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arxiv: 2510.19928 · v2 · pith:CBPHLAHTnew · submitted 2025-10-22 · 🪐 quant-ph · cond-mat.other

Mind the gaps: The fraught road to quantum advantage

Pith reviewed 2026-05-18 01:46 UTC · model grok-4.3

classification 🪐 quant-ph cond-mat.other
keywords quantum computingNISQfault toleranceerror correctionquantum algorithmsquantum simulationquantum advantage
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The pith

Four hurdles must be cleared to advance from noisy quantum devices to practical fault-tolerant ones.

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The paper identifies four major hurdles separating current noisy intermediate-scale quantum devices from future fault-tolerant application-scale quantum machines. These include moving from error mitigation to active error detection and correction, advancing to scalable fault tolerance, developing mature verifiable algorithms from early heuristics, and achieving credible advantages in quantum simulation rather than exploratory work. By targeting these transitions specifically, the authors suggest that progress toward broadly useful quantum computing can be accelerated, which matters because it provides a roadmap to make quantum computers solve problems that are out of reach for classical systems.

Core claim

Quantum computing is advancing rapidly, yet substantial gaps separate today's noisy intermediate-scale quantum (NISQ) devices from tomorrow's fault-tolerant application-scale quantum (FASQ) machines. The central discovery is the identification of four related hurdles: from error mitigation to active error detection and correction, from rudimentary error correction to scalable fault tolerance, from early heuristics to mature verifiable algorithms, and from exploratory simulators to credible advantage in quantum simulation. Targeting these will accelerate progress toward broadly useful quantum computing.

What carries the argument

The four related hurdles that structure the path from noisy intermediate-scale quantum devices to fault-tolerant application-scale quantum machines.

If this is right

  • Efforts should shift from error mitigation to active detection and correction to enable reliable operations.
  • Research must scale rudimentary error correction up to full fault tolerance for larger systems.
  • Algorithm development should move beyond early heuristics toward mature and verifiable methods.
  • Quantum simulations must transition from exploratory work to showing credible advantages over classical approaches.

Where Pith is reading between the lines

These are editorial extensions of the paper, not claims the author makes directly.

  • Successfully addressing these hurdles could enable quantum simulations of molecular systems that remain intractable for classical computers.
  • This framing of the challenges may help align research priorities and resource allocation across different teams.
  • Additional issues around software ecosystems or hardware scaling could surface once these four areas are resolved.

Load-bearing premise

The four listed hurdles are the primary barriers separating current devices from future machines, and that addressing them in sequence will accelerate progress to useful quantum computing.

What would settle it

A demonstration of broad quantum advantage in a practical task that bypasses one or more of the four transitions, such as achieving it with only error mitigation and no active correction.

read the original abstract

Quantum computing is advancing rapidly, yet substantial gaps separate today's noisy intermediate-scale quantum (NISQ) devices from tomorrow's fault-tolerant application-scale quantum (FASQ) machines. We identify four related hurdles along the road ahead: (i) from error mitigation to active error detection and correction, (ii) from rudimentary error correction to scalable fault tolerance, (iii) from early heuristics to mature, verifiable algorithms, and (iv) from exploratory simulators to credible advantage in quantum simulation. Targeting these transitions will accelerate progress toward broadly useful quantum computing.

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, simulated authors' rebuttal, and a circularity audit. Tearing a paper down is the easy half of reading it; the pith above is the substance, this is the friction.

Referee Report

0 major / 1 minor

Summary. The manuscript is a perspective article that identifies four key transitions required to bridge the gap between current noisy intermediate-scale quantum (NISQ) devices and future fault-tolerant application-scale quantum (FASQ) machines. These are: (i) shifting from error mitigation to active error detection and correction, (ii) advancing from rudimentary error correction to scalable fault tolerance, (iii) moving from early heuristics to mature and verifiable algorithms, and (iv) progressing from exploratory simulators to achieving credible advantage in quantum simulation. The paper concludes that focusing on these areas will accelerate the development of broadly useful quantum computing.

Significance. The paper synthesizes current understanding of the limitations in quantum hardware and algorithms to provide a structured roadmap. Its significance lies in offering a clear classification of challenges that could help direct research efforts in the quantum computing field. As it relies on established domain knowledge rather than new empirical or theoretical results, its value is in the perspective it offers rather than in novel findings.

minor comments (1)
  1. The abstract could briefly note the intended readership (e.g., experimentalists vs. theorists) to sharpen the framing of the four hurdles.

Simulated Author's Rebuttal

0 responses · 0 unresolved

We thank the referee for their positive review and for recommending acceptance of the manuscript. The referee's summary accurately reflects the structure and intent of our perspective article on the four transitions from NISQ to FASQ devices.

Circularity Check

0 steps flagged

No significant circularity; perspective piece without derivation chain

full rationale

This is an expert perspective article that enumerates four high-level transitions (error mitigation to detection/correction; rudimentary correction to scalable fault tolerance; heuristics to verifiable algorithms; exploratory to credible simulation advantage) and recommends targeting them to accelerate progress. No equations, quantitative predictions, fitted parameters, or load-bearing self-citations appear in the provided text. The central claim is a domain-consensus recommendation rather than a falsifiable derivation that reduces to its own inputs by construction.

Axiom & Free-Parameter Ledger

0 free parameters · 1 axioms · 0 invented entities

The paper rests on standard domain knowledge in quantum error correction and NISQ limitations without introducing new free parameters, axioms beyond established physics, or invented entities.

axioms (1)
  • domain assumption NISQ devices suffer from noise levels that preclude direct fault-tolerant operation at scale
    Invoked in the opening contrast between NISQ and FASQ regimes.

pith-pipeline@v0.9.0 · 5606 in / 1117 out tokens · 28114 ms · 2026-05-18T01:46:48.930546+00:00 · methodology

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Forward citations

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Reference graph

Works this paper leans on

217 extracted references · 217 canonical work pages · cited by 16 Pith papers · 12 internal anchors

  1. [1]

    strongly correlated

    proposed that a machine that computes quantum properties of many strongly interacting particles should be a quantum machine rather than a conventional computer. Dirac’s claim that many-electron problems are too hard to solve (classically) is in some respects misleading. Heuristic classical algorithms for this problem, such as density functional theory [17...

  2. [2]

    R. P. Feynman, Simulating physics with computers, Int. J. Th. Phys.21, 467 (1982)

  3. [3]

    R. P. Feynman, Quantum mechanical computers, Found. Phys. 16, 507 (1986)

  4. [4]

    Deutsch, Quantum theory, the Church-Turing principle and the universal quantum computer, Proc

    D. Deutsch, Quantum theory, the Church-Turing principle and the universal quantum computer, Proc. Roy. Soc. A400, 97 (1985)

  5. [5]

    P. W. Shor, Algorithms for quantum computation: discrete logarithms and factoring, Proc. 50th Ann. Symp. Found. Comp. Sc. , 124 (1994)

  6. [6]

    Preskill, Quantum computing in the NISQ era and beyond, Quantum2, 79 (2018)

    J. Preskill, Quantum computing in the NISQ era and beyond, Quantum2, 79 (2018)

  7. [7]

    Morvan, B

    A. Morvan, B. Villalonga, X. Mi, S. Mandrà, A. Bengtsson, P. Klimov, Z. Chen, S. Hong, C. Erickson, I. Drozdov,et al., Phase transitions in random circuit sampling, Nature634, 328 (2024)

  8. [8]

    P. W. Shor, Scheme for reducing decoherence in quantum com- puter memory, Phys. Rev. A52, R2493 (1995)

  9. [9]

    P. W. Shor, Fault-tolerant quantum computation, inProceedings of 37th conference on foundations of computer science(IEEE,

  10. [10]

    J. Lee, D. W. Berry, C. Gidney, W. J. Huggins, J. R. McClean, N. Wiebe, and R. Babbush, Even more efficient quantum com- putations of chemistry through tensor hypercontraction, PRX Quantum2, 030305 (2021)

  11. [11]

    How to factor 2048 bit RSA integers with less than a million noisy qubits

    C. Gidney, How to factor 2048 bit RSA integers with less than a million noisy qubits, (2025), arXiv:2505.15917

  12. [12]

    Bacon, Software of QIP, by QIP, and for QIP (2022), keynote presentation at QIP 2022

    D. Bacon, Software of QIP, by QIP, and for QIP (2022), keynote presentation at QIP 2022

  13. [13]

    Preskill, Beyond NISQ: The megaquop machine, ACM Trans

    J. Preskill, Beyond NISQ: The megaquop machine, ACM Trans. Quant. Comp.6, 1 (2025)

  14. [15]

    King, Quantum algorithms: A call to action (2025)

    R. King, Quantum algorithms: A call to action (2025)

  15. [16]

    Aaronson, A

    S. Aaronson, A. M. Childs, E. Farhi, A. W. Harrow, and B. C. Sanders, Future of quantum computing, (2025), arXiv:2506.19232

  16. [17]

    A framework for quantum advantage,

    O. Lanes, M. Beji, A. D. Corcoles, C. Dalyac, J. M. Gam- betta, L. Henriet, A. Javadi-Abhari, A. Kandala, A. Mezzacapo, C. Porter,et al., A framework for quantum advantage, (2025), arXiv:2506.20658

  17. [18]

    Huang, S

    H.-Y . Huang, S. Choi, J. R. McClean, and J. Preskill, The vast world of quantum advantage, (2025), arXiv:2508.05720

  18. [19]

    Kapit, P

    E. Kapit, P. Love, J. Larson, A. Sornborger, E. Crane, A. Schuckert, T. Tomesh, F. Chong, and S. Kais, Roadblocks and opportunities in quantum algorithms – insights from the National Quantum Initiative Joint Algorithms Workshop, May 20-22, 2024, (2025), arXiv:2508.13973

  19. [20]

    A. M. Dalzell, S. McArdle, M. Berta, P. Bienias, C.-F. Chen, A. Gilyén, C. T. Hann, M. J. Kastoryano, E. T. Khabiboulline, A. Kubica,et al., Quantum algorithms: A survey of applications and end-to-end complexities, (2023), arXiv:2310.03011

  20. [21]

    Haeffner, C

    H. Haeffner, C. F. Roos, and R. Blatt, Quantum computing with trapped ions, Phys. Rep.469, 155 (2008)

  21. [22]

    J.-S. Chen, E. Nielsen, M. Ebert, V . Inlek, K. Wright, V . Chap- lin, A. Maksymov, E. Páez, A. Poudel, P. Maunz, and J. Gamble, Benchmarking a trapped-ion quantum computer with 30 qubits, Quantum8, 1516 (2024)

  22. [23]

    DeCrosset al., Computational power of random quan- tum circuits in arbitrary geometries, Phys

    M. DeCrosset al., Computational power of random quan- tum circuits in arbitrary geometries, Phys. Rev. X15, 021052 (2025)

  23. [24]

    Quantum error correction below the su rface-code threshold

    R. Acharyaet al., Quantum error correction below the surface code threshold, (2024), arxiv:2408.13687

  24. [25]

    Castelvecchi, IBM releases first-ever 1,000-qubit quantum chip, Nature624, 238 (2023)

    D. Castelvecchi, IBM releases first-ever 1,000-qubit quantum chip, Nature624, 238 (2023)

  25. [26]

    Bravyi, O

    S. Bravyi, O. Dial, J. M. Gambetta, D. Gil, and Z. Nazario, The future of quantum computing with superconducting qubits, J. Applied Phys.132, 160902 (2022)

  26. [27]

    Bernien, S

    H. Bernien, S. Schwartz, A. Keesling, H. Levine, A. Omran, H. Pichler, S. Choi, A. S. Zibrov, M. Endres, M. Greiner, V . Vuletic, and M. Lukin, Probing many-body dynamics on a 51-atom quantum simulator, Nature551, 579 (2017)

  27. [28]

    Bluvstein, S

    D. Bluvstein, S. J. Evered, A. A. Geim, S. H. Li, H. Zhou, T. Manovitz, S. Ebadi, M. Cain, M. Kalinowski, D. Hangleiter, J. P. Bonilla Ataides, N. Maskara, I. Cong, X. Gao, P. S. Rodriguez, T. Karolyshyn, G. Semeghini, M. J. Gullans, M. Greiner, V . Vuletic, and M. D. Lukin, Logical quantum processor based on reconfigurable atom arrays, Nature626, 58 (2024)

  28. [29]

    Saffman, T

    M. Saffman, T. G. Walker, and K. Mølmer, Quantum informa- tion with Rydberg atoms, Rev. Mod. Phys.82, 2313 (2010)

  29. [30]

    S. J. Evered, D. Bluvstein, M. Kalinowski, S. Ebadi, T. Manovitz, H. Zhou, S. H. Li, A. A. Geim, T. T. Wang, N. Maskara, H. Levine, G. Semeghini, M. Greiner, V . Vuleti´c, and M. D. Lukin, High-fidelity parallel entangling gates on a neutral-atom quantum computer, Nature622, 268 (2023)

  30. [31]

    High-fidelity collisional quantum gates with fermionic atoms

    P. Bojovi´c, T. Hilker, S. Wang, J. Obermeyer, M. Barendregt, D. Tell, T. Chalopin, P. M. Preiss, I. Bloch, and T. Franz, High- fidelity collisional quantum gates with fermionic atoms, (2025), arXiv:2506.14711

  31. [32]

    M. Liu, R. Shaydulin, P. Niroula, M. DeCross, S.-H. Hung, W. Y . Kon, E. Cervero-Martín, K. Chakraborty, O. Amer, S. Aaronson,et al., Certified randomness using a trapped-ion quantum processor, Nature618, 500 (2025)

  32. [33]

    Y . Kim, A. Eddins, S. Anand, K. X. Wei, E. Van Den Berg, S. Rosenblatt, H. Nayfeh, Y . Wu, M. Zaletel, K. Temme,et al., Evidence for the utility of quantum computing before fault tolerance, Nature618, 500 (2023)

  33. [34]

    D. A. Abanin, R. Acharya, L. Aghababaie-Beni, G. Aigeldinger, A. Ajoy, R. Alcaraz, I. Aleiner, T. I. Andersen, M. Ansmann, F. Arute,et al., Constructive interference at the edge of quantum ergodic dynamics, (2025), arXiv:2506.10191

  34. [35]

    Knill, Leibfried, R

    E. Knill, Leibfried, R. Reichle, J. Britton, R. B. Blakestad, J., Jost, C. Langer, R. Ozeri, S. Seidelin, and J. Wineland, Randomized benchmarking of quantum gates, Phys. Rev. A77, 012307 (2008)

  35. [36]

    Eisert, D

    J. Eisert, D. Hangleiter, N. Walk, I. Roth, D. Markham, R. Parekh, U. Chabaud, and E. Kashefi, Quantum certifica- tion and benchmarking, Nature Rev. Phys.2, 382 (2020)

  36. [37]

    Hashim, L

    A. Hashim, L. B. Nguyen, N. Goss, B. Marinelli, R. K. Naik, T. Chistolini, J. Hines, J. Marceaux, Y . Kim, P. Gokhale, T. Tomesh, S. Chen, L. Jiang, S. Ferracin, K. Rudinger, T. Proc- tor, K. C. Young, I. Siddiqi, and R. Blume-Kohout, Practical introduction to benchmarking and characterization of quantum computers, PRX Quantum6, 030202 (2025)

  37. [38]

    IQM, IQM quantum computers achieves new technology mile- stones with 99.9% 2-qubit gate fidelity and 1 millisecond co- herence time (2024)

  38. [39]

    Google Quantum AI, Willow spec sheet (2024)

  39. [40]

    T. M. Graham, Y . Song, J. Scott, C. Poole, L. Phuttitarn, K. Jooya, P. Eichler, X. Jiang, A. Marra, B. Grinkemeyer, M. Kwon, M. Ebert, J. Cherek, M. T. Lichtman, M. Gillette, J. Gilbert, D. Bowman, T. Ballance, C. Campbell, E. D. Dahl, O. Crawford, N. S. Blunt, B. Rogers, T. Noel, and M. Saffman, Multi-qubit entanglement and algorithms on a neutral-atom ...

  40. [41]

    D. A. Rower, L. Ding, H. Zhang, M. Hays, J. An, P. M. Harring- ton, I. T. Rosen, J. M. Gertler, T. M. Hazard, B. M. Niedzielski, M. E. Schwartz, S. Gustavsson, K. Serniak, J. A. Grover, and W. D. Oliver, Suppressing counter-rotating errors for fast single- qubit gates with fluxonium, PRX Quantum5, 040342 (2024)

  41. [42]

    Z. Li, P. Liu, P. Zhao, Z. Mi, H. Xu, X. Liang, T. Su, W. Sun, G. Xue, J.-N. Zhang, W. Liu, Y . Jin, and H. Yu, npj Quant. Inf. 9, 111 (2023)

  42. [43]

    Bengtsson, A

    A. Bengtsson, A. Opremcak, M. Khezri, D. Sank, A. Bourassa, K. J. Satzinger, S. Hong, C. Erickson, B. J. Lester, K. C. Miao, A. N. Korotkov, J. Kelly, Z. Chen, and P. V . Klimov, Model- based optimization of superconducting qubit readout, Phys. Rev. Lett.132, 100603 (2024)

  43. [44]

    Neven, Meet willow, our state-of-the-art quantum chip (2024)

    H. Neven, Meet willow, our state-of-the-art quantum chip (2024)

  44. [45]

    D. Gao, D. Fan, C. Zha, J. Bei, G. Cai, J. Cai, S. Cao, F. Chen, J. Chen, K. Chen,et al., Establishing a new benchmark in quantum computational advantage with 105-qubit Zuchongzhi 3.0 processor, Phys. Rev. Lett.134, 090601 (2025)

  45. [46]

    IBM Newsroom, IBM launches its most advanced quantum computers, fueling new scientific value and progress towards quantum advantage (2024)

  46. [47]

    Y . Quek, D. S. França, S. Khatri, J. J. Meyer, and J. Eisert, Exponentially tighter bounds on limitations of quantum error, mitigation, Nature Phys.20, 1648 (2024)

  47. [48]

    Schuster, C

    T. Schuster, C. Yin, X. Gao, and N. Y . Yao, A polynomial- time classical algorithm for noisy quantum circuits, (2024), arXiv:2407.12768

  48. [49]

    A. A. Mele, A. Angrisani, S. Ghosh, S. Khatri, J. Eisert, D. S. França, and Y . Quek, Noise-induced shallow circuits and ab- sence of barren plateaus, (2024), arXiv:2403.13927

  49. [50]

    Deshpande, P

    A. Deshpande, P. Niroula, O. Shtanko, A. V . Gorshkov, B. Fef- ferman, and M. J. Gullans, Tight bounds on the convergence of noisy random circuits to the uniform distribution, PRX Quan- tum3, 040329 (2022). 13

  50. [51]

    Stilck Franca and R

    D. Stilck Franca and R. García-Patrón, Limitations of optimiza- tion algorithms on noisy quantum devices, Nature Phys.17, 1221 (2020)

  51. [52]

    Quantum Refrigerator

    M. Ben-Or, D. Gottesman, and A. Hassidim, Quantum refriger- ator, arXiv (2013), arXiv:1301.1995

  52. [53]

    Simulating quantum circuits with arbitrary local noise using Pauli Propagation

    A. Angrisani, A. A. Mele, M. S. Rudolph, M. Cerezo, and Z. Holmes, Simulating quantum circuits with arbitrary local noise using Pauli propagation, (2025), arxiv:2501.13101

  53. [54]

    Z. Cai, R. Babbush, S. C. Benjamin, S. Endo, W. J. Huggins, Y . Li, J. R. McClean, and T. E. O’Brien, Quantum error mitiga- tion, Rev. Mod. Phys.95, 045005 (2023)

  54. [55]

    Giurgica-Tiron, Y

    T. Giurgica-Tiron, Y . Hindy, R. LaRose, A. Mari, and W. J. Zeng, Digital zero noise extrapolation for quantum error miti- gation, 2020 IEEE Int. Conf. Quant. Comp. Eng. (QCE) , 306 (2020)

  55. [56]

    A. Mari, N. Shammah, and W. J. Zeng, Extending quantum probabilistic error cancellation by noise scaling, Phys. Rev. A 104, 052607 (2021)

  56. [57]

    LaRose, A

    R. LaRose, A. Mari, S. Kaiser, P. J. Karalekas, A. A. Alves, P. Czarnik, M. E. Mandouh, M. H. Gordon, Y . Hindy, A. Robert- son, P. Thakre, M. Wahl, D. Samuel, R. Mistri, M. Tremblay, N. Gardner, N. T. Stemen, N. Shammah, and W. J. Zeng, Mi- tiq: A software package for error mitigation on noisy quantum computers, Quantum6, 774 (2022)

  57. [58]

    J. R. McClean, Z. Jiang, N. C. Rubin, R. Babbush, and H. Neven, Decoding quantum errors with subspace expansions, Nature Comm.11, 636 (2020)

  58. [59]

    F. B. Maciejewski, Z. Zimborás, and M. Oszmaniec, Mitigation of readout noise in near-term quantum devices by classical post-processing based on detector tomography, Quantum4, 257 (2020)

  59. [60]

    Takagi, H

    R. Takagi, H. Tajima, and M. Gu, Universal sampling lower bounds for quantum error mitigation, Phys. Rev. Lett.131, 210602 (2023)

  60. [61]

    Exponen- tially tighter bounds on limitations of quantum er- ror mitigation,

    R. Takagi, S. Endo, S. Minagawa, and M. Gu, Fundamental lim- its of quantum error mitigation, npj Quant. Inf.8, 114 (2022), arXiv:2210.11505

  61. [62]

    On the importance of er- ror mitigation for quantum computation,

    D. Aharonov, O. Alberton, I. Arad, Y . Atia, E. Bairey, Z. Brak- erski, I. Cohen, O. Golan, I. Gurwich, O. Kenneth,et al., On the importance of error mitigation for quantum computation, (2025), arXiv:2503.17243

  62. [63]

    Reliable high-accuracy error mitigation for utility-scale quantum circuits

    D. Aharonov, O. Alberton, I. Arad, Y . Atia, E. Bairey, M. B. Dov, A. Berkovitch, Z. Brakerski, I. Cohen, E. Fuchs,et al., Re- liable high-accuracy error mitigation for utility-scale quantum circuits, (2025), arXiv:2508.10997

  63. [64]

    Cotler, S

    J. Cotler, S. Choi, A. Lukin, H. Gharibyan, T. Grover, M. E. Tai, M. Rispoli, R. Schittko, P. M. Preiss, A. M. Kaufman,et al., Quantum virtual cooling, Phys. Rev. X9, 031013 (2019)

  64. [65]

    Seif, Z.-P

    A. Seif, Z.-P. Cian, S. Zhou, S. Chen, and L. Jiang, Shadow distillation: Quantum error mitigation with classical shadows for near-term quantum processors, PRX Quantum4, 010303 (2023)

  65. [66]

    W. J. Huggins, S. McArdle, T. E. O’Brien, J. Lee, N. C. Rubin, S. Boixo, K. B. Whaley, R. Babbush, and J. R. McClean, Vir- tual distillation for quantum error mitigation, Phys. Rev. X11, 041036 (2021)

  66. [67]

    Koczor, Exponential error suppression for near-term quan- tum devices, Phys

    B. Koczor, Exponential error suppression for near-term quan- tum devices, Phys. Rev. X11, 031057 (2021)

  67. [68]

    Onorati, J

    E. Onorati, J. Kitzinger, J. Helsen, M. Ioannou, A. H. Werner, I. Roth, and J. Eisert, Noise-mitigated randomized mea- surements and self-calibrating shadow estimation, (2024), arXiv:2403.04751

  68. [69]

    Z. Liu, X. Zhang, Y .-Y . Fei, and Z. Cai, Virtual channel purifi- cation, (2024), arXiv:2402.07866

  69. [70]

    M. A. Wahl, A. Mari, N. Shammah, W. J. Zeng, and G. S. Ravi, Zero noise extrapolation on logical qubits by scaling the error correction code distance, 2023 IEEE Int. Conf. Quant. Comp. Eng. (QCE)1, 888 (2023)

  70. [71]

    Suzuki, S

    Y . Suzuki, S. Endo, K. Fujii, and Y . Tokunaga, Quantum error mitigation as a universal error reduction technique: Applica- tions from the NISQ to the fault-tolerant quantum computing eras, PRX Quantum3, 010345 (2022)

  71. [72]

    Camilo, T

    G. Camilo, T. O. Maciel, A. Tosta, A. Alhajri, T. de Lima Silva, D. S. França, and L. Aolita, Compilation-informed probabilistic quantum error cancellation, (2025), arXiv:2508.20174

  72. [73]

    B. M. Terhal, Quantum error correction for quantum memories, Rev. Mod. Phys.87, 307 (2015)

  73. [74]

    E. T. Campbell, B. M. Terhal, and C. Vuillot, Roads towards fault-tolerant universal quantum computation, Nature549, 172 (2017)

  74. [75]

    Roffe, Quantum error correction: An introductory guide, Contemp

    J. Roffe, Quantum error correction: An introductory guide, Contemp. Phys.60, 226 (2019)

  75. [76]

    A. M. Steane, Error correcting codes in quantum theory, Phys. Rev. Lett.77, 793 (1996)

  76. [77]

    Aharonov and M

    D. Aharonov and M. Ben-Or, Fault-tolerant quantum compu- tation with constant error, STOC ’97: Proc. 29th Ann. ACM Symp. Th. Comp. , 176

  77. [78]

    Knill, R

    E. Knill, R. Laflamme, and W. H. Zurek, Resilient quantum computation: error models and thresholds, Proc. Roy. Soc. Lond. A454, 365 (1998)

  78. [79]

    Preskill, Reliable quantum computers, Proc

    J. Preskill, Reliable quantum computers, Proc. Roy. Soc. Lond. A454, 385 (1998)

  79. [80]

    Eastin and E

    B. Eastin and E. Knill, Restrictions on transversal encoded quantum gate sets, Phys. Rev. Lett.102, 110502 (2009)

  80. [81]

    A. Y . Kitaev, Anyons in an exactly solved model and beyond, Ann. Phys.321, 2 (2006)

Showing first 80 references.