Maximum Entropy Analytic Continuation of Quantum Monte Carlo Data
نویسنده
چکیده
We present a pedagogical discussion of the Maximum Entropy Method which is a precise and systematic way of analytically continuing Euclidean-time quantum Monte Carlo results to real frequencies. Here, Bayesian statistics are used to determine which of the infinite number of real-frequency spectra are consistent with the QMC data is most probable. Bayesian inference is also used to qualify the solution and optimize the inputs. We develop the Bayesian formalism, present a detailed description of the data qualification, sketch an efficient algorithm to solve for the optimal spectra, and present a detailed case study to demonstrate the method.
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