Corrections to finite-size scaling in the 3D Ising model based on non-perturbative approaches and Monte Carlo simulations
J. Kaupuzs, R.V.N. Melnik, J. Rimsans

TL;DR
This paper investigates corrections to finite-size scaling in the 3D Ising model using non-perturbative analytical methods and Monte Carlo simulations, providing new estimates for correction exponents and discussing their impact on critical exponent determination.
Contribution
It introduces a non-perturbative approach to estimate correction-to-scaling exponents and analyzes the dependence of these estimates on different finite-size scaling methods.
Findings
Correction exponent (gamma-1)/nu is approximately 0.38.
Numerical estimate of omega is 0.25(33), consistent with theoretical bounds.
Estimates of omega vary significantly across methods, affecting critical exponent calculations.
Abstract
Corrections to scaling in the 3D Ising model are studied based on non-perturbative analytical arguments and Monte Carlo (MC) simulation data for different lattice sizes L. Analytical arguments show the existence of corrections with the exponent (gamma-1)/nu (approximately 0.38), the leading correction-to-scaling exponent being omega =< (gamma-1)/nu. A numerical estimation of omega from the susceptibility data within 40 =< L =< 2048 yields omega=0.25(33). It is consistent with the statement omega =< (gamma-1)/nu, as well as with the value omega = 1/8 of the GFD theory. We reconsider the MC estimation of omega from smaller lattice sizes to show that it does not lead to conclusive results, since the obtained values of omega depend on the particular method chosen. In particular, estimates ranging from omega =1.274(72) to omega=0.18(37) are obtained by four different finite-size scaling…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsTheoretical and Computational Physics · Markov Chains and Monte Carlo Methods · Stochastic processes and statistical mechanics
