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