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Classification of patterns representing Apples and Oranges in three-qubit system

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Abstract

The study of the classification of Apples and Oranges in a warehouse has been undertaken in a three-qubit system using the method of repeated iterations in Grover’s algorithm and Ventura’s algorithm separately. Operator describing an inversion about average has been constructed as a square matrix of order eight, the phase inversion operators and corresponding iteration operators for patterns separately representing Apples and Oranges have been derived, and various possible superpositions as the choice for search states for the classification of these patterns have been obtained for starting states consisting of two patterns and a single pattern, respectively. It has been demonstrated that on the second iteration of the exclusion superposition by the corresponding iteration operators, the patterns Apples and Oranges, respectively, are most suitably classified using the Grover’s algorithm. The probabilities of classifications of Apples have also been calculated by using Ventura’s algorithm (Ventura and Martinez in Inf Sci 124:273–296, 2000; Found Phys Lett 12:547–559, 1999) for all the possible superpositions as the search states, and the results have been compared with those of Grover’s algorithm and it has been demonstrated that in general for classification of a given pattern (Apples) in three-qubit system, the Grover’s and Ventura’s algorithms are effective in the cases where the number of patterns in the stored database is larger or smaller, respectively.

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References

  1. Feynman, R.P.: Simulating physics with computers. Int. Theor. Phys. 26(21), 467–488 (1982)

    Article  MathSciNet  Google Scholar 

  2. Shor, P.W.: Algorithms for quantum computation: discrete logarithm and factoring. In: Proceedings of 35th Annual Symposium, Found of Computer Science, Los. Alamitos, IEEE Comp. Press, pp. 20–22 (1994)

  3. Grover, L.K.: A fast quantum mechanical algorithm for data base search. In: Proceedings of 28th Annual ACM Symposium On Theory of Computing, Philadelphia, Pennsylvania, ACM Press, pp. 212–221 (1996)

  4. Simon, D.: On the power of quantum computation. SIAM J. Comput. 26(5), 1474–1483 (1997)

    Article  MathSciNet  MATH  Google Scholar 

  5. Ezhov, A.A., Nifanova, A.V., Ventura, Dan: Quantum associative memories with distributed queries. Inf. Sci. 128, 271–293 (2000)

    Article  MathSciNet  MATH  Google Scholar 

  6. Li, S.S., Nie, Y.Y., Hong, Z.H., Yi, X.J., Huang, Y.B.: Controlled teleportation using four-particle cluster state. Commun. Theor. Phys. 50, 633–640 (2008)

    Article  ADS  MathSciNet  Google Scholar 

  7. Huang, Y.B., Li, S.S., Nie, Y.Y.: Controlled dense coding between multi particles. Int. J. Theor. Phys. 48, 95–100 (2009)

    Article  MATH  Google Scholar 

  8. Li, S.S.: Dense coding with cluster state via local measurement. Int. J. Theor. Phys. 51, 724–730 (2012)

    Article  MathSciNet  MATH  Google Scholar 

  9. Wang, Z.S., Wu, C., Feng, X.L., Kwek, L.C., Lai, C.H., Oh, C.H., Vedral, V.: Non-adiabatic geometric quantum computation. Phys. Rev. A 76, 044303–307 (2007)

    Article  ADS  MathSciNet  Google Scholar 

  10. Wang, Z.S.: Geometric quantum computation and dynamical variable operators. Phys. Rev. A 79, 024304–308 (2009)

    Article  ADS  MathSciNet  Google Scholar 

  11. Jennewein, T., Simon, C., Weihs, G., Weinfurter, H., Zeilinger, A.: Quantum cryptography with entangled photons. Phys. Rev. Lett. 84, 4729–4732 (2000)

    Article  ADS  Google Scholar 

  12. Naik, D.S., Peterson, C.G., White, A.G., Burglund, A.J., Kwiat, P.G.: Entangled state quantum cryptography. Phys. Rev. Lett. 84, 4733–4736 (2000)

    Article  ADS  Google Scholar 

  13. Tittel, W., Bendel, J., Zbinden, H., Gisin, N.: Quantum cryptography using entangled photons in energy-time bell states. Phys. Rev. Lett. 84, 4737–4740 (2000)

    Article  ADS  Google Scholar 

  14. Tan, H.T., Zhang, W.M., Li, G.: Entangling two distant nanocavities via a waveguide. Phys. Rev. A 83, 032102–108 (2011)

    Article  ADS  Google Scholar 

  15. Singh, Manu P., Rajput, B.S.: Role of entanglement in quantum neural networks (QNN). J. Mod. Phys. 6, 1908–1920 (2015)

    Article  Google Scholar 

  16. Singh, Manu P., Rajput, B.S.: Maximally entangled states of two-qubit systems. Int. J. Theor. Phys. 52, 4237–4255 (2013)

    Article  MathSciNet  MATH  Google Scholar 

  17. Singh, Manu P., Rajput, B.S.: Applications of Singh-Rajput MES in recall operations of quantum associative memory for a two-qubit system. Int. J. Theor. Phys. 54(10), 3443–34460 (2015)

    Article  Google Scholar 

  18. Singh, Manu P., Rajput, B.S.: Processes of quantum associative memory (QuAM) through new maximally entangled states (Singh-Rajput MES). Int. J. Theor. Phys. 55(2), 124–140 (2016)

    Article  MathSciNet  Google Scholar 

  19. Singh, Manu P., Rajput, B.S.: Pattern classification in two-qubit and three-qubit systems. Euro. Phys. J. Plus 129(57), 1–13 (2014)

    Google Scholar 

  20. Singh, Manu P., Rajput, B.S.: New maximally entangled states and pattern classification. Int. J. Theor. Phys. 53(9), 3226–3238 (2014)

    Article  MATH  Google Scholar 

  21. Grover, L.K.: Quantum mechanics helps in searching for a needle in haystack. Phys. Rev. Lett. 79, 325–328 (1997)

    Article  ADS  Google Scholar 

  22. Wootters, W.K.: Entanglement of formation and concurrence. Quantum Inf. Comput. 1(1), 27–44 (2001)

    MathSciNet  MATH  Google Scholar 

  23. Ventura, D., Martinez, T.: Quantum associative Memory. Inf. Sci. 124, 273–296 (2000)

    Article  MathSciNet  Google Scholar 

  24. Ventura, D., Martinez, T.: Initializing the amplitude distribution of a quantum state. Found. Phys. Lett. 12, 547–559 (1999)

    Article  MathSciNet  Google Scholar 

  25. Arima, K., Miyajima, H., Shigei, N., Maeda, M.: Some properties of quantum data search algorithms. IN: The 23rd International Conference on Circuits/Systems, Computers and Communications (ITC-CSCC 2008)

  26. Ventura, D.: On the utility of entanglement in quantum neural computing. In: Proceedings of International Joint Conference on Neural Networks, pp. 1565–1570 (2001)

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Acknowledgements

Authors thankfully acknowledge the financial support of University Grants Commission (UGC), New Delhi (India), in the form of a major research project: MRP-Major-Comp-2013-39460. They also express their gratefulness to Prof. B.S. Rajput for useful discussion and encouragement.

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Correspondence to Kishori Radhey.

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Singh, M.P., Radhey, K., Saraswat, V.K. et al. Classification of patterns representing Apples and Oranges in three-qubit system. Quantum Inf Process 16, 16 (2017). https://doi.org/10.1007/s11128-016-1472-z

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  • DOI: https://doi.org/10.1007/s11128-016-1472-z

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