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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 ∼8000  |$\rm deg^2$| 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 multiwavelength 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 modelling 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. [ABSTRACT FROM AUTHOR]

Astrophysical surveys rely heavily on the classification of sources as stars, galaxies, or quasars from multiband 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 a 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 Javalambre Physics of the Accelerating Universe Astrophysical Survey (J-PAS) collaboration covering ∼1 deg2 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. [ABSTRACT FROM AUTHOR]

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, J 0378 − r, J 0390 − r, uJPAS − r , show the strongest metallicity dependence, around 0.25 mag dex−1. The sensitivities decrease to about 0.1 mag dex−1 for the J0400 − r, J0410 − r , and J 0420 − r colours. The locus fitting residuals show peaks at the J 0390, J 0430, J 0510, and J 0520 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 J 0520 and J 0510 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. [ABSTRACT FROM AUTHOR]

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 M 81/M 82/NGC 3077 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 component analysis projection. Our method accounts for missing data and photometric errors. We report 642 new GC candidates in a region of 3.5 deg2 around the triplet, ranked according to their Gaia astrometric proper motions when available. We find tantalizing evidence for an overdensity of GC candidate sources forming a bridge connecting M 81 and M 82. 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 threefold, stresses the usefulness of multiband surveys in finding these objects, and provides a testbed for further studies analysing their spatial distribution around nearby (spirals) galaxies. [ABSTRACT FROM AUTHOR]

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 (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 ∼ 0.56 and G abs ∼ 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 subtypes in the HR diagram and discuss the possible location of detached CVs, going through the orbital period gap. [ABSTRACT FROM AUTHOR]

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 (Advance Large Homogeneous Area Medium Band Redshift Astronomical) survey, which covered an effective area of 2.38 deg2 with 20 contiguous medium-band optical filters down to F814W ≃ 24.5. Using two different configurations of ELDAR in which we require the detection of at least two and three emission lines, respectively, we extract two catalogues of type-I AGN. The first is composed of 585 sources (79 per cent of them spectroscopically unknown) down to F814W = 22.5 at zphot > 1, which corresponds to a surface density of 209 deg-2. In the second, the 494 selected sources (83 per cent of them spectroscopically unknown) reach F814W= 23 at zphot > 1.5, for a corresponding number density of 176 deg-2. Then, using samples of spectroscopically known AGN in the ALHAMBRA fields, for the two catalogues we estimate a completeness of 73 per cent and 67 per cent, and a redshift precision of 1.01 per cent and 0.86 per cent (with outliers fractions of 8.1 per cent and 5.8 per cent). At z > 2, where our selection performs best, we reach 85 per cent and 77 per cent completeness and we find no contamination from galaxies. [ABSTRACT FROM AUTHOR]

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-S0s. We re-address this question by analysing the morphology, structural distortion level and star formation enhancement of a sample of massive galaxies (M* > 5 × 1010 M⊙) lying on the Red Sequence and its surroundings at 0.3 < z < 1.5. We have used an initial sample of ∼1800 sources with Ks < 20.5 mag over an area ∼155 arcmin2 on the Groth Strip, combining data from the Rainbow Extragalactic Database and the Galaxy Origins and Young Assembly survey. Red galaxy classes that can be directly associated with intermediate stages of major mergers and with 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 < z < 1.5, consisting in the conversion of irregular discs into irregular spheroids, and of these ones into regular spheroids. This result implies: (1) the massive red regular galaxies at low redshifts derive from the irregular ones populating the Red Sequence and its neighbourhood at earlier epochs up to z ∼ 1.5; (2) the progenitors of the bulk of present-day massive red regular galaxies have been discs that seem to have migrated to the Red Sequence mostly through major mergers at 0.6 < z < 1.2 (these mergers thus starting at z ∼ 1.5) and (3) the formation of E-S0s that end up with M* > 1011 M⊙ at z = 0 through gas-rich major mergers has frozen since z ∼ 0.6. All these facts support that major mergers have played a dominant role in the definitive buildup of present-day E-S0s with M* > 1011 M⊙ at 0.6 < z < 1.2, in good agreement with hierarchical scenarios of galaxy formation. [ABSTRACT FROM PUBLISHER]