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Incorporating probabilistic terms in mathematical models is crucial for capturing and quantifying uncertainties in real-world systems, especially when the solution is not unique or exhibits sudden qualitative changes as parameters vary.…

Numerical Analysis · Mathematics 2026-02-17 Isabella Carla Gonnella , Moaad Khamlich , Federico Pichi , Gianluigi Rozza

We present a Markov-chain analysis of blockwise-stochastic algorithms for solving partially block-separable optimization problems. Our main contributions to the extensive literature on these methods are statements about the Markov operators…

Optimization and Control · Mathematics 2023-11-01 D. Russell Luke

We introduce a hull operator on Poisson point processes, the easiest example being the convex hull of the support of a point process in Euclidean space. Assuming that the intensity measure of the process is known on the set generated by the…

Probability · Mathematics 2024-02-02 Günter Last , Ilya Molchanov

We develop a numerical strategy to solve multi-dimensional Poisson equations on dynamically adapted grids for evolutionary problems disclosing propagating fronts. The method is an extension of the multiresolution finite volume scheme used…

Analysis of PDEs · Mathematics 2015-05-12 Max Duarte , Zdenek Bonaventura , Marc Massot , Anne Bourdon

The theory of sparse stochastic processes offers a broad class of statistical models to study signals. In this framework, signals are represented as realizations of random processes that are solution of linear stochastic differential…

Probability · Mathematics 2017-02-17 Julien Fageot , Virginie Uhlmann , Michael Unser

The set of common numerical and analytical problems is introduced in the form of the generalized multidimensional discrete Poisson equation. It is shown that its solutions with square-summable discrete derivatives are unique up to a…

Mathematical Physics · Physics 2011-09-27 Roman Werpachowski

We develop a variational method of deriving stochastic partial differential equations whose solutions follow the flow of a stochastic vector field. As an example in one spatial dimension we numerically simulate singular solutions (peakons)…

Chaotic Dynamics · Physics 2016-09-06 DD Holm , TM Tyranowski

The statistical physics approach to the number partioning problem, a classical NP-hard problem, is both simple and rewarding. Very basic notions and methods from statistical mechanics are enough to obtain analytical results for the phase…

Condensed Matter · Physics 2007-05-23 Stephan Mertens

The Vlasov equation embodies the smooth field approximation of the self-consistent equation of motion for charged particle beams. This framework is fundamentally altered if we include the fluctuating forces that originate from the actual…

Accelerator Physics · Physics 2023-04-26 Jürgen Struckmeier

Goal of this paper is to investigate several numerical schemes for the resolution of two anisotropic Vlasov equations. These two toy-models arise from a kinetic description of a tokamak plasma confined by strong magnetic fields. The…

Numerical Analysis · Mathematics 2017-08-10 Baptiste Fedele , Claudia Negulescu

Motivated by the recent contribution \cite{BB17} we study the scaling limit behavior of a class of one-dimensional stochastic differential equations which has a unique attracting point subject to a small additional repulsive perturbation.…

Mathematical Physics · Physics 2019-06-26 Martin Kolb , Matthias Liesenfeld

This paper revises traditional phenomenological approaches to the application of Vlasov equation to describe the dissipative systems. The original equation by A.A. Vlasov obtained differs from the classical Vlasov equation used in the…

Computational Physics · Physics 2018-11-29 E. E. Perepelkin , B. I. Sadovnikov , N. G. Inozemtseva , D. A. Suchkov

A practical introduction to stochastic modelling of reaction-diffusion processes is presented. No prior knowledge of stochastic simulations is assumed. The methods are explained using illustrative examples. The article starts with the…

Subcellular Processes · Quantitative Biology 2007-11-19 Radek Erban , Jonathan Chapman , Philip Maini

The Poisson process is the most elementary continuous-time stochastic process that models a stream of repeating events. It is uniquely characterised by a single parameter called the rate. Instead of a single value for this rate, we here…

Probability · Mathematics 2019-06-05 Alexander Erreygers , Jasper De Bock

This paper establishes an existence theory for distributed periodic solutions to Newton's equation with stochastic time-periodic forcing, where the friction matrix is the Hessian of a twice continuously differentiable friction function.…

Dynamical Systems · Mathematics 2025-09-10 Junxia Duan , Jifa Jiang , Jie Xu

In this paper, we present very first results for the adaptive solution on a grid of the phase space of the Vlasov equation arising in particles accelarator and plasma physics. The numerical algorithm is based on a semi-Lagrangian method…

Numerical Analysis · Mathematics 2007-05-23 Nicolas Besse , Francis Filbet , Michael Gutnic , Ioana Paun , Eric Sonnendrücker

We develop an asymptotic-preserving scheme to solve evolution problems containing stiff transport terms. This scheme is based to a micro-macro decomposition of the unknown, coupled with a stabilization procedure. The numerical method is…

Numerical Analysis · Mathematics 2018-02-21 Baptiste Fedele , Claudia Negulescu , Stefan Possanner

We derive the existence and uniqueness of the generalized backward doubly stochastic differential equation with sub-differential of a lower semi-continuous convex function under a non Lipschitz condition. This study allows us give a…

Probability · Mathematics 2025-01-06 Yong Ren , Auguste Aman , Qing Zhou

A Hamiltonian approach to the solution of the Vlasov-Poisson equations has been developed. Based on a nonlinear canonical transformation, the rapidly oscillating terms in the original Hamiltonian are transformed away, yielding a new…

Accelerator Physics · Physics 2009-11-07 Stephan I. Tzenov , Ronald C. Davidson

This paper considers the probabilistic representation of the solutions of ordinary differential equations (ODEs) by the generation of marked random trees in which marks can be interpreted as mutant types in population genetics models. We…

Probability · Mathematics 2025-11-11 Qiao Huang , Nicolas Privault