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.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Notes
- 1.
This method acts as if a roulette with random pointers is spun, and each individual owns a portion of the roulette which corresponds to its expected number of children.
References
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)
Baker, J.E.: Adaptive selection methods for genetic algorithms. In: International Conference on Genetic Algorithms, pp. 101–111 (1985)
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)
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 2010
Koza, J.R.: Genetic Programming: On the Programming of Computers by Means of Natural Selection. MIT Press, Cambridge (1992)
Li, M., Zheng, Y., Hsiao, M.S., Huang, C.: Reversible logic synthesis through ant colony optimization. In: DATE, pp. 307–310 (2010)
Lukac, M., et al.: Evolutionary approach to quantum and reversible circuits synthesis. Artif. Intell. Rev. 20(3), 361–417 (2003)
Maslov, D.: Reversible logic synthesis benchmarks page (2018). http://webhome.cs.uvic.ca/~dmaslov/
Mishchenko, A., Perkowski, M.A.: Logic synthesis of reversible wave cascades. In: IWLS, pp. 197–202 (2002)
Nielsen, M., Chuang, I.: Quantum Computation and Quantum Information. Cambridge Univ. Press, Cambridge (2000)
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_20
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 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)
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)
Silva, S., Almeida, J.: Gplab-a genetic programming toolbox for matlab. In: Proceedings of the Nordic MATLAB Conference (NMC-2003), pp. 273–278 (2005)
Wille, R., Drechsler, R.: BDD-based synthesis of reversible logic for large functions. In: DAC, pp. 270–275 (2009)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2018 Springer Nature Switzerland AG
About this paper
Cite this paper
Sarvaghad-Moghaddam, M., Niemann, P., Drechsler, R. (2018). Multi-objective Synthesis of Quantum Circuits Using Genetic Programming. In: Kari, J., Ulidowski, I. (eds) Reversible Computation. RC 2018. Lecture Notes in Computer Science(), vol 11106. Springer, Cham. https://doi.org/10.1007/978-3-319-99498-7_15
Download citation
DOI: https://doi.org/10.1007/978-3-319-99498-7_15
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-99497-0
Online ISBN: 978-3-319-99498-7
eBook Packages: Computer ScienceComputer Science (R0)