arXiv subjects

K. Taylor

Publications and source records attributed to K. Taylor.

At least 19 recordsLinked to original sources

arXiv2026

J-PAS & FLAMINGO: Cosmic voids and void galaxies in the gravitational landscape of photometric surveys

Photometric surveys offer a powerful way to map the large-scale structure of the Universe, but their redshift errors complicate the identification of cosmic voids, challenging studies of their environmental effect on galaxy properties. We present an approach to robustly identify dynamically relevant voids and void galaxies in galaxy mocks of the Javalambre Physics of the Accelerating Universe Astrophysical Survey (J-PAS), testing whether known trends in void galaxy properties survive photometric redshift errors. Using FLAMINGO mocks at z = 0.3 and mi < 20, we compare a FLAMINGO-based ideal (FBI) mock to a FLAMINGO-based JP mock with J-PAS-like redshift errors. We mitigate redshift errors using a quasi-gravitational potential field in the two galaxy mocks. We apply a watershed algorithm to the thresholded quasi-potential field to identify dynamically dominant voids, and define massive void galaxies alongside a comparison sample in high-density regions. Photometric errors lead to a slightly lower void abundance and a marginal shift toward larger, less spherical voids, but overall size and ellipticity distributions agree well between mocks. Their main impact is contamination of void interiors in the JP density profiles by galaxies scattered from high-density regions. We recover a reasonable number of FBI sample voids in the JP sample, with excellent size and shape agreement, occupying ~63% of the thresholded quasi-potential volume. In both mocks, void galaxies show lower stellar masses, bluer colours, and enhanced star formation relative to equal-mass galaxies in high-density regions. These results suggest a quasi-potential can mitigate redshift errors at the level expected for J-PAS, enabling identification of reliable, dynamically dominant voids that are less sensitive to small-scale noise. The massive void galaxy population shows the expected trends relative to high-density environments.

astro-ph.CO↗

arXiv2026

OJAL\'A: 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 $\sigma_{\rm NMAD} < 0.01$, while for QSOs, the precision improves significantly at $z > 1.5$, reaching $\sigma_{\rm NMAD} \approx 0.006$ 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$\alpha$ 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.

astro-ph.GA↗

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$\alpha$, H$\beta$, [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.

astro-ph.GA↗

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 {\AA}. 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 $\xi_\mathrm{ion}$ 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.

astro-ph.GA↗

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$\alpha$+[NII] complex and 7,200 in [OIII]$\lambda 5007$, 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.

astro-ph.GA↗

arXiv2025

J-PAS: A Neural Network Approach to Single Stellar Population Characterization

J-PAS (Javalambre Physics of the Accelerating Universe Astrophysical Survey) will present a groundbreaking photometric survey covering 8500 deg$^2$ of the visible sky from Javalambre, capturing data in 56 narrow band filters. This survey promises to revolutionize galaxy evolution studies by observing $\sim$10$^8$ galaxies with low spectral resolution. A crucial aspect of this analysis involves predicting stellar population parameters from the observed galaxy photometry. In this study, we combine the exquisite J-PAS photometry with state-of-the-art single stellar population (SSP) libraries to accurately predict stellar age, metallicity, and dust attenuation with a neural network (NN) model. The NN is trained on synthetic J-PAS photometry from different SSP librares (E-MILES, Charlot & Bruzual, XSL), to enhance the robustness of our predictions against individual SSP model variations and limitations. To create mock samples with varying observed magnitudes we add artificial noise in the form of random Gaussian variations within typical observational uncertainties in each band. Our results indicate that the NN can accurately estimate stellar parameters for SSP models without evident degeneracies, surpassing a bayesian SED-fitting method on the same test set. We obtain median bias, scatter and percentage of outliers $\mu$ = (0.01 dex, 0.00 dex, 0.00 mag), $\sigma_{NMAD}$ = (0.23 dex, 0.29 dex, 0.04 mag), f$_{o}$ = (17 %, 24 %, 1 %) at $ i \sim$17 mag for age, metallicity and dust attenuation, respectively. The accuracy of the predictions is highly dependent on the signal-to-noise (S/N) ratio of the photometry, achieving robust predictions up to $i$ $\sim$ 20 mag.

astro-ph.GA↗

arXiv2025

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.

astro-ph.GA↗

arXiv2025

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

We report the discovery of a massive and potentially largest Ly$\alpha$ 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$\sigma$ 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$\alpha$ luminosity of $\sim 5.8 \pm 0.7 \times 10^{44}$ erg s$^{-1}$ signify the presence of a giant Enormous Ly$\alpha$ 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$\alpha$ 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.

astro-ph.GA↗

arXiv2025

The J-PAS survey: The effect of photometric redshift errors on cosmic voids

We investigated the impact of photometric redshift errors in the ongoing Javalambre Physics of the Accelerating Universe Astrophysical Survey (J-PAS) on void identification and properties using a watershed-based method, aiming to assess the recovery of individual voids and the overall void environment. We created galaxy mock catalogues for redshift z = 0.1 using the IllustrisTNG300-1 simulation, defining two datasets: an $ideal$ sample ($m_r < 21$ mag) and a $perturbed$ sample with the Z-coordinate errors mimicking J-PAS's line-of-sight errors, derived from the precursor miniJPAS survey data. We identified voids using ZOBOV, a watershed algorithm. We found 1065 voids in the $ideal$ sample and 2558 voids in the $perturbed$ sample. The $perturbed$ sample voids have, on average, smaller sizes and denser interiors. We filtered out voids based on density and radius in order to eliminate overdense and small spurious instances. The stacked density profile of filtered voids in the $perturbed$ sample remains close to the average density even at the boundary peak, indicating a strong blurring of structures by the redshift errors. The number of $ideal$ sample voids for which at least $50\%$ of the volume is recovered by a void in the $perturbed$ sample is 53 (29 for the filtered sample). The volume occupied by these voids is less than $10\%$ of the simulation volume. Merging voids in the $perturbed$ sample marginally improves the recovery. The overall volumes defined as voids in the two samples have an overlap of $80\%$, making up $61\%$ of the simulation box volume. While some statistical properties of voids might be recovered sufficiently well, the watershed algorithms may not be optimal for recovering the large-scale structure voids if applied straight to photometric redshift survey data.

astro-ph.CO↗

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 ($0.05 10.7$).

astro-ph.GA↗

arXiv2023

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.

astro-ph.GA↗

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 $\sigma_z=0.0037(1+z)$ 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↗

arXiv2023

The miniJPAS survey: AGN & host galaxy co-evolution of X-ray selected sources

Studies indicate strong evidence of a scaling relation in the local Universe between the supermassive black hole mass ($M_\rm{BH}$) and the stellar mass of their host galaxies ($M_\star$). They even show similar histories across cosmic times of their differential terms: star formation rate (SFR) and black hole accretion rate (BHAR). However, a clear picture of this coevolution is far from being understood. We select an X-ray sample of active galactic nuclei (AGN) up to $z=2.5$ in the miniJPAS footprint. Their X-ray to infrared spectral energy distributions (SEDs) have been modeled with CIGALE, constraining the emission to 68 bands. For a final sample of 308 galaxies, we derive their physical properties (e.g., $M_\star$, $\rm{SFR}$, $\rm{SFH}$, and $L_\rm{AGN}$). We also fit their optical spectra for a subsample of 113 sources to estimate the $M_\rm{BH}$. We calculate the BHAR depending on two radiative efficiency regimes. We find that the Eddington ratios ($\lambda$) and its popular proxy ($L_\rm{X}$/$M_\star$) have 0.6 dex of difference, and a KS-test indicates that they come from different distributions. Our sources exhibit a considerable scatter on the $M_\rm{BH}$-$M_\star$ relation, which can explain the difference between $\lambda$ and its proxy. We also model three evolution scenarios to recover the integral properties at $z=0$. Using the SFR and BHAR, we show a notable diminution in the scattering between $M_\rm{BH}$-$M_\star$. For the last scenario, we consider the SFH and a simple energy budget for the AGN accretion, obtaining a relation similar to the local Universe. Our study covers $\sim 1$ deg$^2$ in the sky and is sensitive to biases in luminosity. Nevertheless, we show that, for bright sources, the link between SFR and BHAR, and their decoupling based on an energy limit is the key that leads to the local $M_\rm{BH}$-$M_\star$ scaling relation.

astro-ph.GA↗

arXiv2023

J-NEP: 60-band photometry and photometric redshifts for the James Webb Space Telescope North Ecliptic Pole Time-Domain Field

The J-PAS survey will observe ~1/3 of the northern sky with a set of 56 narrow-band filters using the dedicated 2.55 m JST telescope at the Javalambre Astrophysical Observatory. Prior to the installation of the main camera, in order to demonstrate the scientific potential of J-PAS, two small surveys were performed with the single-CCD Pathfinder camera: miniJPAS (~1 deg2 along the Extended Groth Strip), and J-NEP (~0.3 deg2 around the JWST North Ecliptic Pole Time Domain Field), including all 56 J-PAS filters as well as u, g, r, and i. J-NEP is ~0.5-1.0 magnitudes deeper than miniJPAS, providing photometry for 24,618 r-band detected sources and photometric redshifts (photo-z) for the 6,662 sources with r<23. In this paper we describe the photometry and photo-z of J-NEP and demonstrate a new method for the removal of systematic offsets in the photometry based on the median colours of galaxies, dubbed "galaxy locus recalibration". This method does not require spectroscopic observations except in a few reference pointings and, unlike previous methods, is applicable to the whole J-PAS survey. We use a spectroscopic sample of 787 galaxies to test the photo-z performance for J-NEP and in comparison to miniJPAS. We find that the deeper J-NEP observations result in a factor ~1.5-2 decrease in sigma_NMAD (a robust estimate of the standard deviation of the photo-z error) and the outlier rate relative to miniJPAS for r>21.5 sources, but no improvement in brighter ones. We find the same relation between sigma_NMAD and odds in J-NEP and miniJPAS, suggesting sigma_NMAD can be predicted for any set of J-PAS sources from their odds distribution alone, with no need for additional spectroscopy to calibrate the relation. We explore the causes for photo-z outliers and find that colour-space degeneracy at low S/N, photometry artifacts, source blending, and exotic spectra are the most important factors.

astro-ph.GA↗

arXiv2022

The miniJPAS survey: stellar atmospheric parameters from 56 optical filters

With a unique set of 54 overlapping narrow-band and two broader filters covering the entire optical range, the incoming Javalambre-Physics of the Accelerating Universe Astrophysical Survey (J-PAS) will provide a great opportunity for stellar physics and near-field cosmology. In this work, we use the miniJPAS data in 56 J-PAS filters and 4 complementary SDSS-like filters to explore and prove the potential of the J-PAS filter system in characterizing stars and deriving their atmospheric parameters. We obtain estimates for the effective temperature with a good precision (<150 K) from spectral energy distribution fitting. We have constructed the metallicity-dependent stellar loci in 59 colours for the miniJPAS FGK dwarf stars, after correcting certain systematic errors in flat-fielding. The very blue colours, including uJAVA-r, J0378-r, J0390-r, uJPAS-r, show the strongest metallicity dependence, around 0.25 mag/dex. The sensitivities decrease to about 0.1 mag/dex for the J0400-r, J0410-r, and J0420-r colours. The locus fitting residuals show peaks at the J0390, J0430, J0510, and J0520 filters, suggesting that individual elemental abundances such as [Ca/Fe], [C/Fe], and [Mg/Fe] can also be determined from the J-PAS photometry. Via stellar loci, we have achieved a typical metallicity precision of 0.1 dex. The miniJPAS filters also demonstrate strong potential in discriminating dwarfs and giants, particularly the J0520 and J0510 filters. Our results demonstrate the power of the J-PAS filter system in stellar parameter determinations and the huge potential of the coming J-PAS survey in stellar and Galactic studies.

astro-ph.SR↗

arXiv2022

TOPz: Photometric redshifts for J-PAS

The importance of photometric galaxy redshift estimation is rapidly increasing with the development of specialised powerful observational facilities. We develop a new photometric redshift estimation workflow TOPz to provide reliable and efficient redshift estimations for the upcoming large-scale survey J-PAS which will observe 8500 deg2 of the northern sky through 54 narrow-band filters. TOPz relies on template-based photo-z estimation with some added J-PAS specific features and possibilities. We present TOPz performance on data from the miniJPAS survey, a precursor to the J-PAS survey with an identical filter system. First, we generated spectral templates based on the miniJPAS sources using the synthetic galaxy spectrum generation software CIGALE. Then we applied corrections to the input photometry by minimising systematic offsets from the template flux in each filter. To assess the accuracy of the redshift estimation, we used spectroscopic redshifts from the DEEP2, DEEP3, and SDSS surveys, available for 1989 miniJPAS galaxies with r < 22 magAB. We also tested how the choice and number of input templates, photo-z priors, and photometric corrections affect the TOPz redshift accuracy. The general performance of the combination of miniJPAS data and the TOPz workflow fulfills the expectations for J-PAS redshift accuracy. Similarly to previous estimates, we find that 38.6% of galaxies with r < 22 mag reach the J-PAS redshift accuracy goal of dz/(1 + z) < 0.003. Limiting the number of spectra in the template set improves the redshift accuracy up to 5%, especially for fainter, noise-dominated sources. Further improvements will be possible once the actual J-PAS data become available.

astro-ph.IM↗