Practical challenges in simulating quantum systems on classical computers have been
widely recognized in the quantum physics and quantum chemistry communities over the …

In the past two decades, the density matrix renormalization group (DMRG) has emerged as
an innovative new method in quantum chemistry relying on a theoretical framework very …

The density-matrix renormalization group (DMRG) is a numerical algorithm for the efficient
truncation of the Hilbert space of low-dimensional strongly correlated quantum systems …

The treatment of high‐dimensional problems such as the Schrödinger equation can be
approached by concepts of tensor product approximation. We present general techniques …

Current descriptions of the ab initio density matrix renormalization group (DMRG) algorithm
use two superficially different languages: an older language of the renormalization group …

During the past 15 years, the density matrix renormalization group (DMRG) has become
increasingly important for ab initio quantum chemistry. Its underlying wavefunction ansatz …

We present a compendium of numerical simulation techniques, based on tensor network
methods, aiming to address problems of many-body quantum mechanics on a classical …

Tensor networks (TNs) have become one of the most essential building blocks for various
fields of theoretical physics such as condensed matter theory, statistical mechanics …

In the last years, a number of theoretical and numerical tools have been developed by a
thriving community formed by people coming from different backgrounds—condensed …

We describe how to efficiently construct the quantum chemical Hamiltonian operator in
matrix product form. We present its implementation as a density matrix renormalization …