Probability Density Estimation Using Neural Networks in Monte Carlo Calculations

International Nuclear Information System (INIS)

Shim, Hyung Jin; Cho, Jin Young; Song, Jae Seung; Kim, Chang Hyo

2008-01-01

The Monte Carlo neutronics analysis requires the capability for a tally distribution estimation like an axial power distribution or a flux gradient in a fuel rod, etc. This problem can be regarded as a probability density function estimation from an observation set. We apply the neural network based density estimation method to an observation and sampling weight set produced by the Monte Carlo calculations. The neural network method is compared with the histogram and the functional expansion tally method for estimating a non-smooth density, a fission source distribution, and an absorption rate's gradient in a burnable absorber rod. The application results shows that the neural network method can approximate a tally distribution quite well. (authors)

Information geometry of density matrices and state estimation

International Nuclear Information System (INIS)

Brody, Dorje C

2011-01-01

Given a pure state vector |x) and a density matrix ρ-hat, the function p(x|ρ-hat)= defines a probability density on the space of pure states parameterised by density matrices. The associated Fisher-Rao information measure is used to define a unitary invariant Riemannian metric on the space of density matrices. An alternative derivation of the metric, based on square-root density matrices and trace norms, is provided. This is applied to the problem of quantum-state estimation. In the simplest case of unitary parameter estimation, new higher-order corrections to the uncertainty relations, applicable to general mixed states, are derived. (fast track communication)

Comparison of volatility function technique for risk-neutral densities estimation

Science.gov (United States)

Bahaludin, Hafizah; Abdullah, Mimi Hafizah

2017-08-01

Volatility function technique by using interpolation approach plays an important role in extracting the risk-neutral density (RND) of options. The aim of this study is to compare the performances of two interpolation approaches namely smoothing spline and fourth order polynomial in extracting the RND. The implied volatility of options with respect to strike prices/delta are interpolated to obtain a well behaved density. The statistical analysis and forecast accuracy are tested using moments of distribution. The difference between the first moment of distribution and the price of underlying asset at maturity is used as an input to analyze forecast accuracy. RNDs are extracted from the Dow Jones Industrial Average (DJIA) index options with a one month constant maturity for the period from January 2011 until December 2015. The empirical results suggest that the estimation of RND using a fourth order polynomial is more appropriate to be used compared to a smoothing spline in which the fourth order polynomial gives the lowest mean square error (MSE). The results can be used to help market participants capture market expectations of the future developments of the underlying asset.

Energy vs. density on paths toward more exact density functionals.

Science.gov (United States)

Kepp, Kasper P

2018-03-14

Recently, the progression toward more exact density functional theory has been questioned, implying a need for more formal ways to systematically measure progress, i.e. a "path". Here I use the Hohenberg-Kohn theorems and the definition of normality by Burke et al. to define a path toward exactness and "straying" from the "path" by separating errors in ρ and E[ρ]. A consistent path toward exactness involves minimizing both errors. Second, a suitably diverse test set of trial densities ρ' can be used to estimate the significance of errors in ρ without knowing the exact densities which are often inaccessible. To illustrate this, the systems previously studied by Medvedev et al., the first ionization energies of atoms with Z = 1 to 10, the ionization energy of water, and the bond dissociation energies of five diatomic molecules were investigated using CCSD(T)/aug-cc-pV5Z as benchmark at chemical accuracy. Four functionals of distinct designs was used: B3LYP, PBE, M06, and S-VWN. For atomic cations regardless of charge and compactness up to Z = 10, the energy effects of the different ρ are energy-wise insignificant. An interesting oscillating behavior in the density sensitivity is observed vs. Z, explained by orbital occupation effects. Finally, it is shown that even large "normal" problems such as the Co-C bond energy of cobalamins can use simpler (e.g. PBE) trial densities to drastically speed up computation by loss of a few kJ mol -1 in accuracy. The proposed method of using a test set of trial densities to estimate the sensitivity and significance of density errors of functionals may be useful for testing and designing new balanced functionals with more systematic improvement of densities and energies.

Regularized Regression and Density Estimation based on Optimal Transport

KAUST Repository

Burger, M.

2012-03-11

The aim of this paper is to investigate a novel nonparametric approach for estimating and smoothing density functions as well as probability densities from discrete samples based on a variational regularization method with the Wasserstein metric as a data fidelity. The approach allows a unified treatment of discrete and continuous probability measures and is hence attractive for various tasks. In particular, the variational model for special regularization functionals yields a natural method for estimating densities and for preserving edges in the case of total variation regularization. In order to compute solutions of the variational problems, a regularized optimal transport problem needs to be solved, for which we discuss several formulations and provide a detailed analysis. Moreover, we compute special self-similar solutions for standard regularization functionals and we discuss several computational approaches and results. © 2012 The Author(s).

On the method of logarithmic cumulants for parametric probability density function estimation.

Science.gov (United States)

Krylov, Vladimir A; Moser, Gabriele; Serpico, Sebastiano B; Zerubia, Josiane

2013-10-01

Parameter estimation of probability density functions is one of the major steps in the area of statistical image and signal processing. In this paper we explore several properties and limitations of the recently proposed method of logarithmic cumulants (MoLC) parameter estimation approach which is an alternative to the classical maximum likelihood (ML) and method of moments (MoM) approaches. We derive the general sufficient condition for a strong consistency of the MoLC estimates which represents an important asymptotic property of any statistical estimator. This result enables the demonstration of the strong consistency of MoLC estimates for a selection of widely used distribution families originating from (but not restricted to) synthetic aperture radar image processing. We then derive the analytical conditions of applicability of MoLC to samples for the distribution families in our selection. Finally, we conduct various synthetic and real data experiments to assess the comparative properties, applicability and small sample performance of MoLC notably for the generalized gamma and K families of distributions. Supervised image classification experiments are considered for medical ultrasound and remote-sensing SAR imagery. The obtained results suggest that MoLC is a feasible and computationally fast yet not universally applicable alternative to MoM. MoLC becomes especially useful when the direct ML approach turns out to be unfeasible.

KDE-Track: An Efficient Dynamic Density Estimator for Data Streams

KAUST Repository

Qahtan, Abdulhakim Ali Ali; Wang, Suojin; Zhang, Xiangliang

2016-01-01

Recent developments in sensors, global positioning system devices and smart phones have increased the availability of spatiotemporal data streams. Developing models for mining such streams is challenged by the huge amount of data that cannot be stored in the memory, the high arrival speed and the dynamic changes in the data distribution. Density estimation is an important technique in stream mining for a wide variety of applications. The construction of kernel density estimators is well studied and documented. However, existing techniques are either expensive or inaccurate and unable to capture the changes in the data distribution. In this paper, we present a method called KDE-Track to estimate the density of spatiotemporal data streams. KDE-Track can efficiently estimate the density function with linear time complexity using interpolation on a kernel model, which is incrementally updated upon the arrival of new samples from the stream. We also propose an accurate and efficient method for selecting the bandwidth value for the kernel density estimator, which increases its accuracy significantly. Both theoretical analysis and experimental validation show that KDE-Track outperforms a set of baseline methods on the estimation accuracy and computing time of complex density structures in data streams.

KDE-Track: An Efficient Dynamic Density Estimator for Data Streams

KAUST Repository

Qahtan, Abdulhakim Ali Ali

2016-11-08

Recent developments in sensors, global positioning system devices and smart phones have increased the availability of spatiotemporal data streams. Developing models for mining such streams is challenged by the huge amount of data that cannot be stored in the memory, the high arrival speed and the dynamic changes in the data distribution. Density estimation is an important technique in stream mining for a wide variety of applications. The construction of kernel density estimators is well studied and documented. However, existing techniques are either expensive or inaccurate and unable to capture the changes in the data distribution. In this paper, we present a method called KDE-Track to estimate the density of spatiotemporal data streams. KDE-Track can efficiently estimate the density function with linear time complexity using interpolation on a kernel model, which is incrementally updated upon the arrival of new samples from the stream. We also propose an accurate and efficient method for selecting the bandwidth value for the kernel density estimator, which increases its accuracy significantly. Both theoretical analysis and experimental validation show that KDE-Track outperforms a set of baseline methods on the estimation accuracy and computing time of complex density structures in data streams.

Assessing a learning process with functional ANOVA estimators of EEG power spectral densities.

Science.gov (United States)

Gutiérrez, David; Ramírez-Moreno, Mauricio A

2016-04-01

We propose to assess the process of learning a task using electroencephalographic (EEG) measurements. In particular, we quantify changes in brain activity associated to the progression of the learning experience through the functional analysis-of-variances (FANOVA) estimators of the EEG power spectral density (PSD). Such functional estimators provide a sense of the effect of training in the EEG dynamics. For that purpose, we implemented an experiment to monitor the process of learning to type using the Colemak keyboard layout during a twelve-lessons training. Hence, our aim is to identify statistically significant changes in PSD of various EEG rhythms at different stages and difficulty levels of the learning process. Those changes are taken into account only when a probabilistic measure of the cognitive state ensures the high engagement of the volunteer to the training. Based on this, a series of statistical tests are performed in order to determine the personalized frequencies and sensors at which changes in PSD occur, then the FANOVA estimates are computed and analyzed. Our experimental results showed a significant decrease in the power of [Formula: see text] and [Formula: see text] rhythms for ten volunteers during the learning process, and such decrease happens regardless of the difficulty of the lesson. These results are in agreement with previous reports of changes in PSD being associated to feature binding and memory encoding.

A Balanced Approach to Adaptive Probability Density Estimation

Directory of Open Access Journals (Sweden)

Julio A. Kovacs

2017-04-01

Full Text Available Our development of a Fast (Mutual Information Matching (FIM of molecular dynamics time series data led us to the general problem of how to accurately estimate the probability density function of a random variable, especially in cases of very uneven samples. Here, we propose a novel Balanced Adaptive Density Estimation (BADE method that effectively optimizes the amount of smoothing at each point. To do this, BADE relies on an efficient nearest-neighbor search which results in good scaling for large data sizes. Our tests on simulated data show that BADE exhibits equal or better accuracy than existing methods, and visual tests on univariate and bivariate experimental data show that the results are also aesthetically pleasing. This is due in part to the use of a visual criterion for setting the smoothing level of the density estimate. Our results suggest that BADE offers an attractive new take on the fundamental density estimation problem in statistics. We have applied it on molecular dynamics simulations of membrane pore formation. We also expect BADE to be generally useful for low-dimensional applications in other statistical application domains such as bioinformatics, signal processing and econometrics.

A note on the conditional density estimate in single functional index model

OpenAIRE

2010-01-01

Abstract In this paper, we consider estimation of the conditional density of a scalar response variable Y given a Hilbertian random variable X when the observations are linked with a single-index structure. We establish the pointwise and the uniform almost complete convergence (with the rate) of the kernel estimate of this model. As an application, we show how our result can be applied in the prediction problem via the conditional mode estimate. Finally, the estimation of the funct...

Estimation of the four-wave mixing noise probability-density function by the multicanonical Monte Carlo method.

Science.gov (United States)

Neokosmidis, Ioannis; Kamalakis, Thomas; Chipouras, Aristides; Sphicopoulos, Thomas

2005-01-01

The performance of high-powered wavelength-division multiplexed (WDM) optical networks can be severely degraded by four-wave-mixing- (FWM-) induced distortion. The multicanonical Monte Carlo method (MCMC) is used to calculate the probability-density function (PDF) of the decision variable of a receiver, limited by FWM noise. Compared with the conventional Monte Carlo method previously used to estimate this PDF, the MCMC method is much faster and can accurately estimate smaller error probabilities. The method takes into account the correlation between the components of the FWM noise, unlike the Gaussian model, which is shown not to provide accurate results.

Urban birds in the Sonoran Desert: estimating population density from point counts

Directory of Open Access Journals (Sweden)

Karina Johnston López

2015-01-01

Full Text Available We conducted bird surveys in Hermosillo, Sonora using distance sampling to characterize detection functions at point-transects for native and non-native urban birds in a desert environment. From March to August 2013 we sampled 240 plots in the city and its surroundings; each plot was visited three times. Our purpose was to provide information for a rapid assessment of bird density in this region by using point counts. We identified 72 species, including six non-native species. Sixteen species had sufficient detections to accurately estimate the parameters of the detection functions. To illustrate the estimation of density from bird count data using our inferred detection functions, we estimated the density of the Eurasian Collared-Dove (Streptopelia decaocto under two different levels of urbanization: highly urbanized (90-100% of urban impact and moderately urbanized zones (39-50% of urban impact. Density of S. decaocto in the highly-urbanized and moderately-urbanized zones was 3.97±0.52 and 2.92±0.52 individuals/ha, respectively. By using our detection functions, avian ecologists can efficiently relocate time and effort that is regularly used for the estimation of detection distances, to increase the number of sites surveyed and to collect other relevant ecological information.

Estimating the population size and colony boundary of subterranean termites by using the density functions of directionally averaged capture probability.

Science.gov (United States)

Su, Nan-Yao; Lee, Sang-Hee

2008-04-01

Marked termites were released in a linear-connected foraging arena, and the spatial heterogeneity of their capture probabilities was averaged for both directions at distance r from release point to obtain a symmetrical distribution, from which the density function of directionally averaged capture probability P(x) was derived. We hypothesized that as marked termites move into the population and given sufficient time, the directionally averaged capture probability may reach an equilibrium P(e) over the distance r and thus satisfy the equal mixing assumption of the mark-recapture protocol. The equilibrium capture probability P(e) was used to estimate the population size N. The hypothesis was tested in a 50-m extended foraging arena to simulate the distance factor of field colonies of subterranean termites. Over the 42-d test period, the density functions of directionally averaged capture probability P(x) exhibited four phases: exponential decline phase, linear decline phase, equilibrium phase, and postequilibrium phase. The equilibrium capture probability P(e), derived as the intercept of the linear regression during the equilibrium phase, correctly projected N estimates that were not significantly different from the known number of workers in the arena. Because the area beneath the probability density function is a constant (50% in this study), preequilibrium regression parameters and P(e) were used to estimate the population boundary distance 1, which is the distance between the release point and the boundary beyond which the population is absent.

Versatile Density Functionals for Computational Surface Science

DEFF Research Database (Denmark)

Wellendorff, Jess

Density functional theory (DFT) emerged almost 50 years ago. Since then DFT has established itself as the central electronic structure methodology for simulating atomicscale systems from a few atoms to a few hundred atoms. This success of DFT is due to a very favorable accuracy-to-computational c......Density functional theory (DFT) emerged almost 50 years ago. Since then DFT has established itself as the central electronic structure methodology for simulating atomicscale systems from a few atoms to a few hundred atoms. This success of DFT is due to a very favorable accuracy...... resampling techniques, thereby systematically avoiding problems with overfitting. The first ever density functional presenting both reliable accuracy and convincing error estimation is generated. The methodology is general enough to be applied to more complex functional forms with higher-dimensional fitting...

Locality of correlation in density functional theory

Energy Technology Data Exchange (ETDEWEB)

Burke, Kieron [Department of Chemistry, University of California, Irvine, California 92697 (United States); Cancio, Antonio [Department of Physics and Astronomy, Ball State University, Muncie, Indiana 47306 (United States); Gould, Tim [Qld Micro- and Nanotechnology Centre, Griffith University, Nathan, Qld 4111 (Australia); Pittalis, Stefano [CNR-Istituto di Nanoscienze, Via Campi 213A, I-41125 Modena (Italy)

2016-08-07

The Hohenberg-Kohn density functional was long ago shown to reduce to the Thomas-Fermi (TF) approximation in the non-relativistic semiclassical (or large-Z) limit for all matter, i.e., the kinetic energy becomes local. Exchange also becomes local in this limit. Numerical data on the correlation energy of atoms support the conjecture that this is also true for correlation, but much less relevant to atoms. We illustrate how expansions around a large particle number are equivalent to local density approximations and their strong relevance to density functional approximations. Analyzing highly accurate atomic correlation energies, we show that E{sub C} → −A{sub C} ZlnZ + B{sub C}Z as Z → ∞, where Z is the atomic number, A{sub C} is known, and we estimate B{sub C} to be about 37 mhartree. The local density approximation yields A{sub C} exactly, but a very incorrect value for B{sub C}, showing that the local approximation is less relevant for the correlation alone. This limit is a benchmark for the non-empirical construction of density functional approximations. We conjecture that, beyond atoms, the leading correction to the local density approximation in the large-Z limit generally takes this form, but with B{sub C} a functional of the TF density for the system. The implications for the construction of approximate density functionals are discussed.

mBEEF-vdW: Robust fitting of error estimation density functionals

DEFF Research Database (Denmark)

Lundgård, Keld Troen; Wellendorff, Jess; Voss, Johannes

2016-01-01

. The functional is fitted within the Bayesian error estimation functional (BEEF) framework [J. Wellendorff et al., Phys. Rev. B 85, 235149 (2012); J. Wellendorff et al., J. Chem. Phys. 140, 144107 (2014)]. We improve the previously used fitting procedures by introducing a robust MM-estimator based loss function...... catalysis, including datasets that were not used for its training. Overall, we find that mBEEF-vdW has a higher general accuracy than competing popular functionals, and it is one of the best performing functionals on chemisorption systems, surface energies, lattice constants, and dispersion. We also show...

Ant-inspired density estimation via random walks.

Science.gov (United States)

Musco, Cameron; Su, Hsin-Hao; Lynch, Nancy A

2017-10-03

Many ant species use distributed population density estimation in applications ranging from quorum sensing, to task allocation, to appraisal of enemy colony strength. It has been shown that ants estimate local population density by tracking encounter rates: The higher the density, the more often the ants bump into each other. We study distributed density estimation from a theoretical perspective. We prove that a group of anonymous agents randomly walking on a grid are able to estimate their density within a small multiplicative error in few steps by measuring their rates of encounter with other agents. Despite dependencies inherent in the fact that nearby agents may collide repeatedly (and, worse, cannot recognize when this happens), our bound nearly matches what would be required to estimate density by independently sampling grid locations. From a biological perspective, our work helps shed light on how ants and other social insects can obtain relatively accurate density estimates via encounter rates. From a technical perspective, our analysis provides tools for understanding complex dependencies in the collision probabilities of multiple random walks. We bound the strength of these dependencies using local mixing properties of the underlying graph. Our results extend beyond the grid to more general graphs, and we discuss applications to size estimation for social networks, density estimation for robot swarms, and random walk-based sampling for sensor networks.

Spin theory of the density functional: reduced matrices and density functions

International Nuclear Information System (INIS)

Pavlov, R.; Delchev, Y.; Pavlova, K.; Maruani, J.

1993-01-01

Expressions for the reduced matrices and density functions of N-fermion systems of arbitrary order s (1<=s<=N) are derived within the frame of rigorous spin approach to the density functional theory (DFT). Using the local-scale transformation method and taking into account the particle spin it is shown that the reduced matrices and density functions are functionals of the total one-fermion density. Similar dependence is found for the distribution density of s-particle aggregates. Generalization and applicability of DFT to the case of s-particle ensembles and aggregates is discussed. 14 refs

The Visualization and Analysis of POI Features under Network Space Supported by Kernel Density Estimation

Directory of Open Access Journals (Sweden)

YU Wenhao

2015-01-01

Full Text Available The distribution pattern and the distribution density of urban facility POIs are of great significance in the fields of infrastructure planning and urban spatial analysis. The kernel density estimation, which has been usually utilized for expressing these spatial characteristics, is superior to other density estimation methods (such as Quadrat analysis, Voronoi-based method, for that the Kernel density estimation considers the regional impact based on the first law of geography. However, the traditional kernel density estimation is mainly based on the Euclidean space, ignoring the fact that the service function and interrelation of urban feasibilities is carried out on the network path distance, neither than conventional Euclidean distance. Hence, this research proposed a computational model of network kernel density estimation, and the extension type of model in the case of adding constraints. This work also discussed the impacts of distance attenuation threshold and height extreme to the representation of kernel density. The large-scale actual data experiment for analyzing the different POIs' distribution patterns (random type, sparse type, regional-intensive type, linear-intensive type discusses the POI infrastructure in the city on the spatial distribution of characteristics, influence factors, and service functions.

Variable Kernel Density Estimation

OpenAIRE

Terrell, George R.; Scott, David W.

1992-01-01

We investigate some of the possibilities for improvement of univariate and multivariate kernel density estimates by varying the window over the domain of estimation, pointwise and globally. Two general approaches are to vary the window width by the point of estimation and by point of the sample observation. The first possibility is shown to be of little efficacy in one variable. In particular, nearest-neighbor estimators in all versions perform poorly in one and two dimensions, but begin to b...

Kernel and wavelet density estimators on manifolds and more general metric spaces

DEFF Research Database (Denmark)

Cleanthous, G.; Georgiadis, Athanasios; Kerkyacharian, G.

We consider the problem of estimating the density of observations taking values in classical or nonclassical spaces such as manifolds and more general metric spaces. Our setting is quite general but also sufficiently rich in allowing the development of smooth functional calculus with well localized...... spectral kernels, Besov regularity spaces, and wavelet type systems. Kernel and both linear and nonlinear wavelet density estimators are introduced and studied. Convergence rates for these estimators are established, which are analogous to the existing results in the classical setting of real...

Density Estimation in Several Populations With Uncertain Population Membership

KAUST Repository

Ma, Yanyuan

2011-09-01

We devise methods to estimate probability density functions of several populations using observations with uncertain population membership, meaning from which population an observation comes is unknown. The probability of an observation being sampled from any given population can be calculated. We develop general estimation procedures and bandwidth selection methods for our setting. We establish large-sample properties and study finite-sample performance using simulation studies. We illustrate our methods with data from a nutrition study.

Intrinsic-density functionals

International Nuclear Information System (INIS)

Engel, J.

2007-01-01

The Hohenberg-Kohn theorem and Kohn-Sham procedure are extended to functionals of the localized intrinsic density of a self-bound system such as a nucleus. After defining the intrinsic-density functional, we modify the usual Kohn-Sham procedure slightly to evaluate the mean-field approximation to the functional, and carefully describe the construction of the leading corrections for a system of fermions in one dimension with a spin-degeneracy equal to the number of particles N. Despite the fact that the corrections are complicated and nonlocal, we are able to construct a local Skyrme-like intrinsic-density functional that, while different from the exact functional, shares with it a minimum value equal to the exact ground-state energy at the exact ground-state intrinsic density, to next-to-leading order in 1/N. We briefly discuss implications for real Skyrme functionals

Effects of stand density on top height estimation for ponderosa pine

Science.gov (United States)

Martin Ritchie; Jianwei Zhang; Todd Hamilton

2012-01-01

Site index, estimated as a function of dominant-tree height and age, is often used as an expression of site quality. This expression is assumed to be effectively independent of stand density. Observation of dominant height at two different ponderosa pine levels-of-growing-stock studies revealed that top height stability with respect to stand density depends on the...

An Efficient Acoustic Density Estimation Method with Human Detectors Applied to Gibbons in Cambodia.

Directory of Open Access Journals (Sweden)

Darren Kidney

Full Text Available Some animal species are hard to see but easy to hear. Standard visual methods for estimating population density for such species are often ineffective or inefficient, but methods based on passive acoustics show more promise. We develop spatially explicit capture-recapture (SECR methods for territorial vocalising species, in which humans act as an acoustic detector array. We use SECR and estimated bearing data from a single-occasion acoustic survey of a gibbon population in northeastern Cambodia to estimate the density of calling groups. The properties of the estimator are assessed using a simulation study, in which a variety of survey designs are also investigated. We then present a new form of the SECR likelihood for multi-occasion data which accounts for the stochastic availability of animals. In the context of gibbon surveys this allows model-based estimation of the proportion of groups that produce territorial vocalisations on a given day, thereby enabling the density of groups, instead of the density of calling groups, to be estimated. We illustrate the performance of this new estimator by simulation. We show that it is possible to estimate density reliably from human acoustic detections of visually cryptic species using SECR methods. For gibbon surveys we also show that incorporating observers' estimates of bearings to detected groups substantially improves estimator performance. Using the new form of the SECR likelihood we demonstrate that estimates of availability, in addition to population density and detection function parameters, can be obtained from multi-occasion data, and that the detection function parameters are not confounded with the availability parameter. This acoustic SECR method provides a means of obtaining reliable density estimates for territorial vocalising species. It is also efficient in terms of data requirements since since it only requires routine survey data. We anticipate that the low-tech field requirements will

Toward accurate and precise estimates of lion density.

Science.gov (United States)

Elliot, Nicholas B; Gopalaswamy, Arjun M

2017-08-01

Reliable estimates of animal density are fundamental to understanding ecological processes and population dynamics. Furthermore, their accuracy is vital to conservation because wildlife authorities rely on estimates to make decisions. However, it is notoriously difficult to accurately estimate density for wide-ranging carnivores that occur at low densities. In recent years, significant progress has been made in density estimation of Asian carnivores, but the methods have not been widely adapted to African carnivores, such as lions (Panthera leo). Although abundance indices for lions may produce poor inferences, they continue to be used to estimate density and inform management and policy. We used sighting data from a 3-month survey and adapted a Bayesian spatially explicit capture-recapture (SECR) model to estimate spatial lion density in the Maasai Mara National Reserve and surrounding conservancies in Kenya. Our unstructured spatial capture-recapture sampling design incorporated search effort to explicitly estimate detection probability and density on a fine spatial scale, making our approach robust in the context of varying detection probabilities. Overall posterior mean lion density was estimated to be 17.08 (posterior SD 1.310) lions >1 year old/100 km 2 , and the sex ratio was estimated at 2.2 females to 1 male. Our modeling framework and narrow posterior SD demonstrate that SECR methods can produce statistically rigorous and precise estimates of population parameters, and we argue that they should be favored over less reliable abundance indices. Furthermore, our approach is flexible enough to incorporate different data types, which enables robust population estimates over relatively short survey periods in a variety of systems. Trend analyses are essential to guide conservation decisions but are frequently based on surveys of differing reliability. We therefore call for a unified framework to assess lion numbers in key populations to improve management and

Construction of New Electronic Density Functionals with Error Estimation Through Fitting

DEFF Research Database (Denmark)

Petzold, V.; Bligaard, T.; Jacobsen, K. W.

2012-01-01

We investigate the possibilities and limitations for the development of new electronic density functionals through large-scale fitting to databases of binding energies obtained experimentally or through high-quality calculations. We show that databases with up to a few hundred entries allow for u...

Estimation of probability density functions of damage parameter for valve leakage detection in reciprocating pump used in nuclear power plants

Energy Technology Data Exchange (ETDEWEB)

Lee, Jong Kyeom; Kim, Tae Yun; Kim, Hyun Su; Chai, Jang Bom; Lee, Jin Woo [Div. of Mechanical Engineering, Ajou University, Suwon (Korea, Republic of)

2016-10-15

This paper presents an advanced estimation method for obtaining the probability density functions of a damage parameter for valve leakage detection in a reciprocating pump. The estimation method is based on a comparison of model data which are simulated by using a mathematical model, and experimental data which are measured on the inside and outside of the reciprocating pump in operation. The mathematical model, which is simplified and extended on the basis of previous models, describes not only the normal state of the pump, but also its abnormal state caused by valve leakage. The pressure in the cylinder is expressed as a function of the crankshaft angle, and an additional volume flow rate due to the valve leakage is quantified by a damage parameter in the mathematical model. The change in the cylinder pressure profiles due to the suction valve leakage is noticeable in the compression and expansion modes of the pump. The damage parameter value over 300 cycles is calculated in two ways, considering advance or delay in the opening and closing angles of the discharge valves. The probability density functions of the damage parameter are compared for diagnosis and prognosis on the basis of the probabilistic features of valve leakage.

Estimation of probability density functions of damage parameter for valve leakage detection in reciprocating pump used in nuclear power plants

International Nuclear Information System (INIS)

Lee, Jong Kyeom; Kim, Tae Yun; Kim, Hyun Su; Chai, Jang Bom; Lee, Jin Woo

2016-01-01

This paper presents an advanced estimation method for obtaining the probability density functions of a damage parameter for valve leakage detection in a reciprocating pump. The estimation method is based on a comparison of model data which are simulated by using a mathematical model, and experimental data which are measured on the inside and outside of the reciprocating pump in operation. The mathematical model, which is simplified and extended on the basis of previous models, describes not only the normal state of the pump, but also its abnormal state caused by valve leakage. The pressure in the cylinder is expressed as a function of the crankshaft angle, and an additional volume flow rate due to the valve leakage is quantified by a damage parameter in the mathematical model. The change in the cylinder pressure profiles due to the suction valve leakage is noticeable in the compression and expansion modes of the pump. The damage parameter value over 300 cycles is calculated in two ways, considering advance or delay in the opening and closing angles of the discharge valves. The probability density functions of the damage parameter are compared for diagnosis and prognosis on the basis of the probabilistic features of valve leakage

Estimation of Probability Density Functions of Damage Parameter for Valve Leakage Detection in Reciprocating Pump Used in Nuclear Power Plants

Directory of Open Access Journals (Sweden)

Jong Kyeom Lee

2016-10-01

Full Text Available This paper presents an advanced estimation method for obtaining the probability density functions of a damage parameter for valve leakage detection in a reciprocating pump. The estimation method is based on a comparison of model data which are simulated by using a mathematical model, and experimental data which are measured on the inside and outside of the reciprocating pump in operation. The mathematical model, which is simplified and extended on the basis of previous models, describes not only the normal state of the pump, but also its abnormal state caused by valve leakage. The pressure in the cylinder is expressed as a function of the crankshaft angle, and an additional volume flow rate due to the valve leakage is quantified by a damage parameter in the mathematical model. The change in the cylinder pressure profiles due to the suction valve leakage is noticeable in the compression and expansion modes of the pump. The damage parameter value over 300 cycles is calculated in two ways, considering advance or delay in the opening and closing angles of the discharge valves. The probability density functions of the damage parameter are compared for diagnosis and prognosis on the basis of the probabilistic features of valve leakage.

A new approach for estimating the density of liquids.

Science.gov (United States)

Sakagami, T; Fuchizaki, K; Ohara, K

2016-10-05

We propose a novel approach with which to estimate the density of liquids. The approach is based on the assumption that the systems would be structurally similar when viewed at around the length scale (inverse wavenumber) of the first peak of the structure factor, unless their thermodynamic states differ significantly. The assumption was implemented via a similarity transformation to the radial distribution function to extract the density from the structure factor of a reference state with a known density. The method was first tested using two model liquids, and could predict the densities within an error of several percent unless the state in question differed significantly from the reference state. The method was then applied to related real liquids, and satisfactory results were obtained for predicted densities. The possibility of applying the method to amorphous materials is discussed.

Network Kernel Density Estimation for the Analysis of Facility POI Hotspots

Directory of Open Access Journals (Sweden)

YU Wenhao

2015-12-01

Full Text Available The distribution pattern of urban facility POIs (points of interest usually forms clusters (i.e. "hotspots" in urban geographic space. To detect such type of hotspot, the methods mostly employ spatial density estimation based on Euclidean distance, ignoring the fact that the service function and interrelation of urban feasibilities is carried out on the network path distance, neither than conventional Euclidean distance. By using these methods, it is difficult to exactly and objectively delimitate the shape and the size of hotspot. Therefore, this research adopts the kernel density estimation based on the network distance to compute the density of hotspot and proposes a simple and efficient algorithm. The algorithm extends the 2D dilation operator to the 1D morphological operator, thus computing the density of network unit. Through evaluation experiment, it is suggested that the algorithm is more efficient and scalable than the existing algorithms. Based on the case study on real POI data, the range of hotspot can highlight the spatial characteristic of urban functions along traffic routes, in order to provide valuable spatial knowledge and information services for the applications of region planning, navigation and geographic information inquiring.

The problem of the universal density functional and the density matrix functional theory

International Nuclear Information System (INIS)

Bobrov, V. B.; Trigger, S. A.

2013-01-01

The analysis in this paper shows that the Hohenberg-Kohn theorem is the constellation of two statements: (i) the mathematically rigorous Hohenberg-Kohn lemma, which demonstrates that the same ground-state density cannot correspond to two different potentials of an external field, and (ii) the hypothesis of the existence of the universal density functional. Based on the obtained explicit expression for the nonrel-ativistic particle energy in a local external field, we prove that the energy of the system of more than two non-interacting electrons cannot be a functional of the inhomogeneous density. This result is generalized to the system of interacting electrons. It means that the Hohenberg-Kohn lemma cannot provide justification of the universal density functional for fermions. At the same time, statements of the density functional theory remain valid when considering any number of noninteracting ground-state bosons due to the Bose condensation effect. In the framework of the density matrix functional theory, the hypothesis of the existence of the universal density matrix functional corresponds to the cases of noninteracting particles and to interaction in the Hartree-Fock approximation.

Robust functional statistics applied to Probability Density Function shape screening of sEMG data.

Science.gov (United States)

Boudaoud, S; Rix, H; Al Harrach, M; Marin, F

2014-01-01

Recent studies pointed out possible shape modifications of the Probability Density Function (PDF) of surface electromyographical (sEMG) data according to several contexts like fatigue and muscle force increase. Following this idea, criteria have been proposed to monitor these shape modifications mainly using High Order Statistics (HOS) parameters like skewness and kurtosis. In experimental conditions, these parameters are confronted with small sample size in the estimation process. This small sample size induces errors in the estimated HOS parameters restraining real-time and precise sEMG PDF shape monitoring. Recently, a functional formalism, the Core Shape Model (CSM), has been used to analyse shape modifications of PDF curves. In this work, taking inspiration from CSM method, robust functional statistics are proposed to emulate both skewness and kurtosis behaviors. These functional statistics combine both kernel density estimation and PDF shape distances to evaluate shape modifications even in presence of small sample size. Then, the proposed statistics are tested, using Monte Carlo simulations, on both normal and Log-normal PDFs that mimic observed sEMG PDF shape behavior during muscle contraction. According to the obtained results, the functional statistics seem to be more robust than HOS parameters to small sample size effect and more accurate in sEMG PDF shape screening applications.

Change-in-ratio density estimator for feral pigs is less biased than closed mark-recapture estimates

Science.gov (United States)

Hanson, L.B.; Grand, J.B.; Mitchell, M.S.; Jolley, D.B.; Sparklin, B.D.; Ditchkoff, S.S.

2008-01-01

Closed-population capture-mark-recapture (CMR) methods can produce biased density estimates for species with low or heterogeneous detection probabilities. In an attempt to address such biases, we developed a density-estimation method based on the change in ratio (CIR) of survival between two populations where survival, calculated using an open-population CMR model, is known to differ. We used our method to estimate density for a feral pig (Sus scrofa) population on Fort Benning, Georgia, USA. To assess its validity, we compared it to an estimate of the minimum density of pigs known to be alive and two estimates based on closed-population CMR models. Comparison of the density estimates revealed that the CIR estimator produced a density estimate with low precision that was reasonable with respect to minimum known density. By contrast, density point estimates using the closed-population CMR models were less than the minimum known density, consistent with biases created by low and heterogeneous capture probabilities for species like feral pigs that may occur in low density or are difficult to capture. Our CIR density estimator may be useful for tracking broad-scale, long-term changes in species, such as large cats, for which closed CMR models are unlikely to work. ?? CSIRO 2008.

Spin-Density Functionals from Current-Density Functional Theory and Vice Versa: A Road towards New Approximations

International Nuclear Information System (INIS)

Capelle, K.; Gross, E.

1997-01-01

It is shown that the exchange-correlation functional of spin-density functional theory is identical, on a certain set of densities, with the exchange-correlation functional of current-density functional theory. This rigorous connection is used to construct new approximations of the exchange-correlation functionals. These include a conceptually new generalized-gradient spin-density functional and a nonlocal current-density functional. copyright 1997 The American Physical Society

Laboratory Density Functionals

OpenAIRE

Giraud, B. G.

2007-01-01

We compare several definitions of the density of a self-bound system, such as a nucleus, in relation with its center-of-mass zero-point motion. A trivial deconvolution relates the internal density to the density defined in the laboratory frame. This result is useful for the practical definition of density functionals.

Optimization of Barron density estimates

Czech Academy of Sciences Publication Activity Database

Vajda, Igor; van der Meulen, E. C.

2001-01-01

Roč. 47, č. 5 (2001), s. 1867-1883 ISSN 0018-9448 R&D Projects: GA ČR GA102/99/1137 Grant - others:Copernicus(XE) 579 Institutional research plan: AV0Z1075907 Keywords : Barron estimator * chi-square criterion * density estimation Subject RIV: BD - Theory of Information Impact factor: 2.077, year: 2001

Technical Note: Cortical thickness and density estimation from clinical CT using a prior thickness-density relationship

Energy Technology Data Exchange (ETDEWEB)

Humbert, Ludovic, E-mail: ludohumberto@gmail.com [Galgo Medical, Barcelona 08036 (Spain); Hazrati Marangalou, Javad; Rietbergen, Bert van [Orthopaedic Biomechanics, Department of Biomedical Engineering, Eindhoven University of Technology, Eindhoven 5600 MB (Netherlands); Río Barquero, Luis Miguel del [CETIR Centre Medic, Barcelona 08029 (Spain); Lenthe, G. Harry van [Biomechanics Section, KU Leuven–University of Leuven, Leuven 3001 (Belgium)

2016-04-15

Purpose: Cortical thickness and density are critical components in determining the strength of bony structures. Computed tomography (CT) is one possible modality for analyzing the cortex in 3D. In this paper, a model-based approach for measuring the cortical bone thickness and density from clinical CT images is proposed. Methods: Density variations across the cortex were modeled as a function of the cortical thickness and density, location of the cortex, density of surrounding tissues, and imaging blur. High resolution micro-CT data of cadaver proximal femurs were analyzed to determine a relationship between cortical thickness and density. This thickness-density relationship was used as prior information to be incorporated in the model to obtain accurate measurements of cortical thickness and density from clinical CT volumes. The method was validated using micro-CT scans of 23 cadaver proximal femurs. Simulated clinical CT images with different voxel sizes were generated from the micro-CT data. Cortical thickness and density were estimated from the simulated images using the proposed method and compared with measurements obtained using the micro-CT images to evaluate the effect of voxel size on the accuracy of the method. Then, 19 of the 23 specimens were imaged using a clinical CT scanner. Cortical thickness and density were estimated from the clinical CT images using the proposed method and compared with the micro-CT measurements. Finally, a case-control study including 20 patients with osteoporosis and 20 age-matched controls with normal bone density was performed to evaluate the proposed method in a clinical context. Results: Cortical thickness (density) estimation errors were 0.07 ± 0.19 mm (−18 ± 92 mg/cm{sup 3}) using the simulated clinical CT volumes with the smallest voxel size (0.33 × 0.33 × 0.5 mm{sup 3}), and 0.10 ± 0.24 mm (−10 ± 115 mg/cm{sup 3}) using the volumes with the largest voxel size (1.0 × 1.0 × 3.0 mm{sup 3}). A trend for the

Technical Note: Cortical thickness and density estimation from clinical CT using a prior thickness-density relationship

International Nuclear Information System (INIS)

Humbert, Ludovic; Hazrati Marangalou, Javad; Rietbergen, Bert van; Río Barquero, Luis Miguel del; Lenthe, G. Harry van

2016-01-01

Purpose: Cortical thickness and density are critical components in determining the strength of bony structures. Computed tomography (CT) is one possible modality for analyzing the cortex in 3D. In this paper, a model-based approach for measuring the cortical bone thickness and density from clinical CT images is proposed. Methods: Density variations across the cortex were modeled as a function of the cortical thickness and density, location of the cortex, density of surrounding tissues, and imaging blur. High resolution micro-CT data of cadaver proximal femurs were analyzed to determine a relationship between cortical thickness and density. This thickness-density relationship was used as prior information to be incorporated in the model to obtain accurate measurements of cortical thickness and density from clinical CT volumes. The method was validated using micro-CT scans of 23 cadaver proximal femurs. Simulated clinical CT images with different voxel sizes were generated from the micro-CT data. Cortical thickness and density were estimated from the simulated images using the proposed method and compared with measurements obtained using the micro-CT images to evaluate the effect of voxel size on the accuracy of the method. Then, 19 of the 23 specimens were imaged using a clinical CT scanner. Cortical thickness and density were estimated from the clinical CT images using the proposed method and compared with the micro-CT measurements. Finally, a case-control study including 20 patients with osteoporosis and 20 age-matched controls with normal bone density was performed to evaluate the proposed method in a clinical context. Results: Cortical thickness (density) estimation errors were 0.07 ± 0.19 mm (−18 ± 92 mg/cm"3) using the simulated clinical CT volumes with the smallest voxel size (0.33 × 0.33 × 0.5 mm"3), and 0.10 ± 0.24 mm (−10 ± 115 mg/cm"3) using the volumes with the largest voxel size (1.0 × 1.0 × 3.0 mm"3). A trend for the cortical thickness and

External field as the functional of inhomogeneous density and the density matrix functional approach

NARCIS (Netherlands)

Bobrov, V.B.; Trigger, S.A.; Vlasov, Y.P.

2012-01-01

Based on the Hohenberg-Kohn lemma and the hypotheses of the density functional existence for the external-field potential, it is shown that the strict result of the density functional theory is the equation of the external-field potential as the density functional. This result leads to the

Orbital functionals in density-matrix- and current-density-functional theory

Energy Technology Data Exchange (ETDEWEB)

Helbig, N

2006-05-15

Density-Functional Theory (DFT), although widely used and very successful in the calculation of several observables, fails to correctly describe strongly correlated materials. In the first part of this work we, therefore, introduce reduced-densitymatrix- functional theory (RDMFT) which is one possible way to treat electron correlation beyond DFT. Within this theory the one-body reduced density matrix (1- RDM) is used as the basic variable. Our main interest is the calculation of the fundamental gap which proves very problematic within DFT. In order to calculate the fundamental gap we generalize RDMFT to fractional particle numbers M by describing the system as an ensemble of an N and an N+1 particle system (with N{<=}M{<=}N+1). For each fixed particle number, M, the total energy is minimized with respect to the natural orbitals and their occupation numbers. This leads to the total energy as a function of M. The derivative of this function with respect to the particle number has a discontinuity at integer particle number which is identical to the gap. In addition, we investigate the necessary and sufficient conditions for the 1- RDM of a system with fractional particle number to be N-representable. Numerical results are presented for alkali atoms, small molecules, and periodic systems. Another problem within DFT is the description of non-relativistic many-electron systems in the presence of magnetic fields. It requires the paramagnetic current density and the spin magnetization to be used as basic variables besides the electron density. However, electron-gas-based functionals of current-spin-density-functional Theory (CSDFT) exhibit derivative discontinuities as a function of the magnetic field whenever a new Landau level is occupied, which makes them difficult to use in practice. Since the appearance of Landau levels is, intrinsically, an orbital effect it is appealing to use orbital-dependent functionals. We have developed a CSDFT version of the optimized

Kernel bandwidth estimation for non-parametric density estimation: a comparative study

CSIR Research Space (South Africa)

Van der Walt, CM

2013-12-01

Full Text Available We investigate the performance of conventional bandwidth estimators for non-parametric kernel density estimation on a number of representative pattern-recognition tasks, to gain a better understanding of the behaviour of these estimators in high...

Estimation of optical rotation of γ-alkylidenebutenolide, cyclopropylamine, cyclopropyl-methanol and cyclopropenone based compounds by a Density Functional Theory (DFT) approach.

Science.gov (United States)

Shahzadi, Iram; Shaukat, Aqsa; Zara, Zeenat; Irfan, Muhammad; Eliasson, Bertil; Ayub, Khurshid; Iqbal, Javed

2017-10-01

Computing the optical rotation of organic molecules can be a real challenge, and various theoretical approaches have been developed in this regard. A benchmark study of optical rotation of various classes of compounds was carried out by Density Functional Theory (DFT) methods. The aim of the present research study was to find out the best-suited functional and basis set to estimate the optical rotations of selected compounds with respect to experimental literature values. Six DFT functional LSDA, BVP86, CAM-B3LYP, B3PW91, and PBE were applied on 22 different compounds. Furthermore, six different basis sets, i.e., 3-21G, 6-31G, aug-cc-pVDZ, aug-cc-pVTZ, DGDZVP, and DGDZVP2 were also applied with the best-suited functional B3LYP. After rigorous effort, it can be safely said that the best combination of functional and basis set is B3LYP/aug-cc-pVTZ for the estimation of optical rotation for selected compounds. © 2017 Wiley Periodicals, Inc.

Breast density estimation from high spectral and spatial resolution MRI

Science.gov (United States)

Li, Hui; Weiss, William A.; Medved, Milica; Abe, Hiroyuki; Newstead, Gillian M.; Karczmar, Gregory S.; Giger, Maryellen L.

2016-01-01

Abstract. A three-dimensional breast density estimation method is presented for high spectral and spatial resolution (HiSS) MR imaging. Twenty-two patients were recruited (under an Institutional Review Board--approved Health Insurance Portability and Accountability Act-compliant protocol) for high-risk breast cancer screening. Each patient received standard-of-care clinical digital x-ray mammograms and MR scans, as well as HiSS scans. The algorithm for breast density estimation includes breast mask generating, breast skin removal, and breast percentage density calculation. The inter- and intra-user variabilities of the HiSS-based density estimation were determined using correlation analysis and limits of agreement. Correlation analysis was also performed between the HiSS-based density estimation and radiologists’ breast imaging-reporting and data system (BI-RADS) density ratings. A correlation coefficient of 0.91 (pdensity estimations. An interclass correlation coefficient of 0.99 (pdensity estimations. A moderate correlation coefficient of 0.55 (p=0.0076) was observed between HiSS-based breast density estimations and radiologists’ BI-RADS. In summary, an objective density estimation method using HiSS spectral data from breast MRI was developed. The high reproducibility with low inter- and low intra-user variabilities shown in this preliminary study suggest that such a HiSS-based density metric may be potentially beneficial in programs requiring breast density such as in breast cancer risk assessment and monitoring effects of therapy. PMID:28042590

Analytical Plug-In Method for Kernel Density Estimator Applied to Genetic Neutrality Study

Directory of Open Access Journals (Sweden)

Samir Saoudi

2008-07-01

Full Text Available The plug-in method enables optimization of the bandwidth of the kernel density estimator in order to estimate probability density functions (pdfs. Here, a faster procedure than that of the common plug-in method is proposed. The mean integrated square error (MISE depends directly upon J(f which is linked to the second-order derivative of the pdf. As we intend to introduce an analytical approximation of J(f, the pdf is estimated only once, at the end of iterations. These two kinds of algorithm are tested on different random variables having distributions known for their difficult estimation. Finally, they are applied to genetic data in order to provide a better characterisation in the mean of neutrality of Tunisian Berber populations.

Local-scaling density-functional method: Intraorbit and interorbit density optimizations

International Nuclear Information System (INIS)

Koga, T.; Yamamoto, Y.; Ludena, E.V.

1991-01-01

The recently proposed local-scaling density-functional theory provides us with a practical method for the direct variational determination of the electron density function ρ(r). The structure of ''orbits,'' which ensures the one-to-one correspondence between the electron density ρ(r) and the N-electron wave function Ψ({r k }), is studied in detail. For the realization of the local-scaling density-functional calculations, procedures for intraorbit and interorbit optimizations of the electron density function are proposed. These procedures are numerically illustrated for the helium atom in its ground state at the beyond-Hartree-Fock level

Nonparametric volatility density estimation for discrete time models

NARCIS (Netherlands)

Es, van Bert; Spreij, P.J.C.; Zanten, van J.H.

2005-01-01

We consider discrete time models for asset prices with a stationary volatility process. We aim at estimating the multivariate density of this process at a set of consecutive time instants. A Fourier-type deconvolution kernel density estimator based on the logarithm of the squared process is proposed

The Wegner Estimate and the Integrated Density of States for some ...

Indian Academy of Sciences (India)

The integrated density of states (IDS) for random operators is an important function describing many physical characteristics of a random system. Properties of the IDS are derived from the Wegner estimate that describes the influence of finite-volume perturbations on a background system. In this paper, we present a simple ...

Global Population Density Grid Time Series Estimates

Data.gov (United States)

National Aeronautics and Space Administration — Global Population Density Grid Time Series Estimates provide a back-cast time series of population density grids based on the year 2000 population grid from SEDAC's...

Density estimates of monarch butterflies overwintering in central Mexico

Directory of Open Access Journals (Sweden)

Wayne E. Thogmartin

2017-04-01

Full Text Available Given the rapid population decline and recent petition for listing of the monarch butterfly (Danaus plexippus L. under the Endangered Species Act, an accurate estimate of the Eastern, migratory population size is needed. Because of difficulty in counting individual monarchs, the number of hectares occupied by monarchs in the overwintering area is commonly used as a proxy for population size, which is then multiplied by the density of individuals per hectare to estimate population size. There is, however, considerable variation in published estimates of overwintering density, ranging from 6.9–60.9 million ha−1. We develop a probability distribution for overwinter density of monarch butterflies from six published density estimates. The mean density among the mixture of the six published estimates was ∼27.9 million butterflies ha−1 (95% CI [2.4–80.7] million ha−1; the mixture distribution is approximately log-normal, and as such is better represented by the median (21.1 million butterflies ha−1. Based upon assumptions regarding the number of milkweed needed to support monarchs, the amount of milkweed (Asclepias spp. lost (0.86 billion stems in the northern US plus the amount of milkweed remaining (1.34 billion stems, we estimate >1.8 billion stems is needed to return monarchs to an average population size of 6 ha. Considerable uncertainty exists in this required amount of milkweed because of the considerable uncertainty occurring in overwinter density estimates. Nevertheless, the estimate is on the same order as other published estimates. The studies included in our synthesis differ substantially by year, location, method, and measures of precision. A better understanding of the factors influencing overwintering density across space and time would be valuable for increasing the precision of conservation recommendations.

Density estimates of monarch butterflies overwintering in central Mexico

Science.gov (United States)

Thogmartin, Wayne E.; Diffendorfer, James E.; Lopez-Hoffman, Laura; Oberhauser, Karen; Pleasants, John M.; Semmens, Brice X.; Semmens, Darius J.; Taylor, Orley R.; Wiederholt, Ruscena

2017-01-01

Given the rapid population decline and recent petition for listing of the monarch butterfly (Danaus plexippus L.) under the Endangered Species Act, an accurate estimate of the Eastern, migratory population size is needed. Because of difficulty in counting individual monarchs, the number of hectares occupied by monarchs in the overwintering area is commonly used as a proxy for population size, which is then multiplied by the density of individuals per hectare to estimate population size. There is, however, considerable variation in published estimates of overwintering density, ranging from 6.9–60.9 million ha−1. We develop a probability distribution for overwinter density of monarch butterflies from six published density estimates. The mean density among the mixture of the six published estimates was ∼27.9 million butterflies ha−1 (95% CI [2.4–80.7] million ha−1); the mixture distribution is approximately log-normal, and as such is better represented by the median (21.1 million butterflies ha−1). Based upon assumptions regarding the number of milkweed needed to support monarchs, the amount of milkweed (Asclepias spp.) lost (0.86 billion stems) in the northern US plus the amount of milkweed remaining (1.34 billion stems), we estimate >1.8 billion stems is needed to return monarchs to an average population size of 6 ha. Considerable uncertainty exists in this required amount of milkweed because of the considerable uncertainty occurring in overwinter density estimates. Nevertheless, the estimate is on the same order as other published estimates. The studies included in our synthesis differ substantially by year, location, method, and measures of precision. A better understanding of the factors influencing overwintering density across space and time would be valuable for increasing the precision of conservation recommendations.

Wave-function functionals for the density

International Nuclear Information System (INIS)

Slamet, Marlina; Pan Xiaoyin; Sahni, Viraht

2011-01-01

We extend the idea of the constrained-search variational method for the construction of wave-function functionals ψ[χ] of functions χ. The search is constrained to those functions χ such that ψ[χ] reproduces the density ρ(r) while simultaneously leading to an upper bound to the energy. The functionals are thereby normalized and automatically satisfy the electron-nucleus coalescence condition. The functionals ψ[χ] are also constructed to satisfy the electron-electron coalescence condition. The method is applied to the ground state of the helium atom to construct functionals ψ[χ] that reproduce the density as given by the Kinoshita correlated wave function. The expectation of single-particle operators W=Σ i r i n , n=-2,-1,1,2, W=Σ i δ(r i ) are exact, as must be the case. The expectations of the kinetic energy operator W=-(1/2)Σ i ∇ i 2 , the two-particle operators W=Σ n u n , n=-2,-1,1,2, where u=|r i -r j |, and the energy are accurate. We note that the construction of such functionals ψ[χ] is an application of the Levy-Lieb constrained-search definition of density functional theory. It is thereby possible to rigorously determine which functional ψ[χ] is closer to the true wave function.

Density functional theory

International Nuclear Information System (INIS)

Das, M.P.

1984-07-01

The state of the art of the density functional formalism (DFT) is reviewed. The theory is quantum statistical in nature; its simplest version is the well-known Thomas-Fermi theory. The DFT is a powerful formalism in which one can treat the effect of interactions in inhomogeneous systems. After some introductory material, the DFT is outlined from the two basic theorems, and various generalizations of the theorems appropriate to several physical situations are pointed out. Next, various approximations to the density functionals are presented and some practical schemes, discussed; the approximations include an electron gas of almost constant density and an electron gas of slowly varying density. Then applications of DFT in various diverse areas of physics (atomic systems, plasmas, liquids, nuclear matter) are mentioned, and its strengths and weaknesses are pointed out. In conclusion, more recent developments of DFT are indicated

Analytical Plug-In Method for Kernel Density Estimator Applied to Genetic Neutrality Study

Science.gov (United States)

Troudi, Molka; Alimi, Adel M.; Saoudi, Samir

2008-12-01

The plug-in method enables optimization of the bandwidth of the kernel density estimator in order to estimate probability density functions (pdfs). Here, a faster procedure than that of the common plug-in method is proposed. The mean integrated square error (MISE) depends directly upon [InlineEquation not available: see fulltext.] which is linked to the second-order derivative of the pdf. As we intend to introduce an analytical approximation of [InlineEquation not available: see fulltext.], the pdf is estimated only once, at the end of iterations. These two kinds of algorithm are tested on different random variables having distributions known for their difficult estimation. Finally, they are applied to genetic data in order to provide a better characterisation in the mean of neutrality of Tunisian Berber populations.

Spin-density functional for exchange anisotropic Heisenberg model

International Nuclear Information System (INIS)

Prata, G.N.; Penteado, P.H.; Souza, F.C.; Libero, Valter L.

2009-01-01

Ground-state energies for antiferromagnetic Heisenberg models with exchange anisotropy are estimated by means of a local-spin approximation made in the context of the density functional theory. Correlation energy is obtained using the non-linear spin-wave theory for homogeneous systems from which the spin functional is built. Although applicable to chains of any size, the results are shown for small number of sites, to exhibit finite-size effects and allow comparison with exact-numerical data from direct diagonalization of small chains.

Estimation of cluster stability using the theory of electron density functional

International Nuclear Information System (INIS)

Borisov, Yu.A.

1985-01-01

Prospects of using simple versions of the electron density functional for studying the energy characteristics of cluster compounds Was discussed. These types of cluster compounds were considered: clusters of Cs, Be, B, Sr, Cd, Sc, In, V, Tl, I elements as intermediate form between molecule and solid body, metalloorganic Mo, W, Tc, Re, Rn clusters and elementoorganic compounds of nido-cluster type. The problem concerning changes in the binding energy of homoatomic clusters depending on their size and three-dimensional structure was analysed

Influence of the level of fit of a density probability function to wind-speed data on the WECS mean power output estimation

International Nuclear Information System (INIS)

Carta, Jose A.; Ramirez, Penelope; Velazquez, Sergio

2008-01-01

Static methods which are based on statistical techniques to estimate the mean power output of a WECS (wind energy conversion system) have been widely employed in the scientific literature related to wind energy. In the static method which we use in this paper, for a given wind regime probability distribution function and a known WECS power curve, the mean power output of a WECS is obtained by resolving the integral, usually using numerical evaluation techniques, of the product of these two functions. In this paper an analysis is made of the influence of the level of fit between an empirical probability density function of a sample of wind speeds and the probability density function of the adjusted theoretical model on the relative error ε made in the estimation of the mean annual power output of a WECS. The mean power output calculated through the use of a quasi-dynamic or chronological method, that is to say using time-series of wind speed data and the power versus wind speed characteristic of the wind turbine, serves as the reference. The suitability of the distributions is judged from the adjusted R 2 statistic (R a 2 ). Hourly mean wind speeds recorded at 16 weather stations located in the Canarian Archipelago, an extensive catalogue of wind-speed probability models and two wind turbines of 330 and 800 kW rated power are used in this paper. Among the general conclusions obtained, the following can be pointed out: (a) that the R a 2 statistic might be useful as an initial gross indicator of the relative error made in the mean annual power output estimation of a WECS when a probabilistic method is employed; (b) the relative errors tend to decrease, in accordance with a trend line defined by a second-order polynomial, as R a 2 increases

Computerized image analysis: estimation of breast density on mammograms

Science.gov (United States)

Zhou, Chuan; Chan, Heang-Ping; Petrick, Nicholas; Sahiner, Berkman; Helvie, Mark A.; Roubidoux, Marilyn A.; Hadjiiski, Lubomir M.; Goodsitt, Mitchell M.

2000-06-01

An automated image analysis tool is being developed for estimation of mammographic breast density, which may be useful for risk estimation or for monitoring breast density change in a prevention or intervention program. A mammogram is digitized using a laser scanner and the resolution is reduced to a pixel size of 0.8 mm X 0.8 mm. Breast density analysis is performed in three stages. First, the breast region is segmented from the surrounding background by an automated breast boundary-tracking algorithm. Second, an adaptive dynamic range compression technique is applied to the breast image to reduce the range of the gray level distribution in the low frequency background and to enhance the differences in the characteristic features of the gray level histogram for breasts of different densities. Third, rule-based classification is used to classify the breast images into several classes according to the characteristic features of their gray level histogram. For each image, a gray level threshold is automatically determined to segment the dense tissue from the breast region. The area of segmented dense tissue as a percentage of the breast area is then estimated. In this preliminary study, we analyzed the interobserver variation of breast density estimation by two experienced radiologists using BI-RADS lexicon. The radiologists' visually estimated percent breast densities were compared with the computer's calculation. The results demonstrate the feasibility of estimating mammographic breast density using computer vision techniques and its potential to improve the accuracy and reproducibility in comparison with the subjective visual assessment by radiologists.

Estimating black bear density using DNA data from hair snares

Science.gov (United States)

Gardner, B.; Royle, J. Andrew; Wegan, M.T.; Rainbolt, R.E.; Curtis, P.D.

2010-01-01

DNA-based mark-recapture has become a methodological cornerstone of research focused on bear species. The objective of such studies is often to estimate population size; however, doing so is frequently complicated by movement of individual bears. Movement affects the probability of detection and the assumption of closure of the population required in most models. To mitigate the bias caused by movement of individuals, population size and density estimates are often adjusted using ad hoc methods, including buffering the minimum polygon of the trapping array. We used a hierarchical, spatial capturerecapture model that contains explicit components for the spatial-point process that governs the distribution of individuals and their exposure to (via movement), and detection by, traps. We modeled detection probability as a function of each individual's distance to the trap and an indicator variable for previous capture to account for possible behavioral responses. We applied our model to a 2006 hair-snare study of a black bear (Ursus americanus) population in northern New York, USA. Based on the microsatellite marker analysis of collected hair samples, 47 individuals were identified. We estimated mean density at 0.20 bears/km2. A positive estimate of the indicator variable suggests that bears are attracted to baited sites; therefore, including a trap-dependence covariate is important when using bait to attract individuals. Bayesian analysis of the model was implemented in WinBUGS, and we provide the model specification. The model can be applied to any spatially organized trapping array (hair snares, camera traps, mist nests, etc.) to estimate density and can also account for heterogeneity and covariate information at the trap or individual level. ?? The Wildlife Society.

Density functionals from deep learning

OpenAIRE

McMahon, Jeffrey M.

2016-01-01

Density-functional theory is a formally exact description of a many-body quantum system in terms of its density; in practice, however, approximations to the universal density functional are required. In this work, a model based on deep learning is developed to approximate this functional. Deep learning allows computational models that are capable of naturally discovering intricate structure in large and/or high-dimensional data sets, with multiple levels of abstraction. As no assumptions are ...

Estimating reliability of degraded system based on the probability density evolution with multi-parameter

Directory of Open Access Journals (Sweden)

Jiang Ge

2017-01-01

Full Text Available System degradation was usually caused by multiple-parameter degradation. The assessment result of system reliability by universal generating function was low accurate when compared with the Monte Carlo simulation. And the probability density function of the system output performance cannot be got. So the reliability assessment method based on the probability density evolution with multi-parameter was presented for complexly degraded system. Firstly, the system output function was founded according to the transitive relation between component parameters and the system output performance. Then, the probability density evolution equation based on the probability conservation principle and the system output function was established. Furthermore, probability distribution characteristics of the system output performance was obtained by solving differential equation. Finally, the reliability of the degraded system was estimated. This method did not need to discrete the performance parameters and can establish continuous probability density function of the system output performance with high calculation efficiency and low cost. Numerical example shows that this method is applicable to evaluate the reliability of multi-parameter degraded system.

MR Imaging-based Estimation of Upper Motor Neuron Density in Patients with Amyotrophic Lateral Sclerosis: A Feasibility Study.

Science.gov (United States)

Chen, Jacqueline; Kostenko, Volodymyr; Pioro, Erik P; Trapp, Bruce D

2018-01-23

Purpose To determine if magnetic resonance (MR) imaging metrics can estimate primary motor cortex (PMC) motor neuron (MN) density in patients with amyotrophic lateral sclerosis (ALS). Materials and Methods Between 2012 and 2014, in situ brain MR imaging was performed in 11 patients with ALS (age range, 35-81 years; seven women and four men) soon after death (mean, 5.5 hours after death; range, 3.2-9.6 hours). The brain was removed, right PMC (RPMC) was excised, and MN density was quantified. RPMC metrics (thickness, volume, and magnetization transfer ratio) were calculated from MR images. Regression modeling was used to estimate MN density by using RPMC and global MR imaging metrics (brain and tissue volumes); clinical variables were subsequently evaluated as additional estimators. Models were tested at in vivo MR imaging by using the same imaging protocol (six patients with ALS; age range, 54-66 years; three women and three men). Results RPMC mean MN density varied over a greater than threefold range across patients and was estimated by a linear function of normalized gray matter volume (adjusted R 2 = 0.51; P = .008; <10% error in most patients). When considering only sporadic ALS, a linear function of normalized RPMC and white matter volumes estimated MN density (adjusted R 2 = 0.98; P = .01; <10% error in all patients). In vivo data analyses detected decreases in MN density over time. Conclusion PMC mean MN density varies widely in end-stage ALS possibly because of disease heterogeneity. MN density can potentially be estimated by MR imaging metrics. © RSNA, 2018 Online supplemental material is available for this article.

Reliability analysis based on a novel density estimation method for structures with correlations

Directory of Open Access Journals (Sweden)

Baoyu LI

2017-06-01

Full Text Available Estimating the Probability Density Function (PDF of the performance function is a direct way for structural reliability analysis, and the failure probability can be easily obtained by integration in the failure domain. However, efficiently estimating the PDF is still an urgent problem to be solved. The existing fractional moment based maximum entropy has provided a very advanced method for the PDF estimation, whereas the main shortcoming is that it limits the application of the reliability analysis method only to structures with independent inputs. While in fact, structures with correlated inputs always exist in engineering, thus this paper improves the maximum entropy method, and applies the Unscented Transformation (UT technique to compute the fractional moments of the performance function for structures with correlations, which is a very efficient moment estimation method for models with any inputs. The proposed method can precisely estimate the probability distributions of performance functions for structures with correlations. Besides, the number of function evaluations of the proposed method in reliability analysis, which is determined by UT, is really small. Several examples are employed to illustrate the accuracy and advantages of the proposed method.

Deep sea animal density and size estimated using a Dual-frequency IDentification SONar (DIDSON) offshore the island of Hawaii

Science.gov (United States)

Giorli, Giacomo; Drazen, Jeffrey C.; Neuheimer, Anna B.; Copeland, Adrienne; Au, Whitlow W. L.

2018-01-01

Pelagic animals that form deep sea scattering layers (DSLs) represent an important link in the food web between zooplankton and top predators. While estimating the composition, density and location of the DSL is important to understand mesopelagic ecosystem dynamics and to predict top predators' distribution, DSL composition and density are often estimated from trawls which may be biased in terms of extrusion, avoidance, and gear-associated biases. Instead, location and biomass of DSLs can be estimated from active acoustic techniques, though estimates are often in aggregate without regard to size or taxon specific information. For the first time in the open ocean, we used a DIDSON sonar to characterize the fauna in DSLs. Estimates of the numerical density and length of animals at different depths and locations along the Kona coast of the Island of Hawaii were determined. Data were collected below and inside the DSLs with the sonar mounted on a profiler. A total of 7068 animals were counted and sized. We estimated numerical densities ranging from 1 to 7 animals/m3 and individuals as long as 3 m were detected. These numerical densities were orders of magnitude higher than those estimated from trawls and average sizes of animals were much larger as well. A mixed model was used to characterize numerical density and length of animals as a function of deep sea layer sampled, location, time of day, and day of the year. Numerical density and length of animals varied by month, with numerical density also a function of depth. The DIDSON proved to be a good tool for open-ocean/deep-sea estimation of the numerical density and size of marine animals, especially larger ones. Further work is needed to understand how this methodology relates to estimates of volume backscatters obtained with standard echosounding techniques, density measures obtained with other sampling methodologies, and to precisely evaluate sampling biases.

Unbiased estimators for spatial distribution functions of classical fluids

Science.gov (United States)

Adib, Artur B.; Jarzynski, Christopher

2005-01-01

We use a statistical-mechanical identity closely related to the familiar virial theorem, to derive unbiased estimators for spatial distribution functions of classical fluids. In particular, we obtain estimators for both the fluid density ρ(r) in the vicinity of a fixed solute and the pair correlation g(r) of a homogeneous classical fluid. We illustrate the utility of our estimators with numerical examples, which reveal advantages over traditional histogram-based methods of computing such distributions.

Multicomponent density functional theory embedding formulation

Energy Technology Data Exchange (ETDEWEB)

Culpitt, Tanner; Brorsen, Kurt R.; Pak, Michael V.; Hammes-Schiffer, Sharon, E-mail: shs3@illinois.edu [Department of Chemistry, University of Illinois at Urbana-Champaign, 600 South Mathews Ave, Urbana, Illinois 61801 (United States)

2016-07-28

Multicomponent density functional theory (DFT) methods have been developed to treat two types of particles, such as electrons and nuclei, quantum mechanically at the same level. In the nuclear-electronic orbital (NEO) approach, all electrons and select nuclei, typically key protons, are treated quantum mechanically. For multicomponent DFT methods developed within the NEO framework, electron-proton correlation functionals based on explicitly correlated wavefunctions have been designed and used in conjunction with well-established electronic exchange-correlation functionals. Herein a general theory for multicomponent embedded DFT is developed to enable the accurate treatment of larger systems. In the general theory, the total electronic density is separated into two subsystem densities, denoted as regular and special, and different electron-proton correlation functionals are used for these two electronic densities. In the specific implementation, the special electron density is defined in terms of spatially localized Kohn-Sham electronic orbitals, and electron-proton correlation is included only for the special electron density. The electron-proton correlation functional depends on only the special electron density and the proton density, whereas the electronic exchange-correlation functional depends on the total electronic density. This scheme includes the essential electron-proton correlation, which is a relatively local effect, as well as the electronic exchange-correlation for the entire system. This multicomponent DFT-in-DFT embedding theory is applied to the HCN and FHF{sup −} molecules in conjunction with two different electron-proton correlation functionals and three different electronic exchange-correlation functionals. The results illustrate that this approach provides qualitatively accurate nuclear densities in a computationally tractable manner. The general theory is also easily extended to other types of partitioning schemes for multicomponent systems.

Influence of the level of fit of a density probability function to wind-speed data on the WECS mean power output estimation

Energy Technology Data Exchange (ETDEWEB)

Carta, Jose A. [Department of Mechanical Engineering, University of Las Palmas de Gran Canaria, Campus de Tafira s/n, 35017 Las Palmas de Gran Canaria, Canary Islands (Spain); Ramirez, Penelope; Velazquez, Sergio [Department of Renewable Energies, Technological Institute of the Canary Islands, Pozo Izquierdo Beach s/n, 35119 Santa Lucia, Gran Canaria, Canary Islands (Spain)

2008-10-15

Static methods which are based on statistical techniques to estimate the mean power output of a WECS (wind energy conversion system) have been widely employed in the scientific literature related to wind energy. In the static method which we use in this paper, for a given wind regime probability distribution function and a known WECS power curve, the mean power output of a WECS is obtained by resolving the integral, usually using numerical evaluation techniques, of the product of these two functions. In this paper an analysis is made of the influence of the level of fit between an empirical probability density function of a sample of wind speeds and the probability density function of the adjusted theoretical model on the relative error {epsilon} made in the estimation of the mean annual power output of a WECS. The mean power output calculated through the use of a quasi-dynamic or chronological method, that is to say using time-series of wind speed data and the power versus wind speed characteristic of the wind turbine, serves as the reference. The suitability of the distributions is judged from the adjusted R{sup 2} statistic (R{sub a}{sup 2}). Hourly mean wind speeds recorded at 16 weather stations located in the Canarian Archipelago, an extensive catalogue of wind-speed probability models and two wind turbines of 330 and 800 kW rated power are used in this paper. Among the general conclusions obtained, the following can be pointed out: (a) that the R{sub a}{sup 2} statistic might be useful as an initial gross indicator of the relative error made in the mean annual power output estimation of a WECS when a probabilistic method is employed; (b) the relative errors tend to decrease, in accordance with a trend line defined by a second-order polynomial, as R{sub a}{sup 2} increases. (author)

Magnetic fields and density functional theory

Energy Technology Data Exchange (ETDEWEB)

Salsbury Jr., Freddie [Univ. of California, Berkeley, CA (United States)

1999-02-01

A major focus of this dissertation is the development of functionals for the magnetic susceptibility and the chemical shielding within the context of magnetic field density functional theory (BDFT). These functionals depend on the electron density in the absence of the field, which is unlike any other treatment of these responses. There have been several advances made within this theory. The first of which is the development of local density functionals for chemical shieldings and magnetic susceptibilities. There are the first such functionals ever proposed. These parameters have been studied by constructing functionals for the current density and then using the Biot-Savart equations to obtain the responses. In order to examine the advantages and disadvantages of the local functionals, they were tested numerically on some small molecules.

Magnetic fields and density functional theory

International Nuclear Information System (INIS)

Salsbury, Freddie Jr.

1999-01-01

A major focus of this dissertation is the development of functionals for the magnetic susceptibility and the chemical shielding within the context of magnetic field density functional theory (BDFT). These functionals depend on the electron density in the absence of the field, which is unlike any other treatment of these responses. There have been several advances made within this theory. The first of which is the development of local density functionals for chemical shieldings and magnetic susceptibilities. There are the first such functionals ever proposed. These parameters have been studied by constructing functionals for the current density and then using the Biot-Savart equations to obtain the responses. In order to examine the advantages and disadvantages of the local functionals, they were tested numerically on some small molecules

Improved Variable Window Kernel Estimates of Probability Densities

OpenAIRE

Hall, Peter; Hu, Tien Chung; Marron, J. S.

1995-01-01

Variable window width kernel density estimators, with the width varying proportionally to the square root of the density, have been thought to have superior asymptotic properties. The rate of convergence has been claimed to be as good as those typical for higher-order kernels, which makes the variable width estimators more attractive because no adjustment is needed to handle the negativity usually entailed by the latter. However, in a recent paper, Terrell and Scott show that these results ca...

Density dependence of the nuclear energy-density functional

Science.gov (United States)

Papakonstantinou, Panagiota; Park, Tae-Sun; Lim, Yeunhwan; Hyun, Chang Ho

2018-01-01

Background: The explicit density dependence in the coupling coefficients entering the nonrelativistic nuclear energy-density functional (EDF) is understood to encode effects of three-nucleon forces and dynamical correlations. The necessity for the density-dependent coupling coefficients to assume the form of a preferably small fractional power of the density ρ is empirical and the power is often chosen arbitrarily. Consequently, precision-oriented parametrizations risk overfitting in the regime of saturation and extrapolations in dilute or dense matter may lose predictive power. Purpose: Beginning with the observation that the Fermi momentum kF, i.e., the cubic root of the density, is a key variable in the description of Fermi systems, we first wish to examine if a power hierarchy in a kF expansion can be inferred from the properties of homogeneous matter in a domain of densities, which is relevant for nuclear structure and neutron stars. For subsequent applications we want to determine a functional that is of good quality but not overtrained. Method: For the EDF, we fit systematically polynomial and other functions of ρ1 /3 to existing microscopic, variational calculations of the energy of symmetric and pure neutron matter (pseudodata) and analyze the behavior of the fits. We select a form and a set of parameters, which we found robust, and examine the parameters' naturalness and the quality of resulting extrapolations. Results: A statistical analysis confirms that low-order terms such as ρ1 /3 and ρ2 /3 are the most relevant ones in the nuclear EDF beyond lowest order. It also hints at a different power hierarchy for symmetric vs. pure neutron matter, supporting the need for more than one density-dependent term in nonrelativistic EDFs. The functional we propose easily accommodates known or adopted properties of nuclear matter near saturation. More importantly, upon extrapolation to dilute or asymmetric matter, it reproduces a range of existing microscopic

Electron mobility in supercritical pentanes as a function of density and temperature

International Nuclear Information System (INIS)

Itoh, Kengo; Nakagawa, Kazumichi; Nishikawa, Masaru

1988-01-01

The excess electron mobility in supercritical n-, iso- and neopentane was measured isothermally as a function of density. The density-normalized mobility μN in all three isomers goes through a minimum at a density below the respective critical densities, and the mobility is quite temperature-dependent in this region, then goes through a minimum. The μN behavior around the minimum in n-pentane is well accounted for by the Cohen-Lekner model with the structure factor S(K) estimated from the speed of sound, while that in iso- and neopentane is not. (author)

Curve fitting of the corporate recovery rates: the comparison of Beta distribution estimation and kernel density estimation.

Science.gov (United States)

Chen, Rongda; Wang, Ze

2013-01-01

Recovery rate is essential to the estimation of the portfolio's loss and economic capital. Neglecting the randomness of the distribution of recovery rate may underestimate the risk. The study introduces two kinds of models of distribution, Beta distribution estimation and kernel density distribution estimation, to simulate the distribution of recovery rates of corporate loans and bonds. As is known, models based on Beta distribution are common in daily usage, such as CreditMetrics by J.P. Morgan, Portfolio Manager by KMV and Losscalc by Moody's. However, it has a fatal defect that it can't fit the bimodal or multimodal distributions such as recovery rates of corporate loans and bonds as Moody's new data show. In order to overcome this flaw, the kernel density estimation is introduced and we compare the simulation results by histogram, Beta distribution estimation and kernel density estimation to reach the conclusion that the Gaussian kernel density distribution really better imitates the distribution of the bimodal or multimodal data samples of corporate loans and bonds. Finally, a Chi-square test of the Gaussian kernel density estimation proves that it can fit the curve of recovery rates of loans and bonds. So using the kernel density distribution to precisely delineate the bimodal recovery rates of bonds is optimal in credit risk management.

Gradient-based stochastic estimation of the density matrix

Science.gov (United States)

Wang, Zhentao; Chern, Gia-Wei; Batista, Cristian D.; Barros, Kipton

2018-03-01

Fast estimation of the single-particle density matrix is key to many applications in quantum chemistry and condensed matter physics. The best numerical methods leverage the fact that the density matrix elements f(H)ij decay rapidly with distance rij between orbitals. This decay is usually exponential. However, for the special case of metals at zero temperature, algebraic decay of the density matrix appears and poses a significant numerical challenge. We introduce a gradient-based probing method to estimate all local density matrix elements at a computational cost that scales linearly with system size. For zero-temperature metals, the stochastic error scales like S-(d+2)/2d, where d is the dimension and S is a prefactor to the computational cost. The convergence becomes exponential if the system is at finite temperature or is insulating.

Density-functional theory for internal magnetic fields

Science.gov (United States)

Tellgren, Erik I.

2018-01-01

A density-functional theory is developed based on the Maxwell-Schrödinger equation with an internal magnetic field in addition to the external electromagnetic potentials. The basic variables of this theory are the electron density and the total magnetic field, which can equivalently be represented as a physical current density. Hence, the theory can be regarded as a physical current density-functional theory and an alternative to the paramagnetic current density-functional theory due to Vignale and Rasolt. The energy functional has strong enough convexity properties to allow a formulation that generalizes Lieb's convex analysis formulation of standard density-functional theory. Several variational principles as well as a Hohenberg-Kohn-like mapping between potentials and ground-state densities follow from the underlying convex structure. Moreover, the energy functional can be regarded as the result of a standard approximation technique (Moreau-Yosida regularization) applied to the conventional Schrödinger ground-state energy, which imposes limits on the maximum curvature of the energy (with respect to the magnetic field) and enables construction of a (Fréchet) differentiable universal density functional.

Density-density functionals and effective potentials in many-body electronic structure calculations

International Nuclear Information System (INIS)

Reboredo, Fernando A.; Kent, Paul R.

2008-01-01

We demonstrate the existence of different density-density functionals designed to retain selected properties of the many-body ground state in a non-interacting solution starting from the standard density functional theory ground state. We focus on diffusion quantum Monte Carlo applications that require trial wave functions with optimal Fermion nodes. The theory is extensible and can be used to understand current practices in several electronic structure methods within a generalized density functional framework. The theory justifies and stimulates the search of optimal empirical density functionals and effective potentials for accurate calculations of the properties of real materials, but also cautions on the limits of their applicability. The concepts are tested and validated with a near-analytic model.

Density estimation by maximum quantum entropy

International Nuclear Information System (INIS)

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

1993-01-01

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

Nonparametric methods for volatility density estimation

NARCIS (Netherlands)

Es, van Bert; Spreij, P.J.C.; Zanten, van J.H.

2009-01-01

Stochastic volatility modelling of financial processes has become increasingly popular. The proposed models usually contain a stationary volatility process. We will motivate and review several nonparametric methods for estimation of the density of the volatility process. Both models based on

Excited-state density functional theory

International Nuclear Information System (INIS)

Harbola, Manoj K; Hemanadhan, M; Shamim, Md; Samal, P

2012-01-01

Starting with a brief introduction to excited-state density functional theory, we present our method of constructing modified local density approximated (MLDA) energy functionals for the excited states. We show that these functionals give accurate results for kinetic energy and exchange energy compared to the ground state LDA functionals. Further, with the inclusion of GGA correction, highly accurate total energies for excited states are obtained. We conclude with a brief discussion on the further direction of research that include the construction of correlation energy functional and exchange potential for excited states.

Curve fitting of the corporate recovery rates: the comparison of Beta distribution estimation and kernel density estimation.

Directory of Open Access Journals (Sweden)

Rongda Chen

Full Text Available Recovery rate is essential to the estimation of the portfolio's loss and economic capital. Neglecting the randomness of the distribution of recovery rate may underestimate the risk. The study introduces two kinds of models of distribution, Beta distribution estimation and kernel density distribution estimation, to simulate the distribution of recovery rates of corporate loans and bonds. As is known, models based on Beta distribution are common in daily usage, such as CreditMetrics by J.P. Morgan, Portfolio Manager by KMV and Losscalc by Moody's. However, it has a fatal defect that it can't fit the bimodal or multimodal distributions such as recovery rates of corporate loans and bonds as Moody's new data show. In order to overcome this flaw, the kernel density estimation is introduced and we compare the simulation results by histogram, Beta distribution estimation and kernel density estimation to reach the conclusion that the Gaussian kernel density distribution really better imitates the distribution of the bimodal or multimodal data samples of corporate loans and bonds. Finally, a Chi-square test of the Gaussian kernel density estimation proves that it can fit the curve of recovery rates of loans and bonds. So using the kernel density distribution to precisely delineate the bimodal recovery rates of bonds is optimal in credit risk management.

Curve Fitting of the Corporate Recovery Rates: The Comparison of Beta Distribution Estimation and Kernel Density Estimation

Science.gov (United States)

Chen, Rongda; Wang, Ze

2013-01-01

Recovery rate is essential to the estimation of the portfolio’s loss and economic capital. Neglecting the randomness of the distribution of recovery rate may underestimate the risk. The study introduces two kinds of models of distribution, Beta distribution estimation and kernel density distribution estimation, to simulate the distribution of recovery rates of corporate loans and bonds. As is known, models based on Beta distribution are common in daily usage, such as CreditMetrics by J.P. Morgan, Portfolio Manager by KMV and Losscalc by Moody’s. However, it has a fatal defect that it can’t fit the bimodal or multimodal distributions such as recovery rates of corporate loans and bonds as Moody’s new data show. In order to overcome this flaw, the kernel density estimation is introduced and we compare the simulation results by histogram, Beta distribution estimation and kernel density estimation to reach the conclusion that the Gaussian kernel density distribution really better imitates the distribution of the bimodal or multimodal data samples of corporate loans and bonds. Finally, a Chi-square test of the Gaussian kernel density estimation proves that it can fit the curve of recovery rates of loans and bonds. So using the kernel density distribution to precisely delineate the bimodal recovery rates of bonds is optimal in credit risk management. PMID:23874558

Modelling the Probability Density Function of IPTV Traffic Packet Delay Variation

Directory of Open Access Journals (Sweden)

Michal Halas

2012-01-01

Full Text Available This article deals with modelling the Probability density function of IPTV traffic packet delay variation. The use of this modelling is in an efficient de-jitter buffer estimation. When an IP packet travels across a network, it experiences delay and its variation. This variation is caused by routing, queueing systems and other influences like the processing delay of the network nodes. When we try to separate these at least three types of delay variation, we need a way to measure these types separately. This work is aimed to the delay variation caused by queueing systems which has the main implications to the form of the Probability density function.

Spectral function from Reduced Density Matrix Functional Theory

Science.gov (United States)

Romaniello, Pina; di Sabatino, Stefano; Berger, Jan A.; Reining, Lucia

2015-03-01

In this work we focus on the calculation of the spectral function, which determines, for example, photoemission spectra, from reduced density matrix functional theory. Starting from its definition in terms of the one-body Green's function we derive an expression for the spectral function that depends on the natural occupation numbers and on an effective energy which accounts for all the charged excitations. This effective energy depends on the two-body as well as higher-order density matrices. Various approximations to this expression are explored by using the exactly solvable Hubbard chains.

Ground-state densities from the Rayleigh-Ritz variation principle and from density-functional theory.

Science.gov (United States)

Kvaal, Simen; Helgaker, Trygve

2015-11-14

The relationship between the densities of ground-state wave functions (i.e., the minimizers of the Rayleigh-Ritz variation principle) and the ground-state densities in density-functional theory (i.e., the minimizers of the Hohenberg-Kohn variation principle) is studied within the framework of convex conjugation, in a generic setting covering molecular systems, solid-state systems, and more. Having introduced admissible density functionals as functionals that produce the exact ground-state energy for a given external potential by minimizing over densities in the Hohenberg-Kohn variation principle, necessary and sufficient conditions on such functionals are established to ensure that the Rayleigh-Ritz ground-state densities and the Hohenberg-Kohn ground-state densities are identical. We apply the results to molecular systems in the Born-Oppenheimer approximation. For any given potential v ∈ L(3/2)(ℝ(3)) + L(∞)(ℝ(3)), we establish a one-to-one correspondence between the mixed ground-state densities of the Rayleigh-Ritz variation principle and the mixed ground-state densities of the Hohenberg-Kohn variation principle when the Lieb density-matrix constrained-search universal density functional is taken as the admissible functional. A similar one-to-one correspondence is established between the pure ground-state densities of the Rayleigh-Ritz variation principle and the pure ground-state densities obtained using the Hohenberg-Kohn variation principle with the Levy-Lieb pure-state constrained-search functional. In other words, all physical ground-state densities (pure or mixed) are recovered with these functionals and no false densities (i.e., minimizing densities that are not physical) exist. The importance of topology (i.e., choice of Banach space of densities and potentials) is emphasized and illustrated. The relevance of these results for current-density-functional theory is examined.

Dual-Layer Density Estimation for Multiple Object Instance Detection

Directory of Open Access Journals (Sweden)

Qiang Zhang

2016-01-01

Full Text Available This paper introduces a dual-layer density estimation-based architecture for multiple object instance detection in robot inventory management applications. The approach consists of raw scale-invariant feature transform (SIFT feature matching and key point projection. The dominant scale ratio and a reference clustering threshold are estimated using the first layer of the density estimation. A cascade of filters is applied after feature template reconstruction and refined feature matching to eliminate false matches. Before the second layer of density estimation, the adaptive threshold is finalized by multiplying an empirical coefficient for the reference value. The coefficient is identified experimentally. Adaptive threshold-based grid voting is applied to find all candidate object instances. Error detection is eliminated using final geometric verification in accordance with Random Sample Consensus (RANSAC. The detection results of the proposed approach are evaluated on a self-built dataset collected in a supermarket. The results demonstrate that the approach provides high robustness and low latency for inventory management application.

Anisotropic Density Estimation in Global Illumination

DEFF Research Database (Denmark)

Schjøth, Lars

2009-01-01

Density estimation employed in multi-pass global illumination algorithms gives cause to a trade-off problem between bias and noise. The problem is seen most evident as blurring of strong illumination features. This thesis addresses the problem, presenting four methods that reduce both noise...

Density functional study of the bonding in small silicon clusters

International Nuclear Information System (INIS)

Fournier, R.; Sinnott, S.B.; DePristo, A.E.

1992-01-01

We report the ground electronic state, equilibrium geometry, vibrational frequencies, and binding energy for various isomers of Si n (n = 2--8) obtained with the linear combination of atomic orbitals-density functional method. We used both a local density approximation approach and one with gradient corrections. Our local density approximation results concerning the relative stability of electronic states and isomers are in agreement with Hartree--Fock and Moller--Plesset (MP2) calculations [K. Raghavachari and C. M. Rohlfing, J. Chem. Phys. 89, 2219 (1988)]. The binding energies calculated with the gradient corrected functional are in good agreement with experiment (Si 2 and Si 3 ) and with the best theoretical estimates. Our analysis of the bonding reveals two limiting modes of bonding and classes of silicon clusters. One class of clusters is characterized by relatively large s atomic populations and a large number of weak bonds, while the other class of clusters is characterized by relatively small s atomic populations and a small number of strong bonds

Self-interaction corrected density functional calculations of molecular Rydberg states

International Nuclear Information System (INIS)

Gudmundsdóttir, Hildur; Zhang, Yao; Weber, Peter M.; Jónsson, Hannes

2013-01-01

A method is presented for calculating the wave function and energy of Rydberg excited states of molecules. A good estimate of the Rydberg state orbital is obtained using ground state density functional theory including Perdew-Zunger self-interaction correction and an optimized effective potential. The total energy of the excited molecule is obtained using the Delta Self-Consistent Field method where an electron is removed from the highest occupied orbital and placed in the Rydberg orbital. Results are presented for the first few Rydberg states of NH 3 , H 2 O, H 2 CO, C 2 H 4 , and N(CH 3 ) 3 . The mean absolute error in the energy of the 33 molecular Rydberg states presented here is 0.18 eV. The orbitals are represented on a real space grid, avoiding the dependence on diffuse atomic basis sets. As in standard density functional theory calculations, the computational effort scales as NM 2 where N is the number of orbitals and M is the number of grid points included in the calculation. Due to the slow scaling of the computational effort with system size and the high level of parallelism in the real space grid approach, the method presented here makes it possible to estimate Rydberg electron binding energy in large molecules

Single-particle energies and density of states in density functional theory

Science.gov (United States)

van Aggelen, H.; Chan, G. K.-L.

2015-07-01

Time-dependent density functional theory (TD-DFT) is commonly used as the foundation to obtain neutral excited states and transition weights in DFT, but does not allow direct access to density of states and single-particle energies, i.e. ionisation energies and electron affinities. Here we show that by extending TD-DFT to a superfluid formulation, which involves operators that break particle-number symmetry, we can obtain the density of states and single-particle energies from the poles of an appropriate superfluid response function. The standard Kohn- Sham eigenvalues emerge as the adiabatic limit of the superfluid response under the assumption that the exchange- correlation functional has no dependence on the superfluid density. The Kohn- Sham eigenvalues can thus be interpreted as approximations to the ionisation energies and electron affinities. Beyond this approximation, the formalism provides an incentive for creating a new class of density functionals specifically targeted at accurate single-particle eigenvalues and bandgaps.

Density of states functions for photonic crystals

International Nuclear Information System (INIS)

McPhedran, R.C.; McOrist, J.; Sterke, C.M. de; Nicorovici, N.A.; Botten, L.C.; Asatryan, A.A.

2004-01-01

We discuss density of states functions for photonic crystals, in the context of the two-dimensional problem for arrays of cylinders of arbitrary cross section. We introduce the mutual density of states (MDOS), and show that this function can be used to calculate both the local density of states (LDOS), which gives position information for emission of radiation from photonic crystals, and the spectral density of states (SDOS), which gives angular information. We establish the connection between MDOS, LDOS, SDOS and the conventional density of states, which depends only on frequency. We relate all four functions to the band structure and propagating states within the crystal, and give numerical examples of the relation between band structure and density of states functions

Nonlocal kinetic-energy-density functionals

International Nuclear Information System (INIS)

Garcia-Gonzalez, P.; Alvarellos, J.E.; Chacon, E.

1996-01-01

In this paper we present nonlocal kinetic-energy functionals T[n] within the average density approximation (ADA) framework, which do not require any extra input when applied to any electron system and recover the exact kinetic energy and the linear response function of a homogeneous system. In contrast with previous ADA functionals, these present good behavior of the long-range tail of the exact weight function. The averaging procedure for the kinetic functional (averaging the Fermi momentum of the electron gas, instead of averaging the electron density) leads to a functional without numerical difficulties in the calculation of extended systems, and it gives excellent results when applied to atoms and jellium surfaces. copyright 1996 The American Physical Society

Density of Jatropha curcas Seed Oil and its Methyl Esters: Measurement and Estimations

Science.gov (United States)

Veny, Harumi; Baroutian, Saeid; Aroua, Mohamed Kheireddine; Hasan, Masitah; Raman, Abdul Aziz; Sulaiman, Nik Meriam Nik

2009-04-01

Density data as a function of temperature have been measured for Jatropha curcas seed oil, as well as biodiesel jatropha methyl esters at temperatures from above their melting points to 90 ° C. The data obtained were used to validate the method proposed by Spencer and Danner using a modified Rackett equation. The experimental and estimated density values using the modified Rackett equation gave almost identical values with average absolute percent deviations less than 0.03% for the jatropha oil and 0.04% for the jatropha methyl esters. The Janarthanan empirical equation was also employed to predict jatropha biodiesel densities. This equation performed equally well with average absolute percent deviations within 0.05%. Two simple linear equations for densities of jatropha oil and its methyl esters are also proposed in this study.

Assessing different parameters estimation methods of Weibull distribution to compute wind power density

International Nuclear Information System (INIS)

Mohammadi, Kasra; Alavi, Omid; Mostafaeipour, Ali; Goudarzi, Navid; Jalilvand, Mahdi

2016-01-01

Highlights: • Effectiveness of six numerical methods is evaluated to determine wind power density. • More appropriate method for computing the daily wind power density is estimated. • Four windy stations located in the south part of Alberta, Canada namely is investigated. • The more appropriate parameters estimation method was not identical among all examined stations. - Abstract: In this study, the effectiveness of six numerical methods is evaluated to determine the shape (k) and scale (c) parameters of Weibull distribution function for the purpose of calculating the wind power density. The selected methods are graphical method (GP), empirical method of Justus (EMJ), empirical method of Lysen (EML), energy pattern factor method (EPF), maximum likelihood method (ML) and modified maximum likelihood method (MML). The purpose of this study is to identify the more appropriate method for computing the wind power density in four stations distributed in Alberta province of Canada namely Edmonton City Center Awos, Grande Prairie A, Lethbridge A and Waterton Park Gate. To provide a complete analysis, the evaluations are performed on both daily and monthly scales. The results indicate that the precision of computed wind power density values change when different parameters estimation methods are used to determine the k and c parameters. Four methods of EMJ, EML, EPF and ML present very favorable efficiency while the GP method shows weak ability for all stations. However, it is found that the more effective method is not similar among stations owing to the difference in the wind characteristics.

Exchange-correlation energies of atoms from efficient density functionals: influence of the electron density

Science.gov (United States)

Tao, Jianmin; Ye, Lin-Hui; Duan, Yuhua

2017-12-01

The primary goal of Kohn-Sham density functional theory is to evaluate the exchange-correlation contribution to electronic properties. However, the accuracy of a density functional can be affected by the electron density. Here we apply the nonempirical Tao-Mo (TM) semilocal functional to study the influence of the electron density on the exchange and correlation energies of atoms and ions, and compare the results with the commonly used nonempirical semilocal functionals local spin-density approximation (LSDA), Perdew-Burke-Ernzerhof (PBE), Tao-Perdew-Staroverov-Scuseria (TPSS), and hybrid functional PBE0. We find that the spin-restricted Hartree-Fock density yields the exchange and correlation energies in good agreement with the Optimized Effective Potential method, particularly for spherical atoms and ions. However, the errors of these semilocal and hybrid functionals become larger for self-consistent densities. We further find that the quality of the electron density have greater effect on the exchange-correlation energies of kinetic energy density-dependent meta-GGA functionals TPSS and TM than on those of the LSDA and GGA, and therefore, should have greater influence on the performance of meta-GGA functionals. Finally, we show that the influence of the density quality on PBE0 is slightly reduced, compared to that of PBE, due to the exact mixing.

A multiconfigurational hybrid density-functional theory

DEFF Research Database (Denmark)

Sharkas, Kamal; Savin, Andreas; Jensen, Hans Jørgen Aagaard

2012-01-01

We propose a multiconfigurational hybrid density-functional theory which rigorously combines a multiconfiguration self-consistent-field calculation with a density-functional approximation based on a linear decomposition of the electron-electron interaction. This gives a straightforward extension ...

Local density approximation for exchange in excited-state density functional theory

OpenAIRE

Harbola, Manoj K.; Samal, Prasanjit

2004-01-01

Local density approximation for the exchange energy is made for treatment of excited-states in density-functional theory. It is shown that taking care of the state-dependence of the LDA exchange energy functional leads to accurate excitation energies.

The Kernel Mixture Network: A Nonparametric Method for Conditional Density Estimation of Continuous Random Variables

OpenAIRE

Ambrogioni, Luca; Güçlü, Umut; van Gerven, Marcel A. J.; Maris, Eric

2017-01-01

This paper introduces the kernel mixture network, a new method for nonparametric estimation of conditional probability densities using neural networks. We model arbitrarily complex conditional densities as linear combinations of a family of kernel functions centered at a subset of training points. The weights are determined by the outer layer of a deep neural network, trained by minimizing the negative log likelihood. This generalizes the popular quantized softmax approach, which can be seen ...

A pdf-Free Change Detection Test Based on Density Difference Estimation.

Science.gov (United States)

Bu, Li; Alippi, Cesare; Zhao, Dongbin

2018-02-01

The ability to detect online changes in stationarity or time variance in a data stream is a hot research topic with striking implications. In this paper, we propose a novel probability density function-free change detection test, which is based on the least squares density-difference estimation method and operates online on multidimensional inputs. The test does not require any assumption about the underlying data distribution, and is able to operate immediately after having been configured by adopting a reservoir sampling mechanism. Thresholds requested to detect a change are automatically derived once a false positive rate is set by the application designer. Comprehensive experiments validate the effectiveness in detection of the proposed method both in terms of detection promptness and accuracy.

Mean density and two-point correlation function for the CfA redshift survey slices

International Nuclear Information System (INIS)

De Lapparent, V.; Geller, M.J.; Huchra, J.P.

1988-01-01

The effect of large-scale inhomogeneities on the determination of the mean number density and the two-point spatial correlation function were investigated for two complete slices of the extension of the Center for Astrophysics (CfA) redshift survey (de Lapparent et al., 1986). It was found that the mean galaxy number density for the two strips is uncertain by 25 percent, more so than previously estimated. The large uncertainty in the mean density introduces substantial uncertainty in the determination of the two-point correlation function, particularly at large scale; thus, for the 12-deg slice of the CfA redshift survey, the amplitude of the correlation function at intermediate scales is uncertain by a factor of 2. The large uncertainties in the correlation functions might reflect the lack of a fair sample. 45 references

Density estimation from local structure

CSIR Research Space (South Africa)

Van der Walt, Christiaan M

2009-11-01

Full Text Available Mixture Model (GMM) density function of the data and the log-likelihood scores are compared to the scores of a GMM trained with the expectation maximization (EM) algorithm on 5 real-world classification datasets (from the UCI collection). They show...

Density meter algorithm and system for estimating sampling/mixing uncertainty

International Nuclear Information System (INIS)

Shine, E.P.

1986-01-01

The Laboratories Department at the Savannah River Plant (SRP) has installed a six-place density meter with an automatic sampling device. This paper describes the statistical software developed to analyze the density of uranyl nitrate solutions using this automated system. The purpose of this software is twofold: to estimate the sampling/mixing and measurement uncertainties in the process and to provide a measurement control program for the density meter. Non-uniformities in density are analyzed both analytically and graphically. The mean density and its limit of error are estimated. Quality control standards are analyzed concurrently with process samples and used to control the density meter measurement error. The analyses are corrected for concentration due to evaporation of samples waiting to be analyzed. The results of this program have been successful in identifying sampling/mixing problems and controlling the quality of analyses

Density meter algorithm and system for estimating sampling/mixing uncertainty

International Nuclear Information System (INIS)

Shine, E.P.

1986-01-01

The Laboratories Department at the Savannah River Plant (SRP) has installed a six-place density meter with an automatic sampling device. This paper describes the statisical software developed to analyze the density of uranyl nitrate solutions using this automated system. The purpose of this software is twofold: to estimate the sampling/mixing and measurement uncertainties in the process and to provide a measurement control program for the density meter. Non-uniformities in density are analyzed both analytically and graphically. The mean density and its limit of error are estimated. Quality control standards are analyzed concurrently with process samples and used to control the density meter measurement error. The analyses are corrected for concentration due to evaporation of samples waiting to be analyzed. The results of this program have been successful in identifying sampling/mixing problems and controlling the quality of analyses

Estimation of electron temperature and density by de convolving the absorption part of the plasma dispersion function

International Nuclear Information System (INIS)

Jimenez D, H.; Cabral P, A.; Melendez L, L.; Lopez C, R.; Colunga S, S.; Valencia A, R.; Cruz J, S.; Gaytan G, E.; Chavez A, E.

1992-04-01

In this work a method to estimate the temperature and density of the electron (T e , n e ), based on the deconvolution of the part of absorption of the dispersion function of the plasma is suggested. The absorptive part of this function, is proportional to the convolution of a Gauss distribution with a Lorentz function. The Gaussian represents to the Maxwell function of velocities distribution of the electrons of the plasma. The Lorentzian represents to the form of it lines of an linearized electrostatic wave that spreads with reduction in the plasma. The complex variable z of the plasma dispersion function is written as: z = u + ia, where u = 2 (w-w 0 ) √ Ln 2 /Γ G is the dimensionless frequency variable, a = Γ L √ Ln 2 /Γ G is the Posener parameter, Γ G = k Γ ' G where k is the wave number of the oscillatory phenomenon, Γ ' G is the FWHM of the Gaussian and Γ L = 2 α, α being the damping constant; i.e the imaginary part of the frequency ω. In this method, it will be assumed that a wave of frequency , and of amplitude small enough to avoid non-linear effects, propagates in the plasma and decays in such a way α is the Landau damping. With this assumption, the method is only valid in the interval k D , where k D is the Debye wave number. Deconvolution of the detected absorption frequency spectrum of the signal, gives the values of Γ G and Γ L from which the values of n e and T e can be deduced. (Author)

Relativistic density functional for nuclear structure

CERN Document Server

2016-01-01

This book aims to provide a detailed introduction to the state-of-the-art covariant density functional theory, which follows the Lorentz invariance from the very beginning and is able to describe nuclear many-body quantum systems microscopically and self-consistently. Covariant density functional theory was introduced in nuclear physics in the 1970s and has since been developed and used to describe the diversity of nuclear properties and phenomena with great success. In order to provide an advanced and updated textbook of covariant density functional theory for graduate students and nuclear physics researchers, this book summarizes the enormous amount of material that has accumulated in the field of covariant density functional theory over the last few decades as well as the latest developments in this area. Moreover, the book contains enough details for readers to follow the formalism and theoretical results, and provides exhaustive references to explore the research literature.

Simplified large African carnivore density estimators from track indices

Directory of Open Access Journals (Sweden)

Christiaan W. Winterbach

2016-12-01

Full Text Available Background The range, population size and trend of large carnivores are important parameters to assess their status globally and to plan conservation strategies. One can use linear models to assess population size and trends of large carnivores from track-based surveys on suitable substrates. The conventional approach of a linear model with intercept may not intercept at zero, but may fit the data better than linear model through the origin. We assess whether a linear regression through the origin is more appropriate than a linear regression with intercept to model large African carnivore densities and track indices. Methods We did simple linear regression with intercept analysis and simple linear regression through the origin and used the confidence interval for ß in the linear model y = αx + ß, Standard Error of Estimate, Mean Squares Residual and Akaike Information Criteria to evaluate the models. Results The Lion on Clay and Low Density on Sand models with intercept were not significant (P > 0.05. The other four models with intercept and the six models thorough origin were all significant (P < 0.05. The models using linear regression with intercept all included zero in the confidence interval for ß and the null hypothesis that ß = 0 could not be rejected. All models showed that the linear model through the origin provided a better fit than the linear model with intercept, as indicated by the Standard Error of Estimate and Mean Square Residuals. Akaike Information Criteria showed that linear models through the origin were better and that none of the linear models with intercept had substantial support. Discussion Our results showed that linear regression through the origin is justified over the more typical linear regression with intercept for all models we tested. A general model can be used to estimate large carnivore densities from track densities across species and study areas. The formula observed track density = 3.26�

Stochastic density functional theory at finite temperatures

Science.gov (United States)

Cytter, Yael; Rabani, Eran; Neuhauser, Daniel; Baer, Roi

2018-03-01

Simulations in the warm dense matter regime using finite temperature Kohn-Sham density functional theory (FT-KS-DFT), while frequently used, are computationally expensive due to the partial occupation of a very large number of high-energy KS eigenstates which are obtained from subspace diagonalization. We have developed a stochastic method for applying FT-KS-DFT, that overcomes the bottleneck of calculating the occupied KS orbitals by directly obtaining the density from the KS Hamiltonian. The proposed algorithm scales as O (" close=")N3T3)">N T-1 and is compared with the high-temperature limit scaling O density approximation (LDA); we demonstrate its efficiency, statistical errors, and bias in the estimation of the free energy per electron for a diamond structure silicon. The bias is small compared to the fluctuations and is independent of system size. In addition to calculating the free energy itself, one can also use the method to calculate its derivatives and obtain the equations of state.

New technique for a simultaneous estimation of the level density and radiative strength functions of dipole transitions at E sub e sub x<=B sub n -0.5 MeV

CERN Document Server

Khitrov, V A

2001-01-01

The new, model-independent method to estimate simultaneously the level densities excited in the (n,gamma) reaction and the radiative strength functions of dipole transitions is developed. The method can be applied for any nucleus and reaction followed by cascade gamma-emission. It is just necessary to measure the intensities of two-step gamma-cascades depopulating one or several high-excited states and determine the quanta ordering in the main portion of the observed cascades. The method provides a sufficiently narrow interval of most probable densities of levels with given J suppi and radiative strength functions of dipole transitions populating them.

Testing and Estimating Shape-Constrained Nonparametric Density and Regression in the Presence of Measurement Error

KAUST Repository

Carroll, Raymond J.

2011-03-01

In many applications we can expect that, or are interested to know if, a density function or a regression curve satisfies some specific shape constraints. For example, when the explanatory variable, X, represents the value taken by a treatment or dosage, the conditional mean of the response, Y , is often anticipated to be a monotone function of X. Indeed, if this regression mean is not monotone (in the appropriate direction) then the medical or commercial value of the treatment is likely to be significantly curtailed, at least for values of X that lie beyond the point at which monotonicity fails. In the case of a density, common shape constraints include log-concavity and unimodality. If we can correctly guess the shape of a curve, then nonparametric estimators can be improved by taking this information into account. Addressing such problems requires a method for testing the hypothesis that the curve of interest satisfies a shape constraint, and, if the conclusion of the test is positive, a technique for estimating the curve subject to the constraint. Nonparametric methodology for solving these problems already exists, but only in cases where the covariates are observed precisely. However in many problems, data can only be observed with measurement errors, and the methods employed in the error-free case typically do not carry over to this error context. In this paper we develop a novel approach to hypothesis testing and function estimation under shape constraints, which is valid in the context of measurement errors. Our method is based on tilting an estimator of the density or the regression mean until it satisfies the shape constraint, and we take as our test statistic the distance through which it is tilted. Bootstrap methods are used to calibrate the test. The constrained curve estimators that we develop are also based on tilting, and in that context our work has points of contact with methodology in the error-free case.

Novel Application of Density Estimation Techniques in Muon Ionization Cooling Experiment

Energy Technology Data Exchange (ETDEWEB)

Mohayai, Tanaz Angelina [IIT, Chicago; Snopok, Pavel [IIT, Chicago; Neuffer, David [Fermilab; Rogers, Chris [Rutherford

2017-10-12

The international Muon Ionization Cooling Experiment (MICE) aims to demonstrate muon beam ionization cooling for the first time and constitutes a key part of the R&D towards a future neutrino factory or muon collider. Beam cooling reduces the size of the phase space volume occupied by the beam. Non-parametric density estimation techniques allow very precise calculation of the muon beam phase-space density and its increase as a result of cooling. These density estimation techniques are investigated in this paper and applied in order to estimate the reduction in muon beam size in MICE under various conditions.

Functional derivative of noninteracting kinetic energy density functional

International Nuclear Information System (INIS)

Liu Shubin; Ayers, Paul W.

2004-01-01

Proofs from different theoretical frameworks, namely, the Hohenbergh-Kohn theorems, the Kohn-Sham scheme, and the first-order density matrix representation, have been presented in this paper to show that the functional derivative of the noninteracting kinetic energy density functional can uniquely be expressed as the negative of the Kohn-Sham effective potential, arbitrary only to an additive orbital-independent constant. Key points leading to the current result as well as confusion about the quantity in the literature are briefly discussed

A hierarchical model for estimating density in camera-trap studies

Science.gov (United States)

Royle, J. Andrew; Nichols, James D.; Karanth, K.Ullas; Gopalaswamy, Arjun M.

2009-01-01

Estimating animal density using capture–recapture data from arrays of detection devices such as camera traps has been problematic due to the movement of individuals and heterogeneity in capture probability among them induced by differential exposure to trapping.We develop a spatial capture–recapture model for estimating density from camera-trapping data which contains explicit models for the spatial point process governing the distribution of individuals and their exposure to and detection by traps.We adopt a Bayesian approach to analysis of the hierarchical model using the technique of data augmentation.The model is applied to photographic capture–recapture data on tigers Panthera tigris in Nagarahole reserve, India. Using this model, we estimate the density of tigers to be 14·3 animals per 100 km2 during 2004.Synthesis and applications. Our modelling framework largely overcomes several weaknesses in conventional approaches to the estimation of animal density from trap arrays. It effectively deals with key problems such as individual heterogeneity in capture probabilities, movement of traps, presence of potential ‘holes’ in the array and ad hoc estimation of sample area. The formulation, thus, greatly enhances flexibility in the conduct of field surveys as well as in the analysis of data, from studies that may involve physical, photographic or DNA-based ‘captures’ of individual animals.

Estimation and display of beam density profiles

Energy Technology Data Exchange (ETDEWEB)

Dasgupta, S; Mukhopadhyay, T; Roy, A; Mallik, C

1989-03-15

A setup in which wire-scanner-type beam-profile monitor data are collected on-line in a nuclear data-acquisition system has been used and a simple algorithm for estimation and display of the current density distribution in a particle beam is described.

Density functionals in the laboratory frame

International Nuclear Information System (INIS)

Giraud, B. G.

2008-01-01

We compare several definitions of the density of a self-bound system, such as a nucleus, in relation with its center-of-mass zero-point motion. A trivial deconvolution relates the internal density to the density defined in the laboratory frame. This result is useful for the practical definition of density functionals

Estimation of electron temperature and density by de convolving the absorption part of the plasma dispersion function

Energy Technology Data Exchange (ETDEWEB)

Jimenez D, H.; Cabral P, A.; Melendez L, L.; Lopez C, R.; Colunga S, S.; Valencia A, R.; Cruz J, S.; Gaytan G, E.; Chavez A, E

1992-04-15

In this work a method to estimate the temperature and density of the electron (T{sub e}, n{sub e}), based on the deconvolution of the part of absorption of the dispersion function of the plasma is suggested. The absorptive part of this function, is proportional to the convolution of a Gauss distribution with a Lorentz function. The Gaussian represents to the Maxwell function of velocities distribution of the electrons of the plasma. The Lorentzian represents to the form of it lines of an linearized electrostatic wave that spreads with reduction in the plasma. The complex variable z of the plasma dispersion function is written as: z = u + ia, where u = 2 (w-w{sub 0}) {radical} Ln 2 /{gamma}{sub G} is the dimensionless frequency variable, a = {gamma}{sub L} {radical} Ln 2 /{gamma}{sub G} is the Posener parameter, {gamma}{sub G} = k {gamma}{sup '}{sub G} where k is the wave number of the oscillatory phenomenon, {gamma}{sup '}{sub G} is the FWHM of the Gaussian and {gamma}{sub L} = 2 {alpha}, {alpha} being the damping constant; i.e the imaginary part of the frequency {omega}. In this method, it will be assumed that a wave of frequency , and of amplitude small enough to avoid non-linear effects, propagates in the plasma and decays in such a way {alpha} is the Landau damping. With this assumption, the method is only valid in the interval k < < k{sub D}, where k{sub D} is the Debye wave number. Deconvolution of the detected absorption frequency spectrum of the signal, gives the values of {gamma}{sub G} and {gamma}{sub L} from which the values of n{sub e} and T{sub e} can be deduced. (Author)

Face Value: Towards Robust Estimates of Snow Leopard Densities.

Directory of Open Access Journals (Sweden)

Justine S Alexander

Full Text Available When densities of large carnivores fall below certain thresholds, dramatic ecological effects can follow, leading to oversimplified ecosystems. Understanding the population status of such species remains a major challenge as they occur in low densities and their ranges are wide. This paper describes the use of non-invasive data collection techniques combined with recent spatial capture-recapture methods to estimate the density of snow leopards Panthera uncia. It also investigates the influence of environmental and human activity indicators on their spatial distribution. A total of 60 camera traps were systematically set up during a three-month period over a 480 km2 study area in Qilianshan National Nature Reserve, Gansu Province, China. We recorded 76 separate snow leopard captures over 2,906 trap-days, representing an average capture success of 2.62 captures/100 trap-days. We identified a total number of 20 unique individuals from photographs and estimated snow leopard density at 3.31 (SE = 1.01 individuals per 100 km2. Results of our simulation exercise indicate that our estimates from the Spatial Capture Recapture models were not optimal to respect to bias and precision (RMSEs for density parameters less or equal to 0.87. Our results underline the critical challenge in achieving sufficient sample sizes of snow leopard captures and recaptures. Possible performance improvements are discussed, principally by optimising effective camera capture and photographic data quality.

Automated mammographic breast density estimation using a fully convolutional network.

Science.gov (United States)

Lee, Juhun; Nishikawa, Robert M

2018-03-01

The purpose of this study was to develop a fully automated algorithm for mammographic breast density estimation using deep learning. Our algorithm used a fully convolutional network, which is a deep learning framework for image segmentation, to segment both the breast and the dense fibroglandular areas on mammographic images. Using the segmented breast and dense areas, our algorithm computed the breast percent density (PD), which is the faction of dense area in a breast. Our dataset included full-field digital screening mammograms of 604 women, which included 1208 mediolateral oblique (MLO) and 1208 craniocaudal (CC) views. We allocated 455, 58, and 91 of 604 women and their exams into training, testing, and validation datasets, respectively. We established ground truth for the breast and the dense fibroglandular areas via manual segmentation and segmentation using a simple thresholding based on BI-RADS density assessments by radiologists, respectively. Using the mammograms and ground truth, we fine-tuned a pretrained deep learning network to train the network to segment both the breast and the fibroglandular areas. Using the validation dataset, we evaluated the performance of the proposed algorithm against radiologists' BI-RADS density assessments. Specifically, we conducted a correlation analysis between a BI-RADS density assessment of a given breast and its corresponding PD estimate by the proposed algorithm. In addition, we evaluated our algorithm in terms of its ability to classify the BI-RADS density using PD estimates, and its ability to provide consistent PD estimates for the left and the right breast and the MLO and CC views of the same women. To show the effectiveness of our algorithm, we compared the performance of our algorithm against a state of the art algorithm, laboratory for individualized breast radiodensity assessment (LIBRA). The PD estimated by our algorithm correlated well with BI-RADS density ratings by radiologists. Pearson's rho values of

3D depth-to-basement and density contrast estimates using gravity and borehole data

Science.gov (United States)

Barbosa, V. C.; Martins, C. M.; Silva, J. B.

2009-05-01

We present a gravity inversion method for simultaneously estimating the 3D basement relief of a sedimentary basin and the parameters defining the parabolic decay of the density contrast with depth in a sedimentary pack assuming the prior knowledge about the basement depth at a few points. The sedimentary pack is approximated by a grid of 3D vertical prisms juxtaposed in both horizontal directions, x and y, of a right-handed coordinate system. The prisms' thicknesses represent the depths to the basement and are the parameters to be estimated from the gravity data. To produce stable depth-to-basement estimates we impose smoothness on the basement depths through minimization of the spatial derivatives of the parameters in the x and y directions. To estimate the parameters defining the parabolic decay of the density contrast with depth we mapped a functional containing prior information about the basement depths at a few points. We apply our method to synthetic data from a simulated complex 3D basement relief with two sedimentary sections having distinct parabolic laws describing the density contrast variation with depth. Our method retrieves the true parameters of the parabolic law of density contrast decay with depth and produces good estimates of the basement relief if the number and the distribution of boreholes are sufficient. We also applied our method to real gravity data from the onshore and part of the shallow offshore Almada Basin, on Brazil's northeastern coast. The estimated 3D Almada's basement shows geologic structures that cannot be easily inferred just from the inspection of the gravity anomaly. The estimated Almada relief presents steep borders evidencing the presence of gravity faults. Also, we note the existence of three terraces separating two local subbasins. These geologic features are consistent with Almada's geodynamic origin (the Mesozoic breakup of Gondwana and the opening of the South Atlantic Ocean) and they are important in understanding

A analytical comparison of different estimators for the density distribution of the catalyst in a experimental riser by a gammametric technique

International Nuclear Information System (INIS)

Lima, Emerson Alexandre de Oliveira; Dantas Carlos C.; Melo, Silvio de Barros; Santos, Valdemir Alexandre dos

2005-01-01

In this paper, we solve the following questions: what will be the estimate of the r = r (x, y, z) function format? Which method would describe the density distribution function more precisely? Which is the best estimator? Also, once the ρ=ρ(x, y, z) format and the approximation technique is defined, comes the experimental arrangement and pass length configuration, which are the next problems to be solved. Finding the best parameter estimation for the ρ=ρ(x, y, z) function according to the C pass lengths and their spatial configuration. The latter is required to define the ρ=ρ(x, y, z) function resolution and the mechanical scanning movements of the arrangement. Such definitions will be implemented for an automate arrangement, by a computational program, to further development of the reconstruction of catalyst density distribution on experimental risers.. The precision evaluation was finally compared to the arrangement geometry that yields the best pass length spatial configuration. The results are shown in graphics for the two known density distributions. As a conclusion, the parameters for an automate arrangement design, are given under the required precision for the catalyst distribution reconstruction. (author)

Estimation of Wheat Plant Density at Early Stages Using High Resolution Imagery

Directory of Open Access Journals (Sweden)

Shouyang Liu

2017-05-01

Full Text Available Crop density is a key agronomical trait used to manage wheat crops and estimate yield. Visual counting of plants in the field is currently the most common method used. However, it is tedious and time consuming. The main objective of this work is to develop a machine vision based method to automate the density survey of wheat at early stages. RGB images taken with a high resolution RGB camera are classified to identify the green pixels corresponding to the plants. Crop rows are extracted and the connected components (objects are identified. A neural network is then trained to estimate the number of plants in the objects using the object features. The method was evaluated over three experiments showing contrasted conditions with sowing densities ranging from 100 to 600 seeds⋅m-2. Results demonstrate that the density is accurately estimated with an average relative error of 12%. The pipeline developed here provides an efficient and accurate estimate of wheat plant density at early stages.

Density-functional expansion methods: Grand challenges.

Science.gov (United States)

Giese, Timothy J; York, Darrin M

2012-03-01

We discuss the source of errors in semiempirical density functional expansion (VE) methods. In particular, we show that VE methods are capable of well-reproducing their standard Kohn-Sham density functional method counterparts, but suffer from large errors upon using one or more of these approximations: the limited size of the atomic orbital basis, the Slater monopole auxiliary basis description of the response density, and the one- and two-body treatment of the core-Hamiltonian matrix elements. In the process of discussing these approximations and highlighting their symptoms, we introduce a new model that supplements the second-order density-functional tight-binding model with a self-consistent charge-dependent chemical potential equalization correction; we review our recently reported method for generalizing the auxiliary basis description of the atomic orbital response density; and we decompose the first-order potential into a summation of additive atomic components and many-body corrections, and from this examination, we provide new insights and preliminary results that motivate and inspire new approximate treatments of the core-Hamiltonian.

Density estimation in tiger populations: combining information for strong inference

Science.gov (United States)

Gopalaswamy, Arjun M.; Royle, J. Andrew; Delampady, Mohan; Nichols, James D.; Karanth, K. Ullas; Macdonald, David W.

2012-01-01

A productive way forward in studies of animal populations is to efficiently make use of all the information available, either as raw data or as published sources, on critical parameters of interest. In this study, we demonstrate two approaches to the use of multiple sources of information on a parameter of fundamental interest to ecologists: animal density. The first approach produces estimates simultaneously from two different sources of data. The second approach was developed for situations in which initial data collection and analysis are followed up by subsequent data collection and prior knowledge is updated with new data using a stepwise process. Both approaches are used to estimate density of a rare and elusive predator, the tiger, by combining photographic and fecal DNA spatial capture–recapture data. The model, which combined information, provided the most precise estimate of density (8.5 ± 1.95 tigers/100 km2 [posterior mean ± SD]) relative to a model that utilized only one data source (photographic, 12.02 ± 3.02 tigers/100 km2 and fecal DNA, 6.65 ± 2.37 tigers/100 km2). Our study demonstrates that, by accounting for multiple sources of available information, estimates of animal density can be significantly improved.

Periodic subsystem density-functional theory

International Nuclear Information System (INIS)

Genova, Alessandro; Pavanello, Michele; Ceresoli, Davide

2014-01-01

By partitioning the electron density into subsystem contributions, the Frozen Density Embedding (FDE) formulation of subsystem Density Functional Theory (DFT) has recently emerged as a powerful tool for reducing the computational scaling of Kohn–Sham DFT. To date, however, FDE has been employed to molecular systems only. Periodic systems, such as metals, semiconductors, and other crystalline solids have been outside the applicability of FDE, mostly because of the lack of a periodic FDE implementation. To fill this gap, in this work we aim at extending FDE to treat subsystems of molecular and periodic character. This goal is achieved by a dual approach. On one side, the development of a theoretical framework for periodic subsystem DFT. On the other, the realization of the method into a parallel computer code. We find that periodic FDE is capable of reproducing total electron densities and (to a lesser extent) also interaction energies of molecular systems weakly interacting with metallic surfaces. In the pilot calculations considered, we find that FDE fails in those cases where there is appreciable density overlap between the subsystems. Conversely, we find FDE to be in semiquantitative agreement with Kohn–Sham DFT when the inter-subsystem density overlap is low. We also conclude that to make FDE a suitable method for describing molecular adsorption at surfaces, kinetic energy density functionals that go beyond the GGA level must be employed

Periodic subsystem density-functional theory

Science.gov (United States)

Genova, Alessandro; Ceresoli, Davide; Pavanello, Michele

2014-11-01

By partitioning the electron density into subsystem contributions, the Frozen Density Embedding (FDE) formulation of subsystem Density Functional Theory (DFT) has recently emerged as a powerful tool for reducing the computational scaling of Kohn-Sham DFT. To date, however, FDE has been employed to molecular systems only. Periodic systems, such as metals, semiconductors, and other crystalline solids have been outside the applicability of FDE, mostly because of the lack of a periodic FDE implementation. To fill this gap, in this work we aim at extending FDE to treat subsystems of molecular and periodic character. This goal is achieved by a dual approach. On one side, the development of a theoretical framework for periodic subsystem DFT. On the other, the realization of the method into a parallel computer code. We find that periodic FDE is capable of reproducing total electron densities and (to a lesser extent) also interaction energies of molecular systems weakly interacting with metallic surfaces. In the pilot calculations considered, we find that FDE fails in those cases where there is appreciable density overlap between the subsystems. Conversely, we find FDE to be in semiquantitative agreement with Kohn-Sham DFT when the inter-subsystem density overlap is low. We also conclude that to make FDE a suitable method for describing molecular adsorption at surfaces, kinetic energy density functionals that go beyond the GGA level must be employed.

Estimation of Nanodiamond Surface Charge Density from Zeta Potential and Molecular Dynamics Simulations.

Science.gov (United States)

Ge, Zhenpeng; Wang, Yi

2017-04-20

Molecular dynamics simulations of nanoparticles (NPs) are increasingly used to study their interactions with various biological macromolecules. Such simulations generally require detailed knowledge of the surface composition of the NP under investigation. Even for some well-characterized nanoparticles, however, this knowledge is not always available. An example is nanodiamond, a nanoscale diamond particle with surface dominated by oxygen-containing functional groups. In this work, we explore using the harmonic restraint method developed by Venable et al., to estimate the surface charge density (σ) of nanodiamonds. Based on the Gouy-Chapman theory, we convert the experimentally determined zeta potential of a nanodiamond to an effective charge density (σ eff ), and then use the latter to estimate σ via molecular dynamics simulations. Through scanning a series of nanodiamond models, we show that the above method provides a straightforward protocol to determine the surface charge density of relatively large (> ∼100 nm) NPs. Overall, our results suggest that despite certain limitation, the above protocol can be readily employed to guide the model construction for MD simulations, which is particularly useful when only limited experimental information on the NP surface composition is available to a modeler.

Estimating snowpack density from Albedo measurement

Science.gov (United States)

James L. Smith; Howard G. Halverson

1979-01-01

Snow is a major source of water in Western United States. Data on snow depth and average snowpack density are used in mathematical models to predict water supply. In California, about 75 percent of the snow survey sites above 2750-meter elevation now used to collect data are in statutory wilderness areas. There is need for a method of estimating the water content of a...

Graphene oxide and adsorption of chloroform: A density functional study

Energy Technology Data Exchange (ETDEWEB)

Kuisma, Elena; Hansson, C. Fredrik; Lindberg, Th. Benjamin; Gillberg, Christoffer A.; Idh, Sebastian; Schröder, Elsebeth, E-mail: schroder@chalmers.se [Quantum Device Physics Laboratory, Microtechnology and Nanoscience (MC2), Chalmers University of Technology, SE-412 96 Göteborg (Sweden)

2016-05-14

Chlorinated hydrocarbon compounds are of environmental concerns, since they are toxic to humans and other mammals, and are widespread, and exposure is hard to avoid. Understanding and improving methods to reduce the amount of the substances are important. We present an atomic-scale calculational study of the adsorption of chlorine-based substance chloroform (CHCl{sub 3}) on graphene oxide, as a step in estimating the capacity of graphene oxide for filtering out such substances, e.g., from drinking water. The calculations are based on density functional theory, and the recently developed consistent-exchange functional for the van der Waals density-functional method is employed. We obtain values of the chloroform adsorption energy varying from roughly 0.2 to 0.4 eV per molecule. This is comparable to previously found results for chloroform adsorbed directly on clean graphene, using similar calculations. In a wet environment, like filters for drinking water, the graphene will not stay clean and will likely oxidize, and thus adsorption onto graphene oxide, rather than clean graphene, is a more relevant process to study.

Quantal density functional theory

CERN Document Server

Sahni, Viraht

2016-01-01

This book deals with quantal density functional theory (QDFT) which is a time-dependent local effective potential theory of the electronic structure of matter. The treated time-independent QDFT constitutes a special case. In the 2nd edition, the theory is extended to include the presence of external magnetostatic fields. The theory is a description of matter based on the ‘quantal Newtonian’ first and second laws which is in terms of “classical” fields that pervade all space, and their quantal sources. The fields, which are explicitly defined, are separately representative of electron correlations due to the Pauli exclusion principle, Coulomb repulsion, correlation-kinetic, correlation-current-density, and correlation-magnetic effects. The book further describes Schrödinger theory from the new physical perspective of fields and quantal sources. It also describes traditional Hohenberg-Kohn-Sham DFT, and explains via QDFT the physics underlying the various energy functionals and functional derivatives o...

Reduced density matrix functional theory via a wave function based approach

Energy Technology Data Exchange (ETDEWEB)

Schade, Robert; Bloechl, Peter [Institute for Theoretical Physics, Clausthal University of Technology, Clausthal (Germany); Pruschke, Thomas [Institute for Theoretical Physics, University of Goettingen, Goettingen (Germany)

2016-07-01

We propose a new method for the calculation of the electronic and atomic structure of correlated electron systems based on reduced density matrix functional theory (rDMFT). The density-matrix functional is evaluated on the fly using Levy's constrained search formalism. The present implementation rests on a local approximation of the interaction reminiscent to that of dynamical mean field theory (DMFT). We focus here on additional approximations to the exact density-matrix functional in the local approximation and evaluate their performance.

A real-space stochastic density matrix approach for density functional electronic structure.

Science.gov (United States)

Beck, Thomas L

2015-12-21

The recent development of real-space grid methods has led to more efficient, accurate, and adaptable approaches for large-scale electrostatics and density functional electronic structure modeling. With the incorporation of multiscale techniques, linear-scaling real-space solvers are possible for density functional problems if localized orbitals are used to represent the Kohn-Sham energy functional. These methods still suffer from high computational and storage overheads, however, due to extensive matrix operations related to the underlying wave function grid representation. In this paper, an alternative stochastic method is outlined that aims to solve directly for the one-electron density matrix in real space. In order to illustrate aspects of the method, model calculations are performed for simple one-dimensional problems that display some features of the more general problem, such as spatial nodes in the density matrix. This orbital-free approach may prove helpful considering a future involving increasingly parallel computing architectures. Its primary advantage is the near-locality of the random walks, allowing for simultaneous updates of the density matrix in different regions of space partitioned across the processors. In addition, it allows for testing and enforcement of the particle number and idempotency constraints through stabilization of a Feynman-Kac functional integral as opposed to the extensive matrix operations in traditional approaches.

Adjusting forest density estimates for surveyor bias in historical tree surveys

Science.gov (United States)

Brice B. Hanberry; Jian Yang; John M. Kabrick; Hong S. He

2012-01-01

The U.S. General Land Office surveys, conducted between the late 1700s to early 1900s, provide records of trees prior to widespread European and American colonial settlement. However, potential and documented surveyor bias raises questions about the reliability of historical tree density estimates and other metrics based on density estimated from these records. In this...

Estimating the effect of urban density on fuel demand

Energy Technology Data Exchange (ETDEWEB)

Karathodorou, Niovi; Graham, Daniel J. [Imperial College London, London, SW7 2AZ (United Kingdom); Noland, Robert B. [Rutgers University, New Brunswick, NJ 08901 (United States)

2010-01-15

Much of the empirical literature on fuel demand presents estimates derived from national data which do not permit any explicit consideration of the spatial structure of the economy. Intuitively we would expect the degree of spatial concentration of activities to have a strong link with transport fuel consumption. The present paper addresses this theme by estimating a fuel demand model for urban areas to provide a direct estimate of the elasticity of demand with respect to urban density. Fuel demand per capita is decomposed into car stock per capita, fuel consumption per kilometre and annual distance driven per car per year. Urban density is found to affect fuel consumption, mostly through variations in the car stock and in the distances travelled, rather than through fuel consumption per kilometre. (author)

Estimation of dislocations density and distribution of dislocations during ECAP-Conform process

Science.gov (United States)

Derakhshan, Jaber Fakhimi; Parsa, Mohammad Habibi; Ayati, Vahid; Jafarian, Hamidreza

2018-01-01

Dislocation density of coarse grain aluminum AA1100 alloy (140 µm) that was severely deformed by Equal Channel Angular Pressing-Conform (ECAP-Conform) are studied at various stages of the process by electron backscattering diffraction (EBSD) method. The geometrically necessary dislocations (GNDs) density and statistically stored dislocations (SSDs) densities were estimate. Then the total dislocations densities are calculated and the dislocation distributions are presented as the contour maps. Estimated average dislocations density for annealed of about 2×1012 m-2 increases to 4×1013 m-2 at the middle of the groove (135° from the entrance), and they reach to 6.4×1013 m-2 at the end of groove just before ECAP region. Calculated average dislocations density for one pass severely deformed Al sample reached to 6.2×1014 m-2. At micrometer scale the behavior of metals especially mechanical properties largely depend on the dislocation density and dislocation distribution. So, yield stresses at different conditions were estimated based on the calculated dislocation densities. Then estimated yield stresses were compared with experimental results and good agreements were found. Although grain size of material did not clearly change, yield stress shown intensive increase due to the development of cell structure. A considerable increase in dislocations density in this process is a good justification for forming subgrains and cell structures during process which it can be reason of increasing in yield stress.

Decay of autoionizing states in time-dependent density functional and reduced density matrix functional theory

Energy Technology Data Exchange (ETDEWEB)

Kapoor, Varun; Brics, Martins; Bauer, Dieter [Institut fuer Physik, Universitaet Rostock, 18051 Rostock (Germany)

2013-07-01

Autoionizing states are inaccessible to time-dependent density functional theory (TDDFT) using known, adiabatic Kohn-Sham (KS) potentials. We determine the exact KS potential for a numerically exactly solvable model Helium atom interacting with a laser field that is populating an autoionizing state. The exact single-particle density of the population in the autoionizing state corresponds to that of the energetically lowest quasi-stationary state in the exact KS potential. We describe how this exact potential controls the decay by a barrier whose height and width allows for the density to tunnel out and decay with the same rate as in the ab initio time-dependent Schroedinger calculation. However, devising a useful exchange-correlation potential that is capable of governing such a scenario in general and in more complex systems is hopeless. As an improvement over TDDFT, time-dependent reduced density matrix functional theory has been proposed. We are able to obtain for the above described autoionization process the exact time-dependent natural orbitals (i.e., the eigenfunctions of the exact, time-dependent one-body reduced density matrix) and study the potentials that appear in the equations of motion for the natural orbitals and the structure of the two-body density matrix expanded in them.

Structural Reliability Using Probability Density Estimation Methods Within NESSUS

Science.gov (United States)

Chamis, Chrisos C. (Technical Monitor); Godines, Cody Ric

2003-01-01

A reliability analysis studies a mathematical model of a physical system taking into account uncertainties of design variables and common results are estimations of a response density, which also implies estimations of its parameters. Some common density parameters include the mean value, the standard deviation, and specific percentile(s) of the response, which are measures of central tendency, variation, and probability regions, respectively. Reliability analyses are important since the results can lead to different designs by calculating the probability of observing safe responses in each of the proposed designs. All of this is done at the expense of added computational time as compared to a single deterministic analysis which will result in one value of the response out of many that make up the density of the response. Sampling methods, such as monte carlo (MC) and latin hypercube sampling (LHS), can be used to perform reliability analyses and can compute nonlinear response density parameters even if the response is dependent on many random variables. Hence, both methods are very robust; however, they are computationally expensive to use in the estimation of the response density parameters. Both methods are 2 of 13 stochastic methods that are contained within the Numerical Evaluation of Stochastic Structures Under Stress (NESSUS) program. NESSUS is a probabilistic finite element analysis (FEA) program that was developed through funding from NASA Glenn Research Center (GRC). It has the additional capability of being linked to other analysis programs; therefore, probabilistic fluid dynamics, fracture mechanics, and heat transfer are only a few of what is possible with this software. The LHS method is the newest addition to the stochastic methods within NESSUS. Part of this work was to enhance NESSUS with the LHS method. The new LHS module is complete, has been successfully integrated with NESSUS, and been used to study four different test cases that have been

Scent Lure Effect on Camera-Trap Based Leopard Density Estimates.

Directory of Open Access Journals (Sweden)

Alexander Richard Braczkowski

Full Text Available Density estimates for large carnivores derived from camera surveys often have wide confidence intervals due to low detection rates. Such estimates are of limited value to authorities, which require precise population estimates to inform conservation strategies. Using lures can potentially increase detection, improving the precision of estimates. However, by altering the spatio-temporal patterning of individuals across the camera array, lures may violate closure, a fundamental assumption of capture-recapture. Here, we test the effect of scent lures on the precision and veracity of density estimates derived from camera-trap surveys of a protected African leopard population. We undertook two surveys (a 'control' and 'treatment' survey on Phinda Game Reserve, South Africa. Survey design remained consistent except a scent lure was applied at camera-trap stations during the treatment survey. Lures did not affect the maximum movement distances (p = 0.96 or temporal activity of female (p = 0.12 or male leopards (p = 0.79, and the assumption of geographic closure was met for both surveys (p >0.05. The numbers of photographic captures were also similar for control and treatment surveys (p = 0.90. Accordingly, density estimates were comparable between surveys (although estimates derived using non-spatial methods (7.28-9.28 leopards/100km2 were considerably higher than estimates from spatially-explicit methods (3.40-3.65 leopards/100km2. The precision of estimates from the control and treatment surveys, were also comparable and this applied to both non-spatial and spatial methods of estimation. Our findings suggest that at least in the context of leopard research in productive habitats, the use of lures is not warranted.

Effects of social organization, trap arrangement and density, sampling scale, and population density on bias in population size estimation using some common mark-recapture estimators.

Directory of Open Access Journals (Sweden)

Manan Gupta

Full Text Available Mark-recapture estimators are commonly used for population size estimation, and typically yield unbiased estimates for most solitary species with low to moderate home range sizes. However, these methods assume independence of captures among individuals, an assumption that is clearly violated in social species that show fission-fusion dynamics, such as the Asian elephant. In the specific case of Asian elephants, doubts have been raised about the accuracy of population size estimates. More importantly, the potential problem for the use of mark-recapture methods posed by social organization in general has not been systematically addressed. We developed an individual-based simulation framework to systematically examine the potential effects of type of social organization, as well as other factors such as trap density and arrangement, spatial scale of sampling, and population density, on bias in population sizes estimated by POPAN, Robust Design, and Robust Design with detection heterogeneity. In the present study, we ran simulations with biological, demographic and ecological parameters relevant to Asian elephant populations, but the simulation framework is easily extended to address questions relevant to other social species. We collected capture history data from the simulations, and used those data to test for bias in population size estimation. Social organization significantly affected bias in most analyses, but the effect sizes were variable, depending on other factors. Social organization tended to introduce large bias when trap arrangement was uniform and sampling effort was low. POPAN clearly outperformed the two Robust Design models we tested, yielding close to zero bias if traps were arranged at random in the study area, and when population density and trap density were not too low. Social organization did not have a major effect on bias for these parameter combinations at which POPAN gave more or less unbiased population size estimates

Improving Frozen Precipitation Density Estimation in Land Surface Modeling

Science.gov (United States)

Sparrow, K.; Fall, G. M.

2017-12-01

The Office of Water Prediction (OWP) produces high-value water supply and flood risk planning information through the use of operational land surface modeling. Improvements in diagnosing frozen precipitation density will benefit the NWS's meteorological and hydrological services by refining estimates of a significant and vital input into land surface models. A current common practice for handling the density of snow accumulation in a land surface model is to use a standard 10:1 snow-to-liquid-equivalent ratio (SLR). Our research findings suggest the possibility of a more skillful approach for assessing the spatial variability of precipitation density. We developed a 30-year SLR climatology for the coterminous US from version 3.22 of the Daily Global Historical Climatology Network - Daily (GHCN-D) dataset. Our methods followed the approach described by Baxter (2005) to estimate mean climatological SLR values at GHCN-D sites in the US, Canada, and Mexico for the years 1986-2015. In addition to the Baxter criteria, the following refinements were made: tests were performed to eliminate SLR outliers and frequent reports of SLR = 10, a linear SLR vs. elevation trend was fitted to station SLR mean values to remove the elevation trend from the data, and detrended SLR residuals were interpolated using ordinary kriging with a spherical semivariogram model. The elevation values of each station were based on the GMTED 2010 digital elevation model and the elevation trend in the data was established via linear least squares approximation. The ordinary kriging procedure was used to interpolate the data into gridded climatological SLR estimates for each calendar month at a 0.125 degree resolution. To assess the skill of this climatology, we compared estimates from our SLR climatology with observations from the GHCN-D dataset to consider the potential use of this climatology as a first guess of frozen precipitation density in an operational land surface model. The difference in

Quantum spin correction scheme based on spin-correlation functional for Kohn-Sham spin density functional theory

International Nuclear Information System (INIS)

Yamanaka, Shusuke; Takeda, Ryo; Nakata, Kazuto; Takada, Toshikazu; Shoji, Mitsuo; Kitagawa, Yasutaka; Yamaguchi, Kizashi

2007-01-01

We present a simple quantum correction scheme for ab initio Kohn-Sham spin density functional theory (KS-SDFT). This scheme is based on a mapping from ab initio results to a Heisenberg model Hamiltonian. The effective exchange integral is estimated by using energies and spin correlation functionals calculated by ab initio KS-SDFT. The quantum-corrected spin-correlation functional is open to be designed to cover specific quantum spin fluctuations. In this article, we present a simple correction for dinuclear compounds having multiple bonds. The computational results are discussed in relation to multireference (MR) DFT, by which we treat the quantum many-body effects explicitly

Self-Interaction Error in Density Functional Theory: An Appraisal.

Science.gov (United States)

Bao, Junwei Lucas; Gagliardi, Laura; Truhlar, Donald G

2018-05-03

Self-interaction error (SIE) is considered to be one of the major sources of error in most approximate exchange-correlation functionals for Kohn-Sham density-functional theory (KS-DFT), and it is large with all local exchange-correlation functionals and with some hybrid functionals. In this work, we consider systems conventionally considered to be dominated by SIE. For these systems, we demonstrate that by using multiconfiguration pair-density functional theory (MC-PDFT), the error of a translated local density-functional approximation is significantly reduced (by a factor of 3) when using an MCSCF density and on-top density, as compared to using KS-DFT with the parent functional; the error in MC-PDFT with local on-top functionals is even lower than the error in some popular KS-DFT hybrid functionals. Density-functional theory, either in MC-PDFT form with local on-top functionals or in KS-DFT form with some functionals having 50% or more nonlocal exchange, has smaller errors for SIE-prone systems than does CASSCF, which has no SIE.

Density functional theory and parallel processing

International Nuclear Information System (INIS)

Ward, R.C.; Geist, G.A.; Butler, W.H.

1987-01-01

The authors demonstrate a method for obtaining the ground state energies and charge densities of a system of atoms described within density functional theory using simulated annealing on a parallel computer

Rational Density Functional Selection Using Game Theory.

Science.gov (United States)

McAnanama-Brereton, Suzanne; Waller, Mark P

2018-01-22

Theoretical chemistry has a paradox of choice due to the availability of a myriad of density functionals and basis sets. Traditionally, a particular density functional is chosen on the basis of the level of user expertise (i.e., subjective experiences). Herein we circumvent the user-centric selection procedure by describing a novel approach for objectively selecting a particular functional for a given application. We achieve this by employing game theory to identify optimal functional/basis set combinations. A three-player (accuracy, complexity, and similarity) game is devised, through which Nash equilibrium solutions can be obtained. This approach has the advantage that results can be systematically improved by enlarging the underlying knowledge base, and the deterministic selection procedure mathematically justifies the density functional and basis set selections.

The oxygen reduction reaction mechanism on Pt(111) from density functional theory calculations

DEFF Research Database (Denmark)

Tripkovic, Vladimir; Skulason, Egill; Siahrostami, Samira

2010-01-01

We study the oxygen reduction reaction (ORR) mechanism on a Pt(1 1 1) surface using density functional theory calculations We find that at low overpotentials the surface is covered with a half dissociated water layer We estimate the barrier for proton transfer to this surface and the barrier...

Infrared thermography for wood density estimation

Science.gov (United States)

López, Gamaliel; Basterra, Luis-Alfonso; Acuña, Luis

2018-03-01

Infrared thermography (IRT) is becoming a commonly used technique to non-destructively inspect and evaluate wood structures. Based on the radiation emitted by all objects, this technique enables the remote visualization of the surface temperature without making contact using a thermographic device. The process of transforming radiant energy into temperature depends on many parameters, and interpreting the results is usually complicated. However, some works have analyzed the operation of IRT and expanded its applications, as found in the latest literature. This work analyzes the effect of density on the thermodynamic behavior of timber to be determined by IRT. The cooling of various wood samples has been registered, and a statistical procedure that enables one to quantitatively estimate the density of timber has been designed. This procedure represents a new method to physically characterize this material.

Evaluating lidar point densities for effective estimation of aboveground biomass

Science.gov (United States)

Wu, Zhuoting; Dye, Dennis G.; Stoker, Jason M.; Vogel, John M.; Velasco, Miguel G.; Middleton, Barry R.

2016-01-01

The U.S. Geological Survey (USGS) 3D Elevation Program (3DEP) was recently established to provide airborne lidar data coverage on a national scale. As part of a broader research effort of the USGS to develop an effective remote sensing-based methodology for the creation of an operational biomass Essential Climate Variable (Biomass ECV) data product, we evaluated the performance of airborne lidar data at various pulse densities against Landsat 8 satellite imagery in estimating above ground biomass for forests and woodlands in a study area in east-central Arizona, U.S. High point density airborne lidar data, were randomly sampled to produce five lidar datasets with reduced densities ranging from 0.5 to 8 point(s)/m2, corresponding to the point density range of 3DEP to provide national lidar coverage over time. Lidar-derived aboveground biomass estimate errors showed an overall decreasing trend as lidar point density increased from 0.5 to 8 points/m2. Landsat 8-based aboveground biomass estimates produced errors larger than the lowest lidar point density of 0.5 point/m2, and therefore Landsat 8 observations alone were ineffective relative to airborne lidar for generating a Biomass ECV product, at least for the forest and woodland vegetation types of the Southwestern U.S. While a national Biomass ECV product with optimal accuracy could potentially be achieved with 3DEP data at 8 points/m2, our results indicate that even lower density lidar data could be sufficient to provide a national Biomass ECV product with accuracies significantly higher than that from Landsat observations alone.

A group contribution method to estimate the densities of ionic liquids

International Nuclear Information System (INIS)

Qiao Yan; Ma Youguang; Huo Yan; Ma Peisheng; Xia Shuqian

2010-01-01

Densities of ionic liquids at different temperature and pressure were collected from 84 references. The collection contains 7381 data points derived from 123 pure ionic liquids and 13 kinds of binary ionic liquids mixtures. In terms of the collected database, a group contribution method based on 51 groups was used to predict the densities of ionic liquids. In group partition, the effect of interaction among several substitutes on the same center was considered. The same structure in different substitutes may have different group values. According to the estimation of pure ionic liquids' densities, the results show that the average relative error is 0.88% and the standard deviation (S) is 0.0181. Using the set of group values three pure ionic liquids densities were predicted, the average relative error is 0.27% and the S is 0.0048. For ionic liquid mixtures, they are thought considered as idea mixtures, so the group contribution method was used to estimate their densities and the average relative error is 1.22% with S is 0.0607. And the method can also be used to estimate the densities of MCl x type ionic liquids which are produced by mixing an ionic liquid with a Cl - anion and a kind of metal chloride.

Subsystem density functional theory with meta-generalized gradient approximation exchange-correlation functionals.

Science.gov (United States)

Śmiga, Szymon; Fabiano, Eduardo; Laricchia, Savio; Constantin, Lucian A; Della Sala, Fabio

2015-04-21

We analyze the methodology and the performance of subsystem density functional theory (DFT) with meta-generalized gradient approximation (meta-GGA) exchange-correlation functionals for non-bonded molecular systems. Meta-GGA functionals depend on the Kohn-Sham kinetic energy density (KED), which is not known as an explicit functional of the density. Therefore, they cannot be directly applied in subsystem DFT calculations. We propose a Laplacian-level approximation to the KED which overcomes this limitation and provides a simple and accurate way to apply meta-GGA exchange-correlation functionals in subsystem DFT calculations. The so obtained density and energy errors, with respect to the corresponding supermolecular calculations, are comparable with conventional approaches, depending almost exclusively on the approximations in the non-additive kinetic embedding term. An embedding energy error decomposition explains the accuracy of our method.

Use of spatial capture–recapture to estimate density of Andean bears in northern Ecuador

Science.gov (United States)

Molina, Santiago; Fuller, Angela K.; Morin, Dana J.; Royle, J. Andrew

2017-01-01

The Andean bear (Tremarctos ornatus) is the only extant species of bear in South America and is considered threatened across its range and endangered in Ecuador. Habitat loss and fragmentation is considered a critical threat to the species, and there is a lack of knowledge regarding its distribution and abundance. The species is thought to occur at low densities, making field studies designed to estimate abundance or density challenging. We conducted a pilot camera-trap study to estimate Andean bear density in a recently identified population of Andean bears northwest of Quito, Ecuador, during 2012. We compared 12 candidate spatial capture–recapture models including covariates on encounter probability and density and estimated a density of 7.45 bears/100 km2 within the region. In addition, we estimated that approximately 40 bears used a recently named Andean bear corridor established by the Secretary of Environment, and we produced a density map for this area. Use of a rub-post with vanilla scent attractant allowed us to capture numerous photographs for each event, improving our ability to identify individual bears by unique facial markings. This study provides the first empirically derived density estimate for Andean bears in Ecuador and should provide direction for future landscape-scale studies interested in conservation initiatives requiring spatially explicit estimates of density.

Uniform magnetic fields in density-functional theory

Science.gov (United States)

Tellgren, Erik I.; Laestadius, Andre; Helgaker, Trygve; Kvaal, Simen; Teale, Andrew M.

2018-01-01

We construct a density-functional formalism adapted to uniform external magnetic fields that is intermediate between conventional density functional theory and Current-Density Functional Theory (CDFT). In the intermediate theory, which we term linear vector potential-DFT (LDFT), the basic variables are the density, the canonical momentum, and the paramagnetic contribution to the magnetic moment. Both a constrained-search formulation and a convex formulation in terms of Legendre-Fenchel transformations are constructed. Many theoretical issues in CDFT find simplified analogs in LDFT. We prove results concerning N-representability, Hohenberg-Kohn-like mappings, existence of minimizers in the constrained-search expression, and a restricted analog to gauge invariance. The issue of additivity of the energy over non-interacting subsystems, which is qualitatively different in LDFT and CDFT, is also discussed.

density functional theory approach

Indian Academy of Sciences (India)

YOGESH ERANDE

2017-07-27

Jul 27, 2017 ... a key role in all optical switching devices, since their optical properties can be .... optimized in the gas phase using Density Functional Theory. (DFT).39 The ...... The Mediation of Electrostatic Effects by Sol- vents J. Am. Chem.

Source Estimation for the Damped Wave Equation Using Modulating Functions Method: Application to the Estimation of the Cerebral Blood Flow

KAUST Repository

Asiri, Sharefa M.

2017-10-19

In this paper, a method based on modulating functions is proposed to estimate the Cerebral Blood Flow (CBF). The problem is written in an input estimation problem for a damped wave equation which is used to model the spatiotemporal variations of blood mass density. The method is described and its performance is assessed through some numerical simulations. The robustness of the method in presence of noise is also studied.

State of the Art in Photon-Density Estimation

DEFF Research Database (Denmark)

Hachisuka, Toshiya; Jarosz, Wojciech; Georgiev, Iliyan

2013-01-01

scattering. Since its introduction, photon-density estimation has been significantly extended in computer graphics with the introduction of: specialized techniques that intelligently modify the positions or bandwidths to reduce visual error using a small number of photons, approaches that eliminate error...

State of the Art in Photon Density Estimation

DEFF Research Database (Denmark)

Hachisuka, Toshiya; Jarosz, Wojciech; Bouchard, Guillaume

2012-01-01

scattering. Since its introduction, photon-density estimation has been significantly extended in computer graphics with the introduction of: specialized techniques that intelligently modify the positions or bandwidths to reduce visual error using a small number of photons, approaches that eliminate error...

Strong Correlation in Kohn-Sham Density Functional Theory

NARCIS (Netherlands)

Malet, F.; Gori Giorgi, P.

2012-01-01

We use the exact strong-interaction limit of the Hohenberg-Kohn energy density functional to approximate the exchange-correlation energy of the restricted Kohn-Sham scheme. Our approximation corresponds to a highly nonlocal density functional whose functional derivative can be easily constructed,

Multiconfiguration Pair-Density Functional Theory Outperforms Kohn-Sham Density Functional Theory and Multireference Perturbation Theory for Ground-State and Excited-State Charge Transfer.

Science.gov (United States)

Ghosh, Soumen; Sonnenberger, Andrew L; Hoyer, Chad E; Truhlar, Donald G; Gagliardi, Laura

2015-08-11

The correct description of charge transfer in ground and excited states is very important for molecular interactions, photochemistry, electrochemistry, and charge transport, but it is very challenging for Kohn-Sham (KS) density functional theory (DFT). KS-DFT exchange-correlation functionals without nonlocal exchange fail to describe both ground- and excited-state charge transfer properly. We have recently proposed a theory called multiconfiguration pair-density functional theory (MC-PDFT), which is based on a combination of multiconfiguration wave function theory with a new type of density functional called an on-top density functional. Here we have used MC-PDFT to study challenging ground- and excited-state charge-transfer processes by using on-top density functionals obtained by translating KS exchange-correlation functionals. For ground-state charge transfer, MC-PDFT performs better than either the PBE exchange-correlation functional or CASPT2 wave function theory. For excited-state charge transfer, MC-PDFT (unlike KS-DFT) shows qualitatively correct behavior at long-range with great improvement in predicted excitation energies.

Functional renormalization group and Kohn-Sham scheme in density functional theory

Science.gov (United States)

Liang, Haozhao; Niu, Yifei; Hatsuda, Tetsuo

2018-04-01

Deriving accurate energy density functional is one of the central problems in condensed matter physics, nuclear physics, and quantum chemistry. We propose a novel method to deduce the energy density functional by combining the idea of the functional renormalization group and the Kohn-Sham scheme in density functional theory. The key idea is to solve the renormalization group flow for the effective action decomposed into the mean-field part and the correlation part. Also, we propose a simple practical method to quantify the uncertainty associated with the truncation of the correlation part. By taking the φ4 theory in zero dimension as a benchmark, we demonstrate that our method shows extremely fast convergence to the exact result even for the highly strong coupling regime.

How accurate are pedotransfer functions for bulk density for Brazilian soils?

Directory of Open Access Journals (Sweden)

Raquel Stucchi Boschi

Full Text Available ABSTRACT: The aim of this study was to evaluate the performance of pedotransfer functions (PTFs available in the literature to estimate soil bulk density (ρb in different regions of Brazil, using different metrics. The predictive capacity of 25 PTFs was evaluated using the mean absolute error (MAE, mean error (ME, root mean squared error (RMSE, coefficient of determination (R2 and the regression error characteristic (REC curve. The models performed differently when comparing observed and estimated ρb values. In general, the PTFs showed a performance close to the mean value of the bulk density data, considered as the simplest possible estimation of an attribute and used as a parameter to compare the performance of existing models (null model. The models developed by Benites et al. (2007 (BEN-C and by Manrique and Jones (1991 (M&J-B presented the best results. The separation of data into two layers according to depth (0-10 cm and 10-30 cm demonstrated better performance in the 10-30 cm layer. The REC curve allowed for a simple and visual evaluation of the PTFs.

Density functional theory: Foundations reviewed

Energy Technology Data Exchange (ETDEWEB)

Kryachko, Eugene S., E-mail: eugene.kryachko@ulg.ac.be [Bogolyubov Institute for Theoretical Physics, Kiev, 03680 (Ukraine); Ludeña, Eduardo V., E-mail: popluabe@yahoo.es [Centro de Química, Instituto Venezolano de Investigaciones Científicas, IVIC, Apartado 21827, Caracas 1020-A (Venezuela, Bolivarian Republic of); Prometheus Program, Senescyt (Ecuador); Grupo Ecuatoriano para el Estudio Experimental y Teórico de Nanosistemas, GETNano, USFQ, N104-E, Quito (Ecuador); Escuela Politécnica Superior del Litoral, ESPOL, Guayaquil (Ecuador)

2014-11-10

Guided by the above motto (quotation), we review a broad range of issues lying at the foundations of Density Functional Theory, DFT, a theory which is currently omnipresent in our everyday computational study of atoms and molecules, solids and nano-materials, and which lies at the heart of modern many-body computational technologies. The key goal is to demonstrate that there are definitely the ways to improve DFT. We start by considering DFT in the larger context provided by reduced density matrix theory (RDMT) and natural orbital functional theory (NOFT), and examine the implications that N-representability conditions on the second-order reduced density matrix (2-RDM) have not only on RDMT and NOFT but, also, by extension, on the functionals of DFT. This examination is timely in view of the fact that necessary and sufficient N-representability conditions on the 2-RDM have recently been attained. In the second place, we review some problems appearing in the original formulation of the first Hohenberg–Kohn theorem which is still a subject of some controversy. In this vein we recall Lieb’s comment on this proof and the extension to this proof given by Pino et al. (2009), and in this context examine the conditions that must be met in order that the one-to-one correspondence between ground-state densities and external potentials remains valid for finite subspaces (namely, the subspaces where all Kohn–Sham solutions are obtained in practical applications). We also consider the issue of whether the Kohn–Sham equations can be derived from basic principles or whether they are postulated. We examine this problem in relation to ab initio DFT. The possibility of postulating arbitrary Kohn–Sham-type equations, where the effective potential is by definition some arbitrary mixture of local and non-local terms, is discussed. We also deal with the issue of whether there exists a universal functional, or whether one should advocate instead the construction of problem

Linear scaling of density functional algorithms

International Nuclear Information System (INIS)

Stechel, E.B.; Feibelman, P.J.; Williams, A.R.

1993-01-01

An efficient density functional algorithm (DFA) that scales linearly with system size will revolutionize electronic structure calculations. Density functional calculations are reliable and accurate in determining many condensed matter and molecular ground-state properties. However, because current DFA's, including methods related to that of Car and Parrinello, scale with the cube of the system size, density functional studies are not routinely applied to large systems. Linear scaling is achieved by constructing functions that are both localized and fully occupied, thereby eliminating the need to calculate global eigenfunctions. It is, however, widely believed that exponential localization requires the existence of an energy gap between the occupied and unoccupied states. Despite this, the authors demonstrate that linear scaling can still be achieved for metals. Using a linear scaling algorithm, they have explicitly constructed localized, almost fully occupied orbitals for the quintessential metallic system, jellium. The algorithm is readily generalizable to any system geometry and Hamiltonian. They will discuss the conceptual issues involved, convergence properties and scaling for their new algorithm

Constructing valid density matrices on an NMR quantum information processor via maximum likelihood estimation

Energy Technology Data Exchange (ETDEWEB)

Singh, Harpreet; Arvind; Dorai, Kavita, E-mail: kavita@iisermohali.ac.in

2016-09-07

Estimation of quantum states is an important step in any quantum information processing experiment. A naive reconstruction of the density matrix from experimental measurements can often give density matrices which are not positive, and hence not physically acceptable. How do we ensure that at all stages of reconstruction, we keep the density matrix positive? Recently a method has been suggested based on maximum likelihood estimation, wherein the density matrix is guaranteed to be positive definite. We experimentally implement this protocol on an NMR quantum information processor. We discuss several examples and compare with the standard method of state estimation. - Highlights: • State estimation using maximum likelihood method was performed on an NMR quantum information processor. • Physically valid density matrices were obtained every time in contrast to standard quantum state tomography. • Density matrices of several different entangled and separable states were reconstructed for two and three qubits.

Density-Functional formalism

International Nuclear Information System (INIS)

Szasz, L.; Berrios-Pagan, I.; McGinn, G.

1975-01-01

A new Density-Functional formula is constructed for atoms. The kinetic energy of the electron is divided into two parts: the kinetic self-energy and the orthogonalization energy. Calculations were made for the total energies of neutral atoms, positive ions and for the He isoelectronic series. For neutral atoms the results match the Hartree-Fock energies within 1% for atoms with N 36 the results generally match the HF energies within 0.1%. For positive ions the results are fair; for the molecular applications a simplified model is developed in which the kinetic energy consists of the Weizsaecker term plus the Fermi energy reduced by a continuous function. (orig.) [de

Density-functional, density-functional tight-binding, and wave-function calculations on biomolecular systems

Czech Academy of Sciences Publication Activity Database

Kubař, Tomáš; Jurečka, Petr; Černý, Jiří; Řezáč, Jan; Otyepka, M.; Valdes, Haydee; Hobza, Pavel

2007-01-01

Roč. 111, č. 26 (2007), s. 5642-5647 ISSN 1089-5639 R&D Projects: GA MŠk LC512; GA AV ČR IAA400550510; GA ČR(CZ) GD203/05/H001; GA ČR GA203/05/0009 Institutional research plan: CEZ:AV0Z40550506 Keywords : density functional theory * empirical dispersion-energy term * non-covalent interactions Subject RIV: CF - Physical ; Theoretical Chemistry Impact factor: 2.918, year: 2007

The force distribution probability function for simple fluids by density functional theory.

Science.gov (United States)

Rickayzen, G; Heyes, D M

2013-02-28

Classical density functional theory (DFT) is used to derive a formula for the probability density distribution function, P(F), and probability distribution function, W(F), for simple fluids, where F is the net force on a particle. The final formula for P(F) ∝ exp(-AF(2)), where A depends on the fluid density, the temperature, and the Fourier transform of the pair potential. The form of the DFT theory used is only applicable to bounded potential fluids. When combined with the hypernetted chain closure of the Ornstein-Zernike equation, the DFT theory for W(F) agrees with molecular dynamics computer simulations for the Gaussian and bounded soft sphere at high density. The Gaussian form for P(F) is still accurate at lower densities (but not too low density) for the two potentials, but with a smaller value for the constant, A, than that predicted by the DFT theory.

Covariance and correlation estimation in electron-density maps.

Science.gov (United States)

Altomare, Angela; Cuocci, Corrado; Giacovazzo, Carmelo; Moliterni, Anna; Rizzi, Rosanna

2012-03-01

Quite recently two papers have been published [Giacovazzo & Mazzone (2011). Acta Cryst. A67, 210-218; Giacovazzo et al. (2011). Acta Cryst. A67, 368-382] which calculate the variance in any point of an electron-density map at any stage of the phasing process. The main aim of the papers was to associate a standard deviation to each pixel of the map, in order to obtain a better estimate of the map reliability. This paper deals with the covariance estimate between points of an electron-density map in any space group, centrosymmetric or non-centrosymmetric, no matter the correlation between the model and target structures. The aim is as follows: to verify if the electron density in one point of the map is amplified or depressed as an effect of the electron density in one or more other points of the map. High values of the covariances are usually connected with undesired features of the map. The phases are the primitive random variables of our probabilistic model; the covariance changes with the quality of the model and therefore with the quality of the phases. The conclusive formulas show that the covariance is also influenced by the Patterson map. Uncertainty on measurements may influence the covariance, particularly in the final stages of the structure refinement; a general formula is obtained taking into account both phase and measurement uncertainty, valid at any stage of the crystal structure solution.

Local and linear chemical reactivity response functions at finite temperature in density functional theory

International Nuclear Information System (INIS)

Franco-Pérez, Marco; Ayers, Paul W.; Gázquez, José L.; Vela, Alberto

2015-01-01

We explore the local and nonlocal response functions of the grand canonical potential density functional at nonzero temperature. In analogy to the zero-temperature treatment, local (e.g., the average electron density and the local softness) and nonlocal (e.g., the softness kernel) intrinsic response functions are defined as partial derivatives of the grand canonical potential with respect to its thermodynamic variables (i.e., the chemical potential of the electron reservoir and the external potential generated by the atomic nuclei). To define the local and nonlocal response functions of the electron density (e.g., the Fukui function, the linear density response function, and the dual descriptor), we differentiate with respect to the average electron number and the external potential. The well-known mathematical relationships between the intrinsic response functions and the electron-density responses are generalized to nonzero temperature, and we prove that in the zero-temperature limit, our results recover well-known identities from the density functional theory of chemical reactivity. Specific working equations and numerical results are provided for the 3-state ensemble model

Robust Estimation of Electron Density From Anatomic Magnetic Resonance Imaging of the Brain Using a Unifying Multi-Atlas Approach

Energy Technology Data Exchange (ETDEWEB)

Ren, Shangjie [Tianjin Key Laboratory of Process Measurement and Control, School of Electrical Engineering and Automation, Tianjin University, Tianjin (China); Department of Radiation Oncology, Stanford University School of Medicine, Palo Alto, California (United States); Hara, Wendy; Wang, Lei; Buyyounouski, Mark K.; Le, Quynh-Thu; Xing, Lei [Department of Radiation Oncology, Stanford University School of Medicine, Palo Alto, California (United States); Li, Ruijiang, E-mail: rli2@stanford.edu [Department of Radiation Oncology, Stanford University School of Medicine, Palo Alto, California (United States)

2017-03-15

Purpose: To develop a reliable method to estimate electron density based on anatomic magnetic resonance imaging (MRI) of the brain. Methods and Materials: We proposed a unifying multi-atlas approach for electron density estimation based on standard T1- and T2-weighted MRI. First, a composite atlas was constructed through a voxelwise matching process using multiple atlases, with the goal of mitigating effects of inherent anatomic variations between patients. Next we computed for each voxel 2 kinds of conditional probabilities: (1) electron density given its image intensity on T1- and T2-weighted MR images; and (2) electron density given its spatial location in a reference anatomy, obtained by deformable image registration. These were combined into a unifying posterior probability density function using the Bayesian formalism, which provided the optimal estimates for electron density. We evaluated the method on 10 patients using leave-one-patient-out cross-validation. Receiver operating characteristic analyses for detecting different tissue types were performed. Results: The proposed method significantly reduced the errors in electron density estimation, with a mean absolute Hounsfield unit error of 119, compared with 140 and 144 (P<.0001) using conventional T1-weighted intensity and geometry-based approaches, respectively. For detection of bony anatomy, the proposed method achieved an 89% area under the curve, 86% sensitivity, 88% specificity, and 90% accuracy, which improved upon intensity and geometry-based approaches (area under the curve: 79% and 80%, respectively). Conclusion: The proposed multi-atlas approach provides robust electron density estimation and bone detection based on anatomic MRI. If validated on a larger population, our work could enable the use of MRI as a primary modality for radiation treatment planning.

Estimating crustal thickness and Vp/Vs ratio with joint constraints of receiver function and gravity data

Science.gov (United States)

Shi, Lei; Guo, Lianghui; Ma, Yawei; Li, Yonghua; Wang, Weilai

2018-05-01

The technique of teleseismic receiver function H-κ stacking is popular for estimating the crustal thickness and Vp/Vs ratio. However, it has large uncertainty or ambiguity when the Moho multiples in receiver function are not easy to be identified. We present an improved technique to estimate the crustal thickness and Vp/Vs ratio by joint constraints of receiver function and gravity data. The complete Bouguer gravity anomalies, composed of the anomalies due to the relief of the Moho interface and the heterogeneous density distribution within the crust, are associated with the crustal thickness, density and Vp/Vs ratio. According to their relationship formulae presented by Lowry and Pérez-Gussinyé, we invert the complete Bouguer gravity anomalies by using a common algorithm of likelihood estimation to obtain the crustal thickness and Vp/Vs ratio, and then utilize them to constrain the receiver function H-κ stacking result. We verified the improved technique on three synthetic crustal models and evaluated the influence of selected parameters, the results of which demonstrated that the novel technique could reduce the ambiguity and enhance the accuracy of estimation. Real data test at two given stations in the NE margin of Tibetan Plateau illustrated that the improved technique provided reliable estimations of crustal thickness and Vp/Vs ratio.

Corruption clubs: empirical evidence from kernel density estimates

NARCIS (Netherlands)

Herzfeld, T.; Weiss, Ch.

2007-01-01

A common finding of many analytical models is the existence of multiple equilibria of corruption. Countries characterized by the same economic, social and cultural background do not necessarily experience the same levels of corruption. In this article, we use Kernel Density Estimation techniques to

Estimation of Bouguer Density Precision: Development of Method for Analysis of La Soufriere Volcano Gravity Data

Directory of Open Access Journals (Sweden)

Hendra Gunawan

2014-06-01

Full Text Available http://dx.doi.org/10.17014/ijog.vol3no3.20084The precision of topographic density (Bouguer density estimation by the Nettleton approach is based on a minimum correlation of Bouguer gravity anomaly and topography. The other method, the Parasnis approach, is based on a minimum correlation of Bouguer gravity anomaly and Bouguer correction. The precision of Bouguer density estimates was investigated by both methods on simple 2D syntetic models and under an assumption free-air anomaly consisting of an effect of topography, an effect of intracrustal, and an isostatic compensation. Based on simulation results, Bouguer density estimates were then investigated for a gravity survey of 2005 on La Soufriere Volcano-Guadeloupe area (Antilles Islands. The Bouguer density based on the Parasnis approach is 2.71 g/cm3 for the whole area, except the edifice area where average topography density estimates are 2.21 g/cm3 where Bouguer density estimates from previous gravity survey of 1975 are 2.67 g/cm3. The Bouguer density in La Soufriere Volcano was uncertainly estimated to be 0.1 g/cm3. For the studied area, the density deduced from refraction seismic data is coherent with the recent Bouguer density estimates. New Bouguer anomaly map based on these Bouguer density values allows to a better geological intepretation.    

Estimating population density and connectivity of American mink using spatial capture-recapture.

Science.gov (United States)

Fuller, Angela K; Sutherland, Chris S; Royle, J Andrew; Hare, Matthew P

2016-06-01

Estimating the abundance or density of populations is fundamental to the conservation and management of species, and as landscapes become more fragmented, maintaining landscape connectivity has become one of the most important challenges for biodiversity conservation. Yet these two issues have never been formally integrated together in a model that simultaneously models abundance while accounting for connectivity of a landscape. We demonstrate an application of using capture-recapture to develop a model of animal density using a least-cost path model for individual encounter probability that accounts for non-Euclidean connectivity in a highly structured network. We utilized scat detection dogs (Canis lupus familiaris) as a means of collecting non-invasive genetic samples of American mink (Neovison vison) individuals and used spatial capture-recapture models (SCR) to gain inferences about mink population density and connectivity. Density of mink was not constant across the landscape, but rather increased with increasing distance from city, town, or village centers, and mink activity was associated with water. The SCR model allowed us to estimate the density and spatial distribution of individuals across a 388 km² area. The model was used to investigate patterns of space usage and to evaluate covariate effects on encounter probabilities, including differences between sexes. This study provides an application of capture-recapture models based on ecological distance, allowing us to directly estimate landscape connectivity. This approach should be widely applicable to provide simultaneous direct estimates of density, space usage, and landscape connectivity for many species.

Estimating population density and connectivity of American mink using spatial capture-recapture

Science.gov (United States)

Fuller, Angela K.; Sutherland, Christopher S.; Royle, Andy; Hare, Matthew P.

2016-01-01

Estimating the abundance or density of populations is fundamental to the conservation and management of species, and as landscapes become more fragmented, maintaining landscape connectivity has become one of the most important challenges for biodiversity conservation. Yet these two issues have never been formally integrated together in a model that simultaneously models abundance while accounting for connectivity of a landscape. We demonstrate an application of using capture–recapture to develop a model of animal density using a least-cost path model for individual encounter probability that accounts for non-Euclidean connectivity in a highly structured network. We utilized scat detection dogs (Canis lupus familiaris) as a means of collecting non-invasive genetic samples of American mink (Neovison vison) individuals and used spatial capture–recapture models (SCR) to gain inferences about mink population density and connectivity. Density of mink was not constant across the landscape, but rather increased with increasing distance from city, town, or village centers, and mink activity was associated with water. The SCR model allowed us to estimate the density and spatial distribution of individuals across a 388 km2 area. The model was used to investigate patterns of space usage and to evaluate covariate effects on encounter probabilities, including differences between sexes. This study provides an application of capture–recapture models based on ecological distance, allowing us to directly estimate landscape connectivity. This approach should be widely applicable to provide simultaneous direct estimates of density, space usage, and landscape connectivity for many species.

An analytical framework for estimating aquatic species density from environmental DNA

Science.gov (United States)

Chambert, Thierry; Pilliod, David S.; Goldberg, Caren S.; Doi, Hideyuki; Takahara, Teruhiko

2018-01-01

Environmental DNA (eDNA) analysis of water samples is on the brink of becoming a standard monitoring method for aquatic species. This method has improved detection rates over conventional survey methods and thus has demonstrated effectiveness for estimation of site occupancy and species distribution. The frontier of eDNA applications, however, is to infer species density. Building upon previous studies, we present and assess a modeling approach that aims at inferring animal density from eDNA. The modeling combines eDNA and animal count data from a subset of sites to estimate species density (and associated uncertainties) at other sites where only eDNA data are available. As a proof of concept, we first perform a cross-validation study using experimental data on carp in mesocosms. In these data, fish densities are known without error, which allows us to test the performance of the method with known data. We then evaluate the model using field data from a study on a stream salamander species to assess the potential of this method to work in natural settings, where density can never be known with absolute certainty. Two alternative distributions (Normal and Negative Binomial) to model variability in eDNA concentration data are assessed. Assessment based on the proof of concept data (carp) revealed that the Negative Binomial model provided much more accurate estimates than the model based on a Normal distribution, likely because eDNA data tend to be overdispersed. Greater imprecision was found when we applied the method to the field data, but the Negative Binomial model still provided useful density estimates. We call for further model development in this direction, as well as further research targeted at sampling design optimization. It will be important to assess these approaches on a broad range of study systems.

A Safari Through Density Functional Theory

Science.gov (United States)

Dreizler, Reiner M.; Lüdde, Cora S.

Density functional theory is widely used to treat quantum many body problems in many areas of physics and related fields. A brief survey of this method covering foundations, functionals and applications is presented here.

THE X-RAY POWER SPECTRAL DENSITY FUNCTION AND BLACK HOLE MASS ESTIMATE FOR THE SEYFERT ACTIVE GALACTIC NUCLEUS IC 4329a

International Nuclear Information System (INIS)

Markowitz, A.

2009-01-01

We present the X-ray broadband power spectral density function (PSD) of the X-ray-luminous Seyfert IC 4329a, constructed from light curves obtained via Rossi X-ray Timing Explorer monitoring and an XMM-Newton observation. Modeling the 3-10 keV PSD using a broken power-law PSD shape, a break in power-law slope is significantly detected at a temporal frequency of 2.5 +2.5 -1.7 x 10 -6 Hz, which corresponds to a PSD break timescale T b of 4.6 +10.1 -2.3 days. Using the relation between T b , black hole mass M BH , and bolometric luminosity as quantified by McHardy and coworkers, we infer a black hole mass estimate of M BH = 1.3 +1.0 -0.3 x 10 8 M sun and an accretion rate relative to Eddington of 0.21 +0.06 -0.10 for this source. Our estimate of M BH is consistent with other estimates, including that derived by the relation between M BH and stellar velocity dispersion. We also present PSDs for the 10-20 and 20-40 keV bands; they lack sufficient temporal frequency coverage to reveal a significant break, but are consistent with the same PSD shape and break frequency as in the 3-10 keV band.

Spatial pattern corrections and sample sizes for forest density estimates of historical tree surveys

Science.gov (United States)

Brice B. Hanberry; Shawn Fraver; Hong S. He; Jian Yang; Dan C. Dey; Brian J. Palik

2011-01-01

The U.S. General Land Office land surveys document trees present during European settlement. However, use of these surveys for calculating historical forest density and other derived metrics is limited by uncertainty about the performance of plotless density estimators under a range of conditions. Therefore, we tested two plotless density estimators, developed by...

Comparison of exact-exchange calculations for solids in current-spin-density- and spin-density-functional theory

DEFF Research Database (Denmark)

Sharma, S.; Pittalis, S.; Kurth, S.

2007-01-01

The relative merits of current-spin-density- and spin-density-functional theory are investigated for solids treated within the exact-exchange-only approximation. Spin-orbit splittings and orbital magnetic moments are determined at zero external magnetic field. We find that for magnetic (Fe, Co......, and Ni) and nonmagnetic (Si and Ge) solids, the exact-exchange current-spin-density functional approach does not significantly improve the accuracy of the corresponding spin-density functional results....

Benchmarking density-functional-theory calculations of rotational g tensors and magnetizabilities using accurate coupled-cluster calculations.

Science.gov (United States)

Lutnaes, Ola B; Teale, Andrew M; Helgaker, Trygve; Tozer, David J; Ruud, Kenneth; Gauss, Jürgen

2009-10-14

An accurate set of benchmark rotational g tensors and magnetizabilities are calculated using coupled-cluster singles-doubles (CCSD) theory and coupled-cluster single-doubles-perturbative-triples [CCSD(T)] theory, in a variety of basis sets consisting of (rotational) London atomic orbitals. The accuracy of the results obtained is established for the rotational g tensors by careful comparison with experimental data, taking into account zero-point vibrational corrections. After an analysis of the basis sets employed, extrapolation techniques are used to provide estimates of the basis-set-limit quantities, thereby establishing an accurate benchmark data set. The utility of the data set is demonstrated by examining a wide variety of density functionals for the calculation of these properties. None of the density-functional methods are competitive with the CCSD or CCSD(T) methods. The need for a careful consideration of vibrational effects is clearly illustrated. Finally, the pure coupled-cluster results are compared with the results of density-functional calculations constrained to give the same electronic density. The importance of current dependence in exchange-correlation functionals is discussed in light of this comparison.

Dynamical density functional theory for dense atomic liquids

International Nuclear Information System (INIS)

Archer, A J

2006-01-01

Starting from Newton's equations of motion, we derive a dynamical density functional theory (DDFT) applicable to atomic liquids. The theory has the feature that it requires as input the Helmholtz free energy functional from equilibrium density functional theory. This means that, given a reliable equilibrium free energy functional, the correct equilibrium fluid density profile is guaranteed. We show that when the isothermal compressibility is small, the DDFT generates the correct value for the speed of sound in a dense liquid. We also interpret the theory as a dynamical equation for a coarse grained fluid density and show that the theory can be used (making further approximations) to derive the standard mode coupling theory that is used to describe the glass transition. The present theory should provide a useful starting point for describing the dynamics of inhomogeneous atomic fluids

Simple descriptors for proton-conducting perovskites from density functional theory

DEFF Research Database (Denmark)

Bork, Nicolai Christian; Bonanos, Nikolaos; Rossmeisl, Jan

2010-01-01

series of (pseudo)cubic perovskites, ABO3, have been investigated using density functional theory calculations. The structures have been optimized and thermodynamic properties and activation energies for the relevant steps of the hydrogen/proton diffusion mechanism have been calculated using...... the nudged elastic band path technique. We find a strong correlation between the O-H binding energy for hydrogen/proton uptake in perovskites and the energy barriers involved in the observed Grotthuss-type diffusion process. We demonstrate the possibility of estimating diffusion rates based on O-H binding...

Constructive definition of functional derivatives in density-functional theory

International Nuclear Information System (INIS)

Luo Ji

2006-01-01

It is shown that the functional derivatives in density-functional theory (DFT) can be explicitly defined within the domain of electron densities restricted by the electron number, and a constructive definition of such restricted derivatives is suggested. With this definition, Kohn-Sham (KS) equations can be established for an N-electron system without extending the functional domain and introducing a Lagrange multiplier. This may clarify some of the fundamental questions raised by Nesbet (1998 Phys. Rev. A 58 R12). The definition naturally leads to the fact that the KS effective potential is determined only to within an additive constant, thus the KS levels can shift freely and the relation between the highest occupied molecular orbital (HOMO) energy and the ionization potential of the system depends on the choice of the constant. On the other hand, if the domain of functionals is indeed extended beyond the electron number restriction, conclusions depend on whether the extended functionals have unrestricted derivatives or not. It is shown that the ensemble extension of DFT to open systems of mixed states (Perdew et al 1982 Phys. Rev. Lett. 49 1691) leads to an energy functional which has no unrestricted derivative at integer electron numbers. Hence after this extension, the relation between the HOMO energy and the ionization potential for an N-electron system is still uncertain. Besides, there are different extensions of the energy functional to a domain of densities unrestricted by the integer electron number, resulting in different unrestricted derivatives and electron systems with different chemical potentials. Even for the exact exchange-correlation potential, there is still an undetermined constant, whether it is a restricted or unrestricted derivative

Density functional theory in quantum chemistry

CERN Document Server

Tsuneda, Takao

2014-01-01

This book examines density functional theory based on the foundation of quantum chemistry. Unconventional in approach, it reviews basic concepts, then describes the physical meanings of state-of-the-art exchange-correlation functionals and their corrections.

Comment on 'Kinetic energy as a density functional'

International Nuclear Information System (INIS)

Holas, A.; March, N.H.

2002-01-01

In a recent paper, Nesbet [Phys. Rev. A 65, 010502(R) (2001)] has proposed dropping ''the widespread but unjustified assumption that the existence of a ground-state density functional for the kinetic energy, T s [ρ], of an N-electron system implies the existence of a density-functional derivative, δT s [ρ]/δρ(r), equivalent to a local potential function,'' because, according to his arguments, this derivative 'has the mathematical character of a linear operator that acts on orbital wave functions'. Our Comment demonstrates that the statement called by Nesbet an 'unjustified assumption' happens, in fact, to be a rigorously proven theorem. Therefore, his previous conclusions stemming from his different view of this derivative, which undermined the foundations of density-functional theory, can be discounted

SYNTHESIS, CHARACTERIZATION AND DENSITY FUNCTIONAL ...

African Journals Online (AJOL)

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We synthesized a number of aniline derivatives containing acyl groups to compare their barriers of rotation around ... KEY WORDS: Monoacyl aniline, Synthesis, Density functional theory, Rotation barrier. INTRODUCTION. Developments in ...

Density functional approach to the many-body problem : Key concepts and exact functionals

NARCIS (Netherlands)

van Leeuwen, Robert

2003-01-01

We give an overview of the fundamental concepts of density functional theory. We give a careful discussion of the several density functionals and their differentiability properties. We show that for nondegenerate ground states we can calculate the necessary functional derivatives by means of linear

Extended screened exchange functional derived from transcorrelated density functional theory.

Science.gov (United States)

Umezawa, Naoto

2017-09-14

We propose a new formulation of the correlation energy functional derived from the transcorrelated method in use in density functional theory (TC-DFT). An effective Hamiltonian, H TC , is introduced by a similarity transformation of a many-body Hamiltonian, H, with respect to a complex function F: H TC =1FHF. It is proved that an expectation value of H TC for a normalized single Slater determinant, D n , corresponds to the total energy: E[n] = ⟨Ψ n |H|Ψ n ⟩/⟨Ψ n |Ψ n ⟩ = ⟨D n |H TC |D n ⟩ under the two assumptions: (1) The electron density nr associated with a trial wave function Ψ n = D n F is v-representable and (2) Ψ n and D n give rise to the same electron density nr. This formulation, therefore, provides an alternative expression of the total energy that is useful for the development of novel correlation energy functionals. By substituting a specific function for F, we successfully derived a model correlation energy functional, which resembles the functional form of the screened exchange method. The proposed functional, named the extended screened exchange (ESX) functional, is described within two-body integrals and is parametrized for a numerically exact correlation energy of the homogeneous electron gas. The ESX functional does not contain any ingredients of (semi-)local functionals and thus is totally free from self-interactions. The computational cost for solving the self-consistent-field equation is comparable to that of the Hartree-Fock method. We apply the ESX functional to electronic structure calculations for a solid silicon, H - ion, and small atoms. The results demonstrate that the TC-DFT formulation is promising for the systematic improvement of the correlation energy functional.

Quantum Crystallography: Density Matrix-Density Functional Theory and the X-Ray Diffraction Experiment

Science.gov (United States)

Soirat, Arnaud J. A.

Density Matrix Theory is a Quantum Mechanical formalism in which the wavefunction is eliminated and its role taken over by reduced density matrices. The interest of this is that, it allows one, in principle, to calculate any electronic property of a physical system, without having to solve the Schrodinger equation, using only two entities much simpler than an N-body wavefunction: first and second -order reduced density matrices. In practice, though, this very promising possibility faces the tremendous theoretical problem of N-representability, which has been solved for the former, but, until now, voids any hope of theoretically determining the latter. However, it has been shown that single determinant reduced density matrices of any order may be recovered from coherent X-ray diffraction data, if one provides a proper Quantum Mechanical description of the Crystallography experiment. A deeper investigation of this method is the purpose of this work, where we, first, further study the calculation of X-ray reduced density matrices N-representable by a single Slater determinant. In this context, we independently derive necessary and sufficient conditions for the uniqueness of the method. We then show how to account for electron correlation in this model. For the first time, indeed, we derive highly accurate, yet practical, density matrices approximately N-representable by correlated-determinant wavefunctions. The interest of such a result lies in the Quantum Mechanical validity of these density matrices, their property of being entirely obtainable from X-ray coherent diffraction data, their very high accuracy conferred by this known property of the N-representing wavefunction, as well as their definition as explicit functionals of the density. All of these properties are finally used in both a theoretical and a numerical application: in the former, we show that these density matrices may be used in the context of Density Functional Theory to highly accurately determine

Density functional theory of nuclei

International Nuclear Information System (INIS)

Terasaki, Jun

2008-01-01

The density functional theory of nuclei has come to draw attention of scientists in the field of nuclear structure because the theory is expected to provide reliable numerical data in wide range on the nuclear chart. This article is organized to present an overview of the theory to the people engaged in the theory of other fields as well as those people in the nuclear physics experiments. At first, the outline of the density functional theory widely used in the electronic systems (condensed matter, atoms, and molecules) was described starting from the Kohn-Sham equation derived on the variational principle. Then the theory used in the field of nuclear physics was presented. Hartree-Fock and Hartree-Fock-Bogolyubov approximation by using Skyrme interaction was explained. Comparison of the results of calculations and experiments of binding energies and ground state mean square charge radii of some magic number nuclei were shown. The similarity and dissimilarity between the two streams were summarized. Finally the activities of the international project of Universal Nuclear Energy Density Functional (UNEDF) which was started recently lead by US scientist was reported. This project is programmed for five years. One of the applications of the project is the calculation of the neutron capture cross section of nuclei on the r-process, which is absolutely necessary for the nucleosynthesis research. (S. Funahashi)

Performance of exchange-correlation functionals in density functional theory calculations for liquid metal: A benchmark test for sodium

Science.gov (United States)

Han, Jeong-Hwan; Oda, Takuji

2018-04-01

The performance of exchange-correlation functionals in density-functional theory (DFT) calculations for liquid metal has not been sufficiently examined. In the present study, benchmark tests of Perdew-Burke-Ernzerhof (PBE), Armiento-Mattsson 2005 (AM05), PBE re-parameterized for solids, and local density approximation (LDA) functionals are conducted for liquid sodium. The pair correlation function, equilibrium atomic volume, bulk modulus, and relative enthalpy are evaluated at 600 K and 1000 K. Compared with the available experimental data, the errors range from -11.2% to 0.0% for the atomic volume, from -5.2% to 22.0% for the bulk modulus, and from -3.5% to 2.5% for the relative enthalpy depending on the DFT functional. The generalized gradient approximation functionals are superior to the LDA functional, and the PBE and AM05 functionals exhibit the best performance. In addition, we assess whether the error tendency in liquid simulations is comparable to that in solid simulations, which would suggest that the atomic volume and relative enthalpy performances are comparable between solid and liquid states but that the bulk modulus performance is not. These benchmark test results indicate that the results of liquid simulations are significantly dependent on the exchange-correlation functional and that the DFT functional performance in solid simulations can be used to roughly estimate the performance in liquid simulations.

Reliability and precision of pellet-group counts for estimating landscape-level deer density

Science.gov (United States)

David S. deCalesta

2013-01-01

This study provides hitherto unavailable methodology for reliably and precisely estimating deer density within forested landscapes, enabling quantitative rather than qualitative deer management. Reliability and precision of the deer pellet-group technique were evaluated in 1 small and 2 large forested landscapes. Density estimates, adjusted to reflect deer harvest and...

Cortical cell and neuron density estimates in one chimpanzee hemisphere.

Science.gov (United States)

Collins, Christine E; Turner, Emily C; Sawyer, Eva Kille; Reed, Jamie L; Young, Nicole A; Flaherty, David K; Kaas, Jon H

2016-01-19

The density of cells and neurons in the neocortex of many mammals varies across cortical areas and regions. This variability is, perhaps, most pronounced in primates. Nonuniformity in the composition of cortex suggests regions of the cortex have different specializations. Specifically, regions with densely packed neurons contain smaller neurons that are activated by relatively few inputs, thereby preserving information, whereas regions that are less densely packed have larger neurons that have more integrative functions. Here we present the numbers of cells and neurons for 742 discrete locations across the neocortex in a chimpanzee. Using isotropic fractionation and flow fractionation methods for cell and neuron counts, we estimate that neocortex of one hemisphere contains 9.5 billion cells and 3.7 billion neurons. Primary visual cortex occupies 35 cm(2) of surface, 10% of the total, and contains 737 million densely packed neurons, 20% of the total neurons contained within the hemisphere. Other areas of high neuron packing include secondary visual areas, somatosensory cortex, and prefrontal granular cortex. Areas of low levels of neuron packing density include motor and premotor cortex. These values reflect those obtained from more limited samples of cortex in humans and other primates.

Regularized Regression and Density Estimation based on Optimal Transport

KAUST Repository

Burger, M.; Franek, M.; Schonlieb, C.-B.

2012-01-01

for estimating densities and for preserving edges in the case of total variation regularization. In order to compute solutions of the variational problems, a regularized optimal transport problem needs to be solved, for which we discuss several formulations

Audio Query by Example Using Similarity Measures between Probability Density Functions of Features

Directory of Open Access Journals (Sweden)

Marko Helén

2010-01-01

Full Text Available This paper proposes a query by example system for generic audio. We estimate the similarity of the example signal and the samples in the queried database by calculating the distance between the probability density functions (pdfs of their frame-wise acoustic features. Since the features are continuous valued, we propose to model them using Gaussian mixture models (GMMs or hidden Markov models (HMMs. The models parametrize each sample efficiently and retain sufficient information for similarity measurement. To measure the distance between the models, we apply a novel Euclidean distance, approximations of Kullback-Leibler divergence, and a cross-likelihood ratio test. The performance of the measures was tested in simulations where audio samples are automatically retrieved from a general audio database, based on the estimated similarity to a user-provided example. The simulations show that the distance between probability density functions is an accurate measure for similarity. Measures based on GMMs or HMMs are shown to produce better results than that of the existing methods based on simpler statistics or histograms of the features. A good performance with low computational cost is obtained with the proposed Euclidean distance.

Current Density Functional Theory Using Meta-Generalized Gradient Exchange-Correlation Functionals.

Science.gov (United States)

Furness, James W; Verbeke, Joachim; Tellgren, Erik I; Stopkowicz, Stella; Ekström, Ulf; Helgaker, Trygve; Teale, Andrew M

2015-09-08

We present the self-consistent implementation of current-dependent (hybrid) meta-generalized gradient approximation (mGGA) density functionals using London atomic orbitals. A previously proposed generalized kinetic energy density is utilized to implement mGGAs in the framework of Kohn-Sham current density functional theory (KS-CDFT). A unique feature of the nonperturbative implementation of these functionals is the ability to seamlessly explore a wide range of magnetic fields up to 1 au (∼235 kT) in strength. CDFT functionals based on the TPSS and B98 forms are investigated, and their performance is assessed by comparison with accurate coupled-cluster singles, doubles, and perturbative triples (CCSD(T)) data. In the weak field regime, magnetic properties such as magnetizabilities and nuclear magnetic resonance shielding constants show modest but systematic improvements over generalized gradient approximations (GGA). However, in the strong field regime, the mGGA-based forms lead to a significantly improved description of the recently proposed perpendicular paramagnetic bonding mechanism, comparing well with CCSD(T) data. In contrast to functionals based on the vorticity, these forms are found to be numerically stable, and their accuracy at high field suggests that the extension of mGGAs to CDFT via the generalized kinetic energy density should provide a useful starting point for further development of CDFT approximations.

On the estimation of the current density in space plasmas: Multi- versus single-point techniques

Science.gov (United States)

Perri, Silvia; Valentini, Francesco; Sorriso-Valvo, Luca; Reda, Antonio; Malara, Francesco

2017-06-01

Thanks to multi-spacecraft mission, it has recently been possible to directly estimate the current density in space plasmas, by using magnetic field time series from four satellites flying in a quasi perfect tetrahedron configuration. The technique developed, commonly called ;curlometer; permits a good estimation of the current density when the magnetic field time series vary linearly in space. This approximation is generally valid for small spacecraft separation. The recent space missions Cluster and Magnetospheric Multiscale (MMS) have provided high resolution measurements with inter-spacecraft separation up to 100 km and 10 km, respectively. The former scale corresponds to the proton gyroradius/ion skin depth in ;typical; solar wind conditions, while the latter to sub-proton scale. However, some works have highlighted an underestimation of the current density via the curlometer technique with respect to the current computed directly from the velocity distribution functions, measured at sub-proton scales resolution with MMS. In this paper we explore the limit of the curlometer technique studying synthetic data sets associated to a cluster of four artificial satellites allowed to fly in a static turbulent field, spanning a wide range of relative separation. This study tries to address the relative importance of measuring plasma moments at very high resolution from a single spacecraft with respect to the multi-spacecraft missions in the current density evaluation.

Using bremsstrahlung for electron density estimation and correction in EAST tokamak

Energy Technology Data Exchange (ETDEWEB)

Chen, Yingjie, E-mail: bestfaye@gmail.com; Wu, Zhenwei; Gao, Wei; Jie, Yinxian; Zhang, Jizong; Huang, Juan; Zhang, Ling; Zhao, Junyu

2013-11-15

Highlights: • The visible bremsstrahlung diagnostic provides a simple and effective tool for electron density estimation in steady state discharges. • This method can make up some disadvantages of present FIR and TS diagnostics in EAST tokamak. • Line averaged electron density has been deduced from central VB signal. The results can also be used for FIR n{sub e} correction. • Typical n{sub e} profiles have been obtained with T{sub e} and reconstructed bremsstrahlung profiles. -- Abstract: In EAST electron density (n{sub e}) is measured by the multi-channel far-infrared (FIR) hydrogen cyanide (HCN) interferometer and Thomson scattering (TS) diagnostics. However, it is difficult to obtain accurate n{sub e} profile for that there are many problems existing in current electron density diagnostics. Since the visible bremsstrahlung (VB) emission coefficient has a strong dependence on electron density, the visible bremsstrahlung measurement system developed to determine the ion effective charge (Z{sub eff}) may also be used for n{sub e} estimation via inverse operations. With assumption that Z{sub eff} has a flat profile and does not change significantly in steady state discharges, line averaged electron density (n{sup ¯}{sub e}) has been deduced from VB signals in L-mode and H-mode discharges in EAST. The results are in good coincidence with n{sup ¯}{sub e} from FIR, which proves that VB measurement is an effective tool for n{sub e} estimation. VB diagnostic is also applied to n{sup ¯}{sub e} correction when FIR n{sup ¯}{sub e} is wrong for the laser phase shift reversal together with noise causes errors when electron density changed rapidly in the H-mode discharges. Typical n{sub e} profiles in L-mode and H-mode phase are also deduced with reconstructed bremsstrahlung profiles.

Comments on the locality in density-functional theory

International Nuclear Information System (INIS)

Lindgren, Ingvar; Salomonson, Sten

2003-01-01

The 'locality hypothesis' in density-functional theory (DFT), implying that the functional derivative is equivalent to a multiplicative local function, forms the basis of models of Kohn-Sham type. This has been generally accepted by the community since the advent of the model, and has later been formally proved for a large class of functionals. The hypothesis has recently been questioned by Nesbet [Phys. Rev. A 58, R12 (1998) and Phys. Rev. A 65, 010502 (2001)], who claims that it fails for the kinetic-energy functional for a system with more than two noninteracting electrons with a nondegenerate ground state. This conclusion has been questioned by Gal [Phys. Rev. A 62, 044501 (2000)] and by Holas and March [Phys. Rev. A 64, 016501 (2001)]. We claim that the arguments of Nesbet are incorrect, since the orbital functional used for the kinetic energy is not a unique functional of the total density in the domain of unnormalized orbitals. We have demonstrated that with a proper definition of the kinetic energy, which is a unique density functional also in the unnormalized region, the derivative can be represented by a single local multiplicative function for all v-representable densities. Therefore, we consider the controversy connected with the issue raised by Nesbet as resolved. We believe that the proof of the differentiability given here can be extended to larger groups of DFT functionals, and works along these lines are in progress

Importance of tree basic density in biomass estimation and associated uncertainties

DEFF Research Database (Denmark)

Njana, Marco Andrew; Meilby, Henrik; Eid, Tron

2016-01-01

Key message Aboveground and belowground tree basic densities varied between and within the three mangrove species. If appropriately determined and applied, basic density may be useful in estimation of tree biomass. Predictive accuracy of the common (i.e. multi-species) models including aboveground...... of sustainable forest management, conservation and enhancement of carbon stocks (REDD+) initiatives offer an opportunity for sustainable management of forests including mangroves. In carbon accounting for REDD+, it is required that carbon estimates prepared for monitoring reporting and verification schemes...... and examine uncertainties in estimation of tree biomass using indirect methods. Methods This study focused on three dominant mangrove species (Avicennia marina (Forssk.) Vierh, Sonneratia alba J. Smith and Rhizophora mucronata Lam.) in Tanzania. A total of 120 trees were destructively sampled for aboveground...

Estimating the Partition Function Zeros by Using the Wang-Landau Monte Carlo Algorithm

Energy Technology Data Exchange (ETDEWEB)

Kim, Seung-Yeon [Korea National University of Transportation, Chungju (Korea, Republic of)

2017-03-15

The concept of the partition function zeros is one of the most efficient methods for investigating the phase transitions and the critical phenomena in various physical systems. Estimating the partition function zeros requires information on the density of states Ω(E) as a function of the energy E. Currently, the Wang-Landau Monte Carlo algorithm is one of the best methods for calculating Ω(E). The partition function zeros in the complex temperature plane of the Ising model on an L × L square lattice (L = 10 ∼ 80) with a periodic boundary condition have been estimated by using the Wang-Landau Monte Carlo algorithm. The efficiency of the Wang-Landau Monte Carlo algorithm and the accuracies of the partition function zeros have been evaluated for three different, 5%, 10%, and 20%, flatness criteria for the histogram H(E).

Multi-objective mixture-based iterated density estimation evolutionary algorithms

NARCIS (Netherlands)

Thierens, D.; Bosman, P.A.N.

2001-01-01

We propose an algorithm for multi-objective optimization using a mixture-based iterated density estimation evolutionary algorithm (MIDEA). The MIDEA algorithm is a prob- abilistic model building evolutionary algo- rithm that constructs at each generation a mixture of factorized probability

EuroMInd-D: A Density Estimate of Monthly Gross Domestic Product for the Euro Area

DEFF Research Database (Denmark)

Proietti, Tommaso; Marczak, Martyna; Mazzi, Gianluigi

EuroMInd-D is a density estimate of monthly gross domestic product (GDP) constructed according to a bottom–up approach, pooling the density estimates of eleven GDP components, by output and expenditure type. The components density estimates are obtained from a medium-size dynamic factor model...... of a set of coincident time series handling mixed frequencies of observation and ragged–edged data structures. They reflect both parameter and filtering uncertainty and are obtained by implementing a bootstrap algorithm for simulating from the distribution of the maximum likelihood estimators of the model...

Trivial constraints on orbital-free kinetic energy density functionals

Science.gov (United States)

Luo, Kai; Trickey, S. B.

2018-03-01

Approximate kinetic energy density functionals (KEDFs) are central to orbital-free density functional theory. Limitations on the spatial derivative dependencies of KEDFs have been claimed from differential virial theorems. We identify a central defect in the argument: the relationships are not true for an arbitrary density but hold only for the minimizing density and corresponding chemical potential. Contrary to the claims therefore, the relationships are not constraints and provide no independent information about the spatial derivative dependencies of approximate KEDFs. A simple argument also shows that validity for arbitrary v-representable densities is not restored by appeal to the density-potential bijection.

Quantifying confidence in density functional theory predictions of magnetic ground states

Science.gov (United States)

Houchins, Gregory; Viswanathan, Venkatasubramanian

2017-10-01

Density functional theory (DFT) simulations, at the generalized gradient approximation (GGA) level, are being routinely used for material discovery based on high-throughput descriptor-based searches. The success of descriptor-based material design relies on eliminating bad candidates and keeping good candidates for further investigation. While DFT has been widely successfully for the former, oftentimes good candidates are lost due to the uncertainty associated with the DFT-predicted material properties. Uncertainty associated with DFT predictions has gained prominence and has led to the development of exchange correlation functionals that have built-in error estimation capability. In this work, we demonstrate the use of built-in error estimation capabilities within the BEEF-vdW exchange correlation functional for quantifying the uncertainty associated with the magnetic ground state of solids. We demonstrate this approach by calculating the uncertainty estimate for the energy difference between the different magnetic states of solids and compare them against a range of GGA exchange correlation functionals as is done in many first-principles calculations of materials. We show that this estimate reasonably bounds the range of values obtained with the different GGA functionals. The estimate is determined as a postprocessing step and thus provides a computationally robust and systematic approach to estimating uncertainty associated with predictions of magnetic ground states. We define a confidence value (c-value) that incorporates all calculated magnetic states in order to quantify the concurrence of the prediction at the GGA level and argue that predictions of magnetic ground states from GGA level DFT is incomplete without an accompanying c-value. We demonstrate the utility of this method using a case study of Li-ion and Na-ion cathode materials and the c-value metric correctly identifies that GGA-level DFT will have low predictability for NaFePO4F . Further, there

Self-consistent embedding of density-matrix renormalization group wavefunctions in a density functional environment.

Science.gov (United States)

Dresselhaus, Thomas; Neugebauer, Johannes; Knecht, Stefan; Keller, Sebastian; Ma, Yingjin; Reiher, Markus

2015-01-28

We present the first implementation of a density matrix renormalization group algorithm embedded in an environment described by density functional theory. The frozen density embedding scheme is used with a freeze-and-thaw strategy for a self-consistent polarization of the orbital-optimized wavefunction and the environmental densities with respect to each other.

Rydberg energies using excited state density functional theory

International Nuclear Information System (INIS)

Cheng, C.-L.; Wu Qin; Van Voorhis, Troy

2008-01-01

We utilize excited state density functional theory (eDFT) to study Rydberg states in atoms. We show both analytically and numerically that semilocal functionals can give quite reasonable Rydberg energies from eDFT, even in cases where time dependent density functional theory (TDDFT) fails catastrophically. We trace these findings to the fact that in eDFT the Kohn-Sham potential for each state is computed using the appropriate excited state density. Unlike the ground state potential, which typically falls off exponentially, the sequence of excited state potentials has a component that falls off polynomially with distance, leading to a Rydberg-type series. We also address the rigorous basis of eDFT for these systems. Perdew and Levy have shown using the constrained search formalism that every stationary density corresponds, in principle, to an exact stationary state of the full many-body Hamiltonian. In the present context, this means that the excited state DFT solutions are rigorous as long as they deliver the minimum noninteracting kinetic energy for the given density. We use optimized effective potential techniques to show that, in some cases, the eDFT Rydberg solutions appear to deliver the minimum kinetic energy because the associated density is not pure state v-representable. We thus find that eDFT plays a complementary role to constrained DFT: The former works only if the excited state density is not the ground state of some potential while the latter applies only when the density is a ground state density.

Estimating abundance and density of Amur tigers along the Sino-Russian border.

Science.gov (United States)

Xiao, Wenhong; Feng, Limin; Mou, Pu; Miquelle, Dale G; Hebblewhite, Mark; Goldberg, Joshua F; Robinson, Hugh S; Zhao, Xiaodan; Zhou, Bo; Wang, Tianming; Ge, Jianping

2016-07-01

As an apex predator the Amur tiger (Panthera tigris altaica) could play a pivotal role in maintaining the integrity of forest ecosystems in Northeast Asia. Due to habitat loss and harvest over the past century, tigers rapidly declined in China and are now restricted to the Russian Far East and bordering habitat in nearby China. To facilitate restoration of the tiger in its historical range, reliable estimates of population size are essential to assess effectiveness of conservation interventions. Here we used camera trap data collected in Hunchun National Nature Reserve from April to June 2013 and 2014 to estimate tiger density and abundance using both maximum likelihood and Bayesian spatially explicit capture-recapture (SECR) methods. A minimum of 8 individuals were detected in both sample periods and the documentation of marking behavior and reproduction suggests the presence of a resident population. Using Bayesian SECR modeling within the 11 400 km(2) state space, density estimates were 0.33 and 0.40 individuals/100 km(2) in 2013 and 2014, respectively, corresponding to an estimated abundance of 38 and 45 animals for this transboundary Sino-Russian population. In a maximum likelihood framework, we estimated densities of 0.30 and 0.24 individuals/100 km(2) corresponding to abundances of 34 and 27, in 2013 and 2014, respectively. These density estimates are comparable to other published estimates for resident Amur tiger populations in the Russian Far East. This study reveals promising signs of tiger recovery in Northeast China, and demonstrates the importance of connectivity between the Russian and Chinese populations for recovering tigers in Northeast China. © 2016 International Society of Zoological Sciences, Institute of Zoology/Chinese Academy of Sciences and John Wiley & Sons Australia, Ltd.

Estimating peer density effects on oral health for community-based older adults.

Science.gov (United States)

Chakraborty, Bibhas; Widener, Michael J; Mirzaei Salehabadi, Sedigheh; Northridge, Mary E; Kum, Susan S; Jin, Zhu; Kunzel, Carol; Palmer, Harvey D; Metcalf, Sara S

2017-12-29

As part of a long-standing line of research regarding how peer density affects health, researchers have sought to understand the multifaceted ways that the density of contemporaries living and interacting in proximity to one another influence social networks and knowledge diffusion, and subsequently health and well-being. This study examined peer density effects on oral health for racial/ethnic minority older adults living in northern Manhattan and the Bronx, New York, NY. Peer age-group density was estimated by smoothing US Census data with 4 kernel bandwidths ranging from 0.25 to 1.50 mile. Logistic regression models were developed using these spatial measures and data from the ElderSmile oral and general health screening program that serves predominantly racial/ethnic minority older adults at community centers in northern Manhattan and the Bronx. The oral health outcomes modeled as dependent variables were ordinal dentition status and binary self-rated oral health. After construction of kernel density surfaces and multiple imputation of missing data, logistic regression analyses were performed to estimate the effects of peer density and other sociodemographic characteristics on the oral health outcomes of dentition status and self-rated oral health. Overall, higher peer density was associated with better oral health for older adults when estimated using smaller bandwidths (0.25 and 0.50 mile). That is, statistically significant relationships (p density and improved dentition status were found when peer density was measured assuming a more local social network. As with dentition status, a positive significant association was found between peer density and fair or better self-rated oral health when peer density was measured assuming a more local social network. This study provides novel evidence that the oral health of community-based older adults is affected by peer density in an urban environment. To the extent that peer density signifies the potential for

A projection and density estimation method for knowledge discovery.

Directory of Open Access Journals (Sweden)

Adam Stanski

Full Text Available A key ingredient to modern data analysis is probability density estimation. However, it is well known that the curse of dimensionality prevents a proper estimation of densities in high dimensions. The problem is typically circumvented by using a fixed set of assumptions about the data, e.g., by assuming partial independence of features, data on a manifold or a customized kernel. These fixed assumptions limit the applicability of a method. In this paper we propose a framework that uses a flexible set of assumptions instead. It allows to tailor a model to various problems by means of 1d-decompositions. The approach achieves a fast runtime and is not limited by the curse of dimensionality as all estimations are performed in 1d-space. The wide range of applications is demonstrated at two very different real world examples. The first is a data mining software that allows the fully automatic discovery of patterns. The software is publicly available for evaluation. As a second example an image segmentation method is realized. It achieves state of the art performance on a benchmark dataset although it uses only a fraction of the training data and very simple features.

[Estimation of Hunan forest carbon density based on spectral mixture analysis of MODIS data].

Science.gov (United States)

Yan, En-ping; Lin, Hui; Wang, Guang-xing; Chen, Zhen-xiong

2015-11-01

With the fast development of remote sensing technology, combining forest inventory sample plot data and remotely sensed images has become a widely used method to map forest carbon density. However, the existence of mixed pixels often impedes the improvement of forest carbon density mapping, especially when low spatial resolution images such as MODIS are used. In this study, MODIS images and national forest inventory sample plot data were used to conduct the study of estimation for forest carbon density. Linear spectral mixture analysis with and without constraint, and nonlinear spectral mixture analysis were compared to derive the fractions of different land use and land cover (LULC) types. Then sequential Gaussian co-simulation algorithm with and without the fraction images from spectral mixture analyses were employed to estimate forest carbon density of Hunan Province. Results showed that 1) Linear spectral mixture analysis with constraint, leading to a mean RMSE of 0.002, more accurately estimated the fractions of LULC types than linear spectral and nonlinear spectral mixture analyses; 2) Integrating spectral mixture analysis model and sequential Gaussian co-simulation algorithm increased the estimation accuracy of forest carbon density to 81.5% from 74.1%, and decreased the RMSE to 5.18 from 7.26; and 3) The mean value of forest carbon density for the province was 30.06 t · hm(-2), ranging from 0.00 to 67.35 t · hm(-2). This implied that the spectral mixture analysis provided a great potential to increase the estimation accuracy of forest carbon density on regional and global level.

Semiautomatic estimation of breast density with DM-Scan software.

Science.gov (United States)

Martínez Gómez, I; Casals El Busto, M; Antón Guirao, J; Ruiz Perales, F; Llobet Azpitarte, R

2014-01-01

To evaluate the reproducibility of the calculation of breast density with DM-Scan software, which is based on the semiautomatic segmentation of fibroglandular tissue, and to compare it with the reproducibility of estimation by visual inspection. The study included 655 direct digital mammograms acquired using craniocaudal projections. Three experienced radiologists analyzed the density of the mammograms using DM-Scan, and the inter- and intra-observer agreement between pairs of radiologists for the Boyd and BI-RADS® scales were calculated using the intraclass correlation coefficient. The Kappa index was used to compare the inter- and intra-observer agreements with those obtained previously for visual inspection in the same set of images. For visual inspection, the mean interobserver agreement was 0,876 (95% CI: 0,873-0,879) on the Boyd scale and 0,823 (95% CI: 0,818-0,829) on the BI-RADS® scale. The mean intraobserver agreement was 0,813 (95% CI: 0,796-0,829) on the Boyd scale and 0,770 (95% CI: 0,742-0,797) on the BI-RADS® scale. For DM-Scan, the mean inter- and intra-observer agreement was 0,92, considerably higher than the agreement for visual inspection. The semiautomatic calculation of breast density using DM-Scan software is more reliable and reproducible than visual estimation and reduces the subjectivity and variability in determining breast density. Copyright © 2012 SERAM. Published by Elsevier Espana. All rights reserved.

Covariant Density Functionals: time-odd channel investigated

International Nuclear Information System (INIS)

Afanasjev, A. V.; Abusara, H.

2009-01-01

The description of exotic nuclear systems and phenomena requires a detailed understanding of all channels of density functional theories. The role of time-odd mean fields, their evidence in experiment, and an accurate description of these fields are subject of current interest. Recent studies advanced the understanding of these fields in energy density functional theories based on the Skyrme force [1,2]. Time-odd mean fields are related to nuclear magnetism in covariant density functional (CDF) theories [3]. They arise from space-like components of vector mesons and Lorentz invariance requires that their coupling strengths are identical to that of time-like components. There were only few limited efforts to understand the role of time-odd mean fields in covariant density functional theory [4,5]. For example, the microscopic role of nuclear magnetism and its impact on rotational properties of nuclei has been studied in Ref. [5]. It is known that time-odd mean fields modify the angular momentum content of the single-particle orbitals and thus the moments of inertia, effective alignments, alignment gains at the band crossings and other physical observables. We aim on more detailed and systematic understanding of the role of time-odd mean fields in covariant density functional theory. This investigation covers both rotating and non-rotating systems. It is shown that contrary to the Skyrme energy density functionals time-odd mean fields of CDF theory always provide additional binding in the systems with broken time-reversal symmetry (rotating nuclei, odd mass nuclei). This additional binding increases with spin and has its maximum exactly at the terminating state [6], where it can reach several MeV. The impact of time-odd mean fields on the properties of rotating systems has been studied in a systematic way (as a function of particle number and deformation) across the nuclear chart [7]. In addition, this contribution extends these studies to non-rotating systems such as

Density functional theory of the electrical double layer: the RFD functional

International Nuclear Information System (INIS)

Gillespie, Dirk; Valisko, Monika; Boda, Dezso

2005-01-01

Density functional theory (DFT) of electrolytes is applied to the electrical double layer under a wide range of conditions. The ions are charged, hard spheres of different size and valence, and the wall creating the double layer is uncharged, weakly charged, and strongly charged. Under all conditions, the density and electrostatic potential profiles calculated using the recently proposed RFD electrostatic functional (Gillespie et al 2002 J. Phys.: Condens. Matter 14 12129; 2003 Phys. Rev. E 68 031503) compare well to Monte Carlo simulations. When the wall is strongly charged, the RFD functional results agree with the results of a simpler perturbative electrostatic DFT, but the two functionals' results qualitatively disagree when the wall is uncharged or weakly charged. The RFD functional reproduces these phenomena of weakly charged double layers. It also reproduces bulk thermodynamic quantities calculated from pair correlation functions

Investigating the impact of uneven magnetic flux density distribution on core loss estimation

DEFF Research Database (Denmark)

Niroumand, Farideh Javidi; Nymand, Morten; Wang, Yiren

2017-01-01

is calculated according to an effective flux density value and the macroscopic dimensions of the cores. However, the flux distribution in the core can alter by core shapes and/or operating conditions due to nonlinear material properties. This paper studies the element-wise estimation of the loss in magnetic......There are several approaches for loss estimation in magnetic cores, and all these approaches highly rely on accurate information about flux density distribution in the cores. It is often assumed that the magnetic flux density evenly distributes throughout the core and the overall core loss...

Trap array configuration influences estimates and precision of black bear density and abundance.

Directory of Open Access Journals (Sweden)

Clay M Wilton

Full Text Available Spatial capture-recapture (SCR models have advanced our ability to estimate population density for wide ranging animals by explicitly incorporating individual movement. Though these models are more robust to various spatial sampling designs, few studies have empirically tested different large-scale trap configurations using SCR models. We investigated how extent of trap coverage and trap spacing affects precision and accuracy of SCR parameters, implementing models using the R package secr. We tested two trapping scenarios, one spatially extensive and one intensive, using black bear (Ursus americanus DNA data from hair snare arrays in south-central Missouri, USA. We also examined the influence that adding a second, lower barbed-wire strand to snares had on quantity and spatial distribution of detections. We simulated trapping data to test bias in density estimates of each configuration under a range of density and detection parameter values. Field data showed that using multiple arrays with intensive snare coverage produced more detections of more individuals than extensive coverage. Consequently, density and detection parameters were more precise for the intensive design. Density was estimated as 1.7 bears per 100 km2 and was 5.5 times greater than that under extensive sampling. Abundance was 279 (95% CI = 193-406 bears in the 16,812 km2 study area. Excluding detections from the lower strand resulted in the loss of 35 detections, 14 unique bears, and the largest recorded movement between snares. All simulations showed low bias for density under both configurations. Results demonstrated that in low density populations with non-uniform distribution of population density, optimizing the tradeoff among snare spacing, coverage, and sample size is of critical importance to estimating parameters with high precision and accuracy. With limited resources, allocating available traps to multiple arrays with intensive trap spacing increased the amount of

Estimation of larval density of Liriomyza sativae Blanchard (Diptera ...

African Journals Online (AJOL)

This study was conducted to develop sequential sampling plans to estimate larval density of Liriomyza sativae Blanchard (Diptera: Agromyzidae) at three precision levels in cucumber greenhouse. The within- greenhouse spatial patterns of larvae were aggregated. The slopes and intercepts of both Iwao's patchiness ...

Nonparametric Bayesian density estimation on manifolds with applications to planar shapes.

Science.gov (United States)

Bhattacharya, Abhishek; Dunson, David B

2010-12-01

Statistical analysis on landmark-based shape spaces has diverse applications in morphometrics, medical diagnostics, machine vision and other areas. These shape spaces are non-Euclidean quotient manifolds. To conduct nonparametric inferences, one may define notions of centre and spread on this manifold and work with their estimates. However, it is useful to consider full likelihood-based methods, which allow nonparametric estimation of the probability density. This article proposes a broad class of mixture models constructed using suitable kernels on a general compact metric space and then on the planar shape space in particular. Following a Bayesian approach with a nonparametric prior on the mixing distribution, conditions are obtained under which the Kullback-Leibler property holds, implying large support and weak posterior consistency. Gibbs sampling methods are developed for posterior computation, and the methods are applied to problems in density estimation and classification with shape-based predictors. Simulation studies show improved estimation performance relative to existing approaches.

Orthogonal bases of radial functions for charge density refinements

International Nuclear Information System (INIS)

Restori, R.

1990-01-01

Charge density determination from X-ray measurements necessitates the evaluation of the Fourier-Bessel transforms of the radial functions used to expand the charge density. Analytical expressions are given here for four sets of orthogonal functions which can substitute for the 'traditional exponential functions' set in least-squares refinements. (orig.)

Time-dependent density-functional tight-binding method with the third-order expansion of electron density.

Science.gov (United States)

Nishimoto, Yoshio

2015-09-07

We develop a formalism for the calculation of excitation energies and excited state gradients for the self-consistent-charge density-functional tight-binding method with the third-order contributions of a Taylor series of the density functional theory energy with respect to the fluctuation of electron density (time-dependent density-functional tight-binding (TD-DFTB3)). The formulation of the excitation energy is based on the existing time-dependent density functional theory and the older TD-DFTB2 formulae. The analytical gradient is computed by solving Z-vector equations, and it requires one to calculate the third-order derivative of the total energy with respect to density matrix elements due to the inclusion of the third-order contributions. The comparison of adiabatic excitation energies for selected small and medium-size molecules using the TD-DFTB2 and TD-DFTB3 methods shows that the inclusion of the third-order contributions does not affect excitation energies significantly. A different set of parameters, which are optimized for DFTB3, slightly improves the prediction of adiabatic excitation energies statistically. The application of TD-DFTB for the prediction of absorption and fluorescence energies of cresyl violet demonstrates that TD-DFTB3 reproduced the experimental fluorescence energy quite well.

Features of the normal choriocapillaris with OCT-angiography: Density estimation and textural properties.

Science.gov (United States)

Montesano, Giovanni; Allegrini, Davide; Colombo, Leonardo; Rossetti, Luca M; Pece, Alfredo

2017-01-01

The main objective of our work is to perform an in depth analysis of the structural features of normal choriocapillaris imaged with OCT Angiography. Specifically, we provide an optimal radius for a circular Region of Interest (ROI) to obtain a stable estimate of the subfoveal choriocapillaris density and characterize its textural properties using Markov Random Fields. On each binarized image of the choriocapillaris OCT Angiography we performed simulated measurements of the subfoveal choriocapillaris densities with circular Regions of Interest (ROIs) of different radii and with small random displacements from the center of the Foveal Avascular Zone (FAZ). We then calculated the variability of the density measure with different ROI radii. We then characterized the textural features of choriocapillaris binary images by estimating the parameters of an Ising model. For each image we calculated the Optimal Radius (OR) as the minimum ROI radius required to obtain a standard deviation in the simulation below 0.01. The density measured with the individual OR was 0.52 ± 0.07 (mean ± STD). Similar density values (0.51 ± 0.07) were obtained using a fixed ROI radius of 450 μm. The Ising model yielded two parameter estimates (β = 0.34 ± 0.03; γ = 0.003 ± 0.012; mean ± STD), characterizing pixel clustering and white pixel density respectively. Using the estimated parameters to synthetize new random textures via simulation we obtained a good reproduction of the original choriocapillaris structural features and density. In conclusion, we developed an extensive characterization of the normal subfoveal choriocapillaris that might be used for flow analysis and applied to the investigation pathological alterations.

Energy vs. density on paths toward exact density functionals

DEFF Research Database (Denmark)

Kepp, Kasper Planeta

2018-01-01

Recently, the progression toward more exact density functional theory has been questioned, implying a need for more formal ways to systematically measure progress, i.e. a “path”. Here I use the Hohenberg-Kohn theorems and the definition of normality by Burke et al. to define a path toward exactness...

EnviroAtlas - Portland, ME - Estimated Intersection Density of Walkable Roads

Data.gov (United States)

U.S. Environmental Protection Agency — This EnviroAtlas dataset estimates the intersection density of walkable roads within a 750 meter radius of any given 10 meter pixel in the community. Intersections...

EnviroAtlas - Woodbine, IA - Estimated Intersection Density of Walkable Roads

Data.gov (United States)

U.S. Environmental Protection Agency — This EnviroAtlas dataset estimates the intersection density of walkable roads within a 750 meter radius of any given 10 meter pixel in the community. Intersections...

EnviroAtlas - Durham, NC - Estimated Intersection Density of Walkable Roads

Data.gov (United States)

U.S. Environmental Protection Agency — This EnviroAtlas dataset estimates the intersection density of walkable roads within a 750 meter radius of any given 10 meter pixel in the community. Intersections...

EnviroAtlas - Fresno, CA - Estimated Intersection Density of Walkable Roads

Data.gov (United States)

U.S. Environmental Protection Agency — This EnviroAtlas dataset estimates the intersection density of walkable roads within a 750 meter radius of any given 10 meter pixel in the community. Intersections...

EnviroAtlas - Cleveland, OH - Estimated Intersection Density of Walkable Roads

Data.gov (United States)

U.S. Environmental Protection Agency — This EnviroAtlas dataset estimates the intersection density of walkable roads within a 750 meter radius of any given 10 meter pixel in the community. Intersections...

EnviroAtlas - Memphis, TN - Estimated Intersection Density of Walkable Roads

Data.gov (United States)

U.S. Environmental Protection Agency — This EnviroAtlas dataset estimates the intersection density of walkable roads within a 750 meter radius of any given 10 meter pixel in the community. Intersections...

EnviroAtlas - Milwaukee, WI - Estimated Intersection Density of Walkable Roads

Data.gov (United States)

U.S. Environmental Protection Agency — This EnviroAtlas dataset estimates the intersection density of walkable roads within a 750 meter radius of any given 10 meter pixel in the community. Intersections...

EnviroAtlas - Portland, OR - Estimated Intersection Density of Walkable Roads

Data.gov (United States)

U.S. Environmental Protection Agency — This EnviroAtlas dataset estimates the intersection density of walkable roads within a 750 meter radius of any given 10 meter pixel in the community. Intersections...

EnviroAtlas - Tampa, FL - Estimated Intersection Density of Walkable Roads

Data.gov (United States)

U.S. Environmental Protection Agency — This EnviroAtlas dataset estimates the intersection density of walkable roads within a 750 meter radius of any given 10 meter pixel in the community. Intersections...

EnviroAtlas - Austin, TX - Estimated Intersection Density of Walkable Roads

Data.gov (United States)

U.S. Environmental Protection Agency — This EnviroAtlas dataset estimates the intersection density of walkable roads within a 750 meter radius of any given 10 meter pixel in the community. Intersections...

EnviroAtlas - Paterson, NJ - Estimated Intersection Density of Walkable Roads

Data.gov (United States)

U.S. Environmental Protection Agency — This EnviroAtlas dataset estimates the intersection density of walkable roads within a 750 meter radius of any given 10 meter pixel in the community. Intersections...

EnviroAtlas - Phoenix, AZ - Estimated Intersection Density of Walkable Roads

Data.gov (United States)

U.S. Environmental Protection Agency — This EnviroAtlas dataset estimates the intersection density of walkable roads within a 750 meter radius of any given 10 meter pixel in the community. Intersections...

EnviroAtlas - Pittsburgh, PA - Estimated Intersection Density of Walkable Roads

Data.gov (United States)

U.S. Environmental Protection Agency — This EnviroAtlas dataset estimates the intersection density of walkable roads within a 750 meter radius of any given 10 meter pixel in the community. Intersections...

Application of independent component analysis for speech-music separation using an efficient score function estimation

Science.gov (United States)

Pishravian, Arash; Aghabozorgi Sahaf, Masoud Reza

2012-12-01

In this paper speech-music separation using Blind Source Separation is discussed. The separating algorithm is based on the mutual information minimization where the natural gradient algorithm is used for minimization. In order to do that, score function estimation from observation signals (combination of speech and music) samples is needed. The accuracy and the speed of the mentioned estimation will affect on the quality of the separated signals and the processing time of the algorithm. The score function estimation in the presented algorithm is based on Gaussian mixture based kernel density estimation method. The experimental results of the presented algorithm on the speech-music separation and comparing to the separating algorithm which is based on the Minimum Mean Square Error estimator, indicate that it can cause better performance and less processing time

Decentralized State-Observer-Based Traffic Density Estimation of Large-Scale Urban Freeway Network by Dynamic Model

Directory of Open Access Journals (Sweden)

Yuqi Guo

2017-08-01

Full Text Available In order to estimate traffic densities in a large-scale urban freeway network in an accurate and timely fashion when traffic sensors do not cover the freeway network completely and thus only local measurement data can be utilized, this paper proposes a decentralized state observer approach based on a macroscopic traffic flow model. Firstly, by using the well-known cell transmission model (CTM, the urban freeway network is modeled in the way of distributed systems. Secondly, based on the model, a decentralized observer is designed. With the help of the Lyapunov function and S-procedure theory, the observer gains are computed by using linear matrix inequality (LMI technique. So, the traffic densities of the whole road network can be estimated by the designed observer. Finally, this method is applied to the outer ring of the Beijing’s second ring road and experimental results demonstrate the effectiveness and applicability of the proposed approach.

EnviroAtlas Estimated Intersection Density of Walkable Roads Web Service

Data.gov (United States)

U.S. Environmental Protection Agency — This EnviroAtlas dataset estimates the intersection density of walkable roads within a 750 meter radius of any given 10 meter pixel in each EnviroAtlas community....

Multicomponent density-functional theory for time-dependent systems

NARCIS (Netherlands)

Butriy, O.; Ebadi, H.; de Boeij, P. L.; van Leeuwen, R.; Gross, E. K. U.

2007-01-01

We derive the basic formalism of density functional theory for time-dependent electron-nuclear systems. The basic variables of this theory are the electron density in body-fixed frame coordinates and the diagonal of the nuclear N-body density matrix. The body-fixed frame transformation is carried

Improved Density Functional Tight Binding Potentials for Metalloid Aluminum Clusters

Science.gov (United States)

2016-06-01

unlimited IMPROVED DENSITY-FUNCTIONAL TIGHT BINDING POTENTIALS FOR METALLOID ALUMINUM CLUSTERS by Joon H. Kim June 2016 Thesis Advisor...DATES COVERED Master’s thesis 4. TITLE AND SUBTITLE IMPROVED DENSITY-FUNCTIONAL TIGHT BINDING POTENTIALS FOR METALLOID ALUMINUM CLUSTERS 5. FUNDING...repulsive potentials for use in density-functional tight binding (DFTB) simulations of low-valence aluminum metalloid clusters . These systems are under

Comparison of several measure-correlate-predict models using support vector regression techniques to estimate wind power densities. A case study

International Nuclear Information System (INIS)

Díaz, Santiago; Carta, José A.; Matías, José M.

2017-01-01

Highlights: • Eight measure-correlate-predict (MCP) models used to estimate the wind power densities (WPDs) at a target site are compared. • Support vector regressions are used as the main prediction techniques in the proposed MCPs. • The most precise MCP uses two sub-models which predict wind speed and air density in an unlinked manner. • The most precise model allows to construct a bivariable (wind speed and air density) WPD probability density function. • MCP models trained to minimise wind speed prediction error do not minimise WPD prediction error. - Abstract: The long-term annual mean wind power density (WPD) is an important indicator of wind as a power source which is usually included in regional wind resource maps as useful prior information to identify potentially attractive sites for the installation of wind projects. In this paper, a comparison is made of eight proposed Measure-Correlate-Predict (MCP) models to estimate the WPDs at a target site. Seven of these models use the Support Vector Regression (SVR) and the eighth the Multiple Linear Regression (MLR) technique, which serves as a basis to compare the performance of the other models. In addition, a wrapper technique with 10-fold cross-validation has been used to select the optimal set of input features for the SVR and MLR models. Some of the eight models were trained to directly estimate the mean hourly WPDs at a target site. Others, however, were firstly trained to estimate the parameters on which the WPD depends (i.e. wind speed and air density) and then, using these parameters, the target site mean hourly WPDs. The explanatory features considered are different combinations of the mean hourly wind speeds, wind directions and air densities recorded in 2014 at ten weather stations in the Canary Archipelago (Spain). The conclusions that can be drawn from the study undertaken include the argument that the most accurate method for the long-term estimation of WPDs requires the execution of a

A density functional approach to ferrogels

Science.gov (United States)

Cremer, P.; Heinen, M.; Menzel, A. M.; Löwen, H.

2017-07-01

Ferrogels consist of magnetic colloidal particles embedded in an elastic polymer matrix. As a consequence, their structural and rheological properties are governed by a competition between magnetic particle-particle interactions and mechanical matrix elasticity. Typically, the particles are permanently fixed within the matrix, which makes them distinguishable by their positions. Over time, particle neighbors do not change due to the fixation by the matrix. Here we present a classical density functional approach for such ferrogels. We map the elastic matrix-induced interactions between neighboring colloidal particles distinguishable by their positions onto effective pairwise interactions between indistinguishable particles similar to a ‘pairwise pseudopotential’. Using Monte-Carlo computer simulations, we demonstrate for one-dimensional dipole-spring models of ferrogels that this mapping is justified. We then use the pseudopotential as an input into classical density functional theory of inhomogeneous fluids and predict the bulk elastic modulus of the ferrogel under various conditions. In addition, we propose the use of an ‘external pseudopotential’ when one switches from the viewpoint of a one-dimensional dipole-spring object to a one-dimensional chain embedded in an infinitely extended bulk matrix. Our mapping approach paves the way to describe various inhomogeneous situations of ferrogels using classical density functional concepts of inhomogeneous fluids.

Recent developments in LIBXC - A comprehensive library of functionals for density functional theory

Science.gov (United States)

Lehtola, Susi; Steigemann, Conrad; Oliveira, Micael J. T.; Marques, Miguel A. L.

2018-01-01

LIBXC is a library of exchange-correlation functionals for density-functional theory. We are concerned with semi-local functionals (or the semi-local part of hybrid functionals), namely local-density approximations, generalized-gradient approximations, and meta-generalized-gradient approximations. Currently we include around 400 functionals for the exchange, correlation, and the kinetic energy, spanning more than 50 years of research. Moreover, LIBXC is by now used by more than 20 codes, not only from the atomic, molecular, and solid-state physics, but also from the quantum chemistry communities.

On the evolution of the density probability density function in strongly self-gravitating systems

International Nuclear Information System (INIS)

Girichidis, Philipp; Konstandin, Lukas; Klessen, Ralf S.; Whitworth, Anthony P.

2014-01-01

The time evolution of the probability density function (PDF) of the mass density is formulated and solved for systems in free-fall using a simple approximate function for the collapse of a sphere. We demonstrate that a pressure-free collapse results in a power-law tail on the high-density side of the PDF. The slope quickly asymptotes to the functional form P V (ρ)∝ρ –1.54 for the (volume-weighted) PDF and P M (ρ)∝ρ –0.54 for the corresponding mass-weighted distribution. From the simple approximation of the PDF we derive analytic descriptions for mass accretion, finding that dynamically quiet systems with narrow density PDFs lead to retarded star formation and low star formation rates (SFRs). Conversely, strong turbulent motions that broaden the PDF accelerate the collapse causing a bursting mode of star formation. Finally, we compare our theoretical work with observations. The measured SFRs are consistent with our model during the early phases of the collapse. Comparison of observed column density PDFs with those derived from our model suggests that observed star-forming cores are roughly in free-fall.

Density functional study of molecular interactions in secondary structures of proteins.

Science.gov (United States)

Takano, Yu; Kusaka, Ayumi; Nakamura, Haruki

2016-01-01

Proteins play diverse and vital roles in biology, which are dominated by their three-dimensional structures. The three-dimensional structure of a protein determines its functions and chemical properties. Protein secondary structures, including α-helices and β-sheets, are key components of the protein architecture. Molecular interactions, in particular hydrogen bonds, play significant roles in the formation of protein secondary structures. Precise and quantitative estimations of these interactions are required to understand the principles underlying the formation of three-dimensional protein structures. In the present study, we have investigated the molecular interactions in α-helices and β-sheets, using ab initio wave function-based methods, the Hartree-Fock method (HF) and the second-order Møller-Plesset perturbation theory (MP2), density functional theory, and molecular mechanics. The characteristic interactions essential for forming the secondary structures are discussed quantitatively.

Functional development in density functional theory for superconductors

Energy Technology Data Exchange (ETDEWEB)

Sanna, Antonio; Gross, E.K.U.; Essenberger, Frank [Max Planck Institute of Microstructure Physics, Halle (Saale) (Germany)

2015-07-01

Density functional theory for superconductors (SCDFT) is a fully parameter-free approach to superconductivity that allows for accurate predictions of critical temperature and properties of superconductors. We report on the most recent extensions of the method, in particular the development of new functionals to: (1) incorporate in a correct fashion Migdal's theorem; (2) compute the excitation spectrum; (3) include spin-fluctuation mediated pairing Applications and predictions are shown for a set of materials, including conventional and unconventional superconductors.

Equation satisfied by electron-electron mutual Coulomb repulsion energy density functional

OpenAIRE

Joubert, Daniel P.

2011-01-01

The electron-electron mutual Coulomb repulsion energy density functional satisfies an equation that links functionals and functional derivatives at N-electron and (N-1)-electron densities for densities determined from the same adiabatic scaled external potential for the N-electron system.

Multivariate density estimation using dimension reducing information and tail flattening transformations for truncated or censored data

DEFF Research Database (Denmark)

Buch-Kromann, Tine; Nielsen, Jens

2012-01-01

This paper introduces a multivariate density estimator for truncated and censored data with special emphasis on extreme values based on survival analysis. A local constant density estimator is considered. We extend this estimator by means of tail flattening transformation, dimension reducing prior...

Density-functional theory in one dimension for contact-interacting fermions

International Nuclear Information System (INIS)

Magyar, R.J.; Burke, K.

2004-01-01

A density-functional theory is developed for fermions in one dimension, interacting via a δ function. Such systems provide a natural testing ground for questions of principle, as the local-density approximation should be highly accurate since for this interaction type the exchange contribution to the local-density approximation is intrinsically self-interaction-free. The exact-exchange contribution to the total energy is a local functional of the density. A local-density approximation for correlation is obtained using perturbation theory and Bethe ansatz results for the one-dimensional contact-interacting uniform Fermi gas. The ground-state energies are calculated for two finite systems, the analogs of helium and of Hooke's atom. The local-density approximation is shown to be excellent as expected

Self-contained filtered density function

Science.gov (United States)

Nouri, A. G.; Nik, M. B.; Givi, P.; Livescu, D.; Pope, S. B.

2017-09-01

The filtered density function (FDF) closure is extended to a "self-contained" format to include the subgrid-scale (SGS) statistics of all of the hydro-thermo-chemical variables in turbulent flows. These are the thermodynamic pressure, the specific internal energy, the velocity vector, and the composition field. In this format, the model is comprehensive and facilitates large-eddy simulation (LES) of flows at both low and high compressibility levels. A transport equation is developed for the joint pressure-energy-velocity-composition filtered mass density function (PEVC-FMDF). In this equation, the effect of convection appears in closed form. The coupling of the hydrodynamics and thermochemistry is modeled via a set of stochastic differential equation for each of the transport variables. This yields a self-contained SGS closure. For demonstration, LES is conducted of a turbulent shear flow with transport of a passive scalar. The consistency of the PEVC-FMDF formulation is established, and its overall predictive capability is appraised via comparison with direct numerical simulation (DNS) data.

On Functional Calculus Estimates

NARCIS (Netherlands)

Schwenninger, F.L.

2015-01-01

This thesis presents various results within the field of operator theory that are formulated in estimates for functional calculi. Functional calculus is the general concept of defining operators of the form $f(A)$, where f is a function and $A$ is an operator, typically on a Banach space. Norm

Microscopically based energy density functionals for nuclei using the density matrix expansion. II. Full optimization and validation

Science.gov (United States)

Navarro Pérez, R.; Schunck, N.; Dyhdalo, A.; Furnstahl, R. J.; Bogner, S. K.

2018-05-01

Background: Energy density functional methods provide a generic framework to compute properties of atomic nuclei starting from models of nuclear potentials and the rules of quantum mechanics. Until now, the overwhelming majority of functionals have been constructed either from empirical nuclear potentials such as the Skyrme or Gogny forces, or from systematic gradient-like expansions in the spirit of the density functional theory for atoms. Purpose: We seek to obtain a usable form of the nuclear energy density functional that is rooted in the modern theory of nuclear forces. We thus consider a functional obtained from the density matrix expansion of local nuclear potentials from chiral effective field theory. We propose a parametrization of this functional carefully calibrated and validated on selected ground-state properties that is suitable for large-scale calculations of nuclear properties. Methods: Our energy functional comprises two main components. The first component is a non-local functional of the density and corresponds to the direct part (Hartree term) of the expectation value of local chiral potentials on a Slater determinant. Contributions to the mean field and the energy of this term are computed by expanding the spatial, finite-range components of the chiral potential onto Gaussian functions. The second component is a local functional of the density and is obtained by applying the density matrix expansion to the exchange part (Fock term) of the expectation value of the local chiral potential. We apply the UNEDF2 optimization protocol to determine the coupling constants of this energy functional. Results: We obtain a set of microscopically constrained functionals for local chiral potentials from leading order up to next-to-next-to-leading order with and without three-body forces and contributions from Δ excitations. These functionals are validated on the calculation of nuclear and neutron matter, nuclear mass tables, single-particle shell structure

Estimating Soil Bulk Density and Total Nitrogen from Catchment ...

African Journals Online (AJOL)

Even though data on soil bulk density (BD) and total nitrogen (TN) are essential for planning modern farming techniques, their data availability is limited for many applications in the developing word. This study is designed to estimate BD and TN from soil properties, land-use systems, soil types and landforms in the ...

Graphene on metals: A van der Waals density functional study

DEFF Research Database (Denmark)

Vanin, Marco; Mortensen, Jens Jørgen; Kelkkanen, Kari André

2010-01-01

We use density functional theory (DFT) with a recently developed van der Waals density functional (vdW-DF) to study the adsorption of graphene on Co, Ni, Pd, Ag, Au, Cu, Pt, and Al(111) surfaces. In contrast to the local-density approximation (LDA) which predicts relatively strong binding for Ni...

Multivariate density estimation theory, practice, and visualization

CERN Document Server

Scott, David W

2015-01-01

David W. Scott, PhD, is Noah Harding Professor in the Department of Statistics at Rice University. The author of over 100 published articles, papers, and book chapters, Dr. Scott is also Fellow of the American Statistical Association (ASA) and the Institute of Mathematical Statistics. He is recipient of the ASA Founder's Award and the Army Wilks Award. His research interests include computational statistics, data visualization, and density estimation. Dr. Scott is also Coeditor of Wiley Interdisciplinary Reviews: Computational Statistics and previous Editor of the Journal of Computational and

Self-diffusion in MgO--a density functional study.

Science.gov (United States)

Runevall, Odd; Sandberg, Nils

2011-08-31

Density functional theory calculations have been performed to study self-diffusion in magnesium oxide, a model material for a wide range of ionic compounds. Formation energies and entropies of Schottky defects and divacancies were obtained by means of total energy and phonon calculations in supercell configurations. Transition state theory was used to estimate defect migration rates, with migration energies taken from static calculations, and the corresponding frequency factors estimated from the phonon spectrum. In all static calculations we corrected for image effects using either a multipole expansion or an extrapolation to the low concentration limit. It is shown that both methods give similar results. The results for self-diffusion of Mg and O confirm the previously established picture, namely that in materials of nominal purity, Mg diffuses extrinsically by a single vacancy mechanism, while O diffuses intrinsically by a divacancy mechanism. Quantitatively, the current results are in very good agreement with experiments concerning O diffusion, while for Mg the absolute diffusion rate is generally underestimated by a factor of 5-10. The reason for this discrepancy is discussed.

Noise-level determination for discrete spectra with Gaussian or Lorentzian probability density functions

International Nuclear Information System (INIS)

Moriya, Netzer

2010-01-01

A method, based on binomial filtering, to estimate the noise level of an arbitrary, smoothed pure signal, contaminated with an additive, uncorrelated noise component is presented. If the noise characteristics of the experimental spectrum are known, as for instance the type of the corresponding probability density function (e.g., Gaussian), the noise properties can be extracted. In such cases, both the noise level, as may arbitrarily be defined, and a simulated white noise component can be generated, such that the simulated noise component is statistically indistinguishable from the true noise component present in the original signal. In this paper we present a detailed analysis of the noise level extraction when the additive noise is Gaussian or Lorentzian. We show that the statistical parameters in these cases (mainly the variance and the half width at half maximum, respectively) can directly be obtained from the experimental spectrum even when the pure signal is erratic. Further discussion is given for cases where the noise probability density function is initially unknown.

Sensitivity and uncertainty analysis for functionals of the time-dependent nuclide density field

International Nuclear Information System (INIS)

Williams, M.L.; Weisbin, C.R.

1978-04-01

An approach to extend the present ORNL sensitivity program to include functionals of the time-dependent nuclide density field is developed. An adjoint equation for the nuclide field was derived previously by using generalized perturbation theory; the present derivation makes use of a variational principle and results in the same equation. The physical significance of this equation is discussed and compared to that of the time-dependent neutron adjoint equation. Computational requirements for determining sensitivity profiles and uncertainties for functionals of the time-dependent nuclide density vector are developed within the framework of the existing FORSS system; in this way the current capability is significantly extended. The development, testing, and use of an adjoint version of the ORIGEN isotope generation and depletion code are documented. Finally, a sample calculation is given which estimates the uncertainty in the plutonium inventory at shutdown of a PWR due to assumed uncertainties in uranium and plutonium cross sections. 8 figures, 4 tables

A citizen science based survey method for estimating the density of urban carnivores

Science.gov (United States)

Baker, Rowenna; Charman, Naomi; Karlsson, Heidi; Yarnell, Richard W.; Mill, Aileen C.; Smith, Graham C.; Tolhurst, Bryony A.

2018-01-01

Globally there are many examples of synanthropic carnivores exploiting growth in urbanisation. As carnivores can come into conflict with humans and are potential vectors of zoonotic disease, assessing densities in suburban areas and identifying factors that influence them are necessary to aid management and mitigation. However, fragmented, privately owned land restricts the use of conventional carnivore surveying techniques in these areas, requiring development of novel methods. We present a method that combines questionnaire distribution to residents with field surveys and GIS, to determine relative density of two urban carnivores in England, Great Britain. We determined the density of: red fox (Vulpes vulpes) social groups in 14, approximately 1km2 suburban areas in 8 different towns and cities; and Eurasian badger (Meles meles) social groups in three suburban areas of one city. Average relative fox group density (FGD) was 3.72 km-2, which was double the estimates for cities with resident foxes in the 1980’s. Density was comparable to an alternative estimate derived from trapping and GPS-tracking, indicating the validity of the method. However, FGD did not correlate with a national dataset based on fox sightings, indicating unreliability of the national data to determine actual densities or to extrapolate a national population estimate. Using species-specific clustering units that reflect social organisation, the method was additionally applied to suburban badgers to derive relative badger group density (BGD) for one city (Brighton, 2.41 km-2). We demonstrate that citizen science approaches can effectively obtain data to assess suburban carnivore density, however publicly derived national data sets need to be locally validated before extrapolations can be undertaken. The method we present for assessing densities of foxes and badgers in British towns and cities is also adaptable to other urban carnivores elsewhere. However this transferability is contingent on

A novel technique for real-time estimation of edge pedestal density gradients via reflectometer time delay data

Energy Technology Data Exchange (ETDEWEB)

Zeng, L., E-mail: zeng@fusion.gat.com; Doyle, E. J.; Rhodes, T. L.; Wang, G.; Sung, C.; Peebles, W. A. [Physics and Astronomy Department, University of California, Los Angeles, California 90095 (United States); Bobrek, M. [Oak Ridge National Laboratory, Oak Ridge, Tennessee 37831-6006 (United States)

2016-11-15

A new model-based technique for fast estimation of the pedestal electron density gradient has been developed. The technique uses ordinary mode polarization profile reflectometer time delay data and does not require direct profile inversion. Because of its simple data processing, the technique can be readily implemented via a Field-Programmable Gate Array, so as to provide a real-time density gradient estimate, suitable for use in plasma control systems such as envisioned for ITER, and possibly for DIII-D and Experimental Advanced Superconducting Tokamak. The method is based on a simple edge plasma model with a linear pedestal density gradient and low scrape-off-layer density. By measuring reflectometer time delays for three adjacent frequencies, the pedestal density gradient can be estimated analytically via the new approach. Using existing DIII-D profile reflectometer data, the estimated density gradients obtained from the new technique are found to be in good agreement with the actual density gradients for a number of dynamic DIII-D plasma conditions.

Nuclear energy density functional from chiral pion-nucleon dynamics revisited

Science.gov (United States)

Kaiser, N.; Weise, W.

2010-05-01

We use a recently improved density-matrix expansion to calculate the nuclear energy density functional in the framework of in-medium chiral perturbation theory. Our calculation treats systematically the effects from 1 π-exchange, iterated 1 π-exchange, and irreducible 2 π-exchange with intermediate Δ-isobar excitations, including Pauli-blocking corrections up to three-loop order. We find that the effective nucleon mass M(ρ) entering the energy density functional is identical to the one of Fermi-liquid theory when employing the improved density-matrix expansion. The strength F(ρ) of the ( surface-term as provided by the pion-exchange dynamics is in good agreement with that of phenomenological Skyrme forces in the density region ρ/2short-range spin-orbit interaction. The strength function F(ρ) multiplying the square of the spin-orbit density comes out much larger than in phenomenological Skyrme forces and it has a pronounced density dependence.

PDE-Foam - a probability-density estimation method using self-adapting phase-space binning

CERN Document Server

Dannheim, Dominik; Voigt, Alexander; Grahn, Karl-Johan; Speckmayer, Peter

2009-01-01

Probability-Density Estimation (PDE) is a multivariate discrimination technique based on sampling signal and background densities defined by event samples from data or Monte-Carlo (MC) simulations in a multi-dimensional phase space. To efficiently use large event samples to estimate the probability density, a binary search tree (range searching) is used in the PDE-RS implementation. It is a generalisation of standard likelihood methods and a powerful classification tool for problems with highly non-linearly correlated observables. In this paper, we present an innovative improvement of the PDE method that uses a self-adapting binning method to divide the multi-dimensional phase space in a finite number of hyper-rectangles (cells). The binning algorithm adjusts the size and position of a predefined number of cells inside the multidimensional phase space, minimizing the variance of the signal and background densities inside the cells. The binned density information is stored in binary trees, allowing for a very ...

The heat current density correlation function: sum rules and thermal conductivity

International Nuclear Information System (INIS)

Singh, Shaminder; Tankeshwar, K; Pathak, K N; Ranganathan, S

2006-01-01

Expressions for the second and fourth sum rules of the heat current density correlation function have been derived in an appropriate ensemble. The thermal conductivity of Lennard-Jones fluids has been calculated using these sum rules for the heat current density correlation function and the Gaussian form of the memory function. It is found that the results obtained for the thermal conductivity are in good agreement with the molecular dynamics simulation results over a wide range of densities and temperatures. Earlier results obtained using the energy current density correlation function are also discussed

The heat current density correlation function: sum rules and thermal conductivity

Energy Technology Data Exchange (ETDEWEB)

Singh, Shaminder [Department of Physics, Panjab University, Chandigarh-160 014 (India); Tankeshwar, K [Department of Physics, Panjab University, Chandigarh-160 014 (India); Pathak, K N [Department of Physics, Panjab University, Chandigarh-160 014 (India); Ranganathan, S [Department of Physics, Royal Military College, Kingston, ON, K7K 7B4 (Canada)

2006-02-01

Expressions for the second and fourth sum rules of the heat current density correlation function have been derived in an appropriate ensemble. The thermal conductivity of Lennard-Jones fluids has been calculated using these sum rules for the heat current density correlation function and the Gaussian form of the memory function. It is found that the results obtained for the thermal conductivity are in good agreement with the molecular dynamics simulation results over a wide range of densities and temperatures. Earlier results obtained using the energy current density correlation function are also discussed.

A classical density functional theory of ionic liquids.

Science.gov (United States)

Forsman, Jan; Woodward, Clifford E; Trulsson, Martin

2011-04-28

We present a simple, classical density functional approach to the study of simple models of room temperature ionic liquids. Dispersion attractions as well as ion correlation effects and excluded volume packing are taken into account. The oligomeric structure, common to many ionic liquid molecules, is handled by a polymer density functional treatment. The theory is evaluated by comparisons with simulations, with an emphasis on the differential capacitance, an experimentally measurable quantity of significant practical interest.

Distributed Noise Generation for Density Estimation Based Clustering without Trusted Third Party

Science.gov (United States)

Su, Chunhua; Bao, Feng; Zhou, Jianying; Takagi, Tsuyoshi; Sakurai, Kouichi

The rapid growth of the Internet provides people with tremendous opportunities for data collection, knowledge discovery and cooperative computation. However, it also brings the problem of sensitive information leakage. Both individuals and enterprises may suffer from the massive data collection and the information retrieval by distrusted parties. In this paper, we propose a privacy-preserving protocol for the distributed kernel density estimation-based clustering. Our scheme applies random data perturbation (RDP) technique and the verifiable secret sharing to solve the security problem of distributed kernel density estimation in [4] which assumed a mediate party to help in the computation.

Effect of Broadband Nature of Marine Mammal Echolocation Clicks on Click-Based Population Density Estimates

Science.gov (United States)

2014-09-30

No. 0704-0188 Public reporting burden for the collection of information is estimated to average 1 hour per response, including the time for reviewing...will be applied also to other species such as sperm whale (Physeter macrocephalus) (whose high source level assures long range detection and amplifies...improve the accuracy of marine mammal density estimation based on counting echolocation clicks, and will be applicable to density estimates obtained

Unsupervised Learning and Pattern Recognition of Biological Data Structures with Density Functional Theory and Machine Learning.

Science.gov (United States)

Chen, Chien-Chang; Juan, Hung-Hui; Tsai, Meng-Yuan; Lu, Henry Horng-Shing

2018-01-11

By introducing the methods of machine learning into the density functional theory, we made a detour for the construction of the most probable density function, which can be estimated by learning relevant features from the system of interest. Using the properties of universal functional, the vital core of density functional theory, the most probable cluster numbers and the corresponding cluster boundaries in a studying system can be simultaneously and automatically determined and the plausibility is erected on the Hohenberg-Kohn theorems. For the method validation and pragmatic applications, interdisciplinary problems from physical to biological systems were enumerated. The amalgamation of uncharged atomic clusters validated the unsupervised searching process of the cluster numbers and the corresponding cluster boundaries were exhibited likewise. High accurate clustering results of the Fisher's iris dataset showed the feasibility and the flexibility of the proposed scheme. Brain tumor detections from low-dimensional magnetic resonance imaging datasets and segmentations of high-dimensional neural network imageries in the Brainbow system were also used to inspect the method practicality. The experimental results exhibit the successful connection between the physical theory and the machine learning methods and will benefit the clinical diagnoses.

Estimating forest canopy bulk density using six indirect methods

Science.gov (United States)

Robert E. Keane; Elizabeth D. Reinhardt; Joe Scott; Kathy Gray; James Reardon

2005-01-01

Canopy bulk density (CBD) is an important crown characteristic needed to predict crown fire spread, yet it is difficult to measure in the field. Presented here is a comprehensive research effort to evaluate six indirect sampling techniques for estimating CBD. As reference data, detailed crown fuel biomass measurements were taken on each tree within fixed-area plots...

Self-contained filtered density function

International Nuclear Information System (INIS)

Nouri, Arash G.; Pope, Stephen B.

2017-01-01

The filtered density function (FDF) closure is extended to a “self-contained” format to include the subgrid-scale (SGS) statistics of all of the hydro-thermo-chemical variables in turbulent flows. These are the thermodynamic pressure, the specific internal energy, the velocity vector, and the composition field. In this format, the model is comprehensive and facilitates large-eddy simulation (LES) of flows at both low and high compressibility levels. A transport equation is developed for the joint pressure-energy-velocity-composition filtered mass density function (PEVC-FMDF). In this equation, the effect of convection appears in closed form. The coupling of the hydrodynamics and thermochemistry is modeled via a set of stochastic differential equation for each of the transport variables. This yields a self-contained SGS closure. We demonstrated how LES is conducted of a turbulent shear flow with transport of a passive scalar. Finally, the consistency of the PEVC-FMDF formulation is established, and its overall predictive capability is appraised via comparison with direct numerical simulation (DNS) data.

Multiconfiguration Pair-Density Functional Theory Is Free From Delocalization Error.

Science.gov (United States)

Bao, Junwei Lucas; Wang, Ying; He, Xiao; Gagliardi, Laura; Truhlar, Donald G

2017-11-16

Delocalization error has been singled out by Yang and co-workers as the dominant error in Kohn-Sham density functional theory (KS-DFT) with conventional approximate functionals. In this Letter, by computing the vertical first ionization energy for well separated He clusters, we show that multiconfiguration pair-density functional theory (MC-PDFT) is free from delocalization error. To put MC-PDFT in perspective, we also compare it with some Kohn-Sham density functionals, including both traditional and modern functionals. Whereas large delocalization errors are almost universal in KS-DFT (the only exception being the very recent corrected functionals of Yang and co-workers), delocalization error is removed by MC-PDFT, which bodes well for its future as a step forward from KS-DFT.

Estimation of transient heat flux density during the heat supply of a catalytic wall steam methane reformer

Science.gov (United States)

Settar, Abdelhakim; Abboudi, Saïd; Madani, Brahim; Nebbali, Rachid

2018-02-01

Due to the endothermic nature of the steam methane reforming reaction, the process is often limited by the heat transfer behavior in the reactors. Poor thermal behavior sometimes leads to slow reaction kinetics, which is characterized by the presence of cold spots in the catalytic zones. Within this framework, the present work consists on a numerical investigation, in conjunction with an experimental one, on the one-dimensional heat transfer phenomenon during the heat supply of a catalytic-wall reactor, which is designed for hydrogen production. The studied reactor is inserted in an electric furnace where the heat requirement of the endothermic reaction is supplied by electric heating system. During the heat supply, an unknown heat flux density, received by the reactive flow, is estimated using inverse methods. In the basis of the catalytic-wall reactor model, an experimental setup is engineered in situ to measure the temperature distribution. Then after, the measurements are injected in the numerical heat flux estimation procedure, which is based on the Function Specification Method (FSM). The measured and estimated temperatures are confronted and the heat flux density which crosses the reactor wall is determined.

Benchmark density functional theory calculations for nanoscale conductance

DEFF Research Database (Denmark)

Strange, Mikkel; Bækgaard, Iben Sig Buur; Thygesen, Kristian Sommer

2008-01-01

We present a set of benchmark calculations for the Kohn-Sham elastic transmission function of five representative single-molecule junctions. The transmission functions are calculated using two different density functional theory methods, namely an ultrasoft pseudopotential plane-wave code...

SURFACE SYMMETRY ENERGY OF NUCLEAR ENERGY DENSITY FUNCTIONALS

Energy Technology Data Exchange (ETDEWEB)

Nikolov, N; Schunck, N; Nazarewicz, W; Bender, M; Pei, J

2010-12-20

We study the bulk deformation properties of the Skyrme nuclear energy density functionals. Following simple arguments based on the leptodermous expansion and liquid drop model, we apply the nuclear density functional theory to assess the role of the surface symmetry energy in nuclei. To this end, we validate the commonly used functional parametrizations against the data on excitation energies of superdeformed band-heads in Hg and Pb isotopes, and fission isomers in actinide nuclei. After subtracting shell effects, the results of our self-consistent calculations are consistent with macroscopic arguments and indicate that experimental data on strongly deformed configurations in neutron-rich nuclei are essential for optimizing future nuclear energy density functionals. The resulting survey provides a useful benchmark for further theoretical improvements. Unlike in nuclei close to the stability valley, whose macroscopic deformability hangs on the balance of surface and Coulomb terms, the deformability of neutron-rich nuclei strongly depends on the surface-symmetry energy; hence, its proper determination is crucial for the stability of deformed phases of the neutron-rich matter and description of fission rates for r-process nucleosynthesis.

Kinetic-energy density functional: Atoms and shell structure

International Nuclear Information System (INIS)

Garcia-Gonzalez, P.; Alvarellos, J.E.; Chacon, E.

1996-01-01

We present a nonlocal kinetic-energy functional which includes an anisotropic average of the density through a symmetrization procedure. This functional allows a better description of the nonlocal effects of the electron system. The main consequence of the symmetrization is the appearance of a clear shell structure in the atomic density profiles, obtained after the minimization of the total energy. Although previous results with some of the nonlocal kinetic functionals have given incipient structures for heavy atoms, only our functional shows a clear shell structure for most of the atoms. The atomic total energies have a good agreement with the exact calculations. Discussion of the chemical potential and the first ionization potential in atoms is included. The functional is also extended to spin-polarized systems. copyright 1996 The American Physical Society

Evidence for top-heavy stellar initial mass functions with increasing density and decreasing metallicity

Science.gov (United States)

Marks, Michael; Kroupa, Pavel; Dabringhausen, Jörg; Pawlowski, Marcel S.

2012-05-01

Residual-gas expulsion after cluster formation has recently been shown to leave an imprint in the low-mass present-day stellar mass function (PDMF) which allowed the estimation of birth conditions of some Galactic globular clusters (GCs) such as mass, radius and star formation efficiency. We show that in order to explain their characteristics (masses, radii, metallicity and PDMF) their stellar initial mass function (IMF) must have been top heavy. It is found that the IMF is required to become more top heavy the lower the cluster metallicity and the larger the pre-GC cloud-core density are. The deduced trends are in qualitative agreement with theoretical expectation. The results are consistent with estimates of the shape of the high-mass end of the IMF in the Arches cluster, Westerlund 1, R136 and NGC 3603, as well as with the IMF independently constrained for ultra-compact dwarf galaxies (UCDs). The latter suggests that GCs and UCDs might have formed along the same channel or that UCDs formed via mergers of GCs. A Fundamental Plane is found which describes the variation of the IMF with density and metallicity of the pre-GC cloud cores. The implications for the evolution of galaxies and chemical enrichment over cosmological times are expected to be major.

Estimation of Correlation Functions by Random Decrement

DEFF Research Database (Denmark)

Asmussen, J. C.; Brincker, Rune

This paper illustrates how correlation functions can be estimated by the random decrement technique. Several different formulations of the random decrement technique, estimating the correlation functions are considered. The speed and accuracy of the different formulations of the random decrement...... and the length of the correlation functions. The accuracy of the estimates with respect to the theoretical correlation functions and the modal parameters are both investigated. The modal parameters are extracted from the correlation functions using the polyreference time domain technique....

EnviroAtlas - New Bedford, MA - Estimated Intersection Density of Walkable Roads

Data.gov (United States)

U.S. Environmental Protection Agency — This EnviroAtlas dataset estimates the intersection density of walkable roads within a 750 meter radius of any given 10 meter pixel in the community. Intersections...

EnviroAtlas - Green Bay, WI - Estimated Intersection Density of Walkable Roads

Data.gov (United States)

U.S. Environmental Protection Agency — This EnviroAtlas dataset estimates the intersection density of walkable roads within a 750 meter radius of any given 10 meter pixel in the community. Intersections...

EnviroAtlas - Des Moines, IA - Estimated Intersection Density of Walkable Roads

Data.gov (United States)

U.S. Environmental Protection Agency — This EnviroAtlas dataset estimates the intersection density of walkable roads within a 750 meter radius of any given 10 meter pixel in the community. Intersections...

EnviroAtlas - New York, NY - Estimated Intersection Density of Walkable Roads

Data.gov (United States)

U.S. Environmental Protection Agency — This EnviroAtlas dataset estimates the intersection density of walkable roads within a 750 meter radius of any given 10 meter pixel in the community. Intersections...

A classical density functional investigation of nucleation

International Nuclear Information System (INIS)

Ghosh, Satinath; Ghosh, Swapan K.

2009-01-01

Study of nucleation and growth phenomena in condensation is of prime importance in various applications such as crystal growth, nanoparticle synthesis, pattern formation etc. The knowledge of nucleation barrier in condensation is necessary to control the nucleation kinetics, size of the nanoparticles etc. Classical nucleation theory (CNT) assumes the density of the drop as bulk density irrespective of the size of the drop and overestimates the nucleation barrier. Here we are interested in solving the problem analytically using density functional theory (DFT) with square gradient approximation along the lines of Cahn and Hilliard. Nucleation barrier and density profile obtained in this work are consistent with other works based on nonclassical theory. (author)

Nonlocal exchange and kinetic-energy density functionals for electronic systems

International Nuclear Information System (INIS)

Glossman, M.D.; Rubio, A.; Balbas, L.C.; Alonso, J.A.

1992-01-01

The nonlocal weighted density approximation (WDA) to the exchange and kinetic-energy functionals of many electron systems proposed several years ago by Alonso and Girifalco is used to compute, within the framework of density functional theory, the ground-state electronic density and total energy of noble gas atoms and of neutral jellium-like sodium clusters containing up to 500 atoms. These results are compared with analogous calculations using the well known Thomas-Fermi-Weizsacker-Dirac (TFWD) approximations for the kinetic (TFW) and exchange (D) energy density functionals. An outstanding improvement of the total and exchange energies, of the density at the nucleus and of the expectation values is obtained for atoms within the WDA scheme. For sodium clusters the authors notice a sizeable contribution of the nonlocal effects to the total energy and to the density profiles. In the limit of very large clusters these effects should affect the surface energy of the bulk metal

ESTIMATE OF STAND DENSITY INDEX FOR EUCALYPTUS UROPHYLLA USING DIFFERENT FIT METHODS

Directory of Open Access Journals (Sweden)

Ernani Lopes Possato

Full Text Available ABSTRACT The Reineke stand density index (SDI was created on 1933 and remains as target of researches due to its importance on helping decision making regarding the management of population density. Part of such works is focused on the manner by which plots were selected and methods for the fit of Reineke model parameters in order to improve the definition of SDI value for the genetic material evaluated. The present study aimed to estimate the SDI value for Eucalyptus urophylla using the Reineke model fitted by the method of linear regression (LR and stochastic frontier analysis (SFA. The database containing pairs of data number of stems per hectare (N and mean quadratic diameter (Dq was selected in three intensities, containing the 8, 30 and 43 plots of greatest density, and models were fitted by LR and SFA on each selected intensities. The intensity of data selection altered slightly the estimates of parameters and SDI when comparing the fits of each method. On the other hand, the adjust method influenced the mean estimated values of slope and SDI, which corresponded to -1.863 and 740 for LR and -1.582 and 810 for SFA.

Constraints on parton density functions from D0

Energy Technology Data Exchange (ETDEWEB)

Hays, Jonathan M.; /Imperial Coll., London

2008-04-01

Five recent results from D0 which either impact or have the potential to impact on uncertainties in parton density functions are presented. Many analyses at D0 are sensitive to the modeling of the partonic structure of the proton. When theoretical and experimental uncertainties are well controlled there exists the possibility for additional constraints on parton density functions (PDF). Five measurements are presented which either have already been included in global parton fits or have the potential to contribute in the future.

Higher-accuracy van der Waals density functional

DEFF Research Database (Denmark)

Lee, Kyuho; Murray, Éamonn D.; Kong, Lingzhu

2010-01-01

We propose a second version of the van der Waals density functional of Dion et al. [Phys. Rev. Lett. 92, 246401 (2004)], employing a more accurate semilocal exchange functional and the use of a large-N asymptote gradient correction in determining the vdW kernel. The predicted binding energy...

Self-interaction error in density functional theory: a mean-field correction for molecules and large systems

International Nuclear Information System (INIS)

Ciofini, Ilaria; Adamo, Carlo; Chermette, Henry

2005-01-01

Corrections to the self-interaction error which is rooted in all standard exchange-correlation functionals in the density functional theory (DFT) have become the object of an increasing interest. After an introduction reminding the origin of the self-interaction error in the DFT formalism, and a brief review of the self-interaction free approximations, we present a simple, yet effective, self-consistent method to correct this error. The model is based on an average density self-interaction correction (ADSIC), where both exchange and Coulomb contributions are screened by a fraction of the electron density. The ansatz on which the method is built makes it particularly appealing, due to its simplicity and its favorable scaling with the size of the system. We have tested the ADSIC approach on one of the classical pathological problem for density functional theory: the direct estimation of the ionization potential from orbital eigenvalues. A large set of different chemical systems, ranging from simple atoms to large fullerenes, has been considered as test cases. Our results show that the ADSIC approach provides good numerical values for all the molecular systems, the agreement with the experimental values increasing, due to its average ansatz, with the size (conjugation) of the systems

A comparative study of density functional and density functional tight binding calculations of defects in graphene

Energy Technology Data Exchange (ETDEWEB)

Zobelli, Alberto [Laboratoire de Physique des Solides, Univ. Paris Sud, CNRS UMR, Orsay (France); Ivanovskaya, Viktoria; Wagner, Philipp; Yaya, Abu; Ewels, Chris P. [Institut des Materiaux Jean Rouxel (IMN), CNRS UMR, University of Nantes (France); Suarez-Martinez, Irene [Nanochemistry Research Institute, Curtin University of Technology, Perth, Western Australia (Australia)

2012-02-15

The density functional tight binding approach (DFTB) is well adapted for the study of point and line defects in graphene based systems. After briefly reviewing the use of DFTB in this area, we present a comparative study of defect structures, energies, and dynamics between DFTB results obtained using the dftb+ code, and density functional results using the localized Gaussian orbital code, AIMPRO. DFTB accurately reproduces structures and energies for a range of point defect structures such as vacancies and Stone-Wales defects in graphene, as well as various unfunctionalized and hydroxylated graphene sheet edges. Migration barriers for the vacancy and Stone-Wales defect formation barriers are accurately reproduced using a nudged elastic band approach. Finally we explore the potential for dynamic defect simulations using DFTB, taking as an example electron irradiation damage in graphene. DFTB-MD derived sputtering energy threshold map for a carbon atom in a graphene plane. (Copyright copyright 2012 WILEY-VCH Verlag GmbH and Co. KGaA, Weinheim)

Existence of time-dependent density-functional theory for open electronic systems: time-dependent holographic electron density theorem.

Science.gov (United States)

Zheng, Xiao; Yam, ChiYung; Wang, Fan; Chen, GuanHua

2011-08-28

We present the time-dependent holographic electron density theorem (TD-HEDT), which lays the foundation of time-dependent density-functional theory (TDDFT) for open electronic systems. For any finite electronic system, the TD-HEDT formally establishes a one-to-one correspondence between the electron density inside any finite subsystem and the time-dependent external potential. As a result, any electronic property of an open system in principle can be determined uniquely by the electron density function inside the open region. Implications of the TD-HEDT on the practicality of TDDFT are also discussed.

Postfragmentation density function for bacterial aggregates in laminar flow.

Science.gov (United States)

Byrne, Erin; Dzul, Steve; Solomon, Michael; Younger, John; Bortz, David M

2011-04-01

The postfragmentation probability density of daughter flocs is one of the least well-understood aspects of modeling flocculation. We use three-dimensional positional data of Klebsiella pneumoniae bacterial flocs in suspension and the knowledge of hydrodynamic properties of a laminar flow field to construct a probability density function of floc volumes after a fragmentation event. We provide computational results which predict that the primary fragmentation mechanism for large flocs is erosion. The postfragmentation probability density function has a strong dependence on the size of the original floc and indicates that most fragmentation events result in clumps of one to three bacteria eroding from the original floc. We also provide numerical evidence that exhaustive fragmentation yields a limiting density inconsistent with the log-normal density predicted in the literature, most likely due to the heterogeneous nature of K. pneumoniae flocs. To support our conclusions, artificial flocs were generated and display similar postfragmentation density and exhaustive fragmentation. ©2011 American Physical Society

Kernel density estimation-based real-time prediction for respiratory motion

International Nuclear Information System (INIS)

Ruan, Dan

2010-01-01

Effective delivery of adaptive radiotherapy requires locating the target with high precision in real time. System latency caused by data acquisition, streaming, processing and delivery control necessitates prediction. Prediction is particularly challenging for highly mobile targets such as thoracic and abdominal tumors undergoing respiration-induced motion. The complexity of the respiratory motion makes it difficult to build and justify explicit models. In this study, we honor the intrinsic uncertainties in respiratory motion and propose a statistical treatment of the prediction problem. Instead of asking for a deterministic covariate-response map and a unique estimate value for future target position, we aim to obtain a distribution of the future target position (response variable) conditioned on the observed historical sample values (covariate variable). The key idea is to estimate the joint probability distribution (pdf) of the covariate and response variables using an efficient kernel density estimation method. Then, the problem of identifying the distribution of the future target position reduces to identifying the section in the joint pdf based on the observed covariate. Subsequently, estimators are derived based on this estimated conditional distribution. This probabilistic perspective has some distinctive advantages over existing deterministic schemes: (1) it is compatible with potentially inconsistent training samples, i.e., when close covariate variables correspond to dramatically different response values; (2) it is not restricted by any prior structural assumption on the map between the covariate and the response; (3) the two-stage setup allows much freedom in choosing statistical estimates and provides a full nonparametric description of the uncertainty for the resulting estimate. We evaluated the prediction performance on ten patient RPM traces, using the root mean squared difference between the prediction and the observed value normalized by the

A canonical process for estimation of convex functions : The "invelope" of integrated Brownian motion +t4

NARCIS (Netherlands)

Groeneboom, P.; Jongbloed, G.; Wellner, J.A.

2001-01-01

A process associated with integrated Brownian motion is introduced that characterizes the limit behavior of nonparametric least squares and maximum likelihood estimators of convex functions and convex densities, respectively. We call this process “the invelope” and show that it is an almost surely

Linking density functional and mode coupling models for supercooled liquids.

Science.gov (United States)

Premkumar, Leishangthem; Bidhoodi, Neeta; Das, Shankar P

2016-03-28

We compare predictions from two familiar models of the metastable supercooled liquid, respectively, constructed with thermodynamic and dynamic approaches. In the so called density functional theory the free energy F[ρ] of the liquid is a functional of the inhomogeneous density ρ(r). The metastable state is identified as a local minimum of F[ρ]. The sharp density profile characterizing ρ(r) is identified as a single particle oscillator, whose frequency is obtained from the parameters of the optimum density function. On the other hand, a dynamic approach to supercooled liquids is taken in the mode coupling theory (MCT) which predict a sharp ergodicity-non-ergodicity transition at a critical density. The single particle dynamics in the non-ergodic state, treated approximately, represents a propagating mode whose characteristic frequency is computed from the corresponding memory function of the MCT. The mass localization parameters in the above two models (treated in their simplest forms) are obtained, respectively, in terms of the corresponding natural frequencies depicted and are shown to have comparable magnitudes.

Linking density functional and mode coupling models for supercooled liquids

Energy Technology Data Exchange (ETDEWEB)

Premkumar, Leishangthem; Bidhoodi, Neeta; Das, Shankar P. [School of Physical Sciences, Jawaharlal Nehru University, New Delhi 110067 (India)

2016-03-28

We compare predictions from two familiar models of the metastable supercooled liquid, respectively, constructed with thermodynamic and dynamic approaches. In the so called density functional theory the free energy F[ρ] of the liquid is a functional of the inhomogeneous density ρ(r). The metastable state is identified as a local minimum of F[ρ]. The sharp density profile characterizing ρ(r) is identified as a single particle oscillator, whose frequency is obtained from the parameters of the optimum density function. On the other hand, a dynamic approach to supercooled liquids is taken in the mode coupling theory (MCT) which predict a sharp ergodicity-non-ergodicity transition at a critical density. The single particle dynamics in the non-ergodic state, treated approximately, represents a propagating mode whose characteristic frequency is computed from the corresponding memory function of the MCT. The mass localization parameters in the above two models (treated in their simplest forms) are obtained, respectively, in terms of the corresponding natural frequencies depicted and are shown to have comparable magnitudes.

Estimating the amount and distribution of radon flux density from the soil surface in China

International Nuclear Information System (INIS)

Zhuo Weihai; Guo Qiuju; Chen Bo; Cheng Guan

2008-01-01

Based on an idealized model, both the annual and the seasonal radon ( 222 Rn) flux densities from the soil surface at 1099 sites in China were estimated by linking a database of soil 226 Ra content and a global ecosystems database. Digital maps of the 222 Rn flux density in China were constructed in a spatial resolution of 25 km x 25 km by interpolation among the estimated data. An area-weighted annual average 222 Rn flux density from the soil surface across China was estimated to be 29.7 ± 9.4 mBq m -2 s -1 . Both regional and seasonal variations in the 222 Rn flux densities are significant in China. Annual average flux densities in the southeastern and northwestern China are generally higher than those in other regions of China, because of high soil 226 Ra content in the southeastern area and high soil aridity in the northwestern one. The seasonal average flux density is generally higher in summer/spring than winter, since relatively higher soil temperature and lower soil water saturation in summer/spring than other seasons are common in China

DNA-based population density estimation of black bear at northern ...

African Journals Online (AJOL)

The analysis of deoxyribonucleic acid (DNA) microsatellites from hair samples obtained by the non-invasive method of traps was used to estimate the population density of black bears (Ursus americanus eremicus) in a mountain located at the county of Lampazos, Nuevo Leon, Mexico. The genotyping of bears was ...

Density functional theory a practical introduction

CERN Document Server

Sholl, David

2009-01-01

Demonstrates how anyone in math, science, and engineering can master DFT calculations Density functional theory (DFT) is one of the most frequently used computational tools for studying and predicting the properties of isolated molecules, bulk solids, and material interfaces, including surfaces. Although the theoretical underpinnings of DFT are quite complicated, this book demonstrates that the basic concepts underlying the calculations are simple enough to be understood by anyone with a background in chemistry, physics, engineering, or mathematics. The authors show how the widespread availability of powerful DFT codes makes it possible for students and researchers to apply this important computational technique to a broad range of fundamental and applied problems. Density Functional Theory: A Practical Introduction offers a concise, easy-to-follow introduction to the key concepts and practical applications of DFT, focusing on plane-wave DFT. The authors have many years of experience introducing DFT to studen...

Teaching Density Functional Theory Through Experiential Learning

International Nuclear Information System (INIS)

Narasimhan, Shobhana

2015-01-01

Today, quantum mechanical density functional theory is often the method of choice for performing accurate calculations on atomic, molecular and condensed matter systems. Here, I share some of my experiences in teaching the necessary basics of solid state physics, as well as the theory and practice of density functional theory, in a number of workshops held in developing countries over the past two decades. I discuss the advantages of supplementing the usual mathematically formal teaching methods, characteristic of graduate courses, with the use of visual imagery and analogies. I also describe a successful experiment we carried out, which resulted in a joint publication co-authored by 67 lecturers and students participating in a summer school. (paper)

Relationship of Quantum Entanglement to Density Functional Theory

OpenAIRE

Rajagopal, A. K.; Rendell, R. W.

2005-01-01

The maximum von Neumann entropy principle subject to given constraints of mean values of some physical observables determines the density matrix. Similarly the stationary action principle in the case of time-dependent (dissipative) situations under similar constraints yields the density matrix. The free energy and measures of entanglement are expressed in terms of such a density matrix and thus define respective functionals of the mean values. In the light of several model calculations, it is...

Estimating Function Approaches for Spatial Point Processes

Science.gov (United States)

Deng, Chong

Spatial point pattern data consist of locations of events that are often of interest in biological and ecological studies. Such data are commonly viewed as a realization from a stochastic process called spatial point process. To fit a parametric spatial point process model to such data, likelihood-based methods have been widely studied. However, while maximum likelihood estimation is often too computationally intensive for Cox and cluster processes, pairwise likelihood methods such as composite likelihood, Palm likelihood usually suffer from the loss of information due to the ignorance of correlation among pairs. For many types of correlated data other than spatial point processes, when likelihood-based approaches are not desirable, estimating functions have been widely used for model fitting. In this dissertation, we explore the estimating function approaches for fitting spatial point process models. These approaches, which are based on the asymptotic optimal estimating function theories, can be used to incorporate the correlation among data and yield more efficient estimators. We conducted a series of studies to demonstrate that these estmating function approaches are good alternatives to balance the trade-off between computation complexity and estimating efficiency. First, we propose a new estimating procedure that improves the efficiency of pairwise composite likelihood method in estimating clustering parameters. Our approach combines estimating functions derived from pairwise composite likeli-hood estimation and estimating functions that account for correlations among the pairwise contributions. Our method can be used to fit a variety of parametric spatial point process models and can yield more efficient estimators for the clustering parameters than pairwise composite likelihood estimation. We demonstrate its efficacy through a simulation study and an application to the longleaf pine data. Second, we further explore the quasi-likelihood approach on fitting

Source-Free Exchange-Correlation Magnetic Fields in Density Functional Theory.

Science.gov (United States)

Sharma, S; Gross, E K U; Sanna, A; Dewhurst, J K

2018-03-13

Spin-dependent exchange-correlation energy functionals in use today depend on the charge density and the magnetization density: E xc [ρ, m]. However, it is also correct to define the functional in terms of the curl of m for physical external fields: E xc [ρ,∇ × m]. The exchange-correlation magnetic field, B xc , then becomes source-free. We study this variation of the theory by uniquely removing the source term from local and generalized gradient approximations to the functional. By doing so, the total Kohn-Sham moments are improved for a wide range of materials for both functionals. Significantly, the moments for the pnictides are now in good agreement with experiment. This source-free method is simple to implement in all existing density functional theory codes.

Joint estimation of crown of thorns (Acanthaster planci densities on the Great Barrier Reef

Directory of Open Access Journals (Sweden)

M. Aaron MacNeil

2016-08-01

Full Text Available Crown-of-thorns starfish (CoTS; Acanthaster spp. are an outbreaking pest among many Indo-Pacific coral reefs that cause substantial ecological and economic damage. Despite ongoing CoTS research, there remain critical gaps in observing CoTS populations and accurately estimating their numbers, greatly limiting understanding of the causes and sources of CoTS outbreaks. Here we address two of these gaps by (1 estimating the detectability of adult CoTS on typical underwater visual count (UVC surveys using covariates and (2 inter-calibrating multiple data sources to estimate CoTS densities within the Cairns sector of the Great Barrier Reef (GBR. We find that, on average, CoTS detectability is high at 0.82 [0.77, 0.87] (median highest posterior density (HPD and [95% uncertainty intervals], with CoTS disc width having the greatest influence on detection. Integrating this information with coincident surveys from alternative sampling programs, we estimate CoTS densities in the Cairns sector of the GBR averaged 44 [41, 48] adults per hectare in 2014.

Chemical hardness and density functional theory

Indian Academy of Sciences (India)

Unknown

RALPH G PEARSON. Chemistry Department, University of California, Santa Barbara, CA 93106, USA. Abstract. The concept of chemical hardness is reviewed from a personal point of view. Keywords. Hardness; softness; hard & soft acids bases (HSAB); principle of maximum hardness. (PMH) density functional theory (DFT) ...

Density functional and neural network analysis

DEFF Research Database (Denmark)

Jalkanen, K. J.; Suhai, S.; Bohr, Henrik

1997-01-01

Density functional theory (DFT) calculations have been carried out for hydrated L-alanine, L-alanyl-L-alanine and N-acetyl L-alanine N'-methylamide and examined with respect to the effect of water on the structure, the vibrational frequencies, vibrational absorption (VA) and vibrational circular...

Ambit determination method in estimating rice plant population density

Directory of Open Access Journals (Sweden)

Abu Bakar, B.,

2017-11-01

Full Text Available Rice plant population density is a key indicator in determining the crop setting and fertilizer application rate. It is therefore essential that the population density is monitored to ensure that a correct crop management decision is taken. The conventional method of determining plant population is by manually counting the total number of rice plant tillers in a 25 cm x 25 cm square frame. Sampling is done by randomly choosing several different locations within a plot to perform tiller counting. This sampling method is time consuming, labour intensive and costly. An alternative fast estimating method was developed to overcome this issue. The method relies on measuring the outer circumference or ambit of the contained rice plants in a 25 cm x 25 cm square frame to determine the number of tillers within that square frame. Data samples of rice variety MR219 were collected from rice plots in the Muda granary area, Sungai Limau Dalam, Kedah. The data were taken at 50 days and 70 days after seeding (DAS. A total of 100 data samples were collected for each sampling day. A good correlation was obtained for the variety of 50 DAS and 70 DAS. The model was then verified by taking 100 samples with the latching strap for 50 DAS and 70 DAS. As a result, this technique can be used as a fast, economical and practical alternative to manual tiller counting. The technique can potentially be used in the development of an electronic sensing system to estimate paddy plant population density.

An asymptotically unbiased minimum density power divergence estimator for the Pareto-tail index

DEFF Research Database (Denmark)

Dierckx, Goedele; Goegebeur, Yuri; Guillou, Armelle

2013-01-01

We introduce a robust and asymptotically unbiased estimator for the tail index of Pareto-type distributions. The estimator is obtained by fitting the extended Pareto distribution to the relative excesses over a high threshold with the minimum density power divergence criterion. Consistency...

Nuclear energy density functional from chiral pion-nucleon dynamics revisited

OpenAIRE

Kaiser, N.; Weise, W.

2009-01-01

We use a recently improved density-matrix expansion to calculate the nuclear energy density functional in the framework of in-medium chiral perturbation theory. Our calculation treats systematically the effects from $1\\pi$-exchange, iterated $1\\pi$-exchange, and irreducible $2\\pi$-exchange with intermediate $\\Delta$-isobar excitations, including Pauli-blocking corrections up to three-loop order. We find that the effective nucleon mass $M^*(\\rho)$ entering the energy density functional is iden...

Density functional theory for adsorption of gas mixtures in metal-organic frameworks.

Science.gov (United States)

Liu, Yu; Liu, Honglai; Hu, Ying; Jiang, Jianwen

2010-03-04

In this work, a recently developed density functional theory in three-dimensional space was extended to the adsorption of gas mixtures. Weighted density approximations to the excess free energy with different weighting functions were adopted for both repulsive and attractive contributions. An equation of state for hard-sphere mixtures and a modified Benedict-Webb-Rubin equation for Lennard-Jones mixtures were used to estimate the excess free energy of a uniform fluid. The theory was applied to the adsorption of CO(2)/CH(4) and CO(2)/N(2) mixtures in two metal-organic frameworks: ZIF-8 and Zn(2)(BDC)(2)(ted). To validate the theoretical predictions, grand canonical Monte Carlo simulations were also conducted. The predicted adsorption and selectivity from DFT were found to agree well with the simulation results. CO(2) has stronger adsorption than CH(4) and N(2), particularly in Zn(2)(BDC)(2)(ted). The selectivity of CO(2) over CH(4) or N(2) increases with increasing pressure as attributed to the cooperative interactions of adsorbed CO(2) molecules. The composition of the gas mixture exhibits a significant effect on adsorption but not on selectivity.

A new approach on seismic mortality estimations based on average population density

Science.gov (United States)

Zhu, Xiaoxin; Sun, Baiqing; Jin, Zhanyong

2016-12-01

This study examines a new methodology to predict the final seismic mortality from earthquakes in China. Most studies established the association between mortality estimation and seismic intensity without considering the population density. In China, however, the data are not always available, especially when it comes to the very urgent relief situation in the disaster. And the population density varies greatly from region to region. This motivates the development of empirical models that use historical death data to provide the path to analyze the death tolls for earthquakes. The present paper employs the average population density to predict the final death tolls in earthquakes using a case-based reasoning model from realistic perspective. To validate the forecasting results, historical data from 18 large-scale earthquakes occurred in China are used to estimate the seismic morality of each case. And a typical earthquake case occurred in the northwest of Sichuan Province is employed to demonstrate the estimation of final death toll. The strength of this paper is that it provides scientific methods with overall forecast errors lower than 20 %, and opens the door for conducting final death forecasts with a qualitative and quantitative approach. Limitations and future research are also analyzed and discussed in the conclusion.

Mammography density estimation with automated volumetic breast density measurement

International Nuclear Information System (INIS)

Ko, Su Yeon; Kim, Eun Kyung; Kim, Min Jung; Moon, Hee Jung

2014-01-01

To compare automated volumetric breast density measurement (VBDM) with radiologists' evaluations based on the Breast Imaging Reporting and Data System (BI-RADS), and to identify the factors associated with technical failure of VBDM. In this study, 1129 women aged 19-82 years who underwent mammography from December 2011 to January 2012 were included. Breast density evaluations by radiologists based on BI-RADS and by VBDM (Volpara Version 1.5.1) were compared. The agreement in interpreting breast density between radiologists and VBDM was determined based on four density grades (D1, D2, D3, and D4) and a binary classification of fatty (D1-2) vs. dense (D3-4) breast using kappa statistics. The association between technical failure of VBDM and patient age, total breast volume, fibroglandular tissue volume, history of partial mastectomy, the frequency of mass > 3 cm, and breast density was analyzed. The agreement between breast density evaluations by radiologists and VBDM was fair (k value = 0.26) when the four density grades (D1/D2/D3/D4) were used and moderate (k value = 0.47) for the binary classification (D1-2/D3-4). Twenty-seven women (2.4%) showed failure of VBDM. Small total breast volume, history of partial mastectomy, and high breast density were significantly associated with technical failure of VBDM (p 0.001 to 0.015). There is fair or moderate agreement in breast density evaluation between radiologists and VBDM. Technical failure of VBDM may be related to small total breast volume, a history of partial mastectomy, and high breast density.

Reduced density matrix functional theory at finite temperature

Energy Technology Data Exchange (ETDEWEB)

Baldsiefen, Tim

2012-10-15

Density functional theory (DFT) is highly successful in many fields of research. There are, however, areas in which its performance is rather limited. An important example is the description of thermodynamical variables of a quantum system in thermodynamical equilibrium. Although the finite-temperature version of DFT (FT-DFT) rests on a firm theoretical basis and is only one year younger than its brother, groundstate DFT, it has been successfully applied to only a few problems. Because FT-DFT, like DFT, is in principle exact, these shortcomings can be attributed to the difficulties of deriving valuable functionals for FT-DFT. In this thesis, we are going to present an alternative theoretical description of quantum systems in thermal equilibrium. It is based on the 1-reduced density matrix (1RDM) of the system, rather than on its density and will rather cumbersomly be called finite-temperature reduced density matrix functional theory (FT-RDMFT). Its zero-temperature counterpart (RDMFT) proved to be successful in several fields, formerly difficult to address via DFT. These fields include, for example, the calculation of dissociation energies or the calculation of the fundamental gap, also for Mott insulators. This success is mainly due to the fact that the 1RDM carries more directly accessible ''manybody'' information than the density alone, leading for example to an exact description of the kinetic energy functional. This sparks the hope that a description of thermodynamical systems employing the 1RDM via FT-RDMFT can yield an improvement over FT-DFT. Giving a short review of RDMFT and pointing out difficulties when describing spin-polarized systems initiates our work. We then lay the theoretical framework for FT-RDMFT by proving the required Hohenberg-Kohn-like theorems, investigating and determining the domain of FT-RDMFT functionals and by deriving several properties of the exact functional. Subsequently, we present a perturbative method to

Reduced density matrix functional theory at finite temperature

International Nuclear Information System (INIS)

Baldsiefen, Tim

2012-10-01

Density functional theory (DFT) is highly successful in many fields of research. There are, however, areas in which its performance is rather limited. An important example is the description of thermodynamical variables of a quantum system in thermodynamical equilibrium. Although the finite-temperature version of DFT (FT-DFT) rests on a firm theoretical basis and is only one year younger than its brother, groundstate DFT, it has been successfully applied to only a few problems. Because FT-DFT, like DFT, is in principle exact, these shortcomings can be attributed to the difficulties of deriving valuable functionals for FT-DFT. In this thesis, we are going to present an alternative theoretical description of quantum systems in thermal equilibrium. It is based on the 1-reduced density matrix (1RDM) of the system, rather than on its density and will rather cumbersomly be called finite-temperature reduced density matrix functional theory (FT-RDMFT). Its zero-temperature counterpart (RDMFT) proved to be successful in several fields, formerly difficult to address via DFT. These fields include, for example, the calculation of dissociation energies or the calculation of the fundamental gap, also for Mott insulators. This success is mainly due to the fact that the 1RDM carries more directly accessible ''manybody'' information than the density alone, leading for example to an exact description of the kinetic energy functional. This sparks the hope that a description of thermodynamical systems employing the 1RDM via FT-RDMFT can yield an improvement over FT-DFT. Giving a short review of RDMFT and pointing out difficulties when describing spin-polarized systems initiates our work. We then lay the theoretical framework for FT-RDMFT by proving the required Hohenberg-Kohn-like theorems, investigating and determining the domain of FT-RDMFT functionals and by deriving several properties of the exact functional. Subsequently, we present a perturbative method to iteratively construct

Improved density functional calculations for atoms, molecules and surfaces

International Nuclear Information System (INIS)

Fricke, B.; Anton, J.; Fritzsche, S.; Sarpe-Tudoran, C.

2005-01-01

The non-collinear and collinear descriptions within relativistic density functional theory is described. We present results of both non-collinear and collinear calculations for atoms, diatomic molecules, and some surface simulations. We find that the accuracy of our density functional calculations for the smaller systems is comparable to good quantum chemical calculations, and thus this method provides a sound basis for larger systems where no such comparison is possible. (author)

Estimate of energy density on CYCLOPS spatial filter pinhole structure

International Nuclear Information System (INIS)

Guch, S. Jr.

1974-01-01

The inclusion of a spatial filter between the B and C stages in CYCLOPS to reduce the effects of small-scale beam self-focusing is discussed. An estimate is made of the energy density to which the pinhole will be subjected, and the survivability of various pinhole materials and designs is discussed

Relativistic density functional theory with picture-change corrected electron density based on infinite-order Douglas-Kroll-Hess method

Science.gov (United States)

Oyama, Takuro; Ikabata, Yasuhiro; Seino, Junji; Nakai, Hiromi

2017-07-01

This Letter proposes a density functional treatment based on the two-component relativistic scheme at the infinite-order Douglas-Kroll-Hess (IODKH) level. The exchange-correlation energy and potential are calculated using the electron density based on the picture-change corrected density operator transformed by the IODKH method. Numerical assessments indicated that the picture-change uncorrected density functional terms generate significant errors, on the order of hartree for heavy atoms. The present scheme was found to reproduce the energetics in the four-component treatment with high accuracy.

Time-dependent quantum fluid density functional theory of hydrogen ...

Indian Academy of Sciences (India)

WINTEC

density functional theory; quantum fluid dynamics. 1. Introduction ... dynamics of strongly non-linear interaction of atoms with intense ... theory and quantum fluid dynamics in real space. .... clear evidence of bond softening since density in the.

Density functional theory for polymeric systems in 2D

International Nuclear Information System (INIS)

Słyk, Edyta; Bryk, Paweł; Roth, Roland

2016-01-01

We propose density functional theory for polymeric fluids in two dimensions. The approach is based on Wertheim’s first order thermodynamic perturbation theory (TPT) and closely follows density functional theory for polymers proposed by Yu and Wu (2002 J. Chem. Phys . 117 2368). As a simple application we evaluate the density profiles of tangent hard-disk polymers at hard walls. The theoretical predictions are compared against the results of the Monte Carlo simulations. We find that for short chain lengths the theoretical density profiles are in an excellent agreement with the Monte Carlo data. The agreement is less satisfactory for longer chains. The performance of the theory can be improved by recasting the approach using the self-consistent field theory formalism. When the self-avoiding chain statistics is used, the theory yields a marked improvement in the low density limit. Further improvements for long chains could be reached by going beyond the first order of TPT. (paper)

Central depression in nucleonic densities: Trend analysis in the nuclear density functional theory approach

Science.gov (United States)

Schuetrumpf, B.; Nazarewicz, W.; Reinhard, P.-G.

2017-08-01

Background: The central depression of nucleonic density, i.e., a reduction of density in the nuclear interior, has been attributed to many factors. For instance, bubble structures in superheavy nuclei are believed to be due to the electrostatic repulsion. In light nuclei, the mechanism behind the density reduction in the interior has been discussed in terms of shell effects associated with occupations of s orbits. Purpose: The main objective of this work is to reveal mechanisms behind the formation of central depression in nucleonic densities in light and heavy nuclei. To this end, we introduce several measures of the internal nucleonic density. Through the statistical analysis, we study the information content of these measures with respect to nuclear matter properties. Method: We apply nuclear density functional theory with Skyrme functionals. Using the statistical tools of linear least square regression, we inspect correlations between various measures of central depression and model parameters, including nuclear matter properties. We study bivariate correlations with selected quantities as well as multiple correlations with groups of parameters. Detailed correlation analysis is carried out for 34Si for which a bubble structure has been reported recently, 48Ca, and N =82 , 126, and 184 isotonic chains. Results: We show that the central depression in medium-mass nuclei is very sensitive to shell effects, whereas for superheavy systems it is firmly driven by the electrostatic repulsion. An appreciable semibubble structure in proton density is predicted for 294Og, which is currently the heaviest nucleus known experimentally. Conclusion: Our correlation analysis reveals that the central density indicators in nuclei below 208Pb carry little information on parameters of nuclear matter; they are predominantly driven by shell structure. On the other hand, in the superheavy nuclei there exists a clear relationship between the central nucleonic density and symmetry energy.

Improving incidence estimation in practice-based sentinel surveillance networks using spatial variation in general practitioner density

Directory of Open Access Journals (Sweden)

Cécile Souty

2016-11-01

Full Text Available Abstract Background In surveillance networks based on voluntary participation of health-care professionals, there is little choice regarding the selection of participants’ characteristics. External information about participants, for example local physician density, can help reduce bias in incidence estimates reported by the surveillance network. Methods There is an inverse association between the number of reported influenza-like illness (ILI cases and local general practitioners (GP density. We formulated and compared estimates of ILI incidence using this relationship. To compare estimates, we simulated epidemics using a spatially explicit disease model and their observation by surveillance networks with different characteristics: random, maximum coverage, largest cities, etc. Results In the French practice-based surveillance network – the “Sentinelles” network – GPs reported 3.6% (95% CI [3;4] less ILI cases as local GP density increased by 1 GP per 10,000 inhabitants. Incidence estimates varied markedly depending on scenarios for participant selection in surveillance. Yet accounting for change in GP density for participants allowed reducing bias. Applied on data from the Sentinelles network, changes in overall incidence ranged between 1.6 and 9.9%. Conclusions Local GP density is a simple measure that provides a way to reduce bias in estimating disease incidence in general practice. It can contribute to improving disease monitoring when it is not possible to choose the characteristics of participants.

Density Functional Methods for Shock Physics and High Energy Density Science

Science.gov (United States)

Desjarlais, Michael

2017-06-01

Molecular dynamics with density functional theory has emerged over the last two decades as a powerful and accurate framework for calculating thermodynamic and transport properties with broad application to dynamic compression, high energy density science, and warm dense matter. These calculations have been extensively validated against shock and ramp wave experiments, are a principal component of high-fidelity equation of state generation, and are having wide-ranging impacts on inertial confinement fusion, planetary science, and shock physics research. In addition to thermodynamic properties, phase boundaries, and the equation of state, one also has access to electrical conductivity, thermal conductivity, and lower energy optical properties. Importantly, all these properties are obtained within the same theoretical framework and are manifestly consistent. In this talk I will give a brief history and overview of molecular dynamics with density functional theory and its use in calculating a wide variety of thermodynamic and transport properties for materials ranging from ambient to extreme conditions and with comparisons to experimental data. I will also discuss some of the limitations and difficulties, as well as active research areas. Sandia is a multi-program laboratory managed and operated by Sandia Corporation, a wholly owned subsidiary of Lockheed Martin Corporation, for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-AC04-94AL85000.

The maximal-density mass function for primordial black hole dark matter

Science.gov (United States)

Lehmann, Benjamin V.; Profumo, Stefano; Yant, Jackson

2018-04-01

The advent of gravitational wave astronomy has rekindled interest in primordial black holes (PBH) as a dark matter candidate. As there are many different observational probes of the PBH density across different masses, constraints on PBH models are dependent on the functional form of the PBH mass function. This complicates general statements about the mass functions allowed by current data, and, in particular, about the maximum total density of PBH. Numerical studies suggest that some forms of extended mass functions face tighter constraints than monochromatic mass functions, but they do not preclude the existence of a functional form for which constraints are relaxed. We use analytical arguments to show that the mass function which maximizes the fraction of the matter density in PBH subject to all constraints is a finite linear combination of monochromatic mass functions. We explicitly compute the maximum fraction of dark matter in PBH for different combinations of current constraints, allowing for total freedom of the mass function. Our framework elucidates the dependence of the maximum PBH density on the form of observational constraints, and we discuss the implications of current and future constraints for the viability of the PBH dark matter paradigm.

Estimation of adsorption-induced pore pressure and confinement in a nanoscopic slit pore by a density functional theory

Science.gov (United States)

Grégoire, David; Malheiro, Carine; Miqueu, Christelle

2018-03-01

This study aims at characterising the adsorption-induced pore pressure and confinement in nanoscopic pores by molecular non-local density functional theory (DFT). Considering its important potential industrial applications, the adsorption of methane in graphitic slit pores has been selected as the test case. While retaining the accuracy of molecular simulations at pore scale, DFT has a very low computational cost that allows obtaining highly resolved pore pressure maps as a function of both pore width and thermodynamic conditions. The dependency of pore pressure on these parameters (pore width, pressure and temperature) is carefully analysed in order to highlight the effect of each parameter on the confined fluid properties that impact the solid matrix.

Fog Density Estimation and Image Defogging Based on Surrogate Modeling for Optical Depth.

Science.gov (United States)

Jiang, Yutong; Sun, Changming; Zhao, Yu; Yang, Li

2017-05-03

In order to estimate fog density correctly and to remove fog from foggy images appropriately, a surrogate model for optical depth is presented in this paper. We comprehensively investigate various fog-relevant features and propose a novel feature based on the hue, saturation, and value color space which correlate well with the perception of fog density. We use a surrogate-based method to learn a refined polynomial regression model for optical depth with informative fog-relevant features such as dark-channel, saturation-value, and chroma which are selected on the basis of sensitivity analysis. Based on the obtained accurate surrogate model for optical depth, an effective method for fog density estimation and image defogging is proposed. The effectiveness of our proposed method is verified quantitatively and qualitatively by the experimental results on both synthetic and real-world foggy images.

Effects of LiDAR point density, sampling size and height threshold on estimation accuracy of crop biophysical parameters.

Science.gov (United States)

Luo, Shezhou; Chen, Jing M; Wang, Cheng; Xi, Xiaohuan; Zeng, Hongcheng; Peng, Dailiang; Li, Dong

2016-05-30

Vegetation leaf area index (LAI), height, and aboveground biomass are key biophysical parameters. Corn is an important and globally distributed crop, and reliable estimations of these parameters are essential for corn yield forecasting, health monitoring and ecosystem modeling. Light Detection and Ranging (LiDAR) is considered an effective technology for estimating vegetation biophysical parameters. However, the estimation accuracies of these parameters are affected by multiple factors. In this study, we first estimated corn LAI, height and biomass (R2 = 0.80, 0.874 and 0.838, respectively) using the original LiDAR data (7.32 points/m2), and the results showed that LiDAR data could accurately estimate these biophysical parameters. Second, comprehensive research was conducted on the effects of LiDAR point density, sampling size and height threshold on the estimation accuracy of LAI, height and biomass. Our findings indicated that LiDAR point density had an important effect on the estimation accuracy for vegetation biophysical parameters, however, high point density did not always produce highly accurate estimates, and reduced point density could deliver reasonable estimation results. Furthermore, the results showed that sampling size and height threshold were additional key factors that affect the estimation accuracy of biophysical parameters. Therefore, the optimal sampling size and the height threshold should be determined to improve the estimation accuracy of biophysical parameters. Our results also implied that a higher LiDAR point density, larger sampling size and height threshold were required to obtain accurate corn LAI estimation when compared with height and biomass estimations. In general, our results provide valuable guidance for LiDAR data acquisition and estimation of vegetation biophysical parameters using LiDAR data.

Benchmarks for electronically excited states: Time-dependent density functional theory and density functional theory based multireference configuration interaction

DEFF Research Database (Denmark)

Silva-Junior, Mario R.; Schreiber, Marko; Sauer, Stephan P. A.

2008-01-01

Time-dependent density functional theory (TD-DFT) and DFT-based multireference configuration interaction (DFT/MRCI) calculations are reported for a recently proposed benchmark set of 28 medium-sized organic molecules. Vertical excitation energies, oscillator strengths, and excited-state dipole...

Balancing Exchange Mixing in Density-Functional Approximations for Iron Porphyrin.

Science.gov (United States)

Berryman, Victoria E J; Boyd, Russell J; Johnson, Erin R

2015-07-14

Predicting the correct ground-state multiplicity for iron(II) porphyrin, a high-spin quintet, remains a significant challenge for electronic-structure methods, including commonly employed density functionals. An even greater challenge for these methods is correctly predicting favorable binding of O2 to iron(II) porphyrin, due to the open-shell singlet character of the adduct. In this work, the performance of a modest set of contemporary density-functional approximations is assessed and the results interpreted using Bader delocalization indices. It is found that inclusion of greater proportions of Hartree-Fock exchange, in hybrid or range-separated hybrid functionals, has opposing effects; it improves the ability of the functional to identify the ground state but is detrimental to predicting favorable dioxygen binding. Because of the uncomplementary nature of these properties, accurate prediction of both the relative spin-state energies and the O2 binding enthalpy eludes conventional density-functional approximations.

Crowd density estimation based on convolutional neural networks with mixed pooling

Science.gov (United States)

Zhang, Li; Zheng, Hong; Zhang, Ying; Zhang, Dongming

2017-09-01

Crowd density estimation is an important topic in the fields of machine learning and video surveillance. Existing methods do not provide satisfactory classification accuracy; moreover, they have difficulty in adapting to complex scenes. Therefore, we propose a method based on convolutional neural networks (CNNs). The proposed method improves performance of crowd density estimation in two key ways. First, we propose a feature pooling method named mixed pooling to regularize the CNNs. It replaces deterministic pooling operations with a parameter that, by studying the algorithm, could combine the conventional max pooling with average pooling methods. Second, we present a classification strategy, in which an image is divided into two cells and respectively categorized. The proposed approach was evaluated on three datasets: two ground truth image sequences and the University of California, San Diego, anomaly detection dataset. The results demonstrate that the proposed approach performs more effectively and easily than other methods.

Estimation of Bouguer Density Precision: Development of Method for Analysis of La Soufriere Volcano Gravity Data

OpenAIRE

Gunawan, Hendra; Micheldiament, Micheldiament; Mikhailov, Valentin

2008-01-01

http://dx.doi.org/10.17014/ijog.vol3no3.20084The precision of topographic density (Bouguer density) estimation by the Nettleton approach is based on a minimum correlation of Bouguer gravity anomaly and topography. The other method, the Parasnis approach, is based on a minimum correlation of Bouguer gravity anomaly and Bouguer correction. The precision of Bouguer density estimates was investigated by both methods on simple 2D syntetic models and under an assumption free-air anomaly consisting ...

Heterogeneous occupancy and density estimates of the pathogenic fungus Batrachochytrium dendrobatidis in waters of North America.

Directory of Open Access Journals (Sweden)

Tara Chestnut

Full Text Available Biodiversity losses are occurring worldwide due to a combination of stressors. For example, by one estimate, 40% of amphibian species are vulnerable to extinction, and disease is one threat to amphibian populations. The emerging infectious disease chytridiomycosis, caused by the aquatic fungus Batrachochytrium dendrobatidis (Bd, is a contributor to amphibian declines worldwide. Bd research has focused on the dynamics of the pathogen in its amphibian hosts, with little emphasis on investigating the dynamics of free-living Bd. Therefore, we investigated patterns of Bd occupancy and density in amphibian habitats using occupancy models, powerful tools for estimating site occupancy and detection probability. Occupancy models have been used to investigate diseases where the focus was on pathogen occurrence in the host. We applied occupancy models to investigate free-living Bd in North American surface waters to determine Bd seasonality, relationships between Bd site occupancy and habitat attributes, and probability of detection from water samples as a function of the number of samples, sample volume, and water quality. We also report on the temporal patterns of Bd density from a 4-year case study of a Bd-positive wetland. We provide evidence that Bd occurs in the environment year-round. Bd exhibited temporal and spatial heterogeneity in density, but did not exhibit seasonality in occupancy. Bd was detected in all months, typically at less than 100 zoospores L(-1. The highest density observed was ∼3 million zoospores L(-1. We detected Bd in 47% of sites sampled, but estimated that Bd occupied 61% of sites, highlighting the importance of accounting for imperfect detection. When Bd was present, there was a 95% chance of detecting it with four samples of 600 ml of water or five samples of 60 mL. Our findings provide important baseline information to advance the study of Bd disease ecology, and advance our understanding of amphibian exposure to free

Estimating state-contingent production functions

DEFF Research Database (Denmark)

Rasmussen, Svend; Karantininis, Kostas

The paper reviews the empirical problem of estimating state-contingent production functions. The major problem is that states of nature may not be registered and/or that the number of observation per state is low. Monte Carlo simulation is used to generate an artificial, uncertain production...... environment based on Cobb Douglas production functions with state-contingent parameters. The pa-rameters are subsequently estimated based on different sizes of samples using Generalized Least Squares and Generalized Maximum Entropy and the results are compared. It is concluded that Maximum Entropy may...

Joint density-functional theory and its application to systems in solution

Science.gov (United States)

Petrosyan, Sahak A.

The physics of solvation, the interaction of water with solutes, plays a central role in chemistry and biochemistry, and it is essential for the very existence of life. Despite the central importance of water and the advent of the quantum theory early in the twentieth century, the link between the fundamental laws of physics and the observable properties of water remain poorly understood to this day. The central goal of this thesis is to develop a new formalism and framework to make the study of systems (solutes or surfaces) in contact with liquid water as practical and accurate as standard electronic structure calculations without the need for explicit averaging over large ensembles of configurations of water molecules. The thesis introduces a new form of density functional theory for the ab initio description of electronic systems in contact with a molecular liquid environment. This theory rigorously joins an electron density-functional for the electrons of a solute with a classical density-functional theory for the liquid into a single variational principle for the free energy of the combined system. Using the new form of density-functional theory for the ab initio description of electronic systems in contact with a molecular liquid environment, the thesis then presents the first detailed study of the impact of a solvent on the surface chemistry of Cr2O3, the passivating layer of stainless steel alloys. In comparison to a vacuum, we predict that the presence of water has little impact on the adsorption of chloride ions to the oxygen-terminated surface but has a dramatic effect on the binding of hydrogen to that surface. A key ingredient of a successful joint density functional theory is a good approximate functional for describing the solvent. We explore how the simplest examples of the best known class of approximate forms for the classical density functional fail when applied directly to water. The thesis then presents a computationally efficient density-functional

Approach to kinetic energy density functionals: Nonlocal terms with the structure of the von Weizsaecker functional

International Nuclear Information System (INIS)

Garcia-Aldea, David; Alvarellos, J. E.

2008-01-01

We propose a kinetic energy density functional scheme with nonlocal terms based on the von Weizsaecker functional, instead of the more traditional approach where the nonlocal terms have the structure of the Thomas-Fermi functional. The proposed functionals recover the exact kinetic energy and reproduce the linear response function of homogeneous electron systems. In order to assess their quality, we have tested the total kinetic energies as well as the kinetic energy density for atoms. The results show that these nonlocal functionals give as good results as the most sophisticated functionals in the literature. The proposed scheme for constructing the functionals means a step ahead in the field of fully nonlocal kinetic energy functionals, because they are capable of giving better local behavior than the semilocal functionals, yielding at the same time accurate results for total kinetic energies. Moreover, the functionals enjoy the possibility of being evaluated as a single integral in momentum space if an adequate reference density is defined, and then quasilinear scaling for the computational cost can be achieved

EnviroAtlas - Minneapolis/St. Paul, MN - Estimated Intersection Density of Walkable Roads

Data.gov (United States)

U.S. Environmental Protection Agency — This EnviroAtlas dataset estimates the intersection density of walkable roads within a 750 meter radius of any given 10 meter pixel in the community. Intersections...

Improving statistical inference on pathogen densities estimated by quantitative molecular methods: malaria gametocytaemia as a case study.

Science.gov (United States)

Walker, Martin; Basáñez, María-Gloria; Ouédraogo, André Lin; Hermsen, Cornelus; Bousema, Teun; Churcher, Thomas S

2015-01-16

Quantitative molecular methods (QMMs) such as quantitative real-time polymerase chain reaction (q-PCR), reverse-transcriptase PCR (qRT-PCR) and quantitative nucleic acid sequence-based amplification (QT-NASBA) are increasingly used to estimate pathogen density in a variety of clinical and epidemiological contexts. These methods are often classified as semi-quantitative, yet estimates of reliability or sensitivity are seldom reported. Here, a statistical framework is developed for assessing the reliability (uncertainty) of pathogen densities estimated using QMMs and the associated diagnostic sensitivity. The method is illustrated with quantification of Plasmodium falciparum gametocytaemia by QT-NASBA. The reliability of pathogen (e.g. gametocyte) densities, and the accompanying diagnostic sensitivity, estimated by two contrasting statistical calibration techniques, are compared; a traditional method and a mixed model Bayesian approach. The latter accounts for statistical dependence of QMM assays run under identical laboratory protocols and permits structural modelling of experimental measurements, allowing precision to vary with pathogen density. Traditional calibration cannot account for inter-assay variability arising from imperfect QMMs and generates estimates of pathogen density that have poor reliability, are variable among assays and inaccurately reflect diagnostic sensitivity. The Bayesian mixed model approach assimilates information from replica QMM assays, improving reliability and inter-assay homogeneity, providing an accurate appraisal of quantitative and diagnostic performance. Bayesian mixed model statistical calibration supersedes traditional techniques in the context of QMM-derived estimates of pathogen density, offering the potential to improve substantially the depth and quality of clinical and epidemiological inference for a wide variety of pathogens.

Estimation of functional failure probability of passive systems based on adaptive importance sampling method

International Nuclear Information System (INIS)

Wang Baosheng; Wang Dongqing; Zhang Jianmin; Jiang Jing

2012-01-01

In order to estimate the functional failure probability of passive systems, an innovative adaptive importance sampling methodology is presented. In the proposed methodology, information of variables is extracted with some pre-sampling of points in the failure region. An important sampling density is then constructed from the sample distribution in the failure region. Taking the AP1000 passive residual heat removal system as an example, the uncertainties related to the model of a passive system and the numerical values of its input parameters are considered in this paper. And then the probability of functional failure is estimated with the combination of the response surface method and adaptive importance sampling method. The numerical results demonstrate the high computed efficiency and excellent computed accuracy of the methodology compared with traditional probability analysis methods. (authors)

Blue functions: probability and current density propagators in non-relativistic quantum mechanics

International Nuclear Information System (INIS)

Withers, L P Jr

2011-01-01

Like a Green function to propagate a particle's wavefunction in time, a Blue function is introduced to propagate the particle's probability and current density. Accordingly, the complete Blue function has four components. They are constructed from path integrals involving a quantity like the action that we call the motion. The Blue function acts on the displaced probability density as the kernel of an integral operator. As a result, we find that the Wigner density occurs as an expression for physical propagation. We also show that, in quantum mechanics, the displaced current density is conserved bilocally (in two places at one time), as expressed by a generalized continuity equation. (paper)

Dietary Energy Density, Renal Function, and Progression of Chronic Kidney Disease

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Mohammad Hossein Rouhani

2016-01-01

Full Text Available Background. There is evidence of the association between dietary energy density and chronic diseases. However, no report exists regarding the relation between DED and chronic kidney disease (CKD. Objective. To examine the association between dietary energy density (DED, renal function, and progression of chronic kidney disease (CKD. Design. Cross-sectional. Setting. Three nephrology clinics. Subjects. Two hundred twenty-one subjects with diagnosed CKD. Main Outcome Measure. Dietary intake of patients was assessed by a validated food frequency questionnaire. DED (in kcal/g was calculated with the use of energy content and weight of solid foods and energy yielding beverages. Renal function was measured by blood urea nitrogen (BUN, serum creatinine (Cr, and estimated glomerular filtration rate (eGFR. Results. Patients in the first tertile of DED consumed more amounts of carbohydrate, dietary fiber, potassium, phosphorus, zinc, magnesium, calcium, folate, vitamin C, and vitamin B2. After adjusting for confounders, we could not find any significant trend for BUN and Cr across tertiles of DED. In multivariate model, an increased risk of being in the higher stage of CKD was found among those in the last tertile of DED (OR: 3.15; 95% CI: 1.30, 7.63; P=0.01. Conclusion. We observed that lower DED was associated with better nutrient intake and lower risk of CKD progression.

Bulk density estimation using a 3-dimensional image acquisition and analysis system

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Heyduk Adam

2016-01-01

Full Text Available The paper presents a concept of dynamic bulk density estimation of a particulate matter stream using a 3-d image analysis system and a conveyor belt scale. A method of image acquisition should be adjusted to the type of scale. The paper presents some laboratory results of static bulk density measurements using the MS Kinect time-of-flight camera and OpenCV/Matlab software. Measurements were made for several different size classes.

Synthesis, Crystal Structure, Density Function Theory, Molecular ...

African Journals Online (AJOL)

Tropical Journal of Pharmaceutical Research February 2016; 15 (2): 385-392 ... tested for its antimicrobial activities and computational studies including density function test (DFT) and docking ... agonists [4], selective dopamine D3 and D4 ...

Non-Parametric Estimation of Correlation Functions

DEFF Research Database (Denmark)

Brincker, Rune; Rytter, Anders; Krenk, Steen

In this paper three methods of non-parametric correlation function estimation are reviewed and evaluated: the direct method, estimation by the Fast Fourier Transform and finally estimation by the Random Decrement technique. The basic ideas of the techniques are reviewed, sources of bias are point...

Applications of Density Functional Theory in Soft Condensed Matter

Science.gov (United States)

Löwen, Hartmut

Applications of classical density functional theory (DFT) to soft matter systems like colloids, liquid crystals and polymer solutions are discussed with a focus on the freezing transition and on nonequilibrium Brownian dynamics. First, after a brief reminder of equilibrium density functional theory, DFT is applied to the freezing transition of liquids into crystalline lattices. In particular, spherical particles with radially symmetric pair potentials will be treated (like hard spheres, the classical one-component plasma or Gaussian-core particles). Second, the DFT will be generalized towards Brownian dynamics in order to tackle nonequilibrium problems. After a general introduction to Brownian dynamics using the complementary Smoluchowski and Langevin pictures appropriate for the dynamics of colloidal suspensions, the dynamical density functional theory (DDFT) will be derived from the Smoluchowski equation. This will be done first for spherical particles (e.g. hard spheres or Gaussian-cores) without hydrodynamic interactions. Then we show how to incorporate hydrodynamic interactions between the colloidal particles into the DDFT framework and compare to Brownian dynamics computer simulations. Third orientational degrees of freedom (rod-like particles) will be considered as well. In the latter case, the stability of intermediate liquid crystalline phases (isotropic, nematic, smectic-A, plastic crystals etc) can be predicted. Finally, the corresponding dynamical extension of density functional theory towards orientational degrees of freedom is proposed and the collective behaviour of "active" (self-propelled) Brownian particles is briefly discussed.

A new estimation method for nuclide number densities in equilibrium cycle

International Nuclear Information System (INIS)

Seino, Takeshi; Sekimoto, Hiroshi; Ando, Yoshihira.

1997-01-01

A new method is proposed for estimating nuclide number densities of LWR equilibrium cycle by multi-recycling calculation. Conventionally, it is necessary to spend a large computation time for attaining the ultimate equilibrium state. Hence, the cycle in nearly constant fuel composition has been considered as an equilibrium state which can be achieved by a few of recycling calculations on a simulated cycle operation under a specific fuel core design. The present method uses steady state fuel nuclide number densities as the initial guess for multi-recycling burnup calculation obtained by a continuously fuel supplied core model. The number densities are modified to be the initial number densities for nuclides of a batch supplied fuel. It was found that the calculated number densities could attain to more precise equilibrium state than that of a conventional multi-recycling calculation with a small number of recyclings. In particular, the present method could give the ultimate equilibrium number densities of the nuclides with the higher mass number than 245 Cm and 244 Pu which were not able to attain to the ultimate equilibrium state within a reasonable number of iterations using a conventional method. (author)

Plato: A localised orbital based density functional theory code

Science.gov (United States)

Kenny, S. D.; Horsfield, A. P.

2009-12-01

The Plato package allows both orthogonal and non-orthogonal tight-binding as well as density functional theory (DFT) calculations to be performed within a single framework. The package also provides extensive tools for analysing the results of simulations as well as a number of tools for creating input files. The code is based upon the ideas first discussed in Sankey and Niklewski (1989) [1] with extensions to allow high-quality DFT calculations to be performed. DFT calculations can utilise either the local density approximation or the generalised gradient approximation. Basis sets from minimal basis through to ones containing multiple radial functions per angular momenta and polarisation functions can be used. Illustrations of how the package has been employed are given along with instructions for its utilisation. Program summaryProgram title: Plato Catalogue identifier: AEFC_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEFC_v1_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: Standard CPC licence, http://cpc.cs.qub.ac.uk/licence/licence.html No. of lines in distributed program, including test data, etc.: 219 974 No. of bytes in distributed program, including test data, etc.: 1 821 493 Distribution format: tar.gz Programming language: C/MPI and PERL Computer: Apple Macintosh, PC, Unix machines Operating system: Unix, Linux and Mac OS X Has the code been vectorised or parallelised?: Yes, up to 256 processors tested RAM: Up to 2 Gbytes per processor Classification: 7.3 External routines: LAPACK, BLAS and optionally ScaLAPACK, BLACS, PBLAS, FFTW Nature of problem: Density functional theory study of electronic structure and total energies of molecules, crystals and surfaces. Solution method: Localised orbital based density functional theory. Restrictions: Tight-binding and density functional theory only, no exact exchange. Unusual features: Both atom centred and uniform meshes available

General framework for fluctuating dynamic density functional theory

Science.gov (United States)

Durán-Olivencia, Miguel A.; Yatsyshin, Peter; Goddard, Benjamin D.; Kalliadasis, Serafim

2017-12-01

We introduce a versatile bottom-up derivation of a formal theoretical framework to describe (passive) soft-matter systems out of equilibrium subject to fluctuations. We provide a unique connection between the constituent-particle dynamics of real systems and the time evolution equation of their measurable (coarse-grained) quantities, such as local density and velocity. The starting point is the full Hamiltonian description of a system of colloidal particles immersed in a fluid of identical bath particles. Then, we average out the bath via Zwanzig’s projection-operator techniques and obtain the stochastic Langevin equations governing the colloidal-particle dynamics. Introducing the appropriate definition of the local number and momentum density fields yields a generalisation of the Dean-Kawasaki (DK) model, which resembles the stochastic Navier-Stokes description of a fluid. Nevertheless, the DK equation still contains all the microscopic information and, for that reason, does not represent the dynamical law of observable quantities. We address this controversial feature of the DK description by carrying out a nonequilibrium ensemble average. Adopting a natural decomposition into local-equilibrium and nonequilibrium contribution, where the former is related to a generalised version of the canonical distribution, we finally obtain the fluctuating-hydrodynamic equation governing the time-evolution of the mesoscopic density and momentum fields. Along the way, we outline the connection between the ad hoc energy functional introduced in previous DK derivations and the free-energy functional from classical density-functional theory. The resultant equation has the structure of a dynamical density-functional theory (DDFT) with an additional fluctuating force coming from the random interactions with the bath. We show that our fluctuating DDFT formalism corresponds to a particular version of the fluctuating Navier-Stokes equations, originally derived by Landau and Lifshitz

What Density Functional Theory could do for Quantum Information

Science.gov (United States)

Mattsson, Ann

2015-03-01

The Hohenberg-Kohn theorem of Density Functional Theory (DFT), and extensions thereof, tells us that all properties of a system of electrons can be determined through their density, which uniquely determines the many-body wave-function. Given access to the appropriate, universal, functionals of the density we would, in theory, be able to determine all observables of any electronic system, without explicit reference to the wave-function. On the other hand, the wave-function is at the core of Quantum Information (QI), with the wave-function of a set of qubits being the central computational resource in a quantum computer. While there is seemingly little overlap between DFT and QI, reliance upon observables form a key connection. Though the time-evolution of the wave-function and associated phase information is fundamental to quantum computation, the initial and final states of a quantum computer are characterized by observables of the system. While observables can be extracted directly from a system's wave-function, DFT tells us that we may be able to intuit a method for extracting them from its density. In this talk, I will review the fundamentals of DFT and how these principles connect to the world of QI. This will range from DFT's utility in the engineering of physical qubits, to the possibility of using it to efficiently (but approximately) simulate Hamiltonians at the logical level. The apparent paradox of describing algorithms based on the quantum mechanical many-body wave-function with a DFT-like theory based on observables will remain a focus throughout. The ultimate goal of this talk is to initiate a dialog about what DFT could do for QI, in theory and in practice. Sandia National Laboratories is a multi-program laboratory managed and operated by Sandia Corporation, a wholly owned subsidiary of Lockheed Martin Corporation, for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-AC04-94AL85000.

The QTP family of consistent functionals and potentials in Kohn-Sham density functional theory

Energy Technology Data Exchange (ETDEWEB)

Jin, Yifan; Bartlett, Rodney J., E-mail: bartlett@qtp.ufl.edu [Quantum Theory Project and Departments of Chemistry and Physics, University of Florida, Gainesville, Florida 32611 (United States)

2016-07-21

This manuscript presents the second, consistent density functional in the QTP (Quantum Theory Project) family, that is, the CAM-QTP(01). It is a new range-separated exchange-correlation functional in which the non-local exchange contribution is 100% at large separation. It follows the same basic principles of this family that the Kohn-Sham eigenvalues of the occupied orbitals approximately equal the vertical ionization energies, which is not fulfilled by most of the traditional density functional methods. This new CAM-QTP(01) functional significantly improves the accuracy of the vertical excitation energies especially for the Rydberg states in the test set. It also reproduces many other properties such as geometries, reaction barrier heights, and atomization energies.

Estimating density of a rare and cryptic high-mountain Galliform species, the Buff-throated Partridge Tetraophasis szechenyii

Directory of Open Access Journals (Sweden)

Yu Xu

2016-06-01

Full Text Available Estimates of abundance or density are essential for wildlife management and conservation. There are few effective density estimates for the Buff-throated Partridge Tetraophasis szechenyii, a rare and elusive high-mountain Galliform species endemic to western China. In this study, we used the temporary emigration N-mixture model to estimate density of this species, with data acquired from playback point count surveys around a sacred area based on indigenous Tibetan culture of protection of wildlife, in Yajiang County, Sichuan, China, during April-June 2009. Within 84 125-m radius points, we recorded 53 partridge groups during three repeats. The best model indicated that detection probability was described by covariates of vegetation cover type, week of visit, time of day, and weather with weak effects, and a partridge group was present during a sampling period with a constant probability. The abundance component was accounted for by vegetation association. Abundance was substantially higher in rhododendron shrubs, fir-larch forests, mixed spruce-larch-birch forests, and especially oak thickets than in pine forests. The model predicted a density of 5.14 groups/km², which is similar to an estimate of 4.7 - 5.3 groups/km² quantified via an intensive spot-mapping effort. The post-hoc estimate of individual density was 14.44 individuals/km², based on the estimated mean group size of 2.81. We suggest that the method we employed is applicable to estimate densities of Buff-throated Partridges in large areas. Given importance of a mosaic habitat for this species, local logging should be regulated. Despite no effect of the conservation area (sacred on the abundance of Buff-throated Partridges, we suggest regulations linking the sacred mountain conservation area with the official conservation system because of strong local participation facilitated by sacred mountains in land conservation.

Density functional study of gamma-aminopropyltriethoxysilane

International Nuclear Information System (INIS)

Bistricic, L; Volovsek, V; Daani, V; Leskovac, M

2006-01-01

Density functional theory calculations using Becke's three-parameter exchange functional in combination with the Lee-Young-Parr correlation functional (B3-LYP) and standard 6-311 + G(d,p) basis set were carried out to study the conformational stability and vibrational spectra of gamma-aminopropyltriethoxysilane. Calculations reveal the existence of two stable conformers trans and gauche. The calculated energy for the gauche conformation was found to be 608 cm -1 above the minimum energy of the trans conformation. Temperature dependence of Raman spectra of liquid APTES and DFT calculation enabled us to identify the vibrational bands characteristic for both conformers. It has been shown that there is an increase in the population of gauche conformer with increasing temperature

Econometric studies of urban population density: a survey.

Science.gov (United States)

Mcdonald, J F

1989-01-01

This paper presents the 1st reasonably comprehensive survey of empirical research of urban population densities since the publication of the book by Edmonston in 1975. The survey summarizes contributions to empirical knowledge that have been made since 1975 and points toward possible areas for additional research. The paper also provides a brief interpretative intellectual history of the topic. It begins with a personal overview of research in the field. The next section discusses econometric issues that arise in the estimation of population density functions in which density is a function only of a distance to the central business district of the urban area. Section 4 summarizes the studies of a single urban area that went beyond the estimation of simple distance-density functions, and Section 5 discusses studies that sought to explain the variations across urban areas in population density patterns. McDonald refers to the standard theory of urban population density throughout the paper. This basic model is presented in the textbook by Mills and Hamilton and it is assumed that the reader is familiar with the model.

Learning Grasp Affordance Densities

DEFF Research Database (Denmark)

Detry, Renaud; Kraft, Dirk; Kroemer, Oliver

2011-01-01

and relies on kernel density estimation to provide a continuous model. Grasp densities are learned and refined from exploration, by letting a robot “play” with an object in a sequence of graspand-drop actions: The robot uses visual cues to generate a set of grasp hypotheses; it then executes......We address the issue of learning and representing object grasp affordance models. We model grasp affordances with continuous probability density functions (grasp densities) which link object-relative grasp poses to their success probability. The underlying function representation is nonparametric...... these and records their outcomes. When a satisfactory number of grasp data is available, an importance-sampling algorithm turns these into a grasp density. We evaluate our method in a largely autonomous learning experiment run on three objects of distinct shapes. The experiment shows how learning increases success...

Open-system Kohn-Sham density functional theory.

Science.gov (United States)

Zhou, Yongxi; Ernzerhof, Matthias

2012-03-07

A simple model for electron transport through molecules is provided by the source-sink potential (SSP) method [F. Goyer, M. Ernzerhof, and M. Zhuang, J. Chem. Phys. 126, 144104 (2007)]. In SSP, the boundary conditions of having an incoming and outgoing electron current are enforced through complex potentials that are added to the Hamiltonian. Depending on the sign of the imaginary part of the potentials, current density is generated or absorbed. In this way, a finite system can be used to model infinite molecular electronic devices. The SSP has originally been developed for the Hückel method and subsequently it has been extended [F. Goyer and M. Ernzerhof, J. Chem. Phys. 134, 174101 (2011)] to the Hubbard model. Here we present a step towards its generalization for first-principles electronic structure theory methods. In particular, drawing on our earlier work, we discuss a new generalized density functional theory for complex non-Hermitian Hamiltonians. This theory enables us to combine SSP and Kohn-Sham theory to obtain a method for the description of open systems that exchange current density with their environment. Similarly, the Hartree-Fock method is extended to the realm of non-Hermitian, SSP containing Hamiltonians. As a proof of principle, we present the first applications of complex-density functional theory (CODFT) as well as non-Hermitian Hartree-Fock theory to electron transport through molecules. © 2012 American Institute of Physics

Impacts of Airborne Lidar Pulse Density on Estimating Biomass Stocks and Changes in a Selectively Logged Tropical Forest

Directory of Open Access Journals (Sweden)

Carlos Alberto Silva

2017-10-01

Full Text Available Airborne lidar is a technology well-suited for mapping many forest attributes, including aboveground biomass (AGB stocks and changes in selective logging in tropical forests. However, trade-offs still exist between lidar pulse density and accuracy of AGB estimates. We assessed the impacts of lidar pulse density on the estimation of AGB stocks and changes using airborne lidar and field plot data in a selectively logged tropical forest located near Paragominas, Pará, Brazil. Field-derived AGB was computed at 85 square 50 × 50 m plots in 2014. Lidar data were acquired in 2012 and 2014, and for each dataset the pulse density was subsampled from its original density of 13.8 and 37.5 pulses·m−2 to lower densities of 12, 10, 8, 6, 4, 2, 0.8, 0.6, 0.4 and 0.2 pulses·m−2. For each pulse density dataset, a power-law model was developed to estimate AGB stocks from lidar-derived mean height and corresponding changes between the years 2012 and 2014. We found that AGB change estimates at the plot level were only slightly affected by pulse density. However, at the landscape level we observed differences in estimated AGB change of >20 Mg·ha−1 when pulse density decreased from 12 to 0.2 pulses·m−2. The effects of pulse density were more pronounced in areas of steep slope, especially when the digital terrain models (DTMs used in the lidar derived forest height were created from reduced pulse density data. In particular, when the DTM from high pulse density in 2014 was used to derive the forest height from both years, the effects on forest height and the estimated AGB stock and changes did not exceed 20 Mg·ha−1. The results suggest that AGB change can be monitored in selective logging in tropical forests with reasonable accuracy and low cost with low pulse density lidar surveys if a baseline high-quality DTM is available from at least one lidar survey. We recommend the results of this study to be considered in developing projects and national

Density Functional Theory and Materials Modeling at Atomistic Length Scales

Directory of Open Access Journals (Sweden)

Swapan K. Ghosh

2002-04-01

Full Text Available Abstract: We discuss the basic concepts of density functional theory (DFT as applied to materials modeling in the microscopic, mesoscopic and macroscopic length scales. The picture that emerges is that of a single unified framework for the study of both quantum and classical systems. While for quantum DFT, the central equation is a one-particle Schrodinger-like Kohn-Sham equation, the classical DFT consists of Boltzmann type distributions, both corresponding to a system of noninteracting particles in the field of a density-dependent effective potential, the exact functional form of which is unknown. One therefore approximates the exchange-correlation potential for quantum systems and the excess free energy density functional or the direct correlation functions for classical systems. Illustrative applications of quantum DFT to microscopic modeling of molecular interaction and that of classical DFT to a mesoscopic modeling of soft condensed matter systems are highlighted.

Estimating the mass density in the thermosphere with the CYGNSS mission.

Science.gov (United States)

Bussy-Virat, C.; Ridley, A. J.

2017-12-01

The Cyclone Global Navigation Satellite System (CYGNSS) mission, launched in December 2016, is a constellation of eight satellites orbiting the Earth at 510 km. Its goal is to improve our understanding of rapid hurricane wind intensification. Each CYGNSS satellite uses GPS signals that are reflected off of the ocean's surface to measure the wind. The GPS can also be used to specify the orbit of the satellites quite precisely. The motion of satellites in low Earth orbit are greatly influenced by the neutral density of the surrounding atmosphere through drag. Modeling the neutral density in the upper atmosphere is a major challenge as it involves a comprehensive understanding of the complex coupling between the thermosphere and the ionosphere, the magnetosphere, and the Sun. This is why thermospheric models (such as NRLMSIS, Jacchia-Bowman, HASDM, GITM, or TIEGCM) can only approximate it with a limited accuracy, which decreases during strong geomagnetic events. Because atmospheric drag directly depends on the thermospheric density, it can be estimated applying filtering methods to the trajectories of the CYGNSS observatories. The CYGNSS mission can provide unique results since the constellation of eight satellites enables multiple measurements of the same region at close intervals ( 10 minutes), which can be used to detect short time scale features. Moreover, the CYGNSS spacecraft can be pitched from a low to high drag attitude configuration, which can be used in the filtering methods to improve the accuracy of the atmospheric density estimation. The methodology and the results of this approach applied to the CYGNSS mission will be presented.

Bone mineral density and menstrual function in adolescent female ...

African Journals Online (AJOL)

Bone mineral density and menstrual function in adolescent female long-distance runners - A prospective comparative study of bone structure and menstrual function in adolescent female endurance athletes from five secondary schools in Pretoria.

Estimation of daily global solar radiation as a function of the solar energy potential at soil surface

International Nuclear Information System (INIS)

Pereira, A.B.; Vrisman, A.L.; Galvani, E.

2002-01-01

The solar radiation received at the surface of the earth, apart from its relevance to several daily human activities, plays an important role in the growth and development of plants. The aim of the current work was to develop and gauge an estimation model for the evaluation of the global solar radiation flux density as a function of the solar energy potential at soil surface. Radiometric data were collected at Ponta Grossa, PR, Brazil (latitude 25°13' S, longitude 50°03' W, altitude 880 m). Estimated values of solar energy potential obtained as a function of only one measurement taken at solar noon time were confronted with those measured by a Robitzsch bimetalic actinograph, for days that presented insolation ratios higher than 0.85. This data set was submitted to a simple linear regression analysis, having been obtained a good adjustment between observed and calculated values. For the estimation of the coefficients a and b of Angström's equation, the method based on the solar energy potential at soil surface was used for the site under study. The methodology was efficient to assess the coefficients, aiming at the determination of the global solar radiation flux density, whith quickness and simplicity, having also found out that the criterium for the estimation of the solar energy potential is equivalent to that of the classical methodology of Angström. Knowledge of the available solar energy potential and global solar radiation flux density is of great importance for the estimation of the maximum atmospheric evaporative demand, of water consumption by irrigated crops, and also for building solar engineering equipment, such as driers, heaters, solar ovens, refrigerators, etc [pt

Semi-local machine-learned kinetic energy density functional with third-order gradients of electron density

Science.gov (United States)

Seino, Junji; Kageyama, Ryo; Fujinami, Mikito; Ikabata, Yasuhiro; Nakai, Hiromi

2018-06-01

A semi-local kinetic energy density functional (KEDF) was constructed based on machine learning (ML). The present scheme adopts electron densities and their gradients up to third-order as the explanatory variables for ML and the Kohn-Sham (KS) kinetic energy density as the response variable in atoms and molecules. Numerical assessments of the present scheme were performed in atomic and molecular systems, including first- and second-period elements. The results of 37 conventional KEDFs with explicit formulae were also compared with those of the ML KEDF with an implicit formula. The inclusion of the higher order gradients reduces the deviation of the total kinetic energies from the KS calculations in a stepwise manner. Furthermore, our scheme with the third-order gradient resulted in the closest kinetic energies to the KS calculations out of the presented functionals.

Direct estimation of functionals of density operators by local operations and classical communication

International Nuclear Information System (INIS)

Alves, Carolina Moura; Horodecki, Pawel; Oi, Daniel K. L.; Kwek, L. C.; Ekert, Artur K.

2003-01-01

We present a method of direct estimation of important properties of a shared bipartite quantum state, within the ''distant laboratories'' paradigm, using only local operations and classical communication. We apply this procedure to spectrum estimation of shared states, and locally implementable structural physical approximations to incompletely positive maps. This procedure can also be applied to the estimation of channel capacity and measures of entanglement

Efficient Estimation of Dynamic Density Functions with Applications in Streaming Data

KAUST Repository

Qahtan, Abdulhakim Ali Ali

2016-01-01

application is to detect outliers in data streams from sensor networks based on the estimated PDF. The method detects outliers accurately and outperforms baseline methods designed for detecting and cleaning outliers in sensor data. The third application

Reconstructing Regional Ionospheric Electron Density: A Combined Spherical Slepian Function and Empirical Orthogonal Function Approach

Science.gov (United States)

Farzaneh, Saeed; Forootan, Ehsan

2018-03-01

The computerized ionospheric tomography is a method for imaging the Earth's ionosphere using a sounding technique and computing the slant total electron content (STEC) values from data of the global positioning system (GPS). The most common approach for ionospheric tomography is the voxel-based model, in which (1) the ionosphere is divided into voxels, (2) the STEC is then measured along (many) satellite signal paths, and finally (3) an inversion procedure is applied to reconstruct the electron density distribution of the ionosphere. In this study, a computationally efficient approach is introduced, which improves the inversion procedure of step 3. Our proposed method combines the empirical orthogonal function and the spherical Slepian base functions to describe the vertical and horizontal distribution of electron density, respectively. Thus, it can be applied on regional and global case studies. Numerical application is demonstrated using the ground-based GPS data over South America. Our results are validated against ionospheric tomography obtained from the constellation observing system for meteorology, ionosphere, and climate (COSMIC) observations and the global ionosphere map estimated by international centers, as well as by comparison with STEC derived from independent GPS stations. Using the proposed approach, we find that while using 30 GPS measurements in South America, one can achieve comparable accuracy with those from COSMIC data within the reported accuracy (1 × 1011 el/cm3) of the product. Comparisons with real observations of two GPS stations indicate an absolute difference is less than 2 TECU (where 1 total electron content unit, TECU, is 1016 electrons/m2).

Response functions of cold neutron matter: density, spin and current fluctuations

Energy Technology Data Exchange (ETDEWEB)

Keller, Jochen; Sedrakian, Armen [Institut fuer Theoretische Physik, Goethe-Universitaet, Frankfurt am Main (Germany)

2014-07-01

We study the response of a single-component pair-correlated baryonic Fermi-liquid to density, spin, and their current perturbations. A complete set of response functions is calculated in the low-temperature regime. We derive the spectral functions of collective excitations associated with the density, density-current, spin, and spin-current perturbations. The dispersion relations of density and spin fluctuations are determined and it is shown that the density fluctuations lead to exciton-like undamped bound states, whereas the spin excitations correspond to diffusive modes above the pair-breaking threshold. The contribution of the collective pair-breaking modes to the specific heat of neutron matter at subnuclear densities is computed and is shown to be comparable to that of the degenerate electron gas at not too low temperatures.

Estimating Stochastic Volatility Models using Prediction-based Estimating Functions

DEFF Research Database (Denmark)

Lunde, Asger; Brix, Anne Floor

to the performance of the GMM estimator based on conditional moments of integrated volatility from Bollerslev and Zhou (2002). The case where the observed log-price process is contaminated by i.i.d. market microstructure (MMS) noise is also investigated. First, the impact of MMS noise on the parameter estimates from......In this paper prediction-based estimating functions (PBEFs), introduced in Sørensen (2000), are reviewed and PBEFs for the Heston (1993) stochastic volatility model are derived. The finite sample performance of the PBEF based estimator is investigated in a Monte Carlo study, and compared...... to correctly account for the noise are investigated. Our Monte Carlo study shows that the estimator based on PBEFs outperforms the GMM estimator, both in the setting with and without MMS noise. Finally, an empirical application investigates the possible challenges and general performance of applying the PBEF...

On extending Kohn-Sham density functionals to systems with fractional number of electrons.

Science.gov (United States)

Li, Chen; Lu, Jianfeng; Yang, Weitao

2017-06-07

We analyze four ways of formulating the Kohn-Sham (KS) density functionals with a fractional number of electrons, through extending the constrained search space from the Kohn-Sham and the generalized Kohn-Sham (GKS) non-interacting v-representable density domain for integer systems to four different sets of densities for fractional systems. In particular, these density sets are (I) ensemble interacting N-representable densities, (II) ensemble non-interacting N-representable densities, (III) non-interacting densities by the Janak construction, and (IV) non-interacting densities whose composing orbitals satisfy the Aufbau occupation principle. By proving the equivalence of the underlying first order reduced density matrices associated with these densities, we show that sets (I), (II), and (III) are equivalent, and all reduce to the Janak construction. Moreover, for functionals with the ensemble v-representable assumption at the minimizer, (III) reduces to (IV) and thus justifies the previous use of the Aufbau protocol within the (G)KS framework in the study of the ground state of fractional electron systems, as defined in the grand canonical ensemble at zero temperature. By further analyzing the Aufbau solution for different density functional approximations (DFAs) in the (G)KS scheme, we rigorously prove that there can be one and only one fractional occupation for the Hartree Fock functional, while there can be multiple fractional occupations for general DFAs in the presence of degeneracy. This has been confirmed by numerical calculations using the local density approximation as a representative of general DFAs. This work thus clarifies important issues on density functional theory calculations for fractional electron systems.

Nonlocal and Nonadiabatic Effects in the Charge-Density Response of Solids: A Time-Dependent Density-Functional Approach

Science.gov (United States)

Panholzer, Martin; Gatti, Matteo; Reining, Lucia

2018-04-01

The charge-density response of extended materials is usually dominated by the collective oscillation of electrons, the plasmons. Beyond this feature, however, intriguing many-body effects are observed. They cannot be described by one of the most widely used approaches for the calculation of dielectric functions, which is time-dependent density functional theory (TDDFT) in the adiabatic local density approximation (ALDA). Here, we propose an approximation to the TDDFT exchange-correlation kernel which is nonadiabatic and nonlocal. It is extracted from correlated calculations in the homogeneous electron gas, where we have tabulated it for a wide range of wave vectors and frequencies. A simple mean density approximation allows one to use it in inhomogeneous materials where the density varies on a scale of 1.6 rs or faster. This kernel contains effects that are completely absent in the ALDA; in particular, it correctly describes the double plasmon in the dynamic structure factor of sodium, and it shows the characteristic low-energy peak that appears in systems with low electronic density. It also leads to an overall quantitative improvement of spectra.

A Comparative Density Functional Theory and Density Functional Tight Binding Study of Phases of Nitrogen Including a High Energy Density Material N8

Directory of Open Access Journals (Sweden)

Nicholas Capel

2015-11-01

Full Text Available We present a comparative dispersion-corrected Density Functional Theory (DFT and Density Functional Tight Binding (DFTB-D study of several phases of nitrogen, including the well-known alpha, beta, and gamma phases as well as recently discovered highly energetic phases: covalently bound cubic gauche (cg nitrogen and molecular (vdW-bound N8 crystals. Among several tested parametrizations of N–N interactions for DFTB, we identify only one that is suitable for modeling of all these phases. This work therefore establishes the applicability of DFTB-D to studies of phases, including highly metastable phases, of nitrogen, which will be of great use for modelling of dynamics of reactions involving these phases, which may not be practical with DFT due to large required space and time scales. We also derive a dispersion-corrected DFT (DFT-D setup (atom-centered basis parameters and Grimme dispersion parameters tuned for accurate description simultaneously of several nitrogen allotropes including covalently and vdW-bound crystals and including high-energy phases.

Automated voxelization of 3D atom probe data through kernel density estimation

International Nuclear Information System (INIS)

Srinivasan, Srikant; Kaluskar, Kaustubh; Dumpala, Santoshrupa; Broderick, Scott; Rajan, Krishna

2015-01-01

Identifying nanoscale chemical features from atom probe tomography (APT) data routinely involves adjustment of voxel size as an input parameter, through visual supervision, making the final outcome user dependent, reliant on heuristic knowledge and potentially prone to error. This work utilizes Kernel density estimators to select an optimal voxel size in an unsupervised manner to perform feature selection, in particular targeting resolution of interfacial features and chemistries. The capability of this approach is demonstrated through analysis of the γ / γ’ interface in a Ni–Al–Cr superalloy. - Highlights: • Develop approach for standardizing aspects of atom probe reconstruction. • Use Kernel density estimators to select optimal voxel sizes in an unsupervised manner. • Perform interfacial analysis of Ni–Al–Cr superalloy, using new automated approach. • Optimize voxel size to preserve the feature of interest and minimizing loss / noise.

Trapping Elusive Cats: Using Intensive Camera Trapping to Estimate the Density of a Rare African Felid.

Science.gov (United States)

Brassine, Eléanor; Parker, Daniel

2015-01-01

Camera trapping studies have become increasingly popular to produce population estimates of individually recognisable mammals. Yet, monitoring techniques for rare species which occur at extremely low densities are lacking. Additionally, species which have unpredictable movements may make obtaining reliable population estimates challenging due to low detectability. Our study explores the effectiveness of intensive camera trapping for estimating cheetah (Acinonyx jubatus) numbers. Using both a more traditional, systematic grid approach and pre-determined, targeted sites for camera placement, the cheetah population of the Northern Tuli Game Reserve, Botswana was sampled between December 2012 and October 2013. Placement of cameras in a regular grid pattern yielded very few (n = 9) cheetah images and these were insufficient to estimate cheetah density. However, pre-selected cheetah scent-marking posts provided 53 images of seven adult cheetahs (0.61 ± 0.18 cheetahs/100 km²). While increasing the length of the camera trapping survey from 90 to 130 days increased the total number of cheetah images obtained (from 53 to 200), no new individuals were recorded and the estimated population density remained stable. Thus, our study demonstrates that targeted camera placement (irrespective of survey duration) is necessary for reliably assessing cheetah densities where populations are naturally very low or dominated by transient individuals. Significantly our approach can easily be applied to other rare predator species.

Trapping Elusive Cats: Using Intensive Camera Trapping to Estimate the Density of a Rare African Felid

Science.gov (United States)

Brassine, Eléanor; Parker, Daniel

2015-01-01

Camera trapping studies have become increasingly popular to produce population estimates of individually recognisable mammals. Yet, monitoring techniques for rare species which occur at extremely low densities are lacking. Additionally, species which have unpredictable movements may make obtaining reliable population estimates challenging due to low detectability. Our study explores the effectiveness of intensive camera trapping for estimating cheetah (Acinonyx jubatus) numbers. Using both a more traditional, systematic grid approach and pre-determined, targeted sites for camera placement, the cheetah population of the Northern Tuli Game Reserve, Botswana was sampled between December 2012 and October 2013. Placement of cameras in a regular grid pattern yielded very few (n = 9) cheetah images and these were insufficient to estimate cheetah density. However, pre-selected cheetah scent-marking posts provided 53 images of seven adult cheetahs (0.61 ± 0.18 cheetahs/100km²). While increasing the length of the camera trapping survey from 90 to 130 days increased the total number of cheetah images obtained (from 53 to 200), no new individuals were recorded and the estimated population density remained stable. Thus, our study demonstrates that targeted camera placement (irrespective of survey duration) is necessary for reliably assessing cheetah densities where populations are naturally very low or dominated by transient individuals. Significantly our approach can easily be applied to other rare predator species. PMID:26698574

Trapping Elusive Cats: Using Intensive Camera Trapping to Estimate the Density of a Rare African Felid.

Directory of Open Access Journals (Sweden)

Eléanor Brassine

Full Text Available Camera trapping studies have become increasingly popular to produce population estimates of individually recognisable mammals. Yet, monitoring techniques for rare species which occur at extremely low densities are lacking. Additionally, species which have unpredictable movements may make obtaining reliable population estimates challenging due to low detectability. Our study explores the effectiveness of intensive camera trapping for estimating cheetah (Acinonyx jubatus numbers. Using both a more traditional, systematic grid approach and pre-determined, targeted sites for camera placement, the cheetah population of the Northern Tuli Game Reserve, Botswana was sampled between December 2012 and October 2013. Placement of cameras in a regular grid pattern yielded very few (n = 9 cheetah images and these were insufficient to estimate cheetah density. However, pre-selected cheetah scent-marking posts provided 53 images of seven adult cheetahs (0.61 ± 0.18 cheetahs/100 km². While increasing the length of the camera trapping survey from 90 to 130 days increased the total number of cheetah images obtained (from 53 to 200, no new individuals were recorded and the estimated population density remained stable. Thus, our study demonstrates that targeted camera placement (irrespective of survey duration is necessary for reliably assessing cheetah densities where populations are naturally very low or dominated by transient individuals. Significantly our approach can easily be applied to other rare predator species.

The use of perturbation theory in density-functional theory

International Nuclear Information System (INIS)

Goerling, A.

1996-01-01

Perturbation theory with respect to the electron-electron interaction leads to expressions for the exchange and correlation energies and potentials in terms of Kohn-Sham orbitals and Kohn-Sham eigenvalues. An exact open-quote exchange-only close-quote procedure for solids is introduced. Results for several semiconductors are presented. Perturbation theory expansions for the hardness of molecules and the bad gap of solids are given. Density-functional exchange and correlation energies for excited states are defined and a perturbation theory based Kohn-Sham formalism to treat excited states within density-functional theory is introduced

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