Implicit numerical approximation for stochastic delay differential equations with the nonlinear diffusion term in the infinite horizon

Fuente: arXiv
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Hauptverfasser: Wang, Yudong, Tian, Hongjiong
Format: Preprint
Veröffentlicht: 2025
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author Wang, Yudong
Tian, Hongjiong
author_facet Wang, Yudong
Tian, Hongjiong
contents This paper investigates the approximation of stochastic delay differential equations (SDDEs) via the backward Euler-Maruyama (BEM) method under generalized monotonicity and Khasminskii-type conditions in the infinite horizon. First, by establishing the uniform moment boundedness and finite-time strong convergence of the BEM method, we prove that for sufficiently small step sizes, the numerical approximations strongly converge to the underlying solution in the infinite horizon with a rate of $1/2$, which coincides with the optimal finite-time strong convergence rate. Next, we establish the uniform boundedness and convergence in probability for the segment processes associated with the BEM method. This analysis further demonstrates that the probability measures of the numerical segment processes converge to the underlying invariant measure of the SDDEs. Finally, a numerical example and simulations are provided to illustrate the theoretical results.
format Preprint
id arxiv_https___arxiv_org_abs_2505_12883
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Implicit numerical approximation for stochastic delay differential equations with the nonlinear diffusion term in the infinite horizon
Wang, Yudong
Tian, Hongjiong
Numerical Analysis
Probability
60H35, 65C30, 65L20,
G.1.7; G.3
This paper investigates the approximation of stochastic delay differential equations (SDDEs) via the backward Euler-Maruyama (BEM) method under generalized monotonicity and Khasminskii-type conditions in the infinite horizon. First, by establishing the uniform moment boundedness and finite-time strong convergence of the BEM method, we prove that for sufficiently small step sizes, the numerical approximations strongly converge to the underlying solution in the infinite horizon with a rate of $1/2$, which coincides with the optimal finite-time strong convergence rate. Next, we establish the uniform boundedness and convergence in probability for the segment processes associated with the BEM method. This analysis further demonstrates that the probability measures of the numerical segment processes converge to the underlying invariant measure of the SDDEs. Finally, a numerical example and simulations are provided to illustrate the theoretical results.
title Implicit numerical approximation for stochastic delay differential equations with the nonlinear diffusion term in the infinite horizon
topic Numerical Analysis
Probability
60H35, 65C30, 65L20,
G.1.7; G.3
url https://arxiv.org/abs/2505.12883