arXiv subjects

N. M. Cardoso

Publications and source records attributed to N. M. Cardoso.

7 recordsLinked to original sources

arXiv2026

CLAS+: A large catalog of Changing-Look AGN candidates selected through S-PLUS narrow-band photometry

Changing-look active galactic nuclei (CLAGN) exhibit rapid spectral transitions on timescales of months to years, challenging standard AGN unification models and providing unique insight into accretion-disk variability and obscuration processes. Despite their scientific importance, systematic searches for CLAGN remain limited by the scarcity of multi-epoch spectroscopy and the difficulty of constructing large samples efficiently. We introduce CLAS+, a catalog constructed by comparing synthetic photometry derived from DESI DR1 and SDSS DR17 spectra with contemporaneous narrow-band imaging from the S-PLUS survey. Applying our pipeline to a parent sample of 98,139 quasars, we select high-confidence CLAGN candidates above a threshold of reduced chi-squared $χ_r^2 > 15$. We identify 3,554 strong CLAGN candidates, corresponding to 3.6\% of the parent sample. This selected fraction is conditional on the adopted criterion and should not be interpreted as an intrinsic CLAGN occurrence rate. Cross-matching with existing CLAGN compilations shows that CLAS+ identifies a large population of previously unreported high-priority candidates (3,481). Among the spectroscopic--photometric comparisons with reliable temporal classification, 40\% are classified as photometric turn-on, 41\% as intermediate, and 19\% as turn-off. We also find an apparent redshift dependence in the relative fractions, with photometric turn-on candidates becoming more common at higher redshifts within the CLAS+ selected sample. Therefore, narrow-band photometry provides a powerful and efficient alternative to purely spectroscopic searches for identifying CLAGN candidates at scale. CLAS+ substantially expands the known CLAGN candidate population and provides a valuable target list for future spectroscopic follow-up and time-domain studies with facilities such as Rubin/LSST.

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arXiv2026

S-PLUS Clusters And Large-scale Environments (SCALE): I. A catalog of known clusters and groups in DR5 and a pilot study of Abell 4038

Within the framework of the Southern Photometric Local Universe Survey (S-PLUS), we introduce ${\bf S}$-PLUS ${\bf C}$lusters ${\bf A}$nd ${\bf L}$arge-scale ${\bf E}$nvironments (SCALE), a project dedicated to the study of galaxy clusters, groups, and their environments using 12-band photometry of S-PLUS combined with spectroscopic and photometric data from the literature. In this first paper, we present a catalog of 83 previously known systems in the redshift range $0.008 \leq z_{\rm spec} \leq 0.1$, for which we derive $R_{200}$, $M_{200}$, and velocity dispersions. Spectroscopic members are selected and matched with S-PLUS photometric redshifts (photo-$z$s). We find very good agreement between literature spectroscopic redshifts (spec-$z$s) and S-PLUS photometric redshifts (photo-$z$s), demonstrating the potential of the latter for cluster and group membership determination. As a proof of concept, we obtain photometric memberships for Abell 4038 using the Reliable Photometric Membership technique. A two- and three-dimensional analysis of the region within $10 h^{-1}$ Mpc ($10\times R_{200}$) from the center of Abell 4038 reveals about a dozen substructures including two additional clusters within $1.3\times R_{200}$ (Abell 4038B and Abell 4049). A color-luminosity segregation analysis shows that more luminous (less luminous) galaxies are redder (bluer), as expected. Low-concentration galaxies ($C \leq 2.5$) exhibit a weaker color-luminosity dependence, compared to higher-concentration ones, indicating mass-dependent evolutionary pathways that challenge a simple morphology-color dichotomy, with low-luminosity galaxies presenting bluer colors largely independent of concentration. The SCALE catalog provides a valuable basis for future studies of large-scale structures and their connection to galaxy evolution.

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arXiv2026

The S-PLUS Fornax Project (S+FP): An extragalactic catalog covering $\sim$ 5 virial radii around NGC 1399 with galaxy properties

Observational extragalactic catalogs over wide sky areas are essential for uncovering the large-scale structure of the Universe. They allow, among others, cosmological studies and density analyses that impose strong constraints on models of galaxy formation and evolution. By taking advantage of the wide field images and the 12 optical bands of the Southern Photometric Local Universe Survey (S-PLUS), we aim at providing a catalog of galaxies located, in projection, towards the Fornax galaxy cluster, within $\sim$ 5 virial radii in right ascension (R.A.) and $\sim$ 3 virial radius in declination (Dec) around NGC,1399, the dominant galaxy of the cluster. Such a catalog will allow unprecedented large-scale structure studies in that sky region. Supervised deep learning algorithms have been developed, utilizing neural networks complemented with dimensionality reduction techniques, to classify and separate spurious objects, stars and galaxies in a photometric catalog previously built for the S-PLUS Fornax Project (S+FP). That catalog was built using a combination of SExtractor configurations optimized for galaxy detection and characterization. A catalog of 119,580 galaxies was obtained in the direction of the Fornax cluster containing photometric information in the 12 optical bands of S-PLUS complemented with GALEX (UV), VHS-VISTA (NIR) and AllWISE (MIR) data. We estimate photometric redshifts (σ_ NMAD $\sim$ 0.0219) with a lower limit of z_ lim $\sim$ 0.03. Stellar masses, star formation rates (SFRs) and D4000_N index estimates were obtained through a machine learning approach, by matching S-PLUS photometric data to SDSS spectroscopic data. The completeness of the catalog (72%) was calculated by comparing with mock catalogs ...

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arXiv2024

The S-PLUS Fornax Project (S+FP): A first 12-band glimpse of the Fornax galaxy cluster

The Fornax galaxy cluster is the richest nearby (D ~ 20 Mpc) galaxy association in the southern sky. As such, it provides a wealth of oportunities to elucidate on the processes where environment holds a key role in transforming galaxies. Although it has been the focus of many studies, Fornax has never been explored with contiguous homogeneous wide-field imaging in 12 photometric narrow- and broad-bands like those provided by the Southern Photometric Local Universe Survey (S-PLUS). In this paper we present the S-PLUS Fornax Project (S+FP) that aims to comprehensively analyse the galaxy content of the Fornax cluster using S-PLUS. Our data set consists of 106 S-PLUS wide-field frames (FoV ~ 1.4 x 1.4 deg$^2$) observed in five SDSS-like ugriz broad-bands and seven narrow-bands covering specific spectroscopic features like [OII], CaII H+K, H$δ$, G-band, Mg b triplet, H$α$, and the CaII triplet. Based on S-PLUS specific automated photometry, aimed at correctly detecting Fornax galaxies and globular clusters in S-PLUS images, our dataset provides the community with catalogues containing homogeneous 12-band photometry for ~ 3 x 10$^6$ resolved and unresolved objects within a region extending over ~ 208 deg$^2$ (~ 5 Rvir in RA) around Fornax' central galaxy, NGC 1399. We further explore the EAGLE and IllustrisTNG cosmological simulations to identify 45 Fornax-like clusters and generate mock images on all 12 S-PLUS bands of these structures down to galaxies with M$\star \geq 10^8$ M$\odot$. The S+FP dataset we put forward in this first paper of a series will enable a variety of studies some of which are briefly presented.

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arXiv2023

Diagnostic diagrams for ram-pressure stripped candidates

This paper presents a method for finding ram-pressure stripped (RPS) galaxy candidates by performing a morphological analysis of galaxy images obtained from the Legacy survey. We consider a sample of about 600 galaxies located in different environments such as groups and clusters, tidally interacting pairs and the field. The sample includes 160 RPS previously classified in the literature into classes from J1 to J5, based on the increasing level of disturbances. Our morphological analysis was done using the {\sc astromorphlib} software followed by the inspection of diagnostic diagrams involving combinations of different parameters like the asymmetry ($A$), concentration ($C$), Sérsic index ($n$), and bulge strength parameters $F(G,\,M_{20})$. We found that some of those diagrams display a distinct region in which galaxies classified as J3, J4 and J5 decouples from isolated galaxies. We call this region as the morphological transition zone and we also found that tidally interacting galaxies in pairs are predominant within this zone. Nevertheless, after visually inspecting the objects in the morphological transition zone to discard obvious contaminants, we ended up with 33 bonafide new RPS candidates in the studied nearby groups and clusters (Hydra, Fornax, and CLoGS sample), of which one-third show clear evidence of unwinding arms. Future works may potentially further increase significantly the samples of known RPS using such method.

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arXiv2022

Deep Learning Assessment of galaxy morphology in S-PLUS DataRelease 1

The morphological diversity of galaxies is a relevant probe of galaxy evolution and cosmological structure formation, but the classification of galaxies in large sky surveys is becoming a significant challenge. We use data from the Stripe-82 area observed by the Southern Photometric Local Universe Survey (S-PLUS) in twelve optical bands, and present a catalogue of the morphologies of galaxies brighter than $r=17$ mag determined both using a novel multi-band morphometric fitting technique and Convolutional Neural Networks (CNNs) for computer vision. Using the CNNs we find that, compared to our baseline results with 3 bands, the performance increases when using 5 broad and 3 narrow bands, but is poorer when using the full $12$ band S-PLUS image set. However, the best result is still achieved with just 3 optical bands when using pre-trained network weights from an ImageNet data set. These results demonstrate the importance of using prior knowledge about neural network weights based on training in unrelated, extensive data sets, when available. Our catalogue contains 3274 galaxies in Stripe-82 that are not present in Galaxy Zoo 1 (GZ1), and we also provide our classifications for 4686 galaxies that were considered ambiguous in GZ1. Finally, we present a prospect of a novel way to take advantage of $12$ band information for morphological classification using morphometric features, and we release a model that has been pre-trained on several bands that could be adapted for classifications using data from other surveys. The morphological catalogues are publicly available.

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arXiv2021

Morphological Classification of Galaxies in S-PLUS using an Ensemble of Convolutional Networks

The universe is composed of galaxies that have diverse shapes. Once the structure of a galaxy is determined, it is possible to obtain important information about its formation and evolution. Morphologically classifying galaxies means cataloging them according to their visual appearance and the classification is linked to the physical properties of the galaxy. A morphological classification made through visual inspection is subject to biases introduced by subjective observations made by human volunteers. For this reason, systematic, objective and easily reproducible classification of galaxies has been gaining importance since the astronomer Edwin Hubble created his famous classification method. In this work, we combine accurate visual classifications of the Galaxy Zoo project with \emph {Deep Learning} methods. The goal is to find an efficient technique at human performance level classification, but in a systematic and automatic way, for classification of elliptical and spiral galaxies. For this, a neural network model was created through an Ensemble of four other convolutional models, allowing a greater accuracy in the classification than what would be obtained with any one individual. Details of the individual models and improvements made are also described. The present work is entirely based on the analysis of images (not parameter tables) from DR1 (www.datalab.noao.edu) of the Southern Photometric Local Universe Survey (S-PLUS). In terms of classification, we achieved, with the Ensemble, an accuracy of $\approx 99 \%$ in the test sample (using pre-trained networks).

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