Gespeichert in:
Bibliographische Detailangaben
Hauptverfasser: Goswami, Shubhang, Barros, Kipton, Carbone, Matthew R.
Format: Preprint
Veröffentlicht: 2023
Schlagworte:
Online-Zugang:https://arxiv.org/abs/2306.11038
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
_version_ 1866913235419004928
author Goswami, Shubhang
Barros, Kipton
Carbone, Matthew R.
author_facet Goswami, Shubhang
Barros, Kipton
Carbone, Matthew R.
contents The rational function approximation provides a natural and interpretable representation of response functions such as the many-body spectral functions. We apply the Vector Fitting (VFIT) algorithm to fit a variety of spectral functions calculated from the Holstein model of electron-phonon interactions. We show that the resulting rational functions are highly efficient in their fitting of sharp features in the spectral functions, and could provide a means to infer physically relevant information from a spectral dataset. The position of the peaks in the approximated spectral function are determined by the location of poles in the complex plane. In addition, we developed an enhanced version of VFIT by introducing a regularization parameter that is slowly annealed to zero. With this new procedure, we demonstrate it is possible to achieve accurate spectral function fits that vary smoothly as a function of physical conditions.
format Preprint
id arxiv_https___arxiv_org_abs_2306_11038
institution arXiv
publishDate 2023
record_format arxiv
spellingShingle Physically interpretable approximations of many-body spectral functions
Goswami, Shubhang
Barros, Kipton
Carbone, Matthew R.
Statistical Mechanics
The rational function approximation provides a natural and interpretable representation of response functions such as the many-body spectral functions. We apply the Vector Fitting (VFIT) algorithm to fit a variety of spectral functions calculated from the Holstein model of electron-phonon interactions. We show that the resulting rational functions are highly efficient in their fitting of sharp features in the spectral functions, and could provide a means to infer physically relevant information from a spectral dataset. The position of the peaks in the approximated spectral function are determined by the location of poles in the complex plane. In addition, we developed an enhanced version of VFIT by introducing a regularization parameter that is slowly annealed to zero. With this new procedure, we demonstrate it is possible to achieve accurate spectral function fits that vary smoothly as a function of physical conditions.
title Physically interpretable approximations of many-body spectral functions
topic Statistical Mechanics
url https://arxiv.org/abs/2306.11038