arXiv subjects

R. M. González Delgado

Publications and source records attributed to R. M. González Delgado.

At least 19 recordsLinked to original sources

arXiv2026

CAVITY: Calar Alto Void Integral-field Treasury surveY: II. Second public data release

Studying galaxy evolution under the unique environmental conditions of cosmic voids provides an opportunity to disentangle the role of the large-scale environment in shaping mass assembly (both baryonic and dark matter), regulating galaxy physical properties, and driving the transformation from star-forming to quiescent systems. We present the second public data release (DR2) of the Calar Alto Void Integral-field Treasury Survey (CAVITY), an ongoing legacy programme designed to study void galaxies (VGs) across a range of nearby ($0.005 \leq z \leq 0.050$) voids with different sizes and dynamical stages, providing 200 science-grade optical integral-field spectroscopy (IFS) data cubes. By doubling the number of galaxies relative to DR1 while maintaining the same selection criteria, DR2 significantly increases the dataset's statistical power, enabling more robust characterization of galaxy properties and their correlations with environment. The observations were obtained with the PMAS/PPAK spectrograph on the 3.5-m Calar Alto telescope using the V500 configuration, covering the optical spectral range of 3745-7500 A at a resolution of 6 A (FWHM). The DR2 VG sample spans a broad range of stellar masses, morphologies, colours, and gas ionisation properties. We describe the sample selection, observing strategy, data reduction pipeline, quality-control procedures, and the public access to the CAVITY datasets and associated ancillary data on the survey's database. In addition, we present a characterisation of the large- and local-scale environments of CAVITY galaxies, showing that the 15 surveyed voids encompass a wide variety of sizes, galaxy richness, galaxy populations, and local structures, including galaxy groups. This release comprises 200 IFS data cubes, publicly available together with the master catalogues at the survey's dedicated webpage: https://cavity.caha.es/data/dr2/.

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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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arXiv2025

Why the Northern Hemisphere Needs a 30-40m Telescope and the Science at Stake: Shaping Galaxies and Their Stars with Stellar Population Gradients, IMF Variations and Environmental Drivers in Cluster Early-Type Galaxies

This white paper highlights how stellar population gradients, chemical abundance patterns, stellar initial mass function (IMF) variations, and structural signatures in early-type galaxies (ETGs), measured at faint and large galactocentric radii, out to $\sim4R_e$, provide powerful diagnostics of their formation and evolutionary histories. These observables encode the combined effects of early dissipative star formation, subsequent accretion and mergers, and internal feedback processes. Achieving such measurements requires high-signal-to-noise, spatially resolved U-band--optical--near-IR spectroscopy at large radii, with enough spatial resolution to study the variation of these properties on $\sim$kpc scales. These capabilities can only be delivered by a 30\,m-class telescope. Disentangling these internal processes from environmental influences further demands observations of galaxies across clusters spanning a wide range of evolutionary stages and local environments. The nearby Virgo, Perseus, and Coma clusters, without any comparable nearby counterparts in the Southern Hemisphere, offer ideal laboratories for this work. Such observations will place stringent constraints on the formation mechanism of ETGs, connecting local cluster ETGs to their high-redshift progenitors. This white paper outlines several key science cases enabled by such a facility: (1) mapping stellar population gradients across environments; (2) tracing IMF variations as a function of evolutionary stage and environment; (3) reconstructing the three-dimensional structure of galaxies through deep integral-field spectroscopy and imaging; and (4) identifying and studying compact and relic systems as progenitors of present-day ETGs.

astro-ph.IM↗

arXiv2025

J-PAS: First Identification, Physical Properties and Ionization Efficiency of Extreme Emission Line Galaxies

Extreme emission line galaxies (EELGs) are key tracers of intense star formation and potential analogues of the sources that reionized the early Universe. Their low-redshift counterparts offer a unique opportunity to study the physical conditions that enable high ionizing-photon escape fractions. We present a robust method to photometrically identify EELGs in the J-PAS survey, which provides 56 optical bands over 8500 deg^2. Using data from a fully observed 30 deg^2 region, we combine narrow-band equivalent widths with machine-learning techniques to select galaxies with emission lines above 300 Å. The method achieves 95% purity and 96% completeness for $i_\mathrm{SDSS}<22.5$ mag. We identify 917 EELGs up to $z=0.8$; spectroscopic cross-matching with DESI/DR1 confirms the reliability of our redshifts and emission-line measurements. The selected galaxies show strong correlations between $ξ_\mathrm{ion}$ and EW([OIII]), consistent with previous low- and high-z studies. Most sources exceed the ionizing efficiency threshold required for reionization, reinforcing their role as local analogues of early-Universe galaxies.

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arXiv2025

J-PAS: A value-added catalogue of optical line intensities for nebular emission galaxies (JOLINES)

We present the value-added catalogue JOLINES (J-PAS optical line intensities for nebular emission galaxies), which provides emission-line fluxes in galaxies at from the spectrophotometric catalogues of miniJPAS, J-NEP and the J-PAS early data release (EDR). This catalogue will be updated with future data releases, offering a growing resource for the study of emission-line galaxies. To obtain reliable emission-line fluxes from narrow-band photometry, we employed spectral energy distribution (SED) fitting using CIGALE, a robust tool that reconstructs the continuum emission and ensures accurate flux measurements. This method effectively mitigates uncertainties associated with direct continuum subtraction techniques, and systematics such as absorption components in the emission lines. We validate our approach using simulated observations of galaxy spectra with added noise, testing the method's performance across different equivalent width (EW) regimes and emission-line strengths. Additionally, we compare the recovered emission-line fluxes with spectroscopic measurements from the Sloan Digital Sky Survey (SDSS) and the Dark Energy Spectroscopic Instrument (DESI). Our results show a tight correlation between photometric and spectroscopic fluxes, particularly for bright emission lines, with a typical dispersion of $\sim$0.3 dex. Reliable fluxes are obtained for emission lines with EW $\gtrsim20\, \rm{\mathring{A}}$, in agreement with previous empirical studies. The current catalogue comprises approximately 13,900 sources with reliable flux measurements in the H$α$+[NII] complex and 7,200 in [OIII]$λ5007$, ensuring statistically robust samples for the brightest optical emission lines. This resource will be expanded in future J-PAS releases, facilitating large-scale studies of star formation, AGN activity, and galaxy evolution.

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arXiv2025

J-PAS: Discovery of RaJav, a bright spatially extended Ly$α$ Nebula at z=2.25

We report the discovery of a massive and potentially largest Ly$α$ Nebula, RaJav, at z=2.25, associated with a quasar pair: the bright SDSS~J162029.07+433451.1 (hereafter J1620+4334) and the faint newly discovered quasar JPAS-9600-10844, at 2.265 $\pm$ 0.021 using the early data release (17 deg$^{2}$) of the J-PAS. The quasar JPAS-9600-10844 embedded in the nebula is located at ~ 60.2 kpc (7.3'') from J1620+4334, and shows a compact structure with broad emission lines (> 3000 km/s), typical of active galactic nuclei. At a 2$σ$ surface brightness (SB) contour of $\sim 1.86 \times 10^{-16}$ erg s$^{-1}$ cm$^{-2}$ arcsec$^{-2}$, the nebula extends > 100 kpcs and has a total Ly$α$ luminosity of $\sim 5.8 \pm 0.7 \times 10^{44}$ erg s$^{-1}$ signify the presence of a giant Enormous Ly$α$ Nebula (ELAN). The nebula traces an over density of quasars at redshift of 2.2-2.3 consistent with the progenitor of a massive galaxy cluster. The extended CIV emission indicates that the circum-galactic medium (CGM) is metal-enriched and not primordial. The current J-PAS observations suggest photoionization and shocks due to outflows as possible ionization mechanisms. The faint extended FUV and NUV continuum emission likely points to ongoing star formation around the two quasars, suggesting a complex interaction in their environments. These findings provide new insights into the environment of quasars and their role in shaping the dynamics and evolution of the CGM at cosmic noon. Further spectroscopic observations will be required to fully characterize the object's nature and its kinematic properties. This study demonstrates the unique capability of J-PAS to detect massive and rare Ly$α$ nebulae, providing new insights into their properties, environments, and connections to large-scale structures in the cosmic web such as filaments and overdensities in a large cosmological volume.

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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.

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arXiv2024

The effect of local and large scale environment on the star formation histories of galaxies

We aim to investigate how the local environment influences the star formation history (SFH) of galaxies residing in various large-scale environments. We categorise a sample of 9384 galaxies into the three primary large scale structures (voids, walls \& filaments, and clusters) and further classify them based on their local environment (as either "singlets" or group members), through a search of companion galaxies within sky-projected distances $Δr_p < 0.45$ Mpc and velocity differences $Δv < 160$ $\text{km s}^{-1}$. Subsequently, we explore these subsamples through SFH data from previous works. Throughout the study, galaxies are divided into long-timescale SFH galaxies (LT-SFH), which assemble their mass steadily along cosmic time, and short-timescale SFH galaxies (ST-SFH), which form their stars early. We then compare characteristic mass assembly look-back times. The distributions of mass assembly look-back times in ST-SFH galaxies are statistically different for singlets and groups. These differences are only found in LT-SFH galaxies when studying these distributions in stellar mass bins. Our results indicate that the large-scale environment is related to a delay in mass assembly of up to $\sim$2 Gyr, while this delay is $<$1 Gyr in the case of local environment. The effect of both kinds of environment is more significant in less massive galaxies, and in LT-SFHs. Our results are consistent with galaxies in groups assembling their stellar mass earlier than singlets, especially in voids and lower mass galaxies. Local environment plays a relevant role in stellar mass assembly times, although we find that large-scale structures also cause a delay in mass assembly, more so in the case of cluster galaxies.

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arXiv2024

Retrieval of the physical parameters of galaxies from WEAVE-StePS-like data using machine learning

The WHT Enhanced Area Velocity Explorer (WEAVE) is a new, massively multiplexing spectrograph. This new instrument will be exploited to obtain high S/N spectra of $\sim$25000 galaxies at intermediate redshifts for the WEAVE Stellar Population Survey (WEAVE-StePS). We test machine learning methods for retrieving the key physical parameters of galaxies from WEAVE-StePS-like spectra using both photometric and spectroscopic information at various S/Ns and redshifts. We simulated $\sim$105000 galaxy spectra assuming SFH with an exponentially declining star formation rate, covering a wide range of ages, stellar metallicities, sSFRs, and dust extinctions. We then evaluated the ability of the random forest and KNN algorithms to correctly predict such parameters assuming no measurement errors. We checked how much the predictive ability deteriorates for different S/Ns and redshifts, finding that both algorithms still accurately estimate the ages and metallicities with low bias. The dispersion varies from 0.08-0.16 dex for ages and 0.11-0.25 dex for metallicity, depending on the redshift and S/N. For dust attenuation, we find a similarly low bias and dispersion. For the sSFR, we find a very good constraining power for star-forming galaxies, log sSFR$\gtrsim$ -11, where the bias is $\sim$ 0.01 dex and the dispersion is $\sim$ 0.10 dex. For more quiescent galaxies, with log sSFR$\lesssim$ -11, we find a higher bias, 0.61-0.86 dex, and a higher dispersion, $\sim$ 0.4 dex, for different S/Ns and redshifts. Generally, we find that the RF outperforms the KNN. Finally, the retrieved sSFR was used to successfully classify galaxies as part of the blue cloud, green valley, or red sequence. We demonstrate that machine learning algorithms can accurately estimate the physical parameters of simulated galaxies even at relatively low S/N=10 per angstrom spectra with available ancillary photometric information.

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arXiv2024

Exploring Galaxy Properties of eCALIFA with Contrastive Learning

Contrastive learning (CL) has emerged as a potent tool for building meaningful latent representations of galaxy properties across a broad spectrum of wavelengths, ranging from optical and infrared to radio frequencies. These representations facilitate a variety of downstream tasks, including galaxy classification, similarity searches, and parameter estimation, which is why they are often referred to as foundation models. In this study, we employ CL on the latest extended DR from CALIFA survey, which encompasses 895 galaxies with enhanced spatial resolution. We demonstrate that CL can be applied to IFU surveys, even with small training sets, to meaningful embedding where galaxies are well-separated based on their physical properties. We discover that the strongest correlations in the embedding space are observed with the EW of Ha morphology, stellar metallicity, age, stellar surface mass density, the [NII]/Ha ratio, and stellar mass, in descending order of correlation strength. Additionally, we illustrate the feasibility of unsupervised separation of galaxy populations along the SFMS, successfully identifying the BC and the RS in a two-cluster scenario, and the GV population in a three-cluster scenario. Our findings indicate that galaxy luminosity profiles have minimal impact on the construction of the embedding space, suggesting that morphology and spectral features play a more significant role in distinguishing between galaxy populations. Moreover, we explore the use of CL for detecting variations in galaxy population distributions across different environments, including voids, clusters, filaments and walls. Nonetheless, we acknowledge the limitations of the CL and our specific training set in detecting subtle differences in galaxy properties, such as the presence of an AGN or other minor scale variations that exceed the scope of primary parameters like stellar mass or morphology.

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arXiv2024

The miniJPAS survey: Maximising the photo-z accuracy from multi-survey datasets with probability conflation

We present a new method for obtaining photometric redshifts (photo-z) for sources observed by multiple photometric surveys using a combination (conflation) of the redshift probability distributions (PDZs) obtained independently from each survey. The conflation of the PDZs has several advantages over the usual method of modelling all the photometry together, including modularity, speed, and accuracy of the results. Using a sample of galaxies with narrow-band photometry in 56 bands from J-PAS and deeper grizy photometry from the Hyper-SuprimeCam Subaru Strategic program (HSC-SSP), we show that PDZ conflation significantly improves photo-z accuracy compared to fitting all the photometry or using a weighted average of point estimates. The improvement over J-PAS alone is particularly strong for i>22 sources, which have low signal-to-noise ratio in the J-PAS bands. For the entire i<22.5 sample, we obtain a 64% (45%) increase in the number of sources with redshift errors |Dz|<0.003, a factor 3.3 (1.9) decrease in the normalised median absolute deviation of the errors (sigma_NMAD), and a factor 3.2 (1.3) decrease in the outlier rate compared to J-PAS (HSC-SSP) alone. The photo-z accuracy gains from combining the PDZs of J-PAS with a deeper broadband survey such as HSC-SSP are equivalent to increasing the depth of J-PAS observations by ~1.2--1.5 magnitudes. These results demonstrate the potential of PDZ conflation and highlight the importance of including the full PDZs in photo-z catalogues.

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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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arXiv2023

The miniJPAS survey: clusters and galaxy groups detection with AMICO

Samples of galaxy clusters allow us to better understand the physics at play in galaxy formation and to constrain cosmological models once their mass, position (for clustering studies) and redshift are known. In this context, large optical data sets play a crucial role. We investigate the capabilities of the Javalambre-Physics of the Accelerating Universe Astrophysical Survey (J-PAS) in detecting and characterizing galaxy groups and clusters. We analyze the data of the miniJPAS survey, obtained with the JPAS-Pathfinder camera and covering $1$ deg$^2$ centered on the AEGIS field to the same depths and with the same 54 narrow band plus 2 broader band near-UV and near-IR filters anticipated for the full J-PAS survey. We use the Adaptive Matched Identifier of Clustered Objects (AMICO) to detect and characterize groups and clusters of galaxies down to $S/N=2.5$ in the redshift range $0.05<z<0.8$. We detect 80, 30 and 11 systems with signal-to-noise ratio larger than 2.5, 3.0 and 3.5, respectively, down to $\sim 10^{13}\,M_{\odot}/h$. We derive mass-proxy scaling relations based on Chandra and XMM-Newton X-ray data for the signal amplitude returned by AMICO, the intrinsic richness and a new proxy that incorporates the galaxies' stellar masses. The latter proxy is made possible thanks to the J-PAS filters and shows a smaller scatter with respect to the richness. We fully characterize the sample and use AMICO to derive a probabilistic membership association of galaxies to the detected groups that we test against spectroscopy. We further show how the narrow band filters of J-PAS provide a gain of up to 100% in signal-to-noise ratio in detection and an uncertainty on the redshift of clusters of only $σ_z=0.0037(1+z)$ placing J-PAS in between broadband photometric and spectroscopic surveys. The performances of AMICO and J-PAS with respect to mass sensitivity, mass-proxies quality

astro-ph.CO↗

arXiv2023

The miniJPAS survey quasar selection III: Classification with artificial neural networks and hybridisation

This paper is part of large effort within the J-PAS collaboration that aims to classify point-like sources in miniJPAS, which were observed in 60 optical bands over $\sim$ 1 deg$^2$ in the AEGIS field. We developed two algorithms based on artificial neural networks (ANN) to classify objects into four categories: stars, galaxies, quasars at low redshift ($z < 2.1)$, and quasars at high redshift ($z \geq 2.1$). As inputs, we used miniJPAS fluxes for one of the classifiers (ANN$_1$) and colours for the other (ANN$_2$). The ANNs were trained and tested using mock data in the first place. We studied the effect of augmenting the training set by creating hybrid objects, which combines fluxes from stars, galaxies, and quasars. Nevertheless, the augmentation processing did not improve the score of the ANN. We also evaluated the performance of the classifiers in a small subset of the SDSS DR12Q superset observed by miniJPAS. In the mock test set, the f1-score for quasars at high redshift with the ANN$_1$ (ANN$_2$) are $0.99$ ($0.99$), $0.93$ ($0.92$), and $0.63$ ($0.57$) for $17 < r \leq 20$, $20 < r \leq 22.5$, and $22.5 < r \leq 23.6$, respectively, where $r$ is the J-PAS rSDSS band. In the case of low-redshift quasars, galaxies, and stars, we reached $0.97$ ($0.97$), $0.82$ ($0.79$), and $0.61$ ($0.58$); $0.94$ ($0.94$), $0.90$ ($0.89$), and $0.81$ ($0.80$); and $1.0$ ($1.0$), $0.96$ ($0.94$), and $0.70$ ($0.52$) in the same r bins. In the SDSS DR12Q superset miniJPAS sample, the weighted f1-score reaches 0.87 (0.88) for objects that are mostly within $20 < r \leq 22.5$. Finally, we estimate the number of point-like sources that are quasars, galaxies, and stars in miniJPAS.

astro-ph.GA↗