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We develop an encounter-based approach for describing restricted diffusion with a gradient drift towards a partially reactive boundary. For this purpose, we introduce an extension of the Dirichlet-to-Neumann operator and use its eigenbasis…

Chemical Physics · Physics 2022-10-10 Denis S. Grebenkov

Systems that evolve towards a state from which they cannot depart are common in nature. But the fluctuation-dissipation theorem, a fundamental result in statistical mechanics, is mainly restricted to systems near-stationarity. In processes…

Statistical Mechanics · Physics 2023-10-25 Prajwal Padmanabha , Sandro Azaele , Amos Maritan

We study the relaxation of a diffusive particle confined in an arbitrary external potential and subject to a non-Markovian resetting protocol. With a constant rate $r$, a previous time $\tau$ between the initial time and the present time…

Statistical Mechanics · Physics 2025-02-14 Denis Boyer , Martin R. Evans , Satya N. Majumdar

Motivated by the dynamics of resonant neurons we discuss the properties of the first passage time (FPT) densities for nonmarkovian differentiable random processes. We start from an exact expression for the FPT density in terms of an…

Data Analysis, Statistics and Probability · Physics 2009-11-11 T. Verechtchaguina , I. M. Sokolov , L. Schimansky-Geier

Diffusion is a fundamental physical phenomenon with critical applications in fields such as metallurgy, cell biology, and population dynamics. While standard diffusion is well-understood, anomalous diffusion often requires complex non-local…

Statistical Mechanics · Physics 2026-01-16 Gabriel Barreiro , Vladimir Pérez-Veloz

Fractional Brownian motion is a Gaussian stochastic process with long-range correlations in time; it has been shown to be a useful model of anomalous diffusion. Here, we investigate the effects of mutual interactions in an ensemble of…

Statistical Mechanics · Physics 2025-09-15 Jonathan House , Rashad Bakhshizada , Skirmantas Janušonis , Ralf Metzler , Thomas Vojta

Generative modeling has recently undergone remarkable advancements, primarily propelled by the transformative implications of Diffusion Probabilistic Models (DPMs). The impressive capability of these models, however, often entails…

Machine Learning · Computer Science 2023-10-03 Gongfan Fang , Xinyin Ma , Xinchao Wang

A new approach to the modeling of nonfree particle diffusion is presented. The approach uses a general setup based on geometric graphs (networks of curves), which means that particle diffusion in anything from arrays of barriers and pore…

Statistical Mechanics · Physics 2018-04-05 Niels Buhl

We examine the reversible adsorption of hard spheres on a random site surface in which the adsorption sites are uniformly and randomly distributed on a plane. Each site can be occupied by one solute provided that the nearest occupied site…

Statistical Mechanics · Physics 2015-06-25 C. Oleyar , J. Talbot

In the upscaling from pore- to continuum (Darcy) scale, reaction and deposition phenomena at the solid-liquid interface of a porous medium have to be represented by macroscopic reaction source terms. The effective rates can be computed, in…

Fluid Dynamics · Physics 2018-07-04 Gianluca Boccardo , Eleonora Crevacore , Rajandrea Sethi , Matteo Icardi

Linear diffusions are used to model a large number of stochastic processes in physics, including small mechanical and electrical systems perturbed by thermal noise, as well as Brownian particles controlled by electrical and optical forces.…

Statistical Mechanics · Physics 2023-05-10 Johan du Buisson , Hugo Touchette

Diffusion models have recently exhibited remarkable abilities to synthesize striking image samples since the introduction of denoising diffusion probabilistic models (DDPMs). Their key idea is to disrupt images into noise through a fixed…

Computer Vision and Pattern Recognition · Computer Science 2023-03-28 Zijian Zhang , Zhou Zhao , Jun Yu , Qi Tian

An encounter-based approach consists in using the boundary local time as a proxy for the number of encounters between a diffusing particle and a target to implement various surface reaction mechanisms on that target. In this paper, we…

Statistical Mechanics · Physics 2023-10-03 Ziyad Benkhadaj , Denis S. Grebenkov

The calculation of the diffusion-controlled reaction rate for partially absorbing, non-spherical boundaries presents a formidable problem of broad relevance. In this paper we take the reference case of a spherical boundary and work out a…

Statistical Mechanics · Physics 2019-11-11 Francesco Piazza , Denis Grebenkov

In this paper we consider a multiparticle version of a recent probabilistic framework for studying diffusion-mediated surface reactions. The basic idea of the probabilistic approach is to consider the joint probability density or…

Statistical Mechanics · Physics 2022-10-19 Paul C Bressloff

We present a unified approach to those observables of stochastic processes under reset that take the form of averages of functionals depending on the most recent renewal period. We derive solutions for the observables, and determine the…

Soft Condensed Matter · Physics 2019-03-28 G. John Lapeyre , Marco Dentz

We prove a central limit theorem for the momentum distribution of a particle undergoing an unbiased spatially periodic random forcing at exponentially distributed times without friction. The start is a linear Boltzmann equation for the…

Mathematical Physics · Physics 2015-05-14 Jeremy Clark , Christian Maes

This paper presents a diffusion process with a novel resetting mechanism in which the amplitude of the process is instantaneously converted to a proportion of its value at random times. This model is described by a Langevin equation with…

Statistical Mechanics · Physics 2022-04-18 J. Kevin Pierce

In this paper, we analyze the mean first passage time (MFPT) for a single Brownian particle to find a stochastically-gated target under the additional condition that the position of the particle is reset to a fixed position $\x_r$ at a rate…

Statistical Mechanics · Physics 2020-10-28 Paul C Bressloff

We introduce the Fixed Point Diffusion Model (FPDM), a novel approach to image generation that integrates the concept of fixed point solving into the framework of diffusion-based generative modeling. Our approach embeds an implicit fixed…

Computer Vision and Pattern Recognition · Computer Science 2024-01-18 Xingjian Bai , Luke Melas-Kyriazi