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 …

Quantum Monte Carlo (QMC) is a family of stochastic methods for solving quantum many-
body problems such as the stationary Schrödinger equation. The review introduces basic …

The ab-initio density matrix renormalization group (DMRG) is a tool that can be applied to a
wide variety of interesting problems in quantum chemistry. Here, we examine the density …

In this work, we report, for the first time, an implementation of fermionic auxiliary-field
quantum Monte Carlo (AFQMC) using matrix product state (MPS) trial wavefunctions …

Tensor network states and specifically matrix-product states have proven to be a powerful
tool for simulating ground states of strongly correlated spin models. Recently, they have also …

We explore different ways of incorporating accurate trial wave functions into free projection
auxiliary-field quantum Monte Carlo (fp-AFQMC). States employed include coupled-cluster …

Quantum computing and quantum Monte Carlo (QMC) are respectively the state-of-the-art
quantum and classical computing methods for understanding many-body quantum systems …

We describe a framework to reduce the computational effort to evaluate large deviation
functions of time integrated observables within nonequilibrium steady states. We do this by …

The tensor network algorithm, a family of prevalent numerical methods for quantum many-
body problems, aptly captures the entanglement properties intrinsic to quantum systems …

The accuracy of phaseless auxiliary-field quantum Monte Carlo (ph-AFQMC) can be
systematically improved with better trial states. Using multi-Slater determinant trial states, ph …