The theory of entanglement provides a fundamentally new language for describing
interactions and correlations in many-body systems. Its vocabulary consists of qubits and …

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

In this Article we describe the OpenMolcas environment and invite the computational
chemistry community to collaborate. The open-source project already includes a large …

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 …

Tensor networks are approximations of high-order tensors which are efficient to work with
and have been very successful for physics and mathematics applications. We demonstrate …

Simulating quantum mechanics is known to be a difficult computational problem, especially
when dealing with large systems. However, this difficulty may be overcome by using some …

This is a partly non-technical introduction to selected topics on tensor network methods,
based on several lectures and introductory seminars given on the subject. It should be a …

We show that the time-dependent variational principle provides a unifying framework for
time-evolution methods and optimization methods in the context of matrix product states. In …

The density-matrix renormalization group method (DMRG) has established itself over the
last decade as the leading method for the simulation of the statics and dynamics of one …

Quantum computers, though not yet available on the market, will revolutionize the future of
information processing. Quantum computers for special purposes like quantum simulators …