From the 1 of 15 linked papers with an AI index.
15 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…
Weak-coupling tensor cross interpolation impurity solver for nonequilibrium dynamical mean-field theory
Shuta Matsuura, Hiroshi Shinaoka, Philipp Werner +1
Simulating nonequilibrium quantum many-body systems remains a major challenge due to the exponential growth of the computational complexity with real time. Here we implement a none…
Parallelized contraction of tensor trains or matrix product operators
Simone FoderÃ, Marc K. Ritter, Hiroshi Shinaoka +1
Tensor Trains (TT), also known as Matrix Product States (MPS) and Matrix Product Operators (MPO), provide a compact and structured representation for high-dimensional data and oper…
Diagnosing phase transitions through time-scale entanglement
Stefan Rohshap, Hirone Ishida, Frederic Bippus +5
Spatial entanglement of quantum states has become a central paradigm of many-body physics. Here, we unearth a fundamentally different form of entanglement, the entanglement between…
Adaptive Patching for Tensor Train Computations
Gianluca Grosso, Marc K. Ritter, Stefan Rohshap +5
Quantics Tensor Train (QTT) operations such as matrix product operator contractions are prohibitively expensive for large bond dimensions. We propose an adaptive patching scheme th…
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…