Abstract: JPMorgan Chase and Argonne National Laboratory are partners in a long-running collaboration. In this talk, I will survey our recent joint results and discuss opportunities for future collaborations. My talk will cover the recent demonstration of a scaling advantage for the Quantum Approximate Optimization Algorithm, as well as other results in quantum optimization and high-performance computing.

Bio: Ruslan Shaydulin is a quantum algorithms researcher at the Global Technology Applied Research center at JPMorgan Chase. Ruslan’s research centers on applying quantum algorithms to classical problems, with a focus on optimization and machine learning. Prior to joining JPMorgan Chase, Ruslan was a Maria Goeppert Mayer fellow at Argonne National Laboratory.