13 papers
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…
Dynamical scaling near the pseudogap quantum critical point of the two-dimensional Hubbard model
Mathias Pelz, Gabriel Kotliar, Jan von Delft +1
We study dynamical scaling in the quantum-critical fan of the pseudogap-metal to Fermi-liquid transition of the two-dimensional Hubbard model. Using a four-patch dynamical cluster…
Quantum criticality in the two-dimensional Hubbard model
Mathias Pelz, Gabriel Kotliar, Jan von Delft +1
We study the normal-state, doping-driven phase diagram of the square-lattice Hubbard model using the dynamical cluster approximation combined with the numerical renormalization gro…
Symmetric estimator for discrete self-energy of discrete many-body systems
Aleksandrs Zacinskis, Frank T. Ebel, Mathias Pelz +5
We derive a discrete spectral representation of the single-particle self-energy using a discrete evaluation of Kugler's symmetric improved estimator. Our construction can be used o…
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…
Revisiting the - Heisenberg Model on a Triangular Lattice: Quasi-Degenerate Ground States and Phase Competition
Oleksandra Kovalska, Ester Pagès Fontanella, Benedikt Schneider +2
It is generally believed that the spin- triangular-lattice - Heisenberg model hosts a quantum spin liquid in the intermediate regime between the …