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In this paper, we are concerned with the numerical solution for the backward fractional Feynman-Kac equation with non-smooth initial data. Here we first provide the regularity estimate of the solution. And then we use the backward Euler and…

Numerical Analysis · Mathematics 2020-06-23 Jing Sun , Daxin Nie , Weihua Deng

Aim of this note is to analyse branching Brownian motion within the class of models introduced in the recent paper [4] and called chemical diffusion master equations. These models provide a description for the probabilistic evolution of…

Probability · Mathematics 2024-01-23 Alberto Lanconelli , Berk Tan Perçin

We consider a rather general class of evolutionary PDEs involving dissipation (of possibly fractional order), which competes with quadratic nonlinearities on the regularity of the overall equation. This includes as prototype models,…

Analysis of PDEs · Mathematics 2015-06-16 Animikh Biswas , Eitan Tadmor

We investigate conditional McKean-Vlasov equations driven by time-space white noise, motivated by the propagation of chaos in an N-particle system with space-time Ornstein-Uhlenbeck dynamics. The framework builds on the stochastic calculus…

Probability · Mathematics 2024-12-31 Nacira Agram , Bernt Øksendal , Frank Proske , Olena Tymoshenko

We compare two approaches to nonequilibrium thermodynamics, the two-generator bracket formulation of time-evolution equations for averages and the macroscopic fluctuation theory, for an isothermal driven diffusive system under steady state…

Statistical Mechanics · Physics 2010-11-10 Hans Christian Ottinger

Microscopic theory of Brownian motion of a particle of mass $M$ in a bath of molecules of mass $m\ll M$ is considered beyond lowest order in the mass ratio $m/M$. The corresponding Langevin equation contains nonlinear corrections to the…

Statistical Mechanics · Physics 2010-01-22 A. V. Plyukhin

The hysteretic behavior of many-particle systems with non-convex free energy can be modeled by nonlocal Fokker-Planck equations that involve two small parameters and are driven by a time- dependent constraint. In this paper we consider the…

Analysis of PDEs · Mathematics 2015-03-03 Michael Herrmann , Barbara Niethammer , Juan J. L. Velázquez

We prove that stochastic replicator dynamics can be interpreted as intrinsic Brownian motion on the simplex equipped the Aitchison geometry. As an immediate consequence we derive three approximation results in the spirit of Wong-Zakai…

Probability · Mathematics 2020-08-13 Tobias Lehmann

Statistical invariance of Wiener increments under SO(n) rotations provides a notion of gauge transformation of state-dependent Brownian motion. We show that the stochastic dynamics of non gauge-invariant systems is not unambiguously…

Statistical Mechanics · Physics 2013-09-06 Matteo Polettini

We study the estimation of the invariant density of additive fractional stochastic differential equations with Hurst parameter $H \in (0,1)$. We first focus on continuous observations and develop a kernel-based estimator achieving faster…

Statistics Theory · Mathematics 2025-12-23 Chiara Amorino , Eulalia Nualart , Fabien Panloup , Julian Sieber

A recently introduced nonlinear Fokker-Planck equation, derived directly from a master equation, comes out as a very general tool to describe phenomenologically systems presenting complex behavior, like anomalous diffusion, in the presence…

Statistical Mechanics · Physics 2009-11-13 Veit Schwammle , Evaldo M. F. Curado , Fernando D. Nobre

We introduce a novel numerical scheme for solving the Fokker-Planck equation of discretized Dean-Kawasaki models with a functional tensor network ansatz. The Dean-Kawasaki model describes density fluctuations of interacting particle…

Numerical Analysis · Mathematics 2026-02-06 Xun Tang , Lexing Ying

This paper explores the well-posedness of the Cauchy problem for the Fokker-Planck equation associated with the partial differential operator $L$ with low regularity condition. To address uniqueness, we apply a recently developed…

Probability · Mathematics 2025-06-03 Haesung Lee

In this article, we study the nonlinear Fokker-Planck (FP) equation that arises as a mean-field (macroscopic) approximation of bounded confidence opinion dynamics, where opinions are influenced by environmental noises and opinions of…

Analysis of PDEs · Mathematics 2020-01-14 M. A. S. Kolarijani , A. V. Proskurnikov , P. Mohajerin Esfahani

We present a method for the nonparametric estimation of the drift function of certain types of stochastic differential equations from the empirical density. It is based on a variational formulation of the Fokker-Planck equation. The…

Data Analysis, Statistics and Probability · Physics 2016-12-16 Philipp Batz , Andreas Ruttor , Manfred Opper

We consider the Cauchy problem for the evolutive discrete p-Laplacian in infinite graphs, with initial data decaying at infinity. We prove optimal sup and gradient bounds for nonnegative solutions, when the initial data has finite mass, and…

Analysis of PDEs · Mathematics 2018-05-08 Daniele Andreucci , Anatoli F. Tedeev

We present the newly developed stochastic model of the galactic cosmic ray (GCR) particles transport in the heliosphere. Mathematically Parker transport equation (PTE) describing non-stationary transport of charged particles in the…

Solar and Stellar Astrophysics · Physics 2015-09-23 A. Wawrzynczak , R. Modzelewska , A. Gil

The fractional Fokker-Planck equation (FFPE) [R. Metzler, E. Barkai, J. Klafter, Phys. Rev. Lett., 82, 3563 (1999)] describes an anomalous sub diffusive behavior of a particle in an external force field. In this paper we present the…

Statistical Mechanics · Physics 2007-05-23 E. Barkai

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

The F\"ollmer process is a Brownian motion conditioned to have a pre-specified distribution at time 1. This process can be interpreted as an "augmented" time-compressed version of the reverse stochastic differential equation (SDE) for the…

Machine Learning · Statistics 2026-05-19 Yuta Koike
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