This review focuses on the field of quantum entanglement applied to condensed matter
physics systems with strong correlations, a domain which has rapidly grown over the last …

We review the development of generative modeling techniques in machine learning for the
purpose of reconstructing real, noisy, many-qubit quantum states. Motivated by its …

Quantum variational algorithms are one of the most promising applications of near-term
quantum computers; however, recent studies have demonstrated that unless the variational …

Generative modeling, which learns joint probability distribution from data and generates
samples according to it, is an important task in machine learning and artificial intelligence …

We investigate the dynamics of two-dimensional quantum spin systems under the combined
effect of random unitary gates and local projective measurements. When considering steady …

Entanglement is one of the most intriguing features of quantum mechanics. It describes non-
local correlations between quantum objects, and is at the heart of quantum information …

We perform a density-matrix renormalization group (DMRG) study of the S= 1 2 Heisenberg
antiferromagnet on the kagome lattice to identify the conjectured spin liquid ground state …

Topologically ordered phases are gapped states, defined by the properties of excitations
when taken around one another. Here we demonstrate a method to extract the statistics and …

The discussions in § 2 and § 3 make it rather clear that while we have to evaluate a
sequence of functional integrals to compute the Rényi entropies, these are rather complex …

General scaling arguments, and the behavior of the thermal entropy density, are shown to
lead to an infrared metric holographically representing a compressible state with hidden …