Abstract
Invalid flux measurements, caused mainly by the South Atlantic Anomaly crossing of the CoRoT satellite, introduce aliases in the periodogram and wrong amplitudes. It has been demonstrated that replacing such invalid data with a linear interpolation is not harmless. On the other side, using power spectrum estimators for unevenly sampled time series is not only less computationally efficient but it leads to difficulties in the interpretation of the results. Therefore, even when the gaps are rather small and the duty cycle is high enough the use of gap-filling methods is a gain in frequency analysis. However, the method must preserve the information contained in the time series. In this work we give a short description of an information preserving method (MIARMA) and show some results when applying it to CoRoT seismo light curves. The method is implemented as the second step of a pipeline for CoRoT data analysis.
Highlights
Invalid flux measurements, caused mainly by the South Atlantic Anomaly crossing of the CoRoT satellite, introduce aliases in the periodogram and wrong amplitudes
The data used in this work have been obtained from the CoRoT archive at the IAS Data Center
MIARMA [1] is a gap-filling method based on autoregressive moving-average modelling of the data, it makes no assumptions about the analyticity of the signal
Summary
Invalid flux measurements, caused mainly by the South Atlantic Anomaly crossing of the CoRoT satellite, introduce aliases in the periodogram and wrong amplitudes. The data used in this work have been obtained from the CoRoT archive at the IAS Data Center.
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