Zero-Variance Principle for Monte Carlo Algorithms
Roland Assaraf,Michel Caffarel +1 more
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TLDR
In this paper, the authors present a general approach to greatly increase at little cost the efficiency of Monte Carlo algorithms by associating a renormalized observable (improved estimator) having the same average but a different variance.Abstract:
We present a general approach to greatly increase at little cost the efficiency of Monte Carlo algorithms. To each observable to be computed we associate a renormalized observable (improved estimator) having the same average but a different variance. By writing down the zero-variance condition a fundamental equation determining the optimal choice for the renormalized observable is derived (zero-variance principle for each observable separately). We show, with several examples including classical and quantum Monte Carlo calculations, that the method can be very powerful.read more
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