Sparse sampling and tensor network representation of two-particle Green's functions
| Autor: | Shinaoka, Hiroshi, Geffroy, Dominique, Wallerberger, Markus, Otsuki, Junya, Yoshimi, Kazuyoshi, Gull, Emanuel, Kuneš, Jan |
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| Rok vydání: | 2019 |
| Předmět: | |
| Zdroj: | SciPost Phys. 8, 012 (2020) |
| Druh dokumentu: | Working Paper |
| DOI: | 10.21468/SciPostPhys.8.1.012 |
| Popis: | 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. Comment: 27 pages in single column format, 12 pages (added missing references) |
| Databáze: | arXiv |
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