Analytic continuation from limited noisy Matsubara data
Numerical Analysis
2022-09-14 v2 Numerical Analysis
Computational Physics
Abstract
This note proposes a new algorithm for estimating spectral function from limited noisy Matsubara data. We consider both the molecule and condensed matter cases. In each case, the algorithm constructs an interpolant of the Matsubara data and uses conformal mapping and Prony's method to estimate the spectral function. Numerical results are provided to demonstrate the performance of the algorithm.
Cite
@article{arxiv.2202.09719,
title = {Analytic continuation from limited noisy Matsubara data},
author = {Lexing Ying},
journal= {arXiv preprint arXiv:2202.09719},
year = {2022}
}