Evolving blackbox quantum algorithms using genetic programming

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@Article{DBLP:journals/aiedam/StadelhoferBS08,

• author = "Ralf Stadelhofer and Wolfgang Banzhaf and Dieter Suter",
• title = "Evolving blackbox quantum algorithms using genetic programming",
• journal = "Artificial Intelligence for Engineering Design, Analysis and Manufacturing",
• volume = "22",
• number = "3",
• year = "2008",
• pages = "285--297",
• DOI = "doi:10.1017/S089006040800019X",
• bibsource = "DBLP, http://dblp.uni-trier.de",
• keywords = "genetic algorithms, genetic programming, Quantum Computation, Quantum Information Processing",
• size = "13 pages",
• abstract = "Although it is known that quantum computers can solve certain computational problems exponentially faster than classical computers, only a small number of quantum algorithms have been developed so far. Designing such algorithms is complicated by the rather nonintuitive character of quantum physics. In this paper we present a genetic programming system that uses some new techniques to develop and improve quantum algorithms. We have used this system to develop two formerly unknown quantum algorithms. We also address a potential deficiency of the quantum decision tree model used to prove lower bounds on the query complexity of the parity problem.",

}

Genetic Programming entries for Ralf Stadelhofer Wolfgang Banzhaf Dieter Suter

Citations