Machine learning (ML) has emerged as a formidable force for identifying hidden but
pertinent patterns within a given data set with the objective of subsequent generation of …

Among various algorithms designed to exploit the specific properties of quantum computers
with respect to classical ones, the quantum adiabatic algorithm is a versatile proposition to …

We review different descriptions of many-body quantum systems in terms of tensor product
states. We introduce several families of such states in terms of the known renormalization …

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 …

The relaxation of few-body quantum systems can strongly depend on the initial state when
the system's semiclassical phase space is mixed; ie, regions of chaotic motion coexist with …

This work explores the use of a tree tensor network ansatz to simulate the ground state of a
local Hamiltonian on a two-dimensional lattice. By exploiting the entropic area law, the tree …

Variational quantum algorithms (VQAs) are expected to establish valuable applications on
near-term quantum computers. However, recent works have pointed out that the …

Motivated by the recent synthesis of two insulating Li 2 IrO 3 polymorphs, where Ir 4+ S eff=
1/2 moments form 3D (“harmonic”) honeycomb structures with threefold coordination, we …

We present a generalization of the Time Dependent Variational Principle (TDVP) to any
finite sized loop-free tensor network. The major advantage of TDVP is that it can be …

We study the scaling of the traces of the integer powers of the partially transposed reduced
density matrix $\mathrm {Tr}({\rho} _ {A}^{{T} _ {2}})^{n} $ and of the entanglement negativity …