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Register a new userSelf-consistent population spectral synthesis with FADO: II. Star formation history of galaxies in spectral synthesis methods
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The field of galaxy evolution will make a great leap forward in the next decade as a consequence of the huge effort by the scientific community in multi-object spectroscopic facilities. To maximise the impact of such incoming data, the analysis methods must also step up, extracting reliable information from the available spectra. In this paper, we aim to investigate the limits and the reliability of different spectral synthesis methods in the estimation of the mean stellar age and metallicity. The main question this work aims to address is which signal-to-noise ratios (S/N) are needed to reliably determine the mean stellar age and metallicity from a galaxy spectrum and how this depends on the tool used to model the spectra. To address this question we built a set of realistic simulated spectra containing stellar and nebular emission, reproducing the evolution of a galaxy in two limiting cases: a constant star formation rate and an exponentially declining star formation. We degraded the synthetic spectra built from these two star formation histories (SFHs) to different S/N and analysed them with three widely used spectral synthesis codes, namely FADO, STECKMAP, and STARLIGHT. For S/N < 5 all three tools show a large diversity in the results. The FADO and STARLIGHT tools find median differences in the light-weighted mean stellar age of ~0.1 dex, while STECKMAP shows a higher value of ~0.2 dex. Detailed investigations of the best-fit spectrum for galaxies with overestimated mass-weighted quantities point towards the inability of purely stellar models to fit the observed spectra around the Balmer jump. Our results imply that when a galaxy enters a phase of high specific star formation rate the neglect of the nebular continuum emission in the fitting process has a strong impact on the estimation of its SFH when purely stellar fitting codes are used, even in presence of high S/N spectra.
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Spectral population synthesis (PS) is a fundamental tool in extragalactic research that aims to decipher the assembly history of galaxies from their SED. However, until recently all PS codes were restricted to purely stellar fits, neglecting the essential contribution of nebular emission (NE). With the advent of FADO, the now possible self-consistent modelling of stellar and NE opens new routes to the exploration of galaxy SFHs. The main goal of this study is to quantitatively explore the accuracy to which FADO can recover physical and evolutionary properties of galaxies and compare its output with that from purely stellar PS codes. With this in mind, FADO and STARLIGHT were applied to synthetic SEDs that track the spectral evolution of stars and gas in extinction-free mock galaxies that form their stellar mass ($M_star$) according to different parametric SFHs. Spectral fits were computed for two different set-ups that approximate the spectral range of SDSS and CALIFA data. Our analysis indicates that FADO can recover the key physical and evolutionary properties of galaxies, such as $M_star$ and mass- and light-weighted mean age and metallicity, with an accuracy better than 0.2 dex. This is the case even in phases of strongly elevated sSFR and thus with considerable NE contamination. As for STARLIGHT, our analysis documents a moderately good agreement with theoretical values only for evolutionary phases for which NE drops to low levels. Indeed, fits with STARLIGHT during phases of high sSFR severely overestimate both $M_star$ and the mass-weighted stellar age, whereas strongly underestimate the light-weighted age and metallicity. The insights from this study suggest that the neglect of nebular continuum emission in STARLIGHT and similar purely stellar PS codes could systematically impact $M_star$ and SFH estimates for star-forming galaxies.
We compare six popularly used evolutionary population synthesis (EPS) models (BC03, CB07, Ma05, GALEV, GRASIL, Vazdekis/Miles) through fitting the full optical spectra of six representative types of galaxies (star-forming and composite galaxies, Seyfert 2s, LINERs, E+A and early-type galaxies), which are taken from the Sloan Digital Sky Survey (SDSS). Throughout our paper, we use the simple stellar populations (SSPs) from each EPS model and the software STARLIGHT to do our fits. Our main results are: Using different EPS models the resulted numerical values of contributed light fractions change obviously, even though the dominant populations are consistent. The stellar population synthesis does depend on the selection of age and metallicity, while it does not depend on the stellar evolution track much. The importance of young populations decreases from star-forming, composite, Seyfert 2, LINER to early-type galaxies, and E+A galaxies lie between composite galaxies and Seyfert 2s in most cases. We conclude that different EPS models do derive different stellar populations, so that it is not reasonable to directly compare stellar populations estimated from different EPS models. To get reliable results, we should use the same EPS model for the compared samples.
We present JEKYLL, a new code for modelling of supernova (SN) spectra and lightcurves based on Monte-Carlo (MC) techniques for the radiative transfer. The code assumes spherical symmetry, homologous expansion and steady state for the matter, but is otherwise capable of solving the time-dependent radiative transfer problem in non-local-thermodynamic-equilibrium (NLTE). The method used was introduced in a series of papers by Lucy, but the full time-dependent NLTE capabilities of it have never been tested. Here, we have extended the method to include non-thermal excitation and ionization as well as charge-transfer and two-photon processes. Based on earlier work, the non-thermal rates are calculated by solving the Spencer-Fano equation. Using a method previously developed for the SUMO code, macroscopic mixing of the material is taken into account in a statistical sense. In addition, a statistical Markov-chain model is used to sample the emission frequency, and we introduce a method to control the sampling of the radiation field. Except for a description of JEKYLL, we provide comparisons with the ARTIS, SUMO and CMFGEN codes, which show good agreement in the calculated spectra as well as the state of the gas. In particular, the comparison with CMFGEN, which is similar in terms of physics but uses a different technique, shows that the Lucy method does indeed converge in the time-dependent NLTE case. Finally, as an example of the time-dependent NLTE capabilities of JEKYLL, we present a model of a Type IIb SN, taken from a set of models presented and discussed in detail in an accompanying paper. Based on this model we investigate the effects of NLTE, in particular those arising from non-thermal excitation and ionization, and find strong effects even on the bolometric lightcurve. This highlights the need for full NLTE calculations when simulating the spectra and lightcurves of SNe.
In a companion paper we have presented many products derived from the application of the spectral synthesis code STARLIGHT to datacubes from the CALIFA survey, including 2D maps of stellar population properties and 1D averages in the temporal and spatial dimensions. Here we evaluate the uncertainties in these products. Uncertainties due to noise and spectral shape calibration errors and to the synthesis method are investigated by means of a suite of simulations based on 1638 CALIFA spectra for NGC 2916, with perturbations amplitudes gauged in terms of the expected errors. A separate study was conducted to assess uncertainties related to the choice of evolutionary synthesis models. We compare results obtained with the Bruzual & Charlot models, a preliminary update of them, and a combination of spectra derived from the Granada and MILES models. About 100k CALIFA spectra are used in this comparison. Noise and shape-related errors at the level expected for CALIFA propagate to 0.10-0.15 dex uncertainties in stellar masses, mean ages and metallicities. Uncertainties in A_V increase from 0.06 mag in the case of random noise to 0.16 mag for shape errors. Higher order products such as SFHs are more uncertain, but still relatively stable. Due to the large number statistics of datacubes, spatial averaging reduces uncertainties while preserving information on the history and structure of stellar populations. Radial profiles of global properties, as well as SFHs averaged over different regions are much more stable than for individual spaxels. Uncertainties related to the choice of base models are larger than those associated with data and method. Differences in mean age, mass and metallicity are ~ 0.15 to 0.25 dex, and 0.1 mag in A_V. Spectral residuals are ~ 1% on average, but with systematic features of up to 4%. The origin of these features is discussed. (Abridged)
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