Analytic continuation from limited noisy Matsubara data

DOI10.1016/J.JCP.2022.111549arXiv2202.09719MaRDI QIDQ6391603

Lexing Ying

Publication date: 19 February 2022

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.

Mathematics Subject Classification ID

Numerical approximation and computational geometry (primarily algorithms) (65Dxx) Numerical linear algebra (65Fxx) Approximations and expansions (41Axx)

This page was built for publication: Analytic continuation from limited noisy Matsubara data

Report a bug (only for logged in users!)Click here to report a bug for this page (MaRDI item Q6391603)