ITensor is a system for programming tensor network calculations with an interface modeled
on tensor diagram notation, which allows users to focus on the connectivity of a tensor …

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 …

The successes and limitations of statistical sampling for a sequence of models studied in the
context of lattice QCD are discussed and the need for new methods to deal with finite …

Differentiable programming is a fresh programming paradigm which composes
parameterized algorithmic components and optimizes them using gradient search. The …

In these lecture notes we give a technical overview of tangent-space methods for matrix
product states in the thermodynamic limit. We introduce the manifold of uniform matrix …

Effectively compressing and optimizing tensor networks requires reliable methods for fixing
the latent degrees of freedom of the tensors, known as the gauge. Here we introduce a new …

Tensor-network states (TNS) are a promising but numerically challenging tool for simulating
two-dimensional (2D) quantum many-body problems. We introduce an isometric restriction …

The nature of the zero-temperature phase diagram of the spin-1/2 J 1-J 2 Heisenberg model
on a square lattice has been debated in the past three decades, and it remains one of the …

We show how fermionic statistics can be naturally incorporated in tensor networks on
arbitrary graphs through the use of graded Hilbert spaces. This formalism allows the use 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 …