Tuning the strength of emergent correlations in a Brownian gas via batch resetting

arXiv (Cornell University) 2026 Preprint Open access

Read full text
Authors: Gabriele de Mauro, Satya N. Majumdar, Grégory Schehr
DOI: 10.1209/0295-5075/ae8b58
Cited by: 0

Abstract

We study a gas of $N$ diffusing particles on the line subject to batch resetting: at rate $r$, a uniformly random subset of $m$ particles is reset to the origin. Despite the absence of interactions, the dynamics generates a nonequilibrium stationary state (NESS) with long-range correlations. Since standard renewal methods fail for $m

Fields of Study & Subjects

Advanced Thermodynamics and Statistical Mechanics Statistical Mechanics and Entropy Stochastic processes and statistical mechanics

Publication details

Journal / source
arXiv (Cornell University)
Publication date
27 January 2026
Document type
Preprint