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A Fokker-Planck equation approach for the treatment of non-Markovian stochastic processes is proposed. The approach is based on the introduction of fictitious trajectories sharing with the real ones their local structure and initial…

Chaotic Dynamics · Physics 2009-11-11 Piero Olla , Luca Pignagnoli

We derive the exact evolution equation for the probability density function of particle displacements generated by arbitrary Gaussian velocity processes, when neither Markovianity and nor stationarity are assumed. Starting from the…

Statistical Mechanics · Physics 2026-05-19 Alessandro Taloni , Gianni Pagnini , Aleksei Chechkin

The purpose of this comment is to correct mistaken assumptions and claims made in the paper Stochastic feedback, nonlinear families of Markov processes, and nonlinear Fokker-Planck equations by T. D. Frank. Our comment centers on the claims…

Statistical Mechanics · Physics 2009-11-13 Joseph L. McCauley

We explore the diffusion process in the non-Markovian spatio-temporal noise.%the escape rate problem in the non-Markovian spatio-temporal random noise. There is a non-trivial short memory regime, i.e., the Markovian limit characterized by a…

Statistical Mechanics · Physics 2009-11-13 Takaaki Monnai , Ayumu Sugita , Katsuhiro Nakamura

The unified description of diffusion processes that cross over from a ballistic behavior at short times to normal or anomalous diffusion (sub- or superdiffusion) at longer times is constructed on the basis of a non-Markovian generalization…

Statistical Mechanics · Physics 2013-03-26 Valery Ilyin , Itamar Procaccia , Anatoly Zagorodny

We demonstrate the equivalence of a Non--Markovian evolution equation with a linear memory--coupling and a Fokker--Planck equation (FPE). In case the feedback term offers a direct and permanent coupling of the current probability density to…

Statistical Mechanics · Physics 2009-11-11 Knud Zabrocki , Steffen Trimper , Svetlana Tatur , Reinhard Mahnke

The stochastic theory of non-relativistic quantum mechanics presented here relies heavily upon the theory of stochastic processes, with its definitions, theorems and specific vocabulary as well. Its main hypothesis states indeed that the…

Quantum Physics · Physics 2014-04-01 Maurice J. M. L. O. Godart

We develop a general theory dealing with stochastic models for dynamical systems that are governed by various nonlinear, ordinary or partial differential, equations. In particular, we address the problem how flows in the random medium…

chao-dyn · Physics 2009-10-31 Piotr Garbaczewski

We solve two long standing problems for stochastic descriptions of open quantum system dynamics. First, we find the classical stochastic processes corresponding to non-Markovian quantum state diffusion and non-Markovian quantum jumps in…

Quantum Physics · Physics 2020-10-14 Kimmo Luoma , Walter T. Strunz , Jyrki Piilo

We study the perturbative response of a complex quantum system on time changes of an external parameter $X$. The driven dynamics is treated in adiabatic basis of the system's Hamiltonian $\hat{H}[X]$. Within a random matrix approach we…

Statistical Mechanics · Physics 2019-12-16 S. V. Radionov

A space fractional diffusion-like equation is introduced, which embodies the nonlocality in time, represented by the memory kernel and the non-locality in space. A specific example of the nonlocal term is considered in combination with…

Statistical Mechanics · Physics 2026-01-06 Pece Trajanovski , Irina Petreska , Katarzyna Gorska , Ljupco Kocarev , Trifce Sandev

The nonlocal porous medium equation considered in this paper is a degenerate nonlinear evolution equation involving a space pseudo-differential operator of fractional order. This space-fractional equation admits an explicit, nonnegative,…

Probability · Mathematics 2019-02-05 Alessandro De Gregorio

In these lecture notes, we explore the mathematical preliminaries and foundational concepts that connect stochastic processes with partial differential equations. We begin by investigating Brownian motion, which serves as a model for random…

Probability · Mathematics 2025-09-15 Helder Rojas

A subdiffusion problem in which the diffusion term is related to a stable stochastic process is introduced. Linear models of these systems have been studied in a general way, but non-linear models require a more specific analysis. The model…

Probability · Mathematics 2021-11-05 Soveny Solís , Vicente Vergara

The computation of the probability of the first-passage time through a given threshold of a stochastic process is a classic problem that appears in many branches of physics. When the stochastic dynamics is markovian, the probability admits…

Statistical Mechanics · Physics 2009-05-05 Michele Maggiore , Antonio Riotto

We derive diffusive macroscopic equations for the particle and energy density of a system whose time evolution is described by a kinetic equation for the one particle position and velocity function f(r,v,t) that consists of a part that…

Statistical Mechanics · Physics 2018-11-14 Pedro L. Garrido , Joel L. Lebowitz

In this article integro-differential Volterra equations whose convolution kernel depends on the vector variable are considered and a connection of these equations with a class of semi-Markov processes is established. The variable order…

Probability · Mathematics 2018-07-19 Mladen Savov , Bruno Toaldo

We consider a Markovian jumping process which is defined in terms of the jump-size distribution and the waiting-time distribution with a position-dependent frequency, in the diffusion limit. We assume the power-law form for the frequency.…

Statistical Mechanics · Physics 2015-07-20 T. Srokowski , A. Kaminska

This paper develops solutions of fractional Fokker-Planck equations describing subdiffusion of probability densities of stochastic dynamical systems driven by non-Gaussian L\'evy processes, with space-time-dependent drift, diffusion and…

Probability · Mathematics 2016-11-29 Erkan Nane , Yinan NI

We propose a novel non-parametric learning paradigm for the identification of drift and diffusion coefficients of multi-dimensional non-linear stochastic differential equations, which relies upon discrete-time observations of the state. The…

Machine Learning · Computer Science 2025-03-11 Riccardo Bonalli , Alessandro Rudi
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