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We present a catalog of stellar parameters (effective temperature $T_{\rm eff}$, surface gravity $\log g$, age, and metallicity [Fe/H]) and elemental-abundance ratios ([C/Fe], [Mg/Fe], and [$\alpha$/Fe]) for some five million stars (4.5 million dwarfs and 0.5 million giants stars) in the Milky Way, based on stellar colors from the Javalambre Photometric Local Universe Survey (J-PLUS) DR3 and \textit{Gaia} EDR3. These estimates are obtained through the construction of a large spectroscopic training set with parameters and abundances adjusted to uniform scales, and trained with a Kernel Principal Component Analysis. Owing to the seven narrow/medium-band filters employed by J-PLUS, we obtain precisions in the abundance estimates that are as good or better than derived from medium-resolution spectroscopy for stars covering a wide range of the parameter space: 0.10-0.20 dex for [Fe/H] and [C/Fe], and 0.05 dex for [Mg/Fe] and [$\alpha$/Fe]. Moreover, systematic errors due to the influence of molecular carbon bands on previous photometric-metallicity estimates (which only included two narrow/medium-band blue filters) have now been removed, resulting in photometric-metallicity estimates down to [Fe/H] $\sim -4.0$, with typical uncertainties of 0.25 dex and 0.40 dex for dwarfs and giants, respectively. This large photometric sample should prove useful for the exploration of the assembly and chemical-evolution history of our Galaxy., Comment: 31 pages, 20 figures, 3 tables, accepeted by ApJ

This paper is focused on the segregation of FGK dwarf and giant stars through narrow-band photometric data using the Spanish Virtual Observatory (SVO) Filter Profile Service and associated photometric tools. We selected spectra from the MILES, STELIB, and ELODIE stellar libraries, and used SVO photometric tools to derive the synthetic photometry in 15 J-PAS narrow filters, which were especially selected to cover spectral features sensitive to gravity changes. Using machine-learning techniques as the Gaussian mixture model and the support vector machine, we defined several criteria based on J-PAS colours to discriminate between dwarf and giant stars. We selected five colour-colour diagrams that presented the most promising separation between both samples. Our results show an overall accuracy in the studied sample of $\sim$0.97 for FGK stars, although a dependence on the luminosity type and the stellar effective temperature was found. We also defined a colour-temperature relation for dwarf stars with effective temperatures between 4\,000 and 7\,000\,K, which allows one to estimate the stellar effective temperature from four J-PAS filters ($J0450$, $J0510$, $J0550$, and $J0620$). Additionally, we extended the study to M-type giant and dwarf stars, achieving a similar accuracy to that for FGK stars., Comment: 19 pages, 18 figures, accepted for publication in A&A

We study the impact of black hole nuclear activity on both the global and radial star formation rate (SFR) profiles in X-ray-selected active galactic nuclei (AGN) in the field of miniJPAS, the precursor of the much wider J-PAS project. Our sample includes 32 AGN with z < 0.3 detected via the XMM-Newton and Chandra surveys. For comparison, we assembled a control sample of 71 star-forming (SF) galaxies with similar magnitudes, sizes, and redshifts. To derive the global properties of both the AGN and the control SF sample, we used CIGALE to fit the spectral energy distributions derived from the 56 narrowband and 4 broadband filters from miniJPAS. We find that AGN tend to reside in more massive galaxies than their SF counterparts. After matching samples based on stellar mass and comparing their SFRs and specific SFRs (sSFRs), no significant differences appear. This suggests that the presence of AGN does not strongly influence overall star formation. However, when we used miniJPAS as an integral field unit (IFU) to dissect galaxies along their position angle, a different picture emerges. We find that AGN tend to be more centrally concentrated in mass with respect to SF galaxies. Moreover, we find a suppression of the sSFR up to 1Re and then an enhancement beyond 1Re , strongly contrasting with the decreasing radial profile of sSFRs in SF galaxies. This could point to an inside-out quenching of AGN host galaxies. These findings suggest that the reason we do not see differences on a global scale is because star formation is suppressed in the central regions and enhanced in the outer regions of AGN host galaxies. While limited in terms of sample size, this work highlights the potential of the upcoming J-PAS as a wide-field low-resolution IFU for thousands of nearby galaxies and AGN., Comment: 21 pages, 20 figures, Accepted for Publication in A&A

We present the second NuSTAR and XMM-Newton extragalactic survey of the JWST North Ecliptic Pole (NEP) Time-Domain Field (TDF). The first NuSTAR NEP-TDF survey (Zhao et al. 2021) had 681 ks total exposure time executed in NuSTAR cycle 5, in 2019 and 2020. This second survey, acquired from 2020 to 2022 in cycle 6, adds 880 ks of NuSTAR exposure time. The overall NuSTAR NEP-TDF survey is the most sensitive NuSTAR extragalactic survey to date, and a total of 60 sources were detected above the 95% reliability threshold. We constrain the hard X-ray number counts, logN-log S, down to 1.7 x 10$^{-14}$ erg cm$^{-2}$ s$^{-1}$ at 8-24 keV and detect an excess of hard X-ray sources at the faint end. About 47% of the NuSTAR-detected sources are heavily obscured (NH > 10$^{23}$ cm$^{-2}$), and 18+20% of the NuSTAR-detected sources are Compton-thick (N>10$^{24}$ cm$^{-2}$). These fractions are consistent with those measured in other NuSTAR surveys. Four sources presented >2$\sigma$ variability in the 3-year survey. In addition to NuSTAR, a total of 62 ks of XMM-Newton observations were taken during NuSTAR cycle 6. The XMM-Newton observations provide soft X-ray (0.5-10keV) coverage in the same field and enable more robust identification of the visible and infrared counterparts of the NuSTAR-detected sources. A total of 286 soft X-ray sources were detected, out of which 214 XMM-Newton sources have secure counterparts from multiwavelength catalogs., Comment: 37 pages, 27 figures, Accepted by ApJ

Extreme Emission Line Galaxies (EELGs) stand as remarkable objects due to their extremely metal poor environment and intense star formation. Considered as local analogues of high-redshift galaxies in the peak of their star-forming activity, they offer insights into conditions prevalent during the early Universe. Assessment of their stellar and gas properties is, therefore, of critical importance, which requires the assembly of a considerable sample, comprehending a broad redshift range. The Javalambre-Physics of the Accelerating Universe Astrophysical Survey (JPAS) plays a significant role in assembling such a sample, encompassing approximately 8000 deg2 and employing 54 narrow-band optical filters. The present work describes the development and subsequent application of the tools that will be employed in the forthcoming JPAS spectrophotometric data, allowing for the massive and automated characterization of EELGs that are expected to be identified. This fully automated pipeline (requiring only the object coordinates from users) constructs Spectral Energy Distributions (SEDs) by retrieving virtually all the available multi-wavelength photometric data archives, employs SED fitting tools and identifies optical emission lines. It was applied to the sample of extreme line emitters identified in the miniJPAS Survey, and its derived physical properties such as stellar mass and age, coupled with fundamental relations, mirror results obtained through spectral modeling of SDSS spectra. Thorough testing using galaxies with documented photometric measurements across different wavelengths confirmed the pipeline's accuracy, demonstrating its capability for automated analysis of sources with varying characteristics, spanning brightness, morphology, and redshifts. The modular nature of this pipeline facilitates any addition from the user., Comment: 15 pages, 9 Figures, accepted for publication in MNRAS

We study the local environmental properties of 418 supernovae (SNe) of all types using data from the Javalambre Photometric Local Universe Survey (J-PLUS), which includes 5 broad- and 7 narrow-band imaging filters, using two independent analyses: 1) the Normalized Cumulative Rank (NCR) method, utilizing all 12 single bands along with five continuum-subtracted narrow-band emission and absorption bands, and 2) simple stellar population (SSP) synthesis, where we build spectral energy distributions (SED) of the surrounding SN environment using the 12 filters. Improvements over previous works include: (i) the extension of the NCR technique to other filters using a set of homogeneous data; (ii) a correction for extinction to all bands based on the relation between the g-i color and the color excess; and (iii) a correction for the [NII] line contamination that falls within the H$\alpha$ filter. All NCR distributions in the broad-band filters, tracing the overall light distribution in each galaxy, are similar to each other, being type Ia, II and IIb SNe are preferably located in redder environments than the other SN types. The radial distribution of the SNe shows that type IIb SNe seem to have a preference for occurring in the inner regions of galaxies. All core-collapse SN (CC) types are strongly correlated to the [OII] emission, which traces SFR. The NCR distributions of the Ca II triplet show a clear division between II/IIb/Ia and Ib/Ic/IIn subtypes, which is interpreted as a difference in the environmental metallicity. Regarding the SSP synthesis, we found that including the 7 J-PLUS narrow filters in the fitting process has a more significant effect for the CC SN environmental parameters than for SNe Ia, shifting their values towards more extinct, younger, and more star-forming environments, due to the presence of strong emission-lines and stellar absorptions in those narrow-bands., Comment: 18 pages, 12 figures, 8 tables. A&A accepted

We present a list of quasar candidates including photometric redshift estimates from the miniJPAS Data Release constructed using SQUEzE. This work is based on machine-learning classification of photometric data of quasar candidates using SQUEzE. It has the advantage that its classification procedure can be explained to some extent, making it less of a `black box' when compared with other classifiers. Another key advantage is that using user-defined metrics means the user has more control over the classification. While SQUEzE was designed for spectroscopic data, here we adapt it for multi-band photometric data, i.e. we treat multiple narrow-band filters as very low-resolution spectra. We train our models using specialized mocks from Queiroz et al. (2022). We estimate our redshift precision using the normalized median absolute deviation, $\sigma_{\rm NMAD}$ applied to our test sample. Our test sample returns an $f_1$ score (effectively the purity and completeness) of 0.49 for quasars down to magnitude $r=24.3$ with $z\geq2.1$ and 0.24 for quasars with $z<2.1$. For high-z quasars, this goes up to 0.9 for $r<21.0$. We present two catalogues of quasar candidates including redshift estimates: 301 from point-like sources and 1049 when also including extended sources. We discuss the impact of including extended sources in our predictions (they are not included in the mocks), as well as the impact of changing the noise model of the mocks. We also give an explanation of SQUEzE reasoning. Our estimates for the redshift precision using the test sample indicate a $\sigma_{NMAD}=0.92\%$ for the entire sample, reduced to 0.81\% for $r<22.5$ and 0.74\% for $r<21.3$. Spectroscopic follow-up of the candidates is required in order to confirm the validity of our findings., Comment: Accepted in A&A 24 pages, 24 figures, 7 tables

We present the Lyman-$a$ (Lya) Luminosity Function (LF) at $2.0543.5. This work serves as a proof-of-concept for the results that can be obtained with the upcoming data releases of the J-PAS survey., Comment: 25 pages, 15 figures, Accepted for publication in A&A

Astrophysical surveys rely heavily on the classification of sources as stars, galaxies or quasars from multi-band photometry. Surveys in narrow-band filters allow for greater discriminatory power, but the variety of different types and redshifts of the objects present a challenge to standard template-based methods. In this work, which is part of larger effort that aims at building a catalogue of quasars from the miniJPAS survey, we present a Machine Learning-based method that employs Convolutional Neural Networks (CNNs) to classify point-like sources including the information in the measurement errors. We validate our methods using data from the miniJPAS survey, a proof-of-concept project of the J-PAS collaboration covering $\sim$ 1 deg$^2$ of the northern sky using the 56 narrow-band filters of the J-PAS survey. Due to the scarcity of real data, we trained our algorithms using mocks that were purpose-built to reproduce the distributions of different types of objects that we expect to find in the miniJPAS survey, as well as the properties of the real observations in terms of signal and noise. We compare the performance of the CNNs with other well-established Machine Learning classification methods based on decision trees, finding that the CNNs improve the classification when the measurement errors are provided as inputs. The predicted distribution of objects in miniJPAS is consistent with the putative luminosity functions of stars, quasars and unresolved galaxies. Our results are a proof-of-concept for the idea that the J-PAS survey will be able to detect unprecedented numbers of quasars with high confidence., Comment: 16 pages, 15 figures, published by MNRAS

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., Comment: 16 pages, 16 figures, 3 tables, accepted by MNRAS

The Ly$\alpha$ emission is an important tracer of neutral gas in a circum-galactic medium (CGM) around high-z QSOs. The origin of Lya emission around QSOs is still under debate which has significant implications for galaxy formation and evolution. In this paper, we study Ly$\alpha$ nebulae around two high redshift QSOs, SDSS J141935.58+525710.7 at $z=3.218$ (hereafter QSO1) and SDSS J141813.40+525240.4 at $z=3.287$ (hereafter QSO2), from the miniJPAS survey within the AEGIS field. Using the contiguous narrow-band (NB) images from the miniJPAS survey and SDSS spectra, we analyzed their morphology, nature, and origin. We report the serendipitous detection of double-core Ly\al\ morphology around two QSOs which is rarely seen among other QSOs. The separations of the two Ly\al~cores are 11.07 $\pm$ 2.26 kpcs (1.47 $\pm$ 0.3$^{\prime\prime}$) and 9.73 $\pm$ 1.55 kpcs (1.31 $\pm$ 0.21$^{\prime\prime}$) with Ly$\alpha$~line luminosities of $\sim$ 3.35 $\times 10^{44}$ erg s $^{-1} $ and $\sim$ 6.99 $\times$ 10$^{44}$ erg s $^{-1}$ for QSO1 and QSO2, respectively. The miniJPAS NB images show evidence of extended Ly$\alpha$ and CIV morphology for both QSOs and extended HeII morphology for QSO1. These two QSOs may be potential candidates for the new enormous Lyman alpha nebula (ELAN) found from the miniJPAS survey due to their extended morphology in the shallow depth and relatively high Ly$\alpha$ luminosities. We suggest that galactic outflows are the major powering mechanism for the double-core Ly$\alpha$ morphology. Considering the relatively shallow exposures of miniJPAS, the objects found here could be the tip of the iceberg of a promising number of such objects that will be uncovered in the upcoming full J-PAS survey and deep IFU observations with 8-10m telescopes will be essential for constraining the underlying physical mechanism that is responsible for the double-cored morphology., Comment: Five figures and two tables (Accepted in Astronomy and Astrophysics)

Globular clusters (GCs) are proxies of the formation assemblies of their host galaxies. However, few studies exist targeting GC systems of spiral galaxies up to several effective radii. Through 12-band Javalambre Photometric Local Universe Survey (J-PLUS) imaging, we study the point sources around the M81/M82/NGC3077 triplet in search of new GC candidates. We develop a tailored classification scheme to search for GC candidates based on their similarity to known GCs via a principal components analysis (PCA) projection. Our method accounts for missing data and photometric errors. We report 642 new GC candidates in a region of 3.5 deg$^2$ around the triplet, ranked according to their Gaia astrometric proper motions when available. We find tantalising evidence for an overdensity of GC candidate sources forming a bridge connecting M81 and M82. Finally, the spatial distribution of the GC candidates $(g-i)$ colours is consistent with halo/intra-cluster GCs, i.e. it gets bluer as they get further from the closest galaxy in the field. We further employ a regression-tree based model to estimate the metallicity distribution of the GC candidates based on their J-PLUS bands. The metallicity distribution of the sample candidates is broad and displays a bump towards the metal-rich end. Our list increases the population of GC candidates around the triplet by 3-fold, stresses the usefulness of multi-band surveys in finding these objects, and provides a testbed for further studies analysing their spatial distribution around nearby (spirals) galaxies., Comment: 20 pages, 18 figures, MNRAS accepted

In this series of papers, we employ several machine learning (ML) methods to classify the point-like sources from the miniJPAS catalogue, and identify quasar candidates. Since no representative sample of spectroscopically confirmed sources exists at present to train these ML algorithms, we rely on mock catalogues. In this first paper we develop a pipeline to compute synthetic photometry of quasars, galaxies and stars using spectra of objects targeted as quasars in the Sloan Digital Sky Survey. To match the same depths and signal-to-noise ratio distributions in all bands expected for miniJPAS point sources in the range $17.5\leq r<24$, we augment our sample of available spectra by shifting the original $r$-band magnitude distributions towards the faint end, ensure that the relative incidence rates of the different objects are distributed according to their respective luminosity functions, and perform a thorough modeling of the noise distribution in each filter, by sampling the flux variance either from Gaussian realizations with given widths, or from combinations of Gaussian functions. Finally, we also add in the mocks the patterns of non-detections which are present in all real observations. Although the mock catalogues presented in this work are a first step towards simulated data sets that match the properties of the miniJPAS observations, these mocks can be adapted to serve the purposes of other photometric surveys., Comment: 20 pages, 18 figures, submitted to MNRAS

Context. The Javalambre Photometric Local Universe Survey (J-PLUS) has obtained precise photometry in twelve specially designed filters for large numbers of Galactic stars. Deriving their precise stellar atmospheric parameters and individual elemental abundances is crucial for studies of Galactic structure, and the assembly history and chemical evolution of our Galaxy. Aims. Our goal is to estimate not only stellar parameters (effective temperature, Teff, surface gravity, log g, and metallicity, [Fe/H]), but also [{\alpha}/Fe] and four elemental abundances ([C/Fe], [N/Fe], [Mg/Fe], and [Ca/Fe]) using data from J-PLUS DR1. Methods. By combining recalibrated photometric data from J-PLUS DR1, Gaia DR2, and spectroscopic labels from LAMOST, we design and train a set of cost-sensitive neural networks, the CSNet, to learn the non-linear mapping from stellar colors to their labels. Results. We have achieved precisions of {\delta}Teff {\sim}55K, {\delta}logg{\sim}0.15dex, and {\delta}[Fe/H]{\sim}0.07dex, respectively, over a wide range of temperature, surface gravity, and metallicity. The uncertainties of the abundance estimates for [{\alpha}/Fe] and the four individual elements are in the range 0.04-0.08 dex. We compare our parameter and abundance estimates with those from other spectroscopic catalogs such as APOGEE and GALAH, and find an overall good agreement. Conclusions. Our results demonstrate the potential of well-designed, high-quality photometric data for determinations of stellar parameters as well as individual elemental abundances. Applying the method to J-PLUS DR1, we have obtained the aforementioned parameters for about two million stars, providing an outstanding data set for chemo-dynamic analyses of the Milky Way. The catalog of the estimated parameters is publicly accessible., Comment: 30 pages, 26 figures, 3 tables, accepted by A&A

Extragalactic globular clusters (GCs) are key objects for studying the history of galaxies. The arrival of wide-field surveys such as the Javalambre Photometric Local Universe Survey (J-PLUS) offers new possibilities for the study of these systems. We perform the first study of GCs in J-PLUS to recover information about the history of NGC 1023 taking advantage of wide-field images and 12 filters. We develop the semiautomatic pipeline GCFinder that detects GC candidates in J-PLUS images and can also be adapted to similar surveys. We study the stellar population properties of a sub-sample of GC candidates using spectral energy distribution (SED) fitting. We find 523 GC candidates in NGC 1023, of which $\sim$300 are new. We identify subpopulations of GC candidates, where age and metallicity distributions have multiple peaks. By comparing our results with simulations, we report a possible broad age-metallicity relation, evidence that NGC 1023 experienced accretion events in the past. The dominating age peak is at $10^{10}$ yr. We report a correlation between masses and ages that suggests that massive GC candidates are more likely to survive the turbulent history of the host galaxy. Modeling the light of NGC 1023, we find two spiral-like arms and detect a displacement of the galaxy's photometric center with respect to the outer isophotes and center of GC distribution ($\sim$700 pc and $\sim$1600 pc, respectively), which could be the result of ongoing interaction between NGC 1023 and NGC 1023A. By studying the GC system of NGC 1023 with J-PLUS we showcase the power of multi-band surveys for this kind of study and find evidence of a complex accretion history of the host galaxy., Comment: Published in A&A, 2022

We explore the stellar content of the Javalambre Photometric Local Universe Survey (J-PLUS) Data Release 2 and show its potential to identify low-metallicity stars using the Stellar Parameters Estimation based on Ensemble Methods (SPEEM) pipeline. SPEEM is a tool to provide determinations of atmospheric parameters for stars and separate stellar sources from quasars, using the unique J-PLUS photometric system. The adoption of adequate selection criteria allows the identification of metal-poor star candidates suitable for spectroscopic follow-up. SPEEM consists of a series of machine learning models which uses a training sample observed by both J-PLUS and the SEGUE spectroscopic survey. The training sample has temperatures Teff between 4\,800 K and 9\,000 K; $\log g$ between 1.0 and 4.5, and $-3.1<[Fe/H]<+0.5$. The performance of the pipeline has been tested with a sample of stars observed by the LAMOST survey within the same parameter range. The average differences between the parameters of a sample of stars observed with SEGUE and J-PLUS, which were obtained with the SEGUE Stellar Parameter Pipeline and SPEEM, respectively, are $\Delta Teff\sim 41$ K, $\Delta \log g\sim 0.11$ dex, and $\Delta [Fe/H]\sim 0.09$ dex. A sample of 177 stars have been identified as new candidates with $[Fe/H]<-2.5$ and 11 of them have been observed with the ISIS spectrograph at the William Herschel Telescope. The spectroscopic analysis confirms that $64\%$ of stars have $[Fe/H]<-2.5$, including one new star with $[Fe/H]<-3.0$. SPEEM in combination with the J-PLUS filter system has shown the potential to estimate the stellar atmospheric parameters (Teff, $\log g$, and [Fe/H]). The spectroscopic validation of the candidates shows that SPEEM yields a success rate of $64\%$ on the identification of very metal-poor star candidates with $[Fe/H]<-2.5$., Comment: Accepted for publication in the Astronomy & Astrophysics Journal

Context: The Javalambre Photometric Local Universe Survey (J-PLUS) is an observational campaign that aims to obtain photometry in 12 ultraviolet-visible filters (0.3-1 {\mu}m) of approximately 8 500 deg{^2} of the sky observable from Javalambre (Teruel, Spain). Due to its characteristics and strategy of observation, this survey will let us analyze a great number of Solar System small bodies, with improved spectrophotometric resolution with respect to previous large-area photometric surveys in optical wavelengths. Aims: The main goal of this work is to present here the first catalog of magnitudes and colors of minor bodies of the Solar System compiled using the first data release (DR1) of the J-PLUS observational campaign: the Moving Objects Observed from Javalambre (MOOJa) catalog. Methods: Using the compiled photometric data we obtained very-low-resolution reflectance (photospectra) spectra of the asteroids. We first used a {\sigma}-clipping algorithm in order to remove outliers and clean the data. We then devised a method to select the optimal solar colors in the J-PLUS photometric system. These solar colors were computed using two different approaches: on one hand, we used different spectra of the Sun, convolved with the filter transmissions of the J-PLUS system, and on the other, we selected a group of solar-type stars in the J-PLUS DR1, according to their computed stellar parameters. Finally, we used the solar colors to obtain the reflectance spectra of the asteroids. Results: We present photometric data in the J-PLUS filters for a total of 3 122 minor bodies (3 666 before outlier removal), and we discuss the main issues of the data, as well as some guidelines to solve them

We consider a cosmological model where dark matter and dark energy feature a coupling that only affects their momentum transfer in the corresponding Euler equations. We perform a fit to cosmological observables and confirm previous findings within these scenarios that favour the presence of a coupling at more than $3\sigma$. This improvement is driven by the Sunyaev-Zeldovich data. We subsequently perform a forecast for future J-PAS data and find that clustering measurements will permit to clearly discern the presence of an interaction within a few percent level with the uncoupled case at more than $10\sigma$ when the complete survey, covering $8500$ sq. deg., is considered. We found that the inclusion of weak lensing measurements will not help to further constrain the coupling parameter. For completeness, we compare to forecasts for DESI and Euclid, which provide similar discriminating power., Comment: 34 pages, 17 figures, added some clarifications and discussions, matches published version

We present the photometric determination of the bright-end (L_Lya>10^43.5 erg/s) of the Lya luminosity function (LF) within four redshifts windows in the interval 2.210^43.3 erg/s) Lya-emitting candidates. We test our selection with two spectroscopic follow-up programs at the GTC telescope, confirming ~89% of the targets as line-emitting sources, with ~64% being genuine z~2.2 QSOs. We extend the 2.22 AGN/QSOs (likely dominant in our samples) are described by a structurally different LF than z>2 star-forming LAEs, namely with L^*_QSOs ~ 100 L^*_LAEs and Phi^*_QSOs ~ 10^-3 Phi^*_LAEs. Finally, our method identifies very efficiently as high-z line-emitters sources without previous spectroscopic confirmation, currently classified as stars (~2000 objects in each redshift bin, on average). Assuming a large predominance of Lya-emitting AGN/QSOs in our samples, this supports the scenario by which these are the most abundant class of z>2 Lya emitters at L_Lya>10^43.3 erg/s., Comment: 27 pages (6 in appendix), 21 figures (5 in appendix), submitted to A&A

Cataclysmic Variables (CVs) are interacting binaries consisting of at least three components that control their colour and magnitude. Using Gaia we here investigate the influence of the physical properties of these binaries on their position in the Hertzsprung-Russell diagram (HR-diagram). The CVs are on average located between the main sequence and the white dwarf regime, the maximum density being at $G_{BP}-G_{RP} \sim 0.56$ and $G_{abs} \sim 10.15$. We find a trend of the orbital period with colour and absolute brightness: with decreasing period, the CVs become bluer and fainter. We also identify the location of the various CV sub-types in the HR-diagram and discuss the possible location of detached CVs, going through the orbital period gap., Comment: 5 pages, 12 figures

We present a synthetic galaxy lightcone specially designed for narrow-band optical photometric surveys. To reduce time-discreteness effects, unlike previous works, we directly include the lightcone construction in the \texttt{L-Galaxies} semi-analytic model applied to the subhalo merger trees of the {\tt Millennium} simulation. Additionally, we add a model for the nebular emission in star-forming regions, which is crucial for correctly predicting the narrow/medium-band photometry of galaxies. Explicitly, we consider, individually for each galaxy, the contribution of 9 different lines: $\rm Ly{\alpha}$ (1216\AA), \Hb (4861\AA), \Ha (6563\AA), {\oii} (3727\AA, 3729\AA), {\oiii} (4959\AA, 5007\AA), $\rm [\ion{Ne}{III}]$ (3870\AA), {\oi} (6300\AA), $\rm [\ion{N}{II}]$ (6548\AA, 6583\AA), and $\rm [\ion{S}{II}]$ (6717\AA, 6731\AA). We validate our lightcone by comparing galaxy number counts, angular clustering, and \Ha, \Hb, {\oii} and {\oiiiFd} luminosity functions to a compilation of observations. As an application of our mock lightcones, we generate catalogues tailored for J-PLUS, a large optical galaxy survey featuring 5 broad and 7 medium band filters. We study the ability of the survey to correctly identify, with a simple \textit{three filter method}, a population of emission-line galaxies at various redshifts. We show that the $4000\AA$ break in the spectral energy distribution of galaxies can be misidentified as line emission. However, all significant excess (larger than 0.4 magnitudes) can be correctly and unambiguously attributed to emission line galaxies. Our catalogues are publicly released to facilitate their use in interpreting narrow-band surveys and for quantifying the impact of line emission in broad band photometry., Comment: Published in A&A; Mock catalogue available at https://www.j-plus.es/ancillarydata/mock\_galaxy\_lightcone

We present ELDAR, a new method that exploits the potential of medium- and narrow-band filter surveys to securely identify active galactic nuclei (AGN) and determine their redshifts. Our methodology improves on traditional approaches by looking for AGN emission lines expected to be identified against the continuum, thanks to the width of the filters. To assess its performance, we apply ELDAR to the data of the ALHAMBRA survey, which covered an effective area of $2.38\,{\rm deg}^2$ with 20 contiguous medium-band optical filters down to F814W$\simeq 24.5$. Using two different configurations of ELDAR in which we require the detection of at least 2 and 3 emission lines, respectively, we extract two catalogues of type-I AGN. The first is composed of 585 sources ($79\,\%$ of them spectroscopically-unknown) down to F814W$=22.5$ at $z_{\rm phot}>1$, which corresponds to a surface density of $209\,{\rm deg}^{-2}$. In the second, the 494 selected sources ($83\,\%$ of them spectroscopically-unknown) reach F814W$=23$ at $z_{\rm phot}>1.5$, for a corresponding number density of $176\,{\rm deg}^{-2}$. Then, using samples of spectroscopically-known AGN in the ALHAMBRA fields, for the two catalogues we estimate a completeness of $73\,\%$ and $67\,\%$, and a redshift precision of $1.01\,\%$ and $0.86\,\%$ (with outliers fractions of $8.1\,\%$ and $5.8\,\%$). At $z>2$, where our selection performs best, we reach $85\,\%$ and $77\,\%$ completeness and we find no contamination from galaxies., Comment: 23 pages, 18 figures, submitted to MNRAS

The impending Javalambre Physics of the accelerating universe Astrophysical Survey (J-PAS) will be the first wide-field survey of $\gtrsim$ 8500 deg$^2$ to reach the `stage IV' category. Because of the redshift resolution afforded by 54 narrow-band filters, J-PAS is particularly suitable for cluster detection in the range z$<$1. The photometric redshift dispersion is estimated to be only $\sim 0.003$ with few outliers $\lesssim$ 4\% for galaxies brighter than $i\sim23$ AB, because of the sensitivity of narrow band imaging to absorption and emission lines. Here we evaluate the cluster selection function for J-PAS using N-body+semi-analytical realistic mock catalogues. We optimally detect clusters from this simulation with the Bayesian Cluster Finder, and we assess the completeness and purity of cluster detection against the mock data. The minimum halo mass threshold we find for detections of galaxy clusters and groups with both $>$80\% completeness and purity is $M_h \sim 5 \times 10^{13}M_{\odot}$ up to $z\sim 0.7$. We also model the optical observable, $M^*_{\rm CL}$-halo mass relation, finding a non-evolution with redshift and main scatter of $\sigma_{M^*_{\rm CL} | M_{\rm h}}\sim 0.14 \,dex$ down to a factor two lower in mass than other planned broad-band stage IV surveys, at least. For the $M_{\rm h} \sim 1 \times 10^{14}M_{\odot}$ Planck mass limit, J-PAS will arrive up to $z\sim 0.85$ with a $\sigma_{M^*_{\rm CL} | M_{\rm h}}\sim 0.12 \, dex$. Therefore J-PAS will provide the largest sample of clusters and groups up to $z\sim 0.8$ with a mass calibration accuracy comparable to X-ray data., Comment: 16 pages, 15 figures, accepted for publication in MNRAS

We present a catalogue of 348 galaxy clusters and groups with $0.2

Some recent observations seem to disagree with hierarchical theories of galaxy formation about the role played by major mergers in the late buildup of massive E-S0's. We re-address this question by analysing the morphology, structural distortion level, and star formation enhancement of a sample of massive galaxies (M_* > 5 * 10^10 Msun) lying on the Red Sequence and its surroundings at 0.3 < z < 1.5. We have used an initial sample of ~1800 sources with K_s < 20.5 mag over an area ~155 arcmin^2 on the Groth Strip, combining data from the Rainbow Extragalactic Database and the GOYA Survey. Red galaxy classes that can be directly associated to intermediate stages of major mergers and to their final products have been defined. We report observational evidence of the existence of a dominant evolutionary path among massive red galaxies at 0.6 10^11 Msun at z=0 through gas-rich major mergers has frozen since z~0.6. All these facts support that major mergers have played the dominant role in the definitive buildup of present-day E-S0's with M_*> 10^11 Msun at 0.6

We present a new cataloge of EROs from the Groth strip and study the relation between their morphology and mass. We find 102 EROs (F814W-K=>4, K<=21.0), over a survey area of 155 arcmin^2. The photometric data include U,B,F606W,F814W,J,K bands. Morphologies are based on a by eye classification and we distinguish between 3 basic classes: compact objects, targets with a disc and/or a bulge component and irregular or merger candidates. The majority of our targets has either a very compact morphology (33+-6%), or show more or less distinct disc components (41+-6%). 14+-4% are merger or irregulars and 7 objects could not be classified. We also study the dependence of structural parameters on morphological appearance. EROs that are either compact or show a distinct bulge component have smaller median effective radii (1.22+-0.14 kpc and 3.31+-0.53 kpc) than disc dominated (5.50+-0.51 kpc) or possible irregular galaxies or merger candidates (4.92+-0.14 kpc). The Sersic index changes from 2.30+-0.34 and 3.24+-0.55, to 1.03+-0.24 and 1.54+-0.40 respectively. Most the EROs in our sample have redshifts between z=1 and z=2; however, compact EROs in our sample are found at redshifts as low as z=0.4 and as high as z=2.8; the latter qualify as well as DRGs. Disc-like EROs are also found up to z=2.8; however those with a bulge-disc structure are only seen at z<1.5. For each of these EROs we determined the stellar mass and mean population age by fitting synthetic Bruzual (2007) spectra to the SED. Mass estimates were obtained by assuming an exponentially declining star formation rate. Total stellar masses are in the range 9.111.0 dominantly show compact morphologies, but also include a significant number of sources with a disc morphology., Comment: 21 pages, 17 figures, accepted for publication in MNRAS