Sparse sampling and tensor network representation of two-particle Green's functions
| Authors | |
|---|---|
| Year of publication | 2020 |
| Type | Article in Periodical |
| Magazine / Source | SciPost Physics |
| MU Faculty or unit | |
| Citation | |
| Web | https://scipost.org/10.21468/SciPostPhys.8.1.012 |
| Doi | http://dx.doi.org/10.21468/SciPostPhys.8.1.012 |
| Keywords | Green's function; Hubbard model; Tensor networks |
| Description | 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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