Stellar populations of galaxies in the ALHAMBRA survey up to z ~ 1

I. MUFFIT: A multi-filter fitting code for stellar population diagnostics

¹ Centro de Estudios de Física del Cosmos de Aragón (CEFCA), Plaza San Juan 1, Floor 2, 44001 Teruel, Spain
e-mail: diaz@cefca.es
² Mullard Space Science Laboratory, University College London, Holmbury St Mary, Dorking, Surrey RH5 6NT, UK
³ IAA-CSIC, Glorieta de la Astronomía s/n, 18008 Granada, Spain
⁴ Observatori Astronòmic, Universitat de València, C/ Catedràtic José Beltrán 2, 46980 Paterna, Spain
⁵ GEPI, Observatoire de Paris, CNRS, Université Paris Diderot, 61, Avenue de l’Observatoire 75014, Paris France
⁶ Instituto de Astrofísica de Canarias, vía Láctea s/n, 38200 La Laguna, Tenerife, Spain
⁷ Departamento de Astrofísica, Facultad de Física, Universidad de La Laguna, 38206 La Laguna, Spain
⁸ Instituto de Astronomía, Geofísica e Ciéncias Atmosféricas, Universidade de São Paulo, São Paulo, Brazil
⁹ Observatório Nacional-MCT, Rua José Cristino, 77, CEP 20921-400, Rio de Janeiro - RJ, Brazil
¹⁰ Department of Theoretical Physics, University of the Basque Country UPV/EHU, 48080 Bilbao, Spain
¹¹ IKERBASQUE, Basque Foundation for Science, 48013 Bilbao, Spain
¹² Departamento de Física Atómica, Molecular y Nuclear, Facultad de Física, Universidad de Sevilla, 41012 Sevilla, Spain
¹³ Institut de Ciències de l’Espai (IEEC-CSIC), Facultat de Ciències, Campus UAB, 08193 Bellaterra, Spain
¹⁴ Instituto de Física de Cantabria (CSIC-UC), 39005 Santander, Spain
¹⁵ Unidad Asociada Observatorio Astronómico (IFCA-UV), 46980 Paterna, Spain
¹⁶ Departamento de Astronomía, Pontificia Universidad Católica, 782-0436 Santiago, Chile
¹⁷ Departament d’Astronomia i Astrofísica, Universitat de València, 46100 Burjassot, Spain
¹⁸ Instituto de Física Teórica, (UAM/CSIC), Universidad Autónoma de Madrid, Cantoblanco, 28049 Madrid, Spain
¹⁹ Campus of International Excellence UAM+CSIC, Cantoblanco, 28049 Madrid, Spain
²⁰ Department of Mechanical Engineering and INSIGNEO Institute for in silico Medicine, University of Sheffield, UK

Received: 24 December 2014
Accepted: 26 May 2015

Abstract

Aims. We present MUFFIT, a new generic code optimized to retrieve the main stellar population parameters of galaxies in photometric multi-filter surveys, and check its reliability and feasibility with real galaxy data from the ALHAMBRA survey.

Methods. Making use of an error-weighted χ²-test, we compare the multi-filter fluxes of galaxies with the synthetic photometry of mixtures of two single stellar populations at different redshifts and extinctions, to provide the most likely range of stellar population parameters (mainly ages and metallicities), extinctions, redshifts, and stellar masses. To improve the diagnostic reliability, MUFFIT identifies and removes from the analysis those bands that are significantly affected by emission lines. The final parameters and their uncertainties are derived by a Monte Carlo method, using the individual photometric uncertainties in each band. Finally, we discuss the accuracies, degeneracies, and reliability of MUFFIT using both simulated and real galaxies from ALHAMBRA, comparing with results from the literature.

Results. MUFFIT is a precise and reliable code to derive stellar population parameters of galaxies in ALHAMBRA. Using the results from photometric-redshift codes as input, MUFFIT improves the photometric-redshift accuracy by ~10–20%. MUFFIT also detects nebular emissions in galaxies, providing physical information about their strengths. The stellar masses derived from MUFFIT show excellent agreement with the COSMOS and SDSS values. In addition, the retrieved age-metallicity locus for a sample of z ≤ 0.22 early-type galaxies in ALHAMBRA at different stellar mass bins are in very good agreement with the ones from SDSS spectroscopic diagnostics. Moreover, a one-to-one comparison between the redshifts, ages, metallicities, and stellar masses derived spectroscopically for SDSS and by MUFFIT for ALHAMBRA reveals good qualitative agreements in all the parameters, hence reinforcing the strengths of multi-filter galaxy data and optimized analysis techniques, like MUFFIT, to conduct reliable stellar population studies.