Euclid Quick Data Release (Q1). Photometric redshifts and physical properties of galaxies through the PHZ processing function

The ESA Euclid mission will measure the photometric redshifts of billions of galaxies to provide an accurate 3D view of the Universe at optical and near-infrared wavelengths. Photometric redshifts are determined by the PHotometric redshift (PHZ) processing function on the basis of the multi-wavelength photometry of Euclid and ground-based observations. In this paper, we describe in detail the so-called PHZ processing used for the first `quick' (Q1) Euclid data release, along with the output products and their validation with respect to the Euclid requirements. The PHZ pipeline is responsible for the following main tasks: i) source classification into star, galaxy, and quasar (or QSO) classes based on photometric colours; ii) determination of photometric redshifts for the core science; and iii) determination of physical properties of galaxies for non-cosmological science. The classification is able to provide a star sample with a high level of purity, a highly complete galaxy sample, and reliable probabilities of belonging to those classes. The identification of QSOs is instead more problematic: photometric information available in the Euclid Wide Survey alone seems to be insufficient to accurately separate QSOs from galaxies. The performance of the pipeline in the determination of photometric redshifts has been tested using the COSMOS2020 catalogue and a large sample of spectroscopic redshifts. The results in both cases are in line with expectations: the precision of the estimates are compatible with Euclid requirements; however, as expected, a bias correction is needed to achieve the accuracy level required for the cosmological probes. Finally, the pipeline provides reliable estimates of the physical properties of galaxies, in good agreement with findings from the COSMOS2020 catalogue -- apart from an unrealistically large fraction of very young galaxies with very high specific star-formation rates. However, the application of appropriate priors is sufficient to obtain reliable physical properties for those problematic objects. We present several areas for improvement for future Euclid data releases.