Directory of Open Access Journals (Sweden)
Yange Shao
2014-01-01
Full Text Available The phenomenon of stochastic synchronization in globally coupled FitzHugh-Nagumo (FHN neuron system subjected to spatially correlated Gaussian noise is investigated based on dynamical mean-field approximation (DMA and direct simulation (DS. Results from DMA are in good quantitative or qualitative agreement with those from DS for weak noise intensity and larger system size. Whether the consisting single FHN neuron is staying at the resting state, subthreshold oscillatory regime, or the spiking state, our investigation shows that the synchronization ratio of the globally coupled system becomes higher as the noise correlation coefficient increases, and thus we conclude that spatial correlation has an active effect on stochastic synchronization, and the neurons can achieve complete synchronization in the sense of statistics when the noise correlation coefficient tends to one. Our investigation also discloses that the noise spatial correlation plays the same beneficial role as the global coupling strength in enhancing stochastic synchronization in the ensemble. The result might be useful in understanding the information coding mechanism in neural systems.
Stochastic population growth in spatially heterogeneous environments.
Evans, Steven N; Ralph, Peter L; Schreiber, Sebastian J; Sen, Arnab
2013-02-01
stochastic growth rate, we derive an explicit expression for the stochastic growth rate for populations living in two patches, determine which choices of the dispersal matrix D produce the maximal stochastic growth rate for a freely dispersing population, derive an analytic approximation of the stochastic growth rate for dispersal limited populations, and use group theoretic techniques to approximate the stochastic growth rate for populations living in multi-scale landscapes (e.g. insects on plants in meadows on islands). Our results provide fundamental insights into "ideal free" movement in the face of uncertainty, the persistence of coupled sink populations, the evolution of dispersal rates, and the single large or several small (SLOSS) debate in conservation biology. For example, our analysis implies that even in the absence of density-dependent feedbacks, ideal-free dispersers occupy multiple patches in spatially heterogeneous environments provided environmental fluctuations are sufficiently strong and sufficiently weakly correlated across space. In contrast, for diffusively dispersing populations living in similar environments, intermediate dispersal rates maximize their stochastic growth rate.
Detecting synchronization in coupled stochastic ecosystem networks
Energy Technology Data Exchange (ETDEWEB)
Kouvaris, N. [Institute of Physical Chemistry, National Center for Scientific Research ' Demokritos' , 15310 Athens (Greece); Department of Mathematical, Physical and Computational Science, Faculty of Engineering, Aristotle University of Thessaloniki, 54124 Thessaloniki (Greece); Provata, A. [Institute of Physical Chemistry, National Center for Scientific Research ' Demokritos' , 15310 Athens (Greece); Kugiumtzis, D., E-mail: dkugiu@gen.auth.g [Department of Mathematical, Physical and Computational Science, Faculty of Engineering, Aristotle University of Thessaloniki, 54124 Thessaloniki (Greece)
2010-01-11
Instantaneous phase difference, synchronization index and mutual information are considered in order to detect phase transitions, collective behaviours and synchronization phenomena that emerge for different levels of diffusive and reactive activity in stochastic networks. The network under investigation is a spatial 2D lattice which serves as a substrate for Lotka-Volterra dynamics with 3rd order nonlinearities. Kinetic Monte Carlo simulations demonstrate that the system spontaneously organizes into a number of asynchronous local oscillators, when only nearest neighbour interactions are considered. In contrast, the oscillators can be correlated, phase synchronized and completely synchronized when introducing different interactivity rules (diffusive or reactive) for nearby and distant species. The quantitative measures of synchronization show that long distance diffusion coupling induces phase synchronization after a well defined transition point, while long distance reaction coupling induces smeared phase synchronization.
Spatial stochastic dynamics enable robust cell polarization.
Directory of Open Access Journals (Sweden)
Michael J Lawson
Full Text Available Although cell polarity is an essential feature of living cells, it is far from being well-understood. Using a combination of computational modeling and biological experiments we closely examine an important prototype of cell polarity: the pheromone-induced formation of the yeast polarisome. Focusing on the role of noise and spatial heterogeneity, we develop and investigate two mechanistic spatial models of polarisome formation, one deterministic and the other stochastic, and compare the contrasting predictions of these two models against experimental phenotypes of wild-type and mutant cells. We find that the stochastic model can more robustly reproduce two fundamental characteristics observed in wild-type cells: a highly polarized phenotype via a mechanism that we refer to as spatial stochastic amplification, and the ability of the polarisome to track a moving pheromone input. Moreover, we find that only the stochastic model can simultaneously reproduce these characteristics of the wild-type phenotype and the multi-polarisome phenotype of a deletion mutant of the scaffolding protein Spa2. Significantly, our analysis also demonstrates that higher levels of stochastic noise results in increased robustness of polarization to parameter variation. Furthermore, our work suggests a novel role for a polarisome protein in the stabilization of actin cables. These findings elucidate the intricate role of spatial stochastic effects in cell polarity, giving support to a cellular model where noise and spatial heterogeneity combine to achieve robust biological function.
Lectures on Topics in Spatial Stochastic Processes
Capasso, Vincenzo; Ivanoff, B Gail; Dozzi, Marco; Dalang, Robert C; Mountford, Thomas S
2003-01-01
The theory of stochastic processes indexed by a partially ordered set has been the subject of much research over the past twenty years. The objective of this CIME International Summer School was to bring to a large audience of young probabilists the general theory of spatial processes, including the theory of set-indexed martingales and to present the different branches of applications of this theory, including stochastic geometry, spatial statistics, empirical processes, spatial estimators and survival analysis. This theory has a broad variety of applications in environmental sciences, social sciences, structure of material and image analysis. In this volume, the reader will find different approaches which foster the development of tools to modelling the spatial aspects of stochastic problems.
Stochastic coupling of two random Boolean networks
Energy Technology Data Exchange (ETDEWEB)
Ho, M.-C. [Department of Physics, National Kaohsiung Normal University, Kaohsiung, Taiwan (China)]. E-mail: t1603@nknucc.nknu.edu.tw; Hung, Y.-C. [Department of Physics, National Sun Yat-sen University, Kaohsiung, Taiwan (China)]. E-mail: d9123801@student.nsysu.edu.tw; Jiang, I-M. [Department of Physics, National Sun Yat-sen University, Kaohsiung, Taiwan (China)
2005-08-29
We study the dynamics of two coupled random Boolean networks. Based on the Boolean model studied by Andrecut and Ali [Int. J. Mod. Phys. B 15 (2001) 17] and the stochastic coupling techniques, the density evolution of networks is precisely described by two deterministic coupled polynomial maps. The iteration results of the model match the real networks well. By using MSE and the maximal Lyapunov exponents, the synchronization phenomena of coupled networks is also under our discussion.
Regulation mechanisms in spatial stochastic development models
Finkelshtein, Dmitri
2008-01-01
The aim of this paper is to analyze different regulation mechanisms in spatial continuous stochastic development models. We describe the density behavior for models with global mortality and local establishment rates. We prove that the local self-regulation via a competition mechanism (density dependent mortality) may suppress a unbounded growth of the averaged density if the competition kernel is superstable.
Aspects of stochastic resonance in Josephson junction, bimodal maps and coupled map lattice
Indian Academy of Sciences (India)
G Ambika; Kamala Menon; K P Harikrishnan
2005-04-01
We present the results of extensive numerical studies on stochastic resonance and its characteristic features in three model systems, namely, a model for Josephson tunnel junctions, the bistable cubic map and a coupled map lattice formed by coupling the cubic maps. Some interesting features regarding the mechanism including multisignal amplification and spatial stochastic resonance are shown.
Stochasticity and Spatial Resonance in Interdecadal Climate Fluctuations.
Saravanan, R.; McWilliams, James C.
1997-09-01
Ocean-atmosphere interaction plays a key role in climate fluctuations on interdecadal timescales. In this study, different aspects of this interaction are investigated using an idealized ocean-atmosphere model, and a hierarchy of uncoupled and stochastic models derived from it. The atmospheric component is an eddy-resolving two-level global primitive equation model with simplified physical parameterizations. The oceanic component is a zonally averaged sector model of the thermohaline circulation. The coupled model exhibits spontaneous oscillations of the thermohaline circulation on interdecadal timescales. The interdecadal oscillation has qualitatively realistic features, such as dipolar sea surface temperature anomalies in the extratropics. Atmospheric forcing of the ocean plays a dominant role in exciting this oscillation. Although the coupled model is in itself deterministic, it is convenient to conceptualize the atmospheric forcing arising from weather excitation as having stochastic time dependence. Spatial correlations inherent in the atmospheric low-frequency variability play a crucial role in determining the oceanic interdecadal variability, through a form of spatial resonance. Local feedback from the ocean affects the amplitude of the interdecadal variability. The spatial patterns of correlations between the atmospheric flow and the oceanic variability fall into two categories: (i) upstream forcing patterns, and (ii) downstream response patterns. Both categories of patterns are expressible as linear combinations of the dominant modes of variability associated with the uncoupled atmosphere.
Stochastic spatial models of plant diseases
Brown, D H
2001-01-01
I present three models of plant--pathogen interactions. The models are stochastic and spatially explicit at the scale of individual plants. For each model, I use a version of pair approximation or moment closure along with a separation of timescales argument to determine the effects of spatial clustering on threshold structure. By computing the spatial structure early in an invasion, I find explicit corrections to mean field theory. In the first chapter, I present a lattice model of a disease that is not directly lethal to its host, but affects its ability to compete with neighbors. I use a type of pair approximation to determine conditions for invasions and coexistence. In the second chapter, I study a basic SIR epidemic point process in continuous space. I implement a multiplicative moment closure scheme to compute the threshold transmission rate as a function of spatial parameters. In the final chapter, I model the evolution of pathogen resistance when two plant species share a pathogen. Evolution may lead...
DEFF Research Database (Denmark)
Barndorff-Nielsen, Ole E.; Benth, Fred Espen; Veraart, Almut
Ambit stochastics is the name for the theory and applications of ambit fields and ambit processes and constitutes a new research area in stochastics for tempo-spatial phenomena. This paper gives an overview of the main findings in ambit stochastics up to date and establishes new results on general...... properties of ambit fields. Moreover, it develops the concept of tempo-spatial stochastic volatility/intermittency within ambit fields. Various types of volatility modulation ranging from stochastic scaling of the amplitude, to stochastic time change and extended subordination of random measures...... and to probability and L\\'{e}vy mixing of volatility/intensity parameters will be developed. Important examples for concrete model specifications within the class of ambit fields are given....
Spatial Stochastic Point Models for Reservoir Characterization
Energy Technology Data Exchange (ETDEWEB)
Syversveen, Anne Randi
1997-12-31
The main part of this thesis discusses stochastic modelling of geology in petroleum reservoirs. A marked point model is defined for objects against a background in a two-dimensional vertical cross section of the reservoir. The model handles conditioning on observations from more than one well for each object and contains interaction between objects, and the objects have the correct length distribution when penetrated by wells. The model is developed in a Bayesian setting. The model and the simulation algorithm are demonstrated by means of an example with simulated data. The thesis also deals with object recognition in image analysis, in a Bayesian framework, and with a special type of spatial Cox processes called log-Gaussian Cox processes. In these processes, the logarithm of the intensity function is a Gaussian process. The class of log-Gaussian Cox processes provides flexible models for clustering. The distribution of such a process is completely characterized by the intensity and the pair correlation function of the Cox process. 170 refs., 37 figs., 5 tabs.
Stochastic Resonance in a Coupled Array Without Periodic Driving
Institute of Scientific and Technical Information of China (English)
钱敏; 张雪娟
2002-01-01
We manifest a stochastic resonance in a two-dimensional square array of coupled oscillators subjected only to white noise and constant driving forces. The result shows that the coherent output of every single oscillator plays the role of periodic input to its neighbours. Even without periodic driving, the cooperation of the white noise and the coupling can also result in the array enhanced stochastic resonance effect. In our investigation, global as well as local noise perturbation is taken into account.
Amplitude death of coupled hair bundles with stochastic channel noise
Kim, Kyung-Joong
2014-01-01
Hair cells conduct auditory transduction in vertebrates. In lower vertebrates such as frogs and turtles, due to the active mechanism in hair cells, hair bundles(stereocilia) can be spontaneously oscillating or quiescent. Recently, the amplitude death phenomenon has been proposed [K.-H. Ahn, J. R. Soc. Interface, {\\bf 10}, 20130525 (2013)] as a mechanism for auditory transduction in frog hair-cell bundles, where sudden cessation of the oscillations arises due to the coupling between non-identical hair bundles. The gating of the ion channel is intrinsically stochastic due to the stochastic nature of the configuration change of the channel. The strength of the noise due to the channel gating can be comparable to the thermal Brownian noise of hair bundles. Thus, we perform stochastic simulations of the elastically coupled hair bundles. In spite of stray noisy fluctuations due to its stochastic dynamics, our simulation shows the transition from collective oscillation to amplitude death as inter-bundle coupling str...
Institute of Scientific and Technical Information of China (English)
Tang Yang; Zhong Hui-Huang; Fang Jian-An
2008-01-01
A general model of linearly stochastically coupled identical connected neural networks with hybrid coupling is proposed,which is composed of constant coupling,coupling discrete time-varying delay and coupling distributed timevarying delay.All the coupling terms are subjected to stochastic disturbances described in terms of Brownian motion,which reflects a more realistic dynamical behaviour of coupled systems in practice.Based on a simple adaptive feedback controller and stochastic stability theory,several sufficient criteria are presented to ensure the synchronization of linearly stochastically coupled complex networks with coupling mixed time-varying delays.Finally,numerical simulatious illustrated by scale-free complex networks verify the effectiveness of the proposed controllers.
Mean Square Synchronization of Stochastic Nonlinear Delayed Coupled Complex Networks
Directory of Open Access Journals (Sweden)
Chengrong Xie
2013-01-01
Full Text Available We investigate the problem of adaptive mean square synchronization for nonlinear delayed coupled complex networks with stochastic perturbation. Based on the LaSalle invariance principle and the properties of the Weiner process, the controller and adaptive laws are designed to ensure achieving stochastic synchronization and topology identification of complex networks. Sufficient conditions are given to ensure the complex networks to be mean square synchronization. Furthermore, numerical simulations are also given to demonstrate the effectiveness of the proposed scheme.
Stochastic geometry, spatial statistics and random fields models and algorithms
2015-01-01
Providing a graduate level introduction to various aspects of stochastic geometry, spatial statistics and random fields, this volume places a special emphasis on fundamental classes of models and algorithms as well as on their applications, for example in materials science, biology and genetics. This book has a strong focus on simulations and includes extensive codes in Matlab and R, which are widely used in the mathematical community. It can be regarded as a continuation of the recent volume 2068 of Lecture Notes in Mathematics, where other issues of stochastic geometry, spatial statistics and random fields were considered, with a focus on asymptotic methods.
Method for generating two coupled Gaussian stochastic processes
Jamali, Tayeb
2016-01-01
Most processes in nature are coupled; however, extensive null models for generating such processes still lacks. We present a new method to generate two coupled Gaussian stochastic processes with arbitrary correlation functions. This method is developed by modifying the Fourier filtering method. The robustness of this method is proved by generating two coupled fractional Brownian motions and extending its range of application to Gaussian random fields.
Synchronization of coupled stochastic oscillators: The effect of topology
Indian Academy of Sciences (India)
Amitabha Nandi; Ram Ramaswamy
2008-06-01
We study sets of genetic networks having stochastic oscillatory dynamics. Depending on the coupling topology we find regimes of phase synchronization of the dynamical variables. We consider the effect of time-delay in the interaction and show that for suitable choices of delay parameter, either in-phase or anti-phase synchronization can occur.
Stochastic and Spatial Equivalences for PALOMA
Directory of Open Access Journals (Sweden)
Paul Piho
2016-07-01
Full Text Available We concentrate our study on a recent process algebra – PALOMA – intended to capture interactions between spatially distributed agents, for example in collective adaptive systems. New agent-based semantic rules for deriving the underlying continuous time Markov chain are given in terms of State to Function Labelled Transition Systems. Furthermore we define a bisimulation with respect to an isometric transformation of space allowing us to compare PALOMA models with respect to their relative rather than absolute locations.
Classical and spatial stochastic processes with applications to biology
Schinazi, Rinaldo B
2014-01-01
The revised and expanded edition of this textbook presents the concepts and applications of random processes with the same illuminating simplicity as its first edition, but with the notable addition of substantial modern material on biological modeling. While still treating many important problems in fields such as engineering and mathematical physics, the book also focuses on the highly relevant topics of cancerous mutations, influenza evolution, drug resistance, and immune response. The models used elegantly apply various classical stochastic models presented earlier in the text, and exercises are included throughout to reinforce essential concepts. The second edition of Classical and Spatial Stochastic Processes is suitable as a textbook for courses in stochastic processes at the advanced-undergraduate and graduate levels, or as a self-study resource for researchers and practitioners in mathematics, engineering, physics, and mathematical biology. Reviews of the first edition: An appetizing textbook for a f...
Energy Technology Data Exchange (ETDEWEB)
Zhang, Qichun; Zhou, Jinglin; Wang, Hong; Chai, Tianyou
2016-08-31
In this paper, stochastic coupling attenuation is investigated for a class of multi-variable bilinear stochastic systems and a novel output feedback m-block backstepping controller with linear estimator is designed, where gradient descent optimization is used to tune the design parameters of the controller. It has been shown that the trajectories of the closed-loop stochastic systems are bounded in probability sense and the stochastic coupling of the system outputs can be effectively attenuated by the proposed control algorithm. Moreover, the stability of the stochastic systems is analyzed and the effectiveness of the proposed method has been demonstrated using a simulated example.
Stochastic and coherent dynamics of single and coupled beta cells
DEFF Research Database (Denmark)
phenomenon, modeled by a slow-fast nonlinear system of ordinary differential equations (ODEs). The single cell oscillations are complex as the dynamical behavior is a result of traversing a series of saddle node and homoclinic bifurcations, controlled by the slow variable. We shall present results...... is the simplest reaction-diffusion partial differential equation....... on the burst period as function of an external applied stochastic term and use a technique for reducing the stochastic differential equations to ODEs for the average and higher order moments. The later method is approximate and we shall discuss the limits of validity. The individual beta cells are coupled...
Gene regulation and noise reduction by coupling of stochastic processes
Ramos, Alexandre F.; Hornos, José Eduardo M.; Reinitz, John
2015-02-01
Here we characterize the low-noise regime of a stochastic model for a negative self-regulating binary gene. The model has two stochastic variables, the protein number and the state of the gene. Each state of the gene behaves as a protein source governed by a Poisson process. The coupling between the two gene states depends on protein number. This fact has a very important implication: There exist protein production regimes characterized by sub-Poissonian noise because of negative covariance between the two stochastic variables of the model. Hence the protein numbers obey a probability distribution that has a peak that is sharper than those of the two coupled Poisson processes that are combined to produce it. Biochemically, the noise reduction in protein number occurs when the switching of the genetic state is more rapid than protein synthesis or degradation. We consider the chemical reaction rates necessary for Poisson and sub-Poisson processes in prokaryotes and eucaryotes. Our results suggest that the coupling of multiple stochastic processes in a negative covariance regime might be a widespread mechanism for noise reduction.
Stochastic population oscillations in spatial predator-prey models
Energy Technology Data Exchange (ETDEWEB)
Taeuber, Uwe C, E-mail: tauber@vt.edu [Department of Physics, Virginia Tech, Blacksburg, VA 24061-0435 (United States)
2011-09-15
It is well-established that including spatial structure and stochastic noise in models for predator-prey interactions invalidates the classical deterministic Lotka-Volterra picture of neutral population cycles. In contrast, stochastic models yield long-lived, but ultimately decaying erratic population oscillations, which can be understood through a resonant amplification mechanism for density fluctuations. In Monte Carlo simulations of spatial stochastic predator-prey systems, one observes striking complex spatio-temporal structures. These spreading activity fronts induce persistent correlations between predators and prey. In the presence of local particle density restrictions (finite prey carrying capacity), there exists an extinction threshold for the predator population. The accompanying continuous non-equilibrium phase transition is governed by the directed-percolation universality class. We employ field-theoretic methods based on the Doi-Peliti representation of the master equation for stochastic particle interaction models to (i) map the ensuing action in the vicinity of the absorbing state phase transition to Reggeon field theory, and (ii) to quantitatively address fluctuation-induced renormalizations of the population oscillation frequency, damping, and diffusion coefficients in the species coexistence phase.
The spatial scale of local adaptation in a stochastic environment.
Hadfield, Jarrod D
2016-07-01
The distribution of phenotypes in space will be a compromise between adaptive plasticity and local adaptation increasing the fit of phenotypes to local conditions and gene flow reducing that fit. Theoretical models on the evolution of quantitative characters on spatially explicit landscapes have only considered scenarios where optimum trait values change as deterministic functions of space. Here, these models are extended to include stochastic spatially autocorrelated aspects to the environment, and consequently the optimal phenotype. Under these conditions, the regression of phenotype on the environmental variable becomes steeper as the spatial scale on which populations are sampled becomes larger. Under certain deterministic models - such as linear clines - the regression is constant. The way in which the regression changes with spatial scale is informative about the degree of phenotypic plasticity, the relative scale of effective gene flow and the environmental dependency of selection. Connections to temporal models are discussed.
Chaos synchronization of two stochastically coupled random Boolean networks
Energy Technology Data Exchange (ETDEWEB)
Hung, Y.-C. [Department of Physics, National Sun Yat-sen University, Kaohsiung, Taiwan (China) and Nonlinear Science Group, Department of Physics, National Kaohsiung Normal University, Kaohsiung, Taiwan (China)]. E-mail: d9123801@student.nsysu.edu.tw; Ho, M.-C. [Nonlinear Science Group, Department of Physics, National Kaohsiung Normal University, Kaohsiung, Taiwan (China)]. E-mail: t1603@nknucc.nknu.edu.tw; Lih, J.-S. [Department of Physics and Geoscience, National Pingtung University of Education, Pingtung, Taiwan (China); Nonlinear Science Group, Department of Physics, National Kaohsiung Normal University, Kaohsiung, Taiwan (China); Jiang, I-M. [Department of Physics, National Sun Yat-sen University, Kaohsiung, Taiwan (China); Nonlinear Science Group, Department of Physics, National Kaohsiung Normal University, Kaohsiung, Taiwan (China)
2006-07-24
In this Letter, we study the chaos synchronization of two stochastically coupled random Boolean networks (RBNs). Instead of using the 'site-by-site and all-to-all' coupling, the coupling mechanism we consider here is that: the nth cell in a network is linked by an arbitrarily chosen cell in the other network with probability {rho}, and it possesses no links with probability 1-{rho}. The mechanism is useful to investigate the coevolution of biological species via horizontal genetic exchange. We show that the density evolution of networks can be described by two deterministic coupled polynomial maps. The complete synchronization occurs when the coupling parameter exceeds a critical value. Moreover, the reverse bifurcations in inhomogeneous condition are observed and under our discussion.
Simulation of Stochastic Processes by Coupled ODE-PDE
Zak, Michail
2008-01-01
A document discusses the emergence of randomness in solutions of coupled, fully deterministic ODE-PDE (ordinary differential equations-partial differential equations) due to failure of the Lipschitz condition as a new phenomenon. It is possible to exploit the special properties of ordinary differential equations (represented by an arbitrarily chosen, dynamical system) coupled with the corresponding Liouville equations (used to describe the evolution of initial uncertainties in terms of joint probability distribution) in order to simulate stochastic processes with the proscribed probability distributions. The important advantage of the proposed approach is that the simulation does not require a random-number generator.
Cooperative Effects of Noise and Coupling on Stochastic Dynamics of a Membrane-Bulk Coupling Model
Institute of Scientific and Technical Information of China (English)
TANG Jun; JIA Ya; YI Ming
2009-01-01
Based on a membrane-bulk coupling cell model proposed by Gomez-Marin et al. [ Phys. Rev. Lett. 98 (2007) 168303], the cooperative effects of noise and coupling on the stochastic dynamical behavior are investigated, For parameters in a certain region, the oscillation can be induced by the cooperative effect of noise and coupling. Whether considering the coupling or not, corresponding coherence resonance phenomena are observed. Furthermore, the effects of two coupling parameters, cell size L and coupling intensity k, on the noise-induced oscillation of membranes are studied. Contrary effects of noise are found in and out of the deterministic oscillatory regions.
Dimension reduction in stochastic analysis of coupled systems
Arnst, Maarten; Phipps, Eric; Red-Horse, John
2011-01-01
Coupled models with multiple physics, scales and/or domains arise in numerous areas of science and engineering. A key challenge in the formulation and implementation of coupled models is in facilitating the communication of information across physics, scale and/or domain interfaces. In a probabilistic context, any information that is communicated between model components is described in a statistical manner and requires an adapted probabilistic representation. While the number of sources of uncertainty can be expected to be large in many coupled problems, our contention is that exchanged statistical information often resides in a much lower dimensional space. In this work, we thus investigate the use of dimension-reduction techniques for the representation of exchanged information. We describe an adaptation of the Karhunen-Loeve decomposition to represent information as it is passed from component to component in a stochastic coupled model. The range of validity of the proposed dimension reduction is demonstr...
A stochastic model for circadian rhythms from coupled ultradian oscillators
Directory of Open Access Journals (Sweden)
Illner Reinhard
2007-01-01
Full Text Available Abstract Background Circadian rhythms with varying components exist in organisms ranging from humans to cyanobacteria. A simple evolutionarily plausible mechanism for the origin of such a variety of circadian oscillators, proposed in earlier work, involves the non-disruptive coupling of pre-existing ultradian transcriptional-translational oscillators (TTOs, producing "beats," in individual cells. However, like other TTO models of circadian rhythms, it is important to establish that the inherent stochasticity of the protein binding and unbinding does not invalidate the finding of clear oscillations with circadian period. Results The TTOs of our model are described in two versions: 1 a version in which the activation or inhibition of genes is regulated stochastically, where the 'unoccupied" (or "free" time of the site under consideration depends on the concentration of a protein complex produced by another site, and 2 a deterministic, "time-averaged" version in which the switching between the "free" and "occupied" states of the sites occurs so rapidly that the stochastic effects average out. The second case is proved to emerge from the first in a mathematically rigorous way. Numerical results for both scenarios are presented and compared. Conclusion Our model proves to be robust to the stochasticity of protein binding/unbinding at experimentally determined rates and even at rates several orders of magnitude slower. We have not only confirmed this by numerical simulation, but have shown in a mathematically rigorous way that the time-averaged deterministic system is indeed the fast-binding-rate limit of the full stochastic model.
Stochastic heterogeneous interaction promotes cooperation in spatial prisoner's dilemma game.
Directory of Open Access Journals (Sweden)
Ping Zhu
Full Text Available Previous studies mostly investigate player's cooperative behavior as affected by game time-scale or individual diversity. In this paper, by involving both time-scale and diversity simultaneously, we explore the effect of stochastic heterogeneous interaction. In our model, the occurrence of game interaction between each pair of linked player obeys a random probability, which is further described by certain distributions. Simulations on a 4-neighbor square lattice show that the cooperation level is remarkably promoted when stochastic heterogeneous interaction is considered. The results are then explained by investigating the mean payoffs, the mean boundary payoffs and the transition probabilities between cooperators and defectors. We also show some typical snapshots and evolution time series of the system. Finally, the 8-neighbor square lattice and BA scale-free network results indicate that the stochastic heterogeneous interaction can be robust against different network topologies. Our work may sharpen the understanding of the joint effect of game time-scale and individual diversity on spatial games.
Stochastic heterogeneous interaction promotes cooperation in spatial prisoner's dilemma game.
Zhu, Ping; Wei, Guiyi
2014-01-01
Previous studies mostly investigate player's cooperative behavior as affected by game time-scale or individual diversity. In this paper, by involving both time-scale and diversity simultaneously, we explore the effect of stochastic heterogeneous interaction. In our model, the occurrence of game interaction between each pair of linked player obeys a random probability, which is further described by certain distributions. Simulations on a 4-neighbor square lattice show that the cooperation level is remarkably promoted when stochastic heterogeneous interaction is considered. The results are then explained by investigating the mean payoffs, the mean boundary payoffs and the transition probabilities between cooperators and defectors. We also show some typical snapshots and evolution time series of the system. Finally, the 8-neighbor square lattice and BA scale-free network results indicate that the stochastic heterogeneous interaction can be robust against different network topologies. Our work may sharpen the understanding of the joint effect of game time-scale and individual diversity on spatial games.
Transport for Stochastic System with Infinite Locally Coupled Oscillators
Institute of Scientific and Technical Information of China (English)
ZHAO Ying-Kui; LI Jing-Hui; ZHAO Xian-Geng
2003-01-01
We consider the transport of particles for spatially periodic system with infinite locally coupled oscillatorsdriven by additive and multiplicative noises. A formula of the probability current derived by us shows that the couplingamong the infinite oscillators is an ingredient for transport. This coupling of the oscillators can induce transport ofparticles in the absence of the correlation of the additive and multiplicative noises, even without the multiplicative noise.
Sokolowski, Thomas; Tkačik, Gašper
Spatio-temporal protein signals play a crucial role in communicating information within and between cells. However, their ability to convey signals robustly is hampered by noise in gene regulation and biochemical transport, occuring at low copy numbers. While we increasingly understand distinct strategies of biochemical noise control, it remains unclear how nature orchestrates them to maximize information flow. Our recent work extends our information-theoretic framework for gene regulation to an explicitly spatial setting. We constructed a stochastic model enabling fast calculation of local means and variances in a spatially coupled gene regulatory system, which we use for rigorous quantification of information flow in an ensemble of units sensing a spatially distributed input and exchanging information via diffusion. By applying our framework to the paradigmatic Bcd-Hbk system in early fly development, we demonstrate that diffusive coupling can be of substantial benefit in encoding positional information, and uncover a novel optimal regulatory strategy relying on spatial coupling. Thanks to the generic methodology employed, our framework is universally applicable for realistic predictive modeling and data-driven inference of multicellular systems engaging in noisy communication. Institute of Science and Technology Austria, Am Campus 1, A-3400 Klosterneuburg, Austria.
A spatial stochastic programming model for timber and core area management under risk of fires
Yu Wei; Michael Bevers; Dung Nguyen; Erin Belval
2014-01-01
Previous stochastic models in harvest scheduling seldom address explicit spatial management concerns under the influence of natural disturbances. We employ multistage stochastic programming models to explore the challenges and advantages of building spatial optimization models that account for the influences of random stand-replacing fires. Our exploratory test models...
Stochastic simulation of spatially correlated geo-processes
Christakos, G.
1987-01-01
In this study, developments in the theory of stochastic simulation are discussed. The unifying element is the notion of Radon projection in Euclidean spaces. This notion provides a natural way of reconstructing the real process from a corresponding process observable on a reduced dimensionality space, where analysis is theoretically easier and computationally tractable. Within this framework, the concept of space transformation is defined and several of its properties, which are of significant importance within the context of spatially correlated processes, are explored. The turning bands operator is shown to follow from this. This strengthens considerably the theoretical background of the geostatistical method of simulation, and some new results are obtained in both the space and frequency domains. The inverse problem is solved generally and the applicability of the method is extended to anisotropic as well as integrated processes. Some ill-posed problems of the inverse operator are discussed. Effects of the measurement error and impulses at origin are examined. Important features of the simulated process as described by geomechanical laws, the morphology of the deposit, etc., may be incorporated in the analysis. The simulation may become a model-dependent procedure and this, in turn, may provide numerical solutions to spatial-temporal geologic models. Because the spatial simu??lation may be technically reduced to unidimensional simulations, various techniques of generating one-dimensional realizations are reviewed. To link theory and practice, an example is computed in detail. ?? 1987 International Association for Mathematical Geology.
A Comparison Theorem for Solution of the Fully Coupled Backward Stochastic Differential Equations
Institute of Scientific and Technical Information of China (English)
郭子君; 吴让泉
2004-01-01
The comparison theorems of solutions for BSDEs in fully coupled forward-backward stochastic differential equations (FBSDEs) are studied in this paper, here in the fully coupled FBSDEs the forward SDEs are the same structure.
Cascades on a stochastic pulse-coupled network.
Wray, C M; Bishop, S R
2014-09-12
While much recent research has focused on understanding isolated cascades of networks, less attention has been given to dynamical processes on networks exhibiting repeated cascades of opposing influence. An example of this is the dynamic behaviour of financial markets where cascades of buying and selling can occur, even over short timescales. To model these phenomena, a stochastic pulse-coupled oscillator network with upper and lower thresholds is described and analysed. Numerical confirmation of asynchronous and synchronous regimes of the system is presented, along with analytical identification of the fixed point state vector of the asynchronous mean field system. A lower bound for the finite system mean field critical value of network coupling probability is found that separates the asynchronous and synchronous regimes. For the low-dimensional mean field system, a closed-form equation is found for cascade size, in terms of the network coupling probability. Finally, a description of how this model can be applied to interacting agents in a financial market is provided.
Spatially-Coupled Random Access on Graphs
Liva, Gianluigi; Lentmaier, Michael; Chiani, Marco
2012-01-01
In this paper we investigate the effect of spatial coupling applied to the recently-proposed coded slotted ALOHA (CSA) random access protocol. Thanks to the bridge between the graphical model describing the iterative interference cancelation process of CSA over the random access frame and the erasure recovery process of low-density parity-check (LDPC) codes over the binary erasure channel (BEC), we propose an access protocol which is inspired by the convolutional LDPC code construction. The proposed protocol exploits the terminations of its graphical model to achieve the spatial coupling effect, attaining performance close to the theoretical limits of CSA. As for the convolutional LDPC code case, large iterative decoding thresholds are obtained by simply increasing the density of the graph. We show that the threshold saturation effect takes place by defining a suitable counterpart of the maximum-a-posteriori decoding threshold of spatially-coupled LDPC code ensembles. In the asymptotic setting, the proposed s...
Analytical approximations for spatial stochastic gene expression in single cells and tissues.
Smith, Stephen; Cianci, Claudia; Grima, Ramon
2016-05-01
Gene expression occurs in an environment in which both stochastic and diffusive effects are significant. Spatial stochastic simulations are computationally expensive compared with their deterministic counterparts, and hence little is currently known of the significance of intrinsic noise in a spatial setting. Starting from the reaction-diffusion master equation (RDME) describing stochastic reaction-diffusion processes, we here derive expressions for the approximate steady-state mean concentrations which are explicit functions of the dimensionality of space, rate constants and diffusion coefficients. The expressions have a simple closed form when the system consists of one effective species. These formulae show that, even for spatially homogeneous systems, mean concentrations can depend on diffusion coefficients: this contradicts the predictions of deterministic reaction-diffusion processes, thus highlighting the importance of intrinsic noise. We confirm our theory by comparison with stochastic simulations, using the RDME and Brownian dynamics, of two models of stochastic and spatial gene expression in single cells and tissues.
Achieving control and synchronization merely through a stochastically adaptive feedback coupling
Lin, Wei; Chen, Xin; Zhou, Shijie
2017-07-01
Techniques of deterministically adaptive feedback couplings have been successfully and extensively applied to realize control or/and synchronization in chaotic dynamical systems and even in complex dynamical networks. In this article, a technique of stochastically adaptive feedback coupling is novelly proposed to not only realize control in chaotic dynamical systems but also achieve synchronization in unidirectionally coupled systems. Compared with those deterministically adaptive couplings, the proposed stochastic technique interestingly shows some advantages from a physical viewpoint of time and energy consumptions. More significantly, the usefulness of the proposed stochastic technique is analytically validated by the theory of stochastic processes. It is anticipated that the proposed stochastic technique will be widely used in achieving system control and network synchronization.
Numerical Approach to Spatial Deterministic-Stochastic Models Arising in Cell Biology.
Directory of Open Access Journals (Sweden)
James C Schaff
2016-12-01
Full Text Available Hybrid deterministic-stochastic methods provide an efficient alternative to a fully stochastic treatment of models which include components with disparate levels of stochasticity. However, general-purpose hybrid solvers for spatially resolved simulations of reaction-diffusion systems are not widely available. Here we describe fundamentals of a general-purpose spatial hybrid method. The method generates realizations of a spatially inhomogeneous hybrid system by appropriately integrating capabilities of a deterministic partial differential equation solver with a popular particle-based stochastic simulator, Smoldyn. Rigorous validation of the algorithm is detailed, using a simple model of calcium 'sparks' as a testbed. The solver is then applied to a deterministic-stochastic model of spontaneous emergence of cell polarity. The approach is general enough to be implemented within biologist-friendly software frameworks such as Virtual Cell.
Mechanism by which spatially homogeneous Yang-Mills fields become stochastic
Energy Technology Data Exchange (ETDEWEB)
Avakyan, A.R.; Arutyunyan, S.G.; Baseyan, G.Z.
1982-11-20
A mechanical system with a nonzero angular momentum, corresponding to spatially homogeneous Yang-Mills fields, is analyzed. Numerical simulations have been carried out. A mechanism by which the fields become stochastic is found.
Stochastic and Macroscopic Thermodynamics of Strongly Coupled Systems
Jarzynski, Christopher
2017-01-01
We develop a thermodynamic framework that describes a classical system of interest S that is strongly coupled to its thermal environment E . Within this framework, seven key thermodynamic quantities—internal energy, entropy, volume, enthalpy, Gibbs free energy, heat, and work—are defined microscopically. These quantities obey thermodynamic relations including both the first and second law, and they satisfy nonequilibrium fluctuation theorems. We additionally impose a macroscopic consistency condition: When S is large, the quantities defined within our framework scale up to their macroscopic counterparts. By satisfying this condition, we demonstrate that a unifying framework can be developed, which encompasses both stochastic thermodynamics at one end, and macroscopic thermodynamics at the other. A central element in our approach is a thermodynamic definition of the volume of the system of interest, which converges to the usual geometric definition when S is large. We also sketch an alternative framework that satisfies the same consistency conditions. The dynamics of the system and environment are modeled using Hamilton's equations in the full phase space.
Accelerated stochastic and hybrid methods for spatial simulations of reaction-diffusion systems
Rossinelli, D; Bayati, B; Koumoutsakos, P.
2008-01-01
Spatial distributions characterize the evolution of reaction-diffusion models of several physical, chemical, and biological systems. We present two novel algorithms for the efficient simulation of these models: Spatial т-Leaping (Sт -Leaping), employing a unified acceleration of the stochastic simulation of reaction and diffusion, and Hybrid т-Leaping (Hт-Leaping), combining a deterministic diffusion approximation with a т-Leaping acceleration of the stochastic reactions. The algorithms are v...
Guo,Qiang; Rajewski, Daniel; Takle, Eugene; Ganapathysubramanian, Baskar
2016-01-01
Current wind turbine simulations successfully use turbulence generating tools for modeling behavior. However, they lack the ability to reproduce variabilities in wind dynamics and inherent stochastic structures (like temporal and spatial coherences, sporadic bursts, high shear regions). This necessitates a more realistic parameterization of the wind that encodes location-, topography-, diurnal-, seasonal and stochastic affects. In this work, we develop a hierarchical temporal and spatial deco...
A Spatial Clustering Approach for Stochastic Fracture Network Modelling
Seifollahi, S.; Dowd, P. A.; Xu, C.; Fadakar, A. Y.
2014-07-01
Fracture network modelling plays an important role in many application areas in which the behaviour of a rock mass is of interest. These areas include mining, civil, petroleum, water and environmental engineering and geothermal systems modelling. The aim is to model the fractured rock to assess fluid flow or the stability of rock blocks. One important step in fracture network modelling is to estimate the number of fractures and the properties of individual fractures such as their size and orientation. Due to the lack of data and the complexity of the problem, there are significant uncertainties associated with fracture network modelling in practice. Our primary interest is the modelling of fracture networks in geothermal systems and, in this paper, we propose a general stochastic approach to fracture network modelling for this application. We focus on using the seismic point cloud detected during the fracture stimulation of a hot dry rock reservoir to create an enhanced geothermal system; these seismic points are the conditioning data in the modelling process. The seismic points can be used to estimate the geographical extent of the reservoir, the amount of fracturing and the detailed geometries of fractures within the reservoir. The objective is to determine a fracture model from the conditioning data by minimizing the sum of the distances of the points from the fitted fracture model. Fractures are represented as line segments connecting two points in two-dimensional applications or as ellipses in three-dimensional (3D) cases. The novelty of our model is twofold: (1) it comprises a comprehensive fracture modification scheme based on simulated annealing and (2) it introduces new spatial approaches, a goodness-of-fit measure for the fitted fracture model, a measure for fracture similarity and a clustering technique for proposing a locally optimal solution for fracture parameters. We use a simulated dataset to demonstrate the application of the proposed approach
Wadop Ngouongo, Y. J.; Djuidjé Kenmoé, G.; Kofané, T. C.
2017-04-01
This work presents the characterization of stochastic resonance (SR) and stochastic antiresonance (SAR) in terms of hysteresis loop area (HLA). In connection with SR and SAR phenomena, we study the dynamics of a chain of particles coupled by nonlinear springs in a periodic sinusoidal potential. The dependence of the coupling parameter as well as the system size on SR and SAR is analysed. We consider the role played by the nonlinear coupling on the SR. We show that there is a range of coupling parameter where only SAR is observed, after this range the SR can occur, however, there also exists a range where neither SAR nor SR appear. It is noted that the maximum and the minimum of the average input energy increases with the coupling parameter. Also demonstrate that there exists an optimal value of the number of particles N for which the average input energy of the first particle reaches the saturation.
FULLY COUPLED FORWARD-BACKWARD STOCHASTIC DIFFERENTIAL EQUATIONS WITH GENERAL MARTINGALE
Institute of Scientific and Technical Information of China (English)
无
2006-01-01
The article first studies the fully coupled Forward-Backward Stochastic Differential Equations (FBSDEs) with the continuous local martingale. The article is mainly divided into two parts. In the first part, it considers Backward Stochastic Differential Equations (BSDEs) with the continuous local martingale. Then, on the basis of it, in the second part it considers the fully coupled FBSDEs with the continuous local martingale.It is proved that their solutions exist and are unique under the monotonicity conditions.
Directory of Open Access Journals (Sweden)
Diniz-Filho José Alexandre Felizola
2000-01-01
Full Text Available In the present study, we used both simulations and real data set analyses to show that, under stochastic processes of population differentiation, the concepts of spatial heterogeneity and spatial pattern overlap. In these processes, the proportion of variation among and within a population (measured by G ST and 1 - G ST, respectively is correlated with the slope and intercept of a Mantel's test relating genetic and geographic distances. Beyond the conceptual interest, the inspection of the relationship between population heterogeneity and spatial pattern can be used to test departures from stochasticity in the study of population differentiation.
Spatially varying embedded stochastic galerkin methods for steady-state PDEs.
Energy Technology Data Exchange (ETDEWEB)
Cyr, Eric C
2013-07-01
Existing discretizations for stochastic PDEs, based on a tensor product between the deterministic basis and the stochastic basis, treat the required resolution of uncertainty as uniform across the physical domain. However, solutions to many PDEs of interest exhibit spatially localized features that may result in uncertainty being severely over or under-resolved by existing discretizations. In this report, we explore the mechanics and accuracy of using a spatially varying stochastic expansion. This is achieved through an adaptive refinement algorithm where simple error estimates are used to independently drive refinement of the stochastic basis at each point in the physical domain. Results are presented comparing the accuracy of the adaptive techinque to the accuracy achieved using uniform refinement.
Spatially varying embedded stochastic galerkin methods for steady-state PDEs.
Energy Technology Data Exchange (ETDEWEB)
Cyr, Eric C
2013-07-01
Existing discretizations for stochastic PDEs, based on a tensor product between the deterministic basis and the stochastic basis, treat the required resolution of uncertainty as uniform across the physical domain. However, solutions to many PDEs of interest exhibit spatially localized features that may result in uncertainty being severely over or under-resolved by existing discretizations. In this report, we explore the mechanics and accuracy of using a spatially varying stochastic expansion. This is achieved through an adaptive refinement algorithm where simple error estimates are used to independently drive refinement of the stochastic basis at each point in the physical domain. Results are presented comparing the accuracy of the adaptive techinque to the accuracy achieved using uniform refinement.
Exact stochastic simulation of coupled chemical reactions with delays
Cai, Xiaodong
2007-03-01
Gillespie's exact stochastic simulation algorithm (SSA) [J. Phys. Chem. 81, 2350 (1977)] has been widely used to simulate the stochastic dynamics of chemically reacting systems. In this algorithm, it is assumed that all reactions occur instantly. While this is true in many cases, it is also possible that some chemical reactions, such as gene transcription and translation in living cells, take certain time to finish after they are initiated. Thus, the product of such reactions will emerge after certain delays. Apparently, Gillespie's SSA is not an exact algorithm for chemical reaction systems with delays. In this paper, the author develops an exact SSA for chemical reaction systems with delays, based upon the same fundamental premise of stochastic kinetics used by Gillespie in the development of his SSA. He then shows that an algorithm modified from Gillespie's SSA by Barrio et al. [PLOS Comput. Biol. 2, 1017 (2006)] is also an exact SSA for chemical reaction systems with delays, but it needs to generate more random variables than the author's algorithm.
Dung Tuan Nguyen
2012-01-01
Forest harvest scheduling has been modeled using deterministic and stochastic programming models. Past models seldom address explicit spatial forest management concerns under the influence of natural disturbances. In this research study, we employ multistage full recourse stochastic programming models to explore the challenges and advantages of building spatial...
Accelerated stochastic and hybrid methods for spatial simulations of reaction diffusion systems
Rossinelli, Diego; Bayati, Basil; Koumoutsakos, Petros
2008-01-01
Spatial distributions characterize the evolution of reaction-diffusion models of several physical, chemical, and biological systems. We present two novel algorithms for the efficient simulation of these models: Spatial τ-Leaping ( Sτ-Leaping), employing a unified acceleration of the stochastic simulation of reaction and diffusion, and Hybrid τ-Leaping ( Hτ-Leaping), combining a deterministic diffusion approximation with a τ-Leaping acceleration of the stochastic reactions. The algorithms are validated by solving Fisher's equation and used to explore the role of the number of particles in pattern formation. The results indicate that the present algorithms have a nearly constant time complexity with respect to the number of events (reaction and diffusion), unlike the exact stochastic simulation algorithm which scales linearly.
Spencer, James S
2015-01-01
We describe further details of the Stochastic Coupled Cluster method and a diagnostic of such calculations, the shoulder height, akin to the plateau found in Full Configuration Interaction Quantum Monte Carlo. We describe an initiator modification to Stochastic Coupled Cluster Theory and show that initiator calculations can be extrapolated to the unbiased limit. We apply this method to the 3D 14-electron uniform electron gas and present complete basis set limit values of the CCSD and previously unattainable CCSDT correlation energies for up to rs = 2, showing a requirement to include triple excitations to accurately calculate energies at high densities.
Escaff, Daniel; Harbola, Upendra; Lindenberg, Katja
2012-07-01
We present a model of identical coupled two-state stochastic units, each of which in isolation is governed by a fixed refractory period. The nonlinear coupling between units directly affects the refractory period, which now depends on the global state of the system and can therefore itself become time dependent. At weak coupling the array settles into a quiescent stationary state. Increasing coupling strength leads to a saddle node bifurcation, beyond which the quiescent state coexists with a stable limit cycle of nonlinear coherent oscillations. We explicitly determine the critical coupling constant for this transition.
Institute of Scientific and Technical Information of China (English)
Yang Xinsong; Cao Jinde
2012-01-01
In this article,we consider the global chaotic synchronization of general coupled neural networks,in which subsystems have both discrete and distributed delays.Stochastic perturbations between subsystems are also considered.On the basis of two simple adaptive pinning feedback control schemes,Lyapunov functional method,and stochastic analysis approach,several sufficient conditions are developed to guarantee global synchronization of the coupled neural networks with two kinds of delay couplings,even if only partial states of the nodes are coupled.The outer-coupling matrices may be symmetric or asymmetric.Unlike existing results that an isolate node is introduced as the pinning target,we pin to help the network realizing synchronization without introducing any isolate node when the network is not synchronized.As a by product,sufficient conditions under which the network realizes synchronization without control are derived.Numerical simulations confirm the effectiveness of the obtained results.
Tonini, A.; Pede, V.
2011-01-01
In this paper, a stochastic frontier model accounting for spatial dependency is developed using generalized maximum entropy estimation. An application is made for measuring total factor productivity in European agriculture. The empirical results show that agricultural productivity growth in Europe i
Stochastic spatial structured model for vertically and horizontally transmitted infection
Silva, Ana T. C.; Assis, Vladimir R. V.; Pinho, Suani T. R.; Tomé, Tânia; de Oliveira, Mário J.
2017-02-01
We study a space structured stochastic model for vertical and horizontal transmitted infection. By means of simple and pair mean-field approximation as well as Monte Carlo simulations, we construct the phase diagram, which displays four states: healthy (H), infected (I), extinct (E), and coexistent (C). In state H only healthy hosts are present, whereas in state I only infected hosts are present. The state E is characterized by the extinction of the hosts whereas in state C there is a coexistence of infected and healthy hosts. In addition to the usual scenario with continuous transition between the I, C and H phases, we found a different scenario with the suppression of the C phase and a discontinuous phase transition between I and H phases.
Doiron, Brent; Lindner, Benjamin; Longtin, André; Maler, Leonard; Bastian, Joseph
2004-07-01
We present results from a novel experimental paradigm to investigate the influence of spatial correlations of stimuli on electrosensory neural network dynamics. Further, a new theoretical analysis for the dynamics of a model network of stochastic leaky integrate-and-fire neurons with delayed feedback is proposed. Experiment and theory for this system both establish that spatial correlations induce a network oscillation, the strength of which is proportional to the degree of stimulus correlation at constant total stimulus power.
Spatially indirect excitons in coupled quantum wells
Energy Technology Data Exchange (ETDEWEB)
Lai, Chih-Wei Eddy [Univ. of California, Berkeley, CA (United States)
2004-03-01
Microscopic quantum phenomena such as interference or phase coherence between different quantum states are rarely manifest in macroscopic systems due to a lack of significant correlation between different states. An exciton system is one candidate for observation of possible quantum collective effects. In the dilute limit, excitons in semiconductors behave as bosons and are expected to undergo Bose-Einstein condensation (BEC) at a temperature several orders of magnitude higher than for atomic BEC because of their light mass. Furthermore, well-developed modern semiconductor technologies offer flexible manipulations of an exciton system. Realization of BEC in solid-state systems can thus provide new opportunities for macroscopic quantum coherence research. In semiconductor coupled quantum wells (CQW) under across-well static electric field, excitons exist as separately confined electron-hole pairs. These spatially indirect excitons exhibit a radiative recombination time much longer than their thermal relaxation time a unique feature in direct band gap semiconductor based structures. Their mutual repulsive dipole interaction further stabilizes the exciton system at low temperature and screens in-plane disorder more effectively. All these features make indirect excitons in CQW a promising system to search for quantum collective effects. Properties of indirect excitons in CQW have been analyzed and investigated extensively. The experimental results based on time-integrated or time-resolved spatially-resolved photoluminescence (PL) spectroscopy and imaging are reported in two categories. (i) Generic indirect exciton systems: general properties of indirect excitons such as the dependence of exciton energy and lifetime on electric fields and densities were examined. (ii) Quasi-two-dimensional confined exciton systems: highly statistically degenerate exciton systems containing more than tens of thousands of excitons within areas as small as (10 micrometer)^{2} were
Arnst, Maarten; Phipps, Eric; Red-Horse, John
2011-01-01
Coupled models with multiple physics, scales and/or domains dominate numerous areas of science and engineering. A key challenge in the formulation and implementation of coupled models is in facilitating the communication of information across physics, scale or domain interfaces. In a probabilistic context, any information that is communicated between model components is described in a statistical manner and requires a probabilistic representation. While the number of sources of uncertainty is often large in many coupled problems, our contention is that exchanged statistical information often resides in a much lower dimensional space. In this work, we thus leverage dimension-reduction techniques to lower the stochastic dimension of uncertainty representations as they are passed from component to component in a stochastic coupled model. The main objective of the paper is to propose measure-transformation techniques that allow for this dimension reduction to be exploited to achieve computational gains. These tec...
Fu, Jin; Wu, Sheng; Li, Hong; Petzold, Linda R.
2014-10-01
The inhomogeneous stochastic simulation algorithm (ISSA) is a fundamental method for spatial stochastic simulation. However, when diffusion events occur more frequently than reaction events, simulating the diffusion events by ISSA is quite costly. To reduce this cost, we propose to use the time dependent propensity function in each step. In this way we can avoid simulating individual diffusion events, and use the time interval between two adjacent reaction events as the simulation stepsize. We demonstrate that the new algorithm can achieve orders of magnitude efficiency gains over widely-used exact algorithms, scales well with increasing grid resolution, and maintains a high level of accuracy.
Energy Technology Data Exchange (ETDEWEB)
Fu, Jin, E-mail: iamfujin@hotmail.com [Department of Computer Science, University of California, Santa Barbara (United States); Wu, Sheng, E-mail: sheng@cs.ucsb.edu [Department of Computer Science, University of California, Santa Barbara (United States); Li, Hong, E-mail: hong.li@teradata.com [Teradata Inc., El Segundo, California (United States); Petzold, Linda R., E-mail: petzold@cs.ucsb.edu [Department of Computer Science, University of California, Santa Barbara (United States)
2014-10-01
The inhomogeneous stochastic simulation algorithm (ISSA) is a fundamental method for spatial stochastic simulation. However, when diffusion events occur more frequently than reaction events, simulating the diffusion events by ISSA is quite costly. To reduce this cost, we propose to use the time dependent propensity function in each step. In this way we can avoid simulating individual diffusion events, and use the time interval between two adjacent reaction events as the simulation stepsize. We demonstrate that the new algorithm can achieve orders of magnitude efficiency gains over widely-used exact algorithms, scales well with increasing grid resolution, and maintains a high level of accuracy.
Non- Markovian Quantum Stochastic Equation For Two Coupled Oscillators
Alpomishev, E X
2016-01-01
The system of nonlinear Langevin equations was obtained by using Hamiltonian's operator of two coupling quantum oscillators which are interacting with heat bath. By using the analytical solution of these equations, the analytical expressions for transport coefficients was found. Generalized Langevin equations and fluctuation-dissipation relations are derived for the case of a nonlinear non-Markovian noise. The explicit expressions for the time-dependent friction and diffusion coefficients are presented for the case of linear couplings in the coordinate between the collective two coupled harmonic oscillators and heat bath.
Spatial and space-time correlations in systems of subpopulations with stochastic migration.
Epperson, B K
1994-10-01
The great majority of models of the population genetics of subdivided populations have made the simplifying assumption that the gene frequencies in migrant groups are deterministic. The present paper examines models which more closely mimic natural conditions, in which the gene frequencies in migrant groups are subject to stochastic effects. It is shown that some types of stochastic migration can cause dramatic changes in spatial correlations and variance. These changes depend on how the stochastic migration effects in the gene frequency recursion equations are shared among nearby subpopulations during the same generation. Only for cases where the effects are completely unshared are the equilibrium spatial and space-time correlations among adult subpopulations unaffected, but the variance is always inflated. The analyses here use novel methods, by recasting population genetic migration-drift models as space-time autoregressive moving average (STARMA) processes. Recent theorems for STARMA processes are employed for finding the spatial correlations, and for the first time in population genetics theory the complete set of space-time correlations, for systems with general patterns of migration rates and numbers of spatial dimensions. The space-time correlations provide a uniquely detailed description of a system, and thus form a link between observed spatial autocorrelation statistics and the underlying space-time population genetic process. STARMA theoretical processes have direct statistical analogues that can be applied for process identification, parameter estimation, model fitting, and forecasting in real systems.
Marchetti, Luca; Priami, Corrado; Thanh, Vo Hong
2016-07-01
This paper introduces HRSSA (Hybrid Rejection-based Stochastic Simulation Algorithm), a new efficient hybrid stochastic simulation algorithm for spatially homogeneous biochemical reaction networks. HRSSA is built on top of RSSA, an exact stochastic simulation algorithm which relies on propensity bounds to select next reaction firings and to reduce the average number of reaction propensity updates needed during the simulation. HRSSA exploits the computational advantage of propensity bounds to manage time-varying transition propensities and to apply dynamic partitioning of reactions, which constitute the two most significant bottlenecks of hybrid simulation. A comprehensive set of simulation benchmarks is provided for evaluating performance and accuracy of HRSSA against other state of the art algorithms.
Energy Technology Data Exchange (ETDEWEB)
Marchetti, Luca, E-mail: marchetti@cosbi.eu [The Microsoft Research – University of Trento Centre for Computational and Systems Biology (COSBI), Piazza Manifattura, 1, 38068 Rovereto (Italy); Priami, Corrado, E-mail: priami@cosbi.eu [The Microsoft Research – University of Trento Centre for Computational and Systems Biology (COSBI), Piazza Manifattura, 1, 38068 Rovereto (Italy); University of Trento, Department of Mathematics (Italy); Thanh, Vo Hong, E-mail: vo@cosbi.eu [The Microsoft Research – University of Trento Centre for Computational and Systems Biology (COSBI), Piazza Manifattura, 1, 38068 Rovereto (Italy)
2016-07-15
This paper introduces HRSSA (Hybrid Rejection-based Stochastic Simulation Algorithm), a new efficient hybrid stochastic simulation algorithm for spatially homogeneous biochemical reaction networks. HRSSA is built on top of RSSA, an exact stochastic simulation algorithm which relies on propensity bounds to select next reaction firings and to reduce the average number of reaction propensity updates needed during the simulation. HRSSA exploits the computational advantage of propensity bounds to manage time-varying transition propensities and to apply dynamic partitioning of reactions, which constitute the two most significant bottlenecks of hybrid simulation. A comprehensive set of simulation benchmarks is provided for evaluating performance and accuracy of HRSSA against other state of the art algorithms.
Coupling of spatially partially coherent beams into planar waveguides.
Partanen, Henri; Tervo, Jani; Turunen, Jari
2015-03-23
The second-order coherence theory of partially spatially coherent light and the overlap integral method are applied to study the end-coupling of stationary multimode light beams into planar waveguides. A method is presented for the determination of the cross-spectral density function of the guided field. Examples are given on the effects of spatial coherence, lateral shift, angular tilt, and defocusing of the incident beam on the coupling efficiency, spatial coherence, and propagation characteristics of the guided field.
Synchronization of Coupled Stochastic Systems Driven by α-Stable Lévy Noises
Directory of Open Access Journals (Sweden)
Anhui Gu
2013-01-01
Full Text Available The synchronization of the solutions to coupled stochastic systems of N-Marcus stochastic ordinary differential equations which are driven by α-stable Lévy noises is investigated (N∈ℕ,1<α<2. We obtain the synchronization between two solutions and among different components of solutions under certain dissipative conditions. The synchronous phenomena persist no matter how large the intensity of the environment noises. These results generalize the work of two Marcus canonical equations in X. M. Liu et al.' s (2010.
Qian, Min; Zhang, Xue-Juan
2002-03-01
This article investigates the influence of noise in a two-dimensional square array of coupled nonlinear oscillators without periodic driving. Array enhanced stochastic resonance under global as well as local noise perturbation is shown to exist under a crucial condition: the value of the rotation number of the deterministic system being zero. Meanwhile, the stochastic synchronization phenomenon is displayed in a wide range of noise intensity whether noise is added globally or locally. Furthermore, for every oscillator, the peak frequency is shown to agree with the rotation number much better than in the uncoupled system.
Yang, Bo; Zhang, Xiao; Zhang, Lu; Luo, Mao-Kang
2016-08-01
The long-time collective behavior of globally coupled Langevin equations in a dichotomous fluctuating potential driven by a periodic source is investigated. By describing the collective behavior using the moments of the mean field and single-particle displacements, we study stochastic resonance and synchronization using the exact steady-state solutions and related stability criteria. Based on the simulation results and the criterion of the stationary regime, the notable differences between the stationary and nonstationary regimes are demonstrated. For the stationary regime, stochastic resonance with synchronization is discussed, and for the nonstationary regime, the volatility clustering phenomenon is observed.
Chaotic synchronization in coupled spatially extended beam-plasma systems
Filatov, Roman A.; Hramov, Alexander E.; ALEXEY A. KORONOVSKII
2006-01-01
The appearance of the chaotic synchronization regimes has been discovered for the coupled spatially extended beam-plasma Pierce systems. The coupling was introduced only on the right bound of each subsystem. It has been shown that with coupling increase the spatially extended beam-plasma systems show the transition from asynchronous behavior to the phase synchronization and then to the complete synchronization regime. For the consideration of the chaotic synchronization we used the concept of...
Designing a stochastic genetic switch by coupling chaos and bistability
Energy Technology Data Exchange (ETDEWEB)
Zhao, Xiang [State Key Laboratory for Mesoscopic Physics and School of Physics, Peking University, Beijing 100871 (China); Ouyang, Qi [State Key Laboratory for Mesoscopic Physics and School of Physics, Peking University, Beijing 100871 (China); Center for Quantitative Biology, Peking University, Beijing 100871 (China); The Peking-Tsinghua Center for Life Sciences, Beijing 100871 (China); Wang, Hongli, E-mail: hlwang@pku.edu.cn [State Key Laboratory for Mesoscopic Physics and School of Physics, Peking University, Beijing 100871 (China); Center for Quantitative Biology, Peking University, Beijing 100871 (China)
2015-11-15
In stem cell differentiation, a pluripotent stem cell becomes progressively specialized and generates specific cell types through a series of epigenetic processes. How cells can precisely determine their fate in a fluctuating environment is a currently unsolved problem. In this paper, we suggest an abstract gene regulatory network to describe mathematically the differentiation phenomenon featuring stochasticity, divergent cell fates, and robustness. The network consists of three functional motifs: an upstream chaotic motif, a buffering motif of incoherent feed forward loop capable of generating a pulse, and a downstream motif which is bistable. The dynamic behavior is typically a transient chaos with fractal basin boundaries. The trajectories take transiently chaotic journeys before divergently settling down to the bistable states. The ratio of the probability that the high state is achieved to the probability that the low state is reached can maintain a constant in a population of cells with varied molecular fluctuations. The ratio can be turned up or down when proper parameters are adjusted. The model suggests a possible mechanism for the robustness against fluctuations that is prominently featured in pluripotent cell differentiations and developmental phenomena.
Selective effects of noise by stochastic multi-resonance in coupled cells system
Institute of Scientific and Technical Information of China (English)
2008-01-01
By investigating a stochastic model for intracellular calcium oscillations proposed by Hfer,we have analyzed the transmission behavior of calcium signaling in a one-dimensional two-way coupled hepatocytes system.It is shown that when the first cell is subjected to the external noise,the output signal-to-noise ratio(SNR) in the cell exhibits two maxima as a function of external noise intensity,indicating the occurrence of stochastic bi-resonance(SBR).It is more important that when cells are coupled together,the resonant behavior in the 1st cell propagates along the chain with different features through the coupling effect.The cells whose locations are comparatively close to or far from the 1st cell can show SBR,while the cells located in the middle position can display stochastic multi-resonance(SMR).Fur-thermore,the number of cells that can show SMR increases with coupling strength enhancing.These results indicate that the cells system may make an effective choice in response to external signaling induced by noise,through the mechanism of SMR by adjusting coupling strength.
Varouchakis, Epsilon A; Hristopulos, D T
2013-01-01
In sparsely monitored basins, accurate mapping of the spatial variability of groundwater level requires the interpolation of scattered data. This paper presents a comparison of deterministic interpolation methods, i.e. inverse distance weight (IDW) and minimum curvature (MC), with stochastic methods, i.e. ordinary kriging (OK), universal kriging (UK) and kriging with Delaunay triangulation (DK). The study area is the Mires Basin of Mesara Valley in Crete (Greece). This sparsely sampled basin has limited groundwater resources which are vital for the island's economy; spatial variations of the groundwater level are important for developing management and monitoring strategies. We evaluate the performance of the interpolation methods with respect to different statistical measures. The Spartan variogram family is applied for the first time to hydrological data and is shown to be optimal with respect to stochastic interpolation of this dataset. The three stochastic methods (OK, DK and UK) perform overall better than the deterministic counterparts (IDW and MC). DK, which is herein for the first time applied to hydrological data, yields the most accurate cross-validation estimate for the lowest value in the dataset. OK and UK lead to smooth isolevel contours, whilst DK and IDW generate more edges. The stochastic methods deliver estimates of prediction uncertainty which becomes highest near the southeastern border of the basin.
Chen, Weiliang
2016-01-01
Stochastic, spatial reaction-diffusion simulations have been widely used in systems biology and computational neuroscience. However, the increasing scale and complexity of simulated models and morphologies have exceeded the capacity of any serial implementation. This led to development of parallel solutions that benefit from the boost in performance of modern large-scale supercomputers. In this paper, we describe an MPI-based, parallel Operator-Splitting implementation for stochastic spatial reaction-diffusion simulations with irregular tetrahedral meshes. The performance of our implementation is first examined and analyzed with simulations of a simple model. We then demonstrate its usage in real-world research by simulating the reaction-diffusion components of a published calcium burst model in both Purkinje neuron sub-branch and full dendrite morphologies. Simulation results indicate that our implementation is capable of achieving super-linear speedup for balanced loading simulations with reasonable molecul...
Stochastic modelling and predictability: analysis of a low-order coupled ocean-atmosphere model.
Vannitsem, Stéphane
2014-06-28
There is a growing interest in developing stochastic schemes for the description of processes that are poorly represented in atmospheric and climate models, in order to increase their variability and reduce the impact of model errors. The use of such noise could however have adverse effects by modifying in undesired ways a certain number of moments of their probability distributions. In this work, the impact of developing a stochastic scheme (based on stochastic averaging) for the ocean is explored in the context of a low-order coupled (deterministic) ocean-atmosphere system. After briefly analysing its variability, its ability in predicting the oceanic flow generated by the coupled system is investigated. Different phases in the error dynamics are found: for short lead times, an initial overdispersion of the ensemble forecast is present while the ensemble mean follows a dynamics reminiscent of the combined amplification of initial condition and model errors for deterministic systems; for longer lead times, a reliable diffusive ensemble spread is observed. These different phases are also found for ensemble-oriented skill measures like the Brier score and the rank histogram. The implications of these features on building stochastic models are then briefly discussed.
Teodorescu, Razvan
2009-10-01
Systems of oscillators coupled non-linearly (stochastically or not) are ubiquitous in nature and can explain many complex phenomena: coupled Josephson junction arrays, cardiac pacemaker cells, swarms or flocks of insects and birds, etc. They are know to have a non-trivial phase diagram, which includes chaotic, partially synchronized, and fully synchronized phases. A traditional model for this class of problems is the Kuramoto system of oscillators, which has been studied extensively for the last three decades. The model is a canonical example for non-equilibrium, dynamical phase transitions, so little understood in physics. From a stochastic analysis point of view, the transition is described by the large deviations principle, which offers little information on the scaling behavior near the critical point. I will discuss a special case of the model, which allows a rigorous analysis of the critical properties of the model, and reveals a new, anomalous scaling behavior in the vicinity of the critical point.
Stochastic Analysis of Nonlinear Coupled Heave-Pitch Motion for the Truss Spar Platform
Institute of Scientific and Technical Information of China (English)
Wenjun Shen; Yougang Tang
2011-01-01
Considering the static stability and the change of the displacement volume,including the influences of higher order nonlinear terms and the instantaneous wave surface,the nonlinear coupled heave-pitch motion was established in stochastic waves.The responses of heave-pitch coupling motion for the Truss Spar platform were investigated.It was found that,when the characteristic frequency of a stochastic wave is close to the natural heave frequency,the large amplitude pitch motion is induced under the parametric-forced excitation,which is called the Mathieu instability.It was observed that the heave mode energy is transferred to pitch mode when the heave motion amplitude exceeds a certain extent.In addition,the probability of internal resonant heave-pitch motion is greatly reduced while the characteristic wave frequency is away from the natural heave frequency.
On the Stochastic Heat Equation with Spatially-Colored Random forcing
Foondun, Mohammud
2010-01-01
We consider the stochastic heat equation of the following form \\frac{\\partial}{\\partial t}u_t(x) = (\\sL u_t)(x) +b(u_t(x)) + \\sigma(u_t(x))\\dot{F}_t(x)\\quad \\text{for}t>0, x\\in \\R^d, where $\\sL$ is the generator of a L\\'evy process and $\\dot{F}$ is a spatially-colored, temporally white, gaussian noise. We will be concerned mainly with the long-term behavior of the mild solution to this stochastic PDE. For the most part, we work under the assumptions that the initial data $u_0$ is a bounded and measurable function and $\\sigma$ is nonconstant and Lipschitz continuous. In this case, we find conditions under which the preceding stochastic PDE admits a unique solution which is also \\emph{weakly intermittent}. In addition, we study the same equation in the case that $\\mathcal{L}u$ is replaced by its massive/dispersive analogue $\\mathcal{L}u-\\lambda u$ where $\\lambda\\in\\R$. Furthermore, we extend our analysis to the case that the initial data $u_0$ is a measure rather than a function. As it turns out, the stochastic...
Stochastic sequence-level model of coupled transcription and translation in prokaryotes
Yli-Harja Olli; Lloyd-Price Jason; Mäkelä Jarno; Ribeiro Andre S
2011-01-01
Abstract Background In prokaryotes, transcription and translation are dynamically coupled, as the latter starts before the former is complete. Also, from one transcript, several translation events occur in parallel. To study how events in transcription elongation affect translation elongation and fluctuations in protein levels, we propose a delayed stochastic model of prokaryotic transcription and translation at the nucleotide and codon level that includes the promoter open complex formation ...
From coupled map lattices to the stochastic Kardar Parisi Zhang equation
Katzav, Eytan; Cugliandolo, Leticia F.
2006-11-01
We discuss the space and time dependence of the continuum limit of an ensemble of coupled logistic maps on a one-dimensional lattice. We show that the resulting partial differential equation has elements of the stochastic Kardar-Parisi-Zhang growth equation and of the Fisher-Kolmogorov-Petrovskii-Piscounov equation describing front propagation. A similar study of the Lyapunov vector confirms that its space-time behaviour is of KPZ type.
Anomalous diffusion and scaling in coupled stochastic processes
Energy Technology Data Exchange (ETDEWEB)
Bel, Golan [Los Alamos National Laboratory; Nemenman, Ilya [Los Alamos National Laboratory
2009-01-01
Inspired by problems in biochemical kinetics, we study statistical properties of an overdamped Langevin processes with the friction coefficient depending on the state of a similar, unobserved, process. Integrating out the latter, we derive the Pocker-Planck the friction coefficient of the first depends on the state of the second. Integrating out the latter, we derive the Focker-Planck equation for the probability distribution of the former. This has the fonn of diffusion equation with time-dependent diffusion coefficient, resulting in an anomalous diffusion. The diffusion exponent can not be predicted using a simple scaling argument, and anomalous scaling appears as well. The diffusion exponent of the Weiss-Havlin comb model is derived as a special case, and the same exponent holds even for weakly coupled processes. We compare our theoretical predictions with numerical simulations and find an excellent agreement. The findings caution against treating biochemical systems with unobserved dynamical degrees of freedom by means of standandard, diffusive Langevin descritpion.
Weisheimer, Antje; Corti, Susanna; Palmer, Tim; Vitart, Frederic
2014-06-28
The finite resolution of general circulation models of the coupled atmosphere-ocean system and the effects of sub-grid-scale variability present a major source of uncertainty in model simulations on all time scales. The European Centre for Medium-Range Weather Forecasts has been at the forefront of developing new approaches to account for these uncertainties. In particular, the stochastically perturbed physical tendency scheme and the stochastically perturbed backscatter algorithm for the atmosphere are now used routinely for global numerical weather prediction. The European Centre also performs long-range predictions of the coupled atmosphere-ocean climate system in operational forecast mode, and the latest seasonal forecasting system--System 4--has the stochastically perturbed tendency and backscatter schemes implemented in a similar way to that for the medium-range weather forecasts. Here, we present results of the impact of these schemes in System 4 by contrasting the operational performance on seasonal time scales during the retrospective forecast period 1981-2010 with comparable simulations that do not account for the representation of model uncertainty. We find that the stochastic tendency perturbation schemes helped to reduce excessively strong convective activity especially over the Maritime Continent and the tropical Western Pacific, leading to reduced biases of the outgoing longwave radiation (OLR), cloud cover, precipitation and near-surface winds. Positive impact was also found for the statistics of the Madden-Julian oscillation (MJO), showing an increase in the frequencies and amplitudes of MJO events. Further, the errors of El Niño southern oscillation forecasts become smaller, whereas increases in ensemble spread lead to a better calibrated system if the stochastic tendency is activated. The backscatter scheme has overall neutral impact. Finally, evidence for noise-activated regime transitions has been found in a cluster analysis of mid
Non-local convergence coupling in a simple stochastic convection model
Brenowitz, N. D.; Frenkel, Y.; Majda, A. J.
2016-06-01
Observational studies show a strong correlation between large-scale wind convergence and precipitation. However, using this as a convective closure assumption to determine the total precipitation in a numerical model typically leads to deleterious wave-CISK behavior such as grid-scale noise. The quasi-equilibrium (QE) schemes ameliorate this issue and smooth the precipitation field, but still inadequately represent the intermittent and organized nature of tropical convection. However, recent observational evidence highlights that the large-scale convergence field primarily affects precipitation by increasing the overall convective cloud fraction rather than the energetics of individual convective elements. In this article, the dynamical consequences of this diagnostic observation are studied using a simple one baroclinic mode stochastic model for convectively coupled waves. A version of this model is implemented which couples the stochastic formation of convective elements to the wind convergence. Linearized analysis shows that using the local convergence results in a classic wave-CISK standing instability where the growth rate increases with the wavenumber. However, using a large-scale averaged convergence restricts the instability to physically plausible scales. Convergence coupling is interpreted as a surrogate for the non-local effects of gregarious convection. In nonlinear stochastic simulations with a non-uniform imposed sea surface temperature (SST) field, the non-local convergence coupling introduces desirable intermittent variability on intraseasonal time scales. Convergence coupling leads to a circulation with a similar mean but higher variability than the equivalent parameterization without convergence coupling. Finally, the model is shown to retain these features on fine and coarse mesh sizes.
Ribeiro, Andre S.
2007-06-01
Genetic toggle switches (TSs) are one of the best studied small gene regulatory networks (GRNs), due to their simplicity and relevant role. They have been interpreted as decision circuits in cell differentiation, a process long hypothesized to be bistable [1], or as cellular memory units [2]. In these contexts, they must be reliable. Once a “decision” is made, the system must remain stable. One way to gain stability is by duplicating the genes of a TS and coupling the two TSs. Using a recent modeling strategy of GRNs, driven by a delayed stochastic simulation algorithm (delayed SSA) that allows modeling transcription and translation as multidelayed reactions, we analyze the stability of systems of coupled TSs. For this, we introduce the coupling strength (C) , a parameter to characterize the GRN structure, against which we compare the GRN stability (S) . We first show that time delays in transcription, associated to the promoter region release, ensure bistability of a TS, given no cooperative binding or self-activation reactions. Next, we couple two TSs and measure their toggling frequencies as C varies. Three dynamical regimes are observed: (i) for weak coupling, high frequency synchronized oscillations, (ii) for average coupling, low frequency synchronized oscillations, and (iii) for strong coupling the system becomes stable after a transient, in one of two steady states. The system stability, S , goes through a first order phase transition as C increases, in the average coupling regime. After, we study the effects of spatial separation in two compartments on the dynamics of two coupled TSs, where spatial separation is modeled as normally distributed random time delayed reactions. The phase transition of S , as C increases, occurs for lower values of C than when the two TSs are in the same compartment. Finally, we couple weakly and homogeneously several TSs within a single compartment and observe that as the number of coupled TSs increases, the system goes
Incoherently Coupled Grey Photovoltaic Spatial Soliton Families
Institute of Scientific and Technical Information of China (English)
WANG Hong-Cheng; SHE Wei-Long
2005-01-01
@@ A theory is developed for incoherently coupled grey photovoltaic soliton families in unbiased photovoltaic crystals.Both the properties and the forming conditions of these soliton families are discussed in detail The theory canalso be used to investigate the dark photovoltaic soliton families. Some relevant examples are presented, in which the photovoltaic-photorefractive crystal is of lithium niobate type.
Mean field analysis of a spatial stochastic model of a gene regulatory network.
Sturrock, M; Murray, P J; Matzavinos, A; Chaplain, M A J
2015-10-01
A gene regulatory network may be defined as a collection of DNA segments which interact with each other indirectly through their RNA and protein products. Such a network is said to contain a negative feedback loop if its products inhibit gene transcription, and a positive feedback loop if a gene product promotes its own production. Negative feedback loops can create oscillations in mRNA and protein levels while positive feedback loops are primarily responsible for signal amplification. It is often the case in real biological systems that both negative and positive feedback loops operate in parameter regimes that result in low copy numbers of gene products. In this paper we investigate the spatio-temporal dynamics of a single feedback loop in a eukaryotic cell. We first develop a simplified spatial stochastic model of a canonical feedback system (either positive or negative). Using a Gillespie's algorithm, we compute sample trajectories and analyse their corresponding statistics. We then derive a system of equations that describe the spatio-temporal evolution of the stochastic means. Subsequently, we examine the spatially homogeneous case and compare the results of numerical simulations with the spatially explicit case. Finally, using a combination of steady-state analysis and data clustering techniques, we explore model behaviour across a subregion of the parameter space that is difficult to access experimentally and compare the parameter landscape of our spatio-temporal and spatially-homogeneous models.
Research on spatial state conversion rule mining and stochastic predicting based on CA
Li, Xinyun; Kong, Xiangqiang
2007-06-01
Spatial dynamic prediction in GIS is the process of spatial calculation that infers the thematic maps in future according to the historical thematic maps, and it is space-time calculation from map to map. There is great application value that spatial dynamic prediction applied to the land planning, urban land-use planning and town planning, but there is some imperfect in method and technique at present. The main technical difficulty is excavation and expression of spatial state conversion rule. In allusion to the deficiency in spatial dynamic prediction using CA, the method which excavated spatial state conversion rule based on spatial data mining was put forward. Stochastic simulation mechanism was put into the prediction calculating based on state conversion rule. The result of prediction was more rational and the relation between the prediction steps and the time course was clearer. The method was applied to prediction of spatial structure change of urban land-use in Jinan. The Urban land-use change maps were predicted in 2006 and 2010 by using the land-use maps in 1998 and 2002. The result of this test was rational by analyzing.
Internal stochastic resonance in two coupled chemical oscil-lators
Institute of Scientific and Technical Information of China (English)
ZHONG; Shi
2001-01-01
［1］Sears, T. J., The calculation of the energy levels of an asymmetric top free radical in a magnetic field, Comput. Phys. Rep., 1984, 2: 1..［2］Davies, P. B., Liu, Y., Liu, Z., Far infrared LMR spectra of monobromomethyl radicals, Chem. Phys. Lett., 1993, 214: 305.［3］Nolte, J., Wagner, H. G., Sears, T. J. et al., The far-infrared laser magnetic resonance spectrum of CH2F, J. Mol. Spec-trosc., 1999, 195: 43.［4］Sears, T. J., ASYTOP--A program for detailed analysis of gas phase magnetic resonance spectra of asymmetric top molecules, Comput. Phys. Commun., 1984, 34: 123.［5］Papousek, D., Aliev, M. R., Molecular Vibrational Rotational Spectra, Prague: Academia, 1982, 72.［6］Matsushima, F., Nagase, H., Nakauchi, T. et al., Frequency measurement of pure rotational transitions of H2O, J. Mol. Spectrosc., 1999, 193: 217.［7］Bowater, I. C., Brown, J. M., Carrington, A., Microwave spectroscopy of nonlinear free radicals, Proc. R. Soc. Lond. A, 1973, 333: 265.［8］Castellano, S., Bothner-by, A. A., Analysis of NMR spectra by least squares, J. Chem. Phys., 1964, 41: 3863.［9］Bird, G. R., Microwave spectrum of NO2, J. Chem. Phys., 1956, 25: 1040.［10］Bird, G. R., Baird, J. C., Jache, A. W. et al., Microwave spectrum of NO2: fine structure and magnetic coupling, J. Chem. Phys., 1964, 40: 3378.［11］Lees, R. M., Curl, R. F., Baker, J. G., Millimeter-wavelength microwave spectrum of nitrogen dioxide, J. Chem. Phys., 1966, 45: 2037.［12］Baron, P. A., Godfrey, P. D., Harris, D. O., Microwave spectrum of NO2 at 70 GHz, J. Chem. Phys., 1974, 60: 3723.［13］Bowman, W. C., De Lucia, F. C., The millimeter and submillimeter spectrum of NO2, J. Chem. Phys., 1982, 77: 92.［14］Semmoud-Monnanteuil, N., Colmont, J. M., Perrin, A. et al., New measurements in the millimeter-wave spectrum of NO2, J. Mol. Spectrosc., 1989, 134: 176.［15］Baskakov, O. I., Moskienko, M. V., Dyubko, S. F., Submillimeter rotational spectrum of nitrogen dioxide, Opt
Synchronization in a network of delay coupled maps with stochastically switching topologies
Nag, Mayurakshi; Poria, Swarup
2016-10-01
The synchronization behavior of delay coupled chaotic smooth unimodal maps over a ring network with stochastic switching of links at every time step is reported in this paper. It is observed that spatiotemporal synchronization never appears for nearest neighbor connections; however, stochastic switching of connections with homogeneous delay $(\\tau)$ is capable of synchronizing the network to homogeneous steady state or periodic orbit or synchronized chaotically oscillating state depending on the delay parameter, stochasticity parameter and map parameters. Linear stability analysis of the synchronized state is done analytically for unit delay and the value of the critical coupling strength, at which the onset of synchronization occurs is determined analytically. The logistic map $rx(1-x)$ (a smooth unimodal map) is chosen for numerical simulation purpose. Synchronized steady state or synchronized period-2 orbit is stabilized for delay $\\tau=1$. On the other hand for delay $\\tau=2$ the network is stabilized to the fixed point of the local map. Numerical simulation results are in good agreement with the analytically obtained linear stability analysis results. Another interesting observation is the existence of synchronized chaos in the network for delay $\\tau>2$. Calculating synchronization error and plotting time series data and Poincare first return map the existence of synchronized chaos is confirmed. The results hold good for other smooth unimodal maps also.
Coupling sample paths to the partial thermodynamic limit in stochastic chemical reaction networks
Levien, Ethan
2016-01-01
We present a new technique for reducing the variance in Monte Carlo estimators of stochastic chemical reaction networks. Our method makes use of the fact that many stochastic reaction networks converge to piecewise deterministic Markov processes in the large system-size limit. The statistics of the piecewise deterministic process can be obtained much more efficiently than those of the exact process. By coupling sample paths of the exact model to the piecewise deterministic process we are able to reduce the variance, and hence the computational complexity of the Monte Carlo estimator. In addition to rigorous results concerning the asymptotic behavior of our method, numerical simulations are performed on some simple biological models suggesting that significant computational gains are made for even moderate system-sizes.
Vladimirov, Igor G
2012-01-01
The paper is concerned with open quantum systems whose Heisenberg dynamics are described by quantum stochastic differential equations driven by external boson fields. The system-field coupling operators are assumed to be quadratic polynomials of the system observables, with the latter satisfying canonical commutation relations. In combination with a cubic system Hamiltonian, this leads to a class of quasilinear quantum stochastic systems which retain algebraic closedness in the evolution of mixed moments of the observables. Although such a system is nonlinear and its quantum state is no longer Gaussian, the dynamics of the moments of any order are amenable to exact analysis, including the computation of their steady-state values. In particular, a generalized criterion is developed for quadratic stability of the quasilinear systems. The results of the paper are applicable to the generation of non-Gaussian quantum states with manageable moments and an optimal design of linear quantum controllers for quasilinear...
Spatially Coupled Ensembles Universally Achieve Capacity under Belief Propagation
Kudekar, Shrinivas; Urbanke, Ruediger
2012-01-01
We investigate spatially coupled code ensembles. For transmission over the binary erasure channel, it was recently shown that spatial coupling increases the belief propagation threshold of the ensemble to essentially the maximum a-priori threshold of the underlying component ensemble. This explains why convolutional LDPC ensembles, originally introduced by Felstrom and Zigangirov, perform so well over this channel. We show that the equivalent result holds true for transmission over general binary-input memoryless output-symmetric channels. More precisely, given a desired error probability and a gap to capacity, we can construct a spatially coupled ensemble which fulfills these constraints universally on this class of channels under belief propagation decoding. In fact, most codes in that ensemble have that property. The quantifier universal refers to the single ensemble/code which is good for all channels but we assume that the channel is known at the receiver. The key technical result is a proof that under b...
Keller, D. E.; Fischer, A. M.; Frei, C.; Liniger, M. A.; Appenzeller, C.; Knutti, R.
2014-07-01
Many climate impact assessments over topographically complex terrain require high-resolution precipitation time-series that have a spatio-temporal correlation structure consistent with observations. This consistency is essential for spatially distributed modelling of processes with non-linear responses to precipitation input (e.g. soil water and river runoff modelling). In this regard, weather generators (WGs) designed and calibrated for multiple sites are an appealing technique to stochastically simulate time-series that approximate the observed temporal and spatial dependencies. In this study, we present a stochastic multi-site precipitation generator and validate it over the hydrological catchment Thur in the Swiss Alps. The model consists of several Richardson-type WGs that are run with correlated random number streams reflecting the observed correlation structure among all possible station pairs. A first-order two-state Markov process simulates intermittence of daily precipitation, while precipitation amounts are simulated from a mixture model of two exponential distributions. The model is calibrated separately for each month over the time-period 1961-2011. The WG is skilful at individual sites in representing the annual cycle of the precipitation statistics, such as mean wet day frequency and intensity as well as monthly precipitation sums. It reproduces realistically the multi-day statistics such as the frequencies of dry and wet spell lengths and precipitation sums over consecutive wet days. Substantial added value is demonstrated in simulating daily areal precipitation sums in comparison to multiple WGs that lack the spatial dependency in the stochastic process: the multi-site WG is capable to capture about 95% of the observed variability in daily area sums, while the summed time-series from multiple single-site WGs only explains about 13%. Limitation of the WG have been detected in reproducing observed variability from year to year, a component that has
Maerker, Michael; Bolus, Michael
2014-05-01
We present a unique spatial dataset of Neanderthal sites in Europe that was used to train a set of stochastic models to reveal the correlations between the site locations and environmental indices. In order to assess the relations between the Neanderthal sites and environmental variables as described above we applied a boosted regression tree approach (TREENET) a statistical mechanics approach (MAXENT) and support vector machines. The stochastic models employ a learning algorithm to identify a model that best fits the relationship between the attribute set (predictor variables (environmental variables) and the classified response variable which is in this case the types of Neanderthal sites. A quantitative evaluation of model performance was done by determining the suitability of the model for the geo-archaeological applications and by helping to identify those aspects of the methodology that need improvements. The models' predictive performances were assessed by constructing the Receiver Operating Characteristics (ROC) curves for each Neanderthal class, both for training and test data. In a ROC curve the Sensitivity is plotted over the False Positive Rate (1-Specificity) for all possible cut-off points. The quality of a ROC curve is quantified by the measure of the parameter area under the ROC curve. The dependent variable or target variable in this study are the locations of Neanderthal sites described by latitude and longitude. The information on the site location was collected from literature and own research. All sites were checked for site accuracy using high resolution maps and google earth. The study illustrates that the models show a distinct ranking in model performance with TREENET outperforming the other approaches. Moreover Pre-Neanderthals, Early Neanderthals and Classic Neanderthals show a specific spatial distribution. However, all models show a wide correspondence in the selection of the most important predictor variables generally showing less
A Generalized Linear Transport Model for Spatially-Correlated Stochastic Media
Davis, Anthony B
2014-01-01
We formulate a new model for transport in stochastic media with long-range spatial correlations where exponential attenuation (controlling the propagation part of the transport) becomes power law. Direct transmission over optical distance $\\tau(s)$, for fixed physical distance $s$, thus becomes $(1+\\tau(s)/a)^{-a}$, with standard exponential decay recovered when $a\\to\\infty$. Atmospheric turbulence phenomenology for fluctuating optical properties rationalizes this switch. Foundational equations for this generalized transport model are stated in integral form for $d=1,2,3$ spatial dimensions. A deterministic numerical solution is developed in $d=1$ using Markov Chain formalism, verified with Monte Carlo, and used to investigate internal radiation fields. Standard two-stream theory, where diffusion is exact, is recovered when $a=\\infty$. Differential diffusion equations are not presently known when $a<\\infty$, nor is the integro-differential form of the generalized transport equation. Monte Carlo simulations...
A Phenomenological Study on Threshold Improvement via Spatial Coupling
Takeuchi, Keigo; Kawabata, Tsutomu
2011-01-01
Kudekar et al. proved an interesting result in low-density parity-check (LDPC) convolutional codes: The belief-propagation (BP) threshold is boosted to the maximum-a-posteriori (MAP) threshold. Furthermore, the authors showed that the BP threshold for code-division multiple-access (CDMA) systems is improved up to a threshold below the optimal one via spatial coupling. In this letter, a phenomenological model for elucidating the essence of these phenomenon, called threshold improvement, is proposed. The main result implies that threshold improvement occurs for spatially-coupled general graphical models.
Nemeth, Noel N.; Bednarcyk, Brett A.; Pineda, Evan; Arnold, Steven; Mital, Subodh; Murthy, Pappu; Walton, Owen
2015-01-01
Reported here is a coupling of two NASA developed codes: CARES (Ceramics Analysis and Reliability Evaluation of Structures) with the MACGMC composite material analysis code. The resulting code is called FEAMACCARES and is constructed as an Abaqus finite element analysis UMAT (user defined material). Here we describe the FEAMACCARES code and an example problem (taken from the open literature) of a laminated CMC in off-axis loading is shown. FEAMACCARES performs stochastic-strength-based damage simulation response of a CMC under multiaxial loading using elastic stiffness reduction of the failed elements.
Institute of Scientific and Technical Information of China (English)
HAN Yin-Xia; LI Jing-Hui; ZHAO Ying-Kui; CHEN Shi-Gang
2005-01-01
In this paper, we study spatially periodic system with infinite globally coupled oscillators driven by temporal-spatial noise and subject to a constant force. The results show that the system exhibits the phenomena of the non-equilibrium phase transition, transport of particles, and the anomalous hysteresis cycle for the mean field and the probability current.
Coupling within Fluvial Geomorphic Systems:Spatial and Temporal Implications
Institute of Scientific and Technical Information of China (English)
无
2000-01-01
Coupling within fluvialsystems relates to the connectivity between the various components of the system. It can be viewed at several scales from local scales of hillslope-to-channel and reachto-reach coupling, to larger scales of zonai coupling between the major functional zones of the fluvial system, and to the scale of regional coupling. Coupling influences how the system responds toenvironmental change and how the effects of environmental change are propagated through the system. This paper provides a review, based largely on previously published work, of the couplingconcept, and how the effective temporal scales vary with the spatial scale of coupling. Local scalecoupling is considered through the hillslope-to-chiannel coupling in the Howgill Fells, northwestEngland, observed over a 30-year monitoring period, together with examples from badlands inSpain, and reach-to-reach coupling on the Rlver Dane, northwest England. At the zonal scale therelative influence of climatic and base-level chunge on coupling through dry-region alluvial fans isconsidered on fan systems in Spain, Nevada, and UAE/Oman. For large scale reg~nal coupling,the response of the Tabernas basih, southeast Spain to tectonic uplift, is examined. The factors in-fluencing coupling mechanisms vary with temporal and spatial scales. At the hillslope-to-channelscale the significant factors are the magnitude and frequency characteristics of sediment generationand removal mechanisms within the context of progressive morphological change. Effectivetimescales range from the individual event to decadal timescales. At the zonal scale, that of allu-vial fans, the significant factors are climatic change, and particularly in the appropriate morpho-logical setting, base-level change. Effective timescales are of the order of hundreds to thousands ofyears. At the regional scale, the response to tectonic uplift may take ＞100 ka to be transmitted4hcoughthe drainage basin.
Drawert, Brian; Trogdon, Michael; Toor, Salman; Petzold, Linda; Hellander, Andreas
2017-01-01
Computational experiments using spatial stochastic simulations have led to important new biological insights, but they require specialized tools and a complex software stack, as well as large and scalable compute and data analysis resources due to the large computational cost associated with Monte Carlo computational workflows. The complexity of setting up and managing a large-scale distributed computation environment to support productive and reproducible modeling can be prohibitive for practitioners in systems biology. This results in a barrier to the adoption of spatial stochastic simulation tools, effectively limiting the type of biological questions addressed by quantitative modeling. In this paper, we present PyURDME, a new, user-friendly spatial modeling and simulation package, and MOLNs, a cloud computing appliance for distributed simulation of stochastic reaction-diffusion models. MOLNs is based on IPython and provides an interactive programming platform for development of sharable and reproducible distributed parallel computational experiments. PMID:28190948
Stochastic Huge-Resonance Caused by Coupling for a Globally Coupled Linear System
Institute of Scientific and Technical Information of China (English)
LI Jing-Hui
2009-01-01
In the paper, we investigate a globally coupled linear system with finite subunits subject to temporal periodic force and with multiplicative dichotomous noise.It is shown that, the global coupling among the subunits can hugely enhance the phenomenon of SR for the amplitude of the average mean field as the functions of the transition rate of the noise and that as the function of the frequency of the signal respectively.
Szabó, J. A.; Kuti, L.; Bakacsi, Zs.; Pásztor, L.; Tahy, Á.
2009-04-01
data for the multi-year simulation of SVAT processes. In order to test the elaborated methods, a sub-area of the full domain has been designated as a pilot area for this study. Considering our aims, major achievements with respect to the objectives have been accomplished for the pilot area within the scope of this work includes: - Harmonized 3D grid model to describe hydraulic properties of the unsaturated zone has been created (Pásztor, L. et al 2002 and 2005, Kuti, L. 2007); - The spatially distributed physically based distributed parameter SVAT model DIWA (DIstributed WAtershed) (Szabó, J.A., 2007) has been adapted; - The stochastic characteristics and parameters of the weather generator has been derived from measured data series; - Coupling the stochastic weather generator with the deterministic DIWA SVAT-type model also has been done. In this paper, the results of the coupled (deterministic - stochastic) model simulation based analysis of regional drought frequency and duration for a sub-area of the full domain of the Great Hungarian Plain will be reported. First the harmonized 3D grid model of the hydraulic properties of the unsaturated zone will be presented. Then a brief characterisation of the DIWA model will be given. The Markov chain based stochastic weather generator also will be presented. Finally, the results of multi-year drought frequency and duration analysis at the pilot area and conclusions will be discussed. Keywords: Drought frequency and duration analysis; multivariate analyses; recurrence analyses; extreme events; stochastic weather generator; spatially distributed SVAT model; 3D grid model of hydraulic properties of the unsaturated zone. References: Kuti, L. (2007): Agrogeological investigation of soil fertility limiting factors int he soil-parent roc-groundwater system in Hungary. In: Environment & Progress, Cluj-Napoca, nr. 10. pp. 131-145. Pásztor, L. - Szabó, J. - Bakacsi, Zs. (2002): GIS processing of large scale soil maps in Hungary
Institute of Scientific and Technical Information of China (English)
Yan-Mei Kang; Mei Wang; Yong Xie
2012-01-01
With coupled weakly-damped periodically driven bistable oscillators subjected to additive and multiplicative noises under concern,the objective of this paper is to check to what extent the resonant point predicted by the Gaussian distribution assumption can approximate the simulated one.The investigation based on the dynamical mean-field approximation and the direct simulation demonstrates that the predicted resonant point and the simulated one are basically coincident for the case of pure additive noise,but for the case including multiplicative noise the situation becomes somewhat complex.Specifically speaking,when stochastic resonance (SR) is observed by changing the additive noise intensity,the predicted resonant point is lower than the simulated one; nevertheless,when SR is observed by changing the multiplicative noise intensity,the predicted resonant point is higher than the simulated one.Our observations imply that the Gaussian distribution assumption can not exactly describe the actual situation,but it is useful to some extent in predicting the low-frequency stochastic resonance of the coupled weakly-damped bistable oscillator.
Zhang, Xinmin; Wu, Bin; Liu, Xiaoyu; Shen, Ziyin
2011-01-01
For multicellular organisms, different tissues coordinate to integrate physiological functions, although this systematically and gradually declines in the aging process. Therefore, an association exists between tissue coordination and aging, and investigating the evolution of tissue coordination with age is of interest. In the past decade, both common and heterogeneous aging processes among tissues were extensively investigated. The results on spatial association of gene changes that determine lifespan appear complex and paradoxical. To reconcile observed commonality and heterogeneity of gene changes among tissues and to address evolution feature of tissue coordination with age, we introduced a new analytical strategy to systematically analyze genome-wide spatio-temporal gene expression profiles. We first applied the approach to natural aging process in three species (Rat, Mouse and Drosophila) and then to anti-aging process in Mouse. The results demonstrated that temporal gene expression alteration in different tissues experiences a progressive association evolution from spatial synchrony to asynchrony and stochasticity with age. This implies that tissue coordination gradually declines with age. Male mice showed earlier spatial asynchrony in gene expression than females, suggesting that male animals are more prone to aging than females. The confirmed anti-aging interventions (resveratrol and caloric restriction) enhanced tissue coordination, indicating their underlying anti-aging mechanism on multiple tissue levels. Further, functional analysis suggested asynchronous DNA/protein damage accumulation as well as asynchronous repair, modification and degradation of DNA/protein in tissues possibly contributes to asynchronous and stochastic changes of tissue microenvironment. This increased risk for a variety of age-related diseases such as neurodegeneration and cancer that eventually accelerate organismal aging and death. Our study suggests a novel molecular event
Strasberg, Philipp; Esposito, Massimiliano
2017-06-01
We consider a classical and possibly driven composite system X ⊗Y weakly coupled to a Markovian thermal reservoir R so that an unambiguous stochastic thermodynamics ensues for X ⊗Y . This setup can be equivalently seen as a system X strongly coupled to a non-Markovian reservoir Y ⊗R . We demonstrate that only in the limit where the dynamics of Y is much faster than X , our unambiguous expressions for thermodynamic quantities, such as heat, entropy, or internal energy, are equivalent to the strong coupling expressions recently obtained in the literature using the Hamiltonian of mean force. By doing so, we also significantly extend these results by formulating them at the level of instantaneous rates and by allowing for time-dependent couplings between X and its environment. Away from the limit where Y evolves much faster than X , previous approaches fail to reproduce the correct results from the original unambiguous formulation, as we illustrate numerically for an underdamped Brownian particle coupled strongly to a non-Markovian reservoir.
Russell, Matthew J.; Jensen, Oliver E.; Galla, Tobias
2016-10-01
Motivated by uncertainty quantification in natural transport systems, we investigate an individual-based transport process involving particles undergoing a random walk along a line of point sinks whose strengths are themselves independent random variables. We assume particles are removed from the system via first-order kinetics. We analyze the system using a hierarchy of approaches when the sinks are sparsely distributed, including a stochastic homogenization approximation that yields explicit predictions for the extrinsic disorder in the stationary state due to sink strength fluctuations. The extrinsic noise induces long-range spatial correlations in the particle concentration, unlike fluctuations due to the intrinsic noise alone. Additionally, the mean concentration profile, averaged over both intrinsic and extrinsic noise, is elevated compared with the corresponding profile from a uniform sink distribution, showing that the classical homogenization approximation can be a biased estimator of the true mean.
InterSpread Plus: a spatial and stochastic simulation model of disease in animal populations.
Stevenson, M A; Sanson, R L; Stern, M W; O'Leary, B D; Sujau, M; Moles-Benfell, N; Morris, R S
2013-04-01
We describe the spatially explicit, stochastic simulation model of disease spread, InterSpread Plus, in terms of its epidemiological framework, operation, and mode of use. The input data required by the model, the method for simulating contact and infection spread, and methods for simulating disease control measures are described. Data and parameters that are essential for disease simulation modelling using InterSpread Plus are distinguished from those that are non-essential, and it is suggested that a rational approach to simulating disease epidemics using this tool is to start with core data and parameters, adding additional layers of complexity if and when the specific requirements of the simulation exercise require it. We recommend that simulation models of disease are best developed as part of epidemic contingency planning so decision makers are familiar with model outputs and assumptions and are well-positioned to evaluate their strengths and weaknesses to make informed decisions in times of crisis.
Besaw, Lance E.; Rizzo, Donna M.
2007-11-01
A novel data-driven artificial neural network (ANN) that quantitatively combines large numbers of multiple types of soft data is presented for performing stochastic simulation and/or spatial estimation. A counterpropagation ANN is extended with a radial basis function to estimate parameter fields that reproduce the spatial structure exhibited in autocorrelated parameters. Applications involve using three geophysical properties measured on a slab of Berea sandstone and the delineation of landfill leachate at a site in the Netherlands using electrical formation conductivity as our primary variable and six types of secondary data (e.g., hydrochemistry, archaea, and bacteria). The ANN estimation fields are statistically similar to geostatistical methods (indicator simulation and cokriging) and reference fields (when available). The method is a nonparametric clustering/classification algorithm that can assimilate significant amounts of disparate data types with both continuous and categorical responses without the computational burden associated with the construction of positive definite covariance and cross-covariance matrices. The combination of simplicity and computational speed makes the method ideally suited for environmental subsurface characterization and other Earth science applications with spatially autocorrelated variables.
Mizrahi, A.; Locatelli, N.; Grollier, J.; Querlioz, D.
2016-08-01
Superparamagnetic tunnel junctions are nanostructures that auto-oscillate stochastically under the effect of thermal noise. Recent works showed that despite their stochasticity, such junctions possess a capability to synchronize to subthreshold voltage drives, in a way that can be enhanced or controlled by adding noise. In this work, we investigate a system composed of two electrically coupled junctions, connected in series to a periodic voltage source. We make use of numerical simulations and of an analytical model to demonstrate that both junctions can be phase locked to the drive, in phase or in antiphase. This synchronization phenomenon can be controlled by both thermal and electrical noises, although the two types of noises induce qualitatively different behaviors. Namely, thermal noise can stabilize a regime where one junction is phase locked to the drive voltage while the other is blocked in one state; on the contrary, electrical noise causes the junctions to have highly correlated behaviors and thus cannot induce the latter. These results open the way for the design of superparamagnetic tunnel junctions that can perform computation through synchronization, and which harvest the largest part of their energy consumption from thermal noise.
The Coupling Effect of Spatial Reticulated Shell Structure with Cables
Institute of Scientific and Technical Information of China (English)
MA Jun; ZHOU Dai; FU Xu-chen
2005-01-01
The spatial reticulated shell structure with cables (RSC) is a kind of coupling working system, which consists of flexible cables, reticulated shell structure (RS) and tower columns. The dynamic analysis of RSC based on the coupling model was carried out. Three kinds of elements such as the spatial bar element, cable element and beam element were introduced to analyze the reticulated shell, cable and tower column respectively. Furthermore,such parameter influences as structural boundary conditions, grid configuration, the span-to-depth ratio and the arrangement of cable system upon structural dynamics were analyzed. The structural vibration modes can be divided into four groups based on some numerical examples. And the frequencies in the same group are very close while the frequencies in different groups are different from each other obviously. It is clear that the sequence of the appearance of the each mode group heavily depends on the comparative stiffness of the tower column system, RS and cables.
Keith, David A; Akçakaya, H Resit; Thuiller, Wilfried; Midgley, Guy F; Pearson, Richard G; Phillips, Steven J; Regan, Helen M; Araújo, Miguel B; Rebelo, Tony G
2008-10-23
Species responses to climate change may be influenced by changes in available habitat, as well as population processes, species interactions and interactions between demographic and landscape dynamics. Current methods for assessing these responses fail to provide an integrated view of these influences because they deal with habitat change or population dynamics, but rarely both. In this study, we linked a time series of habitat suitability models with spatially explicit stochastic population models to explore factors that influence the viability of plant species populations under stable and changing climate scenarios in South African fynbos, a global biodiversity hot spot. Results indicate that complex interactions between life history, disturbance regime and distribution pattern mediate species extinction risks under climate change. Our novel mechanistic approach allows more complete and direct appraisal of future biotic responses than do static bioclimatic habitat modelling approaches, and will ultimately support development of more effective conservation strategies to mitigate biodiversity losses due to climate change.
Directory of Open Access Journals (Sweden)
Driss Sarsri
2014-05-01
Full Text Available In this paper, we propose a method to calculate the first two moments (mean and variance of the structural dynamics response of a structure with uncertain variables and subjected to random excitation. For this, Newmark method is used to transform the equation of motion of the structure into a quasistatic equilibrium equation in the time domain. The Neumann development method was coupled with Monte Carlo simulations to calculate the statistical values of the random response. The use of modal synthesis methods can reduce the dimensions of the model before integration of the equation of motion. Numerical applications have been developed to highlight effectiveness of the method developed to analyze the stochastic response of large structures.
Stochastic sequence-level model of coupled transcription and translation in prokaryotes
Directory of Open Access Journals (Sweden)
Yli-Harja Olli
2011-04-01
Full Text Available Abstract Background In prokaryotes, transcription and translation are dynamically coupled, as the latter starts before the former is complete. Also, from one transcript, several translation events occur in parallel. To study how events in transcription elongation affect translation elongation and fluctuations in protein levels, we propose a delayed stochastic model of prokaryotic transcription and translation at the nucleotide and codon level that includes the promoter open complex formation and alternative pathways to elongation, namely pausing, arrests, editing, pyrophosphorolysis, RNA polymerase traffic, and premature termination. Stepwise translation can start after the ribosome binding site is formed and accounts for variable codon translation rates, ribosome traffic, back-translocation, drop-off, and trans-translation. Results First, we show that the model accurately matches measurements of sequence-dependent translation elongation dynamics. Next, we characterize the degree of coupling between fluctuations in RNA and protein levels, and its dependence on the rates of transcription and translation initiation. Finally, modeling sequence-specific transcriptional pauses, we find that these affect protein noise levels. Conclusions For parameter values within realistic intervals, transcription and translation are found to be tightly coupled in Escherichia coli, as the noise in protein levels is mostly determined by the underlying noise in RNA levels. Sequence-dependent events in transcription elongation, e.g. pauses, are found to cause tangible effects in the degree of fluctuations in protein levels.
Stochastic sequence-level model of coupled transcription and translation in prokaryotes.
Mäkelä, Jarno; Lloyd-Price, Jason; Yli-Harja, Olli; Ribeiro, Andre S
2011-04-26
In prokaryotes, transcription and translation are dynamically coupled, as the latter starts before the former is complete. Also, from one transcript, several translation events occur in parallel. To study how events in transcription elongation affect translation elongation and fluctuations in protein levels, we propose a delayed stochastic model of prokaryotic transcription and translation at the nucleotide and codon level that includes the promoter open complex formation and alternative pathways to elongation, namely pausing, arrests, editing, pyrophosphorolysis, RNA polymerase traffic, and premature termination. Stepwise translation can start after the ribosome binding site is formed and accounts for variable codon translation rates, ribosome traffic, back-translocation, drop-off, and trans-translation. First, we show that the model accurately matches measurements of sequence-dependent translation elongation dynamics. Next, we characterize the degree of coupling between fluctuations in RNA and protein levels, and its dependence on the rates of transcription and translation initiation. Finally, modeling sequence-specific transcriptional pauses, we find that these affect protein noise levels. For parameter values within realistic intervals, transcription and translation are found to be tightly coupled in Escherichia coli, as the noise in protein levels is mostly determined by the underlying noise in RNA levels. Sequence-dependent events in transcription elongation, e.g. pauses, are found to cause tangible effects in the degree of fluctuations in protein levels.
Institute of Scientific and Technical Information of China (English)
2008-01-01
Toxins, such as tetraethylammonium (TEA) and tetrodotoxin (TTX), can make potassium or sodium ion channels poisoned, respectively, and hence reduce the number of working ion channels and lead to the diminishment of conductance. In this paper, we have studied by numerical simulations the effects of sodium and potassium ion channel poisoning on the collective spiking activity of an array of coupled stochastic Hodgkin-Huxley (HH) neurons. It is found for a given number of neurons sodium or potas- sium ion channel block can either enhance or reduce the collective spiking regularity, depending on the membrane patch size. For a given smaller or larger patch size, potassium and sodium ion channel block can reduce or enhance the collective spiking regularity, but they have different patch size ranges for the transformation. This result shows that sodium or potassium ion channel block might have dif- ferent effects on the collective spiking activity in coupled HH neurons from the effects for a single neuron, which represents the interplay among the diminishment of maximal conductance and the in- crease of channel noise strength due to the channel blocks, as well as the bi-directional coupling be- tween the neurons.
Institute of Scientific and Technical Information of China (English)
GONG YuBing; XU Bo; MA XiaoGuang; HAN JiQu
2008-01-01
Toxins, such as tetraethylammonium (TEA) and tetrodotoxin (TTX), can make potassium or sodium ion channels poisoned, respectively, and hence reduce the number of working ion channels and lead to the diminishment of conductance. In this paper, we have studied by numerical simulations the effects of sodium and potassium ion channel poisoning on the collective spiking activity of an array of coupled stochastic Hodgkin-Huxley (HH) neurons. It is found for a given number of neurons sodium or potas-sium ion channel block can either enhance or reduce the collective spiking regularity, depending on the membrane patch size. For a given smaller or larger patch size, potassium and sodium ion channel block can reduce or enhance the collective spiking regularity, but they have different patch size ranges for the transformation. This result shows that sodium or potassium ion channel block might have dif-ferent effects on the collective spiking activity in coupled HH neurons from the effects for a single neuron, which represents the interplay among the diminishment of maximal conductance and the in-crease of channel noise strength due to the channel blocks, as well as the bi-directional coupling be-tween the neurons.
Stochastic phase resetting of two coupled phase oscillators stimulated at different times
Tass, Peter A.
2003-05-01
A model of two coupled phase oscillators is presented, where the oscillators are subject to random forces and are stimulated at different times. Transient phase dynamics, synchronization, and desynchronization, which are stimulus locked (i.e., tightly time locked to a repetitively administered stimulus), are investigated. Complex coordinated responses, in terms of a noise-induced switching across trials between qualitatively different responses, may occur when the two oscillators are reset close to an unstable fixed point of their relative phases. This can be achieved with an appropriately chosen delay between the two stimuli. The switching of the responses shows up as a coordinated cross-trial (CT) response clustering of the oscillators, where the two oscillators produce two different pairs of responses. By varying noise amplitude and coupling strength we observe a stochastic resonance and a coupling-mediated resonance of the CT response clustering, respectively. The presented data analysis method makes it possible to detect such processes in numerical and experimental signals. Its time resolution is enormous, since it is only restricted by the time resolution of the preprocessing necessary for extracting the phases from experimental data. In contrast, standard data analysis tools applied across trials relative to stimulus onset, such as CT averaging (where an ensemble of poststimulus responses is simply averaged), CT standard deviation, and CT cross correlation, fail in detecting complex coordinated responses and lead to severe misinterpretations and artifacts. The consequences for the analysis of evoked responses in medicine and neuroscience are significant and are discussed in detail.
Earthquake nucleation in a stochastic fault model of globally coupled units with interaction delays
Vasović, Nebojša; Kostić, Srđan; Franović, Igor; Todorović, Kristina
2016-09-01
In present paper we analyze dynamics of fault motion by considering delayed interaction of 100 all-to-all coupled blocks with rate-dependent friction law in presence of random seismic noise. Such a model sufficiently well describes a real fault motion, whose prevailing stochastic nature is implied by surrogate data analysis of available GPS measurements of active fault movement. Interaction of blocks in an analyzed model is studied as a function of time delay, observed both for dynamics of individual faults and phenomenological models. Analyzed model is examined as a system of all-to-all coupled blocks according to typical assumption of compound faults as complex of globally coupled segments. We apply numerical methods to show that there are local bifurcations from equilibrium state to periodic oscillations, with an occurrence of irregular aperiodic behavior when initial conditions are set away from the equilibrium point. Such a behavior indicates a possible existence of a bi-stable dynamical regime, due to effect of the introduced seismic noise or the existence of global attractor. The latter assumption is additionally confirmed by analyzing the corresponding mean-field approximated model. In this bi-stable regime, distribution of event magnitudes follows Gutenberg-Richter power law with satisfying statistical accuracy, including the b-value within the real observed range.
Threshold Saturation on BMS Channels via Spatial Coupling
Kudekar, Shrinivas; Richardson, Tom; Urbanke, Ruediger
2010-01-01
We consider spatially coupled code ensembles. A particular instance are convolutional LDPC ensembles. It was recently shown that, for transmission over the binary erasure channel, this coupling increases the belief propagation threshold of the ensemble to the maximum a-priori threshold of the underlying component ensemble. We report on empirical evidence which suggest that the same phenomenon also occurs when transmission takes place over a general binary memoryless symmetric channel. This is confirmed both by simulations as well as by computing EBP GEXIT curves and by comparing the empirical BP thresholds of coupled ensembles to the empirically determined MAP thresholds of the underlying regular ensembles. We further consider ways of reducing the rate-loss incurred by such constructions.
XMDS2: Fast, scalable simulation of coupled stochastic partial differential equations
Dennis, Graham R.; Hope, Joseph J.; Johnsson, Mattias T.
2013-01-01
XMDS2 is a cross-platform, GPL-licensed, open source package for numerically integrating initial value problems that range from a single ordinary differential equation up to systems of coupled stochastic partial differential equations. The equations are described in a high-level XML-based script, and the package generates low-level optionally parallelised C++ code for the efficient solution of those equations. It combines the advantages of high-level simulations, namely fast and low-error development, with the speed, portability and scalability of hand-written code. XMDS2 is a complete redesign of the XMDS package, and features support for a much wider problem space while also producing faster code. Program summaryProgram title: XMDS2 Catalogue identifier: AENK_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AENK_v1_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: GNU General Public License, version 2 No. of lines in distributed program, including test data, etc.: 872490 No. of bytes in distributed program, including test data, etc.: 45522370 Distribution format: tar.gz Programming language: Python and C++. Computer: Any computer with a Unix-like system, a C++ compiler and Python. Operating system: Any Unix-like system; developed under Mac OS X and GNU/Linux. RAM: Problem dependent (roughly 50 bytes per grid point) Classification: 4.3, 6.5. External routines: The external libraries required are problem-dependent. Uses FFTW3 Fourier transforms (used only for FFT-based spectral methods), dSFMT random number generation (used only for stochastic problems), MPI message-passing interface (used only for distributed problems), HDF5, GNU Scientific Library (used only for Bessel-based spectral methods) and a BLAS implementation (used only for non-FFT-based spectral methods). Nature of problem: General coupled initial-value stochastic partial differential equations. Solution method: Spectral method
Rupprecht, Jean-Francois; Tessier, Gilles
2016-01-01
Widefield stochastic microscopy techniques such as PALM or STORM rely on the progressive accumulation of a large number of frames, each containing a scarce number of super-resolved point images. We justify that the redundancy in the localization of detected events imposes a specific limit on the temporal resolution. Based on a theoretical model, we derive analytical predictions for the minimal time required to obtain a reliable image at a given spatial resolution, called image completion time. In contrast to standard assumptions, we find that the image completion time scales logarithmically with the ratio of the image size by the spatial resolution volume. We justify that this non-linear relation is the hallmark of a random coverage problem. We propose a method to estimate the risk that the image reconstruction is not complete, which we apply to an experimental data set. Our results provide a theoretical framework to quantify the pattern detection efficiency and to optimize the trade-off between image coverag...
Institute of Scientific and Technical Information of China (English)
2009-01-01
The paper is concerned with a stochastic optimal control problem in which the controlled system is described by a fully coupled nonlinear forward-backward stochastic differential equation driven by a Brownian motion.It is required that all admissible control processes are adapted to a given subfiltration of the filtration generated by the underlying Brownian motion.For this type of partial information control,one sufficient(a verification theorem) and one necessary conditions of optimality are proved.The control domain need to be convex and the forward diffusion coefficient of the system can contain the control variable.
Institute of Scientific and Technical Information of China (English)
MENG QingXin
2009-01-01
The paper is concerned with a stochastic optimal control problem in which the controlled system is described by a fully coupled nonlinear forward-backward stochastic differential equation driven by a Brownian motion. It is required that all admissible control processes are adapted to a given subfiltration of the filtration generated by the underlying Brownian motion. For this type of partial information control, one sufficient (a verification theorem) and one necessary conditions of optimality are proved. The control domain need to be convex and the forward diffusion coefficient of the system can contain the control variable.
Energy Technology Data Exchange (ETDEWEB)
Wu, Wei [Department of Physics and Astronomy and Department of Chemistry, State University of New York at Stony Brook, Stony Brook, New York 11794 (United States); Wang, Jin, E-mail: jin.wang.1@stonybrook.edu [Department of Physics and Astronomy and Department of Chemistry, State University of New York at Stony Brook, Stony Brook, New York 11794 (United States); State Key Laboratory of Electroanalytical Chemistry, Changchun Institute of Applied Chemistry, Chinese Academy of Sciences, 130022 Changchun, China and College of Physics, Jilin University, 130021 Changchun (China)
2014-09-14
We have established a general non-equilibrium thermodynamic formalism consistently applicable to both spatially homogeneous and, more importantly, spatially inhomogeneous systems, governed by the Langevin and Fokker-Planck stochastic dynamics with multiple state transition mechanisms, using the potential-flux landscape framework as a bridge connecting stochastic dynamics with non-equilibrium thermodynamics. A set of non-equilibrium thermodynamic equations, quantifying the relations of the non-equilibrium entropy, entropy flow, entropy production, and other thermodynamic quantities, together with their specific expressions, is constructed from a set of dynamical decomposition equations associated with the potential-flux landscape framework. The flux velocity plays a pivotal role on both the dynamic and thermodynamic levels. On the dynamic level, it represents a dynamic force breaking detailed balance, entailing the dynamical decomposition equations. On the thermodynamic level, it represents a thermodynamic force generating entropy production, manifested in the non-equilibrium thermodynamic equations. The Ornstein-Uhlenbeck process and more specific examples, the spatial stochastic neuronal model, in particular, are studied to test and illustrate the general theory. This theoretical framework is particularly suitable to study the non-equilibrium (thermo)dynamics of spatially inhomogeneous systems abundant in nature. This paper is the second of a series.
Human seizures couple across spatial scales through travelling wave dynamics
Martinet, L.-E.; Fiddyment, G.; Madsen, J. R.; Eskandar, E. N.; Truccolo, W.; Eden, U. T.; Cash, S. S.; Kramer, M. A.
2017-04-01
Epilepsy--the propensity toward recurrent, unprovoked seizures--is a devastating disease affecting 65 million people worldwide. Understanding and treating this disease remains a challenge, as seizures manifest through mechanisms and features that span spatial and temporal scales. Here we address this challenge through the analysis and modelling of human brain voltage activity recorded simultaneously across microscopic and macroscopic spatial scales. We show that during seizure large-scale neural populations spanning centimetres of cortex coordinate with small neural groups spanning cortical columns, and provide evidence that rapidly propagating waves of activity underlie this increased inter-scale coupling. We develop a corresponding computational model to propose specific mechanisms--namely, the effects of an increased extracellular potassium concentration diffusing in space--that support the observed spatiotemporal dynamics. Understanding the multi-scale, spatiotemporal dynamics of human seizures--and connecting these dynamics to specific biological mechanisms--promises new insights to treat this devastating disease.
Electric currents couple spatially separated biogeochemical processes in marine sediment
DEFF Research Database (Denmark)
Nielsen, Lars Peter; Risgaard-Petersen, Nils; Fossing, Henrik
2010-01-01
Some bacteria are capable of extracellular electron transfer, thereby enabling them to use electron acceptors and donors without direct cell contact 1, 2, 3, 4 . Beyond the micrometre scale, however, no firm evidence has previously existed that spatially segregated biogeochemical processes can...... be coupled by electric currents in nature. Here we provide evidence that electric currents running through defaunated sediment couple oxygen consumption at the sediment surface to oxidation of hydrogen sulphide and organic carbon deep within the sediment. Altering the oxygen concentration in the sea water...... in the sediment was driven by electrons conducted from the anoxic zone. A distinct pH peak in the oxic zone could be explained by electrochemical oxygen reduction, but not by any conventional sets of aerobic sediment processes. We suggest that the electric current was conducted by bacterial nanowires combined...
Zhang, Jianlei; Chu, Tianguang; Perc, Matjaz; 10.1371/journal.pone.0021787
2011-01-01
We study the evolution of cooperation among selfish individuals in the stochastic strategy spatial prisoner's dilemma game. We equip players with the particle swarm optimization technique, and find that it may lead to highly cooperative states even if the temptations to defect are strong. The concept of particle swarm optimization was originally introduced within a simple model of social dynamics that can describe the formation of a swarm, i.e., analogous to a swarm of bees searching for a food source. Essentially, particle swarm optimization foresees changes in the velocity profile of each player, such that the best locations are targeted and eventually occupied. In our case, each player keeps track of the highest payoff attained within a local topological neighborhood and its individual highest payoff. Thus, players make use of their own memory that keeps score of the most profitable strategy in previous actions, as well as use of the knowledge gained by the swarm as a whole, to find the best available stra...
Spatial stochastic simulation offers potential as a quantitative method for pest risk analysis.
Rafoss, Trond
2003-08-01
Pest risk analysis represents an emerging field of risk analysis that evaluates the potential risks of the introduction and establishment of plant pests into a new geographic location and then assesses the management options to reduce those potential risks. Development of new and adapted methodology is required to answer questions concerning pest risk analysis of exotic plant pests. This research describes a new method for predicting the potential establishment and spread of a plant pest into new areas using a case study, Ralstonia solanacearum, a bacterial disease of potato. This method combines current quantitative methodologies, stochastic simulation, and geographic information systems with knowledge of pest biology and environmental data to derive new information about pest establishment potential in a geographical region where a pest had not been introduced. This proposed method extends an existing methodology for matching pest characteristics with environmental conditions by modeling and simulating dissemination behavior of a pest organism. Issues related to integrating spatial variables into risk analysis models are further discussed in this article.
Sumata, H.; Kauker, F.; Gerdes, R.; Köberle, C.; Karcher, M.
2012-11-01
Two types of optimization methods were applied to a parameter optimization problem in a coupled ocean-sea ice model, and applicability and efficiency of the respective methods were examined. One is a finite difference method based on a traditional gradient descent approach, while the other adopts genetic algorithms as an example of stochastic approaches. Several series of parameter optimization experiments were performed by minimizing a cost function composed of model-data misfit of ice concentration, ice drift velocity and ice thickness. The finite difference method fails to estimate optimal parameters due to an ill-shaped nature of the cost function, whereas the genetic algorithms can effectively estimate near optimal parameters with a practical number of iterations. The results of the study indicate that a sophisticated stochastic approach is of practical use to a parameter optimization of a coupled ocean-sea ice model.
Demaeyer, Jonathan
2016-01-01
A stochastic subgrid-scale parameterization based on the Ruelle's response theory and proposed in Wouters and Lucarini (2012) is tested in the context of a low-order coupled ocean-atmosphere model for which a part of the atmospheric modes are considered as unresolved. A natural separation of the phase-space into an invariant set and its complement allows for an analytical derivation of the different terms involved in the parameterization, namely the average, the fluctuation and the long memory terms. In this case, the fluctuation term is an additive stochastic noise. Its application to the low-order system reveals that a considerable correction of the low-frequency variability along the invariant subset can be obtained, provided that the coupling is sufficiently weak. This new approach of scale separation opens new avenues of subgrid-scale parameterizations in multiscale systems used for climate forecasts.
Zhang, Jianlei; Zhang, Chunyan; Chu, Tianguang; Perc, Matjaž
2011-01-01
We study the evolution of cooperation among selfish individuals in the stochastic strategy spatial prisoner's dilemma game. We equip players with the particle swarm optimization technique, and find that it may lead to highly cooperative states even if the temptations to defect are strong. The concept of particle swarm optimization was originally introduced within a simple model of social dynamics that can describe the formation of a swarm, i.e., analogous to a swarm of bees searching for a food source. Essentially, particle swarm optimization foresees changes in the velocity profile of each player, such that the best locations are targeted and eventually occupied. In our case, each player keeps track of the highest payoff attained within a local topological neighborhood and its individual highest payoff. Thus, players make use of their own memory that keeps score of the most profitable strategy in previous actions, as well as use of the knowledge gained by the swarm as a whole, to find the best available strategy for themselves and the society. Following extensive simulations of this setup, we find a significant increase in the level of cooperation for a wide range of parameters, and also a full resolution of the prisoner's dilemma. We also demonstrate extreme efficiency of the optimization algorithm when dealing with environments that strongly favor the proliferation of defection, which in turn suggests that swarming could be an important phenomenon by means of which cooperation can be sustained even under highly unfavorable conditions. We thus present an alternative way of understanding the evolution of cooperative behavior and its ubiquitous presence in nature, and we hope that this study will be inspirational for future efforts aimed in this direction.
Directory of Open Access Journals (Sweden)
Jianlei Zhang
Full Text Available We study the evolution of cooperation among selfish individuals in the stochastic strategy spatial prisoner's dilemma game. We equip players with the particle swarm optimization technique, and find that it may lead to highly cooperative states even if the temptations to defect are strong. The concept of particle swarm optimization was originally introduced within a simple model of social dynamics that can describe the formation of a swarm, i.e., analogous to a swarm of bees searching for a food source. Essentially, particle swarm optimization foresees changes in the velocity profile of each player, such that the best locations are targeted and eventually occupied. In our case, each player keeps track of the highest payoff attained within a local topological neighborhood and its individual highest payoff. Thus, players make use of their own memory that keeps score of the most profitable strategy in previous actions, as well as use of the knowledge gained by the swarm as a whole, to find the best available strategy for themselves and the society. Following extensive simulations of this setup, we find a significant increase in the level of cooperation for a wide range of parameters, and also a full resolution of the prisoner's dilemma. We also demonstrate extreme efficiency of the optimization algorithm when dealing with environments that strongly favor the proliferation of defection, which in turn suggests that swarming could be an important phenomenon by means of which cooperation can be sustained even under highly unfavorable conditions. We thus present an alternative way of understanding the evolution of cooperative behavior and its ubiquitous presence in nature, and we hope that this study will be inspirational for future efforts aimed in this direction.
Ramon, Ceon; Holmes, Mark D
2013-01-01
The stochastic behavior of the phase synchronization index (SI) and cross-frequency couplings on different days during a hospital stay of three epileptic patients was studied for non-invasive localization of the epileptogenic areas from high density, 256-channel, scalp EEG (dEEG) recordings. The study was performed with short-duration (0-180 s), seizure-free, epileptiform-free, and spike-free interictal dEEG data on different days of three subjects. The seizure areas were localized with subdural recordings with an 8 × 8 macro-electrode grid array and strip electrodes. The study was performed in theta (3-7 Hz), alpha (7-12 Hz), beta (12-30 Hz), and low gamma (30-50 Hz) bands. A detrended fluctuation analysis was used to find the long range temporal correlations in the SI that reveals the stochastic behavior of the SI in a given time period. The phase synchronization was computed after taking Hilbert transform of the EEG data. Contour plots were constructed with 20 s time-frames using a montage of the layout of 256 electrode positions. It was found that the stochastic behavior of the SI was higher in epileptogenic areas and in nearby areas on different days for each subject. The low gamma band was found to be the best to localize the epileptic sites. Also, a stable higher pattern of SI emerged after 60-120 s in the epileptogenic areas. The cross-frequency couplings of SI in theta-gamma, beta-gamma, and alpha-gamma bands were decreased and spatial patterns were fragmented in epileptogenic areas. Combinations of an increase in the stochastic behavior of the SI and decrease in cross-frequency couplings are potential markers to assist in localizing epileptogenic areas. These findings suggest that it is possible to localize the epileptogenic areas non-invasively from a short-duration (∼180 s), seizure-free and spike-free interictal scalp dEEG recordings.
Directory of Open Access Journals (Sweden)
Krisztian Magori
Full Text Available BACKGROUND: Dengue is the most important mosquito-borne viral disease affecting humans. The only prevention measure currently available is the control of its vectors, primarily Aedes aegypti. Recent advances in genetic engineering have opened the possibility for a new range of control strategies based on genetically modified mosquitoes. Assessing the potential efficacy of genetic (and conventional strategies requires the availability of modeling tools that accurately describe the dynamics and genetics of Ae. aegypti populations. METHODOLOGY/PRINCIPAL FINDINGS: We describe in this paper a new modeling tool of Ae. aegypti population dynamics and genetics named Skeeter Buster. This model operates at the scale of individual water-filled containers for immature stages and individual properties (houses for adults. The biology of cohorts of mosquitoes is modeled based on the algorithms used in the non-spatial Container Inhabiting Mosquitoes Simulation Model (CIMSiM. Additional features incorporated into Skeeter Buster include stochasticity, spatial structure and detailed population genetics. We observe that the stochastic modeling of individual containers in Skeeter Buster is associated with a strongly reduced temporal variation in stage-specific population densities. We show that heterogeneity in container composition of individual properties has a major impact on spatial heterogeneity in population density between properties. We detail how adult dispersal reduces this spatial heterogeneity. Finally, we present the predicted genetic structure of the population by calculating F(ST values and isolation by distance patterns, and examine the effects of adult dispersal and container movement between properties. CONCLUSIONS/SIGNIFICANCE: We demonstrate that the incorporated stochasticity and level of spatial detail have major impacts on the simulated population dynamics, which could potentially impact predictions in terms of control measures. The capacity
Stochastic multi-reference perturbation theory with application to linearized coupled cluster method
Jeanmairet, Guillaume; Alavi, Ali
2016-01-01
In this article we report a stochastic evaluation of the recently proposed LCC multireference perturbation theory [Sharma S., and Alavi A., J. Chem. Phys. 143, 102815, (2015)]. In this method both the zeroth order and first order wavefunctions are sampled stochastically by propagating simultaneously two populations of signed walkers. The sampling of the zeroth order wavefunction follows a set of stochastic processes identical to the one used in the FCIQMC method. To sample the first order wavefunction, the usual FCIQMC algorithm is augmented with a source term that spawns walkers in the sampled first order wavefunction from the zeroth order wavefunction. The second order energy is also computed stochastically but requires no additional overhead outside of the added cost of sampling the first order wavefunction. This fully stochastic method opens up the possibility of simultaneously treating large active spaces to account for static correlation and recovering the dynamical correlation using perturbation theory...
Xu, Lei; Zhai, Wanming
2017-10-01
This paper devotes to develop a computational model for stochastic analysis and reliability assessment of vehicle-track systems subject to earthquakes and track random irregularities. In this model, the earthquake is expressed as non-stationary random process simulated by spectral representation and random function, and the track random irregularities with ergodic properties on amplitudes, wavelengths and probabilities are characterized by a track irregularity probabilistic model, and then the number theoretical method (NTM) is applied to effectively select representative samples of earthquakes and track random irregularities. Furthermore, a vehicle-track coupled model is presented to obtain the dynamic responses of vehicle-track systems due to the earthquakes and track random irregularities at time-domain, and the probability density evolution method (PDEM) is introduced to describe the evolutionary process of probability from excitation input to response output by assuming the vehicle-track system as a probabilistic conservative system, which lays the foundation on reliability assessment of vehicle-track systems. The effectiveness of the proposed model is validated by comparing to the results of Monte-Carlo method from statistical viewpoint. As an illustrative example, the random vibrations of a high-speed railway vehicle running on the track slabs excited by lateral seismic waves and track random irregularities are analyzed, from which some significant conclusions can be drawn, e.g., track irregularities will additionally promote the dynamic influence of earthquakes especially on maximum values and dispersion degree of responses; the characteristic frequencies or frequency ranges respectively governed by earthquakes and track random irregularities are greatly different, moreover, the lateral seismic waves will dominate or even change the characteristic frequencies of system responses of some lateral dynamic indices at low frequency.
Kuwahara, Jun; Miyata, Hajime; Konno, Hidetoshi
2017-09-01
Recently, complex dynamics of globally coupled oscillators have been attracting many researcher's attentions. In spite of their numerous studies, their features of nonlinear oscillator systems with global and local couplings in two-dimension (2D) are not understood fully. The paper focuses on 2D states of coherent, clustered and chaotic oscillation especially under the effect of negative global coupling (NGC) in 2D Alief-Panfilov model. It is found that the tuning NGC can cause various new coupling-parameter dependency on the features of oscillations. Then quantitative characterization of various states of oscillations (so called spiral wave turbulence) is examined by using the pragmatic information (PI) which have been utilized in analyzing multimode laser, solar activity and neuronal systems. It is demonstrated that the dynamics of the PI for various oscillations can be characterized successfully by the Hyper-Gamma stochastic process.
Shi, L; Rekola, H T; Martikainen, J -P; Moerland, R J; Törmä, P
2014-01-01
We study spatial coherence properties of a system composed of periodic silver nanoparticle arrays covered with a fluorescent organic molecule (DiD) film. The evolution of spatial coherence of this composite structure from the weak to the strong coupling regime is investigated by systematically varying the coupling strength between the localized DiD excitons and the collective, delocalized modes of the nanoparticle array known as surface lattice resonances. A gradual evolution of coherence from the weak to the strong coupling regime is observed, with the strong coupling features clearly visible in interference fringes. A high degree of spatial coherence is demonstrated in the strong coupling regime, even when the mode is very excitonlike (80%), in contrast to the purely localized nature of molecular excitons. We show that coherence appears in proportion to the weight of the plasmonic component of the mode throughout the weak-to-strong coupling crossover, providing evidence for the hybrid nature of the normal m...
Improvement of BP-Based CDMA Multiuser Detection by Spatial Coupling
Takeuchi, Keigo; Kawabata, Tsutomu
2011-01-01
Kudekar et al. proved that the belief-propagation (BP) threshold for low-density parity-check (LDPC) codes can be boosted up to the maximum-a-posteriori (MAP) threshold by spatial coupling. In this paper, spatial coupling is applied to randomly-spread code-division multiple-access (CDMA) systems in order to improve the performance of BP-based multiuser detection (MUD). Spatially-coupled CDMA systems can be regarded as multi-code CDMA systems with two transmission phases. The large-system analysis shows that spatial coupling can improve the BP performance, while there is a gap between the BP performance and the optimal performance.
Orbital effects of spatial variations of fundamental coupling constants
Iorio, Lorenzo
2011-01-01
We deal with the effects induced on the orbit of a test particle revolving around a central body by putative spatial variations of fundamental coupling constants $\\zeta$. In particular, we assume a dipole gradient for $\\zeta(\\bds r)/\\bar{\\zeta}$ along a generic direction $\\bds{\\hat{k}}$ in space. We analytically work out the long-term variations of all the six standard Keplerian orbital elements parameterizing the orbit of a test particle in a gravitationally bound two-body system. It turns out that, apart from the semi-major axis $a$, the eccentricity $e$, the inclination $I$, the longitude of the ascending node $\\Omega$, the longitude of pericenter $\\pi$ and the mean anomaly $\\mathcal{M}$ undergo non-zero long-term changes. By using the usual decomposition along the radial ($R$), transverse ($T$) and normal ($N$) directions, we also analytically work out the long-term changes $\\Delta R,\\Delta T,\\Delta N$ and $\\Delta v_R,\\Delta v_T,\\Delta v_N$ experienced by the position and the velocity vectors $\\bds r$ and...
Loll, Per; Moldrup, Per
2000-04-01
Field-scale pesticide leaching risk assessments were performed by incorporating a numerical, one-dimensional, water and pesticide transport and fate model into the two-step stochastic modeling approach by Loll and Moldrup [1998]. The numerical model included first-order pesticide degradation, linear equilibrium adsorption, and plant uptake of water and pesticide. Simazine was used as a model pesticide, and leaching risk was expressed as the cumulative mass fraction of applied pesticide leached below 100 cm after 1 year. Spatial variability in soil physical and biochemical data, as well as measured meteorological data from an average and a relatively wet year, was considered for two Danish field sites: (1) a coarse sandy soil, with relatively small variability in hydraulic properties, and (2) a sandy loam, with large variability in hydraulic properties. The two-step stochastic modeling approach was used to investigate the relative impact of spatial variability in saturated hydraulic conductivity Ks, soil-water retention through the Campbell [974] soil-water retention parameter b, and pesticide sorption through the organic carbon content (OC). For the coarse sandy soil, field-scale spatial variability in OC was the single most important parameter influencing leaching risk, whereas for the sandy loam, Ks was found more important than OC. The relative impact of field-scale spatial variability in these parameters was found independent of the meteorological conditions, whereas the absolute level of leaching risk was highly dependent on the meteorological conditions. Assuming a linear dependency between pesticide half-life and OC, a unified approach to modeling simultaneous field-scale variability in biodegradation and adsorption was proposed. Leaching risk assessments based on this approach showed that the parts of the field with both low biological activity and low adsorption capacity contributed with a dramatic increase in leaching risk, and suggested that field
Energy Technology Data Exchange (ETDEWEB)
Lee, Kok Foong [Department of Chemical Engineering and Biotechnology, University of Cambridge, New Museums Site, Pembroke Street, Cambridge CB2 3RA (United Kingdom); Patterson, Robert I.A.; Wagner, Wolfgang [Weierstrass Institute for Applied Analysis and Stochastics, Mohrenstraße 39, 10117 Berlin (Germany); Kraft, Markus, E-mail: mk306@cam.ac.uk [Department of Chemical Engineering and Biotechnology, University of Cambridge, New Museums Site, Pembroke Street, Cambridge CB2 3RA (United Kingdom); School of Chemical and Biomedical Engineering, Nanyang Technological University, 62 Nanyang Drive, Singapore, 637459 (Singapore)
2015-12-15
Graphical abstract: -- Highlights: •Problems concerning multi-compartment population balance equations are studied. •A class of fragmentation weight transfer functions is presented. •Three stochastic weighted algorithms are compared against the direct simulation algorithm. •The numerical errors of the stochastic solutions are assessed as a function of fragmentation rate. •The algorithms are applied to a multi-dimensional granulation model. -- Abstract: This paper introduces stochastic weighted particle algorithms for the solution of multi-compartment population balance equations. In particular, it presents a class of fragmentation weight transfer functions which are constructed such that the number of computational particles stays constant during fragmentation events. The weight transfer functions are constructed based on systems of weighted computational particles and each of it leads to a stochastic particle algorithm for the numerical treatment of population balance equations. Besides fragmentation, the algorithms also consider physical processes such as coagulation and the exchange of mass with the surroundings. The numerical properties of the algorithms are compared to the direct simulation algorithm and an existing method for the fragmentation of weighted particles. It is found that the new algorithms show better numerical performance over the two existing methods especially for systems with significant amount of large particles and high fragmentation rates.
Optimal coupling of heat and electricity systems: A stochastic hierarchical approach
DEFF Research Database (Denmark)
Mitridati, Lesia Marie-Jeanne Mariane; Pinson, Pierre
2016-01-01
already exist due to the participation of CHPs in both markets. New market structures must be developed in order to exploit these synergies. Recognizing the above-mentioned challenges this paper proposes a stochastic hierarchical formulation of the heat economic dispatch problem in a system with high...
Modulation properties of spatial three-waveguide system using weakly coupled mode theory
Institute of Scientific and Technical Information of China (English)
Yiling Sun; Jianxia Pan
2007-01-01
Based on the weakly coupled mode theory, the modulation properties of three-waveguide system are analyzed in general. We examine the modulation behavior for two cases that a voltage is applied on the beamlaunched waveguide or non-beam-launched waveguide. The analytical intensity distributions in both cases are given. Applications of the spatial multi-waveguide coupling systems include spatial light modulators,optical switches, optical interconnection, and spatial optical signal processing.
Plyasunov, S
2005-01-01
This paper is concerned with classes of models of stochastic reaction dynamics with time-scales separation. We demonstrate that the existence of the time-scale separation naturally leads to the application of the averaging principle and elimination of degrees of freedom via the renormalization of transition rates of slow reactions. The method suggested in this work is more general than other approaches presented previously: it is not limited to a particular type of stochastic processes and can be applied to different types of processes describing fast dynamics, and also provides crossover to the case when separation of time scales is not well pronounced. We derive a family of exact fluctuation-dissipation relations which establish the connection between effective rates and the statistics of the reaction events in fast reaction channels. An illustration of the technique is provided. Examples show that renormalized transition rates exhibit in general non-exponential relaxation behavior with a broad range of pos...
Coupled stochastic soil moisture simulation-optimization model of deficit irrigation
Alizadeh, Hosein; Mousavi, S. Jamshid
2013-07-01
This study presents an explicit stochastic optimization-simulation model of short-term deficit irrigation management for large-scale irrigation districts. The model which is a nonlinear nonconvex program with an economic objective function is built on an agrohydrological simulation component. The simulation component integrates (1) an explicit stochastic model of soil moisture dynamics of the crop-root zone considering interaction of stochastic rainfall and irrigation with shallow water table effects, (2) a conceptual root zone salt balance model, and 3) the FAO crop yield model. Particle Swarm Optimization algorithm, linked to the simulation component, solves the resulting nonconvex program with a significantly better computational performance compared to a Monte Carlo-based implicit stochastic optimization model. The model has been tested first by applying it in single-crop irrigation problems through which the effects of the severity of water deficit on the objective function (net benefit), root-zone water balance, and irrigation water needs have been assessed. Then, the model has been applied in Dasht-e-Abbas and Ein-khosh Fakkeh Irrigation Districts (DAID and EFID) of the Karkheh Basin in southwest of Iran. While the maximum net benefit has been obtained for a stress-avoidance (SA) irrigation policy, the highest water profitability has been resulted when only about 60% of the water used in the SA policy is applied. The DAID with respectively 33% of total cultivated area and 37% of total applied water has produced only 14% of the total net benefit due to low-valued crops and adverse soil and shallow water table conditions.
Institute of Scientific and Technical Information of China (English)
Katsuaki Koike
2011-01-01
Sample data in the Earth and environmental sciences are limited in quantity and sampling location and therefore, sophisticated spatial modeling techniques are indispensable for accurate imaging of complicated structures and properties of geomaterials. This paper presents several effective methods that are grouped into two categories depending on the nature of regionalized data used. Type I data originate from plural populations and type II data satisfy the prerequisite of stationarity and have distinct spatial correlations. For the type I data, three methods are shown to be effective and demonstrated to produce plausible results: (1) a spline-based method, (2) a combination of a spline-based method with a stochastic simulation, and (3) a neural network method. Geostatistics proves to be a powerful tool for type II data. Three new approaches of geostatistics are presented with case studies: an application to directional data such as fracture, multi-scale modeling that incorporates a scaling law,and space-time joint analysis for multivariate data. Methods for improving the contribution of such spatial modeling to Earth and environmental sciences are also discussed and future important problems to be solved are summarized.
Immonen, Taina; Gibson, Richard; Leitner, Thomas; Miller, Melanie A; Arts, Eric J; Somersalo, Erkki; Calvetti, Daniela
2012-11-01
We present a new hybrid stochastic-deterministic, spatially distributed computational model to simulate growth competition assays on a relatively immobile monolayer of peripheral blood mononuclear cells (PBMCs), commonly used for determining ex vivo fitness of human immunodeficiency virus type-1 (HIV-1). The novel features of our approach include incorporation of viral diffusion through a deterministic diffusion model while simulating cellular dynamics via a stochastic Markov chain model. The model accounts for multiple infections of target cells, CD4-downregulation, and the delay between the infection of a cell and the production of new virus particles. The minimum threshold level of infection induced by a virus inoculum is determined via a series of dilution experiments, and is used to determine the probability of infection of a susceptible cell as a function of local virus density. We illustrate how this model can be used for estimating the distribution of cells infected by either a single virus type or two competing viruses. Our model captures experimentally observed variation in the fitness difference between two virus strains, and suggests a way to minimize variation and dual infection in experiments.
Lin, Hai; Shuai, J. W.
2010-04-01
A stochastic spatial model based on the Monte Carlo approach is developed to study the dynamics of human immunodeficiency virus (HIV) infection. We aim to propose a more detailed and realistic simulation frame by incorporating many important features of HIV dynamics, which include infections, replications and mutations of viruses, antigen recognitions, activations and proliferations of lymphocytes, and diffusions, encounters and interactions of virions and lymphocytes. Our model successfully reproduces the three-phase pattern observed in HIV infection, and the simulation results for the time distribution from infection to AIDS onset are also in good agreement with the clinical data. The interactions of viruses and the immune system in all the three phases are investigated. We assess the relative importance of various immune system components in the acute phase. The dynamics of how the two important factors, namely the viral diversity and the asymmetric battle between HIV and the immune system, result in AIDS are investigated in detail with the model.
Energy Technology Data Exchange (ETDEWEB)
Lin Hai [Department of Chemical Biology, Xiamen University, Xiamen 361005 (China); Shuai, J W, E-mail: jianweishuai@xmu.edu.c [Department of Physics and Institute of Theoretical Physics and Astrophysics, Xiamen University, Xiamen 361005 (China)
2010-04-15
A stochastic spatial model based on the Monte Carlo approach is developed to study the dynamics of human immunodeficiency virus (HIV) infection. We aim to propose a more detailed and realistic simulation frame by incorporating many important features of HIV dynamics, which include infections, replications and mutations of viruses, antigen recognitions, activations and proliferations of lymphocytes, and diffusions, encounters and interactions of virions and lymphocytes. Our model successfully reproduces the three-phase pattern observed in HIV infection, and the simulation results for the time distribution from infection to AIDS onset are also in good agreement with the clinical data. The interactions of viruses and the immune system in all the three phases are investigated. We assess the relative importance of various immune system components in the acute phase. The dynamics of how the two important factors, namely the viral diversity and the asymmetric battle between HIV and the immune system, result in AIDS are investigated in detail with the model.
Parasuraman, Ramviyas; Fabry, Thomas; Molinari, Luca; Kershaw, Keith; Di Castro, Mario; Masi, Alessandro; Ferre, Manuel
2014-12-12
The reliability of wireless communication in a network of mobile wireless robot nodes depends on the received radio signal strength (RSS). When the robot nodes are deployed in hostile environments with ionizing radiations (such as in some scientific facilities), there is a possibility that some electronic components may fail randomly (due to radiation effects), which causes problems in wireless connectivity. The objective of this paper is to maximize robot mission capabilities by maximizing the wireless network capacity and to reduce the risk of communication failure. Thus, in this paper, we consider a multi-node wireless tethering structure called the "server-relay-client" framework that uses (multiple) relay nodes in between a server and a client node. We propose a robust stochastic optimization (RSO) algorithm using a multi-sensor-based RSS sampling method at the relay nodes to efficiently improve and balance the RSS between the source and client nodes to improve the network capacity and to provide redundant networking abilities. We use pre-processing techniques, such as exponential moving averaging and spatial averaging filters on the RSS data for smoothing. We apply a receiver spatial diversity concept and employ a position controller on the relay node using a stochastic gradient ascent method for self-positioning the relay node to achieve the RSS balancing task. The effectiveness of the proposed solution is validated by extensive simulations and field experiments in CERN facilities. For the field trials, we used a youBot mobile robot platform as the relay node, and two stand-alone Raspberry Pi computers as the client and server nodes. The algorithm has been proven to be robust to noise in the radio signals and to work effectively even under non-line-of-sight conditions.
Directory of Open Access Journals (Sweden)
Ramviyas Parasuraman
2014-12-01
Full Text Available The reliability of wireless communication in a network of mobile wireless robot nodes depends on the received radio signal strength (RSS. When the robot nodes are deployed in hostile environments with ionizing radiations (such as in some scientific facilities, there is a possibility that some electronic components may fail randomly (due to radiation effects, which causes problems in wireless connectivity. The objective of this paper is to maximize robot mission capabilities by maximizing the wireless network capacity and to reduce the risk of communication failure. Thus, in this paper, we consider a multi-node wireless tethering structure called the “server-relay-client” framework that uses (multiple relay nodes in between a server and a client node. We propose a robust stochastic optimization (RSO algorithm using a multi-sensor-based RSS sampling method at the relay nodes to efficiently improve and balance the RSS between the source and client nodes to improve the network capacity and to provide redundant networking abilities. We use pre-processing techniques, such as exponential moving averaging and spatial averaging filters on the RSS data for smoothing. We apply a receiver spatial diversity concept and employ a position controller on the relay node using a stochastic gradient ascent method for self-positioning the relay node to achieve the RSS balancing task. The effectiveness of the proposed solution is validated by extensive simulations and field experiments in CERN facilities. For the field trials, we used a youBot mobile robot platform as the relay node, and two stand-alone Raspberry Pi computers as the client and server nodes. The algorithm has been proven to be robust to noise in the radio signals and to work effectively even under non-line-of-sight conditions.
The spatial light receiver and its coupling characteristics
Hu, Qinggui; Li, Chengzhong
2017-07-01
The effective couple of the space light into the optical fiber is the key point of the free-space optical communication. In order to solve this problem, the novel tapered optical fiber head is proposed. The special tapered structure could improve coupling efficiency through expanding the light receiving area. In order to study its coupling characteristics, the longitudinal propagation constant of the connector is expanded by Taylor series according to the wave theory. And the approximate solution of the power distribution is obtained. Then, the coupling efficiency measurement experiment with the tapered connectors and the conmmon connector is finished. The experimental result is consistent with the theoretical analysis basically. This work provides a theoretical reference for the design of the new tapered connector, which could be adopted in the free-space optical communication.
Institute of Scientific and Technical Information of China (English)
ZHOU Wen; PENG Xin-jun; LIU Xiang; YAN Zheng-lou; WANG Yi-fei
2008-01-01
In this paper,we develop a modified accelerated stochastic simulation method for chemically reacting systems,called the "final all possible steps"(FAPS)method,which obtains the reliable statistics of all species in any time during the time course with fewer simulation times.Moreover,the FAPS method can be incorporated into the leap methods,which makes the simulation of larger systems more efficient.Numerical results indicate that the proposed methods can be applied to a wide range of chemically reacting systems with a high-precision level and obtain a significant improvement on efficiency over the existing methods.
Directory of Open Access Journals (Sweden)
Yilun Shang
2012-07-01
Full Text Available In this paper, we investigate the leader-follower synchronization ofcoupled second-order linear harmonic oscillators with the presence ofrandom noises and time delays. The interaction topology is modeledby a weighted directed graph and the weights are perturbed by whitenoise. On the basis of stability theory of stochastic differential delayequations, algebraic graph theory and matrix theory, we show that thecoupled harmonic oscillators can be synchronized almost surely withrandom perturbation and time delays. Numerical examples are presentedto illustrate our theoretical results.
Llopis-Albert, Carlos; Merigó, José M.; Xu, Yejun
2016-09-01
This paper presents an alternative approach to deal with seawater intrusion problems, that overcomes some of the limitations of previous works, by coupling the well-known SWI2 package for MODFLOW with a stochastic inverse model named GC method. On the one hand, the SWI2 allows a vertically integrated variable-density groundwater flow and seawater intrusion in coastal multi-aquifer systems, and a reduction in number of required model cells and the elimination of the need to solve the advective-dispersive transport equation, which leads to substantial model run-time savings. On the other hand, the GC method allows dealing with groundwater parameter uncertainty by constraining stochastic simulations to flow and mass transport data (i.e., hydraulic conductivity, freshwater heads, saltwater concentrations and travel times) and also to secondary information obtained from expert judgment or geophysical surveys, thus reducing uncertainty and increasing reliability in meeting the environmental standards. The methodology has been successfully applied to a transient movement of the freshwater-seawater interface in response to changing freshwater inflow in a two-aquifer coastal aquifer system, where an uncertainty assessment has been carried out by means of Monte Carlo simulation techniques. The approach also allows partially overcoming the neglected diffusion and dispersion processes after the conditioning process since the uncertainty is reduced and results are closer to available data.
A tightly-coupled domain-decomposition approach for highly nonlinear stochastic multiphysics systems
Taverniers, Søren; Tartakovsky, Daniel M.
2017-02-01
Multiphysics simulations often involve nonlinear components that are driven by internally generated or externally imposed random fluctuations. When used with a domain-decomposition (DD) algorithm, such components have to be coupled in a way that both accurately propagates the noise between the subdomains and lends itself to a stable and cost-effective temporal integration. We develop a conservative DD approach in which tight coupling is obtained by using a Jacobian-free Newton-Krylov (JfNK) method with a generalized minimum residual iterative linear solver. This strategy is tested on a coupled nonlinear diffusion system forced by a truncated Gaussian noise at the boundary. Enforcement of path-wise continuity of the state variable and its flux, as opposed to continuity in the mean, at interfaces between subdomains enables the DD algorithm to correctly propagate boundary fluctuations throughout the computational domain. Reliance on a single Newton iteration (explicit coupling), rather than on the fully converged JfNK (implicit) coupling, may increase the solution error by an order of magnitude. Increase in communication frequency between the DD components reduces the explicit coupling's error, but makes it less efficient than the implicit coupling at comparable error levels for all noise strengths considered. Finally, the DD algorithm with the implicit JfNK coupling resolves temporally-correlated fluctuations of the boundary noise when the correlation time of the latter exceeds some multiple of an appropriately defined characteristic diffusion time.
Flux for a System with Infinite Globally Coupled Oscillators Driven by Temporal-Spatial Noises
Institute of Scientific and Technical Information of China (English)
HAN Yin-Xia; LI Jing-Hui; CHEN Shi-Gang
2003-01-01
The transport of a spatially periodic system with infinite globally coupled oscillators driven by temporalspatial noises is investigated. The probability current shows that the correlation of the multiplicative noises with the space, the spatial asymmetry, and the coupling among the different oscillators are ingredients for the transport of particles. It is a new phenomenon that the correlation of the multiplicative noises with the space can induce the nonzero flux.
Coupled spatial multi-mode solitons in microcavity wires
Slavcheva, G; Pimenov, A
2016-01-01
A modal expansion approach is developed and employed to investigate and elucidate the nonlinear mechanism behind the multistability and formation of coupled multi-mode polariton solitons in microcavity wires. With pump switched on and realistic dissipation parameters, truncating the expansion up to the second-order wire mode, our model predicts two distinct coupled soliton branches: stable and ustable. Modulational stability of the homogeneous solution and soliton branches stability are studied. Our simplified 1D model is in remarkably good agreement with the full 2D mean-field Gross-Pitaevskii model, reproducing correctly the soliton existence domain upon variation of pump amplitude and the onset of multistability.
Veeraraghavan, Rengasayee; Gourdie, Robert G
2016-11-07
The spatial association between proteins is crucial to understanding how they function in biological systems. Colocalization analysis of fluorescence microscopy images is widely used to assess this. However, colocalization analysis performed on two-dimensional images with diffraction-limited resolution merely indicates that the proteins are within 200-300 nm of each other in the xy-plane and within 500-700 nm of each other along the z-axis. Here we demonstrate a novel three-dimensional quantitative analysis applicable to single-molecule positional data: stochastic optical reconstruction microscopy-based relative localization analysis (STORM-RLA). This method offers significant advantages: 1) STORM imaging affords 20-nm resolution in the xy-plane and quantitative assessment of the frequency and degree of overlap between clusters of colabeled proteins; and 3) STORM-RLA also calculates the precise distances between both overlapping and nonoverlapping clusters in three dimensions. Thus STORM-RLA represents a significant advance in the high-throughput quantitative assessment of the spatial organization of proteins. © 2016 Veeraraghavan and Gourdie. This article is distributed by The American Society for Cell Biology under license from the author(s). Two months after publication it is available to the public under an Attribution–Noncommercial–Share Alike 3.0 Unported Creative Commons License (http://creativecommons.org/licenses/by-nc-sa/3.0).
Comparison of deterministic and stochastic methods to predict spatial variation of groundwater depth
Adhikary, Partha Pratim; Dash, Ch. Jyotiprava
2014-11-01
Accurate and reliable interpolation of groundwater depth over a region is a pre-requisite for efficient planning and management of water resources. The performance of two deterministic, such as inverse distance weighting (IDW) and radial basis function (RBF) and two stochastic, i.e., ordinary kriging (OK) and universal kriging (UK) interpolation methods was compared to predict spatio-temporal variation of groundwater depth. Pre- and post-monsoon groundwater level data for the year 2006 from 110 different locations over Delhi were used. Analyses revealed that OK and UK methods outperformed the IDW method, and UK performed better than OK. RBF also performed better than IDW and OK. IDW and RBF methods slightly underestimated and both the kriging methods slightly overestimated the prediction of water table depth. OK, RBF and UK yielded 27.52, 27.66 and 51.11 % lower RMSE, 27.49, 35.34 and 51.28 % lower MRE, and 14.21, 16.12 and 21.36 % higher R 2 over IDW. The isodepth-area curves indicated the possibility of exploitation of groundwater up to a depth of 20 m.
National Research Council Canada - National Science Library
Chiba, Ryoichi
2009-01-01
... and lower surfaces of the discs are insulated or heat is dissipated with uniform heat transfer coefficients (HTCs) throughout the surfaces. In actual thermal environments, the HTCs of object surfaces are known to vary spatially and depend heavily on the motion of the surrounding media and the surface properties including surface asperities [7,8] . Obviousl...
Electric currents couple spatially separated biogeochemical processes in marine sediment
DEFF Research Database (Denmark)
Nielsen, Lars Peter; Risgaard-Petersen, Nils; Fossing, Henrik;
2010-01-01
be coupled by electric currents in nature. Here we provide evidence that electric currents running through defaunated sediment couple oxygen consumption at the sediment surface to oxidation of hydrogen sulphide and organic carbon deep within the sediment. Altering the oxygen concentration in the sea water...... in the sediment was driven by electrons conducted from the anoxic zone. A distinct pH peak in the oxic zone could be explained by electrochemical oxygen reduction, but not by any conventional sets of aerobic sediment processes. We suggest that the electric current was conducted by bacterial nanowires combined...... with pyrite, soluble electron shuttles and outer-membrane cytochromes. Electrical communication between distant chemical and biological processes in nature adds a new dimension to our understanding of biogeochemistry and microbial ecology....
Electromagnetic Design of a Magnetically-Coupled Spatial Power Combiner
Bulcha, B.; Cataldo, G.; Stevenson, T. R.; U-Yen, K.; Moseley, S. H.; Wollack, E. J.
2017-01-01
The design of a two-dimensional beam-combining network employing a parallel-plate superconducting waveguide with a mono-crystalline silicon dielectric is presented. This novel beam-combining network structure employs an array of magnetically coupled antenna elements to achieve high coupling efficiency and full sampling of the intensity distribution while avoiding diffractive losses in the multi-mode region defined by the parallel-plate waveguide. These attributes enable the structures use in realizing compact far-infrared spectrometers for astrophysical and instrumentation applications. When configured with a suitable corporate-feed power-combiner, this fully sampled array can be used to realize a low-sidelobe apodized response without incurring a reduction in coupling efficiency. To control undesired reflections over a wide range of angles in the finite-sized parallel-plate waveguide region, a wideband meta-material electromagnetic absorber structure is implemented. This adiabatic structure absorbs greater than 99 of the power over the 1.7:1 operational band at angles ranging from normal (0 degree) to near parallel (180 degree) incidence. Design, simulations, and application of the device will be presented.
Zheng, Fei; Zhu, Jiang
2016-12-01
How to design a reliable ensemble prediction strategy with considering the major uncertainties of a forecasting system is a crucial issue for performing an ensemble forecast. In this study, a new stochastic perturbation technique is developed to improve the prediction skills of El Niño-Southern Oscillation (ENSO) through using an intermediate coupled model. We first estimate and analyze the model uncertainties from the ensemble Kalman filter analysis results through assimilating the observed sea surface temperatures. Then, based on the pre-analyzed properties of model errors, we develop a zero-mean stochastic model-error model to characterize the model uncertainties mainly induced by the missed physical processes of the original model (e.g., stochastic atmospheric forcing, extra-tropical effects, Indian Ocean Dipole). Finally, we perturb each member of an ensemble forecast at each step by the developed stochastic model-error model during the 12-month forecasting process, and add the zero-mean perturbations into the physical fields to mimic the presence of missing processes and high-frequency stochastic noises. The impacts of stochastic model-error perturbations on ENSO deterministic predictions are examined by performing two sets of 21-year hindcast experiments, which are initialized from the same initial conditions and differentiated by whether they consider the stochastic perturbations. The comparison results show that the stochastic perturbations have a significant effect on improving the ensemble-mean prediction skills during the entire 12-month forecasting process. This improvement occurs mainly because the nonlinear terms in the model can form a positive ensemble-mean from a series of zero-mean perturbations, which reduces the forecasting biases and then corrects the forecast through this nonlinear heating mechanism.
Stochastic Urban Pluvial Flood Hazard Maps Based upon a Spatial-Temporal Rainfall Generator
Nuno Eduardo Simões; Susana Ochoa-Rodríguez; Li-Pen Wang; Rui Daniel Pina; Alfeu Sá Marques; Christian Onof; Leitão, João P.
2015-01-01
It is a common practice to assign the return period of a given storm event to the urban pluvial flood event that such storm generates. However, this approach may be inappropriate as rainfall events with the same return period can produce different urban pluvial flooding events, i.e., with different associated flood extent, water levels and return periods. This depends on the characteristics of the rainfall events, such as spatial variability, and on other characteristics of the sewer system a...
Utagawa, Akira; Sahashi, Tohru; Asai, Tetsuya; Amemiya, Yoshihito
We found a new class of stochastic resonance (SR) in a simple neural network that consists of i) photoreceptors generating nonuniform outputs for common inputs with random offsets, ii) an ensemble of noisy McCulloch-Pitts (MP) neurons each of which has random threshold values in the temporal domain, iii) local coupling connections between the photoreceptors and the MP neurons with variable receptive fields (RFs), iv) output cells, and v) local coupling connections between the MP neurons and the output cells. We calculated correlation values between the inputs and the outputs as a function of the RF size and intensities of the random components in photoreceptors and the MP neurons. We show the existence of “optimal noise intensities” of the MP neurons under the nonidentical photoreceptors and “nonzero optimal RF sizes, ” which indicated that optimal correlation values of this SR model were determined by two critical parameters; noise intensities (well-known) and RF sizes as a new parameter.
Scheerlinck, N.; Verboven, P.; Stigter, J.D.; Baerdenmaeker, de J.; Impe, van J.F.; Nicolai, B.A.
2000-01-01
A first-order perturbation algorithm for the computation of mean values and variances of transient temperature and moisture fields during coupled heat and mass transfer problems with random field parameters has been developed and implemented. The algorithm is based on the Galerkin finite-element dis
Vector nematicons: Coupled spatial solitons in nematic liquid crystals
Horikis, Theodoros P.; Frantzeskakis, Dimitrios J.
2016-11-01
Families of soliton pairs, namely vector solitons, are found within the context of a coupled nonlocal nonlinear Schrödinger system of equations, as appropriate for modeling beam propagation in nematic liquid crystals. In the focusing case, bright soliton pairs have been found to exist provided their amplitudes satisfy a specific condition. In our analytical approach, focused on the defocusing regime, we rely on a multiscale expansion methods, which reveals the existence of dark-dark and antidark-antidark solitons, obeying an effective Korteweg-de Vries equation, as well as dark-bright solitons, obeying an effective Mel'nikov system. These pairs are discriminated by the sign of a constant that links all physical parameters of the system to the amplitude of the stable continuous wave solutions, and, much like the focusing case, the solitons' amplitudes are linked, leading to mutual guiding.
Nichols, J.M.; Moniz, L.; Nichols, J.D.; Pecora, L.M.; Cooch, E.
2005-01-01
A number of important questions in ecology involve the possibility of interactions or ?coupling? among potential components of ecological systems. The basic question of whether two components are coupled (exhibit dynamical interdependence) is relevant to investigations of movement of animals over space, population regulation, food webs and trophic interactions, and is also useful in the design of monitoring programs. For example, in spatially extended systems, coupling among populations in different locations implies the existence of redundant information in the system and the possibility of exploiting this redundancy in the development of spatial sampling designs. One approach to the identification of coupling involves study of the purported mechanisms linking system components. Another approach is based on time series of two potential components of the same system and, in previous ecological work, has relied on linear cross-correlation analysis. Here we present two different attractor-based approaches, continuity and mutual prediction, for determining the degree to which two population time series (e.g., at different spatial locations) are coupled. Both approaches are demonstrated on a one-dimensional predator?prey model system exhibiting complex dynamics. Of particular interest is the spatial asymmetry introduced into the model as linearly declining resource for the prey over the domain of the spatial coordinate. Results from these approaches are then compared to the more standard cross-correlation analysis. In contrast to cross-correlation, both continuity and mutual prediction are clearly able to discern the asymmetry in the flow of information through this system.
Long-range correlations in a simple stochastic model of coupled transport
Energy Technology Data Exchange (ETDEWEB)
Larralde, Hernan [Instituto de Ciencias Fisicas, Universidad Nacional Autonoma de Mexico, Apartado Postal 48-3, 62551 Cuernavaca, Morelos (Mexico); Sanders, David P [Departamento de Fisica, Facultad de Ciencias, Universidad Nacional Autonoma de Mexico, Ciudad Universitaria, 04510 Mexico DF (Mexico)], E-mail: hernan@fis.unam.mx, E-mail: dps@fciencias.unam.mx
2009-08-21
We study coupled transport in the nonequilibrium stationary state of a model consisting of independent random walkers, moving along a one-dimensional channel, which carry a conserved energy-like quantity, with density and temperature gradients imposed by reservoirs at the ends of the channel. In our model, walkers interact with other walkers at the same site by sharing energy at each time step, but the amount of energy carried does not affect the motion of the walkers. We find that already in this simple model long-range correlations arise in the nonequilibrium stationary state which are similar to those observed in more realistic models of coupled transport. We derive an analytical expression for the source of these correlations, which we use to obtain semi-analytical results for the correlations themselves assuming a local-equilibrium hypothesis. These are in very good agreement with results from direct numerical simulations.
Stochastic analysis of transverse dispersion in density-coupled transport in aquifers
Welty, C.; Kane, A. C.; Kauffman, L.J.
2003-01-01
Spectral perturbation techniques have been used previously to derive integral expressions for dispersive mixing in concentration-dependent transport in three-dimensional, heterogeneous porous media, where fluid density and viscosity are functions of solute concentration. Whereas earlier work focused on evaluating longitudinal dispersivity in isotropic media and incorporating the result in a mean one-dimensional transport model, the emphasis of this paper is on evaluation of the complete dispersion tensor, including the more general case of anisotropic media. Approximate analytic expressions for all components of the macroscopic dispersivity tensor are derived, and the tensor is shown to be asymmetric. The tensor is separated into its symmetric and antisymmetric parts, where the symmetric part is used to calculate the principal components and principal directions of dispersivity, and the antisymmetric part of the tensor is shown to modify the velocity of the solute body compared to that of the background fluid. An example set of numerical simulations incorporating the tensor illustrates the effect of density-coupled dispersivity on a sinking plume in an aquifer. The simulations show that the effective transverse vertical spreading in a sinking plume to be significantly greater than would be predicted by a standard density-coupled transport model that does not incorporate the coupling in the dispersivity tensor.
Selection in spatial stochastic models of cancer: Migration as a key modulator of fitness
Directory of Open Access Journals (Sweden)
Stupack Dwayne
2010-04-01
Full Text Available Abstract Background We study the selection dynamics in a heterogeneous spatial colony of cells. We use two spatial generalizations of the Moran process, which include cell divisions, death and migration. In the first model, migration is included explicitly as movement to a proximal location. In the second, migration is implicit, through the varied ability of cell types to place their offspring a distance away, in response to another cell's death. Results In both models, we find that migration has a direct positive impact on the ability of a single mutant cell to invade a pre-existing colony. Thus, a decrease in the growth potential can be compensated by an increase in cell migration. We further find that the neutral ridges (the set of all types with the invasion probability equal to that of the host cells remain invariant under the increase of system size (for large system sizes, thus making the invasion probability a universal characteristic of the cells selection status. We find that repeated instances of large scale cell-death, such as might arise during therapeutic intervention or host response, strongly select for the migratory phenotype. Conclusions These models can help explain the many examples in the biological literature, where genes involved in cell's migratory and invasive machinery are also associated with increased cellular fitness, even though there is no known direct effect of these genes on the cellular reproduction. The models can also help to explain how chemotherapy may provide a selection mechanism for highly invasive phenotypes. Reviewers This article was reviewed by Marek Kimmel and Glenn Webb.
2016-01-01
Mutual coupling inside antenna array is usually caused by two routes: signal leakage via conducting currents on the metallic background or surface wave along substrates; radio leakage received from space between antenna elements. The former one can be depressed by changing the distribution of surface currents, as reported in literatures. But when it comes to the latter one, the radiation-leakage-caused coupling, traditional approaches using circuit manipulation may be inefficient. In this art...
Seyyedi, H.; Kaheil, Y.; Anagnostou, E. N.; McCollum, J.; Beighley, E.
2013-12-01
Deriving flood maps requires an accurate characterization of precipitation variability at high spatio-temporal resolution. Most of the available global-scale gridded precipitation products are available at resolutions (e.g., 25 km) not directly applicable to flood modeling. An error correction and spatial downscaling method based on a two-dimensional satellite rainfall error model (SREM2D) is tested in this study based on a long-term (2001-2010) dataset. Specifically, the model is applied on two rainfall datasets: a satellite precipitation product (TRMM-3B42.V7 at 0.25 degree) and a global land-atmosphere re-analysis product (GLDAS-CLM at 1 degree), to produce error corrected rainfall ensembles at 0.05 degree spatial resolution. The NCEP hourly, 4-km resolution multi-sensor precipitation product (WSR-88D stage IV gauge-adjusted radar-rainfall product) is used as the reference rainfall dataset. The Hillslope River Routing (HRR) hydrologic model is forced with the downscaled ensemble rainfall data to produce an ensemble of runoff values. The Susquehanna River basin is the study area, consisting of 1000 sub-basins ranging from 39 to 67,000 square kilometers including complex terrain and high latitude locations. There are 437 significant storm events selected over the study area based on the 10-year database. The analysis performed is based on 60 percent of events in each season kept for model calibration and 40 percent for validation. The statistical analysis consists of two parts: (1) evaluation of error metrics (relative standard deviation and efficiency coefficient) to quantify improvements in rainfall and runoff simulations as function of basin size and storm severity, and (2) ensemble verification (exceedance probability and mean uncertainty ratio) of the rainfall and runoff ensembles to assess the accuracy of the ensemble-based uncertainty characterization. The study investigates how well the ensemble of downscaled and error-corrected rainfall data performs
Zhao, Fu; Landis, Heather R; Skerlos, Steven J
2005-01-01
A methodology for producing a pore-scale, 3D computational model of porous filter permeability is developed that is based on the analysis of 2D images of the filter matrix and first principles. The computationally reconstructed porous filter model retains statistical details of porosity and the spatial correlations of porosity within the filter and can be used to calculate permeability for either isotropic or 1D anisotropic porous filters. In the isotropic case, validation of the methodology was conducted using 0.2 and 0.8 microm ceramic membrane filters,forwhich it is shown that the image-based computational models provide a viable statistical reproduction of actual porosity characteristics. It is also shown that these models can predict water flux directly from first principles with deviations from experimental measurements in the range of experimental error. In the anisotropic case, validation of the methodology was conducted using a natural river sand filter. For this case, it is shown that the methodology yields predictions of filtration velocity that are similar or better than predictions offered by existing filtration models. It was found for the sand filter that the deviation between observation and prediction was mostly due to swelling during the preparation of the sand filter for imaging and can be reduced significantly using alternative methods reported in the literature. On the basis of these results, it is concluded that the computational reconstruction methodology is valid for porous filter modeling, and given that it captures pore-scale details, it has potential application to the investigation of permeability decline underthe influence of pore-scale fouling mechanisms.
Directory of Open Access Journals (Sweden)
Daniel Stockholm
Full Text Available BACKGROUND: In culture, isogenic mammalian cells typically display enduring phenotypic heterogeneity that arises from fluctuations of gene expression and other intracellular processes. This diversity is not just simple noise but has biological relevance by generating plasticity. Noise driven plasticity was suggested to be a stem cell-specific feature. RESULTS: Here we show that the phenotypes of proliferating tissue progenitor cells such as primary mononuclear muscle cells can also spontaneously fluctuate between different states characterized by the either high or low expression of the muscle-specific cell surface molecule CD56 and by the corresponding high or low capacity to form myotubes. Although this capacity is a cell-intrinsic property, the cells switch their phenotype under the constraints imposed by the highly heterogeneous microenvironment created by their own collective movement. The resulting heterogeneous cell population is characterized by a dynamic equilibrium between "high CD56" and "low CD56" phenotype cells with distinct spatial distribution. Computer simulations reveal that this complex dynamic is consistent with a context-dependent noise driven bistable model where local microenvironment acts on the cellular state by encouraging the cell to fluctuate between the phenotypes until the low noise state is found. CONCLUSIONS: These observations suggest that phenotypic fluctuations may be a general feature of any non-terminally differentiated cell. The cellular microenvironment created by the cells themselves contributes actively and continuously to the generation of fluctuations depending on their phenotype. As a result, the cell phenotype is determined by the joint action of the cell-intrinsic fluctuations and by collective cell-to-cell interactions.
A coupled deterministic/stochastic method for computing neutron capture therapy dose rates
Hubbard, Thomas Richard
Neutron capture therapy (NCT) is an experimental method of treating brain tumors and other cancers by: (1) injecting or infusing the patient with a tumor-seeking, neutron target-labeled drug; and (2) irradiating the patient in an intense epithermal neutron fluence. The nuclear reaction between the neutrons and the target nuclei (e.g. sp{10}B(n,alpha)sp7Lirbrack releases energy in the form of high-LET (i.e. energy deposited within the range of a cell diameter) reaction particles which selectively kill the tumor cell. The efficacy of NCT is partly dependent on the delivery of maximum thermal neutron fluence to the tumor and the minimization of radiation dose to healthy tissue. Since the filtered neutron source (e.g. research reactor) usually provides a broad energy spectrum of highly-penetrating neutron and gamma-photon radiation, detailed transport calculations are necessary in order to plan treatments that use optimal treatment facility configurations and patient positioning. Current computational methods for NCT use either discrete ordinates calculation or, more often, Monte Carlo simulation to predict neutron fluences in the vicinity of the tumor. These methods do not, however, accurately calculate the transport of radiation throughout the entire facility or the deposition of dose in all the various parts of the body due to shortcomings of using either method alone. A computational method, specifically designed for NCT problems, has been adapted from the MASH methodology and couples a forward discrete ordinates (Ssb{n}) calculation with an adjoint Monte Carlo run to predict the dose at any point within the patient. The transport from the source through the filter/collimator is performed with a forward DORT run, and this is then coupled to adjoint MORSE results at a selected coupling parallelepiped which surrounds human phantom. Another routine was written to allow the user to generate the MORSE models at various angles and positions within the treatment room. The
DEFF Research Database (Denmark)
Davidsen, Claus; Liu, Suxia; Mo, Xingguo
2015-01-01
for pre-treatment of the water before use. Similarly, treatment of the return flow can reduce the BOD load to the river. A traditional SDP approach is used to solve one-step-ahead sub-problems for all combinations of discrete reservoir storage, Markov Chain inflow clas-ses and monthly time steps...... and customizable method. The method has been applied to the Ziya River basin, an economic hotspot located on the North China Plain in Northern China. The basin is subject to severe water scarcity, and the rivers are heavily polluted with wastewater and nutrients from diffuse sources. The coupled hydro......-economic optimiza-tion model can be used to assess costs of meeting additional constraints such as minimum water qual-ity or to economically prioritize investments in waste water treatment facilities based on economic criteria....
Les trajectoires spatiales d’activité des couples The spatial trajectories of couples’ activities
Directory of Open Access Journals (Sweden)
Eva Lelièvre
2010-07-01
Full Text Available Après avoir examiné les avancées récentes de l’observation et de l’analyse des contextes des parcours individuels en démographie, nous proposons ici de traiter le premier niveau interpersonnel des biographies liées : celui des deux membres d’un couple. Pour cela nous reconstituons la trajectoire de l’espace d’activité des deux conjoints formée des lieux de résidence et de travail qui se succèdent tout au long de leur union à partir des données de l’enquête Biographies et entourage de l’Ined. Puis nous présentons une approche holiste de ces trajectoires permettant d’en dégager une typologie grâce à la mise en œuvre d’une analyse qualitative harmonique dont nous détaillons les principes. La description de ces trajectoires éclaire les arbitrages des couples qui se jouent dans les stratégies de localisation, au confluent du travail, de la famille et du logement. Néanmoins, une discussion précise des limites et des pistes futures est proposée pour dépasser cette première application.After an overview of recent trends in data collection and of the different strategies applied to the demographic analysis of life courses embedded in their context, this paper presents the analysis of a specific level of interpersonal interaction : the intertwined dynamics of the life courses of both members of a couple. To this end, we reconstruct the dynamics of the activity space of couples defined as the territory covered by their place(s of residence and place(s of work since the beginning of their union, taking advantage of a rich data source, the INED Biographies et entourage survey. We then detail the principles of the data analysis method (Qualitative Harmonic Analysis. The description drawn from the typology obtained sheds light on the choices couples make for their residential moves, taking into account their family and occupational priorities. The limits of the method and future research paths are then discussed in
Pan, Bai Cao; Tang, Wen Xuan; Qi, Mei Qing; Ma, Hui Feng; Tao, Zui; Cui, Tie Jun
2016-01-01
Mutual coupling inside antenna array is usually caused by two routes: signal leakage via conducting currents on the metallic background or surface wave along substrates; radio leakage received from space between antenna elements. The former one can be depressed by changing the distribution of surface currents, as reported in literatures. But when it comes to the latter one, the radiation-leakage-caused coupling, traditional approaches using circuit manipulation may be inefficient. In this article, we propose and design a new type of decoupling module, which is composed of coupled metamaterial (MTM) slabs. Two classes of MTM particles, the interdigital structure (IS) and the split-ring resonators (SRRs), are adopted to provide the first and second modulations of signal. We validate its function to reduce the radiation leakage between two dual-polarized patch antennas. A prototype is fabricated in a volume with subwavelength scale (0.6λ × 0.3λ × 0.053λ) to provide 7dB improvement for both co-polarization and cross-polarization isolations from 1.95 to 2.2 GHz. The design has good potential for wireless communication and radar systems. PMID:27444147
Pan, Bai Cao; Tang, Wen Xuan; Qi, Mei Qing; Ma, Hui Feng; Tao, Zui; Cui, Tie Jun
2016-07-22
Mutual coupling inside antenna array is usually caused by two routes: signal leakage via conducting currents on the metallic background or surface wave along substrates; radio leakage received from space between antenna elements. The former one can be depressed by changing the distribution of surface currents, as reported in literatures. But when it comes to the latter one, the radiation-leakage-caused coupling, traditional approaches using circuit manipulation may be inefficient. In this article, we propose and design a new type of decoupling module, which is composed of coupled metamaterial (MTM) slabs. Two classes of MTM particles, the interdigital structure (IS) and the split-ring resonators (SRRs), are adopted to provide the first and second modulations of signal. We validate its function to reduce the radiation leakage between two dual-polarized patch antennas. A prototype is fabricated in a volume with subwavelength scale (0.6λ × 0.3λ × 0.053λ) to provide 7dB improvement for both co-polarization and cross-polarization isolations from 1.95 to 2.2 GHz. The design has good potential for wireless communication and radar systems.
A spatially indirect exciton in vertically coupled quantum dots : 1/Q-expansion
Lozovik, YE; Mur, VD; Narozhny, NB; Petrosyan, AN
2004-01-01
A spatially indirect exciton in vertically coupled quantum dots is considered with the use of 1/Q-expansion, where Q is the dimensionless quantum parameter determined by the ratio of characteristic Coulomb energy of electron-hole interaction to the energy of one-particle transition in a confining po
Davidsen, Claus; Liu, Suxia; Mo, Xingguo; Engelund Holm, Peter; Trapp, Stefan; Rosbjerg, Dan; Bauer-Gottwein, Peter
2015-04-01
Few studies address water quality in hydro-economic models, which often focus primarily on optimal allocation of water quantities. Water quality and water quantity are closely coupled, and optimal management with focus solely on either quantity or quality may cause large costs in terms of the oth-er component. In this study, we couple water quality and water quantity in a joint hydro-economic catchment-scale optimization problem. Stochastic dynamic programming (SDP) is used to minimize the basin-wide total costs arising from water allocation, water curtailment and water treatment. The simple water quality module can handle conservative pollutants, first order depletion and non-linear reactions. For demonstration purposes, we model pollutant releases as biochemical oxygen demand (BOD) and use the Streeter-Phelps equation for oxygen deficit to compute the resulting min-imum dissolved oxygen concentrations. Inelastic water demands, fixed water allocation curtailment costs and fixed wastewater treatment costs (before and after use) are estimated for the water users (agriculture, industry and domestic). If the BOD concentration exceeds a given user pollution thresh-old, the user will need to pay for pre-treatment of the water before use. Similarly, treatment of the return flow can reduce the BOD load to the river. A traditional SDP approach is used to solve one-step-ahead sub-problems for all combinations of discrete reservoir storage, Markov Chain inflow clas-ses and monthly time steps. Pollution concentration nodes are introduced for each user group and untreated return flow from the users contribute to increased BOD concentrations in the river. The pollutant concentrations in each node depend on multiple decision variables (allocation and wastewater treatment) rendering the objective function non-linear. Therefore, the pollution concen-tration decisions are outsourced to a genetic algorithm, which calls a linear program to determine the remainder of the decision
Generalized stochastic Schroedinger equations for state vector collapse
Adler, Stephen Louis; Adler, Stephen L.; Brun, Todd A.
2001-01-01
A number of authors have proposed stochastic versions of the Schr\\"odinger equation, either as effective evolution equations for open quantum systems or as alternative theories with an intrinsic collapse mechanism. We discuss here two directions for generalization of these equations. First, we study a general class of norm preserving stochastic evolution equations, and show that even after making several specializations, there is an infinity of possible stochastic Schr\\"odinger equations for which state vector collapse is provable. Second, we explore the problem of formulating a relativistic stochastic Schr\\"odinger equation, using a manifestly covariant equation for a quantum field system based on the interaction picture of Tomonaga and Schwinger. The stochastic noise term in this equation can couple to any local scalar density that commutes with the interaction energy density, and leads to collapse onto spatially localized eigenstates. However, as found in a similar model by Pearle, the equation predicts an...
Stochastic Samples versus Vacuum Expectation Values in Cosmology
Tsamis, N C; Woodard, R P
2010-01-01
Particle theorists typically use expectation values to study the quantum back-reaction on inflation, whereas many cosmologists stress the stochastic nature of the process. While expectation values certainly give misleading results for some things, such as the stress tensor, we argue that operators exist for which there is no essential problem. We quantify this by examining the stochastic properties of a noninteracting, massless, minimally coupled scalar on a locally de Sitter background. The square of the stochastic realization of this field seems to provide an example of great relevance for which expectation values are not misleading. We also examine the frequently expressed concern that significant back-reaction from expectation values necessarily implies large stochastic fluctuations between nearby spatial points. Rather than viewing the stochastic formalism in opposition to expectation values, we argue that it provides a marvelously simple way of capturing the leading infrared logarithm corrections to the...
Bouzat, Sebastián
2016-01-01
One-dimensional models coupling a Langevin equation for the cargo position to stochastic stepping dynamics for the motors constitute a relevant framework for analyzing multiple-motor microtubule transport. In this work we explore the consistence of these models focusing on the effects of the thermal noise. We study how to define consistent stepping and detachment rates for the motors as functions of the local forces acting on them in such a way that the cargo velocity and run-time match previously specified functions of the external load, which are set on the base of experimental results. We show that due to the influence of the thermal fluctuations this is not a trivial problem, even for the single-motor case. As a solution, we propose a motor stepping dynamics which considers memory on the motor force. This model leads to better results for single-motor transport than the approaches previously considered in the literature. Moreover, it gives a much better prediction for the stall force of the two-motor case, highly compatible with the experimental findings. We also analyze the fast fluctuations of the cargo position and the influence of the viscosity, comparing the proposed model to the standard one, and we show how the differences on the single-motor dynamics propagate to the multiple motor situations. Finally, we find that the one-dimensional character of the models impede an appropriate description of the fast fluctuations of the cargo position at small loads. We show how this problem can be solved by considering two-dimensional models.
[Spatial coupling characteristics of eco-environment quality and economic poverty in Lüliang area].
Li, Jing-Yi; Wang, Yan-Hui
2014-06-01
It is one of the important strategies during the poverty alleviation to maintain a basic balance between the eco-environment and economic development in poor areas. Taking the whole 20 counties in Lüliang national contiguous special poverty-stricken areas and the surrounding 36 counties as multi-type and multi-scale typical study areas, the relationship between eco-environment quality and poverty in the poverty-stricken areas was explored in this paper. Firstly, the region's ecological poverty index system was systematically built, and by integrated use of the subjective and objective weighting method, the ecological environment quality was evaluated in the perspective of natural environment. Then, the coupling coordination degree was calculated by coupling the ecological environment quality index and the average disposable income. Finally, the spatial variation was analyzed in detail respectively at provincial, city and county scales. Results showed that as a whole, the spatial autocorrelation coefficient of coupling coordination degree was relatively higher in the study area, and the coupling coordination degree in the eastern part was higher than that in the western part; the whole coupling coordination degree in Shanxi Province was slightly higher than in Shaanxi Province; the national poverty counties presented a state of recession, and their coordinated development degrees were far lower than that of non-national poverty counties.
Pedretti, Daniele; Masetti, Marco; Beretta, Giovanni Pietro
2017-10-01
The expected long-term efficiency of vertical cutoff walls coupled to pump-and-treat technologies to contain solute plumes in highly heterogeneous aquifers was analyzed. A well-characterized case study in Italy, with a hydrogeological database of 471 results from hydraulic tests performed on the aquifer and the surrounding 2-km-long cement-bentonite (CB) walls, was used to build a conceptual model and assess a representative remediation site adopting coupled technologies. In the studied area, the aquifer hydraulic conductivity Ka [m/d] is log-normally distributed with mean E (Ya) = 0.32 , variance σYa2 = 6.36 (Ya = lnKa) and spatial correlation well described by an exponential isotropic variogram with integral scale less than 1/12 the domain size. The hardened CB wall's hydraulic conductivity, Kw [m/d], displayed strong scaling effects and a lognormal distribution with mean E (Yw) = - 3.43 and σYw2 = 0.53 (Yw =log10Kw). No spatial correlation of Kw was detected. Using this information, conservative transport was simulated across a CB wall in spatially correlated 1-D random Ya fields within a numerical Monte Carlo framework. Multiple scenarios representing different Kw values were tested. A continuous solute source with known concentration and deterministic drains' discharge rates were assumed. The efficiency of the confining system was measured by the probability of exceedance of concentration over a threshold (C∗) at a control section 10 years after the initial solute release. It was found that the stronger the aquifer heterogeneity, the higher the expected efficiency of the confinement system and the lower the likelihood of aquifer pollution. This behavior can be explained because, for the analyzed aquifer conditions, a lower Ka generates more pronounced drawdown in the water table in the proximity of the drain and consequently a higher advective flux towards the confined area, which counteracts diffusive fluxes across the walls. Thus, a higher σYa2 results
Kudekar, Shrinivas; Urbanke, Ruediger
2010-01-01
Convolutional LDPC ensembles, introduced by Felstrom and Zigangirov, have excellent thresholds and these thresholds are rapidly increasing as a function of the average degree. Several variations on the basic theme have been proposed to date, all of which share the good performance characteristics of convolutional LDPC ensembles. We describe the fundamental mechanism which explains why "convolutional-like" or "spatially coupled" codes perform so well. In essence, the spatial coupling of the individual code structure has the effect of increasing the belief-propagation (BP) threshold of the new ensemble to its maximum possible value, namely the maximum-a-posteriori (MAP) threshold of the underlying ensemble. For this reason we call this phenomenon "threshold saturation." This gives an entirely new way of approaching capacity. One significant advantage of such a construction is that one can create capacity-approaching ensembles with an error correcting radius which is increasing in the blocklength. Our proof make...
Extreme parameter sensitivity of transient persistence in spatially coupled ecological systems
Institute of Scientific and Technical Information of China (English)
无
2011-01-01
This paper investigates persistence of transient dynamics depending on parameters in spatially coupled ecological systems. We emphasis that the persistence time can be obtained by populations of species or Lyapunov exponents of transient dynamics. It is found that extreme sensitive dependence of persistence on parameters occurs commonly in ecological models. A non-zero uncertainty exponent is used to characterize the high sensitivity in a reasonable parameter region. The result of a small uncertainty expone...
Simulation of spatially coupling dynamic response of train-track time-variant system
Institute of Scientific and Technical Information of China (English)
向俊; 李德建; 曾庆元
2003-01-01
There exist three problems in the calculation of lateral vibration of the train-track time-variant system athome and abroad and the method to solve them is presented. Spatially coupling vibration analysis model of train-track time-variant system is put forward. Each vehicle is modeled as a multi-body system with 26 degrees of freedomand the action of coupler is also considered. The track structure is modeled as an assembly of track elements with 30degrees of freedom, then the spatially coupling vibration matrix equation of the train-track time-variant system is es-tablished on the basis of the principle of total potential energy with stationary value and the "set-in-right-position"rule. The track vertical geometric irregularity is considered as the excitation source of the vertical vibration of thesystem, and the hunting wave of car bogie frame is taken as the excitation source of lateral vibration of the system.The spatially coupling vibration matrix equation of the system is solved by Wilson-θ direct integration method. Theapproximation of the calculated results to the spot test results demonstrates the feasibility and effectiveness of thepresented analysis method. Finally, some other vibration responses of the system are also obtained.
Directory of Open Access Journals (Sweden)
Qasim Ali
Full Text Available The transportation of camp firewood infested by non-native forest pests such as Asian long-horned beetle (ALB and emerald ash borer (EAB has severe impacts on North American forests. Once invasive forest pests are established, it can be difficult to eradicate them. Hence, preventing the long-distance transport of firewood by individuals is crucial.Here we develop a stochastic simulation model that captures the interaction between forest pest infestations and human decisions regarding firewood transportation. The population of trees is distributed across 10 patches (parks comprising a "low volume" partition of 5 patches that experience a low volume of park visitors, and a "high volume" partition of 5 patches experiencing a high visitor volume. The infestation spreads within a patch--and also between patches--according to the probability of between-patch firewood transportation. Individuals decide to transport firewood or buy it locally based on the costs of locally purchased versus transported firewood, social norms, social learning, and level of concern for observed infestations.We find that the average time until a patch becomes infested depends nonlinearly on many model parameters. In particular, modest increases in the tree removal rate, modest increases in public concern for infestation, and modest decreases in the cost of locally purchased firewood, relative to baseline (current values, cause very large increases in the average time until a patch becomes infested due to firewood transport from other patches, thereby better preventing long-distance spread. Patches that experience lower visitor volumes benefit more from firewood movement restrictions than patches that experience higher visitor volumes. Also, cross-patch infestations not only seed new infestations, they can also worsen existing infestations to a surprising extent: long-term infestations are more intense in the high volume patches than the low volume patches, even when
Przysucha, Eryk P; Maraj, Brian K V
2013-07-01
The nature of intra- and interlimb (bimanual) coordination was examined in ten boys with (M = 10.5 years, SD = 1.0) and without DCD (M = 10.8 years, SD = .9) in a two-handed catching task. Children with developmental coordination disorder (DCD) caught significantly fewer balls (MDCD = 56%, SD = 17.6 vs. MnoDCD = 93%, SD = 7.5), and both groups solved the "degrees of freedom problem" differently at intralimb level of coordination. Typically developing children coupled and decoupled the respective spatial relations, whereas the majority of children with DCD segmented their actions. At interlimb level, both groups exhibited a comparable degree of spatial symmetry. However, individual profiles also showed that children with varying degrees of movement issues exhibited movement patterns that were qualitatively and functionally diverse. Overall, in the context of previous research on interlimb coordination it appears that spatial, in addition to temporal organization, may be jeopardized in at least some children with DCD.
Energy Technology Data Exchange (ETDEWEB)
Lin, H.T. [Department of Information Management, Cheng Shiu University, Kaoshuing, Taiwan (China); Cheng, C.H. [Key Laboratory of Magnetic Levitation and Maglev Trains (Ministry of Education of China), Superconductivity R and D Center (SRDC), Mail Stop 165, Southwest Jiaotong University, Chengdu, Sichuan 610031 (China); Ke, C.; Pan, M. [School of Materials Science and Engineering, University of New South Wale, Sydney, 2052 NSW (Australia); Zhao, Y., E-mail: yzhao@swjtu.edu.cn [Key Laboratory of Magnetic Levitation and Maglev Trains (Ministry of Education of China), Superconductivity R and D Center (SRDC), Mail Stop 165, Southwest Jiaotong University, Chengdu, Sichuan 610031 (China)] [School of Materials Science and Engineering, University of New South Wale, Sydney, 2052 NSW (Australia)
2011-11-15
Mean field approach is a good way of dealing with chaos of vortex motion in a background of many vortices. The vortex motion under the damping mode is a kind of self-organized motion. The spatial chaos can dominate the chaotic behavior of the system. Vortex motion in the background of many vortices is investigated by a mean field approach. Effects of the vortex-vortex coupling, the driving frequency, and the vortex viscosity on the vortex motion have been studied to reveal the interaction between the spatial and temporal chaos. It is found that the mean-field approach is a good approximation to describe the vortex motion in one dimensional vortex system. The vortex motion under the damping mode is a kind of self-organized motion. The spatial chaos can dominate the chaotic behavior of the system.
Dynamical hysteresis and spatial synchronization in coupled non-identical chaotic oscillators
Indian Academy of Sciences (India)
Awadesh Prasad; Leon D Iasemidis; Shivkumar Sabesan; Kostas Tsakalis
2005-04-01
We identify a novel phenomenon in distinct (namely non-identical) coupled chaotic systems, which we term dynamical hysteresis. This behavior, which appears to be universal, is defined in terms of the system dynamics (quantified for example through the Lyapunov exponents), and arises from the presence of at least two coexisting stable attractors over a finite range of coupling, with a change of stability outside this range. Further characterization via mutual synchronization indices reveals that one attractor corresponds to spatially synchronized oscillators, while the other corresponds to desynchronized oscillators. Dynamical hysteresis may thus help to understand critical aspects of the dynamical behavior of complex biological systems, e.g. seizures in the epileptic brain can be viewed as transitions between different dynamical phases caused by time dependence in the brain's internal coupling.
Kraenkel, R. A.; da Silva, D. J. Pamplona
2010-01-01
We consider the dynamics of a biological population described by the Fisher-Kolmogorov-Petrovskii-Piskunov (FKPP) equation in the case where the spatial domain consists of alternating favorable and adverse patches whose sizes are distributed randomly. For the one-dimensional case we define a stochastic analogue of the classical critical patch size. We address the issue of persistence of a population and we show that the minimum fraction of the length of favorable segments to the total length is always smaller in the stochastic case than in a periodic arrangement. In this sense, spatial stochasticity favors viability of a population.
Spatial coupling analysis of regional economic development and environmental pollution in China
Institute of Scientific and Technical Information of China (English)
MA Li; JIN Fengjun; SONG Zhouying; LIU Yi
2013-01-01
Given the great number of studies focusing on the temporal interaction between economic and environmental subsystems,it is useful to perform a quantitative spatial assessment of these subsystems.In this paper,comprehensive assessment indicators for regional economic development and environmental pollution subsystems are constructed.Then,the degree of coupling and coordination of the regional economy-environment system is calculated for 350 prefectural units in China.It is found that the economic development and environmental pollution in most prefectural units is still at a low level of coupling and coordination.According to the coupling and coordination values,the Chinese territory can be divided into four types of area:economy-environment harmonious area,economy-environment gearing area,economy-environment rivaling area and low coupling degree of economy-environment area.Based on a structural analysis of the industrial sector in the four types of areas,there is a spatial relationship between the regional industrial sector structure and the coupling-coordination level.In the economy-environment harmonious area,the sectors of manufacturing of high-technology and high value-added products,such as communications,computer and electronic equipment,transport equipment and electrical machinery,account for a large proportion of the value of local industrial output.The industrial value of the economy-environment gearing area is concentrated on the manufacturing of machinery and equipment,and contains a few polluting sectors such as ferrous and non-ferrous metallurgy,chemical manufacturing and electricity generation.The economy--environment rivaling area is the type of area where polluting sectors concentrate,such as iron and steel,petrifaction,coal mining,building materials and electricity generation.In the low coupling degree of economy-environment area,its industry is concentrated on the production and processing of primary products.
Institute of Scientific and Technical Information of China (English)
王经明; 李竞生; 高智联; 杨保禹
1998-01-01
This study is concerned with developing a two-dimensional two-phase model thatsimulate the movement of non-aqueous phase liquid (NAPL) in a fracture-rock matrix system. Theintrinsic permeability and the fracture aperture are represented in the model via its Karhunen-Loeve expansion. Other parameters and the nodal unknowns, water saturations and waterpressures, are represented by their stochastic spectral expanions. The errors resulting fromtruncation of Karhunen - Loeve and polynomial chaos expansions to a finite number of terms areanalyzed. The eigenvalues of stochastic process is found out for any point in the special domain ofthe problem at any instant in time.
Loscar, Ernesto S; Candia, Julián
2013-10-01
We study the irreversible growth of magnetic thin films under the influence of spatially periodic fields by means of extensive Monte Carlo simulations. We find first-order pseudo-phase-transitions that separate a dynamically disordered phase from a dynamically ordered phase. By analogy with time-dependent oscillating fields applied to Ising-type models, we qualitatively associate this dynamic transition with the localization-delocalization transition of spatial hysteresis loops. Depending on the relative width of the magnetic film L compared to the wavelength of the external field λ, different transition regimes are observed. For small systems (L λ), the transition is driven by anomalous stochastic resonance. The origin of the latter is identified as due to the emergence of an additional relevant length scale, namely, the roughness of the spin domain switching interface. The distinction between different stochastic resonance regimes is discussed at length both qualitatively by means of snapshot configurations and quantitatively via residence-length and order-parameter probability distributions.
Directory of Open Access Journals (Sweden)
P. Gagnon
2013-06-01
Full Text Available Regional Climate Models (RCMs are valuable tools to evaluate impacts of climate change (CC at regional scale. However, as the size of the area of interest decreases, the ability of a RCM to simulate extreme precipitation events decreases due to the spatial resolution. Thus, it is difficult to evaluate whether a RCM bias on localized extreme precipitation is caused by the spatial resolution or by a misrepresentation of the physical processes in the model. Thereby, it is difficult to trust the CC impact projections for localized extreme precipitation. Stochastic spatial disaggregation models can bring the RCM precipitation data at a finer scale and reduce the bias caused by spatial resolution. In addition, disaggregation models can generate an ensemble of outputs, producing an interval of possible values instead of a unique discrete value. The objective of this work is to evaluate whether a stochastic spatial disaggregation model applied on annual maximum daily precipitation: (i enables the validation of a RCM for a period of reference, and (ii modifies the evaluation of CC impacts over a small area. Three simulations of the Canadian RCM (CRCM covering the period 1961–2099 are used over a small watershed (130 km2 located in southern Québec, Canada. The disaggregation model applied is based on Gibbs sampling and accounts for physical properties of the event (wind speed, wind direction, and convective available potential energy (CAPE, leading to realistic spatial distributions of precipitation. The results indicate that disaggregation has a significant impact on the validation. However it does not provide a precise estimate of the simulation bias because of the difference in resolution between disaggregated values (4 km and observations, and because of the underestimation of the spatial variability by the disaggregation model for the most convective events. Nevertheless, disaggregation permits to determine that the simulations used mostly
Galka, Andreas; Ozaki, Tohru; Muhle, Hiltrud; Stephani, Ulrich; Siniatchkin, Michael
2008-01-01
We discuss a model for the dynamics of the primary current density vector field within the grey matter of human brain. The model is based on a linear damped wave equation, driven by a stochastic term. By employing a realistically shaped average brain model and an estimate of the matrix which maps the primary currents distributed over grey matter to the electric potentials at the surface of the head, the model can be put into relation with recordings of the electroencephalogram (EEG). Through ...
Coupled-mode theory for photonic band-gap inhibition of spatial instabilities.
Gomila, Damià; Oppo, Gian-Luca
2005-07-01
We study the inhibition of pattern formation in nonlinear optical systems using intracavity photonic crystals. We consider mean-field models for singly and doubly degenerate optical parametric oscillators. Analytical expressions for the new (higher) modulational thresholds and the size of the "band gap" as a function of the system and photonic crystal parameters are obtained via a coupled-mode theory. Then, by means of a nonlinear analysis, we derive amplitude equations for the unstable modes and find the stationary solutions above threshold. The form of the unstable mode is different in the lower and upper parts of the band gap. In each part there is bistability between two spatially shifted patterns. In large systems stable wall defects between the two solutions are formed and we provide analytical expressions for their shape. The analytical results are favorably compared with results obtained from the full system equations. Inhibition of pattern formation can be used to spatially control signal generation in the transverse plane.
Study on spatial distribution of plasma parameters in a magnetized inductively coupled plasma
Energy Technology Data Exchange (ETDEWEB)
Cheong, Hee-Woon; Lee, Woohyun; Kim, Ji-Won; Whang, Ki-Woong, E-mail: kwhang@snu.ac.kr [Plasma Laboratory, Inter-University Semiconductor Research Center, Department of Electrical and Computer Engineering, Seoul National University, Seoul 151-742 (Korea, Republic of); Kim, Hyuk [Samsung Electronics Co., Banwol-dong, Hwaseong 445-701 (Korea, Republic of); Park, Wanjae [Tokyo Electron Miyagi Ltd., Taiwa-cho, Kurokawa-gun, Miyagi 981-3629 (Japan)
2015-07-15
Spatial distributions of various plasma parameters such as plasma density, electron temperature, and radical density in an inductively coupled plasma (ICP) and a magnetized inductively coupled plasma (M-ICP) were investigated and compared. Electron temperature in between the rf window and the substrate holder of M-ICP was higher than that of ICP, whereas the one just above the substrate holder of M-ICP was similar to that of ICP when a weak (<8 G) magnetic field was employed. As a result, radical densities in M-ICP were higher than those in ICP and the etch rate of oxide in M-ICP was faster than that in ICP without severe electron charging in 90 nm high aspect ratio contact hole etch.
Lin, Alexander J.; Konecky, Soren D.; Rice, Tyler B.; Green, Kim N.; Choi, Bernard; Durkin, Anthony J.; Tromberg, Bruce J.
2012-02-01
Early neurovascular coupling (NVC) changes in Alzheimer's disease can potentially provide imaging biomarkers to assist with diagnosis and treatment. Previous efforts to quantify NVC with intrinsic signal imaging have required assumptions of baseline optical pathlength to calculate changes in oxy- and deoxy-hemoglobin concentrations during evoked stimuli. In this work, we present an economical spatial frequency domain imaging (SFDI) platform utilizing a commercially available LED projector, camera, and off-the-shelf optical components suitable for imaging dynamic optical properties. The fast acquisition platform described in this work is validated on silicone phantoms and demonstrated in neuroimaging of a mouse model.
Quantum Entanglement in a System of Two Spatially Separated Atoms Coupled to the Thermal Reservoir
Institute of Scientific and Technical Information of China (English)
LIAO Xiang-Ping; FANG Mao-Fa; ZHENG Xiao-Juan; CAI Jian-Wu
2006-01-01
We study quantum entanglement between two spatially separated atoms coupled to the thermal reservoir. The influences of the initial state of the system, the atomic frequency difference and the mean number of the thermal field on the entanglement are examined. The results show that the maximum of the entanglement obtained with nonidentical atoms is greater than that obtained with identical atoms. The degree of entanglement is progressively decreased with the increase of the thermal noise. Interestingly, the two atoms can be easily entangled even when the two atoms are initially prepared in the most mixed states.
Directory of Open Access Journals (Sweden)
Chifu Yang
2013-02-01
Full Text Available The workspace of a spatial 6‐DOF electro‐hydraulic parallel manipulator is strongly coupled, due to its multi‐closed‐loop kinematic structure and the coupling complicates motion planning and control of the parallel manipulator. This paper clearly analyses the strong dynamic coupling property in the workspace of a spatial 6‐DOF parallel manipulator, using modal decoupling theory and a frequency responses characteristics analysis method. The dynamic model of a spatial 6‐DOF electro‐hydraulic parallel manipulator is expressed with the Kane method and hydromechanics principles. The modal analysis method is used to establish the map between strong coupling workspace and decoupled modal space and the dynamic coupling relationship and coupling strength between workspaces are exactly revealed. The quantitative evaluation index of dynamic coupling is presented. Moreover, the relationship between dynamic coupling effects and input is discussed through applying frequency characteristics analysis. Experimental results show the workspace of the parallel manipulator is strongly coupled and the coupling property is coincident with theoretical results.
Energy Technology Data Exchange (ETDEWEB)
Zhong, Buqing; Liang, Tao, E-mail: liangt@igsnrr.ac.cn; Wang, Lingqing; Li, Kexin
2014-08-15
An extensive soil survey was conducted to study pollution sources and delineate contamination of heavy metals in one of the metalliferous industrial bases, in the karst areas of southwest China. A total of 597 topsoil samples were collected and the concentrations of five heavy metals, namely Cd, As (metalloid), Pb, Hg and Cr were analyzed. Stochastic models including a conditional inference tree (CIT) and a finite mixture distribution model (FMDM) were applied to identify the sources and partition the contribution from natural and anthropogenic sources for heavy metal in topsoils of the study area. Regression trees for Cd, As, Pb and Hg were proved to depend mostly on indicators of anthropogenic activities such as industrial type and distance from urban area, while the regression tree for Cr was found to be mainly influenced by the geogenic characteristics. The FMDM analysis showed that the geometric means of modeled background values for Cd, As, Pb, Hg and Cr were close to their background values previously reported in the study area, while the contamination of Cd and Hg were widespread in the study area, imposing potentially detrimental effects on organisms through the food chain. Finally, the probabilities of single and multiple heavy metals exceeding the threshold values derived from the FMDM were estimated using indicator kriging (IK) and multivariate indicator kriging (MVIK). The high probabilities exceeding the thresholds of heavy metals were associated with metalliferous production and atmospheric deposition of heavy metals transported from the urban and industrial areas. Geostatistics coupled with stochastic models provide an effective way to delineate multiple heavy metal pollution to facilitate improved environmental management. - Highlights: • Conditional inference tree can identify variables controlling metal distribution. • Finite mixture distribution model can partition natural and anthropogenic sources. • Geostatistics with stochastic models
Fisher, Charles K; Al-Hashimi, Hashim M
2009-05-07
NMR spectroscopy is one of the most powerful techniques for studying the internal dynamics of biomolecules. Current formalisms approximate the dynamics using simple continuous motional models or models involving discrete jumps between a small number of states. However, no approach currently exists for interpreting NMR data in terms of continuous spatially complex motional paths that may feature more than one distinct maneuver. Here, we present an approach for approximately reconstructing spatially complex continuous motions of chiral domains using NMR anisotropic interactions. The key is to express Wigner matrix elements, which can be determined experimentally using residual dipolar couplings, as a line integral over a curve in configuration space containing an ensemble of conformations and to approximate the curve using a series of geodesic segments. Using this approach and five sets of synthetic residual dipolar couplings computed for five linearly independent alignment conditions, we show that it is theoretically possible to reconstruct salient features of a multisegment interhelical motional trajectory obtained from a 65 ns molecular dynamics simulation of a stem-loop RNA. Our study shows that the 3-D atomic reconstruction of complex motions in biomolecules is within experimental reach.
Coupling NLDAS Model Output with MODIS Products for Improved Spatial Evapotranspiration Estimates
Kim, J.; Hogue, T.
2008-12-01
Given the growing concern over regional water supplies in much of the arid west, the quantification of water use by urban and agricultural landscapes is critically important. Water lost through evapotranspiration (ET) typically can not be recaptured or recycled, increasing the need for accurate accounting of ET in regional water management and planning. In this study, we investigate a method to better capture the spatial characteristics of ET by coupling operational North American Land Data Assimilation System (NLDAS) Noah Land Surface Model (LSM) outputs and a previously developed MODIS-based Potential Evapotranspiration (PET) product. The resultant product is higher resolution (1km) than the NLDAS model ET outputs (~12.5 km) and provides improved estimates within highly heterogeneous terrain and landscapes. We undertake this study in the Southern California region which provides an excellent case study for examining the developed product's ability to estimate vegetation dynamics over rapidly growing, and highly-irrigated, urban ecosystems. General trends in both products are similar; however the coupled MODIS-NLDAS ET product shows higher spatial variability, better capturing land surface heterogeneity than the NLDAS-based ET. Improved ET representation is especially obvious during the spring season, when precipitation is muted and evaporative flux is dominant. We also quantify seasonal landscape water demand over urban landscapes in several major counties (i.e. Los Angeles, San Diego and Riverside) using the MODIS-NLDAS ET model.
Yilmaz, Ergin; Baysal, Veli; Ozer, Mahmut
2015-08-01
We investigate the effects of time-periodic coupling strength on the temporal coherence or firing regularity of a scale-free network consisting of stochastic Hodgkin-Huxley (H-H) neurons. The temporal coherence exhibits a resonance-like behavior depending on the cell size or the channel noise intensity. The best temporal coherence requires an optimal channel noise intensity, and this coherence can be significantly increased by time-periodic coupling strength when its frequency matches the integer multiples of the intrinsic subthreshold oscillation frequency of H-H neuron. Particularly, we find the multiple-coherence resonance depending on frequency of time-periodic coupling strength at the optimal noise intensity. We also obtain a resonance-like dependence of temporal coherence on the amplitude of time-periodic coupling strength. Additionally, we investigate the effects of average degree on the temporal coherence and find that the temporal coherence exhibits a resonance-like behavior with respect to the network average degree, indicating that the best regularity requires an optimal average degree.
Lyubomirskiy, Mikhail; Snigireva, Irina; Snigirev, Anatoly
2016-06-13
We have implemented a modified Young's double slit experiment using pinholes with tunable separation distance coupled with compound refractive lens for hard X-ray spatial coherence characterization. Varying distance between the apertures provides a high sensitivity to the determination of spatial coherence across a wide range of experimental parameters. The use of refractive lenses as a Fourier transformer ensures far field registration conditions and allows the realization of a very compact experimental setup in comparison with the classical Young technique and its derivatives. The tunable double aperture interferometer was experimentally tested at the ESRF ID06 beamline in the energy range from 8 to 25 keV. The spatial coherence and the source size were measured by evaluating the visibility of the interference fringes at various separation distances between the apertures and this value agrees very well with the data obtained by other techniques. The proposed scheme can be used for comprehensive characterization of the coherence properties of the source on low emittance synchrotrons in the hard X-ray region.
Transport of quantum excitations coupled to spatially extended nonlinear many-body systems
Iubini, Stefano; Boada, Octavi; Omar, Yasser; Piazza, Francesco
2015-11-01
The role of noise in the transport properties of quantum excitations is a topic of great importance in many fields, from organic semiconductors for technological applications to light-harvesting complexes in photosynthesis. In this paper we study a semi-classical model where a tight-binding Hamiltonian is fully coupled to an underlying spatially extended nonlinear chain of atoms. We show that the transport properties of a quantum excitation are subtly modulated by (i) the specific type (local versus non-local) of exciton-phonon coupling and by (ii) nonlinear effects of the underlying lattice. We report a non-monotonic dependence of the exciton diffusion coefficient on temperature, in agreement with earlier predictions, as a direct consequence of the lattice-induced fluctuations in the hopping rates due to long-wavelength vibrational modes. A standard measure of transport efficiency confirms that both nonlinearity in the underlying lattice and off-diagonal exciton-phonon coupling promote transport efficiency at high temperatures, preventing the Zeno-like quench observed in other models lacking an explicit noise-providing dynamical system.
Cervera, Javier; Manzanares, Jose Antonio; Mafe, Salvador
2015-02-19
We analyze the coupling of model nonexcitable (non-neural) cells assuming that the cell membrane potential is the basic individual property. We obtain this potential on the basis of the inward and outward rectifying voltage-gated channels characteristic of cell membranes. We concentrate on the electrical coupling of a cell ensemble rather than on the biochemical and mechanical characteristics of the individual cells, obtain the map of single cell potentials using simple assumptions, and suggest procedures to collectively modify this spatial map. The response of the cell ensemble to an external perturbation and the consequences of cell isolation, heterogeneity, and ensemble size are also analyzed. The results suggest that simple coupling mechanisms can be significant for the biophysical chemistry of model biomolecular ensembles. In particular, the spatiotemporal map of single cell potentials should be relevant for the uptake and distribution of charged nanoparticles over model cell ensembles and the collective properties of droplet networks incorporating protein ion channels inserted in lipid bilayers.
Energy Technology Data Exchange (ETDEWEB)
Kim, Hyun Jun [Department of Electrical Engineering, Hanyang University, Seoul 133-791 (Korea, Republic of); R and D Center for PSK-INC Corporation, Hwaseong-si 445-170 (Korea, Republic of); Hwang, Hye Ju; Cho, Jeong Hee; Chae, Hee Sun [R and D Center for PSK-INC Corporation, Hwaseong-si 445-170 (Korea, Republic of); Kim, Dong Hwan [Department of Nanoscale Semiconductor Engineering, Hanyang University, Seoul 133-791 (Korea, Republic of); Chung, Chin-Wook, E-mail: joykang@hanyang.ac.kr [Department of Electrical Engineering, Hanyang University, Seoul 133-791 (Korea, Republic of)
2015-04-15
The electrical characteristics and the spatial distribution of oxygen plasma according to the number of turns in ferrite inductively coupled plasmas (ferrite ICPs) are investigated. Through a new ICP model, which includes the capacitive coupling and the power loss of the ferrite material with the conventional ICP model, the variation of the oxygen discharge characteristics depending on the number of turns is simply understood by the electrical measurement, such as the antenna voltages and the currents. As the number of the turns increases, the capacitive coupling dominantly affects the spatial plasma distribution. This capacitive coupling results in a center focused density profile along the radial direction. In spite of the same discharge conditions (discharge chamber, neutral gas, and pressure), the spatial plasma distribution over 450 mm has drastic changes by increasing number of the turns. In addition, the effect of the negative species to the density profile is compared with the argon discharge characteristics at the same discharge configuration.
Institute of Scientific and Technical Information of China (English)
丁锋; 汪菲菲
2014-01-01
针对多元线性回归系统，利用耦合辨识概念和多新息辨识理论，讨论了多元随机梯度算法、多元多新息随机梯度算法，以及变递推间隔多元多新息梯度算法，进一步分解多元系统为一些子系统，给出了耦合子系统随机梯度算法、耦合随机梯度算法、耦合子系统多新息随机梯度算法、耦合多新息随机梯度算法，并将这些方法推广到多元伪线性滑动平均系统和多元伪线性自回归滑动平均系统。文中给出了几个典型耦合随机梯度算法、耦合多新息随机梯度算法的计算步骤和示意图。%For multivariate linear regression systems,using the coupling identification concept and the multi-inno-vation identification theory,this paper discusses a multivariate stochastic gradient algorithm,a multivariate multi-in-novation stochastic gradient algorithm,and an interval-varying multivariate multi-innovation gradient algorithm,de-composes a multivariate system into several subsystems,and presents a coupled subsystem stochastic gradient algo-rithm,a coupled stochastic gradient algorithm,a coupled subsystems multi-innovation stochastic gradient algorithm and a coupled multi-innovation stochastic gradient algorithm.These methods are extended to multivariate pseudo-lin-ear moving average systems and multivariate pseudo-linear autoregressive moving average systems.Finally,this paper gives the steps and diagrams for computing the parameter estimates using several typical coupled stochastic gradient algorithms and coupled multi-innovation stochastic gradient algorithms.
Stochastic volatility and stochastic leverage
DEFF Research Database (Denmark)
Veraart, Almut; Veraart, Luitgard A. M.
This paper proposes the new concept of stochastic leverage in stochastic volatility models. Stochastic leverage refers to a stochastic process which replaces the classical constant correlation parameter between the asset return and the stochastic volatility process. We provide a systematic...... treatment of stochastic leverage and propose to model the stochastic leverage effect explicitly, e.g. by means of a linear transformation of a Jacobi process. Such models are both analytically tractable and allow for a direct economic interpretation. In particular, we propose two new stochastic volatility...... models which allow for a stochastic leverage effect: the generalised Heston model and the generalised Barndorff-Nielsen & Shephard model. We investigate the impact of a stochastic leverage effect in the risk neutral world by focusing on implied volatilities generated by option prices derived from our new...
Parasuraman, Ramviyas; Molinari, Luca; Kershaw, Keith; Di Castro, Mario; Masi, Alessandro; Ferre, Manuel
2014-01-01
The reliability of wireless communication in a network of mobile wireless robot nodes depends on the received radio signal strength (RSS). When the robot nodes are deployed in hostile environments with ionizing radiations (such as in some scientific facilities), there is a possibility that some electronic components may fail randomly (due to radiation effects), which causes problems in wireless connectivity. The objective of this paper is to maximize robot mission capabilities by maximizing the wireless network capacity and to reduce the risk of communication failure. Thus, in this paper, we consider a multi-node wireless tethering structure called the “server-relay-client” framework that uses (multiple) relay nodes in between a server and a client node. We propose a robust stochastic optimization (RSO) algorithm using a multi-sensor-based RSS sampling method at the relay nodes to efficiently improve and balance the RSS between the source and client nodes to improve the network capacity and to provide red...
Tague, C.
2007-12-01
One of the primary roles of modeling in critical zone research studies is to provide a framework for integrating field measurements and theory and for generalizing results across space and time. In the Southern Sierra Critical Zone Observatory (SCZO), significant spatial heterogeneity associated with mountainous terrain combined with high inter-annual and seasonal variation in climate, necessitates the use of spatial-temporal models for generating landscape scale understanding and predictions. Science questions related to coupled hydrologic and biogeochemical fluxes within the critical zone require a framework that can account for multiple and interacting processes. One of the core tools for the SCZO will be RHESSYs (Regional hydro-ecologic simulation system). RHESSys is an existing GIS-based model of hydrology and biogeochemical cycling. For the SCZO, we use RHESSys as an open-source, objected oriented model that can be extended to incorporate findings from field-based monitoring and analysis. We use the model as a framework for data assimilation, spatial-temporal interpolation, prediction, and scenario and hypothesis generation. Here we demonstrate the use of RHESSys as a hypothesis generation tool. We show how initial RHESSys predictions can be used to estimate when and where connectivity within the critical zone will lead to significant spatial or temporal gradients in vegetation carbon and moisture fluxes. We use the model to explore the potential implications of heterogeneity in critical zone controls on hydrologic processes at two scales: micro and macro. At the micro scale, we examine the role of preferential flowpaths. At the macro scale we consider the importance of upland-riparian zone connectivity. We show how the model can be used to design efficient field experiments by, a-priori providing quantitative estimate of uncertainty and highlighting when and where measurements might most effectively reduce that uncertainty.
The situated HKB model: how sensorimotor spatial coupling can alter oscillatory brain dynamics.
Aguilera, Miguel; Bedia, Manuel G; Santos, Bruno A; Barandiaran, Xabier E
2013-01-01
Despite the increase of both dynamic and embodied/situated approaches in cognitive science, there is still little research on how coordination dynamics under a closed sensorimotor loop might induce qualitatively different patterns of neural oscillations compared to those found in isolated systems. We take as a departure point the Haken-Kelso-Bunz (HKB) model, a generic model for dynamic coordination between two oscillatory components, which has proven useful for a vast range of applications in cognitive science and whose dynamical properties are well understood. In order to explore the properties of this model under closed sensorimotor conditions we present what we call the situated HKB model: a robotic model that performs a gradient climbing task and whose "brain" is modeled by the HKB equation. We solve the differential equations that define the agent-environment coupling for increasing values of the agent's sensitivity (sensor gain), finding different behavioral strategies. These results are compared with two different models: a decoupled HKB with no sensory input and a passively-coupled HKB that is also decoupled but receives a structured input generated by a situated agent. We can precisely quantify and qualitatively describe how the properties of the system, when studied in coupled conditions, radically change in a manner that cannot be deduced from the decoupled HKB models alone. We also present the notion of neurodynamic signature as the dynamic pattern that correlates with a specific behavior and we show how only a situated agent can display this signature compared to an agent that simply receives the exact same sensory input. To our knowledge, this is the first analytical solution of the HKB equation in a sensorimotor loop and qualitative and quantitative analytic comparison of spatially coupled vs. decoupled oscillatory controllers. Finally, we discuss the limitations and possible generalization of our model to contemporary neuroscience and philosophy of
The Situated HKB Model: how sensorimotor spatial coupling can alter oscillatory brain dynamics
Directory of Open Access Journals (Sweden)
Miguel eAguilera
2013-08-01
Full Text Available Despite the increase both of dynamic and embodied/situated approaches in cognitive science, there is still little research on how coordination dynamics under a closed sensorimotor loop might induce qualitatively different patterns of neural oscillations compared to those found in isolated systems. We take as a departure point the HKB model, a generic model for dynamic coordination between two oscillatory components, which has proven useful for a vast range of applications in cognitive science and whose dynamical properties are well understood. In order to explore the properties of this model under closed sensorimotor conditions we present what we call the situated HKB model: a robotic model that performs a gradient climbing task and whose "brain" is modelled by the HKB equation. We solve the differential equations that define the agent-environment coupling for increasing values of the agent's sensitivity (sensor gain, finding different behavioural strategies. These results are compared with two different models: a decoupled HKB with no sensory input and a passively-coupled HKB that is also decoupled but receives a structured input generated by a situated agent. We can precisely quantify and qualitatively describe how the properties of the system, when studied in coupled conditions, radically change in a manner that cannot be deduced from the decoupled HKB models alone. We also present the notion of neurodynamic signature as the dynamic pattern that correlates with a specific behaviour and we show how only a situated agent can display this signature compared to an agent that simply receives the exact same sensory input.To our knowledge, this is the first analytical solution of the HKB equation in a sensorimotor loop and qualitative and quantitative analytic comparison of spatially coupled vs. decoupled oscillatory controllers. Finally, we discuss the limitations and possible generalization of our model to contemporary neuroscience and philosophy
Energy Technology Data Exchange (ETDEWEB)
Blaskiewicz, M.
2011-01-01
Stochastic Cooling was invented by Simon van der Meer and was demonstrated at the CERN ISR and ICE (Initial Cooling Experiment). Operational systems were developed at Fermilab and CERN. A complete theory of cooling of unbunched beams was developed, and was applied at CERN and Fermilab. Several new and existing rings employ coasting beam cooling. Bunched beam cooling was demonstrated in ICE and has been observed in several rings designed for coasting beam cooling. High energy bunched beams have proven more difficult. Signal suppression was achieved in the Tevatron, though operational cooling was not pursued at Fermilab. Longitudinal cooling was achieved in the RHIC collider. More recently a vertical cooling system in RHIC cooled both transverse dimensions via betatron coupling.
Directory of Open Access Journals (Sweden)
Jianfeng Zheng
2012-01-01
Full Text Available This paper is aimed at studying the impacts of mutual coupling, matching networks, and polarization of antennas on performances of Multiple-Input Multiple-Output (MIMO systems employing Spatial Multiplexing (SM. In particular, the uncoded average Bit Error Rate (BER of MIMO systems is investigated. An accurate signal analysis framework based on circuit network parameters is presented to describe the transmit/receive characteristics of the matched/unmatched antenna array. The studied arrays consist of matched/unmatched compact copolarization and polarization diversity antenna array. Monte-Carlo numerical simulations are used to study the BER performances of the SM MIMO systems using maximum-likelihood and/or zero-forcing detection schemes. The simulation results demonstrate that the use of matching networks can improve the BER performance of SM MIMO systems significantly, and the BER performance deterioration due to antenna orientation randomness can be compensated by use of polarization diversity antenna arrays.
Ohya, Yoshinobu; Ishikawa, Kenji; Komuro, Tatsuya; Yamaguchi, Tsuyoshi; Takeda, Keigo; Kondo, Hiroki; Sekine, Makoto; Hori, Masaru
2017-04-01
We present experimentally determined spatial profiles of the interelectrode electron density (n e) in dual-frequency capacitively coupled plasmas in which the negative direct current (dc) bias voltage (V dc) is superposed; in the experiment, 13 MHz (P low) was applied to the lower electrode and 60 MHz (P high) to the upper electrode. The bulk n e increased substantially with increases in the external power, P high, P low, and with increases in V dc. When P low was insufficient, the bulk n e decreased as the V dc bias increased. The bulk n e increased due to its dependence on V dc, especially for |V dc| > 500 V. This may correspond to the sheath voltages (V s) of the lower electrode. The n e values in front of the upper electrode were coupled with the V dc: the V dc dependence first decreased and then increased. The dc currents (I dc) of the upper electrode were collected when a large P low was applied. The value of I dc at the threshold value of V dc ≈ V s (e.g. ‑500 V) increased with an increase in n e. When |V dc| exceeded the threshold, the spatial n e profile and the I dc dependence were changed relative to the electrical characteristics of the dc superposition; this led to a change in the location of the maximum n e, the width of the area of n e depletion in front of the electrodes, and a transition in the electron heating modes.
Directory of Open Access Journals (Sweden)
Sara M Szczepanski
2014-08-01
Full Text Available Attention is a core cognitive mechanism that allows the brain to allocate limited resources depending on current task demands. A number of frontal and posterior parietal cortical areas, referred to collectively as the fronto-parietal attentional control network, are engaged during attentional allocation in both humans and non-human primates. Numerous studies have examined this network in the human brain using various neuroimaging and scalp electrophysiological techniques. However, little is known about how these frontal and parietal areas interact dynamically to produce behavior on a fine temporal (sub-second and spatial (sub-centimeter scale. We addressed how human fronto-parietal regions control visuospatial attention on a fine spatiotemporal scale by recording electrocorticography (ECoG signals measured directly from subdural electrode arrays that were implanted in patients undergoing intracranial monitoring for localization of epileptic foci. Subjects (n = 8 performed a spatial-cuing task, in which they allocated visuospatial attention to either the right or left visual field and detected the appearance of a target. We found increases in high gamma (HG power (70-250 Hz time-locked to trial onset that remained elevated throughout the attentional allocation period over frontal, parietal, and visual areas. These HG power increases were modulated by the phase of the ongoing delta/theta (2-5 Hz oscillation during attentional allocation. Critically, we found that the strength of this delta/theta phase-HG amplitude coupling predicted reaction times to detected targets on a trial-by-trial basis. These results highlight the role of delta/theta phase-HG amplitude coupling as a mechanism for sub-second facilitation and coordination within human fronto-parietal cortex that is guided by momentary attentional demands.
Szymanowski, Mariusz; Kryza, Maciej
2017-02-01
Our study examines the role of auxiliary variables in the process of spatial modelling and mapping of climatological elements, with air temperature in Poland used as an example. The multivariable algorithms are the most frequently applied for spatialization of air temperature, and their results in many studies are proved to be better in comparison to those obtained by various one-dimensional techniques. In most of the previous studies, two main strategies were used to perform multidimensional spatial interpolation of air temperature. First, it was accepted that all variables significantly correlated with air temperature should be incorporated into the model. Second, it was assumed that the more spatial variation of air temperature was deterministically explained, the better was the quality of spatial interpolation. The main goal of the paper was to examine both above-mentioned assumptions. The analysis was performed using data from 250 meteorological stations and for 69 air temperature cases aggregated on different levels: from daily means to 10-year annual mean. Two cases were considered for detailed analysis. The set of potential auxiliary variables covered 11 environmental predictors of air temperature. Another purpose of the study was to compare the results of interpolation given by various multivariable methods using the same set of explanatory variables. Two regression models: multiple linear (MLR) and geographically weighted (GWR) method, as well as their extensions to the regression-kriging form, MLRK and GWRK, respectively, were examined. Stepwise regression was used to select variables for the individual models and the cross-validation method was used to validate the results with a special attention paid to statistically significant improvement of the model using the mean absolute error (MAE) criterion. The main results of this study led to rejection of both assumptions considered. Usually, including more than two or three of the most significantly
Spatial and frequency dependence of plasma currents in a 300 mm capacitively coupled plasma reactor
Energy Technology Data Exchange (ETDEWEB)
Miller, Paul A [Sandia National Laboratories, MS 1423, PO Box 5800, Albuquerque, NM 87185-1423 (United States); Barnat, Edward V [Sandia National Laboratories, MS 1423, PO Box 5800, Albuquerque, NM 87185-1423 (United States); Hebner, Gregory A [Sandia National Laboratories, MS 1423, PO Box 5800, Albuquerque, NM 87185-1423 (United States); Paterson, Alex M [Applied Materials, Inc., 974 Arques Avenue, Sunnyvale, CA 94086 (United States); Holland, John P [Applied Materials, Inc., 974 Arques Avenue, Sunnyvale, CA 94086 (United States)
2006-11-01
There is much interest in scaling rf-excited capacitively coupled plasma reactors to larger sizes and to higher frequencies. As the size approaches operating wavelength, concerns arise about non-uniformity across the work piece, particularly in light of the well-documented slow-surface-wave phenomenon. We present measurements and calculations of spatial and frequency dependence of rf magnetic fields inside argon plasma in an industrially relevant, 300 mm plasma-processing chamber. The results show distinct differences in the spatial distributions and harmonic content of rf fields in the plasma at the three frequencies studied (13.56, 60 and 176 MHz). Evidence of a slow-wave structure was not apparent. The results suggest that interaction between the plasma and the rf excitation circuit may strongly influence the structures of these magnetic fields and that this interaction is frequency dependent. At the higher frequencies, wave propagation becomes extremely complex; it is controlled by the strong electrical nonlinearity of the sheath and is not explained simply by previous models.
Li, Bing-Wei; Cao, Xiao-Zhi; Fu, Chenbo
2017-05-01
Many biological and chemical systems could be modeled by a population of oscillators coupled indirectly via a dynamical environment. Essentially, the environment by which the individual element communicates with each other is heterogeneous. Nevertheless, most of previous works considered the homogeneous case only. Here we investigated the dynamical behaviors in a population of spatially distributed chaotic oscillators immersed in a heterogeneous environment. Various dynamical synchronization states (such as oscillation death, phase synchronization, and complete synchronized oscillation) as well as their transitions were explored. In particular, we uncovered a non-traditional quorum sensing transition: increasing the population density leaded to a transition from oscillation death to synchronized oscillation at first, but further increasing the density resulted in degeneration from complete synchronization to phase synchronization or even from phase synchronization to desynchronization. The underlying mechanism of this finding was attributed to the dual roles played by the population density. What's more, by treating the environment as another component of the oscillator, the full system was then effectively equivalent to a locally coupled system. This fact allowed us to utilize the master stability functions approach to predict the occurrence of complete synchronization oscillation, which agreed with that from the direct numerical integration of the system. The potential candidates for the experimental realization of our model were also discussed.
Galka, Andreas; Ozaki, Tohru; Muhle, Hiltrud; Stephani, Ulrich; Siniatchkin, Michael
2008-06-01
We discuss a model for the dynamics of the primary current density vector field within the grey matter of human brain. The model is based on a linear damped wave equation, driven by a stochastic term. By employing a realistically shaped average brain model and an estimate of the matrix which maps the primary currents distributed over grey matter to the electric potentials at the surface of the head, the model can be put into relation with recordings of the electroencephalogram (EEG). Through this step it becomes possible to employ EEG recordings for the purpose of estimating the primary current density vector field, i.e. finding a solution of the inverse problem of EEG generation. As a technique for inferring the unobserved high-dimensional primary current density field from EEG data of much lower dimension, a linear state space modelling approach is suggested, based on a generalisation of Kalman filtering, in combination with maximum-likelihood parameter estimation. The resulting algorithm for estimating dynamical solutions of the EEG inverse problem is applied to the task of localising the source of an epileptic spike from a clinical EEG data set; for comparison, we apply to the same task also a non-dynamical standard algorithm.
Directory of Open Access Journals (Sweden)
Martin Ubertini
Full Text Available The high degree of physical factors in intertidal estuarine ecosystem increases material processing between benthic and pelagic compartments. In these ecosystems, microphytobenthos resuspension is a major phenomenon since its contribution to higher trophic levels can be highly significant. Understanding the sediment and associated microphytobenthos resuspension and its fate in the water column is indispensable for measuring the food available to benthic and pelagic food webs. To identify and hierarchize the physical/biological factors potentially involved in MPB resuspension, the entire intertidal area and surrounding water column of an estuarine ecosystem, the Bay des Veys, was sampled during ebb tide. A wide range of physical parameters (hydrodynamic regime, grain size of the sediment, and suspended matter and biological parameters (flora and fauna assemblages, chlorophyll were analyzed to characterize benthic-pelagic coupling at the bay scale. Samples were collected in two contrasted periods, spring and late summer, to assess the impact of forcing variables on benthic-pelagic coupling. A mapping approach using kriging interpolation enabled us to overlay benthic and pelagic maps of physical and biological variables, for both hydrological conditions and trophic indicators. Pelagic Chl a concentration was the best predictor explaining the suspension-feeders spatial distribution. Our results also suggest a perennial spatio-temporal structure of both benthic and pelagic compartments in the ecosystem, at least when the system is not imposed to intense wind, with MPB distribution controlled by both grain size and bathymetry. The benthic component appeared to control the pelagic one via resuspension phenomena at the scale of the bay. Co-inertia analysis showed closer benthic-pelagic coupling between the variables in spring. The higher MPB biomass observed in summer suggests a higher contribution to filter-feeders diets, indicating a higher
Stochastic Shadowing and Stochastic Stability
Todorov, Dmitry
2014-01-01
The notion of stochastic shadowing property is introduced. Relations to stochastic stability and standard shadowing are studied. Using tent map as an example it is proved that, in contrast to what happens for standard shadowing, there are significantly non-uniformly hyperbolic systems that satisfy stochastic shadowing property.
Institute of Scientific and Technical Information of China (English)
林敏; 张美丽; 黄咏梅
2011-01-01
The interaction of a coupled system and an external force is analyzed.The method of controlling stochastic energetic resonance is proposed from the viewpoint of work done and energy.According to the stochastic dynamics described by two-dimensional coupled Langevin equation, the thermodynamic relations of coupled systems based on single stochastic trajectories are established using microcosmic dynamics and macroscopic thermodynamic methods.By adjusting the periodic external force acting upon the control system, the work that is done on the coupled system by the input force acting on a controlled system and energy conversion relations are quantitatively characterized.The results show that the interaction of a coupled system, an input force and noise can be controlled by the control signal, and stochastic energetic resonance in a coupled system can be effectively controlled by the control signal.%分析了耦合系统与外界作用力的交互作用,从做功与能量的角度提出了控制随机能量共振的方法.根据二维耦合Langevin方程的随机动力学特性,采用微观动力学和宏观热力学方法,建立了基于单一随机轨线的耦合系统的热力学关系.通过调节施加于控制系统的周期性外力,定量刻画了作用于被控系统的输入力对耦合系统做功的大小与能量转换关系.结果表明,控制信号能控制耦合系统与输入力和噪声之间的相互作用,能有效地控制耦合系统的随机能量共振.
Directory of Open Access Journals (Sweden)
Kenichi W Okamoto
Full Text Available Two basic strategies have been proposed for using transgenic Aedes aegypti mosquitoes to decrease dengue virus transmission: population reduction and population replacement. Here we model releases of a strain of Ae. aegypti carrying both a gene causing conditional adult female mortality and a gene blocking virus transmission into a wild population to assess whether such releases could reduce the number of competent vectors. We find this "reduce and replace" strategy can decrease the frequency of competent vectors below 50% two years after releases end. Therefore, this combined approach appears preferable to releasing a strain carrying only a female-killing gene, which is likely to merely result in temporary population suppression. However, the fixation of anti-pathogen genes in the population is unlikely. Genetic drift at small population sizes and the spatially heterogeneous nature of the population recovery after releases end prevent complete replacement of the competent vector population. Furthermore, releasing more individuals can be counter-productive in the face of immigration by wild-type mosquitoes, as greater population reduction amplifies the impact wild-type migrants have on the long-term frequency of the anti-pathogen gene. We expect the results presented here to give pause to expectations for driving an anti-pathogen construct to fixation by relying on releasing individuals carrying this two-gene construct. Nevertheless, in some dengue-endemic environments, a spatially heterogeneous decrease in competent vectors may still facilitate decreasing disease incidence.
Frank, Andreas O; Freudenberger, J Christoph; Shaytan, Alexey K; Kessler, Horst; Luy, Burkhard
2015-03-01
Residual dipolar couplings are highly useful NMR parameters for calculating and refining molecular structures, dynamics, and interactions. For some applications, however, it is inevitable that the preferred orientation of a molecule in an alignment medium is calculated a priori. Several methods have been developed to predict molecular orientations and residual dipolar couplings. Being beneficial for macromolecules and selected small-molecule applications, such approaches lack sufficient accuracy for a large number of organic compounds for which the fine structure and eventually the flexibility of all involved molecules have to be considered or are limited to specific, well-studied liquid crystals. We introduce a simplified model for detailed all-atom molecular dynamics calculations with a polymer strand lined up along the principal axis as a new approach to simulate the preferred orientation of small to medium-sized solutes in polymer-based, gel-type alignment media. As is shown by a first example of strychnine in a polystyrene/CDCl3 gel, the simulations potentially enable the accurate prediction of residual dipolar couplings taking into account structural details and dynamic averaging effects of both the polymer and the solute.
Driver, Jeffrey H; Price, Paul S; Van Wesenbeeck, Ian; Ross, John H; Gehen, Sean; Holden, Larry R; Landenberger, Bryce; Hastings, Kerry; Yan, Zhongyu June; Rasoulpour, Reza
2016-11-15
Dow AgroSciences (DAS) markets and sells 1,3-Dichloropropene (1,3-D), the active ingredient in Telone®, which is used as a pre-plant soil fumigant nematicide in economically important crops in California. 1,3-D has been regulated as a "probable human carcinogen" and the California Department of Pesticide Regulation limits use of 1,3-D based on human health risk assessments for bystanders. This paper presents a risk characterization for bystanders based on advances in the assessment of both exposure and hazard. The revised bystander risk assessment incorporates significant advances: 1) new data on residency duration and mobility in communities where 1,3-D is in high demand; 2) new information on spatial and temporal concentrations of 1,3-D in air based on multi-year modeling using a validated model; and 3) a new stochastic spatial and temporal model of long-term exposures. Predicted distributions of long-term, chronic exposures indicate that current, and anticipated uses of 1,3-D would result in lifetime average daily doses lower than 0.002mg/kg/d, a dose associated with theoretical lifetime excess cancer risk of 95% of the local population based on a non-threshold risk assessment approach. Additionally, examination of 1,3-D toxicity studies including new chronic toxicity data and mechanism of action supports the use of a non-linear, threshold based risk assessment approach. The estimated maximum annual average daily dose of 1000-fold, a clear indication of acceptable risk for human health. In summary, the best available science supports 1,3-D's threshold nature of hazard and the revised exposure assessment supports that current agricultural uses of 1,3-D are associated with reasonable certainty of no harm, i.e., estimated long-term exposures pose insignificant health risks to bystanders even when the non-threshold approach is assumed.
Stochastic modeling and analysis of telecoms networks
Decreusefond, Laurent
2012-01-01
This book addresses the stochastic modeling of telecommunication networks, introducing the main mathematical tools for that purpose, such as Markov processes, real and spatial point processes and stochastic recursions, and presenting a wide list of results on stability, performances and comparison of systems.The authors propose a comprehensive mathematical construction of the foundations of stochastic network theory: Markov chains, continuous time Markov chains are extensively studied using an original martingale-based approach. A complete presentation of stochastic recursions from an
Directory of Open Access Journals (Sweden)
Sean P Parsons
2016-02-01
Full Text Available Pacemaker activities generated by networks of interstitial cells of Cajal (ICC, in conjunction with the enteric nervous system, orchestrate most motor patterns in the gastrointestinal tract. It was our objective to understand the role of network features of ICC associated with the myenteric plexus (ICC-MP in the shaping of motor patterns of the small intestine. To that end, a model of weakly coupled oscillators (oscillators influence each other's phase but not amplitude was created with most parameters derived from experimental data. The ICC network is a uniform two dimensional network coupled by gap junctions. All ICC generate pacemaker (slow wave activity with a frequency gradient in mice from 50/min at the proximal end of the intestine to 40/min at the distal end. Key features of motor patterns, directly related to the underlying pacemaker activity, are frequency steps and dislocations. These were accurately mimicked by reduction of coupling strength at a point in the chain of oscillators. When coupling strength was expressed as a product of gap junction density and conductance, and gap junction density was varied randomly along the chain (i.e. spatial noise with a long-tailed distribution, plateau steps occurred at points of low density. As gap junction conductance was decreased, the number of plateaus increased, mimicking the effect of the gap junction inhibitor carbenoxolone. When spatial noise was added to the natural interval gradient, as gap junction conductance decreased, the number of plateaus increased as before but in addition the phase waves frequently changed direction of apparent propagation, again mimicking the effect of carbenoxolone. In summary, key features of the motor patterns that are governed by pacemaker activity may be a direct consequence of biological noise, specifically spatial noise in gap junction coupling and pacemaker frequency.
Parsons, Sean P.; Huizinga, Jan D.
2016-01-01
Pacemaker activities generated by networks of interstitial cells of Cajal (ICC), in conjunction with the enteric nervous system, orchestrate most motor patterns in the gastrointestinal tract. It was our objective to understand the role of network features of ICC associated with the myenteric plexus (ICC-MP) in the shaping of motor patterns of the small intestine. To that end, a model of weakly coupled oscillators (oscillators influence each other's phase but not amplitude) was created with most parameters derived from experimental data. The ICC network is a uniform two dimensional network coupled by gap junctions. All ICC generate pacemaker (slow wave) activity with a frequency gradient in mice from 50/min at the proximal end of the intestine to 40/min at the distal end. Key features of motor patterns, directly related to the underlying pacemaker activity, are frequency steps and dislocations. These were accurately mimicked by reduction of coupling strength at a point in the chain of oscillators. When coupling strength was expressed as a product of gap junction density and conductance, and gap junction density was varied randomly along the chain (i.e., spatial noise) with a long-tailed distribution, plateau steps occurred at pointsof low density. As gap junction conductance was decreased, the number of plateaus increased, mimicking the effect of the gap junction inhibitor carbenoxolone. When spatial noise was added to the natural interval gradient, as gap junction conductance decreased, the number of plateaus increased as before but in addition the phase waves frequently changed direction of apparent propagation, again mimicking the effect of carbenoxolone. In summary, key features of the motor patterns that are governed by pacemaker activity may be a direct consequence of biological noise, specifically spatial noise in gap junction coupling and pacemaker frequency. PMID:26869875
Parsons, Sean P; Huizinga, Jan D
2016-01-01
Pacemaker activities generated by networks of interstitial cells of Cajal (ICC), in conjunction with the enteric nervous system, orchestrate most motor patterns in the gastrointestinal tract. It was our objective to understand the role of network features of ICC associated with the myenteric plexus (ICC-MP) in the shaping of motor patterns of the small intestine. To that end, a model of weakly coupled oscillators (oscillators influence each other's phase but not amplitude) was created with most parameters derived from experimental data. The ICC network is a uniform two dimensional network coupled by gap junctions. All ICC generate pacemaker (slow wave) activity with a frequency gradient in mice from 50/min at the proximal end of the intestine to 40/min at the distal end. Key features of motor patterns, directly related to the underlying pacemaker activity, are frequency steps and dislocations. These were accurately mimicked by reduction of coupling strength at a point in the chain of oscillators. When coupling strength was expressed as a product of gap junction density and conductance, and gap junction density was varied randomly along the chain (i.e., spatial noise) with a long-tailed distribution, plateau steps occurred at pointsof low density. As gap junction conductance was decreased, the number of plateaus increased, mimicking the effect of the gap junction inhibitor carbenoxolone. When spatial noise was added to the natural interval gradient, as gap junction conductance decreased, the number of plateaus increased as before but in addition the phase waves frequently changed direction of apparent propagation, again mimicking the effect of carbenoxolone. In summary, key features of the motor patterns that are governed by pacemaker activity may be a direct consequence of biological noise, specifically spatial noise in gap junction coupling and pacemaker frequency.
Szatmári, Gábor; Barta, Károly; Pásztor, László
2015-04-01
Modelling of large-scale spatial variability of soil properties is a promising subject in soil science, as well as in general environmental research, since the resulted model(s) can be applied to solve various problems. In addition to "purely" map an environmental element, the spatial uncertainty of the map product can deduced, specific areas could be identified and/or delineated (contaminated or endangered regions, plots for fertilization, etc.). Geostatistics, which can be regarded as a subset of statistics specialized in analysis and interpretation of geographically referenced data, offer a huge amount of tools to solve these tasks. Numerous spatial modeling methods have been developed in the past decades based on the regionalized variable theory. One of these techniques is sequential stochastic simulation, which can be conditioned with universal kriging (also referred to as regression kriging). As opposed to universal kriging (UK), sequential simulation conditioned with universal kriging (SSUK) provides not just one but several alternative and equally probable "maps", i.e. realizations. The realizations reproduce the global statistics (e.g. sample histogram, variogram), i.e. they reflect/model the reality in a certain global (and not local!) sense. In this paper we present and test SSUK developed in R-code and its utilizations in a water erosion affected study area. Furthermore, we compare the results from UK and SSUK. For this purpose, two soil variables were selected: soil organic matter (SOM) content and rooting depth (RD). SSUK approach is illustrated with a legacy soil dataset from a study area endangered by water erosion in Central Hungary. Legacy soil data was collected in the end of the 1980s in the framework of the National Land Evaluation Programme. Spatially exhaustive covariates were derived from a digital elevation model and from the land-use-map of the study area. SSUK was built upon a UK prediction system for both variables and 200 realizations
Coupling Mars' Dust and Water Cycles: Effects on Dust Lifting Vigor, Spatial Extent and Seasonality
Kahre, M. A.; Hollingsworth, J. L.; Haberle, R. M.; Montmessin, F.
2012-01-01
, thereby modifying the thermal structure of the atmosphere and its circulation. Results presented in other papers at this workshop show that including the radiative effects of water ice clouds greatly influence the water cycle and the vigor of weather systems in both the northern and southern hemispheres. Our goal is to investigate the effects of fully coupling the dust and water cycles on the dust cycle. We show that including water ice clouds and their radiative effects greatly affect the magnitude, spatial extent and seasonality of dust lifting and the season of maximum atmospheric dust loading.
Hoch, Jannis; van Beek, Rens; Winsemius, Hessel; Bierkens, Marc
2017-04-01
In recent years, losses due to riverine inundations have been increasing due to growth of both population and asset values in floodplain areas as well as changes in river regimes. As global flood risk will even increase in the future, it is paramount for the scientific community to provide sound flood hazard, exposure, and vulnerability estimates for improved flood risk management. Since inundations are a large-scale hazard, two main requirements for modelling efforts can be formulated. First, large-scale models need to be applied to capture the spatial correlation of flood events in neighbouring river basins, and second, modelling approaches need to be able to simulate future climate conditions and the resulting hydrologic response. Both requirements can be met by employing global hydrologic models (GHM). Obtaining the required information from GHM at a locally relevant resolution, however, remains a major research challenge. For instance, the coarse spatial resolution of such models hampers a detailed representation of channel and floodplain geometry, and simplistic routing schemes implemented often fail to capture discharge dynamics. In addition to other current approaches trying to overcome these issues, Hoch et al. (2016, in review) applied a spatially explicit coupling scheme between the global hydrologic model PCR-GLOBWB and the hydrodynamic model Delft3D Flexible Mesh. Two main features are central to this study. First, the water balance computations were performed by PCR-GLOBWB, while the routing was explicitly performed by FM solving the full shallow water equations. Results indeed showed that such a spatial coupling approach can simulate discharge more accurately than both models stand-alone. Second, the model domain was schematized by a flexible mesh which allows for smaller grids for areas such as channel and floodplain areas while preserving coarser spatial resolution in more remote areas. As a result, computational costs can be strongly reduced
Juricke, Stephan; Jung, Thomas
2014-06-28
The influence of a stochastic sea ice strength parametrization on the mean climate is investigated in a coupled atmosphere-sea ice-ocean model. The results are compared with an uncoupled simulation with a prescribed atmosphere. It is found that the stochastic sea ice parametrization causes an effective weakening of the sea ice. In the uncoupled model this leads to an Arctic sea ice volume increase of about 10-20% after an accumulation period of approximately 20-30 years. In the coupled model, no such increase is found. Rather, the stochastic perturbations lead to a spatial redistribution of the Arctic sea ice thickness field. A mechanism involving a slightly negative atmospheric feedback is proposed that can explain the different responses in the coupled and uncoupled system. Changes in integrated Antarctic sea ice quantities caused by the stochastic parametrization are generally small, as memory is lost during the melting season because of an almost complete loss of sea ice. However, stochastic sea ice perturbations affect regional sea ice characteristics in the Southern Hemisphere, both in the uncoupled and coupled model. Remote impacts of the stochastic sea ice parametrization on the mean climate of non-polar regions were found to be small.
Huijbers, C.M.; Nagelekerken, I.; Debrot, A.O.; Jongejans, E.
2013-01-01
Marine spatial population dynamics are often addressed with a focus on larval dispersal, without taking into account movement behavior of individuals in later life stages. Processes occurring during demersal life stages may also drive spatial population dynamics if habitat quality is perceived diffe
McKean, Henry P
2005-01-01
This little book is a brilliant introduction to an important boundary field between the theory of probability and differential equations. -E. B. Dynkin, Mathematical Reviews This well-written book has been used for many years to learn about stochastic integrals. The book starts with the presentation of Brownian motion, then deals with stochastic integrals and differentials, including the famous Itô lemma. The rest of the book is devoted to various topics of stochastic integral equations, including those on smooth manifolds. Originally published in 1969, this classic book is ideal for supplemen
Parzen, Emanuel
2015-01-01
Well-written and accessible, this classic introduction to stochastic processes and related mathematics is appropriate for advanced undergraduate students of mathematics with a knowledge of calculus and continuous probability theory. The treatment offers examples of the wide variety of empirical phenomena for which stochastic processes provide mathematical models, and it develops the methods of probability model-building.Chapter 1 presents precise definitions of the notions of a random variable and a stochastic process and introduces the Wiener and Poisson processes. Subsequent chapters examine
DEFF Research Database (Denmark)
Jensen, Karsten Høgh; Mantoglou, Aristotelis
1992-01-01
unsaturated flow equation representing the mean system behavior is solved using a finite difference numerical solution technique. The effective parameters are evaluated from the stochastic theory formulas before entering them into the numerical solution for each iteration. The stochastic model is applied......A stochastic unsaturated flow theory and a numerical simulation model have been coupled in order to estimate the large-scale mean behavior of an unsaturated flow system in a spatially variable soil. On the basis of the theoretical developments of Mantoglou and Gelhar (1987a, b, c), the theory......, similar to the local flow equation. in which effective model parameters occur (e.g., effective hydraulic conductivity). Further, the theory predicts the variance (prediction error) of the capillary tension head due to the spatial variability of the local hydraulic soil properties. The governing...
Stochastic simulation in systems biology
Directory of Open Access Journals (Sweden)
Tamás Székely Jr.
2014-11-01
There are many different types of stochastic methods. We focus on one group that has become especially popular in systems biology, biochemistry, chemistry and physics. These discrete-state stochastic methods do not follow individuals over time; rather they track only total populations. They also assume that the volume of interest is spatially homogeneous. We give an overview of these methods, with a discussion of the advantages and disadvantages of each, and suggest when each is more appropriate to use. We also include references to software implementations of them, so that beginners can quickly start using stochastic methods for practical problems of interest.
Schneider, Johannes J
2007-01-01
This book addresses stochastic optimization procedures in a broad manner. The first part offers an overview of relevant optimization philosophies; the second deals with benchmark problems in depth, by applying a selection of optimization procedures. Written primarily with scientists and students from the physical and engineering sciences in mind, this book addresses a larger community of all who wish to learn about stochastic optimization techniques and how to use them.
Liu, Chuangye; Nguyen, Nghiem V.; Wang, Zhi-Qiang
2016-10-01
In this paper, we investigate the orbital stability of solitary-wave solutions for an m-coupled nonlinear Schrödinger system i /∂ ∂ t u j + /∂ 2 ∂ x 2 u j + ∑ i = 1 m b i j |" separators=" u i | 2 u j = 0 , j = 1 , … , m , where m ≥ 2, uj are complex-valued functions of (x, t) ∈ ℝ2, bjj ∈ ℝ, j = 1, 2, …, m, and bij, i ≠ j are positive coupling constants satisfying bij = bji. It will be shown that spatially synchronized solitary-wave solutions of the m-coupled nonlinear Schrödinger system exist and are orbitally stable. Here, by synchronized solutions we mean solutions in which the components are proportional to one another. Our results completely settle the question on the existence and stability of synchronized solitary waves for the m-coupled system while only partial results were known in the literature for the cases of m ≥ 3 heretofore. Furthermore, the conditions imposed on the symmetric matrix B = (bij) satisfied here are both sufficient and necessary for the m-coupled nonlinear Schrödinger system to admit synchronized ground-state solutions.
Frequency Resonance in Stochastic Systems
Institute of Scientific and Technical Information of China (English)
钱敏; 张雪娟
2003-01-01
The phenomenon of frequency resonance, which is usually related to deterministic systems, is investigated in stochastic systems. We show that for those autonomous systems driven only by white noise, if the output power spectrum exhibits a nonzero peak frequency, then applying a periodic signel just on this noise-induced central frequency can also induce a resonance phenomenon, which we call the frequency stochastic resonance. The effect of such a resonance in a coupled stochastic system is shown to be much better than that in a single-oscillator system.
Spatial versus temporal deterministic wave breakup of nonlinearly coupled light waves.
Salerno, D; Minardi, S; Trull, J; Varanavicius, A; Tamosauskas, G; Valiulis, G; Dubietis, A; Caironi, D; Trillo, S; Piskarskas, A; Di Trapani, P
2003-10-01
We investigate experimentally the competition between spatial and temporal breakup due to modulational instability in chi((2)) nonlinear mixing. The modulation of the wave packets caused by the energy exchange between fundamental and second-harmonic components is found to be the prevailing trigger mechanism which, according to the relative weight of diffraction and dispersion, leads to the appearance of a multisoliton pattern in the low-dimensional spatial or temporal domain.
Analyzing Spatial and Temporal Variation in Precipitation Estimates in a Coupled Model
Tomkins, C. D.; Springer, E. P.; Costigan, K. R.
2001-12-01
Integrated modeling efforts at the Los Alamos National Laboratory aim to simulate the hydrologic cycle and study the impacts of climate variability and land use changes on water resources and ecosystem function at the regional scale. The integrated model couples three existing models independently responsible for addressing the atmospheric, land surface, and ground water components: the Regional Atmospheric Model System (RAMS), the Los Alamos Distributed Hydrologic System (LADHS), and the Finite Element and Heat Mass (FEHM). The upper Rio Grande Basin, extending 92,000 km2 over northern New Mexico and southern Colorado, serves as the test site for this model. RAMS uses nested grids to simulate meteorological variables, with the smallest grid over the Rio Grande having 5-km horizontal grid spacing. As LADHS grid spacing is 100 m, a downscaling approach is needed to estimate meteorological variables from the 5km RAMS grid for input into LADHS. This study presents daily and cumulative precipitation predictions, in the month of October for water year 1993, and an approach to compare LADHS downscaled precipitation to RAMS-simulated precipitation. The downscaling algorithm is based on kriging, using topography as a covariate to distribute the precipitation and thereby incorporating the topographical resolution achieved at the 100m-grid resolution in LADHS. The results of the downscaling are analyzed in terms of the level of variance introduced into the model, mean simulated precipitation, and the correlation between the LADHS and RAMS estimates. Previous work presented a comparison of RAMS-simulated and observed precipitation recorded at COOP and SNOTEL sites. The effects of downscaling the RAMS precipitation were evaluated using Spearman and linear correlations and by examining the variance of both populations. The study focuses on determining how the downscaling changes the distribution of precipitation compared to the RAMS estimates. Spearman correlations computed for
Spatial Fluctuations of Loose Spin Coupling in CuMn/Co Multilayers
Saerbeck, T.; Loh, N.; Lott, D.; Toperverg, B. P.; Mulders, A. M.; Rodríguez, A. Fraile; Freeland, J. W.; Ali, M.; Hickey, B. J.; Stampfl, A. P. J.; Klose, F.; Stamps, R. L.
2011-09-01
A detailed investigation of magnetic impurity-mediated interlayer exchange coupling observed in Cu0.94Mn0.06/Co multilayers using polarized neutron reflectometry and magnetic x-ray techniques is reported. Excellent descriptions of temperature and magnetic field dependent biquadratic coupling are obtained using a variant of the loose spin model that takes into account the distribution of the impurity Mn ions in three dimensions. Positional disorder of the magnetic impurities is shown to enhance biquadratic coupling via a new contribution J2fluct, leading to a temperature dependent canting of magnetic domains in the multilayer. These results provide measurable effects on RKKY coupling associated with the distribution of impurities within planes parallel to the interfaces.
Distributed optical fiber sensor for spatial location of polarization mode coupling
Cokgor, Ilkan; Handerek, Vincent A.; Rogers, Alan J.
1993-03-01
Transverse stress applied to a highly birefringent fiber at an arbitrary angle (other than 0 or 90 degrees) to the fiber birefringence axes causes rotation of the birefringence axes and changes the beat length of the fiber in that section. If one of the polarization modes is excited at the input, coupling of light from one mode to the other will be observed at a stress point. The presentation describes a method for determining the locations of discrete mode coupling points spaced along a polarization maintaining fiber using a pump-prob architecture based on the optical Kerr effect. Probe light experiences coupling at different stress locations. Counterpropagating strong pump light also experiences coupling while inducing additional birefringence, and changing the polarization state of the probe at the output. This system may be made temperature independent by introducing a phase tracking/triggering system. The advantages and limitations of this technique are described.
Schmidt, Lennart; Krischer, Katharina
2015-06-01
We study an oscillatory medium with a nonlinear global coupling that gives rise to a harmonic mean-field oscillation with constant amplitude and frequency. Two types of cluster states are found, each undergoing a symmetry-breaking transition towards a related chimera state. We demonstrate that the diffusional coupling is non-essential for these complex dynamics. Furthermore, we investigate localized turbulence and discuss whether it can be categorized as a chimera state.
Faugloire, Elise; Lejeune, Laure
2014-12-01
This study quantified the effectiveness of tactile guidance in indicating a direction to turn to and measured its benefits compared to spatial language. The device (CAYLAR), which was composed of 8 vibrators, specified the requested direction by a vibration at the corresponding location around the waist. Twelve participants were tested in normal light and in total darkness with 3 guidance conditions: spatial language, a long tactile rhythm (1 s on/4 s off vibrations) providing a single stimulation before movement, and a short rhythm (200 ms on/200 ms off vibrations) allowing information-movement coupling during body rotation. We measured response time, heading error, and asked participants to rate task easiness, intuitiveness and perceived accuracy for each guidance mode. Accuracy was higher and participants' ratings were more positive with the short tactile mode than with the 2 other modes. Compared to spatial language, tactile guidance, regardless of the vibration rhythm, also allowed faster responses and did not impair accuracy in the absence of vision. These findings quantitatively demonstrate that tactile guidance is particularly effective when it is reciprocally related to movement. We discuss implications of the benefits of perception-action coupling for the design of tactile navigation devices.
Variational principles for stochastic soliton dynamics.
Holm, Darryl D; Tyranowski, Tomasz M
2016-03-01
We develop a variational method of deriving stochastic partial differential equations whose solutions follow the flow of a stochastic vector field. As an example in one spatial dimension, we numerically simulate singular solutions (peakons) of the stochastically perturbed Camassa-Holm (CH) equation derived using this method. These numerical simulations show that peakon soliton solutions of the stochastically perturbed CH equation persist and provide an interesting laboratory for investigating the sensitivity and accuracy of adding stochasticity to finite dimensional solutions of stochastic partial differential equations. In particular, some choices of stochastic perturbations of the peakon dynamics by Wiener noise (canonical Hamiltonian stochastic deformations, CH-SD) allow peakons to interpenetrate and exchange order on the real line in overtaking collisions, although this behaviour does not occur for other choices of stochastic perturbations which preserve the Euler-Poincaré structure of the CH equation (parametric stochastic deformations, P-SD), and it also does not occur for peakon solutions of the unperturbed deterministic CH equation. The discussion raises issues about the science of stochastic deformations of finite-dimensional approximations of evolutionary partial differential equation and the sensitivity of the resulting solutions to the choices made in stochastic modelling.
Energy Technology Data Exchange (ETDEWEB)
Babichenko, V.S. [RRC Kurchatov Institute, Kurchatov Sq., 1, 123182 Moscow (Russian Federation); Polishchuk, I.Ya., E-mail: iyppolishchuk@gmail.com [RRC Kurchatov Institute, Kurchatov Sq., 1, 123182 Moscow (Russian Federation); Moscow Institute of Physics and Technology, 141700, 9, Institutskii per., Dolgoprudny, Moscow Region (Russian Federation)
2014-11-15
The many-body correlation effects in the spatially separated electron and hole layers in the coupled quantum wells are investigated. A special case of the many-component electron–hole system is considered. It is shown that if the hole mass is much greater than the electron mass, the negative correlation energy is mainly determined by the holes. The ground state of the system is found to be the 2D electron–hole liquid with the energy smaller than the exciton phase. It is shown that the system decays into the spatially separated neutral electron–hole drops if the initially created charge density in the layers is smaller than the certain critical value n{sub eq}.
Heckmann, Tobias; Hilger, Ludwig; Vehling, Lucas; Becht, Michael
2016-05-01
The estimation of catchment-scale rockfall rates relies on the regionalisation of local measurements. Here, we propose a new framework for such a regionalisation by the example of a case study in the Upper Kaunertal, Austrian Central Alps (62.5 km2). Measurements of rockfall deposition during 12 months onto six collector nets within the study area were combined with published mean annual rates from the literature, and a probability density function was fitted to these data. A numerical model involving a random walk routing scheme and a one-parameter friction model was used to simulate rockfall trajectories, starting from potential rockfall source areas that were delineated from a digital elevation model. Rockfall rates sampled from the fitted probability density function were assigned to these trajectories in order to model the spatial distribution and to estimate the amount of rockfall deposition. By recording all trajectories as edges of a network of raster cells, and by aggregating the latter to landforms (or landform types) as delineated in a geomorphological map of the study area, rockfall sediment flux from sources to different landforms could be quantified. Specifically, the geomorphic coupling of rockfall sources to storage landforms and the glacial and fluvial sediment cascade was investigated using this network model. The total rockfall contribution to the sediment budget of the Upper Kaunertal is estimated at c. 8000 Mg yr- 1, 16.5% of which is delivered to the glaciers, and hence to the proglacial zone. The network approach is favourable, for example because multiple scenarios (involving different probability density functions) can be calculated on the basis of the same set of trajectories, and because deposits can be back-linked to their respective sources. While the methodological framework constitutes the main aim of our paper, we also discuss how the estimation of the budget can be improved on the basis of spatially distributed production rates.
Jedidi, Kamel; DeSarbo, Wayne S.
1991-01-01
A stochastic multidimensional scaling procedure is presented for analysis of three-mode, three-way pick any/"J" data. The procedure fits both vector and ideal-point models and characterizes the effect of situations by a set of dimension weights. An application in the area of consumer psychology is discussed. (SLD)
Chang, Mou-Hsiung
2015-01-01
The classical probability theory initiated by Kolmogorov and its quantum counterpart, pioneered by von Neumann, were created at about the same time in the 1930s, but development of the quantum theory has trailed far behind. Although highly appealing, the quantum theory has a steep learning curve, requiring tools from both probability and analysis and a facility for combining the two viewpoints. This book is a systematic, self-contained account of the core of quantum probability and quantum stochastic processes for graduate students and researchers. The only assumed background is knowledge of the basic theory of Hilbert spaces, bounded linear operators, and classical Markov processes. From there, the book introduces additional tools from analysis, and then builds the quantum probability framework needed to support applications to quantum control and quantum information and communication. These include quantum noise, quantum stochastic calculus, stochastic quantum differential equations, quantum Markov semigrou...
Stochastic partial differential equations
Chow, Pao-Liu
2014-01-01
Preliminaries Introduction Some Examples Brownian Motions and Martingales Stochastic Integrals Stochastic Differential Equations of Itô Type Lévy Processes and Stochastic IntegralsStochastic Differential Equations of Lévy Type Comments Scalar Equations of First Order Introduction Generalized Itô's Formula Linear Stochastic Equations Quasilinear Equations General Remarks Stochastic Parabolic Equations Introduction Preliminaries Solution of Stochastic Heat EquationLinear Equations with Additive Noise Some Regularity Properties Stochastic Reaction-Diffusion Equations Parabolic Equations with Grad
Stochastic Constraint Programming
Walsh, Toby
2009-01-01
To model combinatorial decision problems involving uncertainty and probability, we introduce stochastic constraint programming. Stochastic constraint programs contain both decision variables (which we can set) and stochastic variables (which follow a probability distribution). They combine together the best features of traditional constraint satisfaction, stochastic integer programming, and stochastic satisfiability. We give a semantics for stochastic constraint programs, and propose a number...
Controlled spatial separation of spins and coherent dynamics in spin-orbit-coupled nanostructures
Lo, Shun-Tsung; Chen, Chin-Hung; Fan, Ju-Chun; Smith, L. W.; Creeth, G. L.; Chang, Che-Wei; Pepper, M.; Griffiths, J. P.; Farrer, I.; Beere, H. E.; Jones, G. A. C.; Ritchie, D. A.; Chen, Tse-Ming
2017-07-01
The spatial separation of electron spins followed by the control of their individual spin dynamics has recently emerged as an essential ingredient in many proposals for spin-based technologies because it would enable both of the two spin species to be simultaneously utilized, distinct from most of the current spintronic studies and technologies wherein only one spin species could be handled at a time. Here we demonstrate that the spatial spin splitting of a coherent beam of electrons can be achieved and controlled using the interplay between an external magnetic field and Rashba spin-orbit interaction in semiconductor nanostructures. The technique of transverse magnetic focusing is used to detect this spin separation. More notably, our ability to engineer the spin-orbit interactions enables us to simultaneously manipulate and probe the coherent spin dynamics of both spin species and hence their correlation, which could open a route towards spintronics and spin-based quantum information processing.
Even-odd spatial nonequivalence for atomic quantum gases with isotropic spin-orbit couplings
Singh, G. S.; Gupta, Reena
2014-05-01
A general expression for the density of states (DOS) of power-law trapped d-dimensional ideal quantum gases with isotropic spin-orbit couplings (SOCs) is derived and is found to bifurcate into even- dand odd- d classes. The expressions for the grand potential and hence for several thermodynamic quantities are then shown to be amenable to exact analytical forms provided d is an odd integer. Also, a condition γ transition temperature and the condensate fraction in a 3D Bose gas under combined presence of the harmonic trapping and the Weyl coupling shows that the condensation is favored by the former but disfavored by the latter. This countering behavior is discussed to be in conformity with the exchange-symmetry-induced statistical interactions resulting from these two entities as enunciated recently [Phys. Rev. A 88, 053607 (2013)].
Wang, Maosheng; Sun, Runzhi
2014-03-01
The cooperative effects of inherent stochasticity and random long-range connections (RLRCs) on synchronization and coherence resonance in networks of calcium oscillators have been investigated. Two different types of collective behaviors, coherence resonance (CR) and synchronization, have been studied numerically in the context of chemical Langevin equations (CLEs). In the CLEs, the reaction steps are all stochastic, including the exchange of calcium ions between adjacent and non-adjacent cells through the gap junctions. The calcium oscillators’ synchronization was characterized by the standard deviation of the cytosolic calcium concentrations. Meanwhile, the temporal coherence of the calcium spike train was characterized by the reciprocal coefficient of variance (RCV). Synchronization induced by RLRCs was observed, namely, the exchange of calcium ions between non-adjacent cells can promote the synchronization of the cells. Moreover, it was found that the RCV shows a clear peak when both inherent stochasticity and RLRCs are optimal, indicating the existence of CR. Since inherent stochasticity and RLRCs are two essential ingredients of cellular processes, synchronization and CR are also important for cells’ functions. The results reported in this paper are expected to be useful for understanding the dynamics of intercellular calcium signaling processes in vivo.
Energy Technology Data Exchange (ETDEWEB)
Bisognano, J.; Leemann, C.
1982-03-01
Stochastic cooling is the damping of betatron oscillations and momentum spread of a particle beam by a feedback system. In its simplest form, a pickup electrode detects the transverse positions or momenta of particles in a storage ring, and the signal produced is amplified and applied downstream to a kicker. The time delay of the cable and electronics is designed to match the transit time of particles along the arc of the storage ring between the pickup and kicker so that an individual particle receives the amplified version of the signal it produced at the pick-up. If there were only a single particle in the ring, it is obvious that betatron oscillations and momentum offset could be damped. However, in addition to its own signal, a particle receives signals from other beam particles. In the limit of an infinite number of particles, no damping could be achieved; we have Liouville's theorem with constant density of the phase space fluid. For a finite, albeit large number of particles, there remains a residue of the single particle damping which is of practical use in accumulating low phase space density beams of particles such as antiprotons. It was the realization of this fact that led to the invention of stochastic cooling by S. van der Meer in 1968. Since its conception, stochastic cooling has been the subject of much theoretical and experimental work. The earliest experiments were performed at the ISR in 1974, with the subsequent ICE studies firmly establishing the stochastic cooling technique. This work directly led to the design and construction of the Antiproton Accumulator at CERN and the beginnings of p anti p colliding beam physics at the SPS. Experiments in stochastic cooling have been performed at Fermilab in collaboration with LBL, and a design is currently under development for a anti p accumulator for the Tevatron.
Stochastic superparameterization in quasigeostrophic turbulence
Energy Technology Data Exchange (ETDEWEB)
Grooms, Ian, E-mail: grooms@cims.nyu.edu [Center for Atmosphere Ocean Science, Courant Institute of Mathematical Sciences, New York University, 251 Mercer St., New York, NY 10012 (United States); Majda, Andrew J., E-mail: jonjon@cims.nyu.edu [Center for Atmosphere Ocean Science, Courant Institute of Mathematical Sciences, New York University, 251 Mercer St., New York, NY 10012 (United States); Center for Prototype Climate Modelling, NYU-Abu Dhabi (United Arab Emirates)
2014-08-15
In this article we expand and develop the authors' recent proposed methodology for efficient stochastic superparameterization algorithms for geophysical turbulence. Geophysical turbulence is characterized by significant intermittent cascades of energy from the unresolved to the resolved scales resulting in complex patterns of waves, jets, and vortices. Conventional superparameterization simulates large scale dynamics on a coarse grid in a physical domain, and couples these dynamics to high-resolution simulations on periodic domains embedded in the coarse grid. Stochastic superparameterization replaces the nonlinear, deterministic eddy equations on periodic embedded domains by quasilinear stochastic approximations on formally infinite embedded domains. The result is a seamless algorithm which never uses a small scale grid and is far cheaper than conventional SP, but with significant success in difficult test problems. Various design choices in the algorithm are investigated in detail here, including decoupling the timescale of evolution on the embedded domains from the length of the time step used on the coarse grid, and sensitivity to certain assumed properties of the eddies (e.g. the shape of the assumed eddy energy spectrum). We present four closures based on stochastic superparameterization which elucidate the properties of the underlying framework: a ‘null hypothesis’ stochastic closure that uncouples the eddies from the mean, a stochastic closure with nonlinearly coupled eddies and mean, a nonlinear deterministic closure, and a stochastic closure based on energy conservation. The different algorithms are compared and contrasted on a stringent test suite for quasigeostrophic turbulence involving two-layer dynamics on a β-plane forced by an imposed background shear. The success of the algorithms developed here suggests that they may be fruitfully applied to more realistic situations. They are expected to be particularly useful in providing accurate and
Spatial spectrograms of vibrating atomic force microscopy cantilevers coupled to sample surfaces
Energy Technology Data Exchange (ETDEWEB)
Wagner, Ryan; Raman, Arvind, E-mail: raman@purdue.edu [Birck Nanotechnology Center, 1205 W. State Street, Purdue University, West Lafayette, Indiana 47907 (United States); Proksch, Roger, E-mail: Roger.Proksch@oxinst.com [Asylum Research, 6310 Hollister Ave., Santa Barbara, California 93117 (United States)
2013-12-23
Many advanced dynamic Atomic Force Microscopy (AFM) techniques such as contact resonance, force modulation, piezoresponse force microscopy, electrochemical strain microscopy, and AFM infrared spectroscopy exploit the dynamic response of a cantilever in contact with a sample to extract local material properties. Achieving quantitative results in these techniques usually requires the assumption of a certain shape of cantilever vibration. We present a technique that allows in-situ measurements of the vibrational shape of AFM cantilevers coupled to surfaces. This technique opens up unique approaches to nanoscale material property mapping, which are not possible with single point measurements alone.
Eichhorn, Ralf; Aurell, Erik
2014-04-01
'Stochastic thermodynamics as a conceptual framework combines the stochastic energetics approach introduced a decade ago by Sekimoto [1] with the idea that entropy can consistently be assigned to a single fluctuating trajectory [2]'. This quote, taken from Udo Seifert's [3] 2008 review, nicely summarizes the basic ideas behind stochastic thermodynamics: for small systems, driven by external forces and in contact with a heat bath at a well-defined temperature, stochastic energetics [4] defines the exchanged work and heat along a single fluctuating trajectory and connects them to changes in the internal (system) energy by an energy balance analogous to the first law of thermodynamics. Additionally, providing a consistent definition of trajectory-wise entropy production gives rise to second-law-like relations and forms the basis for a 'stochastic thermodynamics' along individual fluctuating trajectories. In order to construct meaningful concepts of work, heat and entropy production for single trajectories, their definitions are based on the stochastic equations of motion modeling the physical system of interest. Because of this, they are valid even for systems that are prevented from equilibrating with the thermal environment by external driving forces (or other sources of non-equilibrium). In that way, the central notions of equilibrium thermodynamics, such as heat, work and entropy, are consistently extended to the non-equilibrium realm. In the (non-equilibrium) ensemble, the trajectory-wise quantities acquire distributions. General statements derived within stochastic thermodynamics typically refer to properties of these distributions, and are valid in the non-equilibrium regime even beyond the linear response. The extension of statistical mechanics and of exact thermodynamic statements to the non-equilibrium realm has been discussed from the early days of statistical mechanics more than 100 years ago. This debate culminated in the development of linear response
Crisan, Dan
2011-01-01
"Stochastic Analysis" aims to provide mathematical tools to describe and model high dimensional random systems. Such tools arise in the study of Stochastic Differential Equations and Stochastic Partial Differential Equations, Infinite Dimensional Stochastic Geometry, Random Media and Interacting Particle Systems, Super-processes, Stochastic Filtering, Mathematical Finance, etc. Stochastic Analysis has emerged as a core area of late 20th century Mathematics and is currently undergoing a rapid scientific development. The special volume "Stochastic Analysis 2010" provides a sa
Testing Spatial Correlation of Subduction Interplate Coupling and Forearc Morpho-Tectonics
Goldfinger, Chris; Meigs, Andrew; Meigs, Andrew; Kaye, Grant D.; VanLaningham, Sam
2005-01-01
Subduction zones that are capable of generating great (Mw greater than 8) earthquakes appear to have a common assemblage of forearc morphologic elements. Although details vary, each have (from the trench landward), an accretionary prism, outer arc high, outer forearc basin, an inner forean: basin, and volcanic arc. This pattern is common in spite of great variation in forearc architecture. Because interseismic strain is known to be associated with a locked seismogenic plate interface, we infer that this common forearc morphology is related, in an unknown way, to the process of interseismic Strain accumulation and release in great earthquakes. To date, however, no clear relationship between the subduction process and the common elements of upper plate form has emerged. Whereas certain elements of the system, i.e. the outer arc high, are reasonably well- understood in a structural context, there is little understanding of the structural or topographic evolution of the other key elements like the inner arc and inner forearc basin, particularly with respect to the coupled zone of earthquake generation. This project developed a model of the seismologic, topographic, and uplift/denudation linkages between forearc topography and the subduction system by: 1) comparing geophysical, geodetic, and topographic data from subduction margins that generate large earthquakes; 2) using existing GPS, seismicity, and other data to model the relationship between seismic cycles involving a locked interface and upper-plate topographic development; and 3) using new GPS data and a range-scale topographic, uplift, and denudation analysis of the presently aseismic Cascadia margin to constrain topographic/plate coupling relationships at this poorly understood margin.
Das, Sudeb; Kundu, Malay Kumar
2012-10-01
In this article, a novel multimodal medical image fusion (MIF) method based on non-subsampled contourlet transform (NSCT) and pulse-coupled neural network (PCNN) is presented. The proposed MIF scheme exploits the advantages of both the NSCT and the PCNN to obtain better fusion results. The source medical images are first decomposed by NSCT. The low-frequency subbands (LFSs) are fused using the 'max selection' rule. For fusing the high-frequency subbands (HFSs), a PCNN model is utilized. Modified spatial frequency in NSCT domain is input to motivate the PCNN, and coefficients in NSCT domain with large firing times are selected as coefficients of the fused image. Finally, inverse NSCT (INSCT) is applied to get the fused image. Subjective as well as objective analysis of the results and comparisons with state-of-the-art MIF techniques show the effectiveness of the proposed scheme in fusing multimodal medical images.
Kasai, Kenta; Sakaniwa, Kohichi
2012-01-01
We study LDPC codes for the channel with $2^m$-ary input $\\underline{x}\\in \\GF(2)^m$ and output $\\underline{y}=\\underline{x}+\\underline{z}\\in \\GF(2)^m$. The receiver knows a subspace $V\\subset \\GF(2)^m$ from which $\\underline{z}=\\underline{y}-\\underline{x}$ is uniformly chosen. Or equivalently, the receiver receives an affine subspace $\\underline{y}-V$ where $\\underline{x}$ lies. We consider a joint iterative decoder involving the channel detector and the LDPC decoder. The decoding system considered in this paper can be viewed as a simplified model of the joint iterative decoder over non-binary modulated signal inputs e.g., $2^m$-QAM. We evaluate the performance of binary spatially-coupled MacKay-Neal code by density evolution. EXIT-like function curve calculations reveal that iterative decoding threshold values are very close to the Shannon limit.
Energy Technology Data Exchange (ETDEWEB)
Maxwell, R M; Kollet, S J
2007-08-23
The impact of three-dimensional subsurface heterogeneity on hillslope runoff generated by excess infiltration (so called Hortonian runoff) is examined. A fully-coupled, parallel subsurface overland flow model is used to simulate runoff from an idealized hillslope. Ensembles of correlated, Gaussian random fields of saturated hydraulic conductivity are used to create uncertainty and variability (i.e. structure) due to subsurface heterogeneity. A large number of cases are simulated in a parametric manner with variance of the hydraulic conductivity varied over two orders of magnitude. These cases include rainfall rates above, equal and below the geometric mean of the hydraulic conductivity distribution. These cases are also compared to theoretical considerations of runoff production based on simple assumptions regarding (1) the rainfall rate and the value of hydraulic conductivity in the surface cell using a spatially-indiscriminant approach; and (2) a percolation-theory type approach to incorporate so-called runon. Simulations to test the ergodicity of hydraulic conductivity on hillslope runoff are also performed. Results show three-dimensional features (particularly in the vertical dimension) in the hydraulic conductivity distributions that create shallow perching, which has an important effect on runoff behavior that is fundamentally different in character than previous two dimensional analyses. The simple theories are shown to be very poor predictors of the saturated area that might runoff due to excess infiltration. It is also shown that ergodicity is reached only for a large number of integral scales ({approx}30) and not for cases where the rainfall rate is less than the geometric mean of the saturated hydraulic conductivity.
Intrinsic Simulations between Stochastic Cellular Automata
Directory of Open Access Journals (Sweden)
Pablo Arrighi
2012-08-01
Full Text Available The paper proposes a simple formalism for dealing with deterministic, non-deterministic and stochastic cellular automata in a unifying and composable manner. Armed with this formalism, we extend the notion of intrinsic simulation between deterministic cellular automata, to the non-deterministic and stochastic settings. We then provide explicit tools to prove or disprove the existence of such a simulation between two stochastic cellular automata, even though the intrinsic simulation relation is shown to be undecidable in dimension two and higher. The key result behind this is the caracterization of equality of stochastic global maps by the existence of a coupling between the random sources. We then prove that there is a universal non-deterministic cellular automaton, but no universal stochastic cellular automaton. Yet we provide stochastic cellular automata achieving optimal partial universality.
Spatial and temporal variability of soil moisture-temperature coupling in current and future climate
Schwingshackl, Clemens; Hirschi, Martin; Seneviratne, Sonia Isabelle
2017-04-01
While climate models generally agree on a future global mean temperature increase, the exact rate of change is still uncertain. The uncertainty is even higher for regional temperature trends that can deviate substantially from the projected global temperature increase. Several studies tried to constrain these regional temperature projections. They found that over land areas soil moisture is an important factor that influences the regional response. Due to the limited knowledge of the influence of soil moisture on atmospheric conditions on global scale the constraint remains still weak, though. Here, we use a framework that is based on the dependence of evaporative fraction (i.e. the fraction of net radiation that goes into latent heat flux) on soil moisture to distinguish between different soil moisture regimes (Seneviratne et al., 2010). It allows to estimate the influence of soil moisture on near-surface air temperature in the current climate and in future projections. While in the wet soil moisture regime, atmospheric conditions and related land surface fluxes can be considered as mostly driven by available energy, in the transitional regime - where evaporative fraction and soil moisture are essentially linearly coupled - soil moisture has an impact on turbulent heat fluxes, air humidity and temperature: Decreasing soil moisture and concomitant decreasing evaporative fraction cause increasing sensible heat flux, which might further lead to higher surface air temperatures. We investigate the strength of the single couplings (soil moisture → latent heat flux → sensible heat flux → air temperature) in order to quantify the influence of soil moisture on surface air temperature in the transitional regime. Moreover, we take into account that the coupling strength can change in the course of the year due to seasonal climate variations. The relations between soil moisture, evaporative fraction and near-surface air temperature in re-analysis and observation
Rajan, P. K.; Khan, Ajmal
1993-01-01
Spatial light modulators (SLMs) are being used in correlation-based optical pattern recognition systems to implement the Fourier domain filters. Currently available SLMs have certain limitations with respect to the realizability of these filters. Therefore, it is necessary to incorporate the SLM constraints in the design of the filters. The design of a SLM-constrained minimum average correlation energy (SLM-MACE) filter using the simulated annealing-based optimization technique was investigated. The SLM-MACE filter was synthesized for three different types of constraints. The performance of the filter was evaluated in terms of its recognition (discrimination) capabilities using computer simulations. The correlation plane characteristics of the SLM-MACE filter were found to be reasonably good. The SLM-MACE filter yielded far better results than the analytical MACE filter implemented on practical SLMs using the constrained magnitude technique. Further, the filter performance was evaluated in the presence of noise in the input test images. This work demonstrated the need to include the SLM constraints in the filter design. Finally, a method is suggested to reduce the computation time required for the synthesis of the SLM-MACE filter.
Energy Technology Data Exchange (ETDEWEB)
Iannucci, J.J.; Horgan, S.A.; Eyer, J.M. [Distributed Utility Associates, San Ramon, CA (United States)] [and others
1996-10-01
This paper discusses the technical potential for hydrogen used as an energy storage medium to couple time-dependent renewable energy into time-dependent electric utility loads. This analysis will provide estimates of regional and national opportunities for hydrogen production, storage and conversion, based on current and near-term leading renewable energy and hydrogen production and storage technologies. Appropriate renewable technologies, wind, photovoltaics and solar thermal, are matched to their most viable regional resources. The renewables are assumed to produce electricity which will be instantaneously used by the local utility to meet its loads; any excess electricity will be used to produce hydrogen electrolytically and stored for later use. Results are derived based on a range of assumptions of renewable power plant capacity and fraction of regional electric load to be met (e.g., the amount of hydrogen storage required to meet the Northwest region`s top 10% of electric load). For each renewable technology national and regional totals will be developed for maximum hydrogen production per year and ranges of hydrogen storage capacity needed in each year (hydroelectric case excluded). The sensitivity of the answers to the fraction of peak load to be served and the land area dedicated for renewable resources are investigated. These analyses can serve as a starting point for projecting the market opportunity for hydrogen storage and distribution technologies. Sensitivities will be performed for hydrogen production, conversion. and storage efficiencies representing current and near-term hydrogen technologies.
New travelling wave solutions for nonlinear stochastic evolution equations
Indian Academy of Sciences (India)
Hyunsoo Kim; Rathinasamy Sakthivel
2013-06-01
The nonlinear stochastic evolution equations have a wide range of applications in physics, chemistry, biology, economics and finance from various points of view. In this paper, the (′/)-expansion method is implemented for obtaining new travelling wave solutions of the nonlinear (2 + 1)-dimensional stochastic Broer–Kaup equation and stochastic coupled Korteweg–de Vries (KdV) equation. The study highlights the significant features of the method employed and its capability of handling nonlinear stochastic problems.
Wei, Qin-Sheng; Yu, Zhi-Gang; Wang, Bao-Dong; Fu, Ming-Zhu; Xia, Chang-Shui; Liu, Lu; Ge, Ren-Feng; Wang, Hui-Wu; Zhan, Run
2016-04-01
This study investigated the coupling of the spatial-temporal variations in nutrient distributions and physical conditions in the southern Yellow Sea (SYS) using data compiled from annual-cycle surveys conducted in 2006-2007 as well as satellite-derived sea-surface temperature (SST) images. The influence of physical dynamics on the distribution and transport of nutrients varied spatially and seasonally in the SYS. The Changjiang Diluted Water (CDW) plume (in summertime), the Subei Coastal Water (SCW) (year-round), and the Lubei Coastal Current (LCC) (in wintertime) served as important sources of nutrients in the inshore area in a dynamic environment. The saline Taiwan Warm Current (TWC) might transport nutrients to the northeast region of the Changjiang Estuary in the summer, and this nutrient source began to increase from spring to summer and decrease when autumn arrived. Three types of nutrient fronts, i.e., estuarine, offshore, and coastal, were identified. A circular nutrient front caused by cross-shelf transport of SCW in the southeast shelf bank area in the winter and spring was observed. The southeastward flow of western coastal cold water in the SYS might be an important conduit for cross-shelf nutrient exchange between the SYS and the East China Sea (ECS). The tongue-shaped low-nutrient region in the western study area in the wintertime was driven by the interaction of the southward Yellow Sea Western Coastal Current (YSWCC) and the biological activity. The vertically variable SCM (subsurface Chl-a maximum) in the central SYS was controlled by coupled physical-chemical processes that involved stratification and associated nutricline. The average nutrient fluxes into the euphotic zone due to upwelling near the frontal zone of the Yellow Sea Cold Water Mass (YSCWM) in the summer are estimated here for the first time: 1.4 ± 0.9 × 103 μmol/m2/d, 0.1 ± 0.1 × 103 μmol/m2/d, and 2.0 ± 1.3 × 103 μmol/m2/d for DIN, PO4-P, and SiO3-Si, respectively. The
Analysis of stochastic effects in Kaldor-type business cycle discrete model
Bashkirtseva, Irina; Ryashko, Lev; Sysolyatina, Anna
2016-07-01
We study nonlinear stochastic phenomena in the discrete Kaldor model of business cycles. A numerical parametric analysis of stochastically forced attractors (equilibria, closed invariant curves, discrete cycles) of this model is performed using the stochastic sensitivity functions technique. A spatial arrangement of random states in stochastic attractors is modeled by confidence domains. The phenomenon of noise-induced transitions "chaos-order" is discussed.
Representing Turbulence Model Uncertainty with Stochastic PDEs
Oliver, Todd; Moser, Robert
2012-11-01
Validation of and uncertainty quantification for extrapolative predictions of RANS turbulence models are necessary to ensure that the models are not used outside of their domain of applicability and to properly inform decisions based on such predictions. In previous work, we have developed and calibrated statistical models for these purposes, but it has been found that incorporating all the knowledge of a domain expert--e.g., realizability, spatial smoothness, and known scalings--in such models is difficult. Here, we explore the use of stochastic PDEs for this purpose. The goal of this formulation is to pose the uncertainty model in a setting where it is easier for physical modelers to express what is known. To explore the approach, multiple stochastic models describing the error in the Reynolds stress are coupled with multiple deterministic turbulence models to make uncertain predictions of channel flow. These predictions are compared with DNS data to assess their credibility. This work is supported by the Department of Energy [National Nuclear Security Administration] under Award Number [DE-FC52-08NA28615].
Stochastic geometry and its applications
Chiu, Sung Nok; Kendall, Wilfrid S; Mecke, Joseph
2013-01-01
An extensive update to a classic text Stochastic geometry and spatial statistics play a fundamental role in many modern branches of physics, materials sciences, engineering, biology and environmental sciences. They offer successful models for the description of random two- and three-dimensional micro and macro structures and statistical methods for their analysis. The previous edition of this book has served as the key reference in its field for over 18 years and is regarded as the best treatment of the subject of stochastic geometry, both as a subject with vital a
Laboratory Evidence for Stochastic Plasma-Wave Growth
Austin, D. R.; Hole, M. J.; Robinson, P. A.; Cairns, Iver H.; Dallaqua, R.
2007-11-01
The first laboratory confirmation of stochastic growth theory is reported. Floating potential fluctuations are measured in a vacuum arc centrifuge using a Langmuir probe. Statistical analysis of the energy density reveals a lognormal distribution over roughly 2 orders of magnitude, with a high-field nonlinear cutoff whose spatial dependence is consistent with the predicted eigenmode profile. These results are consistent with stochastic growth and nonlinear saturation of a spatially extended eigenmode, the first evidence for stochastic growth of an extended structure.
Directory of Open Access Journals (Sweden)
Romanu Ekaterini
2006-01-01
Full Text Available This article shows the similarities between Claude Debussy’s and Iannis Xenakis’ philosophy of music and work, in particular the formers Jeux and the latter’s Metastasis and the stochastic works succeeding it, which seem to proceed parallel (with no personal contact to what is perceived as the evolution of 20th century Western music. Those two composers observed the dominant (German tradition as outsiders, and negated some of its elements considered as constant or natural by "traditional" innovators (i.e. serialists: the linearity of musical texture, its form and rhythm.
Stochastic electrodynamics simulations for collective atom response in optical cavities
Lee, Mark D.; Jenkins, Stewart D.; Bronstein, Yael; Ruostekoski, Janne
2017-08-01
We study the collective optical response of an atomic ensemble confined within a single-mode optical cavity by stochastic electrodynamics simulations that include the effects of atomic position correlations, internal level structure, and spatial variations in cavity coupling strength and atom density. In the limit of low light intensity, the simulations exactly reproduce the full quantum field-theoretical description for cold stationary atoms and at higher light intensities we introduce semiclassical approximations to atomic saturation that we compare with the exact solution in the case of two atoms. We find that collective subradiant modes of the atoms, with very narrow linewidths, can be coupled to the cavity field by spatial variation of the atomic transition frequency and resolved at low intensities, and show that they can be specifically driven by tailored transverse pumping beams. We show that the cavity optical response, in particular both the subradiant mode profile and the resonance shift of the cavity mode, can be used as a diagnostic tool for the position correlations of the atoms and hence the atomic quantum many-body phase. The quantum effects are found to be most prominent close to the narrow subradiant mode resonances at high light intensities. Although an optical cavity can generally strongly enhance quantum fluctuations via light confinement, we show that the semiclassical approximation to the stochastic electrodynamics model provides at least a qualitative agreement with the exact optical response outside the subradiant mode resonances even in the presence of significant saturation of the atoms.
Leem, Hyun Tae; Choi, Yong; Kim, Kyu Bom; Lee, Sangwon; Yamamoto, Seiichi; Yeom, Jung-Yeol
2017-02-01
In positron emission tomography (PET) for breast, brain and small animal imaging, the spatial resolution of a PET detector is crucial to obtain high quality PET images. In this study, a PET detector for sub-millimeter spatial resolution imaging purpose was assembled using 4×4 pixels of a digital silicon photomultiplier (dSiPM, DPC-3200-22-44, Philips) coupled with a 15×15 LGSO array with BaSO4 reflector, and a 1 mm thick acrylic light guide for light distribution between the dSiPM pixels. The active area of each dSiPM pixel was 3.2×3.9 mm2 and the size of each LGSO scintillator element was 0.7×0.7×6 mm3. In this paper, we experimentally demonstrated the performance of the PET detector by measuring the energy resolution, 2D flood map, peak to valley (P/V) ratio, and coincidence resolving time (CRT). All measurements were performed at a temperature of 10±1 ℃. The average energy resolution was 15.6% (without correcting for saturation effects) at 511 keV and the best CRT was 242±5 ps. The 2D flood map obtained with an energy window of 400-600 keV demonstrated clear identification of all pixels, and the average P/V ratio of the X- and Y-directions were 7.31 and 7.81, respectively. This study demonstrated that the PET detector could be suitable for application in high resolution PET while achieving good timing resolution.
Stochastic superparameterization in quasigeostrophic turbulence
Grooms, Ian
2013-01-01
In this article we expand and develop the authors' recent proposed methodology for efficient stochastic superparameterization (SP) algorithms for geophysical turbulence. Geophysical turbulence is characterized by significant intermittent cascades of energy from the unresolved to the resolved scales resulting in complex patterns of waves, jets, and vortices. Conventional SP simulates large scale dynamics on a coarse grid in a physical domain, and couples these dynamics to high-resolution simulations on periodic domains embedded in the coarse grid. Stochastic SP replaces the nonlinear, deterministic eddy equations on periodic embedded domains by quasilinear stochastic approximations on formally infinite embedded domains. The result is a seamless algorithm which never uses a small scale grid and is far cheaper than conventional SP, but with significant success in difficult test problems. Various design choices in the algorithm are investigated in detail here, including decoupling the timescale of evolution on th...
Principal axes for stochastic dynamics.
Vasconcelos, V V; Raischel, F; Haase, M; Peinke, J; Wächter, M; Lind, P G; Kleinhans, D
2011-09-01
We introduce a general procedure for directly ascertaining how many independent stochastic sources exist in a complex system modeled through a set of coupled Langevin equations of arbitrary dimension. The procedure is based on the computation of the eigenvalues and the corresponding eigenvectors of local diffusion matrices. We demonstrate our algorithm by applying it to two examples of systems showing Hopf bifurcation. We argue that computing the eigenvectors associated to the eigenvalues of the diffusion matrix at local mesh points in the phase space enables one to define vector fields of stochastic eigendirections. In particular, the eigenvector associated to the lowest eigenvalue defines the path of minimum stochastic forcing in phase space, and a transform to a new coordinate system aligned with the eigenvectors can increase the predictability of the system.
Principal axes for stochastic dynamics
Vasconcelos, V V; Haase, M; Peinke, J; Wächter, M; Lind, P G; Kleinhans, D
2011-01-01
We introduce a general procedure for directly ascertaining how many independent stochastic sources exist in a complex system modeled through a set of coupled Langevin equations of arbitrary dimension. The procedure is based on the computation of the eigenvalues and the corresponding eigenvectors of local diffusion matrices. We demonstrate our algorithm by applying it to two examples of systems showing Hopf-bifurcation. We argue that computing the eigenvectors associated to the eigenvalues of the diffusion matrix at local mesh points in the phase space enables one to define vector fields of stochastic eigendirections. In particular, the eigenvector associated to the lowest eigenvalue defines the path of minimum stochastic forcing in phase space, and a transform to a new coordinate system aligned with the eigenvectors can increase the predictability of the system.
Pallud, C.; Masue-Slowey, Y.; Fendorf, S.
2010-05-01
Iron (hydr)oxides are ubiquitous in soils and sediments and play a dominant role in the geochemistry of surface and subsurface environments. Their fate depends on local environmental conditions, which in structured soils may vary significantly over short distances due to mass-transfer limitations on solute delivery and metabolite removal. In the present study, artificial soil aggregates were used to investigate the coupling of physical and biogeochemical processes affecting the spatial distribution of iron (Fe) phases resulting from reductive transformation of ferrihydrite. Spherical aggregates made of ferrihydrite-coated sand were inoculated with the dissimilatory Fe-reducing bacterium Shewanella putrefaciens strain CN-32, and placed into a flow reactor, the reaction cell simulates a diffusion-dominated soil aggregate surrounded by an advective flow domain. The spatial and temporal evolution of secondary mineralization products resulting from dissimilatory Fe reduction of ferrihydrite were followed within the aggregates in response to a range of flow rates and lactate concentrations. Strong radial variations in the distribution of secondary phases were observed owing to diffusively controlled delivery of lactate and efflux of Fe(II) and bicarbonate. In the aggregate cortex, only limited formation of secondary Fe phases were observed over 30 d of reaction, despite high rates of ferrihydrite reduction. Under all flow conditions tested, ferrihydrite transformation was limited in the cortex (70-85 mol.% Fe remained as ferrihydrite) because metabolites such as Fe(II) and bicarbonate were efficiently removed in outflow solutes. In contrast, within the inner fractions of the aggregate, limited mass-transfer results in metabolite (Fe(II) and bicarbonate) build-up and the consummate transformation of ferrihydrite - only 15-40 mol.% Fe remained as ferrihydrite after 30 d of reaction. Goethite/lepidocrocite, and minor amounts of magnetite, formed in the aggregate mid
Stochastic simulation in systems biology.
Székely, Tamás; Burrage, Kevin
2014-11-01
Natural systems are, almost by definition, heterogeneous: this can be either a boon or an obstacle to be overcome, depending on the situation. Traditionally, when constructing mathematical models of these systems, heterogeneity has typically been ignored, despite its critical role. However, in recent years, stochastic computational methods have become commonplace in science. They are able to appropriately account for heterogeneity; indeed, they are based around the premise that systems inherently contain at least one source of heterogeneity (namely, intrinsic heterogeneity). In this mini-review, we give a brief introduction to theoretical modelling and simulation in systems biology and discuss the three different sources of heterogeneity in natural systems. Our main topic is an overview of stochastic simulation methods in systems biology. There are many different types of stochastic methods. We focus on one group that has become especially popular in systems biology, biochemistry, chemistry and physics. These discrete-state stochastic methods do not follow individuals over time; rather they track only total populations. They also assume that the volume of interest is spatially homogeneous. We give an overview of these methods, with a discussion of the advantages and disadvantages of each, and suggest when each is more appropriate to use. We also include references to software implementations of them, so that beginners can quickly start using stochastic methods for practical problems of interest.
Häger, Christian; Brännström, Fredrik; Alvarado, Alex; Agrell, Erik
2014-01-01
We study the design of spectrally efficient fiber-optical communication systems based on different spatially coupled (SC) forward error correction (FEC) schemes. In particular, we optimize the allocation of the coded bits from the FEC encoder to the modulation bits of the signal constellation. Two SC code classes are considered. The codes in the first class are protograph-based low-density parity-check (LDPC) codes which are decoded using iterative soft-decision decoding. The codes in the second class are generalized LDPC codes which are decoded using iterative hard-decision decoding. For both code classes, the bit allocation is optimized for the terminated and tailbiting SC cases based on a density evolution analysis. An optimized bit allocation can significantly improve the performance of tailbiting SC codes codes over the baseline sequential allocation, up to the point where they have a comparable gap to capacity as their terminated counterparts, at a lower FEC overhead. For the considered terminated SC co...
Directory of Open Access Journals (Sweden)
Zhigang Zhang
2015-01-01
Full Text Available A two-node spatial beam element with the Euler-Bernoulli assumption is developed for the nonlinear dynamic analysis of slender beams undergoing arbitrary rigid motions and large deformations. During the analysis, the global displacement and rotation vectors with six degrees of freedom are selected as the nodal coordinates. In addition, the “shear locking” problem is avoided successfully since the beam cross-sections are always perpendicular to the current neutral axes by employing a special coupled interpolation of the centroid position and the cross-section orientation. Then a scheme is presented where the original transient strains representing the nodal forces are replaced by proposed average strains over a small time interval. Thus all the high frequencies can be filtered out and a corresponding equivalent internal damping will be produced in this new formulation, which can improve the computation performance of the proposed element for solving the stiff problem and evaluate the governing equations even by using the nonstiff ordinary differential equation solver. Finally, several numerical examples are carried out to verify the validation and efficiency of this proposed formulation by comparison with the analytical solutions and other research works.
Stewart, Lauren; Verdonschot, Rinus G; Nasralla, Patrick; Lanipekun, Jennifer
2013-01-01
The principle of common coding suggests that a joint representation is formed when actions are repeatedly paired with a specific perceptual event. Musicians are occupationally specialized with regard to the coupling between actions and their auditory effects. In the present study, we employed a novel paradigm to demonstrate automatic action-effect associations in pianists. Pianists and nonmusicians pressed keys according to aurally presented number sequences. Numbers were presented at pitches that were neutral, congruent, or incongruent with respect to pitches that would normally be produced by such actions. Response time differences were seen between congruent and incongruent sequences in pianists alone. A second experiment was conducted to determine whether these effects could be attributed to the existence of previously documented spatial/pitch compatibility effects. In a "stretched" version of the task, the pitch distance over which the numbers were presented was enlarged to a range that could not be produced by the hand span used in Experiment 1. The finding of a larger response time difference between congruent and incongruent trials in the original, standard, version compared with the stretched version, in pianists, but not in nonmusicians, indicates that the effects obtained are, at least partially, attributable to learned action effects.
Lanchier, Nicolas
2017-01-01
Three coherent parts form the material covered in this text, portions of which have not been widely covered in traditional textbooks. In this coverage the reader is quickly introduced to several different topics enriched with 175 exercises which focus on real-world problems. Exercises range from the classics of probability theory to more exotic research-oriented problems based on numerical simulations. Intended for graduate students in mathematics and applied sciences, the text provides the tools and training needed to write and use programs for research purposes. The first part of the text begins with a brief review of measure theory and revisits the main concepts of probability theory, from random variables to the standard limit theorems. The second part covers traditional material on stochastic processes, including martingales, discrete-time Markov chains, Poisson processes, and continuous-time Markov chains. The theory developed is illustrated by a variety of examples surrounding applications such as the ...
Institute of Scientific and Technical Information of China (English)
无
2007-01-01
In this paper, the stochastic flow of mappings generated by a Feller convolution semigroup on a compact metric space is studied. This kind of flow is the generalization of superprocesses of stochastic flows and stochastic diffeomorphism induced by the strong solutions of stochastic differential equations.
Stochastic Averaging and Stochastic Extremum Seeking
Liu, Shu-Jun
2012-01-01
Stochastic Averaging and Stochastic Extremum Seeking develops methods of mathematical analysis inspired by the interest in reverse engineering and analysis of bacterial convergence by chemotaxis and to apply similar stochastic optimization techniques in other environments. The first half of the text presents significant advances in stochastic averaging theory, necessitated by the fact that existing theorems are restricted to systems with linear growth, globally exponentially stable average models, vanishing stochastic perturbations, and prevent analysis over infinite time horizon. The second half of the text introduces stochastic extremum seeking algorithms for model-free optimization of systems in real time using stochastic perturbations for estimation of their gradients. Both gradient- and Newton-based algorithms are presented, offering the user the choice between the simplicity of implementation (gradient) and the ability to achieve a known, arbitrary convergence rate (Newton). The design of algorithms...
Sobczyk, K
1985-01-01
This is a concise, unified exposition of the existing methods of analysis of linear stochastic waves with particular reference to the most recent results. Both scalar and vector waves are considered. Principal attention is concentrated on wave propagation in stochastic media and wave scattering at stochastic surfaces. However, discussion extends also to various mathematical aspects of stochastic wave equations and problems of modelling stochastic media.
Stochastic homothetically revealed preference for tight stochastic demand functions
Jan Heufer
2009-01-01
This paper strengthens the framework of stochastic revealed preferences introduced by Bandyopadhyay et al. (1999, 2004) for stochastic homothetically revealed preferences for tight stochastic demand functions.
Stochastic genome-nuclear lamina interactions
Kind, Jop; van Steensel, Bas
2014-01-01
The nuclear lamina (NL) is thought to aid in the spatial organization of interphase chromosomes by providing an anchoring platform for hundreds of large genomic regions named lamina associated domains (LADs). Recently, a new live-cell imaging approach demonstrated directly that LAD-NL interactions are dynamic and in part stochastic. Here we discuss implications of these new findings and introduce Lamin A and BAF as potential modulators of stochastic LAD positioning. PMID:24717229
Soman, M. R.; Hall, D. J.; Tutt, J. H.; Murray, N. J.; Holland, A. D.; Schmitt, T.; Raabe, J.; Schmitt, B.
2013-01-01
The Super Advanced X-ray Emission Spectrometer (SAXES) is an instrument at the Swiss Light Source designed for Resonant Inelastic X-ray Scattering with an energy resolution (E/ΔE) better than 12000 at 930 eV. Improvements to the instrument have been predicted that could allow the energy resolution to be improved by a factor of two. To achieve this, the spatial resolution of the detector (currently a Charge-Coupled Device, CCD) over which the energy spectrum is dispersed would have to be improved to better than 5 μm. X-ray photons with energies between a few hundred to a few thousand electron volts primarily interact within the field-free region of back-illuminated CCDs, where each photon forms an electron cloud that diffuses isotropically before reaching the depleted region close to the electrodes. Each photon's electron cloud is likely to be detected as an event with signal split across multiple pixels. Analysing these split events using centroiding techniques allows the photon's interaction position to be determined to a sub-pixel level. PolLux is a soft X-ray microspectroscopy endstation at the Swiss Light Source that can focus 200 eV to 1200 eV X-rays to a spot size of approximately 20 nm. Previous studies using data taken with a linear scan across the centre of a pixel in 3 μm steps predicted an improved resolution by applying centroiding techniques and using an Electron-Multiplying CCD (EM-CCD). In this study, a full 2D map of the centroiding accuracy in the pixel is presented, formed by rastering in two dimensions across the image plane in single micron steps. The improved spatial resolution from centroiding events in the EM-CCD in all areas of the pixel over the standard CCD is attributed to the improved signal to noise ratio provided by the multiplication register even at high pixel readout speeds (tens of MHz).
Institute of Scientific and Technical Information of China (English)
鹿振宇; 黄攀峰
2015-01-01
For a kind of coupled parameters multivariable system, the coupled multi-innovation stochastic gradient(C-MISG) identification method is proposed to estimate the parameters, and its performance analysis is made. The basic idea of this method is utilizing the historical information to extend the scalar innovation item to an innovation vector to enhance the identified effect of each subsystem. Simulation results show that increasing the innovation length can enhance the convergence rate and accuracy of the identified results.%针对一类耦合参数多变量系统,提出一种耦合多新息随机梯度方法.通过该方法进行参数辨识并对该方法进行性能分析.该方法的基本思路在于利用历史新息中包含的信息,将耦合随机梯度算法中的新息项扩展为多新息向量,从而提升耦合随机梯度算法中单个子系统的辨识效果.仿真结果表明,通过增加新息长度可以提升辨识结果的收敛速度和精度.
CAM Stochastic Volatility Model for Option Pricing
Directory of Open Access Journals (Sweden)
Wanwan Huang
2016-01-01
Full Text Available The coupled additive and multiplicative (CAM noises model is a stochastic volatility model for derivative pricing. Unlike the other stochastic volatility models in the literature, the CAM model uses two Brownian motions, one multiplicative and one additive, to model the volatility process. We provide empirical evidence that suggests a nontrivial relationship between the kurtosis and skewness of asset prices and that the CAM model is able to capture this relationship, whereas the traditional stochastic volatility models cannot. We introduce a control variate method and Monte Carlo estimators for some of the sensitivities (Greeks of the model. We also derive an approximation for the characteristic function of the model.
Stochastic control of traffic patterns
DEFF Research Database (Denmark)
Gaididei, Yuri B.; Gorria, Carlos; Berkemer, Rainer
2013-01-01
A stochastic modulation of the safety distance can reduce traffic jams. It is found that the effect of random modulation on congestive flow formation depends on the spatial correlation of the noise. Jam creation is suppressed for highly correlated noise. The results demonstrate the advantage...... of heterogeneous performance of the drivers in time as well as individually. This opens the possibility for the construction of technical tools to control traffic jam formation....
Complexity and synchronization in stochastic chaotic systems
Son Dang, Thai; Palit, Sanjay Kumar; Mukherjee, Sayan; Hoang, Thang Manh; Banerjee, Santo
2016-02-01
We investigate the complexity of a hyperchaotic dynamical system perturbed by noise and various nonlinear speech and music signals. The complexity is measured by the weighted recurrence entropy of the hyperchaotic and stochastic systems. The synchronization phenomenon between two stochastic systems with complex coupling is also investigated. These criteria are tested on chaotic and perturbed systems by mean conditional recurrence and normalized synchronization error. Numerical results including surface plots, normalized synchronization errors, complexity variations etc show the effectiveness of the proposed analysis.
Monostable array-enhanced stochastic resonance.
Lindner, J F; Breen, B J; Wills, M E; Bulsara, A R; Ditto, W L
2001-05-01
We present a simple nonlinear system that exhibits multiple distinct stochastic resonances. By adjusting the noise and coupling of an array of underdamped, monostable oscillators, we modify the array's natural frequencies so that the spectral response of a typical oscillator in an array of N oscillators exhibits N-1 different stochastic resonances. Such families of resonances may elucidate and facilitate a variety of noise-mediated cooperative phenomena, such as noise-enhanced propagation, in a broad class of similar nonlinear systems.
Ma, Jing; Ma, Lie; Yang, Qingbo; Ran, Qiwen
2015-11-01
The average efficiency of spatial light coupling into a single-mode optical fiber is widely used but cannot estimate the signal-to-noise ratio (SNR) and bit error rate (BER) in free-space optical communication. We provide a statistical model for coupling efficiency and derive the exact expression of the probability density function (PDF). The simulation results confirm that the model is reasonable in the condition of different turbulence intensities and wavefront compensation terms, which is also consistent with our outdoor experiment. We also estimate the average SNR and BER using the PDF. The model is quite useful in a satellite-to-ground laser communication downlink.
Amos, Martyn
2008-01-01
Purpose: To present an algorithm for spatially sorting objects into an annular structure. Design/Methodology/Approach: A swarm-based model that requires only stochastic agent behaviour coupled with a pheromone-inspired "attraction-repulsion" mechanism. Findings: The algorithm consistently generates high-quality annular structures, and is particularly powerful in situations where the initial configuration of objects is similar to those observed in nature. Research limitations/implications: Experimental evidence supports previous theoretical arguments about the nature and mechanism of spatial sorting by insects. Practical implications: The algorithm may find applications in distributed robotics. Originality/value: The model offers a powerful minimal algorithmic framework, and also sheds further light on the nature of attraction-repulsion algorithms and underlying natural processes.
Stochastic Physicochemical Dynamics
Tsekov, R.
2001-02-01
fluctuations. The range of validity of the Boltzmann-Einstein principle is also discussed and a generalized alternative is proposed. Both expressions coincide in the small fluctuation limit, providing a normal distribution density. Fluctuation Stability of Thin Liquid Films: Memory effect of Brownian motion in an incompressible fluid is studied. The reasoning is based on the Mori-Zwanzig formalism and a new formulation of the Langevin force as a result of collisions between an effective and the Brownian particles. Thus, the stochastic force autocorrelation function with finite dispersion and the corresponding Brownian particle velocity autocorrelation function are obtained. It is demonstrated that the dynamic structure is very important for the rate of drainage of a thin liquid film and it can be effectively taken into account by a dynamic fractal dimension. It is shown that the latter is a powerful tool for description of the film drainage and classifies all the known results from the literature. The obtained general expression for the thinning rate is a heuristic one and predicts variety of drainage models, which are even difficult to simulate in practice. It is a typical example of a scaling law, which explains the origin of the complicate dependence of the thinning rate on the film radius. On the basis of the theory of stochastic processes the evolution of the spatial correlation function of the surface waves on a thin liquid film as well as the corresponding root mean square amplitude A(t) and number of uncorrelated subdomains N(t) are obtained. A formulation of the life time of unstable nonthinning films is proposed, based on the evolution of A and N. It is shown that the presence of uncorrelated subdomains shortens the life time of the film. Some numerical results for A(t) and N(t) at different film thicknesses h and areas S, are demonstrated, taking into account only van der Waals and capillary forces. Resonant Diffusion in Molecular Solid Structures: A new approach to
Indian Academy of Sciences (India)
Guha Dharmarajan
2015-03-01
Inbreeding in parasite populations can have important epidemiological and evolutionary implications. However, theoretical models have predominantly focussed on the evolution of parasite populations under strong selection or in epidemic situations, and our understanding of neutral gene dynamics in parasite populations at equilibrium has been limited to verbal arguments or conceptual models. This study focusses on how host–parasite population dynamics affects observed levels of inbreeding in a random sample of parasites from an infinite population of hosts by bridging traditional genetic and parasitological processes utilizing a backward–forward branching Markov process embedded within a flexible statistical framework, the logarithmic-poisson mixture model. My results indicate that levels of inbreeding in parasites are impacted by demographic and/or transmission dynamics (subdivided mating, aggregated transmission dynamics and host spatial structure), and that this inbreeding is poorly estimated by ‘equilibrium’ levels of inbreeding calculated assuming regular systems of mating. Specifically, the model reveals that at low levels of inbreeding ( ≤ 0.1), equilibrium levels of inbreeding are lower than those observed, while at high levels of inbreeding the opposite pattern occurs. The model also indicates that inbreeding could have important epidemiological implications (e.g., the spread of recessive drug resistance genes) by directly impacting the observed frequency of rare homozygotes in parasite populations. My results indicate that frequencies of rare homozygotes are affected by aggregated transmission dynamics and host spatial structure, and also that an increase in the frequency of rare homozygotes can be caused by a decrease in effective population size solely due to the presence of a subdivided breeding system.
Directory of Open Access Journals (Sweden)
Xiaoteng Cen
2015-01-01
Full Text Available Despite the unprecedented rate of urbanization throughout the world, human society is still facing the challenge of coordinating urban socioeconomic development and ecological conservation. In this article, we integrated socioeconomic data and spatial metrics to investigate the coupling relationship between intensive land use (ILU system and landscape ecological security (LES system for urban sustainable development, and to determine how these systems interact with each other. The values of ILU and LES were first calculated according to two evaluation subsystems under the pressure-state-response (PSR framework. A coupling model was then established to analyze the coupling relationship within these two subsystems. The results showed that the levels of both subsystems were generally increasing, but there were several fluctuation changes in LES. The interaction in each system was time lagged; urban land use/cover change (LUCC and ecosystem transformation were determined by political business cycles and influenced by specific factors. The coupling relationship underwent a coordinated development mode from 1992–2012. From the findings we concluded that the coupling system maintained a stable condition and underwent evolving threshold values. The integrated ILU and LES system was a coupling system in which subsystems were related to each other and internal elements had mutual effects. Finally, it was suggested that our results provided a multi-level interdisciplinary perspective on linking socioeconomic-ecological systems. The implications for urban sustainable development were also discussed.
The stochastic integrable AKNS hierarchy
Arnaudon, Alexis
2015-01-01
We derive a stochastic AKNS hierarchy using geometrical methods. The integrability is shown via a stochastic zero curvature relation associated with a stochastic isospectral problem. We expose some of the stochastic integrable partial differential equations which extend the stochastic KdV equation discovered by M. Wadati in 1983 for all the AKNS flows. We also show how to find stochastic solitons from the stochastic evolution of the scattering data of the stochastic IST. We finally expose som...
QUANTUM STOCHASTIC PROCESSES: BOSON AND FERMION BROWNIAN MOTION
Directory of Open Access Journals (Sweden)
A.E.Kobryn
2003-01-01
Full Text Available Dynamics of quantum systems which are stochastically perturbed by linear coupling to the reservoir can be studied in terms of quantum stochastic differential equations (for example, quantum stochastic Liouville equation and quantum Langevin equation. In order to work it out one needs to define the quantum Brownian motion. As far as only its boson version has been known until recently, in the present paper we present the definition which makes it possible to consider the fermion Brownian motion as well.
Moawia Alghalith
2012-01-01
We present new stochastic differential equations, that are more general and simpler than the existing Ito-based stochastic differential equations. As an example, we apply our approach to the investment (portfolio) model.
Stochastic processes - quantum physics
Energy Technology Data Exchange (ETDEWEB)
Streit, L. (Bielefeld Univ. (Germany, F.R.))
1984-01-01
The author presents an elementary introduction to stochastic processes. He starts from simple quantum mechanics and considers problems in probability, finally presenting quantum dynamics in terms of stochastic processes.
Parameterization of stochastic multiscale triads
Wouters, Jeroen; Iankov Dolaptchiev, Stamen; Lucarini, Valerio; Achatz, Ulrich
2016-11-01
We discuss applications of a recently developed method for model reduction based on linear response theory of weakly coupled dynamical systems. We apply the weak coupling method to simple stochastic differential equations with slow and fast degrees of freedom. The weak coupling model reduction method results in general in a non-Markovian system; we therefore discuss the Markovianization of the system to allow for straightforward numerical integration. We compare the applied method to the equations obtained through homogenization in the limit of large timescale separation between slow and fast degrees of freedom. We numerically compare the ensemble spread from a fixed initial condition, correlation functions and exit times from a domain. The weak coupling method gives more accurate results in all test cases, albeit with a higher numerical cost.
Stochastic tools in turbulence
Lumey, John L
2012-01-01
Stochastic Tools in Turbulence discusses the available mathematical tools to describe stochastic vector fields to solve problems related to these fields. The book deals with the needs of turbulence in relation to stochastic vector fields, particularly, on three-dimensional aspects, linear problems, and stochastic model building. The text describes probability distributions and densities, including Lebesgue integration, conditional probabilities, conditional expectations, statistical independence, lack of correlation. The book also explains the significance of the moments, the properties of the
A Stochastic Skeleton Model for the MJO
Stechmann, S. N.; Thual, S.; Majda, A.
2014-12-01
The Madden-Julian oscillation (MJO) is the dominant mode of variability in the tropical atmosphere on intraseasonal time scales and planetary spatial scales. Despite the primary importance of the MJO and the decades of research progress since its original discovery, a generally accepted theory for its essential mechanisms has remained elusive. In recent work by two of the authors, a minimal dynamical model has been proposed that recovers robustly the most fundamental MJO features of (i) a slow eastward speed of roughly 5 m/s, (ii) a peculiar dispersion relation with dω/dk≈0, and (iii) a horizontal quadrupole vortex structure. This model, the skeleton model, depicts the MJO as a neutrally stable atmospheric wave that involves a simple multiscale interaction between planetary dry dynamics, planetary lower-tropospheric moisture, and the planetary envelope of synoptic-scale activity. In this article, it is shown that the skeleton model can further account for (iv) the intermittent generation of MJO events and (v) the organization of MJO events into wave trains with growth and demise, as seen in nature. The goal is achieved by developing a simple stochastic parameterization for the unresolved details of synoptic-scale activity, which is coupled to otherwise deterministic processes in the skeleton model. In particular, the intermittent initiation, propagation, and shut down of MJO wave trains in the skeleton model occur through these stochastic effects. This includes examples with a background warm pool where some initial MJO-like disturbances propagate through the western region but stall at the peak of background convection/heating corresponding to the Maritime Continent in nature. Also shown are examples with an idealized seasonal cycle, namely a background warm pool state of heating/moistening displacing meridionally during the year. This seasonally varying case considers both equatorial and off-equatorial components of the envelope of synoptic scale convective
Speich, Matthias; Lischke, Heike; Scherstjanoi, Marc; Zappa, Massimiliano
2016-04-01
Various modeling studies have shown that global climate and land use change are expected to have important impacts on the hydrology and vegetation dynamics of European mountainous regions. However, these models focus on either hydrological or ecological processes, while the respective other processes are represented in a simplified manner, e.g. using static parameters or empirical process formulations. This way, dynamic feedbacks between the water cycle and forest dynamics are neglected, which can influence long-term predictions. Integration of dynamic hydrological and ecological models increases the confidence in long-term forecasts by explicitly addressing this feedback. We present FORHYCS, a spatially distributed, coupled eco-hydrological model. FORHYCS is designed for application in temperate and Alpine regions at landscape scale, and consists of the integration of the rainfall-runoff model PREVAH and the forest-landscape model TreeMig. Both these models have previously been used in long-term climate impact studies in Switzerland. In the new, coupled model, both individual models are run simultaneously while exchanging information via a set of interface variables. The forest-landscape model is driven by annual bioclimatic variables (drought stress, snow cover duration, degree-day sum and winter chill), which are obtained through yearly integration of the local water balance as calculated by the hydrological model at an hourly time step. Growth, establishment and mortality of tree species, as simulated by the forest-landscape model, are used to calculate vegetation parameters (leaf area index and fractional vegetation cover), which in turn influence the partitioning of precipitation into interception loss, transpiration, evaporation, soil moisture storage and runoff. Furthermore, the vegetation cover in each grid cell is used to determine and update its land cover class, which allows the simulation of forest advancement or retreat and its hydrological
Energy Technology Data Exchange (ETDEWEB)
Brennan,J.M.; Blaskiewicz, M. M.; Severino, F.
2009-05-04
After the success of longitudinal stochastic cooling of bunched heavy ion beam in RHIC, transverse stochastic cooling in the vertical plane of Yellow ring was installed and is being commissioned with proton beam. This report presents the status of the effort and gives an estimate, based on simulation, of the RHIC luminosity with stochastic cooling in all planes.
Stochastic structure formation in random media
Klyatskin, V. I.
2016-01-01
Stochastic structure formation in random media is considered using examples of elementary dynamical systems related to the two-dimensional geophysical fluid dynamics (Gaussian random fields) and to stochastically excited dynamical systems described by partial differential equations (lognormal random fields). In the latter case, spatial structures (clusters) may form with a probability of one in almost every system realization due to rare events happening with vanishing probability. Problems involving stochastic parametric excitation occur in fluid dynamics, magnetohydrodynamics, plasma physics, astrophysics, and radiophysics. A more complicated stochastic problem dealing with anomalous structures on the sea surface (rogue waves) is also considered, where the random Gaussian generation of sea surface roughness is accompanied by parametric excitation.
Institute of Scientific and Technical Information of China (English)
刘艳君; 丁锋
2016-01-01
It is an issue that multivariable systems with high dimensions have many parameters, resulting in heavy computational costs in identification methods. Therefore, a coupled stochastic gradient algorithm is derived for multivariable systems based on the coupling identification concept. The identification model is decomposed into several single-output systems, and the parameter estimates are coupled during the subsystem identification by using the gradient search. The convergence properties are analyzed by using the martingale convergence theorem. Compared with the recursive least squares algorithm and the coupled least squares algorithm, the proposed algorithm has less computational load. The convergence rate can be improved by introducing a forgetting factor. Performance analysis verifies that the proposed algorithm converges. The simulation results show the effectiveness of the proposed algorithm.%针对多变量系统维数大、参数多、一般的辨识算法计算量大的问题，基于耦合辨识概念，推导多变量系统的耦合随机梯度算法，利用鞅收敛定理分析算法的收敛性能。算法的主要思想是将系统模型分解为多个单输出子系统，在子系统的递推辨识过程中，将每个子系统的参数估计值耦合起来。所提出算法与最小二乘算法和耦合最小二乘算法相比，具有较少的计算量，收敛速度可以通过引入遗忘因子得到改善。性能分析表明了所提出算法收敛，仿真实例验证了算法的有效性。
Gagnon, Patrick; Chrétien, François; Thériault, Georges
2017-01-01
Land leveling impact on water quality had not received much attention for fields in humid continental climate. The objectives of this study were to isolate the impact of land leveling, performed on an agricultural field (Québec, Canada) in spring 2012, on runoff and TSS load and to make recommendations to attenuate adverse environmental impacts of land leveling, if any. A total of 66 runoff events, including 22 with total suspended sediments (TSS) load estimates, from 2010 to 2014 were analyzed. To this end, deterministic models were coupled to an adaptive Metropolis-Hastings algorithm to estimate the unknown distribution of the parameters representing the most important effects, namely land leveling, tillage, and crop cover. Simulated runoff events were generated by the hydrological model SWMM version 5 while simulated TSS loads were generated by an empirical equation based on the Revised Universal Soil Loss Equation version 2 (RUSLE2). Thanks to the algorithm used, it was demonstrated that land leveling significantly decreased total runoff volume at least for the two following years. The impact on peak flow was mixed: land leveling significantly decreased peak flow for a typical stratiform rainfall event but the effect was unclear for a typical convective rainfall event. Based on 90% confidence interval, TSS load increased from 10 to 1000 times immediately after land leveling (spring 2012) compared to pre-land leveling events. The TSS load increase remained significant one year after land leveling, with TSS loads 5-20 times higher compared to pre-land leveling events. It would thus be recommended to grow crops with high ground coverage ratios coupled with cover crops during the year when land leveling is done. Sediment retention structures could also be installed at the beginning of the land leveling process to provide protection against the short term and delayed impact on water quality.
Asynchronous stochastic approximation with differential inclusions
Directory of Open Access Journals (Sweden)
David S. Leslie
2012-01-01
Full Text Available The asymptotic pseudo-trajectory approach to stochastic approximation of Benaïm, Hofbauer and Sorin is extended for asynchronous stochastic approximations with a set-valued mean field. The asynchronicity of the process is incorporated into the mean field to produce convergence results which remain similar to those of an equivalent synchronous process. In addition, this allows many of the restrictive assumptions previously associated with asynchronous stochastic approximation to be removed. The framework is extended for a coupled asynchronous stochastic approximation process with set-valued mean fields. Two-timescales arguments are used here in a similar manner to the original work in this area by Borkar. The applicability of this approach is demonstrated through learning in a Markov decision process.
Stochastic Modeling of Soil Salinity
Suweis, S; Van der Zee, S E A T M; Daly, E; Maritan, A; Porporato, A; 10.1029/2010GL042495
2012-01-01
A minimalist stochastic model of primary soil salinity is proposed, in which the rate of soil salinization is determined by the balance between dry and wet salt deposition and the intermittent leaching events caused by rainfall events. The long term probability density functions of salt mass and concentration are found by reducing the coupled soil moisture and salt mass balance equation to a single stochastic differential equation driven by multiplicative Poisson noise. The novel analytical solutions provide insight on the interplay of the main soil, plant and climate parameters responsible for long-term soil salinization. In particular, they show the existence of two distinct regimes, one where the mean salt mass remains nearly constant (or decreases) with increasing rainfall frequency, and another where mean salt content increases markedly with increasing rainfall frequency. As a result, relatively small reductions of rainfall in drier climates may entail dramatic shifts in long-term soil salinization trend...
A NOTE ON THE STOCHASTIC ROOTS OF STOCHASTIC MATRICES
Institute of Scientific and Technical Information of China (English)
Qi-Ming HE; Eldon GUNN
2003-01-01
In this paper, we study the stochastic root matrices of stochastic matrices. All stochastic roots of 2×2 stochastic matrices are found explicitly. A method based on characteristic polynomial of matrix is developed to find all real root matrices that are functions of the original 3×3 matrix, including all possible (function) stochastic root matrices. In addition, we comment on some numerical methods for computing stochastic root matrices of stochastic matrices.
Park, I. J.; Woo, S. I.
1993-09-01
Gas-phase coupling between two Pd(110) single crystals in a UHV CO oxidation reaction in a continuous stirred tank reactor (CSTR) has been simulated by solving gas-phase mass balance equations with kinetic rate equations. This work was motivated by the experimental results which show that the frequency of partial pressure change in carbon monoxide is the same as the frequency of the work function change in the oscillation region and that the coupling between the two crystals occurred entirely via CO partial pressure. The computer simulation described here gives qualitative agreement with the experimental results. The change in the oscillatory region originating from the coupling of chemical oscillators which are slightly different to each other is successfully demonstrated by this model. The coupling of two oscillators having a simple periodic oscillation to produce mixed-mode oscillation was also successfully simulated.
Energy Technology Data Exchange (ETDEWEB)
Prasankumar, Rohit P [Los Alamos National Laboratory; Taylor, Antoinette J [Los Alamos National Laboratory
2009-01-01
Ultrafast density-dependent optical spectroscopic measurements on a quantum dots-in-a-well heterostructure reveal several distinctive phenomena, most notably a strong coupling between the quantum well population and light absorption at the quantum dot excited state.
Ogawa, Shigeyoshi
2017-01-01
This book presents an elementary introduction to the theory of noncausal stochastic calculus that arises as a natural alternative to the standard theory of stochastic calculus founded in 1944 by Professor Kiyoshi Itô. As is generally known, Itô Calculus is essentially based on the "hypothesis of causality", asking random functions to be adapted to a natural filtration generated by Brownian motion or more generally by square integrable martingale. The intention in this book is to establish a stochastic calculus that is free from this "hypothesis of causality". To be more precise, a noncausal theory of stochastic calculus is developed in this book, based on the noncausal integral introduced by the author in 1979. After studying basic properties of the noncausal stochastic integral, various concrete problems of noncausal nature are considered, mostly concerning stochastic functional equations such as SDE, SIE, SPDE, and others, to show not only the necessity of such theory of noncausal stochastic calculus but ...
Stochastic Lie group integrators
Malham, Simon J A
2007-01-01
We present Lie group integrators for nonlinear stochastic differential equations with non-commutative vector fields whose solution evolves on a smooth finite dimensional manifold. Given a Lie group action that generates transport along the manifold, we pull back the stochastic flow on the manifold to the Lie group via the action, and subsequently pull back the flow to the corresponding Lie algebra via the exponential map. We construct an approximation to the stochastic flow in the Lie algebra via closed operations and then push back to the Lie group and then to the manifold, thus ensuring our approximation lies in the manifold. We call such schemes stochastic Munthe-Kaas methods after their deterministic counterparts. We also present stochastic Lie group integration schemes based on Castell--Gaines methods. These involve using an underlying ordinary differential integrator to approximate the flow generated by a truncated stochastic exponential Lie series. They become stochastic Lie group integrator schemes if...
Pakhomov, A V; Babushkin, I V; Arkhipov, M V; Tolmachev, Yu A; Rosanov, N N
2016-01-01
We study the optical response of a resonant medium possessing the nonlinear coupling to external field under excitation by few-cycle pump pulses. A theoretical approach is developed, allowing to analyze unipolar half-cycle pulse generation in such a geometry. Our approach is applicable for the arbitrary coupling functions as well as arbitrarily curved pump pulse wavefronts and defines a general framework to produce unipolar pulses of desired form.
Directory of Open Access Journals (Sweden)
D. Yu. Klimushkin
2006-09-01
Full Text Available The paper employs the frame of a 1-D inhomogeneous model of space plasma,to examine the spatial structure and growth rate of drift mirror modes, often suggested for interpreting some oscillation types in space plasma. Owing to its coupling with the Alfvén mode, the drift mirror mode attains dispersion across magnetic shells (dependence of the frequency on the wave-vector's radial component, k_{r}. The spatial structure of a mode confined across magnetic shells is studied. The scale of spatial localization of the wave is shown to be determined by the plasma inhomogeneity scale and by the azimuthal component of the wave vector. The wave propagates across magnetic shells, its amplitude modulated along the radial coordinate by the Gauss function. Coupling with the Alfvén mode strongly influences the growth rate of the drift mirror instability. The mirror mode can only exist in a narrow range of parameters. In the general case, the mode represents an Alfvén wave modified by plasma inhomogeneity.
Jian, Wenjuan; Chen, Minyou; McFarland, Dennis J
2017-03-25
Phase-locking value (PLV) is a potentially useful feature in sensorimotor rhythm-based brain-computer interface (BCI). However, volume conduction may cause spurious zero-phase coupling between two EEG signals and it is not clear whether PLV effects are independent of spectral amplitude. Volume conduction might be reduced by spatial filtering, but it is uncertain what impact this might have on PLV. Therefore, the goal of this study was to explore whether zero-phase PLV is meaningful and how it is affected by spatial filtering. Both amplitude and PLV feature were extracted in the frequency band of 10-15 Hz by classical methods using archival EEG data of 18 subjects trained on a two-target BCI task. The results show that with right ear-referenced data, there is meaningful long-range zero-phase synchronization likely involving the primary motor area and the supplementary motor area that cannot be explained by volume conduction. Another novel finding is that the large Laplacian spatial filter enhances the amplitude feature but eliminates most of the phase information seen in ear-referenced data. A bipolar channel using phase-coupled areas also includes both phase and amplitude information and has a significant practical advantage since fewer channels required.
A hybrid algorithm for coupling partial differential equation and compartment-based dynamics.
Harrison, Jonathan U; Yates, Christian A
2016-09-01
Stochastic simulation methods can be applied successfully to model exact spatio-temporally resolved reaction-diffusion systems. However, in many cases, these methods can quickly become extremely computationally intensive with increasing particle numbers. An alternative description of many of these systems can be derived in the diffusive limit as a deterministic, continuum system of partial differential equations (PDEs). Although the numerical solution of such PDEs is, in general, much more efficient than the full stochastic simulation, the deterministic continuum description is generally not valid when copy numbers are low and stochastic effects dominate. Therefore, to take advantage of the benefits of both of these types of models, each of which may be appropriate in different parts of a spatial domain, we have developed an algorithm that can be used to couple these two types of model together. This hybrid coupling algorithm uses an overlap region between the two modelling regimes. By coupling fluxes at one end of the interface and using a concentration-matching condition at the other end, we ensure that mass is appropriately transferred between PDE- and compartment-based regimes. Our methodology gives notable reductions in simulation time in comparison with using a fully stochastic model, while maintaining the important stochastic features of the system and providing detail in appropriate areas of the domain. We test our hybrid methodology robustly by applying it to several biologically motivated problems including diffusion and morphogen gradient formation. Our analysis shows that the resulting error is small, unbiased and does not grow over time.
Martínez-López, Beatriz; Ivorra, Benjamin; Ramos, Angel Manuel; Fernández-Carrión, Eduardo; Alexandrov, Tsviatko; Sánchez-Vizcaíno, José Manuel
2013-07-26
The study presented here is one of the very first aimed at exploring the potential spread of classical swine fever (CSF) from backyard pigs to other domestic pigs. Specifically, we used a spatial stochastic spread model, called Be-FAST, to evaluate the potential spread of CSF virus (CSFV) in Bulgaria, which holds a large number of backyards (96% of the total number of pig farms) and is one of the very few countries for which backyard pigs and farm counts are available. The model revealed that, despite backyard pigs being very likely to become infected, infections from backyard pigs to other domestic pigs were rare. In general, the magnitude and duration of the CSF simulated epidemics were small, with a median [95% PI] number of infected farms per epidemic of 1 [1,4] and a median [95% PI] duration of the epidemic of 44 [17,101] days. CSFV transmission occurs primarily (81.16%) due to indirect contacts (i.e. vehicles, people and local spread) whereas detection of infected premises was mainly (69%) associated with the observation of clinical signs on farm rather than with implementation of tracing or zoning. Methods and results of this study may support the implementation of risk-based strategies more cost-effectively to prevent, control and, ultimately, eradicate CSF from Bulgaria. The model may also be easily adapted to other countries in which the backyard system is predominant. It can also be used to simulate other similar diseases such as African swine fever. Copyright © 2013 Elsevier B.V. All rights reserved.
FORWARD-BACKWARD STOCHASTIC DIFFERENTIAL EQUATIONS WITH STOPPING TIME
Institute of Scientific and Technical Information of China (English)
吴臻
2004-01-01
The existence and uniqueness results of fully coupled forward-backward stochastic differential equations with stopping time (unbounded) is obtained. One kind of comparison theorem for this kind of equations is also proved.
Numerical Stochastic Perturbation Theory and the Gradient Flow
Brida, Mattia Dalla
2013-01-01
We study the Yang-Mills gradient flow using numerical stochastic perturbation theory. As an application of the method we consider the recently proposed gradient flow coupling in the Schr\\"odinger functional for the pure SU(3) gauge theory.
Formal Abstractions for Automated Verification and Synthesis of Stochastic Systems
Esmaeil Zadeh Soudjani, S.
2014-01-01
Stochastic hybrid systems involve the coupling of discrete, continuous, and probabilistic phenomena, in which the composition of continuous and discrete variables captures the behavior of physical systems interacting with digital, computational devices. Because of their versatility and generality, m
Formal Abstractions for Automated Verification and Synthesis of Stochastic Systems
Esmaeil Zadeh Soudjani, S.
2014-01-01
Stochastic hybrid systems involve the coupling of discrete, continuous, and probabilistic phenomena, in which the composition of continuous and discrete variables captures the behavior of physical systems interacting with digital, computational devices. Because of their versatility and generality, m
Directory of Open Access Journals (Sweden)
Jinliang Huang
demonstrates that the coupled effects of natural and anthropogenic controls involved in watershed processes, contribute to the seasonal and spatial variation of headwater stream water quality in a coastal watershed with high spatial variability and intensive anthropogenic activities.
DEFF Research Database (Denmark)
Schrum, Corinna; St. John, Michael; Alekseeva, I.
2006-01-01
The 3-D coupled biophysical model ECOSMO (ECOSystern MOdel) has been applied to simulate the spatial and temporal variability of primary and secondary production and biomass in the North Sea in 1984, In order to assess the spatial and temporal dynamics of these components, statistical methods based...... and production in the North Sea. Employing these techniques made it possible to separate regional and temporal variability into the annual pattern, its temporal characteristics and some basic regional modulations of the average seasonal signal. The analysis was able to identify the modulation of average seasonal...... and the end of April, with little to no diatom biomass in the second half of summer. Conversely flagellate biomass did not peak before the beginning of May and showed a relatively constant summer production and an autumn bloom. (c) 2006 Published by Elsevier B.V....
Proper orthogonal decomposition-based spectral higher-order stochastic estimation
Energy Technology Data Exchange (ETDEWEB)
Baars, Woutijn J., E-mail: wbaars@unimelb.edu.au [Department of Mechanical Engineering, The University of Melbourne, Melbourne, Victoria 3010 (Australia); Tinney, Charles E. [Center for Aeromechanics Research, The University of Texas at Austin, Austin, Texas 78712 (United States)
2014-05-15
A unique routine, capable of identifying both linear and higher-order coherence in multiple-input/output systems, is presented. The technique combines two well-established methods: Proper Orthogonal Decomposition (POD) and Higher-Order Spectra Analysis. The latter of these is based on known methods for characterizing nonlinear systems by way of Volterra series. In that, both linear and higher-order kernels are formed to quantify the spectral (nonlinear) transfer of energy between the system's input and output. This reduces essentially to spectral Linear Stochastic Estimation when only first-order terms are considered, and is therefore presented in the context of stochastic estimation as spectral Higher-Order Stochastic Estimation (HOSE). The trade-off to seeking higher-order transfer kernels is that the increased complexity restricts the analysis to single-input/output systems. Low-dimensional (POD-based) analysis techniques are inserted to alleviate this void as POD coefficients represent the dynamics of the spatial structures (modes) of a multi-degree-of-freedom system. The mathematical framework behind this POD-based HOSE method is first described. The method is then tested in the context of jet aeroacoustics by modeling acoustically efficient large-scale instabilities as combinations of wave packets. The growth, saturation, and decay of these spatially convecting wave packets are shown to couple both linearly and nonlinearly in the near-field to produce waveforms that propagate acoustically to the far-field for different frequency combinations.
PC analysis of stochastic differential equations driven by Wiener noise
Le Maitre, Olivier
2015-03-01
A polynomial chaos (PC) analysis with stochastic expansion coefficients is proposed for stochastic differential equations driven by additive or multiplicative Wiener noise. It is shown that for this setting, a Galerkin formalism naturally leads to the definition of a hierarchy of stochastic differential equations governing the evolution of the PC modes. Under the mild assumption that the Wiener and uncertain parameters can be treated as independent random variables, it is also shown that the Galerkin formalism naturally separates parametric uncertainty and stochastic forcing dependences. This enables us to perform an orthogonal decomposition of the process variance, and consequently identify contributions arising from the uncertainty in parameters, the stochastic forcing, and a coupled term. Insight gained from this decomposition is illustrated in light of implementation to simplified linear and non-linear problems; the case of a stochastic bifurcation is also considered.
Eluszkiewicz, Janusz; Nehrkorn, Thomas; Wofsy, Steven C.; Matross, Daniel; Gerbig, Christoph; Lin, John C.; Freitas, Saulo; Longo, Marcos; Andrews, Arlyn E.; Peters, Wouter
2007-01-01
This paper evaluates simulations of atmospheric CO2 measured in 2004 at continental surface and airborne receptors, intended to test the capability to use data with high temporal and spatial resolution for analyses of carbon sources and sinks at regional and continental scales. The simulations were performed using the Stochastic Time-Inverted Lagrangian Transport (STILT) model driven by the Weather Forecast and Research (WRF) model, and linked to surface fluxes from the satellite-driven Vegetation Photosynthesis and Respiration Model (VPRM). The simulations provide detailed representations of hourly CO2 tower data and reproduce the shapes of airborne vertical profiles with high fidelity. WRF meteorology gives superior model performance compared with standard meteorological products, and the impact of including WRF convective mass fluxes in the STILT trajectory calculations is significant in individual cases. Important biases in the simulation are associated with the nighttime CO2 build-up and subsequent morning transition to convective conditions, and with errors in the advected lateral boundary condition. Comparison of STILT simulations driven by the WRF model against those driven by the Brazilian variant of the Regional Atmospheric Modeling System (BRAMS) shows that model-to-model differences are smaller than between an individual transport model and observations, pointing to systematic errors in the simulated transport. Future developments in the WRF model s data assimilation capabilities, basic research into the fundamental aspects of trajectory calculations, and intercomparison studies involving other transport models, are possible venues for reducing these errors. Overall, the STILT/WRF/VPRM offers a powerful tool for continental and regional scale carbon flux estimates.
Wenwu Tang; Wenpeng Feng; Meijuan Jia; Jiyang Shi; Huifang Zuo; Christina E. Stringer; Carl C. Trettin
2017-01-01
Mangroves are an important terrestrial carbon reservoir with numerous ecosystem services. Yet, it is difficult to inventory mangroves because of their low accessibility. A sampling approach that produces accurate assessment while maximizing logistical integrity of inventory operation is often required. Spatial decision support systems (SDSSs) provide support for...
Fundamentals of Stochastic Networks
Ibe, Oliver C
2011-01-01
An interdisciplinary approach to understanding queueing and graphical networks In today's era of interdisciplinary studies and research activities, network models are becoming increasingly important in various areas where they have not regularly been used. Combining techniques from stochastic processes and graph theory to analyze the behavior of networks, Fundamentals of Stochastic Networks provides an interdisciplinary approach by including practical applications of these stochastic networks in various fields of study, from engineering and operations management to communications and the physi
Mechanical Autonomous Stochastic Heat Engine
Serra-Garcia, Marc; Foehr, André; Molerón, Miguel; Lydon, Joseph; Chong, Christopher; Daraio, Chiara
2016-07-01
Stochastic heat engines are devices that generate work from random thermal motion using a small number of highly fluctuating degrees of freedom. Proposals for such devices have existed for more than a century and include the Maxwell demon and the Feynman ratchet. Only recently have they been demonstrated experimentally, using, e.g., thermal cycles implemented in optical traps. However, recent experimental demonstrations of classical stochastic heat engines are nonautonomous, since they require an external control system that prescribes a heating and cooling cycle and consume more energy than they produce. We present a heat engine consisting of three coupled mechanical resonators (two ribbons and a cantilever) subject to a stochastic drive. The engine uses geometric nonlinearities in the resonating ribbons to autonomously convert a random excitation into a low-entropy, nonpassive oscillation of the cantilever. The engine presents the anomalous heat transport property of negative thermal conductivity, consisting in the ability to passively transfer energy from a cold reservoir to a hot reservoir.
Fluctuations as stochastic deformation
Kazinski, P. O.
2008-04-01
A notion of stochastic deformation is introduced and the corresponding algebraic deformation procedure is developed. This procedure is analogous to the deformation of an algebra of observables like deformation quantization, but for an imaginary deformation parameter (the Planck constant). This method is demonstrated on diverse relativistic and nonrelativistic models with finite and infinite degrees of freedom. It is shown that under stochastic deformation the model of a nonrelativistic particle interacting with the electromagnetic field on a curved background passes into the stochastic model described by the Fokker-Planck equation with the diffusion tensor being the inverse metric tensor. The first stochastic correction to the Newton equations for this system is found. The Klein-Kramers equation is also derived as the stochastic deformation of a certain classical model. Relativistic generalizations of the Fokker-Planck and Klein-Kramers equations are obtained by applying the procedure of stochastic deformation to appropriate relativistic classical models. The analog of the Fokker-Planck equation associated with the stochastic Lorentz-Dirac equation is derived too. The stochastic deformation of the models of a free scalar field and an electromagnetic field is investigated. It turns out that in the latter case the obtained stochastic model describes a fluctuating electromagnetic field in a transparent medium.
Singular stochastic differential equations
Cherny, Alexander S
2005-01-01
The authors introduce, in this research monograph on stochastic differential equations, a class of points termed isolated singular points. Stochastic differential equations possessing such points (called singular stochastic differential equations here) arise often in theory and in applications. However, known conditions for the existence and uniqueness of a solution typically fail for such equations. The book concentrates on the study of the existence, the uniqueness, and, what is most important, on the qualitative behaviour of solutions of singular stochastic differential equations. This is done by providing a qualitative classification of isolated singular points, into 48 possible types.
Stacking with Stochastic Cooling
Caspers, Friedhelm
2004-01-01
Accumulation of large stacks of antiprotons or ions with the aid of stochastic cooling is more delicate than cooling a constant intensity beam. Basically the difficulty stems from the fact that the optimized gain and the cooling rate are inversely proportional to the number of particles seen by the cooling system. Therefore, to maintain fast stacking, the newly injected batch has to be strongly protected from the Schottky noise of the stack. Vice versa the stack has to be efficiently shielded against the high gain cooling system for the injected beam. In the antiproton accumulators with stacking ratios up to 105, the problem is solved by radial separation of the injection and the stack orbits in a region of large dispersion. An array of several tapered cooling systems with a matched gain profile provides a continuous particle flux towards the high-density stack core. Shielding of the different systems from each other is obtained both through the spatial separation and via the revolution frequencies (filters)....
Le Pichon, C.; Coustillas, J.; Zahm, A.; Bunel, M.; Gazeau-Nadin, C.; Rochard, E.
2017-09-01
Acoustic telemetry and GIS-based spatial analysis were used to investigate the summer habitat use and movement patterns of three fish species in the tidal freshwaters of the Seine estuary (France). Experimental displacement of tagged individuals of thin-lipped grey mullet (Liza ramada), European eel (Anguilla anguilla), and common bream (Abramis brama) were conducted to test for their spatial fidelity and home range establishment. Most tagged individuals (95%) successfully returned to their previously occupied capture site, showing spatial homing abilities. The studied upstream tidal freshwater segment of the Seine estuary was regularly used by grey mullet as a part of its larger summer home range, while European eel and common bream were resident in this segment. The fidelity of eel to small nocturnal refuges and the regular use of intertidal waterbodies at high tide by grey mullet and bream suggested that they possess a capacity of acquiring spatial memory of habitats in a fluctuating environment. Importantly, the scale of movements travelled by each species was positively related to tidal phase. Grey mullet and bream, both visual feeders, exhibited short-term tidal movements to known habitats, providing food resources and contiguous resting habitat suggesting that they have shown behavioural strategies adaptive to fluctuating environments. Eel, in contrast, was found to have a different strategy strongly related to diel dynamics: it stayed in subtidal habitats rich in refuges that remained available at low tide. The results of this study emphasize the importance of restoring intertidal waterbodies and the relevance of considering the availability of adjacent subtidal habitats providing refuge at low tides.
Energy Technology Data Exchange (ETDEWEB)
Brennan J. M.; Blaskiewicz, M.; Mernick, K.
2012-05-20
The full 6-dimensional [x,x'; y,y'; z,z'] stochastic cooling system for RHIC was completed and operational for the FY12 Uranium-Uranium collider run. Cooling enhances the integrated luminosity of the Uranium collisions by a factor of 5, primarily by reducing the transverse emittances but also by cooling in the longitudinal plane to preserve the bunch length. The components have been deployed incrementally over the past several runs, beginning with longitudinal cooling, then cooling in the vertical planes but multiplexed between the Yellow and Blue rings, next cooling both rings simultaneously in vertical (the horizontal plane was cooled by betatron coupling), and now simultaneous horizontal cooling has been commissioned. The system operated between 5 and 9 GHz and with 3 x 10{sup 8} Uranium ions per bunch and produces a cooling half-time of approximately 20 minutes. The ultimate emittance is determined by the balance between cooling and emittance growth from Intra-Beam Scattering. Specific details of the apparatus and mathematical techniques for calculating its performance have been published elsewhere. Here we report on: the method of operation, results with beam, and comparison of results to simulations.
Collados-Lara, Antonio-Juan; Pulido-Velazquez, David; Pardo-Iguzquiza, Eulogio
2017-04-01
and drought statistic of the historical data. A multi-objective analysis using basic statistics (mean, standard deviation and asymmetry coefficient) and droughts statistics (duration, magnitude and intensity) has been performed to identify which models are better in terms of goodness of fit to reproduce the historical series. The drought statistics have been obtained from the Standard Precipitation index (SPI) series using the Theory of Runs. This analysis allows discriminate the best RCM and the best combination of model and correction technique in the bias-correction method. We have also analyzed the possibilities of using different Stochastic Weather Generators to approximate the basic and droughts statistics of the historical series. These analyses have been performed in our case study in a lumped and in a distributed way in order to assess its sensibility to the spatial scale. The statistic of the future temperature series obtained with different ensemble options are quite homogeneous, but the precipitation shows a higher sensibility to the adopted method and spatial scale. The global increment in the mean temperature values are 31.79 %, 31.79 %, 31.03 % and 31.74 % for the distributed bias-correction, distributed delta-change, lumped bias-correction and lumped delta-change ensembles respectively and in the precipitation they are -25.48 %, -28.49 %, -26.42 % and -27.35% respectively. Acknowledgments: This research work has been partially supported by the GESINHIMPADAPT project (CGL2013-48424-C2-2-R) with Spanish MINECO funds. We would also like to thank Spain02 and CORDEX projects for the data provided for this study and the R package qmap.
Kovalskyy, V.; Henebry, G. M.; Adusei, B.; Hansen, M.; Roy, D. P.; Senay, G.; Mocko, D. M.
2011-01-01
A new model coupling scheme with remote sensing data assimilation was developed for estimation of daily actual evapotranspiration (ET). The scheme represents a mix of the VegET, a physically based model to estimate ET from a water balance, and an event driven phenology model (EDPM), where the EDPM is an empirically derived crop specific model capable of producing seasonal trajectories of canopy attributes. In this experiment, the scheme was deployed in a spatially explicit manner within the croplands of the Northern Great Plains. The evaluation was carried out using 2007-2009 land surface forcing data from the North American Land Data Assimilation System (NLDAS) and crop maps derived from remotely sensed data of NASA's Moderate Resolution Imaging Spectroradiometer (MODIS). We compared the canopy parameters produced by the phenology model with normalized difference vegetation index (NDVI) data derived from the MODIS nadir bi-directional reflectance distribution function (BRDF) adjusted reflectance (NBAR) product. The expectations of the EDPM performance in prognostic mode were met, producing determination coefficient (r2) of 0.8 +/-.0.15. Model estimates of NDVI yielded root mean square error (RMSE) of 0.1 +/-.0.035 for the entire study area. Retrospective correction of canopy dynamics with MODIS NDVI brought the errors down to just below 10% of observed data range. The ET estimates produced by the coupled scheme were compared with ones from the MODIS land product suite. The expected r2=0.7 +/-.15 and RMSE = 11.2 +/-.4 mm per 8 days were met and even exceeded by the coupling scheme0 functioning in both prognostic and retrospective modes. Minor setbacks of the EDPM and VegET performance (r2 about 0.5 and additional 30 % of RMSR) were found on the peripheries of the study area and attributed to the insufficient EDPM training and to spatially varying accuracy of crop maps. Overall the experiment provided sufficient evidence of soundness and robustness of the EDPM and
The pattern for waiting time in the context of multiple stochastic process
Jamali, Tayeb; Farahani, S Vasheghani
2015-01-01
The aim here is to provide a deeper understanding on the concept of waiting time in application to multiple stochastic processes. This obliges us to work with the vector stochastic process which enables considering at least two stochastic process at simultaneous time instances. In the present study the plan is to master vector stochastic processes by developing the level crossing method. The reason that the previous level-crossing methods lack generality is based on their individual element studies, where the coupling between the components of the vector stochastic process had been simply neglected. In the present work by introducing the generalized level crossing method, consideration of coupling between the components has become possible. This enables analyzing and hence extracting information out of coupled processes usually faced when working in tensor environments. The results obtained by this technique state that in addition to the point distribution of the vector stochastic process, the coupling plays ...
Scattering theory of stochastic electromagnetic light waves.
Wang, Tao; Zhao, Daomu
2010-07-15
We generalize scattering theory to stochastic electromagnetic light waves. It is shown that when a stochastic electromagnetic light wave is scattered from a medium, the properties of the scattered field can be characterized by a 3 x 3 cross-spectral density matrix. An example of scattering of a spatially coherent electromagnetic light wave from a deterministic medium is discussed. Some interesting phenomena emerge, including the changes of the spectral degree of coherence and of the spectral degree of polarization of the scattered field.
Stochastic longshore current dynamics
Restrepo, Juan M.; Venkataramani, Shankar
2016-12-01
We develop a stochastic parametrization, based on a 'simple' deterministic model for the dynamics of steady longshore currents, that produces ensembles that are statistically consistent with field observations of these currents. Unlike deterministic models, stochastic parameterization incorporates randomness and hence can only match the observations in a statistical sense. Unlike statistical emulators, in which the model is tuned to the statistical structure of the observation, stochastic parametrization are not directly tuned to match the statistics of the observations. Rather, stochastic parameterization combines deterministic, i.e physics based models with stochastic models for the "missing physics" to create hybrid models, that are stochastic, but yet can be used for making predictions, especially in the context of data assimilation. We introduce a novel measure of the utility of stochastic models of complex processes, that we call consistency of sensitivity. A model with poor consistency of sensitivity requires a great deal of tuning of parameters and has a very narrow range of realistic parameters leading to outcomes consistent with a reasonable spectrum of physical outcomes. We apply this metric to our stochastic parametrization and show that, the loss of certainty inherent in model due to its stochastic nature is offset by the model's resulting consistency of sensitivity. In particular, the stochastic model still retains the forward sensitivity of the deterministic model and hence respects important structural/physical constraints, yet has a broader range of parameters capable of producing outcomes consistent with the field data used in evaluating the model. This leads to an expanded range of model applicability. We show, in the context of data assimilation, the stochastic parametrization of longshore currents achieves good results in capturing the statistics of observation that were not used in tuning the model.
Colin, F.; Moussa, R.
2009-04-01
In rural basins, agricultural landscape management highly influences water and pollutants transfers. Landuse, agricultural practices and their spatial arrangements are at issue. Hydrological model are widely used to explore impacts of anthropogenic influences on experimental catchments. But planning all spatial arrangements leads to a possible cases count which cannot be considered. On the basis of the recent « numerical experiment » approach, we propose a « numerical tracer function » which had to be coupled to a distributed rainfall-runoff model. This function simulate the transfer of a virtual tracer successively spread on each distributed unit inside the catchment. It allows to rank hydrological spatial units according to their hydrological contribution to the surface flows, particularly at the catchment outlet. It was used with the distributed model MHYDAS in an agricultural context. The case study concerns the experimental Roujan vine-growing catchment (1km², south of France) studied since 1992. In this Mediterranean context, we focus on the soil hydraulic conductivity distributed parameter because it highly depends on weed control practices (chemical weeding induces a lot more runoff than mechanical weeding). We checked model sensitivity analysis to soil hydraulic conductivity spatial arrangement on runoff coefficient, peak discharge and catchment lag-time. Results show (i) the use of the tracer function is more efficient than a random approach to improve sensitivity to spatial arrangements from point of view of simulated discharge range, (ii) the first factor explaining hydrological simulations variability was practices area ratio, (iii) variability induced by practices spatial arrangements was significant on runoff coefficient and peak discharge for balanced practices area ratio and on lag-time for low area ratio of chemical weeding practices. From the actual situation on the experimental Roujan catchment (40% of tilled and 60% of non tilled vineyard
Wang, T.; Zhang, H.; Lin, H.
2017-09-01
surfaces has increasingly roused widely interests of researchers in monitoring urban development and determining the overall environmental health of a watershed. However, studies on the impervious surface using multi-spectral imageries is insufficient and inaccurate due to the complexity of urban infrastructures base on the need to further recognize these impervious surface materials in a finer scale. Hyperspectral imageries have been proved to be sensitive to subtle spectral differences thus capable to exquisitely discriminate these similar materials while limited to the low spatial resolution. Coupled nonnegative matrix factorization (CNMF) unmixing method is one of the most physically straightforward and easily complemented hyperspectral pan-sharpening methods that could produce fused data with both high spectral and spatial resolution. This paper aimed to exploit the latent capacity and tentative validation of CNMF on the killer application of mapping urban impervious surfaces in complexed metropolitan environments like Hong Kong. Experiments showed that the fusion of high spectral and spatial resolution image could provide more accurate and comprehensive information on urban impervious surface estimation.
Stochastic resonance and chaotic resonance in bimodal maps: A case study
Indian Academy of Sciences (India)
G Ambika; N V Sujatha; K P Harikrishnan
2002-09-01
We present the results of an extensive numerical study on the phenomenon of stochastic resonance in a bimodal cubic map. Both Gaussian random noise as well as deterministic chaos are used as input to drive the system between the basins. Our main result is that when two identical systems capable of stochastic resonance are coupled, the SNR of either system is enhanced at an optimum coupling strength. Our results may be relevant for the study of stochastic resonance in biological systems.
A Stochastic Employment Problem
Wu, Teng
2013-01-01
The Stochastic Employment Problem(SEP) is a variation of the Stochastic Assignment Problem which analyzes the scenario that one assigns balls into boxes. Balls arrive sequentially with each one having a binary vector X = (X[subscript 1], X[subscript 2],...,X[subscript n]) attached, with the interpretation being that if X[subscript i] = 1 the ball…
Stochastic Convection Parameterizations
Teixeira, Joao; Reynolds, Carolyn; Suselj, Kay; Matheou, Georgios
2012-01-01
computational fluid dynamics, radiation, clouds, turbulence, convection, gravity waves, surface interaction, radiation interaction, cloud and aerosol microphysics, complexity (vegetation, biogeochemistry, radiation versus turbulence/convection stochastic approach, non-linearities, Monte Carlo, high resolutions, large-Eddy Simulations, cloud structure, plumes, saturation in tropics, forecasting, parameterizations, stochastic, radiation-clod interaction, hurricane forecasts
Instantaneous stochastic perturbation theory
Lüscher, Martin
2015-01-01
A form of stochastic perturbation theory is described, where the representative stochastic fields are generated instantaneously rather than through a Markov process. The correctness of the procedure is established to all orders of the expansion and for a wide class of field theories that includes all common formulations of lattice QCD.
Verhoosel, C.V.; Gutiérrez, M.A.; Hulshoff, S.J.
2006-01-01
The field of fluid-structure interaction is combined with the field of stochastics to perform a stochastic flutter analysis. Various methods to directly incorporate the effects of uncertainties in the flutter analysis are investigated. The panel problem with a supersonic fluid flowing over it is con
Han, Bangshuai; Benner, Shawn G.; Bolte, John P.; Vache, Kellie B.; Flores, Alejandro N.
2017-07-01
Humans have significantly altered the redistribution of water in intensively managed hydrologic systems, shifting the spatiotemporal patterns of surface water. Evaluating water availability requires integration of hydrologic processes and associated human influences. In this study, we summarize the development and evaluation of an extensible hydrologic model that explicitly integrates water rights to spatially distribute irrigation waters in a semi-arid agricultural region in the western US, using the Envision integrated modeling platform. The model captures both human and biophysical systems, particularly the diversion of water from the Boise River, which is the main water source that supports irrigated agriculture in this region. In agricultural areas, water demand is estimated as a function of crop type and local environmental conditions. Surface water to meet crop demand is diverted from the stream reaches, constrained by the amount of water available in the stream, the water-rights-appropriated amount, and the priority dates associated with particular places of use. Results, measured by flow rates at gaged stream and canal locations within the study area, suggest that the impacts of irrigation activities on the magnitude and timing of flows through this intensively managed system are well captured. The multi-year averaged diverted water from the Boise River matches observations well, reflecting the appropriation of water according to the water rights database. Because of the spatially explicit implementation of surface water diversion, the model can help diagnose places and times where water resources are likely insufficient to meet agricultural water demands, and inform future water management decisions.
Greenwood, Priscilla E
2016-01-01
This book describes a large number of open problems in the theory of stochastic neural systems, with the aim of enticing probabilists to work on them. This includes problems arising from stochastic models of individual neurons as well as those arising from stochastic models of the activities of small and large networks of interconnected neurons. The necessary neuroscience background to these problems is outlined within the text, so readers can grasp the context in which they arise. This book will be useful for graduate students and instructors providing material and references for applying probability to stochastic neuron modeling. Methods and results are presented, but the emphasis is on questions where additional stochastic analysis may contribute neuroscience insight. An extensive bibliography is included. Dr. Priscilla E. Greenwood is a Professor Emerita in the Department of Mathematics at the University of British Columbia. Dr. Lawrence M. Ward is a Professor in the Department of Psychology and the Brain...
Stochastic volatility selected readings
Shephard, Neil
2005-01-01
Neil Shephard has brought together a set of classic and central papers that have contributed to our understanding of financial volatility. They cover stocks, bonds and currencies and range from 1973 up to 2001. Shephard, a leading researcher in the field, provides a substantial introduction in which he discusses all major issues involved. General Introduction N. Shephard. Part I: Model Building. 1. A Subordinated Stochastic Process Model with Finite Variance for Speculative Prices, (P. K. Clark). 2. Financial Returns Modelled by the Product of Two Stochastic Processes: A Study of Daily Sugar Prices, 1961-7, S. J. Taylor. 3. The Behavior of Random Variables with Nonstationary Variance and the Distribution of Security Prices, B. Rosenberg. 4. The Pricing of Options on Assets with Stochastic Volatilities, J. Hull and A. White. 5. The Dynamics of Exchange Rate Volatility: A Multivariate Latent Factor ARCH Model, F. X. Diebold and M. Nerlove. 6. Multivariate Stochastic Variance Models. 7. Stochastic Autoregressive...
Stochastic Power Grid Analysis Considering Process Variations
Ghanta, Praveen; Panda, Rajendran; Wang, Janet
2011-01-01
In this paper, we investigate the impact of interconnect and device process variations on voltage fluctuations in power grids. We consider random variations in the power grid's electrical parameters as spatial stochastic processes and propose a new and efficient method to compute the stochastic voltage response of the power grid. Our approach provides an explicit analytical representation of the stochastic voltage response using orthogonal polynomials in a Hilbert space. The approach has been implemented in a prototype software called OPERA (Orthogonal Polynomial Expansions for Response Analysis). Use of OPERA on industrial power grids demonstrated speed-ups of up to two orders of magnitude. The results also show a significant variation of about $\\pm$ 35% in the nominal voltage drops at various nodes of the power grids and demonstrate the need for variation-aware power grid analysis.
Stochastic description for open quantum systems
Calzetta, E A; Verdaguer, E; Calzetta, Esteban; Roura, Albert; Verdaguer, Enric
2000-01-01
A linear open quantum system consisting of a harmonic oscillator coupled linearly to an infinite set of independent harmonic oscillators is considered; these oscillators have a general spectral density function and are initially in thermal equilibrium. Using the influence functional formalism a formal Langevin equation can be introduced to describe the system's fully quantum properties even beyond the semiclassical regime. It is shown that the reduced Wigner function for the system is exactly the formal distribution function resulting from averaging both over the initial conditions and the stochastic source of the formal Langevin equation. The master equation for the reduced density matrix is then obtained in the same way a Fokker-Planck equation can always be derived from a Langevin equation characterizing a stochastic process. We also show that the quantum correlation functions for the system can be deduced within the stochastic description provided by the Langevin equation. It is emphasized that when the s...
Algorithm refinement for stochastic partial differential equations.
Energy Technology Data Exchange (ETDEWEB)
Alexander, F. J. (Francis J.); Garcia, Alejandro L.,; Tartakovsky, D. M. (Daniel M.)
2001-01-01
A hybrid particle/continuum algorithm is formulated for Fickian diffusion in the fluctuating hydrodynamic limit. The particles are taken as independent random walkers; the fluctuating diffusion equation is solved by finite differences with deterministic and white-noise fluxes. At the interface between the particle and continuum computations the coupling is by flux matching, giving exact mass conservation. This methodology is an extension of Adaptive Mesh and Algorithm Refinement to stochastic partial differential equations. A variety of numerical experiments were performed for both steady and time-dependent scenarios. In all cases the mean and variance of density are captured correctly by the stochastic hybrid algorithm. For a non-stochastic version (i.e., using only deterministic continuum fluxes) the mean density is correct, but the variance is reduced except within the particle region, far from the interface. Extensions of the methodology to fluid mechanics applications are discussed.
Stochastic Reservoir Characterization Constrained by Seismic Data
Energy Technology Data Exchange (ETDEWEB)
Eide, Alfhild Lien
1999-07-01
In order to predict future production of oil and gas from a petroleum reservoir, it is important to have a good description of the reservoir in terms of geometry and physical parameters. This description is used as input to large numerical models for the fluid flow in the reservoir. With increased quality of seismic data, it is becoming possible to extend their use from the study of large geologic structures such as seismic horizons to characterization of the properties of the reservoir between the horizons. Uncertainties because of the low resolution of seismic data can be successfully handled by means of stochastic modeling, and spatial statistics can provide tools for interpolation and simulation of reservoir properties not completely resolved by seismic data. This thesis deals with stochastic reservoir modeling conditioned to seismic data and well data. Part I presents a new model for stochastic reservoir characterization conditioned to seismic traces. Part II deals with stochastic simulation of high resolution impedance conditioned to measured impedance. Part III develops a new stochastic model for calcite cemented objects in a sandstone background; it is a superposition of a marked point model for the calcites and a continuous model for the background.
Diomede, Tommaso; Marsigli, Chiara; Nerozzi, Fabrizio; Papetti, Paola; Paccagnella, Tiziana
2008-11-01
River hydrograph forecasts are highly sensitive to the space-time variability of the meteorological inputs, particularly in the case of watersheds characterised by a complex topography and whose hydrological processes are simulated by means of distributed rainfall-runoff models. An accurate representation of the space-time structure of the event that might occur is, therefore, essential when atmospheric and hydrological models are coupled in order to achieve successful streamflow predictions for medium-sized catchments. Even though the scale compatibility between atmospheric and hydrological models no longer seems to represent a serious problem for a direct one-way coupling, the quality and the reliability of deterministic quantitative precipitation forecasts (QPFs) are often unsatisfactory in driving hydrological models. This is because uncertainties in QPFs are, nowadays, still considerable at the scales of interest for hydrological purposes. In this work, different configurations of the non-hydrostatic meteorological model Lokal Modell (LM) have been tested for four rain events, with the aim of improving the description of the phenomena related to the precipitation. Then, LM QPFs have been coupled with the distributed rainfall-runoff model TOPKAPI, in order to assess the results in terms of discharge forecast over the Reno river basin, a medium-sized catchment in northern Italy. The coupling of atmospheric and hydrological models offers a complementary tool to evaluate the meteorological model performance. In addition, an empirical approach is proposed in order to take into account the spatial uncertainty affecting the precipitation forecast. The methodology is based on an ensemble of future rainfall scenarios, which is built by shifting in eight different directions the precipitation patterns forecasted by LM. An ensemble of discharge forecasts is then generated by feeding the hydrological model with these rain time series, thus, enabling a probabilistic
DEFF Research Database (Denmark)
Zhou, Qiang; Nielsen, Søren R.K.; Qu, Weilian
2010-01-01
Considering the coupling between the in-plane and out-of-plane vibration, the stochastic response of an inclined shallow cable with linear viscous dampers subjected to Gaussian white noise excitation is investigated in this paper. Selecting the static deflection shape due to a concentrated force ...
Stochastic and coherence resonance in an in silico neural model.
Chiu, Alan W L; Bardakjian, Berj L
2004-05-01
We show that it is possible for chaotic systems to display the main features of stochastic and coherence resonance. In particular, a model of coupled nonlinear oscillators which emulates the transmembrane voltage activities in CA3 neurons, operating in a chaotic regime and in the presence of noise, can exhibit coherence resonance and stochastic resonance. Certain firing frequencies become more "rhythmic" for some optimal values of noise intensity. The effect of noise in different coupling pathways is investigated. We found that the effect of coherence resonance and stochastic resonance are more prominent if noise is presented in either electric field or gap junction coupling pathways. Frequency sensitivity of the model is investigated as a preliminary step in illustrating the principles of possible epileptic seizure control strategies using "chaos control" concepts. Significant effects of stochastic resonance are observed in the 4-8 Hz range. Weaker effects can be found in the 1-4 Hz and 8-10 Hz ranges whereas 0.5 Hz does not exhibit any resonance phenomenon. Our results suggest that: (a) Stochastic resonance could enhance the intrinsic 4-8 Hz rhythms in CA3 neurons more prominently via field coupling pathways. It could also help explain why some reported seizure control strategies using pulse-trains would only be effective at 0.5 Hz. (b) Stochastic resonance-like behavior can occur in the gamma range only if noise is presented via chemical synaptic pathways.
Nonlinear effect of dispersal rate on spatial synchrony of predator-prey cycles.
Fox, Jeremy W; Legault, Geoffrey; Legault, Geoff; Vasseur, David A; Einarson, Jodie A
2013-01-01
Spatially-separated populations often exhibit positively correlated fluctuations in abundance and other population variables, a phenomenon known as spatial synchrony. Generation and maintenance of synchrony requires forces that rapidly restore synchrony in the face of desynchronizing forces such as demographic and environmental stochasticity. One such force is dispersal, which couples local populations together, thereby synchronizing them. Theory predicts that average spatial synchrony can be a nonlinear function of dispersal rate, but the form of the dispersal rate-synchrony relationship has never been quantified for any system. Theory also predicts that in the presence of demographic and environmental stochasticity, realized levels of synchrony can exhibit high variability around the average, so that ecologically-identical metapopulations might exhibit very different levels of synchrony. We quantified the dispersal rate-synchrony relationship using a model system of protist predator-prey cycles in pairs of laboratory microcosms linked by different rates of dispersal. Paired predator-prey cycles initially were anti-synchronous, and were subject to demographic stochasticity and spatially-uncorrelated temperature fluctuations, challenging the ability of dispersal to rapidly synchronize them. Mean synchrony of prey cycles was a nonlinear, saturating function of dispersal rate. Even extremely low rates of dispersal (systems are sufficient to generate and maintain synchrony of cyclic population dynamics, at least when environments are not too spatially heterogeneous.
Stochastic models of intracellular calcium signals
Energy Technology Data Exchange (ETDEWEB)
Rüdiger, Sten, E-mail: sten.ruediger@physik.hu-berlin.de
2014-01-10
Cellular signaling operates in a noisy environment shaped by low molecular concentrations and cellular heterogeneity. For calcium release through intracellular channels–one of the most important cellular signaling mechanisms–feedback by liberated calcium endows fluctuations with critical functions in signal generation and formation. In this review it is first described, under which general conditions the environment makes stochasticity relevant, and which conditions allow approximating or deterministic equations. This analysis provides a framework, in which one can deduce an efficient hybrid description combining stochastic and deterministic evolution laws. Within the hybrid approach, Markov chains model gating of channels, while the concentrations of calcium and calcium binding molecules (buffers) are described by reaction–diffusion equations. The article further focuses on the spatial representation of subcellular calcium domains related to intracellular calcium channels. It presents analysis for single channels and clusters of channels and reviews the effects of buffers on the calcium release. For clustered channels, we discuss the application and validity of coarse-graining as well as approaches based on continuous gating variables (Fokker–Planck and chemical Langevin equations). Comparison with recent experiments substantiates the stochastic and spatial approach, identifies minimal requirements for a realistic modeling, and facilitates an understanding of collective channel behavior. At the end of the review, implications of stochastic and local modeling for the generation and properties of cell-wide release and the integration of calcium dynamics into cellular signaling models are discussed.
Pouliot, Jacynthe; Bédard, Karine; Kirkwood, Donna; Lachance, Bernard
2008-05-01
Topological relationships between geological objects are of great interest for mining and petroleum exploration. Indeed, adjacency, inclusion and intersection are common relationships between geological objects such as faults, geological units, fractures, mineralized zones and reservoirs. However, in the context of 3D modeling, actual geometric data models used to store those objects are not designed to manage explicit topological relationships. For example, with Gocad© software, topological analyses are possible but they require a series of successive manipulations and are time consuming. This paper presents the development of a 3D topological query prototype, TQuery, compatible with Gocad© modeling platform. It allows the user to export Gocad© objects to a data storage model that regularizes the topological relationships between objects. The development of TQuery was oriented towards the use of volumetric objects that are composed of tetrahedrons. Exported data are then retrieved and used for 3D topological and spatial queries. One of the advantages of TQuery is that different types of objects can be queried at the same time without restricting the operations to voxel regions. TQuery allows the user to analyze data more quickly and efficiently and does not require a 3D modeling specialist to use it, which is particularly attractive in the context of a decision-making aid. The prototype was tested on a 3D GeoModel of a continental red-bed copper deposit in the Silurian Robitaille Formation (Transfiguration property, Québec, Canada).
Sequential stochastic optimization
Cairoli, Renzo
1996-01-01
Sequential Stochastic Optimization provides mathematicians and applied researchers with a well-developed framework in which stochastic optimization problems can be formulated and solved. Offering much material that is either new or has never before appeared in book form, it lucidly presents a unified theory of optimal stopping and optimal sequential control of stochastic processes. This book has been carefully organized so that little prior knowledge of the subject is assumed; its only prerequisites are a standard graduate course in probability theory and some familiarity with discrete-paramet
Fundamentals of Stochastic Filtering
Crisan, Dan
2008-01-01
The objective of stochastic filtering is to determine the best estimate for the state of a stochastic dynamical system from partial observations. The solution of this problem in the linear case is the well known Kalman-Bucy filter which has found widespread practical application. The purpose of this book is to provide a rigorous mathematical treatment of the non-linear stochastic filtering problem using modern methods. Particular emphasis is placed on the theoretical analysis of numerical methods for the solution of the filtering problem via particle methods. The book should provide sufficient
Zeng, Kuanhong; Wang, Denglong; She, Yanchao; Luo, Xiaoqin
2013-11-01
We study analytically the properties of the optical absorption and the spatial weak-light solitons in a quantum dot molecule system with the interdot tunneling coupling (ITC). It is shown that, for the linear case, there exists tunneling induced transparency (TIT) in the context of a weak ITC, while the TIT can be replaced by Autler-Townes splitting in the presence of a strong ITC. For the nonlinear case, it is probable to realize the spatial optical solitons even under weak light intensity. Interestingly, we find that there appears transformation behavior between the bright and dark solitons by properly turning both the ITC strength and the detuning of the probe field. Meanwhile, the transformation condition of the bright and dark solitons is obtained. Additionally it is also found that the amplitude of the solitons first descends and then rises with the increasing of ITC strength. Our results may have potential applications for nonlinear optical experiments and optical telecommunication engineering in solid systems.
Hirano, Koichi; Komiya, Zen
2008-01-01
We have succeeded in establishing a cosmological model with a non-minimally coupled scalar field $\\phi$ that can account not only for the spatial periodicity or the {\\it picket-fence structure} exhibited by the galaxy $N$-$z$ relation of the 2dF survey but also for the spatial power spectrum of the cosmic microwave background radiation (CMB) temperature anisotropy observed by the WMAP satellite. The Hubble diagram of our model also compares well with the observation of Type Ia supernovae. The scalar field of our model universe starts from an extremely small value at around the nucleosynthesis epoch, remains in that state for sufficiently long periods, allowing sufficient time for the CMB temperature anisotropy to form, and then starts to grow in magnitude at the redshift $z$ of $\\sim 1$, followed by a damping oscillation which is required to reproduce the observed picket-fence structure of the $N$-$z$ relation. To realize such behavior of the scalar field, we have found it necessary to introduce a new form of...
Restricted phase-space approximation in real-time stochastic quantization
Anzaki, Ryoji; Hidaka, Yoshimasa; Oka, Takashi
2014-01-01
We perform and extend real-time numerical simulation of a scalar quantum field theory using stochastic quantization. After a brief review of the quantization method, we calculate the propagator and the perturbative series and compare with analytical results. This is a first step toward general applications, and we focus only on the vacuum properties of the theory; this enables us to handle the boundary condition by the $i\\epsilon$ prescription. Then, we explicitly check the convergence and solve the differential equation in frequency space. For clarity we drop the spatial-derivative terms and make a comparison between our results and the numerically exact results obtained by diagonalization of the Hamiltonian. While we can control stability of the numerical simulation for any coupling strength, our results turn out to flow into an unphysical attractor if the simulation is out of the weak-coupling regime. We propose a simple truncation scheme to incorporate the interaction terms, which we name the "restricted ...
Marko, K.; Zulkarnain, F.; Kusratmoko, E.
2016-11-01
Land cover changes particular in urban catchment area has been rapidly occur. Land cover changes occur as a result of increasing demand for built-up area. Various kinds of environmental and hydrological problems e.g. floods and urban heat island can happen if the changes are uncontrolled. This study aims to predict land cover changes using coupling of Markov chains and cellular automata. One of the most rapid land cover changes is occurs at upper Ci Leungsi catchment area that located near Bekasi City and Jakarta Metropolitan Area. Markov chains has a good ability to predict the probability of change statistically while cellular automata believed as a powerful method in reading the spatial patterns of change. Temporal land cover data was obtained by remote sensing satellite imageries. In addition, this study also used multi-criteria analysis to determine which driving factor that could stimulate the changes such as proximity, elevation, and slope. Coupling of these two methods could give better prediction model rather than just using it separately. The prediction model was validated using existing 2015 land cover data and shown a satisfactory kappa coefficient. The most significant increasing land cover is built-up area from 24% to 53%.
DuRousseau, Donald R; Beeton, Theresa A
2015-09-01
Evaluating relationship intervention programs traditionally involves the use of self-report surveys or observational studies to assess changes in behavior. Instead, to investigate intervention-related changes in behavior, our study evaluates spatial-frequency electroencephalography (EEG) patterns from the brains of couples participating in an Imago Relationship workshop and 12 weeks of group counseling sessions lasting approximately 90 days. This explorative study recorded 32-channel EEGs from nine committed distressed couples prior to, during and immediately following the Imago Relationship Therapy program. A repeated measures t-Test approach was applied to investigate if significant group level brain pattern changes could be identified in key resting state networks in the brains of the participants that could be correlated with changes in relationship outcome. The study results show that significant reductions in EEG power in the alpha2, beta3 and gamma bands were evident in the averaged brain activity in the pre-frontal, frontal and temporal-parietal cortices that are anatomically associated with the frontal executive, default mode and salience networks of the human brain. Our current understanding of system level neural connectivity and network dynamics strongly indicates that each of these systems is integrally required in learning and implementing a complex communication process taught in the Imago intervention. Thus, a high degree of hemispheric lateralization is consistent with our understanding of language function and mood regulation in the brain and is consistent with recent research into the use of resting frontal EEG asymmetry as an indicator of behavioral changes in distressed couples undergoing a program for relationship improvement. Although preliminary, these results further indicate that the EEG is an inexpensive and easily quantifiable measure, and possibly predictor, of behavioral changes in response to a cognitive behavioral intervention.
Stochastic differential equations and applications
Friedman, Avner
2006-01-01
This text develops the theory of systems of stochastic differential equations, and it presents applications in probability, partial differential equations, and stochastic control problems. Originally published in two volumes, it combines a book of basic theory and selected topics with a book of applications.The first part explores Markov processes and Brownian motion; the stochastic integral and stochastic differential equations; elliptic and parabolic partial differential equations and their relations to stochastic differential equations; the Cameron-Martin-Girsanov theorem; and asymptotic es
Oceanic stochastic parametrizations in a seasonal forecast system
Andrejczuk, M; Juricke, S; Palmer, T N; Weisheimer, A; Zanna, L
2015-01-01
We study the impact of three stochastic parametrizations in the ocean component of a coupled model, on forecast reliability over seasonal timescales. The relative impacts of these schemes upon the ocean mean state and ensemble spread are analyzed. The oceanic variability induced by the atmospheric forcing of the coupled system is, in most regions, the major source of ensemble spread. The largest impact on spread and bias came from the Stochastically Perturbed Parametrization Tendency (SPPT) scheme - which has proven particularly effective in the atmosphere. The key regions affected are eddy-active regions, namely the western boundary currents and the Southern Ocean. However, unlike its impact in the atmosphere, SPPT in the ocean did not result in a significant decrease in forecast error. Whilst there are good grounds for implementing stochastic schemes in ocean models, our results suggest that they will have to be more sophisticated. Some suggestions for next-generation stochastic schemes are made.
Frédéric, Pierret
2014-01-01
The equations of celestial mechanics that govern the variation of the orbital elements are completely derived for stochastic perturbation which generalized the classic perturbation equations which are used since Gauss, starting from Newton's equation and it's solution. The six most understandable orbital element, the semi-major axis, the eccentricity, the inclination, the longitude of the ascending node, the pericenter angle and the mean motion are express in term of the angular momentum vector $\\textbf{H}$ per unit of mass and the energy $E$ per unit of mass. We differentiate those expressions using It\\^o's theory of differential equations due to the stochastic nature of the perturbing force. The result is applied to the two-body problem perturbed by a stochastic dust cloud and also perturbed by a stochastic dynamical oblateness of the central body.
Doberkat, Ernst-Erich
2009-01-01
Combining coalgebraic reasoning, stochastic systems and logic, this volume presents the principles of coalgebraic logic from a categorical perspective. Modal logics are also discussed, including probabilistic interpretations and an analysis of Kripke models.
Stochastic modelling of turbulence
DEFF Research Database (Denmark)
Sørensen, Emil Hedevang Lohse
This thesis addresses stochastic modelling of turbulence with applications to wind energy in mind. The primary tool is ambit processes, a recently developed class of computationally tractable stochastic processes based on integration with respect to Lévy bases. The subject of ambit processes...... stochastic turbulence model based on ambit processes is proposed. It is shown how a prescribed isotropic covariance structure can be reproduced. Non-Gaussian turbulence models are obtained through non-Gaussian Lévy bases or through volatility modulation of Lévy bases. As opposed to spectral models operating...... is dissipated into heat due to the internal friction caused by viscosity. An existing stochastic model, also expressed in terms of ambit processes, is extended and shown to give a universal and parsimonious description of the turbulent energy dissipation. The volatility modulation, referred to above, has...
Stochastic calculus with infinitesimals
Herzberg, Frederik
2013-01-01
Stochastic analysis is not only a thriving area of pure mathematics with intriguing connections to partial differential equations and differential geometry. It also has numerous applications in the natural and social sciences (for instance in financial mathematics or theoretical quantum mechanics) and therefore appears in physics and economics curricula as well. However, existing approaches to stochastic analysis either presuppose various concepts from measure theory and functional analysis or lack full mathematical rigour. This short book proposes to solve the dilemma: By adopting E. Nelson's "radically elementary" theory of continuous-time stochastic processes, it is based on a demonstrably consistent use of infinitesimals and thus permits a radically simplified, yet perfectly rigorous approach to stochastic calculus and its fascinating applications, some of which (notably the Black-Scholes theory of option pricing and the Feynman path integral) are also discussed in the book.
Stochastic processes inference theory
Rao, Malempati M
2014-01-01
This is the revised and enlarged 2nd edition of the authors’ original text, which was intended to be a modest complement to Grenander's fundamental memoir on stochastic processes and related inference theory. The present volume gives a substantial account of regression analysis, both for stochastic processes and measures, and includes recent material on Ridge regression with some unexpected applications, for example in econometrics. The first three chapters can be used for a quarter or semester graduate course on inference on stochastic processes. The remaining chapters provide more advanced material on stochastic analysis suitable for graduate seminars and discussions, leading to dissertation or research work. In general, the book will be of interest to researchers in probability theory, mathematical statistics and electrical and information theory.
Notes on the Stochastic Exponential and Logarithm
Larsson, Martin; Ruf, Johannes
2017-01-01
Stochastic exponentials are defined for semimartingales on stochastic intervals, and stochastic logarithms are defined for nonnegative semimartingales, up to the first time the semimartingale hits zero continuously. In the case of (nonnegative) local supermartingales, these two stochastic transformations are inverse to each other. The reciprocal of a stochastic exponential is again a stochastic exponential on a stochastic interval.
Edenhofer, Peter; Ulamec, Stephan
2015-04-01
The paper is devoted to results of doctoral research work at University of Bochum as applied to the radar transmission experiment CONSERT of the ESA cometary mission Rosetta. This research aims at achieving the limits of optimum spatial (and temporal) resolution for radar remote sensing by implementation of covariance informations concerned with error-balanced control as well as coherence of wave propagation effects through random composite media involved (based on Joel Franklin's approach of extended stochastic inversion). As a consequence the well-known inherent numerical instabilities of remote sensing are significantly reduced in a robust way by increasing the weight of main diagonal elements of the resulting composite matrix to be inverted with respect to off-diagonal elements following synergy relations as to the principle of correlation receiver in wireless telecommunications. It is shown that the enhancement of resolution for remote sensing holds for an integral and differential equation approach of inversion as well. In addition to that the paper presents a discussion on how the efficiency of inversion for radar data gets achieved by an overall optimization of inversion due to a novel neuro-genetic approach. Such kind of approach is in synergy with the priority research program "Organic Computing" of DFG / German Research Organization. This Neuro-Genetic Optimization (NGO) turns out, firstly, to take into account more detailed physical informations supporting further improved resolution such as the process of accretion for cometary nucleus, wave propagation effects from rough surfaces, ground clutter, nonlinear focusing, etc. as well as, secondly, to accelerate the computing process of inversion in a really significantly enhanced and fast way, e.g., enabling online-control of autonomous processes such as detection of unknown objects, navigation, etc. The paper describes in some detail how this neuro-genetic approach of optimization is incorporated into the
Stochastic finite element applications in rigid pavement performance
Attoh-Okine, Nii O.
1999-05-01
Rigid pavement structures have uncertainties and variability in their structural layers and components. These variations and uncertainties are seldomly included in performance assessment and evaluation in pavement systems. This paper proposes to use Stochastic Finite Element Method (SFEM) in rigid pavement faulting and load transfer efficiency. The SFEM uses random parameters, as stochastic process namely random fields. These random fields are characterized, quantitatively by spatial functions of statistical moment like the mean, variance and covariance.
Stochastic single-molecule dynamics of synaptic membrane protein domains
Kahraman, Osman; Haselwandter, Christoph A
2016-01-01
Motivated by single-molecule experiments on synaptic membrane protein domains, we use a stochastic lattice model to study protein reaction and diffusion processes in crowded membranes. We find that the stochastic reaction-diffusion dynamics of synaptic proteins provide a simple physical mechanism for collective fluctuations in synaptic domains, the molecular turnover observed at synaptic domains, key features of the single-molecule trajectories observed for synaptic proteins, and spatially inhomogeneous protein lifetimes at the cell membrane. Our results suggest that central aspects of the single-molecule and collective dynamics observed for membrane protein domains can be understood in terms of stochastic reaction-diffusion processes at the cell membrane.
Wandering bumps in stochastic neural fields
Kilpatrick, Zachary P
2012-01-01
We study the effects of noise on stationary pulse solutions (bumps) in spatially extended neural fields. The dynamics of a neural field is described by an integrodifferential equation whose integral term characterizes synaptic interactions between neurons in different spatial locations of the network. Translationally symmetric neural fields support a continuum of stationary bump solutions, which may be centered at any spatial location. Random fluctuations are introduced by modeling the system as a spatially extended Langevin equation whose noise term we take to be multiplicative or additive. For nonzero noise, these bumps are shown to wander about the domain in a purely diffusive way. We can approximate the effective diffusion coefficient using a small noise expansion. Upon breaking the (continuous) translation symmetry of the system using a spatially heterogeneous inputs or synapses, bumps in the stochastic neural field can become temporarily pinned to a finite number of locations in the network. In the case...
Geometric Stochastic Resonance
Ghosh, Pulak Kumar; Savel'ev, Sergey E; Nori, Franco
2015-01-01
A Brownian particle moving across a porous membrane subject to an oscillating force exhibits stochastic resonance with properties which strongly depend on the geometry of the confining cavities on the two sides of the membrane. Such a manifestation of stochastic resonance requires neither energetic nor entropic barriers, and can thus be regarded as a purely geometric effect. The magnitude of this effect is sensitive to the geometry of both the cavities and the pores, thus leading to distinctive optimal synchronization conditions.
Pricing Arithmetic Asian Options under Hybrid Stochastic and Local Volatility
Directory of Open Access Journals (Sweden)
Min-Ku Lee
2014-01-01
Full Text Available Recently, hybrid stochastic and local volatility models have become an industry standard for the pricing of derivatives and other problems in finance. In this study, we use a multiscale stochastic volatility model incorporated by the constant elasticity of variance to understand the price structure of continuous arithmetic average Asian options. The multiscale partial differential equation for the option price is approximated by a couple of single scale partial differential equations. In terms of the elasticity parameter governing the leverage effect, a correction to the stochastic volatility model is made for more efficient pricing and hedging of Asian options.
Work producing reservoirs: Stochastic thermodynamics with generalized Gibbs ensembles
Horowitz, Jordan M.; Esposito, Massimiliano
2016-08-01
We develop a consistent stochastic thermodynamics for environments composed of thermodynamic reservoirs in an external conservative force field, that is, environments described by the generalized or Gibbs canonical ensemble. We demonstrate that small systems weakly coupled to such reservoirs exchange both heat and work by verifying a local detailed balance relation for the induced stochastic dynamics. Based on this analysis, we help to rationalize the observation that nonthermal reservoirs can increase the efficiency of thermodynamic heat engines.
DEFF Research Database (Denmark)
Zhou, Qiang; Nielsen, Søren R.K.; Qu, Weilian
2010-01-01
at the dampers location and the first sine term as shape functions, a reduced four-degree-of-freedom system of nonlinear stochastic ordinary differential equations are derived to describe dynamic response of the cable. Since only polynomial-type terms are contained, the fourth-order cumulant-neglect closure......Considering the coupling between the in-plane and out-of-plane vibration, the stochastic response of an inclined shallow cable with linear viscous dampers subjected to Gaussian white noise excitation is investigated in this paper. Selecting the static deflection shape due to a concentrated force...
Stochastic Controls on Nitrate Transport and Cycling
Botter, G.; Settin, T.; Alessi Celegon, E.; Marani, M.; Rinaldo, A.
2005-12-01
In this paper, the impact of nutrient inputs on basin-scale nitrates losses is investigated in a probabilistic framework by means of a continuous, geomorphologically based, Montecarlo approach, which explicitly tackles the random character of the processes controlling nitrates generation, transformation and transport in river basins. This is obtained by coupling the stochastic generation of climatic and rainfall series with simplified hydrologic and biogeochemical models operating at the hillslope scale. Special attention is devoted to the spatial and temporal variability of nitrogen sources of agricultural origin and to the effect of temporally distributed rainfall fields on the ensuing nitrates leaching. The influence of random climatic variables on bio-geochemical processes affecting the nitrogen cycle in the soil-water system (e.g. plant uptake, nitrification and denitrification, mineralization), is also considered. The approach developed has been applied to a catchment located in North-Eastern Italy and is used to provide probabilistic estimates of the NO_3 load transferred downstream, which is received and accumulated in the Venice lagoon. We found that the nitrogen load introduced by fertilizations significantly affects the pdf of the nitrates content in the soil moisture, leading to prolonged risks of increased nitrates leaching from soil. The model allowed the estimation of the impact of different practices on the probabilistic structure of the basin-scale hydrologic and chemical response. As a result, the return period of the water volumes and of the nitrates loads released into the Venice lagoon has been linked directly to the ongoing climatic, pluviometric and agricultural regimes, with relevant implications for environmental planning activities aimed at achieving sustainable management practices.
da Silva, Robert L; Krumholz, Mark R
2014-01-01
The integrated light of a stellar population, measured through photometric filters that are sensitive to the presence of young stars, is often used to infer the star formation rate (SFR) for that population. However, these techniques rely on an assumption that star formation is a continuous process, whereas in reality stars form in discrete spatially- and temporally-correlated structures. This discreteness causes the light output to undergo significant time-dependent fluctuations, which, if not accounted for, introduce errors and biases in the inferred SFRs. We use SLUG (a code that Stochastically Lights Up Galaxies) to simulate galaxies undergoing stochastic star formation. We then use these simulations to present a quantitative analysis of these effects and provide tools for calculating probability distribution functions of SFRs given a set of observations. We show that, depending on the SFR tracer used, stochastic fluctuations can produce non-trivial errors at SFRs as high as 1 Msun/yr, and we suggest meth...
Suk, Heejun
2016-08-01
This paper presents a semi-analytical procedure for solving coupled the multispecies reactive solute transport equations, with a sequential first-order reaction network on spatially or temporally varying flow velocities and dispersion coefficients involving distinct retardation factors. This proposed approach was developed to overcome the limitation reported by Suk (2013) regarding the identical retardation values for all reactive species, while maintaining the extensive capability of the previous Suk method involving spatially variable or temporally variable coefficients of transport, general initial conditions, and arbitrary temporal variable inlet concentration. The proposed approach sequentially calculates the concentration distributions of each species by employing only the generalized integral transform technique (GITT). Because the proposed solutions for each species' concentration distributions have separable forms in space and time, the solution for subsequent species (daughter species) can be obtained using only the GITT without the decomposition by change-of-variables method imposing the limitation of identical retardation values for all the reactive species by directly substituting solutions for the preceding species (parent species) into the transport equation of subsequent species (daughter species). The proposed solutions were compared with previously published analytical solutions or numerical solutions of the numerical code of the Two-Dimensional Subsurface Flow, Fate and Transport of Microbes and Chemicals (2DFATMIC) in three verification examples. In these examples, the proposed solutions were well matched with previous analytical solutions and the numerical solutions obtained by 2DFATMIC model. A hypothetical single-well push-pull test example and a scale-dependent dispersion example were designed to demonstrate the practical application of the proposed solution to a real field problem.
Directory of Open Access Journals (Sweden)
Sei-Jung Lee
2017-08-01
Full Text Available An inflammatory form of phagocyte death evoked by the Gram-negative bacterium Vibrio (V. vulnificus (WT is one of hallmarks to promote their colonization, but the virulence factor and infectious mechanism involved in this process remain largely unknown. Here, we identified extracellular metalloprotease VvpM as a new virulence factor and investigated the molecular mechanism of VvpM which acts during the regulation of the inflammatory form of macrophage death and bacterial colonization. Mutation of the vvpM gene appeared to play major role in the prevention of IL-1β production due to V. vulnificus infection in macrophage. However, the recombinant protein (r VvpM caused IL-1β production coupled with necrotic cell death, which is highly susceptible to the knockdown of annexin A2 (ANXA2 located in both membrane lipid and non-lipid rafts. In lipid rafts, rVvpM recruited NOX enzymes coupled with ANXA2 to facilitate the production of ROS responsible for the epigenetic and transcriptional regulation of NF-κB in the IL-1β promoter. rVvpM acting on non-lipid rafts increased LC3 puncta formation and autophagic flux, which are required for the mRNA expression of Atg5 involved in the autophagosome formation process. The autophagy activation caused by rVvpM induced NLRP3 inflammasome-dependent caspase-1 activation in the promoting of IL-1β production. In mouse models of V. vulnificus infection, the VvpM mutant failed to elevate the level of pro-inflammatory responses closely related to IL-1β production and prevented bacterial colonization. These findings delineate VvpM efficiently regulates two pathogenic pathways that stimulate NF-κB-dependent IL-1β production and autophagy-mediated NLRP3 inflammasome via distinct spatial targeting by ANXA2.
Stacking with stochastic cooling
Energy Technology Data Exchange (ETDEWEB)
Caspers, Fritz E-mail: Fritz.Caspers@cern.ch; Moehl, Dieter
2004-10-11
Accumulation of large stacks of antiprotons or ions with the aid of stochastic cooling is more delicate than cooling a constant intensity beam. Basically the difficulty stems from the fact that the optimized gain and the cooling rate are inversely proportional to the number of particles 'seen' by the cooling system. Therefore, to maintain fast stacking, the newly injected batch has to be strongly 'protected' from the Schottky noise of the stack. Vice versa the stack has to be efficiently 'shielded' against the high gain cooling system for the injected beam. In the antiproton accumulators with stacking ratios up to 10{sup 5} the problem is solved by radial separation of the injection and the stack orbits in a region of large dispersion. An array of several tapered cooling systems with a matched gain profile provides a continuous particle flux towards the high-density stack core. Shielding of the different systems from each other is obtained both through the spatial separation and via the revolution frequencies (filters). In the 'old AA', where the antiproton collection and stacking was done in one single ring, the injected beam was further shielded during cooling by means of a movable shutter. The complexity of these systems is very high. For more modest stacking ratios, one might use azimuthal rather than radial separation of stack and injected beam. Schematically half of the circumference would be used to accept and cool new beam and the remainder to house the stack. Fast gating is then required between the high gain cooling of the injected beam and the low gain stack cooling. RF-gymnastics are used to merge the pre-cooled batch with the stack, to re-create free space for the next injection, and to capture the new batch. This scheme is less demanding for the storage ring lattice, but at the expense of some reduction in stacking rate. The talk reviews the 'radial' separation schemes and also gives some
Quantum Spontaneous Stochasticity
Eyink, Gregory L
2015-01-01
The quantum wave-function of a massive particle with small initial uncertainties (consistent with the uncertainty relation) is believed to spread very slowly, so that the dynamics is deterministic. This assumes that the classical motions for given initial data are unique. In fluid turbulence non-uniqueness due to "roughness" of the advecting velocity field is known to lead to stochastic motion of classical particles. Vanishingly small random perturbations are magnified by Richardson diffusion in a "nearly rough" velocity field so that motion remains stochastic as the noise disappears, or classical spontaneous stochasticity, . Analogies between stochastic particle motion in turbulence and quantum evolution suggest that there should be quantum spontaneous stochasticity (QSS). We show this for 1D models of a particle in a repulsive potential that is "nearly rough" with $V(x) \\sim C|x|^{1+\\alpha}$ at distances $|x|\\gg \\ell$ , for some UV cut-off $\\ell$, and for initial Gaussian wave-packet centered at 0. We consi...
Irving, J. D.; Singha, K.
2010-12-01
Traditionally, hydrological measurements have been used to estimate subsurface properties controlling groundwater flow and contaminant transport. However, such measurements are limited by their support volume and expense. A considerable benefit of geophysical measurements is that they provide a degree of spatial coverage and resolution that are unattainable with other methods, and the data can be acquired in a cost-effective manner. In particular, dynamic geophysical data allow us to indirectly observe changes in hydrological state variables as flow and transport processes occur, and can thus provide a link to hydrological properties when coupled with a process-based model. Stochastic fusion of these two data types offers the potential to provide not only estimates of subsurface hydrological properties, but also a quantification of their uncertainty. This information is critical when considering the end use of the data, which may be for groundwater remediation and management decision making. Here, we examine a number of key issues in the stochastic fusion of dynamic hydrogeophysical data. We focus our attention on the specific problem of integrating time-lapse crosshole electrical resistivity measurements and saline tracer-test concentration data in order to estimate the spatial distribution of hydraulic conductivity (K). To assimilate the geophysical and hydrological measurements in a stochastic manner, we use a Bayesian Markov-chain-Monte-Carlo (McMC) methodology. This provides multiple realizations of the subsurface K field that are consistent with the measured data and assumptions regarding model structure and data errors. To account for incomplete petrophysical knowledge, the geophysical and hydrological forward models are linked through an uncertain relationship between electrical resistivity and concentration following the general form of Archie’s law. To make the spatially distributed, fully stochastic inverse problem computationally tractable, we take
A linear thermohaline oscillator driven by stochastic atmospheric forcing
Griffies, S M; Griffies, Stephen M.; Tziperman, Eli
1995-01-01
The interdecadal variability of a stochastically forced four-box model of the oceanic meridional thermohaline circulation (THC) is described and compared to the THC variability in the coupled ocean-atmosphere GCM of Delworth, Manabe, and Stouffer (1993). The box model is placed in a linearly stable thermally dominant mean state under mixed boundary conditions. A linear stability analysis of this state reveals one damped oscillatory THC mode in addition to purely damped modes. The variability of the model under a moderate amount of stochastic forcing, meant to emulate the random variability of the atmosphere affecting the coupled model's interdecadal THC variability, is studied. A linear interpretation, in which the damped oscillatory mode is of primary importance, is sufficient for understanding the mechanism accounting for the stochastically forced variability. Direct comparison of the variability in the box model and coupled GCM reveals common qualitative aspects. Such a comparison supports, although does n...
Power, M. E.; Moreno-Mateos, D.; Uno, H.; Bode, C.; Rainey, W.
2010-12-01
Background/Question/Methods. Network configuration of river drainages affects ecological exchange between mainstem channels and smaller tributaries, and between coupled terrestrial and aquatic habitats. Seasonal complementarity of fluxes may enhance predator densities and persistence in linked habitats under continental climate regimes (Nakano and Murakami 2001). In a Mediterranean watershed (the upper South Fork Eel River of Northern California (39°44’N, 123°37’W)), we studied spatial and seasonal patterns in insect fluxes among river, wetland, and forest habitats. We quantified insect emergence with vertical traps, and lateral fluxes between six wetland and eight river reaches and the upland forest adjacent to each. Insect horizontal fluxes were sampled using sticky traps along 50-150 m transects from the moister to the dryer habitats. We also studied vertical gradients of insect fluxes over rivers (up to 7 m) and in the forest (up to 40 m). Ca. 1800 traps and 40,000 insects were quantified. Results/Conclusions. In contrast to linked forest-river ecosystems in Hokkaido, peaks of insect fluxes in aquatic versus terrestrial habitats of the Eel River basin were less offset, and the seasonality of terrestrial versus river peaks was reversed. From late April through May, when the whole landscape was moist, there was no spatial variation in insect abundance-activity along forest, wetland, or river transects, and abundances averaged 315 insects m-2d-1. As the uplands dried out, from June to September, insect abundance peaked in wetlands and near the river, but dropped in the forest to average 32 insects m-2d-1 . The wetlands, with three abundance peaks distributed through spring, summer, and fall, maintained insect fluxes when river and forest fluxes were low. Vertically arrayed sticky traps over the river documented maximal insect activity-abundance near the water surface. In some positions, movements appeared random (equal downstream and upstream fluxes), but at
Conservation of Total Vorticity for a 2D Stochastic Navier Stokes Equation
Directory of Open Access Journals (Sweden)
Peter M. Kotelenez
2011-01-01
Full Text Available We consider point vortices whose positions satisfy a stochastic ordinary differential equation on ℝ2 perturbed by spatially correlated Brownian noise. The associated signed point measure-valued empirical process turns out to be a weak solution to a stochastic Navier-Stokes equation (SNSE with a state-dependent stochastic term. As the number of vortices tends to infinity, we obtain a smooth solution to the SNSE, and we prove the conservation of total vorticity in this continuum limit.
Stochastic P systems and the simulation of biochemical processes with dynamic compartments.
Spicher, Antoine; Michel, Olivier; Cieslak, Mikolaj; Giavitto, Jean-Louis; Prusinkiewicz, Przemyslaw
2008-03-01
We introduce a sequential rewriting strategy for P systems based on Gillespie's stochastic simulation algorithm, and show that the resulting formalism of stochastic P systems makes it possible to simulate biochemical processes in dynamically changing, nested compartments. Stochastic P systems have been implemented using the spatially explicit programming language MGS. Implementation examples include models of the Lotka-Volterra auto-catalytic system, and the life cycle of the Semliki Forest virus.
Magnetohydrodynamic stability of stochastically driven accretion flows.
Nath, Sujit Kumar; Mukhopadhyay, Banibrata; Chattopadhyay, Amit K
2013-07-01
We investigate the evolution of magnetohydrodynamic (or hydromagnetic as coined by Chandrasekhar) perturbations in the presence of stochastic noise in rotating shear flows. The particular emphasis is the flows whose angular velocity decreases but specific angular momentum increases with increasing radial coordinate. Such flows, however, are Rayleigh stable but must be turbulent in order to explain astrophysical observed data and, hence, reveal a mismatch between the linear theory and observations and experiments. The mismatch seems to have been resolved, at least in certain regimes, in the presence of a weak magnetic field, revealing magnetorotational instability. The present work explores the effects of stochastic noise on such magnetohydrodynamic flows, in order to resolve the above mismatch generically for the hot flows. We essentially concentrate on a small section of such a flow which is nothing but a plane shear flow supplemented by the Coriolis effect, mimicking a small section of an astrophysical accretion disk around a compact object. It is found that such stochastically driven flows exhibit large temporal and spatial autocorrelations and cross-correlations of perturbation and, hence, large energy dissipations of perturbation, which generate instability. Interestingly, autocorrelations and cross-correlations appear independent of background angular velocity profiles, which are Rayleigh stable, indicating their universality. This work initiates our attempt to understand the evolution of three-dimensional hydromagnetic perturbations in rotating shear flows in the presence of stochastic noise.
Institute of Scientific and Technical Information of China (English)
丁锋; 汪菲菲; 汪学海
2014-01-01
For multivariate pseudo-linear regressive moving average systems,a multivariate extended stochastic gra-dient(ESG) algorithm is discussed.In order to reduce the computational cost of the identification algorithm,we de-compose a multivariate system into several subsystems,and derive a partially coupled(subsystem) ESG algorithm and a partially coupled( subsystem) multi-innovation ESG algorithm according to the coupling identification concept and the multi-innovation identification theory. Furthermore, we extend these methods to multivariate pseudo-linear autoregressive moving average systems and present a partially coupled( subsystem) generalized extended stochastic gradient ( GESG ) algorithm and a partially coupled ( subsystem ) multi-innovation GESG algorithm. The computational efficiencies of the multivariate ESG algorithm,the partially coupled ESG algorithm and the partially coupled multi-innovation ESG algorithm are analyzed.%针对多元伪线性滑动平均系统，讨论了多元增广随机梯度算法，为减小算法的计算量，将系统分解为一些子系统，给出了子系统增广随机梯度算法，利用耦合辨识概念和多新息辨识理论，推导了部分耦合（子系统）增广随机梯度算法、部分耦合（子系统）多新息增广随机梯度算法。进一步将提出的方法推广到多元伪线性自回归滑动平均系统，给出了部分耦合（子系统）广义增广随机梯度算法、部分耦合（子系统）多新息广义增广随机梯度算法。文中分析了多元增广随机梯度算法、部分耦合增广随机梯度算法、部分耦合多新息增广随机梯度算法的计算量。
Stochastic optimization methods
Marti, Kurt
2005-01-01
Optimization problems arising in practice involve random parameters. For the computation of robust optimal solutions, i.e., optimal solutions being insensitive with respect to random parameter variations, deterministic substitute problems are needed. Based on the distribution of the random data, and using decision theoretical concepts, optimization problems under stochastic uncertainty are converted into deterministic substitute problems. Due to the occurring probabilities and expectations, approximative solution techniques must be applied. Deterministic and stochastic approximation methods and their analytical properties are provided: Taylor expansion, regression and response surface methods, probability inequalities, First Order Reliability Methods, convex approximation/deterministic descent directions/efficient points, stochastic approximation methods, differentiation of probability and mean value functions. Convergence results of the resulting iterative solution procedures are given.
Stochastic dynamics and irreversibility
Tomé, Tânia
2015-01-01
This textbook presents an exposition of stochastic dynamics and irreversibility. It comprises the principles of probability theory and the stochastic dynamics in continuous spaces, described by Langevin and Fokker-Planck equations, and in discrete spaces, described by Markov chains and master equations. Special concern is given to the study of irreversibility, both in systems that evolve to equilibrium and in nonequilibrium stationary states. Attention is also given to the study of models displaying phase transitions and critical phenomema both in thermodynamic equilibrium and out of equilibrium. These models include the linear Glauber model, the Glauber-Ising model, lattice models with absorbing states such as the contact process and those used in population dynamic and spreading of epidemic, probabilistic cellular automata, reaction-diffusion processes, random sequential adsorption and dynamic percolation. A stochastic approach to chemical reaction is also presented.The textbook is intended for students of ...
Maximal stochastic transport in the Lorenz equations
Energy Technology Data Exchange (ETDEWEB)
Agarwal, Sahil, E-mail: sahil.agarwal@yale.edu [Program in Applied Mathematics, Yale University, New Haven (United States); Wettlaufer, J.S., E-mail: john.wettlaufer@yale.edu [Program in Applied Mathematics, Yale University, New Haven (United States); Departments of Geology & Geophysics, Mathematics and Physics, Yale University, New Haven (United States); Mathematical Institute, University of Oxford, Oxford (United Kingdom); Nordita, Royal Institute of Technology and Stockholm University, Stockholm (Sweden)
2016-01-08
We calculate the stochastic upper bounds for the Lorenz equations using an extension of the background method. In analogy with Rayleigh–Bénard convection the upper bounds are for heat transport versus Rayleigh number. As might be expected, the stochastic upper bounds are larger than the deterministic counterpart of Souza and Doering [1], but their variation with noise amplitude exhibits interesting behavior. Below the transition to chaotic dynamics the upper bounds increase monotonically with noise amplitude. However, in the chaotic regime this monotonicity depends on the number of realizations in the ensemble; at a particular Rayleigh number the bound may increase or decrease with noise amplitude. The origin of this behavior is the coupling between the noise and unstable periodic orbits, the degree of which depends on the degree to which the ensemble represents the ergodic set. This is confirmed by examining the close returns plots of the full solutions to the stochastic equations and the numerical convergence of the noise correlations. The numerical convergence of both the ensemble and time averages of the noise correlations is sufficiently slow that it is the limiting aspect of the realization of these bounds. Finally, we note that the full solutions of the stochastic equations demonstrate that the effect of noise is equivalent to the effect of chaos.
Hermann, Albert J.; Hinckley, Sarah; Dobbins, Elizabeth L.; Haidvogel, Dale B.; Bond, Nicholas A.; Mordy, Calvin; Kachel, Nancy; Stabeno, Phyllis J.
2009-12-01
The Coastal Gulf of Alaska (CGOA) is productive, with large populations of fish, seabirds, and marine mammals; yet it is subject to downwelling-favorable coastal winds. Downwelling regions in other parts of the world are typically much less productive than their upwelling counterparts. Alternate sources of nutrients to feed primary production in the topographically complex CGOA are poorly known and difficult to quantify. Here we diagnose the output from a spatially nested, coupled hydrodynamic and lower trophic level model of the CGOA, to quantify both horizontal and vertical nutrient fluxes into the euphotic zone. Our nested model includes both nitrogen and iron limitation of phytoplankton production, and is driven by a fine-scale atmospheric model that resolves the effects of local orography on the coastal winds. Results indicate significant "rivers" of cross-shelf nitrogen flux due to horizontal advection, as well as "fountains" of vertical transport over shallow banks due to tidal mixing. Using these results, we constructed a provisional budget of nutrient transport among subregions of the CGOA. Contrary to expectations, this budget reveals substantial upwelling of nutrients over major portions of the shelf, driven by local wind-stress curl. These effects are large enough to overwhelm the smaller downwelling flux at the coast throughout the growing season. Vertical mixing by winds and tides, and horizontal flux from the deep basin, are other substantial contributors to nutrients above the 15-m horizon. These findings help to explain the productivity of this coastal ecosystem.
Stochastic models, estimation, and control
Maybeck, Peter S
1982-01-01
This volume builds upon the foundations set in Volumes 1 and 2. Chapter 13 introduces the basic concepts of stochastic control and dynamic programming as the fundamental means of synthesizing optimal stochastic control laws.
STOCHASTIC COOLING FOR BUNCHED BEAMS.
Energy Technology Data Exchange (ETDEWEB)
BLASKIEWICZ, M.
2005-05-16
Problems associated with bunched beam stochastic cooling are reviewed. A longitudinal stochastic cooling system for RHIC is under construction and has been partially commissioned. The state of the system and future plans are discussed.
Pierret, Frédéric
2016-02-01
We derived the equations of Celestial Mechanics governing the variation of the orbital elements under a stochastic perturbation, thereby generalizing the classical Gauss equations. Explicit formulas are given for the semimajor axis, the eccentricity, the inclination, the longitude of the ascending node, the pericenter angle, and the mean anomaly, which are expressed in term of the angular momentum vector H per unit of mass and the energy E per unit of mass. Together, these formulas are called the stochastic Gauss equations, and they are illustrated numerically on an example from satellite dynamics.
Stochastic dynamics and control
Sun, Jian-Qiao; Zaslavsky, George
2006-01-01
This book is a result of many years of author's research and teaching on random vibration and control. It was used as lecture notes for a graduate course. It provides a systematic review of theory of probability, stochastic processes, and stochastic calculus. The feedback control is also reviewed in the book. Random vibration analyses of SDOF, MDOF and continuous structural systems are presented in a pedagogical order. The application of the random vibration theory to reliability and fatigue analysis is also discussed. Recent research results on fatigue analysis of non-Gaussian stress proc
Foundations of stochastic analysis
Rao, M M; Lukacs, E
1981-01-01
Foundations of Stochastic Analysis deals with the foundations of the theory of Kolmogorov and Bochner and its impact on the growth of stochastic analysis. Topics covered range from conditional expectations and probabilities to projective and direct limits, as well as martingales and likelihood ratios. Abstract martingales and their applications are also discussed. Comprised of five chapters, this volume begins with an overview of the basic Kolmogorov-Bochner theorem, followed by a discussion on conditional expectations and probabilities containing several characterizations of operators and mea
Stochastic Electrochemical Kinetics
Beruski, O
2016-01-01
A model enabling the extension of the Stochastic Simulation Algorithm to electrochemical systems is proposed. The physical justifications and constraints for the derivation of a chemical master equation are provided and discussed. The electrochemical driving forces are included in the mathematical framework, and equations are provided for the associated electric responses. The implementation for potentiostatic and galvanostatic systems is presented, with results pointing out the stochastic nature of the algorithm. The electric responses presented are in line with the expected results from the theory, providing a new tool for the modeling of electrochemical kinetics.
Markov stochasticity coordinates
Eliazar, Iddo
2017-01-01
Markov dynamics constitute one of the most fundamental models of random motion between the states of a system of interest. Markov dynamics have diverse applications in many fields of science and engineering, and are particularly applicable in the context of random motion in networks. In this paper we present a two-dimensional gauging method of the randomness of Markov dynamics. The method-termed Markov Stochasticity Coordinates-is established, discussed, and exemplified. Also, the method is tweaked to quantify the stochasticity of the first-passage-times of Markov dynamics, and the socioeconomic equality and mobility in human societies.
Markov stochasticity coordinates
Energy Technology Data Exchange (ETDEWEB)
Eliazar, Iddo, E-mail: iddo.eliazar@intel.com
2017-01-15
Markov dynamics constitute one of the most fundamental models of random motion between the states of a system of interest. Markov dynamics have diverse applications in many fields of science and engineering, and are particularly applicable in the context of random motion in networks. In this paper we present a two-dimensional gauging method of the randomness of Markov dynamics. The method–termed Markov Stochasticity Coordinates–is established, discussed, and exemplified. Also, the method is tweaked to quantify the stochasticity of the first-passage-times of Markov dynamics, and the socioeconomic equality and mobility in human societies.
Stochasticity in reproductive opportunity and the evolution of egg limitation in insects.
Rosenheim, Jay A
2011-08-01
Is reproduction by adult female insects limited by the finite time available to locate hosts (time limitation) or by the finite supply of eggs (egg limitation)? An influential model predicted that stochasticity in reproductive opportunity favors elevated fecundity, rendering egg limitation sufficiently rare that its importance would be greatly diminished. Here, I use models to explore how stochasticity shapes fecundity, the likelihood of egg limitation, and the ecological importance of egg limitation. The models make three predictions. First, whereas spatially stochastic environments favor increased fecundity, temporally stochastic environments favor increases, decreases, or intermediate maxima in fecundity, depending on egg costs. Second, even when spatially or temporally stochastic environments favor life histories with less-frequent egg limitation, stochasticity still increases the proportion of all eggs laid in the population that is laid by females destined to become egg limited. This counterintuitive result is explained by noting that stochasticity concentrates reproduction in the hands of a few females that are likely to become egg limited. Third, spatially or temporally stochastic environments amplify the constraints imposed by time and eggs on total reproduction by the population. I conclude that both egg and time constraints are fundamental in shaping insect reproductive behavior and population dynamics in stochastic environments.
Stochastic integrals: a combinatorial approach
Rota, Gian-Carlo; Wallstrom, Timothy C.
1997-01-01
A combinatorial definition of multiple stochastic integrals is given in the setting of random measures. It is shown that some properties of such stochastic integrals, formerly known to hold in special cases, are instances of combinatorial identities on the lattice of partitions of a set. The notion of stochastic sequences of binomial type is introduced as a generalization of special polynomial sequences occuring in stochastic integration, such as Hermite, Poisson–Charlier an...
Hamiltonian mechanics of stochastic acceleration.
Burby, J W; Zhmoginov, A I; Qin, H
2013-11-08
We show how to find the physical Langevin equation describing the trajectories of particles undergoing collisionless stochastic acceleration. These stochastic differential equations retain not only one-, but two-particle statistics, and inherit the Hamiltonian nature of the underlying microscopic equations. This opens the door to using stochastic variational integrators to perform simulations of stochastic interactions such as Fermi acceleration. We illustrate the theory by applying it to two example problems.
Stochastic integral equations without probability
Mikosch, T; Norvaisa, R
2000-01-01
A pathwise approach to stochastic integral equations is advocated. Linear extended Riemann-Stieltjes integral equations driven by certain stochastic processes are solved. Boundedness of the p-variation for some 0
stochastic process. Typical examples of such
Analysis of bilinear stochastic systems
Willsky, A. S.; Martin, D. N.; Marcus, S. I.
1975-01-01
Analysis of stochastic dynamical systems that involve multiplicative (bilinear) noise processes. After defining the systems of interest, consideration is given to the evolution of the moments of such systems, the question of stochastic stability, and estimation for bilinear stochastic systems. Both exact and approximate methods of analysis are introduced, and, in particular, the uses of Lie-theoretic concepts and harmonic analysis are discussed.
Delayed stochastic resonance with 1-D chain of binary elements
Ohira, Toru
2001-03-01
We discuss a simple model of 1-dimensional chain of binary stochastic elements with delayed interaction. Each element makes transitions between its two states, with probabilities which depends on the fixed-interval-past state of the preceding element in the chain. We show that rather regular spiking behavior emerges with suitably tuned parameters. This can be seen as a stochastic resonance just from noise and delay coupling alone without external oscillatory signals. This phenomena is analyzed theoretically and its applications to communication systems or biological systems are discussed. This is an extension of previous woks on delayed stochastic resonance with single[1] and two units [2]. [1] Toru Ohira and Yuzuru Sato, "Resonance with noise and delay", PRL vol 82, pp.2811-2815 (1999). [2] Toru Ohira and Yuzuru Sato, "Resonance in Delayed Stochastic Dynamics", Statistical Physics, (Tokuyama and Stanley, eds.) , AIP conference Proceedings 519, pp. 628-634 (2000).
The stochastic quality calculus
DEFF Research Database (Denmark)
Zeng, Kebin; Nielson, Flemming; Nielson, Hanne Riis
2014-01-01
We introduce the Stochastic Quality Calculus in order to model and reason about distributed processes that rely on each other in order to achieve their overall behaviour. The calculus supports broadcast communication in a truly concurrent setting. Generally distributed delays are associated...
Stochastic Control - External Models
DEFF Research Database (Denmark)
Poulsen, Niels Kjølstad
2005-01-01
This note is devoted to control of stochastic systems described in discrete time. We are concerned with external descriptions or transfer function model, where we have a dynamic model for the input output relation only (i.e.. no direct internal information). The methods are based on LTI systems...
D.F. Schrager
2006-01-01
We propose a new model for stochastic mortality. The model is based on the literature on affine term structure models. It satisfies three important requirements for application in practice: analytical tractibility, clear interpretation of the factors and compatibility with financial option pricing m
Wheeler, Tim Allan; Holder, Martin; Winner, Hermann; Kochenderfer, Mykel
2017-01-01
Accurate simulation and validation of advanced driver assistance systems requires accurate sensor models. Modeling automotive radar is complicated by effects such as multipath reflections, interference, reflective surfaces, discrete cells, and attenuation. Detailed radar simulations based on physical principles exist but are computationally intractable for realistic automotive scenes. This paper describes a methodology for the construction of stochastic automotive radar models based on deep l...
Energy Technology Data Exchange (ETDEWEB)
Tollestrup, A.V.; Dugan, G
1983-12-01
Major headings in this review include: proton sources; antiproton production; antiproton sources and Liouville, the role of the Debuncher; transverse stochastic cooling, time domain; the accumulator; frequency domain; pickups and kickers; Fokker-Planck equation; calculation of constants in the Fokker-Planck equation; and beam feedback. (GHT)
Multistage quadratic stochastic programming
Lau, Karen K.; Womersley, Robert S.
2001-04-01
Quadratic stochastic programming (QSP) in which each subproblem is a convex piecewise quadratic program with stochastic data, is a natural extension of stochastic linear programming. This allows the use of quadratic or piecewise quadratic objective functions which are essential for controlling risk in financial and project planning. Two-stage QSP is a special case of extended linear-quadratic programming (ELQP). The recourse functions in QSP are piecewise quadratic convex and Lipschitz continuous. Moreover, they have Lipschitz gradients if each QP subproblem is strictly convex and differentiable. Using these properties, a generalized Newton algorithm exhibiting global and superlinear convergence has been proposed recently for the two stage case. We extend the generalized Newton algorithm to multistage QSP and show that it is globally and finitely convergent under suitable conditions. We present numerical results on randomly generated data and modified publicly available stochastic linear programming test sets. Efficiency schemes on different scenario tree structures are discussed. The large-scale deterministic equivalent of the multistage QSP is also generated and their accuracy compared.
On a stochastic differential equation arising in a price impact model
Peter Bank; Dmitry Kramkov
2011-01-01
Comment: 20 pages. Keywords: Clark-Ocone formula, large investor, Malliavin derivative, Pareto allocation, price impact, Sobolev's embedding, stochastic differential equation; a couple of minor editorial corrections to make it identical to the paper accepted to Stochastic Processes and Their Applications
Parameter estimation in stochastic differential equations
Bishwal, Jaya P N
2008-01-01
Parameter estimation in stochastic differential equations and stochastic partial differential equations is the science, art and technology of modelling complex phenomena and making beautiful decisions. The subject has attracted researchers from several areas of mathematics and other related fields like economics and finance. This volume presents the estimation of the unknown parameters in the corresponding continuous models based on continuous and discrete observations and examines extensively maximum likelihood, minimum contrast and Bayesian methods. Useful because of the current availability of high frequency data is the study of refined asymptotic properties of several estimators when the observation time length is large and the observation time interval is small. Also space time white noise driven models, useful for spatial data, and more sophisticated non-Markovian and non-semimartingale models like fractional diffusions that model the long memory phenomena are examined in this volume.
Stochastically driven instability in rotating shear flows
Mukhopadhyay, Banibrata
2012-01-01
Origin of hydrodynamic turbulence in rotating shear flows is investigated. The particular emphasis is the flows whose angular velocity decreases but specific angular momentum increases with increasing radial coordinate. Such flows are Rayleigh stable, but must be turbulent in order to explain observed data. Such a mismatch between the linear theory and observations/experiments is more severe when any hydromagnetic/magnetohydrodynamic instability and then the corresponding turbulence therein is ruled out. The present work explores the effect of stochastic noise on such hydrodynamic flows. We essentially concentrate on a small section of such a flow which is nothing but a plane shear flow supplemented by the Coriolis effect. This also mimics a small section of an astrophysical accretion disk. It is found that such stochastically driven flows exhibit large temporal and spatial correlations of perturbation velocities, and hence large energy dissipations of perturbation, which presumably generate instability. A ra...
Stochastic discrete model of karstic networks
Jaquet, O.; Siegel, P.; Klubertanz, G.; Benabderrhamane, H.
Karst aquifers are characterised by an extreme spatial heterogeneity that strongly influences their hydraulic behaviour and the transport of pollutants. These aquifers are particularly vulnerable to contamination because of their highly permeable networks of conduits. A stochastic model is proposed for the simulation of the geometry of karstic networks at a regional scale. The model integrates the relevant physical processes governing the formation of karstic networks. The discrete simulation of karstic networks is performed with a modified lattice-gas cellular automaton for a representative description of the karstic aquifer geometry. Consequently, more reliable modelling results can be obtained for the management and the protection of karst aquifers. The stochastic model was applied jointly with groundwater modelling techniques to a regional karst aquifer in France for the purpose of resolving surface pollution issues.
Qu, Guosheng; van Nues, Rob W; Watkins, Nicholas J; Maxwell, E Stuart
2011-01-01
Box C/D ribonucleoprotein particles guide the 2'-O-ribose methylation of target nucleotides in both archaeal and eukaryotic RNAs. These complexes contain two functional centers, assembled around the C/D and C'/D' motifs in the box C/D RNA. The C/D and C'/D' RNPs of the archaeal snoRNA-like RNP (sRNP) are spatially and functionally coupled. Here, we show that similar coupling also occurs in eukaryotic box C/D snoRNPs. The C/D RNP guided 2'-O-methylation when the C'/D' motif was either mutated or ablated. In contrast, the C'/D' RNP was inactive as an independent complex. Additional experiments demonstrated that the internal C'/D' RNP is spatially coupled to the terminal box C/D complex. Pulldown experiments also indicated that all four core proteins are independently recruited to the box C/D and C'/D' motifs. Therefore, the spatial-functional coupling of box C/D and C'/D' RNPs is an evolutionarily conserved feature of both archaeal and eukaryotic box C/D RNP complexes.
Csiszar, Susan A; Diamond, Miriam L; Daggupaty, Sreerama M
2014-01-21
SO-MUM, a coupled atmospheric transport and multimedia urban model, was used to estimate spatially resolved (5 × 5 km(2)) air emissions and chemical fate based on measured air concentrations and chemical mass inventories within Toronto, Canada. Approximately 95% and 70% of Σ5PCBs (CB-28, -52, -101, -153, and -180) and Σ5PBDEs (BDE-28, -47, -100, -154, and -183) emissions of 17 (2-36) and 18 (3-42) kg y(-1), respectively, undergo atmospheric transport from the city, which is partly over Lake Ontario. The urban air plume was found to reach about 50 km for PCBs and PBDEs, in the direction of prevailing winds which is almost twice the distance of the wind-independent plume. The distance traveled by the plume is a function of prevailing wind velocity, the geographic distribution of the chemical inventory, and gas-particle partitioning. Soil wash-off of historically accumulated Σ5PCBs to surface water contributed ∼ 0.4 kg y(-1) (of mainly higher congeners) to near-shore Lake Ontario compared with volatilization of ∼ 6 kg y(-1) of mainly lighter congeners. Atmospheric emissions from primary sources followed by deposition to surface films and subsequent wash-off to surface water contributed ∼ 1 kg y(-1) and was the main route of Σ5PBDE loadings to near-shore Lake Ontario which acts as a net PBDE sink. Secondary emissions of PCBs and PBDEs from at least a ∼ 900,000 km(2) rural land area would be needed to produce the equivalent primary emissions as Toronto (∼ 640 km(2)). These results provide clear support for reducing inventories of these POPs.
National Research Council Canada - National Science Library
Bühn, Bernhard; Pimentel, Márcio M; Matteini, Massimo; Dantas, Elton L
2009-01-01
...), are widely used to decipher geological processes. A new method developed in the last couple of years, the laser ablation multi-collector inductively coupled plasma mass spectrometry (LA-MC-ICP-MS...
Limits for Stochastic Reaction Networks
DEFF Research Database (Denmark)
Cappelletti, Daniele
at a certain time are stochastically modelled by means of a continuous-time Markov chain. Our work concerns primarily stochastic reaction systems, and their asymptotic properties. In Paper I, we consider a reaction system with intermediate species, i.e. species that are produced and fast degraded along a path...... of the stochastic reaction systems. Specically, we build a theory for stochastic reaction systems that is parallel to the deciency zero theory for deterministic systems, which dates back to the 70s. A deciency theory for stochastic reaction systems was missing, and few results connecting deciency and stochastic....... Such species, in the deterministic modelling regime, assume always the same value at any positive steady state. In the stochastic setting, we prove that, if the initial condition is a point in the basin of attraction of a positive steady state of the corresponding deterministic model and tends to innity...
Stochastic processes in cell biology
Bressloff, Paul C
2014-01-01
This book develops the theory of continuous and discrete stochastic processes within the context of cell biology. A wide range of biological topics are covered including normal and anomalous diffusion in complex cellular environments, stochastic ion channels and excitable systems, stochastic calcium signaling, molecular motors, intracellular transport, signal transduction, bacterial chemotaxis, robustness in gene networks, genetic switches and oscillators, cell polarization, polymerization, cellular length control, and branching processes. The book also provides a pedagogical introduction to the theory of stochastic process – Fokker Planck equations, stochastic differential equations, master equations and jump Markov processes, diffusion approximations and the system size expansion, first passage time problems, stochastic hybrid systems, reaction-diffusion equations, exclusion processes, WKB methods, martingales and branching processes, stochastic calculus, and numerical methods. This text is primarily...
Institute of Scientific and Technical Information of China (English)
Hongheng LI; Qi L(U)
2012-01-01
The authors establish the null controllability for some systems coupled by two backward stochastic heat equations.The desired controllability result is obtained by means of proving a suitable observability estimate for the dual system of the controlled system.
Dynamic stochastic optimization
Ermoliev, Yuri; Pflug, Georg
2004-01-01
Uncertainties and changes are pervasive characteristics of modern systems involving interactions between humans, economics, nature and technology. These systems are often too complex to allow for precise evaluations and, as a result, the lack of proper management (control) may create significant risks. In order to develop robust strategies we need approaches which explic itly deal with uncertainties, risks and changing conditions. One rather general approach is to characterize (explicitly or implicitly) uncertainties by objec tive or subjective probabilities (measures of confidence or belief). This leads us to stochastic optimization problems which can rarely be solved by using the standard deterministic optimization and optimal control methods. In the stochastic optimization the accent is on problems with a large number of deci sion and random variables, and consequently the focus ofattention is directed to efficient solution procedures rather than to (analytical) closed-form solu tions. Objective an...
Directory of Open Access Journals (Sweden)
William Margulies
2004-11-01
Full Text Available In this paper, we study a specific stochastic differential equation depending on a parameter and obtain a representation of its probability density function in terms of Jacobi Functions. The equation arose in a control problem with a quadratic performance criteria. The quadratic performance is used to eliminate the control in the standard Hamilton-Jacobi variational technique. The resulting stochastic differential equation has a noise amplitude which complicates the solution. We then solve Kolmogorov's partial differential equation for the probability density function by using Jacobi Functions. A particular value of the parameter makes the solution a Martingale and in this case we prove that the solution goes to zero almost surely as time tends to infinity.
Stochastic porous media equations
Barbu, Viorel; Röckner, Michael
2016-01-01
Focusing on stochastic porous media equations, this book places an emphasis on existence theorems, asymptotic behavior and ergodic properties of the associated transition semigroup. Stochastic perturbations of the porous media equation have reviously been considered by physicists, but rigorous mathematical existence results have only recently been found. The porous media equation models a number of different physical phenomena, including the flow of an ideal gas and the diffusion of a compressible fluid through porous media, and also thermal propagation in plasma and plasma radiation. Another important application is to a model of the standard self-organized criticality process, called the "sand-pile model" or the "Bak-Tang-Wiesenfeld model". The book will be of interest to PhD students and researchers in mathematics, physics and biology.
Multistage stochastic optimization
Pflug, Georg Ch
2014-01-01
Multistage stochastic optimization problems appear in many ways in finance, insurance, energy production and trading, logistics and transportation, among other areas. They describe decision situations under uncertainty and with a longer planning horizon. This book contains a comprehensive treatment of today’s state of the art in multistage stochastic optimization. It covers the mathematical backgrounds of approximation theory as well as numerous practical algorithms and examples for the generation and handling of scenario trees. A special emphasis is put on estimation and bounding of the modeling error using novel distance concepts, on time consistency and the role of model ambiguity in the decision process. An extensive treatment of examples from electricity production, asset liability management and inventory control concludes the book
Samuelson, Paul A.
1971-01-01
Because a commodity like wheat can be carried forward from one period to the next, speculative arbitrage serves to link its prices at different points of time. Since, however, the size of the harvest depends on complicated probability processes impossible to forecast with certainty, the minimal model for understanding market behavior must involve stochastic processes. The present study, on the basis of the axiom that it is the expected rather than the known-for-certain prices which enter into all arbitrage relations and carryover decisions, determines the behavior of price as the solution to a stochastic-dynamic-programming problem. The resulting stationary time series possesses an ergodic state and normative properties like those often observed for real-world bourses. PMID:16591903
Essentials of stochastic processes
Durrett, Richard
2016-01-01
Building upon the previous editions, this textbook is a first course in stochastic processes taken by undergraduate and graduate students (MS and PhD students from math, statistics, economics, computer science, engineering, and finance departments) who have had a course in probability theory. It covers Markov chains in discrete and continuous time, Poisson processes, renewal processes, martingales, and option pricing. One can only learn a subject by seeing it in action, so there are a large number of examples and more than 300 carefully chosen exercises to deepen the reader’s understanding. Drawing from teaching experience and student feedback, there are many new examples and problems with solutions that use TI-83 to eliminate the tedious details of solving linear equations by hand, and the collection of exercises is much improved, with many more biological examples. Originally included in previous editions, material too advanced for this first course in stochastic processes has been eliminated while treatm...
Stochastic calculus and applications
Cohen, Samuel N
2015-01-01
Completely revised and greatly expanded, the new edition of this text takes readers who have been exposed to only basic courses in analysis through the modern general theory of random processes and stochastic integrals as used by systems theorists, electronic engineers and, more recently, those working in quantitative and mathematical finance. Building upon the original release of this title, this text will be of great interest to research mathematicians and graduate students working in those fields, as well as quants in the finance industry. New features of this edition include: End of chapter exercises; New chapters on basic measure theory and Backward SDEs; Reworked proofs, examples and explanatory material; Increased focus on motivating the mathematics; Extensive topical index. "Such a self-contained and complete exposition of stochastic calculus and applications fills an existing gap in the literature. The book can be recommended for first-year graduate studies. It will be useful for all who intend to wo...
Dynamics of stochastic systems
Klyatskin, Valery I
2005-01-01
Fluctuating parameters appear in a variety of physical systems and phenomena. They typically come either as random forces/sources, or advecting velocities, or media (material) parameters, like refraction index, conductivity, diffusivity, etc. The well known example of Brownian particle suspended in fluid and subjected to random molecular bombardment laid the foundation for modern stochastic calculus and statistical physics. Other important examples include turbulent transport and diffusion of particle-tracers (pollutants), or continuous densities (''''oil slicks''''), wave propagation and scattering in randomly inhomogeneous media, for instance light or sound propagating in the turbulent atmosphere.Such models naturally render to statistical description, where the input parameters and solutions are expressed by random processes and fields.The fundamental problem of stochastic dynamics is to identify the essential characteristics of system (its state and evolution), and relate those to the input parameters of ...
Stochasticity in numerical solutions of the nonlinear Schroedinger equation
Shen, Mei-Mei; Nicholson, D. R.
1987-01-01
The cubically nonlinear Schroedinger equation is an important model of nonlinear phenomena in fluids and plasmas. Numerical solutions in a spatially periodic system commonly involve truncation to a finite number of Fourier modes. These solutions are found to be stochastic in the sense that the largest Liapunov exponent is positive. As the number of modes is increased, the size of this exponent appears to converge to zero, in agreement with the recent demonstration of the integrability of the spatially periodic case.
Stochastic gravitoelectromagnetic inflation
Aguilar, J E M; Bellini, Mauricio
2006-01-01
Gravitoelectromagnetic inflation was recently introduced to describe, in an unified manner, electromagnetic, gravitatory and inflaton fields in the early (accelerated) inflationary universe from a 5D vacuum state. In this paper, we study a stochastic treatment for the gravitoelectromagnetic components $A_B=(A_{\\mu},\\phi)$, on cosmological scales. We focus our study on the seed magnetic fields on super Hubble scales, which could play an important role in large scale structure formation of the universe.
Holmes-Cerfon, Miranda
2016-11-01
We study a model of rolling particles subject to stochastic fluctuations, which may be relevant in systems of nano- or microscale particles where rolling is an approximation for strong static friction. We consider the simplest possible nontrivial system: a linear polymer of three disks constrained to remain in contact and immersed in an equilibrium heat bath so the internal angle of the polymer changes due to stochastic fluctuations. We compare two cases: one where the disks can slide relative to each other and the other where they are constrained to roll, like gears. Starting from the Langevin equations with arbitrary linear velocity constraints, we use formal homogenization theory to derive the overdamped equations that describe the process in configuration space only. The resulting dynamics have the formal structure of a Brownian motion on a Riemannian or sub-Riemannian manifold, depending on if the velocity constraints are holonomic or nonholonomic. We use this to compute the trimer's equilibrium distribution with and without the rolling constraints. Surprisingly, the two distributions are different. We suggest two possible interpretations of this result: either (i) dry friction (or other dissipative, nonequilibrium forces) changes basic thermodynamic quantities like the free energy of a system, a statement that could be tested experimentally, or (ii) as a lesson in modeling rolling or friction more generally as a velocity constraint when stochastic fluctuations are present. In the latter case, we speculate there could be a "roughness" entropy whose inclusion as an effective force could compensate the constraint and preserve classical Boltzmann statistics. Regardless of the interpretation, our calculation shows the word "rolling" must be used with care when stochastic fluctuations are present.
Identifiability in stochastic models
1992-01-01
The problem of identifiability is basic to all statistical methods and data analysis, occurring in such diverse areas as Reliability Theory, Survival Analysis, and Econometrics, where stochastic modeling is widely used. Mathematics dealing with identifiability per se is closely related to the so-called branch of ""characterization problems"" in Probability Theory. This book brings together relevant material on identifiability as it occurs in these diverse fields.
Stochastic Thermodynamics of Learning
Goldt, Sebastian; Seifert, Udo
2017-01-01
Virtually every organism gathers information about its noisy environment and builds models from those data, mostly using neural networks. Here, we use stochastic thermodynamics to analyze the learning of a classification rule by a neural network. We show that the information acquired by the network is bounded by the thermodynamic cost of learning and introduce a learning efficiency η ≤1 . We discuss the conditions for optimal learning and analyze Hebbian learning in the thermodynamic limit.
Stochastic Games. I. Foundations,
1982-04-01
stimulate discussion and critical coment. Requests for single copies of a Paper will be filled by the Cowles Foundation within the limits of the supply...underpinning for the theory of stochastic games. Section 2 is a reworking of the Bevley- Kohlberg result integrated with Shapley’s; the "black magic" of... Kohlberg : The values of the r-discount game, and the stationary optimal strategies, have Puiseaux expansions. L.. 11" 6 3. More generally, consider an
Stochastic gravitoelectromagnetic inflation
Madriz Aguilar, José Edgar; Bellini, Mauricio
2006-11-01
Gravitoelectromagnetic inflation was recently introduced to describe, in an unified manner, electromagnetic, gravitatory and inflaton fields in the early (accelerated) inflationary universe from a 5D vacuum state. In this Letter, we study a stochastic treatment for the gravitoelectromagnetic components A=(A,φ), on cosmological scales. We focus our study on the seed magnetic fields on super-Hubble scales, which could play an important role in large scale structure formation of the universe.
Stochastic power system operation
Power, Michael
2010-01-01
This paper outlines how to economically and reliably operate a power system with high levels of renewable generation which are stochastic in nature. It outlines the challenges for system operators, and suggests tools and methods for meeting this challenge, which is one of the most fundamental since large scale power networks were instituted. The Ireland power system, due to its nature and level of renewable generation, is considered as an example in this paper.
Stochastic Thermodynamics of Learning
Goldt, Sebastian
2016-01-01
Virtually every organism gathers information about its noisy environment and builds models from that data, mostly using neural networks. Here, we use stochastic thermodynamics to analyse the learning of a classification rule by a neural network. We show that the information acquired by the network is bounded by the thermodynamic cost of learning and introduce a learning efficiency $\\eta\\le1$. We discuss the conditions for optimal learning and analyse Hebbian learning in the thermodynamic limit.
Stochastic Nonlinear Aeroelasticity
2009-01-01
STOCHASTIC NONLINEAR AEROELASTICITY 5a. CONTRACT NUMBER In- house 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 0601102 6. AUTHOR(S) Philip S...ABSTRACT This report documents the culmination of in- house work in the area of uncertainty quantification and probabilistic techniques for... coff U∞ cs ea lw cw Figure 6: Wing and store geometry (left), wing box structural model (middle), flutter distribution (right
Stochastic Effects in Computational Biology of Space Radiation Cancer Risk
Cucinotta, Francis A.; Pluth, Janis; Harper, Jane; O'Neill, Peter
2007-01-01
Estimating risk from space radiation poses important questions on the radiobiology of protons and heavy ions. We are considering systems biology models to study radiation induced repair foci (RIRF) at low doses, in which less than one-track on average transverses the cell, and the subsequent DNA damage processing and signal transduction events. Computational approaches for describing protein regulatory networks coupled to DNA and oxidative damage sites include systems of differential equations, stochastic equations, and Monte-Carlo simulations. We review recent developments in the mathematical description of protein regulatory networks and possible approaches to radiation effects simulation. These include robustness, which states that regulatory networks maintain their functions against external and internal perturbations due to compensating properties of redundancy and molecular feedback controls, and modularity, which leads to general theorems for considering molecules that interact through a regulatory mechanism without exchange of matter leading to a block diagonal reduction of the connecting pathways. Identifying rate-limiting steps, robustness, and modularity in pathways perturbed by radiation damage are shown to be valid techniques for reducing large molecular systems to realistic computer simulations. Other techniques studied are the use of steady-state analysis, and the introduction of composite molecules or rate-constants to represent small collections of reactants. Applications of these techniques to describe spatial and temporal distributions of RIRF and cell populations following low dose irradiation are described.
Stochasticity Modeling in Memristors
Naous, Rawan
2015-10-26
Diverse models have been proposed over the past years to explain the exhibiting behavior of memristors, the fourth fundamental circuit element. The models varied in complexity ranging from a description of physical mechanisms to a more generalized mathematical modeling. Nonetheless, stochasticity, a widespread observed phenomenon, has been immensely overlooked from the modeling perspective. This inherent variability within the operation of the memristor is a vital feature for the integration of this nonlinear device into the stochastic electronics realm of study. In this paper, experimentally observed innate stochasticity is modeled in a circuit compatible format. The model proposed is generic and could be incorporated into variants of threshold-based memristor models in which apparent variations in the output hysteresis convey the switching threshold shift. Further application as a noise injection alternative paves the way for novel approaches in the fields of neuromorphic engineering circuits design. On the other hand, extra caution needs to be paid to variability intolerant digital designs based on non-deterministic memristor logic.
Simulation of Stochastic Partial Differential Equations and Stochastic Active Contours
Lang, Annika
2007-01-01
This thesis discusses several aspects of the simulation of stochastic partial differential equations. First, two fast algorithms for the approximation of infinite dimensional Gaussian random fields with given covariance are introduced. Later Hilbert space-valued Wiener processes are constructed out of these random fields. A short introduction to infinite-dimensional stochastic analysis and stochastic differential equations is given. Furthermore different definitions of numerical stability for...
Robust authentication through stochastic femtosecond laser filament induced scattering surfaces
Zhang, Haisu; Tzortzakis, Stelios
2016-05-01
We demonstrate a reliable authentication method by femtosecond laser filament induced scattering surfaces. The stochastic nonlinear laser fabrication nature results in unique authentication robust properties. This work provides a simple and viable solution for practical applications in product authentication, while also opens the way for incorporating such elements in transparent media and coupling those in integrated optical circuits.
Stochastic Simulation of Chemical Exchange in Two Dimensional Infrared Spectroscopy
Sanda, F; Sanda, Frantisek; Mukamel, Shaul
2006-01-01
The stochastic Liouville equations are employed to investigate the combined signatures of chemical exchange (two-state-jump) and spectral diffusion (coupling to an overdamped Brownian oscillator) in the coherent response of an anharmonic vibration to three femtosecond infrared pulses. Simulations reproduce the main features recently observed in the OD stretch of phenol in benzene.
Random Perturbation of Forward-Backward Stochastic Differential Equations
Zhang, Liangquan
2012-01-01
In this paper, we consider a kind of coupled Forward-Backward Stochastic Differential Equations (FBSDEs in short) with parameter $\\varepsilon >0.$%. We study the convergence of distributions of $(X^{\\varepsilon,t,x},Y^{\\varepsilon,t,x}),$ as $\\varepsilon \\rightarrow 0,$ and prove the Freidlin-Wentzell's large deviation principle as well.
Quattrochi, Dale A.; Estes, Maurice G., Jr.; Crosson, William; Johnson, Hoyt; Khan, Maudood
2006-01-01
with USGS lkm land use/land cover data that have traditionally been used in modeling. Air quality prediction for future scenarios to 2030 is being facilitated by land use projections using a spatial growth model. Land use projections were developed using the 2030 Regional Transportation Plan developed by the Atlanta Regional Commission, the regional planning agency for the area. This allows the Georgia Environmental Protection Division to evaluate how these transportation plans will affect future air quality. The coupled SGM and air quality modeling approach provides insight on what the impacts of Atlanta s growth will be on the local and regional environment and exists as a mechanism that can be used by policy makers to make rational decisions on urban growth and sustainability for the metropolitan area in the future.
Quattrochi, Dale A.; Estes, Maurice G., Jr.; Crosson, William; Khan, Maudood
2006-01-01
island mitigation strategies. The National Land Cover Dataset at 30m resolution is being used as the land use/land cover input and aggregated to the 4km scale for the MM5 mesoscale meteorological model and the (CMAQ) modeling schemes. Use of these data have been found to better characterize low density/suburban development as compared with USGS 1km land use/land cover data that have traditionally been used in modeling. Air quality prediction for future scenarios to 2030 is being facilitated by land use projections using a spatial growth model. Land use projections were developed using the 2030 Regional Transportation Plan developed by the Atlanta Regional Commission, the regional planning agency for the area. This allows the State Environmental Protection agency to evaluate how these transportation plans will affect future air quality. The coupled SGM and air quality modeling approach provides insight on what the impacts of Atlanta s growth will be on the local and regional environment and exists as a mechanism that can be used by policy makers to make rationale decisions on urban growth and sustainability for the metropolitan area in the future.
Numerical Methods for Stochastic Partial Differential Equations
Energy Technology Data Exchange (ETDEWEB)
Sharp, D.H.; Habib, S.; Mineev, M.B.
1999-07-08
This is the final report of a Laboratory Directed Research and Development (LDRD) project at the Los Alamos National laboratory (LANL). The objectives of this proposal were (1) the development of methods for understanding and control of spacetime discretization errors in nonlinear stochastic partial differential equations, and (2) the development of new and improved practical numerical methods for the solutions of these equations. The authors have succeeded in establishing two methods for error control: the functional Fokker-Planck equation for calculating the time discretization error and the transfer integral method for calculating the spatial discretization error. In addition they have developed a new second-order stochastic algorithm for multiplicative noise applicable to the case of colored noises, and which requires only a single random sequence generation per time step. All of these results have been verified via high-resolution numerical simulations and have been successfully applied to physical test cases. They have also made substantial progress on a longstanding problem in the dynamics of unstable fluid interfaces in porous media. This work has lead to highly accurate quasi-analytic solutions of idealized versions of this problem. These may be of use in benchmarking numerical solutions of the full stochastic PDEs that govern real-world problems.
New algorithms and new results for strong coupling LQCD
Unger, Wolfgang
2012-01-01
We present and compare new types of algorithms for lattice QCD with staggered fermions in the limit of infinite gauge coupling. These algorithms are formulated on a discrete spatial lattice but with continuous Euclidean time. They make use of the exact Hamiltonian, with the inverse temperature beta as the only input parameter. This formulation turns out to be analogous to that of a quantum spin system. The sign problem is completely absent, at zero and non-zero baryon density. We compare the performance of a continuous-time worm algorithm and of a Stochastic Series Expansion algorithm (SSE), which operates on equivalence classes of time-ordered interactions. Finally, we apply the SSE algorithm to a first exploratory study of two-flavor strong coupling lattice QCD, which is manageable in the Hamiltonian formulation because the sign problem can be controlled.
Non-Markovian Fermionic Stochastic Schr\\"{o}dinger Equation for Open System Dynamics
Shi, Wufu; Yu, Ting
2012-01-01
In this paper we present an exact Grassmann stochastic Schr\\"{o}dinger equation for the dynamics of an open fermionic quantum system coupled to a reservoir consisting of a finite or infinite number of fermions. We use this stochastic approach to derive the exact master equation for a fermionic system strongly coupled to electronic reservoirs. The generality and applicability of this Grassmann stochastic approach is justified and exemplified by several quantum open system problems concerning quantum decoherence and quantum transport for both vacuum and finite-temperature fermionic reservoirs. We show that the quantum coherence property of the quantum dot system can be profoundly modified by the environment memory.
Sun, Yongzheng; Li, Wang; Zhao, Donghua
2012-06-01
In this paper, the finite-time stochastic outer synchronization between two different complex dynamical networks with noise perturbation is investigated. By using suitable controllers, sufficient conditions for finite-time stochastic outer synchronization are derived based on the finite-time stability theory of stochastic differential equations. It is noticed that the coupling configuration matrix is not necessary to be symmetric or irreducible, and the inner coupling matrix need not be symmetric. Finally, numerical examples are examined to illustrate the effectiveness of the analytical results. The effect of control parameters on the settling time is also numerically demonstrated.
Stochastic Time-Dependent Current-Density Functional Theory
D'Agosta, Roberto
2008-03-01
Static and dynamical density functional methods have been applied with a certain degree of success to a variety of closed quantum mechanical systems, i.e., systems that can be described via a Hamiltonian dynamics. However, the relevance of open quantum systems - those coupled to external environments, e.g., baths or reservoirs - cannot be overestimated. To investigate open quantum systems with DFT methods we have introduced a new theory, we have named Stochastic Time-Dependent Current Density Functional theory (S-TDCDFT) [1]: starting from a suitable description of the system dynamics via a stochastic Schrödinger equation [2], we have proven that given an initial quantum state and the coupling between the system and the environment, there is a one-to-one correspondence between the ensemble-averaged current density and the external vector potential applied to the system.In this talk, I will introduce the stochastic formalism needed for the description of open quantum systems, discuss in details the theorem of Stochastic TD-CDFT, and provide few examples of its applicability like the dissipative dynamics of excited systems, quantum-measurement theory and other applications relevant to charge and energy transport in nanoscale systems.[1] M. Di Ventra and R. D'Agosta, Physical Review Letters 98, 226403 (2007)[2] N.G. van Kampen, Stochastic processes in Physics and Chemistry, (North Holland, 2001), 2nd ed.
Some stochastic aspects of quantization
Indian Academy of Sciences (India)
Ichiro Ohba
2002-08-01
From the advent of quantum mechanics, various types of stochastic-dynamical approach to quantum mechanics have been tried. We discuss how to utilize Nelson’s stochastic quantum mechanics to analyze the tunneling phenomena, how to derive relativistic ﬁeld equations via the Poisson process and how to describe a quantum dynamics of open systems by the use of quantum state diffusion, or the stochastic Schrödinger equation.
Stochastic Analysis of Cylindrical Shell
Directory of Open Access Journals (Sweden)
Grzywiński Maksym
2014-06-01
Full Text Available The paper deals with some chosen aspects of stochastic structural analysis and its application in the engineering practice. The main aim of the study is to apply the generalized stochastic perturbation techniques based on classical Taylor expansion with a single random variable for solution of stochastic problems in structural mechanics. The study is illustrated by numerical results concerning an industrial thin shell structure modeled as a 3-D structure.
Verification of Stochastic Process Calculi
DEFF Research Database (Denmark)
Skrypnyuk, Nataliya
Stochastic process calculi represent widely accepted formalisms within Computer Science for modelling nondeterministic stochastic systems in a compositional way. Similar to process calculi in general, they are suited for modelling systems in a hierarchical manner, by explicitly specifying...... subsystems as well as their interdependences and communication channels. Stochastic process calculi incorporate both the quantified uncertainty on probabilities or durations of events and nondeterministic choices between several possible continuations of the system behaviour. Modelling of a system is often...
Stochastic Nature in Cellular Processes
Institute of Scientific and Technical Information of China (English)
刘波; 刘圣君; 王祺; 晏世伟; 耿轶钊; SAKATA Fumihiko; GAO Xing-Fa
2011-01-01
The importance of stochasticity in cellular processes is increasingly recognized in both theoretical and experimental studies. General features of stochasticity in gene regulation and expression are briefly reviewed in this article, which include the main experimental phenomena, classification, quantization and regulation of noises. The correlation and transmission of noise in cascade networks are analyzed further and the stochastic simulation methods that can capture effects of intrinsic and extrinsic noise are described.
Kalligiannaki, Evangelia; Plechac, Petr
2012-01-01
We propose a hierarchy of multi-level kinetic Monte Carlo methods for sampling high-dimensional, stochastic lattice particle dynamics with complex interactions. The method is based on the efficient coupling of different spatial resolution levels, taking advantage of the low sampling cost in a coarse space and by developing local reconstruction strategies from coarse-grained dynamics. Microscopic reconstruction corrects possibly significant errors introduced through coarse-graining, leading to the controlled-error approximation of the sampled stochastic process. In this manner, the proposed multi-level algorithm overcomes known shortcomings of coarse-graining of particle systems with complex interactions such as combined long and short-range particle interactions and/or complex lattice geometries. Specifically, we provide error analysis for the approximation of long-time stationary dynamics in terms of relative entropy and prove that information loss in the multi-level methods is growing linearly in time, whic...
Mesoscopic Fluctuations in Stochastic Spacetime
Shiokawa, K
2000-01-01
Mesoscopic effects associated with wave propagation in spacetime with metric stochasticity are studied. We show that the scalar and spinor waves in a stochastic spacetime behave similarly to the electrons in a disordered system. Viewing this as the quantum transport problem, mesoscopic fluctuations in such a spacetime are discussed. The conductance and its fluctuations are expressed in terms of a nonlinear sigma model in the closed time path formalism. We show that the conductance fluctuations are universal, independent of the volume of the stochastic region and the amount of stochasticity.
A recurrent stochastic binary network
Institute of Scientific and Technical Information of China (English)
赵杰煜
2001-01-01
Stochastic neural networks are usually built by introducing random fluctuations into the network. A natural method is to use stochastic connections rather than stochastic activation functions. We propose a new model in which each neuron has very simple functionality but all the connections are stochastic. It is shown that the stationary distribution of the network uniquely exists and it is approximately a Boltzmann-Gibbs distribution. The relationship between the model and the Markov random field is discussed. New techniques to implement simulated annealing and Boltzmann learning are proposed. Simulation results on the graph bisection problem and image recognition show that the network is powerful enough to solve real world problems.
Postmodern string theory stochastic formulation
Aurilia, A
1994-01-01
In this paper we study the dynamics of a statistical ensemble of strings, building on a recently proposed gauge theory of the string geodesic field. We show that this stochastic approach is equivalent to the Carath\\'eodory formulation of the Nambu-Goto action, supplemented by an averaging procedure over the family of classical string world-sheets which are solutions of the equation of motion. In this new framework, the string geodesic field is reinterpreted as the Gibbs current density associated with the string statistical ensemble. Next, we show that the classical field equations derived from the string gauge action, can be obtained as the semi-classical limit of the string functional wave equation. For closed strings, the wave equation itself is completely analogous to the Wheeler-DeWitt equation used in quantum cosmology. Thus, in the string case, the wave function has support on the space of all possible spatial loop configurations. Finally, we show that the string distribution induces a multi-phase, or ...
The two-regime method for optimizing stochastic reaction-diffusion simulations
Flegg, M. B.
2011-10-19
Spatial organization and noise play an important role in molecular systems biology. In recent years, a number of software packages have been developed for stochastic spatio-temporal simulation, ranging from detailed molecular-based approaches to less detailed compartment-based simulations. Compartment-based approaches yield quick and accurate mesoscopic results, but lack the level of detail that is characteristic of the computationally intensive molecular-based models. Often microscopic detail is only required in a small region (e.g. close to the cell membrane). Currently, the best way to achieve microscopic detail is to use a resource-intensive simulation over the whole domain. We develop the two-regime method (TRM) in which a molecular-based algorithm is used where desired and a compartment-based approach is used elsewhere. We present easy-to-implement coupling conditions which ensure that the TRM results have the same accuracy as a detailed molecular-based model in the whole simulation domain. Therefore, the TRM combines strengths of previously developed stochastic reaction-diffusion software to efficiently explore the behaviour of biological models. Illustrative examples and the mathematical justification of the TRM are also presented.
Lee, Mark D.; Jenkins, Stewart D.; Ruostekoski, Janne
2016-06-01
We derive equations for the strongly coupled system of light and dense atomic ensembles. The formalism includes an arbitrary internal-level structure for the atoms and is not restricted to weak excitation of atoms by light. In the low-light-intensity limit for atoms with a single electronic ground state, the full quantum field-theoretical representation of the model can be solved exactly by means of classical stochastic electrodynamics simulations for stationary atoms that represent cold atomic ensembles. Simulations for the optical response of atoms in a quantum degenerate regime require one to synthesize a stochastic ensemble of atomic positions that generates the corresponding quantum statistical position correlations between the atoms. In the case of multiple ground levels or at light intensities where saturation becomes important, the classical simulations require approximations that neglect quantum fluctuations between the levels. We show how the model is extended to incorporate corrections due to quantum fluctuations that result from virtual scattering processes. In the low-light-intensity limit, we illustrate the simulations in a system of atoms in a Mott-insulator state in a two-dimensional optical lattice, where recurrent scattering of light induces strong interatomic correlations. These correlations result in collective many-atom subradiant and superradiant states and a strong dependence of the response on the spatial confinement within the lattice sites.
A trigonometric method for the linear stochastic wave equation
Cohen, D; Sigg, M
2012-01-01
A fully discrete approximation of the linear stochastic wave equation driven by additive noise is presented. A standard finite element method is used for the spatial discretisation and a stochastic trigonometric scheme for the temporal approximation. This explicit time integrator allows for error bounds independent of the space discretisation and thus do not have a step size restriction as in the often used St\\"ormer-Verlet-leap-frog scheme. Moreover it enjoys a trace formula as does the exact solution of our problem. These favourable properties are demonstrated with numerical experiments.
Adaptive mesh refinement for stochastic reaction-diffusion processes
Bayati, Basil; Chatelain, Philippe; Koumoutsakos, Petros
2011-01-01
We present an algorithm for adaptive mesh refinement applied to mesoscopic stochastic simulations of spatially evolving reaction-diffusion processes. The transition rates for the diffusion process are derived on adaptive, locally refined structured meshes. Convergence of the diffusion process is presented and the fluctuations of the stochastic process are verified. Furthermore, a refinement criterion is proposed for the evolution of the adaptive mesh. The method is validated in simulations of reaction-diffusion processes as described by the Fisher-Kolmogorov and Gray-Scott equations.
Stochastic evolutions of dynamic traffic flow modeling and applications
Chen, Xiqun (Michael); Shi, Qixin
2015-01-01
This book reveals the underlying mechanisms of complexity and stochastic evolutions of traffic flows. Using Eulerian and Lagrangian measurements, the authors propose lognormal headway/spacing/velocity distributions and subsequently develop a Markov car-following model to describe drivers’ random choices concerning headways/spacings, putting forward a stochastic fundamental diagram model for wide scattering flow-density points. In the context of highway onramp bottlenecks, the authors present a traffic flow breakdown probability model and spatial-temporal queuing model to improve the stability and reliability of road traffic flows. This book is intended for researchers and graduate students in the fields of transportation engineering and civil engineering.
Portfolio Optimization with Stochastic Dividends and Stochastic Volatility
Varga, Katherine Yvonne
2015-01-01
We consider an optimal investment-consumption portfolio optimization model in which an investor receives stochastic dividends. As a first problem, we allow the drift of stock price to be a bounded function. Next, we consider a stochastic volatility model. In each problem, we use the dynamic programming method to derive the Hamilton-Jacobi-Bellman…