Approximate Quantum Adders with Genetic Algorithms: An IBM Quantum Experience

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@Article{Li:2017:QMQM,
  author =       "Rui Li and Unai Alvarez-Rodriguez and Lucas Lamata and 
                 Enrique Solano",
  title =        "Approximate Quantum Adders with Genetic Algorithms: An
                 {IBM} Quantum Experience",
  journal =      "Quantum Measurements and Quantum Metrology",
  year =         "2017",
  volume =       "4",
  number =       "1",
  pages =        "1--7",
  keywords =     "genetic algorithms, genetic programming, Quantum
                 Information, Quantum Algorithms",
  URL =          "https://arxiv.org/pdf/1611.07851",
  URL =          "https://www.degruyter.com/view/j/qmetro.2017.4.issue-1/qmetro-2017-0001/qmetro-2017-0001.xml",
  DOI =          "doi:10.1515/qmetro-2017-0001",
  size =         "7 pages",
  abstract =     "It has been proven that quantum adders are forbidden
                 by the laws of quantum mechanics. We analyse
                 theoretical proposals for the implementation of
                 approximate quantum adders and optimize them by means
                 of genetic algorithms, improving previous protocols in
                 terms of efficiency and fidelity. Furthermore, we
                 experimentally realize a suitable approximate quantum
                 adder with the cloud quantum computing facilities
                 provided by IBM Quantum Experience. The development of
                 approximate quantum adders enhances the toolbox of
                 quantum information protocols, paving the way for novel
                 applications in quantum technologies.",
}

Genetic Programming entries for Rui Li Unai Alvarez-Rodriguez Lucas Lamata Enrique Solano

Citations