AQC 2016 - Boosting Quantum Annealer Performance via Quantum Persistence

A Google TechTalk, June 29, 2016, presented by Gili Rosenberg (1QBit) ABSTRACT: We propose a novel method for reducing the number of variables in quadratic unconstrained binary optimization problems, using a quantum annealer to fix the state of a large portion of the variables to values with a high probability of being optimal. The method significantly increases the success rate when compared with calling the quantum annealer without using it. The results can be further enhanced by applying the method iteratively or combining it with classical pre-processing. We present results for both Chimera graph-structured problems and embedded problems from real-world applications. Hamed Karimi, 1QB Information Technologies (1QBit) Presented at the Adiabatic Quantum Computing Conference, June 26-29, 2016, at Google's Los Angeles office.