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We study systematics associated with estimating simple stellar population (SSP) parameters – age, metallicity [M/H], α-enhancement [α/Fe], and initial mass function (IMF) shape – and associated M*/L gradients, of elliptical slow rotators (E-SRs), fast rotators (E-FRs), and S0s from stacked spectra of galaxies in the MaNGA survey. These systematics arise from (i) how one normalizes the spectra when stacking; (ii) having to subtract emission before estimating absorption line strengths; (iii) the decision to fit the whole spectrum or just a few absorption lines; (iv) SSP model differences (e.g. isochrones, enrichment, IMF). The MILES+Padova SSP models, fit to the Hβ, 〈Fe〉, TiO2SDSS, and [MgFe] Lick indices in the stacks, indicate that out to the half-light radius Re: (a) ages are younger and [α/Fe] values are lower in the central regions but the opposite is true of [M/H]; (b) the IMF is more bottom-heavy in the center, but is close to Kroupa beyond about Re/2; (c) this makes M*/L about 2 × larger in the central regions than beyond Re/2. While the models of Conroy et al. return similar [M/H] and [α/Fe] profiles, the age and (hence) M*/L profiles can differ significantly even for solar abundances and a Kroupa IMF; different responses to non-solar abundances and IMF parametrization further compound these differences. There are clear (model independent) differences between E-SRs, E-FRs, and S0s: younger ages and less enhanced [α/Fe] values suggest that E-FRs and S0s are not SSPs, but relaxing this assumption is unlikely to change their inferred M*/L gradients significantly.

 

Gradients in the stellar populations (SP) of galaxies – e.g. in age, metallicity, stellar initial mass function (IMF) – can result in gradients in the stellar-mass-to-light ratio, M*/L. Such gradients imply that the distribution of the stellar mass and light is different. For old SPs, e.g. in early-type galaxies at z ∼ 0, the M*/L gradients are weak if driven by variations in age and metallicity, but significantly larger if driven by the IMF. A gradient which has larger M*/L in the centre increases the estimated total stellar mass (M*) and reduces the scale which contains half this mass (Re,*), compared to when the gradient is ignored. For the IMF gradients inferred from fitting MILES simple SP models to the H β, 〈Fe〉, [MgFe], and TiO2SDSS absorption lines measured in spatially resolved spectra of early-type galaxies in the MaNGA survey, the fractional change in Re,* can be significantly larger than that in M*, especially when the light is more centrally concentrated. The Re,*–M* correlation which results from accounting for IMF gradients is offset to smaller sizes by 0.3 dex compared to when these gradients are ignored. Comparisons with ‘quiescent’ galaxies at higher z must account for evolution in SP gradients (especially age and IMF) and in the light profile before drawing conclusions about how Re,* and M* evolve. The implied merging between higher z and the present is less contrived if Re,*/Re at z ∼ 0 is closer to our IMF-driven gradient calibration than to unity.

 

ABSTRACT We present the MaNGA PyMorph photometric Value Added Catalogue (MPP-VAC-DR17) and the MaNGA Deep Learning Morphological VAC (MDLM-VAC-DR17) for the final data release of the MaNGA survey, which is part of the SDSS Data Release 17 (DR17). The MPP-VAC-DR17 provides photometric parameters from Sérsic and Sérsic+Exponential fits to the two-dimensional surface brightness profiles of the MaNGA DR17 galaxy sample in the g, r, and i bands (e.g. total fluxes, half-light radii, bulge-disc fractions, ellipticities, position angles, etc.). The MDLM-VAC-DR17 provides deep-learning-based morphological classifications for the same galaxies. The MDLM-VAC-DR17 includes a number of morphological properties, for example, a T-Type, a finer separation between elliptical and S0, as well as the identification of edge-on and barred galaxies. While the MPP-VAC-DR17 simply extends the MaNGA PyMorph photometric VAC published in the SDSS Data Release 15 (MPP-VAC-DR15) to now include galaxies that were added to make the final DR17, the MDLM-VAC-DR17 implements some changes and improvements compared to the previous release (MDLM-VAC-DR15): Namely, the low end of the T-Types is better recovered in this new version. The catalogue also includes a separation between early or late type, which classifies the two populations in a complementary way to the T-Type, especially at the intermediate types (−1 < T-Type < 2), where the T-Type values show a large scatter. In addition, k-fold-based uncertainties on the classifications are also provided. To ensure robustness and reliability, we have also visually inspected all the images. We describe the content of the catalogues and show some interesting ways in which they can be combined. 

ABSTRACT Early-type galaxies – slow and fast rotating ellipticals (E-SRs and E-FRs) and S0s/lenticulars – define a Fundamental Plane (FP) in the space of half-light radius Re, enclosed surface brightness Ie, and velocity dispersion σe. Since Ie and σe are distance-independent measurements, the thickness of the FP is often expressed in terms of the accuracy with which Ie and σe can be used to estimate sizes Re. We show that: (1) The thickness of the FP depends strongly on morphology. If the sample only includes E-SRs, then the observed scatter in Re is $\sim 16{{\ \rm per\ cent}}$, of which only $\sim 9{{\ \rm per\ cent}}$ is intrinsic. Removing galaxies with M* < 1011 M⊙ further reduces the observed scatter to $\sim 13{{\ \rm per\ cent}}$ ($\sim 4{{\ \rm per\ cent}}$ intrinsic). The observed scatter increases to $\sim 25{{\ \rm per\ cent}}$ usually quoted in the literature if E-FRs and S0s are added. If the FP is defined using the eigenvectors of the covariance matrix of the observables, then the E-SRs again define an exceptionally thin FP, with intrinsic scatter of only 5 per cent orthogonal to the plane. (2) The structure within the FP is most easily understood as arising from the fact that Ie and σe are nearly independent, whereas the Re−Ie and Re−σe correlations are nearly equal and opposite. (3) If the coefficients of the FP differ from those associated with the virial theorem the plane is said to be ‘tilted’. If we multiply Ie by the global stellar mass-to-light ratio M*/L and we account for non-homology across the population by using Sérsic photometry, then the resulting stellar mass FP is less tilted. Accounting self-consistently for M*/L gradients will change the tilt. The tilt we currently see suggests that the efficiency of turning baryons into stars increases and/or the dark matter fraction decreases as stellar surface brightness increases. 

Abstract This is the third paper of a series where we study the stellar population gradients (SP; ages, metallicities, α-element abundance ratios and stellar initial mass functions) of early type galaxies (ETGs) at z ≤ 0.08 from the MaNGA-DR15 survey. In this work we focus on the S0 population and quantify how the SP varies across the population as well as with galactocentric distance. We do this by measuring Lick indices and comparing them to stellar population synthesis models. This requires spectra with high signal-to-noise which we achieve by stacking in bins of luminosity (Lr) and central velocity dispersion (σ0). We find that: 1) There is a bimodality in the S0 population: S0s more massive than 3 × 1010M⊙ show stronger velocity dispersion and age gradients (age and σr decrease outwards) but little or no metallicity gradient, while the less massive ones present relatively flat age and velocity dispersion profiles, but a significant metallicity gradient (i.e. [M/H] decreases outwards). Above 2 × 1011M⊙ the number of S0s drops sharply. These two mass scales are also where global scaling relations of ETGs change slope. 2) S0s have steeper velocity dispersion profiles than fast rotating elliptical galaxies (E-FRs) of the same luminosity and velocity dispersion. The kinematic profiles and stellar population gradients of E-FRs are both more similar to those of slow rotating ellipticals (E-SRs) than to S0s, suggesting that E-FRs are not simply S0s viewed face-on. 3) At fixed σ0, more luminous S0s and E-FRs are younger, more metal rich and less α-enhanced. Evidently for these galaxies, the usual statement that ‘massive galaxies are older’ is not true if σ0 is held fixed. 

ABSTRACT We estimate ages, metallicities, α-element abundance ratios, and stellar initial mass functions (IMFs) of elliptical (E) and S0 galaxies from the MaNGA-DR15 survey. We stack spectra and use a variety of single stellar population synthesis models to interpret the absorption line strengths in these spectra. We quantify how these properties vary across the population, as well as with galactocentric distance. This paper is the first of a series and is based on a sample of pure elliptical galaxies at z ≤ 0.08. We confirm previous work showing that IMFs in Es with the largest luminosity (Lr) and central velocity dispersion (σ0) appear to be increasingly bottom heavy towards their centres. For these galaxies the stellar mass-to-light ratio decreases at most by a factor of 2 from the central regions to Re. In contrast, for lower Lr and σ0 galaxies, the IMF is shallower and M*/Lr in the central regions is similar to the outskirts, although quantitative estimates depend on assumptions about element abundance gradients. Accounting self-consistently for these gradients when estimating both M* and Mdyn brings the two into good agreement: gradients reduce Mdyn by ∼0.2 dex while only slightly increasing the M* inferred using a Kroupa IMF. This is a different resolution of the M*–Mdyn discrepancy than has been followed in the recent literature where M* of massive galaxies is increased by adopting a Salpeter IMF throughout the galaxy while leaving Mdyn unchanged. A companion paper discusses how stellar population differences are even more pronounced if one separates slow from fast rotators. 

ABSTRACT We present estimates of stellar population (SP) gradients from stacked spectra of slow rotator (SR) and fast rotator (SR) elliptical galaxies from the MaNGA-DR15 survey. We find that (1) FRs are ∼5 Gyr younger, more metal rich, less α-enhanced and smaller than SRs of the same luminosity Lr and central velocity dispersion σ0. This explains why when one combines SRs and FRs, objects which are small for their Lr and σ0 tend to be younger. Their SP gradients are also different. (2) Ignoring the FR/SR dichotomy leads one to conclude that compact galaxies are older than their larger counterparts of the same mass, even though almost the opposite is true for FRs and SRs individually. (3) SRs with σ0 ≤ 250 km s−1 are remarkably homogeneous within ∼Re: they are old, α-enhanced, and only slightly supersolar in metallicity. These SRs show no gradients in age and M*/Lr, negative gradients in metallicity, and slightly positive gradients in [α/Fe] (the latter are model dependent). SRs with σ0 ≥ 250 km s−1 are slightly younger and more metal rich, contradicting previous work suggesting that age increases with σ0. They also show larger M*/Lr gradients. (4) Self-consistently accounting for M*/L gradients yields Mdyn ≈ M* because gradients reduce Mdyn by ∼0.2 dex while only slightly increasing the M* inferred using a Kroupa (not Salpeter) initial mass function. (5) The SR population starts to dominate the counts above $M_*\ge 3\times 10^{11}\, \mathrm{M}_\odot$; this is the same scale at which the size–mass correlation and other scaling relations change. Our results support the finding that this is an important mass scale that correlates with the environment and above which mergers matter. 

We compare the two largest galaxy morphology catalogues, which separate early- and late-type galaxies at intermediate redshift. The two catalogues were built by applying supervised deep learning (convolutional neural networks, CNNs) to the Dark Energy Survey data down to a magnitude limit of ∼21 mag. The methodologies used for the construction of the catalogues include differences such as the cutout sizes, the labels used for training, and the input to the CNN – monochromatic images versus gri-band normalized images. In addition, one catalogue is trained using bright galaxies observed with DES (i < 18), while the other is trained with bright galaxies (r < 17.5) and ‘emulated’ galaxies up to r-band magnitude 22.5. Despite the different approaches, the agreement between the two catalogues is excellent up to i < 19, demonstrating that CNN predictions are reliable for samples at least one magnitude fainter than the training sample limit. It also shows that morphological classifications based on monochromatic images are comparable to those based on gri-band images, at least in the bright regime. At fainter magnitudes, i > 19, the overall agreement is good (∼95 per cent), but is mostly driven by the large spiral fraction in the two catalogues. In contrast, the agreement within the elliptical population is not as good, especially at faint magnitudes. By studying the mismatched cases, we are able to identify lenticular galaxies (at least up to i < 19), which are difficult to distinguish using standard classification approaches. The synergy of both catalogues provides an unique opportunity to select a population of unusual galaxies.

 

Abstract We present morphological classifications of ∼27 million galaxies from the Dark Energy Survey (DES) Data Release 1 (DR1) using a supervised deep learning algorithm. The classification scheme separates: (a) early-type galaxies (ETGs) from late-types (LTGs), and (b) face-on galaxies from edge-on. Our Convolutional Neural Networks (CNNs) are trained on a small subset of DES objects with previously known classifications. These typically have mr ≲ 17.7mag; we model fainter objects to mr < 21.5 mag by simulating what the brighter objects with well determined classifications would look like if they were at higher redshifts. The CNNs reach 97% accuracy to mr < 21.5 on their training sets, suggesting that they are able to recover features more accurately than the human eye. We then used the trained CNNs to classify the vast majority of the other DES images. The final catalog comprises five independent CNN predictions for each classification scheme, helping to determine if the CNN predictions are robust or not. We obtain secure classifications for ∼ 87% and 73% of the catalog for the ETG vs. LTG and edge-on vs. face-on models, respectively. Combining the two classifications (a) and (b) helps to increase the purity of the ETG sample and to identify edge-on lenticular galaxies (as ETGs with high ellipticity). Where a comparison is possible, our classifications correlate very well with Sérsic index (n), ellipticity (ε) and spectral type, even for the fainter galaxies. This is the largest multi-band catalog of automated galaxy morphologies to date.