An analytic sifting approach to optimization of LNN reversible circuits

Martin Lukac, Pawel Kerntopf, Michitaka Kameyama

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

2 Citations (Scopus)

Abstract

In this paper we propose an analytic approach to the variable sifting based on weighting of qubits and gates. The proposed scheme allows to optimally sift gates (multi-control single-target reversible gates) within a linear number of steps of computation and provides in general smaller amount of SWAP gates required to transform a reversible circuit into an Linear Nearest Neighbor (LNN) model than other competing approaches. The method is analyzed for two different models of implementations, is verified on experimental data and results are compared to the state of the art algorithms for the design of LNN circuits.

Original languageEnglish
Title of host publicationProceedings of the International Conference on Information and Digital Technologies, IDT 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages240-245
Number of pages6
ISBN (Electronic)9781509056880
DOIs
Publication statusPublished - Sep 1 2017
Event2017 International Conference on Information and Digital Technologies, IDT 2017 - Zilina, Slovakia
Duration: Jul 5 2017Jul 7 2017

Conference

Conference2017 International Conference on Information and Digital Technologies, IDT 2017
CountrySlovakia
CityZilina
Period7/5/177/7/17

Keywords

  • Gate reordering
  • LNN Model
  • Qubit sifting
  • Reversible Circuits

ASJC Scopus subject areas

  • Instrumentation
  • Computer Networks and Communications
  • Hardware and Architecture
  • Electrical and Electronic Engineering
  • Safety, Risk, Reliability and Quality

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  • Cite this

    Lukac, M., Kerntopf, P., & Kameyama, M. (2017). An analytic sifting approach to optimization of LNN reversible circuits. In Proceedings of the International Conference on Information and Digital Technologies, IDT 2017 (pp. 240-245). [8024303] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/DT.2017.8024303