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Related papers: On $\mathcal H^1$ and entropic convergence for con…

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This review concerns recent results on the quantitative study of convergence towards the stationary state for spatially inhomogeneous kinetic equations. We focus on analytical results obtained by means of certain probabilistic techniques…

Analysis of PDEs · Mathematics 2023-04-05 Havva Yoldaş

By constructing successful couplings for degenerate diffusion processes, explicit derivative formula and Harnack type inequalities are presented for solutions to a class of degenerate Fokker-Planck equations on $\R^m\times\R^{d}$. The main…

Probability · Mathematics 2012-03-13 Arnaud Guillin , Feng-Yu Wang

Similarity-sensitive entropy measures the uncertainty of a probability law relative to a similarity kernel that encodes the distinguishability between states. We develop a measure-theoretic treatment covering both finite similarity matrices…

Probability · Mathematics 2026-05-29 Joseph Samuel Miller

We consider a class of stochastic processes and establish its connection to $p$-harmonic functions. In particular, we obtain stochastic approximations that converge uniformly to a $p$-harmonic function, with an explicit convergence rate,…

Analysis of PDEs · Mathematics 2016-05-19 Hannes Luiro , Mikko Parviainen

It is known that many classical inequalities linked to convolutions can be obtained by looking at the monotonicity in time of convolutions of powers of solutions to the heat equation, provided that both the exponents and the coefficients of…

Mathematical Physics · Physics 2013-09-26 Giuseppe Toscani

The entropy of a binary symmetric Hidden Markov Process is calculated as an expansion in the noise parameter epsilon. We map the problem onto a one-dimensional Ising model in a large field of random signs and calculate the expansion…

Information Theory · Computer Science 2009-11-11 O. Zuk , I. Kanter , E. Domany

In this article we derive Talagrand's $T_2$ inequality on the path space w.r.t. the maximum norm for various stochastic processes, including solutions of one-dimensional stochastic differential equations with measurable drifts, backward…

Probability · Mathematics 2020-08-12 Daniel Bartl , Ludovic Tangpi

The paper presents efficient approaches for evaluating convergence rate in total variation for finite and general linear Markov chains. The motivation for studying convergence rate in this metric is its usefulness in various limit theorems.…

Probability · Mathematics 2026-01-21 Alexander Veretennikov

In a quantum (inhomogeneous) Markov process $\rho_1:=\Gamma_1(\rho)$, $\rho_2:=\Gamma_1(\rho_1)$, ..., where $\Gamma_i$ are CPTP maps and $\rho$ is the initial state, the the state of the system is either oscillatory or convergent to a…

Quantum Physics · Physics 2012-12-17 Keiji Matsumoto

The study of time-inhomogeneous Markov jump processes is a traditional topic within probability theory that has recently attracted substantial attention in various applications. However, their flexibility also incurs a substantial…

Probability · Mathematics 2023-11-03 Martin Bladt , Oscar Peralta

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 consider a Markovian evolution on point processes, the $\Psi$--process, on the unit interval in which points are added according to a rule that depends only on the spacings of the existing point configuration. Having chosen a spacing, a…

Probability · Mathematics 2020-07-01 Pascal Maillard , Elliot Paquette

We consider the class of Piecewise Deterministic Markov Processes (PDMP), whose state space is $\R\_{+}^{*}$, that possess an increasing deterministic motion and that shrink deterministically when they jump. Well known examples for this…

Statistics Theory · Mathematics 2015-03-12 Nathalie Krell

Assuming the dynamical convergence $P_t^\varepsilon\to\bar P_t$ for singular limits of time-homogeneous Markov diffusion semigroups, we develop a semigroup-level framework that upgrades this convergence into four levels of thermodynamic…

Probability · Mathematics 2026-03-17 Xinyu Zhang , Liu Hong

Following earlier work, reference is made to the classical entropic force which results from spatially variable disorder, an exclusively repulsive force. In terms of macroscopic variables it is applied to magnetohydrodynamics, causing minor…

Space Physics · Physics 2023-05-16 W. Baumjohann , R. A. Treumann

Motivated by entropic optimal transport, time reversal of diffusion processes is revisited. An integration by parts formula is derived for the carr\'e du champ of a Markov process in an abstract space. It leads to a time reversal formula…

Probability · Mathematics 2022-09-05 Patrick Cattiaux , Giovanni Conforti , Ivan Gentil , Christian Léonard

In piecewise-deterministic Markov processes (PDMPs) the state of a finite-dimensional system evolves continuously, but the evolutive equation may change randomly as a result of discrete switches. A running cost is integrated along the…

Optimization and Control · Mathematics 2023-02-27 Elliot Cartee , Antonio Farah , April Nellis , Jacob van Hook , Alexander Vladimirsky

We propose a method based on continuous time Markov chain approximation to compute the distribution of Parisian stopping times and price Parisian options under general one-dimensional Markov processes. We prove the convergence of the method…

Computational Finance · Quantitative Finance 2021-07-15 Gongqiu Zhang , Lingfei Li

General hyperbolic systems of balance laws with inhomogeneity in space and time in all constitutive functions are studied in the context of relative entropy. A framework is developed in this setting that contributes to a measure-valued weak…

Analysis of PDEs · Mathematics 2022-06-02 Cleopatra Christoforou

The master equation and, more generally, Markov processes are routinely used as models for stochastic processes. They are often justified on the basis of randomization and coarse-graining assumptions. Here instead, we derive n-th order…

Statistical Mechanics · Physics 2012-09-27 Julian Lee , Steve Pressé