We present a generalization of the discrete Lehmann representation (DLR) to three-point
correlation and vertex functions in imaginary time and Matsubara frequency. The …

By merging algorithmic Matsubara integration with discrete pole representations we present
a procedure to generate fully analytic closed form results for impurity problems at fixed …

We present a method to accelerate the numerical evaluation of spatial integrals of Feynman
diagrams when expressed on the real frequency axis. This can be realized through use of a …

We present a systematic study of the interaction, do**, and layer dependence of the dx 2−
y 2-wave pairing susceptibility of the Hubbard model for a stacked 2D square lattice. We …

We present a symbolic algorithm for the fully analytic treatment of perturbative expansions of
Hamiltonians with general two-body interactions. The method merges well-known analytics …

We compute the perturbative expansion for the effective interaction W of the half-filled 2-
dimensional Hubbard model. We derive extensions of standard random-phase …

We compute the diagrammatic expansion of the particle-particle susceptibility via algorithmic
Matsubara integration and compute the correlated pairing susceptibility in the …

We present torchami, an advanced implementation of algorithmic Matsubara integration
(AMI) that utilizes pytorch as a backend to provide easy parallelization and GPU support …

We study the two-dimensional extended Hubbard model on a square lattice and incorporate
spin-differentiated nearest neighbor (NN) interactions where the equal-spin ($ V_ {uu} $) …

In the first part of this work we introduce the symbolic determinant method (symDET) for
constructing many-body perturbative expansions which is motivated by the Algorithmic …