Our understanding of the structure, composition and evolution of galaxies hasstrongly improved in the last decades, mostly due to new results based on large spectro-scopic and imaging surveys. In particular, the nature of ionized gas, its ionization mech-anisms, its relation with the stellar properties and chemical composition, the existence ofscaling relations that describe the cycle between stars and gas, and the corresponding evo-lution patterns have been widely explored and described. More recently, the introduction ofadditional techniques, in particular integral field spectroscopy, and their use in large galaxysurveys, have forced us to re-interpret most of those recent results from a spatially resolvedperspective. This review is aimed to complement recent efforts to compile and summarizethis change of paradigm in the interpretation of galaxy evolution. To this end we replicatepublished results, and present novel ones, based on the largest compilation of IFS data ofgalaxies in the nearby universe to date.

We present here the analysis performed using the pyPipe3D pipeline for the final MaNGA data set included in the Sloan Digital Sky Survey data release 17. This data set comprises more than 10,000 individual data cubes, being the integral field spectroscopic (IFS) galaxy survey with the largest number of galaxies. pyPipe3D processes the IFS data cubes to extract spatially resolved spectroscopic properties of both the stellar population and the ionized gas emission lines. A brief summary of the properties of the sample and the characteristics of the analyzed data are included. The article provides details of: (i) the analysis performed; (ii) a description of the pipeline; (iii) the adopted stellar population library; (iv) the morphological and photometric analysis; (v) the adopted data model for the spatially resolved properties derived; and (vi) the individual integrated and characteristic galaxy properties included in the final catalog. Comparisons with the results from a previous version of the pipeline for earlier data releases and from other tools using this data set are included. A practical example of how to use the full data set and the final catalog illustrates how to handle the delivered product. Our full analysis can be accessed and downloaded from our web page.

The colour-magnitude diagrams of some intermediate-age clusters (1-2 Gyr) star clusters show unexpectedly broad main-sequence turnoffs, raising the possibility that these clusters have experienced more than one episode of star formation. Such a scenario predicts the existence of an extended main sequence turn off (eMSTO) only in clusters with escape velocities above a certain threshold (> 15 km s −1 ), which would allow them to retain or accrete gas that eventually would fuel a secondary extended starformation episode. This paper presents a test of this scenario based on the study of the young and massive cluster NGC 7252: W3. We use the HST photometry from WFPC2 and WFC3 images obtained with UV and optical filters, as well as MagE echellette spectrograph data from the Las Campanas Clay 6.5m telescope, in order to construct the observed UV/optical SED of NGC 7252: W3. The observations are then compared with synthetic spectra based on different star formation histories consistent with those of the eMSTO clusters. We find that the SED of this cluster is best fitted by a synthetic spectrum with a single stellar population of age 570 +70 −62 Myr and mass 1.13 +0.14 −0.13 × 10 8 M ⊙ , confirming earlier works on NGC 7252:W3. We also estimate the lower limit on the central escape velocity of 193 km s −1 . We rule out extended star-formation histories, like those inferred for the eMSTO clusters in the Magellanic Clouds, at high confidence. We conclude that the escape velocity of a cluster does not dictate whether a cluster can undergo extended periods of star formation.

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ABSTRACT. We explore the ability of four different inverse population synthesis codes to recover the physical properties of galaxies from their spectra by SED fitting. Three codes, DynBaS, TGASPEX, and GASPEX, have been implemented by the authors and are described in detail in the paper. STARLIGHT, the fourth code, is publicly available. DynBaS selects dynamically a different spectral basis to expand the spectrum of each target galaxy, and TGASPEX uses an unconstrained age basis, whereas GASPEX and STARLIGHT use for all fits a fixed spectral basis selected a priori by the code developers. Variable and unconstrained basis reflect the peculiarities of the fitted spectrum and allow for simple and robust solutions to the problem of extracting galaxy parameters from spectral fits. We assemble a Synthetic Spectral Atlas of Galaxies (SSAG), 3 comprising 100,000 galaxy spectra corresponding to an equal number of star formation histories based on the recipe of Chen et al. We select a subset of 120 galaxies from SSAG with a color distribution similar to that of local galaxies in the seventh data release (DR7) of the Sloan Digital Sky Survey (SDSS), and produce 30 random noise realizations for each of these spectra. For each spectrum, we recover the mass, mean age, metallicity, internal dust extinction, and velocity dispersion characterizing the dominant stellar population in the problem galaxy. All methods produce almost-perfect fits to the target spectrum, but the recovered physical parameters can differ significantly. Our tests provide a quantitative measure of the accuracy and precision with which these parameters are recovered by each method. From a statistical point of view, all methods yield similar precisions, whereas DynBaS produces solutions with minimal systematic biases in the distributions of residuals for all of these parameters. We caution the reader that the results obtained in our consistency tests represent lower limits to the uncertainties in parameter determination. Our tests compare theoretical galaxy spectra built from the same synthesis models used in the fits. Using different synthesis models and the lack of particular stellar types in the synthesis models but present in real galaxies will increase these errors considerably. Additional sources of error expected to be present in real galaxy spectra are not easy to emulate, and again will result in larger errors.