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We study a large deviation functional of density fluctuation by analyzing stochastic non-linear diffusion equations driven by the difference between the densities fixed at the boundaries. By using a fundamental equality that yields the…

Statistical Mechanics · Physics 2009-11-13 Shin-ichi Sasa

We derive analytic formulas to reconstruct particle-averaged quantities from experimental results that suffer from the efficiency loss of particle measurements. These formulas are derived under the assumption that the probabilities of…

Data Analysis, Statistics and Probability · Physics 2025-10-17 Masakiyo Kitazawa , ShinIchi Esumi , Takafumi Niida , Toshihiro Nonaka

We present a novel approach to Bayesian inference and general Bayesian computation that is defined through a sequential decision loop. Our method defines a recursive partitioning of the sample space. It neither relies on gradients nor…

Machine Learning · Statistics 2021-06-10 Erik Bodin , Zhenwen Dai , Neill D. F. Campbell , Carl Henrik Ek

This paper develops methods of distributed Bayesian hypothesis tests for fault detection and diagnosis that are based on belief propagation and optimization in graphical models. The main challenges in developing distributed statistical…

Systems and Control · Computer Science 2015-01-20 Kwang-Ki K. Kim

This paper deals with the estimation of the quadrature error of a Gaussian formula for weight functions involving fractional powers, exponentials and Bessel functions of the first kind. For this purpose, in this work the averaged and…

Numerical Analysis · Mathematics 2023-01-30 Eleonora Denich

A variational formulation for the calculation of interacting fermion systems based on the density-matrix functional theory is presented. Our formalism provides for a natural integration of explicit many-particle effects into standard…

Strongly Correlated Electrons · Physics 2013-05-29 Peter E. Bloechl , Christian F. J. Walther , Thomas Pruschke

Multicellular systems play a key role in bioprocess and biomedical engineering. Cell ensembles encountered in these setups show phenotypic variability like size and biochemical composition. As this variability may result in undesired…

Systems and Control · Computer Science 2018-07-16 Armin Küper , Robert Dürr , Steffen Waldherr

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…

Computational Physics · Physics 2016-08-02 Jeffrey M. McMahon

Machine learning techniques are utilized to estimate the electronic band gap energy and forecast the band gap category of materials based on experimentally quantifiable properties. The determination of band gap energy is critical for…

Materials Science · Physics 2024-03-11 Sagar Prakash Barad , Sajag Kumar , Subhankar Mishra

Alchemical perturbation density functional theory has been shown to be an efficient and computationally inexpensive way to explore chemical compound space. We investigate approximations made, in terms of atomic basis sets and perturbation…

Chemical Physics · Physics 2020-10-28 Giorgio Domenichini , Guido Falk von Rudorff , O. Anatole von Lilienfeld

Response calculations in density functional theory aim at computing the change in ground-state density induced by an external perturbation. At finite temperature these are usually performed by computing variations of orbitals, which involve…

Numerical Analysis · Mathematics 2023-04-04 Eric Cancès , Michael F. Herbst , Gaspard Kemlin , Antoine Levitt , Benjamin Stamm

When a mathematical or computational model is used to analyse some system, it is usual that some parameters resp.\ functions or fields in the model are not known, and hence uncertain. These parametric quantities are then identified by…

Probability · Mathematics 2016-07-01 Hermann G. Matthies , Elmar Zander , Bojana Rosic , Alexander Litvinenko

We argue that any general mathematical measure of density error, no matter how reasonable, is too arbitrary to be of universal use. However the energy functional itself provides a universal relevant measure of density errors. For the…

Computational Physics · Physics 2018-11-13 Eunji Sim , Suhwan Song , Kieron Burke

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…

Chemical Physics · Physics 2016-06-01 Aurora Pribram-Jones , Kieron Burke

The energy-energy correlation function of the two-dimensional Ising model with weakly fluctuating random bonds is evaluated in the large scale limit. Two correlation lengths exist in contrast to one correlation length in the pure 2D Ising…

Condensed Matter · Physics 2007-05-23 K. Ziegler

Since the baryon-number susceptibilities are correlated with the cumulant of baryon-number fluctuations in experiments, we do calculations of the susceptibilities and compare them with the experimental fluctuation data under the framework…

High Energy Physics - Phenomenology · Physics 2015-06-23 A-Meng Zhao , Zhu-Fang Cui , Yu Jiang , Hong-Shi Zong

We present a review of the basic ideas and techniques of the spectral density functional theory which are currently used in electronic structure calculations of strongly-correlated materials where the one-electron description breaks down.…

Strongly Correlated Electrons · Physics 2009-11-11 G. Kotliar , S. Y. Savrasov , K. Haule , V. S. Oudovenko , O. Parcollet , C. A. Marianetti

The skewness and the kurtosis of the baryon number distributions are computed within QCD-improved low energy effective models including quantum thermal and density fluctuations. The results are compared with the Beam Energy Scan experiment…

High Energy Physics - Phenomenology · Physics 2016-06-01 Wei-jie Fu , Jan M. Pawlowski

We combine density-functional theory with density-matrix functional theory to get the best of both worlds. This is achieved by range separation of the electronic interaction which permits to rigorously combine a short-range density…

Chemical Physics · Physics 2015-05-19 Daniel R. Rohr , Julien Toulouse , Katarzyna Pernal

Motivated by inferring cellular signaling networks using noisy flow cytometry data, we develop procedures to draw inference for Bayesian networks based on error-prone data. Two methods for inferring causal relationships between nodes in a…

Methodology · Statistics 2020-02-11 Xianzheng Huang , Hongmei Zhang