arXiv subjects

H. Domínguez Sánchez

Publications and source records attributed to H. Domínguez Sánchez.

At least 37 records · Page 2Linked to original sources

arXiv2024

J-PLUS: The fraction of calcium white dwarfs along the cooling sequence

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.

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arXiv2024

MaNGA AGN dwarf galaxies (MAD) -- I. A new sample of AGN in dwarf galaxies with spatially resolved spectroscopy

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.

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arXiv2023

On the nature of disks at high redshift seen by JWST/CEERS with contrastive learning and cosmological simulations

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.

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arXiv2023

Identification of tidal features in deep optical galaxy images with Convolutional Neural Networks

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$6000 simulated images classified by professional astronomers. The mock Hyper Suprime Cam Subaru (HSC) images include variations with redshift, projection angle and surface brightness ($μ_{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.

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arXiv2023

J-PLUS: Towards an homogeneous photometric calibration using Gaia BP/RP low-resolution spectra

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.

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arXiv2022

Euclid preparation XXVI. The Euclid Morphology Challenge. Towards structural parameters for billions of galaxies

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 Sérsic 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 Sérsic 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.

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arXiv2022

Lessons Learned from the Two Largest Galaxy Morphological Classification Catalogues built by Convolutional Neural Networks

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.

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arXiv2022

From naked spheroids to disky galaxies: how do massive disk galaxies shape their morphology?

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 $0.14<z\leq 1$ in the wavelength range $0.5-1.6$ $μ$m, deriving the uncontaminated spectral energy distributions of their bulges and disks separately. This spectrophotometric decomposition allows us to compare the stellar populations properties of each component in individual galaxies. We find that the majority of massive galaxies ($\sim85\%$) builds inside-out, growing their extended stellar disk around the central spheroid. Some bulges and disks could start forming at similar epochs, but these bulges grow more rapidly than their disks, assembling $80\%$ of their mass in $\sim0.7$ Gyr and $\sim3.5$ Gyr, respectively. Moreover, we infer that both older bulges and older disks are more massive and compact than younger stellar structures. In particular, we find that bulges display a bimodal distribution of mass-weighted ages, i.e., they form in two waves. In contrast, our analysis of the disk components indicates that they form at $z\sim1$ for both first and second-wave bulges. This translates to first-wave bulges taking longer in acquiring a stellar disk ($5.2$ Gyr) compared to second-wave less-compact spheroids ($0.7$ Gyr). We do not find distinct properties (e.g., mass, star formation timescale, and mass surface density) for the disks in both types of galaxies. We conclude that the bulge mass and compactness mainly regulate the timing of the stellar disk growth, driving the morphological evolution of massive disk galaxies.

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arXiv2021

Differential attenuation in star-forming galaxies at 0.3 $\lesssim$ $z$ $\lesssim$ 1.5 in the SHARDS/CANDELS field

We use a sample of 706 galaxies, selected as [OII]$λ$3727 ([OII]) emitters in the Survey for High-$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$α$ 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$α$, 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.

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arXiv2021

SDSS-IV DR17: Final Release of MaNGA PyMorph Photometric and Deep Learning Morphological Catalogs

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 Sèrsic and Sèrsic+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.

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arXiv2021

Pushing automated morphological classifications to their limits with the Dark Energy Survey

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 Sérsic index (\textit{n}), ellipticity ($ε$) and spectral type, even for the fainter galaxies. This is the largest multi-band catalog of automated galaxy morphologies to date.

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arXiv2020

Hidden AGN in dwarf galaxies revealed by MaNGA: light echoes, off-nuclear wanderers, and a new broad-line AGN

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$α$ 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.

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arXiv2020

Galaxy properties as revealed by MaNGA. III. Kinematic profiles and stellar population gradients in S0s

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 $z\le 0.08$ 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 ($σ_0$). 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 $σ_r$ 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 $σ_0$, 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 $σ_0$ is held fixed.

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arXiv2019

Galaxy properties as revealed by MaNGA II. Differences in stellar populations of slow and fast rotator ellipticals and dependence on environment

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 $α$-enhanced and smaller than SRs of the same luminosity $L_r$ and central velocity dispersion $σ_0$. This explains why when one combines SRs and FRs, objects which are small for their $L_r$ and $σ_0$ 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 $σ_0\le 250$ km s$^{-1}$ are remarkably homogeneous within $\sim R_e$: they are old, $α$-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 [$α$/Fe] (the latter are model dependent). SRs with $σ_0\ge 250$ km $s^{-1}$ are slightly younger and more metal rich, contradicting previous work suggesting that age increases with $σ_0$. 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.

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arXiv2019

Galaxy properties as revealed by MaNGA. I. Constraints on Initial Mass Function and M$_{*}$/L gradients in ellipticals

We estimate ages, metallicities, $α$-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 ($σ_0$) 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 $σ_0$ 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.

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arXiv2019

Transfer learning for galaxy morphology from one survey to another

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.

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arXiv2018

SDSS-IV MaNGA PyMorph Photometric and Deep Learning Morphological Catalogs and implications for bulge properties and stellar angular momentum

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 Sérsic and Sérsic+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-Sérsic fits to late- and early-type galaxies are likely to return Sérsic 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.

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arXiv2018

A simultaneous search for High-$z$ LAEs and LBGs in the SHARDS survey

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$α$ 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.

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