Status: Valid
Owner: ----
Labels: Type-Enhancement Quantum
New issue 3252 by [email protected]: Quantum Circuit Optimization with
Genetic Algorithms
http://code.google.com/p/sympy/issues/detail?id=3252
Genetic algorithms have been gaining attention as an approach to generating
new quantum algorithms. Historically, genetic algorithms were effective
solutions to optimization problems, and theoretically, the idea can be
extended to optimizing circuits, classical or quantum. The qcevolve module
is an attempt at testing this hypothesis. Using a set of known circuit
identities (obtained using the utilities in the identitysearch module),
genetic algorithms can perform random mutations on an arbitrary circuit and
presumably arrive at a maximally optimal circuit. These mutations can be
identity insertions, removals, replacements, or any operator the
experimentalist wishes to define. At the moment, the module plans to use
the Pyevolve engine to run the genetic algorithms.
References: http://arxiv.org/pdf/0708.3278v1.pdf
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