Splitting AVF method for generalized Langevin equations: probability density function and geometric ergodicity

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Hauptverfasser: Dai, Xinjie, Liu, Xingyu, Jin, Diancong, Sun, Liying
Format: Preprint
Veröffentlicht: 2026
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author Dai, Xinjie
Liu, Xingyu
Jin, Diancong
Sun, Liying
author_facet Dai, Xinjie
Liu, Xingyu
Jin, Diancong
Sun, Liying
contents The generalized Langevin equation (GLE) constitutes a fundamental model for describing nonequilibrium dynamics with memory effects. To overcome the numerical challenges arising from superquadratically growing potentials and degenerate noise, we propose and analyze a structure-preserving splitting averaged vector field (AVF) method for a quasi-Markovian GLE. The core advantage of this method lies in its ability to simultaneously preserve the exponential integrability, Malliavin differentiability, and ergodicity of the underlying continuous system. Notably, by leveraging exponential integrability, Malliavin differentiability, and uniform non-degeneracy of the numerical solution, we obtain the existence and smoothness of its probability density function, which converges to that of the exact solution with first-order accuracy. Furthermore, by validating the Lyapunov condition and the minorization condition using a localized technique, we establish the geometric ergodicity of the numerical solution. Finally, numerical experiments are conducted to confirm the theoretical results.
format Preprint
id arxiv_https___arxiv_org_abs_2604_25717
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Splitting AVF method for generalized Langevin equations: probability density function and geometric ergodicity
Dai, Xinjie
Liu, Xingyu
Jin, Diancong
Sun, Liying
Numerical Analysis
Probability
The generalized Langevin equation (GLE) constitutes a fundamental model for describing nonequilibrium dynamics with memory effects. To overcome the numerical challenges arising from superquadratically growing potentials and degenerate noise, we propose and analyze a structure-preserving splitting averaged vector field (AVF) method for a quasi-Markovian GLE. The core advantage of this method lies in its ability to simultaneously preserve the exponential integrability, Malliavin differentiability, and ergodicity of the underlying continuous system. Notably, by leveraging exponential integrability, Malliavin differentiability, and uniform non-degeneracy of the numerical solution, we obtain the existence and smoothness of its probability density function, which converges to that of the exact solution with first-order accuracy. Furthermore, by validating the Lyapunov condition and the minorization condition using a localized technique, we establish the geometric ergodicity of the numerical solution. Finally, numerical experiments are conducted to confirm the theoretical results.
title Splitting AVF method for generalized Langevin equations: probability density function and geometric ergodicity
topic Numerical Analysis
Probability
url https://arxiv.org/abs/2604.25717