The Javalambre-Physics of the Accelerating Universe Astrophysical Survey (J-PAS; https://j-pas.org) is a multifilter photometric sky survey using a unique set of 56 narrow-band filters (145Å FWHM) and one broad-band, i, covering the visible range at a magnitude depth of AB~22. It is being carried out at the Observatorio Astrofísico de Javalambre (OAJ), Spain, since 2023. It aims to cover thousands of square degrees of the the observable sky from the OAJ and to determine precise photometric redshifts for around 1.3x10⁸ galaxies . The survey is conducted with the Javalambre Panoramic Camera (JPCam) attached to the 2.5m-class telescope, Javalambre Survey Telescope (JST250). JPCam consists of a mosaic of 14 identical 9.2k x 9.2k CCDs which cover 3.4deg² in total on the sky. On top of each CCD, a different narrow-band filter is positioned through a set of 5 filter trays of 14 slots each.
The J-PAS survey strategy and the instrumentation employed pose important challenges in the data processing, some of them listed hereafter.
Large FoV systems are prone to suffer from stray light that is not properly corrected with the classical flat-fielding. The needed illumination correction is obtained from the 2D residuals of the photometric calibration performed taking as reference Gaia DR3. Other remarkable difficulty is dealing with the variety of background patterns observed through the set of J-PAS narrow-band filters together with other ambient illumination gradients under the presence of the Moon. Another significant challenge is the two-dimensional mixture of PSFs in the stacked images for each filter, due to the fact that the observations are often made on different dates and seeing conditions. This has an important impact on the proper estimation of the photometric aperture corrections on those combined frames. On the electronics side, a specific procedure has to be implemented in order to correct from a time-varying bias signal of the CCDs.
In this talk I will discuss these and other challenges and the solutions we have successfully implemented. I will also announce the upcoming public early data release of J-PAS, scheduled for the end of 2024.