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Worm Algorithm for Problems of Quantum and Classical Statistics

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arxiv 0910.1393 v3 pith:SJ6TKUTF submitted 2009-10-08 cond-mat.stat-mech hep-lat

N. Prokof'ev , B. Svistunov This is my paper · ORCID
classification cond-mat.stat-mechhep-lat
keywords algorithmchapterquantumwormapproachbookcarrclassical
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This is a chapter of the multi-author book "Understanding Quantum Phase Transitions," edited by Lincoln Carr and published by Taylor and Francis. In this chapter, we give a general introduction to the worm algorithm and present important results highlighting the power of the approach

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Cited by 1 Pith paper

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  1. High-precision Monte Carlo study of several models in the three-dimensional U(1) universality class

    cond-mat.stat-mech 2019-08 accept novelty 7.0 of 10

    Finite-size scaling of wrapping probabilities gives Tc(XY)=2.2018441(5), Tc(Villain)=0.33306704(7), (t/U)c=0.0597291(8), nu=0.67183(18), and eta=0.03853(48) for the 3D U(1) universality class.

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