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相关论文: Kullback--Leibler Divergence of a Freely Cooling G…

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Whereas the original Boltzmann's $H$-theorem applies to elastic collisions, its rigorous generalization to the inelastic case is still lacking. Nonetheless, it has been conjectured in the literature that the relative entropy of the velocity…

软凝聚态物质 · 物理学 2021-06-09 Alberto Megías , Andrés Santos

Universal hypothesis testing refers to the problem of deciding whether samples come from a nominal distribution or an unknown distribution that is different from the nominal distribution. Hoeffding's test, whose test statistic is equivalent…

信息论 · 计算机科学 2017-11-15 Pengfei Yang , Biao Chen

The velocity distribution of inelastic granular gas is examined numerically on two dimensional hard disk system in nearly elastic regime using molecular dynamical simulations. The system is prepared initially in the equilibrium state with…

统计力学 · 物理学 2009-11-07 Hiizu Nakanishi

One of the fundamental open questions in plasma physics is the role of non-thermal particles distributions in poorly collisional plasma environments, a system commonly found throughout the Universe, e.g. the solar wind and the Earth's…

等离子体物理 · 物理学 2021-04-15 Belén Acosta , Denisse Pastén , Pablo S. Moya

The inhomogeneous cooling state describing the hydrodynamic behavior of a freely evolving granular gas strongly confined between two parallel plates is studied, using a Boltzmann kinetic equation derived recently. By extending the idea of…

统计力学 · 物理学 2019-12-20 J. Javier Brey , M. I. García de Soria , P. Maynar

We study the problem of characterizing the stability of Kullback-Leibler (KL) divergence under Gaussian perturbations beyond Gaussian families. Existing relaxed triangle inequalities for KL divergence critically rely on the assumption that…

机器学习 · 计算机科学 2026-04-17 Jialu Pan , Yufeng Zhang , Nan Hu , Zhenbang Chen , Ji Wang , Keqin Li

We examine the estimation of the Kullback-Leibler (KL) divergence and the use of the goodness-of-fit test for multivariate continuous distributions. Our starting point is the maximum entropy principle for Shannon entropy: among all…

统计理论 · 数学 2026-03-10 Mehmet Siddik Cadirci , Martin Singull

The $H$-theorem, originally derived at the level of Boltzmann non-linear kinetic equation for a dilute gas undergoing elastic collisions, strongly constrains the velocity distribution of the gas to evolve irreversibly towards equilibrium.…

统计力学 · 物理学 2016-03-24 M. I. García de Soria , P. Maynar , S. Mischler , C. Mouhot , T. Rey , E. Trizac

The Kullback-Leibler (KL) divergence is not a proper distance metric and does not satisfy the triangle inequality, posing theoretical challenges in certain practical applications. Existing work has demonstrated that KL divergence between…

机器学习 · 统计学 2026-03-03 Shiji Xiao , Yufeng Zhang , Chubo Liu , Yan Ding , Keqin Li , Kenli Li

We study the single particle velocity distribution for a granular fluid of inelastic hard spheres or disks, using the Enskog-Boltzmann equation, both for the homogeneous cooling of a freely evolving system and for the stationary state of a…

统计力学 · 物理学 2007-05-23 T. P. C. van Noije , M. H. Ernst

The authors present a study of the non equilibrium statistical properties of a one dimensional hard-rod fluid dissipating energy via inelastic collisions and subject to the action of a Gaussian heat bath, simulating an external driving…

材料科学 · 物理学 2009-11-13 Umberto Marini-Bettolo-Marconi , Pedro Tarazona , Fabio Cecconi

We consider the single-particle velocity distribution of a one-dimensional fluid of inelastic particles. Both the freely evolving (cooling) system and the non-equilibrium stationary state obtained in the presence of random forcing are…

统计力学 · 物理学 2009-11-07 A. Barrat , T. Biben , Z. Racz , E. Trizac , F. van Wijland

This short note is on a property of the Kullback-Leibler (KL) divergence which indicates that independent Gaussian distributions minimize the KL divergence from given independent Gaussian distributions. The primary purpose of this note is…

信息论 · 计算机科学 2020-12-04 Song Fang , Quanyan Zhu

An approximate partition functional is derived for the infinite-dimensional Hubbard model. This functional naturally includes the exact solution of the Falicov-Kimball model as a special case, and is exact in the uncorrelated and atomic…

凝聚态物理 · 物理学 2009-10-22 Y. M. Li , N. d'Ambrumenil

This study aims to quantify and visualize the degradation of fidelity (information degradation) that inevitably accompanies the replication of information within the framework of information thermodynamics and to propose an…

数学物理 · 物理学 2025-11-20 Tatsuaki Tsuruyama

The expansion of the velocity distribution function for the homogeneous cooling state (HCS) in a Sonine polynomial series around a Maxwellian is shown to be divergent, though Borel resummable. A convergent expansion for the HCS has been…

软凝聚态物质 · 物理学 2007-05-23 S. H. Noskowicz , O. Bar-Lev , D. Serero , I. Goldhirsch

We propose a variational framework for nonequilibrium thermodynamics built around the effective number of accessible state, a multiplicative count that ranges from for a uniform distribution to one under complete localization, and whose…

统计力学 · 物理学 2025-09-12 Mesfin Taye

In this article we study a fully relativistic model of a two dimensional hard-disk gas. This model avoids the general problems associated with relativistic particle collisions and is therefore an ideal system to study relativistic effects…

统计力学 · 物理学 2009-11-13 Afshin Montakhab , Malihe Ghodrat , Mahmood Barati

This work presents an upper-bound to value that the Kullback-Leibler (KL) divergence can reach for a class of probability distributions called quantum distributions (QD). The aim is to find a distribution $U$ which maximizes the KL…

机器学习 · 计算机科学 2020-12-11 Vincenzo Bonnici

Kullback-Leibler (KL) divergence is one of the most important divergence measures between probability distributions. In this paper, we prove several properties of KL divergence between multivariate Gaussian distributions. First, for any two…

信息论 · 计算机科学 2023-01-24 Yufeng Zhang , Wanwei Liu , Zhenbang Chen , Ji Wang , Kenli Li
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