The study of stellar populations in galaxies is entering a new era with the availability of large and high‐quality data bases of both observed galactic spectra and state‐of‐the‐art evolutionary synthesis models. In this paper we investigate the power of spectral synthesis as a means to estimate the physical properties of galaxies. Spectral synthesis is nothing more than the decomposition of an observed spectrum in terms of a superposition of a base of simple stellar populations of various ages and metallicities, producing as output the star formation and chemical histories of a galaxy, its extinction and velocity dispersion. Our implementation of this method uses the recent models of Bruzual & Charlot and observed spectra in the 3650–8000 Å range. The reliability of this approach is studied by three different means: (1) simulations, (2) comparison with previous work based on a different technique, and (3) analysis of the consistency of results obtained for a sample of galaxies from the Sloan Digital Sky Survey (SDSS). We find that spectral synthesis provides reliable physical parameters as long as one does not attempt a very detailed description of the star formation and chemical histories. Robust and physically interesting parameters are obtained by combining the (individually uncertain) strengths of each simple stellar population in the base. In particular, we show that, besides providing excellent fits to observed galaxy spectra, this method is able to recover useful information on the distributions of stellar ages and, more importantly, stellar metallicities. Stellar masses, velocity dispersion and extinction are also found to be accurately retrieved for realistic signal‐to‐noise ratios. We apply this synthesis method to a volume‐limited sample of 50 362 galaxies from the SDSS Data Release 2, producing a catalogue of stellar population properties. Emission lines are also studied, their measurement being performed after subtracting the computed starlight spectrum from the observed one. A comparison with recent estimates of both observed and physical properties of these galaxies obtained by other groups shows good qualitative and quantitative agreement, despite substantial differences in the methods of analysis. The confidence in the present method is further strengthened by several empirical and astrophysically reasonable correlations between synthesis results and independent quantities. For instance, we report the existence of strong correlations between stellar and nebular metallicities, stellar and nebular extinctions, mean stellar age and equivalent width of Hα and 4000‐Å break, and between stellar mass and velocity dispersion.
We use the WHα versus [N ii]/Hα (WHAN) diagram introduced by us in previous work to provide a comprehensive emission‐line classification of Sloan Digital Sky Survey galaxies. This classification is able to cope with the large population of weak line galaxies that do not appear in traditional diagrams due to a lack of some of the diagnostic lines. A further advantage of the WHAN diagram is to allow the differentiation between two very distinct classes that overlap in the low‐ionization nuclear emission‐line region (LINER) region of traditional diagnostic diagrams. These are galaxies hosting a weakly active galactic nucleus (wAGN) and ‘retired galaxies’ (RGs), i.e. galaxies that have stopped forming stars and are ionized by their hot low‐mass evolved stars. A useful criterion to distinguish true from fake AGN (i.e. the RGs) is the value of ξ, which measures the ratio of the extinction‐corrected Hα luminosity with respect to the Hα luminosity expected from photoionization by stellar populations older than 108 yr. We find that ξ follows a markedly bimodal distribution, with a ξ≫ 1 population composed by systems undergoing star formation and/or nuclear activity, and a peak at ξ∼ 1 corresponding to the prediction of the RG model. We base our classification scheme not on ξ but on a more readily available and model‐independent quantity which provides an excellent observational proxy for ξ: the equivalent width of Hα. Based on the bimodal distribution of WHα, we set the practical division between wAGN and RGs at WHα= 3 Å. Five classes of galaxies are identified within the WHAN diagram: pure star‐forming galaxies: and WHα > 3 Å; strong AGN (i.e. Seyferts): and WHα > 6 Å; weak AGN: and WHα between 3 and 6 Å; RGs (i.e. fake AGN): WHα < 3 Å; passive galaxies (actually, lineless galaxies): WHα and W[N ii] < 0.5 Å. A comparative analysis of star formation histories and of other physical and observational properties in these different classes of galaxies corroborates our proposed differentiation between RGs and wAGN in the LINER‐like family. This analysis also shows similarities between strong and weak AGN on the one hand, and retired and passive galaxies on the other.
A numerous population of weak line galaxies (WLGs) is often left out of statistical studies on emission‐line galaxies (ELGs) due to the absence of an adequate classification scheme, since classical diagnostic diagrams, such as [O iii]/Hβ versus [N ii]/Hα (the BPT diagram), require the measurement of at least four emission lines. This paper aims to remedy this situation by transposing the usual divisory lines between star‐forming (SF) galaxies and active galactic nuclei (AGN) hosts and between Seyferts and LINERs to diagrams that are more economical in terms of line quality requirements. By doing this, we rescue from the classification limbo a substantial number of sources and modify the global census of ELGs. More specifically, (1) we use the Sloan Digital Sky Survey Data Release 7 to constitute a suitable sample of 280 000 ELGs, one‐third of which are WLGs. (2) Galaxies with strong emission lines are classified using the widely applied criteria of Kewley et al., Kauffmann et al. and Stasińska et al. to distinguish SF galaxies and AGN hosts and Kewley et al. to distinguish Seyferts from LINERs. (3) We transpose these classification schemes to alternative diagrams keeping [N ii]/Hα as a horizontal axis, but replacing Hβ by a stronger line (Hα or [O ii]), or substituting the ionization‐level sensitive [O iii]/Hβ ratio with the equivalent width of Hα(WHα). Optimized equations for the transposed divisory lines are provided. (4) We show that nothing significant is lost in the translation, but that the new diagrams allow one to classify up to 50 per cent more ELGs. (5) Introducing WLGs in the census of galaxies in the local Universe increases the proportion of metal‐rich SF galaxies and especially LINERs. In the course of this analysis, we were led to make the following points. (i) The Kewley et al. BPT line for galaxy classification is generally ill‐used. (ii) Replacing [O iii]/Hβ by WHα in the classification introduces a change in the philosophy of the distinction between LINERs and Seyferts, but not in its results. Because the WHα versus [N ii]/Hα diagram can be applied to the largest sample of ELGs without loss of discriminating power between Seyferts and LINERs, we recommend its use in further studies. (iii) The dichotomy between Seyferts and LINERs is washed out by WLGs in the BPT plane, but it subsists in other diagnostic diagrams. This suggests that the right wing in the BPT diagram is indeed populated by at least two classes, tentatively identified with bona fide AGN and ‘retired’ galaxies that have stopped forming stars and are ionized by their old stellar populations.
This paper considers the techniques to distinguish normal star‐forming (NSF) galaxies and active galactic nuclei (AGNs) hosts using optical spectra. The observational data base is a set of 20 000 galaxies extracted from the Sloan Digital Sky Survey, for which we have determined the emission‐line intensities after subtracting the stellar continuum obtained from spectral synthesis. Our analysis is based on photoionization models computed using the stellar ionizing radiation predicted by population synthesis codes (essentially starburst99) and, for the AGNs, a broken power‐law spectrum. We explain why, among the four classical emission‐line diagnostic diagrams, ([O iii]/Hβ versus [O ii]/Hβ, [O iii]/Hβ versus [N ii]/Hα (the BPT diagram), [O iii]/Hβ versus [S ii]/Hα and [O iii]/Hβ versus [O i]/Hα), the BPT one works best. We show, however, that none of these diagrams is efficient in detecting AGNs in metal‐poor galaxies, should such cases exist. We propose a new divisory line between ‘pure’ NSF galaxies and AGN hosts: y= (−30.787 + 1.1358x+ 0.27297x2) tanh (5.7409x) − 31.093, where y= log([O iii]/Hβ), and x= log([N ii]/Hα). According to our models, the divisory line drawn empirically by Kauffmann et al. includes among NSF galaxies objects that may have an AGN contribution to Hβ of up to 3 per cent. The Kewley et al. line allows for an AGN contribution of roughly 20 per cent. About 20 per cent of the galaxies in our entire sample that can be represented in the BTP diagram are found between our divisory line and the Kauffmann et al. line, meaning that the local Universe contains a fair proportion of galaxies with a very low‐level nuclear activity, in agreement with the statistics from observations of nuclei of nearby galaxies. We also show that a classification into NSF and AGN galaxies using only [N ii]/Hα is feasible and useful. Finally, we propose a new classification diagram, the DEW diagram, plotting Dn(4000) versus max(EW[O ii], EW[Ne iii]). This diagram can be used with optical spectra for galaxies with redshifts up to z= 1.3, meaning an important progress over classifications proposed up to now. Since the DEW diagram requires only a small range in wavelength, it can also be used at even larger redshifts in suitable atmospheric windows. It also has the advantage of not requiring stellar synthesis analysis to subtract the stars and of allowing one to see all the galaxies in the same diagram, including passive galaxies.
We study the evolution of 82302 star-forming (SF) galaxies from the SDSS. Our main goals are to explore new ways of handling star formation histories (SFH) obtained with our publicly available spectral synthesis code STARLIGHT, and apply them to investigate how SFHs vary as a function of nebular metallicity (Zneb). Our main results are: (1) A conventional correlation analysis shows how global properties such as luminosity, mass, dust content, mean stellar metallicity and mean stellar age relate to Zneb. (2) We present a simple formalism which compresses the results of the synthesis into time-dependent star formation rates (SFR) and mass assembly histories. (3) The current SFR derived from the population synthesis and that from H-alpha are shown to agree within a factor of two. Thus we now have a way to estimate SFR in AGN hosts, where the H-alpha method cannot be applied. (4) Fully time-dependent SFHs are derived for all galaxies and averaged over six Zneb bins spanning the entire SF wing in the [OIII]/H-beta X [NII]/H-alpha diagram. (5) We find that SFHs vary systematically along the SF sequence, such that low-Zneb systems evolve slower and are currently forming stars at a higher relative rate. (6) At any given time, the distribution of specific SFRs for galaxies within a Zneb-bin is broad and roughly log-normal. (7) The same results are found grouping galaxies in stellar mass (M*) or surface mass density (S*) bins. (8) The overall pattern of SFHs as a function of Zneb, M* or S* is robust against changes in selection criteria, choice of evolutionary synthesis models for the spectral fits, and differential extinction effects. (Abridged)Comment: Accepted for publication in MNRA
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.