Analytic Continuation of Quantum Monte Carlo Data by Stochastic Analytical Inference
Abstract
We present an algorithm for the analytic continuation of imaginary-time quantum Monte Carlo data which is strictly based on principles of Bayesian statistical inference. Within this framework we are able to obtain an explicit expression for the calculation of a weighted average over possible energy spectra, which can be evaluated by standard Monte Carlo simulations, yielding as by-product also the distribution function as function of the regularization parameter. Our algorithm thus avoids the usual ad-hoc assumptions introduced in similar algortihms to fix the regularization parameter. We apply the algorithm to imaginary-time quantum Monte Carlo data and compare the resulting energy spectra with those from a standard maximum entropy calculation.
Cite
@article{arxiv.0912.5204,
title = {Analytic Continuation of Quantum Monte Carlo Data by Stochastic Analytical Inference},
author = {S. Fuchs and T. Pruschke and M. Jarrell},
journal= {arXiv preprint arXiv:0912.5204},
year = {2013}
}