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In this study, we develop a stochastic optimal control approach with reinforcement learning structure to learn the unknown parameters appeared in the drift and diffusion terms of the stochastic differential equation. By choosing an…

Optimization and Control · Mathematics 2023-08-22 Shuzhen Yang

Nonparametric estimation for semilinear SPDEs, namely stochastic reaction-diffusion equations in one space dimension, is studied. We consider observations of the solution field on a discrete grid in time and space with infill asymptotics in…

Statistics Theory · Mathematics 2023-02-03 Florian Hildebrandt , Mathias Trabs

Model predictive control strategies require to solve in an sequential manner, many, possibly non-convex, optimization problems. In this work, we propose an interacting stochastic agent system to solve those problems. The agents evolve in…

Optimization and Control · Mathematics 2023-12-21 Giacomo Borghi , Michael Herty

In this paper, we show that unbalanced optimal transport provides a convenient framework to handle reaction and diffusion processes in a unified metric framework. We use a constructive method, alternating minimizing movements for the…

Analysis of PDEs · Mathematics 2017-04-18 Thomas Gallouët , Maxime Laborde , Léonard Monsaingeon

We introduce a general procedure for directly ascertaining how many independent stochastic sources exist in a complex system modeled through a set of coupled Langevin equations of arbitrary dimension. The procedure is based on the…

Data Analysis, Statistics and Probability · Physics 2013-06-03 V. V. Vasconcelos , F. Raischel , M. Haase , J. Peinke , M. Wächter , P. G. Lind , D. Kleinhans

We discuss nonconforming virtual element method for convection dominated (diffusive coefficient is very small compared to convective coefficient and reac- tion coefficient ) convection-diffusion-reaction equation using L^2 projection…

Numerical Analysis · Mathematics 2016-01-07 Dibyendu Adak , E. Natarajan

We analyze the static response to perturbations of nonequilibrium steady states that can be modeled as one-dimensional diffusions on the circle. We demonstrate that an arbitrary perturbation can be broken up into a combination of three…

Statistical Mechanics · Physics 2022-01-11 Qi Gao , Hyun-Myung Chun , Jordan M. Horowitz

We present DEF (\textbf{\ul{D}}iffusion-augmented \textbf{\ul{E}}nsemble \textbf{\ul{F}}orecasting), a novel approach for generating initial condition perturbations. Modern approaches to initial condition perturbations are primarily…

Machine Learning · Computer Science 2025-06-10 David Millard , Arielle Carr , Stéphane Gaudreault , Ali Baheri

Stochastic differential equations have proved to be a valuable governing framework for many real-world systems which exhibit ``noise'' or randomness in their evolution. One quality of interest in such systems is the shape of their…

Dynamical Systems · Mathematics 2025-02-04 David Sabin-Miller , Daniel M. Abrams

We a controlled system driven by a coupled forward-backward stochastic differential equation (FBSDE) with a non degenerate diffusion matrix. The cost functional is defined by the solution of the controlled backward stochastic differential…

Optimization and Control · Mathematics 2017-02-02 Khaled Bahlali , Omar Kebiri , Brahim Mezerdi , Ahmed Mtiraoui

The modeling and simulation of stochastic reaction-diffusion processes is a topic of steady interest that is approached with a wide range of methods. \rev{At the level of particle-resolved descriptions, where chemical reactions are coupled…

In contrast to normal diffusion, there is no canonical model for reactions between chemical species which move by anomalous subdiffusion. Indeed, the type of mesoscopic equation describing reaction-subdiffusion depends on subtle assumptions…

Statistical Mechanics · Physics 2020-10-23 Sean D Lawley

We introduce a scheme for deriving an optimally-parametrised Langevin dynamics of few collective variables from data generated in molecular dynamics simulations. The drift and the position-dependent diffusion profiles governing the Langevin…

Statistical Mechanics · Physics 2008-08-22 Cristian Micheletti , Giovanni Bussi , Alessandro Laio

We present a numerical algorithm that allows the approximation of optimal controls for stochastic reaction-diffusion equations with additive noise by first reducing the problem to controls of feedback form and then approximating the…

Optimization and Control · Mathematics 2023-09-15 Wilhelm Stannat , Alexander Vogler , Lukas Wessels

We construct path integrals for stochastic hybrid reaction-diffusion (RD) processes, in which the reaction terms depend on the discrete state of a randomly switching environment. We proceed by spatially discretizing a given RD system and…

Statistical Mechanics · Physics 2021-10-15 Paul C. Bressloff

Deriving evolution equations accounting for both anomalous diffusion and reactions is notoriously difficult, even in the simplest cases. In contrast to normal diffusion, reaction kinetics cannot be incorporated into evolution equations…

Statistical Mechanics · Physics 2020-10-23 Sean D Lawley

We propose a stochastic branching particle-based method for solving nonlinear non-conservative advection-diffusion-reaction equations. The method splits the evolution into an advection-diffusion step, based on a linearized Kolmogorov…

Numerical Analysis · Mathematics 2025-12-02 Liyao Lyu , Huan Lei

We expand on a recent study of a lattice model of interacting particles [Phys. Rev. Lett. 111, 110601 (2013)]. The adsorption isotherm and equilibrium fluctuations in particle number are discussed as a function of the interaction. Their…

Statistical Mechanics · Physics 2014-11-20 T. Becker , K. Nelissen , B. Cleuren , B. Partoens , C. Van den Broeck

A multi-relaxation-time discrete Boltzmann model (DBM) with split collision is proposed for both subsonic and supersonic compressible reacting flows, where chemical reactions take place among various components. The physical model is based…

Statistical Mechanics · Physics 2024-04-23 Chuandong Lin , Kai H. Luo , Huilin Lai

We study a system of diffusing point particles in which any triplet of particles reacts and is removed from the system when the relative proximity of the constituent particles satisfies a predefined condition. Proximity-based reaction…

Numerical Analysis · Mathematics 2025-04-07 Taylor Kearney , Ricardo Ruiz-Baier , Mark B. Flegg
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