Saved in:
Bibliographic Details
Main Authors: Ma, Yi-Ping, Sudakow, Ivan, Krapivsky, P. L., Vakulenko, Sergey A.
Format: Preprint
Published: 2025
Subjects:
Online Access:https://arxiv.org/abs/2510.07301
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1866908921580486656
author Ma, Yi-Ping
Sudakow, Ivan
Krapivsky, P. L.
Vakulenko, Sergey A.
author_facet Ma, Yi-Ping
Sudakow, Ivan
Krapivsky, P. L.
Vakulenko, Sergey A.
contents We study the dynamics of a mean-field Ising model whose coupling depends on the magnetization via a linear feedback function. A key feature of this linear feedback Ising model (FIM) is the possibility of temperature-induced bistability, where a temperature increase can favor bistability between two phases. We show that the linear FIM provides a minimal model for a transcritical bifurcation as the temperature varies. Moreover, there can be two or three critical temperatures when the external magnetic field is non-negative. In the bistable region, we identify a Maxwell temperature where the two phases are equally probable, and we find that increasing the temperature favors the lower phase. We show that the probability distribution becomes non-Gaussian on certain time intervals when the magnetization converges algebraically at either zero temperature or critical temperatures. Near critical points in the parameter space, we derive a Fokker-Planck equation, construct the families of equilibrium distributions, and formulate scaling laws for transition rates between two stable equilibria. The linear FIM offers considerable flexibility in controlling steady-state bifurcations and their associated equilibrium distributions, which can be desirable for modeling feedback systems across various disciplines.
format Preprint
id arxiv_https___arxiv_org_abs_2510_07301
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Dynamics of feedback Ising model
Ma, Yi-Ping
Sudakow, Ivan
Krapivsky, P. L.
Vakulenko, Sergey A.
Statistical Mechanics
Dynamical Systems
We study the dynamics of a mean-field Ising model whose coupling depends on the magnetization via a linear feedback function. A key feature of this linear feedback Ising model (FIM) is the possibility of temperature-induced bistability, where a temperature increase can favor bistability between two phases. We show that the linear FIM provides a minimal model for a transcritical bifurcation as the temperature varies. Moreover, there can be two or three critical temperatures when the external magnetic field is non-negative. In the bistable region, we identify a Maxwell temperature where the two phases are equally probable, and we find that increasing the temperature favors the lower phase. We show that the probability distribution becomes non-Gaussian on certain time intervals when the magnetization converges algebraically at either zero temperature or critical temperatures. Near critical points in the parameter space, we derive a Fokker-Planck equation, construct the families of equilibrium distributions, and formulate scaling laws for transition rates between two stable equilibria. The linear FIM offers considerable flexibility in controlling steady-state bifurcations and their associated equilibrium distributions, which can be desirable for modeling feedback systems across various disciplines.
title Dynamics of feedback Ising model
topic Statistical Mechanics
Dynamical Systems
url https://arxiv.org/abs/2510.07301