Abstract
A new method of extracting the low-lying energy spectrum from Monte Carlo estimates of Euclidean-space correlation functions which incorporates Bayesian inference is described and tested. The procedure fully exploits the information present in the correlation functions at small temporal separations and uses this information in a way consistent with fundamental probabilistic hypotheses. The computed errors on the best-fit energies include both statistical uncertainties and systematic errors associated with the treatment of contamination from higher-lying stationary states. Difficulties in performing the integrals needed to compute these error estimates are briefly discussed.
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