A fractal analysis application of the pre-whitening technique to δ Scuti stars time series

Abstract

ABSTRACT Fractal fingerprints have been found recently in the light curves of several δ Scuti stars observed by Convection Rotation and planetary Transits(CoRoT) satellite. This sole fact might pose a problem for the detection of pulsation frequencies using classical pre-whitening techniques, but it is also a potentially rich source for information about physical mechanisms associated with stellar variability. Assuming that a light curve is composed of a superposition of oscillation modes with a fractal background noise, in this work we applied the Coarse Graining Spectral Analysis (CGSA), a fast Fourier transform (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 pre-whitening techniques in the light curves of δ Scuti stars. This might be crucial to understand the amount of frequencies excited in these kinds 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 pre-whitening cascade based on the percentage of fractal component in the residuals.