, are produced in the Western Pacific Ocean region to demonstrate and evaluate the proposed methodology. Comparisons with in situ drifting buoy observations show that the merged SSTs are accurate and the bias and root-mean-square errors for the comparison are 0.15°C and 0.72°C, respectively.

  12. A Bayesian maximum entropy-based methodology for optimal spatiotemporal design of groundwater monitoring networks.

    Science.gov (United States)

    Hosseini, Marjan; Kerachian, Reza

    2017-09-01

    This paper presents a new methodology for analyzing the spatiotemporal variability of water table levels and redesigning a groundwater level monitoring network (GLMN) using the Bayesian Maximum Entropy (BME) technique and a multi-criteria decision-making approach based on ordered weighted averaging (OWA). The spatial sampling is determined using a hexagonal gridding pattern and a new method, which is proposed to assign a removal priority number to each pre-existing station. To design temporal sampling, a new approach is also applied to consider uncertainty caused by lack of information. In this approach, different time lag values are tested by regarding another source of information, which is simulation result of a numerical groundwater flow model. Furthermore, to incorporate the existing uncertainties in available monitoring data, the flexibility of the BME interpolation technique is taken into account in applying soft data and improving the accuracy of the calculations. To examine the methodology, it is applied to the Dehgolan plain in northwestern Iran. Based on the results, a configuration of 33 monitoring stations for a regular hexagonal grid of side length 3600 m is proposed, in which the time lag between samples is equal to 5 weeks. Since the variance estimation errors of the BME method are almost identical for redesigned and existing networks, the redesigned monitoring network is more cost-effective and efficient than the existing monitoring network with 52 stations and monthly sampling frequency.

  13. Causal nexus between energy consumption and carbon dioxide emission for Malaysia using maximum entropy bootstrap approach.

    Science.gov (United States)

    Gul, Sehrish; Zou, Xiang; Hassan, Che Hashim; Azam, Muhammad; Zaman, Khalid

    2015-12-01

    This study investigates the relationship between energy consumption and carbon dioxide emission in the causal framework, as the direction of causality remains has a significant policy implication for developed and developing countries. The study employed maximum entropy bootstrap (Meboot) approach to examine the causal nexus between energy consumption and carbon dioxide emission using bivariate as well as multivariate framework for Malaysia, over a period of 1975-2013. This is a unified approach without requiring the use of conventional techniques based on asymptotical theory such as testing for possible unit root and cointegration. In addition, it can be applied in the presence of non-stationary of any type including structural breaks without any type of data transformation to achieve stationary. Thus, it provides more reliable and robust inferences which are insensitive to time span as well as lag length used. The empirical results show that there is a unidirectional causality running from energy consumption to carbon emission both in the bivariate model and multivariate framework, while controlling for broad money supply and population density. The results indicate that Malaysia is an energy-dependent country and hence energy is stimulus to carbon emissions.

  14. The Maximum Entropy Limit of Small-scale Magnetic Field Fluctuations in the Quiet Sun

    Science.gov (United States)

    Gorobets, A. Y.; Berdyugina, S. V.; Riethmüller, T. L.; Blanco Rodríguez, J.; Solanki, S. K.; Barthol, P.; Gandorfer, A.; Gizon, L.; Hirzberger, J.; van Noort, M.; Del Toro Iniesta, J. C.; Orozco Suárez, D.; Schmidt, W.; Martínez Pillet, V.; Knölker, M.

    2017-11-01

    The observed magnetic field on the solar surface is characterized by a very complex spatial and temporal behavior. Although feature-tracking algorithms have allowed us to deepen our understanding of this behavior, subjectivity plays an important role in the identification and tracking of such features. In this paper, we continue studies of the temporal stochasticity of the magnetic field on the solar surface without relying either on the concept of magnetic features or on subjective assumptions about their identification and interaction. We propose a data analysis method to quantify fluctuations of the line-of-sight magnetic field by means of reducing the temporal field’s evolution to the regular Markov process. We build a representative model of fluctuations converging to the unique stationary (equilibrium) distribution in the long time limit with maximum entropy. We obtained different rates of convergence to the equilibrium at fixed noise cutoff for two sets of data. This indicates a strong influence of the data spatial resolution and mixing-polarity fluctuations on the relaxation process. The analysis is applied to observations of magnetic fields of the relatively quiet areas around an active region carried out during the second flight of the Sunrise/IMaX and quiet Sun areas at the disk center from the Helioseismic and Magnetic Imager on board the Solar Dynamics Observatory satellite.

  15. A basic introduction to the thermodynamics of the Earth system far from equilibrium and maximum entropy production

    Science.gov (United States)

    Kleidon, A.

    2010-01-01

    The Earth system is remarkably different from its planetary neighbours in that it shows pronounced, strong global cycling of matter. These global cycles result in the maintenance of a unique thermodynamic state of the Earth's atmosphere which is far from thermodynamic equilibrium (TE). Here, I provide a simple introduction of the thermodynamic basis to understand why Earth system processes operate so far away from TE. I use a simple toy model to illustrate the application of non-equilibrium thermodynamics and to classify applications of the proposed principle of maximum entropy production (MEP) to such processes into three different cases of contrasting flexibility in the boundary conditions. I then provide a brief overview of the different processes within the Earth system that produce entropy, review actual examples of MEP in environmental and ecological systems, and discuss the role of interactions among dissipative processes in making boundary conditions more flexible. I close with a brief summary and conclusion. PMID:20368248

  16. A basic introduction to the thermodynamics of the Earth system far from equilibrium and maximum entropy production.

    Science.gov (United States)

    Kleidon, A

    2010-05-12

    The Earth system is remarkably different from its planetary neighbours in that it shows pronounced, strong global cycling of matter. These global cycles result in the maintenance of a unique thermodynamic state of the Earth's atmosphere which is far from thermodynamic equilibrium (TE). Here, I provide a simple introduction of the thermodynamic basis to understand why Earth system processes operate so far away from TE. I use a simple toy model to illustrate the application of non-equilibrium thermodynamics and to classify applications of the proposed principle of maximum entropy production (MEP) to such processes into three different cases of contrasting flexibility in the boundary conditions. I then provide a brief overview of the different processes within the Earth system that produce entropy, review actual examples of MEP in environmental and ecological systems, and discuss the role of interactions among dissipative processes in making boundary conditions more flexible. I close with a brief summary and conclusion.

  17. Quantum maximum-entropy principle for closed quantum hydrodynamic transport within a Wigner function formalism

    International Nuclear Information System (INIS)

    Trovato, M.; Reggiani, L.

    2011-01-01

    By introducing a quantum entropy functional of the reduced density matrix, the principle of quantum maximum entropy is asserted as fundamental principle of quantum statistical mechanics. Accordingly, we develop a comprehensive theoretical formalism to construct rigorously a closed quantum hydrodynamic transport within a Wigner function approach. The theoretical formalism is formulated in both thermodynamic equilibrium and nonequilibrium conditions, and the quantum contributions are obtained by only assuming that the Lagrange multipliers can be expanded in powers of (ℎ/2π) 2 . In particular, by using an arbitrary number of moments, we prove that (1) on a macroscopic scale all nonlocal effects, compatible with the uncertainty principle, are imputable to high-order spatial derivatives, both of the numerical density n and of the effective temperature T; (2) the results available from the literature in the framework of both a quantum Boltzmann gas and a degenerate quantum Fermi gas are recovered as a particular case; (3) the statistics for the quantum Fermi and Bose gases at different levels of degeneracy are explicitly incorporated; (4) a set of relevant applications admitting exact analytical equations are explicitly given and discussed; (5) the quantum maximum entropy principle keeps full validity in the classical limit, when (ℎ/2π)→0.

  18. Applications of the principle of maximum entropy: from physics to ecology.

    Science.gov (United States)

    Banavar, Jayanth R; Maritan, Amos; Volkov, Igor

    2010-02-17

    There are numerous situations in physics and other disciplines which can be described at different levels of detail in terms of probability distributions. Such descriptions arise either intrinsically as in quantum mechanics, or because of the vast amount of details necessary for a complete description as, for example, in Brownian motion and in many-body systems. We show that an application of the principle of maximum entropy for estimating the underlying probability distribution can depend on the variables used for describing the system. The choice of characterization of the system carries with it implicit assumptions about fundamental attributes such as whether the system is classical or quantum mechanical or equivalently whether the individuals are distinguishable or indistinguishable. We show that the correct procedure entails the maximization of the relative entropy subject to known constraints and, additionally, requires knowledge of the behavior of the system in the absence of these constraints. We present an application of the principle of maximum entropy to understanding species diversity in ecology and introduce a new statistical ensemble corresponding to the distribution of a variable population of individuals into a set of species not defined a priori.

  19. Applications of the principle of maximum entropy: from physics to ecology

    International Nuclear Information System (INIS)

    Banavar, Jayanth R; Volkov, Igor; Maritan, Amos

    2010-01-01

    There are numerous situations in physics and other disciplines which can be described at different levels of detail in terms of probability distributions. Such descriptions arise either intrinsically as in quantum mechanics, or because of the vast amount of details necessary for a complete description as, for example, in Brownian motion and in many-body systems. We show that an application of the principle of maximum entropy for estimating the underlying probability distribution can depend on the variables used for describing the system. The choice of characterization of the system carries with it implicit assumptions about fundamental attributes such as whether the system is classical or quantum mechanical or equivalently whether the individuals are distinguishable or indistinguishable. We show that the correct procedure entails the maximization of the relative entropy subject to known constraints and, additionally, requires knowledge of the behavior of the system in the absence of these constraints. We present an application of the principle of maximum entropy to understanding species diversity in ecology and introduce a new statistical ensemble corresponding to the distribution of a variable population of individuals into a set of species not defined a priori. (topical review)

  20. Downstream-Conditioned Maximum Entropy Method for Exit Boundary Conditions in the Lattice Boltzmann Method

    Directory of Open Access Journals (Sweden)

    Javier A. Dottori

    2015-01-01

    Full Text Available A method for modeling outflow boundary conditions in the lattice Boltzmann method (LBM based on the maximization of the local entropy is presented. The maximization procedure is constrained by macroscopic values and downstream components. The method is applied to fully developed boundary conditions of the Navier-Stokes equations in rectangular channels. Comparisons are made with other alternative methods. In addition, the new downstream-conditioned entropy is studied and it was found that there is a correlation with the velocity gradient during the flow development.

  1. Microscopic model for the non-linear fluctuating hydrodynamic of {sup 4} He superfluid helium deduced by maximum entropy method; Modelo microscopico para la hidrodinamica fluctuante no lineal del {sup 4}He superfluido deducido mediante el metodo de maxima entropia

    Energy Technology Data Exchange (ETDEWEB)

    Alvarez R, J.T

    1998-10-01

    This thesis presents a microscopic model for the non-linear fluctuating hydrodynamic of superfluid helium ({sup 4} He), model developed by means of the Maximum Entropy Method (Maxent). In the chapter 1, it is demonstrated the necessity to developing a microscopic model for the fluctuating hydrodynamic of the superfluid helium, starting from to show a brief overview of the theories and experiments developed in order to explain the behavior of the superfluid helium. On the other hand, it is presented the Morozov heuristic method for the construction of the non-linear hydrodynamic fluctuating of simple fluid. Method that will be generalized for the construction of the non-linear fluctuating hydrodynamic of the superfluid helium. Besides, it is presented a brief summary of the content of the thesis. In the chapter 2, it is reproduced the construction of a Generalized Fokker-Planck equation, (GFP), for a distribution function associated with the coarse grained variables. Function defined with aid of a nonequilibrium statistical operator {rho}hut{sub FP} that is evaluated as Wigneris function through {rho}{sub CG} obtained by Maxent. Later this equation of GFP is reduced to a non-linear local FP equation from considering a slow and Markov process in the coarse grained variables. In this equation appears a matrix D{sub mn} defined with a nonequilibrium coarse grained statistical operator {rho}hut{sub CG}, matrix elements are used in the construction of the non-linear fluctuating hydrodynamics equations of the superfluid helium. In the chapter 3, the Lagrange multipliers are evaluated for to determine {rho}hut{sub CG} by means of the local equilibrium statistical operator {rho}hut{sub l}-tilde with the hypothesis that the system presents small fluctuations. Also are determined the currents associated with the coarse grained variables and furthermore are evaluated the matrix elements D{sub mn} but with aid of a quasi equilibrium statistical operator {rho}hut{sub qe} instead

  2. The maximum entropy determination of nuclear densities of calcium isotopes from elastic scattering of alpha particles

    International Nuclear Information System (INIS)

    Engel, Y.M.; Friedman, E.; Levine, R.D.

    1982-01-01

    Radial moments of the real part of the optical potential for elastic scattering of 104 MeV α particles are used as constraints, in determining the nuclear density of maximal entropy. The potential is related to the density by the folding model. (orig.)

  3. An entropy model for artificial grammar learning

    Directory of Open Access Journals (Sweden)

    Emmanuel Pothos

    2010-06-01

    Full Text Available A model is proposed to characterize the type of knowledge acquired in Artificial Grammar Learning (AGL. In particular, Shannon entropy is employed to compute the complexity of different test items in an AGL task, relative to the training items. According to this model, the more predictable a test item is from the training items, the more likely it is that this item should be selected as compatible with the training items. The predictions of the entropy model are explored in relation to the results from several previous AGL datasets and compared to other AGL measures. This particular approach in AGL resonates well with similar models in categorization and reasoning which also postulate that cognitive processing is geared towards the reduction of entropy.

  4. An entropy-assisted musculoskeletal shoulder model.

    Science.gov (United States)

    Xu, Xu; Lin, Jia-Hua; McGorry, Raymond W

    2017-04-01

    Optimization combined with a musculoskeletal shoulder model has been used to estimate mechanical loading of musculoskeletal elements around the shoulder. Traditionally, the objective function is to minimize the summation of the total activities of the muscles with forces, moments, and stability constraints. Such an objective function, however, tends to neglect the antagonist muscle co-contraction. In this study, an objective function including an entropy term is proposed to address muscle co-contractions. A musculoskeletal shoulder model is developed to apply the proposed objective function. To find the optimal weight for the entropy term, an experiment was conducted. In the experiment, participants generated various 3-D shoulder moments in six shoulder postures. The surface EMG of 8 shoulder muscles was measured and compared with the predicted muscle activities based on the proposed objective function using Bhattacharyya distance and concordance ratio under different weight of the entropy term. The results show that a small weight of the entropy term can improve the predictability of the model in terms of muscle activities. Such a result suggests that the concept of entropy could be helpful for further understanding the mechanism of muscle co-contractions as well as developing a shoulder biomechanical model with greater validity. Copyright © 2017 Elsevier Ltd. All rights reserved.

  5. Improvement of the detector resolution in X-ray spectrometry by using the maximum entropy method

    International Nuclear Information System (INIS)

    Fernández, Jorge E.; Scot, Viviana; Giulio, Eugenio Di; Sabbatucci, Lorenzo

    2015-01-01

    In every X-ray spectroscopy measurement the influence of the detection system causes loss of information. Different mechanisms contribute to form the so-called detector response function (DRF): the detector efficiency, the escape of photons as a consequence of photoelectric or scattering interactions, the spectrum smearing due to the energy resolution, and, in solid states detectors (SSD), the charge collection artifacts. To recover the original spectrum, it is necessary to remove the detector influence by solving the so-called inverse problem. The maximum entropy unfolding technique solves this problem by imposing a set of constraints, taking advantage of the known a priori information and preserving the positive-defined character of the X-ray spectrum. This method has been included in the tool UMESTRAT (Unfolding Maximum Entropy STRATegy), which adopts a semi-automatic strategy to solve the unfolding problem based on a suitable combination of the codes MAXED and GRAVEL, developed at PTB. In the past UMESTRAT proved the capability to resolve characteristic peaks which were revealed as overlapped by a Si SSD, giving good qualitative results. In order to obtain quantitative results, UMESTRAT has been modified to include the additional constraint of the total number of photons of the spectrum, which can be easily determined by inverting the diagonal efficiency matrix. The features of the improved code are illustrated with some examples of unfolding from three commonly used SSD like Si, Ge, and CdTe. The quantitative unfolding can be considered as a software improvement of the detector resolution. - Highlights: • Radiation detection introduces distortions in X- and Gamma-ray spectrum measurements. • UMESTRAT is a graphical tool to unfold X- and Gamma-ray spectra. • UMESTRAT uses the maximum entropy method. • UMESTRAT’s new version produces unfolded spectra with quantitative meaning. • UMESTRAT is a software tool to improve the detector resolution.

  6. Maximum Entropy Approach in Dynamic Contrast-Enhanced Magnetic Resonance Imaging.

    Science.gov (United States)

    Farsani, Zahra Amini; Schmid, Volker J

    2017-01-01

    In the estimation of physiological kinetic parameters from Dynamic Contrast-Enhanced Magnetic Resonance Imaging (DCE-MRI) data, the determination of the arterial input function (AIF) plays a key role. This paper proposes a Bayesian method to estimate the physiological parameters of DCE-MRI along with the AIF in situations, where no measurement of the AIF is available. In the proposed algorithm, the maximum entropy method (MEM) is combined with the maximum a posterior approach (MAP). To this end, MEM is used to specify a prior probability distribution of the unknown AIF. The ability of this method to estimate the AIF is validated using the Kullback-Leibler divergence. Subsequently, the kinetic parameters can be estimated with MAP. The proposed algorithm is evaluated with a data set from a breast cancer MRI study. The application shows that the AIF can reliably be determined from the DCE-MRI data using MEM. Kinetic parameters can be estimated subsequently. The maximum entropy method is a powerful tool to reconstructing images from many types of data. This method is useful for generating the probability distribution based on given information. The proposed method gives an alternative way to assess the input function from the existing data. The proposed method allows a good fit of the data and therefore a better estimation of the kinetic parameters. In the end, this allows for a more reliable use of DCE-MRI. Schattauer GmbH.

  7. Direct comparison of phase-sensitive vibrational sum frequency generation with maximum entropy method: case study of water.

    Science.gov (United States)

    de Beer, Alex G F; Samson, Jean-Sebastièn; Hua, Wei; Huang, Zishuai; Chen, Xiangke; Allen, Heather C; Roke, Sylvie

    2011-12-14

    We present a direct comparison of phase sensitive sum-frequency generation experiments with phase reconstruction obtained by the maximum entropy method. We show that both methods lead to the same complex spectrum. Furthermore, we discuss the strengths and weaknesses of each of these methods, analyzing possible sources of experimental and analytical errors. A simulation program for maximum entropy phase reconstruction is available at: http://lbp.epfl.ch/. © 2011 American Institute of Physics

  8. Analysis of positron lifetime spectra using quantified maximum entropy and a general linear filter

    International Nuclear Information System (INIS)

    Shukla, A.; Peter, M.; Hoffmann, L.

    1993-01-01

    Two new approaches are used to analyze positron annihilation lifetime spectra. A general linear filter is designed to filter the noise from lifetime data. The quantified maximum entropy method is used to solve the inverse problem of finding the lifetimes and intensities present in data. We determine optimal values of parameters needed for fitting using Bayesian methods. Estimates of errors are provided. We present results on simulated and experimental data with extensive tests to show the utility of this method and compare it with other existing methods. (orig.)

  9. Spectral density analysis of time correlation functions in lattice QCD using the maximum entropy method

    International Nuclear Information System (INIS)

    Fiebig, H. Rudolf

    2002-01-01

    We study various aspects of extracting spectral information from time correlation functions of lattice QCD by means of Bayesian inference with an entropic prior, the maximum entropy method (MEM). Correlator functions of a heavy-light meson-meson system serve as a repository for lattice data with diverse statistical quality. Attention is given to spectral mass density functions, inferred from the data, and their dependence on the parameters of the MEM. We propose to employ simulated annealing, or cooling, to solve the Bayesian inference problem, and discuss the practical issues of the approach

  10. The Maximum Entropy Production Principle: Its Theoretical Foundations and Applications to the Earth System

    Directory of Open Access Journals (Sweden)

    Axel Kleidon

    2010-03-01

    Full Text Available The Maximum Entropy Production (MEP principle has been remarkably successful in producing accurate predictions for non-equilibrium states. We argue that this is because the MEP principle is an effective inference procedure that produces the best predictions from the available information. Since all Earth system processes are subject to the conservation of energy, mass and momentum, we argue that in practical terms the MEP principle should be applied to Earth system processes in terms of the already established framework of non-equilibrium thermodynamics, with the assumption of local thermodynamic equilibrium at the appropriate scales.

  11. Nuclear Enhanced X-ray Maximum Entropy Method Used to Analyze Local Distortions in Simple Structures

    DEFF Research Database (Denmark)

    Christensen, Sebastian; Bindzus, Niels; Christensen, Mogens

    We introduce a novel method for reconstructing pseudo nuclear density distributions (NDDs): Nuclear Enhanced X-ray Maximum Entropy Method (NEXMEM). NEXMEM offers an alternative route to experimental NDDs, exploiting the superior quality of synchrotron X-ray data compared to neutron data. The method...... proposed to result from anharmonic phonon scattering or from local fluctuating dipoles on the Pb site.[1,2] No macroscopic symmetry change are associated with these effects, rendering them invisible to conventional crystallographic techniques. For this reason PbX was until recently believed to adopt...

  12. Chaos control of ferroresonance system based on RBF-maximum entropy clustering algorithm

    International Nuclear Information System (INIS)

    Liu Fan; Sun Caixin; Sima Wenxia; Liao Ruijin; Guo Fei

    2006-01-01

    With regards to the ferroresonance overvoltage of neutral grounded power system, a maximum-entropy learning algorithm based on radial basis function neural networks is used to control the chaotic system. The algorithm optimizes the object function to derive learning rule of central vectors, and uses the clustering function of network hidden layers. It improves the regression and learning ability of neural networks. The numerical experiment of ferroresonance system testifies the effectiveness and feasibility of using the algorithm to control chaos in neutral grounded system

  13. Maximum-entropy data restoration using both real- and Fourier-space analysis

    International Nuclear Information System (INIS)

    Anderson, D.M.; Martin, D.C.; Thomas, E.L.

    1989-01-01

    An extension of the maximum-entropy (ME) data-restoration method is presented that is sensitive to periodic correlations in data. The method takes advantage of the higher signal-to-noise ratio for periodic information in Fourier space, thus enhancing statistically significant frequencies in a manner which avoids the user bias inherent in conventional Fourier filtering. This procedure incorporates concepts underlying new approaches in quantum mechanics that consider entropies in both position and momentum spaces, although the emphasis here is on data restoration rather than quantum physics. After a fast Fourier transform of the image, the phases are saved and the array of Fourier moduli are restored using the maximum-entropy criterion. A first-order continuation method is introduced that speeds convergence of the ME computation. The restored moduli together with the original phases are then Fourier inverted to yield a new image; traditional real-space ME restoration is applied to this new image completing one stage in the restoration process. In test cases improvement can be obtained from two to four stages of iteration. It is shown that in traditional Fourier filtering spurious features can be induced by selection or elimination of Fourier components without regard to their statistical significance. With the present approach there is no such freedom for the user to exert personal bias, so that features present in the final image and power spectrum are those which have survived the tests of statistical significance in both real and Fourier space. However, it is still possible for periodicities to 'bleed' across sharp boundaries. An 'uncertainty' relation is derived describing the inverse relationship between the resolution of these boundaries and the level of noise that can be eliminated. (orig./BHO)

  14. Algorithms for optimized maximum entropy and diagnostic tools for analytic continuation

    Science.gov (United States)

    Bergeron, Dominic; Tremblay, A.-M. S.

    2016-08-01

    Analytic continuation of numerical data obtained in imaginary time or frequency has become an essential part of many branches of quantum computational physics. It is, however, an ill-conditioned procedure and thus a hard numerical problem. The maximum-entropy approach, based on Bayesian inference, is the most widely used method to tackle that problem. Although the approach is well established and among the most reliable and efficient ones, useful developments of the method and of its implementation are still possible. In addition, while a few free software implementations are available, a well-documented, optimized, general purpose, and user-friendly software dedicated to that specific task is still lacking. Here we analyze all aspects of the implementation that are critical for accuracy and speed and present a highly optimized approach to maximum entropy. Original algorithmic and conceptual contributions include (1) numerical approximations that yield a computational complexity that is almost independent of temperature and spectrum shape (including sharp Drude peaks in broad background, for example) while ensuring quantitative accuracy of the result whenever precision of the data is sufficient, (2) a robust method of choosing the entropy weight α that follows from a simple consistency condition of the approach and the observation that information- and noise-fitting regimes can be identified clearly from the behavior of χ2 with respect to α , and (3) several diagnostics to assess the reliability of the result. Benchmarks with test spectral functions of different complexity and an example with an actual physical simulation are presented. Our implementation, which covers most typical cases for fermions, bosons, and response functions, is available as an open source, user-friendly software.

  15. Calculating the Prior Probability Distribution for a Causal Network Using Maximum Entropy: Alternative Approaches

    Directory of Open Access Journals (Sweden)

    Michael J. Markham

    2011-07-01

    Full Text Available Some problems occurring in Expert Systems can be resolved by employing a causal (Bayesian network and methodologies exist for this purpose. These require data in a specific form and make assumptions about the independence relationships involved. Methodologies using Maximum Entropy (ME are free from these conditions and have the potential to be used in a wider context including systems consisting of given sets of linear and independence constraints, subject to consistency and convergence. ME can also be used to validate results from the causal network methodologies. Three ME methods for determining the prior probability distribution of causal network systems are considered. The first method is Sequential Maximum Entropy in which the computation of a progression of local distributions leads to the over-all distribution. This is followed by development of the Method of Tribus. The development takes the form of an algorithm that includes the handling of explicit independence constraints. These fall into two groups those relating parents of vertices, and those deduced from triangulation of the remaining graph. The third method involves a variation in the part of that algorithm which handles independence constraints. Evidence is presented that this adaptation only requires the linear constraints and the parental independence constraints to emulate the second method in a substantial class of examples.

  16. Maximum entropy methods for extracting the learned features of deep neural networks.

    Science.gov (United States)

    Finnegan, Alex; Song, Jun S

    2017-10-01

    New architectures of multilayer artificial neural networks and new methods for training them are rapidly revolutionizing the application of machine learning in diverse fields, including business, social science, physical sciences, and biology. Interpreting deep neural networks, however, currently remains elusive, and a critical challenge lies in understanding which meaningful features a network is actually learning. We present a general method for interpreting deep neural networks and extracting network-learned features from input data. We describe our algorithm in the context of biological sequence analysis. Our approach, based on ideas from statistical physics, samples from the maximum entropy distribution over possible sequences, anchored at an input sequence and subject to constraints implied by the empirical function learned by a network. Using our framework, we demonstrate that local transcription factor binding motifs can be identified from a network trained on ChIP-seq data and that nucleosome positioning signals are indeed learned by a network trained on chemical cleavage nucleosome maps. Imposing a further constraint on the maximum entropy distribution also allows us to probe whether a network is learning global sequence features, such as the high GC content in nucleosome-rich regions. This work thus provides valuable mathematical tools for interpreting and extracting learned features from feed-forward neural networks.

  17. Maximum entropy estimation of a Benzene contaminated plume using ecotoxicological assays

    International Nuclear Information System (INIS)

    Wahyudi, Agung; Bartzke, Mariana; Küster, Eberhard; Bogaert, Patrick

    2013-01-01

    Ecotoxicological bioassays, e.g. based on Danio rerio teratogenicity (DarT) or the acute luminescence inhibition with Vibrio fischeri, could potentially lead to significant benefits for detecting on site contaminations on qualitative or semi-quantitative bases. The aim was to use the observed effects of two ecotoxicological assays for estimating the extent of a Benzene groundwater contamination plume. We used a Maximum Entropy (MaxEnt) method to rebuild a bivariate probability table that links the observed toxicity from the bioassays with Benzene concentrations. Compared with direct mapping of the contamination plume as obtained from groundwater samples, the MaxEnt concentration map exhibits on average slightly higher concentrations though the global pattern is close to it. This suggest MaxEnt is a valuable method to build a relationship between quantitative data, e.g. contaminant concentrations, and more qualitative or indirect measurements, in a spatial mapping framework, which is especially useful when clear quantitative relation is not at hand. - Highlights: ► Ecotoxicological shows significant benefits for detecting on site contaminations. ► MaxEnt to rebuild qualitative link on concentration and ecotoxicological assays. ► MaxEnt shows similar pattern when compared with concentrations map of groundwater. ► MaxEnt is a valuable method especially when quantitative relation is not at hand. - A Maximum Entropy method to rebuild qualitative relationships between Benzene groundwater concentrations and their ecotoxicological effect.

  18. Maximum Entropy Production Is Not a Steady State Attractor for 2D Fluid Convection

    Directory of Open Access Journals (Sweden)

    Stuart Bartlett

    2016-12-01

    Full Text Available Multiple authors have claimed that the natural convection of a fluid is a process that exhibits maximum entropy production (MEP. However, almost all such investigations were limited to fixed temperature boundary conditions (BCs. It was found that under those conditions, the system tends to maximize its heat flux, and hence it was concluded that the MEP state is a dynamical attractor. However, since entropy production varies with heat flux and difference of inverse temperature, it is essential that any complete investigation of entropy production allows for variations in heat flux and temperature difference. Only then can we legitimately assess whether the MEP state is the most attractive. Our previous work made use of negative feedback BCs to explore this possibility. We found that the steady state of the system was far from the MEP state. For any system, entropy production can only be maximized subject to a finite set of physical and material constraints. In the case of our previous work, it was possible that the adopted set of fluid parameters were constraining the system in such a way that it was entirely prevented from reaching the MEP state. Hence, in the present work, we used a different set of boundary parameters, such that the steady states of the system were in the local vicinity of the MEP state. If MEP was indeed an attractor, relaxing those constraints of our previous work should have caused a discrete perturbation to the surface of steady state heat flux values near the value corresponding to MEP. We found no such perturbation, and hence no discernible attraction to the MEP state. Furthermore, systems with fixed flux BCs actually minimize their entropy production (relative to the alternative stable state, that of pure diffusive heat transport. This leads us to conclude that the principle of MEP is not an accurate indicator of which stable steady state a convective system will adopt. However, for all BCs considered, the quotient of

  19. Modeling Electric Discharges with Entropy Production Rate Principles

    Directory of Open Access Journals (Sweden)

    Thomas Christen

    2009-12-01

    Full Text Available Under which circumstances are variational principles based on entropy production rate useful tools for modeling steady states of electric (gas discharge systems far from equilibrium? It is first shown how various different approaches, as Steenbeck’s minimum voltage and Prigogine’s minimum entropy production rate principles are related to the maximum entropy production rate principle (MEPP. Secondly, three typical examples are discussed, which provide a certain insight in the structure of the models that are candidates for MEPP application. It is then thirdly argued that MEPP, although not being an exact physical law, may provide reasonable model parameter estimates, provided the constraints contain the relevant (nonlinear physical effects and the parameters to be determined are related to disregarded weak constraints that affect mainly global entropy production. Finally, it is additionally conjectured that a further reason for the success of MEPP in certain far from equilibrium systems might be based on a hidden linearity of the underlying kinetic equation(s.

  20. Maximum Entropy Methods as the Bridge Between Microscopic and Macroscopic Theory

    Science.gov (United States)

    Taylor, Jamie M.

    2016-09-01

    This paper is concerned with an investigation into a function of macroscopic variables known as the singular potential, building on previous work by Ball and Majumdar. The singular potential is a function of the admissible statistical averages of probability distributions on a state space, defined so that it corresponds to the maximum possible entropy given known observed statistical averages, although non-classical entropy-like objective functions will also be considered. First the set of admissible moments must be established, and under the conditions presented in this work the set is open, bounded and convex allowing a description in terms of supporting hyperplanes, which provides estimates on the development of singularities for related probability distributions. Under appropriate conditions it is shown that the singular potential is strictly convex, as differentiable as the microscopic entropy, and blows up uniformly as the macroscopic variable tends to the boundary of the set of admissible moments. Applications of the singular potential are then discussed, and particular consideration will be given to certain free-energy functionals typical in mean-field theory, demonstrating an equivalence between certain microscopic and macroscopic free-energy functionals. This allows statements about L^1-local minimisers of Onsager's free energy to be obtained which cannot be given by two-sided variations, and overcomes the need to ensure local minimisers are bounded away from zero and +∞ before taking L^∞ variations. The analysis also permits the definition of a dual order parameter for which Onsager's free energy allows an explicit representation. Also, the difficulties in approximating the singular potential by everywhere defined functions, in particular by polynomial functions, are addressed, with examples demonstrating the failure of the Taylor approximation to preserve relevant shape properties of the singular potential.

  1. Spectral maximum entropy hydrodynamics of fermionic radiation: a three-moment system for one-dimensional flows

    International Nuclear Information System (INIS)

    Banach, Zbigniew; Larecki, Wieslaw

    2013-01-01

    The spectral formulation of the nine-moment radiation hydrodynamics resulting from using the Boltzmann entropy maximization procedure is considered. The analysis is restricted to the one-dimensional flows of a gas of massless fermions. The objective of the paper is to demonstrate that, for such flows, the spectral nine-moment maximum entropy hydrodynamics of fermionic radiation is not a purely formal theory. We first determine the domains of admissible values of the spectral moments and of the Lagrange multipliers corresponding to them. We then prove the existence of a solution to the constrained entropy optimization problem. Due to the strict concavity of the entropy functional defined on the space of distribution functions, there exists a one-to-one correspondence between the Lagrange multipliers and the moments. The maximum entropy closure of moment equations results in the symmetric conservative system of first-order partial differential equations for the Lagrange multipliers. However, this system can be transformed into the equivalent system of conservation equations for the moments. These two systems are consistent with the additional conservation equation interpreted as the balance of entropy. Exploiting the above facts, we arrive at the differential relations satisfied by the entropy function and the additional function required to close the system of moment equations. We refer to this additional function as the moment closure function. In general, the moment closure and entropy–entropy flux functions cannot be explicitly calculated in terms of the moments determining the state of a gas. Therefore, we develop a perturbation method of calculating these functions. Some additional analytical (and also numerical) results are obtained, assuming that the maximum entropy distribution function tends to the Maxwell–Boltzmann limit. (paper)

  2. Maximum entropy formalism for the analytic continuation of matrix-valued Green's functions

    Science.gov (United States)

    Kraberger, Gernot J.; Triebl, Robert; Zingl, Manuel; Aichhorn, Markus

    2017-10-01

    We present a generalization of the maximum entropy method to the analytic continuation of matrix-valued Green's functions. To treat off-diagonal elements correctly based on Bayesian probability theory, the entropy term has to be extended for spectral functions that are possibly negative in some frequency ranges. In that way, all matrix elements of the Green's function matrix can be analytically continued; we introduce a computationally cheap element-wise method for this purpose. However, this method cannot ensure important constraints on the mathematical properties of the resulting spectral functions, namely positive semidefiniteness and Hermiticity. To improve on this, we present a full matrix formalism, where all matrix elements are treated simultaneously. We show the capabilities of these methods using insulating and metallic dynamical mean-field theory (DMFT) Green's functions as test cases. Finally, we apply the methods to realistic material calculations for LaTiO3, where off-diagonal matrix elements in the Green's function appear due to the distorted crystal structure.

  3. Imaging VLBI polarimetry data from Active Galactic Nuclei using the Maximum Entropy Method

    Directory of Open Access Journals (Sweden)

    Coughlan Colm P.

    2013-12-01

    Full Text Available Mapping the relativistic jets emanating from AGN requires the use of a deconvolution algorithm to account for the effects of missing baseline spacings. The CLEAN algorithm is the most commonly used algorithm in VLBI imaging today and is suitable for imaging polarisation data. The Maximum Entropy Method (MEM is presented as an alternative with some advantages over the CLEAN algorithm, including better spatial resolution and a more rigorous and unbiased approach to deconvolution. We have developed a MEM code suitable for deconvolving VLBI polarisation data. Monte Carlo simulations investigating the performance of CLEAN and the MEM code on a variety of source types are being carried out. Real polarisation (VLBA data taken at multiple wavelengths have also been deconvolved using MEM, and several of the resulting polarisation and Faraday rotation maps are presented and discussed.

  4. Halo-independence with quantified maximum entropy at DAMA/LIBRA

    Energy Technology Data Exchange (ETDEWEB)

    Fowlie, Andrew, E-mail: andrew.j.fowlie@googlemail.com [ARC Centre of Excellence for Particle Physics at the Tera-scale, Monash University, Melbourne, Victoria 3800 (Australia)

    2017-10-01

    Using the DAMA/LIBRA anomaly as an example, we formalise the notion of halo-independence in the context of Bayesian statistics and quantified maximum entropy. We consider an infinite set of possible profiles, weighted by an entropic prior and constrained by a likelihood describing noisy measurements of modulated moments by DAMA/LIBRA. Assuming an isotropic dark matter (DM) profile in the galactic rest frame, we find the most plausible DM profiles and predictions for unmodulated signal rates at DAMA/LIBRA. The entropic prior contains an a priori unknown regularisation factor, β, that describes the strength of our conviction that the profile is approximately Maxwellian. By varying β, we smoothly interpolate between a halo-independent and a halo-dependent analysis, thus exploring the impact of prior information about the DM profile.

  5. Spectrum unfolding, sensitivity analysis and propagation of uncertainties with the maximum entropy deconvolution code MAXED

    CERN Document Server

    Reginatto, M; Neumann, S

    2002-01-01

    MAXED was developed to apply the maximum entropy principle to the unfolding of neutron spectrometric measurements. The approach followed in MAXED has several features that make it attractive: it permits inclusion of a priori information in a well-defined and mathematically consistent way, the algorithm used to derive the solution spectrum is not ad hoc (it can be justified on the basis of arguments that originate in information theory), and the solution spectrum is a non-negative function that can be written in closed form. This last feature permits the use of standard methods for the sensitivity analysis and propagation of uncertainties of MAXED solution spectra. We illustrate its use with unfoldings of NE 213 scintillation detector measurements of photon calibration spectra, and of multisphere neutron spectrometer measurements of cosmic-ray induced neutrons at high altitude (approx 20 km) in the atmosphere.

  6. Comparison of two views of maximum entropy in biodiversity: Frank (2011) and Pueyo et al. (2007).

    Science.gov (United States)

    Pueyo, Salvador

    2012-05-01

    An increasing number of authors agree in that the maximum entropy principle (MaxEnt) is essential for the understanding of macroecological patterns. However, there are subtle but crucial differences among the approaches by several of these authors. This poses a major obstacle for anyone interested in applying the methodology of MaxEnt in this context. In a recent publication, Frank (2011) gives some arguments why his own approach would represent an improvement as compared to the earlier paper by Pueyo et al. (2007) and also to the views by Edwin T. Jaynes, who first formulated MaxEnt in the context of statistical physics. Here I show that his criticisms are flawed and that there are fundamental reasons to prefer the original approach.

  7. Bayesian and maximum entropy methods for fusion diagnostic measurements with compact neutron spectrometers

    International Nuclear Information System (INIS)

    Reginatto, Marcel; Zimbal, Andreas

    2008-01-01

    In applications of neutron spectrometry to fusion diagnostics, it is advantageous to use methods of data analysis which can extract information from the spectrum that is directly related to the parameters of interest that describe the plasma. We present here methods of data analysis which were developed with this goal in mind, and which were applied to spectrometric measurements made with an organic liquid scintillation detector (type NE213). In our approach, we combine Bayesian parameter estimation methods and unfolding methods based on the maximum entropy principle. This two-step method allows us to optimize the analysis of the data depending on the type of information that we want to extract from the measurements. To illustrate these methods, we analyze neutron measurements made at the PTB accelerator under controlled conditions, using accelerator-produced neutron beams. Although the methods have been chosen with a specific application in mind, they are general enough to be useful for many other types of measurements

  8. An understanding of human dynamics in urban subway traffic from the Maximum Entropy Principle

    Science.gov (United States)

    Yong, Nuo; Ni, Shunjiang; Shen, Shifei; Ji, Xuewei

    2016-08-01

    We studied the distribution of entry time interval in Beijing subway traffic by analyzing the smart card transaction data, and then deduced the probability distribution function of entry time interval based on the Maximum Entropy Principle. Both theoretical derivation and data statistics indicated that the entry time interval obeys power-law distribution with an exponential cutoff. In addition, we pointed out the constraint conditions for the distribution form and discussed how the constraints affect the distribution function. It is speculated that for bursts and heavy tails in human dynamics, when the fitted power exponent is less than 1.0, it cannot be a pure power-law distribution, but with an exponential cutoff, which may be ignored in the previous studies.

  9. Bayesian Maximum Entropy Based Algorithm for Digital X-ray Mammogram Processing

    Directory of Open Access Journals (Sweden)

    Radu Mutihac

    2009-06-01

    Full Text Available Basics of Bayesian statistics in inverse problems using the maximum entropy principle are summarized in connection with the restoration of positive, additive images from various types of data like X-ray digital mammograms. An efficient iterative algorithm for image restoration from large data sets based on the conjugate gradient method and Lagrange multipliers in nonlinear optimization of a specific potential function was developed. The point spread function of the imaging system was determined by numerical simulations of inhomogeneous breast-like tissue with microcalcification inclusions of various opacities. The processed digital and digitized mammograms resulted superior in comparison with their raw counterparts in terms of contrast, resolution, noise, and visibility of details.

  10. Entropy Characterization of Random Network Models

    Directory of Open Access Journals (Sweden)

    Pedro J. Zufiria

    2017-06-01

    Full Text Available This paper elaborates on the Random Network Model (RNM as a mathematical framework for modelling and analyzing the generation of complex networks. Such framework allows the analysis of the relationship between several network characterizing features (link density, clustering coefficient, degree distribution, connectivity, etc. and entropy-based complexity measures, providing new insight on the generation and characterization of random networks. Some theoretical and computational results illustrate the utility of the proposed framework.

  11. FOREST TREE SPECIES DISTRIBUTION MAPPING USING LANDSAT SATELLITE IMAGERY AND TOPOGRAPHIC VARIABLES WITH THE MAXIMUM ENTROPY METHOD IN MONGOLIA

    Directory of Open Access Journals (Sweden)

    S. H. Chiang

    2016-06-01

    Full Text Available Forest is a very important ecosystem and natural resource for living things. Based on forest inventories, government is able to make decisions to converse, improve and manage forests in a sustainable way. Field work for forestry investigation is difficult and time consuming, because it needs intensive physical labor and the costs are high, especially surveying in remote mountainous regions. A reliable forest inventory can give us a more accurate and timely information to develop new and efficient approaches of forest management. The remote sensing technology has been recently used for forest investigation at a large scale. To produce an informative forest inventory, forest attributes, including tree species are unavoidably required to be considered. In this study the aim is to classify forest tree species in Erdenebulgan County, Huwsgul province in Mongolia, using Maximum Entropy method. The study area is covered by a dense forest which is almost 70% of total territorial extension of Erdenebulgan County and is located in a high mountain region in northern Mongolia. For this study, Landsat satellite imagery and a Digital Elevation Model (DEM were acquired to perform tree species mapping. The forest tree species inventory map was collected from the Forest Division of the Mongolian Ministry of Nature and Environment as training data and also used as ground truth to perform the accuracy assessment of the tree species classification. Landsat images and DEM were processed for maximum entropy modeling, and this study applied the model with two experiments. The first one is to use Landsat surface reflectance for tree species classification; and the second experiment incorporates terrain variables in addition to the Landsat surface reflectance to perform the tree species classification. All experimental results were compared with the tree species inventory to assess the classification accuracy. Results show that the second one which uses Landsat surface

  12. Forest Tree Species Distribution Mapping Using Landsat Satellite Imagery and Topographic Variables with the Maximum Entropy Method in Mongolia

    Science.gov (United States)

    Hao Chiang, Shou; Valdez, Miguel; Chen, Chi-Farn

    2016-06-01

    Forest is a very important ecosystem and natural resource for living things. Based on forest inventories, government is able to make decisions to converse, improve and manage forests in a sustainable way. Field work for forestry investigation is difficult and time consuming, because it needs intensive physical labor and the costs are high, especially surveying in remote mountainous regions. A reliable forest inventory can give us a more accurate and timely information to develop new and efficient approaches of forest management. The remote sensing technology has been recently used for forest investigation at a large scale. To produce an informative forest inventory, forest attributes, including tree species are unavoidably required to be considered. In this study the aim is to classify forest tree species in Erdenebulgan County, Huwsgul province in Mongolia, using Maximum Entropy method. The study area is covered by a dense forest which is almost 70% of total territorial extension of Erdenebulgan County and is located in a high mountain region in northern Mongolia. For this study, Landsat satellite imagery and a Digital Elevation Model (DEM) were acquired to perform tree species mapping. The forest tree species inventory map was collected from the Forest Division of the Mongolian Ministry of Nature and Environment as training data and also used as ground truth to perform the accuracy assessment of the tree species classification. Landsat images and DEM were processed for maximum entropy modeling, and this study applied the model with two experiments. The first one is to use Landsat surface reflectance for tree species classification; and the second experiment incorporates terrain variables in addition to the Landsat surface reflectance to perform the tree species classification. All experimental results were compared with the tree species inventory to assess the classification accuracy. Results show that the second one which uses Landsat surface reflectance coupled

  13. Configurational entropy in brane-world models

    Energy Technology Data Exchange (ETDEWEB)

    Correa, R.A.C. [CCNH, Universidade Federal do ABC, Santo Andre, SP (Brazil); Rocha, Roldao da [CMCC, Universidade Federal do ABC, Santo Andre, SP (Brazil); International School for Advanced Studies (SISSA), Trieste (Italy)

    2015-11-15

    In this work we investigate the entropic information on thick brane-world scenarios and its consequences. The brane-world entropic information is studied for the sine-Gordon model and hence the brane-world entropic information measure is shown to be an accurate way for providing the most suitable range for the bulk AdS curvature, in particular from the informational content of physical solutions. Besides, the brane-world configurational entropy is employed to demonstrate a high organisational degree in the structure of the configuration of the system, for large values of a parameter of the sine-Gordon model but the one related to the AdS curvature. The Gleiser and Stamatopoulos procedure is finally applied in order to achieve a precise correlation between the energy of the system and the brane-world configurational entropy. (orig.)

  14. Configurational entropy in brane-world models

    Energy Technology Data Exchange (ETDEWEB)

    Correa, R. A. C., E-mail: fis04132@gmail.com [CCNH, Universidade Federal do ABC, 09210-580, Santo André, SP (Brazil); Rocha, Roldão da, E-mail: roldao.rocha@ufabc.edu.br [CMCC, Universidade Federal do ABC, 09210-580, Santo André, SP (Brazil); International School for Advanced Studies (SISSA), Via Bonomea 265, 34136, Trieste (Italy)

    2015-11-02

    In this work we investigate the entropic information on thick brane-world scenarios and its consequences. The brane-world entropic information is studied for the sine-Gordon model and hence the brane-world entropic information measure is shown to be an accurate way for providing the most suitable range for the bulk AdS curvature, in particular from the informational content of physical solutions. Besides, the brane-world configurational entropy is employed to demonstrate a high organisational degree in the structure of the configuration of the system, for large values of a parameter of the sine-Gordon model but the one related to the AdS curvature. The Gleiser and Stamatopoulos procedure is finally applied in order to achieve a precise correlation between the energy of the system and the brane-world configurational entropy.

  15. Configurational entropy in brane-world models

    International Nuclear Information System (INIS)

    Correa, R. A. C.; Rocha, Roldão da

    2015-01-01

    In this work we investigate the entropic information on thick brane-world scenarios and its consequences. The brane-world entropic information is studied for the sine-Gordon model and hence the brane-world entropic information measure is shown to be an accurate way for providing the most suitable range for the bulk AdS curvature, in particular from the informational content of physical solutions. Besides, the brane-world configurational entropy is employed to demonstrate a high organisational degree in the structure of the configuration of the system, for large values of a parameter of the sine-Gordon model but the one related to the AdS curvature. The Gleiser and Stamatopoulos procedure is finally applied in order to achieve a precise correlation between the energy of the system and the brane-world configurational entropy

  16. Dynamics of non-stationary processes that follow the maximum of the Rényi entropy principle.

    Science.gov (United States)

    Shalymov, Dmitry S; Fradkov, Alexander L

    2016-01-01

    We propose dynamics equations which describe the behaviour of non-stationary processes that follow the maximum Rényi entropy principle. The equations are derived on the basis of the speed-gradient principle originated in the control theory. The maximum of the Rényi entropy principle is analysed for discrete and continuous cases, and both a discrete random variable and probability density function (PDF) are used. We consider mass conservation and energy conservation constraints and demonstrate the uniqueness of the limit distribution and asymptotic convergence of the PDF for both cases. The coincidence of the limit distribution of the proposed equations with the Rényi distribution is examined.

  17. The Maximum Entropy Method for Optical Spectrum Analysis of Real-Time TDDFT

    International Nuclear Information System (INIS)

    Toogoshi, M; Kano, S S; Zempo, Y

    2015-01-01

    The maximum entropy method (MEM) is one of the key techniques for spectral analysis. The major feature is that spectra in the low frequency part can be described by the short time-series data. Thus, we applied MEM to analyse the spectrum from the time dependent dipole moment obtained from the time-dependent density functional theory (TDDFT) calculation in real time. It is intensively studied for computing optical properties. In the MEM analysis, however, the maximum lag of the autocorrelation is restricted by the total number of time-series data. We proposed that, as an improved MEM analysis, we use the concatenated data set made from the several-times repeated raw data. We have applied this technique to the spectral analysis of the TDDFT dipole moment of ethylene and oligo-fluorene with n = 8. As a result, the higher resolution can be obtained, which is closer to that of FT with practically time-evoluted data as the same total number of time steps. The efficiency and the characteristic feature of this technique are presented in this paper. (paper)

  18. Non-equilibrium thermodynamics, maximum entropy production and Earth-system evolution.

    Science.gov (United States)

    Kleidon, Axel

    2010-01-13

    The present-day atmosphere is in a unique state far from thermodynamic equilibrium. This uniqueness is for instance reflected in the high concentration of molecular oxygen and the low relative humidity in the atmosphere. Given that the concentration of atmospheric oxygen has likely increased throughout Earth-system history, we can ask whether this trend can be generalized to a trend of Earth-system evolution that is directed away from thermodynamic equilibrium, why we would expect such a trend to take place and what it would imply for Earth-system evolution as a whole. The justification for such a trend could be found in the proposed general principle of maximum entropy production (MEP), which states that non-equilibrium thermodynamic systems maintain steady states at which entropy production is maximized. Here, I justify and demonstrate this application of MEP to the Earth at the planetary scale. I first describe the non-equilibrium thermodynamic nature of Earth-system processes and distinguish processes that drive the system's state away from equilibrium from those that are directed towards equilibrium. I formulate the interactions among these processes from a thermodynamic perspective and then connect them to a holistic view of the planetary thermodynamic state of the Earth system. In conclusion, non-equilibrium thermodynamics and MEP have the potential to provide a simple and holistic theory of Earth-system functioning. This theory can be used to derive overall evolutionary trends of the Earth's past, identify the role that life plays in driving thermodynamic states far from equilibrium, identify habitability in other planetary environments and evaluate human impacts on Earth-system functioning. This journal is © 2010 The Royal Society

  19. An Instructive Model of Entropy

    Science.gov (United States)

    Zimmerman, Seth

    2010-01-01

    This article first notes the misinterpretation of a common thought experiment, and the misleading comment that "systems tend to flow from less probable to more probable macrostates". It analyses the experiment, generalizes it and introduces a new tool of investigation, the simplectic structure. A time-symmetric model is built upon this structure,…

  20. Test the principle of maximum entropy in constant sum 2×2 game: Evidence in experimental economics

    International Nuclear Information System (INIS)

    Xu, Bin; Zhang, Hongen; Wang, Zhijian; Zhang, Jianbo

    2012-01-01

    By using laboratory experimental data, we test the uncertainty of strategy type in various competing environments with two-person constant sum 2×2 game in the social system. It firstly shows that, in these competing game environments, the outcome of human's decision-making obeys the principle of the maximum entropy. -- Highlights: ► Test the uncertainty in two-person constant sum games with experimental data. ► On game level, the constant sum game fits the principle of maximum entropy. ► On group level, all empirical entropy values are close to theoretical maxima. ► The results can be different for the games that are not constant sum game.

  1. Test the principle of maximum entropy in constant sum 2×2 game: Evidence in experimental economics

    Energy Technology Data Exchange (ETDEWEB)

    Xu, Bin, E-mail: xubin211@zju.edu.cn [Experimental Social Science Laboratory, Zhejiang University, Hangzhou, 310058 (China); Public Administration College, Zhejiang Gongshang University, Hangzhou, 310018 (China); Zhang, Hongen, E-mail: hongen777@163.com [Department of Physics, Zhejiang University, Hangzhou, 310027 (China); Wang, Zhijian, E-mail: wangzj@zju.edu.cn [Experimental Social Science Laboratory, Zhejiang University, Hangzhou, 310058 (China); Zhang, Jianbo, E-mail: jbzhang08@zju.edu.cn [Department of Physics, Zhejiang University, Hangzhou, 310027 (China)

    2012-03-19

    By using laboratory experimental data, we test the uncertainty of strategy type in various competing environments with two-person constant sum 2×2 game in the social system. It firstly shows that, in these competing game environments, the outcome of human's decision-making obeys the principle of the maximum entropy. -- Highlights: ► Test the uncertainty in two-person constant sum games with experimental data. ► On game level, the constant sum game fits the principle of maximum entropy. ► On group level, all empirical entropy values are close to theoretical maxima. ► The results can be different for the games that are not constant sum game.

  2. Electron density profile reconstruction by maximum entropy method with multichannel HCN laser interferometer system on SPAC VII

    International Nuclear Information System (INIS)

    Kubo, S.; Narihara, K.; Tomita, Y.; Hasegawa, M.; Tsuzuki, T.; Mohri, A.

    1988-01-01

    A multichannel HCN laser interferometer system has been developed to investigate the plasma electron confinement properties in SPAC VII device. Maximum entropy method is applied to reconstruct the electron density profile from measured line integrated data. Particle diffusion coefficient in the peripheral region of the REB ring core spherator was obtained from the evolution of the density profile. (author)

  3. Well posedness and maximum entropy approximation for the dynamics of quantitative traits

    KAUST Repository

    Boďová , Katarí na; Haskovec, Jan; Markowich, Peter A.

    2017-01-01

    We study the Fokker–Planck equation derived in the large system limit of the Markovian process describing the dynamics of quantitative traits. The Fokker–Planck equation is posed on a bounded domain and its transport and diffusion coefficients vanish on the domain’s boundary. We first argue that, despite this degeneracy, the standard no-flux boundary condition is valid. We derive the weak formulation of the problem and prove the existence and uniqueness of its solutions by constructing the corresponding contraction semigroup on a suitable function space. Then, we prove that for the parameter regime with high enough mutation rate the problem exhibits a positive spectral gap, which implies exponential convergence to equilibrium.Next, we provide a simple derivation of the so-called Dynamic Maximum Entropy (DynMaxEnt) method for approximation of observables (moments) of the Fokker–Planck solution, which can be interpreted as a nonlinear Galerkin approximation. The limited applicability of the DynMaxEnt method inspires us to introduce its modified version that is valid for the whole range of admissible parameters. Finally, we present several numerical experiments to demonstrate the performance of both the original and modified DynMaxEnt methods. We observe that in the parameter regimes where both methods are valid, the modified one exhibits slightly better approximation properties compared to the original one.

  4. LQG and maximum entropy control design for the Hubble Space Telescope

    Science.gov (United States)

    Collins, Emmanuel G., Jr.; Richter, Stephen

    Solar array vibrations are responsible for serious pointing control problems on the Hubble Space Telescope (HST). The original HST control law was not designed to attenuate these disturbances because they were not perceived to be a problem prior to launch. However, significant solar array vibrations do occur due to large changes in the thermal environment as the HST orbits the earth. Using classical techniques, Marshall Space Flight Center in conjunction with Lockheed Missiles and Space Company developed modified HST controllers that were able to suppress the influence of the vibrations of the solar arrays on the line-of-sight (LOS) performance. Substantial LOS improvement was observed when two of these controllers were implemented on orbit. This paper describes the development of modified HST controllers by using modern control techniques, particularly linear-quadratic-gaussian (LQG) design and Maximum Entropy robust control design, a generalization of LQG that incorporates robustness constraints with respect to modal errors. The fundamental issues are discussed candidly and controllers designed using these modern techniques are described.

  5. Decision Aggregation in Distributed Classification by a Transductive Extension of Maximum Entropy/Improved Iterative Scaling

    Directory of Open Access Journals (Sweden)

    George Kesidis

    2008-06-01

    Full Text Available In many ensemble classification paradigms, the function which combines local/base classifier decisions is learned in a supervised fashion. Such methods require common labeled training examples across the classifier ensemble. However, in some scenarios, where an ensemble solution is necessitated, common labeled data may not exist: (i legacy/proprietary classifiers, and (ii spatially distributed and/or multiple modality sensors. In such cases, it is standard to apply fixed (untrained decision aggregation such as voting, averaging, or naive Bayes rules. In recent work, an alternative transductive learning strategy was proposed. There, decisions on test samples were chosen aiming to satisfy constraints measured by each local classifier. This approach was shown to reliably correct for class prior mismatch and to robustly account for classifier dependencies. Significant gains in accuracy over fixed aggregation rules were demonstrated. There are two main limitations of that work. First, feasibility of the constraints was not guaranteed. Second, heuristic learning was applied. Here, we overcome these problems via a transductive extension of maximum entropy/improved iterative scaling for aggregation in distributed classification. This method is shown to achieve improved decision accuracy over the earlier transductive approach and fixed rules on a number of UC Irvine datasets.

  6. Bayesian Maximum Entropy space/time estimation of surface water chloride in Maryland using river distances.

    Science.gov (United States)

    Jat, Prahlad; Serre, Marc L

    2016-12-01

    Widespread contamination of surface water chloride is an emerging environmental concern. Consequently accurate and cost-effective methods are needed to estimate chloride along all river miles of potentially contaminated watersheds. Here we introduce a Bayesian Maximum Entropy (BME) space/time geostatistical estimation framework that uses river distances, and we compare it with Euclidean BME to estimate surface water chloride from 2005 to 2014 in the Gunpowder-Patapsco, Severn, and Patuxent subbasins in Maryland. River BME improves the cross-validation R 2 by 23.67% over Euclidean BME, and river BME maps are significantly different than Euclidean BME maps, indicating that it is important to use river BME maps to assess water quality impairment. The river BME maps of chloride concentration show wide contamination throughout Baltimore and Columbia-Ellicott cities, the disappearance of a clean buffer separating these two large urban areas, and the emergence of multiple localized pockets of contamination in surrounding areas. The number of impaired river miles increased by 0.55% per year in 2005-2009 and by 1.23% per year in 2011-2014, corresponding to a marked acceleration of the rate of impairment. Our results support the need for control measures and increased monitoring of unassessed river miles. Copyright © 2016. Published by Elsevier Ltd.

  7. Improving Bayesian credibility intervals for classifier error rates using maximum entropy empirical priors.

    Science.gov (United States)

    Gustafsson, Mats G; Wallman, Mikael; Wickenberg Bolin, Ulrika; Göransson, Hanna; Fryknäs, M; Andersson, Claes R; Isaksson, Anders

    2010-06-01

    Successful use of classifiers that learn to make decisions from a set of patient examples require robust methods for performance estimation. Recently many promising approaches for determination of an upper bound for the error rate of a single classifier have been reported but the Bayesian credibility interval (CI) obtained from a conventional holdout test still delivers one of the tightest bounds. The conventional Bayesian CI becomes unacceptably large in real world applications where the test set sizes are less than a few hundred. The source of this problem is that fact that the CI is determined exclusively by the result on the test examples. In other words, there is no information at all provided by the uniform prior density distribution employed which reflects complete lack of prior knowledge about the unknown error rate. Therefore, the aim of the study reported here was to study a maximum entropy (ME) based approach to improved prior knowledge and Bayesian CIs, demonstrating its relevance for biomedical research and clinical practice. It is demonstrated how a refined non-uniform prior density distribution can be obtained by means of the ME principle using empirical results from a few designs and tests using non-overlapping sets of examples. Experimental results show that ME based priors improve the CIs when employed to four quite different simulated and two real world data sets. An empirically derived ME prior seems promising for improving the Bayesian CI for the unknown error rate of a designed classifier. Copyright 2010 Elsevier B.V. All rights reserved.

  8. Maximum entropy reconstruction of poloidal magnetic field and radial electric field profiles in tokamaks

    Science.gov (United States)

    Chen, Yihang; Xiao, Chijie; Yang, Xiaoyi; Wang, Tianbo; Xu, Tianchao; Yu, Yi; Xu, Min; Wang, Long; Lin, Chen; Wang, Xiaogang

    2017-10-01

    The Laser-driven Ion beam trace probe (LITP) is a new diagnostic method for measuring poloidal magnetic field (Bp) and radial electric field (Er) in tokamaks. LITP injects a laser-driven ion beam into the tokamak, and Bp and Er profiles can be reconstructed using tomography methods. A reconstruction code has been developed to validate the LITP theory, and both 2D reconstruction of Bp and simultaneous reconstruction of Bp and Er have been attained. To reconstruct from experimental data with noise, Maximum Entropy and Gaussian-Bayesian tomography methods were applied and improved according to the characteristics of the LITP problem. With these improved methods, a reconstruction error level below 15% has been attained with a data noise level of 10%. These methods will be further tested and applied in the following LITP experiments. Supported by the ITER-CHINA program 2015GB120001, CHINA MOST under 2012YQ030142 and National Natural Science Foundation Abstract of China under 11575014 and 11375053.

  9. Linearized semiclassical initial value time correlation functions with maximum entropy analytic continuation.

    Science.gov (United States)

    Liu, Jian; Miller, William H

    2008-09-28

    The maximum entropy analytic continuation (MEAC) method is used to extend the range of accuracy of the linearized semiclassical initial value representation (LSC-IVR)/classical Wigner approximation for real time correlation functions. LSC-IVR provides a very effective "prior" for the MEAC procedure since it is very good for short times, exact for all time and temperature for harmonic potentials (even for correlation functions of nonlinear operators), and becomes exact in the classical high temperature limit. This combined MEAC+LSC/IVR approach is applied here to two highly nonlinear dynamical systems, a pure quartic potential in one dimensional and liquid para-hydrogen at two thermal state points (25 and 14 K under nearly zero external pressure). The former example shows the MEAC procedure to be a very significant enhancement of the LSC-IVR for correlation functions of both linear and nonlinear operators, and especially at low temperature where semiclassical approximations are least accurate. For liquid para-hydrogen, the LSC-IVR is seen already to be excellent at T=25 K, but the MEAC procedure produces a significant correction at the lower temperature (T=14 K). Comparisons are also made as to how the MEAC procedure is able to provide corrections for other trajectory-based dynamical approximations when used as priors.

  10. A Maximum Entropy-Based Chaotic Time-Variant Fragile Watermarking Scheme for Image Tampering Detection

    Directory of Open Access Journals (Sweden)

    Guo-Jheng Yang

    2013-08-01

    Full Text Available The fragile watermarking technique is used to protect intellectual property rights while also providing security and rigorous protection. In order to protect the copyright of the creators, it can be implanted in some representative text or totem. Because all of the media on the Internet are digital, protection has become a critical issue, and determining how to use digital watermarks to protect digital media is thus the topic of our research. This paper uses the Logistic map with parameter u = 4 to generate chaotic dynamic behavior with the maximum entropy 1. This approach increases the security and rigor of the protection. The main research target of information hiding is determining how to hide confidential data so that the naked eye cannot see the difference. Next, we introduce one method of information hiding. Generally speaking, if the image only goes through Arnold’s cat map and the Logistic map, it seems to lack sufficient security. Therefore, our emphasis is on controlling Arnold’s cat map and the initial value of the chaos system to undergo small changes and generate different chaos sequences. Thus, the current time is used to not only make encryption more stringent but also to enhance the security of the digital media.

  11. Analysis of QCD sum rule based on the maximum entropy method

    International Nuclear Information System (INIS)

    Gubler, Philipp

    2012-01-01

    QCD sum rule was developed about thirty years ago and has been used up to the present to calculate various physical quantities like hadrons. It has been, however, needed to assume 'pole + continuum' for the spectral function in the conventional analyses. Application of this method therefore came across with difficulties when the above assumption is not satisfied. In order to avoid this difficulty, analysis to make use of the maximum entropy method (MEM) has been developed by the present author. It is reported here how far this new method can be successfully applied. In the first section, the general feature of the QCD sum rule is introduced. In section 2, it is discussed why the analysis by the QCD sum rule based on the MEM is so effective. In section 3, the MEM analysis process is described, and in the subsection 3.1 likelihood function and prior probability are considered then in subsection 3.2 numerical analyses are picked up. In section 4, some cases of applications are described starting with ρ mesons, then charmoniums in the finite temperature and finally recent developments. Some figures of the spectral functions are shown. In section 5, summing up of the present analysis method and future view are given. (S. Funahashi)

  12. Well posedness and maximum entropy approximation for the dynamics of quantitative traits

    KAUST Repository

    Boďová, Katarína

    2017-11-06

    We study the Fokker–Planck equation derived in the large system limit of the Markovian process describing the dynamics of quantitative traits. The Fokker–Planck equation is posed on a bounded domain and its transport and diffusion coefficients vanish on the domain’s boundary. We first argue that, despite this degeneracy, the standard no-flux boundary condition is valid. We derive the weak formulation of the problem and prove the existence and uniqueness of its solutions by constructing the corresponding contraction semigroup on a suitable function space. Then, we prove that for the parameter regime with high enough mutation rate the problem exhibits a positive spectral gap, which implies exponential convergence to equilibrium.Next, we provide a simple derivation of the so-called Dynamic Maximum Entropy (DynMaxEnt) method for approximation of observables (moments) of the Fokker–Planck solution, which can be interpreted as a nonlinear Galerkin approximation. The limited applicability of the DynMaxEnt method inspires us to introduce its modified version that is valid for the whole range of admissible parameters. Finally, we present several numerical experiments to demonstrate the performance of both the original and modified DynMaxEnt methods. We observe that in the parameter regimes where both methods are valid, the modified one exhibits slightly better approximation properties compared to the original one.

  13. Black hole entropy in the O(N) model

    International Nuclear Information System (INIS)

    Kabat, D.; Shenker, S.H.; Strassler, M.J.

    1995-01-01

    We consider corrections to the entropy of a black hole from an O(N)-invariant linear σ model. We obtain the entropy from a 1/N expansion of the partition function on a cone. The entropy arises from diagrams which are analogous to those introduced by Susskind and Uglum to explain black hole entropy in string theory. The interpretation of the σ-model entropy depends on scale. At short distances, it has a state counting interpretation, as the entropy of entanglement of the N fields φ a . In the infrared, the effective theory has a single composite field σ∼φ a φ a , and the state counting interpretation of the entropy is lost. copyright 1995 The American Physical Society

  14. Developing Soil Moisture Profiles Utilizing Remotely Sensed MW and TIR Based SM Estimates Through Principle of Maximum Entropy

    Science.gov (United States)

    Mishra, V.; Cruise, J. F.; Mecikalski, J. R.

    2015-12-01

    Developing accurate vertical soil moisture profiles with minimum input requirements is important to agricultural as well as land surface modeling. Earlier studies show that the principle of maximum entropy (POME) can be utilized to develop vertical soil moisture profiles with accuracy (MAE of about 1% for a monotonically dry profile; nearly 2% for monotonically wet profiles and 3.8% for mixed profiles) with minimum constraints (surface, mean and bottom soil moisture contents). In this study, the constraints for the vertical soil moisture profiles were obtained from remotely sensed data. Low resolution (25 km) MW soil moisture estimates (AMSR-E) were downscaled to 4 km using a soil evaporation efficiency index based disaggregation approach. The downscaled MW soil moisture estimates served as a surface boundary condition, while 4 km resolution TIR based Atmospheric Land Exchange Inverse (ALEXI) estimates provided the required mean root-zone soil moisture content. Bottom soil moisture content is assumed to be a soil dependent constant. Mulit-year (2002-2011) gridded profiles were developed for the southeastern United States using the POME method. The soil moisture profiles were compared to those generated in land surface models (Land Information System (LIS) and an agricultural model DSSAT) along with available NRCS SCAN sites in the study region. The end product, spatial soil moisture profiles, can be assimilated into agricultural and hydrologic models in lieu of precipitation for data scarce regions.Developing accurate vertical soil moisture profiles with minimum input requirements is important to agricultural as well as land surface modeling. Previous studies have shown that the principle of maximum entropy (POME) can be utilized with minimal constraints to develop vertical soil moisture profiles with accuracy (MAE = 1% for monotonically dry profiles; MAE = 2% for monotonically wet profiles and MAE = 3.8% for mixed profiles) when compared to laboratory and field

  15. Maximum entropy approach to H-theory: Statistical mechanics of hierarchical systems.

    Science.gov (United States)

    Vasconcelos, Giovani L; Salazar, Domingos S P; Macêdo, A M S

    2018-02-01

    A formalism, called H-theory, is applied to the problem of statistical equilibrium of a hierarchical complex system with multiple time and length scales. In this approach, the system is formally treated as being composed of a small subsystem-representing the region where the measurements are made-in contact with a set of "nested heat reservoirs" corresponding to the hierarchical structure of the system, where the temperatures of the reservoirs are allowed to fluctuate owing to the complex interactions between degrees of freedom at different scales. The probability distribution function (pdf) of the temperature of the reservoir at a given scale, conditioned on the temperature of the reservoir at the next largest scale in the hierarchy, is determined from a maximum entropy principle subject to appropriate constraints that describe the thermal equilibrium properties of the system. The marginal temperature distribution of the innermost reservoir is obtained by integrating over the conditional distributions of all larger scales, and the resulting pdf is written in analytical form in terms of certain special transcendental functions, known as the Fox H functions. The distribution of states of the small subsystem is then computed by averaging the quasiequilibrium Boltzmann distribution over the temperature of the innermost reservoir. This distribution can also be written in terms of H functions. The general family of distributions reported here recovers, as particular cases, the stationary distributions recently obtained by Macêdo et al. [Phys. Rev. E 95, 032315 (2017)10.1103/PhysRevE.95.032315] from a stochastic dynamical approach to the problem.

  16. Simultaneous State and Parameter Estimation Using Maximum Relative Entropy with Nonhomogenous Differential Equation Constraints

    Directory of Open Access Journals (Sweden)

    Adom Giffin

    2014-09-01

    Full Text Available In this paper, we continue our efforts to show how maximum relative entropy (MrE can be used as a universal updating algorithm. Here, our purpose is to tackle a joint state and parameter estimation problem where our system is nonlinear and in a non-equilibrium state, i.e., perturbed by varying external forces. Traditional parameter estimation can be performed by using filters, such as the extended Kalman filter (EKF. However, as shown with a toy example of a system with first order non-homogeneous ordinary differential equations, assumptions made by the EKF algorithm (such as the Markov assumption may not be valid. The problem can be solved with exponential smoothing, e.g., exponentially weighted moving average (EWMA. Although this has been shown to produce acceptable filtering results in real exponential systems, it still cannot simultaneously estimate both the state and its parameters and has its own assumptions that are not always valid, for example when jump discontinuities exist. We show that by applying MrE as a filter, we can not only develop the closed form solutions, but we can also infer the parameters of the differential equation simultaneously with the means. This is useful in real, physical systems, where we want to not only filter the noise from our measurements, but we also want to simultaneously infer the parameters of the dynamics of a nonlinear and non-equilibrium system. Although there were many assumptions made throughout the paper to illustrate that EKF and exponential smoothing are special cases ofMrE, we are not “constrained”, by these assumptions. In other words, MrE is completely general and can be used in broader ways.

  17. Spatiotemporal fusion of multiple-satellite aerosol optical depth (AOD) products using Bayesian maximum entropy method

    Science.gov (United States)

    Tang, Qingxin; Bo, Yanchen; Zhu, Yuxin

    2016-04-01

    Merging multisensor aerosol optical depth (AOD) products is an effective way to produce more spatiotemporally complete and accurate AOD products. A spatiotemporal statistical data fusion framework based on a Bayesian maximum entropy (BME) method was developed for merging satellite AOD products in East Asia. The advantages of the presented merging framework are that it not only utilizes the spatiotemporal autocorrelations but also explicitly incorporates the uncertainties of the AOD products being merged. The satellite AOD products used for merging are the Moderate Resolution Imaging Spectroradiometer (MODIS) Collection 5.1 Level-2 AOD products (MOD04_L2) and the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) Deep Blue Level 2 AOD products (SWDB_L2). The results show that the average completeness of the merged AOD data is 95.2%,which is significantly superior to the completeness of MOD04_L2 (22.9%) and SWDB_L2 (20.2%). By comparing the merged AOD to the Aerosol Robotic Network AOD records, the results show that the correlation coefficient (0.75), root-mean-square error (0.29), and mean bias (0.068) of the merged AOD are close to those (the correlation coefficient (0.82), root-mean-square error (0.19), and mean bias (0.059)) of the MODIS AOD. In the regions where both MODIS and SeaWiFS have valid observations, the accuracy of the merged AOD is higher than those of MODIS and SeaWiFS AODs. Even in regions where both MODIS and SeaWiFS AODs are missing, the accuracy of the merged AOD is also close to the accuracy of the regions where both MODIS and SeaWiFS have valid observations.

  18. Entropy in the Tangled Nature Model of evolution

    DEFF Research Database (Denmark)

    Roach, Ty N.F.; Nulton, James; Sibani, Paolo

    2017-01-01

    Applications of entropy principles to evolution and ecology are of tantamount importance given the central role spatiotemporal structuring plays in both evolution and ecological succession. We obtain here a qualitative interpretation of the role of entropy in evolving ecological systems. Our...... interpretation is supported by mathematical arguments using simulation data generated by the Tangled Nature Model (TNM), a stochastic model of evolving ecologies. We define two types of configurational entropy and study their empirical time dependence obtained from the data. Both entropy measures increase...... logarithmically with time, while the entropy per individual decreases in time, in parallel with the growth of emergent structures visible from other aspects of the simulation. We discuss the biological relevance of these entropies to describe niche space and functional space of ecosystems, as well as their use...

  19. MAXED, a computer code for the deconvolution of multisphere neutron spectrometer data using the maximum entropy method

    International Nuclear Information System (INIS)

    Reginatto, M.; Goldhagen, P.

    1998-06-01

    The problem of analyzing data from a multisphere neutron spectrometer to infer the energy spectrum of the incident neutrons is discussed. The main features of the code MAXED, a computer program developed to apply the maximum entropy principle to the deconvolution (unfolding) of multisphere neutron spectrometer data, are described, and the use of the code is illustrated with an example. A user's guide for the code MAXED is included in an appendix. The code is available from the authors upon request

  20. On the equivalence between the minimum entropy generation rate and the maximum conversion rate for a reactive system

    International Nuclear Information System (INIS)

    Bispo, Heleno; Silva, Nilton; Brito, Romildo; Manzi, João

    2013-01-01

    Highlights: • Minimum entropy generation (MEG) principle improved the reaction performance. • MEG rate and the maximum conversion equivalence have been analyzed. • Temperature and residence time are used to the domain establishment of MEG. • Satisfying the temperature and residence time relationship results a optimal performance. - Abstract: The analysis of the equivalence between the minimum entropy generation (MEG) rate and the maximum conversion rate for a reactive system is the main purpose of this paper. While being used as a strategy of optimization, the minimum entropy production was applied to the production of propylene glycol in a Continuous Stirred-Tank Reactor (CSTR) with a view to determining the best operating conditions, and under such conditions, a high conversion rate was found. The effects of the key variables and restrictions on the validity domain of MEG were investigated, which raises issues that are included within a broad discussion. The results from simulations indicate that from the chemical reaction standpoint a maximum conversion rate can be considered as equivalent to MEG. Such a result can be clearly explained by examining the classical Maxwell–Boltzmann distribution, where the molecules of the reactive system under the condition of the MEG rate present a distribution of energy with reduced dispersion resulting in a better quality of collision between molecules with a higher conversion rate

  1. Entropy of measurement and erasure: Szilard's membrane model revisited

    Science.gov (United States)

    Leff, Harvey S.; Rex, Andrew F.

    1994-11-01

    It is widely believed that measurement is accompanied by irreversible entropy increase. This conventional wisdom is based in part on Szilard's 1929 study of entropy decrease in a thermodynamic system by intelligent intervention (i.e., a Maxwell's demon) and Brillouin's association of entropy with information. Bennett subsequently argued that information acquisition is not necessarily irreversible, but information erasure must be dissipative (Landauer's principle). Inspired by the ensuing debate, we revisit the membrane model introduced by Szilard and find that it can illustrate and clarify (1) reversible measurement, (2) information storage, (3) decoupling of the memory from the system being measured, and (4) entropy increase associated with memory erasure and resetting.

  2. Entanglement entropy in a holographic p-wave superconductor model

    Directory of Open Access Journals (Sweden)

    Li-Fang Li

    2015-05-01

    Full Text Available In a recent paper, arXiv:1309.4877, a holographic p-wave model has been proposed in an Einstein–Maxwell-complex vector field theory with a negative cosmological constant. The model exhibits rich phase structure depending on the mass and the charge of the vector field. We investigate the behavior of the entanglement entropy of dual field theory in this model. When the above two model parameters change, we observe the second order, first order and zeroth order phase transitions from the behavior of the entanglement entropy at some intermediate temperatures. These imply that the entanglement entropy can indicate not only the occurrence of the phase transition, but also the order of the phase transition. The entanglement entropy is indeed a good probe to phase transition. Furthermore, the “retrograde condensation” which is a sub-dominated phase is also reflected on the entanglement entropy.

  3. Entanglement entropy in a holographic p-wave superconductor model

    Energy Technology Data Exchange (ETDEWEB)

    Li, Li-Fang, E-mail: lilf@itp.ac.cn [State Key Laboratory of Space Weather, Center for Space Science and Applied Research, Chinese Academy of Sciences, Beijing 100190 (China); Cai, Rong-Gen, E-mail: cairg@itp.ac.cn [State Key Laboratory of Theoretical Physics, Institute of Theoretical Physics, Chinese Academy of Sciences, Beijing 100190 (China); Li, Li, E-mail: liliphy@itp.ac.cn [State Key Laboratory of Theoretical Physics, Institute of Theoretical Physics, Chinese Academy of Sciences, Beijing 100190 (China); Shen, Chao, E-mail: sc@nssc.ac.cn [State Key Laboratory of Space Weather, Center for Space Science and Applied Research, Chinese Academy of Sciences, Beijing 100190 (China)

    2015-05-15

    In a recent paper, (arXiv:1309.4877), a holographic p-wave model has been proposed in an Einstein–Maxwell-complex vector field theory with a negative cosmological constant. The model exhibits rich phase structure depending on the mass and the charge of the vector field. We investigate the behavior of the entanglement entropy of dual field theory in this model. When the above two model parameters change, we observe the second order, first order and zeroth order phase transitions from the behavior of the entanglement entropy at some intermediate temperatures. These imply that the entanglement entropy can indicate not only the occurrence of the phase transition, but also the order of the phase transition. The entanglement entropy is indeed a good probe to phase transition. Furthermore, the “retrograde condensation” which is a sub-dominated phase is also reflected on the entanglement entropy.

  4. Using maximum entropy to predict suitable habitat for the endangered dwarf wedgemussel in the Maryland Coastal Plain

    Science.gov (United States)

    Campbell, Cara; Hilderbrand, Robert H.

    2017-01-01

    Species distribution modelling can be useful for the conservation of rare and endangered species. Freshwater mussel declines have thinned species ranges producing spatially fragmented distributions across large areas. Spatial fragmentation in combination with a complex life history and heterogeneous environment makes predictive modelling difficult.A machine learning approach (maximum entropy) was used to model occurrences and suitable habitat for the federally endangered dwarf wedgemussel, Alasmidonta heterodon, in Maryland's Coastal Plain catchments. Landscape-scale predictors (e.g. land cover, land use, soil characteristics, geology, flow characteristics, and climate) were used to predict the suitability of individual stream segments for A. heterodon.The best model contained variables at three scales: minimum elevation (segment scale), percentage Tertiary deposits, low intensity development, and woody wetlands (sub-catchment), and percentage low intensity development, pasture/hay agriculture, and average depth to the water table (catchment). Despite a very small sample size owing to the rarity of A. heterodon, cross-validated prediction accuracy was 91%.Most predicted suitable segments occur in catchments not known to contain A. heterodon, which provides opportunities for new discoveries or population restoration. These model predictions can guide surveys toward the streams with the best chance of containing the species or, alternatively, away from those streams with little chance of containing A. heterodon.Developed reaches had low predicted suitability for A. heterodon in the Coastal Plain. Urban and exurban sprawl continues to modify stream ecosystems in the region, underscoring the need to preserve existing populations and to discover and protect new populations.

  5. A parametrization of two-dimensional turbulence based on a maximum entropy production principle with a local conservation of energy

    International Nuclear Information System (INIS)

    Chavanis, Pierre-Henri

    2014-01-01

    In the context of two-dimensional (2D) turbulence, we apply the maximum entropy production principle (MEPP) by enforcing a local conservation of energy. This leads to an equation for the vorticity distribution that conserves all the Casimirs, the energy, and that increases monotonically the mixing entropy (H-theorem). Furthermore, the equation for the coarse-grained vorticity dissipates monotonically all the generalized enstrophies. These equations may provide a parametrization of 2D turbulence. They do not generally relax towards the maximum entropy state. The vorticity current vanishes for any steady state of the 2D Euler equation. Interestingly, the equation for the coarse-grained vorticity obtained from the MEPP turns out to coincide, after some algebraic manipulations, with the one obtained with the anticipated vorticity method. This shows a connection between these two approaches when the conservation of energy is treated locally. Furthermore, the newly derived equation, which incorporates a diffusion term and a drift term, has a nice physical interpretation in terms of a selective decay principle. This sheds new light on both the MEPP and the anticipated vorticity method. (paper)

  6. Entropy, complexity, and Markov diagrams for random walk cancer models.

    Science.gov (United States)

    Newton, Paul K; Mason, Jeremy; Hurt, Brian; Bethel, Kelly; Bazhenova, Lyudmila; Nieva, Jorge; Kuhn, Peter

    2014-12-19

    The notion of entropy is used to compare the complexity associated with 12 common cancers based on metastatic tumor distribution autopsy data. We characterize power-law distributions, entropy, and Kullback-Liebler divergence associated with each primary cancer as compared with data for all cancer types aggregated. We then correlate entropy values with other measures of complexity associated with Markov chain dynamical systems models of progression. The Markov transition matrix associated with each cancer is associated with a directed graph model where nodes are anatomical locations where a metastatic tumor could develop, and edge weightings are transition probabilities of progression from site to site. The steady-state distribution corresponds to the autopsy data distribution. Entropy correlates well with the overall complexity of the reduced directed graph structure for each cancer and with a measure of systemic interconnectedness of the graph, called graph conductance. The models suggest that grouping cancers according to their entropy values, with skin, breast, kidney, and lung cancers being prototypical high entropy cancers, stomach, uterine, pancreatic and ovarian being mid-level entropy cancers, and colorectal, cervical, bladder, and prostate cancers being prototypical low entropy cancers, provides a potentially useful framework for viewing metastatic cancer in terms of predictability, complexity, and metastatic potential.

  7. THE LICK AGN MONITORING PROJECT: VELOCITY-DELAY MAPS FROM THE MAXIMUM-ENTROPY METHOD FOR Arp 151

    International Nuclear Information System (INIS)

    Bentz, Misty C.; Barth, Aaron J.; Walsh, Jonelle L.; Horne, Keith; Bennert, Vardha Nicola; Treu, Tommaso; Canalizo, Gabriela; Filippenko, Alexei V.; Gates, Elinor L.; Malkan, Matthew A.; Minezaki, Takeo; Woo, Jong-Hak

    2010-01-01

    We present velocity-delay maps for optical H I, He I, and He II recombination lines in Arp 151, recovered by fitting a reverberation model to spectrophotometric monitoring data using the maximum-entropy method. H I response is detected over the range 0-15 days, with the response confined within the virial envelope. The Balmer-line maps have similar morphologies but exhibit radial stratification, with progressively longer delays for Hγ to Hβ to Hα. The He I and He II response is confined within 1-2 days. There is a deficit of prompt response in the Balmer-line cores but strong prompt response in the red wings. Comparison with simple models identifies two classes that reproduce these features: free-falling gas and a half-illuminated disk with a hot spot at small radius on the receding lune. Symmetrically illuminated models with gas orbiting in an inclined disk or an isotropic distribution of randomly inclined circular orbits can reproduce the virial structure but not the observed asymmetry. Radial outflows are also largely ruled out by the observed asymmetry. A warped-disk geometry provides a physically plausible mechanism for the asymmetric illumination and hot spot features. Simple estimates show that a disk in the broad-line region of Arp 151 could be unstable to warping induced by radiation pressure. Our results demonstrate the potential power of detailed modeling combined with monitoring campaigns at higher cadence to characterize the gas kinematics and physical processes that give rise to the broad emission lines in active galactic nuclei.

  8. Analysis of entropy models with equality and inequality constraints

    Energy Technology Data Exchange (ETDEWEB)

    Jefferson, T R; Scott, C H

    1979-06-01

    Entropy models are emerging as valuable tools in the study of various social problems of spatial interaction. With the development of the modeling has come diversity. Increased flexibility in the model can be obtained by allowing certain constraints to be relaxed from equality to inequality. To provide a better understanding of these entropy models they are analyzed by geometric programming. Dual mathematical programs and algorithms are obtained. 7 references.

  9. Maximum Kolmogorov-Sinai Entropy Versus Minimum Mixing Time in Markov Chains

    Science.gov (United States)

    Mihelich, M.; Dubrulle, B.; Paillard, D.; Kral, Q.; Faranda, D.

    2018-01-01

    We establish a link between the maximization of Kolmogorov Sinai entropy (KSE) and the minimization of the mixing time for general Markov chains. Since the maximisation of KSE is analytical and easier to compute in general than mixing time, this link provides a new faster method to approximate the minimum mixing time dynamics. It could be interesting in computer sciences and statistical physics, for computations that use random walks on graphs that can be represented as Markov chains.

  10. Absorption and scattering coefficients estimation in two-dimensional participating media using the generalized maximum entropy and Levenberg-Marquardt methods

    International Nuclear Information System (INIS)

    Berrocal T, Mariella J.; Roberty, Nilson C.; Silva Neto, Antonio J.; Universidade Federal, Rio de Janeiro, RJ

    2002-01-01

    The solution of inverse problems in participating media where there is emission, absorption and dispersion of the radiation possesses several applications in engineering and medicine. The objective of this work is to estimative the coefficients of absorption and dispersion in two-dimensional heterogeneous participating media, using in independent form the Generalized Maximum Entropy and Levenberg Marquardt methods. Both methods are based on the solution of the direct problem that is modeled by the Boltzmann equation in cartesian geometry. Some cases testes are presented. (author)

  11. Studies of the pressure dependence of the charge density distribution in cerium phosphide by the maximum-entropy method

    CERN Document Server

    Ishimatsu, N; Takata, M; Nishibori, E; Sakata, M; Hayashi, J; Shirotani, I; Shimomura, O

    2002-01-01

    The physical properties relating to 4f electrons in cerium phosphide, especially the temperature dependence and the isomorphous transition that occurs at around 10 GPa, were studied by means of x-ray powder diffraction and charge density distribution maps derived by the maximum-entropy method. The compressibility of CeP was exactly determined using a helium pressure medium and the anomaly that indicated the isomorphous transition was observed in the compressibility. We also discuss the anisotropic charge density distribution of Ce ions and its temperature dependence.

  12. Minimum and Maximum Entropy Distributions for Binary Systems with Known Means and Pairwise Correlations

    Science.gov (United States)

    2017-08-21

    number of neurons. Time is discretized and we assume any neuron can spike no more than once in a time bin. We have ν ≤ µ because ν is the probability of a...Comput. Appl. Math . 2000, 121, 331–354. 27. Shalizi, C.; Crutchfield, J. Computational mechanics: Pattern and prediction, structure and simplicity. J...Minimization of a Linearly Constrained Function by Partition of Feasible Domain. Math . Oper. Res. 1983, 8, 215–230. Entropy 2017, 19, 427 33 of 33 54. Candes, E

  13. Maximum entropy algorithm and its implementation for the neutral beam profile measurement

    Energy Technology Data Exchange (ETDEWEB)

    Lee, Seung Wook; Cho, Gyu Seong [Korea Advanced Institute of Science and Technology, Taejon (Korea, Republic of); Cho, Yong Sub [Korea Atomic Energy Research Institute, Taejon (Korea, Republic of)

    1997-12-31

    A tomography algorithm to maximize the entropy of image using Lagrangian multiplier technique and conjugate gradient method has been designed for the measurement of 2D spatial distribution of intense neutral beams of KSTAR NBI (Korea Superconducting Tokamak Advanced Research Neutral Beam Injector), which is now being designed. A possible detection system was assumed and a numerical simulation has been implemented to test the reconstruction quality of given beam profiles. This algorithm has the good applicability for sparse projection data and thus, can be used for the neutral beam tomography. 8 refs., 3 figs. (Author)

  14. Maximum entropy algorithm and its implementation for the neutral beam profile measurement

    Energy Technology Data Exchange (ETDEWEB)

    Lee, Seung Wook; Cho, Gyu Seong [Korea Advanced Institute of Science and Technology, Taejon (Korea, Republic of); Cho, Yong Sub [Korea Atomic Energy Research Institute, Taejon (Korea, Republic of)

    1998-12-31

    A tomography algorithm to maximize the entropy of image using Lagrangian multiplier technique and conjugate gradient method has been designed for the measurement of 2D spatial distribution of intense neutral beams of KSTAR NBI (Korea Superconducting Tokamak Advanced Research Neutral Beam Injector), which is now being designed. A possible detection system was assumed and a numerical simulation has been implemented to test the reconstruction quality of given beam profiles. This algorithm has the good applicability for sparse projection data and thus, can be used for the neutral beam tomography. 8 refs., 3 figs. (Author)

  15. Adaptive Statistical Language Modeling; A Maximum Entropy Approach

    Science.gov (United States)

    1994-04-19

    t= A’S OAKLAND DODGERS BASEBALL CATCHER ATHLETICS INNING GAMES GAME DAVE LEAGUE SERIES TEAM SEASON FRANCISCO BAY SAN PARK BALL RUNS A.’S -= A.’S...by the MI-3g Measure ’EM -- ’EM YOU SEASON GAME GAMES LEAGUE TEAM GUYS I BASEBALL COACH TEAM’S FOOTBALL WON HERE ME SEASONS TEAMS MY CHAMPIONSHIP ’N

  16. Coupling diffusion and maximum entropy models to estimate thermal inertia

    Science.gov (United States)

    Thermal inertia is a physical property of soil at the land surface related to water content. We have developed a method for estimating soil thermal inertia using two daily measurements of surface temperature, to capture the diurnal range, and diurnal time series of net radiation and specific humidi...

  17. Entropy in the Tangled Nature Model of Evolution

    Directory of Open Access Journals (Sweden)

    Ty N. F. Roach

    2017-04-01

    Full Text Available Applications of entropy principles to evolution and ecology are of tantamount importance given the central role spatiotemporal structuring plays in both evolution and ecological succession. We obtain here a qualitative interpretation of the role of entropy in evolving ecological systems. Our interpretation is supported by mathematical arguments using simulation data generated by the Tangled Nature Model (TNM, a stochastic model of evolving ecologies. We define two types of configurational entropy and study their empirical time dependence obtained from the data. Both entropy measures increase logarithmically with time, while the entropy per individual decreases in time, in parallel with the growth of emergent structures visible from other aspects of the simulation. We discuss the biological relevance of these entropies to describe niche space and functional space of ecosystems, as well as their use in characterizing the number of taxonomic configurations compatible with different niche partitioning and functionality. The TNM serves as an illustrative example of how to calculate and interpret these entropies, which are, however, also relevant to real ecosystems, where they can be used to calculate the number of functional and taxonomic configurations that an ecosystem can realize.

  18. Entropies from Markov Models as Complexity Measures of Embedded Attractors

    Directory of Open Access Journals (Sweden)

    Julián D. Arias-Londoño

    2015-06-01

    Full Text Available This paper addresses the problem of measuring complexity from embedded attractors as a way to characterize changes in the dynamical behavior of different types of systems with a quasi-periodic behavior by observing their outputs. With the aim of measuring the stability of the trajectories of the attractor along time, this paper proposes three new estimations of entropy that are derived from a Markov model of the embedded attractor. The proposed estimators are compared with traditional nonparametric entropy measures, such as approximate entropy, sample entropy and fuzzy entropy, which only take into account the spatial dimension of the trajectory. The method proposes the use of an unsupervised algorithm to find the principal curve, which is considered as the “profile trajectory”, that will serve to adjust the Markov model. The new entropy measures are evaluated using three synthetic experiments and three datasets of physiological signals. In terms of consistency and discrimination capabilities, the results show that the proposed measures perform better than the other entropy measures used for comparison purposes.

  19. Generalized entropy formalism and a new holographic dark energy model

    Science.gov (United States)

    Sayahian Jahromi, A.; Moosavi, S. A.; Moradpour, H.; Morais Graça, J. P.; Lobo, I. P.; Salako, I. G.; Jawad, A.

    2018-05-01

    Recently, the Rényi and Tsallis generalized entropies have extensively been used in order to study various cosmological and gravitational setups. Here, using a special type of generalized entropy, a generalization of both the Rényi and Tsallis entropy, together with holographic principle, we build a new model for holographic dark energy. Thereinafter, considering a flat FRW universe, filled by a pressureless component and the new obtained dark energy model, the evolution of cosmos has been investigated showing satisfactory results and behavior. In our model, the Hubble horizon plays the role of IR cutoff, and there is no mutual interaction between the cosmos components. Our results indicate that the generalized entropy formalism may open a new window to become more familiar with the nature of spacetime and its properties.

  20. Suggestion of a Management Model: Total Entropy Management

    OpenAIRE

    Goksel Alpan,; Ismail Efil

    2011-01-01

    “Entropy” can be defined as the measure of disorder, uncertainty and consumed energy in a system or in the Universe. In the study, entropy concept is used as metaphor and it is aimed to construct the conceptual basis of a new management model which can be utilized to manage all entropy sources effectively. The study is conveyed with a multidisciplinary and holistic approach and by the use of qualitative research techniques. In the study, it is examined the relations of the entropy concept wit...

  1. Entropy model of dissipative structure on corporate social responsibility

    Science.gov (United States)

    Li, Zuozhi; Jiang, Jie

    2017-06-01

    Enterprise is prompted to fulfill the social responsibility requirement by the internal and external environment. In this complex system, some studies suggest that firms have an orderly or chaotic entropy exchange behavior. Based on the theory of dissipative structure, this paper constructs the entropy index system of corporate social responsibility(CSR) and explores the dissipative structure of CSR through Brusselator model criterion. Picking up listed companies of the equipment manufacturing, the research shows that CSR has positive incentive to negative entropy and promotes the stability of dissipative structure. In short, the dissipative structure of CSR has a positive impact on the interests of stakeholders and corporate social images.

  2. The inverse Fourier problem in the case of poor resolution in one given direction: the maximum-entropy solution

    International Nuclear Information System (INIS)

    Papoular, R.J.; Zheludev, A.; Ressouche, E.; Schweizer, J.

    1995-01-01

    When density distributions in crystals are reconstructed from 3D diffraction data, a problem sometimes occurs when the spatial resolution in one given direction is very small compared to that in perpendicular directions. In this case, a 2D projected density is usually reconstructed. For this task, the conventional Fourier inversion method only makes use of those structure factors measured in the projection plane. All the other structure factors contribute zero to the reconstruction of a projected density. On the contrary, the maximum-entropy method uses all the 3D data, to yield 3D-enhanced 2D projected density maps. It is even possible to reconstruct a projection in the extreme case when not one structure factor in the plane of projection is known. In the case of poor resolution along one given direction, a Fourier inversion reconstruction gives very low quality 3D densities 'smeared' in the third dimension. The application of the maximum-entropy procedure reduces the smearing significantly and reasonably well resolved projections along most directions can now be obtained from the MaxEnt 3D density. To illustrate these two ideas, particular examples based on real polarized neutron diffraction data sets are presented. (orig.)

  3. Developing the fuzzy c-means clustering algorithm based on maximum entropy for multitarget tracking in a cluttered environment

    Science.gov (United States)

    Chen, Xiao; Li, Yaan; Yu, Jing; Li, Yuxing

    2018-01-01

    For fast and more effective implementation of tracking multiple targets in a cluttered environment, we propose a multiple targets tracking (MTT) algorithm called maximum entropy fuzzy c-means clustering joint probabilistic data association that combines fuzzy c-means clustering and the joint probabilistic data association (PDA) algorithm. The algorithm uses the membership value to express the probability of the target originating from measurement. The membership value is obtained through fuzzy c-means clustering objective function optimized by the maximum entropy principle. When considering the effect of the public measurement, we use a correction factor to adjust the association probability matrix to estimate the state of the target. As this algorithm avoids confirmation matrix splitting, it can solve the high computational load problem of the joint PDA algorithm. The results of simulations and analysis conducted for tracking neighbor parallel targets and cross targets in a different density cluttered environment show that the proposed algorithm can realize MTT quickly and efficiently in a cluttered environment. Further, the performance of the proposed algorithm remains constant with increasing process noise variance. The proposed algorithm has the advantages of efficiency and low computational load, which can ensure optimum performance when tracking multiple targets in a dense cluttered environment.

  4. The determination of nuclear charge distributions using a Bayesian maximum entropy method

    International Nuclear Information System (INIS)

    Macaulay, V.A.; Buck, B.

    1995-01-01

    We treat the inference of nuclear charge densities from measurements of elastic electron scattering cross sections. In order to get the most reliable information from expensively acquired, incomplete and noisy measurements, we use Bayesian probability theory. Very little prior information about the charge densities is assumed. We derive a prior probability distribution which is a generalization of a form used widely in image restoration based on the entropy of a physical density. From the posterior distribution of possible densities, we select the most probable one, and show how error bars can be evaluated. These have very reasonable properties, such as increasing without bound as hypotheses about finer scale structures are included in the hypothesis space. The methods are demonstrated by using data on the nuclei 4 He and 12 C. (orig.)

  5. Irreversible entropy model for damage diagnosis in resistors

    Energy Technology Data Exchange (ETDEWEB)

    Cuadras, Angel, E-mail: angel.cuadras@upc.edu; Crisóstomo, Javier; Ovejas, Victoria J.; Quilez, Marcos [Instrumentation, Sensor and Interfaces Group, Electronic Engineering Department, Escola d' Enginyeria de Telecomunicació i Aeronàutica de Castelldefels EETAC, Universitat Politècnica de Catalunya, Barcelona Tech (UPC), Castelldefels-Barcelona (Spain)

    2015-10-28

    We propose a method to characterize electrical resistor damage based on entropy measurements. Irreversible entropy and the rate at which it is generated are more convenient parameters than resistance for describing damage because they are essentially positive in virtue of the second law of thermodynamics, whereas resistance may increase or decrease depending on the degradation mechanism. Commercial resistors were tested in order to characterize the damage induced by power surges. Resistors were biased with constant and pulsed voltage signals, leading to power dissipation in the range of 4–8 W, which is well above the 0.25 W nominal power to initiate failure. Entropy was inferred from the added power and temperature evolution. A model is proposed to understand the relationship among resistance, entropy, and damage. The power surge dissipates into heat (Joule effect) and damages the resistor. The results show a correlation between entropy generation rate and resistor failure. We conclude that damage can be conveniently assessed from irreversible entropy generation. Our results for resistors can be easily extrapolated to other systems or machines that can be modeled based on their resistance.

  6. Irreversible entropy model for damage diagnosis in resistors

    International Nuclear Information System (INIS)

    Cuadras, Angel; Crisóstomo, Javier; Ovejas, Victoria J.; Quilez, Marcos

    2015-01-01

    We propose a method to characterize electrical resistor damage based on entropy measurements. Irreversible entropy and the rate at which it is generated are more convenient parameters than resistance for describing damage because they are essentially positive in virtue of the second law of thermodynamics, whereas resistance may increase or decrease depending on the degradation mechanism. Commercial resistors were tested in order to characterize the damage induced by power surges. Resistors were biased with constant and pulsed voltage signals, leading to power dissipation in the range of 4–8 W, which is well above the 0.25 W nominal power to initiate failure. Entropy was inferred from the added power and temperature evolution. A model is proposed to understand the relationship among resistance, entropy, and damage. The power surge dissipates into heat (Joule effect) and damages the resistor. The results show a correlation between entropy generation rate and resistor failure. We conclude that damage can be conveniently assessed from irreversible entropy generation. Our results for resistors can be easily extrapolated to other systems or machines that can be modeled based on their resistance

  7. Field space entanglement entropy, zero modes and Lifshitz models

    Science.gov (United States)

    Huffel, Helmuth; Kelnhofer, Gerald

    2017-12-01

    The field space entanglement entropy of a quantum field theory is obtained by integrating out a subset of its fields. We study an interacting quantum field theory consisting of massless scalar fields on a closed compact manifold M. To this model we associate its Lifshitz dual model. The ground states of both models are invariant under constant shifts. We interpret this invariance as gauge symmetry and subject the models to proper gauge fixing. By applying the heat kernel regularization one can show that the field space entanglement entropies of the massless scalar field model and of its Lifshitz dual are agreeing.

  8. Field space entanglement entropy, zero modes and Lifshitz models

    Directory of Open Access Journals (Sweden)

    Helmuth Huffel

    2017-12-01

    Full Text Available The field space entanglement entropy of a quantum field theory is obtained by integrating out a subset of its fields. We study an interacting quantum field theory consisting of massless scalar fields on a closed compact manifold M. To this model we associate its Lifshitz dual model. The ground states of both models are invariant under constant shifts. We interpret this invariance as gauge symmetry and subject the models to proper gauge fixing. By applying the heat kernel regularization one can show that the field space entanglement entropies of the massless scalar field model and of its Lifshitz dual are agreeing.

  9. Identification of a Threshold Value for the DEMATEL Method: Using the Maximum Mean De-Entropy Algorithm

    Science.gov (United States)

    Chung-Wei, Li; Gwo-Hshiung, Tzeng

    To deal with complex problems, structuring them through graphical representations and analyzing causal influences can aid in illuminating complex issues, systems, or concepts. The DEMATEL method is a methodology which can be used for researching and solving complicated and intertwined problem groups. The end product of the DEMATEL process is a visual representation—the impact-relations map—by which respondents organize their own actions in the world. The applicability of the DEMATEL method is widespread, ranging from analyzing world problematique decision making to industrial planning. The most important property of the DEMATEL method used in the multi-criteria decision making (MCDM) field is to construct interrelations between criteria. In order to obtain a suitable impact-relations map, an appropriate threshold value is needed to obtain adequate information for further analysis and decision-making. In this paper, we propose a method based on the entropy approach, the maximum mean de-entropy algorithm, to achieve this purpose. Using real cases to find the interrelationships between the criteria for evaluating effects in E-learning programs as an examples, we will compare the results obtained from the respondents and from our method, and discuss that the different impact-relations maps from these two methods.

  10. Spectral shaping of a randomized PWM DC-DC converter using maximum entropy probability distributions

    CSIR Research Space (South Africa)

    Dove, Albert

    2017-01-01

    Full Text Available maintaining constraints in a DC-DC converter is investigated. A probability distribution whose aim is to ensure maximal harmonic spreading and yet mainaint constraints is presented. The PDFs are determined from a direct application of the method of Maximum...

  11. Electronic structure of beta-FeSi sub 2 obtained by maximum entropy method and photoemission spectroscopy

    CERN Document Server

    Kakemoto, H; Makita, Y; Kino, Y; Tsukamoto, T; Shin, S; Wada, S; Tsurumi, T

    2003-01-01

    The electronic structure of beta-FeSi sub 2 was investigated by maximum entropy method (MEM) and photoemission spectroscopy. The electronic structure obtained by MEM using X-ray diffraction data at room temperature (RT) showed covalent bonds of Fe-Si and Si-Si electrons. The photoemission spectra of beta-FeSi sub 2 at RT were changed by incidence photon energies. For photon energies between 50 and 100 eV, resonant photoemission spectra caused by a super Coster-Kronig transition were observed. In order to reduce resonant effect about Fe(3d) for obtained photoemission spectra, difference spectrum between 53 and 57 eV was calculated, and it was compared with ab-initio band calculation and spectra function.

  12. Efficient reliability analysis of structures with the rotational quasi-symmetric point- and the maximum entropy methods

    Science.gov (United States)

    Xu, Jun; Dang, Chao; Kong, Fan

    2017-10-01

    This paper presents a new method for efficient structural reliability analysis. In this method, a rotational quasi-symmetric point method (RQ-SPM) is proposed for evaluating the fractional moments of the performance function. Then, the derivation of the performance function's probability density function (PDF) is carried out based on the maximum entropy method in which constraints are specified in terms of fractional moments. In this regard, the probability of failure can be obtained by a simple integral over the performance function's PDF. Six examples, including a finite element-based reliability analysis and a dynamic system with strong nonlinearity, are used to illustrate the efficacy of the proposed method. All the computed results are compared with those by Monte Carlo simulation (MCS). It is found that the proposed method can provide very accurate results with low computational effort.

  13. A brief critique of the Adam-Gibbs entropy model

    DEFF Research Database (Denmark)

    Dyre, J. C.; Hecksher, Tina; Niss, Kristine

    2009-01-01

    This paper critically discusses the entropy model proposed by Adam and Gibbs in 1965 for the dramatic temperature dependence of glass-forming liquids' average relaxation time, which is one of the most influential models during the last four decades. We discuss the Adam-Gibbs model's theoretical...

  14. Entropy in the classical and quantum polymer black hole models

    International Nuclear Information System (INIS)

    Livine, Etera R; Terno, Daniel R

    2012-01-01

    We investigate the entropy counting for black hole horizons in loop quantum gravity (LQG). We argue that the space of 3D closed polyhedra is the classical counterpart of the space of SU(2) intertwiners at the quantum level. Then computing the entropy for the boundary horizon amounts to calculating the density of polyhedra or the number of intertwiners at fixed total area. Following the previous work (Bianchi 2011 Class. Quantum Grav. 28 114006) we dub these the classical and quantum polymer models for isolated horizons in LQG. We provide exact micro-canonical calculations for both models and we show that the classical counting of polyhedra accounts for most of the features of the intertwiner counting (leading order entropy and log-correction), thus providing us with a simpler model to further investigate correlations and dynamics. To illustrate this, we also produce an exact formula for the dimension of the intertwiner space as a density of ‘almost-closed polyhedra’. (paper)

  15. A Trustworthiness Evaluation Method for Software Architectures Based on the Principle of Maximum Entropy (POME and the Grey Decision-Making Method (GDMM

    Directory of Open Access Journals (Sweden)

    Rong Jiang

    2014-09-01

    Full Text Available As the early design decision-making structure, a software architecture plays a key role in the final software product quality and the whole project. In the software design and development process, an effective evaluation of the trustworthiness of a software architecture can help making scientific and reasonable decisions on the architecture, which are necessary for the construction of highly trustworthy software. In consideration of lacking the trustworthiness evaluation and measurement studies for software architecture, this paper provides one trustworthy attribute model of software architecture. Based on this model, the paper proposes to use the Principle of Maximum Entropy (POME and Grey Decision-making Method (GDMM as the trustworthiness evaluation method of a software architecture and proves the scientificity and rationality of this method, as well as verifies the feasibility through case analysis.

  16. Entropy exchange and entanglement in the Jaynes-Cummings model

    International Nuclear Information System (INIS)

    Boukobza, E.; Tannor, D.J.

    2005-01-01

    The Jaynes-Cummings model (JCM) is the simplest fully quantum model that describes the interaction between light and matter. We extend a previous analysis by Phoenix and Knight [Ann. Phys. 186, 381 (1988)] of the JCM by considering mixed states of both the light and matter. We present examples of qualitatively different entropic correlations. In particular, we explore the regime of entropy exchange between light and matter, i.e., where the rate of change of the two are anticorrelated. This behavior contrasts with the case of pure light-matter states in which the rate of change of the two entropies are positively correlated and in fact identical. We give an analytical derivation of the anticorrelation phenomenon and discuss the regime of its validity. Finally, we show a strong correlation between the region of the Bloch sphere characterized by entropy exchange and that characterized by minimal entanglement as measured by the negative eigenvalues of the partially transposed density matrix

  17. A Dynamic Model of Information and Entropy

    Directory of Open Access Journals (Sweden)

    Stuart D. Walker

    2010-01-01

    Full Text Available We discuss the possibility of a relativistic relationship between information and entropy, closely analogous to the classical Maxwell electro-magnetic wave equations. Inherent to the analysis is the description of information as residing in points of non-analyticity; yet ultimately also exhibiting a distributed characteristic: additionally analogous, therefore, to the wave-particle duality of light. At cosmological scales our vector differential equations predict conservation of information in black holes, whereas regular- and Z-DNA molecules correspond to helical solutions at microscopic levels. We further propose that regular- and Z-DNA are equivalent to the alternative words chosen from an alphabet to maintain the equilibrium of an information transmission system.

  18. Improved Maximum Parsimony Models for Phylogenetic Networks.

    Science.gov (United States)

    Van Iersel, Leo; Jones, Mark; Scornavacca, Celine

    2018-05-01

    Phylogenetic networks are well suited to represent evolutionary histories comprising reticulate evolution. Several methods aiming at reconstructing explicit phylogenetic networks have been developed in the last two decades. In this article, we propose a new definition of maximum parsimony for phylogenetic networks that permits to model biological scenarios that cannot be modeled by the definitions currently present in the literature (namely, the "hardwired" and "softwired" parsimony). Building on this new definition, we provide several algorithmic results that lay the foundations for new parsimony-based methods for phylogenetic network reconstruction.

  19. Classic maximum entropy recovery of the average joint distribution of apparent FRET efficiency and fluorescence photons for single-molecule burst measurements.

    Science.gov (United States)

    DeVore, Matthew S; Gull, Stephen F; Johnson, Carey K

    2012-04-05

    We describe a method for analysis of single-molecule Förster resonance energy transfer (FRET) burst measurements using classic maximum entropy. Classic maximum entropy determines the Bayesian inference for the joint probability describing the total fluorescence photons and the apparent FRET efficiency. The method was tested with simulated data and then with DNA labeled with fluorescent dyes. The most probable joint distribution can be marginalized to obtain both the overall distribution of fluorescence photons and the apparent FRET efficiency distribution. This method proves to be ideal for determining the distance distribution of FRET-labeled biomolecules, and it successfully predicts the shape of the recovered distributions.

  20. Bias-based modeling and entropy analysis of PUFs

    NARCIS (Netherlands)

    van den Berg, R.; Skoric, B.; Leest, van der V.

    2013-01-01

    Physical Unclonable Functions (PUFs) are increasingly becoming a well-known security primitive for secure key storage and anti-counterfeiting. For both applications it is imperative that PUFs provide enough entropy. The aim of this paper is to propose a new model for binary-output PUFs such as SRAM,

  1. Modelling maximum likelihood estimation of availability

    International Nuclear Information System (INIS)

    Waller, R.A.; Tietjen, G.L.; Rock, G.W.

    1975-01-01

    Suppose the performance of a nuclear powered electrical generating power plant is continuously monitored to record the sequence of failure and repairs during sustained operation. The purpose of this study is to assess one method of estimating the performance of the power plant when the measure of performance is availability. That is, we determine the probability that the plant is operational at time t. To study the availability of a power plant, we first assume statistical models for the variables, X and Y, which denote the time-to-failure and the time-to-repair variables, respectively. Once those statistical models are specified, the availability, A(t), can be expressed as a function of some or all of their parameters. Usually those parameters are unknown in practice and so A(t) is unknown. This paper discusses the maximum likelihood estimator of A(t) when the time-to-failure model for X is an exponential density with parameter, lambda, and the time-to-repair model for Y is an exponential density with parameter, theta. Under the assumption of exponential models for X and Y, it follows that the instantaneous availability at time t is A(t)=lambda/(lambda+theta)+theta/(lambda+theta)exp[-[(1/lambda)+(1/theta)]t] with t>0. Also, the steady-state availability is A(infinity)=lambda/(lambda+theta). We use the observations from n failure-repair cycles of the power plant, say X 1 , X 2 , ..., Xsub(n), Y 1 , Y 2 , ..., Ysub(n) to present the maximum likelihood estimators of A(t) and A(infinity). The exact sampling distributions for those estimators and some statistical properties are discussed before a simulation model is used to determine 95% simulation intervals for A(t). The methodology is applied to two examples which approximate the operating history of two nuclear power plants. (author)

  2. BRISENT: An Entropy-Based Model for Bridge-Pier Scour Estimation under Complex Hydraulic Scenarios

    Directory of Open Access Journals (Sweden)

    Alonso Pizarro

    2017-11-01

    Full Text Available The goal of this paper is to introduce the first clear-water scour model based on both the informational entropy concept and the principle of maximum entropy, showing that a variational approach is ideal for describing erosional processes under complex situations. The proposed bridge–pier scour entropic (BRISENT model is capable of reproducing the main dynamics of scour depth evolution under steady hydraulic conditions, step-wise hydrographs, and flood waves. For the calibration process, 266 clear-water scour experiments from 20 precedent studies were considered, where the dimensionless parameters varied widely. Simple formulations are proposed to estimate BRISENT’s fitting coefficients, in which the ratio between pier-diameter and sediment-size was the most critical physical characteristic controlling scour model parametrization. A validation process considering highly unsteady and multi-peaked hydrographs was carried out, showing that the proposed BRISENT model reproduces scour evolution with high accuracy.

  3. Application of SNODAS and hydrologic models to enhance entropy-based snow monitoring network design

    Science.gov (United States)

    Keum, Jongho; Coulibaly, Paulin; Razavi, Tara; Tapsoba, Dominique; Gobena, Adam; Weber, Frank; Pietroniro, Alain

    2018-06-01

    Snow has a unique characteristic in the water cycle, that is, snow falls during the entire winter season, but the discharge from snowmelt is typically delayed until the melting period and occurs in a relatively short period. Therefore, reliable observations from an optimal snow monitoring network are necessary for an efficient management of snowmelt water for flood prevention and hydropower generation. The Dual Entropy and Multiobjective Optimization is applied to design snow monitoring networks in La Grande River Basin in Québec and Columbia River Basin in British Columbia. While the networks are optimized to have the maximum amount of information with minimum redundancy based on entropy concepts, this study extends the traditional entropy applications to the hydrometric network design by introducing several improvements. First, several data quantization cases and their effects on the snow network design problems were explored. Second, the applicability the Snow Data Assimilation System (SNODAS) products as synthetic datasets of potential stations was demonstrated in the design of the snow monitoring network of the Columbia River Basin. Third, beyond finding the Pareto-optimal networks from the entropy with multi-objective optimization, the networks obtained for La Grande River Basin were further evaluated by applying three hydrologic models. The calibrated hydrologic models simulated discharges using the updated snow water equivalent data from the Pareto-optimal networks. Then, the model performances for high flows were compared to determine the best optimal network for enhanced spring runoff forecasting.

  4. n-Order and maximum fuzzy similarity entropy for discrimination of signals of different complexity: Application to fetal heart rate signals.

    Science.gov (United States)

    Zaylaa, Amira; Oudjemia, Souad; Charara, Jamal; Girault, Jean-Marc

    2015-09-01

    This paper presents two new concepts for discrimination of signals of different complexity. The first focused initially on solving the problem of setting entropy descriptors by varying the pattern size instead of the tolerance. This led to the search for the optimal pattern size that maximized the similarity entropy. The second paradigm was based on the n-order similarity entropy that encompasses the 1-order similarity entropy. To improve the statistical stability, n-order fuzzy similarity entropy was proposed. Fractional Brownian motion was simulated to validate the different methods proposed, and fetal heart rate signals were used to discriminate normal from abnormal fetuses. In all cases, it was found that it was possible to discriminate time series of different complexity such as fractional Brownian motion and fetal heart rate signals. The best levels of performance in terms of sensitivity (90%) and specificity (90%) were obtained with the n-order fuzzy similarity entropy. However, it was shown that the optimal pattern size and the maximum similarity measurement were related to intrinsic features of the time series. Copyright © 2015 Elsevier Ltd. All rights reserved.

  5. Mixture models with entropy regularization for community detection in networks

    Science.gov (United States)

    Chang, Zhenhai; Yin, Xianjun; Jia, Caiyan; Wang, Xiaoyang

    2018-04-01

    Community detection is a key exploratory tool in network analysis and has received much attention in recent years. NMM (Newman's mixture model) is one of the best models for exploring a range of network structures including community structure, bipartite and core-periphery structures, etc. However, NMM needs to know the number of communities in advance. Therefore, in this study, we have proposed an entropy regularized mixture model (called EMM), which is capable of inferring the number of communities and identifying network structure contained in a network, simultaneously. In the model, by minimizing the entropy of mixing coefficients of NMM using EM (expectation-maximization) solution, the small clusters contained little information can be discarded step by step. The empirical study on both synthetic networks and real networks has shown that the proposed model EMM is superior to the state-of-the-art methods.

  6. Spatiotemporal analysis and mapping of oral cancer risk in changhua county (taiwan): an application of generalized bayesian maximum entropy method.

    Science.gov (United States)

    Yu, Hwa-Lung; Chiang, Chi-Ting; Lin, Shu-De; Chang, Tsun-Kuo

    2010-02-01

    Incidence rate of oral cancer in Changhua County is the highest among the 23 counties of Taiwan during 2001. However, in health data analysis, crude or adjusted incidence rates of a rare event (e.g., cancer) for small populations often exhibit high variances and are, thus, less reliable. We proposed a generalized Bayesian Maximum Entropy (GBME) analysis of spatiotemporal disease mapping under conditions of considerable data uncertainty. GBME was used to study the oral cancer population incidence in Changhua County (Taiwan). Methodologically, GBME is based on an epistematics principles framework and generates spatiotemporal estimates of oral cancer incidence rates. In a way, it accounts for the multi-sourced uncertainty of rates, including small population effects, and the composite space-time dependence of rare events in terms of an extended Poisson-based semivariogram. The results showed that GBME analysis alleviates the noises of oral cancer data from population size effect. Comparing to the raw incidence data, the maps of GBME-estimated results can identify high risk oral cancer regions in Changhua County, where the prevalence of betel quid chewing and cigarette smoking is relatively higher than the rest of the areas. GBME method is a valuable tool for spatiotemporal disease mapping under conditions of uncertainty. 2010 Elsevier Inc. All rights reserved.

  7. Precipitation Interpolation by Multivariate Bayesian Maximum Entropy Based on Meteorological Data in Yun- Gui-Guang region, Mainland China

    Science.gov (United States)

    Wang, Chaolin; Zhong, Shaobo; Zhang, Fushen; Huang, Quanyi

    2016-11-01

    Precipitation interpolation has been a hot area of research for many years. It had close relation to meteorological factors. In this paper, precipitation from 91 meteorological stations located in and around Yunnan, Guizhou and Guangxi Zhuang provinces (or autonomous region), Mainland China was taken into consideration for spatial interpolation. Multivariate Bayesian maximum entropy (BME) method with auxiliary variables, including mean relative humidity, water vapour pressure, mean temperature, mean wind speed and terrain elevation, was used to get more accurate regional distribution of annual precipitation. The means, standard deviations, skewness and kurtosis of meteorological factors were calculated. Variogram and cross- variogram were fitted between precipitation and auxiliary variables. The results showed that the multivariate BME method was precise with hard and soft data, probability density function. Annual mean precipitation was positively correlated with mean relative humidity, mean water vapour pressure, mean temperature and mean wind speed, negatively correlated with terrain elevation. The results are supposed to provide substantial reference for research of drought and waterlog in the region.

  8. Maximum entropy state of the quasi-geostrophic bi-disperse point vortex system: bifurcation phenomena under periodic boundary conditions

    Energy Technology Data Exchange (ETDEWEB)

    Funakoshi, Satoshi; Sato, Tomoyoshi; Miyazaki, Takeshi, E-mail: funakosi@miyazaki.mce.uec.ac.jp, E-mail: miyazaki@mce.uec.ac.jp [Department of Mechanical Engineering and Intelligent Systems, University of Electro-Communications, 1-5-1, Chofugaoka, Chofu, Tokyo 182-8585 (Japan)

    2012-06-01

    We investigate the statistical mechanics of quasi-geostrophic point vortices of mixed sign (bi-disperse system) numerically and theoretically. Direct numerical simulations under periodic boundary conditions are performed using a fast special-purpose computer for molecular dynamics (GRAPE-DR). Clustering of point vortices of like sign is observed and two-dimensional (2D) equilibrium states are formed. It is shown that they are the solutions of the 2D mean-field equation, i.e. the sinh-Poisson equation. The sinh-Poisson equation is generalized to study the 3D nature of the equilibrium states, and a new mean-field equation with the 3D Laplace operator is derived based on the maximum entropy theory. 3D solutions are obtained at very low energy level. These solution branches, however, cannot be traced up to the higher energy level at which the direct numerical simulations are performed, and transitions to 2D solution branches take place when the energy is increased. (paper)

  9. Recognition of Wheat Spike from Field Based Phenotype Platform Using Multi-Sensor Fusion and Improved Maximum Entropy Segmentation Algorithms

    Directory of Open Access Journals (Sweden)

    Chengquan Zhou

    2018-02-01

    Full Text Available To obtain an accurate count of wheat spikes, which is crucial for estimating yield, this paper proposes a new algorithm that uses computer vision to achieve this goal from an image. First, a home-built semi-autonomous multi-sensor field-based phenotype platform (FPP is used to obtain orthographic images of wheat plots at the filling stage. The data acquisition system of the FPP provides high-definition RGB images and multispectral images of the corresponding quadrats. Then, the high-definition panchromatic images are obtained by fusion of three channels of RGB. The Gram–Schmidt fusion algorithm is then used to fuse these multispectral and panchromatic images, thereby improving the color identification degree of the targets. Next, the maximum entropy segmentation method is used to do the coarse-segmentation. The threshold of this method is determined by a firefly algorithm based on chaos theory (FACT, and then a morphological filter is used to de-noise the coarse-segmentation results. Finally, morphological reconstruction theory is applied to segment the adhesive part of the de-noised image and realize the fine-segmentation of the image. The computer-generated counting results for the wheat plots, using independent regional statistical function in Matlab R2017b software, are then compared with field measurements which indicate that the proposed method provides a more accurate count of wheat spikes when compared with other traditional fusion and segmentation methods mentioned in this paper.

  10. Identification of Random Dynamic Force Using an Improved Maximum Entropy Regularization Combined with a Novel Conjugate Gradient

    Directory of Open Access Journals (Sweden)

    ChunPing Ren

    2017-01-01

    Full Text Available We propose a novel mathematical algorithm to offer a solution for the inverse random dynamic force identification in practical engineering. Dealing with the random dynamic force identification problem using the proposed algorithm, an improved maximum entropy (IME regularization technique is transformed into an unconstrained optimization problem, and a novel conjugate gradient (NCG method was applied to solve the objective function, which was abbreviated as IME-NCG algorithm. The result of IME-NCG algorithm is compared with that of ME, ME-CG, ME-NCG, and IME-CG algorithm; it is found that IME-NCG algorithm is available for identifying the random dynamic force due to smaller root mean-square-error (RMSE, lower restoration time, and fewer iterative steps. Example of engineering application shows that L-curve method is introduced which is better than Generalized Cross Validation (GCV method and is applied to select regularization parameter; thus the proposed algorithm can be helpful to alleviate the ill-conditioned problem in identification of dynamic force and to acquire an optimal solution of inverse problem in practical engineering.

  11. Nonadditive entropy maximization is inconsistent with Bayesian updating

    Science.gov (United States)

    Pressé, Steve

    2014-11-01

    The maximum entropy method—used to infer probabilistic models from data—is a special case of Bayes's model inference prescription which, in turn, is grounded in basic propositional logic. By contrast to the maximum entropy method, the compatibility of nonadditive entropy maximization with Bayes's model inference prescription has never been established. Here we demonstrate that nonadditive entropy maximization is incompatible with Bayesian updating and discuss the immediate implications of this finding. We focus our attention on special cases as illustrations.

  12. Inflation via logarithmic entropy-corrected holographic dark energy model

    Energy Technology Data Exchange (ETDEWEB)

    Darabi, F.; Felegary, F. [Azarbaijan Shahid Madani University, Department of Physics, Tabriz (Iran, Islamic Republic of); Setare, M.R. [University of Kurdistan, Department of Science, Bijar (Iran, Islamic Republic of)

    2016-12-15

    We study the inflation in terms of the logarithmic entropy-corrected holographic dark energy (LECHDE) model with future event horizon, particle horizon, and Hubble horizon cut-offs, and we compare the results with those obtained in the study of inflation by the holographic dark energy HDE model. In comparison, the spectrum of primordial scalar power spectrum in the LECHDE model becomes redder than the spectrum in the HDE model. Moreover, the consistency with the observational data in the LECHDE model of inflation constrains the reheating temperature and Hubble parameter by one parameter of holographic dark energy and two new parameters of logarithmic corrections. (orig.)

  13. Inflation via logarithmic entropy-corrected holographic dark energy model

    International Nuclear Information System (INIS)

    Darabi, F.; Felegary, F.; Setare, M.R.

    2016-01-01

    We study the inflation in terms of the logarithmic entropy-corrected holographic dark energy (LECHDE) model with future event horizon, particle horizon, and Hubble horizon cut-offs, and we compare the results with those obtained in the study of inflation by the holographic dark energy HDE model. In comparison, the spectrum of primordial scalar power spectrum in the LECHDE model becomes redder than the spectrum in the HDE model. Moreover, the consistency with the observational data in the LECHDE model of inflation constrains the reheating temperature and Hubble parameter by one parameter of holographic dark energy and two new parameters of logarithmic corrections. (orig.)

  14. Entropy Parameter M in Modeling a Flow Duration Curve

    Directory of Open Access Journals (Sweden)

    Yu Zhang

    2017-12-01

    Full Text Available A flow duration curve (FDC is widely used for predicting water supply, hydropower, environmental flow, sediment load, and pollutant load. Among different methods of constructing an FDC, the entropy-based method, developed recently, is appealing because of its several desirable characteristics, such as simplicity, flexibility, and statistical basis. This method contains a parameter, called entropy parameter M, which constitutes the basis for constructing the FDC. Since M is related to the ratio of the average streamflow to the maximum streamflow which, in turn, is related to the drainage area, it may be possible to determine M a priori and construct an FDC for ungauged basins. This paper, therefore, analyzed the characteristics of M in both space and time using streamflow data from 73 gauging stations in the Brazos River basin, Texas, USA. Results showed that the M values were impacted by reservoir operation and possibly climate change. The values were fluctuating, but relatively stable, after the operation of the reservoirs. Parameter M was found to change inversely with the ratio of average streamflow to the maximum streamflow. When there was an extreme event, there occurred a jump in the M value. Further, spatially, M had a larger value if the drainage area was small.

  15. Modelling maximum canopy conductance and transpiration in ...

    African Journals Online (AJOL)

    There is much current interest in predicting the maximum amount of water that can be transpired by Eucalyptus trees. It is possible that industrial waste water may be applied as irrigation water to eucalypts and it is important to predict the maximum transpiration rates of these plantations in an attempt to dispose of this ...

  16. Improving Estimations of Spatial Distribution of Soil Respiration Using the Bayesian Maximum Entropy Algorithm and Soil Temperature as Auxiliary Data.

    Directory of Open Access Journals (Sweden)

    Junguo Hu

    Full Text Available Soil respiration inherently shows strong spatial variability. It is difficult to obtain an accurate characterization of soil respiration with an insufficient number of monitoring points. However, it is expensive and cumbersome to deploy many sensors. To solve this problem, we proposed employing the Bayesian Maximum Entropy (BME algorithm, using soil temperature as auxiliary information, to study the spatial distribution of soil respiration. The BME algorithm used the soft data (auxiliary information effectively to improve the estimation accuracy of the spatiotemporal distribution of soil respiration. Based on the functional relationship between soil temperature and soil respiration, the BME algorithm satisfactorily integrated soil temperature data into said spatial distribution. As a means of comparison, we also applied the Ordinary Kriging (OK and Co-Kriging (Co-OK methods. The results indicated that the root mean squared errors (RMSEs and absolute values of bias for both Day 1 and Day 2 were the lowest for the BME method, thus demonstrating its higher estimation accuracy. Further, we compared the performance of the BME algorithm coupled with auxiliary information, namely soil temperature data, and the OK method without auxiliary information in the same study area for 9, 21, and 37 sampled points. The results showed that the RMSEs for the BME algorithm (0.972 and 1.193 were less than those for the OK method (1.146 and 1.539 when the number of sampled points was 9 and 37, respectively. This indicates that the former method using auxiliary information could reduce the required number of sampling points for studying spatial distribution of soil respiration. Thus, the BME algorithm, coupled with soil temperature data, can not only improve the accuracy of soil respiration spatial interpolation but can also reduce the number of sampling points.

  17. Improving Estimations of Spatial Distribution of Soil Respiration Using the Bayesian Maximum Entropy Algorithm and Soil Temperature as Auxiliary Data.

    Science.gov (United States)

    Hu, Junguo; Zhou, Jian; Zhou, Guomo; Luo, Yiqi; Xu, Xiaojun; Li, Pingheng; Liang, Junyi

    2016-01-01

    Soil respiration inherently shows strong spatial variability. It is difficult to obtain an accurate characterization of soil respiration with an insufficient number of monitoring points. However, it is expensive and cumbersome to deploy many sensors. To solve this problem, we proposed employing the Bayesian Maximum Entropy (BME) algorithm, using soil temperature as auxiliary information, to study the spatial distribution of soil respiration. The BME algorithm used the soft data (auxiliary information) effectively to improve the estimation accuracy of the spatiotemporal distribution of soil respiration. Based on the functional relationship between soil temperature and soil respiration, the BME algorithm satisfactorily integrated soil temperature data into said spatial distribution. As a means of comparison, we also applied the Ordinary Kriging (OK) and Co-Kriging (Co-OK) methods. The results indicated that the root mean squared errors (RMSEs) and absolute values of bias for both Day 1 and Day 2 were the lowest for the BME method, thus demonstrating its higher estimation accuracy. Further, we compared the performance of the BME algorithm coupled with auxiliary information, namely soil temperature data, and the OK method without auxiliary information in the same study area for 9, 21, and 37 sampled points. The results showed that the RMSEs for the BME algorithm (0.972 and 1.193) were less than those for the OK method (1.146 and 1.539) when the number of sampled points was 9 and 37, respectively. This indicates that the former method using auxiliary information could reduce the required number of sampling points for studying spatial distribution of soil respiration. Thus, the BME algorithm, coupled with soil temperature data, can not only improve the accuracy of soil respiration spatial interpolation but can also reduce the number of sampling points.

  18. Estimation of Land Surface Temperature through Blending MODIS and AMSR-E Data with the Bayesian Maximum Entropy Method

    Directory of Open Access Journals (Sweden)

    Xiaokang Kou

    2016-01-01

    Full Text Available Land surface temperature (LST plays a major role in the study of surface energy balances. Remote sensing techniques provide ways to monitor LST at large scales. However, due to atmospheric influences, significant missing data exist in LST products retrieved from satellite thermal infrared (TIR remotely sensed data. Although passive microwaves (PMWs are able to overcome these atmospheric influences while estimating LST, the data are constrained by low spatial resolution. In this study, to obtain complete and high-quality LST data, the Bayesian Maximum Entropy (BME method was introduced to merge 0.01° and 0.25° LSTs inversed from MODIS and AMSR-E data, respectively. The result showed that the missing LSTs in cloudy pixels were filled completely, and the availability of merged LSTs reaches 100%. Because the depths of LST and soil temperature measurements are different, before validating the merged LST, the station measurements were calibrated with an empirical equation between MODIS LST and 0~5 cm soil temperatures. The results showed that the accuracy of merged LSTs increased with the increasing quantity of utilized data, and as the availability of utilized data increased from 25.2% to 91.4%, the RMSEs of the merged data decreased from 4.53 °C to 2.31 °C. In addition, compared with the filling gap method in which MODIS LST gaps were filled with AMSR-E LST directly, the merged LSTs from the BME method showed better spatial continuity. The different penetration depths of TIR and PMWs may influence fusion performance and still require further studies.

  19. Transport methods: general. 6. A Flux-Limited Diffusion Theory Derived from the Maximum Entropy Eddington Factor

    International Nuclear Information System (INIS)

    Yin, Chukai; Su, Bingjing

    2001-01-01

    The Minerbo's maximum entropy Eddington factor (MEEF) method was proposed as a low-order approximation to transport theory, in which the first two moment equations are closed for the scalar flux f and the current F through a statistically derived nonlinear Eddington factor f. This closure has the ability to handle various degrees of anisotropy of angular flux and is well justified both numerically and theoretically. Thus, a lot of efforts have been made to use this approximation in transport computations, especially in the radiative transfer and astrophysics communities. However, the method suffers numerical instability and may lead to anomalous solutions if the equations are solved by certain commonly used (implicit) mesh schemes. Studies on numerical stability in one-dimensional cases show that the MEEF equations can be solved satisfactorily by an implicit scheme (of treating δΦ/δx) if the angular flux is not too anisotropic so that f 32 , the classic diffusion solution P 1 , the MEEF solution f M obtained by Riemann solvers, and the NFLD solution D M for the two problems, respectively. In Fig. 1, NFLD and MEEF quantitatively predict very close results. However, the NFLD solution is qualitatively better because it is continuous while MEEF predicts unphysical jumps near the middle of the slab. In Fig. 2, the NFLD and MEEF solutions are almost identical, except near the material interface. In summary, the flux-limited diffusion theory derived from the MEEF description is quantitatively as accurate as the MEEF method. However, it is more qualitatively correct and user-friendly than the MEEF method and can be applied efficiently to various steady-state problems. Numerical tests show that this method is widely valid and overall predicts better results than other low-order approximations for various kinds of problems, including eigenvalue problems. Thus, it is an appealing approximate solution technique that is fast computationally and yet is accurate enough for a

  20. Ising model on tangled chain - 1: Free energy and entropy

    International Nuclear Information System (INIS)

    Mejdani, R.

    1993-04-01

    In this paper we have considered an Ising model defined on tangled chain, in which more bonds have been added to those of pure Ising chain. to understand their competition, particularly between ferromagnetic and antiferromagnetic bonds, we have studied, using the transfer matrix method, some simple analytical calculations and an iterative algorithm, the behaviour of the free energy and entropy, particularly in the zero-field and zero temperature limit, for different configurations of the ferromagnetic tangled chain and different types of addition interaction (ferromagnetic or antiferromagnetic). We found that the condition J=J' between the ferromagnetic interaction J along the chain and the antiferromagnetic interaction J' across the chain is somewhat as a ''transition-region'' condition for this behaviour. Our results indicate also the existence of non-zero entropy at zero temperature. (author). 17 refs, 8 figs

  1. Entanglement generation and entropy growth due to intrinsic decoherence in the Jaynes-Cummings model

    International Nuclear Information System (INIS)

    Obada, A.-S.F.; Hessian, Hosny A.

    2004-01-01

    We study how intrinsic decoherence leads to growing entropy and a strong degradation of the maximal generated entanglement in the multiquanta Jaynes-Cummings model. We find an exact solution of the Milburn equation in multiquanta precesses and calculate the partial entropy of the particle (atom or trapped ion) and field subsystem as well as total entropy. As the total entropy is not conserved, and it is shown to increase as time develops, one cannot use the partial field or atomic entropy as a direct measure of particle-field entanglement. For a good entropy measure, we also calculate the negativity of the eigenvalues of the partially transposed density matrix. We find that, at least qualitatively, the difference of the total entropy to the sum of field and atom partial entropies can be also used as an entanglement measure. Our results show that the degree of entanglement is very sensitive to any change in the intrinsic decoherence parameter

  2. Modeling maximum daily temperature using a varying coefficient regression model

    Science.gov (United States)

    Han Li; Xinwei Deng; Dong-Yum Kim; Eric P. Smith

    2014-01-01

    Relationships between stream water and air temperatures are often modeled using linear or nonlinear regression methods. Despite a strong relationship between water and air temperatures and a variety of models that are effective for data summarized on a weekly basis, such models did not yield consistently good predictions for summaries such as daily maximum temperature...

  3. A Review of Solid-Solution Models of High-Entropy Alloys Based on Ab Initio Calculations

    Directory of Open Access Journals (Sweden)

    Fuyang Tian

    2017-11-01

    Full Text Available Similar to the importance of XRD in experiments, ab initio calculations, as a powerful tool, have been applied to predict the new potential materials and investigate the intrinsic properties of materials in theory. As a typical solid-solution material, the large degree of uncertainty of high-entropy alloys (HEAs results in the difficulty of ab initio calculations application to HEAs. The present review focuses on the available ab initio based solid-solution models (virtual lattice approximation, coherent potential approximation, special quasirandom structure, similar local atomic environment, maximum-entropy method, and hybrid Monte Carlo/molecular dynamics and their applications and limits in single phase HEAs.

  4. Exploiting Maximum Entropy method and ASTER data for assessing debris flow and debris slide susceptibility for the Giampilieri catchment (north-eastern Sicily, Italy).

    KAUST Repository

    Lombardo, Luigi; Bachofer, F.; Cama, M.; Mä rker, M.; Rotigliano, E.

    2016-01-01

    This study aims at evaluating the performance of the Maximum Entropy method in assessing landslide susceptibility, exploiting topographic and multispectral remote sensing predictors. We selected the catchment of the Giampilieri stream, which is located in the north-eastern sector of Sicily (southern Italy), as test site. On 1/10/2009, a storm rainfall triggered in this area hundreds of debris flow/avalanche phenomena causing extensive economical damage and loss of life. Within this area a presence-only-based statistical method was applied to obtain susceptibility models capable of distinguish future activation sites of debris flow and debris slide, which where the main source failure mechanisms for flow or avalanche type propagation. The set of predictors used in this experiment comprised primary and secondary topographic attributes, derived by processing a high resolution digital elevation model, CORINE land cover data and a set of vegetation and mineral indices obtained by processing multispectral ASTER images. All the selected data sources are dated before the disaster. A spatially random partition technique was adopted for validation, generating fifty replicates for each of the two considered movement typologies in order to assess accuracy, precision and reliability of the models. The debris slide and debris flow susceptibility models produced high performances with the first type being the best fitted. The evaluation of the probability estimates around the mean value for each mapped pixel shows an inverted relation, with the most robust models corresponding to the debris flows. With respect to the role of each predictor within the modelling phase, debris flows appeared to be primarily controlled by topographic attributes whilst the debris slides were better explained by remotely sensed derived indices, particularly by the occurrence of previous wildfires across the slope. The overall excellent performances of the two models suggest promising perspectives for

  5. Exploiting Maximum Entropy method and ASTER data for assessing debris flow and debris slide susceptibility for the Giampilieri catchment (north-eastern Sicily, Italy).

    KAUST Repository

    Lombardo, Luigi

    2016-07-18

    This study aims at evaluating the performance of the Maximum Entropy method in assessing landslide susceptibility, exploiting topographic and multispectral remote sensing predictors. We selected the catchment of the Giampilieri stream, which is located in the north-eastern sector of Sicily (southern Italy), as test site. On 1/10/2009, a storm rainfall triggered in this area hundreds of debris flow/avalanche phenomena causing extensive economical damage and loss of life. Within this area a presence-only-based statistical method was applied to obtain susceptibility models capable of distinguish future activation sites of debris flow and debris slide, which where the main source failure mechanisms for flow or avalanche type propagation. The set of predictors used in this experiment comprised primary and secondary topographic attributes, derived by processing a high resolution digital elevation model, CORINE land cover data and a set of vegetation and mineral indices obtained by processing multispectral ASTER images. All the selected data sources are dated before the disaster. A spatially random partition technique was adopted for validation, generating fifty replicates for each of the two considered movement typologies in order to assess accuracy, precision and reliability of the models. The debris slide and debris flow susceptibility models produced high performances with the first type being the best fitted. The evaluation of the probability estimates around the mean value for each mapped pixel shows an inverted relation, with the most robust models corresponding to the debris flows. With respect to the role of each predictor within the modelling phase, debris flows appeared to be primarily controlled by topographic attributes whilst the debris slides were better explained by remotely sensed derived indices, particularly by the occurrence of previous wildfires across the slope. The overall excellent performances of the two models suggest promising perspectives for

  6. Feedback structure based entropy approach for multiple-model estimation

    Institute of Scientific and Technical Information of China (English)

    Shen-tu Han; Xue Anke; Guo Yunfei

    2013-01-01

    The variable-structure multiple-model (VSMM) approach, one of the multiple-model (MM) methods, is a popular and effective approach in handling problems with mode uncertainties. The model sequence set adaptation (MSA) is the key to design a better VSMM. However, MSA methods in the literature have big room to improve both theoretically and practically. To this end, we propose a feedback structure based entropy approach that could find the model sequence sets with the smallest size under certain conditions. The filtered data are fed back in real time and can be used by the minimum entropy (ME) based VSMM algorithms, i.e., MEVSMM. Firstly, the full Markov chains are used to achieve optimal solutions. Secondly, the myopic method together with particle filter (PF) and the challenge match algorithm are also used to achieve sub-optimal solutions, a trade-off between practicability and optimality. The numerical results show that the proposed algorithm provides not only refined model sets but also a good robustness margin and very high accuracy.

  7. Horton Ratios Link Self-Similarity with Maximum Entropy of Eco-Geomorphological Properties in Stream Networks

    Directory of Open Access Journals (Sweden)

    Bruce T. Milne

    2017-05-01

    Full Text Available Stream networks are branched structures wherein water and energy move between land and atmosphere, modulated by evapotranspiration and its interaction with the gravitational dissipation of potential energy as runoff. These actions vary among climates characterized by Budyko theory, yet have not been integrated with Horton scaling, the ubiquitous pattern of eco-hydrological variation among Strahler streams that populate river basins. From Budyko theory, we reveal optimum entropy coincident with high biodiversity. Basins on either side of optimum respond in opposite ways to precipitation, which we evaluated for the classic Hubbard Brook experiment in New Hampshire and for the Whitewater River basin in Kansas. We demonstrate that Horton ratios are equivalent to Lagrange multipliers used in the extremum function leading to Shannon information entropy being maximal, subject to constraints. Properties of stream networks vary with constraints and inter-annual variation in water balance that challenge vegetation to match expected resource supply throughout the network. The entropy-Horton framework informs questions of biodiversity, resilience to perturbations in water supply, changes in potential evapotranspiration, and land use changes that move ecosystems away from optimal entropy with concomitant loss of productivity and biodiversity.

  8. A Novel Entropy-Based Decoding Algorithm for a Generalized High-Order Discrete Hidden Markov Model

    Directory of Open Access Journals (Sweden)

    Jason Chin-Tiong Chan

    2018-01-01

    Full Text Available The optimal state sequence of a generalized High-Order Hidden Markov Model (HHMM is tracked from a given observational sequence using the classical Viterbi algorithm. This classical algorithm is based on maximum likelihood criterion. We introduce an entropy-based Viterbi algorithm for tracking the optimal state sequence of a HHMM. The entropy of a state sequence is a useful quantity, providing a measure of the uncertainty of a HHMM. There will be no uncertainty if there is only one possible optimal state sequence for HHMM. This entropy-based decoding algorithm can be formulated in an extended or a reduction approach. We extend the entropy-based algorithm for computing the optimal state sequence that was developed from a first-order to a generalized HHMM with a single observational sequence. This extended algorithm performs the computation exponentially with respect to the order of HMM. The computational complexity of this extended algorithm is due to the growth of the model parameters. We introduce an efficient entropy-based decoding algorithm that used reduction approach, namely, entropy-based order-transformation forward algorithm (EOTFA to compute the optimal state sequence of any generalized HHMM. This EOTFA algorithm involves a transformation of a generalized high-order HMM into an equivalent first-order HMM and an entropy-based decoding algorithm is developed based on the equivalent first-order HMM. This algorithm performs the computation based on the observational sequence and it requires OTN~2 calculations, where N~ is the number of states in an equivalent first-order model and T is the length of observational sequence.

  9. Singularities and Entropy in Bulk Viscosity Dark Energy Model

    International Nuclear Information System (INIS)

    Meng Xinhe; Dou Xu

    2011-01-01

    In this paper bulk viscosity is introduced to describe the effects of cosmic non-perfect fluid on the cosmos evolution and to build the unified dark energy (DE) with (dark) matter models. Also we derive a general relation between the bulk viscosity form and Hubble parameter that can provide a procedure for the viscosity DE model building. Especially, a redshift dependent viscosity parameter ζ ∝ λ 0 + λ 1 (1 + z) n proposed in the previous work [X.H. Meng and X. Dou, Commun. Theor. Phys. 52 (2009) 377] is investigated extensively in this present work. Further more we use the recently released supernova dataset (the Constitution dataset) to constrain the model parameters. In order to differentiate the proposed concrete dark energy models from the well known ΛCDM model, statefinder diagnostic method is applied to this bulk viscosity model, as a complementary to the Om parameter diagnostic and the deceleration parameter analysis performed by us before. The DE model evolution behavior and tendency are shown in the plane of the statefinder diagnostic parameter pair {r, s} as axes where the fixed point represents the ΛCDM model. The possible singularity property in this bulk viscosity cosmology is also discussed to which we can conclude that in the different parameter regions chosen properly, this concrete viscosity DE model can have various late evolution behaviors and the late time singularity could be avoided. We also calculate the cosmic entropy in the bulk viscosity dark energy frame, and find that the total entropy in the viscosity DE model increases monotonously with respect to the scale factor evolution, thus this monotonous increasing property can indicate an arrow of time in the universe evolution, though the quantum version of the arrow of time is still very puzzling. (geophysics, astronomy, and astrophysics)

  10. Accurate modeling and maximum power point detection of ...

    African Journals Online (AJOL)

    Accurate modeling and maximum power point detection of photovoltaic ... Determination of MPP enables the PV system to deliver maximum available power. ..... adaptive artificial neural network: Proposition for a new sizing procedure.

  11. Population distribution of flexible molecules from maximum entropy analysis using different priors as background information: application to the Φ, Ψ-conformational space of the α-(1-->2)-linked mannose disaccharide present in N- and O-linked glycoproteins.

    Science.gov (United States)

    Säwén, Elin; Massad, Tariq; Landersjö, Clas; Damberg, Peter; Widmalm, Göran

    2010-08-21

    The conformational space available to the flexible molecule α-D-Manp-(1-->2)-α-D-Manp-OMe, a model for the α-(1-->2)-linked mannose disaccharide in N- or O-linked glycoproteins, is determined using experimental data and molecular simulation combined with a maximum entropy approach that leads to a converged population distribution utilizing different input information. A database survey of the Protein Data Bank where structures having the constituent disaccharide were retrieved resulted in an ensemble with >200 structures. Subsequent filtering removed erroneous structures and gave the database (DB) ensemble having three classes of mannose-containing compounds, viz., N- and O-linked structures, and ligands to proteins. A molecular dynamics (MD) simulation of the disaccharide revealed a two-state equilibrium with a major and a minor conformational state, i.e., the MD ensemble. These two different conformation ensembles of the disaccharide were compared to measured experimental spectroscopic data for the molecule in water solution. However, neither of the two populations were compatible with experimental data from optical rotation, NMR (1)H,(1)H cross-relaxation rates as well as homo- and heteronuclear (3)J couplings. The conformational distributions were subsequently used as background information to generate priors that were used in a maximum entropy analysis. The resulting posteriors, i.e., the population distributions after the application of the maximum entropy analysis, still showed notable deviations that were not anticipated based on the prior information. Therefore, reparameterization of homo- and heteronuclear Karplus relationships for the glycosidic torsion angles Φ and Ψ were carried out in which the importance of electronegative substituents on the coupling pathway was deemed essential resulting in four derived equations, two (3)J(COCC) and two (3)J(COCH) being different for the Φ and Ψ torsions, respectively. These Karplus relationships are denoted

  12. Entropy maximization under the constraints on the generalized Gini index and its application in modeling income distributions

    Science.gov (United States)

    Khosravi Tanak, A.; Mohtashami Borzadaran, G. R.; Ahmadi, J.

    2015-11-01

    In economics and social sciences, the inequality measures such as Gini index, Pietra index etc., are commonly used to measure the statistical dispersion. There is a generalization of Gini index which includes it as special case. In this paper, we use principle of maximum entropy to approximate the model of income distribution with a given mean and generalized Gini index. Many distributions have been used as descriptive models for the distribution of income. The most widely known of these models are the generalized beta of second kind and its subclass distributions. The obtained maximum entropy distributions are fitted to the US family total money income in 2009, 2011 and 2013 and their relative performances with respect to generalized beta of second kind family are compared.

  13. Tsallis Entropy Theory for Modeling in Water Engineering: A Review

    Directory of Open Access Journals (Sweden)

    Vijay P. Singh

    2017-11-01

    Full Text Available Water engineering is an amalgam of engineering (e.g., hydraulics, hydrology, irrigation, ecosystems, environment, water resources and non-engineering (e.g., social, economic, political aspects that are needed for planning, designing and managing water systems. These aspects and the associated issues have been dealt with in the literature using different techniques that are based on different concepts and assumptions. A fundamental question that still remains is: Can we develop a unifying theory for addressing these? The second law of thermodynamics permits us to develop a theory that helps address these in a unified manner. This theory can be referred to as the entropy theory. The thermodynamic entropy theory is analogous to the Shannon entropy or the information theory. Perhaps, the most popular generalization of the Shannon entropy is the Tsallis entropy. The Tsallis entropy has been applied to a wide spectrum of problems in water engineering. This paper provides an overview of Tsallis entropy theory in water engineering. After some basic description of entropy and Tsallis entropy, a review of its applications in water engineering is presented, based on three types of problems: (1 problems requiring entropy maximization; (2 problems requiring coupling Tsallis entropy theory with another theory; and (3 problems involving physical relations.

  14. Physical entropy, information entropy and their evolution equations

    Institute of Scientific and Technical Information of China (English)

    2001-01-01

    Inspired by the evolution equation of nonequilibrium statistical physics entropy and the concise statistical formula of the entropy production rate, we develop a theory of the dynamic information entropy and build a nonlinear evolution equation of the information entropy density changing in time and state variable space. Its mathematical form and physical meaning are similar to the evolution equation of the physical entropy: The time rate of change of information entropy density originates together from drift, diffusion and production. The concise statistical formula of information entropy production rate is similar to that of physical entropy also. Furthermore, we study the similarity and difference between physical entropy and information entropy and the possible unification of the two statistical entropies, and discuss the relationship among the principle of entropy increase, the principle of equilibrium maximum entropy and the principle of maximum information entropy as well as the connection between them and the entropy evolution equation.

  15. Probability distributions of bed load particle velocities, accelerations, hop distances, and travel times informed by Jaynes's principle of maximum entropy

    Science.gov (United States)

    Furbish, David; Schmeeckle, Mark; Schumer, Rina; Fathel, Siobhan

    2016-01-01

    We describe the most likely forms of the probability distributions of bed load particle velocities, accelerations, hop distances, and travel times, in a manner that formally appeals to inferential statistics while honoring mechanical and kinematic constraints imposed by equilibrium transport conditions. The analysis is based on E. Jaynes's elaboration of the implications of the similarity between the Gibbs entropy in statistical mechanics and the Shannon entropy in information theory. By maximizing the information entropy of a distribution subject to known constraints on its moments, our choice of the form of the distribution is unbiased. The analysis suggests that particle velocities and travel times are exponentially distributed and that particle accelerations follow a Laplace distribution with zero mean. Particle hop distances, viewed alone, ought to be distributed exponentially. However, the covariance between hop distances and travel times precludes this result. Instead, the covariance structure suggests that hop distances follow a Weibull distribution. These distributions are consistent with high-resolution measurements obtained from high-speed imaging of bed load particle motions. The analysis brings us closer to choosing distributions based on our mechanical insight.

  16. ACCUMULATED DEFORMATION MODELING OF PERMANENT WAY BASED ON ENTROPY SYSTEM

    Directory of Open Access Journals (Sweden)

    D. M. Kurhan

    2015-07-01

    Full Text Available Purpose. The work provides a theoretical research about the possibility of using methods that determine the lifetime of a railway track not only in terms of total stresses, and accounting its structure and dynamic characteristics. The aim of these studies is creation the model of deformations accumulation for assessment of service life of a railway track taking into account these features. Methodology. To simulate a gradual change state during the operation (accumulation of deformations the railway track is presented as a system that consists of many particles of different materials collected in a coherent design. It is appropriate to speak not about the appearance of deformations of a certain size in a certain section of the track, and the probability of such event on the site. If to operate the probability of occurrence of deviations, comfortable state of the system is characterized by the number of breaks of the conditional internal connections. The same state of the system may correspond to different combinations of breaks. The more breaks, the more the number of options changes in the structure of the system appropriate to its current state. Such a process can be represented as a gradual transition from an ordered state to a chaotic one. To describe the characteristics of the system used the numerical value of the entropy. Findings. Its entropy is constantly increasing at system aging. The growth of entropy is expressed by changes in the internal energy of the system, which can be determined using mechanical work forces, which leads to deformation. This gives the opportunity to show quantitative indication of breaking the bonds in the system as a consequence of performing mechanical work. According to the results of theoretical research methods for estimation of the timing of life cycles of railway operation considering such factors as the structure of the flow of trains, construction of the permanent way, the movement of trains at high

  17. Towards the entropy of gravity time-dependent models via the Cardy-Verlinde formula

    International Nuclear Information System (INIS)

    Obregon, Octavio; Patino, Leonardo; Quevedo, Hernando

    2003-01-01

    For models with several time-dependent components, generalized entropies can be defined. This is shown for the Bianchi type IX model. We first derive the Cardy-Verlinde formula under the assumption that the first law of thermodynamics is valid. This leads to an explicit expression of the total entropy associated with this type of universe. Assuming the validity of the Cardy entropy formula, we obtain expressions for the corresponding Bekenstein, Bekenstein-Hawking and Hubble entropies. We discuss the validity of the Cardy-Verlinde formula and possible extensions of the outlined procedure to other time-dependent models

  18. Entropy-Based Experimental Design for Optimal Model Discrimination in the Geosciences

    Directory of Open Access Journals (Sweden)

    Wolfgang Nowak

    2016-11-01

    Full Text Available Choosing between competing models lies at the heart of scientific work, and is a frequent motivation for experimentation. Optimal experimental design (OD methods maximize the benefit of experiments towards a specified goal. We advance and demonstrate an OD approach to maximize the information gained towards model selection. We make use of so-called model choice indicators, which are random variables with an expected value equal to Bayesian model weights. Their uncertainty can be measured with Shannon entropy. Since the experimental data are still random variables in the planning phase of an experiment, we use mutual information (the expected reduction in Shannon entropy to quantify the information gained from a proposed experimental design. For implementation, we use the Preposterior Data Impact Assessor framework (PreDIA, because it is free of the lower-order approximations of mutual information often found in the geosciences. In comparison to other studies in statistics, our framework is not restricted to sequential design or to discrete-valued data, and it can handle measurement errors. As an application example, we optimize an experiment about the transport of contaminants in clay, featuring the problem of choosing between competing isotherms to describe sorption. We compare the results of optimizing towards maximum model discrimination with an alternative OD approach that minimizes the overall predictive uncertainty under model choice uncertainty.

  19. Emergence of spacetime dynamics in entropy corrected and braneworld models

    International Nuclear Information System (INIS)

    Sheykhi, A.; Dehghani, M.H.; Hosseini, S.E.

    2013-01-01

    A very interesting new proposal on the origin of the cosmic expansion was recently suggested by Padmanabhan [arXiv:1206.4916]. He argued that the difference between the surface degrees of freedom and the bulk degrees of freedom in a region of space drives the accelerated expansion of the universe, as well as the standard Friedmann equation through relation ΔV = Δt(N sur −N bulk ). In this paper, we first present the general expression for the number of degrees of freedom on the holographic surface, N sur , using the general entropy corrected formula S = A/(4L p 2 )+s(A). Then, as two example, by applying the Padmanabhan's idea we extract the corresponding Friedmann equations in the presence of power-law and logarithmic correction terms in the entropy. We also extend the study to RS II and DGP braneworld models and derive successfully the correct form of the Friedmann equations in these theories. Our study further supports the viability of Padmanabhan's proposal

  20. Evidence of shallow positron traps in ion-implanted InP observed by maximum entropy reconstruction of positron lifetime distribution: a test of MELT

    International Nuclear Information System (INIS)

    Chen, Z.Q.; Wang, S.J.

    1999-01-01

    A newly developed maximum entropy method, which was realized by the computer program MELT introduced by Shukla et al., was used to analyze positron lifetime spectra measured in semiconductors. Several simulation studies were done to test the performance of this algorithm. Reliable reconstruction of positron lifetime distributions can be extracted at relatively lower counts, which shows the applicability and superiority of this method. Two positron lifetime spectra measured in ion-implanted p-InP(Zn) at 140 and 280 K, respectively were analyzed by this program. The lifetime distribution differed greatly for the two temperatures, giving direct evidence of the existence of shallow positron traps at low temperature

  1. Shifting distributions of adult Atlantic sturgeon amidst post-industrialization and future impacts in the Delaware River: a maximum entropy approach.

    Directory of Open Access Journals (Sweden)

    Matthew W Breece

    Full Text Available Atlantic sturgeon (Acipenser oxyrinchus oxyrinchus experienced severe declines due to habitat destruction and overfishing beginning in the late 19(th century. Subsequent to the boom and bust period of exploitation, there has been minimal fishing pressure and improving habitats. However, lack of recovery led to the 2012 listing of Atlantic sturgeon under the Endangered Species Act. Although habitats may be improving, the availability of high quality spawning habitat, essential for the survival and development of eggs and larvae may still be a limiting factor in the recovery of Atlantic sturgeon. To estimate adult Atlantic sturgeon spatial distributions during riverine occupancy in the Delaware River, we utilized a maximum entropy (MaxEnt approach along with passive biotelemetry during the likely spawning season. We found that substrate composition and distance from the salt front significantly influenced the locations of adult Atlantic sturgeon in the Delaware River. To broaden the scope of this study we projected our model onto four scenarios depicting varying locations of the salt front in the Delaware River: the contemporary location of the salt front during the likely spawning season, the location of the salt front during the historic fishery in the late 19(th century, an estimated shift in the salt front by the year 2100 due to climate change, and an extreme drought scenario, similar to that which occurred in the 1960's. The movement of the salt front upstream as a result of dredging and climate change likely eliminated historic spawning habitats and currently threatens areas where Atlantic sturgeon spawning may be taking place. Identifying where suitable spawning substrate and water chemistry intersect with the likely occurrence of adult Atlantic sturgeon in the Delaware River highlights essential spawning habitats, enhancing recovery prospects for this imperiled species.

  2. Models, Entropy and Information of Temporal Social Networks

    Science.gov (United States)

    Zhao, Kun; Karsai, Márton; Bianconi, Ginestra

    Temporal social networks are characterized by heterogeneous duration of contacts, which can either follow a power-law distribution, such as in face-to-face interactions, or a Weibull distribution, such as in mobile-phone communication. Here we model the dynamics of face-to-face interaction and mobile phone communication by a reinforcement dynamics, which explains the data observed in these different types of social interactions. We quantify the information encoded in the dynamics of these networks by the entropy of temporal networks. Finally, we show evidence that human dynamics is able to modulate the information present in social network dynamics when it follows circadian rhythms and when it is interfacing with a new technology such as the mobile-phone communication technology.

  3. Maximum likelihood estimation of finite mixture model for economic data

    Science.gov (United States)

    Phoong, Seuk-Yen; Ismail, Mohd Tahir

    2014-06-01

    Finite mixture model is a mixture model with finite-dimension. This models are provides a natural representation of heterogeneity in a finite number of latent classes. In addition, finite mixture models also known as latent class models or unsupervised learning models. Recently, maximum likelihood estimation fitted finite mixture models has greatly drawn statistician's attention. The main reason is because maximum likelihood estimation is a powerful statistical method which provides consistent findings as the sample sizes increases to infinity. Thus, the application of maximum likelihood estimation is used to fit finite mixture model in the present paper in order to explore the relationship between nonlinear economic data. In this paper, a two-component normal mixture model is fitted by maximum likelihood estimation in order to investigate the relationship among stock market price and rubber price for sampled countries. Results described that there is a negative effect among rubber price and stock market price for Malaysia, Thailand, Philippines and Indonesia.

  4. Reconstruction of calmodulin single-molecule FRET states, dye interactions, and CaMKII peptide binding by MultiNest and classic maximum entropy

    Science.gov (United States)

    DeVore, Matthew S.; Gull, Stephen F.; Johnson, Carey K.

    2013-08-01

    We analyzed single molecule FRET burst measurements using Bayesian nested sampling. The MultiNest algorithm produces accurate FRET efficiency distributions from single-molecule data. FRET efficiency distributions recovered by MultiNest and classic maximum entropy are compared for simulated data and for calmodulin labeled at residues 44 and 117. MultiNest compares favorably with maximum entropy analysis for simulated data, judged by the Bayesian evidence. FRET efficiency distributions recovered for calmodulin labeled with two different FRET dye pairs depended on the dye pair and changed upon Ca2+ binding. We also looked at the FRET efficiency distributions of calmodulin bound to the calcium/calmodulin dependent protein kinase II (CaMKII) binding domain. For both dye pairs, the FRET efficiency distribution collapsed to a single peak in the case of calmodulin bound to the CaMKII peptide. These measurements strongly suggest that consideration of dye-protein interactions is crucial in forming an accurate picture of protein conformations from FRET data.

  5. Reconstruction of Calmodulin Single-Molecule FRET States, Dye-Interactions, and CaMKII Peptide Binding by MultiNest and Classic Maximum Entropy.

    Science.gov (United States)

    Devore, Matthew S; Gull, Stephen F; Johnson, Carey K

    2013-08-30

    We analyze single molecule FRET burst measurements using Bayesian nested sampling. The MultiNest algorithm produces accurate FRET efficiency distributions from single-molecule data. FRET efficiency distributions recovered by MultiNest and classic maximum entropy are compared for simulated data and for calmodulin labeled at residues 44 and 117. MultiNest compares favorably with maximum entropy analysis for simulated data, judged by the Bayesian evidence. FRET efficiency distributions recovered for calmodulin labeled with two different FRET dye pairs depended on the dye pair and changed upon Ca 2+ binding. We also looked at the FRET efficiency distributions of calmodulin bound to the calcium/calmodulin dependent protein kinase II (CaMKII) binding domain. For both dye pairs, the FRET efficiency distribution collapsed to a single peak in the case of calmodulin bound to the CaMKII peptide. These measurements strongly suggest that consideration of dye-protein interactions is crucial in forming an accurate picture of protein conformations from FRET data.

  6. Constraints and entropy in a model of network evolution

    Science.gov (United States)

    Tee, Philip; Wakeman, Ian; Parisis, George; Dawes, Jonathan; Kiss, István Z.

    2017-11-01

    Barabási-Albert's "Scale Free" model is the starting point for much of the accepted theory of the evolution of real world communication networks. Careful comparison of the theory with a wide range of real world networks, however, indicates that the model is in some cases, only a rough approximation to the dynamical evolution of real networks. In particular, the exponent γ of the power law distribution of degree is predicted by the model to be exactly 3, whereas in a number of real world networks it has values between 1.2 and 2.9. In addition, the degree distributions of real networks exhibit cut offs at high node degree, which indicates the existence of maximal node degrees for these networks. In this paper we propose a simple extension to the "Scale Free" model, which offers better agreement with the experimental data. This improvement is satisfying, but the model still does not explain why the attachment probabilities should favor high degree nodes, or indeed how constraints arrive in non-physical networks. Using recent advances in the analysis of the entropy of graphs at the node level we propose a first principles derivation for the "Scale Free" and "constraints" model from thermodynamic principles, and demonstrate that both preferential attachment and constraints could arise as a natural consequence of the second law of thermodynamics.

  7. Entropy Error Model of Planar Geometry Features in GIS

    Institute of Scientific and Technical Information of China (English)

    LI Dajun; GUAN Yunlan; GONG Jianya; DU Daosheng

    2003-01-01

    Positional error of line segments is usually described by using "g-band", however, its band width is in relation to the confidence level choice. In fact, given different confidence levels, a series of concentric bands can be obtained. To overcome the effect of confidence level on the error indicator, by introducing the union entropy theory, we propose an entropy error ellipse index of point, then extend it to line segment and polygon,and establish an entropy error band of line segment and an entropy error donut of polygon. The research shows that the entropy error index can be determined uniquely and is not influenced by confidence level, and that they are suitable for positional uncertainty of planar geometry features.

  8. Two aspects of black hole entropy in Lanczos-Lovelock models of gravity

    Science.gov (United States)

    Kolekar, Sanved; Kothawala, Dawood; Padmanabhan, T.

    2012-03-01

    We consider two specific approaches to evaluate the black hole entropy which are known to produce correct results in the case of Einstein’s theory and generalize them to Lanczos-Lovelock models. In the first approach (which could be called extrinsic), we use a procedure motivated by earlier work by Pretorius, Vollick, and Israel, and by Oppenheim, and evaluate the entropy of a configuration of densely packed gravitating shells on the verge of forming a black hole in Lanczos-Lovelock theories of gravity. We find that this matter entropy is not equal to (it is less than) Wald entropy, except in the case of Einstein theory, where they are equal. The matter entropy is proportional to the Wald entropy if we consider a specific mth-order Lanczos-Lovelock model, with the proportionality constant depending on the spacetime dimensions D and the order m of the Lanczos-Lovelock theory as (D-2m)/(D-2). Since the proportionality constant depends on m, the proportionality between matter entropy and Wald entropy breaks down when we consider a sum of Lanczos-Lovelock actions involving different m. In the second approach (which could be called intrinsic), we generalize a procedure, previously introduced by Padmanabhan in the context of general relativity, to study off-shell entropy of a class of metrics with horizon using a path integral method. We consider the Euclidean action of Lanczos-Lovelock models for a class of metrics off shell and interpret it as a partition function. We show that in the case of spherically symmetric metrics, one can interpret the Euclidean action as the free energy and read off both the entropy and energy of a black hole spacetime. Surprisingly enough, this leads to exactly the Wald entropy and the energy of the spacetime in Lanczos-Lovelock models obtained by other methods. We comment on possible implications of the result.

  9. Black Hole Entropy Calculation in a Modified Thin Film Model Jingyi ...

    Indian Academy of Sciences (India)

    Abstract. The thin film model is modified to calculate the black hole entropy. The difference from the original method is that the Parikh–. Wilczek tunnelling framework is introduced and the self-gravitation of the emission particles is taken into account. In terms of our improvement, if the entropy is still proportional to the area, ...

  10. Parameters Tuning of Model Free Adaptive Control Based on Minimum Entropy

    Institute of Scientific and Technical Information of China (English)

    Chao Ji; Jing Wang; Liulin Cao; Qibing Jin

    2014-01-01

    Dynamic linearization based model free adaptive control(MFAC) algorithm has been widely used in practical systems, in which some parameters should be tuned before it is successfully applied to process industries. Considering the random noise existing in real processes, a parameter tuning method based on minimum entropy optimization is proposed,and the feature of entropy is used to accurately describe the system uncertainty. For cases of Gaussian stochastic noise and non-Gaussian stochastic noise, an entropy recursive optimization algorithm is derived based on approximate model or identified model. The extensive simulation results show the effectiveness of the minimum entropy optimization for the partial form dynamic linearization based MFAC. The parameters tuned by the minimum entropy optimization index shows stronger stability and more robustness than these tuned by other traditional index,such as integral of the squared error(ISE) or integral of timeweighted absolute error(ITAE), when the system stochastic noise exists.

  11. Entropy-Based Model for Interpreting Life Systems in Traditional Chinese Medicine

    Directory of Open Access Journals (Sweden)

    Guo-lian Kang

    2008-01-01

    Full Text Available Traditional Chinese medicine (TCM treats qi as the core of the human life systems. Starting with a hypothetical correlation between TCM qi and the entropy theory, we address in this article a holistic model for evaluating and unveiling the rule of TCM life systems. Several new concepts such as acquired life entropy (ALE, acquired life entropy flow (ALEF and acquired life entropy production (ALEP are propounded to interpret TCM life systems. Using the entropy theory, mathematical models are established for ALE, ALEF and ALEP, which reflect the evolution of life systems. Some criteria are given on physiological activities and pathological changes of the body in different stages of life. Moreover, a real data-based simulation shows life entropies of the human body with different ages, Cold and Hot constitutions and in different seasons in North China are coincided with the manifestations of qi as well as the life evolution in TCM descriptions. Especially, based on the comparative and quantitative analysis, the entropy-based model can nicely describe the evolution of life entropies in Cold and Hot individuals thereby fitting the Yin–Yang theory in TCM. Thus, this work establishes a novel approach to interpret the fundamental principles in TCM, and provides an alternative understanding for the complex life systems.

  12. Information theory explanation of the fluctuation theorem, maximum entropy production and self-organized criticality in non-equilibrium stationary states

    CERN Document Server

    Dewar, R

    2003-01-01

    Jaynes' information theory formalism of statistical mechanics is applied to the stationary states of open, non-equilibrium systems. First, it is shown that the probability distribution p subGAMMA of the underlying microscopic phase space trajectories GAMMA over a time interval of length tau satisfies p subGAMMA propor to exp(tau sigma subGAMMA/2k sub B) where sigma subGAMMA is the time-averaged rate of entropy production of GAMMA. Three consequences of this result are then derived: (1) the fluctuation theorem, which describes the exponentially declining probability of deviations from the second law of thermodynamics as tau -> infinity; (2) the selection principle of maximum entropy production for non-equilibrium stationary states, empirical support for which has been found in studies of phenomena as diverse as the Earth's climate and crystal growth morphology; and (3) the emergence of self-organized criticality for flux-driven systems in the slowly-driven limit. The explanation of these results on general inf...

  13. Numerical Simulation of Entropy Growth for a Nonlinear Evolutionary Model of Random Markets

    Directory of Open Access Journals (Sweden)

    Mahdi Keshtkar

    2016-01-01

    Full Text Available In this communication, the generalized continuous economic model for random markets is revisited. In this model for random markets, agents trade by pairs and exchange their money in a random and conservative way. They display the exponential wealth distribution as asymptotic equilibrium, independently of the effectiveness of the transactions and of the limitation of the total wealth. In the current work, entropy of mentioned model is defined and then some theorems on entropy growth of this evolutionary problem are given. Furthermore, the entropy increasing by simulation on some numerical examples is verified.

  14. Studies on entanglement entropy for Hubbard model with hole-doping and external magnetic field

    International Nuclear Information System (INIS)

    Yao, K.L.; Li, Y.C.; Sun, X.Z.; Liu, Q.M.; Qin, Y.; Fu, H.H.; Gao, G.Y.

    2005-01-01

    By using the density matrix renormalization group (DMRG) method for the one-dimensional (1D) Hubbard model, we have studied the von Neumann entropy of a quantum system, which describes the entanglement of the system block and the rest of the chain. It is found that there is a close relation between the entanglement entropy and properties of the system. The hole-doping can alter the charge-charge and spin-spin interactions, resulting in charge polarization along the chain. By comparing the results before and after the doping, we find that doping favors increase of the von Neumann entropy and thus also favors the exchange of information along the chain. Furthermore, we calculated the spin and entropy distribution in external magnetic filed. It is confirmed that both the charge-charge and the spin-spin interactions affect the exchange of information along the chain, making the entanglement entropy redistribute

  15. Entropy-based model for miRNA isoform analysis.

    Directory of Open Access Journals (Sweden)

    Shengqin Wang

    Full Text Available MiRNAs have been widely studied due to their important post-transcriptional regulatory roles in gene expression. Many reports have demonstrated the evidence of miRNA isoform products (isomiRs in high-throughput small RNA sequencing data. However, the biological function involved in these molecules is still not well investigated. Here, we developed a Shannon entropy-based model to estimate isomiR expression profiles of high-throughput small RNA sequencing data extracted from miRBase webserver. By using the Kolmogorov-Smirnov statistical test (KS test, we demonstrated that the 5p and 3p miRNAs present more variants than the single arm miRNAs. We also found that the isomiR variant, except the 3' isomiR variant, is strongly correlated with Minimum Free Energy (MFE of pre-miRNA, suggesting the intrinsic feature of pre-miRNA should be one of the important factors for the miRNA regulation. The functional enrichment analysis showed that the miRNAs with high variation, particularly the 5' end variation, are enriched in a set of critical functions, supporting these molecules should not be randomly produced. Our results provide a probabilistic framework for miRNA isoforms analysis, and give functional insights into pre-miRNA processing.

  16. Entanglement entropy production in gravitational collapse: covariant regularization and solvable models

    Science.gov (United States)

    Bianchi, Eugenio; De Lorenzo, Tommaso; Smerlak, Matteo

    2015-06-01

    We study the dynamics of vacuum entanglement in the process of gravitational collapse and subsequent black hole evaporation. In the first part of the paper, we introduce a covariant regularization of entanglement entropy tailored to curved spacetimes; this regularization allows us to propose precise definitions for the concepts of black hole "exterior entropy" and "radiation entropy." For a Vaidya model of collapse we find results consistent with the standard thermodynamic properties of Hawking radiation. In the second part of the paper, we compute the vacuum entanglement entropy of various spherically-symmetric spacetimes of interest, including the nonsingular black hole model of Bardeen, Hayward, Frolov and Rovelli-Vidotto and the "black hole fireworks" model of Haggard-Rovelli. We discuss specifically the role of event and trapping horizons in connection with the behavior of the radiation entropy at future null infinity. We observe in particular that ( i) in the presence of an event horizon the radiation entropy diverges at the end of the evaporation process, ( ii) in models of nonsingular evaporation (with a trapped region but no event horizon) the generalized second law holds only at early times and is violated in the "purifying" phase, ( iii) at late times the radiation entropy can become negative (i.e. the radiation can be less correlated than the vacuum) before going back to zero leading to an up-down-up behavior for the Page curve of a unitarily evaporating black hole.

  17. Cluster-size entropy in the Axelrod model of social influence: Small-world networks and mass media

    Science.gov (United States)

    Gandica, Y.; Charmell, A.; Villegas-Febres, J.; Bonalde, I.

    2011-10-01

    We study the Axelrod's cultural adaptation model using the concept of cluster-size entropy Sc, which gives information on the variability of the cultural cluster size present in the system. Using networks of different topologies, from regular to random, we find that the critical point of the well-known nonequilibrium monocultural-multicultural (order-disorder) transition of the Axelrod model is given by the maximum of the Sc(q) distributions. The width of the cluster entropy distributions can be used to qualitatively determine whether the transition is first or second order. By scaling the cluster entropy distributions we were able to obtain a relationship between the critical cultural trait qc and the number F of cultural features in two-dimensional regular networks. We also analyze the effect of the mass media (external field) on social systems within the Axelrod model in a square network. We find a partially ordered phase whose largest cultural cluster is not aligned with the external field, in contrast with a recent suggestion that this type of phase cannot be formed in regular networks. We draw a q-B phase diagram for the Axelrod model in regular networks.

  18. Dynamic approximate entropy electroanatomic maps detect rotors in a simulated atrial fibrillation model.

    Science.gov (United States)

    Ugarte, Juan P; Orozco-Duque, Andrés; Tobón, Catalina; Kremen, Vaclav; Novak, Daniel; Saiz, Javier; Oesterlein, Tobias; Schmitt, Clauss; Luik, Armin; Bustamante, John

    2014-01-01

    There is evidence that rotors could be drivers that maintain atrial fibrillation. Complex fractionated atrial electrograms have been located in rotor tip areas. However, the concept of electrogram fractionation, defined using time intervals, is still controversial as a tool for locating target sites for ablation. We hypothesize that the fractionation phenomenon is better described using non-linear dynamic measures, such as approximate entropy, and that this tool could be used for locating the rotor tip. The aim of this work has been to determine the relationship between approximate entropy and fractionated electrograms, and to develop a new tool for rotor mapping based on fractionation levels. Two episodes of chronic atrial fibrillation were simulated in a 3D human atrial model, in which rotors were observed. Dynamic approximate entropy maps were calculated using unipolar electrogram signals generated over the whole surface of the 3D atrial model. In addition, we optimized the approximate entropy calculation using two real multi-center databases of fractionated electrogram signals, labeled in 4 levels of fractionation. We found that the values of approximate entropy and the levels of fractionation are positively correlated. This allows the dynamic approximate entropy maps to localize the tips from stable and meandering rotors. Furthermore, we assessed the optimized approximate entropy using bipolar electrograms generated over a vicinity enclosing a rotor, achieving rotor detection. Our results suggest that high approximate entropy values are able to detect a high level of fractionation and to locate rotor tips in simulated atrial fibrillation episodes. We suggest that dynamic approximate entropy maps could become a tool for atrial fibrillation rotor mapping.

  19. Dynamic Approximate Entropy Electroanatomic Maps Detect Rotors in a Simulated Atrial Fibrillation Model

    Science.gov (United States)

    Ugarte, Juan P.; Orozco-Duque, Andrés; Tobón, Catalina; Kremen, Vaclav; Novak, Daniel; Saiz, Javier; Oesterlein, Tobias; Schmitt, Clauss; Luik, Armin; Bustamante, John

    2014-01-01

    There is evidence that rotors could be drivers that maintain atrial fibrillation. Complex fractionated atrial electrograms have been located in rotor tip areas. However, the concept of electrogram fractionation, defined using time intervals, is still controversial as a tool for locating target sites for ablation. We hypothesize that the fractionation phenomenon is better described using non-linear dynamic measures, such as approximate entropy, and that this tool could be used for locating the rotor tip. The aim of this work has been to determine the relationship between approximate entropy and fractionated electrograms, and to develop a new tool for rotor mapping based on fractionation levels. Two episodes of chronic atrial fibrillation were simulated in a 3D human atrial model, in which rotors were observed. Dynamic approximate entropy maps were calculated using unipolar electrogram signals generated over the whole surface of the 3D atrial model. In addition, we optimized the approximate entropy calculation using two real multi-center databases of fractionated electrogram signals, labeled in 4 levels of fractionation. We found that the values of approximate entropy and the levels of fractionation are positively correlated. This allows the dynamic approximate entropy maps to localize the tips from stable and meandering rotors. Furthermore, we assessed the optimized approximate entropy using bipolar electrograms generated over a vicinity enclosing a rotor, achieving rotor detection. Our results suggest that high approximate entropy values are able to detect a high level of fractionation and to locate rotor tips in simulated atrial fibrillation episodes. We suggest that dynamic approximate entropy maps could become a tool for atrial fibrillation rotor mapping. PMID:25489858

  20. Regional Analysis of Precipitation by Means of Bivariate Distribution Adjusted by Maximum Entropy; Analisis regional de precipitacion con base en una distribucion bivariada ajustada por maxima entropia

    Energy Technology Data Exchange (ETDEWEB)

    Escalante Sandoval, Carlos A.; Dominguez Esquivel, Jose Y. [Universidad Nacional Autonoma de Mexico (Mexico)

    2001-09-01

    The principle of maximum entropy (POME) is used to derive an alternative method of parameter estimation for the bivariate Gumbel distribution. A simple algorithm for this parameter estimation technique is presented. This method is applied to analyze the precipitation in a region of Mexico. Design events are compered with those obtained by the maximum likelihood procedure. According to the results, the proposed technique is a suitable option to be considered when performing frequency analysis of precipitation with small samples. [Spanish] El principio de maxima entropia, conocido como POME, es utilizado para derivar un procedimiento alternativo de estimacion de parametros de la distribucion bivariada de valores extremos con marginales Gumbel. El modelo se aplica al analisis de la precipitacion maxima en 24 horas en una region de Mexico y los eventos de diseno obtenidos son comparados con los proporcionados por la tecnica de maxima verosimilitud. De acuerdo con los resultados obtenidos, se concluye que la tecnica propuesta representa una buena opcion, sobre todo para el caso de muestras pequenas.

  1. ENTROPY CHARACTERISTICS IN MODELS FOR COORDINATION OF NEIGHBORING ROAD SECTIONS

    Directory of Open Access Journals (Sweden)

    N. I. Kulbashnaya

    2016-01-01

    Full Text Available The paper considers an application of entropy characteristics as criteria to coordinate traffic conditions at neighboring road sections. It has been proved that the entropy characteristics are widely used in the methods that take into account information influence of the environment on drivers and in the mechanisms that create such traffic conditions which ensure preservation of the optimal level of driver’s emotional tension during the drive. Solution of such problem is considered in the aspect of coordination of traffic conditions at neighboring road sections that, in its turn, is directed on exclusion of any driver’s transitional processes. Methodology for coordination of traffic conditions at neighboring road sections is based on the E. V. Gavrilov’s concept on coordination of some parameters of road sections which can be expressed in the entropy characteristics. The paper proposes to execute selection of coordination criteria according to accident rates because while moving along neighboring road sections traffic conditions change drastically that can result in creation of an accident situation. Relative organization of a driver’s perception field and driver’s interaction with the traffic environment has been selected as entropy characteristics. Therefore, the given characteristics are made conditional to the road accidents rate. The investigation results have revealed a strong correlation between the relative organization of the driver’s perception field and the relative organization of the driver’s interaction with the traffic environment and the accident rate. Results of the executed experiment have proved an influence of the accident rate on the investigated entropy characteristics.

  2. Entropy analysis on non-equilibrium two-phase flow models

    International Nuclear Information System (INIS)

    Karwat, H.; Ruan, Y.Q.

    1995-01-01

    A method of entropy analysis according to the second law of thermodynamics is proposed for the assessment of a class of practical non-equilibrium two-phase flow models. Entropy conditions are derived directly from a local instantaneous formulation for an arbitrary control volume of a structural two-phase fluid, which are finally expressed in terms of the averaged thermodynamic independent variables and their time derivatives as well as the boundary conditions for the volume. On the basis of a widely used thermal-hydraulic system code it is demonstrated with practical examples that entropy production rates in control volumes can be numerically quantified by using the data from the output data files. Entropy analysis using the proposed method is useful in identifying some potential problems in two-phase flow models and predictions as well as in studying the effects of some free parameters in closure relationships

  3. Entropy analysis on non-equilibrium two-phase flow models

    Energy Technology Data Exchange (ETDEWEB)

    Karwat, H.; Ruan, Y.Q. [Technische Universitaet Muenchen, Garching (Germany)

    1995-09-01

    A method of entropy analysis according to the second law of thermodynamics is proposed for the assessment of a class of practical non-equilibrium two-phase flow models. Entropy conditions are derived directly from a local instantaneous formulation for an arbitrary control volume of a structural two-phase fluid, which are finally expressed in terms of the averaged thermodynamic independent variables and their time derivatives as well as the boundary conditions for the volume. On the basis of a widely used thermal-hydraulic system code it is demonstrated with practical examples that entropy production rates in control volumes can be numerically quantified by using the data from the output data files. Entropy analysis using the proposed method is useful in identifying some potential problems in two-phase flow models and predictions as well as in studying the effects of some free parameters in closure relationships.

  4. Entanglement entropy production in gravitational collapse: covariant regularization and solvable models

    International Nuclear Information System (INIS)

    Bianchi, Eugenio; Lorenzo, Tommaso De; Smerlak, Matteo

    2015-01-01

    We study the dynamics of vacuum entanglement in the process of gravitational collapse and subsequent black hole evaporation. In the first part of the paper, we introduce a covariant regularization of entanglement entropy tailored to curved spacetimes; this regularization allows us to propose precise definitions for the concepts of black hole “exterior entropy” and “radiation entropy.” For a Vaidya model of collapse we find results consistent with the standard thermodynamic properties of Hawking radiation. In the second part of the paper, we compute the vacuum entanglement entropy of various spherically-symmetric spacetimes of interest, including the nonsingular black hole model of Bardeen, Hayward, Frolov and Rovelli-Vidotto and the “black hole fireworks” model of Haggard-Rovelli. We discuss specifically the role of event and trapping horizons in connection with the behavior of the radiation entropy at future null infinity. We observe in particular that (i) in the presence of an event horizon the radiation entropy diverges at the end of the evaporation process, (ii) in models of nonsingular evaporation (with a trapped region but no event horizon) the generalized second law holds only at early times and is violated in the “purifying” phase, (iii) at late times the radiation entropy can become negative (i.e. the radiation can be less correlated than the vacuum) before going back to zero leading to an up-down-up behavior for the Page curve of a unitarily evaporating black hole.

  5. Testing the Beta-Lognormal Model in Amazonian Rainfall Fields Using the Generalized Space q-Entropy

    Directory of Open Access Journals (Sweden)

    Hernán D. Salas

    2017-12-01

    Full Text Available We study spatial scaling and complexity properties of Amazonian radar rainfall fields using the Beta-Lognormal Model (BL-Model with the aim to characterize and model the process at a broad range of spatial scales. The Generalized Space q-Entropy Function (GSEF, an entropic measure defined as a continuous set of power laws covering a broad range of spatial scales, S q ( λ ∼ λ Ω ( q , is used as a tool to check the ability of the BL-Model to represent observed 2-D radar rainfall fields. In addition, we evaluate the effect of the amount of zeros, the variability of rainfall intensity, the number of bins used to estimate the probability mass function, and the record length on the GSFE estimation. Our results show that: (i the BL-Model adequately represents the scaling properties of the q-entropy, S q, for Amazonian rainfall fields across a range of spatial scales λ from 2 km to 64 km; (ii the q-entropy in rainfall fields can be characterized by a non-additivity value, q s a t, at which rainfall reaches a maximum scaling exponent, Ω s a t; (iii the maximum scaling exponent Ω s a t is directly related to the amount of zeros in rainfall fields and is not sensitive to either the number of bins to estimate the probability mass function or the variability of rainfall intensity; and (iv for small-samples, the GSEF of rainfall fields may incur in considerable bias. Finally, for synthetic 2-D rainfall fields from the BL-Model, we look for a connection between intermittency using a metric based on generalized Hurst exponents, M ( q 1 , q 2 , and the non-extensive order (q-order of a system, Θ q, which relates to the GSEF. Our results do not exhibit evidence of such relationship.

  6. Expected Shannon Entropy and Shannon Differentiation between Subpopulations for Neutral Genes under the Finite Island Model.

    Science.gov (United States)

    Chao, Anne; Jost, Lou; Hsieh, T C; Ma, K H; Sherwin, William B; Rollins, Lee Ann

    2015-01-01

    Shannon entropy H and related measures are increasingly used in molecular ecology and population genetics because (1) unlike measures based on heterozygosity or allele number, these measures weigh alleles in proportion to their population fraction, thus capturing a previously-ignored aspect of allele frequency distributions that may be important in many applications; (2) these measures connect directly to the rich predictive mathematics of information theory; (3) Shannon entropy is completely additive and has an explicitly hierarchical nature; and (4) Shannon entropy-based differentiation measures obey strong monotonicity properties that heterozygosity-based measures lack. We derive simple new expressions for the expected values of the Shannon entropy of the equilibrium allele distribution at a neutral locus in a single isolated population under two models of mutation: the infinite allele model and the stepwise mutation model. Surprisingly, this complex stochastic system for each model has an entropy expressable as a simple combination of well-known mathematical functions. Moreover, entropy- and heterozygosity-based measures for each model are linked by simple relationships that are shown by simulations to be approximately valid even far from equilibrium. We also identify a bridge between the two models of mutation. We apply our approach to subdivided populations which follow the finite island model, obtaining the Shannon entropy of the equilibrium allele distributions of the subpopulations and of the total population. We also derive the expected mutual information and normalized mutual information ("Shannon differentiation") between subpopulations at equilibrium, and identify the model parameters that determine them. We apply our measures to data from the common starling (Sturnus vulgaris) in Australia. Our measures provide a test for neutrality that is robust to violations of equilibrium assumptions, as verified on real world data from starlings.

  7. Expected Shannon Entropy and Shannon Differentiation between Subpopulations for Neutral Genes under the Finite Island Model.

    Directory of Open Access Journals (Sweden)

    Anne Chao

    Full Text Available Shannon entropy H and related measures are increasingly used in molecular ecology and population genetics because (1 unlike measures based on heterozygosity or allele number, these measures weigh alleles in proportion to their population fraction, thus capturing a previously-ignored aspect of allele frequency distributions that may be important in many applications; (2 these measures connect directly to the rich predictive mathematics of information theory; (3 Shannon entropy is completely additive and has an explicitly hierarchical nature; and (4 Shannon entropy-based differentiation measures obey strong monotonicity properties that heterozygosity-based measures lack. We derive simple new expressions for the expected values of the Shannon entropy of the equilibrium allele distribution at a neutral locus in a single isolated population under two models of mutation: the infinite allele model and the stepwise mutation model. Surprisingly, this complex stochastic system for each model has an entropy expressable as a simple combination of well-known mathematical functions. Moreover, entropy- and heterozygosity-based measures for each model are linked by simple relationships that are shown by simulations to be approximately valid even far from equilibrium. We also identify a bridge between the two models of mutation. We apply our approach to subdivided populations which follow the finite island model, obtaining the Shannon entropy of the equilibrium allele distributions of the subpopulations and of the total population. We also derive the expected mutual information and normalized mutual information ("Shannon differentiation" between subpopulations at equilibrium, and identify the model parameters that determine them. We apply our measures to data from the common starling (Sturnus vulgaris in Australia. Our measures provide a test for neutrality that is robust to violations of equilibrium assumptions, as verified on real world data from starlings.

  8. Optimal item discrimination and maximum information for logistic IRT models

    NARCIS (Netherlands)

    Veerkamp, W.J.J.; Veerkamp, Wim J.J.; Berger, Martijn P.F.; Berger, Martijn

    1999-01-01

    Items with the highest discrimination parameter values in a logistic item response theory model do not necessarily give maximum information. This paper derives discrimination parameter values, as functions of the guessing parameter and distances between person parameters and item difficulty, that

  9. Landau damping: the mechanics model and its ultimate entropy gain

    International Nuclear Information System (INIS)

    Hannay, J H; Kluge, Michel

    2011-01-01

    Classical mechanics has only been invoked to account for Landau damping in a rather half-hearted way, alongside plasma perturbation theory. In particular this invocation is essential for the study of the saturation, or post-linear (or 'nonlinear') regime of the damping initiated by Dawson and O'Neill. By embracing mechanics wholeheartedly here, with its attendant phase space, one can access results, old and new, cleanly and directly, and with one fewer numerical integration for the post-linear regime. By using a summation technique familiar in semiclassical quantum mechanics (Poisson summation), the one remaining numerical integration can be much improved in accuracy. Also accessible from mechanics is the ultimate entropy gain. Though zero for any finite time (in the absence of coarse graining), the entropy gain is ultimately non-zero (at infinite time the required coarse graining is zero). It is calculated analytically by using the appropriate asymptotics, hitherto not fully exploited.

  10. Chaos control in an economic model via minimum entropy strategy

    Energy Technology Data Exchange (ETDEWEB)

    Salarieh, Hassan [Center of Excellence in Design, Robotics and Automation, Department of Mechanical Engineering, Sharif University of Technology, P.O. Box 11365-9567, Tehran (Iran, Islamic Republic of)], E-mail: salarieh@mech.sharif.edu; Alasty, Aria [Center of Excellence in Design, Robotics and Automation, Department of Mechanical Engineering, Sharif University of Technology, P.O. Box 11365-9567, Tehran (Iran, Islamic Republic of); National Research Institute for Science Policy (NRISP), Soheil Street, Shirazi Avenue, Tehran (Iran, Islamic Republic of)], E-mail: aalasti@sharif.edu

    2009-04-30

    In this paper, minimum entropy algorithm for controlling chaos, is applied to a Cournot duopoly with different constant marginal costs, as a discrete-time dynamical system which shows chaotic behavior. The ME control is implemented through delayed feedback. It is assumed that the equations of the dynamical system are not known, so the feedback gain cannot be obtained analytically from the system equations. In the ME method the feedback gain is obtained adaptively in such a way that the entropy of the system converges to zero, hence a fixed point of the system will be stabilized. Application of the proposed method with different economic control strategies is numerically investigated. Simulation results show the effectiveness of the ME method for controlling chaos in economic systems with unknown equations.

  11. The moving-window Bayesian maximum entropy framework: estimation of PM(2.5) yearly average concentration across the contiguous United States.

    Science.gov (United States)

    Akita, Yasuyuki; Chen, Jiu-Chiuan; Serre, Marc L

    2012-09-01

    Geostatistical methods are widely used in estimating long-term exposures for epidemiological studies on air pollution, despite their limited capabilities to handle spatial non-stationarity over large geographic domains and the uncertainty associated with missing monitoring data. We developed a moving-window (MW) Bayesian maximum entropy (BME) method and applied this framework to estimate fine particulate matter (PM(2.5)) yearly average concentrations over the contiguous US. The MW approach accounts for the spatial non-stationarity, while the BME method rigorously processes the uncertainty associated with data missingness in the air-monitoring system. In the cross-validation analyses conducted on a set of randomly selected complete PM(2.5) data in 2003 and on simulated data with different degrees of missing data, we demonstrate that the MW approach alone leads to at least 17.8% reduction in mean square error (MSE) in estimating the yearly PM(2.5). Moreover, the MWBME method further reduces the MSE by 8.4-43.7%, with the proportion of incomplete data increased from 18.3% to 82.0%. The MWBME approach leads to significant reductions in estimation error and thus is recommended for epidemiological studies investigating the effect of long-term exposure to PM(2.5) across large geographical domains with expected spatial non-stationarity.

  12. The moving-window Bayesian Maximum Entropy framework: Estimation of PM2.5 yearly average concentration across the contiguous United States

    Science.gov (United States)

    Akita, Yasuyuki; Chen, Jiu-Chiuan; Serre, Marc L.

    2013-01-01

    Geostatistical methods are widely used in estimating long-term exposures for air pollution epidemiological studies, despite their limited capabilities to handle spatial non-stationarity over large geographic domains and uncertainty associated with missing monitoring data. We developed a moving-window (MW) Bayesian Maximum Entropy (BME) method and applied this framework to estimate fine particulate matter (PM2.5) yearly average concentrations over the contiguous U.S. The MW approach accounts for the spatial non-stationarity, while the BME method rigorously processes the uncertainty associated with data missingnees in the air monitoring system. In the cross-validation analyses conducted on a set of randomly selected complete PM2.5 data in 2003 and on simulated data with different degrees of missing data, we demonstrate that the MW approach alone leads to at least 17.8% reduction in mean square error (MSE) in estimating the yearly PM2.5. Moreover, the MWBME method further reduces the MSE by 8.4% to 43.7% with the proportion of incomplete data increased from 18.3% to 82.0%. The MWBME approach leads to significant reductions in estimation error and thus is recommended for epidemiological studies investigating the effect of long-term exposure to PM2.5 across large geographical domains with expected spatial non-stationarity. PMID:22739679

  13. Maximum Mass of Hybrid Stars in the Quark Bag Model

    Science.gov (United States)

    Alaverdyan, G. B.; Vartanyan, Yu. L.

    2017-12-01

    The effect of model parameters in the equation of state for quark matter on the magnitude of the maximum mass of hybrid stars is examined. Quark matter is described in terms of the extended MIT bag model including corrections for one-gluon exchange. For nucleon matter in the range of densities corresponding to the phase transition, a relativistic equation of state is used that is calculated with two-particle correlations taken into account based on using the Bonn meson-exchange potential. The Maxwell construction is used to calculate the characteristics of the first order phase transition and it is shown that for a fixed value of the strong interaction constant αs, the baryon concentrations of the coexisting phases grow monotonically as the bag constant B increases. It is shown that for a fixed value of the strong interaction constant αs, the maximum mass of a hybrid star increases as the bag constant B decreases. For a given value of the bag parameter B, the maximum mass rises as the strong interaction constant αs increases. It is shown that the configurations of hybrid stars with maximum masses equal to or exceeding the mass of the currently known most massive pulsar are possible for values of the strong interaction constant αs > 0.6 and sufficiently low values of the bag constant.

  14. Entropy correlation and entanglement for mixed states in an algebraic model

    International Nuclear Information System (INIS)

    Hou Xiwen; Chen Jinghua; Wan Mingfang; Ma Zhongqi

    2009-01-01

    As an alternative with potential connections to actual experiments, other than the systems more usually used in the field of entanglement, the dynamics of entropy correlation and entanglement between two anharmonic vibrations in a well-established algebraic model, with parameters extracted from fitting to highly excited spectral experimental results for molecules H 2 O and SO 2 , is studied in terms of the linear entropy and two negativities for various initial states that are respectively taken to be the mixed density matrices of thermal states and squeezed states on each mode. For a suitable parameter in initial states the entropies in two stretches can show positive correlation or anti-correlation. And the linear entropy of each mode is positively correlated with the negativities just for the mixed-squeezed states with small parameters in H 2 O while they do not display any correlation in other cases. For the mixed-squeezed states the negativities exhibit dominantly positive correlations with an effective mutual entropy. The differences in the linear entropy and the negativities between H 2 O and SO 2 are discussed as well. Those are useful for molecular quantum computing and quantum information processing

  15. Neuronal Entropy-Rate Feature of Entopeduncular Nucleus in Rat Model of Parkinson's Disease.

    Science.gov (United States)

    Darbin, Olivier; Jin, Xingxing; Von Wrangel, Christof; Schwabe, Kerstin; Nambu, Atsushi; Naritoku, Dean K; Krauss, Joachim K; Alam, Mesbah

    2016-03-01

    The function of the nigro-striatal pathway on neuronal entropy in the basal ganglia (BG) output nucleus, i.e. the entopeduncular nucleus (EPN) was investigated in the unilaterally 6-hyroxydopamine (6-OHDA)-lesioned rat model of Parkinson's disease (PD). In both control subjects and subjects with 6-OHDA lesion of dopamine (DA) the nigro-striatal pathway, a histological hallmark for parkinsonism, neuronal entropy in EPN was maximal in neurons with firing rates ranging between 15 and 25 Hz. In 6-OHDA lesioned rats, neuronal entropy in the EPN was specifically higher in neurons with firing rates above 25 Hz. Our data establishes that the nigro-striatal pathway controls neuronal entropy in motor circuitry and that the parkinsonian condition is associated with abnormal relationship between firing rate and neuronal entropy in BG output nuclei. The neuronal firing rates and entropy relationship provide putative relevant electrophysiological information to investigate the sensory-motor processing in normal condition and conditions such as movement disorders.

  16. Marginal Maximum Likelihood Estimation of Item Response Models in R

    Directory of Open Access Journals (Sweden)

    Matthew S. Johnson

    2007-02-01

    Full Text Available Item response theory (IRT models are a class of statistical models used by researchers to describe the response behaviors of individuals to a set of categorically scored items. The most common IRT models can be classified as generalized linear fixed- and/or mixed-effect models. Although IRT models appear most often in the psychological testing literature, researchers in other fields have successfully utilized IRT-like models in a wide variety of applications. This paper discusses the three major methods of estimation in IRT and develops R functions utilizing the built-in capabilities of the R environment to find the marginal maximum likelihood estimates of the generalized partial credit model. The currently available R packages ltm is also discussed.

  17. Maximum parsimony, substitution model, and probability phylogenetic trees.

    Science.gov (United States)

    Weng, J F; Thomas, D A; Mareels, I

    2011-01-01

    The problem of inferring phylogenies (phylogenetic trees) is one of the main problems in computational biology. There are three main methods for inferring phylogenies-Maximum Parsimony (MP), Distance Matrix (DM) and Maximum Likelihood (ML), of which the MP method is the most well-studied and popular method. In the MP method the optimization criterion is the number of substitutions of the nucleotides computed by the differences in the investigated nucleotide sequences. However, the MP method is often criticized as it only counts the substitutions observable at the current time and all the unobservable substitutions that really occur in the evolutionary history are omitted. In order to take into account the unobservable substitutions, some substitution models have been established and they are now widely used in the DM and ML methods but these substitution models cannot be used within the classical MP method. Recently the authors proposed a probability representation model for phylogenetic trees and the reconstructed trees in this model are called probability phylogenetic trees. One of the advantages of the probability representation model is that it can include a substitution model to infer phylogenetic trees based on the MP principle. In this paper we explain how to use a substitution model in the reconstruction of probability phylogenetic trees and show the advantage of this approach with examples.

  18. An information entropy model on clinical assessment of patients based on the holographic field of meridian

    Science.gov (United States)

    Wu, Jingjing; Wu, Xinming; Li, Pengfei; Li, Nan; Mao, Xiaomei; Chai, Lihe

    2017-04-01

    Meridian system is not only the basis of traditional Chinese medicine (TCM) method (e.g. acupuncture, massage), but also the core of TCM's basic theory. This paper has introduced a new informational perspective to understand the reality and the holographic field of meridian. Based on maximum information entropy principle (MIEP), a dynamic equation for the holographic field has been deduced, which reflects the evolutionary characteristics of meridian. By using self-organizing artificial neural network as algorithm, the evolutionary dynamic equation of the holographic field can be resolved to assess properties of meridians and clinically diagnose the health characteristics of patients. Finally, through some cases from clinical patients (e.g. a 30-year-old male patient, an apoplectic patient, an epilepsy patient), we use this model to assess the evolutionary properties of meridians. It is proved that this model not only has significant implications in revealing the essence of meridian in TCM, but also may play a guiding role in clinical assessment of patients based on the holographic field of meridians.

  19. Query construction, entropy, and generalization in neural-network models

    Science.gov (United States)

    Sollich, Peter

    1994-05-01

    We study query construction algorithms, which aim at improving the generalization ability of systems that learn from examples by choosing optimal, nonredundant training sets. We set up a general probabilistic framework for deriving such algorithms from the requirement of optimizing a suitable objective function; specifically, we consider the objective functions entropy (or information gain) and generalization error. For two learning scenarios, the high-low game and the linear perceptron, we evaluate the generalization performance obtained by applying the corresponding query construction algorithms and compare it to training on random examples. We find qualitative differences between the two scenarios due to the different structure of the underlying rules (nonlinear and ``noninvertible'' versus linear); in particular, for the linear perceptron, random examples lead to the same generalization ability as a sequence of queries in the limit of an infinite number of examples. We also investigate learning algorithms which are ill matched to the learning environment and find that, in this case, minimum entropy queries can in fact yield a lower generalization ability than random examples. Finally, we study the efficiency of single queries and its dependence on the learning history, i.e., on whether the previous training examples were generated randomly or by querying, and the difference between globally and locally optimal query construction.

  20. Thermodynamic modeling, energy equipartition, and nonconservation of entropy for discrete-time dynamical systems

    Directory of Open Access Journals (Sweden)

    Chellaboina Vijaysekhar

    2005-01-01

    Full Text Available We develop thermodynamic models for discrete-time large-scale dynamical systems. Specifically, using compartmental dynamical system theory, we develop energy flow models possessing energy conservation, energy equipartition, temperature equipartition, and entropy nonconservation principles for discrete-time, large-scale dynamical systems. Furthermore, we introduce a new and dual notion to entropy; namely, ectropy, as a measure of the tendency of a dynamical system to do useful work and grow more organized, and show that conservation of energy in an isolated thermodynamic system necessarily leads to nonconservation of ectropy and entropy. In addition, using the system ectropy as a Lyapunov function candidate, we show that our discrete-time, large-scale thermodynamic energy flow model has convergent trajectories to Lyapunov stable equilibria determined by the system initial subsystem energies.

  1. Entropy concentration and the empirical coding game

    NARCIS (Netherlands)

    Grünwald, P.D.

    2008-01-01

    We give a characterization of maximum entropy/minimum relative entropy inference by providing two 'strong entropy concentration' theorems. These theorems unify and generalize Jaynes''concentration phenomenon' and Van Campenhout and Cover's 'conditional limit theorem'. The theorems characterize

  2. Stock Selection for Portfolios Using Expected Utility-Entropy Decision Model

    Directory of Open Access Journals (Sweden)

    Jiping Yang

    2017-09-01

    Full Text Available Yang and Qiu proposed and then recently improved an expected utility-entropy (EU-E measure of risk and decision model. When segregation holds, Luce et al. derived an expected utility term, plus a constant multiplies the Shannon entropy as the representation of risky choices, further demonstrating the reasonability of the EU-E decision model. In this paper, we apply the EU-E decision model to selecting the set of stocks to be included in the portfolios. We first select 7 and 10 stocks from the 30 component stocks of Dow Jones Industrial Average index, and then derive and compare the efficient portfolios in the mean-variance framework. The conclusions imply that efficient portfolios composed of 7(10 stocks selected using the EU-E model with intermediate intervals of the tradeoff coefficients are more efficient than that composed of the sets of stocks selected using the expected utility model. Furthermore, the efficient portfolio of 7(10 stocks selected by the EU-E decision model have almost the same efficient frontier as that of the sample of all stocks. This suggests the necessity of incorporating both the expected utility and Shannon entropy together when taking risky decisions, further demonstrating the importance of Shannon entropy as the measure of uncertainty, as well as the applicability of the EU-E model as a decision-making model.

  3. Solutions to the Cosmic Initial Entropy Problem without Equilibrium Initial Conditions

    Directory of Open Access Journals (Sweden)

    Vihan M. Patel

    2017-08-01

    Full Text Available The entropy of the observable universe is increasing. Thus, at earlier times the entropy was lower. However, the cosmic microwave background radiation reveals an apparently high entropy universe close to thermal and chemical equilibrium. A two-part solution to this cosmic initial entropy problem is proposed. Following Penrose, we argue that the evenly distributed matter of the early universe is equivalent to low gravitational entropy. There are two competing explanations for how this initial low gravitational entropy comes about. (1 Inflation and baryogenesis produce a virtually homogeneous distribution of matter with a low gravitational entropy. (2 Dissatisfied with explaining a low gravitational entropy as the product of a ‘special’ scalar field, some theorists argue (following Boltzmann for a “more natural” initial condition in which the entire universe is in an initial equilibrium state of maximum entropy. In this equilibrium model, our observable universe is an unusual low entropy fluctuation embedded in a high entropy universe. The anthropic principle and the fluctuation theorem suggest that this low entropy region should be as small as possible and have as large an entropy as possible, consistent with our existence. However, our low entropy universe is much larger than needed to produce observers, and we see no evidence for an embedding in a higher entropy background. The initial conditions of inflationary models are as natural as the equilibrium background favored by many theorists.

  4. Configurational Information as Potentially Negative Entropy: The Triple Helix Model

    Directory of Open Access Journals (Sweden)

    Loet Leydesdorff

    2008-10-01

    Full Text Available Configurational information is generated when three or more sources of variance interact. The variations not only disturb each other relationally, but by selecting upon each other, they are also positioned in a configuration. A configuration can be stabilized and/or globalized. Different stabilizations can be considered as second-order variation, and globalization as a second-order selection. The positive manifestations and the negative selections operate upon one another by adding and reducing uncertainty, respectively. Reduction of uncertainty in a configuration can be measured in bits of information. The variables can also be considered as dimensions of the probabilistic entropy in the system(s under study. The configurational information then provides us with a measure of synergy within a complex system. For example, the knowledge base of an economy can be considered as such a synergy in the otherwise virtual (that is, fourth dimension of a regime

  5. Software Code Smell Prediction Model Using Shannon, Rényi and Tsallis Entropies

    Directory of Open Access Journals (Sweden)

    Aakanshi Gupta

    2018-05-01

    Full Text Available The current era demands high quality software in a limited time period to achieve new goals and heights. To meet user requirements, the source codes undergo frequent modifications which can generate the bad smells in software that deteriorate the quality and reliability of software. Source code of the open source software is easily accessible by any developer, thus frequently modifiable. In this paper, we have proposed a mathematical model to predict the bad smells using the concept of entropy as defined by the Information Theory. Open-source software Apache Abdera is taken into consideration for calculating the bad smells. Bad smells are collected using a detection tool from sub components of the Apache Abdera project, and different measures of entropy (Shannon, Rényi and Tsallis entropy. By applying non-linear regression techniques, the bad smells that can arise in the future versions of software are predicted based on the observed bad smells and entropy measures. The proposed model has been validated using goodness of fit parameters (prediction error, bias, variation, and Root Mean Squared Prediction Error (RMSPE. The values of model performance statistics ( R 2 , adjusted R 2 , Mean Square Error (MSE and standard error also justify the proposed model. We have compared the results of the prediction model with the observed results on real data. The results of the model might be helpful for software development industries and future researchers.

  6. Large time behavior of entropy solutions to one-dimensional unipolar hydrodynamic model for semiconductor devices

    Science.gov (United States)

    Huang, Feimin; Li, Tianhong; Yu, Huimin; Yuan, Difan

    2018-06-01

    We are concerned with the global existence and large time behavior of entropy solutions to the one-dimensional unipolar hydrodynamic model for semiconductors in the form of Euler-Poisson equations in a bounded interval. In this paper, we first prove the global existence of entropy solution by vanishing viscosity and compensated compactness framework. In particular, the solutions are uniformly bounded with respect to space and time variables by introducing modified Riemann invariants and the theory of invariant region. Based on the uniform estimates of density, we further show that the entropy solution converges to the corresponding unique stationary solution exponentially in time. No any smallness condition is assumed on the initial data and doping profile. Moreover, the novelty in this paper is about the unform bound with respect to time for the weak solutions of the isentropic Euler-Poisson system.

  7. Entropy squeezing for a two-level atom in the Jaynes-Cummings model with an intensity-depend coupling

    Institute of Scientific and Technical Information of China (English)

    李春先; 方卯发

    2003-01-01

    We study the squeezing for a two-level atom in the Jaynes-Cummings model with intensity-dependent coupling using quantum information entropy, and examine the influences of the initial state of the system on the squeezed component number and direction of the information entropy squeezing. Our results show that, the squeezed component number depends on the atomic initial distribution angle, while the squeezed direction is determined by both the phases of the atom and the field for the information entropy squeezing. Quantum information entropy is shown to be a remarkable precision measure for atomic squeezing.

  8. Entropy squeezing for a two—level atom in the Jaynes—Cummings model with an intensity—depend coupling

    Institute of Scientific and Technical Information of China (English)

    李春先; 方卯发; 等

    2003-01-01

    We study the squeezing for a two-level atom in the Jaynes-Cumings model with intensity-dependent coupling using quantum information entropy,and examine the influences of the initial state of the system on the squeezed component number and direction of the information entropy squeezing.Our results show that,the squeezed component number depends on the atomic initial distribution angle,while the squeezed direction is determined by both the phases of the atom and the field for the information entropy squeezing.Quantum information entropy is shown to be a remarkable precision measure for atomic squeezing.

  9. Esscher transforms and the minimal entropy martingale measure for exponential Lévy models

    DEFF Research Database (Denmark)

    Hubalek, Friedrich; Sgarra, C.

    In this paper we offer a systematic survey and comparison of the Esscher martingale transform for linear processes, the Esscher martingale transform for exponential processes, and the minimal entropy martingale measure for exponential lévy models and present some new results in order to give...

  10. Modeling Mediterranean Ocean climate of the Last Glacial Maximum

    Directory of Open Access Journals (Sweden)

    U. Mikolajewicz

    2011-03-01

    Full Text Available A regional ocean general circulation model of the Mediterranean is used to study the climate of the Last Glacial Maximum. The atmospheric forcing for these simulations has been derived from simulations with an atmospheric general circulation model, which in turn was forced with surface conditions from a coarse resolution earth system model. The model is successful in reproducing the general patterns of reconstructed sea surface temperature anomalies with the strongest cooling in summer in the northwestern Mediterranean and weak cooling in the Levantine, although the model underestimates the extent of the summer cooling in the western Mediterranean. However, there is a strong vertical gradient associated with this pattern of summer cooling, which makes the comparison with reconstructions complicated. The exchange with the Atlantic is decreased to roughly one half of its present value, which can be explained by the shallower Strait of Gibraltar as a consequence of lower global sea level. This reduced exchange causes a strong increase of salinity in the Mediterranean in spite of reduced net evaporation.

  11. [GSH fermentation process modeling using entropy-criterion based RBF neural network model].

    Science.gov (United States)

    Tan, Zuoping; Wang, Shitong; Deng, Zhaohong; Du, Guocheng

    2008-05-01

    The prediction accuracy and generalization of GSH fermentation process modeling are often deteriorated by noise existing in the corresponding experimental data. In order to avoid this problem, we present a novel RBF neural network modeling approach based on entropy criterion. It considers the whole distribution structure of the training data set in the parameter learning process compared with the traditional MSE-criterion based parameter learning, and thus effectively avoids the weak generalization and over-learning. Then the proposed approach is applied to the GSH fermentation process modeling. Our results demonstrate that this proposed method has better prediction accuracy, generalization and robustness such that it offers a potential application merit for the GSH fermentation process modeling.

  12. On the Entropy Based Associative Memory Model with Higher-Order Correlations

    Directory of Open Access Journals (Sweden)

    Masahiro Nakagawa

    2010-01-01

    Full Text Available In this paper, an entropy based associative memory model will be proposed and applied to memory retrievals with an orthogonal learning model so as to compare with the conventional model based on the quadratic Lyapunov functional to be minimized during the retrieval process. In the present approach, the updating dynamics will be constructed on the basis of the entropy minimization strategy which may be reduced asymptotically to the above-mentioned conventional dynamics as a special case ignoring the higher-order correlations. According to the introduction of the entropy functional, one may involve higer-order correlation effects between neurons in a self-contained manner without any heuristic coupling coefficients as in the conventional manner. In fact we shall show such higher order coupling tensors are to be uniquely determined in the framework of the entropy based approach. From numerical results, it will be found that the presently proposed novel approach realizes much larger memory capacity than that of the quadratic Lyapunov functional approach, e.g., associatron.

  13. Entropy and equilibrium via games of complexity

    Science.gov (United States)

    Topsøe, Flemming

    2004-09-01

    It is suggested that thermodynamical equilibrium equals game theoretical equilibrium. Aspects of this thesis are discussed. The philosophy is consistent with maximum entropy thinking of Jaynes, but goes one step deeper by deriving the maximum entropy principle from an underlying game theoretical principle. The games introduced are based on measures of complexity. Entropy is viewed as minimal complexity. It is demonstrated that Tsallis entropy ( q-entropy) and Kaniadakis entropy ( κ-entropy) can be obtained in this way, based on suitable complexity measures. A certain unifying effect is obtained by embedding these measures in a two-parameter family of entropy functions.

  14. Maximum likelihood approach for several stochastic volatility models

    International Nuclear Information System (INIS)

    Camprodon, Jordi; Perelló, Josep

    2012-01-01

    Volatility measures the amplitude of price fluctuations. Despite it being one of the most important quantities in finance, volatility is not directly observable. Here we apply a maximum likelihood method which assumes that price and volatility follow a two-dimensional diffusion process where volatility is the stochastic diffusion coefficient of the log-price dynamics. We apply this method to the simplest versions of the expOU, the OU and the Heston stochastic volatility models and we study their performance in terms of the log-price probability, the volatility probability, and its Mean First-Passage Time. The approach has some predictive power on the future returns amplitude by only knowing the current volatility. The assumed models do not consider long-range volatility autocorrelation and the asymmetric return-volatility cross-correlation but the method still yields very naturally these two important stylized facts. We apply the method to different market indices and with a good performance in all cases. (paper)

  15. Fault Detection and Diagnosis for Gas Turbines Based on a Kernelized Information Entropy Model

    Directory of Open Access Journals (Sweden)

    Weiying Wang

    2014-01-01

    Full Text Available Gas turbines are considered as one kind of the most important devices in power engineering and have been widely used in power generation, airplanes, and naval ships and also in oil drilling platforms. However, they are monitored without man on duty in the most cases. It is highly desirable to develop techniques and systems to remotely monitor their conditions and analyze their faults. In this work, we introduce a remote system for online condition monitoring and fault diagnosis of gas turbine on offshore oil well drilling platforms based on a kernelized information entropy model. Shannon information entropy is generalized for measuring the uniformity of exhaust temperatures, which reflect the overall states of the gas paths of gas turbine. In addition, we also extend the entropy to compute the information quantity of features in kernel spaces, which help to select the informative features for a certain recognition task. Finally, we introduce the information entropy based decision tree algorithm to extract rules from fault samples. The experiments on some real-world data show the effectiveness of the proposed algorithms.

  16. Fault detection and diagnosis for gas turbines based on a kernelized information entropy model.

    Science.gov (United States)

    Wang, Weiying; Xu, Zhiqiang; Tang, Rui; Li, Shuying; Wu, Wei

    2014-01-01

    Gas turbines are considered as one kind of the most important devices in power engineering and have been widely used in power generation, airplanes, and naval ships and also in oil drilling platforms. However, they are monitored without man on duty in the most cases. It is highly desirable to develop techniques and systems to remotely monitor their conditions and analyze their faults. In this work, we introduce a remote system for online condition monitoring and fault diagnosis of gas turbine on offshore oil well drilling platforms based on a kernelized information entropy model. Shannon information entropy is generalized for measuring the uniformity of exhaust temperatures, which reflect the overall states of the gas paths of gas turbine. In addition, we also extend the entropy to compute the information quantity of features in kernel spaces, which help to select the informative features for a certain recognition task. Finally, we introduce the information entropy based decision tree algorithm to extract rules from fault samples. The experiments on some real-world data show the effectiveness of the proposed algorithms.

  17. Multiscale Shannon's Entropy Modeling of Orientation and Distance in Steel Fiber Micro-Tomography Data.

    Science.gov (United States)

    Chiverton, John P; Ige, Olubisi; Barnett, Stephanie J; Parry, Tony

    2017-11-01

    This paper is concerned with the modeling and analysis of the orientation and distance between steel fibers in X-ray micro-tomography data. The advantage of combining both orientation and separation in a model is that it helps provide a detailed understanding of how the steel fibers are arranged, which is easy to compare. The developed models are designed to summarize the randomness of the orientation distribution of the steel fibers both locally and across an entire volume based on multiscale entropy. Theoretical modeling, simulation, and application to real imaging data are shown here. The theoretical modeling of multiscale entropy for orientation includes a proof showing the final form of the multiscale taken over a linear range of scales. A series of image processing operations are also included to overcome interslice connectivity issues to help derive the statistical descriptions of the orientation distributions of the steel fibers. The results demonstrate that multiscale entropy provides unique insights into both simulated and real imaging data of steel fiber reinforced concrete.

  18. Studies on entanglement entropy for Hubbard model with hole-doping and external magnetic field [rapid communication

    Science.gov (United States)

    Yao, K. L.; Li, Y. C.; Sun, X. Z.; Liu, Q. M.; Qin, Y.; Fu, H. H.; Gao, G. Y.

    2005-10-01

    By using the density matrix renormalization group (DMRG) method for the one-dimensional (1D) Hubbard model, we have studied the von Neumann entropy of a quantum system, which describes the entanglement of the system block and the rest of the chain. It is found that there is a close relation between the entanglement entropy and properties of the system. The hole-doping can alter the charge charge and spin spin interactions, resulting in charge polarization along the chain. By comparing the results before and after the doping, we find that doping favors increase of the von Neumann entropy and thus also favors the exchange of information along the chain. Furthermore, we calculated the spin and entropy distribution in external magnetic filed. It is confirmed that both the charge charge and the spin spin interactions affect the exchange of information along the chain, making the entanglement entropy redistribute.

  19. Backward transfer entropy: Informational measure for detecting hidden Markov models and its interpretations in thermodynamics, gambling and causality

    Science.gov (United States)

    Ito, Sosuke

    2016-01-01

    The transfer entropy is a well-established measure of information flow, which quantifies directed influence between two stochastic time series and has been shown to be useful in a variety fields of science. Here we introduce the transfer entropy of the backward time series called the backward transfer entropy, and show that the backward transfer entropy quantifies how far it is from dynamics to a hidden Markov model. Furthermore, we discuss physical interpretations of the backward transfer entropy in completely different settings of thermodynamics for information processing and the gambling with side information. In both settings of thermodynamics and the gambling, the backward transfer entropy characterizes a possible loss of some benefit, where the conventional transfer entropy characterizes a possible benefit. Our result implies the deep connection between thermodynamics and the gambling in the presence of information flow, and that the backward transfer entropy would be useful as a novel measure of information flow in nonequilibrium thermodynamics, biochemical sciences, economics and statistics. PMID:27833120

  20. Reconstructing interacting entropy-corrected holographic scalar field models of dark energy in the non-flat universe

    Energy Technology Data Exchange (ETDEWEB)

    Karami, K; Khaledian, M S [Department of Physics, University of Kurdistan, Pasdaran Street, Sanandaj (Iran, Islamic Republic of); Jamil, Mubasher, E-mail: KKarami@uok.ac.ir, E-mail: MS.Khaledian@uok.ac.ir, E-mail: mjamil@camp.nust.edu.pk [Center for Advanced Mathematics and Physics (CAMP), National University of Sciences and Technology (NUST), Islamabad (Pakistan)

    2011-02-15

    Here we consider the entropy-corrected version of the holographic dark energy (DE) model in the non-flat universe. We obtain the equation of state parameter in the presence of interaction between DE and dark matter. Moreover, we reconstruct the potential and the dynamics of the quintessence, tachyon, K-essence and dilaton scalar field models according to the evolutionary behavior of the interacting entropy-corrected holographic DE model.

  1. Prediction Model of Collapse Risk Based on Information Entropy and Distance Discriminant Analysis Method

    Directory of Open Access Journals (Sweden)

    Hujun He

    2017-01-01

    Full Text Available The prediction and risk classification of collapse is an important issue in the process of highway construction in mountainous regions. Based on the principles of information entropy and Mahalanobis distance discriminant analysis, we have produced a collapse hazard prediction model. We used the entropy measure method to reduce the influence indexes of the collapse activity and extracted the nine main indexes affecting collapse activity as the discriminant factors of the distance discriminant analysis model (i.e., slope shape, aspect, gradient, and height, along with exposure of the structural face, stratum lithology, relationship between weakness face and free face, vegetation cover rate, and degree of rock weathering. We employ postearthquake collapse data in relation to construction of the Yingxiu-Wolong highway, Hanchuan County, China, as training samples for analysis. The results were analyzed using the back substitution estimation method, showing high accuracy and no errors, and were the same as the prediction result of uncertainty measure. Results show that the classification model based on information entropy and distance discriminant analysis achieves the purpose of index optimization and has excellent performance, high prediction accuracy, and a zero false-positive rate. The model can be used as a tool for future evaluation of collapse risk.

  2. Partition Function and Configurational Entropy in Non-Equilibrium States: A New Theoretical Model

    Directory of Open Access Journals (Sweden)

    Akira Takada

    2018-03-01

    Full Text Available A new model of non-equilibrium thermodynamic states has been investigated on the basis of the fact that all thermodynamic variables can be derived from partition functions. We have thus attempted to define partition functions for non-equilibrium conditions by introducing the concept of pseudo-temperature distributions. These pseudo-temperatures are configurational in origin and distinct from kinetic (phonon temperatures because they refer to the particular fragments of the system with specific energies. This definition allows thermodynamic states to be described either for equilibrium or non-equilibrium conditions. In addition; a new formulation of an extended canonical partition function; internal energy and entropy are derived from this new temperature definition. With this new model; computational experiments are performed on simple non-interacting systems to investigate cooling and two distinct relaxational effects in terms of the time profiles of the partition function; internal energy and configurational entropy.

  3. On a Generalized Entropy Measure Leading to the Pathway Model with a Preliminary Application to Solar Neutrino Data

    Directory of Open Access Journals (Sweden)

    Hans J. Haubold

    2013-09-01

    Full Text Available An entropy for the scalar variable case, parallel to Havrda-Charvat entropy, was introduced by the first author, and the properties and its connection to Tsallis non-extensive statistical mechanics and the Mathai pathway model were examined by the authors in previous papers. In the current paper, we extend the entropy to cover the scalar case, multivariable case, and matrix variate case. Then, this measure is optimized under different types of restrictions, and a number of models in the multivariable case and matrix variable case are obtained. Connections of these models to problems in statistical and physical sciences are pointed out. An application of the simplest case of the pathway model to the interpretation of solar neutrino data by applying standard deviation analysis and diffusion entropy analysis is provided.

  4. Absorption and scattering coefficients estimation in two-dimensional participating media using the generalized maximum entropy and Levenberg-Marquardt methods; Estimacion del coeficiente de absorcion y dispersion en medios participantes bidimensionales utilizando el metodo de maxima entropia generalizada y el metodo Levenberg-Marquardt

    Energy Technology Data Exchange (ETDEWEB)

    Berrocal T, Mariella J. [Universidade Federal, Rio de Janeiro, RJ (Brazil). Coordenacao dos Programas de Pos-graduacao de Engenharia. Programa de Engenharia Nuclear]|[Universidad Nacional de Ingenieria, Lima (Peru); Roberty, Nilson C. [Universidade Federal, Rio de Janeiro, RJ (Brazil). Coordenacao dos Programas de Pos-graduacao de Engenharia. Programa de Engenharia Nuclear; Silva Neto, Antonio J. [Universidade do Estado, Nova Friburgo, RJ (Brazil). Instituto Politecnico. Dept. de Engenharia Mecanica e Energia]|[Universidade Federal, Rio de Janeiro, RJ (Brazil). Coordenacao dos Programas de Pos-graduacao de Engenharia. Programa de Engenharia Nuclear

    2002-07-01

    The solution of inverse problems in participating media where there is emission, absorption and dispersion of the radiation possesses several applications in engineering and medicine. The objective of this work is to estimative the coefficients of absorption and dispersion in two-dimensional heterogeneous participating media, using in independent form the Generalized Maximum Entropy and Levenberg Marquardt methods. Both methods are based on the solution of the direct problem that is modeled by the Boltzmann equation in cartesian geometry. Some cases testes are presented. (author)

  5. An improved thin film brick-wall model of black hole entropy

    CERN Document Server

    Liu Wen Biao

    2001-01-01

    The authors improve the brick-wall model to take only the contribution of a thin film near the event horizon into account. This improvement not only gives them a satisfactory result, but also avoids some drawbacks in the original brick-wall method such as the little mass approximation, neglecting logarithm term, and taking the term L/sup 3/ as the contribution of the vacuum surrounding a black hole. It is found that there is an intrinsic relation between the event horizon and the entropy. The event horizon is the characteristic of a black hole, so the entropy calculating of a black hole is also naturally related to its horizon. (12 refs).

  6. Evaluation of Intensive Construction Land Use in the Emerging City Based on PSR-Entropy model

    Science.gov (United States)

    Jia, Yuanyuan; Lei, Guangyu

    2018-01-01

    A comprehensive understanding of emerging city land utilization and the evaluation of intensive land use in the Emerging City will provide the comprehensive and reliable technical basis for the planning and management. It is an important node. According to the Han cheng from 2008 to 2016 years of land use, based on PSR-Entropy model of land use evaluation system, using entropy method to determine the index weight, the introduction of comprehensive index method to evaluate the degree of land use. The results show that the intensive land use comprehensive evaluation index of Han cheng increased from 2008 to 2015, but the land intensive use can not achieve the standards. The potential of further enhancing space is relatively large.

  7. Study of the droplet size of sprays generated by swirl nozzles dedicated to gasoline direct injection: measurement and application of the maximum entropy formalism; Etude de la granulometrie des sprays produits par des injecteurs a swirl destines a l'injection directe essence: mesures et application du formalisme d'entropie maximum

    Energy Technology Data Exchange (ETDEWEB)

    Boyaval, S.

    2000-06-15

    This PhD presents a study on a series of high pressure swirl atomizers dedicated to Gasoline Direct Injection (GDI). Measurements are performed in stationary and pulsed working conditions. A great aspect of this thesis is the development of an original experimental set-up to correct multiple light scattering that biases the drop size distributions measurements obtained with a laser diffraction technique (Malvern 2600D). This technique allows to perform a study of drop size characteristics near the injector tip. Correction factors on drop size characteristics and on the diffracted intensities are defined from the developed procedure. Another point consists in applying the Maximum Entropy Formalism (MEF) to calculate drop size distributions. Comparisons between experimental distributions corrected with the correction factors and the calculated distributions show good agreement. This work points out that the mean diameter D{sub 43}, which is also the mean of the volume drop size distribution, and the relative volume span factor {delta}{sub v} are important characteristics of volume drop size distributions. The end of the thesis proposes to determine local drop size characteristics from a new development of deconvolution technique for line-of-sight scattering measurements. The first results show reliable behaviours of radial evolution of local characteristics. In GDI application, we notice that the critical point is the opening stage of the injection. This study shows clearly the effects of injection pressure and nozzle internal geometry on the working characteristics of these injectors, in particular, the influence of the pre-spray. This work points out important behaviours that the improvement of GDI principle ought to consider. (author)

  8. A Software Technology Transition Entropy Based Engineering Model

    Science.gov (United States)

    2002-03-01

    Systems Basics, p273). (Prigogine 1997 p81). It is not the place of this research to provide a mathematical formalism with theorems and lemmas. Rather...science). The ancient philosophers, 27 Pythagoras , Protagoras, Socrates, and Plato start the first discourse (the message) that has continued...unpacking of the technology "message" from Pythagoras . This process is characterized by accumulation learning, modeled by learning curves in

  9. Modelling information flow along the human connectome using maximum flow.

    Science.gov (United States)

    Lyoo, Youngwook; Kim, Jieun E; Yoon, Sujung

    2018-01-01

    The human connectome is a complex network that transmits information between interlinked brain regions. Using graph theory, previously well-known network measures of integration between brain regions have been constructed under the key assumption that information flows strictly along the shortest paths possible between two nodes. However, it is now apparent that information does flow through non-shortest paths in many real-world networks such as cellular networks, social networks, and the internet. In the current hypothesis, we present a novel framework using the maximum flow to quantify information flow along all possible paths within the brain, so as to implement an analogy to network traffic. We hypothesize that the connection strengths of brain networks represent a limit on the amount of information that can flow through the connections per unit of time. This allows us to compute the maximum amount of information flow between two brain regions along all possible paths. Using this novel framework of maximum flow, previous network topological measures are expanded to account for information flow through non-shortest paths. The most important advantage of the current approach using maximum flow is that it can integrate the weighted connectivity data in a way that better reflects the real information flow of the brain network. The current framework and its concept regarding maximum flow provides insight on how network structure shapes information flow in contrast to graph theory, and suggests future applications such as investigating structural and functional connectomes at a neuronal level. Copyright © 2017 Elsevier Ltd. All rights reserved.

  10. RNA Thermodynamic Structural Entropy.

    Science.gov (United States)

    Garcia-Martin, Juan Antonio; Clote, Peter

    2015-01-01

    Conformational entropy for atomic-level, three dimensional biomolecules is known experimentally to play an important role in protein-ligand discrimination, yet reliable computation of entropy remains a difficult problem. Here we describe the first two accurate and efficient algorithms to compute the conformational entropy for RNA secondary structures, with respect to the Turner energy model, where free energy parameters are determined from UV absorption experiments. An algorithm to compute the derivational entropy for RNA secondary structures had previously been introduced, using stochastic context free grammars (SCFGs). However, the numerical value of derivational entropy depends heavily on the chosen context free grammar and on the training set used to estimate rule probabilities. Using data from the Rfam database, we determine that both of our thermodynamic methods, which agree in numerical value, are substantially faster than the SCFG method. Thermodynamic structural entropy is much smaller than derivational entropy, and the correlation between length-normalized thermodynamic entropy and derivational entropy is moderately weak to poor. In applications, we plot the structural entropy as a function of temperature for known thermoswitches, such as the repression of heat shock gene expression (ROSE) element, we determine that the correlation between hammerhead ribozyme cleavage activity and total free energy is improved by including an additional free energy term arising from conformational entropy, and we plot the structural entropy of windows of the HIV-1 genome. Our software RNAentropy can compute structural entropy for any user-specified temperature, and supports both the Turner'99 and Turner'04 energy parameters. It follows that RNAentropy is state-of-the-art software to compute RNA secondary structure conformational entropy. Source code is available at https://github.com/clotelab/RNAentropy/; a full web server is available at http

  11. RNA Thermodynamic Structural Entropy.

    Directory of Open Access Journals (Sweden)

    Juan Antonio Garcia-Martin

    Full Text Available Conformational entropy for atomic-level, three dimensional biomolecules is known experimentally to play an important role in protein-ligand discrimination, yet reliable computation of entropy remains a difficult problem. Here we describe the first two accurate and efficient algorithms to compute the conformational entropy for RNA secondary structures, with respect to the Turner energy model, where free energy parameters are determined from UV absorption experiments. An algorithm to compute the derivational entropy for RNA secondary structures had previously been introduced, using stochastic context free grammars (SCFGs. However, the numerical value of derivational entropy depends heavily on the chosen context free grammar and on the training set used to estimate rule probabilities. Using data from the Rfam database, we determine that both of our thermodynamic methods, which agree in numerical value, are substantially faster than the SCFG method. Thermodynamic structural entropy is much smaller than derivational entropy, and the correlation between length-normalized thermodynamic entropy and derivational entropy is moderately weak to poor. In applications, we plot the structural entropy as a function of temperature for known thermoswitches, such as the repression of heat shock gene expression (ROSE element, we determine that the correlation between hammerhead ribozyme cleavage activity and total free energy is improved by including an additional free energy term arising from conformational entropy, and we plot the structural entropy of windows of the HIV-1 genome. Our software RNAentropy can compute structural entropy for any user-specified temperature, and supports both the Turner'99 and Turner'04 energy parameters. It follows that RNAentropy is state-of-the-art software to compute RNA secondary structure conformational entropy. Source code is available at https://github.com/clotelab/RNAentropy/; a full web server is available at http

  12. Anelastic Models of Fully-Convective Stars: Differential Rotation, Meridional Circulation and Residual Entropy

    Science.gov (United States)

    Sainsbury-Martinez, Felix; Browning, Matthew; Miesch, Mark; Featherstone, Nicholas A.

    2018-01-01

    Low-Mass stars are typically fully convective, and as such their dynamics may differ significantly from sun-like stars. Here we present a series of 3D anelastic HD and MHD simulations of fully convective stars, designed to investigate how the meridional circulation, the differential rotation, and residual entropy are affected by both varying stellar parameters, such as the luminosity or the rotation rate, and by the presence of a magnetic field. We also investigate, more specifically, a theoretical model in which isorotation contours and residual entropy (σ‧ = σ ‑ σ(r)) are intrinsically linked via the thermal wind equation (as proposed in the Solar context by Balbus in 2009). We have selected our simulation parameters in such as way as to span the transition between Solar-like differential rotation (fast equator + slow poles) and ‘anti-Solar’ differential rotation (slow equator + fast poles), as characterised by the convective Rossby number and △Ω. We illustrate the transition from single-celled to multi-celled MC profiles, and from positive to negative latitudinal entropy gradients. We show that an extrapolation involving both TWB and the σ‧/Ω link provides a reasonable estimate for the interior profile of our fully convective stars. Finally, we also present a selection of MHD simulations which exhibit an almost unsuppressed differential rotation profile, with energy balances remaining dominated by kinetic components.

  13. Modeling and Analysis of Entropy Generation in Light Heating of Nanoscaled Silicon and Germanium Thin Films

    Directory of Open Access Journals (Sweden)

    José Ernesto Nájera-Carpio

    2015-07-01

    Full Text Available In this work, the irreversible processes in light heating of Silicon (Si and Germanium (Ge thin films are examined. Each film is exposed to light irradiation with radiative and convective boundary conditions. Heat, electron and hole transport and generation-recombination processes of electron-hole pairs are studied in terms of a phenomenological model obtained from basic principles of irreversible thermodynamics. We present an analysis of the contributions to the entropy production in the stationary state due to the dissipative effects associated with electron and hole transport, generation-recombination of electron-hole pairs as well as heat transport. The most significant contribution to the entropy production comes from the interaction of light with the medium in both Si and Ge. This interaction includes two processes, namely, the generation of electron-hole pairs and the transferring of energy from the absorbed light to the lattice. In Si the following contribution in magnitude comes from the heat transport. In Ge all the remaining contributions to entropy production have nearly the same order of magnitude. The results are compared and explained addressing the differences in the magnitude of the thermodynamic forces, Onsager’s coefficients and transport properties of Si and Ge.

  14. A Complementary Vision Strategy for Autonomous Robots in Underground Terrains using SRM and Entropy Models

    Directory of Open Access Journals (Sweden)

    Omowunmi Isafiade

    2013-09-01

    Full Text Available This work investigates robots' perception in underground terrains (mines and tunnels using statistical region merging (SRM and the entropy models. A probabilistic approach based on the local entropy is employed. The entropy is measured within a fixed window on a stream of mine and tunnel frames to compute features used in the segmentation process, while SRM reconstructs the main structural components of an imagery by a simple but effective statistical analysis. An investigation is conducted on different regions of the mine, such as the shaft, stope and gallery, using publicly available mine frames, with a stream of locally captured mine images. Furthermore, an investigation is also conducted on a stream of dynamic underground tunnel image frames, using the XBOX Kinect 3D sensors. The Kinect sensors produce streams of red, green and blue (RGB and depth images of 640 × 480 resolution at 30 frames per second. Integrating the depth information into drivability gives a strong cue to the analysis, which detects 3D results augmenting drivable and non-drivable regions in 2D. The results of the 2D and 3D experiment with different terrains, mines and tunnels, together with the qualitative and quantitative evaluations, reveal that a good drivable region can be detected in dynamic underground terrains.

  15. Spatial Estimation of Losses Attributable to Meteorological Disasters in a Specific Area (105.0°E–115.0°E, 25°N–35°N Using Bayesian Maximum Entropy and Partial Least Squares Regression

    Directory of Open Access Journals (Sweden)

    F. S. Zhang

    2016-01-01

    Full Text Available The spatial mapping of losses attributable to such disasters is now well established as a means of describing the spatial patterns of disaster risk, and it has been shown to be suitable for many types of major meteorological disasters. However, few studies have been carried out by developing a regression model to estimate the effects of the spatial distribution of meteorological factors on losses associated with meteorological disasters. In this study, the proposed approach is capable of the following: (a estimating the spatial distributions of seven meteorological factors using Bayesian maximum entropy, (b identifying the four mapping methods used in this research with the best performance based on the cross validation, and (c establishing a fitted model between the PLS components and disaster losses information using partial least squares regression within a specific research area. The results showed the following: (a best mapping results were produced by multivariate Bayesian maximum entropy with probabilistic soft data; (b the regression model using three PLS components, extracted from seven meteorological factors by PLS method, was the most predictive by means of PRESS/SS test; (c northern Hunan Province sustains the most damage, and southeastern Gansu Province and western Guizhou Province sustained the least.

  16. An 18 Moments Model for Dense Gases: Entropy and Galilean Relativity Principles without Expansions

    Directory of Open Access Journals (Sweden)

    M. Cristina Carrisi

    2015-01-01

    Full Text Available The 14 moments model for dense gases, introduced in the last few years by Arima, Taniguchi, Ruggeri and Sugiyama, is here extended up to 18 moments. They have found the closure of the balance equations up to a finite order with respect to equilibrium; it is also possible to impose for that model the entropy and Galilean relativity principles up to whatever order with respect to equilibrium, but by using Taylor’s expansion. Here, the exact solution is found, without expansions, but a bigger number of moments has to be considered and reasons will be shown suggesting that this number is at least 18.

  17. More dimensions: Less entropy

    International Nuclear Information System (INIS)

    Kolb, E.W.; Lindley, D.; Seckel, D.

    1984-01-01

    For a cosmological model with d noncompact and D compact spatial dimensions and symmetry R 1 x S/sup d/ x S/sup D/, we calculate the entropy produced in d dimensions due to the compactification of D dimensions and show it too small to be of cosmological interest. Although insufficient entropy is produced in the model we study, the contraction of extra dimensions does lead to entropy production. We discuss modifications of our assumptions, including changing our condition for decoupling of the extra dimensions, which may lead to a large entropy production and change our conclusions

  18. Adjoint entropy vs topological entropy

    OpenAIRE

    Giordano Bruno, Anna

    2012-01-01

    Recently the adjoint algebraic entropy of endomorphisms of abelian groups was introduced and studied. We generalize the notion of adjoint entropy to continuous endomorphisms of topological abelian groups. Indeed, the adjoint algebraic entropy is defined using the family of all finite-index subgroups, while we take only the subfamily of all open finite-index subgroups to define the topological adjoint entropy. This allows us to compare the (topological) adjoint entropy with the known topologic...

  19. Transplanckian entanglement entropy

    International Nuclear Information System (INIS)

    Chang, Darwin; Chu, C.-S.; Lin Fengli

    2004-01-01

    The entanglement entropy of the event horizon is known to be plagued by the UV divergence due to the infinitely blue-shifted near horizon modes. In this Letter we calculate the entanglement entropy using the transplanckian dispersion relation, which has been proposed to model the quantum gravity effects. We show that, very generally, the entropy is rendered UV finite due to the suppression of high energy modes effected by the transplanckian dispersion relation

  20. Properties of Linear Entropy in k-Photon Jaynes-Cummings Model with Stark Shift and Kerr-Like Medium

    International Nuclear Information System (INIS)

    Liao Qinghong; Wang Yueyuan; Liu Shutian; Ahmad, Muhammad Ashfaq

    2010-01-01

    The time evolution of the linear entropy of an atom in k-photon Jaynes-Cummings model is investigated taking into consideration Stark shift and Kerr-like medium. The effect of both the Stark shift and Kerr-like medium on the linear entropy is analyzed using a numerical technique for the field initially in coherent state and in even coherent state. The results show that the presence of the Kerr-like medium and Stark shift has an important effect on the properties of the entropy and entanglement. It is also shown that the setting of the initial state plays a significant role in the evolution of the linear entropy and entanglement. (electromagnetism, optics, acoustics, heat transfer, classical mechanics, and fluid dynamics)

  1. Quasi-exact solvability and entropies of the one-dimensional regularised Calogero model

    Science.gov (United States)

    Pont, Federico M.; Osenda, Omar; Serra, Pablo

    2018-05-01

    The Calogero model can be regularised through the introduction of a cutoff parameter which removes the divergence in the interaction term. In this work we show that the one-dimensional two-particle regularised Calogero model is quasi-exactly solvable and that for certain values of the Hamiltonian parameters the eigenfunctions can be written in terms of Heun’s confluent polynomials. These eigenfunctions are such that the reduced density matrix of the two-particle density operator can be obtained exactly as well as its entanglement spectrum. We found that the number of non-zero eigenvalues of the reduced density matrix is finite in these cases. The limits for the cutoff distance going to zero (Calogero) and infinity are analysed and all the previously obtained results for the Calogero model are reproduced. Once the exact eigenfunctions are obtained, the exact von Neumann and Rényi entanglement entropies are studied to characterise the physical traits of the model. The quasi-exactly solvable character of the model is assessed studying the numerically calculated Rényi entropy and entanglement spectrum for the whole parameter space.

  2. Applications of Entropy in Finance: A Review

    Directory of Open Access Journals (Sweden)

    Guanqun Tong

    2013-11-01

    Full Text Available Although the concept of entropy is originated from thermodynamics, its concepts and relevant principles, especially the principles of maximum entropy and minimum cross-entropy, have been extensively applied in finance. In this paper, we review the concepts and principles of entropy, as well as their applications in the field of finance, especially in portfolio selection and asset pricing. Furthermore, we review the effects of the applications of entropy and compare them with other traditional and new methods.

  3. Periodic matrix population models: growth rate, basic reproduction number, and entropy.

    Science.gov (United States)

    Bacaër, Nicolas

    2009-10-01

    This article considers three different aspects of periodic matrix population models. First, a formula for the sensitivity analysis of the growth rate lambda is obtained that is simpler than the one obtained by Caswell and Trevisan. Secondly, the formula for the basic reproduction number R0 in a constant environment is generalized to the case of a periodic environment. Some inequalities between lambda and R0 proved by Cushing and Zhou are also generalized to the periodic case. Finally, we add some remarks on Demetrius' notion of evolutionary entropy H and its relationship to the growth rate lambda in the periodic case.

  4. Entropy and transverse section reconstruction

    International Nuclear Information System (INIS)

    Gullberg, G.T.

    1976-01-01

    A new approach to the reconstruction of a transverse section using projection data from multiple views incorporates the concept of maximum entropy. The principle of maximizing information entropy embodies the assurance of minimizing bias or prejudice in the reconstruction. Using maximum entropy is a necessary condition for the reconstructed image. This entropy criterion is most appropriate for 3-D reconstruction of objects from projections where the system is underdetermined or the data are limited statistically. This is the case in nuclear medicine time limitations in patient studies do not yield sufficient projections

  5. EEG entropy measures in anesthesia

    Directory of Open Access Journals (Sweden)

    Zhenhu eLiang

    2015-02-01

    Full Text Available Objective: Entropy algorithms have been widely used in analyzing EEG signals during anesthesia. However, a systematic comparison of these entropy algorithms in assessing anesthesia drugs’ effect is lacking. In this study, we compare the capability of twelve entropy indices for monitoring depth of anesthesia (DoA and detecting the burst suppression pattern (BSP, in anesthesia induced by GA-BAergic agents.Methods: Twelve indices were investigated, namely Response Entropy (RE and State entropy (SE, three wavelet entropy (WE measures (Shannon WE (SWE, Tsallis WE (TWE and Renyi WE (RWE, Hilbert-Huang spectral entropy (HHSE, approximate entropy (ApEn, sample entropy (SampEn, Fuzzy entropy, and three permutation entropy (PE measures (Shannon PE (SPE, Tsallis PE (TPE and Renyi PE (RPE. Two EEG data sets from sevoflurane-induced and isoflu-rane-induced anesthesia respectively were selected to assess the capability of each entropy index in DoA monitoring and BSP detection. To validate the effectiveness of these entropy algorithms, phar-macokinetic / pharmacodynamic (PK/PD modeling and prediction probability analysis were applied. The multifractal detrended fluctuation analysis (MDFA as a non-entropy measure was compared.Results: All the entropy and MDFA indices could track the changes in EEG pattern during different anesthesia states. Three PE measures outperformed the other entropy indices, with less baseline vari-ability, higher coefficient of determination and prediction probability, and RPE performed best; ApEn and SampEn discriminated BSP best. Additionally, these entropy measures showed an ad-vantage in computation efficiency compared with MDFA.Conclusion: Each entropy index has its advantages and disadvantages in estimating DoA. Overall, it is suggested that the RPE index was a superior measure.Significance: Investigating the advantages and disadvantages of these entropy indices could help improve current clinical indices for monitoring DoA.

  6. Spatially-Explicit Bayesian Information Entropy Metrics for Calibrating Landscape Transformation Models

    Directory of Open Access Journals (Sweden)

    Kostas Alexandridis

    2013-06-01

    Full Text Available Assessing spatial model performance often presents challenges related to the choice and suitability of traditional statistical methods in capturing the true validity and dynamics of the predicted outcomes. The stochastic nature of many of our contemporary spatial models of land use change necessitate the testing and development of new and innovative methodologies in statistical spatial assessment. In many cases, spatial model performance depends critically on the spatially-explicit prior distributions, characteristics, availability and prevalence of the variables and factors under study. This study explores the statistical spatial characteristics of statistical model assessment of modeling land use change dynamics in a seven-county study area in South-Eastern Wisconsin during the historical period of 1963–1990. The artificial neural network-based Land Transformation Model (LTM predictions are used to compare simulated with historical land use transformations in urban/suburban landscapes. We introduce a range of Bayesian information entropy statistical spatial metrics for assessing the model performance across multiple simulation testing runs. Bayesian entropic estimates of model performance are compared against information-theoretic stochastic entropy estimates and theoretically-derived accuracy assessments. We argue for the critical role of informational uncertainty across different scales of spatial resolution in informing spatial landscape model assessment. Our analysis reveals how incorporation of spatial and landscape information asymmetry estimates can improve our stochastic assessments of spatial model predictions. Finally our study shows how spatially-explicit entropic classification accuracy estimates can work closely with dynamic modeling methodologies in improving our scientific understanding of landscape change as a complex adaptive system and process.

  7. The logistic model-generated carrying capacities, maximum ...

    African Journals Online (AJOL)

    This paper deals with the derivation of logistic models for cattle, sheep and goats in a commercial ranching system in Machakos District, Kenya, a savannah ecosystem with average annual rainfall of 589.3 ± 159.3mm and an area of 10 117ha. It involves modelling livestock population dynamics as discrete-time logistic ...

  8. Bayesian or Laplacien inference, entropy and information theory and information geometry in data and signal processing

    Science.gov (United States)

    Mohammad-Djafari, Ali

    2015-01-01

    The main object of this tutorial article is first to review the main inference tools using Bayesian approach, Entropy, Information theory and their corresponding geometries. This review is focused mainly on the ways these tools have been used in data, signal and image processing. After a short introduction of the different quantities related to the Bayes rule, the entropy and the Maximum Entropy Principle (MEP), relative entropy and the Kullback-Leibler divergence, Fisher information, we will study their use in different fields of data and signal processing such as: entropy in source separation, Fisher information in model order selection, different Maximum Entropy based methods in time series spectral estimation and finally, general linear inverse problems.

  9. Dynamics of Entropy in Quantum-like Model of Decision Making

    Science.gov (United States)

    Basieva, Irina; Khrennikov, Andrei; Asano, Masanari; Ohya, Masanori; Tanaka, Yoshiharu

    2011-03-01

    We present a quantum-like model of decision making in games of the Prisoner's Dilemma type. By this model the brain processes information by using representation of mental states in complex Hilbert space. Driven by the master equation the mental state of a player, say Alice, approaches an equilibrium point in the space of density matrices. By using this equilibrium point Alice determines her mixed (i.e., probabilistic) strategy with respect to Bob. Thus our model is a model of thinking through decoherence of initially pure mental state. Decoherence is induced by interaction with memory and external environment. In this paper we study (numerically) dynamics of quantum entropy of Alice's state in the process of decision making. Our analysis demonstrates that this dynamics depends nontrivially on the initial state of Alice's mind on her own actions and her prediction state (for possible actions of Bob.)

  10. Copula Entropy coupled with Wavelet Neural Network Model for Hydrological Prediction

    Science.gov (United States)

    Wang, Yin; Yue, JiGuang; Liu, ShuGuang; Wang, Li

    2018-02-01

    Artificial Neural network(ANN) has been widely used in hydrological forecasting. in this paper an attempt has been made to find an alternative method for hydrological prediction by combining Copula Entropy(CE) with Wavelet Neural Network(WNN), CE theory permits to calculate mutual information(MI) to select Input variables which avoids the limitations of the traditional linear correlation(LCC) analysis. Wavelet analysis can provide the exact locality of any changes in the dynamical patterns of the sequence Coupled with ANN Strong non-linear fitting ability. WNN model was able to provide a good fit with the hydrological data. finally, the hybrid model(CE+WNN) have been applied to daily water level of Taihu Lake Basin, and compared with CE ANN, LCC WNN and LCC ANN. Results showed that the hybrid model produced better results in estimating the hydrograph properties than the latter models.

  11. Entropy and Graph Based Modelling of Document Coherence using Discourse Entities

    DEFF Research Database (Denmark)

    Petersen, Casper; Lioma, Christina; Simonsen, Jakob Grue

    2015-01-01

    We present two novel models of document coherence and their application to information retrieval (IR). Both models approximate document coherence using discourse entities, e.g. the subject or object of a sentence. Our first model views text as a Markov process generating sequences of discourse...... entities (entity n-grams); we use the entropy of these entity n-grams to approximate the rate at which new information appears in text, reasoning that as more new words appear, the topic increasingly drifts and text coherence decreases. Our second model extends the work of Guinaudeau & Strube [28......] that represents text as a graph of discourse entities, linked by different relations, such as their distance or adjacency in text. We use several graph topology metrics to approximate different aspects of the discourse flow that can indicate coherence, such as the average clustering or betweenness of discourse...

  12. Quantum Gravity and Maximum Attainable Velocities in the Standard Model

    International Nuclear Information System (INIS)

    Alfaro, Jorge

    2007-01-01

    A main difficulty in the quantization of the gravitational field is the lack of experiments that discriminate among the theories proposed to quantize gravity. Recently we showed that the Standard Model(SM) itself contains tiny Lorentz invariance violation(LIV) terms coming from QG. All terms depend on one arbitrary parameter α that set the scale of QG effects. In this talk we review the LIV for mesons nucleons and leptons and apply it to study several effects, including the GZK anomaly

  13. Nonlinear model dynamics for closed-system, constrained, maximal-entropy-generation relaxation by energy redistribution

    International Nuclear Information System (INIS)

    Beretta, Gian Paolo

    2006-01-01

    We discuss a nonlinear model for relaxation by energy redistribution within an isolated, closed system composed of noninteracting identical particles with energy levels e i with i=1,2,...,N. The time-dependent occupation probabilities p i (t) are assumed to obey the nonlinear rate equations τ dp i /dt=-p i ln p i -α(t)p i -β(t)e i p i where α(t) and β(t) are functionals of the p i (t)'s that maintain invariant the mean energy E=Σ i=1 N e i p i (t) and the normalization condition 1=Σ i=1 N p i (t). The entropy S(t)=-k B Σ i=1 N p i (t)ln p i (t) is a nondecreasing function of time until the initially nonzero occupation probabilities reach a Boltzmann-like canonical distribution over the occupied energy eigenstates. Initially zero occupation probabilities, instead, remain zero at all times. The solutions p i (t) of the rate equations are unique and well defined for arbitrary initial conditions p i (0) and for all times. The existence and uniqueness both forward and backward in time allows the reconstruction of the ancestral or primordial lowest entropy state. By casting the rate equations in terms not of the p i 's but of their positive square roots √(p i ), they unfold from the assumption that time evolution is at all times along the local direction of steepest entropy ascent or, equivalently, of maximal entropy generation. These rate equations have the same mathematical structure and basic features as the nonlinear dynamical equation proposed in a series of papers ending with G. P. Beretta, Found. Phys. 17, 365 (1987) and recently rediscovered by S. Gheorghiu-Svirschevski [Phys. Rev. A 63, 022105 (2001);63, 054102 (2001)]. Numerical results illustrate the features of the dynamics and the differences from the rate equations recently considered for the same problem by M. Lemanska and Z. Jaeger [Physica D 170, 72 (2002)]. We also interpret the functionals k B α(t) and k B β(t) as nonequilibrium generalizations of the thermodynamic-equilibrium Massieu

  14. Combined Population Dynamics and Entropy Modelling Supports Patient Stratification in Chronic Myeloid Leukemia

    Science.gov (United States)

    Brehme, Marc; Koschmieder, Steffen; Montazeri, Maryam; Copland, Mhairi; Oehler, Vivian G.; Radich, Jerald P.; Brümmendorf, Tim H.; Schuppert, Andreas

    2016-04-01

    Modelling the parameters of multistep carcinogenesis is key for a better understanding of cancer progression, biomarker identification and the design of individualized therapies. Using chronic myeloid leukemia (CML) as a paradigm for hierarchical disease evolution we show that combined population dynamic modelling and CML patient biopsy genomic analysis enables patient stratification at unprecedented resolution. Linking CD34+ similarity as a disease progression marker to patient-derived gene expression entropy separated established CML progression stages and uncovered additional heterogeneity within disease stages. Importantly, our patient data informed model enables quantitative approximation of individual patients’ disease history within chronic phase (CP) and significantly separates “early” from “late” CP. Our findings provide a novel rationale for personalized and genome-informed disease progression risk assessment that is independent and complementary to conventional measures of CML disease burden and prognosis.

  15. Generalized second law of thermodynamics for non-canonical scalar field model with corrected-entropy

    International Nuclear Information System (INIS)

    Das, Sudipta; Mamon, Abdulla Al; Debnath, Ujjal

    2015-01-01

    In this work, we have considered a non-canonical scalar field dark energy model in the framework of flat FRW background. It has also been assumed that the dark matter sector interacts with the non-canonical dark energy sector through some interaction term. Using the solutions for this interacting non-canonical scalar field dark energy model, we have investigated the validity of generalized second law (GSL) of thermodynamics in various scenarios using first law and area law of thermodynamics. For this purpose, we have assumed two types of horizons viz apparent horizon and event horizon for the universe and using first law of thermodynamics, we have examined the validity of GSL on both apparent and event horizons. Next, we have considered two types of entropy-corrections on apparent and event horizons. Using the modified area law, we have examined the validity of GSL of thermodynamics on apparent and event horizons under some restrictions of model parameters. (orig.)

  16. Using Improved Entropy-Cloud Model to Select High-Speed Railway Express Freight Train Service Sites

    Directory of Open Access Journals (Sweden)

    Wencheng Huang

    2017-01-01

    Full Text Available High-speed railway (HSR express freight train service sites selection is critical to the development of China’s Third Party Logistics market. In this paper, we formulate an improved entropy-cloud model based approach to solve the HSR express sites selection problem for the first time. The basic data of the indicators, for example, existing railway network conditions, traffic environment, express freight market demand, and policy, will be used as the inputs. We apply improved entropy method to obtain each subindicator’s weight. The cloud model will be used to select and classify each station under evaluation.

  17. Entropy of international trades

    Science.gov (United States)

    Oh, Chang-Young; Lee, D.-S.

    2017-05-01

    The organization of international trades is highly complex under the collective efforts towards economic profits of participating countries given inhomogeneous resources for production. Considering the trade flux as the probability of exporting a product from a country to another, we evaluate the entropy of the world trades in the period 1950-2000. The trade entropy has increased with time, and we show that it is mainly due to the extension of trade partnership. For a given number of trade partners, the mean trade entropy is about 60% of the maximum possible entropy, independent of time, which can be regarded as a characteristic of the trade fluxes' heterogeneity and is shown to be derived from the scaling and functional behaviors of the universal trade-flux distribution. The correlation and time evolution of the individual countries' gross-domestic products and the number of trade partners show that most countries achieved their economic growth partly by extending their trade relationship.

  18. An entropy approach to size and variance heterogeneity

    NARCIS (Netherlands)

    Balasubramanyan, L.; Stefanou, S.E.; Stokes, J.R.

    2012-01-01

    In this paper, we investigate the effect of bank size differences on cost efficiency heterogeneity using a heteroskedastic stochastic frontier model. This model is implemented by using an information theoretic maximum entropy approach. We explicitly model both bank size and variance heterogeneity

  19. Using Graph and Vertex Entropy to Compare Empirical Graphs with Theoretical Graph Models

    Directory of Open Access Journals (Sweden)

    Tomasz Kajdanowicz

    2016-09-01

    Full Text Available Over the years, several theoretical graph generation models have been proposed. Among the most prominent are: the Erdős–Renyi random graph model, Watts–Strogatz small world model, Albert–Barabási preferential attachment model, Price citation model, and many more. Often, researchers working with real-world data are interested in understanding the generative phenomena underlying their empirical graphs. They want to know which of the theoretical graph generation models would most probably generate a particular empirical graph. In other words, they expect some similarity assessment between the empirical graph and graphs artificially created from theoretical graph generation models. Usually, in order to assess the similarity of two graphs, centrality measure distributions are compared. For a theoretical graph model this means comparing the empirical graph to a single realization of a theoretical graph model, where the realization is generated from the given model using an arbitrary set of parameters. The similarity between centrality measure distributions can be measured using standard statistical tests, e.g., the Kolmogorov–Smirnov test of distances between cumulative distributions. However, this approach is both error-prone and leads to incorrect conclusions, as we show in our experiments. Therefore, we propose a new method for graph comparison and type classification by comparing the entropies of centrality measure distributions (degree centrality, betweenness centrality, closeness centrality. We demonstrate that our approach can help assign the empirical graph to the most similar theoretical model using a simple unsupervised learning method.

  20. Configurational entropy as a tool to select a physical thick brane model

    Science.gov (United States)

    Chinaglia, M.; Cruz, W. T.; Correa, R. A. C.; de Paula, W.; Moraes, P. H. R. S.

    2018-04-01

    We analize braneworld scenarios via a configurational entropy (CE) formalism. Braneworld scenarios have drawn attention mainly due to the fact that they can explain the hierarchy problem and unify the fundamental forces through a symmetry breaking procedure. Those scenarios localize matter in a (3 + 1) hypersurface, the brane, which is inserted in a higher dimensional space, the bulk. Novel analytical braneworld models, in which the warp factor depends on a free parameter n, were recently released in the literature. In this article we will provide a way to constrain this parameter through the relation between information and dynamics of a system described by the CE. We demonstrate that in some cases the CE is an important tool in order to provide the most probable physical system among all the possibilities. In addition, we show that the highest CE is correlated to a tachyonic sector of the configuration, where the solutions for the corresponding model are dynamically unstable.

  1. Rényi Entropies from Random Quenches in Atomic Hubbard and Spin Models

    Science.gov (United States)

    Elben, A.; Vermersch, B.; Dalmonte, M.; Cirac, J. I.; Zoller, P.

    2018-02-01

    We present a scheme for measuring Rényi entropies in generic atomic Hubbard and spin models using single copies of a quantum state and for partitions in arbitrary spatial dimensions. Our approach is based on the generation of random unitaries from random quenches, implemented using engineered time-dependent disorder potentials, and standard projective measurements, as realized by quantum gas microscopes. By analyzing the properties of the generated unitaries and the role of statistical errors, with respect to the size of the partition, we show that the protocol can be realized in existing quantum simulators and used to measure, for instance, area law scaling of entanglement in two-dimensional spin models or the entanglement growth in many-body localized systems.

  2. Carbon emission analysis and evaluation of industrial departments in China: An improved environmental DEA cross model based on information entropy.

    Science.gov (United States)

    Han, Yongming; Long, Chang; Geng, Zhiqiang; Zhang, Keyu

    2018-01-01

    Environmental protection and carbon emission reduction play a crucial role in the sustainable development procedure. However, the environmental efficiency analysis and evaluation based on the traditional data envelopment analysis (DEA) cross model is subjective and inaccurate, because all elements in a column or a row of the cross evaluation matrix (CEM) in the traditional DEA cross model are given the same weight. Therefore, this paper proposes an improved environmental DEA cross model based on the information entropy to analyze and evaluate the carbon emission of industrial departments in China. The information entropy is applied to build the entropy distance based on the turbulence of the whole system, and calculate the weights in the CEM of the environmental DEA cross model in a dynamic way. The theoretical results show that the new weight constructed based on the information entropy is unique and optimal globally by using the Monte Carlo simulation. Finally, compared with the traditional environmental DEA and DEA cross model, the improved environmental DEA cross model has a better efficiency discrimination ability based on the data of industrial departments in China. Moreover, the proposed model can obtain the potential of carbon emission reduction of industrial departments to improve the energy efficiency. Copyright © 2017 Elsevier Ltd. All rights reserved.

  3. Inflection points of microcanonical entropy: Monte Carlo simulation of q state Potts model on a finite square lattice

    Energy Technology Data Exchange (ETDEWEB)

    Praveen, E., E-mail: svmstaya@gmail.com; Satyanarayana, S. V. M., E-mail: svmstaya@gmail.com [Department of Physics, Pondicherry University, Puducherry-605014 (India)

    2014-04-24

    Traditional definition of phase transition involves an infinitely large system in thermodynamic limit. Finite systems such as biological proteins exhibit cooperative behavior similar to phase transitions. We employ recently discovered analysis of inflection points of microcanonical entropy to estimate the transition temperature of the phase transition in q state Potts model on a finite two dimensional square lattice for q=3 (second order) and q=8 (first order). The difference of energy density of states (DOS) Δ ln g(E) = ln g(E+ ΔE) −ln g(E) exhibits a point of inflexion at a value corresponding to inverse transition temperature. This feature is common to systems exhibiting both first as well as second order transitions. While the difference of DOS registers a monotonic variation around the point of inflexion for systems exhibiting second order transition, it has an S-shape with a minimum and maximum around the point of inflexion for the case of first order transition.

  4. Inflection points of microcanonical entropy: Monte Carlo simulation of q state Potts model on a finite square lattice

    International Nuclear Information System (INIS)

    Praveen, E.; Satyanarayana, S. V. M.

    2014-01-01

    Traditional definition of phase transition involves an infinitely large system in thermodynamic limit. Finite systems such as biological proteins exhibit cooperative behavior similar to phase transitions. We employ recently discovered analysis of inflection points of microcanonical entropy to estimate the transition temperature of the phase transition in q state Potts model on a finite two dimensional square lattice for q=3 (second order) and q=8 (first order). The difference of energy density of states (DOS) Δ ln g(E) = ln g(E+ ΔE) −ln g(E) exhibits a point of inflexion at a value corresponding to inverse transition temperature. This feature is common to systems exhibiting both first as well as second order transitions. While the difference of DOS registers a monotonic variation around the point of inflexion for systems exhibiting second order transition, it has an S-shape with a minimum and maximum around the point of inflexion for the case of first order transition

  5. Parametric Bayesian Estimation of Differential Entropy and Relative Entropy

    Directory of Open Access Journals (Sweden)

    Maya Gupta

    2010-04-01

    Full Text Available Given iid samples drawn from a distribution with known parametric form, we propose the minimization of expected Bregman divergence to form Bayesian estimates of differential entropy and relative entropy, and derive such estimators for the uniform, Gaussian, Wishart, and inverse Wishart distributions. Additionally, formulas are given for a log gamma Bregman divergence and the differential entropy and relative entropy for the Wishart and inverse Wishart. The results, as always with Bayesian estimates, depend on the accuracy of the prior parameters, but example simulations show that the performance can be substantially improved compared to maximum likelihood or state-of-the-art nonparametric estimators.

  6. EEG entropy measures in anesthesia

    Science.gov (United States)

    Liang, Zhenhu; Wang, Yinghua; Sun, Xue; Li, Duan; Voss, Logan J.; Sleigh, Jamie W.; Hagihira, Satoshi; Li, Xiaoli

    2015-01-01

    Highlights: ► Twelve entropy indices were systematically compared in monitoring depth of anesthesia and detecting burst suppression.► Renyi permutation entropy performed best in tracking EEG changes associated with different anesthesia states.► Approximate Entropy and Sample Entropy performed best in detecting burst suppression. Objective: Entropy algorithms have been widely used in analyzing EEG signals during anesthesia. However, a systematic comparison of these entropy algorithms in assessing anesthesia drugs' effect is lacking. In this study, we compare the capability of 12 entropy indices for monitoring depth of anesthesia (DoA) and detecting the burst suppression pattern (BSP), in anesthesia induced by GABAergic agents. Methods: Twelve indices were investigated, namely Response Entropy (RE) and State entropy (SE), three wavelet entropy (WE) measures [Shannon WE (SWE), Tsallis WE (TWE), and Renyi WE (RWE)], Hilbert-Huang spectral entropy (HHSE), approximate entropy (ApEn), sample entropy (SampEn), Fuzzy entropy, and three permutation entropy (PE) measures [Shannon PE (SPE), Tsallis PE (TPE) and Renyi PE (RPE)]. Two EEG data sets from sevoflurane-induced and isoflurane-induced anesthesia respectively were selected to assess the capability of each entropy index in DoA monitoring and BSP detection. To validate the effectiveness of these entropy algorithms, pharmacokinetic/pharmacodynamic (PK/PD) modeling and prediction probability (Pk) analysis were applied. The multifractal detrended fluctuation analysis (MDFA) as a non-entropy measure was compared. Results: All the entropy and MDFA indices could track the changes in EEG pattern during different anesthesia states. Three PE measures outperformed the other entropy indices, with less baseline variability, higher coefficient of determination (R2) and prediction probability, and RPE performed best; ApEn and SampEn discriminated BSP best. Additionally, these entropy measures showed an advantage in computation

  7. The holographic entropy cone

    Energy Technology Data Exchange (ETDEWEB)

    Bao, Ning [Institute for Quantum Information and Matter, California Institute of Technology,Pasadena, CA 91125 (United States); Walter Burke Institute for Theoretical Physics, California Institute of Technology,452-48, Pasadena, CA 91125 (United States); Nezami, Sepehr [Stanford Institute for Theoretical Physics, Stanford University,Stanford, CA 94305 (United States); Ooguri, Hirosi [Walter Burke Institute for Theoretical Physics, California Institute of Technology,452-48, Pasadena, CA 91125 (United States); Kavli Institute for the Physics and Mathematics of the Universe, University of Tokyo,Kashiwa 277-8583 (Japan); Stoica, Bogdan [Walter Burke Institute for Theoretical Physics, California Institute of Technology,452-48, Pasadena, CA 91125 (United States); Sully, James [Theory Group, SLAC National Accelerator Laboratory, Stanford University,Menlo Park, CA 94025 (United States); Walter, Michael [Stanford Institute for Theoretical Physics, Stanford University,Stanford, CA 94305 (United States)

    2015-09-21

    We initiate a systematic enumeration and classification of entropy inequalities satisfied by the Ryu-Takayanagi formula for conformal field theory states with smooth holographic dual geometries. For 2, 3, and 4 regions, we prove that the strong subadditivity and the monogamy of mutual information give the complete set of inequalities. This is in contrast to the situation for generic quantum systems, where a complete set of entropy inequalities is not known for 4 or more regions. We also find an infinite new family of inequalities applicable to 5 or more regions. The set of all holographic entropy inequalities bounds the phase space of Ryu-Takayanagi entropies, defining the holographic entropy cone. We characterize this entropy cone by reducing geometries to minimal graph models that encode the possible cutting and gluing relations of minimal surfaces. We find that, for a fixed number of regions, there are only finitely many independent entropy inequalities. To establish new holographic entropy inequalities, we introduce a combinatorial proof technique that may also be of independent interest in Riemannian geometry and graph theory.

  8. The holographic entropy cone

    International Nuclear Information System (INIS)

    Bao, Ning; Nezami, Sepehr; Ooguri, Hirosi; Stoica, Bogdan; Sully, James; Walter, Michael

    2015-01-01

    We initiate a systematic enumeration and classification of entropy inequalities satisfied by the Ryu-Takayanagi formula for conformal field theory states with smooth holographic dual geometries. For 2, 3, and 4 regions, we prove that the strong subadditivity and the monogamy of mutual information give the complete set of inequalities. This is in contrast to the situation for generic quantum systems, where a complete set of entropy inequalities is not known for 4 or more regions. We also find an infinite new family of inequalities applicable to 5 or more regions. The set of all holographic entropy inequalities bounds the phase space of Ryu-Takayanagi entropies, defining the holographic entropy cone. We characterize this entropy cone by reducing geometries to minimal graph models that encode the possible cutting and gluing relations of minimal surfaces. We find that, for a fixed number of regions, there are only finitely many independent entropy inequalities. To establish new holographic entropy inequalities, we introduce a combinatorial proof technique that may also be of independent interest in Riemannian geometry and graph theory.

  9. A positive and entropy-satisfying finite volume scheme for the Baer–Nunziato model

    Energy Technology Data Exchange (ETDEWEB)

    Coquel, Frédéric, E-mail: frederic.coquel@cmap.polytechnique.fr [CMAP, École Polytechnique CNRS, UMR 7641, Route de Saclay, F-91128 Palaiseau cedex (France); Hérard, Jean-Marc, E-mail: jean-marc.herard@edf.fr [EDF-R& D, Département MFEE, 6 Quai Watier, F-78401 Chatou Cedex (France); Saleh, Khaled, E-mail: saleh@math.univ-lyon1.fr [Université de Lyon, CNRS UMR 5208, Université Lyon 1, Institut Camille Jordan, 43 bd 11 novembre 1918, F-69622 Villeurbanne cedex (France)

    2017-02-01

    We present a relaxation scheme for approximating the entropy dissipating weak solutions of the Baer–Nunziato two-phase flow model. This relaxation scheme is straightforwardly obtained as an extension of the relaxation scheme designed in for the isentropic Baer–Nunziato model and consequently inherits its main properties. To our knowledge, this is the only existing scheme for which the approximated phase fractions, phase densities and phase internal energies are proven to remain positive without any restrictive condition other than a classical fully computable CFL condition. For ideal gas and stiffened gas equations of state, real values of the phasic speeds of sound are also proven to be maintained by the numerical scheme. It is also the only scheme for which a discrete entropy inequality is proven, under a CFL condition derived from the natural sub-characteristic condition associated with the relaxation approximation. This last property, which ensures the non-linear stability of the numerical method, is satisfied for any admissible equation of state. We provide a numerical study for the convergence of the approximate solutions towards some exact Riemann solutions. The numerical simulations show that the relaxation scheme compares well with two of the most popular existing schemes available for the Baer–Nunziato model, namely Schwendeman–Wahle–Kapila's Godunov-type scheme and Tokareva–Toro's HLLC scheme . The relaxation scheme also shows a higher precision and a lower computational cost (for comparable accuracy) than a standard numerical scheme used in the nuclear industry, namely Rusanov's scheme. Finally, we assess the good behavior of the scheme when approximating vanishing phase solutions.

  10. A positive and entropy-satisfying finite volume scheme for the Baer-Nunziato model

    Science.gov (United States)

    Coquel, Frédéric; Hérard, Jean-Marc; Saleh, Khaled

    2017-02-01

    We present a relaxation scheme for approximating the entropy dissipating weak solutions of the Baer-Nunziato two-phase flow model. This relaxation scheme is straightforwardly obtained as an extension of the relaxation scheme designed in [16] for the isentropic Baer-Nunziato model and consequently inherits its main properties. To our knowledge, this is the only existing scheme for which the approximated phase fractions, phase densities and phase internal energies are proven to remain positive without any restrictive condition other than a classical fully computable CFL condition. For ideal gas and stiffened gas equations of state, real values of the phasic speeds of sound are also proven to be maintained by the numerical scheme. It is also the only scheme for which a discrete entropy inequality is proven, under a CFL condition derived from the natural sub-characteristic condition associated with the relaxation approximation. This last property, which ensures the non-linear stability of the numerical method, is satisfied for any admissible equation of state. We provide a numerical study for the convergence of the approximate solutions towards some exact Riemann solutions. The numerical simulations show that the relaxation scheme compares well with two of the most popular existing schemes available for the Baer-Nunziato model, namely Schwendeman-Wahle-Kapila's Godunov-type scheme [39] and Tokareva-Toro's HLLC scheme [44]. The relaxation scheme also shows a higher precision and a lower computational cost (for comparable accuracy) than a standard numerical scheme used in the nuclear industry, namely Rusanov's scheme. Finally, we assess the good behavior of the scheme when approximating vanishing phase solutions.

  11. Existence and uniqueness of the maximum likelihood estimator for models with a Kronecker product covariance structure

    NARCIS (Netherlands)

    Ros, B.P.; Bijma, F.; de Munck, J.C.; de Gunst, M.C.M.

    2016-01-01

    This paper deals with multivariate Gaussian models for which the covariance matrix is a Kronecker product of two matrices. We consider maximum likelihood estimation of the model parameters, in particular of the covariance matrix. There is no explicit expression for the maximum likelihood estimator

  12. A Case Study on a Combination NDVI Forecasting Model Based on the Entropy Weight Method

    Energy Technology Data Exchange (ETDEWEB)

    Huang, Shengzhi; Ming, Bo; Huang, Qiang; Leng, Guoyong; Hou, Beibei

    2017-05-05

    It is critically meaningful to accurately predict NDVI (Normalized Difference Vegetation Index), which helps guide regional ecological remediation and environmental managements. In this study, a combination forecasting model (CFM) was proposed to improve the performance of NDVI predictions in the Yellow River Basin (YRB) based on three individual forecasting models, i.e., the Multiple Linear Regression (MLR), Artificial Neural Network (ANN), and Support Vector Machine (SVM) models. The entropy weight method was employed to determine the weight coefficient for each individual model depending on its predictive performance. Results showed that: (1) ANN exhibits the highest fitting capability among the four orecasting models in the calibration period, whilst its generalization ability becomes weak in the validation period; MLR has a poor performance in both calibration and validation periods; the predicted results of CFM in the calibration period have the highest stability; (2) CFM generally outperforms all individual models in the validation period, and can improve the reliability and stability of predicted results through combining the strengths while reducing the weaknesses of individual models; (3) the performances of all forecasting models are better in dense vegetation areas than in sparse vegetation areas.

  13. Symplectic entropy

    International Nuclear Information System (INIS)

    De Nicola, Sergio; Fedele, Renato; Man'ko, Margarita A; Man'ko, Vladimir I

    2007-01-01

    The tomographic-probability description of quantum states is reviewed. The symplectic tomography of quantum states with continuous variables is studied. The symplectic entropy of the states with continuous variables is discussed and its relation to Shannon entropy and information is elucidated. The known entropic uncertainty relations of the probability distribution in position and momentum of a particle are extended and new uncertainty relations for symplectic entropy are obtained. The partial case of symplectic entropy, which is optical entropy of quantum states, is considered. The entropy associated to optical tomogram is shown to satisfy the new entropic uncertainty relation. The example of Gaussian states of harmonic oscillator is studied and the entropic uncertainty relations for optical tomograms of the Gaussian state are shown to minimize the uncertainty relation

  14. Exact valence bond entanglement entropy and probability distribution in the XXX spin chain and the potts model.

    Science.gov (United States)

    Jacobsen, J L; Saleur, H

    2008-02-29

    We determine exactly the probability distribution of the number N_(c) of valence bonds connecting a subsystem of length L>1 to the rest of the system in the ground state of the XXX antiferromagnetic spin chain. This provides, in particular, the asymptotic behavior of the valence-bond entanglement entropy S_(VB)=N_(c)ln2=4ln2/pi(2)lnL disproving a recent conjecture that this should be related with the von Neumann entropy, and thus equal to 1/3lnL. Our results generalize to the Q-state Potts model.

  15. Calculation of entropy of liquid metals using acoustic measurements in the framework of the rigid sphere model

    International Nuclear Information System (INIS)

    Tekuchev, V.V.; Barashkov, B.I.; Rygalov, L.N.; Dolzhikov, Yu.S.

    2001-01-01

    For the first time one obtained the polytherms of ultrasound velocity for liquid high-melting metals within wide temperature range. In terms of the rigid sphere model on the basis of the acoustic data one calculated the entropy values for 34 liquid metals at the melting point. The average discrepancy of the calculated values of entropy with the published one constitutes 8.2%. With increase of metal valency the error increases from 2.8 up to 13%. In case of francium, radium, promethium, actinium, hafnium, polonium, rhenium one obtained data for the first time [ru

  16. NbTaV-(Ti,W) refractory high-entropy alloys: Experiments and modeling

    Energy Technology Data Exchange (ETDEWEB)

    Yao, H.W. [Laboratory of Applied Physics and Mechanics of Advanced Materials, College of Materials Science and Engineering, Taiyuan University of Technology, Taiyuan 030024 (China); Qiao, J.W., E-mail: qiaojunwei@gmail.com [Laboratory of Applied Physics and Mechanics of Advanced Materials, College of Materials Science and Engineering, Taiyuan University of Technology, Taiyuan 030024 (China); Gao, M.C., E-mail: michael.gao@netl.doe.gov [National Energy Technology Laboratory, 1450 Queen Ave SW, Albany, OR 97321 (United States); AECOM, P.O. Box 1959, Albany, OR 97321 (United States); Hawk, J.A. [National Energy Technology Laboratory, 1450 Queen Ave SW, Albany, OR 97321 (United States); Ma, S.G. [Institute of Applied Mechanics and Biomedical Engineering, Taiyuan University of Technology, Taiyuan 030024 (China); Zhou, H.F. [Laboratory of Applied Physics and Mechanics of Advanced Materials, College of Materials Science and Engineering, Taiyuan University of Technology, Taiyuan 030024 (China); Zhang, Y. [State Key Laboratory for Advanced Metals and Materials, University of Science and Technology Beijing, Beijing 100083 (China)

    2016-09-30

    This study reports the design and development of ductile and strong refractory single-phase high-entropy alloys (HEAs) for high temperature applications, based on NbTaV with addition of Ti and W. Assisted by CALPHAD modeling, a single body-centered cubic solid solution phase was experimentally confirmed in the as-cast ingots using X-ray diffraction and scanning electron microscopy. The observed elemental segregation in each alloy qualitatively agrees with CALPHAD prediction. The Vickers microhardnesses (and yield strengths) of the alloys are about 3 (and 3.5–4.4) times that those estimated from the rule of mixture. While NbTaTiVW shows an impressive yield strength of 1420 MPa with fracture strain of 20%, NbTaTiV exhibits exceptional compressive ductility at room temperature.

  17. Nonequilibrium entropies

    International Nuclear Information System (INIS)

    Maes, Christian

    2012-01-01

    In contrast to the quite unique entropy concept useful for systems in (local) thermodynamic equilibrium, there is a variety of quite distinct nonequilibrium entropies, reflecting different physical points. We disentangle these entropies as they relate to heat, fluctuations, response, time asymmetry, variational principles, monotonicity, volume contraction or statistical forces. However, not all of those extensions yield state quantities as understood thermodynamically. At the end we sketch how aspects of dynamical activity can take over for obtaining an extended Clausius relation.

  18. Integrating Entropy and Closed Frequent Pattern Mining for Social Network Modelling and Analysis

    Science.gov (United States)

    Adnan, Muhaimenul; Alhajj, Reda; Rokne, Jon

    The recent increase in the explicitly available social networks has attracted the attention of the research community to investigate how it would be possible to benefit from such a powerful model in producing effective solutions for problems in other domains where the social network is implicit; we argue that social networks do exist around us but the key issue is how to realize and analyze them. This chapter presents a novel approach for constructing a social network model by an integrated framework that first preparing the data to be analyzed and then applies entropy and frequent closed patterns mining for network construction. For a given problem, we first prepare the data by identifying items and transactions, which arc the basic ingredients for frequent closed patterns mining. Items arc main objects in the problem and a transaction is a set of items that could exist together at one time (e.g., items purchased in one visit to the supermarket). Transactions could be analyzed to discover frequent closed patterns using any of the well-known techniques. Frequent closed patterns have the advantage that they successfully grab the inherent information content of the dataset and is applicable to a broader set of domains. Entropies of the frequent closed patterns arc used to keep the dimensionality of the feature vectors to a reasonable size; it is a kind of feature reduction process. Finally, we analyze the dynamic behavior of the constructed social network. Experiments were conducted on a synthetic dataset and on the Enron corpus email dataset. The results presented in the chapter show that social networks extracted from a feature set as frequent closed patterns successfully carry the community structure information. Moreover, for the Enron email dataset, we present an analysis to dynamically indicate the deviations from each user's individual and community profile. These indications of deviations can be very useful to identify unusual events.

  19. Modeling of Maximum Power Point Tracking Controller for Solar Power System

    Directory of Open Access Journals (Sweden)

    Aryuanto Soetedjo

    2012-09-01

    Full Text Available In this paper, a Maximum Power Point Tracking (MPPT controller for solar power system is modeled using MATLAB Simulink. The model consists of PV module, buck converter, and MPPT controller. The contribution of the work is in the modeling of buck converter that allowing the input voltage of the converter, i.e. output voltage of PV is changed by varying the duty cycle, so that the maximum power point could be tracked when the environmental changes. The simulation results show that the developed model performs well in tracking the maximum power point (MPP of the PV module using Perturb and Observe (P&O Algorithm.

  20. Entropy: From Thermodynamics to Hydrology

    Directory of Open Access Journals (Sweden)

    Demetris Koutsoyiannis

    2014-02-01

    Full Text Available Some known results from statistical thermophysics as well as from hydrology are revisited from a different perspective trying: (a to unify the notion of entropy in thermodynamic and statistical/stochastic approaches of complex hydrological systems and (b to show the power of entropy and the principle of maximum entropy in inference, both deductive and inductive. The capability for deductive reasoning is illustrated by deriving the law of phase change transition of water (Clausius-Clapeyron from scratch by maximizing entropy in a formal probabilistic frame. However, such deductive reasoning cannot work in more complex hydrological systems with diverse elements, yet the entropy maximization framework can help in inductive inference, necessarily based on data. Several examples of this type are provided in an attempt to link statistical thermophysics with hydrology with a unifying view of entropy.