Survey on Computational Applications of Tensor-Network Simulations

Abstract

Tensor networks are a popular and computationally efficient approach to simulate general quantum systems on classical computers and, in a broader sense, a framework for dealing with high-dimensional numerical problems. This paper presents a broad but not exhaustive literature review of state-of-the-art applications of tensor networks and related topics across many research domains, including: machine learning, mathematical optimization, materials science, quantum chemistry and quantum circuit simulation. This review aims to clarify which classes of relevant applications have been proposed for which class of tensor networks, as well as to highlight main application results and limitations compared with other classical or quantum simulation methods. We intend this review to be a high-level tour on tensor network applications that is easy to read by non-experts, so basic technical details of tensor networks are summarized.