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We prove a maximum principle for local solutions of quasi-linear parabolic stochastic PDEs, with non-homogeneous second order operator on a bounded domain and driven by a space-time white noise. Our method based on an approximation of the…

Probability · Mathematics 2012-09-03 Laurent Denis , Anis Matoussi

We prove the existence and uniqueness of solution of the obstacle problem for quasilinear Stochastic PDEs with non-homogeneous second order operator. Our method is based on analytical technics coming from the parabolic potential theory. The…

Probability · Mathematics 2013-01-08 Denis Laurent , Matoussi Anis , Zhang Jing

In this paper we are concerned with the maximum principle for quasi-linear backward stochastic partial differential equations (BSPDEs for short) of parabolic type. We first prove the existence and uniqueness of the weak solution to…

Probability · Mathematics 2011-03-08 Jinniao Qiu , Shanjian Tang

We prove an existence and uniqueness result for quasilinear Stochastic PDEs with obstacle (OSPDE in short). Our method is based on analytical technics coming from the parabolic potential theory. The solution is expressed as a pair $(u,\nu)$…

Probability · Mathematics 2014-03-28 Laurent Denis , Anis Matoussi , Jing Zhang

This paper establishes a maximum principle for quasi-linear reflected backward stochastic partial differential equations (RBSPDEs for short). We prove the existence and uniqueness of the weak solution to RBSPDEs allowing for non-zero…

Analysis of PDEs · Mathematics 2016-04-11 Guanxing Fu , Ulrich Horst , Jinniao Qiu

We prove an existence and uniqueness result for two-obstacle problem for quasilinear Stochastic PDEs (DOSPDEs for short). The method is based on the probabilistic interpretation of the solution by using the backward doubly stochastic…

Probability · Mathematics 2020-12-08 Laurent Denis , Anis Matoussi , Jing Zhang

We prove an existence and uniqueness result for the obstacle problem for quasilinear stochastic integral-partial differential equations. Our method is based on the probabilistic interpretation of the solution using backward doubly SDEs with…

Probability · Mathematics 2018-06-08 Yuchao Dong , Xue Yang , Jing Zhang

We prove an existence and uniqueness result for quasilinear Stochastic PDEs with Obstacle (in short OSPDE) under a weaker integrability condition on the coefficient and the barrier.

Probability · Mathematics 2013-04-19 Laurent Denis , Anis Matoussi , Jing Zhang

We prove the existence and uniqueness of solution of the obstacle problem for quasilinear stochastic partial differential equations (OSPDEs for short) with Neumann boundary condition. Our method is based on the analytical technics coming…

Probability · Mathematics 2018-06-08 Yuchao Dong , Xue Yang , Jing Zhang

In this paper we prove necessary conditions for optimality of a stochastic control problem for a class of stochastic partial differential equations that is controlled through the boundary. This kind of problems can be interpreted as a…

Probability · Mathematics 2016-12-05 Giuseppina Guatteri

We prove the existence and uniqueness of solution of quasilinear stochastic partial differential equations with obstacle (OSPDEs in short) in degenerate case. Using De Giorgi's iteration, we deduce the $L^p-$estimates for the time-space…

Probability · Mathematics 2018-04-25 Xue Yang , Jing Zhang

We prove an existence and uniqueness result for the obstacle problem of quasilinear parabolic stochastic PDEs. The method is based on the probabilistic interpretation of the solution by using the backward doubly stochastic differential…

Probability · Mathematics 2010-10-13 Anis Matoussi , Lucretiu Stoica

The aim of this paper is to derive a maximum principle for a control problem governed by a stochastic partial differential equation (SPDE) with locally monotone coefficients. In particular, necessary conditions for optimality for this…

Optimization and Control · Mathematics 2019-10-11 Edson Alberto Coayla-Teran

We study a control problem where the state equation is a nonlinear partial differential equation of the calculus of variation in a bounded domain, perturbed by noise. We allow the control to act on the boundary and set stochastic boundary…

Probability · Mathematics 2025-11-26 Stefano Bonaccorsi , Adrian Zalinescu

In this note, we give the stochastic maximum principle for optimal control of stochastic PDEs in the general case (when the control domain need not be convex and the diffusion coefficient can contain a control variable).

Optimization and Control · Mathematics 2012-06-12 Marco Fuhrman , Ying Hu , Gianmario Tessitore

We consider partial differential equations (PDEs) characterized by an upper barrier that depends on the solution itself and a fixed lower barrier, while accommodating a non-local driver. First, we show a Feynman-Kac representation for the…

Probability · Mathematics 2024-09-04 Magnus Perninge

We give a simple proof of the strong maximum principle for viscosity subsolutions of fully nonlinear elliptic PDEs on the form $$ F(x,u,Du,D^2u) = 0 $$ under suitable structure conditions on the equation allowing for non-Lipschitz growth in…

Analysis of PDEs · Mathematics 2020-08-24 Niklas L. P. Lundström , Marcus Olofsson , Olli Toivanen

In this article, we prove the existence of at least one positive solution for the mixed local-nonlocal semipositone problem \begin{equation*} \left\{ \begin{aligned} -\Delta_p u+ (-\Delta)^s_p u &= \lambda f(u) && \text{in } \Omega, u &= 0…

Analysis of PDEs · Mathematics 2026-04-08 Komal Verma , Gaurav Dwivedi

We prove a version of the stochastic maximum principle, in the sense of Pontryagin, for the finite horizon optimal control of a stochastic partial differential equation driven by an infinite dimensional additive noise. In particular we…

Probability · Mathematics 2017-03-14 Marco Fuhrman , Carlo Orrieri

We extend Peng's maximum principle for semilinear stochastic partial differential equations (SPDEs) in one space-dimension with non-convex control domains and control-dependent diffusion coefficients to the case of general cost functionals…

Probability · Mathematics 2021-10-28 Wilhelm Stannat , Lukas Wessels
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