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We define the operator $D^+_VD^-_W:=\Delta_{W,V}$ on the one-dimensional torus $\mathbb{T}$. Here, $W$ and $V$ are functions inducing (possibly atomic) positive Borel measures on $\mathbb{T}$, and the derivatives are generalized lateral…

Analysis of PDEs · Mathematics 2025-02-05 Alexandre B. Simas , Kelvin J. R. Sousa

This paper studies the existence and uniqueness of solution of It\^o type stochastic differential equation $dx(t)=b(t, x(t), \om)dt+\si(t,x(t), \om) d B(t)$, where $B(t)$ is a fractional Brownian motion of Hurst parameter $H>1/2$ and…

Probability · Mathematics 2016-12-20 Yaozhong Hu

We extend Walsh's theory of martingale measures in order to deal with hyperbolic stochastic partial differential equations that are second order in time, such as the wave equation and the beam equation, and driven by spatially homogeneous…

Probability · Mathematics 2011-02-18 Robert C. Dalang , Carl Mueller

We study strictly parabolic stochastic partial differential equations on $\R^d$, $d\ge 1$, driven by a Gaussian noise white in time and coloured in space. Assuming that the coefficients of the differential operator are random, we give…

Probability · Mathematics 2007-05-23 Marco Ferrante , Marta Sanz-Solé

In our pursuit of finding a zero for a monotone and Lipschitz continuous operator $M : \R^n \rightarrow \R^n$ amidst noisy evaluations, we explore an associated differential equation within a stochastic framework, incorporating a correction…

Optimization and Control · Mathematics 2024-04-30 Radu Ioan Bot , Chiara Schindler

These notes are based on a series of lectures given first at the University of Warwick in spring 2008 and then at the Courant Institute, Imperial College London, and EPFL. It is an attempt to give a reasonably self-contained presentation of…

Probability · Mathematics 2023-07-04 Martin Hairer

We analyze infinite-dimensional non-linear degenerate stochastic differential equations with multiplicative noise. First, essential m-dissipativity of their associated Kolmogorov backward generators on $L^2(\mu^{\Phi})$ defined on smooth…

Probability · Mathematics 2023-06-26 Alexander Bertram , Benedikt Eisenhuth , Martin Grothaus

We establish a general theory of optimal strong error estimation for numerical approximations of a second-order parabolic stochastic partial differential equation with monotone drift driven by a multiplicative infinite-dimensional Wiener…

Numerical Analysis · Mathematics 2022-03-02 Zhihui Liu , Zhonghua Qiao

We consider a stochastic parabolic partial differential equation with Dirichlet boundary conditions, multiplicative stochastic noise, and a monotone parabolic operator A. The growth and coercivity of A is controlled by a general N-function…

Analysis of PDEs · Mathematics 2025-06-17 Piotr Gwiazda , Jakub Woźnicki , Aneta Wróblewska-Kamińska , Aleksandra Zimmermann

We aim to solve a structured convex optimization problem, where a nonsmooth function is composed with a linear operator. When opting for full splitting schemes, usually, primal-dual type methods are employed as they are effective and also…

Optimization and Control · Mathematics 2019-05-17 Radu Ioan Bot , Axel Böhm

We present a versatile framework to study strong existence and uniqueness for stochastic differential equations (SDEs) in Hilbert spaces with irregular drift. We consider an SDE in a separable Hilbert space $H$ \begin{equation*} dX_t= (A…

Probability · Mathematics 2026-02-16 Lukas Anzeletti , Oleg Butkovsky , Máté Gerencsér , Alexander Shaposhnikov

This paper presents a general approach to linear stochastic processes driven by various random noises. Mathematically, such processes are described by linear stochastic differential equations of arbitrary order (the simplest non-trivial…

Condensed Matter · Physics 2009-10-28 Alon Drory

We study the stochastic nonlinear Schroedinger equations with linear multiplicative noise, particularly in the defocusing mass-critical and energy-critical cases. For general initial data, we prove the global existence and uniqueness of…

Probability · Mathematics 2018-11-06 Deng Zhang

In this paper, we aim to develop a new weak formulation that ensures well-posedness for a broad range of stochastic partial differential equations with pseudo-differential operators whose symbols depend only on time and spatial frequencies.…

Probability · Mathematics 2024-09-10 Jae-Hwan Choi , Ildoo Kim

A new class of fractional-order stochastic evolution equations of the form $(\partial_t + A)^\gamma X(t) = \dot{W}^Q(t)$, $t\in[0,T]$, $\gamma \in (0,\infty)$, is introduced, where $-A$ generates a $C_0$-semigroup on a separable Hilbert…

Probability · Mathematics 2026-01-06 Kristin Kirchner , Joshua Willems

In this paper we aim at generalizing the results of A. K. Zvonkin and A. Y. Veretennikov on the construction of unique strong solutions of stochastic differential equations with singular drift vector field and additive noise in the…

Probability · Mathematics 2019-03-15 David Baños , Martin Bauer , Thilo Meyer-Brandis , Frank Proske

Inspired by path-integral solutions to the quantum relaxation problem, we develop a numerical method to solve classical stochastic differential equations with multiplicative noise that avoids averaging over trajectories. To test the method,…

Statistical Mechanics · Physics 2023-12-12 Ryan T. Grimm , Joel D. Eaves

We consider semilinear stochastic evolution equations on Hilbert spaces with multiplicative Wiener noise and linear drift term of the type $A + \varepsilon G$, with $A$ and $G$ maximal monotone operators and $\varepsilon$ a "small"…

Probability · Mathematics 2021-01-01 Carlo Marinelli

In this article, we have analyzed the full discretization of the Stochastic semilinear Schr\"{o}dinger equation in a bounded convex polygonal domain driven by multiplicative Wiener noise. We use the finite element method for spatial…

Numerical Analysis · Mathematics 2025-04-22 Suprio Bhar , Mrinmay Biswas , Mangala Prasad

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