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A physical-mathematical approach to anomalous diffusion may be based on generalized diffusion equations (containing derivatives of fractional order in space or/and time) and related random walk models. The fundamental solution (for the…

Statistical Mechanics · Physics 2007-09-25 Rudolf Gorenflo , Francesco Mainardi , Daniele Moretti , Gianni Pagnini , Paolo Paradisi

Consider a particle diffusing in a confined volume which is divided into two equal regions. In one region the diffusion coefficient is twice the value of the diffusion coefficient in the other region. Will the particle spend equal…

Dynamical Systems · Mathematics 2015-06-04 P. F. Tupper , Xin Yang

We analyze a pair of diffusion equations which are derived in the infinite system--size limit from a microscopic, individual--based, stochastic model. Deviations from the conventional Fickian picture are found which ultimately relate to the…

Statistical Mechanics · Physics 2015-05-18 Duccio Fanelli , Alan J. McKane

Systems are studied in which transport is possible due to large extension with open boundaries in certain directions but the particles responsible for transport can disappear from it by leaving it in other directions, by chemical reaction…

chao-dyn · Physics 2008-02-03 Z. Kaufmann

The purpose of this paper is to consider the exit-time problem for a finite-range Markov jump process, i.e, the distance the particle can jump is bounded independent of its location. Such jump diffusions are expedient models for anomalous…

Probability · Mathematics 2015-01-29 Nathanial Burch , Marta D'Elia , R. B. Lehoucq

We discuss diffusion properties of a dynamical system, which is characterised by long-tail distributions and finite correlations. The particle velocity has the stable L\'evy distribution; it is assumed as a jumping process (the kangaroo…

Statistical Mechanics · Physics 2011-06-21 Tomasz Srokowski

Diffusive molecular dynamics is a novel model for materials with atomistic resolution that can reach diffusive time scales. The main ideas of diffusive molecular dynamics are to first minimize an approximate variational Gaussian free energy…

Numerical Analysis · Mathematics 2015-06-09 Gideon Simpson , Mitchell Luskin , David J. Srolovitz

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

Physical laws governing population dynamics are generally expressed as differential equations. Research in recent decades has incorporated fractional-order (non-integer) derivatives into differential models of natural phenomena, such as…

Numerical Analysis · Mathematics 2022-12-08 A. P. Harris , T. A. Biala , A. Q. M. Khaliq

In this work, we characterize the solution of a system of elliptic integro-differential equations describing a phenotypically structured population subject to mutation, selection and migration between two habitats. Assuming that the effects…

Analysis of PDEs · Mathematics 2016-12-20 Sepideh Mirrahimi

A key feature of the classical Fluctuation Dissipation theorem is its ability to approximate the average response of a dynamical system to a sufficiently small external perturbation from an appropriate time correlation function of the…

Mathematical Physics · Physics 2019-10-02 Rafail V. Abramov

We propose a new evolutionary dynamics for population games with a discrete strategy set, inspired by the theory of optimal transport and Mean field games. The dynamics can be described as a Fokker-Planck equation on a discrete strategy…

Optimization and Control · Mathematics 2018-11-14 Shui-Nee Chow , Wuchen Li , Jun Lu , Haomin Zhou

The drift diffusion model (DDM) is a model of sequential sampling with diffusion (Brownian) signals, where the decision maker accumulates evidence until the process hits a stopping boundary, and then stops and chooses the alternative that…

Econometrics · Economics 2022-10-12 Drew Fudenberg , Whitney K. Newey , Philipp Strack , Tomasz Strzalecki

The method of potential solutions of Fokker-Planck equations is used to develop a transport equation for the joint probability of N stochastic variables with Lochner's generalized Dirichlet distribution (R.H. Lochner, A Generalized…

Mathematical Physics · Physics 2013-10-02 J. Bakosi , J. R. Ristorcelli

Stochastic kinetic models (SKMs) are increasingly used to account for the inherent stochasticity exhibited by interacting populations of species in areas such as epidemiology, population ecology and systems biology. Species numbers are…

Computation · Statistics 2023-04-06 Tom E. Lowe , Andrew Golightly , Chris Sherlock

Metastable condensed matter typically fluctuates about local energy minima at the femtosecond time scale before transitioning between local minima after nanoseconds or microseconds. This vast scale separation limits the applicability of…

Computational Physics · Physics 2017-11-22 Brittan A Farmer , Mitchell Luskin , Petr Plecháč , Gideon Simpson

A large deviation principle is established for a two-scale stochastic system in which the slow component is a continuous process given by a small noise finite dimensional It\^{o} stochastic differential equation, and the fast component is a…

Probability · Mathematics 2017-05-09 Amarjit Budhiraja , Paul Dupuis , Arnab Ganguly

We employ a generalization of Einstein's random walk paradigm for diffusion to derive a class of multidimensional degenerate nonlinear parabolic equations in non-divergence form. Specifically, in these equations, the diffusion coefficient…

Analysis of PDEs · Mathematics 2023-07-14 Ivan C. Christov , Isanka Garli Hevage , Akif Ibraguimov , Rahnuma Islam

The growth of the average kinetic energy of classical particles is studied for potentials that are random both in space and time. Such potentials are relevant for recent experiments in optics and in atom optics. It is found that for small…

Statistical Mechanics · Physics 2013-08-30 Yevgeny Krivolapov , Shmuel Fishman

Diffusion models have emerged as powerful tools for generative modeling, demonstrating exceptional capability in capturing target data distributions from large datasets. However, fine-tuning these massive models for specific downstream…

Machine Learning · Computer Science 2025-09-01 Yinbin Han , Meisam Razaviyayn , Renyuan Xu