Efficient ab initio many-body calculations based on sparse modeling of Matsubara Green's function
Hiroshi Shinaoka, Naoya Chikano, Emanuel Gull, Jia Li, Takuya Nomoto, Junya Otsuki, Markus Wallerberger, Tianchun Wang, Kazuyoshi Yoshimi
SciPost Phys. Lect. Notes 63 (2022) · published 22 September 2022
- doi: 10.21468/SciPostPhysLectNotes.63
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Abstract
This lecture note reviews recently proposed sparse-modeling approaches for efficient ab initio many-body calculations based on the data compression of Green's functions. The sparse-modeling techniques are based on a compact orthogonal basis, an intermediate representation (IR) basis, for imaginary-time and Matsubara Green's functions. A sparse sampling method based on the IR basis enables solving diagrammatic equations efficiently. We describe the basic properties of the IR basis, the sparse sampling method and its applications to ab initio calculations based on the GW approximation and the Migdal-Eliashberg theory. We also describe a numerical library for the IR basis and the sparse sampling method, sparse-ir, and provide its sample codes. This lecture note follows the Japanese review article with major revisions [H. Shinaoka et al., Solid State Physics 56(6), 301 (2021)].
Cited by 9
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Authors / Affiliations: mappings to Contributors and Organizations
See all Organizations.- 1 Hiroshi Shinaoka,
- 1 Naoya Chikano,
- 2 Emanuel Gull,
- 2 Jia Li,
- 3 Takuya Nomoto,
- 4 Junya Otsuki,
- 5 Markus Wallerberger,
- 3 Tianchun Wang,
- 3 Kazuyoshi Yoshimi
- 1 埼玉大学 / Saitama University
- 2 University of Michigan–Ann Arbor [UM]
- 3 東京大学 / University of Tokyo [UT]
- 4 岡山大学 / Okayama University
- 5 Technische Universität Wien / Vienna University of Technology [TUW]
- Austrian Science Fund (FWF) (through Organization: Fonds zur Förderung der wissenschaftlichen Forschung / FWF Austrian Science Fund [FWF])
- Japan Science and Technology Agency [JST]
- 日本学術振興会 / Japan Society for the Promotion of Science [JSPS]
- Simons Foundation