Algorithms, complexity, and quantum many-body physics

Par

Cunlu Zhou

University of New Mexico

mercredi 28 février 2024, 10:30-11:30 EST, Salle 3195

Pavillon André-Aisenstadt, Université de Montréal, 2920 Chemin de la Tour

Abstract: In this talk, I will discuss three results about algorithms, complexity, and quantum many-body physics. The first one is about the so-called Hamiltonian Variational Ansatz, which is used in Variational Quantum Algorithms (VQAs) for approximating the ground states of condensed matter physics models. The second one is about a Quantum Phase Estimation (QPE) algorithm based on compressed sensing that is suitable for early fault-tolerant quantum computers. The last one is about an SU(2) symmetric semidefinite programming (SDP) hierarchy for the so-called Quantum MaxCut problem, which connects the Heisenberg model in condensed matter physics with optimization algorithms and fundamental computational complexity questions such as the so-called Quantum PCP Conjecture. The talk is going to be rather high level, and no special background in quantum computation or theoretical computer science is assumed.

Bio: Dr. Zhou is currently an FRHTP Postdoctoral Fellow at the Center for Quantum Information and Control at the University of New Mexico. He completed his PhD in Mathematics in 2019 at the University of Notre Dame under the supervision of Roxana Smarandache and Leonid Faybusovich. Following his graduation, he undertook a postdoctoral position with Henry Yuen in the Department of Computer Science at the University of Toronto. His research interests lie at the interdisciplinary crossroads of optimization, machine learning, quantum computing, and quantum many-body physics.