Introduction to quantum error correction with stabilizer codes
Open accessThe claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Many important QEC codes can be described using the stabilizer formalism, including the Shor code, the Steane code, the five-qubit code, CSS codes, and surface code-type constructions.
“Many of the most important QEC codes can be described this way, including the Shor code, the Steane code, the five-qubit code, CSS codes, and surface code-type constructions.”
From Quantum error correction and fault tolerance: A comprehensive tutorial (2026) · cites this paper as [95]
The Introduction (p. 3) explicitly says the Shor code can be viewed as a stabilizer code; §4.4 (p. 46) constructs the five-qubit code using stabilizer generators, and §5 (p. 56) connects topological codes, including toric and planar constructions, to stabilizer codes. The passages found do not establish the claim’s additional examples of the Steane code and CSS codes. (LLM, conf=0.86)
Experimental — accuracy not yet measured
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
Part of this paper’s reference list could not be split into single entries.
Quantum Computing in the NISQ era and beyond
Preskill, J. (2018) · Quantum · doi:10.22331/q-2018-08-06-79 · Cited by 8,830 · see citing works
Variational quantum algorithms
Cerezo, M., Arrasmith, A., Babbush, R., Benjamin, S. C., Endo, S., Fujii, K., McClean, J. R., Mitarai, K., Yuan, X., Cincio, L., et al. (2021) · Nature Reviews Physics · doi:10.1038/s42254-021-00348-9 · Cited by 3,385 · see citing works
Quantum computations: algorithms and error correction
Kitaev, A. Y. (1997) · Russian Mathematical Surveys · doi:10.1070/rm1997v052n06abeh002155 · Cited by 1,424 · see citing works
An introduction to quantum machine learning
Schuld, M., Sinayskiy, I., & Petruccione, F. (2015) · Contemporary Physics · doi:10.1080/00107514.2014.964942 · Cited by 1,381 · see citing works
Quantum error correction for quantum memories
Terhal, B. M. (2015) · Reviews of Modern Physics · doi:10.1103/revmodphys.87.307 · Cited by 1,354 · see citing works
Circuit-centric quantum classifiers
Schuld, M., Bocharov, A., Svore, K. M., & Wiebe, N. (2020) · Physical Review A · doi:10.1103/physreva.101.032308 · Cited by 1,057 · see citing works
Goals and opportunities in quantum simulation
Cirac, J. I., & Zoller, P. (2012) · Nature Physics · doi:10.1038/nphys2275 · Cited by 891 · see citing works
Buluta, I., & Nori, F. (2009) · Science · doi:10.1126/science.1177838 · Cited by 876 · see citing works
Efficient Quantum Algorithms for Simulating Sparse Hamiltonians
Berry, D. W., Ahokas, G., Cleve, R., & Sanders, B. C. (2007) · Communications in Mathematical Physics · doi:10.1007/s00220-006-0150-x · Cited by 692 · see citing works
Realizing repeated quantum error correction in a distance-three surface code
Krinner, S., Lacroix, N., Remm, A., Di Paolo, A., Genois, E., Leroux, C., Hellings, C., Lazar, S., Swiadek, F., Herrmann, J., et al. (2022) · Nature · doi:10.1038/s41586-022-04566-8 · Cited by 686 · see citing works
Fault-tolerant quantum computation with constant error
Aharonov, D., & Ben-Or, M. (1997) · Proceedings of the twenty-ninth annual ACM symposium on Theory of computing - STOC '97 · doi:10.1145/258533.258579 · Cited by 631 · see citing works
Surface code quantum computing by lattice surgery
Horsman, D., Fowler, A. G., Devitt, S., & Meter, R. V. (2012) · New Journal of Physics · doi:10.1088/1367-2630/14/12/123011 · Cited by 598 · see citing works
High-threshold universal quantum computation on the surface code
Fowler, A. G., Stephens, A. M., & Groszkowski, P. (2009) · Physical Review A · doi:10.1103/physreva.80.052312 · Cited by 486 · see citing works
Potential of quantum computing for drug discovery
Cao, Y., Romero, J., & Aspuru-Guzik, A. (2018) · IBM Journal of Research and Development · doi:10.1147/jrd.2018.2888987 · Cited by 357 · see citing works
Quantum error correction beyond qubits
Aoki, T., Takahashi, G., Kajiya, T., Yoshikawa, J.-I., Braunstein, S. L., van Loock, P., & Furusawa, A. (2009) · Nature Physics · doi:10.1038/nphys1309 · Cited by 144 · see citing works
Learning high-accuracy error decoding for quantum processors
Bausch, J., Senior, A. W., Heras, F. J. H., Edlich, T., Davies, A., Newman, M., Jones, C., Satzinger, K., Niu, M. Y., Blackwell, S., et al. (2024) · Nature · doi:10.1038/s41586-024-08148-8 · Cited by 106 · see citing works
Flagged first, then by citations
Research works printed but not linked: 104
- [1][1] Michael A Nielsen and Isaac L Chuang. Quantum computation and quantum information . Cambridge university press, 2010. 1, 2.1, 2.2 -
- [5][5] Andrew J Daley, Immanuel Bloch, Christian Kokail, Stuart Flannigan, Natalie Pearson, Matthias Troyer, and Peter Zoller. Practical quantum advantage in quantum simulation. Nature , 607(7920):667676, 2022. 1 -
- [6][6] Richard P. Feynman. Simulating physics with computers. International Journal of Theoretical Physics , 21(6-7):467-488, June 1982. 1 -
- [7][7] Iulia M Georgescu, Sahel Ashhab, and Franco Nori. Quantum simulation. Reviews of Modern Physics , 86(1):153-185, 2014. 1 -
- [9][9] Benedict Leimkuhler and Sebastian Reich. Simulating hamiltonian dynamics . Number 14 in Cambridge Monographs on Applied and Computational Mathematics. Cambridge university press, 2004. 1 -
- [10][10] Seth Lloyd. Universal quantum simulators. Science , 273(5278):1073-1078, 1996. 1 -
- [12][12] Andreas Trabesinger. Quantum simulation. Nature Physics , 8(4):263-263, 2012. 1 -
- [13][13] Ryan Babbush, Nathan Wiebe, Jarrod McClean, James McClain, Hartmut Neven, and Garnet Kin-Lic Chan. Low-depth quantum simulation of materials. Physical Review X , 8(1):011044, 2018. 1 -
- [15][15] Laura Clinton, Toby Cubitt, Brian Flynn, Filippo Maria Gambetta, Joel Klassen, Ashley Montanaro, Stephen Piddock, Raul A Santos, and Evan Sheridan. Towards near-term quantum simulation of materials. Nature Communications , 15(1):211, 2024. 1 -
- [16][16] Gautam Kumar, Sahil Yadav, Aniruddha Mukherjee, Vikas Hassija, and Mohsen Guizani. Recent advances in quantum computing for drug discovery and development. IEEE Access , 2024. 1 -
- [17][17] AE Azzaoui, Tae Woo Kim, Yi Pan, and Jong Hyuk Park. A quantum approximate optimization algorithm based on blockchain heuristic approach for scalable and secure smart logistics systems. Human-centric Computing and Information Sciences , 11(46):1-12, 2021. 1 -
- [18][18] Andreas Bayerstadler, Guillaume Becquin, Julia Binder, Thierry Botter, Hans Ehm, Thomas Ehmer, Marvin Erdmann, Norbert Gaus, Philipp Harbach, Maximilian Hess, et al. Industry quantum computing applications. EPJ Quantum Technology , 8(1):25, 2021. 1 -
- [19][19] Daniel J Egger, Claudio Gambella, Jakub Marecek, Scott McFaddin, Martin Mevissen, Rudy Raymond, Andrea Simonetto, Stefan Woerner, and Elena Yndurain. Quantum computing for finance: State-ofthe-art and future prospects. IEEE Transactions on Quantum Engineering , 1:1-24, 2020. 1 -
- [20][20] Dylan Herman, Cody Googin, Xiaoyuan Liu, Yue Sun, Alexey Galda, Ilya Safro, Marco Pistoia, and Yuri Alexeev. Quantum computing for finance. Nature Reviews Physics , 5(8):450-465, 2023. 1 -
- [22][22] Alejandro Perdomo-Ortiz, Alexander Feldman, Asier Ozaeta, Sergei V Isakov, Zheng Zhu, Bryan O'Gorman, Helmut G Katzgraber, Alexander Diedrich, Hartmut Neven, Johan de Kleer, et al. Readiness of quantum optimization machines for industrial applications. Physical Review Applied , 12(1):014004, 2019. 1 -
- [23][23] Sean J Weinberg, Fabio Sanches, Takanori Ide, Kazumitzu Kamiya, and Randall Correll. Supply chain logistics with quantum and classical annealing algorithms. Scientific Reports , 13(1):4770, 2023. 1 -
- [24][24] Kostas Blekos, Dean Brand, Andrea Ceschini, Chiao-Hui Chou, Rui-Hao Li, Komal Pandya, and Alessandro Summer. A review on quantum approximate optimization algorithm and its variants. Physics Reports , 1068:1-66, 2024. 1 -
- [25][25] Edward Farhi, Jeffrey Goldstone, and Sam Gutmann. A quantum approximate optimization algorithm. arXiv preprint arXiv:1411.4028 , 2014. 1 - · arXiv
- [26][26] Leo Zhou, Sheng-Tao Wang, Soonwon Choi, Hannes Pichler, and Mikhail D Lukin. Quantum approximate optimization algorithm: Performance, mechanism, and implementation on near-term devices. Physical Review X , 10(2):021067, 2020. 1 -
- [27][27] Jacob Biamonte, Peter Wittek, Nicola Pancotti, Patrick Rebentrost, Nathan Wiebe, and Seth Lloyd. Quantum machine learning. Nature , 549(7671):195-202, 2017. 1 -
- [28][28] Marco Cerezo, Guillaume Verdon, Hsin-Yuan Huang, Lukasz Cincio, and Patrick J Coles. Challenges and opportunities in quantum machine learning. Nature computational science , 2(9):567-576, 2022. 1 -
- [31][31] Samuel Yen-Chi Chen, Chao-Han Huck Yang, Jun Qi, Pin-Yu Chen, Xiaoli Ma, and Hsi-Sheng Goan. Variational quantum circuits for deep reinforcement learning. IEEE access , 8:141007-141024, 2020. 1 -
- [33][33] Riccardo Di Sipio, Jia-Hong Huang, Samuel Yen-Chi Chen, Stefano Mangini, and Marcel Worring. The dawn of quantum natural language processing. In ICASSP 2022-2022 IEEE international conference on acoustics, speech and signal processing (ICASSP) , pages 8612-8616. IEEE, 2022. 1 -
- [34][34] Ethan N Evans, Matthew Cook, Zachary P Bradshaw, and Margarite L LaBorde. Learning with sasquatch: a novel variational quantum transformer architecture with kernel-based self-attention. arXiv preprint arXiv:2403.14753 , 2024. 1 - · arXiv
- [36][36] Guangxi Li, Xuanqiang Zhao, and Xin Wang. Quantum self-attention neural networks for text classification. Science China Information Sciences , 67(4):142501, 2024. 1 -
- [37][37] Simon J Devitt, William J Munro, and Kae Nemoto. Quantum error correction for beginners. Reports on Progress in Physics , 76(7):076001, 2013. 1 -
- [38][38] Daniel Gottesman. An introduction to quantum error correction. In Proceedings of Symposia in Applied Mathematics , volume 58, pages 221-236, 2002. 1 -
- [39][39] Emanuel Knill and Raymond Laflamme. Theory of quantum error-correcting codes. Physical Review A , 55(2):900, 1997. 1 -
- [40][40] Daniel A Lidar and Todd A Brun. Quantum error correction . Cambridge university press, 2013. 1 -
- [41][41] Joschka Roffe. Quantum error correction: an introductory guide. Contemporary Physics , 60(3):226245, 2019. 1 -
- [42][42] Andrew Cross, Ali Javadi-Abhari, Thomas Alexander, Niel De Beaudrap, Lev S Bishop, Steven Heidel, Colm A Ryan, Prasahnt Sivarajah, John Smolin, Jay M Gambetta, et al. Openqasm 3: A broader and deeper quantum assembly language. ACM Transactions on Quantum Computing , 3(3):1-50, 2022. 1 -
- [47][47] Ville Bergholm, Josh Izaac, Maria Schuld, Christian Gogolin, Shahnawaz Ahmed, Vishnu Ajith, M Sohaib Alam, Guillermo Alonso-Linaje, B AkashNarayanan, Ali Asadi, et al. Pennylane: Automatic differentiation of hybrid quantum-classical computations. arXiv preprint arXiv:1811.04968 , 2018. 1 - · arXiv
- [49][49] Charles H Bennett, David P DiVincenzo, John A Smolin, and William K Wootters. Mixed-state entanglement and quantum error correction. Physical Review A , 54(5):3824, 1996. 1 -
- [50][50] A Robert Calderbank and Peter W Shor. Good quantum error-correcting codes exist. Physical Review A , 54(2):1098, 1996. 1, 3 -
- [51][51] Raymond Laflamme, Cesar Miquel, Juan Pablo Paz, and Wojciech Hubert Zurek. Perfect quantum error correcting code. Physical Review Letters , 77(1):198, 1996. 1 -
- [52][52] Andrew M Steane. Error correcting codes in quantum theory. Physical Review Letters , 77(5):793, 1996. 1 -
- [53][53] Peter W Shor. Scheme for reducing decoherence in quantum computer memory. Physical review A , 52(4):R2493, 1995. 1, 3.7 -
- [54][54] Daniel Gottesman. Theory of fault-tolerant quantum computation. Physical Review A , 57(1):127, 1998. 1, 4.6 -
- [55][55] A.Yu. Kitaev. Fault-tolerant quantum computation by anyons. Annals of Physics , 303(1):2-30, January 2003. 1 -
- [56][56] Eric Dennis, Alexei Kitaev, Andrew Landahl, and John Preskill. Topological quantum memory. Journal of Mathematical Physics , 43(9):4452-4505, September 2002. 1, 5.5, 6 -
- [57][57] Austin G. Fowler, Matteo Mariantoni, John M. Martinis, and Andrew N. Cleland. Surface codes: Towards practical large-scale quantum computation. Physical Review A , 86(3), September 2012. 1, 5.5 -
- [58][58] Robert Raussendorf and Jim Harrington. Fault-tolerant quantum computation with high threshold in two dimensions. Physical Review Letters , 98(19), May 2007. 1 -
- [61][61] Ramamurti Shankar. Principles of quantum mechanics . Springer Science & Business Media, 2012. 2.1 -
- [63][63] Samuel L Braunstein. Error correction for continuous quantum variables. Physical Review Letters , 80(18):4084, 1998. 2.1 -
- [64][64] Seth Lloyd and Jean-Jacques E Slotine. Analog quantum error correction. Physical Review Letters , 80(18):4088, 1998. 2.1 -
- [65][65] Brian C Hall. Quantum Theory for Mathematicians . Springer, 2013. 2.1 -
- [66][66] Hilbrand Johannes Groenewold and Hilbrand Johannes Groenewold. On the principles of elementary quantum mechanics . Springer, 1946. 2.1 -
- [70][70] Walther Gerlach and Otto Stern. Der experimentelle nachweis der richtungsquantelung im magnetfeld. Walther Gerlach (1889-1979) Eine Auswahl aus seinen Schriften und Briefen , pages 26-29, 1989. 2.1 -
- [71][71] Jun John Sakurai and Jim Napolitano. Modern quantum mechanics . Cambridge University Press, 2020. 2.1 -
- [72][72] Llu´ ıs Masanes, Thomas D Galley, and Markus P M¨ uller. The measurement postulates of quantum mechanics are operationally redundant. Nature communications , 10(1):1361, 2019. 2.1 -
- [73][73] Adrian Kent. The measurement postulates of quantum mechanics are not redundant. arXiv preprint arXiv:2307.06191 , 2023. 2.1 - · arXiv
- [76][76] Hugh Everett. 'Relative State' Formulation of Quantum Mechanics. Reviews of Modern Physics , 29(3):454-462, July 1957. 2.1 -
- [77][77] D.Z. Albert. Quantum Mechanics and Experience . Emersion: Emergent Village Resources for Communities of Faith Series. Harvard University Press, 1994. 2.1 -
- [78][78] Harvey R. Brown and David Wallace. Solving the measurement problem: De broglie-bohm loses out to everett. Foundations of Physics , 35(4):517-540, April 2005. 2.1 -
- [79][79] T. Maudlin. Quantum Non-Locality and Relativity: Metaphysical Intimations of Modern Physics . Wiley, 2011. 2.1 -
- [80][80] Hrvoje Nikoli´ c. Relativistic quantum mechanics and the bohmian interpretation. Foundations of Physics Letters , 18(6):549-561, November 2005. 2.1 -
- [81][81] Simon Saunders, Jonathan Barrett, Adrian Kent, and David Wallace. Many Worlds?: Everett, Quantum Theory, and Reality . Oxford University Press, 06 2010. 2.1 -
- [82][82] Phillip Kaye, Raymond Laflamme, and Michele Mosca. An introduction to quantum computing . OUP Oxford, 2006. 2.2 -
- [83][83] Richard Jozsa and. Fidelity for mixed quantum states. Journal of Modern Optics , 41(12):2315-2323, 1994. 2.3 -
- [84][84] A. Uhlmann. The 'transition probability' in the state space of a *-algebra. Reports on Mathematical Physics , 9(2):273-279, 1976. 2.3 -
- [86][86] Zachary P. Bradshaw, Margarite L. LaBorde, and Mark M. Wilde. Cycle index polynomials and generalized quantum separability tests. Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences , 479(2274), June 2023. 2.3 -
- [87][87] Adriano Barenco, Andr´ e Berthiaume, David Deutsch, Artur Ekert, Richard Jozsa, and Chiara Macchiavello. Stabilization of quantum computations by symmetrization. SIAM Journal on Computing , 26(5):1541-1557, 1997. 2.3 -
- [88][88] Andrew Steane. Multiple-Particle Interference and Quantum Error Correction. Proceedings of the Royal Society of London Series A , 452(1954):2551-2577, November 1996. 3 -
- [89][89] C.E. Shannon and W. Weaver. The Mathematical Theory of Communication . University of Illinois Press, 1962. 3.1 -
- [90][90] Irving S Reed and Gustave Solomon. Polynomial codes over certain finite fields. Journal of the society for industrial and applied mathematics , 8(2):300-304, 1960. 3.1 -
- [91][91] R. W. Hamming. Error detecting and error correcting codes. The Bell System Technical Journal , 29(2):147-160, 1950. 3.2 -
- [93][93] M. J. E. Golay. Notes on digital coding. Proceedings of the IRE , 37:657, 1949. 3.2 -
- [94][94] M. Golay. Complementary series. IRE Transactions on Information Theory , 7(2):82-87, 1961. 3.2 -
- [97][97] David S. Dummit and Richard M. Foote. Abstract Algebra . Wiley, 3rd edition, 2004. 4 -
- [98][98] B. Steinberg. Representation Theory of Finite Groups: An Introductory Approach . Universitext. Springer New York, 2011. 4.2 -
- [99][99] S. Roman. Advanced Linear Algebra . Graduate Texts in Mathematics. Springer New York, 2007. 4.5 -
- [100][100] H. Weyl. The Classical Groups: Their Invariants and Representations . Number no. 1, pt. 1 in Princeton Landmarks in Mathematics and Physics. Princeton University Press, 1946. 4.5 -
- [101][101] Pavithran Iyer and David Poulin. Hardness of decoding quantum stabilizer codes. IEEE Transactions on Information Theory , 61(9):5209-5223, 2015. 4.6 -
- [103][103] Stefan Krastanov and Liang Jiang. Deep neural network probabilistic decoder for stabilizer codes. Scientific reports , 7(1):11003, 2017. 4.6, 6.2 -
- [104][104] Giacomo Torlai and Roger G Melko. Neural decoder for topological codes. Physical review letters , 119(3):030501, 2017. 4.6 -
- [105][105] Savvas Varsamopoulos, Ben Criger, and Koen Bertels. Decoding small surface codes with feedforward neural networks. Quantum Science and Technology , 3(1):015004, November 2017. 4.6, 5.5, 6.2, 6.3 -
- [108][108] Emanuel Knill, Raymond Laflamme, and Wojciech H Zurek. Resilient quantum computation: error models and thresholds. Proceedings of the Royal Society of London. Series A: Mathematical, Physical and Engineering Sciences , 454(1969):365-384, 1998. 4.6 -
- [109][109] Emanuel Knill, Raymond Laflamme, and Wojciech H Zurek. Resilient quantum computation. Science , 279(5349):342-345, 1998. 4.6 -
- [110][110] John Preskill. Reliable quantum computers. Proceedings of the Royal Society of London. Series A: Mathematical, Physical and Engineering Sciences , 454(1969):385-410, 1998. 4.6 -
- [111][111] A. Hatcher. Algebraic Topology . Algebraic Topology. Cambridge University Press, 2002. 5, 5.1 -
- [112][112] K. Fujii. Quantum Computation with Topological Codes: From Qubit to Topological Fault-Tolerance . SpringerBriefs in Mathematical Physics. Springer Nature Singapore, 2015. 5 -
- [116][116] Earl T. Campbell, Barbara M. Terhal, and Christophe Vuillot. Roads towards fault-tolerant universal quantum computation. Nature , 549(7671):172-179, September 2017. 5.5 -
- [117][117] H Bombin and M A Martin-Delgado. Quantum measurements and gates by code deformation. Journal of Physics A: Mathematical and Theoretical , 42(9):095302, February 2009. 5.5 -
- [119][119] Jack Edmonds. Paths, trees, and flowers. Canadian Journal of Mathematics , 17:449-467, 1965. 5.5, 6 -
- [123][123] Guillaume Duclos-Cianci and David Poulin. Fast decoders for topological quantum codes. Physical Review Letters , 104(5), February 2010. 5.5, 6 -
- [124][124] Savvas Varsamopoulos, Koen Bertels, and Carmen Garcia Almudever. Comparing neural network based decoders for the surface code. IEEE Transactions on Computers , 69(2):300-311, February 2020. 5.5, 6.3 -
- [131][131] Savvas Varsamopoulos, Koen Bertels, and Carmen G. Almudever. Decoding surface code with a distributed neural network-based decoder. Quantum Machine Intelligence , 2(1):3, Mar 2020. 6, 6.3 -
- [132][132] Ryan Sweke, Markus S Kesselring, Evert P L van Nieuwenburg, and Jens Eisert. Reinforcement learning decoders for fault-tolerant quantum computation. Machine Learning: Science and Technology , 2(2):025005, December 2020. 6 -
- [134][134] Laia Domingo Colomer, Michalis Skotiniotis, and Ramon Mu˜ noz-Tapia. Reinforcement learning for optimal error correction of toric codes. Physics Letters A , 384(17):126353, June 2020. 6 -
- [135][135] Christopher M. Bishop. Pattern Recognition and Machine Learning . Springer, 2006. 6.1 -
- [136][136] Kevin P. Murphy. Machine Learning: A Probabilistic Perspective . MIT press, 2012. 6.1 -
- [137][137] L´ eon Bottou. Large-scale machine learning with stochastic gradient descent. In Proceedings of COMPSTAT'2010 , pages 177-186. Springer, 2010. 6.1 -
- [138][138] Kurt Hornik, Maxwell Stinchcombe, and Halbert White. Multilayer feedforward networks are universal approximators. Neural Networks , 2(5):359-366, 1989. 6.1 -
- [139][139] Ian Goodfellow, Yoshua Bengio, and Aaron Courville. Deep Learning . MIT Press, 2016. 6.1 -
- [140][140] Y. Lecun, L. Bottou, Y. Bengio, and P. Haffner. Gradient-based learning applied to document recognition. Proceedings of the IEEE , 86(11):2278-2324, 1998. 6.1, 6.1 -
- [141][141] Jeffrey L. Elman. Finding structure in time. Cognitive Science , 14(2):179-211, 1990. 6.1 -
- [142][142] Y. Bengio, P. Simard, and P. Frasconi. Learning long-term dependencies with gradient descent is difficult. IEEE Transactions on Neural Networks , 5(2):157-166, 1994. 6.1 -
- [143][143] Sepp Hochreiter and J¨ urgen Schmidhuber. Long short-term memory. Neural Comput. , 9(8):1735-1780, November 1997. 6.1, 6.3 -
- [146][146] Anmol Gulati, James Qin, Chung-Cheng Chiu, Niki Parmar, Yu Zhang, Jiahui Yu, Wei Han, Shibo Wang, Zhengdong Zhang, Yonghui Wu, et al. Conformer: Convolution-augmented transformer for speech recognition. In Proceedings of Interspeech , 2020. 6.1 -
- [147][147] Razvan Pascanu, Tomas Mikolov, and Yoshua Bengio. On the difficulty of training recurrent neural networks. In Sanjoy Dasgupta and David McAllester, editors, Proceedings of the 30th International Conference on Machine Learning , volume 28 of Proceedings of Machine Learning Research , pages 1310-1318, Atlanta, Georgia, USA, 17-19 Jun 2013. PMLR. 6.3 -
- [148][148] Xavier Glorot and Yoshua Bengio. Understanding the difficulty of training deep feedforward neural networks. In Yee Whye Teh and Mike Titterington, editors, Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics , volume 9 of Proceedings of Machine Learning Research , pages 249-256, Chia Laguna Resort, Sardinia, Italy, 13-15 May 2010. PMLR. 6.3 -
- [150][150] Natalie C. Brown, Andrew Cross, and Kenneth R. Brown. Critical faults of leakage errors on the surface code. In 2020 IEEE International Conference on Quantum Computing and Engineering (QCE) , pages 286-294, 2020. 6.4 -
- [152][152] Christopher Chamberland and Pooya Ronagh. Deep neural decoders for near term fault-tolerant experiments. Quantum Science and Technology , 3(4):044002, July 2018. 6.5 -
- [154][154] M. Schuld and F. Petruccione. Machine Learning with Quantum Computers . Quantum Science and Technology. Springer International Publishing, 2021. 6.5 -
Cited by
Sorted by citations
Quantum error correction and fault tolerance: A comprehensive tutorial
Spencer, D. J., Jain, S. P., Tanggara, A., Sun, Z., Haug, T., Khu, D., & Bharti, K. (2026) · arXiv
- Authors
- Bradshaw, Z. P., Dale, J. J., & Evans, E. N.
- Corresponding author
- Bradshaw, Zachary P.
- Venue
- Annals of Physics
- Publisher
- Elsevier BV
- Published
- 2026-04
- Volume
- 487
- Pages
- 170353
- ISSN
- 0003-4916 (ISSN-L)
- OpenAlex
- W4416283374
- Cited by
- 4
- References
- 16
- Citations by year
- 2026: 3 · 2025: 1
- FWCI
- 6.89
- Type
- journal article
- Language
- en
- Open access
- green
- arxiv.org
- Licence
- www.elsevier.com/tdm/userlicense/1.0/ (tdm)
- www.elsevier.com/legal/tdmrep-license (tdm)
- www.elsevier.com/open-access/userlicense/1.0/ (am, 304 d)
- doi.org/10.15223/policy-017 (stm-asf)
- doi.org/10.15223/policy-037 (stm-asf)
- doi.org/10.15223/policy-012 (stm-asf)
- doi.org/10.15223/policy-029 (stm-asf)
- doi.org/10.15223/policy-004 (stm-asf)
- Locations
- Annals of Physics (publishedVersion)
- arXiv (Cornell University) (submittedVersion)
- arXiv (Cornell University)
- Funders
- Naval Surface Warfare Center
- Office of Naval Research (N0001425GI00778)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Quantum Computing Algorithms and Architecture
- Physical Sciences › Computer Science › Artificial Intelligence › Quantum Information and Cryptography
- Physical Sciences › Computer Science › Artificial Intelligence › Coding theory and cryptography
- Keywords
- quantum error correction, stabilizer codes, quantum computing, topological codes, homological algebra, neural network decoding, OpenQASM, quantum error-correcting codes
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review