Advertisement

Multi-objective Synthesis of Quantum Circuits Using Genetic Programming

  • Moein Sarvaghad-Moghaddam
  • Philipp NiemannEmail author
  • Rolf Drechsler
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11106)

Abstract

With the emergence of more and more powerful quantum computers, synthesis of quantum circuits that realize a given quantum functionality on those devices has become an important research topic. As quantum algorithms often contain a substantial Boolean component, many synthesis approaches focus on reversible circuits. While some of these methods can be applied on rather large functions, they often yield circuits that are far from being optimal. Aiming at better solutions, evolutionary algorithms can be used as possible alternatives to above methods. However, while previous work in this area clearly demonstrated the potential of this direction, it often focuses on a single optimization objective and employs cost functions that are not very well suited for quantum-technological implementations of the resulting circuits.

In this paper, we propose a framework for multi-objective synthesis of quantum circuits based on Genetic Programming that puts a focus on quantum-specific aspects and can be tuned towards several relevant/related cost metrics. A preliminary evaluation indicates that the proposed approach is competitive to previous ones. In some cases, the generated circuits even improve over existing results on all optimization objectives simultaneously, even though the latter were found by specifically targeting a single objective.

References

  1. 1.
    Abubakar, M.Y., Jung, L.T., Zakaria, N., Younes, A., Abdel-Aty, A.: Reversible circuit synthesis by genetic programming using dynamic gate libraries. Quantum Inf. Process. 16(6), 160 (2017)MathSciNetCrossRefGoogle Scholar
  2. 2.
    Baker, J.E.: Adaptive selection methods for genetic algorithms. In: International Conference on Genetic Algorithms, pp. 101–111 (1985)Google Scholar
  3. 3.
    Datta, K., Sengupta, I., Rahaman, H.: Particle swarm optimization based reversible circuit synthesis using mixed control toffoli gates. J. Low Power Electron. 9(3), 363–372 (2013)CrossRefGoogle Scholar
  4. 4.
    Kole, D.K., Rahaman, H., Das, D.K., Bhattacharya, B.B.: Optimal reversible logic circuit synthesis based on a hybrid DFS-BFS technique. In: International Symposium on Electronic System Design, pp. 208–212, December 2010Google Scholar
  5. 5.
    Koza, J.R.: Genetic Programming: On the Programming of Computers by Means of Natural Selection. MIT Press, Cambridge (1992)zbMATHGoogle Scholar
  6. 6.
    Li, M., Zheng, Y., Hsiao, M.S., Huang, C.: Reversible logic synthesis through ant colony optimization. In: DATE, pp. 307–310 (2010)Google Scholar
  7. 7.
    Lukac, M., et al.: Evolutionary approach to quantum and reversible circuits synthesis. Artif. Intell. Rev. 20(3), 361–417 (2003)MathSciNetCrossRefGoogle Scholar
  8. 8.
    Maslov, D.: Reversible logic synthesis benchmarks page (2018). http://webhome.cs.uvic.ca/~dmaslov/
  9. 9.
    Mishchenko, A., Perkowski, M.A.: Logic synthesis of reversible wave cascades. In: IWLS, pp. 197–202 (2002)Google Scholar
  10. 10.
    Nielsen, M., Chuang, I.: Quantum Computation and Quantum Information. Cambridge Univ. Press, Cambridge (2000)zbMATHGoogle Scholar
  11. 11.
    Ruican, C., Udrescu, M., Prodan, L., Vladutiu, M.: Automatic synthesis for quantum circuits using genetic algorithms. In: Beliczynski, B., Dzielinski, A., Iwanowski, M., Ribeiro, B. (eds.) ICANNGA 2007. LNCS, vol. 4431, pp. 174–183. Springer, Heidelberg (2007).  https://doi.org/10.1007/978-3-540-71618-1_20CrossRefGoogle Scholar
  12. 12.
    Saeedi, M., Zamani, M.S., Sedighi, M., Sasanian, Z.: Reversible circuit synthesis using a cycle-based approach. J. Emerg. Technol. Comput. Syst. 6(4), 13:1–13:26 (2010).  https://doi.org/10.1145/1877745.1877747. Article no 13CrossRefGoogle Scholar
  13. 13.
    Shende, V.V., Bullock, S.S., Markov, I.L.: Synthesis of quantum-logic circuits. IEEE Trans. CAD of Integr. Circ. Syst. 25(6), 1000–1010 (2006)CrossRefGoogle Scholar
  14. 14.
    Shende, V.V., Prasad, A.K., Markov, I.L., Hayes, J.P.: Synthesis of reversible logic circuits. IEEE Trans. CAD Integr. Circ. Syst. 22(6), 710–722 (2003)CrossRefGoogle Scholar
  15. 15.
    Silva, S., Almeida, J.: Gplab-a genetic programming toolbox for matlab. In: Proceedings of the Nordic MATLAB Conference (NMC-2003), pp. 273–278 (2005)Google Scholar
  16. 16.
    Wille, R., Drechsler, R.: BDD-based synthesis of reversible logic for large functions. In: DAC, pp. 270–275 (2009)Google Scholar

Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

  • Moein Sarvaghad-Moghaddam
    • 1
  • Philipp Niemann
    • 2
    • 3
    Email author
  • Rolf Drechsler
    • 2
    • 3
  1. 1.Young Researchers and Elite Club, Mashhad BranchIslamic Azad UniversityMashhadIran
  2. 2.Group of Computer ArchitectureUniversity of BremenBremenGermany
  3. 3.Cyber-Physical Systems, DFKI GmbHBremenGermany

Personalised recommendations