In addition to the large systematic differences arising from assumptions about the stellar mass-to-light ratio, the massive end of the stellar mass function is rather sensitive to how one fits the ...light profiles of the most luminous galaxies. We quantify this by comparing the luminosity and stellar mass functions based on the Sloan Digital Sky Survey (SDSS) cmodel magnitudes, and PyMorph single-Sérsic and Sérsic-exponential fits to the surface brightness profiles of galaxies in the SDSS. The PyMorph fits return more light, so that the predicted masses are larger than when cmodel magnitudes are used. As a result, the total stellar mass density at z ∼ 0.1 is about 1.2 times larger than in our previous analysis of the SDSS. The differences are most pronounced at the massive end, where the measured number density of objects having M
* ≥ 6 × 1011 M is approximately five times larger. Alternatively, at number densities of 10−6 Mpc−3, the limiting stellar mass is two times larger. The differences with respect to fits by other authors, typically based on Petrosian-like magnitudes, are even more dramatic, although some of these differences are due to sky-subtraction problems, and are sometimes masked by large differences in the assumed M
*/L (even after scaling to the same initial mass function). Our results impact studies of the growth and assembly of stellar mass in galaxies, and of the relation between stellar and halo mass, so we provide simple analytic fits to these new luminosity and stellar mass functions and quantify how they depend on morphology, as well as the binned counts in electronic format. While these allow one to quantify the differences which arise because of the assumed light profile, and we believe our Sérsic-exponential based results to be the most realistic of the models we have tested, we caution that which profile is the most appropriate at the high-mass end is still debated.
Abstract
We present a morphological catalogue for ∼670 000 galaxies in the Sloan Digital Sky Survey in two flavours: T-type, related to the Hubble sequence, and Galaxy Zoo 2 (GZ2 hereafter) ...classification scheme. By combining accurate existing visual classification catalogues with machine learning, we provide the largest and most accurate morphological catalogue up to date. The classifications are obtained with Deep Learning algorithms using Convolutional Neural Networks (CNNs). We use two visual classification catalogues, GZ2 and Nair & Abraham (2010), for training CNNs with colour images in order to obtain T-types and a series of GZ2 type questions (disc/features, edge-on galaxies, bar signature, bulge prominence, roundness, and mergers). We also provide an additional probability enabling a separation between pure elliptical (E) from S0, where the T-type model is not so efficient. For the T-type, our results show smaller offset and scatter than previous models trained with support vector machines. For the GZ2 type questions, our models have large accuracy (>97 per cent), precision and recall values (>90 per cent), when applied to a test sample with the same characteristics as the one used for training. The catalogue is publicly released with the paper.
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
Numerous ongoing and future large area surveys (e.g. Dark Energy Survey, EUCLID, Large Synoptic Survey Telescope, Wide Field Infrared Survey Telescope) will increase by several orders of ...magnitude the volume of data that can be exploited for galaxy morphology studies. The full potential of these surveys can be unlocked only with the development of automated, fast, and reliable analysis methods. In this paper, we present DeepLeGATo, a new method for 2-D photometric galaxy profile modelling, based on convolutional neural networks. Our code is trained and validated on analytic profiles (HST/CANDELS F160W filter) and it is able to retrieve the full set of parameters of one-component Sérsic models: total magnitude, effective radius, Sérsic index, and axis ratio. We show detailed comparisons between our code and galfit. On simulated data, our method is more accurate than galfit and ∼3000 time faster on GPU (∼50 times when running on the same CPU). On real data, DeepLeGATo trained on simulations behaves similarly to galfit on isolated galaxies. With a fast domain adaptation step made with the 0.1–0.8 per cent the size of the training set, our code is easily capable to reproduce the results obtained with galfit even on crowded regions. DeepLeGATo does not require any human intervention beyond the training step, rendering it much automated than traditional profiling methods. The development of this method for more complex models (two-component galaxies, variable point spread function, dense sky regions) could constitute a fundamental tool in the era of big data in astronomy.
Abstract
We quantify the systematic effects on the stellar mass function that arise from assumptions about the stellar population, as well as how one fits the light profiles of the most luminous ...galaxies at z ∼ 0.1. When comparing results from the literature, we are careful to separate out these effects. Our analysis shows that while systematics in the estimated comoving number density that arise from different treatments of the stellar population remain of the order of ≤0.5 dex, systematics in photometry are now about 0.1 dex, in contrast to some recent claims in the literature. Compared to these more recent analyses, previous work based on Sloan Digital Sky Survey pipeline photometry leads to underestimates of ρ*(≥M*) by factors of 3–10 in the mass range 1011–1011.6 M⊙, but up to a factor of 100 at higher stellar masses. This impacts studies that match massive galaxies to dark matter haloes. Although systematics that arise from different treatments of the stellar population remain of the order of ≤0.5 dex, our finding that systematics in photometry now amount to only about 0.1 dex in the stellar mass density is a significant improvement with respect to a decade ago. Our results highlight the importance of using the same stellar population and photometric models whenever low- and high-redshift samples are compared.
Abstract
Mid-infrared (mid-IR) observations are powerful in identifying heavily obscured active galactic nuclei (AGN) that have weak emission in other wavelengths. Data from the Mid-Infrared ...Instrument (MIRI) on board the James Webb Space Telescope provides an excellent opportunity to perform such studies. We take advantage of the MIRI imaging data from the Cosmic Evolution Early Release Science Survey to investigate the AGN population in the distant universe. We estimate the source properties of MIRI-selected objects by utilizing spectral energy distribution (SED) modeling, and classify them into star-forming galaxies (SFs), SF-AGN mixed objects, and AGN. The source numbers of these types are 433, 102, and 25, respectively, from four MIRI pointings covering ∼9 arcmin
2
. The sample spans a redshift range of ≈0–5. We derive the median SEDs for all three source types, respectively, and publicly release them. The median MIRI SED of AGN is similar to the typical SEDs of hot dust-obscured galaxies and Seyfert 2s, for which the mid-IR SEDs are dominated by emission from AGN-heated hot dust. Based on our SED-fit results, we estimate the black hole accretion density (BHAD; i.e., total BH growth rate per comoving volume) as a function of redshift. At
z
< 3, the resulting BHAD agrees with the X-ray measurements in general. At
z
> 3, we identify a total of 27 AGN and SF-AGN mixed objects, leading to that our high-
z
BHAD is substantially higher than the X-ray results (∼0.5 dex at
z
≈ 3–5). This difference indicates MIRI can identify a large population of heavily obscured AGN missed by X-ray surveys at high redshifts.
We quantify the systematics in the size–luminosity relation of galaxies in the Sloan Digital Sky Survey main sample (i.e. at z ∼ 0.1) which arise from fitting different one- and two-component model ...profiles to the r-band images. For objects brighter than L
*, fitting a single Sérsic profile to what is really a two-component SerExp system leads to biases: the half-light radius is increasingly overestimated as n of the fitted single component increases; it is also overestimated at B/T ∼ 0.6. For such objects, the assumption of a single Sérsic component is particularly misleading. However, the net effect on the R-L relation is small, except for the most luminous tail. We then study how this relation depends on morphology. Our analysis is one of the first to use Bayesian-classifier-derived weights, rather than hard cuts, to define morphology. For the R-L relation Es, S0s and Sas are early types, whereas Sbs and Scds are late, although S0s tend to be 15 per cent smaller than Es of the same luminosity, and faint Sbs are more than 25 per cent smaller than faint Scds. Neither the early- nor the late-type relations are pure power laws: both show significant curvature, which we quantify. This curvature confirms that two mass scales are special for both early- and late-type galaxies: M
* ∼ 3 × 1010 and 2 × 1011 M⊙. Also, although the R
disc-L
disc and R
disc-M
*disc relations of discs of disc-dominated galaxies run parallel to the corresponding relations for the total light in late types (i.e. they are significantly curved), R
bulge-L
bulge and R
bulge-M
*bulge for bulge-dominated systems show almost no curvature (i.e. unlike for the total light of early-type galaxies). Finally, the intrinsic scatter in the R-L relation decreases at large L and/or M
* and should provide additional constraints on models of how the most massive galaxies formed.
We use machine learning to identify in color images of high-redshift galaxies an astrophysical phenomenon predicted by cosmological simulations. This phenomenon, called the blue nugget (BN) phase, is ...the compact star-forming phase in the central regions of many growing galaxies that follows an earlier phase of gas compaction and is followed by a central quenching phase. We train a convolutional neural network (CNN) with mock "observed" images of simulated galaxies at three phases of evolution- pre-BN, BN, and post-BN-and demonstrate that the CNN successfully retrieves the three phases in other simulated galaxies. We show that BNs are identified by the CNN within a time window of ∼0.15 Hubble times. When the trained CNN is applied to observed galaxies from the CANDELS survey at z = 1-3, it successfully identifies galaxies at the three phases. We find that the observed BNs are preferentially found in galaxies at a characteristic stellar mass range, 109.2-10.3 M at all redshifts. This is consistent with the characteristic galaxy mass for BNs as detected in the simulations and is meaningful because it is revealed in the observations when the direct information concerning the total galaxy luminosity has been eliminated from the training set. This technique can be applied to the classification of other astrophysical phenomena for improved comparison of theory and observations in the era of large imaging surveys and cosmological simulations.
We study the dependence of the galaxy size evolution on morphology, stellar mass and large-scale environment for a sample of 298 group and 384 field quiescent early-type galaxies from the COSMOS ...survey, selected from z ∼ 1 to the present, and with masses log(M/M) > 10.5.
From a detailed morphological analysis we infer that ∼80 per cent of passive galaxies with mass log(M/M) > 10.5 have an early-type morphology and that this fraction does not evolve over the last 6 Gyr. However, the relative abundance of lenticular and elliptical galaxies depends on stellar mass. Elliptical galaxies dominate only at the very high mass end - log(M/M) > 11 - while S0 galaxies dominate at lower stellar masses - 10.5 < log(M/M) < 11.
The galaxy size growth depends on galaxy mass range and early-type galaxy morphology, e.g. elliptical galaxies evolve differently than lenticular galaxies. At the low-mass end - 10.5 < log(M/M) < 11 - ellipticals do not show strong size growth from z ∼ 1 to the present (10 to 30 per cent depending on the morphological classification). On the other end, massive ellipticals - log(M/M) > 11.2 - approximately doubled their size. Interestingly, lenticular galaxies display different behaviour: they appear more compact on average and they do show a size growth of ∼60 per cent since z = 1 independent of stellar mass range.
We compare our results with state-of-the art semi-analytic models. While major and minor mergers can account for most of the galaxy size growth, we find that with present data and the theoretical uncertainties in the modelling we cannot state clear evidence favouring either merger or mass-loss via quasar and/or stellar winds as the primary mechanism driving the evolution.
The galaxy mass-size relation and size growth do not depend on environment in the halo mass range explored in this work (field to group mass log(M
h/M) < 14), i.e. group and field galaxies follow the same trends. At low redshift, where we examine both Sloan Digital Sky Survey and COSMOS groups, this result is at variance with predictions from some current hierarchical models that show a clear dependence of size growth on halo mass for massive ellipticals (log(M
*/M) > 11.2). In future work, we will analyse in detail if this result is specific of the observations and model used in this work.
Brightest Cluster Galaxies (BCG) and satellite galaxies lie on the same mass-size relation, at variance with predictions from hierarchical models, which predict that BCGs should have larger sizes than satellites because they experience more mergers in groups over the halo mass range probed.
ABSTRACT
This paper studies pseudo-bulges (P-bulges) and classical bulges (C-bulges) in Sloan Digital Sky Survey (SDSS) central galaxies using the new bulge indicator ΔΣ1, which measures relative ...central stellar-mass surface density within 1 kpc. We compare ΔΣ1 to the established bulge-type indicator Δ〈μe〉 from Gadotti (2009) and show that classifying by ΔΣ1 agrees well with Δ〈μe〉. ΔΣ1 requires no bulge–disc decomposition and can be measured on SDSS images out to z = 0.07. Bulge types using it are mapped on to 20 different structural and stellar-population properties for 12 000 SDSS central galaxies with masses 10.0 < log M*/M⊙ < 10.4. New trends emerge from this large sample. Structural parameters show fairly linear log–log relations versus ΔΣ1 and Δ〈μe〉 with only moderate scatter, while stellar-population parameters show a highly non-linear ‘elbow’ in which specific star formation rate remains roughly flat with increasing central density and then falls rapidly at the elbow, where galaxies begin to quench. P-bulges occupy the low-density end of the horizontal arm of the elbow and are universally star forming, while C-bulges occupy the elbow and the vertical branch and exhibit a wide range of star formation rates at a fixed density. The non-linear relation between central density and star formation rate has been seen before, but this mapping on to bulge class is new. The wide range of star formation rates in C-bulges helps to explain why bulge classifications using different parameters have sometimes disagreed in the past. The elbow-shaped relation between density and stellar indices suggests that central structure and stellar populations evolve at different rates as galaxies begin to quench.
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