Tensor network is a fundamental mathematical tool with a huge range of applications in
physics, such as condensed matter physics, statistic physics, high energy physics, and …

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 …

The thermal or equilibrium ensemble is one of the most ubiquitous states of matter. For
models comprised of many locally interacting quantum particles, it describes a wide range of …

An infinite projected entangled pair state (iPEPS) is a tensor network ansatz to represent a
quantum state on an infinite 2D lattice whose accuracy is controlled by the bond dimension …

The nature of the 1/9-magnetization plateau of the spin-1 2 kagome Heisenberg
antiferromagnet remains controversial due to the exotic physical properties and high …

An algorithm for imaginary time evolution of a fermionic projected entangled pair state with
ancillas from infinite temperature down to a finite temperature state is presented. As a …

The simple update (SU) and full update (FU) are the two paradigmatic time evolution
algorithms for a tensor network known as the infinite projected entangled pair state (iPEPS) …

The projected entangled pair state (PEPS) ansatz can represent a thermal state in a strongly
correlated system. We introduce a variational algorithm to optimize this tensor network …

It is a hot topic how entanglement, a quantity from quantum information theory, can assist
machine learning. In this work, we implement numerical experiments to classify …

Tensor network algorithms have proven to be very powerful tools for studying one-and two-
dimensional quantum many-body systems. However, their application to three-dimensional …