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REVIEW 4 major objections 4 minor 1 cited by

When Quantum Meets Classical: Characterizing Hybrid Quantum-Classical Issues Discussed in Developer Forums

T0 review · 4 major / 4 minor · reviewed 2026-08-12 · deepseek-v4-flash

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Pith's one-line read This paper claims that hybrid quantum-classical applications fail predominantly by crashing and that most of those failures come from application-developer mistakes, not quantum hardware or platform defects.

desk verdict Useful first taxonomy of hybrid quantum-classical issues from forums, but treat the headline frequencies as PennyLane-heavy sample statistics until per-source breakdowns and coding-reliability checks are added. read the letter →

arxiv 2411.16884 v2 pith:RPQPSS4P submitted 2024-11-25 cs.SE

Jake Zappin , Trevor Stalnaker , Oscar Chaparro , Denys Poshyvanyk This is my paper · ORCID
classification cs.SE
keywords hybridquantum-classicalcomputingsoftwareengineeringbugtaxonomydeveloperforumsquantumbugscrashanalysisempiricalcross-domainissues
verification ladder T0 review T1 audit T2 compute T3 formal

The pith

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

The reading

The paper sets out to give the first empirically grounded account of what repeatedly goes wrong when developers build hybrid quantum-classical (HQC) applications—software that splits a computation between a quantum processor or simulator and a classical machine. After manually coding 531 real-world issues from two quantum-focused developer forums, the authors claim two headline results: HQC application failures are crash-dominant, with 74% of issues ending in a crash, and about 70% of issues are caused by mistakes made by the application developer rather than by quantum hardware or platform defects. They also claim to have identified a new class of 'cross-domain' issues that sit at the boundary between the quantum and classical subsystems and can typically be resolved by changing either side. If these claims are right, they give both application and platform developers a concrete, frequency-ordered map of where to spend effort on debugging tools, documentation, and training.

What carries the argument

The load-bearing object is the taxonomy itself, built from a coding pipeline: keyword search (general, quantum-specific, hybrid-algorithm, and PennyLane-template terms) over two forums, manual relevance screening of 8,278 mined threads down to 1,215 relevant ones, independent coding by two authors, iterative refinement of subcategories through open coding, and reconciliation meetings. The taxonomy carries the argument because every headline statistic—74% crashes, 70% programmer-caused errors, and the cross-domain category—is a count over its coded categories. The 'cross-domain' node is the paper's principal novel contribution: issues that manifest in either subsystem and are fixable from either side, which prior platform- and library-centered bug studies did not distinguish.

What would settle it

Apply the same coding scheme to a fresh sample of HQC issues drawn from a different source—for example, issue trackers of non-vendor application repositories or a second forum—and compare the category proportions. If crashes do not remain the dominant manifestation (near 74%) and programmer error does not remain the leading cause (near 70%), then the paper's headline numbers are properties of its forum sample rather than of hybrid quantum-classical development.

Watch

Extended reading notes

Core claim

The paper's central claim is that recurring problems in hybrid quantum-classical development can be organized into a four-level taxonomy of five top-level categories—Software Faults (121 issues), Library and Platform Issues (116), Developer Errors (140), Configuration Issues (82), and Hardware/Simulator Issues (24)—and that the distribution of these issues overturns a purely quantum-focused picture of quantum software bugs. The authors report that 316 of 483 classifiable issues are classical in origin, 76 are quantum-specific, and 91 are cross-domain, a category they say earlier bug taxonomies missed because those studies separated quantum and classical bugs. They find crashes are the dominant manifestation across all domains, and programmer error is the dominant cause, with platform issues second. The paper presents this taxonomy as a practical troubleshooting and testing aid, not merely a classification, and releases the coded dataset for reuse.

Load-bearing premise

The study's findings rest on the assumption that the 1,215 forum threads selected by keyword search and single-author relevance screening fairly represent the full population of hybrid quantum-classical development problems; if that sample skews toward one platform or toward beginners, the headline percentages would not generalize.

Editorial extensions

If this is right

  • Crash prevention becomes the top priority for HQC reliability work: 359 of 483 classified issues ended in a crash, so debugging and testing tools should target crash-inducing conditions first.
  • Developer education and documentation may reduce failures more than hardware improvements, since 338 of 483 issues were traced to programmer error.
  • Cross-domain issues (91 of 483) are a distinct failure class requiring tools that understand the quantum-classical boundary, such as embedding, encoding, and hybrid algorithm design.
  • The taxonomy's frequency counts let testers prioritize: configuration (82), library/platform (116), and developer errors (140) are the largest actionable clusters.

Reading between the lines

Editorial extensions of the paper, not claims the author makes directly.

  • Because the primary forum belongs to one quantum platform vendor, the 74% and 70% figures may partly reflect that vendor's ecosystem and the kinds of questions forum users ask; re-running the coding on issues from other ecosystems or from GitHub issue trackers would test the numbers' generalizability.
  • If crash dominance holds across sources, HQC application development today resembles systems programming—where crashes dominate—rather than numerical software, where incorrect output typically dominates; error-handling and defensive-programming practices from systems engineering may transfer directly.
  • A natural next study would be to track how the cross-domain issue category maps onto API design: if most cross-domain bugs are triggered by data-shape or differentiability mismatches, platform APIs that make those contracts explicit could eliminate a measurable share of issues.
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Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, and a circularity audit.

Referee Report

4 major / 4 minor

Summary. The paper presents an empirical study of 531 issues drawn from 447 discussion threads on the Xanadu Discussion Forums (XDF) and the Quantum Computing Stack Exchange (QCSE). The authors construct a four-level taxonomy of recurring issues in hybrid quantum-classical (HQC) applications, classify issues as quantum-specific, classical, or cross-domain, and analyze how issues manifest and what causes them. They report that crashes dominate (74% of studied issues) and that most issues are caused by application developers (70%). The paper closes with recommendations for application developers and platform maintainers, and it makes a replication package publicly available.

Significance. If the quantitative results are supported, the paper is a valuable contribution to quantum software engineering: it is among the first studies to focus on HQC application issues from developer forums, it identifies a cross-domain issue category not present in earlier quantum bug taxonomies, and it provides a labeled dataset for future research. The two-phase coding procedure, reconciliation meetings, sample-size-based coding effort, and public replication package are notable strengths. However, the headline frequencies are not currently supported as generalizable because they pool a vendor-specific PennyLane forum with a general forum, and the quantitative tables contain internal inconsistencies. The taxonomy itself and the qualitative recommendations remain useful even if the aggregate percentages require revision.

major comments (4)
  1. [Sec. IV.A.1, Table III and Tables V/VII] The pooled 74% crash-dominance and 70% programmer-error claims are computed on a sample in which XDF contributes 377 of 531 coded issues (about 71%), and XDF is a vendor-run PennyLane forum. Tables V and VII report only pooled totals, so it is impossible to determine whether these rates are properties of HQC development generally or of the XDF/PennyLane ecosystem. This concern is reinforced by the keyword list in Table II, which includes PennyLane template names such as 'AmplitudeEmbedding'. Please report per-source breakdowns for origin, manifestation, and cause, and test for homogeneity between XDF and QCSE (e.g., a chi-square or Fisher test) before drawing general conclusions.
  2. [Sec. IV.B.2 and Sec. VI] All frequencies in the paper depend on the 1,215-thread relevant corpus, but relevance screening was performed by a single author with no reported agreement measure; the threats-to-validity section acknowledges this subjectivity but does not quantify it. Please provide an inter-rater reliability check on a sample of screened threads, or at minimum discuss the direction and magnitude of screening bias that could result from the single-author procedure.
  3. [Tables V, VI, and VIII] The manifestation counts are internally inconsistent. Table V reports 483 total issues with 359 crashes, 69 incorrect outputs, 30 slow executions, 19 unknown manifestations, and 6 warnings. Table VI reports 531 total issues with 393 crashes, 79 incorrect outputs, 33 slow executions, 17 unknown manifestations, and 9 warnings. Table VIII again reports a different warning count (7) and gives a crash percentage of 2.0% for Platform Limitation, which does not match any denominator in the table. The relationship between the 483 categorized issues and the 531 total issues (including the 48 unknown-cause issues) is not explained, so the headline 74% figure cannot be verified as stated. Please reconcile these tables and specify the exact denominator for every percentage.
  4. [Sec. V.D, Sec. V.A, and Table VII] The 70% programmer-error figure is at least partly definitional. The taxonomy defines Developer Errors (140 issues) as mistakes made by application developers and Configuration Issues (82 issues) as problems generally caused by the developer, so the dominance of Programmer Error in Table VII is built into the classification scheme. To make the causal claim meaningful, please report the cause distribution after excluding these definitional categories, or show that the cause labels were assigned independently of the issue-type taxonomy.
minor comments (4)
  1. [Sec. V.C] The text lists 'Warnings (19)' and 'Unknown (6)', but Table V reports Warning 6 and Unknown 19; these two counts appear to be swapped and should be corrected.
  2. [Sec. V.A] The text says 'In an additional 48 discussion threads, we encountered issues which we could not categorize into the taxonomy', but Table III reports only 447 coded threads in total. Please clarify whether the 48 refers to threads or issues and how these relate to the 447 coded threads.
  3. [Table VIII] The percentages in Table VIII should be recomputed from the reconciled counts; several entries (e.g., the 2.0% for Platform Limitation in the Crash column) are inconsistent with both the column totals and the row totals.
  4. [Sec. IV.C] The sample size calculation is mentioned only as '95% confidence interval and 5% error margin for each data source'; please provide the population sizes, the sampling method, and the resulting sample sizes to allow readers to assess representativeness.

Circularity Check

0 steps flagged · score 1.0 of 10

No significant circularity: the study is a descriptive taxonomy of forum threads, and its headline frequencies are summaries of the same dataset rather than independent predictions.

full rationale

The paper makes no first-principles derivation or predictive claim: the taxonomy and the 74% crash / 70% programmer-error frequencies are descriptive summaries of 531 manually coded forum issues. The taxonomy was explicitly derived from the same threads it describes, so it cannot be circular in the sense of fitting a parameter and then predicting it back. The only self-citation ([90], Chaparro et al.) supports a side remark about classical bug-report quality and is not load-bearing. The 70% programmer-caused figure is partly colored by category definitions (e.g., 'Developer Errors' are defined as mistakes made by application developers), but the paper transparently reports this overlap ('Programmer Errors caused all Developer Errors') and does not present it as a validation result; this is a construct-validity limitation acknowledged in Section VI, not a circular derivation. The study is appropriately self-contained against its data sources, and no external benchmark or uniqueness theorem is invoked.

Assumptions & free parameters 0 free parameters · 2 assumptions · 0 invented entities

This is an empirical software engineering study, not a derivation; there are no fitted parameters or invented entities. The central claims rest on assumptions about data source representativeness and coding reliability.

assumptions (2)
  • domain assumption Forum discussion threads accurately reflect real issues encountered by HQC developers
    The study relies on self-reported issues from XDF and QCSE; these may be biased toward questions that novices ask or issues that platform staff choose to answer.
  • domain assumption The coding framework and taxonomic categories capture the true underlying distribution of issue types
    Two authors coded threads with reconciliation, but no inter-rater reliability metric is reported, so the reliability of the classification is not quantitatively assessed.

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Cite this review

Pith. "Pith review of When Quantum Meets Classical: Characterizing Hybrid Quantum-Classical Issues Discussed in Developer Forums." pith.science (2026). https://pith.science/paper/RPQPSS4P

@misc{pith2026241116884,
  author       = {Pith},
  title        = {Pith review of: When Quantum Meets Classical: Characterizing Hybrid Quantum-Classical Issues Discussed in Developer Forums},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/RPQPSS4P}},
  note         = {Machine review of arXiv:2411.16884}
}
read the original abstract

Recent advances in quantum computing have sparked excitement that this new computing paradigm could solve previously intractable problems. However, due to the faulty nature of current quantum hardware and quantum-intrinsic noise, the full potential of quantum computing is still years away. Hybrid quantum-classical computing has emerged as a possible compromise that achieves the best of both worlds. In this paper, we look at hybrid quantum-classical computing from a software engineering perspective and present the first empirical study focused on characterizing and evaluating recurrent issues faced by developers of hybrid quantum-classical applications. The study comprised a thorough analysis of 531 real-world issues faced by developers -- including software faults, hardware failures, quantum library errors, and developer mistakes -- documented in discussion threads from forums dedicated to quantum computing. By qualitatively analyzing such forum threads, we derive a comprehensive taxonomy of recurring issues in hybrid quantum-classical applications that can be used by both application and platform developers to improve the reliability of hybrid applications. The study considered how these recurring issues manifest and their causes, determining that hybrid applications are crash-dominant (74% of studied issues) and that errors were predominantly introduced by application developers (70% of issues). We conclude by identifying recurring obstacles for developers of hybrid applications and actionable recommendations to overcome them.

Figures

Figures reproduced from arXiv: 2411.16884 by the authors.

Figure 1
Figure 1. Taxonomy of issues encountered by developers of HQC applications [PITH_FULL_IMAGE:figures/full_fig_p006_1.png] view at source ↗
Figure 1
Figure 1. We group the identified HQC issues into three categories: [PITH_FULL_IMAGE:figures/full_fig_p007_1.png] view at source ↗
Figure 2
Figure 2. Example PennyLane Warning Messages Two warning messages encountered by devs in PennyLane that change application behavior regardless of what the was specified in the code [84]. automatic fallback to a different simulator or function due to some detected incompatibility or inefficiency [83, 84]. Unknown (6): Some analyzed threads did not provide enough information to ascertain how an issue manifests. We labeled these… view at source ↗
Figures from the paper (3 more)
Figure 3
Figure 3. Figure 3: Platform Limitation Example Attempting multiple measurements on the same wire with non-commutable observables (PauliX / PauliZ) causes errors due to PennyLane restrictions [89] TABLE VII: Instances of Issue Causes by Origin Quantum-Specific Classical Cross-Domain All I…
Figure 4
Figure 4. Figure 4: Platform Quirk Example with Cross-Domain Fixes [PITH_FULL_IMAGE:figures/full_fig_p010_4.png]
Figure 5
Figure 5. Figure 5: Platform Quirks Examples Redefining testAmp() to take a keyword argument resolves the error since AmplitudeEmbedding only accepts non-differentiable data. Integration of New Features: A notable hurdle, representing 6.4% of encountered issues, was the lack of support fo…

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Forward citations

Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

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Reference graph

Works this paper leans on

94 extracted references · 63 canonical work pages · cited by 1 Pith paper

  1. [1]

    Quantum computing 40 years later,

    J. Preskill, “Quantum computing 40 years later,” in Feynman Lectures on Computation. CRC Press, 2023, pp. 193–244

    2023

  2. [2]

    Quantum computing: Beyond the limits of conventional computation,

    M. Nagy and S. G. Akl, “Quantum computing: Beyond the limits of conventional computation,” The International Journal of Parallel, Emergent and Distributed Systems , vol. 22, no. 2, pp. 123–135, 2007

    2007

  3. [3]

    Qiskit: An open-source framework for quantum computing,

    G. Aleksandrowicz, T. Alexander, P. Barkoutsos, L. Bello, Y . Ben-Haim, D. Bucher, F. J. Cabrera-Hern ´andez, J. Carballo-Franquis, A. Chen, C.-F. Chen et al., “Qiskit: An open-source framework for quantum computing,” Accessed on: Mar , vol. 16, 2019

    2019

  4. [4]

    G. A. Q. Team, “Cirq,” 2018. [Online]. Available: https://github .com/ quantumlib/Cirq

    2018

  5. [5]

    Q# enabling scalable quantum computing and development with a high-level dsl,

    K. Svore, A. Geller, M. Troyer, J. Azariah, C. Granade, B. Heim, V . Kliuchnikov, M. Mykhailova, A. Paz, and M. Roetteler, “Q# enabling scalable quantum computing and development with a high-level dsl,” in Proceedings of the real world domain specific languages workshop 2018 , 2018, pp. 1–10

    2018

  6. [6]

    Pennylane: Automatic differentiation of hybrid quantum-classical computations,

    V . Bergholm, J. Izaac, M. Schuld, C. Gogolin, S. Ahmed, V . Ajith, M. S. Alam, G. Alonso-Linaje, B. AkashNarayanan, A. Asadi et al., “Pennylane: Automatic differentiation of hybrid quantum-classical computations,” arXiv preprint arXiv:1811.04968 , 2018

    arXiv 2018

  7. [7]

    Quantum computing at an inflection point: Are we ready for a new paradigm,

    A. Bhasin and M. Tripathi, “Quantum computing at an inflection point: Are we ready for a new paradigm,” IEEE Transactions on Engineering Management, 2021

    2021

  8. [8]

    On the role of entanglement in quantum- computational speed-up,

    R. Jozsa and N. Linden, “On the role of entanglement in quantum- computational speed-up,” Proceedings of the Royal Society of London. Series A: Mathematical, Physical and Engineering Sciences , vol. 459, no. 2036, pp. 2011–2032, 2003

    2011

Show all 94 references
  1. [9]

    Real-time decoding for fault-tolerant quantum computing: Progress, challenges and outlook,

    F. Battistel, C. Chamberland, K. Johar, R. W. Overwater, F. Sebastiano, L. Skoric, Y . Ueno, and M. Usman, “Real-time decoding for fault-tolerant quantum computing: Progress, challenges and outlook,” arXiv preprint arXiv:2303.00054, 2023

    2023 arXiv

  2. [10]

    Hybrid quantum-classical algorithms in the noisy intermediate-scale quantum era and beyond,

    A. Callison and N. Chancellor, “Hybrid quantum-classical algorithms in the noisy intermediate-scale quantum era and beyond,” Physical Review A, vol. 106, no. 1, p. 010101, 2022

    2022

  3. [11]

    Hybrid quantum-classical neural networks,

    D. Arthur and P. Date, “Hybrid quantum-classical neural networks,” in 2022 IEEE International Conference on Quantum Computing and Engineering (QCE). IEEE, 2022, pp. 49–55

    2022

  4. [12]

    Hybrid quantum-classical algorithms and quantum error mitigation,

    S. Endo, Z. Cai, S. C. Benjamin, and X. Yuan, “Hybrid quantum-classical algorithms and quantum error mitigation,” Journal of the Physical Society of Japan, vol. 90, no. 3, p. 032001, 2021

    2021

  5. [13]

    Hybrid quantum-classical convolutional neural network model for covid- 19 prediction using chest x-ray images,

    E. H. Houssein, Z. Abohashima, M. Elhoseny, and W. M. Mohamed, “Hybrid quantum-classical convolutional neural network model for covid- 19 prediction using chest x-ray images,” Journal of Computational Design and Engineering, vol. 9, no. 2, pp. 343–363, 2022

    2022

  6. [14]

    Toward a quantum software engineering,

    M. Piattini, M. Serrano, R. Perez-Castillo, G. Petersen, and J. L. Hevia, “Toward a quantum software engineering,” IT Professional, vol. 23, no. 1, pp. 62–66, 2021

    2021

  7. [15]

    When software engineering meets quantum computing,

    S. Ali, T. Yue, and R. Abreu, “When software engineering meets quantum computing,” Communications of the ACM , vol. 65, no. 4, pp. 84–88, 2022

    2022

  8. [16]

    Quantum software engineering: Landscapes and horizons,

    J. Zhao, “Quantum software engineering: Landscapes and horizons,” arXiv preprint arXiv:2007.07047 , 2020

    2007 arXiv

  9. [17]

    Software engineering for’quantum advantage’,

    L. S. Barbosa, “Software engineering for’quantum advantage’,” in Proceedings of the IEEE/ACM 42nd International Conference on Software Engineering Workshops, 2020, pp. 427–429

    2020

  10. [18]

    Muskit: A mutation analysis tool for quantum software testing,

    E. Mendiluze, S. Ali, P. Arcaini, and T. Yue, “Muskit: A mutation analysis tool for quantum software testing,” in 2021 36th IEEE/ACM International Conference on Automated Software Engineering (ASE) . IEEE, 2021, pp. 1266–1270

    2021

  11. [19]

    Bugs in quantum computing platforms: an empirical study,

    M. Paltenghi and M. Pradel, “Bugs in quantum computing platforms: an empirical study,” Proceedings of the ACM on Programming Languages , vol. 6, no. OOPSLA1, pp. 1–27, 2022

    2022

  12. [20]

    Bug characteristics in quantum software ecosystem,

    H. Li, F. Khomh, L. Tidjon et al. , “Bug characteristics in quantum software ecosystem,” arXiv preprint arXiv:2204.11965 , 2022

    2022 arXiv

  13. [21]

    Identifying bug patterns in quantum programs,

    P. Zhao, J. Zhao, and L. Ma, “Identifying bug patterns in quantum programs,” in 2021 IEEE/ACM 2nd International Workshop on Quantum Software Engineering (Q-SE) . IEEE, 2021, pp. 16–21

    2021

  14. [22]

    A comprehensive study of bug fixes in quantum programs,

    J. Luo, P. Zhao, Z. Miao, S. Lan, and J. Zhao, “A comprehensive study of bug fixes in quantum programs,” in 2022 IEEE International Conference on Software Analysis, Evolution and Reengineering (SANER) . IEEE, 2022, pp. 1239–1246

    2022

  15. [23]

    Bugs4q: A benchmark of real bugs for quantum programs,

    P. Zhao, J. Zhao, Z. Miao, and S. Lan, “Bugs4q: A benchmark of real bugs for quantum programs,” in 2021 36th IEEE/ACM International Conference on Automated Software Engineering (ASE) . IEEE, 2021, pp. 1373–1376

    2021

  16. [24]

    An empirical study of bugs in quantum machine learning frameworks,

    P. Zhao, X. Wu, J. Luo, Z. Li, and J. Zhao, “An empirical study of bugs in quantum machine learning frameworks,” arXiv preprint arXiv:2306.06369, 2023

    2023 arXiv

  17. [25]

    The theory of variational hybrid quantum-classical algorithms,

    J. R. McClean, J. Romero, R. Babbush, and A. Aspuru-Guzik, “The theory of variational hybrid quantum-classical algorithms,” New Journal of Physics, vol. 18, no. 2, p. 023023, 2016

    2016

  18. [26]

    Hybrid quantum–classical optimization with cardinality constraints and appli- cations to finance,

    S. Fern ´andez-Lorenzo, D. Porras, and J. J. Garc ´ıa-Ripoll, “Hybrid quantum–classical optimization with cardinality constraints and appli- cations to finance,” Quantum Science and Technology , vol. 6, no. 3, p. 034010, 2021

    2021

  19. [27]

    Implementation of a hybrid classical-quantum annealing algorithm for logistic network design,

    Y . Ding, X. Chen, L. Lamata, E. Solano, and M. Sanz, “Implementation of a hybrid classical-quantum annealing algorithm for logistic network design,” SN Computer Science , vol. 2, pp. 1–9, 2021

    2021

  20. [28]

    Hybrid quantum-classical search algorithms,

    A. Rosmanis, “Hybrid quantum-classical search algorithms,” arXiv preprint arXiv:2202.11443, 2022

    2022 arXiv

  21. [29]

    The past, present, and future of us government investment in quantum information science: https://www. quantum. gov,

    C. Walsh, “The past, present, and future of us government investment in quantum information science: https://www. quantum. gov,” 2023

    2023

  22. [30]

    Industry quantum computing applications,

    A. Bayerstadler, G. Becquin, J. Binder, T. Botter, H. Ehm, T. Ehmer, M. Erdmann, N. Gaus, P. Harbach, M. Hess et al., “Industry quantum computing applications,” EPJ Quantum Technology, vol. 8, no. 1, p. 25, 2021

    2021

  23. [31]

    Xanadu discussion forums,

    X. AI, “Xanadu discussion forums,” 2023. [Online]. Available: https://discuss.pennylane.ai/

    2023

  24. [32]

    Quantum computing stack exchange forums,

    Q. C. S. Exchange, “Quantum computing stack exchange forums,” 2023. [Online]. Available: https://quantumcomputing .stackexchange.com/

    2023

  25. [33]

    Online replication package,

    “Online replication package,” https://archive.softwareheritage.org/browse/ origin/directory/?origin url=https://github.com/jakezappin/HQC Bug Replication, 2024

    2024

  26. [34]

    Quantum computing,

    J. L. Hevia, G. Peterssen, C. Ebert, and M. Piattini, “Quantum computing,” IEEE Software, vol. 38, no. 5, pp. 7–15, 2021

    2021

  27. [35]

    Quantum computing: an introduction,

    T. Hey, “Quantum computing: an introduction,” Computing & Control Engineering Journal, vol. 10, no. 3, pp. 105–112, 1999

    1999

  28. [36]

    An introduction to quantum computing for non-physicists,

    E. Rieffel and W. Polak, “An introduction to quantum computing for non-physicists,” ACM Computing Surveys (CSUR) , vol. 32, no. 3, pp. 300–335, 2000

    2000

  29. [37]

    Einstein, M

    A. Einstein, M. Born, and H. Born, The Born-Einstein Letters: Correspondence Between Albert Einstein and Max and Hedwig Born from 1916-1955, with Commentaries by Max Born. Macmillan, 1971. [Online]. Available: https://books.google.com/books?id=HvZAAQAAIAAJ

    1916

  30. [38]

    Quantum computational chemistry,

    S. McArdle, S. Endo, A. Aspuru-Guzik, S. C. Benjamin, and X. Yuan, “Quantum computational chemistry,” Reviews of Modern Physics , vol. 92, no. 1, p. 015003, 2020

    2020

  31. [39]

    Evidence of scaling advantage for the quantum approximate optimization algorithm on a classically intractable problem,

    R. Shaydulin, C. Li, S. Chakrabarti, M. DeCross, D. Herman, N. Kumar, J. Larson, D. Lykov, P. Minssen, Y . Sun et al. , “Evidence of scaling advantage for the quantum approximate optimization algorithm on a classically intractable problem,” arXiv preprint arXiv:2308.02342 , 2023

    2023 arXiv

  32. [40]

    An efficient quantum computing technique for cracking rsa using shor’s algorithm,

    V . Bhatia and K. Ramkumar, “An efficient quantum computing technique for cracking rsa using shor’s algorithm,” in 2020 IEEE 5th international conference on computing communication and automation (ICCCA) . IEEE, 2020, pp. 89–94

    2020

  33. [41]

    Opportunities and challenges for quantum-assisted machine learning in near-term quantum computers,

    A. Perdomo-Ortiz, M. Benedetti, J. Realpe-G ´omez, and R. Biswas, “Opportunities and challenges for quantum-assisted machine learning in near-term quantum computers,” Quantum Science and Technology , vol. 3, no. 3, p. 030502, 2018

    2018

  34. [42]

    Quantum computing in the nisq era and beyond,

    J. Preskill, “Quantum computing in the nisq era and beyond,” Quantum, vol. 2, p. 79, 2018

    2018

  35. [43]

    Fault-tolerant quantum computation,

    ——, “Fault-tolerant quantum computation,” in Introduction to quantum computation and information . World Scientific, 1998, pp. 213–269

    1998

  36. [44]

    An introduction to quantum error correction and fault- tolerant quantum computation,

    D. Gottesman, “An introduction to quantum error correction and fault- tolerant quantum computation,” in Quantum information science and its contributions to mathematics, Proceedings of Symposia in Applied Mathematics, vol. 68, 2010, pp. 13–58

    2010

  37. [45]

    Ibm releases first-ever 1,000-qubit quantum chip,

    D. Castelvecchi, “Ibm releases first-ever 1,000-qubit quantum chip,”

  38. [46]

    Ibm unveils 400 qubit-plus quantum processor and next-generation ibm quantum system two,

    IBM, “Ibm unveils 400 qubit-plus quantum processor and next-generation ibm quantum system two,” 2022. [Online]. Available: https://newsroom.ibm.com/2022-11-09-IBM-Unveils-400-Qubit-Plus- Quantum-Processor-and-Next-Generation-IBM-Quantum-System-Two 12

    2022

  39. [47]

    Noisy intermediate-scale quantum algorithms,

    K. Bharti, A. Cervera-Lierta, T. H. Kyaw, T. Haug, S. Alperin-Lea, A. Anand, M. Degroote, H. Heimonen, J. S. Kottmann, T. Menke et al., “Noisy intermediate-scale quantum algorithms,” Reviews of Modern Physics, vol. 94, no. 1, p. 015004, 2022

    2022

  40. [48]

    Not all qubits are created equal: A case for variability-aware policies for nisq-era quantum computers,

    S. S. Tannu and M. K. Qureshi, “Not all qubits are created equal: A case for variability-aware policies for nisq-era quantum computers,” in Proceedings of the Twenty-Fourth International Conference on Archi- tectural Support for Programming Languages and Operating Systems , 20...

    2019

  41. [49]

    Classification of hybrid quantum-classical computing,

    F. Phillipson, N. Neumann, and R. Wezeman, “Classification of hybrid quantum-classical computing,” in International Conference on Computa- tional Science. Springer, 2023, pp. 18–33

    2023

  42. [50]

    Hybrid variational quantum eigensolvers: merging computational models,

    A. Chan, Z. Shi, L. Dellantonio, W. D ¨ur, and C. A. Muschik, “Hybrid variational quantum eigensolvers: merging computational models,” arXiv preprint arXiv:2305.19200, 2023

    2023 arXiv

  43. [51]

    Genetic algorithms as classical optimizer for the quantum approximate optimization algorithm,

    G. Acampora, A. Chiatto, and A. Vitiello, “Genetic algorithms as classical optimizer for the quantum approximate optimization algorithm,” Applied Soft Computing, vol. 142, p. 110296, 2023

    2023

  44. [52]

    A survey of nisq era hybrid quantum-classical machine learning research,

    G. De Luca, “A survey of nisq era hybrid quantum-classical machine learning research,” Journal of Artificial Intelligence and Technology , vol. 2, no. 1, pp. 9–15, 2022

    2022

  45. [53]

    Quantum machine learning for classical data,

    L. Wossnig, “Quantum machine learning for classical data,”arXiv preprint arXiv:2105.03684, 2021

    2021 arXiv

  46. [54]

    Q- pac: Automated detection of quantum bug-fix patterns,

    P. K. Nayak, K. V . Kher, M. B. Chandra, M. Rao, and L. Zhang, “Q- pac: Automated detection of quantum bug-fix patterns,” arXiv preprint arXiv:2311.17705, 2023

    2023 arXiv

  47. [55]

    Qiskit algorithms migration guide,

    I. Qiskit, “Qiskit algorithms migration guide,” 2021. [Online]. Available: https://qiskit .org/documentation/stable/0.28/aqua tutorials/ Qiskit%20Algorithms%20Migration%20Guide.html

    2021

  48. [56]

    Xanadu, linkedin profile,

    X. AI, “Xanadu, linkedin profile,” 2023. [Online]. Available: https://ca.linkedin.com/company/xanaduai

    2023

  49. [57]

    Not all bugs are the same: Understanding, characterizing, and classifying bug types,

    G. Catolino, F. Palomba, A. Zaidman, and F. Ferrucci, “Not all bugs are the same: Understanding, characterizing, and classifying bug types,” Journal of Systems and Software , vol. 152, pp. 165–181, 2019

    2019

  50. [58]

    Spencer, Card sorting: Designing usable categories

    D. Spencer, Card sorting: Designing usable categories . Rosenfeld Media, 2009

    2009

  51. [59]

    Optimization of function,

    “Optimization of function,” 4 2022. [Online]. Available: https: //discuss.pennylane.ai/t/optimization-of-function/1829

    2022

  52. [60]

    Failing to create a circuit for a large molecule,

    “Failing to create a circuit for a large molecule,” 7 2023. [Online]. Available: https://discuss.pennylane.ai/t/failing-to-create-a-circuit-for-a- large-molecule/3183

    2023

  53. [61]

    Pennylane-qiskit connection error,

    “Pennylane-qiskit connection error,” 9 2020. [Online]. Available: https://discuss.pennylane.ai/t/pennylane-qiskit-connection-error/571

    2020

  54. [62]

    The requested hardware device is offline for maintenance,

    “The requested hardware device is offline for maintenance,” 2

  55. [63]

    Classical algorithm to find the ground state of a hamiltonian,

    “Classical algorithm to find the ground state of a hamiltonian,” 12 2022. [Online]. Avail- able: https://discuss .pennylane.ai/t/getting-x8-photon-count-data-to- agree-with-numerical-prediction-for-beamsplitter-phase-sweep/1530/

    2022

  56. [64]

    Noisy channels with default.qubit,

    “Noisy channels with default.qubit,” 3 2021. [Online]. Available: https://discuss.pennylane.ai/t/noisy-channels-with-default-qubit/896

    2021

  57. [65]

    Issue in running the qiskit tutorial for qsvm,

    “Issue in running the qiskit tutorial for qsvm,” 4 2021. [Online]. Available: https://quantumcomputing .stackexchange.com/ questions/16800/issue-in-running-the-qiskit-tutorial-for-qsvm

    2021

  58. [66]

    Problems with forest plugin,

    “Problems with forest plugin,” 9 2020. [Online]. Available: https: //discuss.pennylane.ai/t/problems-with-forest-plugin/558

    2020

  59. [67]

    Quantum natural gradient optimizer with user-defined gates,

    “Quantum natural gradient optimizer with user-defined gates,” 4

  60. [68]

    Pennylane for quantum machine learning,

    “Pennylane for quantum machine learning,” 1 2021. [Online]. Available: https://discuss.pennylane.ai/t/pennylane-for-quantum-machine- learning/766

    2021

  61. [69]

    Different results with vqe on versions 0.26.0 and 0.27.0,

    “Different results with vqe on versions 0.26.0 and 0.27.0,” 12 2022. [Online]. Available: https://discuss .pennylane.ai/t/different-results-with- vqe-on-versions-0-26-0-and-0-27-0/2332

    2022

  62. [70]

    Available: https://discuss .pennylane.ai/t/quantum-natural- gradient-optimizer-with-user-defined-gates/1006

    [Online]. Available: https://discuss .pennylane.ai/t/quantum-natural- gradient-optimizer-with-user-defined-gates/1006

  63. [71]

    Error while converting qnode output to ndarray,

    “Error while converting qnode output to ndarray,” 4 2021. [Online]. Available: https://discuss .pennylane.ai/t/error-while-converting-qnode- output-to-ndarray/971

    2021

  64. [72]

    Api error when trying to access ibm quantum computer using ibmq api token,

    “Api error when trying to access ibm quantum computer using ibmq api token,” 2 2021. [Online]. Available: https: //quantumcomputing.stackexchange.com/questions/15910/api-error- when-trying-to-access-ibm-quantum-computer-using-ibmq-api-token

    2021

  65. [73]

    Bit flip, separable state and several question about cirq,

    “Bit flip, separable state and several question about cirq,” 10 2020. [On- line]. Available: https://quantumcomputing.stackexchange.com/questions/ 14288/bit-flip-separable-state-and-several-question-about-cirq

    2020

  66. [74]

    qiskit: Traveling salesman problem using qaoa fails for more than 3 cities,

    “qiskit: Traveling salesman problem using qaoa fails for more than 3 cities,” 10 2021. [Online]. Available: https://quantumcomputing.stackexchange.com/questions/15163/qiskit- traveling-salesman-problem-using-qaoa-fails-for-more-than-3-cities

    2021

  67. [75]

    The infeasibility of the ‘qiskit.aer’ training cost function?

    “The infeasibility of the ‘qiskit.aer’ training cost function?” 3 2023. [Online]. Available: https://discuss .pennylane.ai/t/the-infeasibility-of-the- qiskit-aer-training-cost-function/2769

    2023

  68. [76]

    How can i use density as output and build my qnn model,

    “How can i use density as output and build my qnn model,” 6 2023. [Online]. Available: https://discuss .pennylane.ai/t/how-can-i-use-density- as-output-and-build-my-qnn-model/3038

    2023

  69. [77]

    How to implement su(2) rotation with qiskit?

    “How to implement su(2) rotation with qiskit?” 5 2022. [Online]. Available: https://quantumcomputing .stackexchange.com/ questions/26548/how-to-implement-su2-rotation-with-qiskit/26572

    2022

  70. [78]

    Cv convolutional neural network,

    “Cv convolutional neural network,” 5 2020. [Online]. Available: https://discuss.pennylane.ai/t/cv-convolutional-neural-network/408

    2020

  71. [79]

    Making a one layer neural network,

    “Making a one layer neural network,” 8 2020. [Online]. Available: https://discuss.pennylane.ai/t/making-a-one-layer-neural-network/504

    2020

  72. [80]

    Is there a way to parallelize the same circuit for multiple input data?

    “Is there a way to parallelize the same circuit for multiple input data?” 2

  73. [81]

    Variational classifiers and qngoptimizer,

    “Variational classifiers and qngoptimizer,” 8 2020. [On- line]. Available: https://discuss .pennylane.ai/t/variational-classifiers- and-qngoptimizer/524

    2020

  74. [82]

    Problem on running quantumgan,

    “Problem on running quantumgan,” 10 2023. [Online]. Available: https://discuss.pennylane.ai/t/problem-on-running-quantumgan/3569

    2023

  75. [83]

    Does pennylane-sf plugin simmulate borealis,

    “Does pennylane-sf plugin simmulate borealis,” 7 2022. [Online]. Available: https://discuss .pennylane.ai/t/does-pennylane-sf- plugin-simmulate-borealis/2053

    2022

  76. [84]

    Available: https://discuss .pennylane.ai/t/is-there-a-way- to-parallelize-the-same-circuit-for-multiple-input-data/2516

    [Online]. Available: https://discuss .pennylane.ai/t/is-there-a-way- to-parallelize-the-same-circuit-for-multiple-input-data/2516

  77. [85]

    qml.mps offset control,

    “qml.mps offset control,” 4 2023. [Online]. Available: https: //discuss.pennylane.ai/t/qml-mps-offset-control/2890

    2023

  78. [86]

    Running 30 qubit highly entangled circuit,

    “Running 30 qubit highly entangled circuit,” 11 2021. [Online]. Available: https://discuss .pennylane.ai/t/running-30-qubit- highly-entangled-circuit/1474

    2021

  79. [87]

    How do bugs surface? a comprehensive study on the characteristics of software bugs manifestation,

    D. Cotroneo, R. Pietrantuono, S. Russo, and K. Trivedi, “How do bugs surface? a comprehensive study on the characteristics of software bugs manifestation,” Journal of Systems and Software , vol. 113, pp. 27–43, 2016

    2016

  80. [88]

    Pennylane 0.19 and lightning qbit,

    “Pennylane 0.19 and lightning qbit,” 11 2021. [Online]. Available: https://discuss.pennylane.ai/t/pennylane-0-19-and-lightning-qbit/1479

    2021

  81. [89]

    One wire with multi-observables,

    “One wire with multi-observables,” 5 2021. [Online]. Available: https://discuss.pennylane.ai/t/one-wire-with-multi-observables/1032/4

    2021

  82. [90]

    Bug characteristics in open source software,

    L. Tan, C. Liu, Z. Li, X. Wang, Y . Zhou, and C. Zhai, “Bug characteristics in open source software,” Empirical software engineering , vol. 19, pp. 1665–1705, 2014

    2014

  83. [92]

    A comprehensive study of real-world numerical bug characteristics,

    A. Di Franco, H. Guo, and C. Rubio-Gonz ´alez, “A comprehensive study of real-world numerical bug characteristics,” in 2017 32nd IEEE/ACM International Conference on Automated Software Engineering (ASE) . IEEE, 2017, pp. 509–519

    2017

  84. [94]

    Assessing the quality of the steps to reproduce in bug reports,

    O. Chaparro, C. Bernal-C ´ardenas, J. Lu, K. Moran, A. Marcus, M. Di Penta, D. Poshyvanyk, and V . Ng, “Assessing the quality of the steps to reproduce in bug reports,” in Proceedings of the 2019 27th ACM Joint Meeting on European Software Engineering Conference and Symposium ...

    2019

  85. [2021]

    Available: https://discuss .pennylane.ai/t/the-requested- hardware-device-is-offline-for-maintenance/798

    [Online]. Available: https://discuss .pennylane.ai/t/the-requested- hardware-device-is-offline-for-maintenance/798

  86. [2023]

    Available: https://www .nature.com/articles/d41586-023- 03854-1

    [Online]. Available: https://www .nature.com/articles/d41586-023- 03854-1

Pith tools

Reviewed August 12, 2026 · model on record in the stance chip above.