From the 1 of 4 linked papers with an AI index.
4 papers
Generalized Keldysh formalism for nonequilibrium correlation functions and its application to fluctuation dynamics
Ken Inayoshi, Hiroshi Shinaoka, Yuta Murakami
The paper presents a generalized Keldysh formalism with a virtual probe field that enables efficient computation of nonequilibrium two‑particle correlation functions, including ver…
A causality-based divide-and-conquer algorithm for nonequilibrium Green's function calculations with quantics tensor trains
Ken Inayoshi, Maksymilian Åroda, Anna Kauch +2
We propose a causality-based divide-and-conquer algorithm for nonequilibrium Green's function calculations with quantics tensor trains. This algorithm enables stable and efficient…
Memory-Efficient Nonequilibrium Green's Function Framework Built On Quantics Tensor Trains
Maksymilian Åroda, Ken Inayoshi, Hiroshi Shinaoka +1
One of the challenges in diagrammatic simulations of nonequilibrium phenomena in lattice models is the large memory demand for storing momentum-dependent two-time correlation funct…
Predictor-corrector method based on dynamic mode decomposition for tensor-train nonequilibrium Green's function calculations
Maksymilian Åroda, Ken Inayoshi, Michael Schüler +2
The nonequilibrium Green's function (NEGF) formalism is a powerful tool to study the nonequilibrium dynamics of correlated lattice systems, but its applicability to realistic syste…