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arxiv: 2207.06431 · v2 · pith:4SPZIJRKnew · submitted 2022-07-13 · 🪐 quant-ph

Suppressing quantum errors by scaling a surface code logical qubit

Rajeev Acharya , Igor Aleiner , Richard Allen , Trond I. Andersen , Markus Ansmann , Frank Arute , Kunal Arya , Abraham Asfaw
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Juan Atalaya Ryan Babbush Dave Bacon Joseph C. Bardin Joao Basso Andreas Bengtsson Sergio Boixo Gina Bortoli Alexandre Bourassa Jenna Bovaird Leon Brill Michael Broughton Bob B. Buckley David A. Buell Tim Burger Brian Burkett Nicholas Bushnell Yu Chen Zijun Chen Ben Chiaro Josh Cogan Roberto Collins Paul Conner William Courtney Alexander L. Crook Ben Curtin Dripto M. Debroy Alexander Del Toro Barba Sean Demura Andrew Dunsworth Daniel Eppens Catherine Erickson Lara Faoro Edward Farhi Reza Fatemi Leslie Flores Burgos Ebrahim Forati Austin G. Fowler Brooks Foxen William Giang Craig Gidney Dar Gilboa Marissa Giustina Alejandro Grajales Dau Jonathan A. Gross Steve Habegger Michael C. Hamilton Matthew P. Harrigan Sean D. Harrington Oscar Higgott Jeremy Hilton Markus Hoffmann Sabrina Hong Trent Huang Ashley Huff William J. Huggins Lev B. Ioffe Sergei V. Isakov Justin Iveland Evan Jeffrey Zhang Jiang Cody Jones Pavol Juhas Dvir Kafri Kostyantyn Kechedzhi Julian Kelly Tanuj Khattar Mostafa Khezri M\'aria Kieferov\'a Seon Kim Alexei Kitaev Paul V. Klimov Andrey R. Klots Alexander N. Korotkov Fedor Kostritsa John Mark Kreikebaum David Landhuis Pavel Laptev Kim-Ming Lau Lily Laws Joonho Lee Kenny Lee Brian J. Lester Alexander Lill Wayne Liu Aditya Locharla Erik Lucero Fionn D. Malone Jeffrey Marshall Orion Martin Jarrod R. McClean Trevor Mccourt Matt McEwen Anthony Megrant Bernardo Meurer Costa Xiao Mi Kevin C. Miao Masoud Mohseni Shirin Montazeri Alexis Morvan Emily Mount Wojciech Mruczkiewicz Ofer Naaman Matthew Neeley Charles Neill Ani Nersisyan Hartmut Neven Michael Newman Jiun How Ng Anthony Nguyen Murray Nguyen Murphy Yuezhen Niu Thomas E. O'Brien Alex Opremcak John Platt Andre Petukhov Rebecca Potter Leonid P. Pryadko Chris Quintana Pedram Roushan Nicholas C. Rubin Negar Saei Daniel Sank Kannan Sankaragomathi Kevin J. Satzinger Henry F. Schurkus Christopher Schuster Michael J. Shearn Aaron Shorter Vladimir Shvarts Jindra Skruzny Vadim Smelyanskiy W. Clarke Smith George Sterling Doug Strain Marco Szalay Alfredo Torres Guifre Vidal Benjamin Villalonga Catherine Vollgraff Heidweiller Theodore White Cheng Xing Z. Jamie Yao Ping Yeh Juhwan Yoo Grayson Young Adam Zalcman Yaxing Zhang Ningfeng Zhu
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classification 🪐 quant-ph
keywords errorlogicalqubitscodequbiterrorsincreasingnumber
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Practical quantum computing will require error rates that are well below what is achievable with physical qubits. Quantum error correction offers a path to algorithmically-relevant error rates by encoding logical qubits within many physical qubits, where increasing the number of physical qubits enhances protection against physical errors. However, introducing more qubits also increases the number of error sources, so the density of errors must be sufficiently low in order for logical performance to improve with increasing code size. Here, we report the measurement of logical qubit performance scaling across multiple code sizes, and demonstrate that our system of superconducting qubits has sufficient performance to overcome the additional errors from increasing qubit number. We find our distance-5 surface code logical qubit modestly outperforms an ensemble of distance-3 logical qubits on average, both in terms of logical error probability over 25 cycles and logical error per cycle ($2.914\%\pm 0.016\%$ compared to $3.028\%\pm 0.023\%$). To investigate damaging, low-probability error sources, we run a distance-25 repetition code and observe a $1.7\times10^{-6}$ logical error per round floor set by a single high-energy event ($1.6\times10^{-7}$ when excluding this event). We are able to accurately model our experiment, and from this model we can extract error budgets that highlight the biggest challenges for future systems. These results mark the first experimental demonstration where quantum error correction begins to improve performance with increasing qubit number, illuminating the path to reaching the logical error rates required for computation.

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