Skip to main content

Towards a Set of Metrics for Quantum Circuits Understandability

  • Conference paper
  • First Online:
Book cover Quality of Information and Communications Technology (QUATIC 2021)

Abstract

Quantum computing is the basis of a new revolution. Several quantum computers are already available and, with them, quantum programming languages, quantum software development kits and platforms, quantum error correction and optimization tools are proposed and presented continuously. In connection with this, disciplines such as the Quantum Software Engineering are appearing for applying the knowledge acquired through time in their corresponding classical relatives. Besides, measurement is well known as a key factor for assessing, and improving if needed, the quality of any model in terms of, for instance, its understandability. The easier to understand a model is, the easier to maintain, reuse, etc. In this work, we present the definition of a set of metrics for assessing the understandability of quantum circuits. Some examples of the calculation of the metrics are also presented. This is just the beginning of a more thorough process in which they will be empirically validated by the performance of empirical studies, especially experiments.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 99.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 129.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Notes

  1. 1.

    https://algassert.com/quirk.

  2. 2.

    https://qiskit.org/.

  3. 3.

    https://www.forbes.com/sites/moorinsights/2019/11/23/quantum-volume-a-yardstick-to-measure-the-power-of-quantum-computers/?sh=1b74bacd5bf4.

  4. 4.

    Other is referred to any other single-qubit gate which is not any of the Pauli nor a Hadamard gate.

References

  1. Abhijith, J., et al.: Quantum algorithm implementations for beginners. arXiv:1804.03719v2 (2020)

  2. Allouche, C., Baboulin, M., Goubault de Brugière, T., Valiron, B.: Reuse Method for Quantum Circuit Synthesis. In: Kilgour, D.M., Kunze, H., Makarov, R., Melnik, R., Wang, Xu. (eds.) AMMCS 2017. SPMS, vol. 259, pp. 3–12. Springer, Cham (2018). https://doi.org/10.1007/978-3-319-99719-3_1

    Chapter  Google Scholar 

  3. Ayral, T., Le Régent, F., Saleem, Z., Alexeev, Y., Suchara, M. Quantum divide and compute: hardware demonstrations and noisy simulations. arXiv:2005.12874v1 (2020)

  4. Azad, U., Papneja, A., Saini, R., Behera, B., Panigrahi, P.: Circuit centric quantum architecture design. IET Quantum Commun. 2, 14–25 (2021)

    Article  Google Scholar 

  5. Bishop, L., Bravyi, S., Cross, A., Gambetta, J., Smolin, J. Quantum volume. https://storageconsortium.de/content/sites/default/files/quantum-volumehp08co1vbo0cc8fr.pdf. Accessed 14 May 2021

  6. Bu, K., Koh, D., Li, L., Luo, Q., Zhang, Y.: Effects of quantum resources on the statistical complexity of quantum circuits. arXiv:2102.03282 (2021)

  7. Burgholzer, L., Wille, R., Advanced equivalence checking for quantum circuits. IEEE Trans. Comput.-Aided Des. Integr. Circuits Syst. (2020). https://doi.org/10.1109/TCAD.2020.3032630

  8. Chaudhuri, A., Sultana, M., Sengupta, D., Chaudhuri, A.: A novel reversible two's complement gate (TCG) and its quantum mapping. In: Devices for Integrated Circuit (DevIC), 252–256. Kalyani, India (2017)

    Google Scholar 

  9. Cruz-Lemus, J., Maes, A., Genero, M., Poels, G., Piattini, M.: The impact of structural complexity on the understandability of UML statechart diagrams. Inf. Sci. 180(11), 2209–2220 (2010)

    Article  MathSciNet  Google Scholar 

  10. Deutsch, D.: Quantum computational networks. Proc. R. Soc. Lond. A425, 73–90 (1989)

    MathSciNet  MATH  Google Scholar 

  11. Garhwal, S., Ghorani, M., Ahmad, A.: Quantum programming language: a systematic review of research topic and top cited languages. Arch. Comput. Methods Eng. 28, 289–310 (2021)

    Article  MathSciNet  Google Scholar 

  12. Genero, M., Piattini, M., Calero, C.: A survey of metrics for UML class diagrams. J. Object Technol. 4(9), 59–92 (2005)

    Article  Google Scholar 

  13. Genero, M., Manso, M., Visaggio, C., Canfora, G., Piattini, M.: Building measure-based prediction models for UML class maintainability. Empir. Softw. Eng. 12(5), 517–549 (2007)

    Article  Google Scholar 

  14. Genero, M., Piattini, M., Chaudron, M.: Quality of UML models. Inf. Softw. Technol. 51(12), 1629–1630 (2009)

    Article  Google Scholar 

  15. Green, A., Lumsdaine, P., Ross, N., Selinger, P., Valiron, B.: Quipper: a scalable quantum programming language. ACM SIGPLAN Not. 48(6), 333–342 (2013)

    Article  Google Scholar 

  16. Gyongyosi, L., Imre, S. Optimizing high-efficiency quantum memory with quantum machine learning for near-term quantum devices. Sci. Rep. 10, 135 (2020)

    Google Scholar 

  17. Haug, T., Bharti, K., Kim, M. Capacity and quantum geometry of parametrized quantum circuits. arXiv:2102.01659v1 (2021)

  18. Humble, T., Thapiliyal, H., Muñoz-Correas, E., Mohiyaddin, F., Bennink, R.: Quantum computing circuits and devices. IEEE Des. Test 36(3), 69–94 (2019)

    Article  Google Scholar 

  19. LaRose, R. (2019). Overview and comparison of gate level quantum software platforms. Quantum 3, 130. arXiv:1807.02500v2 (2019)

  20. Maslov, D., Miller, M.: Comparison of the cost metrics for reversible and quantum logic synthesis. IET Comput. Digital Tech. 1(2), 98–104 (2007)

    Article  Google Scholar 

  21. Miller, S.: Quantum resource counts for operations constructed from an addition circuit. In: 2020 IEEE Computer Society Annual Symposium on VLSI (ISVLSI), 141–146. Limassol, Cyprus (2020)

    Google Scholar 

  22. Mosca, M., Roetteler, M., Selinger, P.: Quantum programming languages (Dagstuhl Seminar 10381). Dagstuhl Rep. 8, 112–132 (2018)

    Google Scholar 

  23. Nelson, H., Poels, G., Genero, M., Piattini, M.: Quality in conceptual modeling: five examples of the state of the art. Data Knowl. Eng. 55(3), 237–242 (2005)

    Article  Google Scholar 

  24. Nielsen, M., Chuang, L.: Quantum Computation and Quantum Information. Cambridge University Press, UK (2010)

    Book  Google Scholar 

  25. Oumarou, O., Paler A., Basmadjian, R.: QUANTIFY: a framework for resource analysis and design verification of quantum circuits. In: 2020 IEEE Computer Society Annual Symposium on VLSI (ISVLSI), 126–131, Limassol, Cyprus. (2020)

    Google Scholar 

  26. Pérez-Delgado, C., Perez-Gonzalez, H.: Towards a quantum software modeling language. In: First International Workshop on Quantum Software Engineering (Q-SE 2020), 442–444 (2020)

    Google Scholar 

  27. Piattini, M., Peterssen, G., Pérez-Castillo, R.: Quantum Computing: a new Software Engineering Golden Age. ACM SIGSOFT Softw. Eng. Newsl. 45(3), 12–14 (2020)

    Article  Google Scholar 

  28. Piattini, M., et al.: The talavera manifesto for quantum software engineering and programming. In: 1st International Workshop on the Quantum Software Engineering and Programming (QANSWER 2020), 11–12. Talavera de la Reina, Spain (2020)

    Google Scholar 

  29. Piattini, M., Serrano, M., Pérez-Castillo, R., Peterssen, G., Hevia, J.: Toward a quantum software engineering. IT Prof. 23(1), 62–66 (2021)

    Article  Google Scholar 

  30. Rieffel, E., Polak, W.: Quantum computing: a gentle introduction. The MIT Press (2011)

    Google Scholar 

  31. Serrano, M., Trujillo, J., Calero, C., Piattini, M.: Metrics for data warehouse conceptual models understandability. Inf. Softw. Technol. 49(8), 851–870 (2007)

    Article  Google Scholar 

  32. Sicilia, M.-A., Sánchez-Alonso, S., Mora-Cantallops, M., García-Barriocanal, E.: On the source code structure of quantum code: insights from Q# and QDK. In: Shepperd, M., Brito e Abreu, F., Rodrigues da Silva, A., Pérez-Castillo, R. (eds.) QUATIC 2020. CCIS, vol. 1266, pp. 292–299. Springer, Cham (2020). https://doi.org/10.1007/978-3-030-58793-2_24

    Chapter  Google Scholar 

  33. Thapliyal, H., Muñoz-Coreas, E.: Design of quantum computing circuits. IT Prof. 21(6), 22–26 (2019)

    Article  Google Scholar 

  34. Yao, A.: Quantum circuit complexity. In: Proceedings of the 34th Annual IEEE Symposium on Foundations of Computer Science, 352–361. Palo Alto, USA (1993)

    Google Scholar 

  35. Zhao, J.: Quantum software engineering. Landscapes and Horizons. arXiv:2007.07047v1 (2020)

  36. Zhao, J.: Some size and structure metrics for quantum software. In: Second International Workshop on Quantum Software Engineering (Q-SE 2021) co-located with ICSE 2021. Madrid, Spain. arXiv:2103.08815v1 (2021)

Download references

Acknowledgments

We would like to thank all the aQuantum members, especially Guido Peterssen and Pepe Hevia, for their help and support. This work was partially funded by the “QHealth: Quantum Pharmacogenomics Applied to Aging” project, part of the 2020 CDTI Missions Program (Center for the Development of Industrial Technology of the Ministry of Science and Innovation of Spain) and the GEMA and TESTIMO projects, funded by “Consejería de Educación, Cultura y Deportes de la Junta de Comunidades de Castilla La Mancha” and “Fondo Europeo de Desarrollo Regional FEDER” under Grants SBPLY/17/180501/000293 (GEMA) and SBPLY/17/180501/000503 (TESTIMO).

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to José A. Cruz-Lemus .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2021 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Cruz-Lemus, J.A., Marcelo, L.A., Piattini, M. (2021). Towards a Set of Metrics for Quantum Circuits Understandability. In: Paiva, A.C.R., Cavalli, A.R., Ventura Martins, P., Pérez-Castillo, R. (eds) Quality of Information and Communications Technology. QUATIC 2021. Communications in Computer and Information Science, vol 1439. Springer, Cham. https://doi.org/10.1007/978-3-030-85347-1_18

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-85347-1_18

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-85346-4

  • Online ISBN: 978-3-030-85347-1

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics