Adaptive Step Size for Hybrid Monte Carlo Algorithm
Philippe de Forcrand, Tetsuya Takaishi
Abstract
We implement an adaptive step size method for the Hybrid Monte Carlo a lgorithm. The adaptive step size is given by solving a symmetric error equation. An integr ator with such an adaptive step size is reversible. Although we observe appreciable variations of the step size, the overhead of the method exceeds its benefits. We propose an explanation for this phenomenon.
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