Impact of gaps in the asteroseismic characterization of pulsating stars

Pascual Granado, J., Suarez, J. C., Garrido, R., Moya, A., Hernández, A. G., Rodon, J. R., Lares Martiz, M. 2018. Impact of gaps in the asteroseismic characterization of pulsating stars. Astronomy and Astrophysics 614, DOI: 10.1051/0004-6361/201732431

It is known that the observed distribution of frequencies in CoRoT and Kepler delta Scuti stars has no parallelism with any theoretical model. Pre-whitening is a widespread technique in the analysis of time series with gaps from pulsating stars located in the classical instability strip, such as delta Scuti stars. However, some studies have pointed out that this technique might introduce biases in the results of the frequency analysis.

Aims. This work aims at studying the biases that can result from pre-whitening in asteroseismology. The results will depend on the intrinsic range and distribution of frequencies of the stars. The periodic nature of the gaps in CoRoT observations, only in the range of the pulsational frequency content of the delta Scuti stars, is shown to be crucial to determining their oscillation frequencies, the first step in performing asteroseismology of these objects. Hence, here we focus on the impact of pre-whitening on the asteroseismic characterization of delta Scuti stars.

Methods. We select a sample of 15 delta Scuti stars observed by the CoRoT satellite, for which ultra-high-quality photometric data have been obtained by its seismic channel. In order to study the impact on the asteroseismic characterization of delta Scuti stars we perform the pre-whitening procedure on three datasets: gapped data, linearly interpolated data, and data with gaps interpolated using Autoregressive and Moving Average models (ARMA).

Results. The different results obtained show that at least in some cases pre-whitening is not an efficient procedure for the deconvolution of the spectral window. Therefore, in order to reduce the effect of the spectral window to a minimum, in addition to performing a pre-whitening of the data, it is necessary to interpolate with an algorithm that is aimed to preserve the original frequency content.

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