More on the long time stability of Feynman-Kac semigroups

被引:15
作者
Ferre, Gregoire [1 ]
Rousset, Mathias [2 ,3 ]
Stoltz, Gabriel [1 ]
机构
[1] Univ Paris Est, CERMICS, ENPC, Inria, F-77455 Marne La Vallee, France
[2] INRIA Rennes, Bretagne Atlantique, Rennes, France
[3] Univ Rennes 1, IRMAR, Rennes, France
来源
STOCHASTICS AND PARTIAL DIFFERENTIAL EQUATIONS-ANALYSIS AND COMPUTATIONS | 2021年 / 9卷 / 03期
基金
欧洲研究理事会;
关键词
Feynman-Kac dynamics; Ergodicity; Spectral analysis; Large deviations; BACKWARD ERROR ANALYSIS; DIFFERENTIAL-EQUATIONS; SUBGEOMETRIC RATES; ERGODIC PROPERTIES; SPECTRAL THEORY; MARKOV; CONVERGENCE; DEVIATIONS; RADIUS;
D O I
10.1007/s40072-020-00178-3
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
Feynman-Kac semigroups appear in various areas of mathematics: non-linear filtering, large deviations theory, spectral analysis of Schrodinger operators among others. Their long time behavior provides important information, for example in terms of ground state energy of Schrodinger operators, or scaled cumulant generating function in large deviations theory. In this paper, we propose a simple and natural extension of the stability analysis of Markov chains for these non-linear evolutions. As other classical ergodicity results, it relies on two assumptions: a Lyapunov condition that induces some compactness, and a minorization condition ensuring some mixing. We show that these conditions are satisfied in a variety of situations, including stochastic differential equations. Illustrative examples are provided, where the stability of the non-linear semigroup arises either from the underlying dynamics or from the Feynman-Kac weight function. We also use our technique to provide uniform in the time step convergence estimates for discretizations of stochastic differential equations.
引用
收藏
页码:630 / 673
页数:44
相关论文
共 61 条
[1]   RANDOM-WALK SIMULATION OF SCHRODINGER EQUATION - H+3 [J].
ANDERSON, JB .
JOURNAL OF CHEMICAL PHYSICS, 1975, 63 (04) :1499-1503
[2]  
[Anonymous], 2006, MATH SURVEYS MONOGRA
[3]   A simple proof of the Poincare inequality for a large class of probability measures including the log-concave case [J].
Bakry, Dominique ;
Barthe, Franck ;
Cattiaux, Patrick ;
Guillin, Arnaud .
ELECTRONIC COMMUNICATIONS IN PROBABILITY, 2008, 13 :60-66
[4]   The law of the Euler scheme for stochastic differential equations .1. Convergence rate of the distribution function [J].
Bally, V ;
Talay, D .
PROBABILITY THEORY AND RELATED FIELDS, 1996, 104 (01) :43-60
[5]   Ergodic Behavior of Non-conservative Semigroups via Generalized Doeblin's Conditions [J].
Bansaye, Vincent ;
Cloez, Bertrand ;
Gabriel, Pierre .
ACTA APPLICANDAE MATHEMATICAE, 2020, 166 (01) :29-72
[6]   Nonasymptotic mixing of the MALA algorithm [J].
Bou-Rabee, N. ;
Hairer, M. .
IMA JOURNAL OF NUMERICAL ANALYSIS, 2013, 33 (01) :80-110
[7]   GROUND-STATE OF THE ELECTRON-GAS BY A STOCHASTIC METHOD [J].
CEPERLEY, DM ;
ALDER, BJ .
PHYSICAL REVIEW LETTERS, 1980, 45 (07) :566-569
[8]  
Champagnat N., 2017, ARXIV170401928
[9]  
Champagnat N., 2017, ANN FS TOULOUSE MATH
[10]   WEAK BACKWARD ERROR ANALYSIS FOR SDEs [J].
Debussche, Arnaud ;
Faou, Erwan .
SIAM JOURNAL ON NUMERICAL ANALYSIS, 2012, 50 (03) :1735-1752