Implementing quantum genetic algorithms: a solution based on Grover's algorithm

ABSTRACT

This paper presents a new methodology for running Genetic Algorithms on a Quantum Computer. To the best of our knowledge and according to reference [6]there are no feasible solutions for the implementation of the Quantum Genetic Algorithms (QGAs). We present a new perspective on how to build the corresponding QGA architecture. It turns out that the genetic strategy is not particularly helpful in our quantum computation approach; therefore our solution consists of designing a special-purpose oracle that will work with a modified version of an already known algorithm (maximum finding [1]), in order to reduce the QGAs to a Grover search. Quantum computation offers incentives for this approach, due to the fact that the qubit representation of the chromosome can encode the entire population as a superposition of basis-state values.

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INDEX TERMS

Primary Classification:
  I. Computing Methodologies
  I.1 SYMBOLIC AND ALGEBRAIC MANIPULATION
      I.1.2 Algorithms
          Subjects: Analysis of algorithms

General Terms:
Algorithms, Theory

Keywords:
genetic algorithms, quantum computing