Sparse sampling and tensor network representation of two-particle Green's functions

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68378271%3A_____%2F20%3A00534736" target="_blank" >RIV/68378271:_____/20:00534736 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/00216224:14310/20:00114507

Výsledek na webu

<a href="http://hdl.handle.net/11104/0312915" target="_blank" >http://hdl.handle.net/11104/0312915</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.21468/SciPostPhys.8.1.012" target="_blank" >10.21468/SciPostPhys.8.1.012</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Sparse sampling and tensor network representation of two-particle Green's functions

Popis výsledku v původním jazyce

Many-body calculations at the two-particle level require a compact representation of two-particle Green's functions. In this paper, we introduce a sparse sampling scheme in the Matsubara frequency domain as well as a tensor network representation for two-particle Green's functions. The sparse sampling is based on the intermediate representation basis and allows an accurate extraction of the generalized susceptibility from a reduced set of Matsubara frequencies. The tensor network representation provides a system independent way to compress the information carried by two-particle Green's functions. We demonstrate efficiency of the present scheme for calculations of static and dynamic susceptibilities in single- and two-band Hubbard models in the framework of dynamical mean-field theory.

Název v anglickém jazyce

Sparse sampling and tensor network representation of two-particle Green's functions

Popis výsledku anglicky

Many-body calculations at the two-particle level require a compact representation of two-particle Green's functions. In this paper, we introduce a sparse sampling scheme in the Matsubara frequency domain as well as a tensor network representation for two-particle Green's functions. The sparse sampling is based on the intermediate representation basis and allows an accurate extraction of the generalized susceptibility from a reduced set of Matsubara frequencies. The tensor network representation provides a system independent way to compress the information carried by two-particle Green's functions. We demonstrate efficiency of the present scheme for calculations of static and dynamic susceptibilities in single- and two-band Hubbard models in the framework of dynamical mean-field theory.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

10302 - Condensed matter physics (including formerly solid state physics, supercond.)

Projekt

<a href="/cs/project/GA19-16937S" target="_blank" >GA19-16937S: Frustrované a nefrustrované spinové systémy s měkkými spiny v relativistických Mottových izolantech</a><br>

Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2020

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

SciPost Physics

ISSN

2542-4653

e-ISSN

—

Svazek periodika

8

Číslo periodika v rámci svazku

1

Stát vydavatele periodika

NL - Nizozemsko

Počet stran výsledku

23

Strana od-do

1-23

Kód UT WoS článku

000512377100012

EID výsledku v databázi Scopus

2-s2.0-85087353200