You are here

Data Driven Analytic Continuation for One Particle Spectral Functions

TitleData Driven Analytic Continuation for One Particle Spectral Functions
Publication TypeBook Chapter
Year of Publication2013
AuthorsLiu, J
EditorSimos, T, Psihoyios, G, Tsitouras, C
Book Title11th International Conference of Numerical Analysis and Applied Mathematics 2013, Pts 1 and 2
Series TitleAIP Conference Proceedings
Volume1558
Pagination1827-1830
PublisherAmer Inst Physics
CityMelville
ISBN Number978-0-7354-1185-2
Accession NumberWOS:000331472800422
KeywordsGlobal minimization, imaginary, inverse problem, non-negative least square fit (NNLS), One-particle spectral function, Pade approximant, quantum monte-carlo, regularization, Temperature Green function, Tikhonov, time Green function
Abstract

In this proceeding, an idea is outlined suggesting a generic treatment on any type of input data for a numerical analytic continuation problem, which is needed when dynamical information is to be extracted from a calculationally convenient one particle imaginary time Green function. The quality of the resulting spectral function will rely only on the data to be treated, viz, data-driven. This is different from the Maximum Entropy or the Stochastic method which relies on an entropy term to guide convergence of the resulting spectral function.

DOI10.1063/1.4825883
Custom 1

Not AL