Originally developed in the context of condensed-matter physics and based on
renormalization group ideas, tensor networks have been revived thanks to quantum …

Tensor networks provide extremely powerful tools for the study of complex classical and
quantum many-body problems. Over the past two decades, the increment in the number of …

We report an accurate and efficient classical simulation of a kicked Ising quantum system on
the heavy hexagon lattice. A simulation of this system was recently performed on a 127-qubit …

We develop a machine learning method to construct accurate ground-state wave functions
of strongly interacting and entangled quantum spin as well as fermionic models on lattices. A …

Variational studies of the tJ model on the square lattice based on infinite projected-
entangled pair states confirm an extremely close competition between a uniform d-wave …

The density matrix renormalization group (DMRG) is one of the most powerful numerical
methods for studying two-dimensional quantum lattice systems, despite a perception that it is …

Featuring detailed explanations of the major algorithms used in quantum Monte Carlo
simulations, this is the first textbook of its kind to provide a pedagogical overview of the field …

We present a scheme to perform an iterative variational optimization with infinite projected
entangled-pair states, a tensor network ansatz for a two-dimensional wave function in the …

We present a conjugate-gradient method for the ground-state optimization of projected
entangled-pair states (PEPS) in the thermodynamic limit, as a direct implementation of the …

The infinite projected entangled pair states (iPEPS) algorithm [J. Jordan, Phys. Rev. Lett.
101, 250602 (2008) PRLTAO 0031-9007 10.1103/PhysRevLett. 101.250602] has become a …