Evolving quantum circuits using genetic programming

被引:0
作者
Rubinstein, BIP [1 ]
机构
[1] Univ Melbourne, Melbourne, Vic 3052, Australia
来源
PROCEEDINGS OF THE 2001 CONGRESS ON EVOLUTIONARY COMPUTATION, VOLS 1 AND 2 | 2001年
关键词
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
This paper presents a new representation and corresponding set of genetic operators for a scheme to evolve quantum circuits with various properties. The scheme is a variant on the techniques of genetic programming and genetic algorithms, having components borrowed from each. By recognising the foundation of a quantum circuit as being a collection of gates, each operating on various categories of qubits and each taking parameters, the scheme can successfully search for most circuits. The algorithm is applied to the problem of entanglement production.
引用
收藏
页码:144 / 151
页数:8
相关论文
共 50 条
  • [21] GPCNN: Evolving Convolutional Neural Networks using Genetic Programming
    McGhie, Abigail
    Xue, Bing
    Zhang, Mengjie
    2020 IEEE SYMPOSIUM SERIES ON COMPUTATIONAL INTELLIGENCE (SSCI), 2020, : 2684 - 2691
  • [22] Evolving data classification programs using genetic parallel programming
    Cheang, SM
    Lee, KH
    Leung, KS
    CEC: 2003 CONGRESS ON EVOLUTIONARY COMPUTATION, VOLS 1-4, PROCEEDINGS, 2003, : 248 - 255
  • [23] Evolving Femtocell Coverage Optimization Algorithms using Genetic Programming
    Ho, Lester T. W.
    Ashraf, Imran
    Claussen, Holger
    2009 IEEE 20TH INTERNATIONAL SYMPOSIUM ON PERSONAL, INDOOR AND MOBILE RADIO COMMUNICATIONS, 2009, : 2132 - 2136
  • [24] Directly Evolving Classifiers for Missing Data using Genetic Programming
    Cao Truong Tran
    Zhang, Mengjie
    Andreae, Peter
    2016 IEEE CONGRESS ON EVOLUTIONARY COMPUTATION (CEC), 2016, : 5278 - 5285
  • [25] Evolving local search heuristics for SAT using genetic programming
    Fukunaga, AS
    GENETIC AND EVOLUTIONARY COMPUTATION GECCO 2004 , PT 2, PROCEEDINGS, 2004, 3103 : 483 - 494
  • [26] Evolving Parametric Models using Genetic Programming with Artificial Selection
    Harding, John
    ECAADE 2016: COMPLEXITY & SIMPLICITY, VOL 1, 2016, : 423 - 432
  • [27] Tolerance design of passive filter circuits using genetic programming
    Hou, HS
    Chang, SJ
    Su, YK
    IEICE TRANSACTIONS ON ELECTRONICS, 2005, E88C (12): : 2388 - 2390
  • [28] Evolving choice structures for genetic programming
    Wang, Shuaiqiang
    Ma, Jun
    Liu, Jiming
    Niu, Xiaofei
    INFORMATION PROCESSING LETTERS, 2010, 110 (20) : 871 - 876
  • [29] Evolving text classifiers with genetic programming
    Hirsch, L
    Saeedi, M
    Hirsch, R
    GENETIC PROGRAMMING, PROCEEDINGS, 2004, 3003 : 309 - 317
  • [30] Evolving Distributed Algorithms With Genetic Programming
    Weise, Thomas
    Tang, Ke
    IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION, 2012, 16 (02) : 242 - 265