Abstract
On galaxy spectra, one can find mainly two features: emission lines, which tell us about the ionised gas content, and the continuum plus absorption lines, which tell us about the stellar content. They thus allow us to derive gas-phase abundances, the main radiation sources, chemical enrichment and star formation histories. Braad-band photometry, on the other hand, is much more limited and hinders our ability to recover a galaxy's physical properties to such a degree of detail. However, with the recent development of redshift surveys using the technology of ultra-narrow filters (≈ 100 Å), such as ALHAMBRA, J-PAS and DES, it will be invaluable to be able to retrieve information on physical properties of galaxies from photometric data. Motivated by this data avalanche (which goes up to the petabyte scale), we decided to build our own SED-fitting code: Magnitudes Analyser (MagAl), which has three modules. 1) A template library generation module: generates empirical and theoretical template libraries. 2) Bayesian fitting module: calculates probability distribution functions (PDFs) for given observed and library template data. This is similar to the method to measure photometric redshifts by Benitez (2000). 3) A result-analyser module: streamlines data analysis from the large output PDFs files. A fourth module to manage 3D data is being developed and a few preliminary tests are also shown. To investigate the reliability of results obtained by MagAl, we have created a mock galaxy sample for the ALHAMBRA survey filter system (http://alhambrasurvey.com) and tried to recover their physical properties. We show that for our sample of simulated galaxies we can measure stellar ages, metallicities and extinctions with a precision of less than 0.3 dex. Also, we apply the code to the ALHAMBRA survey catalog and show that we can measure stellar masses with an accuracy of 0.2 dex when comparing to previous results like COSMOS masses measured by Bundy et al. (2006).
