Comparison of density estimators. [Estimation of probability density functions
Energy Technology Data Exchange (ETDEWEB)
Kao, S.; Monahan, J.F.
1977-09-01
Recent work in the field of probability density estimation has included the introduction of some new methods, such as the polynomial and spline methods and the nearest neighbor method, and the study of asymptotic properties in depth. This earlier work is summarized here. In addition, the computational complexity of the various algorithms is analyzed, as are some simulations. The object is to compare the performance of the various methods in small samples and their sensitivity to change in their parameters, and to attempt to discover at what point a sample is so small that density estimation can no longer be worthwhile. (RWR)
Green's function based density estimation
Energy Technology Data Exchange (ETDEWEB)
Kovesarki, Peter; Brock, Ian C.; Nuncio Quiroz, Adriana Elizabeth [Physikalisches Institut, Universitaet Bonn (Germany)
2012-07-01
A method was developed based on Green's function identities to estimate probability densities. This can be used for likelihood estimations and for binary classifications. It offers several advantages over neural networks, boosted decision trees and other, regression based classifiers. For example, it is less prone to overtraining, and it is much easier to combine several samples. Some capabilities are demonstrated using ATLAS data.
Bayesian error estimation in density-functional theory
DEFF Research Database (Denmark)
Mortensen, Jens Jørgen; Kaasbjerg, Kristen; Frederiksen, Søren Lund
2005-01-01
We present a practical scheme for performing error estimates for density-functional theory calculations. The approach, which is based on ideas from Bayesian statistics, involves creating an ensemble of exchange-correlation functionals by comparing with an experimental database of binding energies...... for molecules and solids. Fluctuations within the ensemble can then be used to estimate errors relative to experiment on calculated quantities such as binding energies, bond lengths, and vibrational frequencies. It is demonstrated that the error bars on energy differences may vary by orders of magnitude...
Directory of Open Access Journals (Sweden)
D.O. Smallwood
1996-01-01
Full Text Available It is shown that the usual method for estimating the coherence functions (ordinary, partial, and multiple for a general multiple-input! multiple-output problem can be expressed as a modified form of Cholesky decomposition of the cross-spectral density matrix of the input and output records. The results can be equivalently obtained using singular value decomposition (SVD of the cross-spectral density matrix. Using SVD suggests a new form of fractional coherence. The formulation as a SVD problem also suggests a way to order the inputs when a natural physical order of the inputs is absent.
Error estimates for density-functional theory predictions of surface energy and work function
De Waele, Sam; Lejaeghere, Kurt; Sluydts, Michael; Cottenier, Stefaan
2016-12-01
Density-functional theory (DFT) predictions of materials properties are becoming ever more widespread. With increased use comes the demand for estimates of the accuracy of DFT results. In view of the importance of reliable surface properties, this work calculates surface energies and work functions for a large and diverse test set of crystalline solids. They are compared to experimental values by performing a linear regression, which results in a measure of the predictable and material-specific error of the theoretical result. Two of the most prevalent functionals, the local density approximation (LDA) and the Perdew-Burke-Ernzerhof parametrization of the generalized gradient approximation (PBE-GGA), are evaluated and compared. Both LDA and GGA-PBE are found to yield accurate work functions with error bars below 0.3 eV, rivaling the experimental precision. LDA also provides satisfactory estimates for the surface energy with error bars smaller than 10%, but GGA-PBE significantly underestimates the surface energy for materials with a large correlation energy.
Kaye, Jason; Yang, Chao
2014-01-01
Kohn-Sham density functional theory is one of the most widely used electronic structure theories. The recently developed adaptive local basis functions form an accurate and systematically improvable basis set for solving Kohn-Sham density functional theory using discontinuous Galerkin methods, requiring a small number of basis functions per atom. In this paper we develop residual-based a posteriori error estimates for the adaptive local basis approach, which can be used to guide non-uniform basis refinement for highly inhomogeneous systems such as surfaces and large molecules. The adaptive local basis functions are non-polynomial basis functions, and standard a posteriori error estimates for $hp$-refinement using polynomial basis functions do not directly apply. We generalize the error estimates for $hp$-refinement to non-polynomial basis functions. We demonstrate the practical use of the a posteriori error estimator in performing three-dimensional Kohn-Sham density functional theory calculations for quasi-2D...
Nonparametric estimate of spectral density functions of sample covariance matrices: A first step
2012-01-01
The density function of the limiting spectral distribution of general sample covariance matrices is usually unknown. We propose to use kernel estimators which are proved to be consistent. A simulation study is also conducted to show the performance of the estimators.
Wavelet Optimal Estimations for Density Functions under Severely Ill-Posed Noises
Directory of Open Access Journals (Sweden)
Rui Li
2013-01-01
Full Text Available Motivated by Lounici and Nickl's work (2011, this paper considers the problem of estimation of a density f based on an independent and identically distributed sample Y1,…,Yn from g=f*φ. We show a wavelet optimal estimation for a density (function over Besov ball Br,qs(L and Lp risk (1≤p<∞ in the presence of severely ill-posed noises. A wavelet linear estimation is firstly presented. Then, we prove a lower bound, which shows our wavelet estimator optimal. In other words, nonlinear wavelet estimations are not needed in that case. It turns out that our results extend some theorems of Pensky and Vidakovic (1999, as well as Fan and Koo (2002.
mBEEF-vdW: Robust fitting of error estimation density functionals
Lundgaard, Keld T.; Wellendorff, Jess; Voss, Johannes; Jacobsen, Karsten W.; Bligaard, Thomas
2016-06-01
We propose a general-purpose semilocal/nonlocal exchange-correlation functional approximation, named mBEEF-vdW. The exchange is a meta generalized gradient approximation, and the correlation is a semilocal and nonlocal mixture, with the Rutgers-Chalmers approximation for van der Waals (vdW) forces. The functional is fitted within the Bayesian error estimation functional (BEEF) framework [J. Wellendorff et al., Phys. Rev. B 85, 235149 (2012), 10.1103/PhysRevB.85.235149; J. Wellendorff et al., J. Chem. Phys. 140, 144107 (2014), 10.1063/1.4870397]. We improve the previously used fitting procedures by introducing a robust MM-estimator based loss function, reducing the sensitivity to outliers in the datasets. To more reliably determine the optimal model complexity, we furthermore introduce a generalization of the bootstrap 0.632 estimator with hierarchical bootstrap sampling and geometric mean estimator over the training datasets. Using this estimator, we show that the robust loss function leads to a 10 % improvement in the estimated prediction error over the previously used least-squares loss function. The mBEEF-vdW functional is benchmarked against popular density functional approximations over a wide range of datasets relevant for heterogeneous 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 the potential-energy curve of graphene on the nickel(111) surface, where mBEEF-vdW matches the experimental binding length. mBEEF-vdW is currently available in gpaw and other density functional theory codes through Libxc, version 3.0.0.
Pedotransfer functions for Irish soils - estimation of bulk density (ρb) per horizon type
Reidy, B.; Simo, I.; Sills, P.; Creamer, R. E.
2016-01-01
Soil bulk density is a key property in defining soil characteristics. It describes the packing structure of the soil and is also essential for the measurement of soil carbon stock and nutrient assessment. In many older surveys this property was neglected and in many modern surveys this property is omitted due to cost both in laboratory and labour and in cases where the core method cannot be applied. To overcome these oversights pedotransfer functions are applied using other known soil properties to estimate bulk density. Pedotransfer functions have been derived from large international data sets across many studies, with their own inherent biases, many ignoring horizonation and depth variances. Initially pedotransfer functions from the literature were used to predict different horizon type bulk densities using local known bulk density data sets. Then the best performing of the pedotransfer functions were selected to recalibrate and then were validated again using the known data. The predicted co-efficient of determination was 0.5 or greater in 12 of the 17 horizon types studied. These new equations allowed gap filling where bulk density data were missing in part or whole soil profiles. This then allowed the development of an indicative soil bulk density map for Ireland at 0-30 and 30-50 cm horizon depths. In general the horizons with the largest known data sets had the best predictions, using the recalibrated and validated pedotransfer functions.
Maccione, Alessandro; Garofalo, Matteo; Nieus, Thierry; Tedesco, Mariateresa; Berdondini, Luca; Martinoia, Sergio
2012-06-15
We used electrophysiological signals recorded by CMOS Micro Electrode Arrays (MEAs) at high spatial resolution to estimate the functional-effective connectivity of sparse hippocampal neuronal networks in vitro by applying a cross-correlation (CC) based method and ad hoc developed spatio-temporal filtering. Low-density cultures were recorded by a recently introduced CMOS-MEA device providing simultaneous multi-site acquisition at high-spatial (21 μm inter-electrode separation) as well as high-temporal resolution (8 kHz per channel). The method is applied to estimate functional connections in different cultures and it is refined by applying spatio-temporal filters that allow pruning of those functional connections not compatible with signal propagation. This approach permits to discriminate between possible causal influence and spurious co-activation, and to obtain detailed maps down to cellular resolution. Further, a thorough analysis of the links strength and time delays (i.e., amplitude and peak position of the CC function) allows characterizing the inferred interconnected networks and supports a possible discrimination of fast mono-synaptic propagations, and slow poly-synaptic pathways. By focusing on specific regions of interest we could observe and analyze microcircuits involving connections among a few cells. Finally, the use of the high-density MEA with low density cultures analyzed with the proposed approach enables to compare the inferred effective links with the network structure obtained by staining procedures.
Institute of Scientific and Technical Information of China (English)
无
2006-01-01
A method to estimate the probabilistic density function (PDF) of shear strength parameters was proposed. The second Chebyshev orthogonal polynomial(SCOP) combined with sample moments (the originmoments)was used to approximate the PDF of parameters. χ2 test was adopted to verify the availability of the method. It is distribution-free because no classical theoretical distributions were assumed in advance and the inference result provides a universal form of probability density curves. Six most commonly-used theoretical distributions named normal, lognormal, extreme value Ⅰ , gama, beta and Weibull distributions were used to verify SCOP method. An example from the observed data of cohesion c of a kind of silt clay was presented for illustrative purpose. The results show that the acceptance levels in SCOP are all smaller than those in the classical finite comparative method and the SCOP function is more accurate and effective in the reliability analysis of geotechnical engineering.
Efficient Estimation of Dynamic Density Functions with Applications in Streaming Data
Qahtan, Abdulhakim
2016-05-11
Recent advances in computing technology allow for collecting vast amount of data that arrive continuously in the form of streams. Mining data streams is challenged by the speed and volume of the arriving data. Furthermore, the underlying distribution of the data changes over the time in unpredicted scenarios. To reduce the computational cost, data streams are often studied in forms of condensed representation, e.g., Probability Density Function (PDF). This thesis aims at developing an online density estimator that builds a model called KDE-Track for characterizing the dynamic density of the data streams. KDE-Track estimates the PDF of the stream at a set of resampling points and uses interpolation to estimate the density at any given point. To reduce the interpolation error and computational complexity, we introduce adaptive resampling where more/less resampling points are used in high/low curved regions of the PDF. The PDF values at the resampling points are updated online to provide up-to-date model of the data stream. Comparing with other existing online density estimators, KDE-Track is often more accurate (as reflected by smaller error values) and more computationally efficient (as reflected by shorter running time). The anytime available PDF estimated by KDE-Track can be applied for visualizing the dynamic density of data streams, outlier detection and change detection in data streams. In this thesis work, the first application is to visualize the taxi traffic volume in New York city. Utilizing KDE-Track allows for visualizing and monitoring the traffic flow on real time without extra overhead and provides insight analysis of the pick up demand that can be utilized by service providers to improve service availability. The second 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
Sadeh, Iftach; Lahav, Ofer
2015-01-01
We present ANNz2, a new implementation of the public software for photometric redshift (photo-z) estimation of Collister and Lahav (2004). Large photometric galaxy surveys are important for cosmological studies, and in particular for characterizing the nature of dark energy. The success of such surveys greatly depends on the ability to measure photo-zs, based on limited spectral data. ANNz2 utilizes multiple machine learning methods, such as artificial neural networks, boosted decision/regression trees and k-nearest neighbours. The objective of the algorithm is to dynamically optimize the performance of the photo-z estimation, and to properly derive the associated uncertainties. In addition to single-value solutions, the new code also generates full probability density functions (PDFs) in two different ways. In addition, estimators are incorporated to mitigate possible problems of spectroscopic training samples which are not representative or are incomplete. ANNz2 is also adapted to provide optimized solution...
mBEEF: An accurate semi-local Bayesian error estimation density functional
Wellendorff, Jess; Lundgaard, Keld T.; Jacobsen, Karsten W.; Bligaard, Thomas
2014-04-01
We present a general-purpose meta-generalized gradient approximation (MGGA) exchange-correlation functional generated within the Bayesian error estimation functional framework [J. Wellendorff, K. T. Lundgaard, A. Møgelhøj, V. Petzold, D. D. Landis, J. K. Nørskov, T. Bligaard, and K. W. Jacobsen, Phys. Rev. B 85, 235149 (2012)]. The functional is designed to give reasonably accurate density functional theory (DFT) predictions of a broad range of properties in materials physics and chemistry, while exhibiting a high degree of transferability. Particularly, it improves upon solid cohesive energies and lattice constants over the BEEF-vdW functional without compromising high performance on adsorption and reaction energies. We thus expect it to be particularly well-suited for studies in surface science and catalysis. An ensemble of functionals for error estimation in DFT is an intrinsic feature of exchange-correlation models designed this way, and we show how the Bayesian ensemble may provide a systematic analysis of the reliability of DFT based simulations.
On the method of logarithmic cumulants for parametric probability density function estimation.
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.
Efficient estimation of dynamic density functions with an application to outlier detection
Qahtan, Abdulhakim Ali Ali
2012-01-01
In this paper, we propose a new method to estimate the dynamic density over data streams, named KDE-Track as it is based on a conventional and widely used Kernel Density Estimation (KDE) method. KDE-Track can efficiently estimate the density with linear complexity by using interpolation on a kernel model, which is incrementally updated upon the arrival of streaming data. Both theoretical analysis and experimental validation show that KDE-Track outperforms traditional KDE and a baseline method Cluster-Kernels on estimation accuracy of the complex density structures in data streams, computing time and memory usage. KDE-Track is also demonstrated on timely catching the dynamic density of synthetic and real-world data. In addition, KDE-Track is used to accurately detect outliers in sensor data and compared with two existing methods developed for detecting outliers and cleaning sensor data. © 2012 ACM.
Constrained Kalman Filtering Via Density Function Truncation for Turbofan Engine Health Estimation
Simon, Dan; Simon, Donald L.
2006-01-01
Kalman filters are often used to estimate the state variables of a dynamic system. However, in the application of Kalman filters some known signal information is often either ignored or dealt with heuristically. For instance, state variable constraints (which may be based on physical considerations) are often neglected because they do not fit easily into the structure of the Kalman filter. This paper develops an analytic method of incorporating state variable inequality constraints in the Kalman filter. The resultant filter truncates the PDF (probability density function) of the Kalman filter estimate at the known constraints and then computes the constrained filter estimate as the mean of the truncated PDF. The incorporation of state variable constraints increases the computational effort of the filter but significantly improves its estimation accuracy. The improvement is demonstrated via simulation results obtained from a turbofan engine model. The turbofan engine model contains 3 state variables, 11 measurements, and 10 component health parameters. It is also shown that the truncated Kalman filter may be a more accurate way of incorporating inequality constraints than other constrained filters (e.g., the projection approach to constrained filtering).
Comparison of volatility function technique for risk-neutral densities estimation
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.
Lussana, C.
2013-04-01
The presented work focuses on the investigation of gridded daily minimum (TN) and maximum (TX) temperature probability density functions (PDFs) with the intent of both characterising a region and detecting extreme values. The empirical PDFs estimation procedure has been realised using the most recent years of gridded temperature analysis fields available at ARPA Lombardia, in Northern Italy. The spatial interpolation is based on an implementation of Optimal Interpolation using observations from a dense surface network of automated weather stations. An effort has been made to identify both the time period and the spatial areas with a stable data density otherwise the elaboration could be influenced by the unsettled station distribution. The PDF used in this study is based on the Gaussian distribution, nevertheless it is designed to have an asymmetrical (skewed) shape in order to enable distinction between warming and cooling events. Once properly defined the occurrence of extreme events, it is possible to straightforwardly deliver to the users the information on a local-scale in a concise way, such as: TX extremely cold/hot or TN extremely cold/hot.
Probability density function and estimation for error of digitized map coordinates in GIS
Institute of Scientific and Technical Information of China (English)
童小华; 刘大杰
2004-01-01
Traditionally, it is widely accepted that measurement error usually obeys the normal distribution. However, in this paper a new idea is proposed that the error in digitized data which is a major derived data source in GIS does not obey the normal distribution but the p-norm distribution with a determinate parameter. Assuming that the error is random and has the same statistical properties, the probability density function of the normal distribution,Laplace distribution and p-norm distribution are derived based on the arithmetic mean axiom, median axiom and pmedian axiom, which means that the normal distribution is only one of these distributions but not the least one.Based on this idea, distribution fitness tests such as Skewness and Kurtosis coefficient test, Pearson chi-square x2 test and Kolmogorov test for digitized data are conducted. The results show that the error in map digitization obeys the p-norm distribution whose parameter is close to 1.60. A least p-norm estimation and the least square estimation of digitized data are further analyzed, showing that the least p-norm adiustment is better than the least square adjustment for digitized data processing in GIS.
Statistical Analysis of the Spectral Density Estimate Obtained via Coifman Scaling Function
2007-01-01
Spectral density built as Fourier transform of covariance sequence of stationary random process is determining the process characteristics and makes for analysis of it’s structure. Thus, one of the main problems in time series analysis is constructing consistent estimates of spectral density via successive, taken after equal periods of time observations of stationary random process. This article is devoted to investigation of problems dealing with application of wavelet anal...
PEDO-TRANSFER FUNCTIONS FOR ESTIMATING SOIL BULK DENSITY IN CENTRAL AMAZONIA
Directory of Open Access Journals (Sweden)
Henrique Seixas Barros
2015-04-01
Full Text Available Under field conditions in the Amazon forest, soil bulk density is difficult to measure. Rigorous methodological criteria must be applied to obtain reliable inventories of C stocks and soil nutrients, making this process expensive and sometimes unfeasible. This study aimed to generate models to estimate soil bulk density based on parameters that can be easily and reliably measured in the field and that are available in many soil-related inventories. Stepwise regression models to predict bulk density were developed using data on soil C content, clay content and pH in water from 140 permanent plots in terra firme (upland forests near Manaus, Amazonas State, Brazil. The model results were interpreted according to the coefficient of determination (R2 and Akaike information criterion (AIC and were validated with a dataset consisting of 125 plots different from those used to generate the models. The model with best performance in estimating soil bulk density under the conditions of this study included clay content and pH in water as independent variables and had R2 = 0.73 and AIC = -250.29. The performance of this model for predicting soil density was compared with that of models from the literature. The results showed that the locally calibrated equation was the most accurate for estimating soil bulk density for upland forests in the Manaus region.
Contingent kernel density estimation.
Directory of Open Access Journals (Sweden)
Scott Fortmann-Roe
Full Text Available Kernel density estimation is a widely used method for estimating a distribution based on a sample of points drawn from that distribution. Generally, in practice some form of error contaminates the sample of observed points. Such error can be the result of imprecise measurements or observation bias. Often this error is negligible and may be disregarded in analysis. In cases where the error is non-negligible, estimation methods should be adjusted to reduce resulting bias. Several modifications of kernel density estimation have been developed to address specific forms of errors. One form of error that has not yet been addressed is the case where observations are nominally placed at the centers of areas from which the points are assumed to have been drawn, where these areas are of varying sizes. In this scenario, the bias arises because the size of the error can vary among points and some subset of points can be known to have smaller error than another subset or the form of the error may change among points. This paper proposes a "contingent kernel density estimation" technique to address this form of error. This new technique adjusts the standard kernel on a point-by-point basis in an adaptive response to changing structure and magnitude of error. In this paper, equations for our contingent kernel technique are derived, the technique is validated using numerical simulations, and an example using the geographic locations of social networking users is worked to demonstrate the utility of the method.
ASYMPTOTIC NORMALITY OF KERNEL ESTIMATES OF A DENSITY FUNCTION UNDER ASSOCIATION DEPENDENCE
Institute of Scientific and Technical Information of China (English)
林正炎
2003-01-01
Let {Xn,n> _ 1} be a strictly stationary sequence of random variables,which are either associated or negatively associated,f(·)be their common density.In this paper,the author shows a central limit theorem for a kernel estimate of f(·)under certain regular conditions.
Chan, Poh Yin; Tong, Chi Ming; Durrant, Marcus C
2011-09-01
An empirical method for estimation of the boiling points of organic molecules based on density functional theory (DFT) calculations with polarized continuum model (PCM) solvent corrections has been developed. The boiling points are calculated as the sum of three contributions. The first term is calculated directly from the structural formula of the molecule, and is related to its effective surface area. The second is a measure of the electronic interactions between molecules, based on the DFT-PCM solvation energy, and the third is employed only for planar aromatic molecules. The method is applicable to a very diverse range of organic molecules, with normal boiling points in the range of -50 to 500 °C, and includes ten different elements (C, H, Br, Cl, F, N, O, P, S and Si). Plots of observed versus calculated boiling points gave R²=0.980 for a training set of 317 molecules, and R²=0.979 for a test set of 74 molecules. The role of intramolecular hydrogen bonding in lowering the boiling points of certain molecules is quantitatively discussed. Crown Copyright © 2011. Published by Elsevier Inc. All rights reserved.
Airborne Crowd Density Estimation
Meynberg, O.; Kuschk, G.
2013-10-01
This paper proposes a new method for estimating human crowd densities from aerial imagery. Applications benefiting from an accurate crowd monitoring system are mainly found in the security sector. Normally crowd density estimation is done through in-situ camera systems mounted on high locations although this is not appropriate in case of very large crowds with thousands of people. Using airborne camera systems in these scenarios is a new research topic. Our method uses a preliminary filtering of the whole image space by suitable and fast interest point detection resulting in a number of image regions, possibly containing human crowds. Validation of these candidates is done by transforming the corresponding image patches into a low-dimensional and discriminative feature space and classifying the results using a support vector machine (SVM). The feature space is spanned by texture features computed by applying a Gabor filter bank with varying scale and orientation to the image patches. For evaluation, we use 5 different image datasets acquired by the 3K+ aerial camera system of the German Aerospace Center during real mass events like concerts or football games. To evaluate the robustness and generality of our method, these datasets are taken from different flight heights between 800 m and 1500 m above ground (keeping a fixed focal length) and varying daylight and shadow conditions. The results of our crowd density estimation are evaluated against a reference data set obtained by manually labeling tens of thousands individual persons in the corresponding datasets and show that our method is able to estimate human crowd densities in challenging realistic scenarios.
Oyang, Yen-Jen; Hwang, Shien-Ching; Ou, Yu-Yen; Chen, Chien-Yu; Chen, Zhi-Wei
2005-01-01
This paper presents a novel learning algorithm for efficient construction of the radial basis function (RBF) networks that can deliver the same level of accuracy as the support vector machines (SVMs) in data classification applications. The proposed learning algorithm works by constructing one RBF subnetwork to approximate the probability density function of each class of objects in the training data set. With respect to algorithm design, the main distinction of the proposed learning algorithm is the novel kernel density estimation algorithm that features an average time complexity of O(n log n), where n is the number of samples in the training data set. One important advantage of the proposed learning algorithm, in comparison with the SVM, is that the proposed learning algorithm generally takes far less time to construct a data classifier with an optimized parameter setting. This feature is of significance for many contemporary applications, in particular, for those applications in which new objects are continuously added into an already large database. Another desirable feature of the proposed learning algorithm is that the RBF networks constructed are capable of carrying out data classification with more than two classes of objects in one single run. In other words, unlike with the SVM, there is no need to resort to mechanisms such as one-against-one or one-against-all for handling datasets with more than two classes of objects. The comparison with SVM is of particular interest, because it has been shown in a number of recent studies that SVM generally are able to deliver higher classification accuracy than the other existing data classification algorithms. As the proposed learning algorithm is instance-based, the data reduction issue is also addressed in this paper. One interesting observation in this regard is that, for all three data sets used in data reduction experiments, the number of training samples remaining after a naive data reduction mechanism is
DEFF Research Database (Denmark)
Wellendorff, Jess; Lundgård, Keld Troen; Møgelhøj, Andreas
2012-01-01
A methodology for semiempirical density functional optimization, using regularization and cross-validation methods from machine learning, is developed. We demonstrate that such methods enable well-behaved exchange-correlation approximations in very flexible model spaces, thus avoiding the overfit...
Maadooliat, Mehdi
2015-10-21
This paper develops a method for simultaneous estimation of density functions for a collection of populations of protein backbone angle pairs using a data-driven, shared basis that is constructed by bivariate spline functions defined on a triangulation of the bivariate domain. The circular nature of angular data is taken into account by imposing appropriate smoothness constraints across boundaries of the triangles. Maximum penalized likelihood is used to fit the model and an alternating blockwise Newton-type algorithm is developed for computation. A simulation study shows that the collective estimation approach is statistically more efficient than estimating the densities individually. The proposed method was used to estimate neighbor-dependent distributions of protein backbone dihedral angles (i.e., Ramachandran distributions). The estimated distributions were applied to protein loop modeling, one of the most challenging open problems in protein structure prediction, by feeding them into an angular-sampling-based loop structure prediction framework. Our estimated distributions compared favorably to the Ramachandran distributions estimated by fitting a hierarchical Dirichlet process model; and in particular, our distributions showed significant improvements on the hard cases where existing methods do not work well.
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 up...... to of the order ten parameters to be adjusted in the exchange enhancement factor. The transferability of models between data is analyzed, and it is shown to be difficult to transfer a model trained exclusively on molecular atomization energies to the treatment of chemisorption systems....
Hammou Elotmany; M'Hamed Eddahbi
2015-01-01
Hammou El-otmany, M'hamed Eddahbi Facult{\\'e} des Sciences et Techniques Marrakech-Maroc Laboratoire de m{\\'e}thodes stochastiques appliqu{\\'e}e a la finance et actuariat (LaMsaFA) Abstract. In the present paper we propose a new stochastic diffusion process with drift proportional to the Weibull density function defined as X $\\epsilon$ = x, dX t = $\\gamma$ t (1 -- t $\\gamma$+1) -- t $\\gamma$ X t dt + $\\sigma$X t dB t , t \\textgreater{} 0, with parameters $\\gamma$ \\textgreater{} 0 and $\\sigma$...
Pande, Vikram
2016-01-01
Graphite is the most widely used and among the most widely-studied anode materials for lithium-ion batteries. Lithium intercalation into graphite has been extensively studied theoretically using density functional theory (DFT) calculations, complemented by experimental studies through X-ray diffraction, spectroscopy, optical imaging and other techniques. However, previous theoretical studies have not directly included van der Waals (vdW) interactions in their density functional theory calculations and vdW interactions play a crucial role in determining the stable phases. In this work, we present a first principles based model using DFT calculations, employing Bayesian Error Estimation Functional with van der Waals (BEEF-vdW) as the exchange correlation functional, and statistical thermodynamics to determine the phase transformations and subsequently, the thermodynamic intercalation potential diagram. We explore the entire configurational phase space by determining the important interactions and applying clust...
Probability Density Estimation for Non-flat Functions%非平坦函数概率密度估计
Institute of Scientific and Technical Information of China (English)
汪洪桥; 蔡艳宁; 付光远; 王仕成
2016-01-01
Aiming at the probability density estimation problem for non-flat functions, this paper constructs a single slack factor multi-scale kernel support vector machine (SVM) probability density estimation model, by improving the form of constraint condition of the traditional SVM model and introducing the multi-scale kernel method. In the model, a single slack factor instead of two types of slack factors is used to control the learning error of SVM, which reduces the computational complexity of model. At the same time, by introducing the multi-scale kernel method, the model can well fit the functions with both the fiercely changed region and the flatly changed region. Through several probability density estimation experiments with typical non-flat functions, the results show that the single slack probability density estimation model has faster learning speed than the common SVM model. And compared with the single kernel method, the multi-scale kernel SVM probability density estimation model has better estimation precision.%针对非平坦函数的概率密度估计问题，通过改进支持向量机（support vector machine，SVM）概率密度估计模型约束条件的形式，并引入多尺度核方法，构建了一种单松弛因子多尺度核支持向量机概率密度估计模型。该模型采用合并的单个松弛因子来控制支持向量机的学习误差，减小了模型的计算复杂度；同时引入了多尺度核方法，使得模型既能适应函数剧烈变化的区域，也能适应平缓变化的区域。基于几种典型非平坦函数进行概率密度估计实验，结果证明，单松弛因子概率密度估计模型比常规支持向量机概率密度估计模型具有更快的学习速度；且相比于单核方法，多尺度核支持向量机概率密度估计模型具有更优的估计精度。
Pan, Guangming; Zhou, Wang
2010-01-01
A consistent kernel estimator of the limiting spectral distribution of general sample covariance matrices was introduced in Jing, Pan, Shao and Zhou (2010). The central limit theorem of the kernel estimator is proved in this paper.
Varying kernel density estimation on ℝ+
Mnatsakanov, Robert; Sarkisian, Khachatur
2015-01-01
In this article a new nonparametric density estimator based on the sequence of asymmetric kernels is proposed. This method is natural when estimating an unknown density function of a positive random variable. The rates of Mean Squared Error, Mean Integrated Squared Error, and the L1-consistency are investigated. Simulation studies are conducted to compare a new estimator and its modified version with traditional kernel density construction. PMID:26740729
Institute of Scientific and Technical Information of China (English)
LIU Dan; WEI Guo; SUN Jin-wei; LIU Xin
2009-01-01
In the osmotic dehydration process of food, on-line estimation of concentrations of two components in ternary solution with NaCI and sucrose was performed based on multi-functional sensing technique.Moving Least Squares were adopted in approximation procedure to estimate the viscosity of such interested ternary solu-tion with the given data set.As a result, in one mode of using total experimental data as calibration data andvalidation data, the relative deviations of estimated viscosities are less than ～ 1.24%.In the other mode, by taking total experimental data except the ones for estimation as calibration data, the relative deviations are less than±3.47%.In the same way, the density of ternary solution can be also estimated with deviations less than ± 0.11% and ± 0.30% respectively in these two models.The satisfactory and accurate results show the ex-traordinary efficiency of Moving Least Squares behaved in signal approximation for multi-functional sensors.
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.
mBEEF-vdW: Robust fitting of error estimation density functionals
DEFF Research Database (Denmark)
Lundgård, Keld Troen; Wellendorff, Jess; Voss, Johannes
2016-01-01
We propose a general-purpose semilocal/nonlocal exchange-correlation functional approximation, named mBEEF-vdW. The exchange is a meta generalized gradient approximation, and the correlation is a semilocal and nonlocal mixture, with the Rutgers-Chalmers approximation for van der Waals (vdW) force...
Laboratory Density Functionals
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.
Laboratory Density Functionals
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.
The X-ray Power Spectral Density Function and Black Hole Mass Estimate for the Seyfert AGN IC 4329a
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) * 10^-6 Hz, which corresponds to a PSD break time scale 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) * 10^8 solar masses 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,...
Variable kernel density estimation in high-dimensional feature spaces
CSIR Research Space (South Africa)
Van der Walt, Christiaan M
2017-02-01
Full Text Available Estimating the joint probability density function of a dataset is a central task in many machine learning applications. In this work we address the fundamental problem of kernel bandwidth estimation for variable kernel density estimation in high...
Parallel Multiscale Autoregressive Density Estimation
Reed, Scott; Oord, Aäron van den; Kalchbrenner, Nal; Colmenarejo, Sergio Gómez; Wang, Ziyu; Belov, Dan; de Freitas, Nando
2017-01-01
PixelCNN achieves state-of-the-art results in density estimation for natural images. Although training is fast, inference is costly, requiring one network evaluation per pixel; O(N) for N pixels. This can be sped up by caching activations, but still involves generating each pixel sequentially. In this work, we propose a parallelized PixelCNN that allows more efficient inference by modeling certain pixel groups as conditionally independent. Our new PixelCNN model achieves competitive density e...
Engel, J
2006-01-01
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.
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...
Bayesian mixture models for spectral density estimation
Cadonna, Annalisa
2017-01-01
We introduce a novel Bayesian modeling approach to spectral density estimation for multiple time series. Considering first the case of non-stationary timeseries, the log-periodogram of each series is modeled as a mixture of Gaussiandistributions with frequency-dependent weights and mean functions. The implied model for the log-spectral density is a mixture of linear mean functionswith frequency-dependent weights. The mixture weights are built throughsuccessive differences of a logit-normal di...
Partition density functional theory
Nafziger, Jonathan
Partition density functional theory (PDFT) is a method for dividing a molecular electronic structure calculation into fragment calculations. The molecular density and energy corresponding to Kohn Sham density-functional theory (KS-DFT) may be exactly recovered from these fragments. Each fragment acts as an isolated system except for the influence of a global one-body 'partition' potential which deforms the fragment densities. In this work, the developments of PDFT are put into the context of other fragment-based density functional methods. We developed three numerical implementations of PDFT: One within the NWChem computational chemistry package using basis sets, and the other two developed from scratch using real-space grids. It is shown that all three of these programs can exactly reproduce a KS-DFT calculation via fragment calculations. The first of our in-house codes handles non-interacting electrons in arbitrary one-dimensional potentials with any number of fragments. This code is used to explore how the exact partition potential changes for different partitionings of the same system and also to study features which determine which systems yield non-integer PDFT occupations and which systems are locked into integer PDFT occupations. The second in-house code, CADMium, performs real-space calculations of diatomic molecules. Features of the exact partition potential are studied for a variety of cases and an analytical formula determining singularities in the partition potential is derived. We introduce an approximation for the non-additive kinetic energy and show how this quantity can be computed exactly. Finally a PDFT functional is developed to address the issues of static correlation and delocalization errors in approximations within DFT. The functional is applied to the dissociation of H2 + and H2.
Quantal density functional theory
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...
Semiclassics in Density Functional Theory
Lee, Donghyung; Cangi, Attila; Elliott, Peter; Burke, Kieron
2009-03-01
Recently, we published an article [1] about the semiclassical origin of density functional theory. We showed that the density and the kinetic energy density of one dimensional finite systems with hard walls can be expressed in terms of the external potential using the semiclassical Green's function method. Here, we show a uniformization scheme for the semiclassical density and the kinetic energy density for turning-point problems.[1] P. Elliott, D. Lee, A. Cangi, and K. Burke, Phys. Rev. Lett. 100, 256406 (2008).
Density Estimation Trees in High Energy Physics
Anderlini, Lucio
2015-01-01
Density Estimation Trees can play an important role in exploratory data analysis for multidimensional, multi-modal data models of large samples. I briefly discuss the algorithm, a self-optimization technique based on kernel density estimation, and some applications in High Energy Physics.
On ARMA Probability Density Estimation.
1981-12-01
definitions of the constants B0k=Ol ,...,q) and ak(kl,...,p) will be given which, for a given function f(.), uniquely define an approximator f pCq .) for each...satisfied. When using f pCq () for approximation purposes it is thus important to always verify whether or not this condition is met. In concluding
Directory of Open Access Journals (Sweden)
Abdelkader Mokkadem
2011-01-01
Full Text Available Let and denote the location and the size of the mode of a probability density. We study the joint convergence rates of semirecursive kernel estimators of and . We show how the estimation of the size of the mode allows measuring the relevance of the estimation of its location. We also enlighten that, beyond their computational advantage on nonrecursive estimators, the semirecursive estimators are preferable to use for the construction of confidence regions.
Scaled density functional theory correlation functionals.
Ghouri, Mohammed M; Singh, Saurabh; Ramachandran, B
2007-10-18
We show that a simple one-parameter scaling of the dynamical correlation energy estimated by the density functional theory (DFT) correlation functionals helps increase the overall accuracy for several local and nonlocal functionals. The approach taken here has been described as the "scaled dynamical correlation" (SDC) method [Ramachandran, J. Phys. Chem. A 2006, 110, 396], and its justification is the same as that of the scaled external correlation (SEC) method of Brown and Truhlar. We examine five local and five nonlocal (hybrid) DFT functionals, the latter group including three functionals developed specifically for kinetics by the Truhlar group. The optimum scale factors are obtained by use of a set of 98 data values consisting of molecules, ions, and transition states. The optimum scale factors, found with a linear regression relationship, are found to differ from unity with a high degree of correlation in nearly every case, indicating that the deviation of calculated results from the experimental values are systematic and proportional to the dynamic correlation energy. As a consequence, the SDC scaling of dynamical correlation decreases the mean errors (signed and unsigned) by significant amounts in an overwhelming majority of cases. These results indicate that there are gains to be realized from further parametrization of several popular exchange-correlation functionals.
Girón, L.; Aperador, W.; Tirado, L.; Franco, F.; Caicedo, J. C.
2017-08-01
The anodized AZ31B magnesium alloys were synthesized via electrodeposition processes. The aim of this work was to determine the electrochemical behavior of magnesium alloys by using anodized alloys as a protective coating. The anodized alloys were characterized by x-ray diffraction, exhibiting the crystallography orientation for Mg and MgO phases. The x-ray photoelectron spectroscopy was used to determine the chemical composition of anodized magnesium alloys. By using electrochemical impedance spectroscopy and Tafel curves, it was possible to estimate the electrochemical behavior of anodized AZ31B magnesium alloys in Hank's balanced salt solution (HBSS). Scanning electron microscopy was performed to analyze chemical changes and morphological surface changes on anodized Mg alloys due to the reaction in HBSS/anodized magnesium surface interface. Electrochemical behavior in HBSS indicates that the coatings may be a promising material for biomedical industry.
Parametric Return Density Estimation for Reinforcement Learning
Morimura, Tetsuro; Kashima, Hisashi; Hachiya, Hirotaka; Tanaka, Toshiyuki
2012-01-01
Most conventional Reinforcement Learning (RL) algorithms aim to optimize decision- making rules in terms of the expected re- turns. However, especially for risk man- agement purposes, other risk-sensitive crite- ria such as the value-at-risk or the expected shortfall are sometimes preferred in real ap- plications. Here, we describe a parametric method for estimating density of the returns, which allows us to handle various criteria in a unified manner. We first extend the Bellman equation for the conditional expected return to cover a conditional probability density of the returns. Then we derive an extension of the TD-learning algorithm for estimating the return densities in an unknown environment. As test instances, several parametric density estimation algorithms are presented for the Gaussian, Laplace, and skewed Laplace dis- tributions. We show that these algorithms lead to risk-sensitive as well as robust RL paradigms through numerical experiments.
DEFF Research Database (Denmark)
Andersen, C K; Andersen, K; Kragh-Sørensen, P
2000-01-01
on these criteria, a two-part model was chosen. In this model, the probability of incurring any costs was estimated using a logistic regression, while the level of the costs was estimated in the second part of the model. The choice of model had a substantial impact on the predicted health care costs, e......Statistical analysis of cost data is often difficult because of highly skewed data resulting from a few patients who incur high costs relative to the majority of patients. When the objective is to predict the cost for an individual patient, the literature suggests that one should choose...... a regression model based on the quality of its predictions. In exploring the econometric issues, the objective of this study was to estimate a cost function in order to estimate the annual health care cost of dementia. Using different models, health care costs were regressed on the degree of dementia, sex, age...
Density functionals from deep learning
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 made as to the form of this structure, this approach is much more powerful and flexible than traditional approaches. As an example application, the model is shown to perform well on approximating the kinetic-energy density functional for noninteracting electrons. The model is analyzed in detail, and its advantages over conventional machine learning are discussed.
Estimating stellar mean density through seismic inversions
Reese, D R; Goupil, M J; Thompson, M J; Deheuvels, S
2012-01-01
Determining the mass of stars is crucial both to improving stellar evolution theory and to characterising exoplanetary systems. Asteroseismology offers a promising way to estimate stellar mean density. When combined with accurate radii determinations, such as is expected from GAIA, this yields accurate stellar masses. The main difficulty is finding the best way to extract the mean density from a set of observed frequencies. We seek to establish a new method for estimating stellar mean density, which combines the simplicity of a scaling law while providing the accuracy of an inversion technique. We provide a framework in which to construct and evaluate kernel-based linear inversions which yield directly the mean density of a star. We then describe three different inversion techniques (SOLA and two scaling laws) and apply them to the sun, several test cases and three stars. The SOLA approach and the scaling law based on the surface correcting technique described by Kjeldsen et al. (2008) yield comparable result...
Vargas-Melendez, Leandro; Boada, Beatriz L; Boada, Maria Jesus L; Gauchia, Antonio; Diaz, Vicente
2017-04-29
Vehicles with a high center of gravity (COG), such as light trucks and heavy vehicles, are prone to rollover. This kind of accident causes nearly 33 % of all deaths from passenger vehicle crashes. Nowadays, these vehicles are incorporating roll stability control (RSC) systems to improve their safety. Most of the RSC systems require the vehicle roll angle as a known input variable to predict the lateral load transfer. The vehicle roll angle can be directly measured by a dual antenna global positioning system (GPS), but it is expensive. For this reason, it is important to estimate the vehicle roll angle from sensors installed onboard in current vehicles. On the other hand, the knowledge of the vehicle's parameters values is essential to obtain an accurate vehicle response. Some of vehicle parameters cannot be easily obtained and they can vary over time. In this paper, an algorithm for the simultaneous on-line estimation of vehicle's roll angle and parameters is proposed. This algorithm uses a probability density function (PDF)-based truncation method in combination with a dual Kalman filter (DKF), to guarantee that both vehicle's states and parameters are within bounds that have a physical meaning, using the information obtained from sensors mounted on vehicles. Experimental results show the effectiveness of the proposed algorithm.
Maximum likelihood estimation for semiparametric density ratio model.
Diao, Guoqing; Ning, Jing; Qin, Jing
2012-06-27
In the statistical literature, the conditional density model specification is commonly used to study regression effects. One attractive model is the semiparametric density ratio model, under which the conditional density function is the product of an unknown baseline density function and a known parametric function containing the covariate information. This model has a natural connection with generalized linear models and is closely related to biased sampling problems. Despite the attractive features and importance of this model, most existing methods are too restrictive since they are based on multi-sample data or conditional likelihood functions. The conditional likelihood approach can eliminate the unknown baseline density but cannot estimate it. We propose efficient estimation procedures based on the nonparametric likelihood. The nonparametric likelihood approach allows for general forms of covariates and estimates the regression parameters and the baseline density simultaneously. Therefore, the nonparametric likelihood approach is more versatile than the conditional likelihood approach especially when estimation of the conditional mean or other quantities of the outcome is of interest. We show that the nonparametric maximum likelihood estimators are consistent, asymptotically normal, and asymptotically efficient. Simulation studies demonstrate that the proposed methods perform well in practical settings. A real example is used for illustration.
Quantiles, parametric-select density estimation, and bi-information parameter estimators
Parzen, E.
1982-01-01
A quantile-based approach to statistical analysis and probability modeling of data is presented which formulates statistical inference problems as functional inference problems in which the parameters to be estimated are density functions. Density estimators can be non-parametric (computed independently of model identified) or parametric-select (approximated by finite parametric models that can provide standard models whose fit can be tested). Exponential models and autoregressive models are approximating densities which can be justified as maximum entropy for respectively the entropy of a probability density and the entropy of a quantile density. Applications of these ideas are outlined to the problems of modeling: (1) univariate data; (2) bivariate data and tests for independence; and (3) two samples and likelihood ratios. It is proposed that bi-information estimation of a density function can be developed by analogy to the problem of identification of regression models.
Livingston, Richard A.; Jin, Shuang
2005-05-01
Bridges and other civil structures can exhibit nonlinear and/or chaotic behavior under ambient traffic or wind loadings. The probability density function (pdf) of the observed structural responses thus plays an important role for long-term structural health monitoring, LRFR and fatigue life analysis. However, the actual pdf of such structural response data often has a very complicated shape due to its fractal nature. Various conventional methods to approximate it can often lead to biased estimates. This paper presents recent research progress at the Turner-Fairbank Highway Research Center of the FHWA in applying a novel probabilistic scaling scheme for enhanced maximum entropy evaluation to find the most unbiased pdf. The maximum entropy method is applied with a fractal interpolation formulation based on contraction mappings through an iterated function system (IFS). Based on a fractal dimension determined from the entire response data set by an algorithm involving the information dimension, a characteristic uncertainty parameter, called the probabilistic scaling factor, can be introduced. This allows significantly enhanced maximum entropy evaluation through the added inferences about the fine scale fluctuations in the response data. Case studies using the dynamic response data sets collected from a real world bridge (Commodore Barry Bridge, PA) and from the simulation of a classical nonlinear chaotic system (the Lorenz system) are presented in this paper. The results illustrate the advantages of the probabilistic scaling method over conventional approaches for finding the unbiased pdf especially in the critical tail region that contains the larger structural responses.
Locality of correlation in density functional theory.
Burke, Kieron; Cancio, Antonio; Gould, Tim; Pittalis, Stefano
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 EC → -AC ZlnZ + BCZ as Z → ∞, where Z is the atomic number, AC is known, and we estimate BC to be about 37 mhartree. The local density approximation yields AC exactly, but a very incorrect value for BC, 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 BC a functional of the TF density for the system. The implications for the construction of approximate density functionals are discussed.
Particle Size Estimation Based on Edge Density
Institute of Scientific and Technical Information of China (English)
WANG Wei-xing
2005-01-01
Given image sequences of closely packed particles, the underlying aim is to estimate diameters without explicit segmentation. In a way, this is similar to the task of counting objects without directly counting them. Such calculations may, for example, be useful fast estimation of particle size in different application areas. The topic is that of estimating average size (=average diameter) of packed particles, from formulas involving edge density, and the edges from moment-based thresholding are used. An average shape factor is involved in the calculations, obtained for some frames from crude partial segmentation. Measurement results from about 80 frames have been analyzed.
Density Functionals of Chemical Bonding
Directory of Open Access Journals (Sweden)
Mihai V. Putz
2008-06-01
Full Text Available The behavior of electrons in general many-electronic systems throughout the density functionals of energy is reviewed. The basic physico-chemical concepts of density functional theory are employed to highlight the energy role in chemical structure while its extended influence in electronic localization function helps in chemical bonding understanding. In this context the energy functionals accompanied by electronic localization functions may provide a comprehensive description of the global-local levels electronic structures in general and of chemical bonds in special. Becke-Edgecombe and authorÃ¢Â€Â™s Markovian electronic localization functions are discussed at atomic, molecular and solid state levels. Then, the analytical survey of the main workable kinetic, exchange, and correlation density functionals within local and gradient density approximations is undertaken. The hierarchy of various energy functionals is formulated by employing both the parabolic and statistical correlation degree of them with the electronegativity and chemical hardness indices by means of quantitative structure-property relationship (QSPR analysis for basic atomic and molecular systems.
DEFF Research Database (Denmark)
Andersen, C K; Andersen, K; Kragh-Sørensen, P
2000-01-01
Statistical analysis of cost data is often difficult because of highly skewed data resulting from a few patients who incur high costs relative to the majority of patients. When the objective is to predict the cost for an individual patient, the literature suggests that one should choose...... a regression model based on the quality of its predictions. In exploring the econometric issues, the objective of this study was to estimate a cost function in order to estimate the annual health care cost of dementia. Using different models, health care costs were regressed on the degree of dementia, sex, age......, marital status and presence of any co-morbidity other than dementia. Models with a log-transformed dependent variable, where predicted health care costs were re-transformed to the unlogged original scale by multiplying the exponential of the expected response on the log-scale with the average...
Gilson, Ronan; Durrant, Marcus C
2009-12-14
The deprotonation energies of the water ligands in a set of 40 d-block metal complexes have been calculated using density functional theory with polarized continuum model solvent corrections. The complexes include 13 aqua ions [M(OH(2))(n)](2+/3+) and a variety of aqua complexes with organic co-ligands, whose experimental pK(a) values have been reported in the literature. For comparison, the deprotonation energies of a set of 60 organic and inorganic molecules with experimental pK(a) values ranging from -25 (HSbF(6)) to +52 (C(2)H(6)) have also been calculated. Three different classes of acids are identified as giving different slopes in plots of pK(a) versus deprotonation energies; namely non-hydroxy acids, hydroxy acids, and the metal complexes. The correlation coefficients for the straight lines obtained for these three classes are 0.96, 0.97 and 0.92 respectively. Better correlations are found for sub-sets of the complexes, such as the 31 first row complexes (correlation coefficient 0.95).For several of the complexes, comparison of the calculated and observed pK(a) values, together with changes in the geometry upon optimization, offer new insights into the possible solution structures. It is concluded that DFT calculations incorporating solvent corrections can be used to give reasonable estimates of pK(a) values for the aqua ligands in a range of complex types.
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...
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...... and bias in estimates. Good results are obtained by the use of anisotropic filtering. Two methods handles the most common cases; filtering illumination reflected from object surfaces. One methods extends filtering to the temporal domain and one performs filtering on illumination from participating media...
Quantal Density Functional Theory II
Sahni, Viraht
2009-01-01
Discusses approximation methods and applications of Quantal Density Functional Theory (QDFT), a local effective-potential-energy theory of electronic structure. This book describes approximations methods based on the incorporation of different electron correlations, as well as a many-body perturbation theory within the context of QDFT
Bird population density estimated from acoustic signals
Dawson, D.K.; Efford, M.G.
2009-01-01
Many animal species are detected primarily by sound. Although songs, calls and other sounds are often used for population assessment, as in bird point counts and hydrophone surveys of cetaceans, there are few rigorous methods for estimating population density from acoustic data. 2. The problem has several parts - distinguishing individuals, adjusting for individuals that are missed, and adjusting for the area sampled. Spatially explicit capture-recapture (SECR) is a statistical methodology that addresses jointly the second and third parts of the problem. We have extended SECR to use uncalibrated information from acoustic signals on the distance to each source. 3. We applied this extension of SECR to data from an acoustic survey of ovenbird Seiurus aurocapilla density in an eastern US deciduous forest with multiple four-microphone arrays. We modelled average power from spectrograms of ovenbird songs measured within a window of 0??7 s duration and frequencies between 4200 and 5200 Hz. 4. The resulting estimates of the density of singing males (0??19 ha -1 SE 0??03 ha-1) were consistent with estimates of the adult male population density from mist-netting (0??36 ha-1 SE 0??12 ha-1). The fitted model predicts sound attenuation of 0??11 dB m-1 (SE 0??01 dB m-1) in excess of losses from spherical spreading. 5.Synthesis and applications. Our method for estimating animal population density from acoustic signals fills a gap in the census methods available for visually cryptic but vocal taxa, including many species of bird and cetacean. The necessary equipment is simple and readily available; as few as two microphones may provide adequate estimates, given spatial replication. The method requires that individuals detected at the same place are acoustically distinguishable and all individuals vocalize during the recording interval, or that the per capita rate of vocalization is known. We believe these requirements can be met, with suitable field methods, for a significant
Regularized Regression and Density Estimation based on Optimal Transport
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).
Density Estimation in Several Populations With Uncertain Population Membership
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.
Multivariate density estimation theory, practice, and visualization
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
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
Regularized Multitask Learning for Multidimensional Log-Density Gradient Estimation.
Yamane, Ikko; Sasaki, Hiroaki; Sugiyama, Masashi
2016-07-01
Log-density gradient estimation is a fundamental statistical problem and possesses various practical applications such as clustering and measuring nongaussianity. A naive two-step approach of first estimating the density and then taking its log gradient is unreliable because an accurate density estimate does not necessarily lead to an accurate log-density gradient estimate. To cope with this problem, a method to directly estimate the log-density gradient without density estimation has been explored and demonstrated to work much better than the two-step method. The objective of this letter is to improve the performance of this direct method in multidimensional cases. Our idea is to regard the problem of log-density gradient estimation in each dimension as a task and apply regularized multitask learning to the direct log-density gradient estimator. We experimentally demonstrate the usefulness of the proposed multitask method in log-density gradient estimation and mode-seeking clustering.
Density Estimations in Laboratory Debris Flow Experiments
Queiroz de Oliveira, Gustavo; Kulisch, Helmut; Malcherek, Andreas; Fischer, Jan-Thomas; Pudasaini, Shiva P.
2016-04-01
Bulk density and its variation is an important physical quantity to estimate the solid-liquid fractions in two-phase debris flows. Here we present mass and flow depth measurements for experiments performed in a large-scale laboratory set up. Once the mixture is released and it moves down the inclined channel, measurements allow us to determine the bulk density evolution throughout the debris flow. Flow depths are determined by ultrasonic pulse reflection, and the mass is measured with a total normal force sensor. The data were obtained at 50 Hz. The initial two phase material was composed of 350 kg debris with water content of 40%. A very fine pebble with mean particle diameter of 3 mm, particle density of 2760 kg/m³ and bulk density of 1400 kg/m³ in dry condition was chosen as the solid material. Measurements reveal that the debris bulk density remains high from the head to the middle of the debris body whereas it drops substantially at the tail. This indicates lower water content at the tail, compared to the head and the middle portion of the debris body. This means that the solid and fluid fractions are varying strongly in a non-linear manner along the flow path, and from the head to the tail of the debris mass. Importantly, this spatial-temporal density variation plays a crucial role in determining the impact forces associated with the dynamics of the flow. Our setup allows for investigating different two phase material compositions, including large fluid fractions, with high resolutions. The considered experimental set up may enable us to transfer the observed phenomena to natural large-scale events. Furthermore, the measurement data allows evaluating results of numerical two-phase mass flow simulations. These experiments are parts of the project avaflow.org that intends to develop a GIS-based open source computational tool to describe wide spectrum of rapid geophysical mass flows, including avalanches and real two-phase debris flows down complex natural
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.
A morpho-density approach to estimating neural connectivity.
Directory of Open Access Journals (Sweden)
Michael P McAssey
Full Text Available Neuronal signal integration and information processing in cortical neuronal networks critically depend on the organization of synaptic connectivity. Because of the challenges involved in measuring a large number of neurons, synaptic connectivity is difficult to determine experimentally. Current computational methods for estimating connectivity typically rely on the juxtaposition of experimentally available neurons and applying mathematical techniques to compute estimates of neural connectivity. However, since the number of available neurons is very limited, these connectivity estimates may be subject to large uncertainties. We use a morpho-density field approach applied to a vast ensemble of model-generated neurons. A morpho-density field (MDF describes the distribution of neural mass in the space around the neural soma. The estimated axonal and dendritic MDFs are derived from 100,000 model neurons that are generated by a stochastic phenomenological model of neurite outgrowth. These MDFs are then used to estimate the connectivity between pairs of neurons as a function of their inter-soma displacement. Compared with other density-field methods, our approach to estimating synaptic connectivity uses fewer restricting assumptions and produces connectivity estimates with a lower standard deviation. An important requirement is that the model-generated neurons reflect accurately the morphology and variation in morphology of the experimental neurons used for optimizing the model parameters. As such, the method remains subject to the uncertainties caused by the limited number of neurons in the experimental data set and by the quality of the model and the assumptions used in creating the MDFs and in calculating estimating connectivity. In summary, MDFs are a powerful tool for visualizing the spatial distribution of axonal and dendritic densities, for estimating the number of potential synapses between neurons with low standard deviation, and for obtaining
Kernel density estimation using graphical processing unit
Sunarko, Su'ud, Zaki
2015-09-01
Kernel density estimation for particles distributed over a 2-dimensional space is calculated using a single graphical processing unit (GTX 660Ti GPU) and CUDA-C language. Parallel calculations are done for particles having bivariate normal distribution and by assigning calculations for equally-spaced node points to each scalar processor in the GPU. The number of particles, blocks and threads are varied to identify favorable configuration. Comparisons are obtained by performing the same calculation using 1, 2 and 4 processors on a 3.0 GHz CPU using MPICH 2.0 routines. Speedups attained with the GPU are in the range of 88 to 349 times compared the multiprocessor CPU. Blocks of 128 threads are found to be the optimum configuration for this case.
SVM for density estimation and application to medical image segmentation
Institute of Scientific and Technical Information of China (English)
ZHANG Zhao; ZHANG Su; ZHANG Chen-xi; CHEN Ya-zhu
2006-01-01
A method of medical image segmentation based on support vector machine (SVM) for density estimation is presented. We used this estimator to construct a prior model of the image intensity and curvature profile of the structure from training images. When segmenting a novel image similar to the training images, the technique of narrow level set method is used. The higher dimensional surface evolution metric is defined by the prior model instead of by energy minimization function. This method offers several advantages. First, SVM for density estimation is consistent and its solution is sparse. Second, compared to the traditional level set methods, this method incorporates shape information on the object to be segmented into the segmentation process.Segmentation results are demonstrated on synthetic images, MR images and ultrasonic images.
Estimating neuronal connectivity from axonal and dendritic density fields
van Pelt, Jaap; van Ooyen, Arjen
2013-01-01
Neurons innervate space by extending axonal and dendritic arborizations. When axons and dendrites come in close proximity of each other, synapses between neurons can be formed. Neurons vary greatly in their morphologies and synaptic connections with other neurons. The size and shape of the arborizations determine the way neurons innervate space. A neuron may therefore be characterized by the spatial distribution of its axonal and dendritic “mass.” A population mean “mass” density field of a particular neuron type can be obtained by averaging over the individual variations in neuron geometries. Connectivity in terms of candidate synaptic contacts between neurons can be determined directly on the basis of their arborizations but also indirectly on the basis of their density fields. To decide when a candidate synapse can be formed, we previously developed a criterion defining that axonal and dendritic line pieces should cross in 3D and have an orthogonal distance less than a threshold value. In this paper, we developed new methodology for applying this criterion to density fields. We show that estimates of the number of contacts between neuron pairs calculated from their density fields are fully consistent with the number of contacts calculated from the actual arborizations. However, the estimation of the connection probability and the expected number of contacts per connection cannot be calculated directly from density fields, because density fields do not carry anymore the correlative structure in the spatial distribution of synaptic contacts. Alternatively, these two connectivity measures can be estimated from the expected number of contacts by using empirical mapping functions. The neurons used for the validation studies were generated by our neuron simulator NETMORPH. An example is given of the estimation of average connectivity and Euclidean pre- and postsynaptic distance distributions in a network of neurons represented by their population mean density
Fujii, Toshiyuki; Moynier, Frédéric; Blichert-Toft, Janne; Albarède, Francis
2014-09-01
This paper reports the values of reduced partition function ratios (as 1000 ln β) for Fe, Ni, Cu, and Zn bound to a number of inorganic and organic ligands. We used Density Functional Techniques to update the existing data and calculate ln β for new ligands. This work allows for the mass-dependent isotope fractionation to be predicted for various inorganic (hydrated cation, hydroxide, chloride, sulfate, sulfide, phosphate) and organic (citrate, amino acid) complexes of Fe, Ni, Cu, and Zn. Isotope fractionation among coexisting complexes of these metals was evaluated from the ln β values in a variety of geochemical and biological environments. The results provide a framework for interpretation of isotope fractionation observed in seawater and chemical sediments, in the roots and aerial parts of plants, and among the organs and body fluids of mammals.
Density and hazard rate estimation for censored and a-mixing data using gamma kernels
2006-01-01
In this paper we consider the nonparametric estimation for a density and hazard rate function for right censored -mixing survival time data using kernel smoothing techniques. Since survival times are positive with potentially a high concentration at zero, one has to take into account the bias problems when the functions are estimated in the boundary region. In this paper, gamma kernel estimators of the density and the hazard rate function are proposed. The estimators use adaptive weights depe...
Estimating Functions and Semiparametric Models
DEFF Research Database (Denmark)
Labouriau, Rodrigo
1996-01-01
The thesis is divided in two parts. The first part treats some topics of the estimation theory for semiparametric models in general. There the classic optimality theory is reviewed and exposed in a suitable way for the further developments given after. Further the theory of estimating functions...... contained in this part of the thesis constitutes an original contribution. There can be found the detailed characterization of the class of regular estimating functions, a calculation of efficient regular asymptotic linear estimating sequences (\\ie the classical optimality theory) and a discussion...... of the attainability of the bounds for the concentration of regular asymptotic linear estimating sequences by estimators derived from estimating functions. The main class of models considered in the second part of the thesis (chapter 5) are constructed by assuming that the expectation of a number of given square...
Mammographic density estimation with automated volumetric breast density measurement.
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.
Mammography density estimation with automated volumetic breast density measurement
Energy Technology Data Exchange (ETDEWEB)
Ko, Su Yeon; Kim, Eun Kyung; Kim, Min Jung; Moon, Hee Jung [Dept. of Radiology, Severance Hospital, Research Institute of Radiological Science, Yonsei University College of Medicine, Seoul (Korea, Republic of)
2014-06-15
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.
Nonparametric estimation of population density for line transect sampling using FOURIER series
Crain, B.R.; Burnham, K.P.; Anderson, D.R.; Lake, J.L.
1979-01-01
A nonparametric, robust density estimation method is explored for the analysis of right-angle distances from a transect line to the objects sighted. The method is based on the FOURIER series expansion of a probability density function over an interval. With only mild assumptions, a general population density estimator of wide applicability is obtained.
Open-cluster density profiles derived using a kernel estimator
Seleznev, Anton F
2016-01-01
Surface and spatial radial density profiles in open clusters are derived using a kernel estimator method. Formulae are obtained for the contribution of every star into the spatial density profile. The evaluation of spatial density profiles is tested against open-cluster models from N-body experiments with N = 500. Surface density profiles are derived for seven open clusters (NGC 1502, 1960, 2287, 2516, 2682, 6819 and 6939) using Two-Micron All-Sky Survey data and for different limiting magnitudes. The selection of an optimal kernel half-width is discussed. It is shown that open-cluster radius estimates hardly depend on the kernel half-width. Hints of stellar mass segregation and structural features indicating cluster non-stationarity in the regular force field are found. A comparison with other investigations shows that the data on open-cluster sizes are often underestimated. The existence of an extended corona around the open cluster NGC 6939 was confirmed. A combined function composed of the King density pr...
Multiconfiguration Pair-Density Functional Theory.
Li Manni, Giovanni; Carlson, Rebecca K; Luo, Sijie; Ma, Dongxia; Olsen, Jeppe; Truhlar, Donald G; Gagliardi, Laura
2014-09-09
We present a new theoretical framework, called Multiconfiguration Pair-Density Functional Theory (MC-PDFT), which combines multiconfigurational wave functions with a generalization of density functional theory (DFT). A multiconfigurational self-consistent-field (MCSCF) wave function with correct spin and space symmetry is used to compute the total electronic density, its gradient, the on-top pair density, and the kinetic and Coulomb contributions to the total electronic energy. We then use a functional of the total density, its gradient, and the on-top pair density to calculate the remaining part of the energy, which we call the on-top-density-functional energy in contrast to the exchange-correlation energy of Kohn-Sham DFT. Because the on-top pair density is an element of the two-particle density matrix, this goes beyond the Hohenberg-Kohn theorem that refers only to the one-particle density. To illustrate the theory, we obtain first approximations to the required new type of density functionals by translating conventional density functionals of the spin densities using a simple prescription, and we perform post-SCF density functional calculations using the total density, density gradient, and on-top pair density from the MCSCF calculations. Double counting of dynamic correlation or exchange does not occur because the MCSCF energy is not used. The theory is illustrated by applications to the bond energies and potential energy curves of H2, N2, F2, CaO, Cr2, and NiCl and the electronic excitation energies of Be, C, N, N(+), O, O(+), Sc(+), Mn, Co, Mo, Ru, N2, HCHO, C4H6, c-C5H6, and pyrazine. The method presented has a computational cost and scaling similar to MCSCF, but a quantitative accuracy, even with the present first approximations to the new types of density functionals, that is comparable to much more expensive multireference perturbation theory methods.
Sun, Haitao
2016-05-16
We propose a new methodology for the first-principles description of the electronic properties relevant for charge transport in organic molecular crystals. This methodology, which is based on the combination of a non-empirical, optimally tuned range-separated hybrid functional with the polarizable continuum model, is applied to a series of eight representative molecular semiconductor crystals. We show that it provides ionization energies, electron affinities, and transport gaps in very good agreement with experimental values as well as with the results of many-body perturbation theory within the GW approximation at a fraction of the computational costs. Hence, this approach represents an easily applicable and computationally efficient tool to estimate the gas-to-crystal-phase shifts of the frontier-orbital quasiparticle energies in organic electronic materials.
Concrete density estimation by rebound hammer method
Ismail, Mohamad Pauzi bin; Jefri, Muhamad Hafizie Bin; Abdullah, Mahadzir Bin; Masenwat, Noor Azreen bin; Sani, Suhairy bin; Mohd, Shukri; Isa, Nasharuddin bin; Mahmud, Mohamad Haniza bin
2016-01-01
Concrete is the most common and cheap material for radiation shielding. Compressive strength is the main parameter checked for determining concrete quality. However, for shielding purposes density is the parameter that needs to be considered. X- and -gamma radiations are effectively absorbed by a material with high atomic number and high density such as concrete. The high strength normally implies to higher density in concrete but this is not always true. This paper explains and discusses the correlation between rebound hammer testing and density for concrete containing hematite aggregates. A comparison is also made with normal concrete i.e. concrete containing crushed granite.
Concrete density estimation by rebound hammer method
Energy Technology Data Exchange (ETDEWEB)
Ismail, Mohamad Pauzi bin, E-mail: pauzi@nm.gov.my; Masenwat, Noor Azreen bin; Sani, Suhairy bin; Mohd, Shukri [NDT Group, Nuclear Malaysia, Bangi, Kajang, Selangor (Malaysia); Jefri, Muhamad Hafizie Bin; Abdullah, Mahadzir Bin [Material Technology Program, Faculty of Applied Sciences, UiTM, Shah Alam, Selangor (Malaysia); Isa, Nasharuddin bin; Mahmud, Mohamad Haniza bin [Pusat Penyelidikan Mineral, Jabatan Mineral dan Geosains, Ipoh, Perak (Malaysia)
2016-01-22
Concrete is the most common and cheap material for radiation shielding. Compressive strength is the main parameter checked for determining concrete quality. However, for shielding purposes density is the parameter that needs to be considered. X- and -gamma radiations are effectively absorbed by a material with high atomic number and high density such as concrete. The high strength normally implies to higher density in concrete but this is not always true. This paper explains and discusses the correlation between rebound hammer testing and density for concrete containing hematite aggregates. A comparison is also made with normal concrete i.e. concrete containing crushed granite.
Gedanken Densities and Exact Constraints in Density Functional Theory
Perdew, John P; Sun, Jianwei; Burke, Kieron
2014-01-01
Approximations to the exact density functional for the exchange-correlation energy of a many-electron ground state can be constructed by satisfying constraints that are universal, i.e., valid for all electron densities. Gedanken densities are designed for the purpose of this construction, but need not be realistic. The uniform electron gas is an old gedanken density. Here, we propose a spherical two-electron gedanken density in which the dimensionless density gradient can be an arbitrary positive constant wherever the density is non-zero. The Lieb-Oxford lower bound on the exchange energy can be satisfied within a generalized gradient approximation (GGA) by bounding its enhancement factor or simplest GGA exchange-energy density. This enhancement-factor bound is well known to be sufficient, but our gedanken density shows that it is also necessary. The conventional exact exchange-energy density satisfies no such local bound, but energy densities are not unique, and the simplest GGA exchange-energy density is no...
Zein, Samir; Neese, Frank
2008-08-28
The paper presents a method comparison for the prediction of zero-field splitting (ZFS) parameters in a series of Mn (II) coordination complexes. The test set consists of Mn (II) complexes that are experimentally well-characterized by X-ray diffraction and high-field electron paramagnetic resonance. Their ZFS parameters have been calculated using density functional theory (DFT) as well as complete active space self-consistent field (CASSCF) methods. It is shown that the recently introduced coupled-perturbed spin-orbit coupling (CP-SOC) approach [ Neese, F. J. Chem. Phys. 2007, 127, 164112 ] together with hybrid-DFT functionals leads to a slope of the correlation line (plot of experimental vs calculated D values) that is essentially unity provided that the direct spin-spin interaction is properly included in the treatment. This is different from our previous DFT study on the same series of complexes where a severe overestimation of the D parameter has been found [ Zein, S. ; Duboc, C. ; Lubitz, W. ; Neese, F. Inorg. Chem. 2008, 47, 134 ]. CASSCF methods have been used to evaluate the ZFS in an "ab initio ligand-field" type treatment. The study demonstrates that a substantial part of the relevant physics is lost in such a treatment since only excitations within the manganese d-manifold are accounted for. Thus, a severe underestimation of the D parameter has been found. Because the CASSCF calculations in combination with quasidegenerate perturbation theory treats the SOC to all orders, we have nevertheless verified that second-order perturbation theory is an adequate approximation in the case of the high-spin d (5) configuration.
Oesch, P A; Illingworth, G D; Labbe, I; Smit, R; Franx, M; van Dokkum, P G; Momcheva, I; Ashby, M L N; Fazio, G G; Huang, J; Willner, S P; Gonzalez, V; Magee, D; Brammer, G B; Skelton, R E
2013-01-01
We present the discovery of four surprisingly bright (H_160 ~ 26 - 27 mag AB) galaxy candidates at z~9-10 in the complete HST CANDELS WFC3/IR GOODS-N imaging data, doubling the number of z~10 galaxy candidates that are known, just 500 Myr after the Big Bang. These sources were identified in a search over the full CANDELS-Deep dataset, building on our previous analysis of the HUDF09/XDF fields and GOODS-S. Three of these four galaxies are significantly detected at 4.5-6.2sigma in the very deep Spitzer/IRAC 4.5 micron data. Furthermore, the brightest of our candidates (at z=10.2+-0.4) is robustly detected also at 3.6 micron (6.9sigma), revealing a flat UV spectral energy distribution with a slope beta=-2.0+-0.2, consistent with demonstrated trends with luminosity at high redshift. The abundance of these luminous candidates suggests that the luminosity function evolves more significantly in phi_* than in L_* at z>~8. Despite the discovery of these luminous candidates, the cosmic star formation rate density for g...
Leininger, J-Philippe; Minot, Christian; Lorant, François; Behar, Françoise
2007-04-26
Density functional B3LYP and BH&HLYP calculations with the 6-31G** basis set have been performed to investigate elementary reactions playing an important role in the pyrolysis of 1-methylnaphthalene. The pathways describing the destiny of the main radicals, H, methyl, hydromethylnaphthyl and methylnaphthyl, have been studied. At low temperature, addition of H atoms on the aromatic ring is favored over hydrogen abstraction. Except at low temperature (below 400 K), the hydromethylnaphthyl radical undergoes preferentially a loss of hydrogen rather than a bimolecular hydrogen transfer with methylnaphthalene or addition reaction on methylnaphthalene forming a hydrogenated dimer. In the range 400-750 K, the formation of methane by hydrogen abstraction of methyl radical on methylnaphthalene is predominant compared to the formation of hydrodimethylnaphthalenes by addition reaction. Rate constants of reactions describing the formation of heavy products like methyldinaphthylmethanes or dimethylbinaphthalenes have been calculated and discussed. They are also compared to recombination reactions from the literature. Rate constants of these reactions have been computed using transition state theory and can be integrated in kinetic radical schemes of methylated polyaromatic compounds pyrolysis from geological to laboratory conditions.
Bell Inequalities and Pseudo-functional densities
Geurdes, J F
2001-01-01
A local hidden variable model with pseudo-functional density function restricted to a binary probability event space is demonstrated to be able to reproduce the quantum correlation in an Einstein Podolsky Rosen Bohm and Aharonov type of experiment. In the density function use is made of Hadamard's finite part which disables the possibility to derive Bell's inequality from models with such a type of density function.
Accurate photometric redshift probability density estimation - method comparison and application
Rau, Markus Michael; Brimioulle, Fabrice; Frank, Eibe; Friedrich, Oliver; Gruen, Daniel; Hoyle, Ben
2015-01-01
We introduce an ordinal classification algorithm for photometric redshift estimation, which vastly improves the reconstruction of photometric redshift probability density functions (PDFs) for individual galaxies and galaxy samples. As a use case we apply our method to CFHTLS galaxies. The ordinal classification algorithm treats distinct redshift bins as ordered values, which improves the quality of photometric redshift PDFs, compared with non-ordinal classification architectures. We also propose a new single value point estimate of the galaxy redshift, that can be used to estimate the full redshift PDF of a galaxy sample. This method is competitive in terms of accuracy with contemporary algorithms, which stack the full redshift PDFs of all galaxies in the sample, but requires orders of magnitudes less storage space. The methods described in this paper greatly improve the log-likelihood of individual object redshift PDFs, when compared with a popular Neural Network code (ANNz). In our use case, this improvemen...
A Density Functional Theory Study
Lim, XiaoZhi
2011-12-11
Complexes with pincer ligand moieties have garnered much attention in the past few decades. They have been shown to be highly active catalysts in several known transition metal-catalyzed organic reactions as well as some unprecedented organic transformations. At the same time, the use of computational organometallic chemistry to aid in the understanding of the mechanisms in organometallic catalysis for the development of improved catalysts is on the rise. While it was common in earlier studies to reduce computational cost by truncating donor group substituents on complexes such as tertbutyl or isopropyl groups to hydrogen or methyl groups, recent advancements in the processing capabilities of computer clusters and codes have streamlined the time required for calculations. As the full modeling of complexes become increasingly popular, a commonly overlooked aspect, especially in the case of complexes bearing isopropyl substituents, is the conformational analysis of complexes. Isopropyl groups generate a different conformer with each 120 ° rotation (rotamer), and it has been found that each rotamer typically resides in its own potential energy well in density functional theory studies. As a result, it can be challenging to select the most appropriate structure for a theoretical study, as the adjustment of isopropyl substituents from a higher-energy rotamer to the lowest-energy rotamer usually does not occur during structure optimization. In this report, the influence of the arrangement of isopropyl substituents in pincer complexes on calculated complex structure energies as well as a case study on the mechanism of the isomerization of an iPrPCP-Fe complex is covered. It was found that as many as 324 rotamers can be generated for a single complex, as in the case of an iPrPCP-Ni formato complex, with the energy difference between the global minimum and the highest local minimum being as large as 16.5 kcalmol-1. In the isomerization of a iPrPCP-Fe complex, it was found
Large Scale Density Estimation of Blue and Fin Whales (LSD)
2015-09-30
1 DISTRIBUTION STATEMENT A. Approved for public release; distribution is unlimited. Large Scale Density Estimation of Blue and Fin Whales ...sensors, or both. The goal of this research is to develop and implement a new method for estimating blue and fin whale density that is effective over...develop and implement a density estimation methodology for quantifying blue and fin whale abundance from passive acoustic data recorded on sparse
Estimation of linear functionals in emission tomography
Energy Technology Data Exchange (ETDEWEB)
Kuruc, A.
1995-08-01
In emission tomography, the spatial distribution of a radioactive tracer is estimated from a finite sample of externally-detected photons. We present an algorithm-independent theory of statistical accuracy attainable in emission tomography that makes minimal assumptions about the underlying image. Let f denote the tracer density as a function of position (i.e., f is the image being estimated). We consider the problem of estimating the linear functional {Phi}(f) {triple_bond} {integral}{phi}(x)f(x) dx, where {phi} is a smooth function, from n independent observations identically distributed according to the Radon transform of f. Assuming only that f is bounded above and below away from 0, we construct statistically efficient estimators for {Phi}(f). By definition, the variance of the efficient estimator is a best-possible lower bound (depending on and f) on the variance of unbiased estimators of {Phi}(f). Our results show that, in general, the efficient estimator will have a smaller variance than the standard estimator based on the filtered-backprojection reconstruction algorithm. The improvement in performance is obtained by exploiting the range properties of the Radon transform.
Joubert, Daniel P.
2012-03-01
It is shown that the density-functional-theory exchange and correlation functionals satisfy 0=γEhx[ρN]+2Ecγ[ρN]-γEhx[ρN-1γ]-2Ecγ[ρN-1γ]+2∫d3r'[ρN-10(r)-ρN-1γ(r)]v0([ρN];r)+∫d3r'[ρN-10(r)-ρN-1γ(r)]r·∇v0([ρN];r)+∫d3r'ρN(r)r·∇vcγ([ρN];r)-∫d3r'ρN-1γ(r)r·∇vcγ([ρN-1γ];r)-∫d3r'fγ(r)r·∇vhxcγ([ρN];r)-2∫d3r'fγ(r)vhxcγ([ρN];r). In the derivation of this equation the adiabatic connection formulation is used, where the ground-state density of an N-electron system ρN is kept constant independent of the electron-electron coupling strength γ. Here Ehx[ρ] is the Hartree plus exchange energy, Ecγ[ρ] is the correlation energy, vhxcγ[ρ] is the Hartree plus exchange-correlation potential, vc[ρ] is the correlation potential, and v0[ρ]is the Kohn-Sham potential. The charge densities ρN and ρN-1γ are the N- and (N-1)-electron ground-state densities of the same Hamiltonian at electron-electron coupling strength γ. fγ(r)=ρN(r)-ρN-1γ(r) is the Fukui function. This equation can be useful in testing the internal self-consistency of approximations to the exchange and correlation functionals. As an example the identity is tested on the analytical Hooke's atom charge density for some frequently used approximate functionals.
Ant-inspired density estimation via random walks.
Musco, Cameron; Su, Hsin-Hao; Lynch, Nancy A
2017-09-19
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.
Density functional theory in quantum chemistry
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.
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...
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 ...
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 ...
Breast density estimation from high spectral and spatial resolution MRI.
Li, Hui; Weiss, William A; Medved, Milica; Abe, Hiroyuki; Newstead, Gillian M; Karczmar, Gregory S; Giger, Maryellen L
2016-10-01
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 ([Formula: see text]) was obtained between left and right breast density estimations. An interclass correlation coefficient of 0.99 ([Formula: see text]) indicated high reliability for the inter-user variability of the HiSS-based breast density estimations. A moderate correlation coefficient of 0.55 ([Formula: see text]) 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.
Current Source Density Estimation for Single Neurons
Directory of Open Access Journals (Sweden)
Dorottya Cserpán
2014-03-01
Full Text Available Recent developments of multielectrode technology made it possible to measure the extracellular potential generated in the neural tissue with spatial precision on the order of tens of micrometers and on submillisecond time scale. Combining such measurements with imaging of single neurons within the studied tissue opens up new experimental possibilities for estimating distribution of current sources along a dendritic tree. In this work we show that if we are able to relate part of the recording of extracellular potential to a specific cell of known morphology we can estimate the spatiotemporal distribution of transmembrane currents along it. We present here an extension of the kernel CSD method (Potworowski et al., 2012 applicable in such case. We test it on several model neurons of progressively complicated morphologies from ball-and-stick to realistic, up to analysis of simulated neuron activity embedded in a substantial working network (Traub et al, 2005. We discuss the caveats and possibilities of this new approach.
Highway traffic model-based density estimation
Morarescu, Irinel - Constantin; CANUDAS DE WIT, Carlos
2011-01-01
International audience; The travel time spent in traffic networks is one of the main concerns of the societies in developed countries. A major requirement for providing traffic control and services is the continuous prediction, for several minutes into the future. This paper focuses on an important ingredient necessary for the traffic forecasting which is the real-time traffic state estimation using only a limited amount of data. Simulation results illustrate the performances of the proposed ...
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.
Toward accurate and precise estimates of lion density.
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
A Tryst With Density: Walter Kohn and Density Functional Theory
Indian Academy of Sciences (India)
Shobhana Narasimhan
2017-08-01
Walter Kohn transformed theoretical chemistry and solid statephysics with his development of density functional theory, forwhich he was awarded the Nobel Prize. This article tries toexplain, in simple terms, why this was an important advancein the field, and to describe precisely what it was that he (togetherwith his collaborators Pierre Hohenberg and Lu JeuSham) achieved.
Multicomponent density functional theory embedding formulation.
Culpitt, Tanner; Brorsen, Kurt R; Pak, Michael V; Hammes-Schiffer, Sharon
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(-) 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.
Multicomponent density functional theory embedding formulation
Culpitt, Tanner; Brorsen, Kurt R.; Pak, Michael V.; Hammes-Schiffer, Sharon
2016-07-01
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- 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.
Density-functional theory of thermoelectric phenomena.
Eich, F G; Di Ventra, M; Vignale, G
2014-05-16
We introduce a nonequilibrium density-functional theory of local temperature and associated local energy density that is suited for the study of thermoelectric phenomena. The theory rests on a local temperature field coupled to the energy-density operator. We identify the excess-energy density, in addition to the particle density, as the basic variable, which is reproduced by an effective noninteracting Kohn-Sham system. A novel Kohn-Sham equation emerges featuring a time-dependent and spatially varying mass which represents local temperature variations. The adiabatic contribution to the Kohn-Sham potentials is related to the entropy viewed as a functional of the particle and energy density. Dissipation can be taken into account by employing linear response theory and the thermoelectric transport coefficients of the electron gas.
Relativistic density functional for nuclear structure
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.
Nuclear Energy Density Functional for KIDS
Gil, Hana; Hyun, Chang Ho; Park, Tae-Sun; Oh, Yongseok
2016-01-01
The density functional theory (DFT) is based on the existence and uniqueness of a universal functional $E[\\rho]$, which determines the dependence of the total energy on single-particle density distributions. However, DFT says nothing about the form of the functional. Our strategy is to first look at what we know, from independent considerations, about the analytical density dependence of the energy of nuclear matter and then, for practical applications, to obtain an appropriate density-dependent effective interaction by reverse engineering. In a previous work on homogeneous matter, we identified the most essential terms to include in our "KIDS" functional, named after the early-stage participating institutes. We now present first results for finite nuclei, namely the energies and radii of $^{16,28}$O, $^{40,60}$Ca.
A multiconfigurational hybrid density-functional theory
Sharkas, Kamal; Jensen, Hans Jørgen Aa; Toulouse, Julien; 10.1063/1.4733672
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 of the usual hybrid approximations by essentially adding a fraction \\lambda of exact static correlation in addition to the fraction \\lambda of exact exchange. Test calculations on the cycloaddition reactions of ozone with ethylene or acetylene and the dissociation of diatomic molecules with the Perdew-Burke-Ernzerhof (PBE) and Becke-Lee-Yang-Parr (BLYP) density functionals show that a good value of \\lambda is 0.25, as in the usual hybrid approximations. The results suggest that the proposed multiconfigurational hybrid approximations can improve over usual density-functional calculations for situations with strong static correlation effects.
Development of New Density Functional Approximations
Su, Neil Qiang; Xu, Xin
2017-05-01
Kohn-Sham density functional theory has become the leading electronic structure method for atoms, molecules, and extended systems. It is in principle exact, but any practical application must rely on density functional approximations (DFAs) for the exchange-correlation energy. Here we emphasize four aspects of the subject: (a) philosophies and strategies for developing DFAs; (b) classification of DFAs; (c) major sources of error in existing DFAs; and (d) some recent developments and future directions.
Fusion of Hard and Soft Information in Nonparametric Density Estimation
2015-06-10
estimation exploiting, in concert, hard and soft information. Although our development, theoretical and numerical, makes no distinction based on sample...Fusion of Hard and Soft Information in Nonparametric Density Estimation∗ Johannes O. Royset Roger J-B Wets Department of Operations Research...univariate density estimation in situations when the sample ( hard information) is supplemented by “soft” information about the random phenomenon. These
Density estimates of monarch butterflies overwintering in central Mexico.
Thogmartin, Wayne E; Diffendorfer, Jay E; López-Hoffman, Laura; Oberhauser, Karen; Pleasants, John; Semmens, Brice X; Semmens, Darius; 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.
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
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.
Comparison of density estimation methods for astronomical datasets
Ferdosi, B.J.; Buddelmeijer, H.; Trager, S.C.; Wilkinson, M.H.F.; Roerdink, J.B.T.M.
2011-01-01
Context. Galaxies are strongly influenced by their environment. Quantifying the galaxy density is a difficult but critical step in studying the properties of galaxies. Aims. We aim to determine differences in density estimation methods and their applicability in astronomical problems. We study the p
Density estimators in particle hydrodynamics - DTFE versus regular SPH
Pelupessy, FI; Schaap, WE; van de Weygaert, R
2003-01-01
We present the results of a study comparing density maps reconstructed by the Delaunay Tessellation Field Estimator (DTFE) and by regular SPH kernel-based techniques. The density maps are constructed from the outcome of an SPH particle hydrodynamics simulation of a multiphase interstellar medium. Th
Some asymptotic results on density estimators by wavelet projections
Varron, Davit
2012-01-01
Let $(X_i)_{i\\geq 1}$ be an i.i.d. sample on $\\RRR^d$ having density $f$. Given a real function $\\phi$ on $\\RRR^d$ with finite variation and given an integer valued sequence $(j_n)$, let $\\fn$ denote the estimator of $f$ by wavelet projection based on $\\phi$ and with multiresolution level equal to $j_n$. We provide exact rates of almost sure convergence to 0 of the quantity $\\sup_{x\\in H}\\mid \\fn(x)-\\EEE(\\fn)(x)\\mid$, when $n2^{-dj_n}/\\log n \\rar \\infty$ and $H$ is a given hypercube of $\\RRR^d$. We then show that, if $n2^{-dj_n}/\\log n \\rar c$ for a constant $c>0$, then the quantity $\\sup_{x\\in H}\\mid \\fn(x)-f\\mid$ almost surely fails to converge to 0.
Estimating maritime snow density from seasonal climate variables
Bormann, K. J.; Evans, J. P.; Westra, S.; McCabe, M. F.; Painter, T. H.
2013-12-01
Snow density is a complex parameter that influences thermal, optical and mechanical snow properties and processes. Depth-integrated properties of snowpacks, including snow density, remain very difficult to obtain remotely. Observations of snow density are therefore limited to in-situ point locations. In maritime snowfields such as those in Australia and in parts of the western US, snow densification rates are enhanced and inter-annual variability is high compared to continental snow regions. In-situ snow observation networks in maritime climates often cannot characterise the variability in snowpack properties at spatial and temporal resolutions required for many modelling and observations-based applications. Regionalised density-time curves are commonly used to approximate snow densities over broad areas. However, these relationships have limited spatial applicability and do not allow for interannual variability in densification rates, which are important in maritime environments. Physically-based density models are relatively complex and rely on empirical algorithms derived from limited observations, which may not represent the variability observed in maritime snow. In this study, seasonal climate factors were used to estimate late season snow densities using multiple linear regressions. Daily snow density estimates were then obtained by projecting linearly to fresh snow densities at the start of the season. When applied spatially, the daily snow density fields compare well to in-situ observations across multiple sites in Australia, and provide a new method for extrapolating existing snow density datasets in maritime snow environments. While the relatively simple algorithm for estimating snow densities has been used in this study to constrain snowmelt rates in a temperature-index model, the estimates may also be used to incorporate variability in snow depth to snow water equivalent conversion.
Probability Density and CFAR Threshold Estimation for Hyperspectral Imaging
Energy Technology Data Exchange (ETDEWEB)
Clark, G A
2004-09-21
The work reported here shows the proof of principle (using a small data set) for a suite of algorithms designed to estimate the probability density function of hyperspectral background data and compute the appropriate Constant False Alarm Rate (CFAR) matched filter decision threshold for a chemical plume detector. Future work will provide a thorough demonstration of the algorithms and their performance with a large data set. The LASI (Large Aperture Search Initiative) Project involves instrumentation and image processing for hyperspectral images of chemical plumes in the atmosphere. The work reported here involves research and development on algorithms for reducing the false alarm rate in chemical plume detection and identification algorithms operating on hyperspectral image cubes. The chemical plume detection algorithms to date have used matched filters designed using generalized maximum likelihood ratio hypothesis testing algorithms [1, 2, 5, 6, 7, 12, 10, 11, 13]. One of the key challenges in hyperspectral imaging research is the high false alarm rate that often results from the plume detector [1, 2]. The overall goal of this work is to extend the classical matched filter detector to apply Constant False Alarm Rate (CFAR) methods to reduce the false alarm rate, or Probability of False Alarm P{sub FA} of the matched filter [4, 8, 9, 12]. A detector designer is interested in minimizing the probability of false alarm while simultaneously maximizing the probability of detection P{sub D}. This is summarized by the Receiver Operating Characteristic Curve (ROC) [10, 11], which is actually a family of curves depicting P{sub D} vs. P{sub FA}parameterized by varying levels of signal to noise (or clutter) ratio (SNR or SCR). Often, it is advantageous to be able to specify a desired P{sub FA} and develop a ROC curve (P{sub D} vs. decision threshold r{sub 0}) for that case. That is the purpose of this work. Specifically, this work develops a set of algorithms and MATLAB
Whitenack, Daniel L; Wasserman, Adam
2012-04-28
Aspects of density functional resonance theory (DFRT) [D. L. Whitenack and A. Wasserman, Phys. Rev. Lett. 107, 163002 (2011)], a recently developed complex-scaled version of ground-state density functional theory (DFT), are studied in detail. The asymptotic behavior of the complex density function is related to the complex resonance energy and system's threshold energy, and the function's local oscillatory behavior is connected with preferential directions of electron decay. Practical considerations for implementation of the theory are addressed including sensitivity to the complex-scaling parameter, θ. In Kohn-Sham DFRT, it is shown that almost all θ-dependence in the calculated energies and lifetimes can be extinguished via use of a proper basis set or fine grid. The highest occupied Kohn-Sham orbital energy and lifetime are related to physical affinity and width, and the threshold energy of the Kohn-Sham system is shown to be equal to the threshold energy of the interacting system shifted by a well-defined functional. Finally, various complex-scaling conditions are derived which relate the functionals of ground-state DFT to those of DFRT via proper scaling factors and a non-Hermitian coupling-constant system.
On estimation of survival function under random censoring model
Institute of Scientific and Technical Information of China (English)
JIANG; Jiancheng(蒋建成); CHENG; Bo(程博); WU; Xizhi(吴喜之)
2002-01-01
We study an estimator of the survival function under the random censoring model. Bahadur-type representation of the estimator is obtained and asymptotic expression for its mean squared errors is given, which leads to the consistency and asymptotic normality of the estimator. A data-driven local bandwidth selection rule for the estimator is proposed. It is worth noting that the estimator is consistent at left boundary points, which contrasts with the cases of density and hazard rate estimation. A Monte Carlo comparison of different estimators is made and it appears that the proposed data-driven estimators have certain advantages over the common Kaplan-Meier estmator.
Functional responses modified by predator density
Kratina, P.; Vos, M.; Bateman, A.W.; Anholt, B.R.
2009-01-01
Realistic functional responses are required for accurate model predictions at the community level. However, controversy remains regarding which types of dependencies need to be included in functional response models. Several studies have shown an effect of very high predator densities on per capita
Particle conservation in dynamical density functional theory.
de Las Heras, Daniel; Brader, Joseph M; Fortini, Andrea; Schmidt, Matthias
2016-06-22
We present the exact adiabatic theory for the dynamics of the inhomogeneous density distribution of a classical fluid. Erroneous particle number fluctuations of dynamical density functional theory are absent, both for canonical and grand canonical initial conditions. We obtain the canonical free energy functional, which yields the adiabatic interparticle forces of overdamped Brownian motion. Using an exact and one of the most advanced approximate hard core free energy functionals, we obtain excellent agreement with simulations. The theory applies to finite systems in and out of equilibrium.
Integer Discontinuity of Density Functional Theory
Mosquera, Martin A
2014-01-01
Density functional approximations to the exchange-correlation energy of Kohn-Sham theory, such as the local density approximation and generalized gradient approximations, lack the well-known integer discontinuity, a feature that is critical to describe molecular dissociation correctly. Moreover, standard approximations to the exchange-correlation energy also fail to yield the correct linear dependence of the ground-state energy on the number of electrons when this is a non-integer number obtained from the grand canonical ensemble statistics. We present a formal framework to restore the integer discontinuity of any density functional approximation. Our formalism derives from a formula for the exact energy functional and a new constrained search functional that recovers the linear dependence of the energy on the number of electrons.
Cortical cell and neuron density estimates in one chimpanzee hemisphere.
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.
Estimating the mass density of neutral gas at $z < 1$
Natarajan, P; Natarajan, Priyamvada; Pettini, Max
1997-01-01
We use the relationships between galactic HI mass and B-band luminosity determined by Rao & Briggs to recalculate the mass density of neutral gas at the present epoch based on more recent measures of the galaxy luminosity function than were available to those authors. We find $\\Omega_{gas}(z=0) value, suggesting that this quantity is now reasonably secure. We then show that, if the scaling between H I mass and B-band luminosity has remained approximately constant since $z = 1$, the evolution of the luminosity function found by the Canada-France redshift survey translates to an increase of obtained quite independently from consideration of the luminosity function of Mg II absorbers at $z = 0.65$. By combining these new estimates with data from damped \\lya systems at higher redshift, it is possible to assemble a rough sketch of the evolution of $Ømega_{gas}$ over the last 90% of the age of the universe. The consumption of H I gas with time is in broad agreement with models of chemical evolution which inclu...
Density functional theory and multiscale materials modeling
Indian Academy of Sciences (India)
Swapan K Ghosh
2003-01-01
One of the vital ingredients in the theoretical tools useful in materials modeling at all the length scales of interest is the concept of density. In the microscopic length scale, it is the electron density that has played a major role in providing a deeper understanding of chemical binding in atoms, molecules and solids. In the intermediate mesoscopic length scale, an appropriate picture of the equilibrium and dynamical processes has been obtained through the single particle number density of the constituent atoms or molecules. A wide class of problems involving nanomaterials, interfacial science and soft condensed matter has been addressed using the density based theoretical formalism as well as atomistic simulation in this regime. In the macroscopic length scale, however, matter is usually treated as a continuous medium and a description using local mass density, energy density and other related density functions has been found to be quite appropriate. A unique single unified theoretical framework that emerges through the density concept at these diverse length scales and is applicable to both quantum and classical systems is the so called density functional theory (DFT) which essentially provides a vehicle to project the many-particle picture to a single particle one. Thus, the central equation for quantum DFT is a one-particle Schrödinger-like Kohn–Sham equation, while the same for classical DFT consists of Boltzmann type distributions, both corresponding to a system of noninteracting particles in the field of a density-dependent effective potential. Selected illustrative applications of quantum DFT to microscopic modeling of intermolecular interaction and that of classical DFT to a mesoscopic modeling of soft condensed matter systems are presented.
Noncovalent Interactions in Density-Functional Theory
DiLabio, Gino A
2014-01-01
Non-covalent interactions are essential in the description of soft matter, including materials of technological importance and biological molecules. In density-functional theory, common approaches fail to describe dispersion forces, an essential component in noncovalent binding interactions. In the last decade, great progress has been made in the development of accurate and computationally-efficient methods to describe noncovalently bound systems within the framework of density-functional theory. In this review, we give an account of the field from a chemical and didactic perspective, describing different approaches to the calculation of dispersion energies and comparing their accuracy, complexity, popularity, and general availability. This review should be useful to the newcomer who wants to learn more about noncovalent interactions and the different methods available at present to describe them using density-functional theory.
Density Functionals with Broad Applicability in Chemistry
Energy Technology Data Exchange (ETDEWEB)
Zhao, Yan; Truhlar, Donald G.
2008-02-01
The research described in this product was performed in part in the Environmental Molecular Sciences Laboratory, a national scientific user facility sponsored by the Department of Energy's Office of Biological and Environmental Research and located at Pacific Northwest National Laboratory. Although density functional theory is widely used in the computational chemistry community, the most popular density functional, B3LYP, has some serious shortcomings: (i) it is better for main-group chemistry than for transition metals; (ii) it systematically underestimates reaction barrier heights; (iii) it is inaccurate for interactions dominated by mediumrange correlation energy, such as van der Waals attraction, aromatic-aromatic stacking, and alkane isomerization energies. We have developed a variety of databases for testing and designing new density functionals. We used these data to design new density functionals, called M06-class (and, earlier, M05-class) functionals, for which we enforced some fundamental exact constraints such as the uniform-electron-gas limit and the absence of self-correlation energy. Our M06-class functionals depend on spin-up and spin-down electron densities (i.e., spin densities), spin density gradients, spin kinetic energy densities, and, for nonlocal (also called hybrid) functionals, Hartree-Fock exchange. We have developed four new functionals that overcome the above-mentioned difficulties: (a) M06, a hybrid meta functional, is a functional with good accuracy “across-theboard” for transition metals, main group thermochemistry, medium-range correlation energy, and barrier heights; (b) M06- 2X, another hybrid meta functional, is not good for transition metals but has excellent performance for main group chemistry, predicts accurate valence and Rydberg electronic excitation energies, and is an excellent functional for aromatic-aromatic stacking interactions; (c) M06-L is not as accurate as M06 for barrier heights but is the most accurate
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
Connection formula for thermal density functional theory
Pribram-Jones, Aurora
2015-01-01
The adiabatic connection formula of ground-state density functional theory relates the correlation energy to a coupling-constant integral over a purely potential contribution, and is widely used to understand and improve approximations. The corresponding formula for thermal density functional theory is cast as an integral over temperatures instead, ranging upwards from the system's physical temperature to infinite temperatures. Several formulas yield one component of the thermal correlation free energy in terms of another, many of which can be expressed either in terms of temperature- or coupling-constant integration. We illustrate with the uniform electron gas.
Density functional calculations of nanoscale conductance
Energy Technology Data Exchange (ETDEWEB)
Koentopp, Max; Chang, Connie [Department of Chemistry and Chemical Biology, Rutgers University, 610 Taylor Road, Piscataway, NJ 08854 (United States); Burke, Kieron [Department of Chemistry, UC Irvine, 1102 Natural Sciences 2, Irvine, CA 92697 (United States); Car, Roberto [Department of Chemistry and Princeton Institute for the Science and Technology of Materials (PRISM), Princeton University, Princeton, NJ 08544 (United States)
2008-02-27
Density functional calculations for the electronic conductance of single molecules are now common. We examine the methodology from a rigorous point of view, discussing where it can be expected to work, and where it should fail. When molecules are weakly coupled to leads, local and gradient-corrected approximations fail, as the Kohn-Sham levels are misaligned. In the weak bias regime, exchange-correlation corrections to the current are missed by the standard methodology. For finite bias, a new methodology for performing calculations can be rigorously derived using an extension of time-dependent current density functional theory from the Schroedinger equation to a master equation. (topical review)
Kernel density estimation of a multidimensional efficiency profile
Poluektov, Anton
2014-01-01
Kernel density estimation is a convenient way to estimate the probability density of a distribution given the sample of data points. However, it has certain drawbacks: proper description of the density using narrow kernels needs large data samples, whereas if the kernel width is large, boundaries and narrow structures tend to be smeared. Here, an approach to correct for such effects, is proposed that uses an approximate density to describe narrow structures and boundaries. The approach is shown to be well suited for the description of the efficiency shape over a multidimensional phase space in a typical particle physics analysis. An example is given for the five-dimensional phase space of the $\\Lambda_b^0\\to D^0p\\pi$ decay.
Optimization of volumetric breast density estimation in digital mammograms.
Holland, Katharina; Gubern-Mérida, Albert; Mann, Ritse M; Karssemeijer, Nico
2017-05-07
Fibroglandular tissue volume and percent density can be estimated in unprocessed mammograms using a physics-based method, which relies on an internal reference value representing the projection of fat only. However, pixels representing fat only may not be present in dense breasts, causing an underestimation of density measurements. In this work, we investigate alternative approaches for obtaining a tissue reference value to improve density estimations, particularly in dense breasts. Two of three investigated reference values (F1, F2) are percentiles of the pixel value distribution in the breast interior (the contact area of breast and compression paddle). F1 is determined in a small breast interior, which minimizes the risk that peripheral pixels are included in the measurement at the cost of increasing the chance that no proper reference can be found. F2 is obtained using a larger breast interior. The new approach which is developed for very dense breasts does not require the presence of a fatty tissue region. As reference region we select the densest region in the mammogram and assume that this represents a projection of entirely dense tissue embedded between the subcutaneous fatty tissue layers. By measuring the thickness of the fat layers a reference (F3) can be computed. To obtain accurate breast density estimates irrespective of breast composition we investigated a combination of the results of the three reference values. We collected 202 pairs of MRI's and digital mammograms from 119 women. We compared the percent dense volume estimates based on both modalities and calculated Pearson's correlation coefficients. With the references F1-F3 we found respectively a correlation of [Formula: see text], [Formula: see text] and [Formula: see text]. Best results were obtained with the combination of the density estimations ([Formula: see text]). Results show that better volumetric density estimates can be obtained with the hybrid method, in particular for dense
Molecular Density Functional Theory of Water
Jeanmairet, Guillaume; Vuilleumier, Rodolphe; Borgis, Daniel; 10.1021/jz301956b
2013-01-01
Three dimensional implementations of liquid state theories offer an efficient alternative to computer simulations for the atomic-level description of aqueous solutions in complex environments. In this context, we present a (classical) molecular density functional theory (MDFT) of water that is derived from first principles and is based on two classical density fields, a scalar one, the particle density, and a vectorial one, the multipolar polarization density. Its implementation requires as input the partial charge distribution of a water molecule and three measurable bulk properties, namely the structure factor and the k-dependent longitudinal and transverse dielectric constants. It has to be complemented by a solute-solvent three-body term that reinforces tetrahedral order at short range. The approach is shown to provide the correct three-dimensional microscopic solvation profile around various molecular solutes, possibly possessing H-bonding sites, at a computer cost two-three orders of magnitude lower tha...
Density functional theory studies of etoricoxib
Sachdeva, Ritika; Kaur, Prabhjot; Singh, V. P.; Saini, G. S. S.
2016-05-01
Etoricoxib is a COX-2 selective inhibitor drug with molecular formula C18H15ClN2O2S. It is primarily used for the treatment of arthritis(rheumatoid, psoriatic, osteoarthritis), ankylosing spondylitis, gout and chronic low back pain. Theoretical studies of the molecule including geometry optimization and vibrational frequency calculations were carried out with the help of density functional theory calculations using 6-311++ g (d, p) basis set and B3LYP functional.
Density estimates of monarch butterflies overwintering in central Mexico
Thogmartin, Wayne; Diffendorfer, Jay E.; Lopez-Hoffman, Laura; Oberhauser, Karen; Pleasants, John; Semmens, Brice Xavier; Semmens, Darius; 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...
Density Functional Simulation of a Breaking Nanowire
DEFF Research Database (Denmark)
Nakamura, A.; Brandbyge, Mads; Hansen, Lars Bruno
1999-01-01
We study the deformation and breaking of an atomic-sized sodium wire using density functional simulations. The wire deforms through sudden atomic rearrangements and smoother atomic displacements. The conductance of the wire exhibits plateaus at integer values in units of 2e(2)/h corresponding...
Density functional and neural network analysis
DEFF Research Database (Denmark)
Jalkanen, K. J.; 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...
Density functional theory with quantum nuclei
Requist, Ryan
2016-01-01
It is proved that the ground state energy of an electron-nuclear system is a variational functional of the conditional electronic density n_R(r), the nuclear wavefunction \\chi(R) and the quantum geometric tensor of the conditional electronic wavefunction $T_{\\mu\
Current Developments in Nuclear Density Functional Methods
Dobaczewski, J
2010-01-01
Density functional theory (DFT) became a universal approach to compute ground-state and excited configurations of many-electron systems held together by an external one-body potential in condensed-matter, atomic, and molecular physics. At present, the DFT strategy is also intensely studied and applied in the area of nuclear structure. The nuclear DFT, a natural extension of the self-consistent mean-field theory, is a tool of choice for computations of ground-state properties and low-lying excitations of medium-mass and heavy nuclei. Over the past thirty-odd years, a lot of experience was accumulated in implementing, adjusting, and using the density-functional methods in nuclei. This research direction is still extremely actively pursued. In particular, current developments concentrate on (i) attempts to improve the performance and precision delivered by the nuclear density-functional methods, (ii) derivations of density functionals from first principles rooted in the low-energy chromodynamics and effective th...
Density functional theory: Fixing Jacob's ladder
Car, Roberto
2016-09-01
Density functional theory calculations can be carried out with different levels of accuracy, forming a hierarchy that is often represented by the rungs of a ladder. Now a new method has been developed that significantly improves the accuracy of the 'third rung' when calculating the properties of diversely bonded systems.
Local Polynomial Estimation of Distribution Functions
Institute of Scientific and Technical Information of China (English)
LI Yong-hong; ZENG Xia
2007-01-01
Under the condition that the total distribution function is continuous and bounded on (-∞,∞), we constructed estimations for distribution and hazard functions with local polynomial method, and obtained the rate of strong convergence of the estimations.
Estimation of volumetric breast density for breast cancer risk prediction
Pawluczyk, Olga; Yaffe, Martin J.; Boyd, Norman F.; Jong, Roberta A.
2000-04-01
Mammographic density (MD) has been shown to be a strong risk predictor for breast cancer. Compared to subjective assessment by a radiologist, computer-aided analysis of digitized mammograms provides a quantitative and more reproducible method for assessing breast density. However, the current methods of estimating breast density based on the area of bright signal in a mammogram do not reflect the true, volumetric quantity of dense tissue in the breast. A computerized method to estimate the amount of radiographically dense tissue in the overall volume of the breast has been developed to provide an automatic, user-independent tool for breast cancer risk assessment. The procedure for volumetric density estimation consists of first correcting the image for inhomogeneity, then performing a volume density calculation. First, optical sensitometry is used to convert all images to the logarithm of relative exposure (LRE), in order to simplify the image correction operations. The field non-uniformity correction, which takes into account heel effect, inverse square law, path obliquity and intrinsic field and grid non- uniformity is obtained by imaging a spherical section PMMA phantom. The processed LRE image of the phantom is then used as a correction offset for actual mammograms. From information about the thickness and placement of the breast, as well as the parameters of a breast-like calibration step wedge placed in the mammogram, MD of the breast is calculated. Post processing and a simple calibration phantom enable user- independent, reliable and repeatable volumetric estimation of density in breast-equivalent phantoms. Initial results obtained on known density phantoms show the estimation to vary less than 5% in MD from the actual value. This can be compared to estimated mammographic density differences of 30% between the true and non-corrected values. Since a more simplistic breast density measurement based on the projected area has been shown to be a strong indicator
Multistate Density Functional Theory for Effective Diabatic Electronic Coupling.
Ren, Haisheng; Provorse, Makenzie R; Bao, Peng; Qu, Zexing; Gao, Jiali
2016-06-16
Multistate density functional theory (MSDFT) is presented to estimate the effective transfer integral associated with electron and hole transfer reactions. In this approach, the charge-localized diabatic states are defined by block localization of Kohn-Sham orbitals, which constrain the electron density for each diabatic state in orbital space. This differs from the procedure used in constrained density functional theory that partitions the density within specific spatial regions. For a series of model systems, the computed transfer integrals are consistent with experimental data and show the expected exponential attenuation with the donor-acceptor separation. The present method can be used to model charge transfer reactions including processes involving coupled electron and proton transfer.
MAXIMUM INFORMATION AND OPTIMUM ESTIMATING FUNCTION
Institute of Scientific and Technical Information of China (English)
林路
2003-01-01
In order to construct estimating functions in some parametric models, this paper introducestwo classes of information matrices. Some necessary and sufficient conditions for the informationmatrices achieving their upper bounds are given. For the problem of estimating the median,some optimum estimating functions based on the information matrices are acquired. Undersome regularity conditions, an approach to carrying out the best basis function is introduced. Innonlinear regression models, an optimum estimating function based on the information matricesis obtained. Some examples are given to illustrate the results. Finally, the concept of optimumestimating function and the methods of constructing optimum estimating function are developedin more general statistical models.
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.
Face Value: Towards Robust Estimates of Snow Leopard Densities.
Alexander, Justine S; Gopalaswamy, Arjun M; Shi, Kun; Riordan, Philip
2015-01-01
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.
Corruption clubs: empirical evidence from kernel density estimates
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
Corruption clubs: empirical evidence from kernel density estimates
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
Density estimation in tiger populations: combining information for strong inference.
Gopalaswamy, Arjun M; Royle, J Andrew; Delampady, Mohan; Nichols, James D; Karanth, K Ullas; Macdonald, David W
2012-07-01
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.
Density estimation in tiger populations: combining information for strong inference
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.
Optimization of volumetric breast density estimation in digital mammograms
Holland, K.; Gubern Merida, A.; Mann, R.M.; Karssemeijer, N.
2017-01-01
Fibroglandular tissue volume and percent density can be estimated in unprocessed mammograms using a physics-based method, which relies on an internal reference value representing the projection of fat only. However, pixels representing fat only may not be present in dense breasts, causing an
State of the Art in Photon-Density Estimation
DEFF Research Database (Denmark)
Hachisuka, Toshiya; Jarosz, Wojciech; Georgiev, Iliyan
2013-01-01
Photon-density estimation techniques are a popular choice for simulating light transport in scenes with complicated geometry and materials. This class of algorithms can be used to accurately simulate inter-reflections, caustics, color bleeding, scattering in participating media, and subsurface sc...
State of the Art in Photon Density Estimation
DEFF Research Database (Denmark)
Hachisuka, Toshiya; Jarosz, Wojciech; Bouchard, Guillaume
2012-01-01
Photon-density estimation techniques are a popular choice for simulating light transport in scenes with complicated geometry and materials. This class of algorithms can be used to accurately simulate inter-reflections, caustics, color bleeding, scattering in participating media, and subsurface sc...
Estimation of the space density of low surface brightness galaxies
Briggs, FH
1997-01-01
The space density of low surface brightness and tiny gas-rich dwarf galaxies are estimated for two recent catalogs: the Arecibo Survey of Northern Dwarf and Low Surface Brightness Galaxies and the Catalog of Low Surface Brightness Galaxies, List II. The goals are (1) to evaluate the additions to the
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...
Spin in Density-Functional Theory
Jacob, Christoph R; 10.1002/qua.24309
2012-01-01
The accurate description of open-shell molecules, in particular of transition metal complexes and clusters, is still an important challenge for quantum chemistry. While density-functional theory (DFT) is widely applied in this area, the sometimes severe limitations of its currently available approximate realizations often preclude its application as a predictive theory. Here, we review the foundations of DFT applied to open-shell systems, both within the nonrelativistic and the relativistic framework. In particular, we provide an in-depth discussion of the exact theory, with a focus on the role of the spin density and possibilities for targeting specific spin states. It turns out that different options exist for setting up Kohn-Sham DFT schemes for open-shell systems, which imply different definitions of the exchange-correlation energy functional and lead to different exact conditions on this functional. Finally, we suggest some possible directions for future developments.
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.
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
Rojas-Lima, J. E.; Domínguez-Pacheco, A.; Hernández-Aguilar, C.; Cruz-Orea, A.
2016-09-01
Considering the necessity of photothermal alternative approaches for characterizing nonhomogeneous materials like maize seeds, the objective of this research work was to analyze statistically the amplitude variations of photopyroelectric signals, by means of nonparametric techniques such as the histogram and the kernel density estimator, and the probability density function of the amplitude variations of two genotypes of maize seeds with different pigmentations and structural components: crystalline and floury. To determine if the probability density function had a known parametric form, the histogram was determined which did not present a known parametric form, so the kernel density estimator using the Gaussian kernel, with an efficiency of 95 % in density estimation, was used to obtain the probability density function. The results obtained indicated that maize seeds could be differentiated in terms of the statistical values for floury and crystalline seeds such as the mean (93.11, 159.21), variance (1.64× 103, 1.48× 103), and standard deviation (40.54, 38.47) obtained from the amplitude variations of photopyroelectric signals in the case of the histogram approach. For the case of the kernel density estimator, seeds can be differentiated in terms of kernel bandwidth or smoothing constant h of 9.85 and 6.09 for floury and crystalline seeds, respectively.
Evaluating lidar point densities for effective estimation of aboveground biomass
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.
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....
Probability distribution functions in the finite density lattice QCD
Ejiri, S; Aoki, S; Kanaya, K; Saito, H; Hatsuda, T; Ohno, H; Umeda, T
2012-01-01
We study the phase structure of QCD at high temperature and density by lattice QCD simulations adopting a histogram method. We try to solve the problems which arise in the numerical study of the finite density QCD, focusing on the probability distribution function (histogram). As a first step, we investigate the quark mass dependence and the chemical potential dependence of the probability distribution function as a function of the Polyakov loop when all quark masses are sufficiently large, and study the properties of the distribution function. The effect from the complex phase of the quark determinant is estimated explicitly. The shape of the distribution function changes with the quark mass and the chemical potential. Through the shape of the distribution, the critical surface which separates the first order transition and crossover regions in the heavy quark region is determined for the 2+1-flavor case.
Compressive and Noncompressive Power Spectral Density Estimation from Periodic Nonuniform Samples
Lexa, Michael A; Thompson, John S
2011-01-01
This paper presents a novel power spectral density estimation technique for bandlimited, wide-sense stationary signals from sub-Nyquist sampled data. The technique employs multi-coset sampling and applies to spectrally sparse and nonsparse power spectra alike. For sparse density functions, we apply compressed sensing theory and the resulting compressive estimates exhibit better tradeoffs among the estimator's resolution, system complexity, and average sampling rate compared to their noncompressive counterparts. Both compressive and noncompressive estimates, however, can be computed at arbitrarily low sampling rates. The estimator does not require signal reconstruction and can be directly obtained from solving either a least squares or a nonnegative least squares problem. The estimates are piecewise constant approximations whose resolutions (width of the piecewise constant segments) are controlled by the periodicity of the multi-coset sampling. The estimates are also statistically consistent. This method is wi...
Adiabatic density-functional perturbation theory
Gonze, Xavier
1995-08-01
The treatment of adiabatic perturbations within density-functional theory is examined, at arbitrary order of the perturbation expansion. Due to the extremal property of the energy functional, standard variation-perturbation theorems can be used. The different methods (Sternheimer equation, extremal principle, Green's function, and sum over state) for obtaining the perturbation expansion of the wave functions are presented. The invariance of the Hilbert space of occupied wave functions with respect to a unitary transformation leads to the definition of a ``parallel-transport-gauge'' and a ``diagonal-gauge'' perturbation expansion. Then, the general expressions are specialized for the second, third, and fourth derivative of the energy, with an example of application of the method up to third order.
Variational estimation of the drift for stochastic differential equations from the empirical density
Batz, Philipp; Ruttor, Andreas; Opper, Manfred
2016-08-01
We present a method for the nonparametric estimation of the drift function of certain types of stochastic differential equations from the empirical density. It is based on a variational formulation of the Fokker-Planck equation. The minimization of an empirical estimate of the variational functional using kernel based regularization can be performed in closed form. We demonstrate the performance of the method on second order, Langevin-type equations and show how the method can be generalized to other noise models.
Variational estimation of the drift for stochastic differential equations from the empirical density
Batz, Philipp; Opper, Manfred
2016-01-01
We present a method for the nonparametric estimation of the drift function of certain types of stochastic differential equations from the empirical density. It is based on a variational formulation of the Fokker-Planck equation. The minimization of an empirical estimate of the variational functional using kernel based regularization can be performed in closed form. We demonstrate the performance of the method on second order, Langevin-type equations and show how the method can be generalized to other noise models.
Density functional theory on phase space
Blanchard, Philippe; Várilly, Joseph C
2010-01-01
Forty-five years after the point de d\\'epart [1] of density functional theory, its applications in chemistry and the study of electronic structures keep steadily growing. However, the precise form of the "divine" energy functional in terms of the electron density [2] still eludes us --and possibly will do so forever [3]. In what follows we examine a formulation in the same spirit with phase-space variables. The validity of Hohenberg-Kohn-Levy-type theorems on phase space is recalled. We study the representability problem for reduced Wigner functions, and proceed to analyze properties of the new functional. Along the way, new results on states in the phase-space formalism of quantum mechanics are established. Natural Wigner orbital theory is developed in depth, with the final aim of constructing accurate correlation-exchange functionals on phase space. A new proof of the overbinding property of the Mueller functional is given. This exact theory supplies its home at long last to that illustrious ancestor, the T...
Pressure Correction in Density Functional Theory Calculations
Lee, S H
2008-01-01
First-principles calculations based on density functional theory have been widely used in studies of the structural, thermoelastic, rheological, and electronic properties of earth-forming materials. The exchange-correlation term, however, is implemented based on various approximations, and this is believed to be the main reason for discrepancies between experiments and theoretical predictions. In this work, by using periclase MgO as a prototype system we examine the discrepancies in pressure and Kohn-Sham energy that are due to the choice of the exchange-correlation functional. For instance, we choose local density approximation and generalized gradient approximation. We perform extensive first-principles calculations at various temperatures and volumes and find that the exchange-correlation-based discrepancies in Kohn-Sham energy and pressure should be independent of temperature. This implies that the physical quantities, such as the equation of states, heat capacity, and the Gr\\"{u}neisen parameter, estimat...
Density functional theory a practical introduction
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
Narasimhan, Shobhana
2015-09-01
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.
Estimation of Enceladus Plume Density Using Cassini Flight Data
Wang, Eric K.; Lee, Allan Y.
2011-01-01
The Cassini spacecraft was launched on October 15, 1997 by a Titan 4B launch vehicle. After an interplanetary cruise of almost seven years, it arrived at Saturn on June 30, 2004. In 2005, Cassini completed three flybys of Enceladus, a small, icy satellite of Saturn. Observations made during these flybys confirmed the existence of water vapor plumes in the south polar region of Enceladus. Five additional low-altitude flybys of Enceladus were successfully executed in 2008-9 to better characterize these watery plumes. During some of these Enceladus flybys, the spacecraft attitude was controlled by a set of three reaction wheels. When the disturbance torque imparted on the spacecraft was predicted to exceed the control authority of the reaction wheels, thrusters were used to control the spacecraft attitude. Using telemetry data of reaction wheel rates or thruster on-times collected from four low-altitude Enceladus flybys (in 2008-10), one can reconstruct the time histories of the Enceladus plume jet density. The 1 sigma uncertainty of the estimated density is 5.9-6.7% (depending on the density estimation methodology employed). These plume density estimates could be used to confirm measurements made by other onboard science instruments and to support the modeling of Enceladus plume jets.
Structure Function Estimated From Histological Tissue Sections.
Han, Aiguo; O'Brien, William D
2016-09-01
Ultrasonic scattering is determined by not only the properties of individual scatterers but also the correlation among scatterer positions. The role of scatterer spatial correlation is significant for dense medium, but has not been fully understood. The effect of scatterer spatial correlation may be modeled by the structure function as a frequency-dependent factor in the backscatter coefficient (BSC) expression. The structure function has been previously estimated from the BSC data. The aim of this study is to estimate the structure function from histology to test if the acoustically estimated structure function is indeed caused by the scatterer spatial distribution. Hematoxylin and eosin stained histological sections from dense cell pellet biophantoms were digitized. The scatterer positions were determined manually from the histological images. The structure function was calculated from the extracted scatterer positions. The structure function obtained from histology showed reasonable agreement in the shape but not in the amplitude, compared with the structure function previously estimated from the backscattered data. Fitting a polydisperse structure function model to the histologically estimated structure function yielded relatively accurate cell radius estimates ([Formula: see text]). Furthermore, two types of mouse tumors that have similar cell size and shape but distinct cell spatial distributions were studied, where the backscattered data were shown to be related to the cell spatial distribution through the structure function estimated from histology. In conclusion, the agreement between acoustically estimated and histologically estimated structure functions suggests that the acoustically estimated structure function is related to the scatterer spatial distribution.
Pribram-Jones, Aurora
Warm dense matter (WDM) is a high energy phase between solids and plasmas, with characteristics of both. It is present in the centers of giant planets, within the earth's core, and on the path to ignition of inertial confinement fusion. The high temperatures and pressures of warm dense matter lead to complications in its simulation, as both classical and quantum effects must be included. One of the most successful simulation methods is density functional theory-molecular dynamics (DFT-MD). Despite great success in a diverse array of applications, DFT-MD remains computationally expensive and it neglects the explicit temperature dependence of electron-electron interactions known to exist within exact DFT. Finite-temperature density functional theory (FT DFT) is an extension of the wildly successful ground-state DFT formalism via thermal ensembles, broadening its quantum mechanical treatment of electrons to include systems at non-zero temperatures. Exact mathematical conditions have been used to predict the behavior of approximations in limiting conditions and to connect FT DFT to the ground-state theory. An introduction to FT DFT is given within the context of ensemble DFT and the larger field of DFT is discussed for context. Ensemble DFT is used to describe ensembles of ground-state and excited systems. Exact conditions in ensemble DFT and the performance of approximations depend on ensemble weights. Using an inversion method, exact Kohn-Sham ensemble potentials are found and compared to approximations. The symmetry eigenstate Hartree-exchange approximation is in good agreement with exact calculations because of its inclusion of an ensemble derivative discontinuity. Since ensemble weights in FT DFT are temperature-dependent Fermi weights, this insight may help develop approximations well-suited to both ground-state and FT DFT. A novel, highly efficient approach to free energy calculations, finite-temperature potential functional theory, is derived, which has the
General degeneracy in density functional perturbation theory
Palenik, Mark C
2016-01-01
Degenerate perturbation theory from quantum mechanics is inadequate in density functional theory (DFT) because of nonlinearity in the Kohn-Sham potential. We develop the fully general degenerate perturbation theory for DFT without assuming that the degeneracy is required by symmetry. The resulting methodology is applied to the iron atom ground state in order to demonstrate the effects of degeneracy that appears both due to symmetry requirements and accidentally, between different representations of the symmetry group.
Computing dispersion interactions in density functional theory
Cooper, V. R.; Kong, L.; Langreth, D. C.
2010-02-01
In this article techniques for including dispersion interactions within density functional theory are examined. In particular comparisons are made between four popular methods: dispersion corrected DFT, pseudopotential correction schemes, symmetry adapted perturbation theory, and a non-local density functional - the so called Rutgers-Chalmers van der Waals density functional (vdW-DF). The S22 benchmark data set is used to evaluate the relative accuracy of these methods and factors such as scalability and transferability are also discussed. We demonstrate that vdW-DF presents an excellent compromise between computational speed and accuracy and lends most easily to full scale application in solid materials. This claim is supported through a brief discussion of a recent large scale application to H2 in a prototype metal organic framework material (MOF), Zn2BDC2TED. The vdW-DF shows overwhelming promise for first-principles studies of physisorbed molecules in porous extended systems; thereby having broad applicability for studies as diverse as molecular adsorption and storage, battery technology, catalysis and gas separations.
A method for density estimation based on expectation identities
Peralta, Joaquín; Loyola, Claudia; Loguercio, Humberto; Davis, Sergio
2017-06-01
We present a simple and direct method for non-parametric estimation of a one-dimensional probability density, based on the application of the recent conjugate variables theorem. The method expands the logarithm of the probability density ln P(x|I) in terms of a complete basis and numerically solves for the coefficients of the expansion using a linear system of equations. No Monte Carlo sampling is needed. We present preliminary results that show the practical usefulness of the method for modeling statistical data.
Unbiased estimators for spatial distribution functions of classical fluids.
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 rho(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.
KDE-Track: An Efficient Dynamic Density Estimator for Data Streams
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.
Photo-z Estimation: An Example of Nonparametric Conditional Density Estimation under Selection Bias
Izbicki, Rafael; Freeman, Peter E
2016-01-01
Redshift is a key quantity for inferring cosmological model parameters. In photometric redshift estimation, cosmologists use the coarse data collected from the vast majority of galaxies to predict the redshift of individual galaxies. To properly quantify the uncertainty in the predictions, however, one needs to go beyond standard regression and instead estimate the full conditional density f(z|x) of a galaxy's redshift z given its photometric covariates x. The problem is further complicated by selection bias: usually only the rarest and brightest galaxies have known redshifts, and these galaxies have characteristics and measured covariates that do not necessarily match those of more numerous and dimmer galaxies of unknown redshift. Unfortunately, there is not much research on how to best estimate complex multivariate densities in such settings. Here we describe a general framework for properly constructing and assessing nonparametric conditional density estimators under selection bias, and for combining two o...
Extended screened exchange functional derived from transcorrelated density functional theory
Umezawa, Naoto
2017-09-01
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, HTC, is introduced by a similarity transformation of a many-body Hamiltonian, H , with respect to a complex function F: HTC=1/F H F . It is proved that an expectation value of HTC for a normalized single Slater determinant, Dn, corresponds to the total energy: E [n ] = ⟨Ψn|H |Ψn ⟩ /⟨Ψn|Ψn ⟩ = ⟨Dn|HTC|Dn ⟩ under the two assumptions: (1) The electron density n (r ) associated with a trial wave function Ψn = DnF is v -representable and (2) Ψn and Dn give rise to the same electron density n (r ). 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.
Large Scale Density Estimation of Blue and Fin Whales (LSD)
2014-09-30
interactions with human activity requires knowledge of how many animals are present in an area during a specific time period. Many marine mammal species ...Ocean at Wake Island will then be applied to the same species in the Indian Ocean at the CTBTO location at Diego Garcia. 1. Develop and implement...proposed density estimation method is also highly dependent on call rate inputs, which are used in the development of species specific multipliers for
Some Bayesian statistical techniques useful in estimating frequency and density
Johnson, D.H.
1977-01-01
This paper presents some elementary applications of Bayesian statistics to problems faced by wildlife biologists. Bayesian confidence limits for frequency of occurrence are shown to be generally superior to classical confidence limits. Population density can be estimated from frequency data if the species is sparsely distributed relative to the size of the sample plot. For other situations, limits are developed based on the normal distribution and prior knowledge that the density is non-negative, which insures that the lower confidence limit is non-negative. Conditions are described under which Bayesian confidence limits are superior to those calculated with classical methods; examples are also given on how prior knowledge of the density can be used to sharpen inferences drawn from a new sample.
Covariance and correlation estimation in electron-density maps.
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.
Density Functional Theory An Advanced Course
Dreizler, Reiner M
2011-01-01
Density Functional Theory (DFT) has firmly established itself as the workhorse for the atomic-level simulation of condensed matter phases, pure or composite materials and quantum chemical systems. The present book is a rigorous and detailed introduction to the foundations up to and including such advanced topics as orbital-dependent functionals and both time-dependent and relativistic DFT. Given the many ramifications of contemporary DFT, this text concentrates on the self-contained presentation of the basics of the most widely used DFT variants. This implies a thorough discussion of the corresponding existence theorems and effective single particle equations, as well as of key approximations utilized in implementations. The formal results are complemented by selected quantitative results, which primarily aim at illustrating strengths and weaknesses of a particular approach or functional. DFT for superconducting or nuclear and hadronic systems are not addressed in this work. The structure and material contain...
Estimating Stochastic Volatility Models using Prediction-based Estimating Functions
DEFF Research Database (Denmark)
Lunde, Asger; Brix, Anne Floor
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 the p......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 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...
Autoregressive Spectral Estimation and Functional Inference.
1982-06-01
spectral density function . Note that F(O) - 0, F(l) = 1, and (15) F(w) = f(w’) dw’, O<w<l...correlation function p(v) is summable, and its spectral density function f(w) is bounded above and below in the sense that the dynamic range of f(w) (2) DR...l The AR(-n) and MA(-) representations have important implications for spectral 6 analysis since they provide formulas for the spectral density function
Covariant density functional theory for nuclear matter
Energy Technology Data Exchange (ETDEWEB)
Badarch, U.
2007-07-01
The present thesis is organized as follows. In Chapter 2 we study the Nucleon-Nucleon (NN) interaction in Dirac-Brueckner (DB) approach. We start by considering the NN interaction in free-space in terms of the Bethe-Salpeter (BS) equation to the meson exchange potential model. Then we present the DB approach for nuclear matter by extending the BS equation for the in-medium NN interaction. From the solution of the three-dimensional in-medium BS equation, we derive the DB self-energies and total binding energy which are the main results of the DB approach, which we later incorporate in the field theoretical calculation of the nuclear equation of state. In Chapter 3, we introduce the basic concepts of density functional theory in the context of Quantum Hadrodynamics (QHD-I). We reach the main point of this work in Chapter 4 where we introduce the DDRH approach. In the DDRH theory, the medium dependence of the meson-nucleon vertices is expressed as functionals of the baryon field operators. Because of the complexities of the operator-valued functionals we decide to use the mean-field approximation. In Chapter 5, we contrast microscopic and phenomenological approaches to extracting density dependent meson-baryon vertices. Chapter 6 gives the results of our studies of the EOS of infinite nuclear matter in detail. Using formulas derived in Chapters 4 and 5 we calculate the properties of symmetric and asymmetric nuclear matter and pure neutron matter. (orig.)
Density Functional Approach Based on Numerically Obtained Bridge Functional
Institute of Scientific and Technical Information of China (English)
ZHOUShi－Qi
2002-01-01
The ornstein-zenike equation is solved with the Rogers-Young approximation for bulk hard sphere fluid and Lennard-Jones fluid for several state points.Then the resulted bulk fluid radial distribution function combined with the test particle method is employed to determine numerically the function relationship of bridge functional as a function of indirect correlation function.It is found that all of the calculated points from different phase space state points for a same type of fluid collapse onto a same smooth curve.Then the numerically obtained curve is used to substitute the analytic expression of the bridge functional as a function of indirect correlation function required in the methodology [J.Chem.Phys,112(2000)8079] to determine the density distribution of non-uniform hard sphere fluid and Lennard-Jones fluid.The good agreement of theoretical predictions with the computer simulation data is obtained.The present numerical procedure incroporates the knowledge of bulk fluid radial distribution function into the constructing of the density functional approximation and makes the original methodology more accurate and more filexible for various interaction potential fluid.
Insight and progress in density functional theory
Yang, Weitao; Mori-Sanchez, Paula; Cohen, Aron J.
2012-12-01
Density functional theory of electronic structure is widely and successfully applied in simulations throughout engineering and sciences. However, there are spectacular failures for many predicted properties. The errors include underestimation of the barriers of chemical reactions, the band gaps of materials, the energies of dissociating molecular ions and charge transfer excitation energies. Typical DFT calculations also fail to describe degenerate or near degenerate systems, as arise in the breaking of chemical bonds, and strongly correlated materials. These errors can all be characterized and understood through the perspective of fractional charges and fractional spins introduced recently.
Density functional and neural network analysis
DEFF Research Database (Denmark)
Jalkanen, K. J.; 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...... dichroism (VCD) intensities. The large changes due to hydration on the structures, relative stability of conformers, and in the VA and VCD spectra observed experimentally are reproduced by the DFT calculations. Furthermore a neural network was constructed for reproducing the inverse scattering data (infer...
Modulation Based on Probability Density Functions
Williams, Glenn L.
2009-01-01
A proposed method of modulating a sinusoidal carrier signal to convey digital information involves the use of histograms representing probability density functions (PDFs) that characterize samples of the signal waveform. The method is based partly on the observation that when a waveform is sampled (whether by analog or digital means) over a time interval at least as long as one half cycle of the waveform, the samples can be sorted by frequency of occurrence, thereby constructing a histogram representing a PDF of the waveform during that time interval.
Energy Technology Data Exchange (ETDEWEB)
Mattsson, Ann Elisabet; Modine, Normand Arthur; Desjarlais, Michael Paul; Muller, Richard Partain; Sears, Mark P.; Wright, Alan Francis
2006-11-01
A finite temperature version of 'exact-exchange' density functional theory (EXX) has been implemented in Sandia's Socorro code. The method uses the optimized effective potential (OEP) formalism and an efficient gradient-based iterative minimization of the energy. The derivation of the gradient is based on the density matrix, simplifying the extension to finite temperatures. A stand-alone all-electron exact-exchange capability has been developed for testing exact exchange and compatible correlation functionals on small systems. Calculations of eigenvalues for the helium atom, beryllium atom, and the hydrogen molecule are reported, showing excellent agreement with highly converged quantumMonte Carlo calculations. Several approaches to the generation of pseudopotentials for use in EXX calculations have been examined and are discussed. The difficult problem of finding a correlation functional compatible with EXX has been studied and some initial findings are reported.
Energy Technology Data Exchange (ETDEWEB)
Oesch, P. A.; Illingworth, G. D.; Magee, D. [UCO/Lick Observatory, University of California, Santa Cruz, 1156 High St, Santa Cruz, CA 95064 (United States); Bouwens, R. J.; Labbé, I.; Smit, R.; Franx, M. [Leiden Observatory, Leiden University, NL-2300 RA Leiden (Netherlands); Van Dokkum, P. G.; Momcheva, I. [Yale Center for Astronomy and Astrophysics, Yale University, New Haven, CT 06520 (United States); Ashby, M. L. N.; Fazio, G. G.; Huang, J.-S.; Willner, S. P. [Harvard-Smithsonian Center for Astrophysics, Cambridge, MA (United States); Gonzalez, V. [University of California, Riverside, 900 University Ave, Riverside, CA 92507 (United States); Trenti, M. [Institute of Astronomy and Kavli Institute for Cosmology, University of Cambridge, Cambridge CB3 0HA (United Kingdom); Brammer, G. B. [Space Telescope Science Institute, 3700 San Martin Drive, Baltimore, MD 21218 (United States); Skelton, R. E. [South African Astronomical Observatory, P.O. Box 9, Observatory 7935 (South Africa); Spitler, L. R., E-mail: pascal.oesch@yale.edu [Department of Physics and Astronomy, Faculty of Sciences, Macquarie University, Sydney, NSW 2109 (Australia)
2014-05-10
We present the discovery of four surprisingly bright (H {sub 160} ∼ 26-27 mag AB) galaxy candidates at z ∼ 9-10 in the complete HST CANDELS WFC3/IR GOODS-N imaging data, doubling the number of z ∼ 10 galaxy candidates that are known, just ∼500 Myr after the big bang. Two similarly bright sources are also detected in a reanalysis of the GOODS-S data set. Three of the four galaxies in GOODS-N are significantly detected at 4.5σ-6.2σ in the very deep Spitzer/IRAC 4.5 μm data, as is one of the GOODS-S candidates. Furthermore, the brightest of our candidates (at z = 10.2 ± 0.4) is robustly detected also at 3.6 μm (6.9σ), revealing a flat UV spectral energy distribution with a slope β = –2.0 ± 0.2, consistent with demonstrated trends with luminosity at high redshift. Thorough testing and use of grism data excludes known low-redshift contamination at high significance, including single emission-line sources, but as-yet unknown low redshift sources could provide an alternative solution given the surprising luminosity of these candidates. Finding such bright galaxies at z ∼ 9-10 suggests that the luminosity function for luminous galaxies might evolve in a complex way at z > 8. The cosmic star formation rate density still shows, however, an order-of-magnitude increase from z ∼ 10 to z ∼ 8 since the dominant contribution comes from low-luminosity sources. Based on the IRAC detections, we derive galaxy stellar masses at z ∼ 10, finding that these luminous objects are typically 10{sup 9} M {sub ☉}. This allows for a first estimate of the cosmic stellar mass density at z ∼ 10 resulting in log{sub 10} ρ{sub ∗}=4.7{sub −0.8}{sup +0.5} M {sub ☉} Mpc{sup –3} for galaxies brighter than M {sub UV} ∼ –18. The remarkable brightness, and hence luminosity, of these z ∼ 9-10 candidates will enable deep spectroscopy to determine their redshift and nature, and highlights the opportunity for the James Webb Space Telescope to map the buildup of
Density Functional Approach Based on Numerically Obtained Bridge Functional
Institute of Scientific and Technical Information of China (English)
ZHOU Shi-Qi
2002-01-01
The Ornstein Zernike equation is solved with the Rogers Young approximation for bulk hard sphere fluidand Lennard-Jones fluid for several state points. Then the resulted bulk fluid radial distribution function combinedwith the test particle method is employed to determine numerically the function relationship of bridge functional as afunction of indirect correlation function. It is found that all of the calculated points from different phase space statepoints for a same type of fluid collapse onto a same smooth curve. Then the numerically obtained curve is used tosubstitute the analytic expression of the bridge functional as a function of indirect correlation function required in themethodology [J. Chem. Phys. 112 (2000) 8079] to deterrnine the density distribution of non-uniform hard spherefluid and Lennard Jones fluid. The good agreement of theoretical predictions with the computer simulation data isobtained. The present numerical procedure incorporates the knowledge of bulk fluid radial distribution function intothe constructing of the density functional approximation and makes the original methodology more accurate and moreflexible for various interaction potential fluid.
Numerical density-to-potential inversions in time-dependent density functional theory.
Jensen, Daniel S; Wasserman, Adam
2016-08-01
We treat the density-to-potential inverse problem of time-dependent density functional theory as an optimization problem with a partial differential equation constraint. The unknown potential is recovered from a target density by applying a multilevel optimization method controlled by error estimates. We employ a classical optimization routine using gradients efficiently computed by the discrete adjoint method. The inverted potential has both a real and imaginary part to reduce reflections at the boundaries and other numerical artifacts. We demonstrate this method on model one-dimensional systems. The method can be straightforwardly extended to a variety of numerical solvers of the time-dependent Kohn-Sham equations and to systems in higher dimensions.
Interpretation of van der Waal density functionals
Hyldgaard, Per; Schröder, Elsebeth
2014-01-01
The nonlocal correlation energy in the van der Waals density functional (vdW-DF) method [Phys. Rev. Lett. 92, 246401 (2004); Phys. Rev. B 76, 125112 (2007); Phys. Rev. B 89, 035412 (2014)] can be interpreted in terms of a coupling of zero-point energies of characteristic modes of semilocal exchange-correlation (xc) holes. These xc holes reflect the internal functional in the framework of the vdW-DF method [Phys. Rev. B 82, 081101(2010)]. We explore the internal xc hole components, showing that they share properties with those of the generalized-gradient approximation. We use these results to illustrate the nonlocality in the vdW-DF description and analyze the vdW-DF formulation of nonlocal correlation.
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
Quantal density functional theory. 2. ed.
Energy Technology Data Exchange (ETDEWEB)
Sahni, Viraht
2016-07-01
This book is on quantal density functional theory (QDFT) which is a time-dependent local effective potential theory of the electronic structure of matter. The time-independent QDFT constitutes a special case. The 2{sup nd} edition describes the further development of the theory, and extends it to include the presence of an external magnetostatic field. The theory is based on the 'quantal Newtonian' second and first laws for the individual electron. These laws are in terms of 'classical' fields that pervade all space, and their quantal sources. The fields are separately representative of the electron correlations that must be accounted for in local potential theory. Recent developments show that irrespective of the type of external field the electrons are subject to, the only correlations beyond those due to the Pauli exclusion principle and Coulomb repulsion that need be considered are solely of the correlation-kinetic effects. Foundational to QDFT, the book describes Schroedinger theory from the new perspective of the single electron in terms of the 'quantal Newtonian' laws. Hohenberg-Kohn density functional theory (DFT), new understandings of the theory and its extension to the presence of an external uniform magnetostatic field are described. The physical interpretation via QDFT, in terms of electron correlations, of Kohn-Sham DFT, approximations to it and Slater theory are provided.
ks: Kernel Density Estimation and Kernel Discriminant Analysis for Multivariate Data in R
Directory of Open Access Journals (Sweden)
Tarn Duong
2007-09-01
Full Text Available Kernel smoothing is one of the most widely used non-parametric data smoothing techniques. We introduce a new R package ks for multivariate kernel smoothing. Currently it contains functionality for kernel density estimation and kernel discriminant analysis. It is a comprehensive package for bandwidth matrix selection, implementing a wide range of data-driven diagonal and unconstrained bandwidth selectors.
Universality principle and the development of classical density functional theory
Institute of Scientific and Technical Information of China (English)
周世琦; 张晓琪
2002-01-01
The universality principle of the free energy density functional and the ‘test particle' trick by Percus are combined to construct the approximate free energy density functional or its functional derivative. Information about the bulk fluid ralial distribution function is integrated into the density functional approximation directly for the first time in the present methodology. The physical foundation of the present methodology also applies to the quantum density functional theory.
A projection and density estimation method for knowledge discovery.
Stanski, Adam; Hellwich, Olaf
2012-01-01
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.
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.
Nitrogenase structure and function relationships by density functional theory.
Harris, Travis V; Szilagyi, Robert K
2011-01-01
Modern density functional theory has tremendous potential with matching popularity in metalloenzymology to reveal the unseen atomic and molecular details of structural data, spectroscopic measurements, and biochemical experiments by providing insights into unobservable structures and states, while also offering theoretical justifications for observed trends and differences. An often untapped potential of this theoretical approach is to bring together diverse experimental structural and reactivity information and allow for these to be critically evaluated at the same level. This is particularly applicable for the tantalizingly complex problem of the structure and molecular mechanism of biological nitrogen fixation. In this chapter we provide a review with extensive practical details of the compilation and evaluation of experimental data for an unbiased and systematic density functional theory analysis that can lead to remarkable new insights about the structure-function relationships of the iron-sulfur clusters of nitrogenase.
Effect of Random Clustering on Surface Damage Density Estimates
Energy Technology Data Exchange (ETDEWEB)
Matthews, M J; Feit, M D
2007-10-29
Identification and spatial registration of laser-induced damage relative to incident fluence profiles is often required to characterize the damage properties of laser optics near damage threshold. Of particular interest in inertial confinement laser systems are large aperture beam damage tests (>1cm{sup 2}) where the number of initiated damage sites for {phi}>14J/cm{sup 2} can approach 10{sup 5}-10{sup 6}, requiring automatic microscopy counting to locate and register individual damage sites. However, as was shown for the case of bacteria counting in biology decades ago, random overlapping or 'clumping' prevents accurate counting of Poisson-distributed objects at high densities, and must be accounted for if the underlying statistics are to be understood. In this work we analyze the effect of random clumping on damage initiation density estimates at fluences above damage threshold. The parameter {psi} = a{rho} = {rho}/{rho}{sub 0}, where a = 1/{rho}{sub 0} is the mean damage site area and {rho} is the mean number density, is used to characterize the onset of clumping, and approximations based on a simple model are used to derive an expression for clumped damage density vs. fluence and damage site size. The influence of the uncorrected {rho} vs. {phi} curve on damage initiation probability predictions is also discussed.
A Concept of Approximated Densities for Efficient Nonlinear Estimation
Directory of Open Access Journals (Sweden)
Virginie F. Ruiz
2002-10-01
Full Text Available This paper presents the theoretical development of a nonlinear adaptive filter based on a concept of filtering by approximated densities (FAD. The most common procedures for nonlinear estimation apply the extended Kalman filter. As opposed to conventional techniques, the proposed recursive algorithm does not require any linearisation. The prediction uses a maximum entropy principle subject to constraints. Thus, the densities created are of an exponential type and depend on a finite number of parameters. The filtering yields recursive equations involving these parameters. The update applies the Bayes theorem. Through simulation on a generic exponential model, the proposed nonlinear filter is implemented and the results prove to be superior to that of the extended Kalman filter and a class of nonlinear filters based on partitioning algorithms.
Estimation of probability densities using scale-free field theories.
Kinney, Justin B
2014-07-01
The question of how best to estimate a continuous probability density from finite data is an intriguing open problem at the interface of statistics and physics. Previous work has argued that this problem can be addressed in a natural way using methods from statistical field theory. Here I describe results that allow this field-theoretic approach to be rapidly and deterministically computed in low dimensions, making it practical for use in day-to-day data analysis. Importantly, this approach does not impose a privileged length scale for smoothness of the inferred probability density, but rather learns a natural length scale from the data due to the tradeoff between goodness of fit and an Occam factor. Open source software implementing this method in one and two dimensions is provided.
Royle, J. Andrew; Chandler, Richard B.; Gazenski, Kimberly D.; Graves, Tabitha A.
2013-01-01
Population size and landscape connectivity are key determinants of population viability, yet no methods exist for simultaneously estimating density and connectivity parameters. Recently developed spatial capture–recapture (SCR) models provide a framework for estimating density of animal populations but thus far have not been used to study connectivity. Rather, all applications of SCR models have used encounter probability models based on the Euclidean distance between traps and animal activity centers, which implies that home ranges are stationary, symmetric, and unaffected by landscape structure. In this paper we devise encounter probability models based on “ecological distance,” i.e., the least-cost path between traps and activity centers, which is a function of both Euclidean distance and animal movement behavior in resistant landscapes. We integrate least-cost path models into a likelihood-based estimation scheme for spatial capture–recapture models in order to estimate population density and parameters of the least-cost encounter probability model. Therefore, it is possible to make explicit inferences about animal density, distribution, and landscape connectivity as it relates to animal movement from standard capture–recapture data. Furthermore, a simulation study demonstrated that ignoring landscape connectivity can result in negatively biased density estimators under the naive SCR model.
Chemistry by Way of Density Functional Theory
Bauschlicher, Charles W., Jr.; Ricca, Alessandra; Partridge, Harry; Langohff, Stephen R.; Arnold, James O. (Technical Monitor)
1996-01-01
In this work we demonstrate that density functional theory (DFT) methods make an important contribution to understanding chemical systems and are an important additional method for the computational chemist. We report calibration calculations obtained with different functionals for the 55 G2 molecules to justify our selection of the B3LYP functional. We show that accurate geometries and vibrational frequencies obtained at the B3LYP level can be combined with traditional methods to simplify the calculation of accurate heats of formation. We illustrate the application of the B3LYP approach to a variety of chemical problems from the vibrational frequencies of polycyclic aromatic hydrocarbons to transition metal systems. We show that the B3LYP method typically performs better than the MP2 method at a significantly lower computational cost. Thus the B3LYP method allows us to extend our studies to much larger systems while maintaining a high degree of accuracy. We show that for transition metal systems, the B3LYP bond energies are typically of sufficient accuracy that they can be used to explain experimental trends and even differentiate between different experimental values. We show that for boron clusters the B3LYP energetics are not as good as for many of the other systems presented, but even in this case the B3LYP approach is able to help understand the experimental trends.
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.
General degeneracy in density functional perturbation theory
Palenik, Mark C.; Dunlap, Brett I.
2017-07-01
Degenerate perturbation theory from quantum mechanics is inadequate in density functional theory (DFT) because of nonlinearity in the Kohn-Sham potential. Herein, we develop the fully general perturbation theory for open-shell, degenerate systems in Kohn-Sham DFT, without assuming the presence of symmetry or equal occupation of degenerate orbitals. To demonstrate the resulting methodology, we apply it to the iron atom in the central field approximation, perturbed by an electric quadrupole. This system was chosen because it displays both symmetry required degeneracy, between the five 3 d orbitals, as well as accidental degeneracy, between the 3 d and 4 s orbitals. The quadrupole potential couples the degenerate 3 d and 4 s states, serving as an example of the most general perturbation.
Phases of Polonium via Density Functional Theory
Verstraete, Matthieu J.
2010-01-01
The thermodynamical properties of the main phases of metallic polonium are examined using density functional theory. The exceptional nature of the solid-solid phase transition of α to β Po is underlined: it induces a lowering in symmetry, from cubic to rhombohedral, with increasing temperature. This is explained as the result of a delicate balance between bonding and entropic effects. Overall agreement with existing experimental data is good by state-of-the-art standards. The phonons of Po present Kohn anomalies, and it is shown that the effect of spin-orbit interactions is the inverse of that in normal metals: due to the nonspherical nature of the Fermi Surface, spin-orbit effects reduce nesting and harden most phonon frequencies.
Effective potential in density matrix functional theory.
Nagy, A; Amovilli, C
2004-10-01
In the previous paper it was shown that in the ground state the diagonal of the spin independent second-order density matrix n can be determined by solving a single auxiliary equation of a two-particle problem. Thus the problem of an arbitrary system with even electrons can be reduced to a two-particle problem. The effective potential of the two-particle equation contains a term v(p) of completely kinetic origin. Virial theorem and hierarchy of equations are derived for v(p) and simple approximations are proposed. A relationship between the effective potential u(p) of the shape function equation and the potential v(p) is established.
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 pointed...... out, and methods to prevent bias are presented. The techniques are evaluated by comparing their speed and accuracy on the simple case of estimating auto-correlation functions for the response of a single degree-of-freedom system loaded with white noise....
Institute of Scientific and Technical Information of China (English)
XUE Yun-feng; WANG Yu-jia; YANG Jie
2009-01-01
A new algorithm for linear instantaneous independent component analysis is proposed based on max-imizing the log-likelihood contrast function which can be changed into a gradient equation. An iterative method is introduced to solve this equation efficiently. The unknown probability density functions as well as their first and second derivatives in the gradient equation are estimated by kernel density method. Computer simulations on artificially generated signals and gray scale natural scene images confirm the efficiency and accuracy of the proposed algorithm.
Estimating purity in terms of correlation functions
Prosen, T; Znidaric, M; Prosen, Tomaz; Seligman, Thomas H.; Znidaric, Marko
2003-01-01
We prove a rigorous inequality estimating the purity of a reduced density matrix of a composite quantum system in terms of cross-correlation of the same state and an arbitrary product state. Various immediate applications of our result are proposed, in particular concerning Gaussian wave-packet propagation under classically regular dynamics.
Receiver function estimated by maximum entropy deconvolution
Institute of Scientific and Technical Information of China (English)
吴庆举; 田小波; 张乃铃; 李卫平; 曾融生
2003-01-01
Maximum entropy deconvolution is presented to estimate receiver function, with the maximum entropy as the rule to determine auto-correlation and cross-correlation functions. The Toeplitz equation and Levinson algorithm are used to calculate the iterative formula of error-predicting filter, and receiver function is then estimated. During extrapolation, reflective coefficient is always less than 1, which keeps maximum entropy deconvolution stable. The maximum entropy of the data outside window increases the resolution of receiver function. Both synthetic and real seismograms show that maximum entropy deconvolution is an effective method to measure receiver function in time-domain.
Building a Universal Nuclear Energy Density Functional
Energy Technology Data Exchange (ETDEWEB)
Carlson, Joe A. [Michigan State Univ., East Lansing, MI (United States); Furnstahl, Dick; Horoi, Mihai; Lust, Rusty; Nazaewicc, Witek; Ng, Esmond; Thompson, Ian; Vary, James
2012-12-30
During the period of Dec. 1 2006 – Jun. 30, 2012, the UNEDF collaboration carried out a comprehensive study of all nuclei, based on the most accurate knowledge of the strong nuclear interaction, the most reliable theoretical approaches, the most advanced algorithms, and extensive computational resources, with a view towards scaling to the petaflop platforms and beyond. The long-term vision initiated with UNEDF is to arrive at a comprehensive, quantitative, and unified description of nuclei and their reactions, grounded in the fundamental interactions between the constituent nucleons. We seek to replace current phenomenological models of nuclear structure and reactions with a well-founded microscopic theory that delivers maximum predictive power with well-quantified uncertainties. Specifically, the mission of this project has been three-fold: First, to find an optimal energy density functional (EDF) using all our knowledge of the nucleonic Hamiltonian and basic nuclear properties; Second, to apply the EDF theory and its extensions to validate the functional using all the available relevant nuclear structure and reaction data; Third, to apply the validated theory to properties of interest that cannot be measured, in particular the properties needed for reaction theory.
Building a Universal Nuclear Energy Density Functional
Energy Technology Data Exchange (ETDEWEB)
Carlson, Joe A. [Michigan State University; Furnstahl, Dick; Horoi, Mihai; Lust, Rusty; Nazaewicc, Witek; Ng, Esmond; Thompson, Ian; Vary, James
2012-12-30
During the period of Dec. 1 2006 – Jun. 30, 2012, the UNEDF collaboration carried out a comprehensive study of all nuclei, based on the most accurate knowledge of the strong nuclear interaction, the most reliable theoretical approaches, the most advanced algorithms, and extensive computational resources, with a view towards scaling to the petaflop platforms and beyond. The long-term vision initiated with UNEDF is to arrive at a comprehensive, quantitative, and unified description of nuclei and their reactions, grounded in the fundamental interactions between the constituent nucleons. We seek to replace current phenomenological models of nuclear structure and reactions with a well-founded microscopic theory that delivers maximum predictive power with well-quantified uncertainties. Specifically, the mission of this project has been three-fold: First, to find an optimal energy density functional (EDF) using all our knowledge of the nucleonic Hamiltonian and basic nuclear properties; Second, to apply the EDF theory and its extensions to validate the functional using all the available relevant nuclear structure and reaction data; Third, to apply the validated theory to properties of interest that cannot be measured, in particular the properties needed for reaction theory.
Inference-less Density Estimation using Copula Bayesian Networks
Elidan, Gal
2012-01-01
We consider learning continuous probabilistic graphical models in the face of missing data. For non-Gaussian models, learning the parameters and structure of such models depends on our ability to perform efficient inference, and can be prohibitive even for relatively modest domains. Recently, we introduced the Copula Bayesian Network (CBN) density model - a flexible framework that captures complex high-dimensional dependency structures while offering direct control over the univariate marginals, leading to improved generalization. In this work we show that the CBN model also offers significant computational advantages when training data is partially observed. Concretely, we leverage on the specialized form of the model to derive a computationally amenable learning objective that is a lower bound on the log-likelihood function. Importantly, our energy-like bound circumvents the need for costly inference of an auxiliary distribution, thus facilitating practical learning of highdimensional densities. We demonstr...
Density functional calculations on hydrocarbon isodesmic reactions
Fortunelli, Alessandro; Selmi, Massimo
1994-06-01
Hartree—Fock, Hartree—Fock-plus-correlation and self-consistent Kohn—Sham calculations are performed on a set of hydrocarbon isodesmic reactions, i.e. reactions among hydrocarbons in which the number and type of carbon—carbon and carbon—hydrogen bonds is conserved. It is found that neither Hartree—Fock nor Kohn—Sham methods correctly predict standard enthalpies, Δ Hr(298 K), of these reactions, even though — for reactions involving molecules containing strained double bonds — the agreement between the theoretical estimates and the experimental values of Δ Hr seems to be improved by the self-consistent solution of the Kohn—Sham equations. The remaining discrepancies are attributed to intramolecular dispersion effects, that are not described by ordinary exchange—correlation functionals, and are eliminated by introducing corrections based on a simple semi-empirical model.
LSTA, Rawane Samb
2010-01-01
This thesis deals with the nonparametric estimation of density f of the regression error term E of the model Y=m(X)+E, assuming its independence with the covariate X. The difficulty linked to this study is the fact that the regression error E is not observed. In a such setup, it would be unwise, for estimating f, to use a conditional approach based upon the probability distribution function of Y given X. Indeed, this approach is affected by the curse of dimensionality, so that the resulting estimator of the residual term E would have considerably a slow rate of convergence if the dimension of X is very high. Two approaches are proposed in this thesis to avoid the curse of dimensionality. The first approach uses the estimated residuals, while the second integrates a nonparametric conditional density estimator of Y given X. If proceeding so can circumvent the curse of dimensionality, a challenging issue is to evaluate the impact of the estimated residuals on the final estimator of the density f. We will also at...
Change-in-ratio density estimator for feral pigs is less biased than closed mark-recapture estimates
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.
Reduced density-matrix functionals from many-particle theory
Schade, Robert; Kamil, Ebad; Blöchl, Peter
2017-07-01
In materials with strong electron correlation the proper treatment of local atomic physics described by orbital occupations is crucial. Reduced density-matrix functional theory is a natural extension of density functional theory for systems that are dominated by orbital physics. We review the current state of reduced density-matrix functional theory (RDMFT). For atomic structure relaxations or ab-initio molecular dynamics the combination of density functional theory (DFT) and dynamical mean-field theory (DMFT) possesses a number of disadvantages, like the cumbersome evaluation of forces. We therefore describe a method, DFT+RDMFT, that combines many-particle effects based on reduced density-matrix functional theory with a density functional-like framework. A recent development is the construction of density-matrix functionals directly from many-particle theory such as methods from quantum chemistry or many-particle Green's functions. We present the underlying exact theorems and describe current progress towards quantitative functionals.
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
Linear parameter estimation of rational biokinetic functions
Doeswijk, T.G.; Keesman, K.J.
2009-01-01
For rational biokinetic functions such as the Michaelis-Menten equation, in general, a nonlinear least-squares method is a good estimator. However, a major drawback of a nonlinear least-squares estimator is that it can end up in a local minimum. Rearranging and linearizing rational biokinetic
Efficient Estimating Functions for Stochastic Differential Equations
DEFF Research Database (Denmark)
Jakobsen, Nina Munkholt
The overall topic of this thesis is approximate martingale estimating function-based estimationfor solutions of stochastic differential equations, sampled at high frequency. Focuslies on the asymptotic properties of the estimators. The first part of the thesis deals with diffusions observed over...
2015-09-30
1 DISTRIBUTION STATEMENT A. Approved for public release; distribution is unlimited. Large Scale Density Estimation of Blue and Fin Whales ...Utilizing Sparse Array Data to Develop and Implement a New Method for Estimating Blue and Fin Whale Density Len Thomas & Danielle Harris Centre...to develop and implement a new method for estimating blue and fin whale density that is effective over large spatial scales and is designed to cope
An Adaptive Background Subtraction Method Based on Kernel Density Estimation
Directory of Open Access Journals (Sweden)
Mignon Park
2012-09-01
Full Text Available In this paper, a pixel-based background modeling method, which uses nonparametric kernel density estimation, is proposed. To reduce the burden of image storage, we modify the original KDE method by using the first frame to initialize it and update it subsequently at every frame by controlling the learning rate according to the situations. We apply an adaptive threshold method based on image changes to effectively subtract the dynamic backgrounds. The devised scheme allows the proposed method to automatically adapt to various environments and effectively extract the foreground. The method presented here exhibits good performance and is suitable for dynamic background environments. The algorithm is tested on various video sequences and compared with other state-of-the-art background subtraction methods so as to verify its performance.
Application of Kernel Density Estimation in Lamb Wave-Based Damage Detection
Directory of Open Access Journals (Sweden)
Long Yu
2012-01-01
Full Text Available The present work concerns the estimation of the probability density function (p.d.f. of measured data in the Lamb wave-based damage detection. Although there was a number of research work which focused on the consensus algorithm of combining all the results of individual sensors, the p.d.f. of measured data, which was the fundamental part of the probability-based method, was still given by experience in existing work. Based on the analysis about the noise-induced errors in measured data, it was learned that the type of distribution was related with the level of noise. In the case of weak noise, the p.d.f. of measured data could be considered as the normal distribution. The empirical methods could give satisfied estimating results. However, in the case of strong noise, the p.d.f. was complex and did not belong to any type of common distribution function. Nonparametric methods, therefore, were needed. As the most popular nonparametric method, kernel density estimation was introduced. In order to demonstrate the performance of the kernel density estimation methods, a numerical model was built to generate the signals of Lamb waves. Three levels of white Gaussian noise were intentionally added into the simulated signals. The estimation results showed that the nonparametric methods outperformed the empirical methods in terms of accuracy.
Revisiting the Fermi Surface in Density Functional Theory
Das, Mukunda P.; Green, Frederick
2016-06-01
The Fermi surface is an abstract object in the reciprocal space of a crystal lattice, enclosing the set of all those electronic band states that are filled according to the Pauli principle. Its topology is dictated by the underlying lattice structure and its volume is the carrier density in the material. The Fermi surface is central to predictions of thermal, electrical, magnetic, optical and superconducting properties in metallic systems. Density functional theory is a first-principles method used to estimate the occupied-band energies and, in particular, the isoenergetic Fermi surface. In this review we survey several key facts about Fermi surfaces in complex systems, where a proper theoretical understanding is still lacking. We address some critical difficulties.
Density functional theory in the solid state.
Hasnip, Philip J; Refson, Keith; Probert, Matt I J; Yates, Jonathan R; Clark, Stewart J; Pickard, Chris J
2014-03-13
Density functional theory (DFT) has been used in many fields of the physical sciences, but none so successfully as in the solid state. From its origins in condensed matter physics, it has expanded into materials science, high-pressure physics and mineralogy, solid-state chemistry and more, powering entire computational subdisciplines. Modern DFT simulation codes can calculate a vast range of structural, chemical, optical, spectroscopic, elastic, vibrational and thermodynamic phenomena. The ability to predict structure-property relationships has revolutionized experimental fields, such as vibrational and solid-state NMR spectroscopy, where it is the primary method to analyse and interpret experimental spectra. In semiconductor physics, great progress has been made in the electronic structure of bulk and defect states despite the severe challenges presented by the description of excited states. Studies are no longer restricted to known crystallographic structures. DFT is increasingly used as an exploratory tool for materials discovery and computational experiments, culminating in ex nihilo crystal structure prediction, which addresses the long-standing difficult problem of how to predict crystal structure polymorphs from nothing but a specified chemical composition. We present an overview of the capabilities of solid-state DFT simulations in all of these topics, illustrated with recent examples using the CASTEP computer program.
Combining Molecular Dynamics and Density Functional Theory
Kaxiras, Efthimios
2015-03-01
The time evolution of a system consisting of electrons and ions is often treated in the Born-Oppenheimer approximation, with electrons in their instantaneous ground state. This approach cannot capture many interesting processes that involved excitation of electrons and its effects on the coupled electron-ion dynamics. The time scale needed to accurately resolve the evolution of electron dynamics is atto-seconds. This poses a challenge to the simulation of important chemical processes that typically take place on time scales of pico-seconds and beyond, such as reactions at surfaces and charge transport in macromolecules. We will present a methodology based on time-dependent density functional theory for electrons, and classical (Ehrenfest) dynamics for the ions, that successfully captures such processes. We will give a review of key features of the method and several applications. These illustrate how the atomic and electronic structure evolution unravels the elementary steps that constitute a chemical reaction. In collaboration with: G. Kolesov, D. Vinichenko, G. Tritsaris, C.M. Friend, Departments of Physics and of Chemistry and Chemical Biology.
Bone mineral density, adiposity and cognitive functions
Directory of Open Access Journals (Sweden)
Hamid R Sohrabi
2015-02-01
Full Text Available Cognitive decline and dementia due to Alzheimer’s disease have been associated with genetic, lifestyle, and environmental factors. A number of potentially modifiable risk factors should be taken into account when preventive or ameliorative interventions targeting dementia and its preclinical stages are investigated. Bone mineral density (BMD and body composition are two such potentially modifiable risk factors, and their association with cognitive decline was investigated in this study. 164 participants, aged 34 to 87 years old (62.78±9.27, were recruited for this longitudinal study and underwent cognitive and clinical examinations at baseline and after three years. Blood samples were collected for apolipoprotein E (APOE genotyping and dual energy x-ray absorptiometry (DXA was conducted at the same day as cognitive assessment. Using hierarchical regression analysis, we found that BMD and lean body mass, as measured using DXA were significant predictors of episodic memory. Age, gender, APOE status and premorbid IQ were controlled for. Specifically, the List A learning from California Verbal Learning Test was significantly associated with BMD and lean mass both at baseline and at follow up assessment. Our findings indicate that there is a significant association between BMD and lean body mass and episodic verbal learning. While the involvement of modifiable lifestyle factors in human cognitive function has been examined in different studies, there is a need for further research to understand the potential underlying mechanisms.
Institute of Scientific and Technical Information of China (English)
Zhou Shi-Qi
2007-01-01
A universal theoretical approach is proposed which enables all hard sphere density functional approximations(DFAs) applicable to van der Waals fluids. The resultant DFA obtained by combining the universal theoretical approach with any hard sphere DFAs only needs as input a second-order direct correlation function (DCF) of a coexistence bulk fluid, and is applicable in both supercritical and subcritical temperature regions. The associated effective hard sphere density can be specified by a hard wall sum rule. It is indicated that the value of the effective hard sphere density so determined can be universal, i.e. can be applied to any external potentials different from the single hard wall. As an illustrating example, the universal theoretical approach is combined with a hard sphere bridge DFA to predict the density profile of a hard core attractive Yukawa model fluid influenced by diverse external fields; agreement between the present formalism's predictions and the corresponding simulation data is good or at least comparable to several previous DFT approaches. The primary advantage of the present theoretical approach combined with other hard sphere DFAs is discussed.
Accounting for Endogeneity in Matching Function Estimation
DEFF Research Database (Denmark)
Borowczyk-Martins, Daniel; Jolivet, Grégory; Postel-Vinay, Fabien
2017-01-01
We show that equilibrium matching models imply that standard estimates of the matching function elasticities are exposed to an endogeneity bias, which arises from the search behavior of agents on either side of the market. We offer an estimation method which, under certain structural assumptions...... about the process driving shocks to matching efficiency, is immune from that bias. Application of our method to the estimation of a basic version of the matching function using aggregate U.S. data from the Job Openings and Labor Turnover Survey (JOLTS) suggests that the bias can be quantitatively...
Brorsen, Kurt R; Yang, Yang; Pak, Michael V; Hammes-Schiffer, Sharon
2017-05-04
The development of approximate exchange-correlation functionals is critical for modern density functional theory. A recent analysis of atomic systems suggested that some modern functionals are straying from the path toward the exact functional because electron densities are becoming less accurate while energies are becoming more accurate since the year 2000. To investigate this trend for more chemically relevant systems, the electron densities in the bonding regions and the atomization energies are analyzed for a series of diatomic molecules with 90 different functionals. For hybrid generalized gradient approximation functionals developed since the year 2000, the errors in densities and atomization energies are decoupled; the accuracy of the energies remains relatively consistent while the accuracy of the densities varies significantly. Such decoupling is not observed for generalized gradient and meta-generalized gradient approximation functionals. Analysis of electron densities in bonding regions is found to be important for the evaluation of functionals for chemical systems.
Wiener Filter Estimation of Transfer Functions
Kessel, Robert
2004-01-01
The use of a Wiener filter estimate for the linear transfer function can significantly improve the description of behavioral dynamics. This report presents a two-pass, Monte-Carlo-based algorithm that is well suited to repeated-trials local average measurements. The Wiener filter transfer functions strongly suppress noise artifacts as well as…
Estimation of Low-Rank Covariance Function
Koltchinskii, Vladimir; Lounici, Karim; Tsybakov, Alexander B.
2015-01-01
We consider the problem of estimating a low rank covariance function $K(t,u)$ of a Gaussian process $S(t), t\\in [0,1]$ based on $n$ i.i.d. copies of $S$ observed in a white noise. We suggest a new estimation procedure adapting simultaneously to the low rank structure and the smoothness of the covariance function. The new procedure is based on nuclear norm penalization and exhibits superior performances as compared to the sample covariance function by a polynomial factor in the sample size $n$...
El-Nahas, Ahmed M.; Simmie, John M.; Mangood, Ahmed H.; Hirao, Kimihiko; Song, Jong-Won; Watson, Mark A.; Taketsugu, Tetsuya; Koga, Nobuaki
2015-07-01
The enthalpies of formation for some selected oxygenates have been calculated by the atomisation energy approach using B3LYP, BHandHLYP, MPW3LYP, MPW1K, MPWB1K, BB1K, MPW1B95, BMK, and long-range corrected (LC-ωPBE, LC-BOP, LCgau-BOP, LC-BOP12, LCgau-B97) density functionals, as well as the composite CBS-QB3 method. Compared with experiment, BMK, LC-ωPBE, LCgau-BOP, LC-BOP12, LCgau-B97, MPW195, MPW3LYP functionals and CBS-QB3 give root mean square errors (RMSE) in enthalpies of formation no greater than 4 kcal/mol, whilst MPW1K and BHandHLYP show much worse performance (RMSE of 20-40 kcal/mol). The B3LYP, MPWB1K, and BB1K results fall between the two extremes. Energy barriers for the dominant paths in the unimolecular decomposition of simple esters (HCO2CH3, C2H5CO2C2H5), C1-C3 acids, and 1-butanol are reproduced well by CBS-QB3, BMK, BB1K, LCgau-B97, and PW1B95 (RMSE = 1-2 kcal/mol), while other LC methods (LC-ωPBE, LC-BOP, LCgau-BOP, and LC-BOP12) show a deviation of up to 4 kcal/mol. For the ionisation potentials, calculated from Koopman's theorem, all of the investigated LC-methods give good results compared with other density functional theory functionals with a maximum deviation of 0.4 eV, except for LCgau-B97, which has an RMSE of 0.7 eV.
2014-09-30
1 DISTRIBUTION STATEMENT A. Approved for public release; distribution is unlimited. Cheap DECAF: Density Estimation for Cetaceans from... cetaceans using passive fixed acoustics rely on large, dense arrays of cabled hydrophones and/or auxiliary information from animal tagging projects...estimating cetacean density. Therefore, the goal of Cheap DECAF is to focus on the development of cetacean density estimation methods using sensors that
Gao, Nuo; Zhu, S A; He, Bin
2005-06-01
We have developed a new algorithm for magnetic resonance electrical impedance tomography (MREIT), which uses only one component of the magnetic flux density to reconstruct the electrical conductivity distribution within the body. The radial basis function (RBF) network and simplex method are used in the present approach to estimate the conductivity distribution by minimizing the errors between the 'measured' and model-predicted magnetic flux densities. Computer simulations were conducted in a realistic-geometry head model to test the feasibility of the proposed approach. Single-variable and three-variable simulations were performed to estimate the brain-skull conductivity ratio and the conductivity values of the brain, skull and scalp layers. When SNR = 15 for magnetic flux density measurements with the target skull-to-brain conductivity ratio being 1/15, the relative error (RE) between the target and estimated conductivity was 0.0737 +/- 0.0746 in the single-variable simulations. In the three-variable simulations, the RE was 0.1676 +/- 0.0317. Effects of electrode position uncertainty were also assessed by computer simulations. The present promising results suggest the feasibility of estimating important conductivity values within the head from noninvasive magnetic flux density measurements.
Ions in solution: density corrected density functional theory (DC-DFT).
Kim, Min-Cheol; Sim, Eunji; Burke, Kieron
2014-05-14
Standard density functional approximations often give questionable results for odd-electron radical complexes, with the error typically attributed to self-interaction. In density corrected density functional theory (DC-DFT), certain classes of density functional theory calculations are significantly improved by using densities more accurate than the self-consistent densities. We discuss how to identify such cases, and how DC-DFT applies more generally. To illustrate, we calculate potential energy surfaces of HO·Cl(-) and HO·H2O complexes using various common approximate functionals, with and without this density correction. Commonly used approximations yield wrongly shaped surfaces and/or incorrect minima when calculated self consistently, while yielding almost identical shapes and minima when density corrected. This improvement is retained even in the presence of implicit solvent.
Ions in solution: Density Corrected Density Functional Theory (DC-DFT)
Kim, Min-Cheol; Burke, Kieron
2014-01-01
Standard density functional approximations often give questionable results for odd-electron radical complexes, with the error typically attributed to self-interaction. In density corrected density functional theory (DC-DFT), certain classes of density functional theory calculations are significantly improved by using densities more accurate than the self-consistent densities. We discuss how to identify such cases, and how DC-DFT applies more generally. To illustrate, we calculate potential energy surfaces of HO$\\cdot$Cl$^-$ and HO$\\cdot$H$_2$O complexes using various common approximate functionals, with and without this density correction. Commonly used approximations yield wrongly shaped surfaces and/or incorrect minima when calculated self consistently, while yielding almost identical shapes and minima when density corrected. This improvement is retained even in the presence of implicit solvent.
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...
Recursive Density Estimation of NA Samples%样本的递归密度估计
Institute of Scientific and Technical Information of China (English)
张冬霞; 梁汉营
2008-01-01
Let{Xn,n≥1} be a strictly stationary sequence of negatively associated random variables with the marginal probability density function f (x). In this paper, we discuss the point asymptotic normality for recursive kernel density estimator of f (x).%设{{Xn, n≥1}是一个严平稳的负相协的随机变量序列,其概率密谋函数为f(x).本文讨论了f(x)的递归核估计量的联合渐近正态性.
Estimating Function Approaches for Spatial Point Processes
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
Energy density functional for nuclei and neutron stars
Erler, J; Nazarewicz, W; Rafalski, M; Reinhard, P -G
2012-01-01
We aim to develop a nuclear energy density functional that can be simultaneously applied to finite nuclei and neutron stars. We use the self-consistent nuclear density functional theory (DFT) with Skyrme energy density functionals and covariance analysis to assess correlations between observables for finite nuclei and neutron stars. In a first step two energy functionals -- a high density energy functional giving reasonable neutron properties, and a low density functional fitted to nuclear properties -- are matched. In a second step, we optimize a new functional using exactly the same protocol as in earlier studies pertaining to nuclei but now including neutron star data. This allows direct comparisons of performance of the new functional relative to the standard one. The new functional TOV-min yields results for nuclear bulk properties (energy, r.m.s. radius, diffraction radius, surface thickness) that are of the same quality as those obtained with the established Skyrme functionals, including SV-min. When c...
On the rate of convergence of the maximum likelihood estimator of a k-monotone density
Institute of Scientific and Technical Information of China (English)
WELLNER; Jon; A
2009-01-01
Bounds for the bracketing entropy of the classes of bounded k-monotone functions on [0,A] are obtained under both the Hellinger distance and the Lp(Q) distance,where 1 p < ∞ and Q is a probability measure on [0,A].The result is then applied to obtain the rate of convergence of the maximum likelihood estimator of a k-monotone density.
On the rate of convergence of the maximum likelihood estimator of a K-monotone density
Institute of Scientific and Technical Information of China (English)
GAO FuChang; WELLNER Jon A
2009-01-01
Bounds for the bracketing entropy of the classes of bounded K-monotone functions on [0, A] are obtained under both the Hellinger distance and the LP(Q) distance, where 1 ≤ p < ∞ and Q is a probability measure on [0, A]. The result is then applied to obtain the rate of convergence of the maximum likelihood estimator of a K-monotone density.
Distributed Density Estimation Based on a Mixture of Factor Analyzers in a Sensor Network
Directory of Open Access Journals (Sweden)
Xin Wei
2015-08-01
Full Text Available Distributed density estimation in sensor networks has received much attention due to its broad applicability. When encountering high-dimensional observations, a mixture of factor analyzers (MFA is taken to replace mixture of Gaussians for describing the distributions of observations. In this paper, we study distributed density estimation based on a mixture of factor analyzers. Existing estimation algorithms of the MFA are for the centralized case, which are not suitable for distributed processing in sensor networks. We present distributed density estimation algorithms for the MFA and its extension, the mixture of Student’s t-factor analyzers (MtFA. We first define an objective function as the linear combination of local log-likelihoods. Then, we give the derivation process of the distributed estimation algorithms for the MFA and MtFA in details, respectively. In these algorithms, the local sufficient statistics (LSS are calculated at first and diffused. Then, each node performs a linear combination of the received LSS from nodes in its neighborhood to obtain the combined sufficient statistics (CSS. Parameters of the MFA and the MtFA can be obtained by using the CSS. Finally, we evaluate the performance of these algorithms by numerical simulations and application example. Experimental results validate the promising performance of the proposed algorithms.
Uncertainty Quantification and Propagation in Nuclear Density Functional Theory
Energy Technology Data Exchange (ETDEWEB)
Schunck, N; McDonnell, J D; Higdon, D; Sarich, J; Wild, S M
2015-03-17
Nuclear density functional theory (DFT) is one of the main theoretical tools used to study the properties of heavy and superheavy elements, or to describe the structure of nuclei far from stability. While on-going eff orts seek to better root nuclear DFT in the theory of nuclear forces, energy functionals remain semi-phenomenological constructions that depend on a set of parameters adjusted to experimental data in fi nite nuclei. In this paper, we review recent eff orts to quantify the related uncertainties, and propagate them to model predictions. In particular, we cover the topics of parameter estimation for inverse problems, statistical analysis of model uncertainties and Bayesian inference methods. Illustrative examples are taken from the literature.
Wavelet-based density estimation for noise reduction in plasma simulations using particles
van yen, Romain Nguyen; del-Castillo-Negrete, Diego; Schneider, Kai; Farge, Marie; Chen, Guangye
2010-04-01
For given computational resources, the accuracy of plasma simulations using particles is mainly limited by the noise due to limited statistical sampling in the reconstruction of the particle distribution function. A method based on wavelet analysis is proposed and tested to reduce this noise. The method, known as wavelet-based density estimation (WBDE), was previously introduced in the statistical literature to estimate probability densities given a finite number of independent measurements. Its novel application to plasma simulations can be viewed as a natural extension of the finite size particles (FSP) approach, with the advantage of estimating more accurately distribution functions that have localized sharp features. The proposed method preserves the moments of the particle distribution function to a good level of accuracy, has no constraints on the dimensionality of the system, does not require an a priori selection of a global smoothing scale, and its able to adapt locally to the smoothness of the density based on the given discrete particle data. Moreover, the computational cost of the denoising stage is of the same order as one time step of a FSP simulation. The method is compared with a recently proposed proper orthogonal decomposition based method, and it is tested with three particle data sets involving different levels of collisionality and interaction with external and self-consistent fields.
THE USE OF MATHEMATICAL MODELS FOR ESTIMATING WOOD BASIC DENSITY OF Eucalyptus sp CLONES
Directory of Open Access Journals (Sweden)
Cláudio Roberto Thiersch
2006-09-01
Full Text Available This study aimed at identifying at what point in the stem, in the longitudinal and cardinal direction, the pylodin penetration depth should be measured, for determining wood basic density, envisaging forestry inventory Data base used in compassed 36 parcels of 400 m2. Around the parcels 216 trees were sealed. Two clones (hybrid of E. grandis and E. urophylla, at the ages of 3; 4, 5 and 6 years, belonging to three different sites in East Brazil, encompassing East and Northeast of Espirito Santo state and south of Bahia state. In each measuring height of diameters it was also measured the penetration depth of the pylodin (in mm. The average basic density of scaled trees, was determined, departing from the cheaps, using the immersion method. The main conclusions were: The density equation, as function of the pylodin measures, age, site, diameters at 1.3m of ground and total height, was more precise, exact and stable than the density equation as function of pylodin, age, site and diameter, which in turn was more exact and stable than the density equation, as function of pylodin measures, age, site, diameter at a 1.3m of the ground and of total height, was precise and exact for all ages and sites, in dependent on if the pylodin measurements were taken in the South or in North fares, or in the average position between them. The height for measurement with pylodin can also be taken in the more ergonomic position of 1.3m. The density estimation, as a function of the measures with the pylodin, or as a function of the use of the pylodin, age, average dominant tree height an diameter at 1.3m of the ground, for both clones, was more precise when the measure with the pylodin was taken at the North face. The average tree basic density must always be taken by a specific equation for each clone, given that these equations differ statistically.
Graphene oxide and adsorption of chloroform: a density functional study
Kuisma, Elena; Lindberg, Th Benjamin; Gillberg, Christoffer A; Idh, Sebastian; Schroder, Elsebeth
2016-01-01
Chlorinated hydrocarbon compounds are of environmental concerns, since they are toxic to humans and other mammals, are widespread, and exposure is hard to avoid. Understanding and improving methods to reduce the amount of the substances is important. We present an atomic-scale calculational study of the adsorption of chlorine-based substance chloroform (CHCl3) 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 (DFT), and the recently developed consistent-exchange functional for the van der Waals density-functional method (vdW-DF-cx) 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 likel...
Limit Distribution Theory for Maximum Likelihood Estimation of a Log-Concave Density.
Balabdaoui, Fadoua; Rufibach, Kaspar; Wellner, Jon A
2009-06-01
We find limiting distributions of the nonparametric maximum likelihood estimator (MLE) of a log-concave density, i.e. a density of the form f(0) = exp varphi(0) where varphi(0) is a concave function on R. Existence, form, characterizations and uniform rates of convergence of the MLE are given by Rufibach (2006) and Dümbgen and Rufibach (2007). The characterization of the log-concave MLE in terms of distribution functions is the same (up to sign) as the characterization of the least squares estimator of a convex density on [0, infinity) as studied by Groeneboom, Jongbloed and Wellner (2001b). We use this connection to show that the limiting distributions of the MLE and its derivative are, under comparable smoothness assumptions, the same (up to sign) as in the convex density estimation problem. In particular, changing the smoothness assumptions of Groeneboom, Jongbloed and Wellner (2001b) slightly by allowing some higher derivatives to vanish at the point of interest, we find that the pointwise limiting distributions depend on the second and third derivatives at 0 of H(k), the "lower invelope" of an integrated Brownian motion process minus a drift term depending on the number of vanishing derivatives of varphi(0) = log f(0) at the point of interest. We also establish the limiting distribution of the resulting estimator of the mode M(f(0)) and establish a new local asymptotic minimax lower bound which shows the optimality of our mode estimator in terms of both rate of convergence and dependence of constants on population values.
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...
Remaining phosphorus estimated by pedotransfer function
Directory of Open Access Journals (Sweden)
Joice Cagliari
2011-02-01
Full Text Available Although the determination of remaining phosphorus (Prem is simple, accurate values could also be estimated with a pedotransfer function (PTF aiming at the additional use of soil analysis data and/or Prem replacement by an even simpler determination. The purpose of this paper was to develop a pedotransfer function to estimate Prem values of soils of the State of São Paulo based on properties with easier or routine laboratory determination. A pedotransfer function was developed by artificial neural networks (ANN from a database of Prem values, pH values measured in 1 mol L-1 NaF solution (pH NaF and soil chemical and physical properties of samples collected during soil classification activities carried out in the State of São Paulo by the Agronomic Institute of Campinas (IAC. Furthermore, a pedotransfer function was developed by regressing Prem values against the same predictor variables of the ANN-based PTF. Results showed that Prem values can be calculated more accurately with the ANN-based pedotransfer function with the input variables pH NaF values along with the sum of exchangeable bases (SB and the exchangeable aluminum (Al3+ soil content. In addition, the accuracy of the Prem estimates by ANN-based PTF were more sensitive to increases in the experimental database size. Although the database used in this study was not comprehensive enough for the establishment of a definitive pedotrasnfer function for Prem estimation, results indicated the inclusion of Prem and pH NaF measurements among the soil testing evaluations as promising ind order to provide a greater database for the development of an ANN-based pedotransfer function for accurate Prem estimates from pH NaF, SB, and Al3+ values.
Robust functional statistics applied to Probability Density Function shape screening of sEMG data.
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.
Cavuoti, Stefano; Brescia, Massimo; Vellucci, Civita; Tortora, Crescenzo; Longo, Giuseppe
2016-01-01
A variety of fundamental astrophysical science topics require the determination of very accurate photometric redshifts (photo-z's). A wide plethora of methods have been developed, based either on template models fitting or on empirical explorations of the photometric parameter space. Machine learning based techniques are not explicitly dependent on the physical priors and able to produce accurate photo-z estimations within the photometric ranges derived from the spectroscopic training set. These estimates, however, are not easy to characterize in terms of a photo-z Probability Density Function (PDF), due to the fact that the analytical relation mapping the photometric parameters onto the redshift space is virtually unknown. We present METAPHOR (Machine-learning Estimation Tool for Accurate PHOtometric Redshifts), a method designed to provide a reliable PDF of the error distribution for empirical techniques. The method is implemented as a modular workflow, whose internal engine for photo-z estimation makes use...
Bioinorganic Chemistry Modeled with the TPSSh Density Functional
DEFF Research Database (Denmark)
Kepp, Kasper Planeta
2008-01-01
In this work, the TPSSh density functional has been benchmarked against a test set of experimental structures and bond energies for 80 transition-metal-containing diatomics. It is found that the TPSSh functional gives structures of the same quality as other commonly used hybrid and nonhybrid func...... promising density functional for use and further development within the field of bioinorganic chemistry....
Efficient Density Functional Approximation for Electronic Properties of Conjugated Systems
Caldas, Marília J.; Pinheiro, José Maximiano, Jr.; Blum, Volker; Rinke, Patrick
2014-03-01
There is on-going discussion about reliable prediction of electronic properties of conjugated oligomers and polymers, such as ionization potential IP and energy gap. Several exchange-correlation (XC) functionals are being used by the density functional theory community, with different success for different properties. In this work we follow a recent proposal: a fraction α of exact exchange is added to the semi-local PBE XC aiming consistency, for a given property, with the results obtained by many-body perturbation theory within the G0W0 approximation. We focus the IP, taken as the negative of the highest occupied molecular orbital energy. We choose α from a study of the prototype family trans-acetylene, and apply this same α to a set of oligomers for which there is experimental data available (acenes, phenylenes and others). Our results indicate we can have excellent estimates, within 0,2eV mean ave. dev. from the experimental values, better than through complete EN - 1 -EN calculations from the starting PBE functional. We also obtain good estimates for the electrical gap and orbital energies close to the band edge. Work supported by FAPESP, CNPq, and CAPES, Brazil, and DAAD, Germany.
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.
Estimating the Importance of Differential Item Functioning.
Rudas, Tamas; Zwick, Rebecca
1997-01-01
The mixture index of fit (T. Rudas et al, 1994) is used to estimate the fraction of a population for which differential item functioning (DIF) occurs, and this approach is compared to the Mantel Haenszel test of DIF. The proposed noniterative procedure provides information about data portions contributing to DIF. (SLD)
Estimating the Importance of Differential Item Functioning.
Rudas, Tamas; Zwick, Rebecca
1997-01-01
The mixture index of fit (T. Rudas et al, 1994) is used to estimate the fraction of a population for which differential item functioning (DIF) occurs, and this approach is compared to the Mantel Haenszel test of DIF. The proposed noniterative procedure provides information about data portions contributing to DIF. (SLD)
Estimating ventilation time scales using overturning stream functions
Thompson, Bijoy; Nycander, Jonas; Nilsson, Johan; Jakobsson, Martin; Döös, Kristofer
2014-06-01
A simple method for estimating ventilation time scales from overturning stream functions is proposed. The stream function may be computed using either geometric coordinates or a generalized vertical coordinate, such as potential density (salinity in our study). The method is tested with a three-dimensional circulation model describing an idealized semi-enclosed ocean basin ventilated through a narrow strait over a sill, and the result is compared to age estimates obtained from a passive numerical age tracer. The best result is obtained when using the stream function in salinity coordinates. In this case, the reservoir-averaged advection time obtained from the overturning stream function in salinity coordinates agrees rather well with the mean age of the age tracer, and the corresponding maximum ages agree very well.
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)
Multicomponent density-functional theory for time-dependent systems
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 ou
Institute of Scientific and Technical Information of China (English)
张路平; 王鲁平; 李飚; 赵明
2015-01-01
In order to improve the performance of the probability hypothesis density (PHD) algorithm based particle filter (PF) in terms of number estimation and states extraction of multiple targets, a new probability hypothesis density filter algorithm based on marginalized particle and kernel density estimation is proposed, which utilizes the idea of marginalized particle filter to enhance the estimating performance of the PHD. The state variables are decomposed into linear and non-linear parts. The particle filter is adopted to predict and estimate the nonlinear states of multi-target after dimensionality reduction, while the Kalman filter is applied to estimate the linear parts under linear Gaussian condition. Embedding the information of the linear states into the estimated nonlinear states helps to reduce the estimating variance and improve the accuracy of target number estimation. The meanshift kernel density estimation, being of the inherent nature of searching peak value via an adaptive gradient ascent iteration, is introduced to cluster particles and extract target states, which is independent of the target number and can converge to the local peak position of the PHD distribution while avoiding the errors due to the inaccuracy in modeling and parameters estimation. Experiments show that the proposed algorithm can obtain higher tracking accuracy when using fewer sampling particles and is of lower computational complexity compared with the PF-PHD.
Delay estimation for CMOS functional cells
DEFF Research Database (Denmark)
Madsen, Jan
1991-01-01
Presents a new RC tree network model for delay estimation of CMOS functional cells. The model is able to reflect topological changes within a cell, which is of particular interest when doing performance driven layout synthesis. Further, a set of algorithms to perform worst case analysis on arbitr......Presents a new RC tree network model for delay estimation of CMOS functional cells. The model is able to reflect topological changes within a cell, which is of particular interest when doing performance driven layout synthesis. Further, a set of algorithms to perform worst case analysis...... on arbitrary CMOS functional cells using the proposed delay model, is presented. Both model and algorithms have been implemented as a part of a cell compiler (CELLO) working in an experimental silicon compiler environment....
Indian Academy of Sciences (India)
Paul W Ayers; Mel Levy
2005-09-01
Using the constrained search and Legendre-transform formalisms, one can derive ``generalized” density-functional theories, in which the fundamental variable is either the electron pair density or the second-order reduced density matrix. In both approaches, the -representability problem is solved by the functional, and the variational principle is with respect to all pair densities (density matrices) that are nonnegative and appropriately normalized. The Legendre-transform formulation provides a lower bound on the constrained-search functional. Noting that experience in density-functional and density-matrix theories suggests that it is easier to approximate functionals than it is to approximate the set of -representable densities sheds some light on the significance of this work.
Exact conditions on the temperature dependence of density functionals
Burke, Kieron; Grabowski, Paul E; Pribram-Jones, Aurora
2015-01-01
Universal exact conditions guided the construction of most ground-state density functional approximations in use today. We derive the relation between the entropy and Mermin free energy density functionals for thermal density functional theory. Both the entropy and sum of kinetic and electron-electron repulsion functionals are shown to be monotonically increasing with temperature, while the Mermin functional is concave downwards. Analogous relations are found for both exchange and correlation. The importance of these conditions is illustrated in two extremes: the Hubbard dimer and the uniform gas.
Exact conditions on the temperature dependence of density functionals
Burke, K.; Smith, J. C.; Grabowski, P. E.; Pribram-Jones, A.
2016-05-01
Universal exact conditions guided the construction of most ground-state density functional approximations in use today. We derive the relation between the entropy and Mermin free energy density functionals for thermal density functional theory. Both the entropy and sum of kinetic and electron-electron repulsion functionals are shown to be monotonically increasing with temperature, while the Mermin functional is concave downwards. Analogous relations are found for both exchange and correlation. The importance of these conditions is illustrated in two extremes: the Hubbard dimer and the uniform gas.
A density functional for sparse matter
DEFF Research Database (Denmark)
Langreth, D.C.; Lundqvist, Bengt; Chakarova-Kack, S.D.;
2009-01-01
forces in molecules, to adsorbed molecules, like benzene, naphthalene, phenol and adenine on graphite, alumina and metals, to polymer and carbon nanotube (CNT) crystals, and hydrogen storage in graphite and metal-organic frameworks (MOFs), and to the structure of DNA and of DNA with intercalators......Sparse matter is abundant and has both strong local bonds and weak nonbonding forces, in particular nonlocal van der Waals (vdW) forces between atoms separated by empty space. It encompasses a broad spectrum of systems, like soft matter, adsorption systems and biostructures. Density...
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 prio...
Exact Maps in Density Functional Theory for Lattice Models
Dimitrov, Tanja; Fuks, Johanna I; Rubio, Angel
2015-01-01
In the present work, we employ exact diagonalization for model systems on a real-space lattice to explicitly construct the exact density-to-potential and for the first time the exact density-to-wavefunction map that underly the Hohenberg-Kohn theorem in density functional theory. Having the explicit wavefunction-to- density map at hand, we are able to construct arbitrary observables as functionals of the ground-state density. We analyze the density-to-potential map as the distance between the fragments of a system increases and the correlation in the system grows. We observe a feature that gradually develops in the density-to-potential map as well as in the density-to-wavefunction map. This feature is inherited by arbitrary expectation values as functional of the ground-state density. We explicitly show the excited-state energies, the excited-state densities, and the correlation entropy as functionals of the ground-state density. All of them show this exact feature that sharpens as the coupling of the fragmen...
Introduction to Classical Density Functional Theory by a Computational Experiment
Jeanmairet, Guillaume; Levy, Nicolas; Levesque, Maximilien; Borgis, Daniel
2014-01-01
We propose an in silico experiment to introduce the classical density functional theory (cDFT). Density functional theories, whether quantum or classical, rely on abstract concepts that are nonintuitive; however, they are at the heart of powerful tools and active fields of research in both physics and chemistry. They led to the 1998 Nobel Prize in…
Molecular density functional theory of water including density-polarization coupling.
Jeanmairet, Guillaume; Levy, Nicolas; Levesque, Maximilien; Borgis, Daniel
2016-06-22
We present a three-dimensional molecular density functional theory of water derived from first-principles that relies on the particle's density and multipolar polarization density and includes the density-polarization coupling. This brings two main benefits: (i) scalar density and vectorial multipolar polarization density fields are much more tractable and give more physical insight than the full position and orientation densities, and (ii) it includes the full density-polarization coupling of water, that is known to be non-vanishing but has never been taken into account. Furthermore, the theory requires only the partial charge distribution of a water molecule and three measurable bulk properties, namely the structure factor and the Fourier components of the longitudinal and transverse dielectric susceptibilities.
Molecular density functional theory of water including density-polarization coupling
Jeanmairet, Guillaume; Levesque, Maximilien; Borgis, Daniel
2016-01-01
We present a three-dimensional molecular density functional theory (MDFT) of water derived from first-principles that relies on the particle's density and multipolar polarization density and includes the density-polarization coupling. This brings two main benefits: ($i$) a scalar density and a vectorial multipolar polarization density fields are much more tractable and give more physical insight than the full position and orientation densities, and ($ii$) it includes the full density-polarization coupling of water, that is known to be non-vanishing but has never been taken into account. Furthermore, the theory requires only the partial charge distribution of a water molecule and three measurable bulk properties, namely the structure factor and the Fourier components of the longitudinal and transverse dielectric susceptibilities.
Zero Order Estimates for Analytic Functions
Zorin, Evgeniy
2011-01-01
The primary goal of this paper is to provide a general multiplicity estimate. Our main theorem allows to reduce a proof of multiplicity lemma to the study of ideals stable under some appropriate transformation of a polynomial ring. In particular, this result leads to a new link between the theory of polarized algebraic dynamical systems and transcendental number theory. On the other hand, it allows to establish an improvement of Nesterenko's conditional result on solutions of systems of differential equations. We also deduce, under some condition on stable varieties, the optimal multiplicity estimate in the case of generalized Mahler's functional equations, previously studied by Mahler, Nishioka, Topfer and others. Further, analyzing stable ideals we prove the unconditional optimal result in the case of linear functional systems of generalized Mahler's type. The latter result generalizes a famous theorem of Nishioka (1986) previously conjectured by Mahler (1969), and simultaneously it gives a counterpart in t...
Spin constraints on nuclear energy density functionals
Robledo, L M; Bertsch, G F
2013-01-01
The Gallagher-Moszkowski rule in the spectroscopy of odd-odd nuclei imposes a new spin constraint on the energy functionals for self-consistent mean field theory. The commonly used parameterization of the effective three-body interaction in the Gogny and Skyrme families of energy functionals is ill-suited to satisfy the spin constraint. In particular, the Gogny parameterization of the three-body interaction has the opposite spin dependence to that required by the observed spectra. The two-body part has a correct sign, but in combination the rule is violated as often as not. We conclude that a new functional form is needed for the effective three-body interaction that can take into better account the different spin-isospin channels of the interaction.
Spectral density estimation for symmetric stable p-adic processes
Directory of Open Access Journals (Sweden)
Rachid Sabre
2013-05-01
Full Text Available Applications of p-adic numbers ar beming increasingly important espcially in the field of applied physics. The objective of this work is to study the estimation of the spectral of p-adic stable processes. An estimator formed by a smoothing periodogram is constructed. It is shwon that this estimator is asymptotically unbiased and consistent. Rates of convergences are also examined.
Local time estimation for the slotted correlation function of randomly sampled LDA data
Energy Technology Data Exchange (ETDEWEB)
Nobach, H. [Fachgebiet Stroemungslehre und Aerodynamik, Technische Universitaet Darmstadt (Germany)
2002-03-01
The task of autocorrelation and power spectral density estimation from velocity data sampled irregularly in time by a laser-Doppler anemometer (LDA) is addressed in this article. A new method based on the slotting technique was found to be a very reliable estimator. This article describes specific improvements of the slotting technique, the model-based variance estimation and the spectral transform leading to more accurate estimates of the autocorrelation function and the power spectral density. Furthermore, the new method yields more information especially at short time lags of the autocorrelation function, which can be used to derive improved estimates of the Taylor time scale. (orig.)
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.
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.
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...... parameters, and conditional simulation filters for simulating from the predictive distribution of GDP. Both algorithms process sequentially the data as they become available in real time. The GDP density estimates for the output and expenditure approach are combined using alternative weighting schemes...
Rigorous home range estimation with movement data: a new autocorrelated kernel density estimator.
Fleming, C H; Fagan, W F; Mueller, T; Olson, K A; Leimgruber, P; Calabrese, J M
2015-05-01
Quantifying animals' home ranges is a key problem in ecology and has important conservation and wildlife management applications. Kernel density estimation (KDE) is a workhorse technique for range delineation problems that is both statistically efficient and nonparametric. KDE assumes that the data are independent and identically distributed (IID). However, animal tracking data, which are routinely used as inputs to KDEs, are inherently autocorrelated and violate this key assumption. As we demonstrate, using realistically autocorrelated data in conventional KDEs results in grossly underestimated home ranges. We further show that the performance of conventional KDEs actually degrades as data quality improves, because autocorrelation strength increases as movement paths become more finely resolved. To remedy these flaws with the traditional KDE method, we derive an autocorrelated KDE (AKDE) from first principles to use autocorrelated data, making it perfectly suited for movement data sets. We illustrate the vastly improved performance of AKDE using analytical arguments, relocation data from Mongolian gazelles, and simulations based upon the gazelle's observed movement process. By yielding better minimum area estimates for threatened wildlife populations, we believe that future widespread use of AKDE will have significant impact on ecology and conservation biology.
The benchmark of gutzwiller density functional theory in hydrogen systems
Energy Technology Data Exchange (ETDEWEB)
Yao, Y.; Wang, Cai-Zhuang; Ho, Kai-Ming
2012-02-23
We propose an approximate form of the exchange-correlation energy functional for the Gutzwiller density functional theory. It satisfies certain physical constraints in both weak and strong electron correlation limits. We benchmark the Gutzwiller density functional approximation in the hydrogen systems, where the static correlation error is shown to be negligible. The good transferability is demonstrated by applications to the hydrogen molecule and some crystal structures.
The Benchmark of Gutzwiller Density Functional Theory in Hydrogen Systems
Energy Technology Data Exchange (ETDEWEB)
Yao, Yongxin; Wang, Cai-Zhuang; Ho, Kai-Ming
2011-01-13
We propose an approximate form of the exchange-correlation energy functional for the Gutzwiller density functional theory. It satisfies certain physical constraints in both weak and strong electron correlation limits. We benchmark the Gutzwiller density functional approximation in the hydrogen systems, where the static correlation error is shown to be negligible. The good transferability is demonstrated by applications to the hydrogen molecule and some crystal structures. © 2011 Wiley Periodicals, Inc. Int J Quantum Chem, 2012
Estimation of current density distribution under electrodes for external defibrillation
Directory of Open Access Journals (Sweden)
Papazov Sava P
2002-12-01
Full Text Available Abstract Background Transthoracic defibrillation is the most common life-saving technique for the restoration of the heart rhythm of cardiac arrest victims. The procedure requires adequate application of large electrodes on the patient chest, to ensure low-resistance electrical contact. The current density distribution under the electrodes is non-uniform, leading to muscle contraction and pain, or risks of burning. The recent introduction of automatic external defibrillators and even wearable defibrillators, presents new demanding requirements for the structure of electrodes. Method and Results Using the pseudo-elliptic differential equation of Laplace type with appropriate boundary conditions and applying finite element method modeling, electrodes of various shapes and structure were studied. The non-uniformity of the current density distribution was shown to be moderately improved by adding a low resistivity layer between the metal and tissue and by a ring around the electrode perimeter. The inclusion of openings in long-term wearable electrodes additionally disturbs the current density profile. However, a number of small-size perforations may result in acceptable current density distribution. Conclusion The current density distribution non-uniformity of circular electrodes is about 30% less than that of square-shaped electrodes. The use of an interface layer of intermediate resistivity, comparable to that of the underlying tissues, and a high-resistivity perimeter ring, can further improve the distribution. The inclusion of skin aeration openings disturbs the current paths, but an appropriate selection of number and size provides a reasonable compromise.
Exact maps in density functional theory for lattice models
Dimitrov, Tanja; Appel, Heiko; Fuks, Johanna I.; Rubio, Angel
2016-08-01
In the present work, we employ exact diagonalization for model systems on a real-space lattice to explicitly construct the exact density-to-potential and graphically illustrate the complete exact density-to-wavefunction map that underly the Hohenberg-Kohn theorem in density functional theory. Having the explicit wavefunction-to-density map at hand, we are able to construct arbitrary observables as functionals of the ground-state density. We analyze the density-to-potential map as the distance between the fragments of a system increases and the correlation in the system grows. We observe a feature that gradually develops in the density-to-potential map as well as in the density-to-wavefunction map. This feature is inherited by arbitrary expectation values as functional of the ground-state density. We explicitly show the excited-state energies, the excited-state densities, and the correlation entropy as functionals of the ground-state density. All of them show this exact feature that sharpens as the coupling of the fragments decreases and the correlation grows. We denominate this feature as intra-system steepening and discuss how it relates to the well-known inter-system derivative discontinuity. The inter-system derivative discontinuity is an exact concept for coupled subsystems with degenerate ground state. However, the coupling between subsystems as in charge transfer processes can lift the degeneracy. An important conclusion is that for such systems with a near-degenerate ground state, the corresponding cut along the particle number N of the exact density functionals is differentiable with a well-defined gradient near integer particle number.
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.
EXACT MINIMAX ESTIMATION OF THE PREDICTIVE DENSITY IN SPARSE GAUSSIAN MODELS.
Mukherjee, Gourab; Johnstone, Iain M
We consider estimating the predictive density under Kullback-Leibler loss in an ℓ0 sparse Gaussian sequence model. Explicit expressions of the first order minimax risk along with its exact constant, asymptotically least favorable priors and optimal predictive density estimates are derived. Compared to the sparse recovery results involving point estimation of the normal mean, new decision theoretic phenomena are seen. Suboptimal performance of the class of plug-in density estimates reflects the predictive nature of the problem and optimal strategies need diversification of the future risk. We find that minimax optimal strategies lie outside the Gaussian family but can be constructed with threshold predictive density estimates. Novel minimax techniques involving simultaneous calibration of the sparsity adjustment and the risk diversification mechanisms are used to design optimal predictive density estimates.
A Joint Density Function in the Renewal Risk Model
Institute of Scientific and Technical Information of China (English)
XU HUAI; TANG LING; Wang De-hui
2013-01-01
In this paper,we consider a general expression for (Φ)(u,x,y),the joint density function of the surplus prior to ruin and the deficit at ruin when the initial surplus is u.In the renewal risk model,this density function is expressed in terms of the corresponding density function when the initial surplus is 0.In the compound Poisson risk process with phase-type claim size,we derive an explicit expression for (Φ)(u,x,y).Finally,we give a numerical example to illustrate the application of these results.
Hilbert Space of Probability Density Functions Based on Aitchison Geometry
Institute of Scientific and Technical Information of China (English)
J. J. EGOZCUE; J. L. D(I)AZ-BARRERO; V. PAWLOWSKY-GLAHN
2006-01-01
The set of probability functions is a convex subset of L1 and it does not have a linear space structure when using ordinary sum and multiplication by real constants. Moreover, difficulties arise when dealing with distances between densities. The crucial point is that usual distances are not invariant under relevant transformations of densities. To overcome these limitations, Aitchison's ideas on compositional data analysis are used, generalizing perturbation and power transformation, as well as the Aitchison inner product, to operations on probability density functions with support on a finite interval. With these operations at hand, it is shown that the set of bounded probability density functions on finite intervals is a pre-Hilbert space. A Hilbert space of densities, whose logarithm is square-integrable, is obtained as the natural completion of the pre-Hilbert space.
Experimental assessment of presumed filtered density function models
Stetsyuk, V.; Soulopoulos, N.; Hardalupas, Y.; Taylor, A. M. K. P.
2015-06-01
Measured filtered density functions (FDFs) as well as assumed beta distribution model of mixture fraction and "subgrid" scale (SGS) scalar variance z '' 2 ¯ , used typically in large eddy simulations, were studied by analysing experimental data, obtained from two-dimensional planar, laser induced fluorescence measurements in isothermal swirling turbulent flows at a constant Reynolds number of 29 000 for different swirl numbers (0.3, 0.58, and 1.07). Two-dimensional spatial filtering, by using a box filter, was performed in order to obtain the filtered variables, namely, resolved mean and "subgrid" scale scalar variance. These were used as inputs for assumed beta distribution of mixture fraction and top-hat FDF shape estimates. The presumed beta distribution model, top-hat FDF, and the measured filtered density functions were used to integrate a laminar flamelet solution in order to calculate the corresponding resolved temperature. The experimentally measured FDFs varied with the flow swirl number and both axial and radial positions in the flow. The FDFs were unimodal at flow regions with low SGS scalar variance, z '' 2 ¯ 0.02. Bimodal FDF could be observed for a filter size of approximately 1.5-2 times the Batchelor scale. Unimodal FDF could be observed for a filter size as large as four times the Batchelor scale under well-mixed conditions. In addition, two common computational models (a gradient assumption and a scale similarity model) for the SGS scalar variance were used with the aim to evaluate their validity through comparison with the experimental data. It was found that the gradient assumption model performed generally better than the scale similarity one.
A molecular density functional theory to study solvation in water
Jeanmairet, Guillaume
2014-01-01
A classical density functional theory is applied to study solvation of solutes in water. An approx- imate form of the excess functional is proposed for water. This functional requires the knowledge of pure solvent direct correlation functions. Those functions can be computed by using molecular simulations such as molecular dynamic or Monte Carlo. It is also possible to use functions that have been determined experimentally. The functional minimization gives access to the solvation free energy and to the equilibrium solvent density. Some correction to the functional are also proposed to get the proper tetrahedral order of solvent molecules around a charged solute and to reproduce the correct long range hydrophobic behavior of big apolar solutes. To proceed the numerical minimization of the functional, the theory has been discretized on two tridimensional grids, one for the space coordinates, the other for the angular coordinates, in a functional minimization code written in modern Fortran, mdft. This program i...
Energy Density Functional for Nuclei and Neutron Stars
Energy Technology Data Exchange (ETDEWEB)
Erler, J. [UTK/ORNL/German Cancer Research Center-Heidelberg; Horowitz, C. J. [UTK/ORNL/Indiana University; Nazarewicz, Witold [UTK/ORNL/University of Warsaw; Rafalski, M. [UTK/ORNL; Reinhard, P.-G. [Universitat Erlangen, Germany
2013-01-01
Background: Recent observational data on neutron star masses and radii provide stringent constraints on the equation of state of neutron rich matter [ Annu. Rev. Nucl. Part. Sci. 62 485 (2012)]. Purpose: We aim to develop a nuclear energy density functional that can be simultaneously applied to finite nuclei and neutron stars. Methods: We use the self-consistent nuclear density functional theory (DFT) with Skyrme energy density functionals and covariance analysis to assess correlations between observables for finite nuclei and neutron stars. In a first step two energy functionals a high density energy functional giving reasonable neutron properties, and a low density functional fitted to nuclear properties are matched. In a second step, we optimize a new functional using exactly the same protocol as in earlier studies pertaining to nuclei but now including neutron star data. This allows direct comparisons of performance of the new functional relative to the standard one. Results: The new functional TOV-min yields results for nuclear bulk properties (energy, rms radius, diffraction radius, and surface thickness) that are of the same quality as those obtained with the established Skyrme functionals, including SV-min. When comparing SV-min and TOV-min, isoscalar nuclear matter indicators vary slightly while isovector properties are changed considerably. We discuss neutron skins, dipole polarizability, separation energies of the heaviest elements, and proton and neutron drip lines. We confirm a correlation between the neutron skin of 208Pb and the neutron star radius. Conclusions: We demonstrate that standard energy density functionals optimized to nuclear data do not carry information on the expected maximum neutron star mass, and that predictions can only be made within an extremely broad uncertainty band. For atomic nuclei, the new functional TOV-min performs at least as well as the standard nuclear functionals, but it also reproduces expected neutron star data
A pdf-Free Change Detection Test Based on Density Difference Estimation.
Bu, Li; Alippi, Cesare; Zhao, Dongbin
2016-11-16
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.
Chestnut, Tara E.; Anderson, Chauncey; Popa, Radu; Blaustein, Andrew R.; Voytek, Mary; Olson, Deanna H.; Kirshtein, Julie
2014-01-01
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-living Bd in aquatic
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
Density functional theory of the crystal field in dioxides
Diviš, M.; Kuriplach, J.; Richter, M.; Steinbeck, L.
1996-04-01
Presented are the results of ab-initio density functional calculations for PrO2 and UO2 using the general potential LAPW and optimized LCAO method in the local density approximation. The crystal field splitting of ionic Pr4+ and U4+ ground states was calculated and compared with predictions of a superposition model.
Charge and spin fluctuations in the density functional theory
Energy Technology Data Exchange (ETDEWEB)
Gyoerffy, B.L.; Barbieri, A. (Bristol Univ. (UK). H.H. Wills Physics Lab.); Staunton, J.B. (Warwick Univ., Coventry (UK). Dept. of Physics); Shelton, W.A.; Stocks, G.M. (Oak Ridge National Lab., TN (USA))
1990-01-01
We introduce a conceptual framework which allow us to treat charge and spin fluctuations about the Local density Approximation (LDA) to the Density Functional Theory (DFT). We illustrate the approach by explicit study of the Disordered Local Moment (DLM) state in Fe above the Curie Temperature {Tc} and the Mott insulating state in MnO. 27 refs., 6 figs.
Excitation Spectra of Nucleobases with Multiconfigurational Density Functional Theory
DEFF Research Database (Denmark)
Hubert, Mickaël; Jensen, Hans Jørgen Aa; Hedegård, Erik D.
2016-01-01
Range-separated hybrid methods between wave function theory and density functional theory (DFT) can provide high-accuracy results, while correcting some of the inherent flaws of both the underlying wave function theory and DFT. We here assess the accuracy for excitation energies of the nucleobases...
Applications and validations of the Minnesota density functionals
Zhao, Yan; Truhlar, Donald G.
2011-01-01
We discuss and review selected recent applications and validations of the Minnesota density functionals, especially the M06 family, emphasizing nanochemistry, organic, inorganic, and biological chemistry, and catalysis and highlighting the broad accuracy of these functionals as compared to previous popular functionals for thermochemistry, kinetics, and noncovalent interactions.
Density Functional Calculations for the Neutron Star Matter at Subnormal Density
Kashiwaba, Yu; Nakatsukasa, Takashi
The pasta phases of nuclear matter, whose existence is suggested at low density, may influence observable properties of neutron stars. In order to investigate properties of the neutron star matter, we calculate self-consistent solutions for the ground states of slab-like phase using the microscopic density functional theory with Bloch wave functions. The calculations are performed at each point of fixed average density and proton fraction (\\bar{ρ },Yp), varying the lattice constant of the unit cell. For small Yp values, the dripped neutrons emerge in the ground state, while the protons constitute the slab (crystallized) structure. The shell effect of protons affects the thickness of the slab nuclei.
Divisive latent class modeling as a density estimation method for categorical data
van der Palm, D.W.; van der Ark, L.A.; Vermunt, J.K.
2016-01-01
Traditionally latent class (LC) analysis is used by applied researchers as a tool for identifying substantively meaningful clusters. More recently, LC models have also been used as a density estimation tool for categorical variables. We introduce a divisive LC (DLC) model as a density estimation too
Confidence estimates in simulation of phase noise or spectral density.
Ashby, Neil
2017-02-13
In this paper we apply the method of discrete simulation of power law noise, developed in [1],[3],[4], to the problem of simulating phase noise for a combination of power law noises. We derive analytic expressions for the probability of observing a value of phase noise L(f) or of any of the onesided spectral densities S(f); Sy(f), or Sx(f), for arbitrary superpositions of power law noise.
Optimisation of in-situ dry density estimation
Directory of Open Access Journals (Sweden)
Morvan Mathilde
2016-01-01
Full Text Available Nowadays, field experiments are mostly used to determine the resistance and settlements of a soil before building. The needed devices were heavy so they cannot be used in every situation. It is the reason why Gourves et al (1998 developed a light dynamic penetrometer called Panda. For this penetrometer, a standardized hammer has to be blown on the head of the piston. For each blow, it measures the driving energy as well as the driving depth of the cone into the soil. The obtained penetrogram gives us the cone resistance variation with depth. For homogeneous soils, three parameters can determined: the critical depth zc, the initial cone resistance qd0 and the cone resistance in depth qd1. In parallel to the improvement of this apparatus, some researches were lead to obtain a relationship between the dry density of soil and the cone resistance in depth qd1. Knowing dry density of soil can allow to evaluate compaction efficiency for example. To achieve this point, a database of soils was initiated. Each of these soils was tested and classified using laboratory tests, among others, grain size distribution, proctor results, Atterberg limits. Penetrometer tests were also performed for three to five densities and for three to five water contents. Using this database, Chaigneau managed to obtain a logarithmic relation linking qd1 and dry density. But this relation varies with the water content. This article presents our recent researches on a mean to obtain a unified relation using water content, saturation degree or suction. To achieve this point, at first we studied the CNR silt responses with saturation degree and water content. Its water retention curve was realised using filter paper method so we can obtain suction. Then we verified the conclusion of this study to seven soils of the database to validate our hypotheses.
Thyroid function and bone mineral density among Indian subjects
Directory of Open Access Journals (Sweden)
Raman K Marwaha
2012-01-01
Full Text Available Background : Thyroid hormones affect bone remodeling in patients with thyroid disease by acting directly or indirectly on bone cells. In view of limited information on correlation of thyroid function with bone mineral density (BMD in euthyroid subjects, we undertook this study to evaluate the correlation between thyroid function with BMD in subjects with normal thyroid function and subclinical hypothyroidism. Material and Methods : A total of 1290 subjects included in this cross sectional study, were divided in Group-1 with normal thyroid function and Group-2 with subclinical hypothyroidism. Fasting blood samples were drawn for the estimation of serum 25(OHD, intact parathyroid hormone, total and ionized calcium, inorganic phosphorus, and alkaline phosphatase. BMD at lumbar spine, femur, and forearm was measured. Results : BMD at all sites (radius, femur, and spine were comparable in both groups. There was no difference in BMD when subjects were divided in tertiles of TSH in either group. In group-1, FT4 and TSH were positively associated with BMD at 33% radius whereas FT3 was negatively associated with BMD at femoral neck in multiple regression analysis after adjustment for age, sex, BMI, 25(OHD and PTH levels. In group-2, there was no association observed between TSH and BMD at any site. Amongst all study subjects FT4 and FT3 were positively correlated with BMD at lumbar spine and radius respectively among all subjects. Conclusion: TSH does not affect BMD in euthyroid subjects and subjects with subclinical hypothyroidism. Thyroid hormones appear to have more pronounced positive effect on cortical than trabecular bone in euthyroid subjects.
Volumetric breast density estimation from full-field digital mammograms.
Engeland, S. van; Snoeren, P.R.; Huisman, H.J.; Boetes, C.; Karssemeijer, N.
2006-01-01
A method is presented for estimation of dense breast tissue volume from mammograms obtained with full-field digital mammography (FFDM). The thickness of dense tissue mapping to a pixel is determined by using a physical model of image acquisition. This model is based on the assumption that the breast
Reflection-asymmetric nuclear deformations within the Density Functional Theory
Olsen, E; Nazarewicz, W; Stoitsov, M; 10.1088/1742-6596/402/1/012034
2013-01-01
Within the nuclear density functional theory (DFT) we study the effect of reflection-asymmetric shapes on ground-state binding energies and binding energy differences. To this end, we developed the new DFT solver AxialHFB that uses an approximate second-order gradient to solve the Hartree-Fock-Bogoliubov equations of superconducting DFT with the quasi-local Skyrme energy density functionals. Illustrative calculations are carried out for even-even isotopes of radium and thorium.
Density Functional Theory with Dissipation: Transport through Single Molecules
Energy Technology Data Exchange (ETDEWEB)
Kieron Burke
2012-04-30
A huge amount of fundamental research was performed on this grant. Most of it focussed on fundamental issues of electronic structure calculations of transport through single molecules, using density functional theory. Achievements were: (1) First density functional theory with dissipation; (2) Pseudopotential plane wave calculations with master equation; (3) Weak bias limit; (4) Long-chain conductance; and (5) Self-interaction effects in tunneling.
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.
Impact of ATLAS Data on Parton Density Functions
Newman, PR; The ATLAS collaboration
2014-01-01
Various measurements provided by the ATLAS collaboration have significant impact on parton density functions. The production of W and Z bosons inclusively or in association with charm-quark have are found to constraint the strange-quark density at medium and low Bjorken-x. Multi-Jet and photon production processes show impact on the gluon density. Off-resonance Drell Yan production at large lepton pair masses may be used to constrain anti-quark density at high x. A qualitative comparison of the ATLAS measurements to predictions based on different PDFs is presented.
Basis convergence of range-separated density-functional theory
Franck, Odile; Luppi, Eleonora; Toulouse, Julien
2014-01-01
Range-separated density-functional theory is an alternative approach to Kohn-Sham density-functional theory. The strategy of range-separated density-functional theory consists in separating the Coulomb electron-electron interaction into long-range and short-range components, and treating the long-range part by an explicit many-body wave-function method and the short-range part by a density-functional approximation. Among the advantages of using many-body methods for the long-range part of the electron-electron interaction is that they are much less sensitive to the one-electron atomic basis compared to the case of the standard Coulomb interaction. Here, we provide a detailed study of the basis convergence of range-separated density-functional theory. We study the convergence of the partial-wave expansion of the long-range wave function near the electron-electron coalescence. We show that the rate of convergence is exponential with respect to the maximal angular momentum L for the long-range wave function, whe...
The Wegner Estimate and the Integrated Density of States for some Random Operators
Indian Academy of Sciences (India)
J M Combes; P D Hislop; Frédéric Klopp; Shu Nakamura
2002-02-01
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 proof of the Wegner estimate applicable to a wide variety of random perturbations of deterministic background operators. The proof yields the correct volume dependence of the upper bound. This implies the local Hölder continuity of the integrated density of states at energies in the unperturbed spectral gap. The proof depends on the -theory of the spectral shift function (SSF), for ≥ 1, applicable to pairs of self-adjoint operators whose difference is in the trace ideal $\\mathcal{I}_p$, for 0 < ≤ 1. We present this and other results on the SSF due to other authors. Under an additional condition of the single-site potential, local Hölder continuity is proved at all energies. Finally, we present extensions of this work to random potentials with nonsign definite single-site potentials.
Density functional theory for polymeric systems in 2D.
Słyk, Edyta; Roth, Roland; Bryk, Paweł
2016-06-22
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.
Estimated global nitrogen deposition using NO2 column density
Lu, Xuehe; Jiang, Hong; Zhang, Xiuying; Liu, Jinxun; Zhang, Zhen; Jin, Jiaxin; Wang, Ying; Xu, Jianhui; Cheng, Miaomiao
2013-01-01
Global nitrogen deposition has increased over the past 100 years. Monitoring and simulation studies of nitrogen deposition have evaluated nitrogen deposition at both the global and regional scale. With the development of remote-sensing instruments, tropospheric NO2 column density retrieved from Global Ozone Monitoring Experiment (GOME) and Scanning Imaging Absorption Spectrometer for Atmospheric Chartography (SCIAMACHY) sensors now provides us with a new opportunity to understand changes in reactive nitrogen in the atmosphere. The concentration of NO2 in the atmosphere has a significant effect on atmospheric nitrogen deposition. According to the general nitrogen deposition calculation method, we use the principal component regression method to evaluate global nitrogen deposition based on global NO2 column density and meteorological data. From the accuracy of the simulation, about 70% of the land area of the Earth passed a significance test of regression. In addition, NO2 column density has a significant influence on regression results over 44% of global land. The simulated results show that global average nitrogen deposition was 0.34 g m−2 yr−1 from 1996 to 2009 and is increasing at about 1% per year. Our simulated results show that China, Europe, and the USA are the three hotspots of nitrogen deposition according to previous research findings. In this study, Southern Asia was found to be another hotspot of nitrogen deposition (about 1.58 g m−2 yr−1 and maintaining a high growth rate). As nitrogen deposition increases, the number of regions threatened by high nitrogen deposits is also increasing. With N emissions continuing to increase in the future, areas whose ecosystem is affected by high level nitrogen deposition will increase.
METAPHOR: Probability density estimation for machine learning based photometric redshifts
Amaro, V.; Cavuoti, S.; Brescia, M.; Vellucci, C.; Tortora, C.; Longo, G.
2017-06-01
We present METAPHOR (Machine-learning Estimation Tool for Accurate PHOtometric Redshifts), a method able to provide a reliable PDF for photometric galaxy redshifts estimated through empirical techniques. METAPHOR is a modular workflow, mainly based on the MLPQNA neural network as internal engine to derive photometric galaxy redshifts, but giving the possibility to easily replace MLPQNA with any other method to predict photo-z's and their PDF. We present here the results about a validation test of the workflow on the galaxies from SDSS-DR9, showing also the universality of the method by replacing MLPQNA with KNN and Random Forest models. The validation test include also a comparison with the PDF's derived from a traditional SED template fitting method (Le Phare).
Directory of Open Access Journals (Sweden)
Shanshan Yang
Full Text Available Detection of dysphonia is useful for monitoring the progression of phonatory impairment for patients with Parkinson's disease (PD, and also helps assess the disease severity. This paper describes the statistical pattern analysis methods to study different vocal measurements of sustained phonations. The feature dimension reduction procedure was implemented by using the sequential forward selection (SFS and kernel principal component analysis (KPCA methods. Four selected vocal measures were projected by the KPCA onto the bivariate feature space, in which the class-conditional feature densities can be approximated with the nonparametric kernel density estimation technique. In the vocal pattern classification experiments, Fisher's linear discriminant analysis (FLDA was applied to perform the linear classification of voice records for healthy control subjects and PD patients, and the maximum a posteriori (MAP decision rule and support vector machine (SVM with radial basis function kernels were employed for the nonlinear classification tasks. Based on the KPCA-mapped feature densities, the MAP classifier successfully distinguished 91.8% voice records, with a sensitivity rate of 0.986, a specificity rate of 0.708, and an area value of 0.94 under the receiver operating characteristic (ROC curve. The diagnostic performance provided by the MAP classifier was superior to those of the FLDA and SVM classifiers. In addition, the classification results indicated that gender is insensitive to dysphonia detection, and the sustained phonations of PD patients with minimal functional disability are more difficult to be correctly identified.
Linear response of homogeneous nuclear matter with energy density functionals
Energy Technology Data Exchange (ETDEWEB)
Pastore, A. [Institut d’Astronomie et d’Astrophysique, CP 226, Université Libre de Bruxelles, B-1050 Bruxelles (Belgium); Davesne, D., E-mail: davesne@ipnl.in2p3.fr [Institut de Physique Nucléaire de Lyon, CNRS-IN2P3, UMR 5822, Université Lyon 1, F-69622 Villeurbanne (France); Navarro, J. [IFIC (CSIC University of Valencia), Apdo. Postal 22085, E-46071 Valencia (Spain)
2015-03-01
Response functions of infinite nuclear matter with arbitrary isospin asymmetry are studied in the framework of the random phase approximation. The residual interaction is derived from a general nuclear Skyrme energy density functional. Besides the usual central, spin–orbit and tensor terms it could also include other components as new density-dependent terms or three-body terms. Algebraic expressions for the response functions are obtained from the Bethe–Salpeter equation for the particle–hole propagator. Applications to symmetric nuclear matter, pure neutron matter and asymmetric nuclear matter are presented and discussed. Spin–isospin strength functions are analyzed for varying conditions of density, momentum transfer, isospin asymmetry, and temperature for some representative Skyrme functionals. Particular attention is paid to the discussion of instabilities, either real or unphysical, which could manifest in finite nuclei.
Inclusion of Dispersion Effects in Density Functional Theory
DEFF Research Database (Denmark)
Møgelhøj, Andreas
In this thesis, applications and development will be presented within the field of van der Waals interactions in density functional theory. The thesis is based on the three projects: i) van der Waals interactions effect on the structure of liquid water at ambient conditions, ii) development...... and benchmarking of a new van der Waals density functional, and iii) the application of the newly developed functional to CO desorption from Ru(0001). The effect of van der Waals interactions in water was studied by performing ab initio molecular dynamics simulations using PBE and the two recent van der Waals...... density functionals optPBE-vdW and vdW-DF2 with identical computational setup. The two van der Waals functionals have been found to give excellent descriptions of the constituents of water (e.g., water dimers and hexamers). Including van der Waals interactions gives a softer water structure as seen from...
Introduction to Classical Density Functional Theory by Computational Experiment
Jeanmairet, Guillaume; Levesque, Maximilien; Borgis, Daniel
2014-01-01
We present here an introductory practical course to classical density functional theory (cDFT). Density functional theories, whether quantum or classical, rely largely on nonintuitive abstract concepts and applied mathematics. They are nevertheless a powerful tool and an active field of research in physics and chemistry that led to the 1998 Nobel prize in chemistry. We here illustrate the DFT in its most mathematically simple and yet physically relevant form: the classical density functional theory of an ideal fluid in an external field, as applied to the prediction of the structure of liquid neon at the molecular scale. This introductory course is built around the production of a cDFT code written by students using the Mathematica language. In this way, they are brought to deal with (i) the cDFT theory itself, (ii) some basic concepts around the statistical mechanics of simple fluids, (iii) the underlying mathematical and numerical problem of functional minimization, and (iv) a functional programming languag...
Sloppy nuclear energy density functionals: effective model reduction
Niksic, Tamara
2016-01-01
Concepts from information geometry are used to analyse parameter sensitivity for a nuclear energy density functional, representative of a class of semi-empirical functionals that start from a microscopically motivated ansatz for the density dependence of the energy of a system of protons and neutrons. It is shown that such functionals are sloppy, characterized by an exponential range of sensitivity to parameter variations. Responsive to only a few stiff parameter combinations, they exhibit an exponential decrease of sensitivity to variations of the remaining soft parameters. By interpreting the space of model predictions as a manifold embedded in the data space, with the parameters of the functional as coordinates on the manifold, it is also shown that the exponential distribution of model manifold widths corresponds to the distribution of parameter sensitivity. Using the Manifold Boundary Approximation Method, we illustrate how to systematically construct effective nuclear density functionals of successively...
Density functionals and dimensional renormalization for an exactly solvable model
Kais, S.; Herschbach, D. R.; Handy, N. C.; Murray, C. W.; Laming, G. J.
1993-07-01
We treat an analytically solvable version of the ``Hooke's Law'' model for a two-electron atom, in which the electron-electron repulsion is Coulombic but the electron-nucleus attraction is replaced by a harmonic oscillator potential. Exact expressions are obtained for the ground-state wave function and electron density, the Hartree-Fock solution, the correlation energy, the Kohn-Sham orbital, and, by inversion, the exchange and correlation functionals. These functionals pertain to the ``intermediate'' density regime (rs≥1.4) for an electron gas. As a test of customary approximations employed in density functional theory, we compare our exact density, exchange, and correlation potentials and energies with results from two approximations. These use Becke's exchange functional and either the Lee-Yang-Parr or the Perdew correlation functional. Both approximations yield rather good results for the density and the exchange and correlation energies, but both deviate markedly from the exact exchange and correlation potentials. We also compare properties of the Hooke's Law model with those of two-electron atoms, including the large dimension limit. A renormalization procedure applied to this very simple limit yields correlation energies as good as those obtained from the approximate functionals, for both the model and actual atoms.
Dual Approach To Superquantile Estimation And Applications To Density Fitting
2016-06-01
Change of Quantile Comparison . . . . . . . . 18 Figure 2.5 Quantile Gradient Relationship to Monotonicity . . . . . . . . . 20 Figure 3.1 DSE and...the basis of maximizing log-likelihood subject to various constraints such as monotonicity and tail convexity. Notice that no data exists beyond the...splines are a flexible set of piecewise polynomial functions that can be used to describe practically any function one could reasonably expect to
The Role of the Basis Set: Assessing Density Functional Theory
Boese, A D; Handy, N C; Martin, Jan M. L.; Handy, Nicholas C.
2003-01-01
When developing and assessing density functional theory methods, a finite basis set is usually employed. In most cases, however, the issue of basis set dependency is neglected. Here, we assess several basis sets and functionals. In addition, the dependency of the semiempirical fits to a given basis set for a generalised gradient approximation and a hybrid functional is investigated. The resulting functionals are then tested for other basis sets, evaluating their errors and transferability.
Nucleation for Lennard-Jones Fluid by Density Functional Theory
Institute of Scientific and Technical Information of China (English)
FU Dong
2005-01-01
@@ A non-mean field density functional theory is employed to investigate the vapour-liquid nucleation. The excess Helmholtz free energy functional is formulated in terms of a local density approximation for short ranged repulsion and a density-gradient expansion for long-ranged attractions. An analytical expression for the direct correlation function of a Lennard-Jones fluid is utilized to take into account the effect of long-ranged attractions on intermolecular correlations. With the predicted bulk properties and surface tension as input, the nucleation properties including density profile, work of formation and number of particles at the reduced temperatures T* = 0.694 and 0.741 are inuestigated. The obtained number of particles in the critical nucleus agrees well with the simulation data.
Transport through correlated systems with density functional theory
Kurth, S.; Stefanucci, G.
2017-10-01
We present recent advances in density functional theory (DFT) for applications in the field of quantum transport, with particular emphasis on transport through strongly correlated systems. We review the foundations of the popular Landauer–Büttiker(LB) + DFT approach. This formalism, when using approximations to the exchange-correlation (xc) potential with steps at integer occupation, correctly captures the Kondo plateau in the zero bias conductance at zero temperature but completely fails to capture the transition to the Coulomb blockade (CB) regime as the temperature increases. To overcome the limitations of LB + DFT, the quantum transport problem is treated from a time-dependent (TD) perspective using TDDFT, an exact framework to deal with nonequilibrium situations. The steady-state limit of TDDFT shows that in addition to an xc potential in the junction, there also exists an xc correction to the applied bias. Open shell molecules in the CB regime provide the most striking examples of the importance of the xc bias correction. Using the Anderson model as guidance we estimate these corrections in the limit of zero bias. For the general case we put forward a steady-state DFT which is based on one-to-one correspondence between the pair of basic variables, steady density on and steady current across the junction and the pair local potential on and bias across the junction. Like TDDFT, this framework also leads to both an xc potential in the junction and an xc correction to the bias. Unlike TDDFT, these potentials are independent of history. We highlight the universal features of both xc potential and xc bias corrections for junctions in the CB regime and provide an accurate parametrization for the Anderson model at arbitrary temperatures and interaction strengths, thus providing a unified DFT description for both Kondo and CB regimes and the transition between them.
Directory of Open Access Journals (Sweden)
Ashot Davtian
2011-05-01
Full Text Available Two methods for the estimation of number per unit volume NV of spherical particles are discussed: the (physical disector (Sterio, 1984 and Saltykov's estimator (Saltykov, 1950; Fullman, 1953. A modification of Saltykov's estimator is proposed which reduces the variance. Formulae for bias and variance are given for both disector and improved Saltykov estimator for the case of randomly positioned particles. They enable the comparison of the two estimators with respect to their precision in terms of mean squared error.
Selberg's Normal Density Theorem for Automorphic L-Functions for GLm
Institute of Scientific and Technical Information of China (English)
Yan QU
2007-01-01
Let π be an irreducible unitary cuspidal representation of GLm(AQ) with m ≥ 2, and L(s, π) the L-function attached to π. Under the Generalized Riemann Hypothesis for L(s, π), we estimate the normal density of primes in short intervals for the automorphic L-function L(s, π). Our result generalizes the corresponding theorem of Selberg for the Riemann zeta-function.
Filtered density function approach for reactive transport in groundwater
Suciu, Nicolae; Schüler, Lennart; Attinger, Sabine; Knabner, Peter
2016-04-01
Spatial filtering may be used in coarse-grained simulations (CGS) of reactive transport in groundwater, similar to the large eddy simulations (LES) in turbulence. The filtered density function (FDF), stochastically equivalent to a probability density function (PDF), provides a statistical description of the sub-grid, unresolved, variability of the concentration field. Besides closing the chemical source terms in the transport equation for the mean concentration, like in LES-FDF methods, the CGS-FDF approach aims at quantifying the uncertainty over the whole hierarchy of heterogeneity scales exhibited by natural porous media. Practically, that means estimating concentration PDFs on coarse grids, at affordable computational costs. To cope with the high dimensionality of the problem in case of multi-component reactive transport and to reduce the numerical diffusion, FDF equations are solved by particle methods. But, while trajectories of computational particles are modeled as stochastic processes indexed by time, the concentration's heterogeneity is modeled as a random field, with multi-dimensional, spatio-temporal sets of indices. To overcome this conceptual inconsistency, we consider FDFs/PDFs of random species concentrations weighted by conserved scalars and we show that their evolution equations can be formulated as Fokker-Planck equations describing stochastically equivalent processes in concentration-position spaces. Numerical solutions can then be approximated by the density in the concentration-position space of an ensemble of computational particles governed by the associated Itô equations. Instead of sequential particle methods we use a global random walk (GRW) algorithm, which is stable, free of numerical diffusion, and practically insensitive to the increase of the number of particles. We illustrate the general FDF approach and the GRW numerical solution for a reduced complexity problem consisting of the transport of a single scalar in groundwater
Specification of Density Functional Approximation by Radial Distribution Function of Bulk Fluid
Institute of Scientific and Technical Information of China (English)
ZHOUShi－Qi
2002-01-01
A systematic methodology is proposed to deal with the weighted density approximation version of classical density functional theory by employing the knowledge of radial distribution function of bulk fluid.The present methodology results from the concept of universality of the free energy density functional combined with the test particle method.It is shown that the new method is very accurate for the predictions of density distribution of a hard sphere fluid at different confining geometries.The physical foundation of the present methodology is also applied to the quantum density functional theory.
Basis convergence of range-separated density-functional theory.
Franck, Odile; Mussard, Bastien; Luppi, Eleonora; Toulouse, Julien
2015-02-21
Range-separated density-functional theory (DFT) is an alternative approach to Kohn-Sham density-functional theory. The strategy of range-separated density-functional theory consists in separating the Coulomb electron-electron interaction into long-range and short-range components and treating the long-range part by an explicit many-body wave-function method and the short-range part by a density-functional approximation. Among the advantages of using many-body methods for the long-range part of the electron-electron interaction is that they are much less sensitive to the one-electron atomic basis compared to the case of the standard Coulomb interaction. Here, we provide a detailed study of the basis convergence of range-separated density-functional theory. We study the convergence of the partial-wave expansion of the long-range wave function near the electron-electron coalescence. We show that the rate of convergence is exponential with respect to the maximal angular momentum L for the long-range wave function, whereas it is polynomial for the case of the Coulomb interaction. We also study the convergence of the long-range second-order Møller-Plesset correlation energy of four systems (He, Ne, N2, and H2O) with cardinal number X of the Dunning basis sets cc - p(C)V XZ and find that the error in the correlation energy is best fitted by an exponential in X. This leads us to propose a three-point complete-basis-set extrapolation scheme for range-separated density-functional theory based on an exponential formula.
A real-space stochastic density matrix approach for density functional electronic structure.
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.
An estimating function approach to linkage heterogeneity
Indian Academy of Sciences (India)
He Gao; Ying Zhou; Weijun Ma; Haidong Liu; Linan Zhao
2013-12-01
Testing linkage heterogeneity between two loci is an important issue in genetics. Currently, there are four methods (K-test, A-test, B-test and D-test) for testing linkage heterogeneity in linkage analysis, which are based on the likelihood-ratio test. Among them, the commonly used methods are the K-test and A-test. In this paper, we present a novel test method which is different from the above four tests, called G-test. The new test statistic is based on estimating function, possessing a theoretic asymptotic distribution, and therefore demonstrates its own advantages. The proposed test is applied to analyse a real pedigree dataset. Our simulation results also indicate that the G-test performs well in terms of power of testing linkage heterogeneity and outperforms the current methods to some degree.
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...
Wigner Function of Density Operator for Negative Binomial Distribution
Institute of Scientific and Technical Information of China (English)
HE Min-Hua; XU Xing-Lei; ZHANG Duan-Ming; LI Hong-Qi; PAN Gui-Jun; YIN Yan-Ping; CHEN Zhi-Yuan
2008-01-01
By using the technique of integration within an ordered product (IWOP) of operator we derive Wigner function of density operator for negative binomial distribution of radiation field in the mixed state case, then we derive the Wigner function of squeezed number state, which yields negative binomial distribution by virtue of the entangled state representation and the entangled Wigner operator.
Density-functional perturbation theory goes time-dependent
Gebauer, Ralph; Rocca, Dario; Baroni, Stefano
2009-01-01
The scope of time-dependent density-functional theory (TDDFT) is limited to the lowest portion of the spectrum of rather small systems (a few tens of atoms at most). In the static regime, density-functional perturbation theory (DFPT) allows one to calculate response functions of systems as large as currently dealt with in ground-state simulations. In this paper we present an effective way of combining DFPT with TDDFT. The dynamical polarizability is first expressed as an off-diagonal matrix e...
Density Functional Theory for General Hard-Core Lattice Gases
Lafuente, Luis; Cuesta, José A.
2004-09-01
We put forward a general procedure to obtain an approximate free-energy density functional for any hard-core lattice gas, regardless of the shape of the particles, the underlying lattice, or the dimension of the system. The procedure is conceptually very simple and recovers effortlessly previous results for some particular systems. Also, the obtained density functionals belong to the class of fundamental measure functionals and, therefore, are always consistent through dimensional reduction. We discuss possible extensions of this method to account for attractive lattice models.
Impact of Building Heights on 3d Urban Density Estimation from Spaceborne Stereo Imagery
Peng, Feifei; Gong, Jianya; Wang, Le; Wu, Huayi; Yang, Jiansi
2016-06-01
In urban planning and design applications, visualization of built up areas in three dimensions (3D) is critical for understanding building density, but the accurate building heights required for 3D density calculation are not always available. To solve this problem, spaceborne stereo imagery is often used to estimate building heights; however estimated building heights might include errors. These errors vary between local areas within a study area and related to the heights of the building themselves, distorting 3D density estimation. The impact of building height accuracy on 3D density estimation must be determined across and within a study area. In our research, accurate planar information from city authorities is used during 3D density estimation as reference data, to avoid the errors inherent to planar information extracted from remotely sensed imagery. Our experimental results show that underestimation of building heights is correlated to underestimation of the Floor Area Ratio (FAR). In local areas, experimental results show that land use blocks with low FAR values often have small errors due to small building height errors for low buildings in the blocks; and blocks with high FAR values often have large errors due to large building height errors for high buildings in the blocks. Our study reveals that the accuracy of 3D density estimated from spaceborne stereo imagery is correlated to heights of buildings in a scene; therefore building heights must be considered when spaceborne stereo imagery is used to estimate 3D density to improve precision.
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.
Density functional for ternary non-additive hard sphere mixtures.
Schmidt, Matthias
2011-10-19
Based on fundamental measure theory, a Helmholtz free energy density functional for three-component mixtures of hard spheres with general, non-additive interaction distances is constructed. The functional constitutes a generalization of the previously given theory for binary non-additive mixtures. The diagrammatic structure of the spatial integrals in both functionals is of star-like (or tree-like) topology. The ternary diagrams possess a higher degree of complexity than the binary diagrams. Results for partial pair correlation functions, obtained via the Ornstein-Zernike route from the second functional derivatives of the excess free energy functional, agree well with Monte Carlo simulation data. © 2011 IOP Publishing Ltd
H\\"ormander Type Functional Calculus and Square Function Estimates
Kriegler, Christoph
2012-01-01
We investigate H\\"ormander spectral multiplier theorems as they hold on $X = L^p(\\Omega),\\: 1 < p < \\infty,$ for many self-adjoint elliptic differential operators $A$ including the standard Laplacian on $\\R^d.$ A strengthened matricial extension is considered, which coincides with a completely bounded map between operator spaces in the case that $X$ is a Hilbert space. We show that the validity of the matricial H\\"ormander theorem can be characterized in terms of square function estimates for imaginary powers $A^{it}$, for resolvents $R(\\lambda,A),$ and for the analytic semigroup $\\exp(-zA).$ We deduce H\\"ormander spectral multiplier theorems for semigroups satisfying generalized Gaussian estimates.
A generalized model for estimating the energy density of invertebrates
James, Daniel A.; Csargo, Isak J.; Von Eschen, Aaron; Thul, Megan D.; Baker, James M.; Hayer, Cari-Ann; Howell, Jessica; Krause, Jacob; Letvin, Alex; Chipps, Steven R.
2012-01-01
Invertebrate energy density (ED) values are traditionally measured using bomb calorimetry. However, many researchers rely on a few published literature sources to obtain ED values because of time and sampling constraints on measuring ED with bomb calorimetry. Literature values often do not account for spatial or temporal variability associated with invertebrate ED. Thus, these values can be unreliable for use in models and other ecological applications. We evaluated the generality of the relationship between invertebrate ED and proportion of dry-to-wet mass (pDM). We then developed and tested a regression model to predict ED from pDM based on a taxonomically, spatially, and temporally diverse sample of invertebrates representing 28 orders in aquatic (freshwater, estuarine, and marine) and terrestrial (temperate and arid) habitats from 4 continents and 2 oceans. Samples included invertebrates collected in all seasons over the last 19 y. Evaluation of these data revealed a significant relationship between ED and pDM (r2 = 0.96, p calorimetry approaches. This model should prove useful for a wide range of ecological studies because it is unaffected by taxonomic, seasonal, or spatial variability.
Nuclear Energy Density Functionals: What do we really know?
Bulgac, Aurel; Jin, Shi
2015-01-01
We present the simplest nuclear energy density functional (NEDF) to date, determined by only 4 significant phenomenological parameters, yet capable of fitting measured nuclear masses with better accuracy than the Bethe-Weizs\\"acker mass formula, while also describing density structures (charge radii, neutron skins etc.) and time-dependent phenomena (induced fission, giant resonances, low energy nuclear collisions, etc.). The 4 significant parameters are necessary to describe bulk nuclear properties (binding energies and charge radii); an additional 2 to 3 parameters have little influence on the bulk nuclear properties, but allow independent control of the density dependence of the symmetry energy and isovector excitations, in particular the Thomas-Reiche-Kuhn sum rule. This Hohenberg-Kohn-style of density functional theory successfully realizes Weizs\\"acker's ideas and provides a computationally tractable model for a variety of static nuclear properties and dynamics, from finite nuclei to neutron stars, where...
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 for ...
In this study density functional theory (DFT) was used to study the adsorption of guaiacol and its initial hydrodeoxygenation (HDO) reactions on Pt(111). Previously reported Brønsted–Evans–Polanyi (BEP) correlations for small open chain molecules are found to be inadequate in estimating the reaction...
Time dependent density functional calculation of plasmon response in clusters
Institute of Scientific and Technical Information of China (English)
Wang Feng(王锋); Zhang Feng-Shou(张丰收); Eric Suraud
2003-01-01
We have introduced a theoretical scheme for the efficient description of the optical response of a cluster based on the time-dependent density functional theory. The practical implementation is done by means of the fully fledged timedependent local density approximation scheme, which is solved directly in the time domain without any linearization.As an example we consider the simple Na2 cluster and compute its surface plasmon photoabsorption cross section, which is in good agreement with the experiments.
Density functional calculations of spin-wave dispersion curves.
Kleinman, Leonard; Niu, Qian
1998-03-01
Extending the density functional method of Kubler et al( J. Kubler et al, J. Phys. F 18, 469 (1983) and J. Phys. Condens. Matter 1, 8155 (1989). ) for calcuating spin density wave ground states (but not making their atomic sphere approximation which requires a constant spin polarization direction in each WS sphere) we dicuss the calculation of frozen spin-wave eigenfunctions and their total energies. From these and the results of Niu's talk, we describe the calculation of spin-wave frequencies.
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.
On Bayes linear unbiased estimation of estimable functions for the singular linear model
Institute of Scientific and Technical Information of China (English)
ZHANG Weiping; WEI Laisheng
2005-01-01
The unique Bayes linear unbiased estimator (Bayes LUE) of estimable functions is derived for the singular linear model. The superiority of Bayes LUE over ordinary best linear unbiased estimator is investigated under mean square error matrix (MSEM)criterion.
MINIMAX INVARIANT ESTIMATOR OF CONTINUOUS DISTRIBUTION FUNCTION UNDER LINEX LOSS
Institute of Scientific and Technical Information of China (English)
Jianhui NING; Minyu XIE
2007-01-01
In this paper we consider the problem of estimation of a continuous distribution function under the LINEX loss function.The best invariant estimator is obtained,and proved to be minimax for any sample size n≥1.
A Probability Density Function for Neutrino Masses and Mixings
Fortin, Jean-François; Marleau, Luc
2016-01-01
The anarchy principle leading to the see-saw ensemble is studied analytically with the usual tools of random matrix theory. The probability density function for the see-saw ensemble of $N\\times N$ matrices is obtained in terms of a multidimensional integral. This integral involves all light neutrino masses, leading to a complicated probability density function. It is shown that the probability density function for the neutrino mixing angles and phases is the appropriate Haar measure. The decoupling of the light neutrino masses and neutrino mixings implies no correlation between the neutrino mass eigenstates and the neutrino mixing matrix, in contradiction with observations but in agreement with some of the claims found in the literature.
Probability density function for neutrino masses and mixings
Fortin, Jean-François; Giasson, Nicolas; Marleau, Luc
2016-12-01
The anarchy principle leading to the seesaw ensemble is studied analytically with the usual tools of random matrix theory. The probability density function for the seesaw ensemble of N ×N matrices is obtained in terms of a multidimensional integral. This integral involves all light neutrino masses, leading to a complicated probability density function. It is shown that the probability density function for the neutrino mixing angles and phases is the appropriate Haar measure. The decoupling of the light neutrino masses and neutrino mixings implies no correlation between the neutrino mass eigenstates and the neutrino mixing matrix and leads to a loss of predictive power when comparing with observations. This decoupling is in agreement with some of the claims found in the literature.
Nuclear energy density functional inspired by an effective field theory
Papakonstantinou, Panagiota; Lim, Yeunhwan; Hyun, Chang Ho
2016-01-01
Inspired by an effective field theory (EFT) for Fermi systems, we write the nuclear energy density functional (EDF) as an expansion in powers of the Fermi momentum $k_F$, or the cubic root of the density $\\rho^{1/3}$. With the help of pseudodata from microscopic calculations we fit the coefficients of the functional within a wide range of densities relevant for nuclei and neutron stars. The functional already at low order can reproduce known or adopted values of nuclear matter near saturation, a range of existing microscopic results on asymmetric matter, and a neutron-star mass-radius relation consistent with observations. Our approach leads to a transparent expansion of Skyrme-type EDFs and opens up many possibilities for future explorations in nuclei and homogeneous matter.
Density functional approach to the many-body problem : Key concepts and exact functionals
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
Multireference spin-adapted variant of density functional theory.
Khait, Yuriy G; Hoffmann, Mark R
2004-03-15
A new Kohn-Sham formalism is developed for studying the lowest molecular electronic states of given space and spin symmetry whose densities are represented by weighted sums of several reference configurations. Unlike standard spin-density functional theory, the new formalism uses total spin conserving spin-density operators and spin-invariant density matrices so that the method is fully spin-adapted and solves the so-called spin-symmetry dilemma. The formalism permits the use of an arbitrary set of reference (noninteracting) configurations with any number of open shells. It is shown that the requirement of degeneracy of the total noninteracting energies of the reference configurations (or configuration state functions) is equivalent to the stationary condition of the exact energy relative to the weights of the configurations (or configuration state functions). Consequently, at any molecular geometry, the weights can be determined by minimization of the energy, and, for given reference weights, the Kohn-Sham orbitals can be determined. From this viewpoint, the developed theory can be interpreted as an analog of the multiconfiguration self-consistent field approach within density functional theory.
Pernal, Katarzyna
2012-05-14
Time-dependent density functional theory (TD-DFT) in the adiabatic formulation exhibits known failures when applied to predicting excitation energies. One of them is the lack of the doubly excited configurations. On the other hand, the time-dependent theory based on a one-electron reduced density matrix functional (time-dependent density matrix functional theory, TD-DMFT) has proven accurate in determining single and double excitations of H(2) molecule if the exact functional is employed in the adiabatic approximation. We propose a new approach for computing excited state energies that relies on functionals of electron density and one-electron reduced density matrix, where the latter is applied in the long-range region of electron-electron interactions. A similar approach has been recently successfully employed in predicting ground state potential energy curves of diatomic molecules even in the dissociation limit, where static correlation effects are dominating. In the paper, a time-dependent functional theory based on the range-separation of electronic interaction operator is rigorously formulated. To turn the approach into a practical scheme the adiabatic approximation is proposed for the short- and long-range components of the coupling matrix present in the linear response equations. In the end, the problem of finding excitation energies is turned into an eigenproblem for a symmetric matrix. Assignment of obtained excitations is discussed and it is shown how to identify double excitations from the analysis of approximate transition density matrix elements. The proposed method used with the short-range local density approximation (srLDA) and the long-range Buijse-Baerends density matrix functional (lrBB) is applied to H(2) molecule (at equilibrium geometry and in the dissociation limit) and to Be atom. The method accounts for double excitations in the investigated systems but, unfortunately, the accuracy of some of them is poor. The quality of the other
Exploration of a modified density dependence in the Skyrme functional
Erler, J; Reinhard, P -G
2010-01-01
A variant of the basic Skyrme-Hartree-Fock (SHF) functional is considered dealing with a new form of density dependence. It employs only integer powers and thus will allow a more sound basis for projection schemes (particle number, angular momentum). We optimize the new functional with exactly the same adjustment strategy as used in an earlier study with a standard Skyrme functional. This allows direct comparisons of the performance of the new functional relative to the standard one. We discuss various observables: bulk properties of finite nuclei, nuclear matter, giant resonances, super-heavy elements, and energy systematics. The new functional performs at least as well as the standard one, but offers a wider range of applicability (e.g. for projection) and more flexibility in the regime of high densities.
Choosing a density functional for static molecular polarizabilities
Wu, Taozhe; Thakkar, Ajit J
2015-01-01
Coupled-cluster calculations of static electronic dipole polarizabilities for 145 organic molecules are performed to create a reference data set. The molecules are composed from carbon, hydrogen, nitrogen, oxygen, fluorine, sulfur, chlorine, and bromine atoms. They range in size from triatomics to 14 atoms. The Hartree-Fock and 2nd-order M{\\o}ller-Plesset methods and 34 density functionals, including local functionals, global hybrid functionals, and range-separated functionals of the long-range-corrected and screened-exchange varieties, are tested against this data set. On the basis of the test results, detailed recommendations are made for selecting density functionals for polarizability computations on relatively small organic molecules.
Crystallization induced by multiple seeds: dynamical density functional approach.
Neuhaus, T; Schmiedeberg, M; Löwen, H
2013-12-01
Using microscopic dynamical density functional theory, we calculate the dynamical formation of polycrystals by following the crystal growth around multiple crystalline seeds imposed to an undercooled fluid. Depending on the undercooling and the size ratio as well as the relative crystal orientation of two neighboring seeds, three possibilities of the final state emerge, namely no crystallization at all, formation of a monocrystal, or two crystallites separated by a curved grain boundary. Our results, which are obtained for two-dimensional hard disk systems using a fundamental-measure density functional, shed new light on the particle-resolved structure and growth of polycrystalline material in general.
Institute of Scientific and Technical Information of China (English)
周世琦
2002-01-01
In this Letter, we truncate the functional expansion of the non-uniform first-order direct correlation function (DCF) around the bulk density at the lowest order. But the truncation is performed formally and exactly by making use of functional counterpart of the Lagrangian theorem of differential calculus. Consequently the expansion coefficient, i.e. the uniform second-order DCF, is replaced by its non-uniform counterpart whose density argument is an appropriate mixture of calculated density distribution and the bulk density with a mixing parameter determined by a hard-wall sum rule. The non-uniform second-order DCF is then approximated by the uniform second-order DCF with an appropriate weighted density as its density argument. The present formally exact truncated functional expansion predicts the density distribution in good agreement with simulation data for hard sphere and Lennard-Jones fluid exerted by an external field.
EnviroAtlas Estimated Intersection Density of Walkable Roads Web Service
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....
EnviroAtlas - Paterson, NJ - Estimated Intersection Density of Walkable Roads
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 - Minneapolis/St. Paul, MN - Estimated Intersection Density of Walkable Roads
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 Bedford, MA - Estimated Intersection Density of Walkable Roads
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
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...
National Research Council Canada - National Science Library
Williamson, Laura D; Brookes, Kate L; Scott, Beth E; Graham, Isla M; Bradbury, Gareth; Hammond, Philip S; Thompson, Paul M; McPherson, Jana
2016-01-01
...‐based visual surveys. Surveys of cetaceans using acoustic loggers or digital cameras provide alternative methods to estimate relative density that have the potential to reduce cost and provide a verifiable record of all detections...
EnviroAtlas - New York, NY - Estimated Intersection Density of Walkable Roads
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
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
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
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
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
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, ME - Estimated Intersection Density of Walkable Roads
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
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
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
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
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
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
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
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...
Specification of Density Functional Approximation by Radial Distribution Function of Bulk Fluid
Institute of Scientific and Technical Information of China (English)
ZHOU Shi-Qi
2002-01-01
A systematic methodology is proposed to deal with the weighted density approximation version of clas-sical density functional theory by employing the knowledge of radial distribution function of bulk fluid. The presentmethodology results from the concept of universality of the free energy density functional combined with the test particlemethod. It is shown that the new method is very accurate for the predictions of density distribution ofa hard sphere fluidat different confining geometries. The physical foundation of the present methodology is also applied to the quantumdensity functional theory.
Cetacean Density Estimation from Novel Acoustic Datasets by Acoustic Propagation Modeling
2014-09-30
1 DISTRIBUTION STATEMENT A. Approved for public release; distribution is unlimited. Cetacean Density Estimation from Novel Acoustic Datasets...OBJECTIVES The objectives of this research are to apply existing methods for cetacean density estimation from passive acoustic recordings made by single...sensors, to novel data sets and cetacean species, as well as refine the existing techniques in order to develop a more generalized model that can be
The importance of spatial models for estimating the strength of density dependence
DEFF Research Database (Denmark)
Thorson, James T.; Skaug, Hans J.; Kristensen, Kasper;
2014-01-01
Identifying the existence and magnitude of density dependence is one of the oldest concerns in ecology. Ecologists have aimed to estimate density dependence in population and community data by fitting a simple autoregressive (Gompertz) model for density dependence to time series of abundance...... for an entire population. However, it is increasingly recognized that spatial heterogeneity in population densities has implications for population and community dynamics. We therefore adapt the Gompertz model to approximate local densities over continuous space instead of population-wide abundance......, and to allow productivity to vary spatially. Using simulated data generated from a spatial model, we show that the conventional (nonspatial) Gompertz model will result in biased estimates of density dependence, e.g., identifying oscillatory dynamics when not present. By contrast, the spatial Gompertz model...
Kimura, Satoko; Akamatsu, Tomonari; Li, Songhai; Dong, Shouyue; Dong, Lijun; Wang, Kexiong; Wang, Ding; Arai, Nobuaki
2010-09-01
A method is presented to estimate the density of finless porpoises using stationed passive acoustic monitoring. The number of click trains detected by stereo acoustic data loggers (A-tag) was converted to an estimate of the density of porpoises. First, an automated off-line filter was developed to detect a click train among noise, and the detection and false-alarm rates were calculated. Second, a density estimation model was proposed. The cue-production rate was measured by biologging experiments. The probability of detecting a cue and the area size were calculated from the source level, beam patterns, and a sound-propagation model. The effect of group size on the cue-detection rate was examined. Third, the proposed model was applied to estimate the density of finless porpoises at four locations from the Yangtze River to the inside of Poyang Lake. The estimated mean density of porpoises in a day decreased from the main stream to the lake. Long-term monitoring during 466 days from June 2007 to May 2009 showed variation in the density 0-4.79. However, the density was fewer than 1 porpoise/km(2) during 94% of the period. These results suggest a potential gap and seasonal migration of the population in the bottleneck of Poyang Lake.
Cavuoti, S.; Amaro, V.; Brescia, M.; Vellucci, C.; Tortora, C.; Longo, G.
2017-02-01
A variety of fundamental astrophysical science topics require the determination of very accurate photometric redshifts (photo-z). A wide plethora of methods have been developed, based either on template models fitting or on empirical explorations of the photometric parameter space. Machine-learning-based techniques are not explicitly dependent on the physical priors and able to produce accurate photo-z estimations within the photometric ranges derived from the spectroscopic training set. These estimates, however, are not easy to characterize in terms of a photo-z probability density function (PDF), due to the fact that the analytical relation mapping the photometric parameters on to the redshift space is virtually unknown. We present METAPHOR (Machine-learning Estimation Tool for Accurate PHOtometric Redshifts), a method designed to provide a reliable PDF of the error distribution for empirical techniques. The method is implemented as a modular workflow, whose internal engine for photo-z estimation makes use of the MLPQNA neural network (Multi Layer Perceptron with Quasi Newton learning rule), with the possibility to easily replace the specific machine-learning model chosen to predict photo-z. We present a summary of results on SDSS-DR9 galaxy data, used also to perform a direct comparison with PDFs obtained by the LE PHARE spectral energy distribution template fitting. We show that METAPHOR is capable to estimate the precision and reliability of photometric redshifts obtained with three different self-adaptive techniques, i.e. MLPQNA, Random Forest and the standard K-Nearest Neighbors models.
Dynamics of localized particles from density functional theory
Reinhardt, J.; Brader, J. M.
2012-01-01
A fundamental assumption of the dynamical density functional theory (DDFT) of colloidal systems is that a grand-canonical free-energy functional may be employed to generate the thermodynamic driving forces. Using one-dimensional hard rods as a model system, we analyze the validity of this key assumption and show that unphysical self-interactions of the tagged particle density fields, arising from coupling to a particle reservoir, are responsible for the excessively fast relaxation predicted by the theory. Moreover, our findings suggest that even employing a canonical functional would not lead to an improvement for many-particle systems, if only the total density is considered. We present several possible schemes to suppress these effects by incorporating tagged densities. When applied to confined systems, we demonstrate, using a simple example, that DDFT necessarily leads to delocalized tagged particle density distributions, which do not respect the fundamental geometrical constraints apparent in Brownian dynamics simulation data. The implication of these results for possible applications of DDFT to treat the glass transition are discussed.
Density functionals for the strong-interaction limit
Seidl, Michael; Perdew, John P.; Kurth, Stefan
2000-07-01
The strong-interaction limit of density-functional (DF) theory is simple and provides information required for an accurate resummation of DF perturbation theory. Here we derive the point-charge-plus-continuum (PC) model for that limit, and its gradient expansion. The exchange-correlation (xc) energy Exc[ρ]≡∫10dαWα[ρ] follows from the xc potential energies Wα at different interaction strengths α>=0 [but at fixed density ρ(r)]. For small α~0, the integrand Wα is obtained accurately from perturbation theory, but the perturbation expansion requires resummation for moderate and large α. For that purpose, we present density functionals for the coefficients in the asymptotic expansion Wα-->W∞+W'∞α-1/2 for α-->∞ in the PC model. WPC∞ arises from strict correlation, and W'PC∞ from zero-point vibration of the electrons around their strictly correlated distributions. The PC values for W∞ and W'∞ agree with those from a self-correlation-free meta-generalized gradient approximation, both for atoms and for atomization energies of molecules. We also (i) explain the difference between the PC cell and the exchange-correlation hole, (ii) present a density-functional measure of correlation strength, (iii) describe the electron localization and spin polarization energy in a highly stretched H2 molecule, and (iv) discuss the soft-plasmon instability of the low-density uniform electron gas.
Using gravity data to estimate the density of surface rocks of Taiwan region
Lo, Y. T.; Horng-Yen, Y.
2016-12-01
Surface rock density within terrain correction step is one of the important parameters for obtaining Bouguer anomaly map. In the past study, we obtain the Bouguer anomaly map considering the average density correction of a wide range of the study area. In this study, we will be the better estimate for the correction of the density of each observation point. A correction density that coincides with surface geology is in order to improve the accuracy of the cloth cover anomaly map. The main idea of estimating correction of the density using gravity data statistics are two method, g-H relationship and Nettleton density profile method, respectively. The common advantages of these methods are in the following: First, density estimating is calculated using existing gravity observations data, it may be avoided the trouble of directly measure the rock density. Second, after the establishment the measuring point s of absolute gravity value, latitude, longitude and elevation into the database, you can always apply its database of information and terrain data with the value to calculate the average rock density on any range. In addition, each measuring point and numerical data of each terrain mesh are independent, if found to be more accurate gravity or terrain data, simply update a document data alone, without having to rebuild the entire database. According the results of estimating density distribution map, the trends are broadly distributed close to Taiwan Geology Division. The average density of the backbone mountain region is about 2.5 to 2.6 g/cm^3, the average density of east Central Mountain Range and Hsuehshan Range are about 2.3 to 2.5 g/cm^3, compared with the western foothills of 2.1-2.3 g/cm^3, the western plains is from 1.8 to 2.0 g/cm^3.
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...... in combination with maximally localized Wannier functions and the norm-conserving pseudopotential code SIESTA which applies an atomic orbital basis set. All calculations have been converged with respect to the supercell size and the number of k(parallel to) points in the surface plane. For all systems we find...
Benchmarking Density Functionals for Chemical Bonds of Gold
DEFF Research Database (Denmark)
Kepp, Kasper Planeta
2017-01-01
Gold plays a major role in nanochemistry, catalysis, and electrochemistry. Accordingly, hundreds of studies apply density functionals to study chemical bonding with gold, yet there is no systematic attempt to assess the accuracy of these methods applied to gold. This paper reports a benchmark...... against 51 experimental bond enthalpies of AuX systems and seven additional polyatomic and cationic molecules. Twelve density functionals were tested, covering meta functionals, hybrids with variable HF exchange, double-hybrid, dispersion-corrected, and nonhybrid GGA functionals. The defined benchmark...... bonds between gold and noble gases. Zero-point vibrational corrections are relatively small for Au-X bonds, ∼ 11-12 kJ/mol except for Au-H bonds. Dispersion typically provides ∼5 kJ/mol of the total bond enthalpy but grows with system size and is 10 kJ/mol for AuXe and AuKr. HF exchange and LYP...
Density-based mixing parameter for hybrid functionals
Marques, Miguel A. L.; Vidal, Julien; Oliveira, Micael J. T.; Reining, Lucia; Botti, Silvana
2011-01-01
A very popular ab initio scheme to calculate electronic properties in solids is the use of hybrid functionals in density functional theory (DFT) that mixes a portion of the Fock exchange with DFT functionals. In spite of its success, a major problem still remains, related to the use of one single mixing parameter for all materials. Guided by physical arguments that connect the mixing parameter to the dielectric properties of the solid, and ultimately to its band gap, we propose a method to calculate this parameter from the electronic density alone. This approach is able to cut significantly the error of traditional hybrid functionals for large and small gap materials, while retaining a good description of the structural properties. Moreover, its implementation is simple and leads to a negligible increase of the computational time.
Linear density response function in the projector augmented wave method
DEFF Research Database (Denmark)
Yan, Jun; Mortensen, Jens Jørgen; Jacobsen, Karsten Wedel;
2011-01-01
We present an implementation of the linear density response function within the projector-augmented wave method with applications to the linear optical and dielectric properties of both solids, surfaces, and interfaces. The response function is represented in plane waves while the single......-particle eigenstates can be expanded on a real space grid or in atomic-orbital basis for increased efficiency. The exchange-correlation kernel is treated at the level of the adiabatic local density approximation (ALDA) and crystal local field effects are included. The calculated static and dynamical dielectric...... functions of Si, C, SiC, AlP, and GaAs compare well with previous calculations. While optical properties of semiconductors, in particular excitonic effects, are generally not well described by ALDA, we obtain excellent agreement with experiments for the surface loss function of graphene and the Mg(0001...
Efficient Diffuse Basis Sets for Density Functional Theory.
Papajak, Ewa; Truhlar, Donald G
2010-03-09
Eliminating all but the s and p diffuse functions on the non-hydrogenic atoms and all diffuse functions on the hydrogen atoms from the aug-cc-pV(x+d)Z basis sets of Dunning and co-workers, where x = D, T, Q, ..., yields the previously proposed "minimally augmented" basis sets, called maug-cc-pV(x+d)Z. Here, we present extensive and systematic tests of these basis sets for density functional calculations of chemical reaction barrier heights, hydrogen bond energies, electron affinities, ionization potentials, and atomization energies. The tests show that the maug-cc-pV(x+d)Z basis sets are as accurate as the aug-cc-pV(x+d)Z ones for density functional calculations, but the computational cost savings are a factor of about two to seven.
Bayesian estimation of the hemodynamic response function in functional MRI
Marrelec, G.; Benali, H.; Ciuciu, P.; Poline, J.-B.
2002-05-01
Functional MRI (fMRI) is a recent, non-invasive technique allowing for the evolution of brain processes to be dynamically followed in various cognitive or behavioral tasks. In BOLD fMRI, what is actually measured is only indirectly related to neuronal activity through a process that is still under investigation. A convenient way to analyze BOLD fMRI data consists of considering the whole brain as a system characterized by a transfer response function, called the Hemodynamic Response Function (HRF). Precise and robust estimation of the HRF has not been achieved yet: parametric methods tend to be robust but require too strong constraints on the shape of the HRF, whereas non-parametric models are not reliable since the problem is badly conditioned. We therefore propose a full Bayesian, non-parametric method that makes use of basic but relevant a priori knowledge about the underlying physiological process to make robust inference about the HRF. We show that this model is very robust to decreasing signal-to-noise ratio and to the actual noise sampling distribution. We finally apply the method to real data, revealing a wide variety of HRF shapes.
Clustering and pasta phases in nuclear density functional theory
Schuetrumpf, Bastian; Nazarewicz, Witold
2016-01-01
Nuclear density functional theory (DFT) is the tool of choice in describing properties of complex nuclei and intricate phases of bulk nucleonic matter. It is a microscopic approach based on an energy density functional representing the nuclear interaction. An attractive feature of nuclear DFT is that it can be applied to both finite nuclei and pasta phases appearing in the inner crust of neutron stars. While nuclear pasta clusters in a neutron star can be easily characterized through their density distributions, the level of clustering of nucleons in a nucleus can often be difficult to assess. To this end, we use the concept of nucleonic localization. We demonstrate that the localization measure provides us with fingerprints of clusters in light and heavy nuclei, including fissioning systems. Furthermore we investigate the rod-like pasta phase using twist-averaged boundary conditions, which enable calculations in finite volumes accessible by state of the art DFT solvers.
Double-hybrid density-functional theory made rigorous
Sharkas, Kamal; Savin, Andreas
2010-01-01
We provide a rigorous derivation of a class of double-hybrid approximations, combining Hartree-Fock exchange and second-order Moller-Plesset correlation with a semilocal exchange-correlation density functional. These double-hybrid approximations contain only one empirical parameter and use a density-scaled correlation energy functional. Neglecting density scaling leads to an one-parameter version of the standard double-hybrid approximations. We assess the performance of these double-hybrid schemes on representative test sets of atomization energies and reaction barrier heights, and we compare to other hybrid approximations, including range-separated hybrids. Our best one-parameter double-hybrid approximation, called 1DH-BLYP, roughly reproduces the two parameters of the standard B2-PLYP or B2GP-PLYP double-hybrid approximations, which shows that these methods are not only empirically close to an optimum for general chemical applications but are also theoretically supported.
Relativistic density functional theory for finite nuclei and neutron stars
Piekarewicz, J
2015-01-01
The main goal of the present contribution is a pedagogical introduction to the fascinating world of neutron stars by relying on relativistic density functional theory. Density functional theory provides a powerful--and perhaps unique--framework for the calculation of both the properties of finite nuclei and neutron stars. Given the enormous densities that may be reached in the core of neutron stars, it is essential that such theoretical framework incorporates from the outset the basic principles of Lorentz covariance and special relativity. After a brief historical perspective, we present the necessary details required to compute the equation of state of dense, neutron-rich matter. As the equation of state is all that is needed to compute the structure of neutron stars, we discuss how nuclear physics--particularly certain kind of laboratory experiments--can provide significant constrains on the behavior of neutron-rich matter.
Neutron skin uncertainties of Skyrme energy density functionals
Kortelainen, M; Nazarewicz, W; Birge, N; Gao, Y; Olsen, E
2013-01-01
Background: Neutron-skin thickness is an excellent indicator of isovector properties of atomic nuclei. As such, it correlates strongly with observables in finite nuclei that depend on neutron-to-proton imbalance and the nuclear symmetry energy that characterizes the equation of state of neutron-rich matter. A rich worldwide experimental program involving studies with rare isotopes, parity violating electron scattering, and astronomical observations is devoted to pinning down the isovector sector of nuclear models. Purpose: We assess the theoretical systematic and statistical uncertainties of neutron-skin thickness and relate them to the equation of state of nuclear matter, and in particular to nuclear symmetry energy parameters. Methods: We use the nuclear superfluid Density Functional Theory with several Skyrme energy density functionals and density dependent pairing. To evaluate statistical errors and their budget, we employ the statistical covariance technique. Results: We find that the errors on neutron s...
Maslennikova, Yu. S.; Nugmanov, I. S.
2016-08-01
The problem of probability density function estimation for a random process is one of the most common in practice. There are several methods to solve this problem. Presented laboratory work uses methods of the mathematical statistics to detect patterns in the realization of random process. On the basis of ergodic theory, we construct algorithm for estimating univariate probability density distribution function for a random process. Correlational analysis of realizations is applied to estimate the necessary size of the sample and the time of observation. Hypothesis testing for two probability distributions (normal and Cauchy) is used on the experimental data, using χ2 criterion. To facilitate understanding and clarity of the problem solved, we use ELVIS II platform and LabVIEW software package that allows us to make the necessary calculations, display results of the experiment and, most importantly, to control the experiment. At the same time students are introduced to a LabVIEW software package and its capabilities.
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.
Probability density functions of instantaneous Stokes parameters on weak scattering
Chen, Xi; Korotkova, Olga
2017-10-01
The single-point probability density functions (PDF) of the instantaneous Stokes parameters of a polarized plane-wave light field scattered from a three-dimensional, statistically stationary, weak medium with Gaussian statistics and Gaussian correlation function have been studied for the first time. Apart from the scattering geometry the PDF distributions of the scattered light have been related to the illumination's polarization state and the correlation properties of the medium.
Lemke, Dorothea; Mattauch, Volkmar; Heidinger, Oliver; Pebesma, Edzer; Hense, Hans-Werner
2015-03-31
Monitoring spatial disease risk (e.g. identifying risk areas) is of great relevance in public health research, especially in cancer epidemiology. A common strategy uses case-control studies and estimates a spatial relative risk function (sRRF) via kernel density estimation (KDE). This study was set up to evaluate the sRRF estimation methods, comparing fixed with adaptive bandwidth-based KDE, and how they were able to detect 'risk areas' with case data from a population-based cancer registry. The sRRF were estimated within a defined area, using locational information on incident cancer cases and on a spatial sample of controls, drawn from a high-resolution population grid recognized as underestimating the resident population in urban centers. The spatial extensions of these areas with underestimated resident population were quantified with population reference data and used in this study as 'true risk areas'. Sensitivity and specificity analyses were conducted by spatial overlay of the 'true risk areas' and the significant (α=.05) p-contour lines obtained from the sRRF. We observed that the fixed bandwidth-based sRRF was distinguished by a conservative behavior in identifying these urban 'risk areas', that is, a reduced sensitivity but increased specificity due to oversmoothing as compared to the adaptive risk estimator. In contrast, the latter appeared more competitive through variance stabilization, resulting in a higher sensitivity, while the specificity was equal as compared to the fixed risk estimator. Halving the originally determined bandwidths led to a simultaneous improvement of sensitivity and specificity of the adaptive sRRF, while the specificity was reduced for the fixed estimator. The fixed risk estimator contrasts with an oversmoothing tendency in urban areas, while overestimating the risk in rural areas. The use of an adaptive bandwidth regime attenuated this pattern, but led in general to a higher false positive rate, because, in our study design
Is Density Functional Theory adequate for quantum transport?
Burke, Kieron
2007-03-01
Density functional calculations for the electronic conductance of single molecules attached to leads are now common. I'll examine the methodology from a rigorous point of view, discussing where it can be expected to work, and where it should fail. When molecules are weakly coupled to leads, local and gradient-corrected approximations fail, as the Kohn-Sham levels are misaligned. In the weak bias regime, XC corrections to the current are missed by the standard methodology. Finally, I will compare and contrast several new methodologies that go beyond the present standard approach of applying the Landauer formula to ground-state DFT. Self-interaction errors in density functional calculations of electronictransport, C. Toher, A. Filippetti, S. Sanvito, and K. Burke, Phys. Rev. Lett. 95, 146402 (2005) The Dramatic Role of the Exchange-Correlation Potential in ab initio Electron Transport Calculations, S-H. Ke, H.U. Baranger, and W. Yang, cond-mat/0609367. Zero-bias molecular electronics: Exchange-correlation corrections to Landauer's formula, M. Koentopp, K. Burke, and F. Evers, Phys. Rev. B Rapid Comm., 73, 121403 (2006). Density Functional Theory of the Electrical Conductivity of Molecular Devices, K. Burke, Roberto Car, and Ralph Gebauer, Phys. Rev. Lett. 94, 146803 (2005). Density functional calculations of nanoscale conductance, Connie Chang, Max Koentopp, Kieron Burke, and Roberto Car, in prep.
Effective Maxwell Equations from Time-dependent Density Functional Theory
Institute of Scientific and Technical Information of China (English)
Weinan E; Jianfeng LU; Xu YANG
2011-01-01
The behavior of interacting electrons in a perfect crystal under macroscopic external electric and magnetic fields is studied. Effective Maxwell equations for the macroscopic electric and magnetic fields are derived starting from time-dependent density functional theory. Effective permittivity and permeability coefficients are obtained.
Density functional theory in surface science and heterogeneous catalysis
DEFF Research Database (Denmark)
Nørskov, Jens Kehlet; Scheffler, M.; Toulhoat, H.
2006-01-01
amount of experimental data gathered during the last decades. This article shows how density functional theory can be used to describe the state of the surface during reactions and the rate of catalytic reactions. It will also show how we are beginning to understand the variation in catalytic activity...
Implementation Strategies for Orbital-dependent Density Functionals
Bento, Marsal E.; Vieira, Daniel
2016-12-01
The development of density functional theory (DFT) has been focused primarily on two main pillars: (1) the pursuit of more accurate exchange-correlation (XC) density functionals; (2) the feasibility of computational implementation when dealing with many-body systems. In this context, this work is aimed on using one-dimensional quantum systems as theoretical laboratories to investigate the implementation of orbital functionals (OFs) of density. By definition, OFs are those which depend only implicitly on the density, via an explicit formulation in terms of Kohn-Sham orbitals. Typical examples are the XC functionals arising from the Perdew-Zunger self-interaction correction (PZSIC). Formally, via Kohn-Sham equations, the implementation of OFs must be performed by means of the optimized effective potential method (OEP), which is known by requiring an excessive computational effort even when dealing with few electrons systems. Here, we proceed a systematical investigation aiming to simplify or avoid the OEP procedure, taking as reference the implementation of the PZSIC correction applied to one-dimensional Hubbard chains.
Equilibrium time correlation functions in the low density limit
Beijeren, H. van; Lanford, O.E.; Lebowitz, J.L.; Spohn, H.
1980-01-01
We consider a system of hard spheres in thermal equilibrium. Using Lanford's result about the convergence of the solutions of the BBGKY hierarchy to the solutions of the Boltzmann hierarchy, we show that in the low-density limit (Boltzmann-Grad limit): (i) the total time correlation function is
Orbital-Free Density Functional Theory for Molecular Structure Calculations
Institute of Scientific and Technical Information of China (English)
Huajie Chen; Aihui Zhou
2008-01-01
We give here an overview of the orbital-free density functional theory that is used for modeling atoms and molecules. We review typical approximations to the kinetic energy, exchange-correlation corrections to the kinetic and Hartree energies, and constructions of the pseudopotentials. We discuss numerical discretizations for the orbital-free methods and include several numerical results for illustrations.
Exact ensemble density-functional theory for excited states
Yang, Zeng-hui; Pribram-Jones, Aurora; Burke, Kieron; Needs, Richard J; Ullrich, Carsten A
2014-01-01
We construct exact Kohn-Sham potentials for the ensemble density-functional theory (EDFT) of excited states from the ground and excited states of helium. The exchange-correlation potential is compared with current approximations, which miss prominent features. The ensemble derivative discontinuity is tested, and the virial theorem is proven and illustrated.
Reproducibility in density functional theory calculations of solids
DEFF Research Database (Denmark)
Lejaeghere, Kurt; Bihlmayer, Gustav; Björkman, Torbjörn
2016-01-01
The widespread popularity of density functional theory has given rise to an extensive range of dedicated codes for predicting molecular and crystalline properties. However, each code implements the formalism in a different way, raising questions about the reproducibility of such predictions. We r...
Implementation Strategies for Orbital-dependent Density Functionals
Bento, Marsal E.; Vieira, Daniel
2016-10-01
The development of density functional theory (DFT) has been focused primarily on two main pillars: (1) the pursuit of more accurate exchange-correlation (XC) density functionals; (2) the feasibility of computational implementation when dealing with many-body systems. In this context, this work is aimed on using one-dimensional quantum systems as theoretical laboratories to investigate the implementation of orbital functionals (OFs) of density. By definition, OFs are those which depend only implicitly on the density, via an explicit formulation in terms of Kohn-Sham orbitals. Typical examples are the XC functionals arising from the Perdew-Zunger self-interaction correction (PZSIC). Formally, via Kohn-Sham equations, the implementation of OFs must be performed by means of the optimized effective potential method (OEP), which is known by requiring an excessive computational effort even when dealing with few electrons systems. Here, we proceed a systematical investigation aiming to simplify or avoid the OEP procedure, taking as reference the implementation of the PZSIC correction applied to one-dimensional Hubbard chains.
Linear-response thermal time-dependent density functional theory
Pribram-Jones, Aurora; Burke, Kieron
2015-01-01
The van Leeuwen proof of linear-response time-dependent density functional theory (TDDFT) is generalized to thermal ensembles. This allows generalization to finite temperatures of the Gross-Kohn relation, the exchange-correlation kernel of TDDFT, and fluctuation dissipation theorem for DFT. This produces a natural method for generating new thermal exchange-correlation (XC) approximations.
Density functional theory is straying from the path toward the exact functional.
Medvedev, Michael G; Bushmarinov, Ivan S; Sun, Jianwei; Perdew, John P; Lyssenko, Konstantin A
2017-01-06
The theorems at the core of density functional theory (DFT) state that the energy of a many-electron system in its ground state is fully defined by its electron density distribution. This connection is made via the exact functional for the energy, which minimizes at the exact density. For years, DFT development focused on energies, implicitly assuming that functionals producing better energies become better approximations of the exact functional. We examined the other side of the coin: the energy-minimizing electron densities for atomic species, as produced by 128 historical and modern DFT functionals. We found that these densities became closer to the exact ones, reflecting theoretical advances, until the early 2000s, when this trend was reversed by unconstrained functionals sacrificing physical rigor for the flexibility of empirical fitting. Copyright © 2017, American Association for the Advancement of Science.
Tran, Fabien; Blaha, Peter
2017-05-04
Recently, exchange-correlation potentials in density functional theory were developed with the goal of providing improved band gaps in solids. Among them, the semilocal potentials are particularly interesting for large systems since they lead to calculations that are much faster than with hybrid functionals or methods like GW. We present an exhaustive comparison of semilocal exchange-correlation potentials for band gap calculations on a large test set of solids, and particular attention is paid to the potential HLE16 proposed by Verma and Truhlar. It is shown that the most accurate potential is the modified Becke-Johnson potential, which, most noticeably, is much more accurate than all other semilocal potentials for strongly correlated systems. This can be attributed to its additional dependence on the kinetic energy density. It is also shown that the modified Becke-Johnson potential is at least as accurate as the hybrid functionals and more reliable for solids with large band gaps.
Estimation of Correlation Functions by the Random Decrement Technique
DEFF Research Database (Denmark)
Brincker, Rune; Krenk, S.; Jensen, Jakob Laigaard
1993-01-01
The Random Decrement (RDD) Technique is a versatile technique for characterization of random signals in the time domain. In this paper a short review of the theoretical basis is given, and the technique is illustrated by estimating auto-correlation functions and cross-correlation functions on modal...... from smaller estimation errors than the corresponding FFT estimates. However, in the case of estimating cross-correlations functions for stochastic processes with low mutual correlation, the FFT technique might be more accurate....
Estimation of Correlation Functions by the Random Decrement Technique
DEFF Research Database (Denmark)
Brincker, Rune; Krenk, Steen; Jensen, Jakob Laigaard
The Random Decrement (RDD) Technique is a versatile technique for characterization of random signals in the time domain. In this paper a short review of the theoretical basis is given, and the technique is illustrated by estimating auto-correlation functions and cross-correlation functions on modal...... from smaller estimation errors than the corresponding FFT estimates. However, in the case of estimating cross-correlations functions for stochastic processes with low mutual correlation, the FFT technique might be more accurate....
Amplitude estimation of a sine function based on confidence intervals and Bayes' theorem
Eversmann, Dennis; Rosenthal, Marcel
2015-01-01
This paper discusses the amplitude estimation using data originating from a sine-like function as probability density function. If a simple least squares fit is used, a significant bias is observed for small amplitudes. It is shown that a proper treatment using the Feldman-Cousins algorithm of likelihood ratios allows one to construct improved confidence intervals. Using Bayes' theorem a probability density function is derived for the amplitude. It is used in an application to show that it leads to better estimates compared to a simple least squares fit.
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...
Technical Summary Objectives: Determine the effect of body mass index (BMI) on the accuracy of body density (Db) estimated with skinfold thickness (SFT) measurements compared to air displacement plethysmography (ADP) in adults. Subjects/Methods: We estimated Db with SFT and ADP in 131 healthy men an...
An asymptotically unbiased minimum density power divergence estimator for the Pareto-tail index
DEFF Research Database (Denmark)
Dierckx, G.; Goegebeur, Y.; Guillou, A.
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 and as...... by a small simulation experiment involving both uncontaminated and contaminated samples. (C) 2013 Elsevier Inc. All rights reserved....
Judgment Pitfalls in Estimating Premorbid Intellectual Function
National Research Council Canada - National Science Library
Kareken, David A
1997-01-01
... on their judgment. Lezak (1983) proposes that clinicians render an estimate synthesized from interview, anecdotal information, demographic characteristics, and patients' patterns of test performance. Similarly, Vanderploeg (1994) recommends integrating estimates from a number of formulas with past academic performance, occupational success, and con...
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.
Kocovsky, Patrick M.; Rudstam, Lars G.; Yule, Daniel L.; Warner, David M.; Schaner, Ted; Pientka, Bernie; Deller, John W.; Waterfield, Holly A.; Witzel, Larry D.; Sullivan, Patrick J.
2013-01-01
Standardized methods of data collection and analysis ensure quality and facilitate comparisons among systems. We evaluated the importance of three recommendations from the Standard Operating Procedure for hydroacoustics in the Laurentian Great Lakes (GLSOP) on density estimates of target species: noise subtraction; setting volume backscattering strength (Sv) thresholds from user-defined minimum target strength (TS) of interest (TS-based Sv threshold); and calculations of an index for multiple targets (Nv index) to identify and remove biased TS values. Eliminating noise had the predictable effect of decreasing density estimates in most lakes. Using the TS-based Sv threshold decreased fish densities in the middle and lower layers in the deepest lakes with abundant invertebrates (e.g., Mysis diluviana). Correcting for biased in situ TS increased measured density up to 86% in the shallower lakes, which had the highest fish densities. The current recommendations by the GLSOP significantly influence acoustic density estimates, but the degree of importance is lake dependent. Applying GLSOP recommendations, whether in the Laurentian Great Lakes or elsewhere, will improve our ability to compare results among lakes. We recommend further development of standards, including minimum TS and analytical cell size, for reducing the effect of biased in situ TS on density estimates.
Balawender, Robert
2009-01-01
The formalism developed in the first paper of the series [arXiv:0901.1060v3] is applied to two thermodynamic systems: (i) of three global observables (the energy, the total electron number and the spin number), (ii) of one global observable (the internal electron energy) and two local (position-dependent) observables (the total electron density and the spin density). The two-component potential of the many-electron system of interest is constructed of a scalar external potential and a collinear magnetic field (coupled only with the spin operator). Various equilibrium characteristics of two systems are defined and investigated. Conditions for the equivalence between two systems (the same equilibrium density matrix demanded) are derived and thoroughly discussed. The applicability of the Hohenberg-Kohn theorem is extended to the thermodynamic spin-density functional theory. Obtained results provide a rigorous mathematical foundation for future derivation of the zero-temperature limit of this theory and determina...
Lei, Youming; Zheng, Fan
2016-12-01
Stochastic chaos induced by diffusion processes, with identical spectral density but different probability density functions (PDFs), is investigated in selected lightly damped Hamiltonian systems. The threshold amplitude of diffusion processes for the onset of chaos is derived by using the stochastic Melnikov method together with a mean-square criterion. Two quasi-Hamiltonian systems, namely, a damped single pendulum and damped Duffing oscillator perturbed by stochastic excitations, are used as illustrative examples. Four different cases of stochastic processes are taking as the driving excitations. It is shown that in such two systems the spectral density of diffusion processes completely determines the threshold amplitude for chaos, regardless of the shape of their PDFs, Gaussian or otherwise. Furthermore, the mean top Lyapunov exponent is employed to verify analytical results. The results obtained by numerical simulations are in accordance with the analytical results. This demonstrates that the stochastic Melnikov method is effective in predicting the onset of chaos in the quasi-Hamiltonian systems.
Lei, Youming; Zheng, Fan
2016-12-01
Stochastic chaos induced by diffusion processes, with identical spectral density but different probability density functions (PDFs), is investigated in selected lightly damped Hamiltonian systems. The threshold amplitude of diffusion processes for the onset of chaos is derived by using the stochastic Melnikov method together with a mean-square criterion. Two quasi-Hamiltonian systems, namely, a damped single pendulum and damped Duffing oscillator perturbed by stochastic excitations, are used as illustrative examples. Four different cases of stochastic processes are taking as the driving excitations. It is shown that in such two systems the spectral density of diffusion processes completely determines the threshold amplitude for chaos, regardless of the shape of their PDFs, Gaussian or otherwise. Furthermore, the mean top Lyapunov exponent is employed to verify analytical results. The results obtained by numerical simulations are in accordance with the analytical results. This demonstrates that the stochastic Melnikov method is effective in predicting the onset of chaos in the quasi-Hamiltonian systems.
Particle vibrational coupling in covariant density functional theory
Ring, P; 10.1134/S1063778809080055
2009-01-01
A consistent combination of covariant density functional theory (CDFT) and Landau-Migdal Theory of Finite Fermi Systems (TFFS) is presented. Both methods are in principle exact, but Landau-Migdal theory cannot describe ground state properties and density functional theory does not take into account the energy dependence of the self-energy and therefore fails to yield proper single-% particle spectra as well as the coupling to complex configurations in the width of giant resonances. Starting from an energy functional, phonons and their vertices are calculated without any further parameters. They form the basis of particle-vibrational coupling leading to an energy dependence of the self-energy and an induced energy-dependent interaction in the response equation. A subtraction procedure avoids double counting. Applications in doubly magic nuclei and in a chain of superfluid nuclei show excellent agreement with experimental data.
Spin projection with double hybrid density functional theory.
Thompson, Lee M; Hratchian, Hrant P
2014-07-21
A spin projected double-hybrid density functional theory is presented that accounts for different scaling of opposite and same spin terms in the second order correction. This method is applied to three dissociation reactions which in the unprojected formalism exhibit significant spin contamination with higher spin states. This gives rise to a distorted potential surface and can lead to poor geometries and energies. The projected method presented is shown to improve the description of the potential over unprojected double hybrid density functional theory. Comparison is made with the reference states of the two double hybrid functionals considered here (B2PLYP and mPW2PLYP) in which the projected potential surface is degraded by an imbalance in the description of dynamic and static correlation.
A method to estimate plant density and plant spacing heterogeneity: application to wheat crops.
Liu, Shouyang; Baret, Fred; Allard, Denis; Jin, Xiuliang; Andrieu, Bruno; Burger, Philippe; Hemmerlé, Matthieu; Comar, Alexis
2017-01-01
Plant density and its non-uniformity drive the competition among plants as well as with weeds. They need thus to be estimated with small uncertainties accuracy. An optimal sampling method is proposed to estimate the plant density in wheat crops from plant counting and reach a given precision. Three experiments were conducted in 2014 resulting in 14 plots across varied sowing density, cultivars and environmental conditions. The coordinates of the plants along the row were measured over RGB high resolution images taken from the ground level. Results show that the spacing between consecutive plants along the row direction are independent and follow a gamma distribution under the varied conditions experienced. A gamma count model was then derived to define the optimal sample size required to estimate plant density for a given precision. Results suggest that measuring the length of segments containing 90 plants will achieve a precision better than 10%, independently from the plant density. This approach appears more efficient than the usual method based on fixed length segments where the number of plants are counted: the optimal length for a given precision on the density estimation will depend on the actual plant density. The gamma count model parameters may also be used to quantify the heterogeneity of plant spacing along the row by exploiting the variability between replicated samples. Results show that to achieve a 10% precision on the estimates of the 2 parameters of the gamma model, 200 elementary samples corresponding to the spacing between 2 consecutive plants should be measured. This method provides an optimal sampling strategy to estimate the plant density and quantify the plant spacing heterogeneity along the row.
A density functional for liquid [sup 3]He
Energy Technology Data Exchange (ETDEWEB)
Barranco, M. (Dept. de Estructura y Constituyentes de la Materia, Barcelona Univ. (Spain)); Jezek, D.M. (Dept. de Estructura y Constituyentes de la Materia, Barcelona Univ. (Spain)); Hernandez, E.S. (Dept. de Fisica, Univ. de Buenos Aires (Argentina)); Navarro, J. (Dept. de Fisica Atomica, Molecular y Nuclear, Valencia Univ. (Spain)); Serra, Ll. (Dipt. di Fisica, Milan Univ. (Italy))
1993-11-01
We present a density functional for the description of liquid [sup 3]He properties at zero temperture in a mean field approximation. Its basic ingredients are a zero-range, particle- and spin-density dependent effective interaction of Skyrme type, and a long-range effective interaction of Lennard-Jones type supplemented with a weighted density approximation similar to the one used in the study of classical fluids, to phenomenologically account for short range correlations. After fixing the value of its parameters, the functional yields a good desription of the equation of state and Landau parameters (spin symmetric and spin antisymmetric as well) from saturation to solidification densities. The zero sound propagation at finite momentum transfer is quantitatively reproduced up to the Fermi momentum, and qualitatively above it. The surface tension is in agreement with experiment, which makes the functional well suited for [sup 3]He drop calculations. We describe the structure of drops made of up to 516 atoms. As a novel application, we discuss the possible appearance of triplet pairing in a nl-shell of a drop applying the formalism to the 1j-shell holding up to 30 atoms from N=169 to 198. (orig.)
Relations among several nuclear and electronic density functional reactivity indexes
Torrent-Sucarrat, Miquel; Luis, Josep M.; Duran, Miquel; Toro-Labbé, Alejandro; Solà, Miquel
2003-11-01
An expansion of the energy functional in terms of the total number of electrons and the normal coordinates within the canonical ensemble is presented. A comparison of this expansion with the expansion of the energy in terms of the total number of electrons and the external potential leads to new relations among common density functional reactivity descriptors. The formulas obtained provide explicit links between important quantities related to the chemical reactivity of a system. In particular, the relation between the nuclear and the electronic Fukui functions is recovered. The connection between the derivatives of the electronic energy and the nuclear repulsion energy with respect to the external potential offers a proof for the "Quantum Chemical le Chatelier Principle." Finally, the nuclear linear response function is defined and the relation of this function with the electronic linear response function is given.
Recent advances in density functional methods, pt. 1-2
Chong, Delano P
1995-01-01
Of all the different areas in computational chemistry, density functional theory (DFT) enjoys the most rapid development. Even at the level of the local density approximation (LDA), which is computationally less demanding, DFT can usually provide better answers than Hartree-Fock formalism for large systems such as clusters and solids. For atoms and molecules, the results from DFT often rival those obtained by ab initio quantum chemistry, partly because larger basis sets can be used. Such encouraging results have in turn stimulated workers to further investigate the formal theory as well as the
Multiphase aluminum equations of state via density functional theory
Sjostrom, Travis; Crockett, Scott; Rudin, Sven
2016-10-01
We have performed density functional theory (DFT) based calculations for aluminum in extreme conditions of both pressure and temperature, up to five times compressed ambient density, and over 1 000 000 K in temperature. In order to cover such a domain, DFT methods including phonon calculations, quantum molecular dynamics, and orbital-free DFT are employed. The results are then used to construct a SESAME equation of state for the aluminum 1100 alloy, encompassing the fcc, hcp, and bcc solid phases as well as the liquid regime. We provide extensive comparison with experiment, and based on this we also provide a slightly modified equation of state for the aluminum 6061 alloy.
Density Functional Theory Studies of Magnetically Confined Fermi Gas
Institute of Scientific and Technical Information of China (English)
陈宇俊; 马红孺
2001-01-01
A theory is developed for magnetically confined Fermi gas at a low temperature based on the density functional theory. The theory is illustrated by the numerical calculation of the density distributions of Fermi atoms 40K with parameters according to DeMarco and Jin's experiment [Science, 285(1999)1703]. Our results are in close agreement with the experiment. To check the theory, we also performed calculations using our theory at a high temperature, which compared very well to the results of the classical limit.
Perspective: Fundamental aspects of time-dependent density functional theory
Maitra, Neepa T.
2016-06-01
In the thirty-two years since the birth of the foundational theorems, time-dependent density functional theory has had a tremendous impact on calculations of electronic spectra and dynamics in chemistry, biology, solid-state physics, and materials science. Alongside the wide-ranging applications, there has been much progress in understanding fundamental aspects of the functionals and the theory itself. This Perspective looks back to some of these developments, reports on some recent progress and current challenges for functionals, and speculates on future directions to improve the accuracy of approximations used in this relatively young theory.
Density-functional formula for strongly correlated systems
Institute of Scientific and Technical Information of China (English)
WANG Huaiyu; HAN Rushan; CHEN Nanxian
2005-01-01
Density functional method is applied for strongly correlated systems. Based on the assumption that the systems are composed of electrons in singly-occupied orbitals and those in doubly-occupied orbitals, a set of self-consistent equations are obtained by standard variation procedure. The equations consist of two parts. One part is to solve the wave functions of the electrons in singly-occupied orbitals and the other is to solve the wave functions of the electrons in doubly-occupied orbitals. The physical meanings of the terms appearing in the equations are discussed.
Dispersion corrections to density functionals for water aromatic interactions.
Zimmerli, Urs; Parrinello, Michele; Koumoutsakos, Petros
2004-02-08
We investigate recently published methods for extending density functional theory to the description of long-range dispersive interactions. In all schemes an empirical correction consisting of a C6r(-6) term is introduced that is damped at short range. The coefficient C6 is calculated either from average molecular or atomic polarizabilities. We calculate geometry-dependent interaction energy profiles for the water benzene cluster and compare the results with second-order Møller-Plesset calculations. Our results indicate that the use of the B3LYP functional in combination with an appropriate mixing rule and damping function is recommended for the interaction of water with aromatics.
Laplacian-level density functionals for the kinetic energy density and exchange-correlation energy
Perdew, John P.; Constantin, Lucian A.
2007-04-01
We construct a Laplacian-level meta-generalized-gradient-approximation (meta-GGA) for the noninteracting (Kohn-Sham orbital) positive kinetic energy density τ of an electronic ground state of density n . This meta-GGA is designed to recover the fourth-order gradient expansion τGE4 in the appropriate slowly varying limit and the von Weizsäcker expression τW=∣∇n∣2/(8n) in the rapidly varying limit. It is constrained to satisfy the rigorous lower bound τW(r)⩽τ(r) . Our meta-GGA is typically a strong improvement over the gradient expansion of τ for atoms, spherical jellium clusters, jellium surfaces, the Airy gas, Hooke’s atom, one-electron Gaussian density, quasi-two-dimensional electron gas, and nonuniformly scaled hydrogen atom. We also construct a Laplacian-level meta-GGA for exchange and correlation by employing our approximate τ in the Tao-Perdew-Staroverov-Scuseria (TPSS) meta-GGA density functional. The Laplacian-level TPSS gives almost the same exchange-correlation enhancement factors and energies as the full TPSS, suggesting that τ and ∇2n carry about the same information beyond that carried by n and ∇n . Our kinetic energy density integrates to an orbital-free kinetic energy functional that is about as accurate as the fourth-order gradient expansion for many real densities (with noticeable improvement in molecular atomization energies), but considerably more accurate for rapidly varying ones.
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
Level density and gamma-ray strength function in the odd-odd 238Np
Tornyi, Tamás Gábor; Eriksen, Tomas Kvalheim; Görgen, Andreas; Giacoppo, Francesca; Hagen, Trine Wiborg; Krasznahorkay, Attila; Larsen, Ann-Cecilie; Renstrøm, Therese; Rose, Sunniva Johanne; Siem, Sunniva; Tveten, Gry Merete
2014-01-01
The level density and gamma-ray strength function in the quasi-continuum of 238Np has been measured using the Oslo method. The level density function follows closely the constant-temperature level density formula and reaches 43 million levels per MeV at Sn = 5.488 MeV of excitation energy. The gamma-ray strength function displays a two-humped resonance at low-energy as also seen in previous investigations of Th, Pa and U isotopes. The structure is interpreted as the scissors resonance and has an average centroid of wSR = 2.26(5) MeV and a total strength of BSR = 10.8(12)m2N, which is in excellent agreement with sum-rule estimates. The scissors resonance is shown to have an impact on the 237Np(n; g)238Np cross section.
Codis, Sandrine; Pichon, Christophe
2016-01-01
In order to quantify the error budget in the measured probability distribution functions of cell densities, the two-point statistics of cosmic densities in concentric spheres is investigated. Bias functions are introduced as the ratio of their two-point correlation function to the two-point correlation of the underlying dark matter distribution. They describe how cell densities are spatially correlated. They are computed here via the so-called large deviation principle in the quasi-linear regime. Their large-separation limit is presented and successfully compared to simulations for density and density slopes: this regime is shown to be rapidly reached allowing to get sub-percent precision for a wide range of densities and variances. The corresponding asymptotic limit provides an estimate of the cosmic variance of standard concentric cell statistics applied to finite surveys. More generally, no assumption on the separation is required for some specific moments of the two-point statistics, for instance when pre...
Szirmai, Jen\\Ho
2011-01-01
The aim of this paper to determine the locally densest horoball packing arrangements and their densities with respect to fully asymptotic tetrahedra with at least one plane of symmetry in hyperbolic 3-space $\\bar{\\mathbf{H}}^3$ extended with its absolute figure, where the ideal centers of horoballs give rise to vertices of a fully asymptotic tetrahedron. We allow horoballs of different types at the various vertices. Moreover, we generalize the notion of the simplicial density function in the extended hyperbolic space $\\bar{\\mathbf{H}}^n, ~(n \\ge 2)$, and prove that, in this sense, {\\it the well known B\\"or\\"oczky--Florian density upper bound for "congruent horoball" packings of $\\bar{\\mathbf{H}}^3$ does not remain valid to the fully asymptotic tetrahedra.} The density of this locally densest packing is $\\approx 0.874994$, may be surprisingly larger than the B\\"or\\"oczky--Florian density upper bound $\\approx 0.853276$ but our local ball arrangement seems not to have extension to the whole hyperbolic space.
Velders, G.J.M.; Feil, D.
1989-01-01
Quantum-chemical density-functional theory (DFT) calculations, using the local-density approximation (LDA), have been performed for hydrogen-bounded silicon clusters to determine the electron density distribution of the Si-Si bond. The density distribution in the bonding region is compared with calc
Clay, Raymond C.; Holzmann, Markus; Ceperley, David M.; Morales, Miguel A.
2016-01-01
An accurate understanding of the phase diagram of dense hydrogen and helium mixtures is a crucial component in the construction of accurate models of Jupiter, Saturn, and Jovian extrasolar planets. Though density-functional-theory-based first-principles methods have the potential to provide the accuracy and computational efficiency required for this task, recent benchmarking in hydrogen has shown that achieving this accuracy requires a judicious choice of functional, and a quantification of the errors introduced. In this work, we present a quantum Monte Carlo (QMC) -based benchmarking study of a wide range of density functionals for use in hydrogen-helium mixtures at thermodynamic conditions relevant for Jovian planets. Not only do we continue our program of benchmarking energetics and pressures, but we deploy QMC-based force estimators and use them to gain insight into how well the local liquid structure is captured by different density functionals. We find that TPSS, BLYP, and vdW-DF are the most accurate functionals by most metrics, and that the enthalpy, energy, and pressure errors are very well behaved as a function of helium concentration. Beyond this, we highlight and analyze the major error trends and relative differences exhibited by the major classes of functionals, and we estimate the magnitudes of these effects when possible.
The force distribution probability function for simple fluids by density functional theory.
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.
Steady-State Density Functional Theory for Finite Bias Conductances.
Stefanucci, G; Kurth, S
2015-12-09
In the framework of density functional theory, a formalism to describe electronic transport in the steady state is proposed which uses the density on the junction and the steady current as basic variables. We prove that, in a finite window around zero bias, there is a one-to-one map between the basic variables and both local potential on as well as bias across the junction. The resulting Kohn-Sham system features two exchange-correlation (xc) potentials, a local xc potential, and an xc contribution to the bias. For weakly coupled junctions the xc potentials exhibit steps in the density-current plane which are shown to be crucial to describe the Coulomb blockade diamonds. At small currents these steps emerge as the equilibrium xc discontinuity bifurcates. The formalism is applied to a model benzene junction, finding perfect agreement with the orthodox theory of Coulomb blockade.
DEFF Research Database (Denmark)
Christensen, Rune; Hansen, Heine Anton; Vegge, Tejs
2015-01-01
through first principle methods. Ensembles generated using a Bayesian error estimation functional, in this case the BEEF-vdW functional[6], are used for the error identification. The ensembles, which consist of perturbations of the main van der Waals density functional, can be generated at low......Density functional theory (DFT) calculations have greatly contributed to the atomic level understanding of electrochemical reactions. However, in some cases, the accuracy can be prohibitively low for a detailed understanding of, e.g. reaction mechanisms. Two cases are examined here, i...... that the systematic error is due to carbon-oxygen double bonds, as the change in number of carbon-oxygen double bonds in the reaction to methanol is two as compared to one for reaction to formic acid. This is subsequently confirmed by further comparisons of functional dependence and a significant source of systematic...
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.
Differentiable but exact formulation of density-functional theory
Kvaal, Simen; Teale, Andrew M; Helgaker, Trygve
2013-01-01
The universal density functional $F$ of density-functional theory is a complicated and ill-behaved function of the density--in particular, $F$ is not differentiable, making many formal manipulations more complicated. Whilst $F$ has been well characterized in terms of convex analysis as forming a conjugate pair $(F,E)$ with the ground-state energy $E$ via the Hohenberg-Kohn and Lieb variation principles, $F$ is only subdifferentiable on a small (but dense) set of its domain. In this article, we apply a tool from convex analysis, Moreau-Yosida regularization, to construct, for any $\\epsilon>0$, pairs of conjugate functionals $({}^\\epsilon\\!E,{}^\\epsilon\\! F)$ that converge to $(E,F)$ pointwise everywhere as $\\epsilon\\rightarrow 0^+$, and such that ${}^\\epsilon\\!F$ is (Fr\\'echet) differentiable. For technical reasons, we limit our attention to molecular electronic systems in a finite but large box, which does not change the physics. It is noteworthy that no information is lost in the Moreau-Yosida regularization...
Differentiable but exact formulation of density-functional theory.
Kvaal, Simen; Ekström, Ulf; Teale, Andrew M; Helgaker, Trygve
2014-05-14
The universal density functional F of density-functional theory is a complicated and ill-behaved function of the density-in particular, F is not differentiable, making many formal manipulations more complicated. While F has been well characterized in terms of convex analysis as forming a conjugate pair (E, F) with the ground-state energy E via the Hohenberg-Kohn and Lieb variation principles, F is nondifferentiable and subdifferentiable only on a small (but dense) subset of its domain. In this article, we apply a tool from convex analysis, Moreau-Yosida regularization, to construct, for any ε > 0, pairs of conjugate functionals ((ε)E, (ε)F) that converge to (E, F) pointwise everywhere as ε → 0(+), and such that (ε)F is (Fréchet) differentiable. For technical reasons, we limit our attention to molecular electronic systems in a finite but large box. It is noteworthy that no information is lost in the Moreau-Yosida regularization: the physical ground-state energy E(v) is exactly recoverable from the regularized ground-state energy (ε)E(v) in a simple way. All concepts and results pertaining to the original (E, F) pair have direct counterparts in results for ((ε)E, (ε)F). The Moreau-Yosida regularization therefore allows for an exact, differentiable formulation of density-functional theory. In particular, taking advantage of the differentiability of (ε)F, a rigorous formulation of Kohn-Sham theory is presented that does not suffer from the noninteracting representability problem in standard Kohn-Sham theory.
Glacial density and GIA in Alaska estimated from ICESat, GPS and GRACE measurements
Jin, Shuanggen; Zhang, T. Y.; Zou, F.
2017-01-01
The density of glacial volume change in Alaska is a key factor in estimating the glacier mass loss from altimetry observations. However, the density of Alaskan glaciers has large uncertainty due to the lack of in situ measurements. In this paper, using the measurements of Ice, Cloud, and land Elevation Satellite (ICESat), Global Positioning System (GPS), and Gravity Recovery and Climate Experiment (GRACE) from 2003 to 2009, an optimal density of glacial volume change with 750 kg/m3 is estimated for the first time to fit the measurements. The glacier mass loss is -57.5 ± 6.5 Gt by converting the volumetric change from ICESat with the estimated density 750 kg/m3. Based on the empirical relation, the depth-density profiles are constructed, which show glacial density variation information with depths in Alaska. By separating the glacier mass loss from glacial isostatic adjustment (GIA) effects in GPS uplift rates and GRACE total water storage trends, the GIA uplift rates are estimated in Alaska. The best fitting model consists of a 60 km elastic lithosphere and 110 km thick asthenosphere with a viscosity of 2.0 × 1019 Pa s over a two-layer mantle.
Estimating population density and connectivity of American mink using spatial capture-recapture
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.
Prediction-based estimating functions: Review and new developments
DEFF Research Database (Denmark)
Sørensen, Michael
2011-01-01
The general theory of prediction-based estimating functions for stochastic process models is reviewed and extended. Particular attention is given to optimal estimation, asymptotic theory and Gaussian processes. Several examples of applications are presented. In particular, partial observation...
Effect of compression paddle tilt correction on volumetric breast density estimation.
Kallenberg, Michiel G J; van Gils, Carla H; Lokate, Mariëtte; den Heeten, Gerard J; Karssemeijer, Nico
2012-08-21
For the acquisition of a mammogram, a breast is compressed between a compression paddle and a support table. When compression is applied with a flexible compression paddle, the upper plate may be tilted, which results in variation in breast thickness from the chest wall to the breast margin. Paddle tilt has been recognized as a major problem in volumetric breast density estimation methods. In previous work, we developed a fully automatic method to correct the image for the effect of compression paddle tilt. In this study, we investigated in three experiments the effect of paddle tilt and its correction on volumetric breast density estimation. Results showed that paddle tilt considerably affected accuracy of volumetric breast density estimation, but that effect could be reduced by tilt correction. By applying tilt correction, a significant increase in correspondence between mammographic density estimates and measurements on MRI was established. We argue that in volumetric breast density estimation, tilt correction is both feasible and essential when mammographic images are acquired with a flexible compression paddle.
X-Ray Methods to Estimate Breast Density Content in Breast Tissue
Maraghechi, Borna
This work focuses on analyzing x-ray methods to estimate the fat and fibroglandular contents in breast biopsies and in breasts. The knowledge of fat in the biopsies could aid in their wide-angle x-ray scatter analyses. A higher mammographic density (fibrous content) in breasts is an indicator of higher cancer risk. Simulations for 5 mm thick breast biopsies composed of fibrous, cancer, and fat and for 4.2 cm thick breast fat/fibrous phantoms were done. Data from experimental studies using plastic biopsies were analyzed. The 5 mm diameter 5 mm thick plastic samples consisted of layers of polycarbonate (lexan), polymethyl methacrylate (PMMA-lucite) and polyethylene (polyet). In terms of the total linear attenuation coefficients, lexan ≡ fibrous, lucite ≡ cancer and polyet ≡ fat. The detectors were of two types, photon counting (CdTe) and energy integrating (CCD). For biopsies, three photon counting methods were performed to estimate the fat (polyet) using simulation and experimental data, respectively. The two basis function method that assumed the biopsies were composed of two materials, fat and a 50:50 mixture of fibrous (lexan) and cancer (lucite) appears to be the most promising method. Discrepancies were observed between the results obtained via simulation and experiment. Potential causes are the spectrum and the attenuation coefficient values used for simulations. An energy integrating method was compared to the two basis function method using experimental and simulation data. A slight advantage was observed for photon counting whereas both detectors gave similar results for the 4.2 cm thick breast phantom simulations. The percentage of fibrous within a 9 cm diameter circular phantom of fibrous/fat tissue was estimated via a fan beam geometry simulation. Both methods yielded good results. Computed tomography (CT) images of the circular phantom were obtained using both detector types. The radon transforms were estimated via four energy integrating
Time-dependent density-functional theory for extended systems
Energy Technology Data Exchange (ETDEWEB)
Botti, Silvana [European Theoretical Spectroscopy Facility (ETSF) (Country Unknown); Schindlmayr, Arno [European Theoretical Spectroscopy Facility (ETSF) (Country Unknown); Del Sole, Rodolfo [European Theoretical Spectroscopy Facility (ETSF) (Country Unknown); Reining, Lucia [European Theoretical Spectroscopy Facility (ETSF) (Country Unknown)
2007-03-15
For the calculation of neutral excitations, time-dependent density functional theory (TDDFT) is an exact reformulation of the many-body time-dependent Schroedinger equation, based on knowledge of the density instead of the many-body wavefunction. The density can be determined in an efficient scheme by solving one-particle non-interacting Schroedinger equations-the Kohn-Sham equations. The complication of the problem is hidden in the-unknown-time-dependent exchange and correlation potential that appears in the Kohn-Sham equations and for which it is essential to find good approximations. Many approximations have been suggested and tested for finite systems, where even the very simple adiabatic local-density approximation (ALDA) has often proved to be successful. In the case of solids, ALDA fails to reproduce optical absorption spectra, which are instead well described by solving the Bethe-Salpeter equation of many-body perturbation theory (MBPT). On the other hand, ALDA can lead to excellent results for loss functions (at vanishing and finite momentum transfer). In view of this and thanks to recent successful developments of improved linear-response kernels derived from MBPT, TDDFT is today considered a promising alternative to MBPT for the calculation of electronic spectra, even for solids. After reviewing the fundamentals of TDDFT within linear response, we discuss different approaches and a variety of applications to extended systems.
Covariant density functional theory: Reexamining the structure of superheavy nuclei
Agbemava, S E; Nakatsukasa, T; Ring, P
2015-01-01
A systematic investigation of even-even superheavy elements in the region of proton numbers $100 \\leq Z \\leq 130$ and in the region of neutron numbers from the proton-drip line up to neutron number $N=196$ is presented. For this study we use five most up-to-date covariant energy density functionals of different types, with a non-linear meson coupling, with density dependent meson couplings, and with density-dependent zero-range interactions. Pairing correlations are treated within relativistic Hartree-Bogoliubov (RHB) theory based on an effective separable particle-particle interaction of finite range and deformation effects are taken into account. This allows us to assess the spread of theoretical predictions within the present covariant models for the binding energies, deformation parameters, shell structures and $\\alpha$-decay half-lives. Contrary to the previous studies in covariant density functional theory, it was found that the impact of $N=172$ spherical shell gap on the structure of superheavy elemen...
Open-system Kohn-Sham density functional theory.
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
Novel blind source separation algorithm using Gaussian mixture density function
Institute of Scientific and Technical Information of China (English)
孔薇; 杨杰; 周越
2004-01-01
The blind source separation (BSS) is an important task for numerous applications in signal processing, communications and array processing. But for many complex sources blind separation algorithms are not efficient because the probability distribution of the sources cannot be estimated accurately. So in this paper, to justify the ME(maximum enteropy) approach, the relation between the ME and the MMI(minimum mutual information) is elucidated first. Then a novel algorithm that uses Gaussian mixture density to approximate the probability distribution of the sources is presented based on the ME approach. The experiment of the BSS of ship-radiated noise demonstrates that the proposed algorithm is valid and efficient.
What Density Functional Theory could do for Quantum Information
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.
Resveratrol preserves cerebrovascular density and cognitive function in aging mice
Directory of Open Access Journals (Sweden)
Charlotte A Oomen
2009-12-01
Full Text Available Resveratrol, a natural polyphenol abundant in grapes and red wine, has been reported to exert numerous beneficial health effects. Among others, acute neuroprotective effects of resveratrol have been reported in several models of neurodegeneration, both in vitro and in vivo. In the present study we examined the neuroprotective effects of long term dietary supplementation with resveratrol in mice on behavioral, neurochemical and cerebrovascular level. We report a preserved cognitive function in resveratrol treated aging mice, as shown by an enhanced acquisition of a spatial Y-maze task. This was paralleled by a higher microvascular density and a lower number of microvascular abnormalities in comparison to aging non-treated control animals. We found no effects of resveratrol supplementation on cholinergic cell number or fiber density. The present findings support the hypothesis that resveratrol exerts beneficial effects on the brain by maintaining cerebrovascular health. Via this mechanism resveratrol can contribute to the preservation of cognitive function during aging.
The neutron polaron as a constraint on nuclear density functionals
Forbes, M M; Hebeler, K; Lesinski, T; Schwenk, A
2013-01-01
We study the energy of an impurity that interacts strongly in a sea of fermions when the effective range of the impurity-fermion interaction becomes important. This directly maps the Fermi polaron of condensed matter physics and ultracold atoms to strongly interacting neutrons. We present first Quantum Monte Carlo results for the neutron polaron and compare these with calculations based on effective field theory that also include contributions beyond effective-range effects. We show that predictions of state-of-the-art nuclear density functionals vary substantially and generally underestimate the neutron polaron energy. Our results thus provide a novel constraint for nuclear density functionals, in particular for the time-odd components.
Excitations and benchmark ensemble density functional theory for two electrons
Pribram-Jones, Aurora; Trail, John R; Burke, Kieron; Needs, Richard J; Ullrich, Carsten A
2014-01-01
A new method for extracting ensemble Kohn-Sham potentials from accurate excited state densities is applied to a variety of two electron systems, exploring the behavior of exact ensemble density functional theory. The issue of separating the Hartree energy and the choice of degenerate eigenstates is explored. A new approximation, spin eigenstate Hartree-exchange (SEHX), is derived. Exact conditions that are proven include the signs of the correlation energy components, the virial theorem for both exchange and correlation, and the asymptotic behavior of the potential for small weights of the excited states. Many energy components are given as a function of the weights for two electrons in a one-dimensional flat box, in a box with a large barrier to create charge transfer excitations, in a three-dimensional harmonic well (Hooke's atom), and for the He atom singlet-triplet ensemble, singlet-triplet-singlet ensemble, and triplet bi-ensemble.
Excitations and benchmark ensemble density functional theory for two electrons
Energy Technology Data Exchange (ETDEWEB)
Pribram-Jones, Aurora; Burke, Kieron [Department of Chemistry, University of California-Irvine, Irvine, California 92697 (United States); Yang, Zeng-hui; Ullrich, Carsten A. [Department of Physics and Astronomy, University of Missouri, Columbia, Missouri 65211 (United States); Trail, John R.; Needs, Richard J. [Theory of Condensed Matter Group, Cavendish Laboratory, University of Cambridge, Cambridge CB3 0HE (United Kingdom)
2014-05-14
A new method for extracting ensemble Kohn-Sham potentials from accurate excited state densities is applied to a variety of two-electron systems, exploring the behavior of exact ensemble density functional theory. The issue of separating the Hartree energy and the choice of degenerate eigenstates is explored. A new approximation, spin eigenstate Hartree-exchange, is derived. Exact conditions that are proven include the signs of the correlation energy components and the asymptotic behavior of the potential for small weights of the excited states. Many energy components are given as a function of the weights for two electrons in a one-dimensional flat box, in a box with a large barrier to create charge transfer excitations, in a three-dimensional harmonic well (Hooke's atom), and for the He atom singlet-triplet ensemble, singlet-triplet-singlet ensemble, and triplet bi-ensemble.
Nonequilibrium Anderson model made simple with density functional theory
Kurth, S.; Stefanucci, G.
2016-12-01
The single-impurity Anderson model is studied within the i-DFT framework, a recently proposed extension of density functional theory (DFT) for the description of electron transport in the steady state. i-DFT is designed to give both the steady current and density at the impurity, and it requires the knowledge of the exchange-correlation (xc) bias and on-site potential (gate). In this work we construct an approximation for both quantities which is accurate in a wide range of temperatures, gates, and biases, thus providing a simple and unifying framework to calculate the differential conductance at negligible computational cost in different regimes. Our results mark a substantial advance for DFT and may inform the construction of functionals applicable to other correlated systems.
Nuclear charge radii: Density functional theory meets Bayesian neural networks
Utama, Raditya; Piekarewicz, Jorge
2016-01-01
The distribution of electric charge in atomic nuclei is fundamental to our understanding of the complex nuclear dynamics and a quintessential observable to validate nuclear structure models. We explore a novel approach that combines sophisticated models of nuclear structure with Bayesian neural networks (BNN) to generate predictions for the charge radii of thousands of nuclei throughout the nuclear chart. A class of relativistic energy density functionals is used to provide robust predictions for nuclear charge radii. In turn, these predictions are refined through Bayesian learning for a neural network that is trained using residuals between theoretical predictions and the experimental data. Although predictions obtained with density functional theory provide a fairly good description of experiment, our results show significant improvement (better than 40%) after BNN refinement. Moreover, these improved results for nuclear charge radii are supplemented with theoretical error bars. We have successfully demonst...
Time-dependent density-functional description of nuclear dynamics
Nakatsukasa, Takashi; Matsuo, Masayuki; Yabana, Kazuhiro
2016-01-01
We present the basic concepts and recent developments in the time-dependent density functional theory (TDDFT) for describing nuclear dynamics at low energy. The symmetry breaking is inherent in nuclear energy density functionals (EDFs), which provides a practical description of important correlations at the ground state. Properties of elementary modes of excitation are strongly influenced by the symmetry breaking and can be studied with TDDFT. In particular, a number of recent developments in the linear response calculation have demonstrated their usefulness in description of collective modes of excitation in nuclei. Unrestricted real-time calculations have also become available in recent years, with new developments for quantitative description of nuclear collision phenomena. There are, however, limitations in the real-time approach; for instance, it cannot describe the many-body quantum tunneling. Thus, we treat the quantum fluctuations associated with slow collective motions assuming that time evolution of...
Semilocal density functional theory with correct surface asymptotics
Constantin, Lucian A.; Fabiano, Eduardo; Pitarke, J. M.; Della Sala, Fabio
2016-03-01
Semilocal density functional theory is the most used computational method for electronic structure calculations in theoretical solid-state physics and quantum chemistry of large systems, providing good accuracy with a very attractive computational cost. Nevertheless, because of the nonlocality of the exchange-correlation hole outside a metal surface, it was always considered inappropriate to describe the correct surface asymptotics. Here, we derive, within the semilocal density functional theory formalism, an exact condition for the imagelike surface asymptotics of both the exchange-correlation energy per particle and potential. We show that this condition can be easily incorporated into a practical computational tool, at the simple meta-generalized-gradient approximation level of theory. Using this tool, we also show that the Airy-gas model exhibits asymptotic properties that are closely related to those at metal surfaces. This result highlights the relevance of the linear effective potential model to the metal surface asymptotics.
Estimation of tiger densities in India using photographic captures and recaptures
Karanth, U.; Nichols, J.D.
1998-01-01
Previously applied methods for estimating tiger (Panthera tigris) abundance using total counts based on tracks have proved unreliable. In this paper we use a field method proposed by Karanth (1995), combining camera-trap photography to identify individual tigers based on stripe patterns, with capture-recapture estimators. We developed a sampling design for camera-trapping and used the approach to estimate tiger population size and density in four representative tiger habitats in different parts of India. The field method worked well and provided data suitable for analysis using closed capture-recapture models. The results suggest the potential for applying this methodology for estimating abundances, survival rates and other population parameters in tigers and other low density, secretive animal species with distinctive coat patterns or other external markings. Estimated probabilities of photo-capturing tigers present in the study sites ranged from 0.75 - 1.00. The estimated mean tiger densities ranged from 4.1 (SE hat= 1.31) to 11.7 (SE hat= 1.93) tigers/100 km2. The results support the previous suggestions of Karanth and Sunquist (1995) that densities of tigers and other large felids may be primarily determined by prey community structure at a given site.
Estimating detection and density of the Andean cat in the high Andes
Reppucci, Juan; Gardner, Beth; Lucherini, Mauro
2011-01-01
The Andean cat (Leopardus jacobita) is one of the most endangered, yet least known, felids. Although the Andean cat is considered at risk of extinction, rigorous quantitative population studies are lacking. Because physical observations of the Andean cat are difficult to make in the wild, we used a camera-trapping array to photo-capture individuals. The survey was conducted in northwestern Argentina at an elevation of approximately 4,200 m during October–December 2006 and April–June 2007. In each year we deployed 22 pairs of camera traps, which were strategically placed. To estimate detection probability and density we applied models for spatial capture–recapture using a Bayesian framework. Estimated densities were 0.07 and 0.12 individual/km2 for 2006 and 2007, respectively. Mean baseline detection probability was estimated at 0.07. By comparison, densities of the Pampas cat (Leopardus colocolo), another poorly known felid that shares its habitat with the Andean cat, were estimated at 0.74–0.79 individual/km2 in the same study area for 2006 and 2007, and its detection probability was estimated at 0.02. Despite having greater detectability, the Andean cat is rarer in the study region than the Pampas cat. Properly accounting for the detection probability is important in making reliable estimates of density, a key parameter in conservation and management decisions for any species.
Density functional theory across chemistry, physics and biology.
van Mourik, Tanja; Bühl, Michael; Gaigeot, Marie-Pierre
2014-03-13
The past decades have seen density functional theory (DFT) evolve from a rising star in computational quantum chemistry to one of its major players. This Theme Issue, which comes half a century after the publication of the Hohenberg-Kohn theorems that laid the foundations of modern DFT, reviews progress and challenges in present-day DFT research. Rather than trying to be comprehensive, this Theme Issue attempts to give a flavour of selected aspects of DFT.
Buckled graphene: A model study based on density functional theory
Khan, Mohammad A.
2010-09-01
We make use of ab initio calculations within density functional theory to investigate the influence of buckling on the electronic structure of single layer graphene. Our systematic study addresses a wide range of bond length and bond angle variations in order to obtain insights into the energy scale associated with the formation of ripples in a graphene sheet. © 2010 Elsevier B.V. All rights reserved.
Probability density function modeling for sub-powered interconnects
Pater, Flavius; Amaricǎi, Alexandru
2016-06-01
This paper proposes three mathematical models for reliability probability density function modeling the interconnect supplied at sub-threshold voltages: spline curve approximations, Gaussian models,and sine interpolation. The proposed analysis aims at determining the most appropriate fitting for the switching delay - probability of correct switching for sub-powered interconnects. We compare the three mathematical models with the Monte-Carlo simulations of interconnects for 45 nm CMOS technology supplied at 0.25V.
Reproducibility in density functional theory calculations of solids
2016-01-01
This is the author accepted manuscript.The final version is available from the American Association for the Advancement of Science via http://dx.doi.org/10.1126/science.aad3000 The widespread popularity of density-functional theory has given rise to a vast range of dedicated codes to predict molecular and crystalline properties. However, each code implements the formalism in a different way, raising questions on the reproducibility of such predictions. We report the results of a community-...
Density functional theory studies of transition metal nanoparticles in catalysis
DEFF Research Database (Denmark)
Greeley, Jeffrey Philip; Rankin, Rees; Zeng, Zhenhua
2013-01-01
Periodic Density Functional Theory calculations are capable of providing powerful insights into the structural, energetics, and electronic phenomena that underlie heterogeneous catalysis on transition metal nanoparticles. Such calculations are now routinely applied to single crystal metal surfaces...... and to subnanometer metal clusters. Descriptions of catalysis on truly nanosized structures, however, are generally not as well developed. In this talk, I will illustrate different approaches to analyzing nanocatalytic phenomena with DFT calculations. I will describe case studies from heterogeneous catalysis...
Density functional theory study on the molecular structure of loganin
Pandey, Anoop Kumar; Siddiqui, Shamoon Ahmad; Dwivedi, Apoorva; Raj, Kanwal; Misra, Neeraj
2011-01-01
The computational Quantum Chemistry (QC) has been used for different types of problems, for example: structural biology, surface phenomena and liquid phase. In this paper we have employed the density functional method for the study of molecular structure of loganin. The equilibrium geometry, harmonic vibrational frequencies and infrared intensities were calculated by B3LYP/6-311G (d, p) method and basis set combinations. It was found that the optimized parameters obtained by the DFT/B3LYP met...
Chemical reactivity in the framework of pair density functional theories.
Otero, Nicolás; Mandado, Marcos
2012-05-15
Chemical reactivity descriptors are derived within the framework of the pair density functional theory. These indices provide valuable information about bonding rearrangements and activating mechanisms upon electrophilic or nucleophilic reactions. Indices derived and tested in this work represent nonlocal counterparts of the local reactivity indices derived in the context of conceptual density functional theory (CDFT) and frequently used in reactivity studies; the Fukui function, the local softness and the dual descriptor. In this work, we show how these nonlocal indices provide a quantum chemical basis to explain the success of qualitative resonance models in chemical reactivity predictions. Also, local information is implicitly contained as CDFT indices are obtained by simple integration. As illustrative examples, we have considered in this work the Markovnikov's rule, the reactivity of enolate anion, the nucleophilic conjugate addition to α,β-unsaturated compounds and the electrophilic aromatic substitution of benzene derivatives. The densities used in this work were obtained with Hartree-Fock, Kohn-Sham DFT, and singles and doubles configuration interaction (CISD) approaches. Copyright © 2012 Wiley Periodicals, Inc.
Linear Scaling Density Functional Calculations with Gaussian Orbitals
Scuseria, Gustavo E.
1999-01-01
Recent advances in linear scaling algorithms that circumvent the computational bottlenecks of large-scale electronic structure simulations make it possible to carry out density functional calculations with Gaussian orbitals on molecules containing more than 1000 atoms and 15000 basis functions using current workstations and personal computers. This paper discusses the recent theoretical developments that have led to these advances and demonstrates in a series of benchmark calculations the present capabilities of state-of-the-art computational quantum chemistry programs for the prediction of molecular structure and properties.
Formation energies of rutile metal dioxides using density functional theory
DEFF Research Database (Denmark)
Martinez, Jose Ignacio; Hansen, Heine Anton; Rossmeisl, Jan
2009-01-01
We apply standard density functional theory at the generalized gradient approximation (GGA) level to study the stability of rutile metal oxides. It is well known that standard GGA exchange and correlation in some cases is not sufficient to address reduction and oxidation reactions. Especially...... and due to a more accurate description of exchange for this particular GGA functional compared to PBE. Furthermore, we would expect the self-interaction problem to be largest for the most localized d orbitals; that means the late 3d metals and since Co, Fe, Ni, and Cu do not form rutile oxides...
Atomistic force field for alumina fit to density functional theory.
Sarsam, Joanne; Finnis, Michael W; Tangney, Paul
2013-11-28
We present a force field for bulk alumina (Al2O3), which has been parametrized by fitting the energies, forces, and stresses of a large database of reference configurations to those calculated with density functional theory (DFT). We use a functional form that is simpler and computationally more efficient than some existing models of alumina parametrized by a similar technique. Nevertheless, we demonstrate an accuracy of our potential that is comparable to those existing models and to DFT. We present calculations of crystal structures and energies, elastic constants, phonon spectra, thermal expansion, and point defect formation energies.
Time-dependent density-functional theory concepts and applications
Ullrich, Carsten A
2011-01-01
Time-dependent density-functional theory (TDDFT) describes the quantum dynamics of interacting electronic many-body systems formally exactly and in a practical and efficient manner. TDDFT has become the leading method for calculating excitation energies and optical properties of large molecules, with accuracies that rival traditional wave-function based methods, but at a fraction of the computational cost.This book is the first graduate-level text on the concepts and applications of TDDFT, including many examples and exercises, and extensive coverage of the literature. The book begins with a s
Effects of tissue heterogeneity on the optical estimate of breast density
Taroni, Paola; Pifferi, Antonio; Quarto, Giovanna; Spinelli, Lorenzo; Torricelli, Alessandro; Abbate, Francesca; Balestreri, Nicola; Ganino, Serena; Menna, Simona; Cassano, Enrico; Cubeddu, Rinaldo
2012-01-01
Breast density is a recognized strong and independent risk factor for developing breast cancer. At present, breast density is assessed based on the radiological appearance of breast tissue, thus relying on the use of ionizing radiation. We have previously obtained encouraging preliminary results with our portable instrument for time domain optical mammography performed at 7 wavelengths (635–1060 nm). In that case, information was averaged over four images (cranio-caudal and oblique views of both breasts) available for each subject. In the present work, we tested the effectiveness of just one or few point measurements, to investigate if tissue heterogeneity significantly affects the correlation between optically derived parameters and mammographic density. Data show that parameters estimated through a single optical measurement correlate strongly with mammographic density estimated by using BIRADS categories. A central position is optimal for the measurement, but its exact location is not critical. PMID:23082283
[Estimation of Hunan forest carbon density based on spectral mixture analysis of MODIS data].
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.