Title
Quantum Relative Entropy Optimization
Abstract
Quantum relative entropies are jointly convex functions of two positive definite matrices that generalize the Kullback-Leibler divergence and arise naturally in quantum information theory. The convexity of these matrix functions rely on deep theorems in mathematical physics, most notably Lieb’s concavity theorem. In this talk I will discuss algorithmic strategies to solve convex optimization involving quantum relative entropies, and applications in quantum information theory.
Speaker Biography
Hamza Fawzi is a professor of applied mathematics at the University of Cambridge. He received his PhD from MIT in 2016. His main research interests are in convex optimization and more specifically semidefinite programming, with applications in physics and engineering. He has received the SIAM activity group in optimization best paper award in 2020 jointly with James Saunderson and Pablo Parrilo.