Matrix-product states have become the de facto standard for the representation of one-
dimensional quantum many body states. During the last few years, numerous new methods …

Tensor product state (TPS) based methods are powerful tools to efficiently simulate quantum
many-body systems in and out of equilibrium. In particular, the one-dimensional matrix …

We introduce an error measure for matrix-product states without requiring the relatively
costly two-site density-matrix renormalization group (2DMRG). This error measure is based …

Quantum lattice models with large local Hilbert spaces emerge across various fields in
quantum many-body physics. Problems such as the interplay between fermions and …

We show that the macroscopic magnetic and electronic properties of strongly correlated
electron systems can be manipulated by coupling them to a cavity mode. As a paradigmatic …

TeNPy (short for'Tensor Network Python') is a python library for the simulation of strongly
correlated quantum systems with tensor networks. The philosophy of this library is to achieve …

We have developed a method to simulate quantum spin models with the Dzyaloshinskii-
Moriya interaction (DMI) using Rydberg atom quantum simulators. Our approach involves a …

We adapt and optimize the projected-pair-entangled-state (PEPS) algorithm on finite lattices
(fPEPS) for two-dimensional Hubbard models and apply the algorithm to the Hubbard model …

Understanding the equilibrium properties and out of equilibrium dynamics of quantum field
theories are key aspects of fundamental problems in theoretical particle physics and …

We study the effects of Coulomb repulsive interactions on a Majorana Benalcazar–Bernevig–
Huges (MBBH) model. The MBBH model belongs to the class of second-order topological …