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Analysis of pulsating variable stars using the visibility graph algorithm

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  • Víctor Muñoz
  • N Elizabeth Garcés

Abstract

We study the light curves of pulsating variable stars using a complex network approach to build visibility graphs. We consider various types of variables stars (e.g., Cepheids, δ Scuti, RR Lyrae), build two types of graphs (the normal visibility graph (VG) and the horizontal visibility graph (HVG)), and calculate various metrics for the resulting networks. We find that all networks have a power-law degree distribution for the VG and an exponential distribution for the HVG, suggesting that it is a universal feature, regardless of the pulsation features. Metrics such as the average degree, the clustering coefficient and the transitivity coefficient, can distinguish between some star types. We also observe that the results are not strongly affected by the presence of observation gaps in the light curves. These findings suggest that the visibility graph algorithm may be a useful technique to study variability in stars.

Suggested Citation

  • Víctor Muñoz & N Elizabeth Garcés, 2021. "Analysis of pulsating variable stars using the visibility graph algorithm," PLOS ONE, Public Library of Science, vol. 16(11), pages 1-32, November.
    • Handle: RePEc:plo:pone00:0259735
    DOI: 10.1371/journal.pone.0259735
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    References listed on IDEAS

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    1. Martín Gómez Ravetti & Laura C Carpi & Bruna Amin Gonçalves & Alejandro C Frery & Osvaldo A Rosso, 2014. "Distinguishing Noise from Chaos: Objective versus Subjective Criteria Using Horizontal Visibility Graph," PLOS ONE, Public Library of Science, vol. 9(9), pages 1-15, September.
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