Evolutionary approach to quantum symbolic logic synthesis

Martin Lukac, Marek Perkowski

Research output: Chapter in Book/Report/Conference proceedingConference contribution

5 Citations (Scopus)

Abstract

In this paper we present an evolutionary approach to the quantum symbolic logic synthesis that was introduced in [1]. We use a Genetic Algorithm to synthesize quantum circuits from examples, allowing to synthesize functions that are both completely and incompletely specified. The symbolic synthesis is implemented in the GA so as to verify our approach. The Occam Razor principle, fundamental to inductive learning as well as to logic synthesis, is satisfied in this approach by seeking circuits of reduced complexity. The GA is tested on a set of benchmark functions representing single output quantum circuits as well as multiple entangled-qubit state generators.

Original languageEnglish
Title of host publication2008 IEEE Congress on Evolutionary Computation, CEC 2008
Pages3374-3380
Number of pages7
DOIs
Publication statusPublished - Nov 17 2008
Event2008 IEEE Congress on Evolutionary Computation, CEC 2008 - Hong Kong, China
Duration: Jun 1 2008Jun 6 2008

Publication series

Name2008 IEEE Congress on Evolutionary Computation, CEC 2008

Other

Other2008 IEEE Congress on Evolutionary Computation, CEC 2008
CountryChina
CityHong Kong
Period6/1/086/6/08

ASJC Scopus subject areas

  • Computational Theory and Mathematics
  • Theoretical Computer Science

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