Astrometric and photometric accuracies in high contrast imaging : The SPHERE speckle calibration tool (SpeCal)

TLDR: The SPHERE consortium developed a dedicated piece of software to process the data as mentioned in this paper, which corrects for instrumental artifacts and uses the speckle calibration tool to minimize the stellar light halo that prevents us from detecting faint sources like exoplanets or circumstellar disks.

Abstract: Context. The consortium of the Spectro-Polarimetric High-contrast Exoplanet REsearch installed at the Very Large Telescope (SPHERE/VLT) has been operating its guaranteed observation time (260 nights over five years) since February 2015. The main part of this time (200 nights) is dedicated to the detection and characterization of young and giant exoplanets on wide orbits.Aims. The large amount of data must be uniformly processed so that accurate and homogeneous measurements of photometry and astrometry can be obtained for any source in the field.Methods. To complement the European Southern Observatory pipeline, the SPHERE consortium developed a dedicated piece of software to process the data. First, the software corrects for instrumental artifacts. Then, it uses the speckle calibration tool (SpeCal) to minimize the stellar light halo that prevents us from detecting faint sources like exoplanets or circumstellar disks. SpeCal is meant to extract the astrometry and photometry of detected point-like sources (exoplanets, brown dwarfs, or background sources). SpeCal was intensively tested to ensure the consistency of all reduced images (cADI, Loci, TLoci, PCA, and others) for any SPHERE observing strategy (ADI, SDI, ASDI as well as the accuracy of the astrometry and photometry of detected point-like sources.Results. SpeCal is robust, user friendly, and efficient at detecting and characterizing point-like sources in high contrast images. It is used to process all SPHERE data systematically, and its outputs have been used for most of the SPHERE consortium papers to date. SpeCal is also a useful framework to compare different algorithms using various sets of data (different observing modes and conditions). Finally, our tests show that the extracted astrometry and photometry are accurate and not biased.