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A new method to detect solar-like oscillations at very low S/N using statistical significance testing

Authors

  • Mikkel N. Lund,

    Corresponding author
    1. School of Physics and Astronomy, University of Birmingham, Birmingham
    2. Stellar Astrophysics Centre (SAC), The Danish National Research Foundation
    • Department of Physics and Astronomy, Aarhus University, Aarhus C, Denmark
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  • William J. Chaplin,

    Corresponding author
    1. School of Physics and Astronomy, University of Birmingham, Birmingham
    2. Stellar Astrophysics Centre (SAC), The Danish National Research Foundation
    • Department of Physics and Astronomy, Aarhus University, Aarhus C, Denmark
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  • Hans Kjeldsen

    Corresponding author
    1. Stellar Astrophysics Centre (SAC), The Danish National Research Foundation
    • Department of Physics and Astronomy, Aarhus University, Aarhus C, Denmark
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Errata

This article is corrected by:

  1. Errata: Erratum: A new method to detect solar-like oscillations at very low S/N using statistical significance testing Volume 427, Issue 4, 3489, Article first published online: 21 December 2012

E-mail: mikkelnl@phys.au.dk (MNL); w.j.chaplin@bham.ac.uk (WJC); hans@phys.au.dk (HK)

ABSTRACT

We introduce a new method to detect solar-like oscillations in frequency power spectra of stellar observations, under conditions of very low signal-to-noise ratio. The Moving-Windowed-Power-Search (MWPS) searches the power spectrum for signatures of excess power, over and above slowly varying (in frequency) background contributions from stellar granulation and shot or instrumental noise. We adopt a false-alarm approach to ascertain whether flagged excess power, which is consistent with the excess expected from solar-like oscillations, is hard to explain by chance alone (and hence a candidate detection).

We apply the method to solar photometry data, whose quality was systematically degraded to test the performance of the MWPS at low signal-to-noise ratios. We also compare the performance of the MWPS against the frequently applied power-spectrum-of-power-spectrum (PS⊗PS) detection method. The MWPS is found to outperform the PS⊗PS method.

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