arXiv subjects

R. A. Dupke

Publications and source records attributed to R. A. Dupke.

At least 19 recordsLinked to original sources

arXiv2026

Stellar characterization with photometric colors from J-PLUS and 2MASS surveys

Aims. We aim at deriving stellar atmospheric parameters based on the photometric data from the Javalambre Photometric Local Universe Survey (J-PLUS) in addition to near-infrared photometry from the Two Micron All-Sky Survey (2MASS). Methods. Our method consists of a semi-supervised machine learning approach based on the k-means method combined with a modified k-nearest neighbors algorithm. This method compares the observed photometry to a set of reference data to estimate the stellar effective temperature ($T_{\rm eff}$), surface gravity ($\log{g}$), and metallicity ([Fe/H]) of stars from J-PLUS Data Release 3 (DR3). Results. We estimated $T_{\rm eff}$, $\log{g}$, and [Fe/H], for approximately 5.6 million stars from J-PLUS DR3, along with their errors.Our results were in agreement with spectroscopic estimates from LAMOST and APOGEE.We also applied a dimension reduction method, seeking greater efficiency by reducing the computation time and minimizing the needed information for calculating the stellar parameters, resulting in a subset of 11 colors. From this approach, stellar parameters were obtained for approximately six million stars. Conclusions. Our results demonstrated the potential of using a method built from machine learning algorithms that do not require prior training. Additionally, it was shown that the proposed method allowed estimating reliable atmospheric parameters even when the available photometry did not fulfill all photometric quality criteria. We defined a neighborhood parameter, which assesses the reliability of our estimations and indicates that objects with smaller neighborhoods values have lower uncertainties.

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arXiv2026

J-PLUS: Spectral classification and photometric redshifts for 79 million sources in the fourth data release

We present spectral classifications and photometric redshifts for 79.2 million sources up to an r-band magnitude of 22 in Data Release 4 of the Javalambre Photometric Local Universe Survey (J-PLUS). Leveraging the 12-band J-PLUS filter system, we compare a template-fitting approach (LePhare) against LeMoNNADE, a morphology-blind machine learning pipeline that uses spectral mixing augmentation to overcome training set limitations. LeMoNNADE consistently outperforms template fitting in precision, robust scatter, and outlier rates. Including WISE infrared photometry breaks optical degeneracies between stars and quasars, reducing the catastrophic outlier rate for quasars from ~40% to ~23% and constraining systemic redshift bias to <1% up to z = 4. We find LeMoNNADE is also less susceptible to redshift aliasing, particularly when adopting the probability density function median. Because the spectroscopic training samples severely under-represent stars, we apply an Expectation-Maximization Bayesian calibration to recover unbiased class probabilities for the magnitude-limited sample. This reveals that extragalactic counts agree with the literature down to the r ~ 20.5 completeness limit. The inferred redshift distribution for r < 21 extragalactic sources peaks at z ~ 0.3, showing broad agreement with existing literature up to z ~ 0.6. The resulting catalogues represent a significant milestone for local Universe science, offering probabilistically calibrated classifications and distances while explicitly characterising faint-end limits and contamination.

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arXiv2026

J-PLUS: The stellar mass function of quiescent and star-forming galaxies at 0.05 <= z <= 0.2

Aims. We derive the stellar mass function (SMF) of quiescent and star-forming galaxies at z <= 0.2 using 12-band optical photometry from the third data release (DR3) of the Javalambre Photometric Local Universe Survey (J-PLUS) over 3,284 deg^2. Methods. We select approximately 890,000 galaxies with r <= 20 mag and photometric redshifts in the range 0.05 <= z <= 0.20. Stellar masses and star formation rates were derived through spectral energy distribution fitting with CIGALE, confronted with spectroscopic samples. Galaxies are classified as star-forming or quiescent based on their specific star formation rate (sSFR), adopting log(sSFR [yr^-1]) = -10.2. We compute SMFs for both populations using the 1/Vmax method, apply completeness corrections, and fit Schechter functions. Results. The SMFs from J-PLUS DR3 are well described by Schechter functions and agree with previous photometric and spectroscopic studies. The characteristic mass for quiescent galaxies, log(M*/Msun) = 10.80, is 0.4 dex larger than that of star-forming galaxies. The faint-end slope is steeper for star-forming galaxies (alpha = -1.2) than for quiescent ones (alpha = -0.7). The quiescent fraction rises by 40 percent per dex in stellar mass, reaching fQ > 0.95 at log(M*/Msun) > 11. Comparisons with the GAEA semi-analytic model reveal an excess of star-forming galaxies at intermediate masses. Conclusions. J-PLUS DR3 stellar mass functions and quiescent fractions are consistent with the literature and provide robust constraints for galaxy formation models. Quiescent galaxies represent 45 percent of number density above log(M*) > 9, but 75 percent of stellar mass density. The use of 12 optical bands, including 7 narrow filters, improves redshift precision by 20 percent, enabling more accurate SED fitting and galaxy classification.

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arXiv2026

OJALÁ: Optimizing J-PAS Astronomy for Large-scale Analysis. A foundation model for the SED of galaxies, QSOs and stars

The advent of large-scale surveys requires efficient ML techniques to exploit the information of massive datasets. We present OJALA, a transformer-based autoregressive foundation model designed to simultaneously classify astronomical objects and infer their physical parameters using 54 narrow bands from J-PAS, combined with broad bands from the DESI Legacy Imaging Surveys and WISE. The model is trained on $\sim20$ million synthetic SEDs generated from DESI DR1 spectra. We validate OJALA using a cross-matched sample of $\sim121,000$ objects between J-PAS and DESI. The model achieves a weighted F1-score of approximately 0.9 for spectral classification (stars, galaxies, and QSOs) at $i < 21$. For galaxies, we recover photo-z with a precision of $σ_{\rm NMAD} < 0.01$, while for QSOs, the precision improves significantly at $z > 1.5$, reaching $σ_{\rm NMAD} \approx 0.006$ at $z \approx 3.5$. We demonstrate robust estimation of physical properties for galaxies, recovering stellar masses and SFR with a scatter of approximately 0.11 dex and 0.22 dex, respectively. Furthermore, the model accurately predicts EWs for major optical emission lines, allowing for the derivation of extinction-corrected H$α$ luminosities with a scatter of 0.29 dex. OJALA successfully reproduces the BPT and WHAN diagnostic diagrams, classifying SF, AGN, and passive galaxies with F1-scores typically ranging from 70% to 90% depending on the diagnostic class. For stars, the model reliably infers effective temperature and metallicity, though surface gravity remains challenging. Finally, we show the modularity of the architecture by fine-tuning the pre-trained embeddings to predict BH masses, a property not included in the primary training, recovering spectroscopic virial estimates with a precision of approximately 0.5 dex. We release the code, model weights, and a comprehensive VAC for the J-PAS EDR.

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arXiv2026

Analysis of spatially resolved stellar populations and emission line properties in nearby galaxies with J-PLUS data. II-Results for the M51 group and first comparison with the M101 group

We characterize the spatially resolved stellar population and emission-line properties of galaxies in the M51 group using the same methodology previously applied to the M101 group, aiming to understand how environmental processes shape galaxy properties across different groups. Properties are derived by applying the \textsc{AlStar} spectral fitting code to multi-band datacubes from the Javalambre Photometric Local Universe Survey (J-PLUS). We present spatially resolved maps of the main stellar population and emission-line properties for the M51 group galaxies. The interacting pair M51a/b displays clearly distinct properties: M51a shows prominent star-forming spiral arms, while its companion is essentially an early-type retired galaxy. M63 exhibits asymmetries in stellar age, dust attenuation, and H$_α$ equivalent width, consistent with outside-in quenching likely related to a past interaction. Relations between physical properties and stellar mass surface density ($Σ_\star$) were investigated. The age-$Σ_\star$ and nebular metallicity-$Σ_\star$ relations are flatter than those in the M101 group. In addition, all galaxies align with the resolved star-forming main sequence, except M51b, which shows the properties of a retired galaxy. Overall, the M51 group displays signatures of more advanced dynamical evolution than the M101 group. This is evidenced by flattened age and nebular metallicity gradients, enhanced dust content, and signs of environmental quenching in some members. In contrast, the less dynamically evolved M101 group largely preserves its inside-out formation signatures. While these results suggest that group mass and interactions influence galaxy evolution even in low-mass environments, the comparison of two systems remains limited by small-number statistics. This study highlights the potential of J-PLUS data for IFS-like analyses of nearby galaxies.

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arXiv2026

Exploring the spatially-resolved capabilities of the J-PAS survey with Py2DJPAS

We present Py2DJPAS, a Python-based tool to automate the analysis of spatially resolved galaxies in the \textbf{miniJPAS} survey, a 1~deg$^2$ precursor of the J-PAS survey, using the same filter system, telescope, and Pathfinder camera. Py2DJPAS streamlines the entire workflow: downloading scientific images and catalogs, performing PSF homogenization, masking, aperture definition, SED fitting, and estimating optical emission line equivalent widths via an artificial neural network. We validate Py2DJPAS on a sample of resolved miniJPAS galaxies, recovering magnitudes in all bands consistent with the catalog ($\sim 10$~\% precision using SExtractor). Local background estimation improves results for faint galaxies and apertures. PSF homogenization enables consistent multi-band photometry in inner apertures, allowing pseudo-spectra generation without artifacts. SED fitting across annular apertures yields residuals $<10$~\%, with no significant wavelength-dependent bias for regions with $S/N>5$. We demonstrate the IFU-like capability of J-PAS by analyzing the spatially resolved properties of galaxy 2470-10239 at $z = 0.078$, comparing them to MaNGA data within 1 half-light radius (HLR). We find excellent agreement in photometric vs. spectroscopic measurements and stellar mass surface density profiles. Our analysis extends to 4 HLR (S/N~$\sim$~5), showing that J-PAS can probe galaxy outskirts, enabling the study of evolutionary processes at large galactocentric distances.

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arXiv2026

The miniJPAS survey: Dissecting galaxy properties across environments with spatially resolved photometry

The Javalambre-Physics of the Accelerating Universe Astrophysical Survey (J-PAS) is an ongoing survey mapping thousands of square degrees in the Northern Hemisphere using 56 narrow-band filters, delivering IFU-like photometric data well suited for studying galaxy properties and evolution. As a precursor, the miniJPAS survey observed a 1 deg$^2$ field with the same filter system, providing an ideal testbed for the study of spatially resolved galaxies. In this work, we investigate the resolved stellar population and emission-line properties of 51 miniJPAS galaxies, classified by spectral type (red or blue) and environment (group or field), and assess the role of environment in galaxy evolution. We use the Py2DJPAS pipeline to process the data, homogenise the images to a common PSF, define galactic regions, and extract photo-spectra. Radial profiles are analysed using elliptical annuli spaced by 0.7 R_EFF, combined with an inside-out segmentation to study star formation histories. Stellar population parameters are derived with the Bayesian SED-fitting code BaySeAGal, while artificial neural networks are used to estimate the equivalent widths of the H$α$, H$β$, [NII], and [OIII] emission lines. We find clear trends in a mass density-colour diagram: denser, redder regions are older, more metal-rich, and have lower specific star formation rates, while bluer, less dense regions show stronger emission lines and higher sSFRs. Red and blue galaxies are well separated in these relations, whereas environmental classification shows no clear distinction. Radial profiles support an inside-out formation scenario, with significant differences between red and blue galaxies but no strong environmental dependence. We suggest that the weak environmental effects may be due to the relatively low stellar masses of the galaxy groups in our sample.

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arXiv2026

J-HERTz: J-PLUS Heritage Exploration of Radio Targets at z $<$ 5

We introduce J-HERTz (J-PLUS Heritage Exploration of Radio Targets at $z < 5$), a new multi-wavelength catalog that combines optical narrow-band photometry from J-PLUS, infrared observations from WISE, and deep low-frequency radio data from LoTSS for nearly half a million sources across 2,100 deg$^2$ of the northern sky. Key innovations of J-HERTz include Bayesian neural network classifications for 390,000 galaxies, 31,000 quasars, and 20,000 stars, along with significantly improved photometric redshifts for 235,000 galaxies compared to previous J-PLUS DR3 and LoTSS DR2 estimates. We identify 831 candidate Galactic radio stars, which, if confirmed, would constitute a significant addition to the number of radio-emitting stars identified to date. Among radio-loud galaxies with spectroscopic observations, $\gtrsim$20% lack Seyfert or LINER signatures, indicating a substantial population of optically quiescent radio galaxies, in agreement with previous works. Spectral energy distribution fitting of their host galaxies using J-PLUS photospectra reveals systematically low specific star formation rates, consistent with quenched stellar populations. J-HERTz thus provides a powerful dataset to exploit radio-optical synergies, enabling studies that span from the origin of stellar radio emission to the AGN life cycle and the role of jet activity in shaping host galaxy evolution.

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arXiv2026

J-PLUS: The planetary nebula population of M 33

In this pilot study, we investigate the PN population in M~33, a nearby spiral galaxy ($\simeq 840$~kpc), using data from the DR3 of the Javalambre-Photometric Local Universe Survey (J-PLUS), a 12-band photometric dataset extensively used to identify H$α$ line emitters. From the 143 known PNe of M~33, the photometry of only 13 are present in the J-PLUS catalog, as available on the J-PLUS portal. With the aim of recovering a larger fraction of the M~33 PN population, the software SExtractor is adopted to extract the sources in the J-PLUS images and obtain the photometric data for the PNe known in the literature, performing PSF photometry when possible. With this procedure the photometry of 98 PNe was obtained using H$α$ image as detection image, including the 13 already present in the J-PLUS catalog. Using diagnostic color-color diagrams (DCCDs) based on criteria developed for Milky Way halo PNe, we identified 16 sources with PN-like colors. Cross-match with existing catalogs revealed that most of these candidates are H II regions, though one source remains unidentified. Additionally, analyzing their full width at half maximum, most of them would not be PN candidates. This highlights the method's ability to select emission-line objects but also underscores the challenge of distinguishing PNe from contaminants using photometry alone. The J-PLUS colors of 98 known PNe were analyzed, together with literature information on their radial velocities, resulting in the identification of one possible halo PN. This is the first paper which aims at detecting extragalactic PNe in multi-band surveys such as J-PLUS, the Southern Local Universe Survey (S-PLUS) and the Javalambre-Physics of the Accelerating Universe Astrophysical Survey (J-PAS), paving the way for similar studies in these surveys for other nearby galaxies, which lack catalogs of known PNe.

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arXiv2025

J-VAR: Analysis of RR Lyrae light curves in seven optical bands

Context:RR Lyrae stars, with their accurate period and amplitude measurements, constrain stellar evolution and map Galactic structure. The Javalambre VARiability (J-VAR) survey is the time-domain extension of the Javalambre Photometric Local Universe survey, which provides time-series data across seven optical bands, including $gri$ and four medium and narrow bands. Aims: Our goal is to construct and analyze light curves for RR Lyrae stars identified in the J-VAR's first data release using the \textit{Gaia} third data release (DR3) Variable Stars catalog as a reference. Methods: The light curves of $315$ RR Lyrae were analyzed by fitting templates from the Sloan Digital Sky Survey Multiband Template Library. The periods and amplitudes for the seven bands in J-VAR were independently obtained from the best-fitted templates. Results: The J-VAR periods show strong agreement with \textit{Gaia} DR3 values. The Bailey diagram for each J-VAR filter shows larger pulsation amplitudes at bluer wavelengths. Amplitudes, after normalizing by the $r$-band amplitude, show an exponential trend, with the bluer J-VAR filter centered at $395~\text{nm}$ having twice the amplitude of the reddest J-VAR passband at $861~\text{nm}$. The normalized amplitudes of the RR Lyrae stars from {\it Gaia} and the Zwicky Transient Facility are consistent with the J-VAR trend. Finally, the SDSS templates derived from broadbands also provide a proper description for the medium and narrow band light curves. Conclusions: The J-VAR RR Lyrae catalog offers reliable pulsation parameters and light curves in seven optical filters, allowing the systematic study of amplitude trends from $395~\text{nm}$ to $860~\text{nm}$.

astro-ph.SR↗

arXiv2025

J-PLUS Reconstructing the Milky Way Disc's star formation history with twelve-filter photometry

Wide-field, multi-filter photometric surveys enable the reconstruction of the Milky Way's star formation history (SFH) on Galactic scales and offer new insights into disc assembly. The twelve-filter system of the Javalambre Photometric Local Universe Survey (J-PLUS) is particularly suitable, as its colours trace stellar chemical abundances and help alleviate the age-metallicity degeneracy in colour-magnitude diagram fitting. We aim to recover the SFH of the Galactic disc and separate its chemically distinct components by combining J-PLUS DR3 photometry with Gaia astrometry. We also evaluate the potential of isochrone fitting to estimate stellar ages and metallicities as proxies for evolutionary trends. We fit magnitudes and parallaxes of $1.38\times10^{6}$ stars using a Bayesian multiple isochrone method. The bright region of the colour-absolute-magnitude diagram ($M_{r}\leq4.2$ mag) constrains ages, while the faint region provides an empirical metallicity prior mitigating the age-metallicity degeneracy. Both PARSEC and BaSTI isochrones, in solar-scaled and $α$-enhanced forms, are adopted. The recovered SFH reveals two sequences: an $α$-enhanced population forming rapidly between $12.5$ and $8$ Gyr ago, enriching from [M/H]$\sim-0.6$ to $0.1$ dex; and a solar-scaled sequence emerging $\sim8$ Gyr ago, dominating after $\sim7$ Gyr with slower enrichment reaching solar metallicity by $3$ Gyr. Metal-rich ([M/H]$\gtrsim0$) stars are confined to $\vert z_{GC}\vert\lesssim1$ kpc, whereas metal-poor ([M/H]$\lesssim-0.5$) stars reach $\vert z_{GC}\vert\sim2$ kpc. Simultaneous fitting of both isochrone families reveals distinct formation epochs for the thin and thick discs. J-PLUS multi-filter photometry, combined with Gaia parallaxes, mitigates age-metallicity degeneracies and enables detailed mapping of the Milky Way's temporal and chemical evolution.

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arXiv2025

J-PLUS: Spectroscopic validation of H$α$ emission line maps in spatially resolved galaxies

We present a dedicated automated pipeline to construct spatially resolved emission H$α$+[NII] maps and to derive the spectral energy distributions (SEDs) in 12 optical filters (five broad and seven narrow/medium) of H$α$ emission line regions in nearby galaxies (z $<$ 0.0165) observed by the Javalambre Photometric Local Universe Survey (J-PLUS). We used the $J0660$ filter of $140$Å width centered at $6600$Å to trace H$α$ + [NII] emission and $r$ and $i$ broad bands were used to estimate the stellar continuum. We create pure emission line images after the continnum subtraction, where the H$α$ emission line regions were detected. This method was also applied to Integral Field Unit (IFU) spectroscopic data from PHANGS-MUSE, CALIFA and MaNGA surveys by building synthetic narrow-bands based on J-PLUS filters. The studied sample includes the cross-matched catalog of these IFU surveys with J-PLUS third data release (DR3), amounting to $2$ PHANGS-MUSE, $78$ CALIFA, and $78$ MaNGA galaxies at $z < 0.0165$, respectively. We compared the H$α$+[NII] radial profiles from J-PLUS and the IFU surveys, finding good agreement within the expected uncertainties. We also compared the SEDs from the emission line regions detected in J-PLUS images, reproducing the main spectral features present in the spectroscopic data. Finally, we compared the emission fluxes from the J-PLUS and IFU surveys accounting for scale differences, finding a difference of only 2% with a dispersion of 7% in the measurements. The J-PLUS data provides reliable spatially resolved H$α$+[NII] emission maps for nearby galaxies. We provide the J-PLUS DR3 catalog for the $158$ galaxies with IFU data, including emission maps, SEDs of star-forming clumps, and radial profiles.

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arXiv2025

J-PLUS: Understanding outlier white dwarfs in the third data release via dimensionality reduction

We present the white dwarf catalog derived from the third data release of the Javalambre Photometric Local Universe Survey (J-PLUS DR3), which covers 3284 deg2 using 12 optical filters. A particular focus is given to the classification of outlier sources. We applied a Bayesian fitting process to the 12-band J-PLUS photometry of white dwarf candidates from Gaia EDR3. The derived parameters were effective temperature, surface gravity, and parallax. We used theoretical models from H- and He-dominated atmospheres, with priors applied to parallax and spectral type. From the posteriors, we derived the probability of an H-dominated atmosphere and of calcium absorption for each source. Outliers were identified as sources with chi2 > 23.2, indicating significant deviations from the best-fitting model. We analyzed the residuals from the fits using the UMAP technique, which enables the classification of outliers into distinct categories. The catalog includes 14844 white dwarfs with r < 20 mag and 1 < parallax < 100 mas, with 72% of the sources lacking spectroscopic (R > 500) classification. The application of UMAP identified three main types of outliers: random measurement fluctuations (391 sources), metal-polluted white dwarfs (98 sources), and two-component systems (282 sources). The last category also includes white dwarfs with strong carbon absorption lines. We validated the J-PLUS classifications by comparison with spectroscopy from SDSS and DESI, and with Gaia BP/RP spectra, confirming a one-to-one correspondence between J-PLUS photometric and spectroscopic classifications. The J-PLUS DR3 white dwarf catalog provides a robust dataset for statistical studies. The use of dimensionality reduction techniques enhances the identification of peculiar objects, making this catalog a valuable resource for the selection of interesting targets such as metal-polluted white dwarfs or binary systems.

astro-ph.SR↗

arXiv2025

Spatially resolved stellar populations and emission lines properties in nearby galaxies with J-PLUS -- I. Method and first results for the M101 group

Spatially resolved maps of stellar populations and nebular emission are key tools for understanding the physical properties and evolutionary stages of galaxies. We aim to characterize the spatially resolved stellar population and emission line properties of galaxies in the M101 group using Javalambre Photometric Local Universe Survey (J-PLUS) data. The datacubes first go through pre-processing steps, which include masking, noise suppression, PSF homogenization, and spatial binning. The improved data are then analyzed with the spectral synthesis code \alstar, which has been previously shown to produce excellent results with the unique 12 bands filter system of J-PLUS and S-PLUS. We produce maps of stellar mass surface density ($Σ_\star$), mean stellar age and metallicity, star formation rate surface density ($Σ_{\rm SFR}$), dust attenuation, and emission line properties such as fluxes and equivalent widths of the main optical lines. Relations among these properties are explored. All galaxies exhibit a well-defined age-$Σ_\star$ relation, except for the dwarfs. Similarly, all of the galaxies follow local $Σ_\star$-$Σ_{\rm SFR}$ star-forming MS relations, with specific star formation rates that grow for less massive systems. A stellar $Σ_\star$-metallicity relation is clearly present in M101, while other galaxies have either flatter or undefined relations. Nebular metallicities correlate with $Σ_\star$ for all galaxies. This study demonstrates the ability of J-PLUS to perform IFS-like analysis of galaxies, offering robust spatially resolved measurements of stellar populations and emission lines over large fields of view. The M101 group analysis showcases the potential for expanding such studies to other groups and clusters, contributing to the understanding of galaxy evolution across different environments.

astro-ph.GA↗

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.

astro-ph.SR↗

arXiv2024

J-PLUS: Bayesian object classification with a strum of BANNJOS

With its 12 optical filters, the Javalambre-Photometric Local Universe Survey (J-PLUS) provides an unprecedented multicolor view of the local Universe. The third data release (DR3) covers 3,192 deg$^2$ and contains 47.4 million objects. However, the classification algorithms currently implemented in its pipeline are deterministic and based solely on the sources morphology. Our goal is classify the sources identified in the J-PLUS DR3 images into stars, quasi-stellar objects (QSOs), and galaxies. For this task, we present BANNJOS, a machine learning pipeline that uses Bayesian neural networks to provide the probability distribution function (PDF) of the classification. BANNJOS is trained on photometric, astrometric, and morphological data from J-PLUS DR3, Gaia DR3, and CatWISE2020, using over 1.2 million objects with spectroscopic classification from SDSS DR18, LAMOST DR9, DESI EDR, and Gaia DR3. Results are validated using $1.4 10^5$ objects and cross-checked against theoretical model predictions. BANNJOS outperforms all previous classifiers in terms of accuracy, precision, and completeness across the entire magnitude range. It delivers over 95% accuracy for objects brighter than $r = 21.5$ mag, and ~90% accuracy for those up to $r = 22$ mag, where J-PLUS completeness is < 25%. BANNJOS is also the first object classifier to provide the full probability distribution function (PDF) of the classification, enabling precise object selection for high purity or completeness, and for identifying objects with complex features, like active galactic nuclei with resolved host galaxies. BANNJOS has effectively classified J-PLUS sources into around 20 million galaxies, 1 million QSOs, and 26 million stars, with full PDFs for each, which allow for later refinement of the sample. The upcoming J-PAS survey, with its 56 color bands, will further enhance BANNJOS's ability to detail each source's nature.

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arXiv2023

The miniJPAS survey: Optical detection of galaxy clusters with PZWav

Galaxy clusters are an essential tool to understand and constrain the cosmological parameters of our Universe. Thanks to its multi-band design, J-PAS offers a unique group and cluster detection window using precise photometric redshifts and sufficient depths. We produce galaxy cluster catalogues from the miniJPAS, which is a pathfinder survey for the wider J-PAS survey, using the PZWav algorithm. Relying only on photometric information, we provide optical mass tracers for the identified clusters, including richness, optical luminosity, and stellar mass. By reanalysing the Chandra mosaic of the AEGIS field, alongside the overlapping XMM-Newton observations, we produce an X-ray catalogue. The analysis reveals the possible presence of structures with masses of 4$\times 10^{13}$ M$_\odot$ at redshift 0.75, highlighting the depth of the survey. Comparing results with those from two other cluster catalogues, provided by AMICO and VT, we find $43$ common clusters with cluster centre offsets of 100$\pm$60 kpc and redshift differences below 0.001. We provide a comparison of the cluster catalogues with a catalogue of massive galaxies and report on the significance of cluster selection. In general, we are able to recover approximately 75$\%$ of the galaxies with $M^{\star} >$2$\times 10^{11}$ M$_\odot$. This study emphasises the potential of the J-PAS survey and the employed techniques down to the group scales.

astro-ph.CO↗

arXiv2023

The miniJPAS survey. Evolution of the luminosity and stellar mass functions of galaxies up to $z \sim 0.7$

We aim at developing a robust methodology for constraining the luminosity and stellar mass functions (LMFs) of galaxies by solely using data from multi-filter surveys and testing the potential of these techniques for determining the evolution of the miniJPAS LMFs up to $z\sim0.7$. Stellar mass and $B$-band luminosity for each of the miniJPAS galaxies are constrained using an updated version of the SED-fitting code MUFFIT, whose values are based on composite stellar population models and the probability distribution functions of the miniJPAS photometric redshifts. Galaxies are classified through the stellar mass versus rest-frame colour diagram corrected for extinction. Different stellar mass and luminosity completeness limits are set and parametrised as a function of redshift, for setting limits in our flux-limited sample ($r_\mathrm{SDSS}<22$). The miniJPAS LMFs are parametrised according to Schechter-like functions via a novel maximum likelihood method accounting for uncertainties, degeneracies, probabilities, completeness, and priors. Overall, our results point to a smooth evolution with redshift ($0.05 10.7$).

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