Heatbath Noise Methods in Lattice QCD
classification
✦ hep-lat
keywords
noisegaussianheatbathvariancealgorithmapproximatelyconvergenceeffective
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In a recent paper, de Forcrand has pointed out that matrix inversions using Gaussian noise need not be iterated to full convergence, but instead may be solved approximately and treated as a heatbath. Gaussian noise however is not optimal for minimizing variance. It shown here how his algorithm may be generalized to a mixture of Gaussian and Z(N) noise, resulting in a smaller effective variance for some operators.
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