Quantum Supremacy using a Programmable Superconducting Processor
Frank Arute
Kunal Arya
Rami Barends
Rupak Biswas
Fernando Brandao
David Buell
Yu Chen
Jimmy Chen
Ben Chiaro
Roberto Collins
William Courtney
Andrew Dunsworth
Edward Farhi
Brooks Foxen
Austin Fowler
Rob Graff
Keith Guerin
Steve Habegger
Michael Hartmann
Alan Ho
Markus Rudolf Hoffmann
Trent Huang
Travis Humble
Sergei Isakov
Kostyantyn Kechedzhi
Sergey Knysh
Alexander Korotkov
Fedor Kostritsa
Dave Landhuis
Mike Lindmark
Dmitry Lyakh
Salvatore Mandrà
Anthony Megrant
Xiao Mi
Kristel Michielsen
Masoud Mohseni
Josh Mutus
Charles Neill
Eric Ostby
Andre Petukhov
Eleanor G. Rieffel
Vadim Smelyanskiy
Kevin Jeffery Sung
Matt Trevithick
Amit Vainsencher
Benjamin Villalonga
Z. Jamie Yao
Ping Yeh
John Martinis
Nature, 574 (2019), 505–510
Abstract
The promise of quantum computers is that certain computational tasks might be executed exponentially faster on a quantum processor than on a classical processor. 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 qubits to create quantum states on 53 qubits, corresponding to a computational state-space of dimension 2^53 (about 10^16). 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 supremacy for this specific computational task, heralding a much-anticipated computing paradigm.
Research Areas
Meet the teams driving innovation
Our teams advance the state of the art through research, systems engineering, and collaboration across Google.
See our teams