Evolutionary approach to quantum symbolic logic synthesis

Martin Lukac, Marek Perkowski

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

5 Citations (Scopus)


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
Number of pages7
Publication statusPublished - 2008 Nov 17
Event2008 IEEE Congress on Evolutionary Computation, CEC 2008 - Hong Kong, China
Duration: 2008 Jun 12008 Jun 6


Other2008 IEEE Congress on Evolutionary Computation, CEC 2008
CityHong Kong

ASJC Scopus subject areas

  • Computational Theory and Mathematics
  • Theoretical Computer Science


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