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We investigate numerical approximations for the stochastic Burgers equation driven by an additive cylindrical fractional Brownian motion with Hurst parameter $H \in (\frac{1}{2}, 1)$. To discretize the continuous problem in space, a…

Numerical Analysis · Mathematics 2026-04-21 Yibo Wang , Wanrong Cao

We consider parabolic stochastic partial differential equations driven by white noise in time. We prove exponential convergence of the transition probabilities towards a unique invariant measure under suitable conditions. These conditions…

Probability · Mathematics 2007-05-23 Martin Hairer

Semilinear hyperbolic stochastic partial differential equations (SPDEs) find widespread applications in the natural and engineering sciences. However, the traditional Gaussian setting may prove too restrictive, as phenomena in mathematical…

Numerical Analysis · Mathematics 2023-07-04 Andrea Barth , Andreas Stein

We study a fully-coupled system of conditional slow-fast McKean-Vlasov Stochastic Differential Equations that exhibit full dependence on both the slow and fast components, as well as on the conditional law of the slow component. Our aim is…

Probability · Mathematics 2023-08-14 Antonios Zitridis

We consider divergence form uniformly parabolic SPDEs with bounded and measurable leading coefficients and possibly growing lower-order coefficients in the deterministic part of the equations. We look for solutions which are summable to the…

Probability · Mathematics 2009-08-13 N. V. Krylov

We introduce an explicit, adaptive time-stepping scheme for the simulation of SPDEs with one-sided Lipschitz drift coefficients. Strong convergence rates are proven for the full space-time discretisation with multiplicative trace-class…

Numerical Analysis · Mathematics 2019-08-27 Stuart Campbell , Gabriel Lord

This note proposes embedding a time dependent PDE into a convection-diffusion type PDE (in one space dimension higher) with singularity, for which two discretization schemes, the classical streamline-diffusion and the EAFE (edge average…

Numerical Analysis · Mathematics 2016-04-05 Randolph E. Bank , Panayot S. Vassilevski , Ludmil T. Zikatanov

We consider a sparse grid collocation method in conjunction with a time discretization of the differential equations for computing expectations of functionals of solutions to differential equations perturbed by time-dependent white noise.…

Numerical Analysis · Mathematics 2015-05-18 Z. Zhang , M. V. Tretyakov , B. Rozovskii , G. E. Karniadakis

In this paper we construct space-time full discretizations of stochastic Allen-Cahn equations driven by space-time white noise on 2D torus. The approximations are implemented by tamed exponential Euler discretization in time and spectral…

Probability · Mathematics 2024-06-07 Ting Ma , Lifei Wang , Huanyu Yang

This work proposes a discretization of the acoustic wave equation with possibly oscillatory coefficients based on a superposition of discrete solutions to spatially localized subproblems computed with an implicit time discretization. Based…

Numerical Analysis · Mathematics 2024-03-11 Dietmar Gallistl , Roland Maier

We study parameter estimation for a linear parabolic second-order stochastic partial differential equation (SPDE) in two space dimensions with a small dispersion parameter using high frequency data with respect to time and space. We set two…

Statistics Theory · Mathematics 2022-06-22 Yozo Tonaki , Yusuke Kaino , Masayuki Uchida

We introduce the concept of numerical Gaussian processes, which we define as Gaussian processes with covariance functions resulting from temporal discretization of time-dependent partial differential equations. Numerical Gaussian processes,…

Machine Learning · Statistics 2017-03-31 Maziar Raissi , Paris Perdikaris , George Em Karniadakis

The discretization of velocity space plays a crucial role in the accuracy and efficiency of multiscale Boltzmann solvers. Conventional velocity space discretization methods suffer from uneven node distribution and mismatch issues, limiting…

Numerical Analysis · Mathematics 2025-11-04 Shanshan Dong , Lu Wang , Xiangxiang Chen , Guanqing Wang

The main goal of this article is to study the effect of small, highly nonlinear, unbounded drifts (small time large deviation principle (LDP) based on exponential equivalence arguments) for a class of stochastic partial differential…

Probability · Mathematics 2022-12-27 Ankit Kumar , Manil T. Mohan

This paper investigates the pathwise uniform convergence in probability of fully discrete finite-element approximations for the two-dimensional stochastic Navier-Stokes equations with multiplicative noise, subject to no-slip boundary…

Numerical Analysis · Mathematics 2025-02-11 Binjie Li , Xiaoping Xie , Qin Zhou

White noise-driven nonlinear stochastic partial differential equations (SPDEs) of parabolic type are frequently used to model physical and biological systems in space dimensions d = 1,2,3. Whereas existence and uniqueness of weak solutions…

Numerical Analysis · Mathematics 2015-05-27 Marc D. Ryser , Nilima Nigam , Paul F. Tupper

We consider finite dimensional rough differential equations driven by centered Gaussian processes. Combining Malliavin calculus, rough paths techniques and interpolation inequalities, we establish upper bounds on the density of the…

Probability · Mathematics 2020-06-18 Benjamin Gess , Cheng Ouyang , Samy Tindel

Convergence results are shown for full discretizations of quasilinear parabolic partial differential equations on evolving surfaces. As a semidiscretization in space the evolving surface finite element method is considered, using a…

Numerical Analysis · Mathematics 2015-04-01 Balázs Kovács , Christian Andreas Power Guerra

We deal with parameter estimation for a linear parabolic second-order stochastic partial differential equation in two space dimensions driven by two types of $Q$-Wiener processes based on high frequency data with respect to time and space.…

Statistics Theory · Mathematics 2023-04-20 Yozo Tonaki , Yusuke Kaino , Masayuki Uchida

The 2D Euler equations are a simple but rich set of non-linear PDEs that describe the evolution of an ideal inviscid fluid, for which one dimension is negligible. Solving numerically these equations can be extremely demanding. Several…

Numerical Analysis · Mathematics 2023-01-18 Paolo Cifani , Sagy Ephrati , Milo Viviani
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