sparse-ir: Optimal compression and sparse sampling of many-body propagators-Reference-Cited by-同舟云学术

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sparse-ir: Optimal compression and sparse sampling of many-body propagators

Published:2023-02 Issue: Volume:21 Page:101266
ISSN:2352-7110
Container-title:SoftwareX
language:en
Short-container-title:SoftwareX

Author:

Wallerberger Markus^ORCID,Badr Samuel,Hoshino Shintaro,Huber Sebastian,Kakizawa Fumiya,Koretsune Takashi,Nagai Yuki,Nogaki Kosuke,Nomoto Takuya,Mori Hitoshi,Otsuki Junya,Ozaki Soshun,Plaikner Thomas,Sakurai Rihito,Vogel Constanze,Witt Niklas,Yoshimi Kazuyoshi,Shinaoka Hiroshi

Funder

JSPS

DFG

Japan Society for the Promotion of Science

Japan Science and Technology Agency

Austrian Science Fund

Precursory Research for Embryonic Science and Technology

Publisher

Elsevier BV

Subject

Computer Science Applications,Software

Reference61 articles.

1. Band-gap problem in semiconductors revisited: Effects of core states and many-body self-consistency;Ku;Phys Rev Lett,2002

2. Efficient temperature-dependent Green’s functions methods for realistic systems: Compact grids for orthogonal polynomial transforms;Kananenka;J Chem Theory Comput,2016

3. Orthogonal polynomial representation of imaginary-time Green’s functions;Boehnke;Phys Rev B,2011

4. Legendre-spectral Dyson equation solver with super-exponential convergence;Dong;J Chem Phys,2020

5. Sparse modeling approach to analytical continuation of imaginary-time quantum Monte Carlo data;Otsuki;Phys Rev E,2017

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4. Tensor hypercontraction for fully self-consistent imaginary-time GF2 and GWSOX methods: Theory, implementation, and role of the Green’s function second-order exchange for intermolecular interactions;The Journal of Chemical Physics;2024-08-26

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