CQuIC Seminars
Quantum Approximation Algorithms
Presented by Ojas Parekh (Sandia)
We will explore synergies between classical discrete optimization problems and the Local Hamiltonian problem, a natural quantum generalization of classical constraint satisfaction problems (CSP). We will consider Quantum Max Cut (QMC), a QMA-hard 2-Local Hamiltonian (2-LH) problem. I will explain why QMC has emerged as a testbed for approximating 2-LH in much the same vein that Max Cut is a canonical CSP that has driven development of classical approximation algorithms based on semidefinite programming hierarchies. I will discuss several recent results including an optimal product-state approximation for QMC and prospects for Unique-Games hardness. This talk is aimed at quantum information scientists, computer scientists, and mathematicians and assumes no background in quantum physics.
3:30 pm, Thursday, November 17, 2022
PAIS-2540, PAIS
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