Skip to main content
Article thumbnail
Location of Repository

Improvement of Monte Carlo estimates with covariance-optimized finite-size scaling at fixed phenomenological coupling

By Francesco Parisen Toldin


In the finite-size scaling analysis of Monte Carlo data, instead of computing the observables at fixed Hamiltonian parameters, one may choose to keep a renormalization-group invariant quantity, also called phenomenological coupling, fixed at a given value. Within this scheme of finite-size scaling, we exploit the statistical covariance between the observables in a Monte Carlo simulation in order to reduce the statistical errors of the quantities involved in the computation of the critical exponents. This method is general and does not require additional computational time. This approach is demonstrated in the Ising model in two and three dimensions, where large gain factors in CPU time are obtained.Comment: 5 pages, 1 figure, 2 tables; v2: slightly changed title, improved presentation, results unchange

Topics: Condensed Matter - Statistical Mechanics, High Energy Physics - Lattice
Year: 2011
DOI identifier: 10.1103/PhysRevE.84.025703
OAI identifier:
Download PDF:
Sorry, we are unable to provide the full text but you may find it at the following location(s):
  • (external link)
  • Suggested articles

    To submit an update or takedown request for this paper, please submit an Update/Correction/Removal Request.