Monte Carlo Quasi-Heatbath by approximate inversion
classification
❄️ cond-mat
hep-lat
keywords
distributionlinearsolvingsystemaccuracyapproximatearbitrarilycarlo
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When sampling the distribution P(phi) ~ exp(-|A phi|^2), a global heatbath normally proceeds by solving the linear system A phi = eta, where eta is a normal Gaussian vector, exactly. This paper shows how to preserve the distribution P(phi) while solving the linear system with arbitrarily low accuracy. Generalizations are presented.
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