Autocorrelation study of the {\Theta} transition for a coarse-grained polymer model

TL;DR

This study uses Monte Carlo simulations to analyze how autocorrelation times in a coarse-grained polymer model reveal the collapse transition, especially useful in finite systems where traditional indicators are less clear.

Contribution

It demonstrates that extremal autocorrelation times serve as effective indicators for the collapse transition in polymer models, addressing challenges in finite system analysis.

Findings

Autocorrelation times peak near the collapse transition.

Autocorrelation analysis helps locate transition points in finite systems.

Critical slowing down correlates with the collapse transition.

Abstract

By means of Metropolis Monte Carlo simulations of a coarse-grained model for flexible polymers, we investigate how the integrated autocorrelation times of different energetic and structural quantities depend on the temperature. We show that, due to critical slowing down, an extremal autocorrelation time can also be considered as an indicator for the collapse transition that helps to locate the transition point. This is particularly useful for finite systems, where response quantities such as the specific heat do not necessarily exhibit clear indications for pronounced thermal activity.