Volume 620, December 2018
|Number of page(s)||9|
|Section||Stellar structure and evolution|
|Published online||27 November 2018|
FliPer: A global measure of power density to estimate surface gravities of main-sequence solar-like stars and red giants
IRFU, CEA, Université Paris-Saclay, 91191 Gif-sur-Yvette, France
2 AIM, CEA, CNRS, Université Paris-Saclay, Université Paris Diderot, Sorbonne Paris Cité, 91191 Gif-sur-Yvette, France
3 School of Physics and Astronomy, University of Birmingham, , Edgbaston, Birmingham B15 2TT, UK
4 Stellar Astrophysics Centre, Department of Physics and Astronomy, Aarhus University, Ny Munkegade 120, 8000 Aarhus C, Denmark
5 Instituto de Astrofísica de Canarias, 38200 La Laguna, Tenerife, Spain
6 Universidad de La Laguna, Dpto. de Astrofísica, 38205 La Laguna, Tenerife, Spain
7 Space Science Institute, 4750 Walnut Street Suite 205, Boulder, CO 80301, USA
8 INAF – Osservatorio Astrofisico di Catania, Via S. Sofia 78, 95123 Catania, Italy
Accepted: 13 September 2018
Asteroseismology provides global stellar parameters such as masses, radii, or surface gravities using mean global seismic parameters and effective temperature for thousands of low-mass stars (0.8 M⊙ < M < 3 M⊙). This methodology has been successfully applied to stars in which acoustic modes excited by turbulent convection are measured. Other methods such as the Flicker technique can also be used to determine stellar surface gravities, but only works for log g above 2.5 dex. In this work, we present a new metric called FliPer (Flicker in spectral power density, in opposition to the standard Flicker measurement which is computed in the time domain); it is able to extend the range for which reliable surface gravities can be obtained (0.1 < log g < 4.6 dex) without performing any seismic analysis for stars brighter than Kp < 14. FliPer takes into account the average variability of a star measured in the power density spectrum in a given range of frequencies. However, FliPer values calculated on several ranges of frequency are required to better characterize a star. Using a large set of asteroseismic targets it is possible to calibrate the behavior of surface gravity with FliPer through machine learning. This calibration made with a random forest regressor covers a wide range of surface gravities from main-sequence stars to subgiants and red giants, with very small uncertainties from 0.04 to 0.1 dex. FliPer values can be inserted in automatic global seismic pipelines to either give an estimation of the stellar surface gravity or to assess the quality of the seismic results by detecting any outliers in the obtained νmax values. FliPer also constrains the surface gravities of main-sequence dwarfs using only long-cadence data for which the Nyquist frequency is too low to measure the acoustic-mode properties.
Key words: asteroseismology / methods: data analysis / stars: oscillations
© ESO 2018
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