Tensor networks provide extremely powerful tools for the study of complex classical and
quantum many-body problems. Over the past two decades, the increment in the number of …

Originally developed in the context of condensed-matter physics and based on
renormalization group ideas, tensor networks have been revived thanks to quantum …

Matrix-product states have become the de facto standard for the representation of one-
dimensional quantum many body states. During the last few years, numerous new methods …

Formulating gauge theories on a lattice offers a genuinely non-perturbative way of studying
quantum field theories, and has led to impressive achievements. In particular, it significantly …

We introduce novel algorithmic solutions for hybrid CPU-multiGPU tensor network state
algorithms utilizing non-Abelian symmetries building on AI-motivated state-of-the-art …

Infinite projected entangled pair states (iPEPS) provide a convenient variational description
of infinite, translationally-invariant two-dimensional quantum states. However, the simulation …

The large deviation statistics of dynamical observables is encoded in the spectral properties
of deformed Markov generators. Recent works have shown that tensor network methods are …

In the physics of the fractional quantum Hall (FQH) effect, a zoo of Abelian topological
phases can be obtained by varying the magnetic field. Aiming to reach the same …

Quantum lattice models with large local Hilbert spaces emerge across various fields in
quantum many-body physics. Problems such as the interplay between fermions and …

Infinite projected entangled pair states (iPEPS), the tensor network ansatz for two-
dimensional systems in the thermodynamic limit, already provide excellent results on ground …