skip to main content
10.1145/3573428.3573520acmotherconferencesArticle/Chapter ViewAbstractPublication PageseitceConference Proceedingsconference-collections
research-article

Circuit Simulation and Optimization of Quantum Search Algorithm

Authors Info & Claims
Published:15 March 2023Publication History

ABSTRACT

At present, the scale of quantum computers in the real sense is still small, and quantum simulation has become one of the important ways of quantum theory research, grover quantum search algorithm is suitable for the search problem of disordered database. Firstly, according to the implementation principle of Grover algorithm and Boolean logic relationship, the design idea of multi-objective Oracle is analyzed, based on IBMQ quantum cloud platform, the quantum circuit of Grover algorithm with multi-objective items is simulated. Based on the characteristics of Grover algorithm and the simulation process of quantum gate, the action of multiple identical quantum gates is combined to reduce the update times of probability amplitude and improve the simulation efficiency. The libquantum quantum simulator is used for experiments and the target item is successfully searched, which proves the feasibility of the optimization method and provides reference for the simulation and optimization of other quantum algorithms.

References

  1. Zhang Yi, Lu Kai, Gao Yinhui. Quantum Algorithms and Quantum-Inspired Algorithms [J]. Journal of Computers, 2013, 36 (09): 1835-1842.Google ScholarGoogle Scholar
  2. Grover L K. A fast quantum mechanical algorithm for database search [C] // Proceedings 28th ACM Symposium on Theory of Computation. New York, 1996: 212-219.Google ScholarGoogle Scholar
  3. Guo Guagncan. Research status and future of quantum information technology[J]. Science in China: Information Science, 2020, 50 (09):1395-1406.Google ScholarGoogle Scholar
  4. Deutsch, D. Quantum theory, the Church-Turing principle and the universal quantum computer [J]. Proceedings of the Royal Society of London, 1985, 400 (1818): 97–117.Google ScholarGoogle Scholar
  5. Alexander Smith, Khashayar Khavari. Quantum Computer Simulation Using CUDA [EB/OL]. http://www.eecg.toronto.edu/∼moshovos/CUDA08/arx/QFT_report.pdf, 2009.Google ScholarGoogle Scholar
  6. Zhang Kun Implementation of efficient quantum search algorithms on NISQ computers [J]. Quantum Information Processing, 2021, 20 (7): 1-27.Google ScholarGoogle Scholar
  7. Gyongyosi L, Imre S. A survey on quantum computing technology [J]. Computer Science Review, 2019, 31: 51-71.Google ScholarGoogle ScholarDigital LibraryDigital Library
  8. Nielsen M A, Chuang I L. Quantum Computation and Quantum Information [M]. British: Cambridge Universith Press, 2000. 240-243.Google ScholarGoogle Scholar
  9. Salas P J. Noise effect on Grover algorithm [J]. The European Physical Journal D, 2008, 46 (2): 365-373.Google ScholarGoogle ScholarCross RefCross Ref
  10. Li D F, Li X X, Huang H T. Phase condition for the Grover algorithm [J]. Theoretical and mathematical physics, 2005, 144 (3):1279-1287.Google ScholarGoogle Scholar
  11. Luan L, Wang Z, Liu S. Progress of Grover Quantum Search Algorithm [J]. Energy Procedia, 2012, 16 (part-PC): 1701-1706.Google ScholarGoogle ScholarCross RefCross Ref
  12. Song Huichao, Liu Xiaonan, Wang Hong, Integer decomposition based on Grover search algorithm [J]. computer science, 2021, 48 (04): 20-25.Google ScholarGoogle Scholar
  13. Buksman E, Oliveira A L, Allende C. Performance and error modeling of Deutsch's algorithm in IBM Q [J]. Revista mexicana de fisica, 2020, 66 (2): 239-245.Google ScholarGoogle Scholar
  14. Sun Xiaoming, A review of some advances in quantum computing [J]. Science in China: Information Science, 2016, 46 (08): 982-1002.Google ScholarGoogle Scholar
  15. Raedt K D, Michielsen K, Raedt H D, Massively parallel quantum computer simulator [J]. Computer Physics Communications, 2007, 176 (2): 121-136.Google ScholarGoogle ScholarCross RefCross Ref
  16. Regan K, Chakrabarti A, Guan C. Algebraic and logical emulations of quantum circuits [M]// Transactions on Computational Science XXXI. Springer, Berlin, Heidelberg, 2018: 41-76.Google ScholarGoogle Scholar

Recommendations

Comments

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Sign in
  • Published in

    cover image ACM Other conferences
    EITCE '22: Proceedings of the 2022 6th International Conference on Electronic Information Technology and Computer Engineering
    October 2022
    1999 pages
    ISBN:9781450397148
    DOI:10.1145/3573428

    Copyright © 2022 ACM

    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

    Publisher

    Association for Computing Machinery

    New York, NY, United States

    Publication History

    • Published: 15 March 2023

    Permissions

    Request permissions about this article.

    Request Permissions

    Check for updates

    Qualifiers

    • research-article
    • Research
    • Refereed limited

    Acceptance Rates

    Overall Acceptance Rate508of972submissions,52%
  • Article Metrics

    • Downloads (Last 12 months)23
    • Downloads (Last 6 weeks)2

    Other Metrics

PDF Format

View or Download as a PDF file.

PDF

eReader

View online with eReader.

eReader

HTML Format

View this article in HTML Format .

View HTML Format