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Surface code error correction offers a highly promising pathway to achieve scalable fault-tolerant quantum computing.
“Stabilizer codes and quantum error correction” (1997)
Daniel Gottesman · 1997
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“Topological quantum memory”
Eric Dennis, Alexei Kitaev, Andrew Landahl, and John Preskill · 2002
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“Fault-tolerant quantum computation with high threshold in two dimensions”
Robert Raussendorf and Jim Harrington · 2007
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“Surface code quantum error correction incorporating accurate error propagation” (2010)
Austin G. Fowler, David S. Wang, and Lloyd C. L. Hollenberg · 2010
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“Fast decoders for topological quantum codes”
Guillaume Duclos-Cianci and David Poulin · 2010
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“Surface code quantum computing with error rates over 1%”
David S. Wang, Austin G. Fowler, and Lloyd C. L. Hollenberg · 2011
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“Towards practical classical processing for the surface code”
Austin G. Fowler, Adam C. Whiteside, and Lloyd C. L. Hollenberg · 2012
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“Strong resilience of topological codes to depolarization”
H. Bombin, Ruben S. Andrist, Masayuki Ohzeki, Helmut G. Katzgraber, and M. A. Martin-Delgado · 2012
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“Surface codes: Towards practical large-scale quantum computation”
Austin G. Fowler, Matteo Mariantoni, John M. Martinis, and Andrew N. Cleland · 2012
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“Optimal complexity correction of correlated errors in the surface code” (2013)
Austin G. Fowler · 2013
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“Fault-tolerant thresholds for quantum error correction with the surface code”
Ashley M. Stephens · 2014
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Austin G. Fowler · 2014
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“Fast fault-tolerant decoder for qubit and qudit surface codes”
Fern H. E. Watson, Hussain Anwar, and Dan E. Browne · 2015
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“A surface code quantum computer in silicon”
Charles D. Hill, Eldad Peretz, Samuel J. Hile, Matthew G. House, Martin Fuechsle, Sven Rogge, Michelle Y. Simmons, and Lloyd C. L. Hollenberg · 2015
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“Surface code architecture for donors and dots in silicon with imprecise and nonuniform qubit couplings”
G. Pica, B. W. Lovett, R. N. Bhatt, T. Schenkel, and S. A. Lyon · 2016
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“Tensorflow: Large-scale machine learning on heterogeneous distributed systems” (2016)
Martín Abadi, Ashish Agarwal, Paul Barham, Eugene Brevdo, Zhifeng Chen, Craig Citro, Greg S. Corrado, Andy Davis, Jeffrey Dean, Matthieu Devin, Sanjay Ghemawat, Ian Goodfellow, Andrew Harp, Geoffrey Irving, Michael Isard, Yangqing Jia, Rafal Jozefowicz, Lukasz Kaiser, Manjunath Kudlur, Josh Levenberg, Dan Mane, Rajat Monga, Sherry Moore, Derek Murray, Chris Olah, Mike Schuster, Jonathon Shlens, Benoit Steiner, Ilya Sutskever, Kunal Talwar, Paul Tucker, Vincent Vanhoucke, Vijay Vasudevan, Fernanda Viegas, Oriol Vinyals, Pete Warden, Martin Wattenberg, Martin Wicke, Yuan Yu, and Xiaoqiang Zheng · 2016
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“Decoding small surface codes with feedforward neural networks”
Savvas Varsamopoulos, Ben Criger, and Koen Bertels · 2017
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“Neural decoder for topological codes”
Giacomo Torlai and Roger G. Melko · 2017
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“Deep neural network probabilistic decoder for stabilizer codes”
Stefan Krastanov and Liang Jiang · 2017
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“Machine-learning-assisted correction of correlated qubit errors in a topological code”
Paul Baireuther, Thomas E. O'Brien, Brian Tarasinski, and Carlo W. J. Beenakker · 2018
Cited alongside, same era.
“Deep neural decoders for near term fault-tolerant experiments”
Christopher Chamberland and Pooya Ronagh · 2018
Cited alongside, same era.
“Machine learning & artificial intelligence in the quantum domain: a review of recent progress”
Vedran Dunjko and Hans J Briegel · 2018
Cited alongside, same era.
“Scalable neural network decoders for higher dimensional quantum codes”
Nikolas P. Breuckmann and Xiaotong Ni · 2018
Cited alongside, same era.
“Quantum chemistry in the age of quantum computing”
Yudong Cao, Jonathan Romero, Jonathan P. Olson, Matthias Degroote, Peter D. Johnson, Mária Kieferová, Ian D. Kivlichan, Tim Menke, Borja Peropadre, Nicolas P. D. Sawaya, Sukin Sim, Libor Veis, and Alán Aspuru-Guzik · 2019
Cited alongside, same era.
“Nisq+: Boosting quantum computing power by approximating quantum error correction”
A. Holmes, M. Jokar, G. Pasandi, Y. Ding, M. Pedram, and F. T. Chong · 2020
Later among the works it cites.
“Engineering long spin coherence times of spin–orbit qubits in silicon”
Takashi Kobayashi, Joseph Salfi, Cassandra Chua, Joost van der Heijden, Matthew G. House, Dimitrie Culcer, Wayne D. Hutchison, Brett C. Johnson, Jeff C. McCallum, Helge Riemann, Nikolay V. Abrosimov, Peter Becker, Hans-Joachim Pohl, Michelle Y. Simmons, and Sven Rogge · 2020
Later among the works it cites.
“Reinforcement learning for optimal error correction of toric codes”
Laia Domingo Colomer, Michalis Skotiniotis, and Ramon Muñoz-Tapia · 2020
Later among the works it cites.
“Neural ensemble decoding for topological quantum error-correcting codes”
Milap Sheth, Sara Zafar Jafarzadeh, and Vlad Gheorghiu · 2020
Later among the works it cites.
“Deep q-learning decoder for depolarizing noise on the toric code”
David Fitzek, Mattias Eliasson, Anton Frisk Kockum, and Mats Granath · 2020
Later among the works it cites.
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Román Orús, Samuel Mugel, and Enrique Lizaso · 2019
Cited alongside, same era.
“A game of surface codes: Large-scale quantum computing with lattice surgery”
Daniel Litinski · 2019
Cited alongside, same era.
“Low overhead quantum computation using lattice surgery” (2019)
Austin G. Fowler and Craig Gidney · 2019
Cited alongside, same era.
“Entanglement stabilization using ancilla-based parity detection and real-time feedback in superconducting circuits”
Christian Kraglund Andersen, Ants Remm, Stefania Lazar, Sebastian Krinner, Johannes Heinsoo, Jean-Claude Besse, Mihai Gabureac, Andreas Wallraff, and Christopher Eichler · 2019
Cited alongside, same era.
“Benchmarking delay and energy of neural inference circuits”
Dmitri E. Nikonov and Ian A. Young · 2019
Cited alongside, same era.
“Quantum error correction for the toric code using deep reinforcement learning”
Philip Andreasson, Joel Johansson, Simon Liljestrand, and Mats Granath · 2019
Cited alongside, same era.
“Advances in quantum cryptography”
S. Pirandola, U. L. Andersen, L. Banchi, M. Berta, D. Bunandar, R. Colbeck, D. Englund, T. Gehring, C. Lupo, C. Ottaviani, J. L. Pereira, M. Razavi, J. Shamsul Shaari, M. Tomamichel, V. C. Usenko, G. Vallone, P. Villoresi, and P. Wallden · 2020
Cited alongside, same era.
“Decoding surface code with a distributed neural network–based decoder”
Savvas Varsamopoulos, Koen Bertels, and Carmen G Almudever · 2020
Later among the works it cites.
“Symmetries for a high-level neural decoder on the toric code”
Thomas Wagner, Hermann Kampermann, and Dagmar Bruß · 2020
Later among the works it cites.
“How to factor 2048 bit RSA integers in 8 hours using 20 million noisy qubits”
Craig Gidney and Martin Ekerå · 2021
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“Even more efficient quantum computations of chemistry through tensor hypercontraction”
Joonho Lee, Dominic W. Berry, Craig Gidney, William J. Huggins, Jarrod R. McClean, Nathan Wiebe, and Ryan Babbush · 2021
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“Exponential suppression of bit or phase errors with cyclic error correction”
Zijun Chen, Kevin J Satzinger, Juan Atalaya, Alexander N Korotkov, Andrew Dunsworth, Daniel Sank, Chris Quintana, Matt McEwen, Rami Barends, Paul V Klimov, et al · 2021
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“Efficient decoding of surface code syndromes for error correction in quantum computing” (2021)
Debasmita Bhoumik, Pinaki Sen, Ritajit Majumdar, Susmita Sur-Kolay, Latesh Kumar K J, and Sundaraja Sitharama Iyengar · 2021
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Oscar Higgott · 2021
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“An exchange-based surface-code quantum computer architecture in silicon” (2021)
Charles D. Hill, Muhammad Usman, and Lloyd C. L. Hollenberg · 2021
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“Almost-linear time decoding algorithm for topological codes”
Nicolas Delfosse and Naomi H. Nickerson · 2021
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“The XZZX surface code”
J. Pablo Bonilla Ataides, David K. Tuckett, Stephen D. Bartlett, Steven T. Flammia, and Benjamin J. Brown · 2021
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“Decoding surface codes with deep reinforcement learning and probabilistic policy reuse” (2022)
Elisha Siddiqui Matekole, Esther Ye, Ramya Iyer, and Samuel Yen-Chi Chen · 2022
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“Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs”
Ramon W. J. Overwater, Masoud Babaie, and Fabio Sebastiano · 2022
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“Scalable neural decoder for topological surface codes”
Kai Meinerz, Chae-Yeun Park, and Simon Trebst · 2022
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