A new wavelet-based approach for the automated treatment of large sets of lunar occultation data

摘要

The introduction of infrared arrays for lunar occultations (LO) work and theimprovement of predictions based on new deep IR catalogues have resulted in alarge increase in the number of observable occultations. We provide the means for an automated reduction of large sets of LO data.This frees the user from the tedious task of estimating first-guess parametersfor the fit of each LO lightcurve. At the end of the process, ready-made plotsand statistics enable the user to identify sources which appear to be resolvedor binary and to initiate their detailed interactive analysis. The pipeline is tailored to array data, including the extraction of thelightcurves from FITS cubes. Because of its robustness and efficiency, thewavelet transform has been chosen to compute the initial guess of theparameters of the lightcurve fit. We illustrate and discuss our automatic reduction pipeline by analyzing alarge volume of novel occultation data recorded at Calar Alto Observatory. Theautomated pipeline package is available from the authors.