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Computing solutions to partial differential equations using the fast Fourier transform can lead to unwanted oscillatory behavior. Due to the periodic nature of the discrete Fourier transform, waves that leave the computational domain on one…

Numerical Analysis · Mathematics 2023-01-18 Anne Liu , Thomas Trogdon

A fully discrete Lagrangian scheme for numerical solution of the nonlinear fourth order DLSS equation in one space dimension is analyzed. The discretization is based on the equation's gradient flow structure in the $L^2$-Wasserstein metric.…

Numerical Analysis · Mathematics 2014-10-08 Daniel Matthes , Horst Osberger

Structure-preserving finite-difference schemes for general nonlinear fourth-order parabolic equations on the one-dimensional torus are derived. Examples include the thin-film and the Derrida-Lebowitz-Speer-Spohn equations. The schemes…

Numerical Analysis · Mathematics 2020-01-14 Marcel Braukhoff , Ansgar Jüngel

We provide a refined explicit estimate of exponential decay rate of underdamped Langevin dynamics in $L^2$ distance, based on a framework developed in [1]. To achieve this, we first prove a Poincar\'{e}-type inequality with Gibbs measure in…

Analysis of PDEs · Mathematics 2023-08-25 Yu Cao , Jianfeng Lu , Lihan Wang

In this paper we present a formulation of the nonlinear stochastic differential equation which allows for systematic approximations. The method is not restricted to the asymptotic, i.e., stationary, regime but can be applied to derive…

chao-dyn · Physics 2009-10-22 A. Crisanti , U. Marini Bettolo Marconi

In this article, we provide a general strategy based on Lyapunov functionals to analyse global asymptotic stability of linear infinite-dimensional systems subject to nonlinear dampings under the assumption that the origin of the system is…

Analysis of PDEs · Mathematics 2018-08-17 Swann Marx , Yacine Chitour , Christophe Prieur

In this work we use the extremization method of various information-theoretic measures (Fisher information, Shannon entropy, Tsallis entropy) for $d$-dimensional quantum systems, which complementary describe the spreading of the quantum…

Quantum Physics · Physics 2016-10-07 I. V. Toranzo , S. López-Rosa , R. O. Esquivel , J. S. Dehesa

We propose and investigate a method for identifying timescales of dissipation in nonequilibrium steady states modeled as discrete-state Markov jump processes. The method is based on how the irreversibility-measured by the statistical…

Statistical Mechanics · Physics 2023-07-24 Freddy A. Cisneros , Nikta Fakhri , Jordan M. Horowitz

We study the nonlinear Fokker-Planck equation on graphs, which is the gradient flow in the space of probability measures supported on the nodes with respect to the discrete Wasserstein metric. The energy functional driving the gradient flow…

Dynamical Systems · Mathematics 2017-09-26 Shui-Nee Chow , Wuchen Li , Haomin Zhou

Boltzmann-Sanov and Cramer-Chernoff's theorems provide large deviation probabilities, entropy, and rate functions for the spatial distribution of systems and the total internal energy of an ensemble respectively. By the method of Lagrange's…

Statistical Mechanics · Physics 2021-09-17 D. P. Shinde

We present in this work variants of existing estimates for the Landau or Landau-Fermi-Dirac entropy dissipation, in terms of Fisher information, in the hard potential case. The specificity of those variants is that the entropy is never used…

Analysis of PDEs · Mathematics 2024-01-08 Laurent Desvillettes

Techniques from numerical bifurcation theory are very useful to study transitions between steady fluid flow patterns and the instabilities involved. Here, we provide computational methodology to use parameter continuation in determining…

Numerical Analysis · Mathematics 2020-11-12 S. Baars , J. P. Viebahn , T. E. Mulder , C. Kuehn , F. W. Wubs , H. A. Dijkstra

The estimation of information measures of continuous distributions based on samples is a fundamental problem in statistics and machine learning. In this paper, we analyze estimates of differential entropy in $K$-dimensional Euclidean space,…

Information Theory · Computer Science 2021-11-29 Georg Pichler , Pablo Piantanida , Günther Koliander

We study the approach to equilibrium of systems of gas particles in terms of relative entropy. The systems are modeled by the Kac master equation in arbitrary dimensions. First, we study the Kac system coupled to a thermostat, and secondly…

Mathematical Physics · Physics 2023-01-24 Lukas Hauger

In this article, we prove the Eyring-Kramers formula for non-reversible metastable diffusion processes that have a Gibbs invariant measure. Our result indicates that non-reversible processes exhibit faster metastable transitions between…

Probability · Mathematics 2021-12-20 Jungkyoung Lee , Insuk Seo

Relative to the Gaussian measure on $\mathbb{R}^d$, entropy and Fisher information are famously related via Gross' logarithmic Sobolev inequality (LSI). These same functionals also separately satisfy convolution inequalities, as proved by…

Information Theory · Computer Science 2016-08-22 Thomas A. Courtade

For stochastic wave equation, when the dissipative damping is a non-globally Lipschitz function of the velocity, there are few results on the long-time dynamics, in particular, the exponential ergodicity and strong law of large numbers, for…

Probability · Mathematics 2024-02-05 Meng Cai , Chuchu Chen , Jialin Hong , Tau Zhou

We introduce a new method permitting the analytical determination of entanglement entropy (and related quantities) between configurations of a quantum field, which is either free or in interaction with a classical source, at two distinct…

High Energy Physics - Theory · Physics 2021-10-13 Jerome Martin , Vincent Vennin

Relying on the reverse-time space-time harmonic property of the ratio of two solutions of the Fokker-Plank equation, we establish an explicit formula for derivative of the \emph{varentropy} for a Markov diffusion process. The formula…

Probability · Mathematics 2023-11-14 Michele Pavon

We present a framework that allows for the non-asymptotic study of the $2$-Wasserstein distance between the invariant distribution of an ergodic stochastic differential equation and the distribution of its numerical approximation in the…

Machine Learning · Statistics 2021-09-27 J. M. Sanz-Serna , Konstantinos C. Zygalakis