# Noise-induced phase transitions: Effects of the noises' statistics and spectrum

## TL;DR

This paper investigates how different noise statistics and spectral properties influence noise-induced phase transitions, revealing that fat-tailed noises counteract correlation effects while compact-support noises enhance them, using mean-field analysis.

## Contribution

It introduces a study of noise effects on phase transitions considering non-Gaussian, colored noises, expanding understanding beyond previous Gaussian white noise assumptions.

## Key findings

- Fat-tailed noises reduce the impact of self-correlation.
- Compact-support noises amplify the effects of self-correlation.
- Distinct noise statistics significantly alter the susceptibility in phase transitions.

## Abstract

The local, uncorrelated multiplicative noises driving a second-order, purely noise-induced, ordering phase transition (NIPT) were assumed to be Gaussian and white in the model of [Phys. Rev. Lett. \textbf{73}, 3395 (1994)]. The potential scientific and technological interest of this phenomenon calls for a study of the effects of the noises' statistics and spectrum. This task is facilitated if these noises are dynamically generated by means of stochastic differential equations (SDE) driven by white noises. One such case is that of Ornstein--Uhlenbeck noises which are stationary, with Gaussian pdf and a variance reduced by the self-correlation time (\tau), and whose effect on the NIPT phase diagram has been studied some time ago. Another such case is when the stationary pdf is a (colored) Tsallis' (q)--\emph{Gaussian} which, being a \emph{fat-tail} distribution for (q>1) and a \emph{compact-support} one for (q<1), allows for a controlled exploration of the effects of the departure from Gaussian statistics. As done before with stochastic resonance and other phenomena, we now exploit this tool to study--within a simple mean-field approximation and with an emphasis on the \emph{order parameter} and the ``\emph{susceptibility}''--the combined effect on NIPT of the noises' statistics and spectrum. Even for relatively small (\tau), it is shown that whereas fat-tail noise distributions ((q>1)) counteract the effect of self-correlation, compact-support ones ((q<1)) enhance it. Also, an interesting effect on the susceptibility is seen in the last case.