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• W4220879497 abstract "Finite-size scaling at fixed renormalization-group invariant is a powerful and flexible technique to analyze Monte Carlo data at a critical point. It consists in fixing a given renormalization-group invariant quantity to a given value, thereby trading its statistical fluctuations with those of a parameter driving the transition. One remarkable feature is the observed significant improvement of statistical accuracy of various quantities, as compared to a standard analysis. We review the method, discussing in detail its implementation, the error analysis, and a previously introduced covariance-based optimization. Comprehensive benchmarks on the Ising model in two and three dimensions show large gains in the statistical accuracy, which are due to cross-correlations between observables. As an application, we compute an accurate estimate of the inverse critical temperature of the improved O(2) ϕ^{4} model on a three-dimensional cubic lattice." @default.
• W4220879497 created "2022-04-03" @default.
• W4220879497 creator A5062435126 @default.
• W4220879497 date "2022-03-24" @default.
• W4220879497 modified "2023-09-26" @default.
• W4220879497 title "Finite-size scaling at fixed renormalization-group invariant" @default.
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• W4220879497 doi "https://doi.org/10.1103/physreve.105.034137" @default.
• W4220879497 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/35428125" @default.
• W4220879497 hasPublicationYear "2022" @default.
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