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.