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

Classical machine learning (ML) provides a potentially powerful approach to solving
challenging quantum many-body problems in physics and chemistry. However, the …

The rates of several device-independent (DI) protocols, including quantum key-distribution
(QKD) and randomness expansion (RE), can be computed via an optimization of the …

We consider a multi-user multi-server mobile edge computing (MEC) network with time-
varying fading channels and formulate an offloading decision and resource allocation …

It is well-known that any sum of squares (SOS) program can be cast as a semidefinite
program (SDP) of a particular structure and that therein lies the computational bottleneck for …

This article studies the data collection problem in an Internet-of-Things (IoT) network with
multiple unmanned aerial vehicles (UAVs) where UAVs first power multiple IoT devices by …

The goal of quantum key distribution (QKD) is to establish a secure key between two parties
connected by an insecure quantum channel. To use a QKD protocol in practice, one has to …

Predicting observables in equilibrium states is a central yet notoriously hard question in
quantum many-body systems. In the physically relevant thermodynamic limit, certain …

Tunable diode laser absorption spectroscopy (TDLAS) tomography has been widely used
for in situ combustion diagnostics, yielding images of both species concentration and …

Having a distance measure between quantum states satisfying the right properties is of
fundamental importance in all areas of quantum information. In this work, we present a …