Data collapse in the critical region using finite-size scaling with subleading corrections

Abstract

We propose a treatment of the subleading corrections to finite-size scaling that preserves the notion of data collapse. This approach is used to extend and improve the usual Binder cumulant analysis. As a demonstration, we present results for the two- and three-dimensional classical Ising models and the two-dimensional, double-layer quantum antiferromagnet.