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M. Moles

Publications and source records attributed to M. Moles.

At least 37 records · Page 2Linked to original sources

The J-PLUS collaboration. Additive versus multiplicative systematics in surveys of the large scale structure of the Universe

Observational and/or astrophysical systematics modulating the observed number of luminous tracers can constitute a major limitation in the cosmological exploitation of surveys of the large scale structure of the universe. Part of this limitation arises on top of our ignorance on how such systematics actually impact the observed galaxy/quasar fields. In this work we develop a generic, hybrid model for an arbitrary number of systematics that may modulate observations in both an additive and a multiplicative way, after applying a nonlinear power law transformation. This model allows us devising a novel algorithm that addresses the identification and correction for either additive and/or multiplicative contaminants. We test this model on galaxy mocks and systematics templates inspired from data of the third data release of the {\it Javalambre Photometric Local Universe Survey} (J-PLUS). We find that our method clearly outperforms standard methods that assume either an additive or multiplicative character for all contaminants in scenarios where both characters are actually acting on the observed data. In simpler scenarios where only an additive or multiplicative imprint on observations is considered, our hybrid method does not lie far behind the corresponding simplified, additive/multiplicative methods. Nonetheless, in scenarios of mild/low impact of systematics, we find that our hybrid approach converges towards the standard method that assumes additive contamination, as predicted by our model describing systematics. Our methodology also allows for the estimation of biases induced by systematics residuals on different angular scales and under different observational configurations, although these predictions necessarily restrict to the subset of {\em known/identified} potential systematics, and say nothing about ``unknown unknowns" possibly impacting the data.

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J-PLUS: Tomographic analysis of galaxy angular density and redshift fluctuations in Data Release 3. Constraints on photo-$z$ errors, linear bias, and peculiar velocities

The {\it Javalambre Photometric Local Universe Survey} (J-PLUS) is a {\it spectro-photometric} survey covering about 3,000~deg$^2$ in its third data release (DR3), and containing about 300,000 galaxies with high quality ({\it odds}$>0.8$) photometric redshifts (hereafter photo-$z$s). We use this galaxy sample to conduct a tomographic study of the counts and redshift angular fluctuations under Gaussian shells sampling the redshift range $z\in[0.05,0.25]$. We confront the angular power spectra of these observables measured under shells centered on 11 different redshifts with theoretical expectations derived from a linear Boltzmann code ({\tt ARFCAMB}). Overall we find that J-PLUS DR3 data are well reproduced by our linear, simplistic model. We obtain that counts (or density) angular fluctuations (hereafter ADF) are very sensitive to the linear galaxy bias $b_g(z)$, although weakly sensitive to radial peculiar velocities of the galaxy field, while suffering from systematics residuals for $z>0.15$. Angular redshift fluctuations (ARF), instead, show higher sensitivity to radial peculiar velocities and also higher sensitivity to the average uncertainty in photo-$z$s ($σ_{\rm Err}$), with no obvious impact from systematics. For $z<0.15$ both ADF and ARF agree on measuring a monotonically increasing linear bias varying from $b_g(z=0.05)\simeq 0.9\pm 0.06$ up to $b_g(z=0.15)\simeq 1.5\pm 0.05$, while, by first time, providing consistent measurements of $σ_{\rm Err}(z)\sim 0.014$ that are $\sim 40~\%$ higher than estimates from the photo-$z$ code {\tt LePhare}, ($σ_{\rm Err}^{\rm LePhare}=0.010$). As expected, this photo-$z$ uncertainty level prevents the detection of radial peculiar velocities in the modest volume sampled by J-PLUS DR3, although prospects for larger galaxy surveys of similar (and higher) photo-$z$ precision are promising.

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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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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.

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

We used the Javalambre Photometric Local Universe Survey (J-PLUS) DR2 photometry in twelve optical bands over 2176 deg2 to estimate the fraction of white dwarfs with presence of CaII H+K absorption along the cooling sequence. We compared the J-PLUS photometry against metal-free theoretical models to estimate the equivalent width in the J0395 passband of 10 nm centered at 395 nm (EW_J0395), a proxy to detect calcium absorption. A total of 4399 white dwarfs within 30000 > Teff > 5500 K and mass M > 0.45 Msun were analyzed. Their EW_J0395 distribution was modeled using two populations, corresponding to polluted and non-polluted systems, to estimate the fraction of calcium white dwarfs (f_Ca) as a function of Teff. The probability for each individual white dwarf of presenting calcium absorption, pca, was also computed. The comparison with both the measured Ca/He abundance and the metal pollution from spectroscopy shows that EW_J0395 correlates with the presence of calcium. The fraction of calcium white dwarfs increases from f_Ca = 0 at Teff = 13500 K to f_Ca = 0.15 at Teff = 5500 K. We compare our results with the fractions derived from the 40 pc spectroscopic sample and from SDSS spectra. The trend found in J-PLUS observations is also present in the 40 pc sample, however SDSS shows a deficit of metal-polluted objects at Teff < 12000 K. Finally, we found 39 white dwarfs with pca > 0.99. Twenty of them have spectra presented in previous studies, whereas we observed six additional targets. These 26 objects were all confirmed as metal-polluted systems. The J-PLUS optical data provide a robust statistical measurement for the presence of CaII H+K absorption in white dwarfs. We find a 15 +- 3 % increase in the fraction of calcium white dwarfs from Teff = 13500 K to 5500 K, which reflects their selection function in the optical from the total population of metal-polluted systems.

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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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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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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.

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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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J-PLUS DR3: Galaxy-Star-Quasar classification

The Javalambre Photometric Local Universe Survey (J-PLUS) is a 12-band photometric survey using the 83-cm JAST telescope. Data Release 3 includes 47.4 million sources. J-PLUS DR3 only provides star-galaxy classification so that quasars are not identified from the other sources. Given the size of the dataset, machine learning methods could provide a valid alternative classification and a solution to the classification of quasars. Our objective is to classify J-PLUS DR3 sources into galaxies, stars and quasars, outperforming the available classifiers in each class. We use an automated machine learning tool called TPOT to find an optimized pipeline to perform the classification. The supervised machine learning algorithms are trained on the crossmatch with SDSS DR18, LAMOST DR8 and Gaia. We checked that the training set of about 660 thousand galaxies, 1.2 million stars and 270 thousand quasars is both representative and contain a minimal presence of contaminants (less than 1%). We considered 37 features: the twelve photometric bands with respective errors, six colors, four morphological parameters, galactic extinction with its error and the PSF relative to the corresponding pointing. With TPOT genetic algorithm, we found that XGBoost provides the best performance: the AUC for galaxies, stars and quasars is above 0.99 and the average precision is above 0.99 for galaxies and stars and 0.96 for quasars. XGBoost outperforms the classifiers already provided in J-PLUS DR3 and also classifies quasars.

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J-PLUS: Photometric Re-calibration with the Stellar Color Regression Method and an Improved Gaia XP Synthetic Photometry Method

We employ the corrected Gaia Early Data Release 3 (EDR3) photometric data and spectroscopic data from the Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST) DR7 to assemble a sample of approximately 0.25 million FGK dwarf photometric standard stars for the 12 J-PLUS filters using the Stellar Color Regression (SCR) method. We then independently validated the J-PLUS DR3 photometry, and uncovered significant systematic errors: up to 15 mmag in the results of Stellar Locus (SL) method, and up to 10 mmag mainly caused by magnitude-, color-, and extinction-dependent errors of the Gaia XP spectra with the Gaia BP/RP (XP) Synthetic Photometry (XPSP) method. We have also further developed the XPSP method using the corrected Gaia XP spectra by Huang et al. (2023) and applied it to the J-PLUS DR3 photometry. This resulted in an agreement of 1-5 mmag with the SCR method, and a two-fold improvement in the J-PLUS zero-point precision. Finally, the zero-point calibration for around 91% of the tiles within the LAMOST observation footprint is determined through the SCR method, with the remaining approximately 9% of tiles outside this footprint relying on the improved XPSP method. The re-calibrated J-PLUS DR3 photometric data establishes a solid data foundation for conducting research that depends on high-precision photometric calibration.

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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

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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.

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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 ($λ$) 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 $λ$ 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.

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

We present the photometric calibration of the twelve optical passbands for the Javalambre Photometric Local Universe Survey (J-PLUS) third data release (DR3), comprising 1642 pointings of two square degrees each. We selected nearly 1.5 million main sequence stars with a signal-to-noise ratio larger than ten in the twelve J-PLUS passbands and available low-resolution (R = 20-80) spectrum from the blue and red photometers (BP/RP) in Gaia DR3. We compared the synthetic photometry from BP/RP spectra with the J-PLUS instrumental magnitudes, after correcting for the magnitude and color terms between both systems, to obtain an homogeneous photometric solution for J-PLUS. To circumvent the current limitations in the absolute calibration of the BP/RP spectra, the absolute color scale was derived using the locus of 109 white dwarfs closer than 100 pc with a negligible interstellar extinction. Finally, the absolute flux scale was anchored to the Panoramic Survey Telescope and Rapid Response System (Pan-STARRS) photometry in the r band. The precision of the J-PLUS photometric calibration, estimated from duplicated objects observed in adjacent pointings and by comparison with the spectro-photometric standard star GD 153, is ~12 mmag in u, J0378, and J0395; and ~7 mmag in J0410, J0430, g, J0515, r, J0660, i, J0861, and z. The estimated accuracy in the calibration along the surveyed area is better than 1% for all the passbands. The Gaia BP/RP spectra provide a high-quality, homogeneous photometric reference in the optical range across the full-sky, in spite of their current limitations as an absolute reference. The calibration method for J-PLUS DR3 reaches an absolute precision and accuracy of 1% in the twelve optical filters within an area of 3284 square degrees.

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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.

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Costs and benefits of automation for astronomical facilities

The Observatorio Astrofísico de Javalambre (OAJ†1) in Spain is a young astronomical facility, conceived and developed from the beginning as a fully automated observatory with the main goal of optimizing the processes in the scientific and general operation of the Observatory. The OAJ has been particularly conceived for carrying out large sky surveys with two unprecedented telescopes of unusually large fields of view (FoV): the JST/T250, a 2.55m telescope of 3deg field of view, and the JAST/T80, an 83cm telescope of 2deg field of view. The most immediate objective of the two telescopes for the next years is carrying out two unique photometric surveys of several thousands square degrees, J-PAS†2 and J-PLUS†3, each of them with a wide range of scientific applications, like e.g. large structure cosmology and Dark Energy, galaxy evolution, supernovae, Milky Way structure, exoplanets, among many others. To do that, JST and JAST are equipped with panoramic cameras under development within the J-PAS collaboration, JPCam and T80Cam respectively, which make use of large format (~ 10k x 10k) CCDs covering the entire focal plane. This paper describes in detail, from operations point of view, a comparison between the detailed cost of the global automation of the Observatory and the standard automation cost for astronomical facilities, in reference to the total investment and highlighting all benefits obtained from this approach and difficulties encountered. The paper also describes the engineering development of the overall facilities and infrastructures for the fully automated observatory and a global overview of current status, pinpointing lessons learned in order to boost observatory operations performance, achieving scientific targets, maintaining quality requirements, but also minimizing operation cost and human resources.

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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.

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