Semidefinite programs are convex optimization problems involving a linear objective
function and a domain of positive-semidefinite matrices. Over the past two decades, they …

In both classical and quantum many-body physics, it is a core issue to characterize statistical
correlations among different degrees of freedom. From this point of view, a natural question …

We report a proof-of-concept demonstration of a quantum order-finding algorithm for
factoring the integer 21. Our demonstration involves the use of a compiled version of the …

Causality is a seminal concept in science: Any research discipline, from sociology and
medicine to physics and chemistry, aims at understanding the causes that could explain the …

Bell inequalities constitute a key tool in quantum information theory: they not only allow one
to reveal nonlocality in composite quantum systems, but, more importantly, they can be used …

We consider the problem of estimating quantum observables on a collection of qubits, given
as a linear combination of Pauli operators, with shallow quantum circuits consisting of single …

We present a method that allows the study of classical and quantum correlations in networks
with causally independent parties, such as the scenario underlying entanglement swap** …

This paper presents a comprehensive exploration of semi-definite programming (SDP)
techniques within the context of quantum information. It examines the mathematical …

The study of nonlocality in scenarios that depart from the bipartite Einstein-Podolsky-Rosen
setup is allowing one to uncover many fundamental features of quantum mechanics …

Machine learning, the core of artificial intelligence and big data science, is one of today's
most rapidly growing interdisciplinary fields. Recently, machine learning tools and …