期刊
SCIPOST PHYSICS
卷 8, 期 1, 页码 -出版社
SCIPOST FOUNDATION
DOI: 10.21468/SciPostPhys.8.1.012
关键词
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资金
- JSPS KAKENHI [18H01158, 16K17735, 18H04301]
- Building of Consortia for the Development of Human Resources in Science and Technology, MEXT, Japan
- ERC under EU [646807]
- Czech Science Foundation (GACR) [GA19-16937S]
- Ministry of Education, Youth and Sports from the Large Infrastructures for Research, Experimental Development and Innovations project IT4Innovations National Supercomputing Center [LM2015070]
- Simons Foundation
- programme Projects of Large Research, Development, and Innovations Infrastructures [CESNET LM2015042]
- European Research Council (ERC) [646807] Funding Source: European Research Council (ERC)
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.
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