Speaker: Juexiao Su
Affiliation: Ph.D. Candidate - UCLA
Abstract: As an emerging technology and new computing paradigm, quantum computing has a great potential to solve problems that are theoretically and empirically hard. Among all the existing quantum computation models, quantum annealing has drawn significant attention in recent years due to the realization of the commercialized quantum annealer, sparking research interests in developing applications to solve problems that are intractable for classical computers.
In this study, we focus on solving Boolean satisfiability (SAT) problem using quantum annealer while addressing practical limitations on actual quantum annealer. We propose a mapping technique that maps SAT problem to quadratic unconstrained binary optimization, and we also devise a tool flow that embeds the QUBO onto the actual architecture of the quantum annealing device. Additionally, our tool optimizes the embedding result by shortening the qubit chain size and enlarging the energy gap, leading to robust computation.
Biography: Juexiao Su is currently a Ph.D. candidate in the Department of Electrical and Computer Engineering under the mentorship of Professor Lei He. He received the M.S. degree from UCLA in 2013, and B.S. Degree from Beihang University, Beijing, China in 2011. He worked as an intern in the Synopsys verification group, and information sciences institute, USC.
Date(s) - Mar 07, 2018
11:30 am - 1:30 pm
E-IV Maxwell Room #57-124
420 Westwood Plaza - 5th Flr. , Los Angeles CA 90095