IDEAS home Printed from https://ideas.repec.org/a/nat/nature/v645y2025i8081d10.1038_s41586-025-09061-4.html
   My bibliography  Save this article

Scaling and logic in the colour code on a superconducting quantum processor

Author

Listed:
  • N. Lacroix

    (Google Research
    ETH Zurich)

  • A. Bourassa

    (Google Research)

  • F. J. H. Heras

    (Google DeepMind)

  • L. M. Zhang

    (Google DeepMind)

  • J. Bausch

    (Google DeepMind)

  • A. W. Senior

    (Google DeepMind)

  • T. Edlich

    (Google DeepMind)

  • N. Shutty

    (Google Research)

  • V. Sivak

    (Google Research)

  • A. Bengtsson

    (Google Research)

  • M. McEwen

    (Google Research)

  • O. Higgott

    (Google Research)

  • D. Kafri

    (Google Research)

  • J. Claes

    (Google Research)

  • A. Morvan

    (Google Research)

  • Z. Chen

    (Google Research)

  • A. Zalcman

    (Google Research)

  • S. Madhuk

    (Google Research)

  • R. Acharya

    (Google Research)

  • L. Aghababaie Beni

    (Google Research)

  • G. Aigeldinger

    (Google Research)

  • R. Alcaraz

    (Google Research)

  • T. I. Andersen

    (Google Research)

  • M. Ansmann

    (Google Research)

  • F. Arute

    (Google Research)

  • K. Arya

    (Google Research)

  • A. Asfaw

    (Google Research)

  • J. Atalaya

    (Google Research)

  • R. Babbush

    (Google Research)

  • B. Ballard

    (Google Research)

  • J. C. Bardin

    (Google Research
    University of Massachusetts)

  • A. Bilmes

    (Google Research)

  • S. Blackwell

    (Google DeepMind)

  • J. Bovaird

    (Google Research)

  • D. Bowers

    (Google Research)

  • L. Brill

    (Google Research)

  • M. Broughton

    (Google Research)

  • D. A. Browne

    (Google Research)

  • B. Buchea

    (Google Research)

  • B. B. Buckley

    (Google Research)

  • T. Burger

    (Google Research)

  • B. Burkett

    (Google Research)

  • N. Bushnell

    (Google Research)

  • A. Cabrera

    (Google Research)

  • J. Campero

    (Google Research)

  • H.-S. Chang

    (Google Research)

  • B. Chiaro

    (Google Research)

  • L.-Y. Chih

    (Google Research)

  • A. Y. Cleland

    (Google Research)

  • J. Cogan

    (Google Research)

  • R. Collins

    (Google Research)

  • P. Conner

    (Google Research)

  • W. Courtney

    (Google Research)

  • A. L. Crook

    (Google Research)

  • B. Curtin

    (Google Research)

  • S. Das

    (Google Research)

  • S. Demura

    (Google Research)

  • L. De Lorenzo

    (Google Research)

  • A. Di Paolo

    (Google Research)

  • P. Donohoe

    (Google Research)

  • I. Drozdov

    (Google Research
    University of Connecticut)

  • A. Dunsworth

    (Google Research)

  • A. Eickbusch

    (Google Research)

  • A. Moshe Elbag

    (Google Research)

  • M. Elzouka

    (Google Research)

  • C. Erickson

    (Google Research)

  • V. S. Ferreira

    (Google Research)

  • L. Flores Burgos

    (Google Research)

  • E. Forati

    (Google Research)

  • A. G. Fowler

    (Google Research)

  • B. Foxen

    (Google Research)

  • S. Ganjam

    (Google Research)

  • G. Garcia

    (Google Research)

  • R. Gasca

    (Google Research)

  • É. Genois

    (Google Research)

  • W. Giang

    (Google Research)

  • D. Gilboa

    (Google Research)

  • R. Gosula

    (Google Research)

  • A. Grajales Dau

    (Google Research)

  • D. Graumann

    (Google Research)

  • A. Greene

    (Google Research)

  • J. A. Gross

    (Google Research)

  • T. Ha

    (Google Research)

  • S. Habegger

    (Google Research)

  • M. Hansen

    (Google Research)

  • M. P. Harrigan

    (Google Research)

  • S. D. Harrington

    (Google Research)

  • S. Heslin

    (Google Research)

  • P. Heu

    (Google Research)

  • R. Hiltermann

    (Google Research)

  • J. Hilton

    (Google Research)

  • S. Hong

    (Google Research)

  • H.-Y. Huang

    (Google Research)

  • A. Huff

    (Google Research)

  • W. J. Huggins

    (Google Research)

  • E. Jeffrey

    (Google Research)

  • Z. Jiang

    (Google Research)

  • X. Jin

    (Google Research)

  • C. Joshi

    (Google Research)

  • P. Juhas

    (Google Research)

  • A. Kabel

    (Google Research)

  • H. Kang

    (Google Research)

  • A. H. Karamlou

    (Google Research)

  • K. Kechedzhi

    (Google Research)

  • T. Khaire

    (Google Research)

  • T. Khattar

    (Google Research)

  • M. Khezri

    (Google Research)

  • S. Kim

    (Google Research)

  • P. V. Klimov

    (Google Research)

  • B. Kobrin

    (Google Research)

  • A. N. Korotkov

    (Google Research)

  • F. Kostritsa

    (Google Research)

  • J. Mark Kreikebaum

    (Google Research)

  • V. D. Kurilovich

    (Google Research)

  • D. Landhuis

    (Google Research)

  • T. Lange-Dei

    (Google Research)

  • B. W. Langley

    (Google Research)

  • P. Laptev

    (Google Research)

  • K.-M. Lau

    (Google Research)

  • J. Ledford

    (Google Research)

  • K. Lee

    (Google Research)

  • B. J. Lester

    (Google Research)

  • L. Le Guevel

    (Google Research)

  • W. Yan Li

    (Google Research)

  • Y. Li

    (Google DeepMind)

  • A. T. Lill

    (Google Research)

  • W. P. Livingston

    (Google Research)

  • A. Locharla

    (Google Research)

  • E. Lucero

    (Google Research)

  • D. Lundahl

    (Google Research)

  • A. Lunt

    (Google Research)

  • A. Maloney

    (Google Research)

  • S. Mandrà

    (Google Research)

  • L. S. Martin

    (Google Research)

  • O. Martin

    (Google Research)

  • C. Maxfield

    (Google Research)

  • J. R. McClean

    (Google Research)

  • S. Meeks

    (Google Research)

  • A. Megrant

    (Google Research)

  • K. C. Miao

    (Google Research)

  • R. Molavi

    (Google Research)

  • S. Molina

    (Google Research)

  • S. Montazeri

    (Google Research)

  • R. Movassagh

    (Google Research)

  • C. Neill

    (Google Research)

  • M. Newman

    (Google Research)

  • A. Nguyen

    (Google Research)

  • M. Nguyen

    (Google Research)

  • C.-H. Ni

    (Google Research)

  • M. Y. Niu

    (Google Research
    University of California)

  • L. Oas

    (Google Research)

  • W. D. Oliver

    (Google Research
    Massachusetts Institute of Technology
    Massachusetts Institute of Technology
    Massachusetts Institute of Technology)

  • R. Orosco

    (Google Research)

  • K. Ottosson

    (Google Research)

  • A. Pizzuto

    (Google Research)

  • R. Potter

    (Google Research)

  • O. Pritchard

    (Google Research)

  • C. Quintana

    (Google Research)

  • G. Ramachandran

    (Google Research)

  • M. J. Reagor

    (Google Research)

  • R. Resnick

    (Google Research)

  • D. M. Rhodes

    (Google Research)

  • G. Roberts

    (Google Research)

  • E. Rosenberg

    (Google Research)

  • E. Rosenfeld

    (Google Research)

  • E. Rossi

    (Google Research)

  • P. Roushan

    (Google Research)

  • K. Sankaragomathi

    (Google Research)

  • H. F. Schurkus

    (Google Research)

  • M. J. Shearn

    (Google Research)

  • A. Shorter

    (Google Research)

  • V. Shvarts

    (Google Research)

  • S. Small

    (Google Research)

  • W. Clarke Smith

    (Google Research)

  • S. Springer

    (Google Research)

  • G. Sterling

    (Google Research)

  • J. Suchard

    (Google Research)

  • A. Szasz

    (Google Research)

  • A. Sztein

    (Google Research)

  • D. Thor

    (Google Research)

  • E. Tomita

    (Google Research)

  • A. Torres

    (Google Research)

  • M. Mert Torunbalci

    (Google Research)

  • A. Vaishnav

    (Google Research)

  • J. Vargas

    (Google Research)

  • S. Vdovichev

    (Google Research)

  • G. Vidal

    (Google Research)

  • C. Vollgraff Heidweiller

    (Google Research)

  • S. Waltman

    (Google Research)

  • J. Waltz

    (Google Research)

  • S. X. Wang

    (Google Research)

  • B. Ware

    (Google Research)

  • T. Weidel

    (Google Research)

  • T. White

    (Google Research)

  • K. Wong

    (Google Research)

  • B. W. K. Woo

    (Google Research)

  • M. Woodson

    (Google Research)

  • C. Xing

    (Google Research)

  • Z. Jamie Yao

    (Google Research)

  • P. Yeh

    (Google Research)

  • B. Ying

    (Google Research)

  • J. Yoo

    (Google Research)

  • N. Yosri

    (Google Research)

  • G. Young

    (Google Research)

  • Y. Zhang

    (Google Research)

  • N. Zhu

    (Google Research)

  • N. Zobrist

    (Google Research)

  • H. Neven

    (Google Research)

  • P. Kohli

    (Google DeepMind)

  • A. Davies

    (Google DeepMind)

  • S. Boixo

    (Google Research)

  • J. Kelly

    (Google Research)

  • C. Jones

    (Google Research)

  • C. Gidney

    (Google Research)

  • K. J. Satzinger

    (Google Research)

Abstract

Quantum error correction1–4 is essential for bridging the gap between the error rates of physical devices and the extremely low error rates required for quantum algorithms. Recent error-correction demonstrations on superconducting processors5–8 have focused primarily on the surface code9, which offers a high error threshold but poses limitations for logical operations. The colour code10 enables more efficient logic, but it requires more complex stabilizer measurements and decoding. Measuring these stabilizers in planar architectures such as superconducting qubits is challenging, and realizations of colour codes11–19 have not addressed performance scaling with code size on any platform. Here we present a comprehensive demonstration of the colour code on a superconducting processor8. Scaling the code distance from three to five suppresses logical errors by a factor of Λ3/5 = 1.56(4). Simulations indicate this performance is below the threshold of the colour code, and the colour code may become more efficient than the surface code following modest device improvements. We test transversal Clifford gates with logical randomized benchmarking20 and inject magic states21, a key resource for universal computation, achieving fidelities exceeding 99% with post-selection. Finally, we teleport logical states between colour codes using lattice surgery22. This work establishes the colour code as a compelling research direction to realize fault-tolerant quantum computation on superconducting processors in the near future.

Suggested Citation

  • N. Lacroix & A. Bourassa & F. J. H. Heras & L. M. Zhang & J. Bausch & A. W. Senior & T. Edlich & N. Shutty & V. Sivak & A. Bengtsson & M. McEwen & O. Higgott & D. Kafri & J. Claes & A. Morvan & Z. Che, 2025. "Scaling and logic in the colour code on a superconducting quantum processor," Nature, Nature, vol. 645(8081), pages 614-619, September.
  • Handle: RePEc:nat:nature:v:645:y:2025:i:8081:d:10.1038_s41586-025-09061-4
    DOI: 10.1038/s41586-025-09061-4
    as

    Download full text from publisher

    File URL: https://www.nature.com/articles/s41586-025-09061-4
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1038/s41586-025-09061-4?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to

    for a different version of it.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:nat:nature:v:645:y:2025:i:8081:d:10.1038_s41586-025-09061-4. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.nature.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.