Searcharxiv⌕ Search

arXiv subjects

A. Ederoclite

Publications and source records attributed to A. Ederoclite.

At least 55 records · Page 3Linked to original sources

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↗

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.

astro-ph.IM↗

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↗

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↗

J-PLUS: Discovery and characterisation of ultracool dwarfs using Virtual Observatory tools II. Second data release and machine learning methodology

Ultracool dwarfs (UCDs) comprise the lowest mass members of the stellar population and brown dwarfs, from M7 V to cooler objects with L, T, and Y spectral types. Most of them have been discovered using wide-field imaging surveys, for which the Virtual Observatory (VO) has proven to be of great utility. We aim to perform a search for UCDs in the entire Javalambre Photometric Local Universe Survey (J-PLUS) second data release (2176 deg$^2$) following a VO methodology. We also explore the ability to reproduce this search with a purely machine learning (ML)-based methodology that relies solely on J-PLUS photometry. We followed three different approaches based on parallaxes, proper motions, and colours, respectively, using the VOSA tool to estimate the effective temperatures. For the ML methodology, we built a two-step method based on principal component analysis and support vector machine algorithms. We identified a total of 7827 new candidate UCDs, which represents an increase of about 135% in the number of UCDs reported in the sky coverage of the J-PLUS second data release. Among the candidate UCDs, we found 122 possible unresolved binary systems, 78 wide multiple systems, and 48 objects with a high Bayesian probability of belonging to a young association. We also identified four objects with strong excess in the filter corresponding to the Ca II H and K emission lines and four other objects with excess emission in the H$α$ filter. With the ML approach, we obtained a recall score of 92% and 91% in the test and blind test, respectively. We consolidated the proposed search methodology for UCDs, which will be used in deeper and larger upcoming surveys such as J-PAS and Euclid. We concluded that the ML methodology is more efficient in the sense that it allows for a larger number of true negatives to be discarded prior to analysis with VOSA, although it is more photometrically restrictive.

astro-ph.SR↗

J-PLUS: Support Vector Regression to Measure Stellar Parameters

Context. Stellar parameters are among the most important characteristics in studies of stars, which are based on atmosphere models in traditional methods. However, time cost and brightness limits restrain the efficiency of spectral observations. The J-PLUS is an observational campaign that aims to obtain photometry in 12 bands. Owing to its characteristics, J-PLUS data have become a valuable resource for studies of stars. Machine learning provides powerful tools to efficiently analyse large data sets, such as the one from J-PLUS, and enable us to expand the research domain to stellar parameters. Aims. The main goal of this study is to construct a SVR algorithm to estimate stellar parameters of the stars in the first data release of the J-PLUS observational campaign. Methods. The training data for the parameters regressions is featured with 12-waveband photometry from J-PLUS, and is cross-identified with spectrum-based catalogs. These catalogs are from the LAMOST, the APOGEE, and the SEGUE. We then label them with the stellar effective temperature, the surface gravity and the metallicity. Ten percent of the sample is held out to apply a blind test. We develop a new method, a multi-model approach in order to fully take into account the uncertainties of both the magnitudes and stellar parameters. The method utilizes more than two hundred models to apply the uncertainty analysis. Results. We present a catalog of 2,493,424 stars with the Root Mean Square Error of 160K in the effective temperature regression, 0.35 in the surface gravity regression and 0.25 in the metallicity regression. We also discuss the advantages of this multi-model approach and compare it to other machine-learning methods.

astro-ph.IM↗

The miniJPAS survey: The galaxy populations in the most massive cluster in miniJPAS, mJPC2470-1771

The miniJPAS is a 1 deg$^2$ survey that uses the Javalambre-Physics of the Accelerating Universe Astrophysical Survey (J-PAS) filter system (54 narrow-band filters) with the Pathfinder camera. We study mJPC2470-1771, the most massive cluster detected in miniJPAS. We study the stellar population properties of the members, their star formation rates (SFR), star formation histories (SFH), the emission line galaxy (ELG) population, their spatial distribution, and the effect of the environment on them, showing the power of J-PAS to study the role of environment in galaxy evolution. We use a spectral energy distribution (SED) fitting code to derive the stellar population properties of the galaxy members: stellar mass, extinction, metallicity, colours, ages, SFH (a delayed-$τ$ model), and SFRs. Artificial Neural Networks are used for the identification of the ELG population through the detection of H$α$, [NII], H$β$, and [OIII] nebular emission. We use the WHAN and BPT diagrams to separate them into star-forming galaxies and AGNs. We find that the fraction of red galaxies increases with the cluster-centric radius. We select 49 ELG, 65.3\% of the them are probably star forming galaxies, and they are dominated by blue galaxies. 24% are likely to host an AGN (Seyfert or LINER galaxies). The rest are difficult to classify and are most likely composite galaxies. Our results are compatible with an scenario where galaxy members were formed roughly at the same epoch, but blue galaxies have had more recent star formation episodes, and they are quenching from inside-out of the cluster centre. The spatial distribution of red galaxies and their properties suggest that they were quenched prior to the cluster accretion or an earlier cluster accretion epoch. AGN feedback and/or mass might also be intervening in the quenching of these galaxies.

astro-ph.GA↗

The miniJPAS survey: The role of group environment in quenching the star formation

The miniJPAS survey has observed $\sim 1$ deg$^2$ on the AEGIS field with 60 bands (spectral resolution of $R \sim 60$) in order to demonstrate the capabilities of the Javalambre-Physics of the Accelerating Universe Astrophysical Survey (J-PAS) that will map $\sim 8000$ deg$^2$ of the northern sky in the next years. This paper shows the power of J-PAS to detect low mass groups and characterise their galaxy populations up to $z \sim 1$. We use the spectral energy distribution fitting code BaySeAGal to derive the stellar population properties of the galaxy members in 80 groups at $z \leq 0.8$ previously detected by the AMICO code, as well as for a galaxy field sample retrieved from the whole miniJPAS sample. We identify blue, red, quiescent, and transition galaxy populations through their rest-frame (extinction corrected) colour, stellar mass ($M_\star$) and specific star formation rate. We measure their abundance as a function of $M_\star$ and environment. We find: (i) The fraction of red and quiescent galaxies in groups increases with $M_\star$ and it is always higher in groups than in the field. (ii) The quenched fraction excess (QFE) in groups strongly increases with $M_\star$, (from a few percent to higher than 60% in the mass range $10^{10} - 3 \times 10 ^{11}$ $M_\odot$. (iii) The abundance excess of transition galaxies in groups shows a modest dependence with $M_\star$ (iv) The fading time scale is very short ($<1.5$ Gyr), indicating that the star formation declines very rapidly in groups. (v) The evolution of the galaxy quenching rate in groups shows a modest but significant evolution since $z\sim0.8$, compatible with an evolution with constant $QFE=0.4$, previously measured for satellites in the nearby Universe, and consistent with a scenario where the low-mass star-forming galaxies in clusters at $z= 1-1.4$ are environmentally quenched.

astro-ph.GA↗

The miniJPAS survey: Identification and characterization of the emission line galaxies down to $z < 0.35$ in the AEGIS field

The Javalambre-Physics of the Accelerating Universe Astrophysical Survey (J-PAS) is expected to map thousands of square degrees of the northern sky with 56 narrowband filters in the upcoming years. This will make J-PAS a very competitive and unbiased emission line survey compared to spectroscopic or narrowband surveys with fewer filters. The miniJPAS survey covered 1 deg$^2$, and it used the same photometric system as J-PAS, but the observations were carried out with the pathfinder J-PAS camera. In this work, we identify and characterize the sample of emission line galaxies (ELGs) from miniJPAS with a redshift lower than $0.35$. Using a method based on artificial neural networks, we detect the ELG population and measure the equivalent width and flux of the $Hα$, $Hβ$, [OIII], and [NII] emission lines. We explore the ionization mechanism using the diagrams [OIII]/H$β$ versus [NII]/H$α$ (BPT) and EW(H$α$) versus [NII]/H$α$ (WHAN). We identify 1787 ELGs ($83$%) from the parent sample (2154 galaxies) in the AEGIS field. For the galaxies with reliable EW values that can be placed in the WHAN diagram (2000 galaxies in total), we obtained that $72.8 \pm 0.4$%, $17.7 \pm 0.4$% , and $9.4 \pm 0.2$% are star-forming (SF), active galactic nucleus (Seyfert), and quiescent galaxies, respectively. Based on the flux of $Hα$ we find that the star formation main sequence is described as $\log$ SFR $[M_\mathrm{\odot} \mathrm{yr}^{-1}] = 0.90^{+ 0.02}_{-0.02} \log M_{\star} [M_\mathrm{\odot}] -8.85^{+ 0.19}_{-0.20}$ and has an intrinsic scatter of $0.20^{+ 0.01}_{-0.01}$. The cosmic evolution of the SFR density ($ρ_{\text{SFR}}$) is derived at three redshift bins: $0 < z \leq 0.15$, $0.15 < z \leq 0.25$, and $0.25 < z \leq 0.35$, which agrees with previous results that were based on measurements of the $Hα$ emission line.

astro-ph.GA↗

J-PLUS: Spectral evolution of white dwarfs by PDF analysis

We estimated the spectral evolution of white dwarfs with effective temperature using the Javalambre Photometric Local Universe Survey (J-PLUS) second data release (DR2), that provides twelve photometric optical passbands over 2176 deg2. We analysed 5926 white dwarfs with r <= 19.5 mag in common between a white dwarf catalog defined from Gaia EDR3 and J-PLUS DR2. We performed a Bayesian analysis by comparing the observed J-PLUS photometry with theoretical models of hydrogen (H) and helium (He) dominated atmospheres. We estimated the PDF for effective temperature (Teff), surface gravity, parallax, and spectral type; and the probability of having a H-dominated atmosphere (pH) for each source. We applied a prior in parallax, using Gaia EDR3 measurements as reference, and derived a self-consistent prior for the atmospheric composition as a function of Teff. We described the fraction of He-dominated atmosphere white dwarfs (fHe) with a linear function of Teff at 5000 < Teff < 30000 K. We found fHe = 0.24 +- 0.01 at Teff = 10000 K, a change rate along the cooling sequence of 0.14 +- 0.02 per 10 kK, and a minimum He-dominated fraction of 0.08 +- 0.02 at the high-temperature end. We tested the obtained pH by comparison with spectroscopic classifications, finding that it is reliable. We estimated the mass distribution for the 351 sources with distance d < 100 pc, mass M > 0.45 Msun, and Teff > 6000 K. The result for H-dominated white dwarfs agrees with previous work, with a dominant M = 0.59 Msun peak and the presence of an excess at M ~ 0.8 Msun. This high-mass excess is absent in the He-dominated distribution, which presents a single peak. The J-PLUS optical data provides a reliable statistical classification of white dwarfs into H- and He-dominated atmospheres. We find a 21 +- 3 % increase in the fraction of He-dominated white dwarfs from Teff = 20000 K to Teff = 5000 K.

astro-ph.SR↗

The miniJPAS survey: White dwarf science with 56 optical filters

We analyze the white dwarf population in miniJPAS, the first square degree observed with 56 medium-band, 145 A in width optical filters by the Javalambre Physics of the accelerating Universe Astrophysical Survey (J-PAS), to provide a data-based forecast for the white dwarf science with low-resolution (R ~ 50) photo-spectra. We define the sample of the bluest point-like sources in miniJPAS with r < 21.5 mag, point-like probability larger than 0.5, (u-r) < 0.80 mag, and (g-i) < 0.25 mag. This sample comprises 33 sources with spectroscopic information, 11 white dwarfs and 22 QSOs. We estimate the effective temperature (Teff), the surface gravity, and the composition of the white dwarf population by a Bayesian fitting to the observed photo-spectra. The miniJPAS data permit the classification of the observed white dwarfs into H-dominated and He-dominated with 99% confidence, and the detection of calcium absorption and polluting metals down to r ~ 21.5 mag at least for sources with 7000 < Teff < 22000 K, the temperature range covered by the white dwarfs in miniJPAS. The effective temperature is estimated with a 2% uncertainty, close to the 1% from spectroscopy. A precise estimation of the surface gravity depends on the available parallax information. In addition, the white dwarf population at Teff > 7000 K can be segregated from the bluest extragalactic QSOs, providing a clean sample based on optical photometry alone. The J-PAS low-resolution photo-spectra provide precise and accurate effective temperatures and atmospheric compositions for white dwarfs, complementing the data from Gaia. J-PAS will also detect and characterize new white dwarfs beyond the Gaia magnitude limit, providing faint candidates for spectroscopic follow up.

astro-ph.SR↗

J-PLUS: Support Vector Machine Applied to STAR-GALAXY-QSOClassification

Context. In modern astronomy, machine learning has proved to be efficient and effective to mine the big data from the newesttelescopes. Spectral surveys enable us to characterize millions of objects, while long exposure time observations and wide surveysconstrain their strides from millions to billions. Aims.In this study, we construct a supervised machine learning algorithm, to classify the objects in the Javalambre Photometric LocalUniverse Survey first data release (J-PLUS DR1). Methods.The sample set is featured with 12-waveband photometry, and magnitudes are labeled with spectrum-based catalogs, in-cluding Sloan Digital Sky Survey spectroscopic data, Large Sky Area Multi-Object Fiber Spectroscopic Telescope, and VERONCAT- Veron Catalog of Quasars & AGN. The performance of the classifier is presented with applications of blind test validations basedon RAdial Velocity Extension, Kepler Input Catalog, 2 MASS Redshift Survey, and the UV-bright Quasar Survey. A new algorithmis applied to constrain the extrapolation that could decrease accuracies for many machine learning classifiers. Results.The accuracies of the classifier are 96.5% in blind test and 97.0% in training cross validation. The F1-scores for each classare presented to show the precision of the classifier. We also discuss different methods to constrain the po

astro-ph.IM↗

J-PLUS: Uncovering a large population of extreme [OIII] emitters in the local Universe

Over the past decades, several studies have discovered a population of galaxies undergoing very strong star formation events, called extreme emission line galaxies (EELGs). In this work, we exploit the capabilities of the Javalambre Photometric Local Universe Survey (J-PLUS), a wide field multifilter survey, with 2000 square degrees observed. We use it to identify EELGs at low redshift by their [OIII]5007 emission line. We intend to provide with a more complete, deep, and less biased sample of local EELGs. We select objects with an excess of flux in the J-PLUS mediumband $J0515$ filter, which covers the [OIII] line at z$<$0.06. We remove contaminants (stars and higher redshift systems) using J-PLUS and WISE infrared data, with SDSS spectra as a benchmark. We perform spectral energy distribution fitting to estimate the properties of the galaxies: line fluxes, equivalent widths (EWs), masses, etc. We identify 466 EELGs at ${\rm z} < 0.06$ with [OIII] EW over 300 \textÅ and $r$-band mag. below 20, of which 411 were previously unknown. Most show compact morphologies, low stellar masses ($\log (M_{\star}/M_{\odot}) \sim {8.13}^{+0.61}_{-0.58}$), low dust extinction ($E(B-V)\sim{0.1}^{+0.2}_{-0.1}$), and very young bursts of star formation (${3.0}^{+2.7}_{-2.0}$ Myr). Our method is up to $\sim$ 20 times more efficient detecting EELGs per Mpc$^3$ than broadband surveys, and as complete as magnitude-limited spectroscopic surveys (and reaching fainter objects). The sample is not directly biased against strong H$α$ emitters, in contrast with broadband surveys. We demonstrate the capability of J-PLUS to identify, following a clear selection process, a large sample of previously unknown EELGs showing unique properties. A fraction of them are likely similar to the first galaxies in the Universe, but at a much lower redshift, which makes them ideal targets for follow-up studies.

astro-ph.GA↗

J-PLUS: Systematic impact of metallicity on photometric calibration with the stellar locus

We present the updated photometric calibration of the twelve optical passbands for the Javalambre Photometric Local Universe Survey (J-PLUS) second data release (DR2), comprising 1088 pointings of two square degrees, and study the systematic impact of metallicity in the stellar locus technique. The [Fe/H] metallicity from LAMOST DR5 for 146184 high-quality calibration stars, defined with S/N > 10 in J-PLUS passbands and S/N > 3 in Gaia parallax, was used to compute the metallicity-dependent stellar locus (ZSL). The initial homogenization of J-PLUS photometry, performed with a unique stellar locus, was refined by including the metallicity effect in colours via the ZSL. The variation of the average metallicity along the Milky Way produces a systematic offset in J-PLUS calibration. This effect is well above 1% for the bluer passbands and amounts 0.07, 0.07, 0.05, 0.03, and 0.02 mag in u, J0378, J0395, J0410, and J0430, respectively. We modelled this effect with the Milky Way location of the J-PLUS pointing, providing also an updated calibration for those observations without LAMOST information. The estimated accuracy in the calibration after including the metallicity effect is at 1% level for the bluer J-PLUS passbands and below for the rest. We conclude that photometric calibration with the stellar locus technique is prone to significant systematic bias along the Milky Way location for passbands bluer than lambda = 4500 A. The updated calibration method for J-PLUS DR2 reaches 1-2% precision and 1% accuracy for twelve optical filters within an area of 2176 square degrees.

astro-ph.GA↗

The miniJPAS Survey: A Study on Wavelength Dependence of the Photon Response Non-uniformity of the JPAS-{\it Pathfinder} Camera

Understanding the origins of small-scale flats of CCDs and their wavelength-dependent variations plays an important role in high-precision photometric, astrometric, and shape measurements of astronomical objects. Based on the unique flat data of 47 narrow-band filters provided by JPAS-{\it Pathfinder}, we analyze the variations of small-scale flats as a function of wavelength. We find moderate variations (from about $1.0\%$ at 390 nm to $0.3\%$ at 890 nm) of small-scale flats among different filters, increasing towards shorter wavelengths. Small-scale flats of two filters close in central wavelengths are strongly correlated. We then use a simple physical model to reproduce the observed variations to a precision of about $\pm 0.14\%$, by considering the variations of charge collection efficiencies, effective areas and thicknesses between CCD pixels. We find that the wavelength-dependent variations of small-scale flats of the JPAS-{\it Pathfinder} camera originate from inhomogeneities of the quantum efficiency (particularly charge collection efficiency) as well as the effective area and thickness of CCD pixels. The former dominates the variations in short wavelengths while the latter two dominate at longer wavelengths. The effects on proper flat-fielding as well as on photometric/flux calibrations for photometric/slit-less spectroscopic surveys are discussed, particularly in blue filters/wavelengths. We also find that different model parameters are sensitive to flats of different wavelengths, depending on the relations between the electron absorption depth, the photon absorption length and the CCD thickness. In order to model the wavelength-dependent variations of small-scale flats, a small number (around ten) of small-scale flats with well-selected wavelengths are sufficient to reconstruct small-scale flats in other wavelengths.

astro-ph.IM↗

The miniJPAS survey: the photometric redshift catalogue

MiniJPAS is a ~1 deg^2 imaging survey of the AEGIS field in 60 bands, performed to demonstrate the scientific potential of the upcoming JPAS survey. Full coverage of the 3800-9100 Årange with 54 narrow and 6 broad optical filters allow for extremely accurate photo-z, which applied over 1000s of deg^2 will enable new applications of the photo-z technique such as measurement of baryonic acoustic oscillations. In this paper we describe the method used to obtain the photo-z included in the publicly available miniJPAS catalogue, and characterise the photo-z performance. We build 100 Åresolution photo-spectra from the PSF-corrected forced-aperture photometry. Systematic offsets in the photometry are corrected by applying magnitude shifts obtained through iterative fitting with stellar population synthesis models. We compute photo-z with a customised version of LePhare, using a set of templates optimised for the J-PAS filter-set. We analyse the accuracy of miniJPAS photo-z and their dependence on multiple quantities using a subsample of 5,266 galaxies with spectroscopic redshifts from SDSS and DEEP, that we find to be representative of the whole r<23 miniJPAS sample. Formal uncertainties for the photo-z that are calculated with the δχ^2 method underestimate the actual redshift errors. The odds parameter has the stronger correlation with |Dz|, and accurately reproduces the probability of a redshift outlier (|Dz|>0.03) irrespective of the magnitude, redshift, or spectral type of the sources. We show that the two main summary statistics characterising the photo-z accuracy for a population of galaxies (snmad and η) can be predicted by the distribution of odds in such population, and use this to estimate them for the whole miniJPAS sample. At r<23 there are 17,500 galaxies/deg^2 with valid photo-z estimates, of which 4,200 are expected to have |Dz|<0.003 (abridged).

astro-ph.GA↗

The GALANTE photometric survey of the northern Galactic plane: Project description and pipeline

The GALANTE optical photometric survey is observing the northern Galactic plane and some adjacent regions using seven narrow- and intermediate-filters, covering a total of 1618 square degrees. The survey has been designed with multiple exposure times and at least two different air masses per field to maximize its photometric dynamic range, comparable to that of Gaia, and ensure the accuracy of its photometric calibration. The goal is to reach at least 1% accuracy and precision in the seven bands for all stars brighter than AB magnitude 17 while detecting fainter stars with lower values of the signal-to-noise ratio.The main purposes of GALANTE are the identification and study of extinguished O+B+WR stars, the derivation of their extinction characteristics, and the cataloguing of F and G stars in the solar neighbourhood. Its data will be also used for a variety of other stellar studies and to generate a high-resolution continuum-free map of the Hα emission in the Galactic plane. We describe the techniques and the pipeline that are being used to process the data, including the basis of an innovative calibration system based on Gaia DR2 and 2MASS photometry.

astro-ph.GA↗

The miniJPAS survey: Identification and characterization of galaxy populations with the J-PAS photometric system

J-PAS will soon start imaging 8000 deg2 of the northern sky with its unique set of 56 filters (R $\sim$ 60). Before, we observed 1 deg2 on the AEGIS field with an interim camera with all the J-PAS filters. With this data (miniJPAS), we aim at proving the scientific potential of J-PAS to identify and characterize the galaxy populations with the goal of performing galaxy evolution studies across cosmic time. Several SED-fitting codes are used to constrain the stellar population properties of a complete flux-limited sample (rSDSS <= 22.5 AB) of miniJPAS galaxies that extends up to z = 1. We find consistent results on the galaxy properties derived from the different codes, independently of the galaxy spectral-type or redshift. For galaxies with SNR>=10, we estimate that the J-PAS photometric system allows to derive stellar population properties with a precision that is equivalent to that obtained with spectroscopic surveys of similar SNR. By using the dust-corrected (u-r) colour-mass diagram, a powerful proxy to characterize galaxy populations, we find that the fraction of red and blue galaxies evolves with cosmic time, with red galaxies being $\sim$ 38% and $\sim$ 18% of the whole population at z = 0.1 and z = 0.5, respectively. At all redshifts, the more massive galaxies belong to the red sequence and these galaxies are typically older and more metal rich than their counterparts in the blue cloud. Our results confirm that with J-PAS data we will be able to analyze large samples of galaxies up to z $\sim$ 1, with galaxy stellar masses above of log(M$_*$/M$_{\odot}$) $\sim$ 8.9, 9.5, and 9.9 at z = 0.3, 0.5, and 0.7, respectively. The SFH of a complete sub-sample of galaxies selected at z $\sim$ 0.1 with log(M$_*$/M$_{\odot}$) > 8.3 constrain the cosmic evolution of the star formation rate density up to z $\sim$ 3 in good agreement with results from cosmological surveys.

astro-ph.GA↗