Quantum Encoded Quantum Evolutionary Algorithm for the Design of Quantum Circuits

Georgiy Krylov, Martin Lukac

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

Abstract

In this paper we present Quanrum Encoded Quantum Evolutionary Algorithm (QEQEA) and compare its performance against a a classical GPU accelerated Genetic Algorithm (GPUGA). The proposed QEQEA differs from existing quantum evolutionary algorithms in several points: Representation of candidates circuits is using qubits and qutrits and the proposed evolutionary operators can theoretically be implemented on quantum computer provided a classical control exists. The synthesized circuits are obtained by a set of measurements performed on the encoding units of quantum representation. Both algorithms are accelerated using (general purpose graphic processing unit) GPGPU. The main target of this paper is not to propose a completely novel quantum genetic algorithm but to rather experimentally estimate the advantages of certain components of genetic algorithm being encoded and implemented in a quantum compatible manner. The algorithms are compared and evaluated on several reversible and quantum circuits. The results demonstrate that on one hand the quantum encoding and quantum implementation compatible implementation provides certain disadvantages with respect to the classical evolutionary computation. On the other hand, encoding certain components in a quantum compatible manner could in theory allow to accelerate the search by providing small overhead when built in quantum computer. Therefore acceleration would in turn counter weight the implementation limitations.

Original languageEnglish
Title of host publicationACM International Conference on Computing Frontiers 2019, CF 2019 - Proceedings
PublisherAssociation for Computing Machinery, Inc
Pages220-225
Number of pages6
ISBN (Electronic)9781450366854
DOIs
Publication statusPublished - Apr 30 2019
Event16th ACM International Conference on Computing Frontiers, CF 2019 - Alghero, Sardinia, Italy
Duration: Apr 30 2019May 2 2019

Publication series

NameACM International Conference on Computing Frontiers 2019, CF 2019 - Proceedings

Conference

Conference16th ACM International Conference on Computing Frontiers, CF 2019
CountryItaly
CityAlghero, Sardinia
Period4/30/195/2/19

Keywords

  • Quantum Circuits
  • Quantum Computer
  • Quantum Genetic Algorithm

ASJC Scopus subject areas

  • Software

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  • Cite this

    Krylov, G., & Lukac, M. (2019). Quantum Encoded Quantum Evolutionary Algorithm for the Design of Quantum Circuits. In ACM International Conference on Computing Frontiers 2019, CF 2019 - Proceedings (pp. 220-225). (ACM International Conference on Computing Frontiers 2019, CF 2019 - Proceedings). Association for Computing Machinery, Inc. https://doi.org/10.1145/3310273.3322826