How hard is it to outperform a classical simulator at running a quantum optimization algorithm?

ORAL

Abstract

Platforms for studying variational quantum-classical algorithms (VQAs) with superconducting qubit processors reaching beyond the limits of exascale emulation limits are on the horizon. In this talk, we review recent work on one pattern of VQA, the QAOA ansatz. First, we refine expected boundaries for scaling up noisy simulation with QAOA with tensor networks, limited by entanglement [1]. Still, initial states and final solutions with QAOA typically have low entanglement. We thus clarify the evolution of entanglement during the execution of the algorithm [2]. Next, we report QAOA runs on the recent Aspen-M 80Q platform at Rigetti [1].

*We acknowledge support by the Quantum Science Center (QSC), a National Quantum Information Science Research Center of the U.S. Department of Energy (DOE) and a Simons Investigatorship. This research used the Lawrencium computational cluster resource provided by the IT Division at the Lawrence Berkeley National Laboratory (supported by the Director, Office of Science, Office of Basic Energy Sciences, of the U.S. Department of Energy under Award No. DE-AC02-05CH11231). This research also used resources of the National Energy Research Scientific Computing Center, a DOE Office of Science User Facility supported by the Office of Science of the U.S. Department of Energy under Contract No. DE-AC02-05CH11231 using NERSC Award No. DDR-ERCAP0022242. This research used resources of the Oak Ridge Leadership Computing Facility, which is a DOE Office of Science User Facility supported under Contract DE-AC05-00OR22725. The experimental results presented here are based upon work supported by the Defense Advanced Research Projects Agency (DARPA) under agreement No. HR00112090058.

–

Publication: [1] arXiv:2206.06348
[2] arXiv:2206.07024

Presenters

  • Maxime Dupont

    • Rigetti Computing

Authors

  • Maxime Dupont

    • Rigetti Computing

  • Nicolas Didier

    • Rigetti Computing

  • Mark J Hodson

    • Rigetti Computing Inc
    • Rigetti Computing

  • Joel E Moore

    • Department of Physics, UC Berkeley and Materials Sciences Division, LBNL
    • University of California, Berkeley

  • Matthew J Reagor

    • Rigetti Quantum Computing
    • Rigetti
    • Rigetti Computing