Efficient Algorithms for Maximum Likelihood Decoding in the Surface Code
TL;DR: Two implementations of the optimal error correction algorithm known as the maximum likelihood decoder (MLD) for the 2D surface code with a noiseless syndrome extraction are described and a significant reduction of the logical error probability for $\chi\ge 4$.
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Abstract: Two implementations of an error-correction algorithm for topological quantum codes are described, and shown to be promising for fighting decoherence and making quantum computing scalable.
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Interfacing spin qubits in quantum dots and donors—hot, dense, and coherent
Lieven M. K. Vandersypen,Lieven M. K. Vandersypen,Hendrik Bluhm,James S. Clarke,Andrew S. Dzurak,Ryoichi Ishihara,Andrea Morello,David J. Reilly,Lars R. Schreiber,Menno Veldhorst +9 more
TL;DR: In this article, the authors review several strategies that are considered to address this crucial challenge in scaling quantum circuits based on electron spin qubits. But, the wiring and interconnect requirements for quantum circuits are completely different from those for classical circuits, as individual direct current, pulsed and in some cases microwave control signals need to be routed from external sources to every qubit.
Suppressing quantum errors by scaling a surface code logical qubit
23 Feb 2023
TL;DR: In this paper , the authors report the measurement of logical qubit performance scaling across several code sizes, and demonstrate that their system of superconducting qubits has sufficient performance to overcome the additional errors from increasing qubit number.
Suppressing quantum errors by scaling a surface code logical qubit
Rajeev Acharya,Igor L. Aleiner,R. Allen,Trond Andersen,Markus Ansmann,Frank Arute,Kunal Arya,Abraham Asfaw,Juan Atalaya,Ryan Babbush,Dave Bacon,Joseph C. Bardin,João Basso,Andreas Bengtsson,Sergio Boixo,G. Bortoli,Alexandre Bourassa,J. Bovaird,L. Brill,Michael Broughton,Bob B. Buckley,David Bull,Tim Burger,B. Burkett,Nicholas Bushnell,Yu Chen,Zijun Chen,Benjamin Chiaro,J. Zachery Cogan,Roberto Collins,P. N. Conner,William Courtney,Alexander L. Crook,Benjamin M. Curtin,Dripto M. Debroy,A. Barba,Sean Demura,Andrew Dunsworth,Daniel Eppens,Catherine Erickson,Lara Faoro,Edward Farhi,Reza Fatemi,L. F. Burgos,Ebrahim Forati,Austin G. Fowler,Brooks Foxen,W. Giang,Craig Gidney,Dar Gilboa,Marissa Giustina,Alejandro Dau,Jonathan A. Gross,Steve Habegger,Michael C. Hamilton,Matthew P. Harrigan,Sean D. Harrington,Oscar Higgott,Jeremy P. Hilton,Michael J. Hoffmann,Sabrina Hong,Trent Huang,Ashley Huff,William J. Huggins,Lev Ioffe,Sergei V. Isakov,Justin Iveland,Evan Jeffrey,Zhang Jiang,C. Jones,Pavol Juhas,Dvir Kafri,Kostyantyn Kechedzhi,Julian Kelly,T. Khattar,Mostafa Khezri,M. Kieferov'a,Seong-Jin Kim,A. Kitaev,Paul V. Klimov,Andrey Klots,Alexander N. Korotkov,Fedor Kostritsa,John Mark Kreikebaum,David Landhuis,Pavel Laptev,K. Lau,L. Laws,JoonHo Lee,Kenny Lee,Brian Lester,Alexander T. Lill,Wayne Liu,A. Locharla,Erik Lucero,Fionn D. Malone,Jeffrey S. Marshall,Orion Martin,Jarrod R. McClean,Trevor McCourt,Matt McEwen,Anthony Megrant,B. 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,J. Ng,A. Nguyen,Murray L. Nguyen,Murphy Yuezhen Niu,Thomas E. O'Brien,A. Opremcak,J. Platt,Andre Petukhov,Rebecca Potter,Leonid P. Pryadko,Chris Quintana,Pedram Roushan,Nicholas C. Rubin,N Moutab Saei,Daniel Sank,Kannan Aryaperumal Sankaragomathi,Kevin J. Satzinger,Henry F. Schurkus,C. Schuster,Michael Shearn,A. Shorter,Vladimir Shvarts,J. Skruzny,Vadim Smelyanskiy,William Smith,George Sterling,Doug Strain,Yuan Su,M. Szalay,A. Torres,G. Vidal,Benjamin Villalonga,C. V. Heidweiller,Ted White,Chen Xing,Ziyue Yao,Pin-Yi Yeh,Juhwan Yoo,G. Young,Adam Zalcman,Yaxing Zhang,Ningfeng Zhu +157 more
TL;DR: In this article , the authors report the measurement of logical qubit performance scaling across several code sizes, and demonstrate that their system of superconducting qubits has sufficient performance to overcome the additional errors from increasing qubit number.
Ultrahigh Error Threshold for Surface Codes with Biased Noise.
TL;DR: It is shown that a simple modification of the surface code can exhibit an enormous gain in the error correction threshold for a noise model in which Pauli Z errors occur more frequently than X or Y errors, and that large efficiency gains can be found by appropriately tailoring codes and decoders to realistic noise models, even under the locality constraints of topological codes.
Neural Decoder for Topological Codes.
Giacomo Torlai,Roger G. Melko +1 more
TL;DR: The neural decoder is constructed from a stochastic neural network called a Boltzmann machine, of the type extensively used in deep learning, and a decoding strategy that is applicable to a wide variety of stabilizer codes with very little specialization is provided.
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