Security proof methods for quantum key distribution, QKD, that are based on the numerical
key rate calculation problem, are powerful in principle. However, the practicality of the …

Quantum relative entropy programs are convex optimization problems which minimize a
linear functional over an affine section of the epigraph of the quantum relative entropy …

Computing key rates in quantum key distribution (QKD) numerically is essential to unlock
more powerful protocols, that use more sophisticated measurement bases or quantum …

Quantum relative entropy (QRE) programming is a recently popular and challenging class of
convex optimization problems with significant applications in quantum computing and …

Spectral functions on Euclidean Jordan algebras arise frequently in convex optimization
models. Despite the success of primal-dual conic interior point solvers, there has been little …

A convex cone is homogeneous if its automorphism group acts transitively on the interior of
the cone. Cones that are homogeneous and self-dual are called symmetric. Conic …

Abstract Domain-Driven Solver (DDS) is a MATLAB-based software package for convex
optimization. The current version of DDS accepts every combination of the following …

Any convex optimization problem may be represented as a conic problem that minimizes a
linear function over the intersection of an affine subspace with a convex cone. An advantage …

Consider a primitive strongly regular graph H. In this work we establish some properties of
the spectrum of H in the environment of a finite dimensional real Euclidean Jordan algebra …

Conic programs that seek to minimize a linear function over an intersection of symmetric
(self-dual and homogeneous) cones are amenable to highly efficient primal-dual interior …