Quantum Device Benchmarking from Many-Body Quantum Chaos

ORAL

Abstract

Here we present a simple and efficient benchmarking protocol to estimate the many-body fidelity between a target state and the actual state obtained from experimental evolution. Our protocol relies only on time evolution of a quantum system undergoing chaotic dynamics, followed by projective measurements in a fixed local basis without any local control; this is in stark contrast to many existing methods which require fine-tuned spatiotemporal control and substantial experimental resources that scale exponentially with system size. Fundamentally, this simplification stems from a universal phenomenon in many-body quantum chaos: the emergence of universal random statistics in a local region. We demonstrate our benchmarking protocol numerically for random unitary circuits, and experimentally using a Rydberg quantum simulator.

*We acknowledge funding provided by the Institute for Quantum Information and Matter, an NSF Physics Frontiers Center (NSF Grant PHY-1733907), the NSF CAREER award (1753386), the AFOSR YIP (FA9550-19-1-0044), the DARPA ONISQ program (W911NF2010021), the Army Research Office MURI program (W911NF2010136), the NSF QLCI program (2016245), and Fred Blum. JC acknowledges support from the IQIM postdoctoral fellowship. ALS acknowledges support from the Eddleman Quantum graduate fellowship. JPC acknowledges support from the PMA Prize postdoctoral fellowship. HP acknowledges support by the Gordon and Betty Moore Foundation. HH is supported by the J. Yang & Family Foundation. AK acknowledges funding from the Harvard Quantum Initiative (HQI) graduate fellowship. JSC is supported by a Junior Fellowship from the Harvard Society of Fellows and the U.S. Department of Energy under grant Contract Number DE-SC0012567. SC acknowledges support from the Miller Institute for Basic Research in Science.

Publication: arXiv:2103.03535; arXiv:2103.03536

Presenters

  • Joonhee Choi

    • Caltech

Authors

  • Joonhee Choi

    • Caltech
  • Adam L Shaw

    • Caltech
  • Ivaylo S Madjarov

    • Caltech
  • Xin Xie

    • Caltech
    • University of Colorado, Boulder
  • Jacob P Covey

    • Caltech
  • Jordan Cotler

    • Harvard
    • Harvard University
  • Daniel Mark

    • MIT
  • Hsin-Yuan Huang

    • Caltech
  • Anant Kale

    • Caltech
    • Harvard University
  • Hannes Pichler

    • Caltech
    • University of Innsbruck
  • Fernando Brandão

    • Caltech
  • Soonwon Choi

    • University of California, Berkeley
  • Manuel Endres

    • Caltech