Stellar populations of galaxies in the ALHAMBRA survey up to z ¿ 1. III. The stellar content of the quiescent galaxy population during the last 8 Gyr
Aims. We aim at constraining the stellar population properties of quiescent galaxies. These properties reveal how these galaxies evolved and assembled since z similar to 1 up to the present time. Methods. Combining the ALHAMBRA multi-filter photo-spectra with the fitting code for spectral energy distribution MUFFIT (MUlti-Filter FITting), we built a complete catalogue of quiescent galaxies via the dust-corrected stellar mass vs. colour diagram. This catalogue includes stellar population properties, such as age, metallicity, extinction, stellar mass, and photometric redshift, retrieved from the analysis of composited populations based on two independent sets of simple stellar population (SSP) models. We developed and applied a novel methodology to provide, for the first time, the analytic probability distribution functions (PDFs) of mass-weighted age, metallicity, and extinction of quiescent galaxies as a function of redshift and stellar mass. We adopted different star formation histories to discard potential systematics in the analysis. Results. The number density of quiescent galaxies is found to increase since z similar to 1, with a more substantial variation at lower stellar mass. Quiescent galaxies feature extinction AV progenitor> bias should also be taken into account. © ESO 2019 ; This work has been partly supported by the Programa Nacional de Astronomia y Astrofisica of the Spanish Ministry of Economy and Competitiveness (MINECO, grants AYA2012-30789 and AYA2015-66211-C2-1-P), by the Ministry of Science and Technology of Taiwan (grant MOST 106-2628-M-001-003-MY3), by the Academia Sinica (grant AS-IA-107-M01), and by the Government of Aragon (Research Group E103). L.A.D.G. also thanks the support of I.F. for o ffering the opportunity to develop part of this research at the Mullard Space Science Laboratory (MSSL). We also acknowledge support from the Spanish Ministry for Economy and Competitiveness and FEDER funds through grants AYA201015081, AYA2010-15169, AYA2010-22111-C03-01, AYA2010-22111-C03-02, AYA2011-29517-C03-01, AYA2012-39620, AYA2013-40611-P, AYA201342227-P, AYA2013-43188-P, AYA2013-48623-C2-1, AYA2013-48623-C2-2, ESP2013-48274, AYA2014-57490-P, AYA2014-58861-C3-1, AYA2016-76682-C3-1-P, AYA2016-77846-P, AYA2016-81065-C2-1, AYA2016-81065-C2-2, Generalitat Valenciana projects Prometeo 2009/064, and PROMETEOII/2014/060, Junta de Andalucia grants TIC114, JA2828, P10-FQM-6444, and Generalitat de Catalunya project SGR-1398. The authors acknowledge Y. Peng and A. Citro for sharing their stellar population numerical results. Throughout this research, we made use of the Matplotlib package (Hunter 2007), a 2D graphics package used for Python that is designed for interactive scripting and quality image generation. This paper is dedicated to Marian Leon Canalejo for being there when L.A.D.G. needed her most and for her patience and continuous encouragement while finishing his Ph.D.