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The approximation of invariant measures for nonlinear ergodic stochastic differential equations (SDEs) is a central problem in scientific computing, with important applications in stochastic sampling, physics, and ecology. We first propose…

Numerical Analysis · Mathematics 2025-11-18 Shan Huang , Xiaoyue Li

We examine the non-ergodic properties of scaled Brownian motion, a non-stationary stochastic process with a time dependent diffusivity of the form $D(t)\simeq t^{\alpha-1}$. We compute the ergodicity breaking parameter EB in the entire…

Statistical Mechanics · Physics 2015-09-02 Hadiseh Safdari , Andrey G. Cherstvy , Aleksei V. Chechkin , Felix Thiel , Igor M. Sokolov , Ralf Metzler

In this paper we systematically investigate the stochastic bifurcations of both ergodic stationary measures and global dynamics for stochastic Kolmogorov differential systems, which relate closely to the change of the sign of Lyapunov…

Dynamical Systems · Mathematics 2024-08-06 Dongmei Xiao , Deng Zhang , Chenwan Zhou

We examine the numerical approximation of a quasilinear stochastic differential equation (SDE) with multiplicative fractional Brownian motion. The stochastic integral is interpreted in the Wick-It\^o-Skorohod (WIS) sense that is well…

Numerical Analysis · Mathematics 2026-04-24 Utku Erdogan , Gabriel J. Lord , Roy B. Schieven

We present an innovating sensitivity analysis for stochastic differential equations: We study the sensitivity, when the Hurst parameter~$H$ of the driving fractional Brownian motion tends to the pure Brownian value, of probability…

Probability · Mathematics 2017-02-14 Alexandre Richard , Denis Talay

Stochastic Gradient Descent (SGD) is commonly modeled as a Langevin process, assuming that minibatch noise acts as Brownian motion. However, this approximation relies on a continuous-time limit and a sqrt(eta) noise scaling that does not…

This paper discusses a new type of anticipated backward stochastic differential equation with a time-delayed generator (DABSDEs, for short) driven by fractional Brownian motion, also known as fractional BSDEs, with Hurst parameter…

Probability · Mathematics 2023-05-24 Pei Zhang , Nur Anisah Mohamed , Adriana Irawati Nur Ibrahim

We consider the problem of nonparametric estimation of the drift and diffusion coefficients of a Stochastic Differential Equation (SDE), based on $n$ independent replicates $\left\{X_i(t)\::\: t\in [0,1]\right\}_{1 \leq i \leq n}$, observed…

Statistics Theory · Mathematics 2023-11-28 Neda Mohammadi , Leonardo Santoro , Victor M. Panaretos

We consider controlled stochastic differential equations (SDEs) with measurable coefficients, a uniformly elliptic diffusion coefficient and an $L_d$-drift. No space-regularity will be assumed for the coefficients. In this framework we…

Analysis of PDEs · Mathematics 2025-09-19 David Criens

A new explicit stabilized scheme of weak order one for stiff and ergodic stochastic differential equations (SDEs) is introduced. In the absence of noise, the new method coincides with the classical deterministic stabilized scheme (or…

Numerical Analysis · Mathematics 2018-06-28 Assyr Abdulle , Ibrahim Almuslimani , Gilles Vilmart

We consider a stochastic version of a system of coupled two equations formulated by Burgers with the aim to describe the laminar and turbulent motions of a fluid in a channel. The existence and uniqueness of the solution as well as the…

Probability · Mathematics 2020-06-19 Szymon Peszat , Krystyna Twardowska , Jerzy Zabczyk

We obtain a stochastic differential equation (SDE) satisfied by the first $n$ coordinates of a Brownian motion on the unit sphere in $\mathbb{R}^{n+\ell}$. The SDE has non-Lipschitz coefficients but we are able to provide an analysis of…

Probability · Mathematics 2018-09-14 Aleksandar Mijatović , Veno Mramor , Gerónimo Uribe Bravo

In this paper we study the deterministic and stochastic homogenisation of free-discontinuity functionals under \emph{linear} growth and coercivity conditions. The main novelty of our deterministic result is that we work under very general…

Analysis of PDEs · Mathematics 2021-01-13 Filippo Cagnetti , Gianni Dal Maso , Lucia Scardia , Caterina Ida Zeppieri

The analysis of local minima in time series data and random landscapes is essential across numerous scientific disciplines, offering critical insights into system dynamics. Recently, Kundu, Majumdar, and Schehr derived the exact…

Statistical Mechanics · Physics 2026-03-19 Maxim Dolgushev , Olivier Bénichou

Despite the success of fractional Brownian motion (fBm) in modeling systems that exhibit anomalous diffusion due to temporal correlations, recent experimental and theoretical studies highlight the necessity for a more comprehensive approach…

Statistical Mechanics · Physics 2024-07-02 Adrian Pacheco-Pozo , Diego Krapf

We introduce a stochastic version of Gubinelli's sewing lemma, providing a sufficient condition for the convergence in moments of some random Riemann sums. Compared with the deterministic sewing lemma, adaptiveness is required and the…

Probability · Mathematics 2021-10-12 Khoa Lê

We investigate the stochastic heat equation driven by space-time white noise defined on an abstract Hilbert space, assuming that the drift and diffusion coefficients are both merely H\"older continuous. Random field SPDEs are covered as…

Probability · Mathematics 2025-08-04 Yi Han

In this paper we study the existence and uniqueness of the strong solution of following d dimensional stochastic differential equation (SDE) driven by Brownian motion: dX(t)=b(t,X(t))dt+a(t,X(t))dB(t), X(0)= x, where B is a d-dimensional…

Probability · Mathematics 2024-07-26 Yaozhong Hu , Qun Shi

We investigate existence, uniqueness and regularity for local solutions of rough parabolic equations with subcritical noise of the form $du_t- L_tu_tdt= N(u_t)dt + \sum_{i = 1}^dF_i(u_t)d\mathbf X^i_t$ where $(L_t)_{t\in[0,T]}$ is a…

Analysis of PDEs · Mathematics 2021-08-24 Andris Gerasimovics , Antoine Hocquet , Torstein Nilssen

For stochastic differential equations (SDEs) with Markovian switching, whose drift and diffusion coefficients are allowed to contain superlinear terms, the backward Euler-Maruyama (BEM) method is proposed to approximate the invariant…

Numerical Analysis · Mathematics 2025-12-10 Wei Liu , Jie Xu
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