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Stochastic gyration driven by dichotomous noises

Title: Stochastic gyration driven by dichotomous noises
Authors: Herbeau, Timothée; Pastur, Leonid; Viot, Pascal; Oshanin, Gleb
Source: Journal of Statistical Mechanics: Theory and Experiment ; volume 2026, issue 1, page 013205 ; ISSN 1742-5468
Publisher Information: IOP Publishing
Publication Year: 2026
Description: We consider the stochastic dynamics of a particle on a plane in the presence of two noises and a confining parabolic potential—an analog of the experimentally relevant Brownian gyrator (BG) model. In contrast to the standard BG model, we suppose here that the time evolution of the position components is driven not by Gaussian white noise, but by two statistically independent dichotomous noises. We calculate analytically the position variances and cross-correlations, as well as the mean angular momentum, which permits us to establish the conditions in which a spontaneous rotational motion of the particle around the origin takes place. We also present a numerical analysis of the mean angular velocity. Finally, we analytically calculate some marginal position probability density functions, revealing a remarkably rich behavior that emerges in such a system of two coupled linear stochastic differential equations. We show that, depending on the values of the parameters characterizing the noise, these distributions approach the steady-state forms defined on a finite support, having very unusual shapes, possessing multiple maxima and minima, plateaus, and exhibiting a discontinuous behavior.
Document Type: article in journal/newspaper
Language: unknown
DOI: 10.1088/1742-5468/ae3081
DOI: 10.1088/1742-5468/ae3081/pdf
Availability: https://doi.org/10.1088/1742-5468/ae3081; https://iopscience.iop.org/article/10.1088/1742-5468/ae3081; https://iopscience.iop.org/article/10.1088/1742-5468/ae3081/pdf
Rights: https://creativecommons.org/licenses/by/4.0/ ; https://iopscience.iop.org/info/page/text-and-data-mining
Accession Number: edsbas.B772AEAD
Database: BASE