Abstract
In this paper we present the average spectrum method, a new method for obtaining real-frequency information from imaginary-time quantum Monte Carlo data. This technique does not require the adjustable parameters, smoothness constraints, or model forms of some previous techniques, yet produces smooth, consistent spectra from noisy data-Various tests of the method on mock data are presented, as well as realistic applications to the two-dimensional Hubbard model.KeywordsAnalytic ContinuationHubbard ModelAverage SpectrumMaximum Entropy MethodPairing SymmetryThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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