How to control nonlinear effects in Binder cumulants

TL;DR

This paper addresses nonlinear effects in finite size scaling of Binder cumulants, proposing a method to improve critical temperature estimates by using volume-dependent linear fits, validated on Dyson's hierarchical model.

Contribution

It introduces a volume-dependent linear fitting method to control nonlinear effects in Binder cumulant analysis, enhancing accuracy in critical parameter estimation.

Findings

Method works well for Dyson's hierarchical model

Estimates of nonlinear effects can be derived from small volume data

Improved crossing patterns among estimates

Abstract

We point out that ignoring nonlinear effects in finite size scaling may lead to errors in estimates of the critical temperature and Binder cumulants. We show that the order of magnitude of these effects can be estimated from data at relatively small volume. Using this estimate, we propose to use linear fits in increasingly small temperature regions as the volume is increased (rather than using a fixed temperature interval). The choice of the exact coefficient of proportionality can be optimized and reveals interesting crossing patterns among estimates. We show that the new procedure works very well for Dyson's hierarchical model. We discuss applications of the method for 3 dimensional spin models and finite temperature lattice gauge theories and comment on the nonlinear effects for existing calculations.