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Partial differential equations with distributional sources---in particular, involving (derivatives of) delta distributions---have become increasingly ubiquitous in numerous areas of physics and applied mathematics. It is often of…

Computational Physics · Physics 2019-11-22 Marius Oltean , Carlos F. Sopuerta , Alessandro D. A. M. Spallicci

This paper is concerned with the existence and uniqueness of weak solutions to the Cauchy-Dirichlet problem of backward stochastic partial differential equations (BSPDEs) with nonhomogeneous terms of quadratic growth in both the gradient of…

Probability · Mathematics 2012-07-24 Kai Du , Shaokuan Chen

We study a generalization of the Brownian bridge as a stochastic process that models the position and velocity of inertial particles between the two end-points of a time interval. The particles experience random acceleration and are assumed…

Systems and Control · Computer Science 2014-07-15 Yongxin Chen , Tryphon Georgiou

We provide a new, concise proof of weak existence and uniqueness of solutions to the stochastic differential equation for the multidimensional skew Brownian motion. We also present an application to Brownian particles with skew-elastic…

Probability · Mathematics 2014-02-25 Rami Atar , Amarjit Budhiraja

A solution to the linear Boltzmann equation satisfies an energy bound, which reflects a natural fact: The energy of particles in a finite volume is bounded in time by the energy of particles initially occupying the volume augmented by the…

Numerical Analysis · Mathematics 2021-01-19 Jonas Bünger , Neeraj Sarna , Manuel Torrilhon

In order to understand the impact of random influences at physical boundary on the evolution of multiscale systems, a stochastic partial differential equation model under a fast random dynamical boundary condition is investigated. The…

Dynamical Systems · Mathematics 2008-08-07 Wei Wang , Jinqiao Duan

In this paper, we study numerical approximations for optimal control of a class of stochastic partial differential equations with partial observations. The system state evolves in a Hilbert space, whereas observations are given in…

Optimization and Control · Mathematics 2025-04-02 Feng Bao , Yanzhao Cao , Hongjiang Qian

Solving partial differential equations (PDEs) is the canonical approach for understanding the behavior of physical systems. However, large scale solutions of PDEs using state of the art discretization techniques remains an expensive…

Computational Engineering, Finance, and Science · Computer Science 2021-01-14 Xiaoxuan Zhang , Krishna Garikipati

We prove the convergence of $ \nN $-particle systems of Brownian particles with logarithmic interaction potentials onto a system described by the infinite-dimensional stochastic differential equation (ISDE). % For this proof we present two…

Probability · Mathematics 2017-06-14 Yosuke Kawamoto , Hirofumi Osada

This paper explores the feasibility of quantum simulation for partial differential equations (PDEs) with physical boundary or interface conditions. Semi-discretisation of such problems does not necessarily yield Hamiltonian dynamics and…

Quantum Physics · Physics 2023-05-05 Shi Jin , Xiantao Li , Nana Liu , Yue Yu

A systematic Bayesian framework is developed for physics constrained parameter inference ofstochastic differential equations (SDE) from partial observations. The physical constraints arederived for stochastic climate models but are…

Data Analysis, Statistics and Probability · Physics 2016-11-25 Daniel Peavoy , Christian L. E. Franzke , Gareth O. Roberts

In this paper we establish the strong existence, pathwise uniqueness and a comparison theorem to a stochastic partial differential equation driven by Gaussian colored noise with non-Lipschitz drift, H\"older continuous diffusion…

Probability · Mathematics 2020-06-02 Jie Xiong , Xu Yang

We prove existence and uniqueness for some nonlinear stochastic differential equation used in molecular dynamics, whose nonlinearity comes from a conditional expectation term. We also introduce an interacting particle system in order to…

Probability · Mathematics 2010-01-16 Benjamin Jourdain , Tony Lelievre , Raphaël Roux

We study a class of partial differential equations (PDEs) in the family of the so-called Euler-Poincar\'e differential systems, with the aim of developing a foundation for numerical algorithms of their solutions. This requires particular…

Numerical Analysis · Mathematics 2015-07-14 Roberto Camassa , Dongyang Kuang , Long Lee

Optimal control of interacting particles governed by stochastic evolution equations in Hilbert spaces is an open area of research. Such systems naturally arise in formulations where each particle is modeled by stochastic partial…

Probability · Mathematics 2025-11-27 Filippo de Feo , Fausto Gozzi , Andrzej Święch , Lukas Wessels

We consider the dynamics of finite systems of point masses which move along the real line. We suppose the particles interact pairwise and undergo perfectly inelastic collisions when they collide. In particular, once particles collide, they…

Analysis of PDEs · Mathematics 2020-07-07 Ryan Hynd

We study measures on random partitions, arising from condensing stochastic particle systems with stationary product distributions. We provide fairly general conditions on the stationary weights, which lead to Poisson-Dirichlet statistics of…

Probability · Mathematics 2023-03-06 Paul Chleboun , Simon Gabriel , Stefan Grosskinsky

We consider a partial differential equation that arises in the coarse-grained description of epitaxial growth processes. This is a parabolic equation whose evolution is governed by the competition between the determinant of the Hessian…

Analysis of PDEs · Mathematics 2015-03-24 Carlos Escudero , Filippo Gazzola , Ireneo Peral

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

Finite dimensional solutions to a class of stochastic partial differential equations are obtained extending the differential constraints method for deterministic PDE to the stochastic framework. A geometrical reformulation of the stochastic…

Probability · Mathematics 2017-12-25 Francesco C. De Vecchi