IDEAS home Printed from https://ideas.repec.org/a/nat/natcom/v7y2016i1d10.1038_ncomms10327.html
   My bibliography  Save this article

Computational multiqubit tunnelling in programmable quantum annealers

Author

Listed:
  • Sergio Boixo

    (Google)

  • Vadim N. Smelyanskiy

    (Google
    NASA Ames Research Center)

  • Alireza Shabani

    (Google)

  • Sergei V. Isakov

    (Google)

  • Mark Dykman

    (Michigan State University)

  • Vasil S. Denchev

    (Google)

  • Mohammad H. Amin

    (D-Wave Systems Inc.
    Simon Fraser University)

  • Anatoly Yu Smirnov

    (D-Wave Systems Inc.)

  • Masoud Mohseni

    (Google)

  • Hartmut Neven

    (Google)

Abstract

Quantum tunnelling is a phenomenon in which a quantum state traverses energy barriers higher than the energy of the state itself. Quantum tunnelling has been hypothesized as an advantageous physical resource for optimization in quantum annealing. However, computational multiqubit tunnelling has not yet been observed, and a theory of co-tunnelling under high- and low-frequency noises is lacking. Here we show that 8-qubit tunnelling plays a computational role in a currently available programmable quantum annealer. We devise a probe for tunnelling, a computational primitive where classical paths are trapped in a false minimum. In support of the design of quantum annealers we develop a nonperturbative theory of open quantum dynamics under realistic noise characteristics. This theory accurately predicts the rate of many-body dissipative quantum tunnelling subject to the polaron effect. Furthermore, we experimentally demonstrate that quantum tunnelling outperforms thermal hopping along classical paths for problems with up to 200 qubits containing the computational primitive.

Suggested Citation

  • Sergio Boixo & Vadim N. Smelyanskiy & Alireza Shabani & Sergei V. Isakov & Mark Dykman & Vasil S. Denchev & Mohammad H. Amin & Anatoly Yu Smirnov & Masoud Mohseni & Hartmut Neven, 2016. "Computational multiqubit tunnelling in programmable quantum annealers," Nature Communications, Nature, vol. 7(1), pages 1-7, April.
    • Handle: RePEc:nat:natcom:v:7:y:2016:i:1:d:10.1038_ncomms10327
    DOI: 10.1038/ncomms10327
    as

    Download full text from publisher

    File URL: https://www.nature.com/articles/ncomms10327
    File Function: Abstract
    Download Restriction: no
    File URL: https://libkey.io/10.1038/ncomms10327?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
    ---><---

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Jaka Vodeb & Michele Diego & Yevhenii Vaskivskyi & Leonard Logaric & Yaroslav Gerasimenko & Viktor Kabanov & Benjamin Lipovsek & Marko Topic & Dragan Mihailovic, 2024. "Non-equilibrium quantum domain reconfiguration dynamics in a two-dimensional electronic crystal and a quantum annealer," Nature Communications, Nature, vol. 15(1), pages 1-7, December.
    2. Jesús Fernández-Villaverde & Isaiah J. Hull, 2023. "Dynamic Programming on a Quantum Annealer: Solving the RBC Model," NBER Working Papers 31326, National Bureau of Economic Research, Inc.
    3. Xunzhao Yin & Yu Qian & Alptekin Vardar & Marcel Günther & Franz Müller & Nellie Laleni & Zijian Zhao & Zhouhang Jiang & Zhiguo Shi & Yiyu Shi & Xiao Gong & Cheng Zhuo & Thomas Kämpfe & Kai Ni, 2024. "Ferroelectric compute-in-memory annealer for combinatorial optimization problems," Nature Communications, Nature, vol. 15(1), pages 1-11, December.
    4. Davide Venturelli & Alexei Kondratyev, 2018. "Reverse Quantum Annealing Approach to Portfolio Optimization Problems," Papers 1810.08584, arXiv.org, revised Oct 2018.

    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:natcom:v:7:y:2016:i:1:d:10.1038_ncomms10327. 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.