Active particle in one dimension subjected to resetting with memory

Fuente: arXiv
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Autores principales: Boyer, Denis, Majumdar, Satya N.
Formato: Preprint
Publicado: 2023
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author Boyer, Denis
Majumdar, Satya N.
author_facet Boyer, Denis
Majumdar, Satya N.
contents The study of diffusion with preferential returns to places visited in the past has attracted an increased attention in recent years. In these highly non-Markov processes, a standard diffusive particle intermittently resets at a given rate to previously visited positions. At each reset, a position to be revisited is randomly chosen with a probability proportional to the accumulated amount of time spent by the particle at that position. These preferential revisits typically generate a very slow diffusion, logarithmic in time, but still with a Gaussian position distribution at late times. Here we consider an active version of this model, where between resets the particle is self-propelled with constant speed and switches direction in one dimension according to a telegraphic noise. Hence there are two sources of non-Markovianity in the problem. We exactly derive the position distribution in Fourier space, as well as the variance of the position at all times. The crossover from the short-time ballistic regime, dominated by activity, to the large-time anomalous logarithmic growth induced by memory is studied. We also analytically derive a large deviation principle for the position, which exhibits a logarithmic time-scaling instead of the usual algebraic form. Interestingly, at large distances, the large deviations become independent of time and match the non-equilibrium steady state of a particle under resetting to its starting position only.
format Preprint
id arxiv_https___arxiv_org_abs_2312_13439
institution arXiv
publishDate 2023
record_format arxiv
spellingShingle Active particle in one dimension subjected to resetting with memory
Boyer, Denis
Majumdar, Satya N.
Statistical Mechanics
The study of diffusion with preferential returns to places visited in the past has attracted an increased attention in recent years. In these highly non-Markov processes, a standard diffusive particle intermittently resets at a given rate to previously visited positions. At each reset, a position to be revisited is randomly chosen with a probability proportional to the accumulated amount of time spent by the particle at that position. These preferential revisits typically generate a very slow diffusion, logarithmic in time, but still with a Gaussian position distribution at late times. Here we consider an active version of this model, where between resets the particle is self-propelled with constant speed and switches direction in one dimension according to a telegraphic noise. Hence there are two sources of non-Markovianity in the problem. We exactly derive the position distribution in Fourier space, as well as the variance of the position at all times. The crossover from the short-time ballistic regime, dominated by activity, to the large-time anomalous logarithmic growth induced by memory is studied. We also analytically derive a large deviation principle for the position, which exhibits a logarithmic time-scaling instead of the usual algebraic form. Interestingly, at large distances, the large deviations become independent of time and match the non-equilibrium steady state of a particle under resetting to its starting position only.
title Active particle in one dimension subjected to resetting with memory
topic Statistical Mechanics
url https://arxiv.org/abs/2312.13439