Deep Learning Seminar
Friday, November 3 1:00 – 2:00pm Curia II (WH2SW)
Hybrid classical/quantum algorithms for Fermion simulation and approximate combinatorial optimization
Nicholas C. Rubin
Rigetti Computing
Hybrid classical/quantum algorithms have the characteristic of utilizing both classical and quantum computational resources to facilitate a computational advantage. This class of algorithms are likely candidates for near-term quantum computers because of their natural robustness to incoherent noise sources. In this talk we will introduce the general paradigm of hybrid classical quantum algorithms and two prominent applications: finding extremal eigenvalues of chemical systems and approximate solutions to combinatorial optimization problems. For each application the circuit ansatz, problem encoding, and optimal sampling bounds are presented in the context of the solution quality being returned by the algorithm. Finally, we demonstrate the implementation details of these algorithms using a programming model and software stack that targets near-term quantum computers.
contact: perdue@fnal.gov
chat on slack: hepmachinelearning.slack.com
