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Stellar disk truncations, also referred to as galaxy edges, are key indicators of galactic size, determined by the radial location of the gas density threshold for star formation. Accurately measuring galaxy sizes for millions of galaxies is essential for understanding the physical processes driving galaxy evolution over cosmic time. In this study, we aim to explore the potential of the Segment Anything Model (SAM), a foundation model designed for image segmentation, to automatically identify disk truncations in galaxy images. With the Euclid Wide Survey poised to deliver vast datasets, our goal is to assess SAM's capability to measure galaxy sizes in a fully automated manner. SAM was applied to a labeled dataset of 1,047 disk-like galaxies with $M_* > 10^{10} M_{\odot}$ at redshifts up to $z \sim 1$, sourced from the HST CANDELS fields. We 'euclidized' the HST galaxy images by creating composite RGB images, using the F160W (H-band), F125W (J-band), and F814W + F606W (I-band + V-band) HST filters, respectively. Using these processed images as input for SAM, we retrieved various truncation masks for each galaxy image under different configurations of the input data. We find excellent agreement between the galaxy sizes identified by SAM and those measured manually (i.e., by using the radial positions of the stellar disk edges in galaxy light profiles), with an average deviation of approximately $3\%$. This error reduces to about $1\%$ when excluding problematic cases. Our results highlight the strong potential of SAM for detecting disk truncations and measuring galaxy sizes across large datasets in an automated way. SAM performs well without requiring extensive image preprocessing, labeled training datasets for truncations (used only for validation), fine-tuning, or additional domain-specific adaptations such as transfer learning., Comment: Accepted for publication in Astronomy & Astrophysics (11 pages, 10 figures)

We used the Javalambre Photometric Local Universe Survey (J-PLUS) DR2 photometry in twelve optical bands over 2176 deg2 to estimate the fraction of white dwarfs with presence of CaII H+K absorption along the cooling sequence. We compared the J-PLUS photometry against metal-free theoretical models to estimate the equivalent width in the J0395 passband of 10 nm centered at 395 nm (EW_J0395), a proxy to detect calcium absorption. A total of 4399 white dwarfs within 30000 > Teff > 5500 K and mass M > 0.45 Msun were analyzed. Their EW_J0395 distribution was modeled using two populations, corresponding to polluted and non-polluted systems, to estimate the fraction of calcium white dwarfs (f_Ca) as a function of Teff. The probability for each individual white dwarf of presenting calcium absorption, pca, was also computed. The comparison with both the measured Ca/He abundance and the metal pollution from spectroscopy shows that EW_J0395 correlates with the presence of calcium. The fraction of calcium white dwarfs increases from f_Ca = 0 at Teff = 13500 K to f_Ca = 0.15 at Teff = 5500 K. We compare our results with the fractions derived from the 40 pc spectroscopic sample and from SDSS spectra. The trend found in J-PLUS observations is also present in the 40 pc sample, however SDSS shows a deficit of metal-polluted objects at Teff < 12000 K. Finally, we found 39 white dwarfs with pca > 0.99. Twenty of them have spectra presented in previous studies, whereas we observed six additional targets. These 26 objects were all confirmed as metal-polluted systems. The J-PLUS optical data provide a robust statistical measurement for the presence of CaII H+K absorption in white dwarfs. We find a 15 +- 3 % increase in the fraction of calcium white dwarfs from Teff = 13500 K to 5500 K, which reflects their selection function in the optical from the total population of metal-polluted systems., Comment: Submitted to Astronomy and Astrophysics. Comments are welcome

The current standard model of cosmology successfully describes a variety of measurements, but the nature of its main ingredients, dark matter and dark energy, remains unknown. Euclid is a medium-class mission in the Cosmic Vision 2015-2025 programme of the European Space Agency (ESA) that will provide high-resolution optical imaging, as well as near-infrared imaging and spectroscopy, over about 14,000 deg^2 of extragalactic sky. In addition to accurate weak lensing and clustering measurements that probe structure formation over half of the age of the Universe, its primary probes for cosmology, these exquisite data will enable a wide range of science. This paper provides a high-level overview of the mission, summarising the survey characteristics, the various data-processing steps, and data products. We also highlight the main science objectives and expected performance., Comment: Accepted for publication in the A&A special issue`Euclid on Sky'

The Euclid mission is expected to image millions of galaxies with high resolution, providing an extensive dataset to study galaxy evolution. We investigate the application of deep learning to predict the detailed morphologies of galaxies in Euclid using Zoobot a convolutional neural network pretrained with 450000 galaxies from the Galaxy Zoo project. We adapted Zoobot for emulated Euclid images, generated based on Hubble Space Telescope COSMOS images, and with labels provided by volunteers in the Galaxy Zoo: Hubble project. We demonstrate that the trained Zoobot model successfully measures detailed morphology for emulated Euclid images. It effectively predicts whether a galaxy has features and identifies and characterises various features such as spiral arms, clumps, bars, disks, and central bulges. When compared to volunteer classifications Zoobot achieves mean vote fraction deviations of less than 12% and an accuracy above 91% for the confident volunteer classifications across most morphology types. However, the performance varies depending on the specific morphological class. For the global classes such as disk or smooth galaxies, the mean deviations are less than 10%, with only 1000 training galaxies necessary to reach this performance. For more detailed structures and complex tasks like detecting and counting spiral arms or clumps, the deviations are slightly higher, around 12% with 60000 galaxies used for training. In order to enhance the performance on complex morphologies, we anticipate that a larger pool of labelled galaxies is needed, which could be obtained using crowdsourcing. Finally, our findings imply that the model can be effectively adapted to new morphological labels. We demonstrate this adaptability by applying Zoobot to peculiar galaxies. In summary, our trained Zoobot CNN can readily predict morphological catalogues for Euclid images., Comment: 27 pages, 26 figures, 5 tables, published in A&A

The finding of active galactic nuclei (AGN) in dwarf galaxies has important implications for galaxy evolution and supermassive black hole formation models. Yet, how AGN in dwarf galaxies form is still debated, in part due to scant demographics. We make use of the MaNGA survey, comprising $\sim$10,000 galaxies at z $<$ 0.15, to identify AGN dwarf galaxies using a spaxel by spaxel classification in three spatially-resolved emission line diagnostic diagrams (the [NII-, [SII]- and [OI]-BPT) and the WHAN diagram. This yields a sample of 664 AGN dwarf galaxies, the largest to date, and an AGN fraction of $\sim20\%$ that is significantly larger than that of single-fiber-spectroscopy studies (i.e. $\sim1\%$). This can be explained by the lower bolometric luminosity ($< 10^{42}$ erg s$^{-1}$) and accretion rate (sub-Eddington) of the MaNGA AGN dwarf galaxies. We additionally identify 1,176 SF-AGN (classified as star-forming in the [NII]-BPT but as AGN in the [SII]- and [OI]-BPT), 122 Composite, and 173 LINER sources. The offset between the optical center of the galaxy and the median position of the AGN spaxels is more than 3 arcsec for $\sim$62\% of the AGN, suggesting that some could be off-nuclear. We also identify seven new broad-line AGN with log $M_\mathrm{BH}$ = 5.0 - 5.9 $M_\mathrm{\odot}$. Our results show how integral-field spectroscopy is a powerful tool for uncovering faint and low-accretion AGN and better constraining the demographics of AGN in dwarf galaxies., Comment: 18 pages, accepted for publication in MNRAS

Forthcoming imaging surveys will potentially increase the number of known galaxy-scale strong lenses by several orders of magnitude. For this to happen, images of tens of millions of galaxies will have to be inspected to identify potential candidates. In this context, deep learning techniques are particularly suitable for the finding patterns in large data sets, and convolutional neural networks (CNNs) in particular can efficiently process large volumes of images. We assess and compare the performance of three network architectures in the classification of strong lensing systems on the basis of their morphological characteristics. We train and test our models on different subsamples of a data set of forty thousand mock images, having characteristics similar to those expected in the wide survey planned with the ESA mission \Euclid, gradually including larger fractions of faint lenses. We also evaluate the importance of adding information about the colour difference between the lens and source galaxies by repeating the same training on single-band and multi-band images. Our models find samples of clear lenses with $\gtrsim 90\%$ precision and completeness, without significant differences in the performance of the three architectures. Nevertheless, when including lenses with fainter arcs in the training set, the three models' performance deteriorates with accuracy values of $\sim 0.87$ to $\sim 0.75$ depending on the model. Our analysis confirms the potential of the application of CNNs to the identification of galaxy-scale strong lenses. We suggest that specific training with separate classes of lenses might be needed for detecting the faint lenses since the addition of the colour information does not yield a significant improvement in the current analysis, with the accuracy ranging from $\sim 0.89$ to $\sim 0.78$ for the different models., Comment: 23 pages,12 figures

Interactions between galaxies leave distinguishable imprints in the form of tidal features which hold important clues about their mass assembly. Unfortunately, these structures are difficult to detect because they are low surface brightness features so deep observations are needed. Upcoming surveys promise several orders of magnitude increase in depth and sky coverage, for which automated methods for tidal feature detection will become mandatory. We test the ability of a convolutional neural network to reproduce human visual classifications for tidal detections. We use as training $\sim$6000 simulated images classified by professional astronomers. The mock Hyper Suprime Cam Subaru (HSC) images include variations with redshift, projection angle and surface brightness ($\mu_{lim}$ =26-35 mag arcsec$^{-2}$). We obtain satisfactory results with accuracy, precision and recall values of Acc=0.84, P=0.72 and R=0.85, respectively, for the test sample. While the accuracy and precision values are roughly constant for all surface brightness, the recall (completeness) is significantly affected by image depth. The recovery rate shows strong dependence on the type of tidal features: we recover all the images showing shell features and 87% of the tidal streams; these fractions are below 75% for mergers, tidal tails and bridges. When applied to real HSC images, the performance of the model worsens significantly. We speculate that this is due to the lack of realism of the simulations and take it as a warning on applying deep learning models to different data domains without prior testing on the actual data., Comment: 13 pages, 10 figures, accepted for publication in MNRAS

Visual inspections of the first optical rest-frame images from JWST have indicated a surprisingly high fraction of disk galaxies at high redshifts. Here, we alternatively apply self-supervised machine learning to explore the morphological diversity at $z \geq 3$. Our proposed data-driven representation scheme of galaxy morphologies, calibrated on mock images from the TNG50 simulation, is shown to be robust to noise and to correlate well with the physical properties of the simulated galaxies, including their 3D structure. We apply the method simultaneously to F200W and F356W galaxy images of a mass-complete sample ($M_*/M_\odot>10^9$) at $ 3 \leq z \leq 6$ from the first JWST/NIRCam CEERS data release. We find that the simulated and observed galaxies do not exactly populate the same manifold in the representation space from contrastive learning. We also find that half the galaxies classified as disks -- either CNN-based or visually -- populate a similar region of the representation space as TNG50 galaxies with low stellar specific angular momentum and non-oblate structure. Although our data-driven study does not allow us to firmly conclude on the true nature of these galaxies, it suggests that the disk fraction at $z \geq 3$ remains uncertain and possibly overestimated by traditional supervised classifications. Deeper imaging and spectroscopic follow-ups as well as comparisons with other simulations will help to unambiguously determine the true nature of these galaxies, and establish more robust constraints on the emergence of disks at very high redshift., Comment: 28 pages, 22 figures. Accepted for publication in ApJ

We present the photometric calibration of the twelve optical passbands for the Javalambre Photometric Local Universe Survey (J-PLUS) third data release (DR3), comprising 1642 pointings of two square degrees each. We selected nearly 1.5 million main sequence stars with a signal-to-noise ratio larger than ten in the twelve J-PLUS passbands and available low-resolution (R = 20-80) spectrum from the blue and red photometers (BP/RP) in Gaia DR3. We compared the synthetic photometry from BP/RP spectra with the J-PLUS instrumental magnitudes, after correcting for the magnitude and color terms between both systems, to obtain an homogeneous photometric solution for J-PLUS. To circumvent the current limitations in the absolute calibration of the BP/RP spectra, the absolute color scale was derived using the locus of 109 white dwarfs closer than 100 pc with a negligible interstellar extinction. Finally, the absolute flux scale was anchored to the Panoramic Survey Telescope and Rapid Response System (Pan-STARRS) photometry in the r band. The precision of the J-PLUS photometric calibration, estimated from duplicated objects observed in adjacent pointings and by comparison with the spectro-photometric standard star GD 153, is ~12 mmag in u, J0378, and J0395; and ~7 mmag in J0410, J0430, g, J0515, r, J0660, i, J0861, and z. The estimated accuracy in the calibration along the surveyed area is better than 1% for all the passbands. The Gaia BP/RP spectra provide a high-quality, homogeneous photometric reference in the optical range across the full-sky, in spite of their current limitations as an absolute reference. The calibration method for J-PLUS DR3 reaches an absolute precision and accuracy of 1% in the twelve optical filters within an area of 3284 square degrees., Comment: Submitted to Astronomy and Astrophysics. 17 pages, 14 figures, 2 appendix. Comments are welcome. arXiv admin note: text overlap with arXiv:2101.12407

We study systematics associated with estimating simple stellar population (SSP) parameters -- age, metallicity [M/H], $\alpha$-enhancement [$\alpha$/Fe] and 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 H$_\beta$, $\langle$Fe$\rangle$, TiO$_{\rm 2SDSS}$ and [MgFe] Lick indices in the stacks, indicate that out to the half-light radius $R_e$: (a) ages are younger and [$\alpha$/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 $R_e/2$; (c) this makes $M_*/L$ about $2\times$ larger in the central regions than beyond $R_e/2$. While the models of Conroy et al. (2018) return similar [M/H] and [$\alpha$/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 [$\alpha$/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., Comment: 22 pages, 23 figures, accepted for publication in MNRAS

The various Euclid imaging surveys will become a reference for studies of galaxy morphology by delivering imaging over an unprecedented area of 15 000 square degrees with high spatial resolution. In order to understand the capabilities of measuring morphologies from Euclid-detected galaxies and to help implement measurements in the pipeline, we have conducted the Euclid Morphology Challenge, which we present in two papers. While the companion paper by Merlin et al. focuses on the analysis of photometry, this paper assesses the accuracy of the parametric galaxy morphology measurements in imaging predicted from within the Euclid Wide Survey. We evaluate the performance of five state-of-the-art surface-brightness-fitting codes DeepLeGATo, Galapagos-2, Morfometryka, Profit and SourceXtractor++ on a sample of about 1.5 million simulated galaxies resembling reduced observations with the Euclid VIS and NIR instruments. The simulations include analytic S\'ersic profiles with one and two components, as well as more realistic galaxies generated with neural networks. We find that, despite some code-specific differences, all methods tend to achieve reliable structural measurements (10% scatter on ideal S\'ersic simulations) down to an apparent magnitude of about 23 in one component and 21 in two components, which correspond to a signal-to-noise ratio of approximately 1 and 5 respectively. We also show that when tested on non-analytic profiles, the results are typically degraded by a factor of 3, driven by systematics. We conclude that the Euclid official Data Releases will deliver robust structural parameters for at least 400 million galaxies in the Euclid Wide Survey by the end of the mission. We find that a key factor for explaining the different behaviour of the codes at the faint end is the set of adopted priors for the various structural parameters., Comment: Accepted by A&A. 30 pages, 23+6 figures, Euclid pre-launch key paper. Companion paper: Euclid Collaboration XXV: Merlin et al. 2022 Minor corrections after journal review

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 $\sim$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 ($\sim$95\%), 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., Comment: 17 pages, 14 figures (1 appendix for galaxy examples including 3 figures)

We investigate the assembly history of massive disk galaxies and describe how they shape their morphology through cosmic time. Using SHARDS and HST data, we modeled the surface brightness distribution of 91 massive galaxies at redshift $0.14

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 are different. For old SPs, e.g., in early-type galaxies at $z\sim 0$, 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 center increases the estimated total stellar mass ($M_*$) and reduces the scale which contains half this mass ($R_{e,*}$), compared to when the gradient is ignored. For the IMF gradients inferred from fitting MILES simple SP models to the H$_\beta$, $\langle$Fe$\rangle$, [MgFe] and TiO$_{\rm 2SDSS}$ absorption lines measured in spatially resolved spectra of early-type galaxies in the MaNGA survey, the fractional change in $R_{e,*}$ can be significantly larger than that in $M_*$, especially when the light is more centrally concentrated. The $R_{e,*}-M_*$ correlation which results is offset by 0.3 dex to smaller sizes 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 the light profile before drawing conclusions about how $R_{e,*}$ and $M_*$ evolve. The implied merging between higher-$z$ and the present is less contrived if $R_{e,*}/R_e$ at $z\sim 0$ is closer to our IMF-driven gradient calibration than to unity., Comment: 16 pages, 15 figures, accepted for publication in MNRAS

We use a sample of 706 galaxies, selected as [OII]$\lambda$3727 ([OII]) emitters in the Survey for High-$z$ Absorption Red and Dead Sources (SHARDS) on the CANDELS/GOODS-N field, to study the differential attenuation of the nebular emission with respect to the stellar continuum. The sample includes only galaxies with a counterpart in the infrared and $\mathrm{log}_{10}(M_{*}/\mathrm{M}_{\odot})$ $>$ 9, over the redshift interval 0.3 $\lesssim$ $z$ $\lesssim$ 1.5. Our methodology consists in the comparison of the star formation rates inferred from [OII] and H$\alpha$ emission lines with a robust quantification of the total star-forming activity (${SFR}_{\mathrm{TOT}}$) that is independently estimated based on both infrared and ultraviolet (UV) luminosities. We obtain $f$$=$$E(B-V)_{\mathrm{stellar}}$/$E(B-V)_{\mathrm{nebular}}$ $=$ 0.69$^{0.71}_{0.69}$ and 0.55$^{0.56}_{0.53}$ for [OII] and H$\alpha$, respectively. Our resulting $f$-factors display a significant positive correlation with the UV attenuation and shallower or not-significant trends with the stellar mass, the $SFR_{\mathrm{TOT}}$, the distance to the main sequence, and the redshift. Finally, our results favour an average nebular attenuation curve similar in shape to the typical dust curve of local starbursts., Comment: 23 pages, 10 figures, 3 tables; accepted for publication in MNRAS

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 S\`ersic and S\`ersic+Exponential fits to the 2D surface brightness profiles of the MaNGA DR17 galaxy sample in the $g$, $r$, and $i$ bands (e.g. total fluxes, half light radii, bulge-disk 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: e.g., 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 which 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 are better recovered in this new version. The catalogue also includes a separation between Early- or Late-type Galaxies (ETG, LTG), 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., Comment: Accepted for publication in MNRAS. Catalogues will be released with SDSS Data Release 17

We present morphological classifications of $\sim$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 $\mathrm{m}_r \lesssim 17.7~\mathrm{mag}$; we model fainter objects to $\mathrm{m}_r < 21.5$ 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 $\mathrm{m}_r<21.5$ 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 $\sim$ 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 S\'ersic index (\textit{n}), ellipticity ($\epsilon$) and spectral type, even for the fainter galaxies. This is the largest multi-band catalog of automated galaxy morphologies to date., Comment: Accepted for publication in MNRAS (2021 February 22); 17 pages, 16 figures

Active galactic nuclei (AGN) in dwarf galaxies could possibly host the relics of those early Universe seed black holes that did not grow into supermassive black holes. Using MaNGA integral field unit (IFU) spectroscopy we have found a sample of 37 dwarf galaxies that show AGN ionisation signatures in spatially-resolved emission line diagnostic diagrams. The AGN signatures are largely missed by integrated emission line diagnostics for 23 of them. The bolometric luminosity of these 23 new AGN candidates is $\lesssim 10^{40}$ erg s$^{-1}$, fainter than that of single-fiber SDSS AGN, X-ray AGN, and radio AGN in dwarf galaxies, which stands IFU spectroscopy as a powerful tool for identifying hidden and faint AGN in dwarf galaxies. The AGN emission is in most cases offset from the optical center of the dwarf galaxy and shows a symmetric morphology, which indicates that either the AGN are off-nuclear, that the central emission of the galaxy is dominated by star formation, or that the AGN are turned-off and we are observing a past ionisation burst. One of the new AGN shows a broad H$\alpha$ emission line component, from which we derive a black hole mass in the realm of intermediate-mass black holes. This constitutes the first hidden type 1 AGN discovered in a dwarf galaxy based on IFU spectroscopy. The finding of this sample of hidden and faint AGN has important implications for population studies of AGN in dwarf galaxies and for seed black hole formation models., Comment: 13 pages, 5 figures, accepted for publication in ApJ Letters

This is the third paper of a series where we study the stellar population gradients (SP; ages, metallicities, $\alpha$-element abundance ratios and stellar initial mass functions) of early type galaxies (ETGs) at $z\le 0.08$ 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 (L$_r$) and central velocity dispersion ($\sigma_0$). We find that: 1) There is a bimodality in the S0 population: S0s more massive than $3\times 10^{10}M_\odot$ show stronger velocity dispersion and age gradients (age and $\sigma_r$ 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 $2\times10^{11}M_\odot$ 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 $\sigma_0$, more luminous S0s and E-FRs are younger, more metal rich and less $\alpha$-enhanced. Evidently for these galaxies, the usual statement that 'massive galaxies are older' is not true if $\sigma_0$ is held fixed., Comment: Accepted for publication in MNRAS. 15 pages, 20 figures

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 $R_e$, enclosed surface brightness $I_e$ and velocity dispersion $\sigma_e$. Since $I_e$ and $\sigma_e$ are distance-independent measurements, the thickness of the FP is often expressed in terms of the accuracy with which $I_e$ and $\sigma_e$ can be used to estimate sizes $R_e$. 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 $R_e$ is $\sim 16\%$, of which only $\sim 9\%$ is intrinsic. Removing galaxies with $M_*<10^{11}M_\odot$ further reduces the observed scatter to $\sim 13\%$ ($\sim 4\%$ intrinsic). The observed scatter increases to the $\sim 25\%$ 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 $5\%$ orthogonal to the plane. 2) The structure within the FP is most easily understood as arising from the fact that $I_e$ and $\sigma_e$ are nearly independent, whereas the $R_e-I_e$ and $R_e-\sigma_e$ 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 $I_e$ by the global stellar mass-to-light ratio $M_*/L$ and we account for non-homology across the population by using S\'ersic 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., Comment: 13 pages, 9 figures, 3 tables, accepted for publication in MNRAS

We estimate ages, metallicities, $\alpha$-element abundance ratios and stellar initial mass functions 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 $\le$ 0.08. We show that the properties of the inner regions of Es with the largest luminosity (L$_r$) and central velocity dispersion ($\sigma_0$) are consistent with those associated with the commonly used Salpeter IMF, whereas a Kroupa-like IMF is a better description at $\sim$ 0.8R/Re (assuming [Ti/Fe] variations are limited). 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 L$_r$ and $\sigma_0$ galaxies, the IMF is shallower and M$_{*}$/L$_r$ in the central regions is similar to the outskirts. Although a factor of 2 is smaller than previous reports based on a handful of galaxies, it is still large enough to matter for dynamical mass estimates. Accounting self-consistently for these gradients when estimating both M$_{*}$ and M$_{dyn}$ brings the two into good agreement: gradients reduce M$_{dyn}$ by $\sim$ 0.2 dex while only slightly increasing the M$_{*}$ inferred using a Kroupa IMF. This is a different resolution of the M$_{*}$-M$_{dyn}$ discrepancy than has been followed in the recent literature where M$_{*}$ of massive galaxies is increased by adopting a Salpeter IMF while leaving Mdyn unchanged. A companion paper discusses how stellar population differences are even more pronounced if one separates slow from fast rotators., Comment: 22 pages, 29 figures, accepted for publication in MNRAS

We present estimates of stellar population (SP) gradients from stacked spectra of slow (SR) and fast (FR) rotator elliptical galaxies from the MaNGA-DR15 survey. We find that: 1) FRs are $\sim 5$ Gyrs younger, more metal rich, less $\alpha$-enhanced and smaller than SRs of the same luminosity $L_r$ and central velocity dispersion $\sigma_0$. This explains why when one combines SRs and FRs, objects which are small for their $L_r$ and $\sigma_0$ 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 $\sigma_0\le 250$ km s$^{-1}$ are remarkably homogeneous within $\sim R_e$: they are old, $\alpha$-enhanced and only slightly super-solar in metallicity. These SRs show no gradients in age and $M_*/L_r$, negative gradients in metallicity, and slightly positive gradients in [$\alpha$/Fe] (the latter are model dependent). SRs with $\sigma_0\ge 250$ km $s^{-1}$ are slightly younger and more metal rich, contradicting previous work suggesting that age increases with $\sigma_0$. They also show larger $M_*/L_r$ gradients. 4) Self-consistently accounting for $M_*/L$ gradients yields $M_{\rm dyn}\approx M_*$ because gradients reduce $M_{\rm dyn}$ by $\sim 0.2$ dex while only slightly increasing the $M_*$ inferred using a Kroupa (not Salpeter) IMF. 5) The FR population all but disappears above $M_*\ge 3\times 10^{11}M_\odot$; 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 which correlates with the environment and above which mergers matter., Comment: 22 pages, 28 figures. Accepted for publication in MNRAS

We describe the SDSS-IV MaNGA PyMorph Photometric (MPP-VAC) and MaNGA Deep Learning Morphology (MDLM-VAC) Value Added Catalogs. The MPP-VAC provides photometric parameters from S\'ersic and S\'ersic+Exponential fits to the 2D surface brightness profiles of the MaNGA DR15 galaxy sample. Compared to previous PyMorph analyses of SDSS imaging, our analysis of the MaNGA DR15 incorporates three improvements: the most recent SDSS images; modified criteria for determining bulge-to-disk decompositions; and the fits in MPP-VAC have been eye-balled, and re-fit if necessary, for additional reliability. A companion catalog, the MDLM-VAC, provides Deep Learning-based morphological classifications for the same galaxies. The MDLM-VAC includes a number of morphological properties (e.g., a TType, and a finer separation between elliptical and S0 galaxies). Combining the MPP- and MDLM-VACs allows to show that the MDLM morphological classifications are more reliable than previous work. It also shows that single-S\'ersic fits to late- and early-type galaxies are likely to return S\'ersic indices of $n \le 2$ and $\ge 4$, respectively, and this correlation between $n$ and morphology extends to the bulge component as well. While the former is well-known, the latter contradicts some recent work suggesting little correlation between $n$-bulge and morphology. Combining both VACs with MaNGA's spatially resolved spectroscopy allows us to study how the stellar angular momentum depends on morphological type. We find correlations between stellar kinematics, photometric properties, and morphological type even though the spectroscopic data played no role in the construction of the MPP- and MDLM-VACs., Comment: 22 pages, 30 figures and 4 tables. Accepted for publication in MNRAS. The MPP-VAC and MDLM-VAC are available online at https://www.sdss.org/dr15/data_access/value-added-catalogs/manga-pymorph-dr15-photometric-catalog and https://www.sdss.org/dr15/data_access/value-added-catalogs/manga-morphology-deep-learning-dr15-catalog

Deep Learning (DL) algorithms for morphological classification of galaxies have proven very successful, mimicking (or even improving) visual classifications. However, these algorithms rely on large training samples of labelled galaxies (typically thousands of them). A key question for using DL classifications in future Big Data surveys is how much of the knowledge acquired from an existing survey can be exported to a new dataset, i.e. if the features learned by the machines are meaningful for different data. We test the performance of DL models, trained with Sloan Digital Sky Survey (SDSS) data, on Dark Energy survey (DES) using images for a sample of $\sim$5000 galaxies with a similar redshift distribution to SDSS. Applying the models directly to DES data provides a reasonable global accuracy ($\sim$ 90%), but small completeness and purity values. A fast domain adaptation step, consisting in a further training with a small DES sample of galaxies ($\sim$500-300), is enough for obtaining an accuracy > 95% and a significant improvement in the completeness and purity values. This demonstrates that, once trained with a particular dataset, machines can quickly adapt to new instrument characteristics (e.g., PSF, seeing, depth), reducing by almost one order of magnitude the necessary training sample for morphological classification. Redshift evolution effects or significant depth differences are not taken into account in this study., Comment: Accepted for publication in MNRAS

We have undertaken a comprehensive search for both Lyman Alpha Emitters (LAEs) and Lyman Break Galaxies (LBGs) in the SHARDS Survey of the GOODS-N field. SHARDS is a deep imaging survey, made with the 10.4 m Gran Telescopio Canarias (GTC), employing 25 medium band filters in the range from 500 to 941 nm. This is the first time that both LAEs and LBGs are surveyed simultaneously in a systematic way in a large field. We draw a sample of 1558 sources; 528 of them are LAEs. Most of the sources (1434) show rest-frame UV continua. A minority of them (124) are pure LAEs with virtually no continuum detected in SHARDS. We study these sources from $z\sim3.35$ up to $z\sim6.8$, well into the epoch of reionization. Note that surveys done with just one or two narrow band filters lack the possibility to spot the rest-frame UV continuum present in most of our LAEs. We derive redshifts, Star Formation Rates (SFRs), Ly$\alpha$ Equivalent Widths (EWs) and Luminosity Functions (LFs). Grouping within our sample is also studied, finding 92 pairs or small groups of galaxies at the same redshift separated by less than 60 comoving kpc. In addition, we relate 87 and 55 UV-selected objects with two known overdensities at $z=4.05$ and $z=5.198$, respectively. Finally, we show that surveys made with broad band filters are prone to introduce many unwanted sources ($\sim20$% interlopers), which means that previous studies may be overestimating the calculated LFs, specially at the faint end., Comment: Accepted for publication in MNRAS. 18 pages, 19 figures

The physical processes driving the evolution of star formation (SF) in galaxies over cosmic time still present many open questions. Recent galaxy surveys allow now to study these processes in great detail at intermediate redshift. In this work, we build a complete sample of star-forming galaxies and analyze their properties, reaching systems with low stellar masses and low star formation rates (SFRs) at intermediate-to-low redshift. We use data from the SHARDS multiband survey in the GOODS-North field. Its depth (up to magnitude $\langle m_{3\sigma}\rangle\sim26.5$) and its spectro-photometric resolution ($R\sim50$) provides us with an ideal dataset to search for emission line galaxies (ELGs). We develop a new algorithm to identify low-redshift ($z$<0.36) ELGs by detecting the [OIII]5007 and $H\alpha$ emission lines simultaneously. We fit the spectral energy distribution (SED) of the selected sample, using a model with two single stellar populations. We find 160 star-forming galaxies with equivalent widths (EWs) as low as 12 {\AA}, with median values for the sample of $\sim$ 35 {\AA} in [OIII]5007 and $\sim$ 56 {\AA} in $H\alpha$, respectively. Results from the SED fitting show a young stellar population with low median metallicity (36% of the solar value) and extinction ($A_V \sim$ 0.37), with median galaxy stellar mass $\sim$ 10$^{8.5}$ M$_{\odot}$. Gas-phase metallicities measured from available spectra are also low. ELGs in our sample present bluer colors in the UVJ plane than the median color-selected star-forming galaxy in SHARDS. We suggest a new (V-J) color criterion to separate ELGs from non-ELGs in blue galaxy samples. In addition, several galaxies present high densities of O-type stars. Robust fits to the full SEDs can only be obtained including an old stellar population, suggesting the young component is built up by a recent burst of SF in an otherwise old galaxy., Comment: Accepted for publication in Astronomy & Astrophysics. 17 pages, 17 figures

We present a morphological catalogue for $\sim$ 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 (disk/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\%), precision and recall values (> 90\%) when applied to a test sample with the same characteristics as the one used for training. The catalogue is publicly released with the paper., Comment: 18 pages, 21 figures; Accepted for publication in MNRAS

Numerous ongoing and future large area surveys (e.g. DES, EUCLID, LSST, WFIRST), 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 only be unlocked with the development of automated, fast and reliable analysis methods. In this paper we present DeepLeGATo, a new method for two-dimensional photometric galaxy profile modeling, 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 S\'ersic models: total magnitude, effective radius, S\'ersic index, 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 run 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 PSF, dense sky regions) could constitute a fundamental tool in the era of big data in astronomy., Comment: 17 pages, 9 figures

We explore the stellar initial mass function (IMF) of a sample of 49 massive quiescent galaxies (MQGs) at 0.9$<$z$<$1.5. We base our analysis on intermediate resolution spectro-photometric data in the GOODS-N field taken in the near-infrared and optical with the HST/WFC3 G141 grism and the Survey for High-z Absorption Red and Dead Sources (SHARDS). To constrain the slope of the IMF, we have measured the TiO$_2$ spectral feature, whose strength depends strongly on the content of low-mass stars, as well as on stellar age. Using ultraviolet to near-infrared individual and stacked spectral energy distributions, we have independently estimated the stellar ages of our galaxies. Knowing the age of the stellar population, we interpret the strong differences in the TiO$_2$ feature as an IMF variation. In particular, for the heaviest z$\sim$1 MQGs (M$>$10$^{11}$Msun) we find an average age of 1.7$\pm$0.3 Gyr and a bottom-heavy IMF ($\Gamma_b$=3.2$\pm$0.2). Lighter MQGs (2$\times$10$^{10}$$<$M$<$10$^{11}$ Msun) at the same redshift are younger on average (1.0$\pm$0.2 Gyr) and present a shallower IMF slope ($\Gamma_b=2.7^{+0.3}_{-0.4}$). Our results are in good agreement with the findings about the IMF slope in early-type galaxies of similar mass in the present-day Universe. This suggests that the IMF, a key characteristic of the stellar populations in galaxies, is bottom-heavier for more massive galaxies and has remained unchanged in the last $\sim$8 Gyr., Comment: 6 pages, 5 figures, accepted for publication in ApJL

We compare various star formation rate (SFR) indicators for star-forming galaxies at $1.4

We study a hundred of galaxies from the spectroscopic Sloan Digital Sky Survey with individual detections in the Far-Infrared Herschel PACS bands (100 or 160 $\mu$m) and in the GALEX Far-UltraViolet band up to z$\sim$0.4 in the COSMOS and Lockman Hole fields. The galaxies are divided into 4 spectral and 4 morphological types. For the star forming and unclassifiable galaxies we calculate dust extinctions from the UV slope, the H$\alpha$/H$\beta$ ratio and the $L_{\rm IR}/L_{\rm UV}$ ratio. There is a tight correlation between the dust extinction and both $L_{\rm IR}$ and metallicity. We calculate SFR$_{total}$ and compare it with other SFR estimates (H$\alpha$, UV, SDSS) finding a very good agreement between them with smaller dispersions than typical SFR uncertainties. We study the effect of mass and metallicity, finding that it is only significant at high masses for SFR$_{H\alpha}$. For the AGN and composite galaxies we find a tight correlation between SFR and L$_{IR}$ ($\sigma\sim$0.29), while the dispersion in the SFR - L$_{UV}$ relation is larger ($\sigma\sim$0.57). The galaxies follow the prescriptions of the Fundamental Plane in the M-Z-SFR space., Comment: 24 pages, 23 figures, accepted for publication in MNRAS

We analyse the rest-frame UV-to-NIR spectral energy distribution (SED) of Lyman break galaxies (LBGs), star-forming (SF) BzK (sBzK), and UV-selected galaxies at 1.5 < z < 2.5 in the COSMOS, GOODS-N, and GOODS-S fields. Additionally, we complement the multi-wavelength coverage of the galaxies located in the GOODS fields with deep FIR data taken from the GOODS-Herschel project. We find that sBzK galaxies represent the general population of SF galaxies at z ~ 2 better than LBGs. For a given stellar mass, LBGs tend to have bluer optical colours than sBzK and UV-selected galaxies. We find clean PACS individual detections for a subsample of 48 LBGs, 89 sBzK, and 91 UV-selected galaxies, that measure their dust emission directly. Their SFR_total = SFR_UV + SFR_IR cannot be recovered with the dust-correction factors derived with their continuum slope and the IRX-beta relations for local starbursts. This has implications, for example, in the definition of the main sequence (MS) at z ~ 2. PACS-detected galaxies are located above the z ~ 2 MS and thus their star formation is probably driven by starburst. This is in agreement with the shape of their IR SEDs. PACS-detected galaxies with redder UV continuum slope and higher stellar mass are more attenuated. We find that for a given UV continuum slope the dustiest galaxies at higher redshifts are more attenuated and that for a given stellar mass the dustiest galaxies at higher redshifts have stronger FIR emission. This suggests an evolution of their dust properties. However, we do not find significant evolution in the relation between dust attenuation and stellar mass with redshift, at least at z < 2.5. There is a subpopulation of 17, 26, and 27 LBGs, sBzK, and UV-selected galaxies, respectively, that are detected in any of the SPIRE bands. We speculate that SPIRE-detected LBGs are the bridging population between sub-mm galaxies and LBGs., Comment: Accepted for publication in MNRAS

Lyman break galaxies (LBGs) represent one of the kinds of star-forming galaxies that are found in the high-redshift universe. The detection of LBGs in the FIR domain can provide very important clues on their dust attenuation and total SFR, allowing a more detailed study than those performed so far. In this work we explore the FIR emission of a sample of 16 LBGs at z ~ 3 in the GOODS-North and GOODS-South fields that are individually detected in PACS-100um or PACS-160um. These detections demonstrate the possibility of measuring the dust emission of LBGs at high redshift. We find that PACS-detected LBGs at z ~ 3 are highly obscured galaxies which belong to the Ultra luminous IR galaxies or Hyper luminous IR galaxies class. Their total SFR cannot be recovered with the dust attenuation factors obtained from their UV continuum slope or their SED-derived dust attenuation employing Bruzual & Charlot (2003) templates. Both methods underestimate the results for most of the galaxies. Comparing with a sample of PACS-detected LBGs at z ~ 1 we find evidences that the FIR emission of LBGs might have changed with redshift in the sense that the dustiest LBGs found at z ~ 3 have more prominent FIR emission, are dustier for a given UV slope, and have higher SFR for a given stellar mass than the dustiest LBGs found at z ~ 1., Comment: Accepted for publication in A&A letters

We have studied the evolution of high redshift quiescent galaxies over an effective area of ~1.7 deg^2 in the COSMOS field. Galaxies have been divided according to their star-formation activity and the evolution of the different populations has been investigated in detail. We have studied an IRAC (mag_3.6 < 22.0) selected sample of ~18000 galaxies at z > 1.4 with multi-wavelength coverage. We have derived accurate photometric redshifts (sigma=0.06) and other important physical parameters through a SED-fitting procedure. We have divided our sample into actively star-forming, intermediate and quiescent galaxies depending on their specific star formation rate. We have computed the galaxy stellar mass function of the total sample and the different populations at z=1.4-3.0. We have studied the properties of high redshift quiescent galaxies finding that they are old (1-4 Gyr), massive (log(M/M_sun)~10.65), weakly star forming stellar populations with low dust extinction (E(B-V) < 0.15) and small e-folding time scales (tau ~ 0.1-0.3 Gyr). We observe a significant evolution of the quiescent stellar mass function from 2.5 < z < 3.0 to 1.4 < z < 1.6, increasing by ~ 1 dex in this redshift interval. We find that z ~ 1.5 is an epoch of transition of the GSMF. The fraction of star-forming galaxies decreases from 60% to 20% from z ~ 2.5-3.0 to z ~ 1.4-1.6 for log(M/M_sun) > 11, while the quiescent population increases from 10% to 50% at the same redshift and mass intervals. We compare the fraction of quiescent galaxies derived with that predicted by theoretical models and find that the Kitzbichler & White (2007) model is the one that better reproduces the data. Finally, we calculate the stellar mass density of the star-forming and quiescent populations finding that there is already a significant number of quiescent galaxies at z > 2.5 (rho~6.0 MsunMpc^-3)., Comment: 17 pages, 20 figures, 5 tables. Accepted for publication in MNRAS