Close galaxy pairs with accurate photometric redshifts
Context. Studies of galaxy pairs can provide valuable information to jointly understand the formation and evolution of galaxies and galaxy groups. Consequently, taking the new high-precision photo-z surveys into account, it is important to have reliable and tested methods that allow us to properly identify these systems and estimate their total masses and other properties. Aims. In view of the forthcoming Physics of the Accelerating Universe Survey (PAUS), we propose and evaluate the performance of an identification algorithm of projected close isolated galaxy pairs. We expect that the photometrically selected systems can adequately reproduce the observational properties and the inferred lensing mass-luminosity relation of a pair of truly bound galaxies that are hosted by the same dark matter halo. Methods. We developed an identification algorithm that considers the projected distance between the galaxies, the projected velocity difference, and an isolation criterion in order to restrict the sample to isolated systems. We applied our identification algorithm using a mock galaxy catalog that mimics the features of PAUS. To evaluate the feasibility of our pair finder, we compared the identified photometric samples with a test sample that considers that both members are included in the same halo. Taking advantage of the lensing properties provided by the mock catalog, we also applied a weak-lensing analysis to determine the mass of the selected systems. Results. Photometrically selected samples tend to show high purity values, but tend to misidentify truly bounded pairs as the photometric redshift errors increase. Nevertheless, overall properties such as the luminosity and mass distributions are successfully reproduced. We also accurately reproduce the lensing mass-luminosity relation as expected for galaxy pairs located in the same halo. ; This project has received funding from the European Union's Horizon 2020 Research and Innovation Programme under the Marie Sklodowska-Curie grant agreement No 734374. This work has been supported by MINECO grants AYA2015-71825 & ESP2015-66861. IEEC is partially funded by the CERCA program of the Generalitat de Catalunya. This work was also partially supported by Agencia Nacional de Promoción Científica y Tecnoóogica (PICT 2015-3098), the Con-sejo Nacional de Investigaciones Científicas y Técnicas (CONICET, Argentina) and the Secretaría de Ciencia y Tecnología de la Universidad Nacional de Córdoba (SeCyT-UNC, Argentina). MS has been supported by the European Union's Horizon 2020 research and innovation programme under the Maria Skłodowska-Curie grant agreement No 754510 and National Science Centre (grant UMO-2016/23/N/ST9/02963). MM acknowledges support from the Beat-riu de Pinos fellowship (2017-BP-00114).