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Sparse sampling and tensor network representation of two-particle Green's functions
- Source :
- SciPost Phys. 8, 012 (2020)
- Publication Year :
- 2019
-
Abstract
- 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.<br />Comment: 27 pages in single column format, 12 pages (added missing references)
- Subjects :
- Condensed Matter - Strongly Correlated Electrons
Physics - Computational Physics
Subjects
Details
- Database :
- arXiv
- Journal :
- SciPost Phys. 8, 012 (2020)
- Publication Type :
- Report
- Accession number :
- edsarx.1909.07519
- Document Type :
- Working Paper
- Full Text :
- https://doi.org/10.21468/SciPostPhys.8.1.012