A fractal analysis application of the prewhitening technique to δ Scuti stars time series

DOI: 
10.1093/mnras/stz1571
Publication date: 
01/06/2019
Main author: 
de Franciscis, S.
IAA authors: 
de Franciscis, S.;Pascual-Granado, J.;Suárez, J. C.;Garrido, R.;Lares-Martiz, M.;Rodón, J. R.
Authors: 
de Franciscis, S.;Pascual-Granado, J.;Suárez, J. C.;García Hernández, A.;Garrido, R.;Lares-Martiz, M.;Rodón, J. R.
Journal: 
Monthly Notices of the Royal Astronomical Society
Refereed: 
Yes
Publication type: 
Article
Pages: 
4457-4463
Abstract: 
Fractal fingerprints have been found recently in the lightcurves of several δ Scuti stars observed by CoRoT satellite. This sole fact might pose a problem for the detection of pulsation frequencies using classical prewhitening techniques, but it is also a potentially rich source for information about physical mechanisms associated to stellar variability. Assuming that a light curve is composed by a superposition of oscillation modes with a fractal background noise, in this work we applied the Coarse Graining Spectral Analysis (CGSA), an FFT based algorithm, which can discriminate in a time series the stochastic fractal power spectra from the harmonic one. We have found that the fractal background component is determining the frequency content extracted using classical prewhitening techniques in the lightcurves of δ Scuti stars. This might be crucial to understand the amount of frequencies excited in these kind of pulsating stars. Additionally, CGSA resulted to be relevant in order to extract the oscillation modes, this points to a new criterion to stop the prewhitening cascade based on the percentage of fractal component in the residuals.
Database: 
ADS
SCOPUS
URL: 
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85072393287&doi=10.1093%2fmnras%2fstz1571&partnerID=40&md5=cd582a070e32a5b41763505d55258526
ADS Bibcode: 
2019MNRAS.487.4457D
Keywords: 
stars: activity;stars: oscillations;stars: variables: δ Scuti