RESEARCH
Tools FADO RemoveYoung
Fitting Analysis using Differential Evolution Optimization (FADO)
Spectral population synthesis through genetic optimization under self-consistency boundary conditions

Abstract
The goal of population spectral synthesis (PSS; also referred to as inverse, semi-empirical evolutionary- or fossil record approach) is to decipher from the spectrum of a galaxy the mass, age and metallicity of its constituent stellar populations. This technique, which is the reverse of but complementary to evolutionary synthesis, has been established as fundamental tool in extragalactic research. It has been extensively applied to large spectroscopic data sets, notably the SDSS, leading to important insights into the galaxy assembly history. However, despite significant improvements over the past decade, all current PSS codes suffer from two major deficiencies that inhibit us from gaining sharp insights into the star-formation history (SFH) of galaxies and potentially introduce substantial biases in studies of their physical properties (e.g., stellar mass, mass-weighted stellar age and specific star formation rate). These are i) the neglect of nebular emission in spectral fits, consequently, ii) the lack of a mechanism that ensures consistency between the best-fitting SFH and the observed nebular emission characteristics of a star-forming (SF) galaxy (e.g., hydrogen Balmer-line luminosities and equivalent widths-EWs, shape of the continuum in the region around the Balmer and Paschen jump). In this article, we present FADO (Fitting Analysis using Differential evolution Optimization) -- a conceptually novel, publicly available PSS tool with the distinctive capability of permitting identification of the SFH that reproduces the observed nebular characteristics of a SF galaxy. This so-far unique self-consistency concept allows us to significantly alleviate degeneracies in current spectral synthesis, thereby opening a new avenue to the exploration of the assembly history of galaxies. The innovative character of FADO is further augmented by its mathematical foundation: FADO is the first PSS code employing genetic differential evolution optimization. This, in conjunction with various other currently unique elements in its mathematical concept and numerical realization (e.g., mid-analysis optimization of the spectral library using artificial intelligence, test for convergence through a procedure inspired by Markov chain Monte Carlo techniques, quasi-parallelization embedded within a modular architecture) results in key improvements with respect to computational efficiency and uniqueness of the best-fitting SFHs. Furthermore, FADO incorporates within a single code the entire chain of pre-processing, modeling, post-processing, storage and graphical representation of the relevant output from PSS, including emission-line measurements and estimates of uncertainties for all primary and secondary products from spectral synthesis (e.g., mass contributions of individual stellar populations, mass- and luminosity-weighted stellar ages and metallicities). This integrated concept greatly simplifies and accelerates a lengthy sequence of individual time-consuming steps that are generally involved in PSS modeling, further enhancing the overall efficiency of the code and inviting to its automated application to large spectroscopic data sets.

Description
FADO comes from the Latin word "fatum" that means fate or destiny. It is also a well known genre of Portuguese music, and by choosing this acronym for this spectral synthesis tool we would like to pay tribute to Portugal. The main goal of FADO is to explore the star-formation and chemical enrichment history (the "Fado") of galaxies based on two hitherto unique elements in spectral fitting models: a) self-consistency between the best-fitting star formation history (SFH) and the nebular characteristics of a galaxy (e.g., hydrogen Balmer-line luminosities and equivalent widths; shape of the nebular continuum, including the Balmer and Paschen discontinuity) and b) genetic optimization and artificial intelligence algorithms.

FADO v.1 distribution package, which contains two different ascii files, ReadMe and Read_F, and one tarball archive FADOv1.tar.gz. FADOv1.tar.gz contains the binary (executable) compiled in both OpenSuSE 13.2 64bit LINUX (FADO) and MAC OS X (FADO_MACOSX). The former is compatible with most LINUX distributions, while the latter was only tested for Yosemite 10.10.3. It contains the configuration files for running FADO: FADO.config and PLOT.config, as well as the "Simple Stellar Population" (SSP) base library with the base file list Base.BC03.L, the FADO v.1 short manual Read_F and this file (in the ReadMe directory) and, for testing purposes, three characteristic de-redshifted spectra from SDSS-DR7 in ascii format, corresponding to a star-forming (spec1.txt), composite (spec2.txt) and LINER (spec3.txt) galaxy. Auxiliary files needed for execution of FADO (.HIfbound_em.ascii, .HeII_fbound.ascii, .HeIfboundem.ascii, grfont.dat and grfont.txt) are also included in the tarball. By decompressing the tarball the following six directories are created: input, output, plots, ReadMe, SSPs and tables (see below for a brief explanation).

Acknowledgments
Publications making use of FADO (or derivatives of it) and its subsequent releases must acknowledge the presentation article of the code by Gomes & Papaderos (2017, A&A, in press).

This work was supported by Fundação para a Ciência e a Tecnologia (FCT) through national funds and by FEDER through COMPETE by the grants UID/FIS/04434/2013 & POCI-01-0145-FEDER-007672 and PTDC/FIS-AST/3214/2012 & FCOMP-01-0124-FEDER-029170. We acknowledge support by European Community Programme (FP7/2007-2013) under grant agreement No. PIRSES-GA-2013-612701 (SELGIFS). J.M.G. was supported by the fellowship SFRH/BPD/66958/2009 funded by FCT (Portugal) and POPH/FSE (EC) and by the fellowship CIAAUP-04/2016-BPD in the context of the FCT project UID/FIS/04434/2013 & POCI-01-0145-FEDER-007672. P.P. was supported by FCT through Investigador FCT contract IF/01220/2013/CP1191/CT0002. We thank Mayanna Gomes for the invaluable discussions related to the field of genetics and Leandro Cardoso for extensive tests of FADO.

Instituto de Astrofísica e Ciências do Espaço Universidade do Porto Faculdade de Ciências da Universidade de Lisboa Fundação para a Ciência e a Tecnologia
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