Evolving Quantum Oracles with Hybrid Quantum-inspired Evolutionary Algorithm

Created by W.Langdon from gp-bibliography.bib Revision:1.3973

@Misc{arXiv:quant-ph/0610105,
  author =       "Shengchao Ding and Zhi Jin and Qing Yang",
  title =        "Evolving Quantum Oracles with Hybrid Quantum-inspired
                 Evolutionary Algorithm",
  howpublished = "arXiv",
  year =         "2008",
  month =        "13 " # oct,
  note =         "arXiv:quant-ph/0610105 v1",
  keywords =     "genetic algorithms, genetic programming",
  URL =          "http://arxiv.org/PS_cache/quant-ph/pdf/0610/0610105v1.pdf",
  size =         "9 pages",
  abstract =     "Quantum oracles play key roles in the studies of
                 quantum computation and quantum information. But
                 implementing quantum oracles efficiently with universal
                 quantum gates is a hard work. Motivated by genetic
                 programming, this paper proposes a novel approach to
                 evolve quantum oracles with a hybrid quantum-inspired
                 evolutionary algorithm. The approach codes quantum
                 circuits with numerical values and combines the cost
                 and correctness of quantum circuits into the fitness
                 function. To speed up the calculation of matrix
                 multiplication in the evaluation of individuals, a fast
                 algorithm of matrix multiplication with Kronecker
                 product is also presented. The experiments show the
                 validity and the effects of some parameters of the
                 presented approach. And some characteristics of the
                 novel approach are discussed too.",
  notes =        "1 Institute of Computing Technology, Chinese Academy
                 of Sciences 2 Academy of Mathematics and Systems
                 Science, Chinese Academy of Sciences 3 Graduate
                 University of the Chinese Academy of Sciences Beijing
                 100080, China 4 School of Computer Science and
                 Technology, South-Central University for Nationalities,
                 Wuhan 430074, China",
}

Genetic Programming entries for Shengchao Ding Zhi Jin Qing Yang

Citations