7 papers
Fundamental weak convergence theorem for stochastic Volterra integral equations and its applications
Xinjie Dai, Qijiao Yin, Diancong Jin
We study weak convergence rates of numerical approximations for stochastic Volterra integral equations (SVIEs), a class of non-Markovian models that arises naturally in stochastic…
A uniform-in-time weakly convergent explicit numerical method for the underdamped Langevin equation with polynomial potentials
Diancong Jin
The underdamped Langevin equation is a fundamental model in statistical mechanics for sampling Gibbs measures and simulating molecular dynamics, for which numerical methods with un…
Splitting AVF method for generalized Langevin equations: probability density function and geometric ergodicity
Xinjie Dai, Xingyu Liu, Diancong Jin +1
The generalized Langevin equation (GLE) constitutes a fundamental model for describing nonequilibrium dynamics with memory effects. To overcome the numerical challenges arising fro…
Asymptotic error distribution of Mittag--Leffler Euler method for a fractional stochastic differential equation
Xinjie Dai, Baiping Zhang, Diancong Jin
In this paper, we investigate the asymptotic distribution of the normalized error for the Mittag--Leffler Euler (MLE) method applied to a class of multidimensional fractional stoch…
Asymptotic error distribution for tamed Euler method with coupled monotonicity condition
Xinjie Dai, Diancong Jin, Jiaoyang Xu
This paper establishes the asymptotic error distribution of the tamed Euler method for stochastic differential equations (SDEs) with a coupled monotonicity condition, that is, the…
Asymptotic error distribution of numerical methods for parabolic SPDEs with multiplicative noise
Jialin Hong, Diancong Jin, Xu Wang
This paper aims to investigate the asymptotic error distribution of several numerical methods for stochastic partial differential equations (SPDEs) with multiplicative noise. First…