Abstract
Because in IBM’s quantum computers, they only provide quantum gates of single quantum bit and two quantum bits, quantum gates of three quantum bits and many quantum bits must manually be decomposed into quantum gates of single quantum bit and two quantum bits. A good quantum algorithm of solving any given problem with the size of the input of n bits must have a constant successful probability of measuring its answer(s) that is close to one as soon as possible. In this chapter, we first illustrate how to decompose quantum gates of three quantum bits and many quantum bits into quantum gates of single quantum bit and two quantum bits. Next, we introduce how to write quantum programs with version 2.0 of Open QASM to implement decomposition among various kinds of quantum gates. A quantum search algorithm that is sometimes known as Grover’s algorithm to find an item in unsorted databases with 2n items that satisfies any given condition can give a quadratic speed-up and is the best one known. Hence, we then describe how to write quantum programs with version 2.0 of Open QASM to implement the quantum search algorithm in order to solve various applications.
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References
Chang, W.-L., Ren, T.-T., Luo, J.n., Feng, M., Guo, M., Lin, K.W.: Quantum algorithms for bio-molecular solutions of the satisfiability problem on a quantum machine. IEEE Trans. Nanobiosci. 7(3), 215–222 (2008)
Chang, W.-L., Yu, Q., Li, Z., Chen, J., Peng, X., Feng, M.: Quantum speedup in solving the maximal-clique problem. Phys. Rev. A 97, 032344 (2018)
Coles, P.J., Eidenbenz, S., Pakin, S., Adedoyin, A., Ambrosiano, J., Anisimov, P., Casper, W., Chennupati, G., Coffrin, C., Djidjev, H., Gunter, D., Karra, S., Lemons, N., Lin, S., Lokhov, A., Malyzhenkov, A., Mascarenas, D., Mniszewski, S., Nadiga, B., O’Malley, D., Oyen, D., Prasad, L., Roberts, R., Romero, P., Santhi, N., Sinitsyn, N., Swart, P., Vuffray, M., Wendelberger, J., Yoon, B., Zamora, R., Zhu, W.: Quantum algorithm implementations for beginners (2018). https://arxiv.org/abs/1804.03719
Cook, S.: The complexity of theorem proving procedures. In: Proceedings of Third Annual ACM Symposium on Theory of Computing, pp. 151–158 (1971)
Garey, M.R., Johnson, D.S.: Computer and Intractability: A Guide to the Theory of NP-Completeness. W. H. Freeman Company (1979). ISBN-13: 978-0716710448
Grover, L.K.: A fast quantum mechanical algorithm for database search. In: Proceedings of the Twenty-Eighth Annual ACM Symposium on Theory of Computing, pp. 212–219 (1996)
Imre, S., Balazs, F.: Quantum Computation and Communications: An Engineering Approach. Wiley, UK (2007). ISBN-10: 047086902X and ISBN-13: 978-0470869024, 2005
Karp, R.: On the computational complexity of combinatorial problems. Networks 5(45), 68 (1975)
Lipton, R.J., Regan, K.W.: Quantum Algorithms via Linear Algebra: A Primer. The MIT Press (2014). ISBN 978-0-262-02839-4
Mandviwalla, A., Ohshiro, K. Ji, B.: Implementing Grover’s algorithm on the IBM quantum computers. In: 2018 IEEE International Conference on Big Data (Big Data), pp. 1–7 (2018). https://doi.org/10.1109/bigdata.2018.8622457
Nielsen, M.A., Chuang, I.L.: Quantum Computation and Quantum Information. Cambridge University Press, New York, NY (2000). ISBN-10: 9781107002173 and ISBN-13: 978-1107002173
Silva, V.: Practical Quantum Computing for Developers: Programming Quantum Rigs in the Cloud using Python, Quantum Assembly Language and IBM Q Experience. Apress, December 13, 2018. ISBN-10: 1484242173 and ISBN-13: 978-1484242179
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Chang, WL., Vasilakos, A.V. (2021). Quantum Search Algorithm and Its Applications. In: Fundamentals of Quantum Programming in IBM's Quantum Computers. Studies in Big Data, vol 81. Springer, Cham. https://doi.org/10.1007/978-3-030-63583-1_3
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DOI: https://doi.org/10.1007/978-3-030-63583-1_3
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