Ground state mass in short lattices by controlling overconfidence and bias in Bayesian fits

Abstract

We investigate the seemingly ill-defined problem of extracting a ground-state mass from a lattice simulation where the extent of the lattice is not long enough to project out the ground-state properly. We regulate the problem using a Bayesian method. We show that controlling meta-parameters (overconfidence) can allow the data to overcome the input priors (bias). We can write the method as a black-box technique which allows extraction of a ground-state mass, even on a relatively short lattice.

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