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1. The ROSAT Raster survey in the north ecliptic pole field: X-ray catalogue and optical identifications

   https://doi.org/10.1051/0004-6361/202039476  

   Hasinger, G. ; Freyberg, M. ; Hu, E. M. ; Waters, C. Z. ; Capak, P. ; Moneti, A. ; McCracken, H. J. ( January 2021 , Astronomy & Astrophysics)

   null (Ed.)

   The north ecliptic pole (NEP) is an important region for extragalactic surveys. Deep and wide contiguous surveys are being performed by several space observatories, most currently with the eROSITA telescope. Several more are planned for the near future. We analyse all the ROSAT pointed and survey observations in a region of 40 deg 2 around the NEP, restricting the ROSAT field of view to the inner 30′ radius. We obtain an X-ray catalogue of 805 sources with 0.5−2 keV fluxes > 2.9 × 10 −15 erg cm −2 s −1 , about a factor of three deeper than the ROSAT All-Sky Survey in this field. The sensitivity and angular resolution of our data are comparable to the eROSITA All-Sky Survey expectations. The 50% position error radius of the sample of X-ray sources is ∼10″. We use HEROES optical and near-infrared imaging photometry from the Subaru and Canada/France/Hawaii telescopes together with GALEX, SDSS, Pan-STARRS, and WISE catalogues, as well as images from a new deep and wide Spitzer survey in the field to statistically identify the X-ray sources and to calculate photometric redshifts for the candidate counterparts. In particular, we utilize mid-infrared (mid-IR) colours to identify active galactic nucleus (AGN) X-ray counterparts. Despite the relatively large error circles and often faint counterparts, together with confusion issues and systematic errors, we obtain a rather reliable catalogue of 766 high-quality optical counterparts, corresponding redshifts and optical classifications. The quality of the dataset is sufficient to look at ensemble properties of X-ray source classes. In particular we find a new population of luminous absorbed X-ray AGN at large redshifts, identified through their mid-IR colours. This populous group of AGN was not recognized in previous X-ray surveys, but could be identified in our work due to the unique combination of survey solid angle, X-ray sensitivity, and quality of the multi-wavelength photometry. We also use the WISE and Spitzer photometry to identify a sample of 185 AGN selected purely through their mid-IR colours, most of which are not detected by ROSAT. Their redshifts and upper limits to X-ray luminosity and X-ray–to–optical flux ratios are even higher than for the new class of X-ray selected luminous type 2 AGN (AGN2); they are probably a natural extension of this sample. This unique dataset is important as a reference sample for future deep surveys in the NEP region, in particular for eROSITA and also for Euclid and SPHEREX. We predict that most of the absorbed distant AGN should be readily picked up by eROSITA, but they require sensitive mid-IR imaging to be recognized as optical counterparts. 

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2. Carbon-enhanced metal-poor star candidates from BP/RP spectra in Gaia DR3

   https://doi.org/10.1093/mnras/stad1675  

   Lucey, Madeline ; Al Kharusi, Nariman ; Hawkins, Keith ; Ting, Yuan-Sen ; Ramachandra, Nesar ; Price-Whelan, Adrian M. ; Beers, Timothy C. ; Lee, Young Sun ; Yoon, Jinmi ( June 2023 , Monthly Notices of the Royal Astronomical Society)

   Carbon-enhanced metal-poor (CEMP) stars comprise almost a third of stars with [Fe/H] < −2, although their origins are still poorly understood. It is highly likely that one sub-class (CEMP-s stars) is tied to mass-transfer events in binary stars, while another sub-class (CEMP-no stars) are enriched by the nucleosynthetic yields of the first generations of stars. Previous studies of CEMP stars have primarily concentrated on the Galactic halo, but more recently they have also been detected in the thick disc and bulge components of the Milky Way. Gaia DR3 has provided an unprecedented sample of over 200 million low-resolution (R ≈ 50) spectra from the BP and RP photometers. Training on the CEMP catalogue from the SDSS/SEGUE database, we use XGBoost to identify the largest all-sky sample of CEMP candidate stars to date. In total, we find 58 872 CEMP star candidates, with an estimated contamination rate of 12 per cent. When comparing to literature high-resolution catalogues, we positively identify 60–68 per cent of the CEMP stars in the data, validating our results and indicating a high completeness rate. Our final catalogue of CEMP candidates spans from the inner to outer Milky Way, with distances as close as r ∼ 0.8 kpc from the Galactic centre, and as far as r > 30 kpc. Future higher resolution spectroscopic follow-up of these candidates will provide validations of their classification and enable investigations of the frequency of CEMP-s and CEMP-no stars throughout the Galaxy, to further constrain the nature of their progenitors.

    

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3. The probabilistic random forest applied to the QUBRICS survey: improving the selection of high-redshift quasars with synthetic data

   https://doi.org/10.1093/mnras/stac2733  

   Guarneri, Francesco ; Calderone, Giorgio ; Cristiani, Stefano ; Porru, Matteo ; Fontanot, Fabio ; Boutsia, Konstantina ; Cupani, Guido ; Grazian, Andrea ; D’Odorico, Valentina ; Murphy, Michael T. ; et al ( October 2022 , Monthly Notices of the Royal Astronomical Society)

   Several recent works have focused on the search for bright, high-z quasars (QSOs) in the South. Among them, the QUasars as BRIght beacons for Cosmology in the Southern hemisphere (QUBRICS) survey has now delivered hundreds of new spectroscopically confirmed QSOs selected by means of machine learning algorithms. Building upon the results obtained by introducing the probabilistic random forest (PRF) for the QUBRICS selection, we explore in this work the feasibility of training the algorithm on synthetic data to improve the completeness in the higher redshift bins. We also compare the performances of the algorithm if colours are used as primary features instead of magnitudes. We generate synthetic data based on a composite QSO spectral energy distribution. We first train the PRF to identify QSOs among stars and galaxies, then separate high-z quasar from low-z contaminants. We apply the algorithm on an updated data set, based on SkyMapper DR3, combined with Gaia eDR3, 2MASS, and WISE magnitudes. We find that employing colours as features slightly improves the results with respect to the algorithm trained on magnitude data. Adding synthetic data to the training set provides significantly better results with respect to the PRF trained only on spectroscopically confirmed QSOs. We estimate, on a testing data set, a completeness of $\sim 86{{\ \rm per\ cent}}$ and a contamination of $\sim 36{{\ \rm per\ cent}}$. Finally, 206 PRF-selected candidates were observed: 149/206 turned out to be genuine QSOs with z > 2.5, 41 with z < 2.5, 3 galaxies and 13 stars. The result confirms the ability of the PRF to select high-z quasars in large data sets.

    

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4. Photometric redshifts for X-ray-selected active galactic nuclei in the eROSITA era

   https://doi.org/10.1093/mnras/stz2159  

   Brescia, M ; Salvato, M ; Cavuoti, S ; Ananna, T T ; Riccio, G ; LaMassa, S M ; Urry, C M ; Longo, G ( October 2019 , Monthly Notices of the Royal Astronomical Society)

   ABSTRACT With the launch of eROSITA (extended Roentgen Survey with an Imaging Telescope Array), successfully occurred on 2019 July 13, we are facing the challenge of computing reliable photometric redshifts for 3 million of active galactic nuclei (AGNs) over the entire sky, having available only patchy and inhomogeneous ancillary data. While we have a good understanding of the photo-z quality obtainable for AGN using spectral energy distribution (SED)-fitting technique, we tested the capability of machine learning (ML), usually reliable in computing photo-z for QSO in wide and shallow areas with rich spectroscopic samples. Using MLPQNA as example of ML, we computed photo-z for the X-ray-selected sources in Stripe 82X, using the publicly available photometric and spectroscopic catalogues. Stripe 82X is at least as deep as eROSITA will be and wide enough to include also rare and bright AGNs. In addition, the availability of ancillary data mimics what can be available in the whole sky. We found that when optical, and near- and mid-infrared data are available, ML and SED fitting perform comparably well in terms of overall accuracy, realistic redshift probability density functions, and fraction of outliers, although they are not the same for the two methods. The results could further improve if the photometry available is accurate and including morphological information. Assuming that we can gather sufficient spectroscopy to build a representative training sample, with the current photometry coverage we can obtain reliable photo-z for a large fraction of sources in the Southern hemisphere well before the spectroscopic follow-up, thus timely enabling the eROSITA science return. The photo-z catalogue is released here. 

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5. Populations of highly variable X-ray sources in the XMM–Newton slew survey

   https://doi.org/10.1093/mnras/stac714  

   Li, Dongyue ; Starling, R. L. C. ; Saxton, R. D. ; Pan, Hai-Wu ; Yuan, Weimin ( March 2022 , Monthly Notices of the Royal Astronomical Society)

   We present the identifications of a flux-limited sample of highly variable X-ray sources on long time-scales from the second catalogue of the XMM–Newton SLew survey (XMMSL2). The carefully constructed sample, comprising 265 sources (2.5 per cent) selected from the XMMSL2 clean catalogue, displayed X-ray variability of a factor of more than 10 in 0.2–2 keV compared to the ROSAT All Sky Survey. Of the sample sources, 94.3 per cent are identified. The identification procedure follows a series of cross-matches with astronomical data bases and multiwavelength catalogues to refine the source position and identify counterparts to the X-ray sources. Assignment of source type utilizes a combination of indicators including counterparts offset, parallax measurement, spectral colours, X-ray luminosity, and light-curve behaviour. We identified 40 per cent of the variables with stars, 10 per cent with accreting binaries, and at least 30.4 per cent with active galactic nuclei. The rest of the variables are identified as galaxies. It is found that the mean effective temperatures of the highly variable stars are lower than those of less variable stars. Our sample of highly variable AGN tend to have lower black hole masses, redshifts, and marginally lower soft X-ray luminosities compared to the less variable ones, while no difference was found in the Eddington ratio distributions. Five flaring events are tidal disruption events published previously. This study has significantly increased the number of variable sources in XMMSL2 with identifications and provides greater insight on the nature of many o f the sources, enabling further studies of highly variable X-ray sources.

    

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