Multi-objective design of quantum circuits using genetic programming
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- @Misc{Sarvaghad-Moghaddam:2016:ArXiv,
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author = "Moein Sarvaghad-Moghaddam",
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title = "Multi-objective design of quantum circuits using
genetic programming",
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howpublished = "ArXiv",
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year = "2016",
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keywords = "genetic algorithms, genetic programming",
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bibdate = "2016-05-02",
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bibsource = "DBLP,
http://dblp.uni-trier.de/db/journals/corr/corr1604.html#Sarvaghad-Moghaddam16",
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URL = "http://arxiv.org/abs/1604.00642",
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abstract = "Quantum computing is a new way of data processing
based on the concept of quantum mechanics. Quantum
circuit design is a process of converting a quantum
gate to a series of basic gates and is divided into two
general categories based on the decomposition and
composition. In the second group, using evolutionary
algorithms and especially genetic algorithms,
multiplication of matrix gates was used to achieve the
final characteristic of quantum circuit. Genetic
programming is a subfield of evolutionary computing in
which computer programs evolve to solve studied
problems. In past research that has been done in the
field of quantum circuits design, only one cost metrics
(usually quantum cost) has been investigated. In this
paper for the first time, a multi-objective approach
has been provided to design quantum circuits using
genetic programming that considers the depth and the
cost of nearest neighbour metrics in addition to
quantum cost metric. Another innovation of this article
is the use of two-step fitness function and taking into
account the equivalence of global phase in quantum
gates. The results show that the proposed method is
able to find a good answer in a short time.",
- }
Genetic Programming entries for
Moein Sarvaghad-Moghaddam
Citations