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Quantum supremacy using a programmable superconducting processor

Author

Listed:
  • Frank Arute

    (Google AI Quantum)

  • Kunal Arya

    (Google AI Quantum)

  • Ryan Babbush

    (Google AI Quantum)

  • Dave Bacon

    (Google AI Quantum)

  • Joseph C. Bardin

    (Google AI Quantum
    University of Massachusetts Amherst)

  • Rami Barends

    (Google AI Quantum)

  • Rupak Biswas

    (NASA Ames Research Center)

  • Sergio Boixo

    (Google AI Quantum)

  • Fernando G. S. L. Brandao

    (Google AI Quantum
    Institute for Quantum Information and Matter, Caltech)

  • David A. Buell

    (Google AI Quantum)

  • Brian Burkett

    (Google AI Quantum)

  • Yu Chen

    (Google AI Quantum)

  • Zijun Chen

    (Google AI Quantum)

  • Ben Chiaro

    (University of California)

  • Roberto Collins

    (Google AI Quantum)

  • William Courtney

    (Google AI Quantum)

  • Andrew Dunsworth

    (Google AI Quantum)

  • Edward Farhi

    (Google AI Quantum)

  • Brooks Foxen

    (Google AI Quantum
    University of California)

  • Austin Fowler

    (Google AI Quantum)

  • Craig Gidney

    (Google AI Quantum)

  • Marissa Giustina

    (Google AI Quantum)

  • Rob Graff

    (Google AI Quantum)

  • Keith Guerin

    (Google AI Quantum)

  • Steve Habegger

    (Google AI Quantum)

  • Matthew P. Harrigan

    (Google AI Quantum)

  • Michael J. Hartmann

    (Google AI Quantum
    Department of Physics)

  • Alan Ho

    (Google AI Quantum)

  • Markus Hoffmann

    (Google AI Quantum)

  • Trent Huang

    (Google AI Quantum)

  • Travis S. Humble

    (Oak Ridge National Laboratory)

  • Sergei V. Isakov

    (Google AI Quantum)

  • Evan Jeffrey

    (Google AI Quantum)

  • Zhang Jiang

    (Google AI Quantum)

  • Dvir Kafri

    (Google AI Quantum)

  • Kostyantyn Kechedzhi

    (Google AI Quantum)

  • Julian Kelly

    (Google AI Quantum)

  • Paul V. Klimov

    (Google AI Quantum)

  • Sergey Knysh

    (Google AI Quantum)

  • Alexander Korotkov

    (Google AI Quantum
    University of California)

  • Fedor Kostritsa

    (Google AI Quantum)

  • David Landhuis

    (Google AI Quantum)

  • Mike Lindmark

    (Google AI Quantum)

  • Erik Lucero

    (Google AI Quantum)

  • Dmitry Lyakh

    (Oak Ridge National Laboratory)

  • Salvatore Mandrà

    (NASA Ames Research Center
    Stinger Ghaffarian Technologies Inc.)

  • Jarrod R. McClean

    (Google AI Quantum)

  • Matthew McEwen

    (University of California)

  • Anthony Megrant

    (Google AI Quantum)

  • Xiao Mi

    (Google AI Quantum)

  • Kristel Michielsen

    (Jülich Supercomputing Centre, Forschungszentrum Jülich
    RWTH Aachen University)

  • Masoud Mohseni

    (Google AI Quantum)

  • Josh Mutus

    (Google AI Quantum)

  • Ofer Naaman

    (Google AI Quantum)

  • Matthew Neeley

    (Google AI Quantum)

  • Charles Neill

    (Google AI Quantum)

  • Murphy Yuezhen Niu

    (Google AI Quantum)

  • Eric Ostby

    (Google AI Quantum)

  • Andre Petukhov

    (Google AI Quantum)

  • John C. Platt

    (Google AI Quantum)

  • Chris Quintana

    (Google AI Quantum)

  • Eleanor G. Rieffel

    (NASA Ames Research Center)

  • Pedram Roushan

    (Google AI Quantum)

  • Nicholas C. Rubin

    (Google AI Quantum)

  • Daniel Sank

    (Google AI Quantum)

  • Kevin J. Satzinger

    (Google AI Quantum)

  • Vadim Smelyanskiy

    (Google AI Quantum)

  • Kevin J. Sung

    (Google AI Quantum
    University of Michigan)

  • Matthew D. Trevithick

    (Google AI Quantum)

  • Amit Vainsencher

    (Google AI Quantum)

  • Benjamin Villalonga

    (Google AI Quantum
    University of Illinois at Urbana-Champaign)

  • Theodore White

    (Google AI Quantum)

  • Z. Jamie Yao

    (Google AI Quantum)

  • Ping Yeh

    (Google AI Quantum)

  • Adam Zalcman

    (Google AI Quantum)

  • Hartmut Neven

    (Google AI Quantum)

  • John M. Martinis

    (Google AI Quantum
    University of California)

Abstract

The promise of quantum computers is that certain computational tasks might be executed exponentially faster on a quantum processor than on a classical processor1. A fundamental challenge is to build a high-fidelity processor capable of running quantum algorithms in an exponentially large computational space. Here we report the use of a processor with programmable superconducting qubits2–7 to create quantum states on 53 qubits, corresponding to a computational state-space of dimension 253 (about 1016). Measurements from repeated experiments sample the resulting probability distribution, which we verify using classical simulations. Our Sycamore processor takes about 200 seconds to sample one instance of a quantum circuit a million times—our benchmarks currently indicate that the equivalent task for a state-of-the-art classical supercomputer would take approximately 10,000 years. This dramatic increase in speed compared to all known classical algorithms is an experimental realization of quantum supremacy8–14 for this specific computational task, heralding a much-anticipated computing paradigm.

Suggested Citation

  • Frank Arute & Kunal Arya & Ryan Babbush & Dave Bacon & Joseph C. Bardin & Rami Barends & Rupak Biswas & Sergio Boixo & Fernando G. S. L. Brandao & David A. Buell & Brian Burkett & Yu Chen & Zijun Chen, 2019. "Quantum supremacy using a programmable superconducting processor," Nature, Nature, vol. 574(7779), pages 505-510, October.
  • Handle: RePEc:nat:nature:v:574:y:2019:i:7779:d:10.1038_s41586-019-1666-5
    DOI: 10.1038/s41586-019-1666-5
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