Nature | Vol 574 | 24 OCTOBER 2019 | 505
Article
Quantum supremacy using a programmable
superconducting processor
Frank Arute
1
, Kunal Arya
1
, Ryan Babbush
1
, Dave Bacon
1
, Joseph C. Bardin
1,2
, Rami Barends
1
,
Rupak Biswas
3
, Sergio Boixo
1
, Fernando G. S. L. Brandao
1,4
, David A. Buell
1
, Brian Burkett
1
,
Yu Chen
1
, Zijun Chen
1
, Ben Chiaro
5
, Roberto Collins
1
, William Courtney
1
, Andrew Dunsworth
1
,
Edward Farhi
1
, Brooks Foxen
1,5
, Austin Fowler
1
, Craig Gidney
1
, Marissa Giustina
1
, Rob Graff
1
,
Keith Guerin
1
, Steve Habegger
1
, Matthew P. Harrigan
1
, Michael J. Hartmann
1,6
, Alan Ho
1
,
Markus Hoffmann
1
, Trent Huang
1
, Travis S. Humble
7
, Sergei V. Isakov
1
, Evan Jeffrey
1
,
Zhang Jiang
1
, Dvir Kafri
1
, Kostyantyn Kechedzhi
1
, Julian Kelly
1
, Paul V. Klimov
1
, Sergey Knysh
1
,
Alexander Korotkov
1,8
, Fedor Kostritsa
1
, David Landhuis
1
, Mike Lindmark
1
, Erik Lucero
1
,
Dmitry Lyakh
9
, Salvatore Mandrà
3,10
, Jarrod R. McClean
1
, Matthew McEwen
5
,
Anthony Megrant
1
, Xiao Mi
1
, Kristel Michielsen
11,12
, Masoud Mohseni
1
, Josh Mutus
1
,
Ofer Naaman
1
, Matthew Neeley
1
, Charles Neill
1
, Murphy Yuezhen Niu
1
, Eric Ostby
1
,
Andre Petukhov
1
, John C. Platt
1
, Chris Quintana
1
, Eleanor G. Rieffel
3
, Pedram Roushan
1
,
Nicholas C. Rubin
1
, Daniel Sank
1
, Kevin J. Satzinger
1
, Vadim Smelyanskiy
1
, Kevin J. Sung
1,13
,
Matthew D. Trevithick
1
, Amit Vainsencher
1
, Benjamin Villalonga
1,14
, Theodore White
1
,
Z. Jamie Yao
1
, Ping Yeh
1
, Adam Zalcman
1
, Hartmut Neven
1
& John M. Martinis
1,5
*
The promise of quantum computers is that certain computational tasks might be
executed exponentially faster on a quantum processor than on a classical processor
1
. A
fundamental challenge is to build a high-delity processor capable of running quantum
algorithms in an exponentially large computational space. Here we report the use of a
processor with programmable superconducting qubits
2–7
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
8–14
for this specic computational task, heralding a much-
anticipated computing paradigm.
In the early 1980s, Richard Feynman proposed that a quantum computer
would be an effective tool with which to solve problems in physics
and chemistry, given that it is exponentially costly to simulate large
quantum systems with classical computers
1
. Realizing Feynman’s vision
poses substantial experimental and theoretical challenges. First, can
a quantum system be engineered to perform a computation in a large
enough computational (Hilbert) space and with a low enough error
rate to provide a quantum speedup? Second, can we formulate a prob-
lem that is hard for a classical computer but easy for a quantum com-
puter? By computing such a benchmark task on our superconducting
qubit processor, we tackle both questions. Our experiment achieves
quantum supremacy, a milestone on the path to full-scale quantum
computing
8–14
.
In reaching this milestone, we show that quantum speedup is achiev-
able in a real-world system and is not precluded by any hidden physical
laws. Quantum supremacy also heralds the era of noisy intermediate-
scale quantum (NISQ) technologies
15
. The benchmark task we demon-
strate has an immediate application in generating certifiable random
numbers (S. Aaronson, manuscript in preparation); other initial uses
for this new computational capability may include optimization
16,17
,
machine learning
18–21
, materials science and chemistry
22–24
. However,
realizing the full promise of quantum computing (using Shor’s algorithm
for factoring, for example) still requires technical leaps to engineer
fault-tolerant logical qubits
25–29
.
To achieve quantum supremacy, we made a number of techni-
cal advances which also pave the way towards error correction. We
https://doi.org/10.1038/s41586-019-1666-5
Received: 22 July 2019
Accepted: 20 September 2019
Published online: 23 October 2019
1
Google AI Quantum, Mountain View, CA, USA.
2
Department of Electrical and Computer Engineering, University of Massachusetts Amherst, Amherst, MA, USA.
3
Quantum Artiicial Intelligence
Laboratory (QuAIL), NASA Ames Research Center, Moffett Field, CA, USA.
4
Institute for Quantum Information and Matter, Caltech, Pasadena, CA, USA.
5
Department of Physics, University of
California, Santa Barbara, CA, USA.
6
Friedrich-Alexander University Erlangen-Nürnberg (FAU), Department of Physics, Erlangen, Germany.
7
Quantum Computing Institute, Oak Ridge National
Laboratory, Oak Ridge, TN, USA.
8
Department of Electrical and Computer Engineering, University of California, Riverside, CA, USA.
9
Scientiic Computing, Oak Ridge Leadership Computing,
Oak Ridge National Laboratory, Oak Ridge, TN, USA.
10
Stinger Ghaffarian Technologies Inc., Greenbelt, MD, USA.
11
Institute for Advanced Simulation, Jülich Supercomputing Centre,
Forschungszentrum Jülich, Jülich, Germany.
12
RWTH Aachen University, Aachen, Germany.
13
Department of Electrical Engineering and Computer Science, University of Michigan, Ann Arbor,
MI, USA.
14
Department of Physics, University of Illinois at Urbana-Champaign, Urbana, IL, USA. *e-mail: jmartinis@google.com