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Related papers: Martingale-driven integrals and singular SPDEs

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This paper aims to investigate numerical approximation of a general second order non-autonomous semilinear parabolic stochastic partial differential equation (SPDE) driven by multiplicative noise. Numerical approximations of autonomous…

Numerical Analysis · Mathematics 2018-09-13 Antoine Tambue , Jean Daniel Mukam

The present paper continues the study of infinite dimensional calculus via regularization, started by C. Di Girolami and the second named author, introducing the notion of "weak Dirichlet process" in this context. Such a process $\X$,…

Probability · Mathematics 2016-06-14 Giorgio Fabbri , Francesco Russo

Motivated by a recent use of Glauber dynamics for Monte-Carlo simulations of path integral representation of quantum spin models [Krzakala, Rosso, Semerjian, and Zamponi, Phys. Rev. B (2008)], we analyse a natural Glauber dynamics for the…

Probability · Mathematics 2015-05-28 Fabio Martinelli , Marc Wouts

We investigate a stochastic version of the Allen-Cahn-Navier-Stokes system in a smooth two- or three-dimensional domain with random initial data. The system consists of a Navier-Stokes equation coupled with a convective Allen-Cahn equation,…

Analysis of PDEs · Mathematics 2022-05-31 Andrea Di Primio , Maurizio Grasselli , Luca Scarpa

The chaos expansion of a general non-linear function of a Gaussian stationary increment process conditioned on its past realizations is derived. This work combines Wiener chaos expansion approach to study the dynamics of a stochastic system…

Probability · Mathematics 2018-04-12 Daniel Alpay , Alon Kipnis

In this paper, the classical Dellacherie's theorem about stochastic process is extended to variable exponent Lebesgue spaces. As its applications, we obtain variable exponent analogues of several famous inequalities in classical martingale…

Functional Analysis · Mathematics 2014-12-30 Peide Liu , Maofa Wang

We present numerical schemes for the strong solution of linear stochastic differential equations driven by an arbitrary number of Wiener processes. These schemes are based on the Neumann (stochastic Taylor) and Magnus expansions. Firstly,…

Numerical Analysis · Mathematics 2007-08-22 Gabriel Lord , Simon J. A. Malham , Anke Wiese

In this paper, we construct a type of interacting particle systems to approximate a class of stochastic different equations whose coefficients depend on the conditional probability distributions of the processes given partial observations.…

Probability · Mathematics 2024-03-27 Kai Du , Yunzhang Li , Yuyang Ye

We consider some versions and generalizations of an approach to the expansion of iterated Ito stochastic integrals of arbitrary multiplicity $k$ $(k\in\mathbb{N})$ based on generalized multiple Fourier series. Expansions of iterated…

Probability · Mathematics 2023-08-01 Dmitriy F. Kuznetsov

A recent paper of Melbourne & Stuart, A note on diffusion limits of chaotic skew product flows, Nonlinearity 24 (2011) 1361-1367, gives a rigorous proof of convergence of a fast-slow deterministic system to a stochastic differential…

Dynamical Systems · Mathematics 2015-06-15 Georg A. Gottwald , Ian Melbourne

The purpose of this work is to build a framework that allows for an in-depth study of various generalisations to inhomogeneous space of models of Borodin-Ferrari, Dieker-Warren, Nordenstam, Warren-Windridge of interacting particles in…

Probability · Mathematics 2023-11-09 Theodoros Assiotis

We study classical stochastic systems with discrete states, coupled to switching external environments. For fast environmental processes we derive reduced dynamics for the system itself, focusing on corrections to the adiabatic limit of…

Statistical Mechanics · Physics 2019-03-27 Peter G. Hufton , Yen Ting Lin , Tobias Galla

Discretizing variational principles, as opposed to discretizing differential equations, leads to discrete-time analogues of mechanics, and, systematically, to geometric numerical integrators. The phase space of such variational…

Mathematical Physics · Physics 2015-05-13 Charles Cuell , George W. Patrick

We study the problem of learning the law of linear stochastic partial differential equations (SPDEs) with additive Gaussian forcing from spatiotemporal observations. Most existing deep learning approaches either assume access to the driving…

Machine Learning · Computer Science 2026-02-13 Sebastian Zeng , Andreas Petersson , Wolfgang Bock

This work addresses the propagation of chaos properties in a class of moderately interacting particle systems for the approximation of singular kinetic McKean-Vlasov SDEs driven by alpha-stable processes.

Analysis of PDEs · Mathematics 2026-02-16 Zimo Hao , Jean-Francois Jabir , Stéphane Menozzi , Michael Röckner , Xicheng Zhang

In this work we firstly prove the well-posedness of the non-linear martingale problem related to a McKean-Vlasov stochastic differential equation with singular interaction kernel in $\mathbb{R}^d$ for $d\geq 3$. The particularity of our…

Probability · Mathematics 2022-09-23 Milica Tomašević , Guillaume Woessner

We prove gradient bounds for the Markov semigroup of the dynamic $\varphi^4_2$-model on a torus of fixed size $L>0$. For sufficiently large mass $m>0$ these estimates imply exponential contraction of the Markov semigroup. Our method is…

Probability · Mathematics 2022-02-23 Florian Kunick , Pavlos Tsatsoulis

We study in this article the stochastic Zakharov-Kuznetsov equation driven by a multiplicative noise. We establish, in space dimensions two and three the global existence of martingale solutions, and in space dimension two the global…

Analysis of PDEs · Mathematics 2013-07-26 Nathan Glatt-Holtz , Roger Temam , Chuntian Wang

Stochastic symmetries and related invariance properties of finite dimensional SDEs driven by general c\`adl\`ag semimartingales taking values in Lie groups are defined and investigated. In order to enlarge the class of possible symmetries…

Probability · Mathematics 2017-08-08 Sergio Albeverio , Francesco C. De Vecchi , Paola Morando , Stefania Ugolini

This work introduces a general framework for establishing the long time accuracy for approximations of Markovian dynamical systems on separable Banach spaces. Our results illuminate the role that a certain uniformity in Wasserstein…

Numerical Analysis · Mathematics 2023-02-06 Nathan E. Glatt-Holtz , Cecilia F. Mondaini