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How to Distinguish Cospectral Graphs

Author

Listed:
  • Saeree Wananiyakul

    (Department of Mathematics and Computer Science, Faculty of Science, Chulalongkorn University, Bangkok 10300, Thailand
    These authors contributed equally to this work.)

  • Jörn Steuding

    (Department of Mathematics, Würzburg University, Am Hubland, 97 218 Würzburg, Germany
    These authors contributed equally to this work.)

  • Janyarak Tongsomporn

    (School of Science, Walailak University, Nakhon Si Thammarat 80160, Thailand
    These authors contributed equally to this work.)

Abstract

We introduce a generalized adjacency matrix in order to distinguish cospectral graphs. Our reasoning is motivated by the work of Johnson and Newman and properties of p -adic numbers. Using a polynomial time algorithm, we comment on computer experiments with which we can distinguish cospectral (non-isomorphic) graphs.

Suggested Citation

  • Saeree Wananiyakul & Jörn Steuding & Janyarak Tongsomporn, 2022. "How to Distinguish Cospectral Graphs," Mathematics, MDPI, vol. 10(24), pages 1-24, December.
    • Handle: RePEc:gam:jmathe:v:10:y:2022:i:24:p:4802-:d:1006088
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    References listed on IDEAS

    as
    1. van Dam, E.R. & Haemers, W.H., 2007. "Developments on Spectral Characterizations of Graphs," Discussion Paper 2007-33, Tilburg University, Center for Economic Research.
    2. van Dam, E.R. & Haemers, W.H. & Koolen, J.H., 2006. "Cospectral Graphs and the Generalized Adjacency Matrix," Discussion Paper 2006-31, Tilburg University, Center for Economic Research.
    3. van Dam, E.R. & Haemers, W.H., 2002. "Which Graphs are Determined by their Spectrum?," Discussion Paper 2002-66, Tilburg University, Center for Economic Research.
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