Skip to main content

Quantum Computing

  • Chapter
  • First Online:
Search and Optimization by Metaheuristics
  • 3389 Accesses

Abstract

Quantum computing is inspired from the theory of quantum mechanics, which describes the behavior of particles of atomic size. Quantum computing is involved with the research on quantum computers and quantum algorithms. Quantum algorithms perform exponentially faster than any of the traditional algorithms [30]. Quantum computers were proposed in the 1980s [1, 6]. This chapter introduces some basic quantum computing algorithms and quantum-based hybrid metaheuristic algorithms.

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 49.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 64.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 99.99
Price excludes VAT (USA)
  • Durable hardcover 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

References

  1. Benioff P. The computer as a physical system: a microscopic quantum mechanical Hamiltonian model of computers as represented by Turing machines. J Stat Phys. 1980;22(5):563–91.

    Article  MathSciNet  Google Scholar 

  2. Boykin PO, Mor T, Roychowdhury V, Vatan F. Algorithms on ensemble quantum computers. Natural Comput. 2010;9(2):329–45.

    Article  MathSciNet  MATH  Google Scholar 

  3. Chiang H-P, Chou Y-H, Chiu C-H, Kuo S-Y, Huang Y-M. A quantum-inspired tabu search algorithm for solving combinatorial optimization problems. Soft Comput. 2014;18:1771–81.

    Google Scholar 

  4. Chuang IL, Gershenfeld N, Kubinec M. Experimental implementation of fast quantum searching. Phys Rev Lett. 1998;80(15):3408–11.

    Article  Google Scholar 

  5. Cory DG, Fahmy AF, Havel TF. Ensemble quantum computing by nuclear magnetic resonance spectroscopy. Proc Natl Acad Sci USA. 1997;94:1634–9.

    Article  Google Scholar 

  6. Deutsch D. Quantum theory, the Church-Turing principle and the universal quantum computer. Proc Royal Soc Lond A. 1985;400(1818):97–117.

    Article  MathSciNet  MATH  Google Scholar 

  7. Deutsch D, Jozsa R. Rapid solution of problems by quantum computation. Proc Royal Soc Lond A. 1992;439(1907):553–8.

    Article  MathSciNet  MATH  Google Scholar 

  8. Gershenfeld N, Chuang IL. Bulk spin-resonance quantum computation. Science. 1997;275(5298):350–6.

    Article  MathSciNet  MATH  Google Scholar 

  9. Grover LK. Quantum mechanics helps in searching for a needle in a haystack. Phys Rev Lett. 1997;79(2):325–8.

    Article  Google Scholar 

  10. Grover LK. A fast quantum mechanical algorithm for database search. In: Proceedings of the 28th annual ACM symposium on theory of computing (STOC’96), Philadelphia, PA, USA, May 1996. New York: ACM Press; 1996. p. 212–219.

    Google Scholar 

  11. Han KH, Kim JH. Quantum-inspired evolutionary algorithm for a class of combinatorial optimization. IEEE Trans Evol Comput. 2002;6(6):580–93.

    Article  Google Scholar 

  12. Han KH, Kim JH. Quantum-inspired evolutionary algorithms with a new termination criterion, \(H_\epsilon \) gate, and two-phase scheme. IEEE Trans Evol Comput. 2004;8(2):156–69.

    Article  Google Scholar 

  13. Han KH, Kim JH. On the analysis of the quantum-inspired evolutionary algorithm with a single individual. In: Proceedings of IEEE congress on evolutionary computation (CEC), Vancouver, BC, Canada, July 2006. p. 2622–2629.

    Google Scholar 

  14. Ibrahim AA, Mohamed A, Shareef H. A novel quantum-inspired binary gravitational search algorithm in obtaining optimal power quality monitor placement. J Appl Sci. 2012;12:822–30.

    Article  Google Scholar 

  15. Jeong Y-W, Park J-B, Jang S-H, Lee KY. A new quantum-inspired binary PSO: application to unit commitment problems for power systems. IEEE Trans Power Syst. 2010;25(3):1486–95.

    Article  Google Scholar 

  16. Jiao L, Li Y, Gong M, Zhang X. Quantum-inspired immune clonal algorithm for global optimization. IEEE Trans Syst Man Cybern Part B. 2008;38(5):1234–53.

    Article  Google Scholar 

  17. Jones JA. Fast searches with nuclear magnetic resonance computers. Science. 1998;280(5361):229.

    Article  Google Scholar 

  18. Jones JA, Mosca M, Hansen RH. Implementation of a quantum search algorithm on a quantum computer. Nature. 1998;393:344–6.

    Article  Google Scholar 

  19. Kadowaki T, Nishimori H. Quantum annealing in the transverse Ising model. Phys Rev E. 1998;58:5355–63.

    Article  Google Scholar 

  20. Kwiat PG, Mitchell JR, Schwindt PDD, White AG. Grover’s search algorithm: an optical approach. J Modern Optics. 2000;47:257–66.

    Article  MathSciNet  Google Scholar 

  21. Liao G. A novel evolutionary algorithm for dynamic economic dispatch with energy saving and emission reduction in power system integrated wind power. Energy. 2011;36:1018–29.

    Article  Google Scholar 

  22. Meng K, Wang HG, Dong ZY, Wong KP. Quantum-inspired particle swarm optimization for valve-point economic load dispatch. IEEE Trans Power Syst. 2010;25(1):215–22.

    Article  Google Scholar 

  23. Montiel O, Rivera A, Sepulveda R. Design and acceleration of a quantum genetic algorithm through the Matlab GPU library. In: Design of intelligent systems based on fuzzy logic, neural networks and nature-inspired optimization, vol. 601 of Studies in Computational Intelligence. Berlin: Springer; 2015. p. 333–345.

    Google Scholar 

  24. Narayanan A, Moore M. Quantum-inspired genetic algorithms. In: Proceedings of IEEE international conference on evolutionary computation, Nogaya, Japan, May 1996. p. 61–66.

    Google Scholar 

  25. Nezamabadi-pour H. A quantum-inspired gravitational search algorithm for binary encoded optimization problems. Eng Appl Artif Intell. 2015;40:62–75.

    Article  Google Scholar 

  26. Nielsen MA, Knill E, Laflamme R. Complete quantum teleportation using nuclear magnetic resonance. Nature. 1998;396:52–5.

    Article  Google Scholar 

  27. Platel MD, Schliebs S, Kasabov N. A versatile quantum-inspired evolutionary algorithm. In: Proceedings of IEEE congress on evolutionary computation (CEC), Singapore, Sept 2007. p. 423–430.

    Google Scholar 

  28. Platel MD, Schliebs S, Kasabov N. Quantum-inspired evolutionary algorithm: a multimodel EDA. IEEE Tran Evol Comput. 2009;13(6):1218–32.

    Article  Google Scholar 

  29. Shor PW. Algorithms for quantum computation: discrete logarithms and factoring. In: Proceedings of the 35th annual symposium on foundations of computer science, Sante Fe, NM, USA, Nov 1994. pp. 124–134.

    Google Scholar 

  30. Shor PW. Polynomial-time algorithms for prime factorization and discrete logarithms on a quantum computer. SIAM J Comput. 1997;26:1484–509.

    Article  MathSciNet  MATH  Google Scholar 

  31. Soleimanpour-moghadam M, Nezamabadi-pour H, Farsangi MM. A quantum-inspired gravitational search algorithm fornumerical function optimization. Inf Sci. 2014;276:83–100.

    Article  MathSciNet  MATH  Google Scholar 

  32. Sun J, Feng B, Xu WB. Particle swarm optimization with particles having quantum behavior. In: Proceedings of IEEE congress on evolutionary computation (CEC), Portland, OR, USA, June 2004. p. 325–331.

    Google Scholar 

  33. Vandersypen LMK, Steffen M, Breyta G, Yannoni CS, Sherwood MH, Chuang IL. Experimental realization of Shor’s quantum factoring algorithm using nuclear magnetic resonance. Nature. 2001;414(6866):883–7.

    Article  Google Scholar 

  34. Vlachogiannis JG, Ostergaard J. Reactive power and voltage control based on general quantum genetic algorithms. Expert Syst Appl. 2009;36:6118–26.

    Article  Google Scholar 

  35. Yang S, Wang M, Jiao L. A genetic algorithm based on quantum chromosome. In: Proceedings of the 7th international conference on signal processing, Beijing, China, Aug 2004. p. 1622–1625.

    Google Scholar 

  36. Zhang G, Jin W, Hu L. A novel parallel quantum genetic algorithm. In: Proceedings of the 4th international conference on parallel and distributed computing, applications and technologies, Chengdu, China, Aug 2003. p. 693–697.

    Google Scholar 

  37. Zhang GX, Rong HN. Real-observation quantum-inspired evolutionary algorithm for a class of numerical optimization problems. In: Proceedings of the 7th international conference on computational science, Beijing, China, May 2007, vol. 4490 of Lecture Notes in Computer Science. Berlin: Springer; 2007. p. 989–996.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Ke-Lin Du .

Rights and permissions

Reprints and permissions

Copyright information

© 2016 Springer International Publishing Switzerland

About this chapter

Cite this chapter

Du, KL., Swamy, M.N.S. (2016). Quantum Computing. In: Search and Optimization by Metaheuristics. Birkhäuser, Cham. https://doi.org/10.1007/978-3-319-41192-7_17

Download citation

Publish with us

Policies and ethics