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- ItemGaia Data Release 2 : Properties and validation of the radial velocities(Les Ulis : EDP Sciences, 2019) Katz, D.; Sartoretti, P.; Cropper, M.; Panuzzo, P.; Seabroke, G.M.; Viala, Y.; Benson, K.; Blomme, R.; Jasniewicz, G.; Jean-Antoine, A.; Huckle, H.; Smith, M.; Baker, S.; Crifo, F.; Damerdji, Y.; David, M.; Dolding, C.; Frémat, Y.; Gosset, E.; Guerrier, A.; Guy, L. P.; Haigron, R.; Janßen, K.; Marchal, O.; Plum, G.; Soubiran, C.; Thévenin, F.; Ajaj, M.; Allende Prieto, C.; Babusiaux, C.; Boudreault, S.; Chemin, L.; Delle Luche, C.; Fabre, C.; Gueguen, A.; Hambly, N. C.; Lasne, Y.; Meynadier, F.; Pailler, F.; Panem, C.; Royer, F.; Tauran, G.; Zurbach, C.; Zwitter, T.; Arenou, F.; Bossini, D.; Gerssen, J.; Gómez, A.; Lemaitre, V.; Leclerc, N.; Morel, T.; Munari, U.; Turon, C.; Vallenari, A.; Žerjal, M.Context. For Gaia DR2, 280 million spectra collected by the Radial Velocity Spectrometer instrument on board Gaia were processed, and median radial velocities were derived for 9.8 million sources brighter than GRVS = 12 mag. Aims. This paper describes the validation and properties of the median radial velocities published in Gaia DR2. Methods. Quality tests and filters were applied to select those of the 9.8 million radial velocities that have the quality to be published in Gaia DR2. The accuracy of the selected sample was assessed with respect to ground-based catalogues. Its precision was estimated using both ground-based catalogues and the distribution of the Gaia radial velocity uncertainties. Results. Gaia DR2 contains median radial velocities for 7 224 631 stars, with Teff in the range [3550; 6900] K, which successfully passed the quality tests. The published median radial velocities provide a full-sky coverage and are complete with respect to the astrometric data to within 77.2% (for G ≤ 12:5 mag). The median radial velocity residuals with respect to the ground-based surveys vary from one catalogue to another, but do not exceed a few 100 m s-1. In addition, the Gaia radial velocities show a positive trend as a function of magnitude, which starts around GRVS ∼ 9 mag and reaches about +500 m s-1 at GRVS = 11:75 mag. The origin of the trend is under investigation, with the aim to correct for it in Gaia DR3. The overall precision, estimated from the median of the Gaia radial velocity uncertainties, is 1.05 km s-1. The radial velocity precision is a function of many parameters, in particular, the magnitude and effective temperature. For bright stars, GRVS 2 [4; 8] mag, the precision, estimated using the full dataset, is in the range 220-350 m s-1, which is about three to five times more precise than the pre-launch specification of 1 km s-1. At the faint end, GRVS = 11:75 mag, the precisions for Teff = 5000 and 6500 K are 1.4 and 3.7 km s-1, respectively.
- ItemTwo new magnetic cataclysmic variables discovered in the 3XMM catalogue(Les Ulis : EDP Sciences, 2018) Webb, N.A.; Schwope, A.; Zolotukhin, I.; Lin, D.; Rosen, S.R.Context. X-ray catalogues provide a wealth of information on many source types, ranging from compact objects to galaxies, clusters of galaxies, stars, and even planets. Thanks to the huge volume of X-ray sources provided in the 3XMM catalogue, along with many source specific products, many new examples from rare classes of sources can be identified. Aims. Through visualising spectra and lightcurves from about 80 observations included in the incremental part of the 3XMM catalogue, 3XMM-DR5, as part of the quality control of the catalogue, we identified two new X-ray sources, 3XMM J183333.1+225136 and 3XMM J184916.1+652943, that were highly variable. This work aims to investigate their nature. Methods. Through simple model fitting of the X-ray spectra and analysis of the X-ray lightcurves of 3XMM J183333.1+225136 and 3XMM J184916.1+652943, along with complementary photometry from the XMM-Newton Optical Monitor, Pan-STARRS and the Stella/WiFSIP and Large Binocular Telescope (LBT) spectra, we suggest that the two sources might be magnetic cataclysmic variables (CVs) of the polar type and we determine some of their properties. Results. Both CVs have very hard spectra, showing no soft excess. They are both situated in the local neighbourhood, located within ∼1 kpc. 3XMM J183333.1+225136 has an orbital period of 2.15 h. It shows features in the lightcurve that may be a total eclipse of the white dwarf. 3XMM J184916.1+652943 has an orbital period of 1.6 h. Given that only a small sky area was searched to identify these CVs, future sensitive all sky surveys such as the eROSITA project should be very successful at uncovering large numbers of such sources.
- ItemGaia Early Data Release 3: The celestial reference frame (Gaia-CRF3)(Les Ulis : EDP Sciences, 2022) Klioner, S.A.; Lindegren, L.; Mignard, F.; Hernández, J.; Ramos-Lerate, M.; Bastian, U.; Biermann, M.; Bombrun, A.; De Torres, A.; Gerlach, E.; Geyer, R.; Fraile, E.; Garabato, D.; García-Lario, P.; Gosset, E.; Haigron, R.; Halbwachs, J.-L.; Hambly, N.C.; Harrison, D.L.; Hestroffer, D.; Hodgkin, S.T.; Hilger, T.; Holl, B.; Janben, K.; Jevardat De Fombelle, G.; Jordan, S.; Krone-Martins, A.; Lanzafame, A.C.; Löffler, W.; Marchal, O.; Marrese, P.M.; Moitinho, A.; Hobbs, D.; Muinonen, K.; Osborne, P.; Pancino, E.; Pauwels, T.; Recio-Blanco, A.; Reylé, C.; Riello, M.; Rimoldini, L.; Roegiers, T.; Rybizki, J.; Lammers, U.L.; Sarro, L.M.; Siopis, C.; Smith, M.; Sozzetti, A.; Utrilla, E.; Van Leeuwen, M.; Abbas, U.; Ábrahám, P.; Abreu Aramburu, A.; Aerts, C.; McMillan, P.J.; Aguado, J.J.; Ajaj, M.; Aldea-Montero, F.; Altavilla, G.; Álvarez, M.A.; Alves, J.; Anderson, R.I.; Anglada Varela, E.; Antoja, T.; Baines, D.; Steidelmüller, H.; Baker, S.G.; Balaguer-Núñez, L.; Balbinot, E.; Balog, Z.; Barache, C.; Barbato, D.; Barros, M.; Barstow, M.A.; Bassilana, J.-L.; Bauchet, N.; Teyssier, D.; Becciani, U.; Bellazzini, M.; Berihuete, A.; Bertone, S.; Bianchi, L.; Binnenfeld, A.; Blanco-Cuaresma, S.; Boch, T.; Bossini, D.; Bouquillon, S.; Raiteri, C.M.; Bragaglia, A.; Bramante, L.; Breedt, E.; Bressan, A.; Brouillet, N.; Brugaletta, E.; Bucciarelli, B.; Burlacu, A.; Butkevich, A.G.; Buzzi, R.; Bartolomé, S.; Caffau, E.; Cancelliere, R.; Cantat-Gaudin, T.; Carballo, R.; Carlucci, T.; Carnerero, M.I.; Carrasco, J.M.; Casamiquela, L.; Castellani, M.; Castro-Ginard, A.; Bernet, M.; Chaoul, L.; Charlot, P.; Chemin, L.; Chiaramida, V.; Chiavassa, A.; Chornay, N.; Comoretto, G.; Contursi, G.; Cooper, W.J.; Cornez, T.; Castañeda, J.; Cowell, S.; Crifo, F.; Cropper, M.; Crosta, M.; Crowley, C.; Dafonte, C.; Dapergolas, A.; David, P.; De Laverny, P.; De Luise, F.; Clotet, M.; De March, R.; De Ridder, J.; De Souza, R.; Del Peloso, E.F.; Del Pozo, E.; Delbo, M.; Delgado, A.; Delisle, J.-B.; Demouchy, C.; Dharmawardena, T.E.; Davidson, M.; Diakite, S.; Diener, C.; Distefano, E.; Dolding, C.; Enke, H.; Fabre, C.; Fabrizio, M.; Faigler, S.; Fedorets, G.; Fernique, P.; Fabricius, C.; Fienga, A.; Figueras, F.; Fournier, Y.; Fouron, C.; Fragkoudi, F.; Gai, M.; Garcia-Gutierrez, A.; Garcia-Reinaldos, M.; García-Torres, M.; Garofalo, A.; Garralda Torres, N.; Gavel, A.; Gavras, P.; Giacobbe, P.; Gilmore, G.; Girona, S.; Giuffrida, G.; Gomel, R.; Gomez, A.; González-Núñez, J.; González-Santamaría, I.; González-Vidal, J.J.; Granvik, M.; Guillout, P.; Guiraud, J.; Gutiérrez-Sánchez, R.; Guy, L.P.; Hatzidimitriou, D.; Hauser, M.; Haywood, M.; Helmer, A.; Helmi, A.; Portell, J.; Sarmiento, M.H.; Hidalgo, S.L.; Hładczuk, N.; Holland, G.; Huckle, H.E.; Jardine, K.; Jasniewicz, G.; Jean-Antoine Piccolo, A.; Jiménez-Arranz, O.; Juaristi Campillo, J.; Rowell, N.; Julbe, F.; Karbevska, L.; Kervella, P.; Khanna, S.; Kordopatis, G.; Korn, A.J.; Kóspál, A.; Kostrzewa-Rutkowska, Z.; Kruszyńska, K.; Kun, M.; Torra, F.; Laizeau, P.; Lambert, S.; Lanza, A.F.; Lasne, Y.; Le Campion, J.-F.; Lebreton, Y.; Lebzelter, T.; Leccia, S.; Leclerc, N.; Lecoeur-Taibi, I.; Torra, J.; Liao, S.; Licata, E.L.; Lindstrøm, H.E.P.; Lister, T.A.; Livanou, E.; Lobel, A.; Lorca, A.; Loup, C.; Madrero Pardo, P.; Magdaleno Romeo, A.; Brown, A.G.A.; Managau, S.; Mann, R.G.; Manteiga, M.; Marchant, J.M.; Marconi, M.; Marcos, J.; Santos, M. M. S. Marcos; Marín Pina, D.; Marinoni, S.; Marocco, F.; Vallenari, A.; Marshall, D.J.; Polo, L. Martin; Martín-Fleitas, J.M.; Marton, G.; Mary, N.; Masip, A.; Massari, D.; Mastrobuono-Battisti, A.; Mazeh, T.; Messina, S.; Prusti, T.; Michalik, D.; Millar, N.R.; Mints, A.; Molina, D.; Molinaro, R.; Molnár, L.; Monari, G.; Monguió, M.; Montegriffo, P.; Montero, A.; De Bruijne, J.H.J.; Mor, R.; Mora, A.; Morbidelli, R.; Morel, T.; Morris, D.; Muraveva, T.; Murphy, C.P.; Musella, I.; Nagy, Z.; Noval, L.; Arenou, F.; Ocaña, F.; Ogden, A.; Ordenovic, C.; Osinde, J.O.; Pagani, C.; Pagano, I.; Palaversa, L.; Palicio, P.A.; Pallas-Quintela, L.; Panahi, A.; Babusiaux, C.; Payne-Wardenaar, S.; Peñalosa Esteller, X.; Penttilä, A.; Pichon, B.; Piersimoni, A.M.; Pineau, F.-X.; Plachy, E.; Plum, G.; Poggio, E.; Prša, A.; Creevey, O.L.; Pulone, L.; Racero, E.; Ragaini, S.; Rainer, M.; Rambaux, N.; Ramos, P.; Re Fiorentin, P.; Regibo, S.; Richards, P.J.; Diaz, C. Rios; Ducourant, C.; Ripepi, V.; Riva, A.; Rix, H.-W.; Rixon, G.; Robichon, N.; Robin, A.C.; Robin, C.; Roelens, M.; Rogues, H.R.O.; Rohrbasser, L.; Evans, D.W.; Romero-Gómez, M.; Royer, F.; Ruz Mieres, D.; Rybicki, K.A.; Sadowski, G.; Sáez Núñez, A.; Sagristà Sellés, A.; Sahlmann, J.; Salguero, E.; Samaras, N.; Eyer, L.; Sanchez Gimenez, V.; Sanna, N.; Santoveña, R.; Sarasso, M.; Schultheis, M.; Sciacca, E.; Segol, M.; Segovia, J.C.; Ségransan, D.; Semeux, D.; Guerra, R.; Shahaf, S.; Siddiqui, H.I.; Siebert, A.; Siltala, L.; Silvelo, A.; Slezak, E.; Slezak, I.; Smart, R.L.; Snaith, O.N.; Solano, E.; Hutton, A.; Solitro, F.; Souami, D.; Souchay, J.; Spagna, A.; Spina, L.; Spoto, F.; Steele, I.A.; Stephenson, C.A.; Süveges, M.; Surdej, J.; Jordi, C.; Szabados, L.; Szegedi-Elek, E.; Taris, F.; Taylor, M.B.; Teixeira, R.; Tolomei, L.; Tonello, N.; Torralba Elipe, G.; Trabucchi, M.; Tsounis, A.T.; Luri, X.; Turon, C.; Ulla, A.; Unger, N.; Vaillant, M.V.; Van Dillen, E.; Van Reeven, W.; Vanel, O.; Vecchiato, A.; Viala, Y.; Vicente, D.; Panem, C.; Voutsinas, S.; Weiler, M.; Wevers, T.; Wyrzykowski, L.; Yoldas, A.; Yvard, P.; Zhao, H.; Zorec, J.; Zucker, S.; Zwitter, T.; Pourbaix, D.; Randich, S.; Sartoretti, P.; Soubiran, C.; Tanga, P.; Walton, N.A.; Bailer-Jones, C.A.L.; Drimmel, R.; Jansen, F.; Katz, D.; Lattanzi, M.G.; Van Leeuwen, F.; Bakker, J.; Cacciari, C.; De Angeli, F.; Fouesneau, M.; Frémat, Y.; Galluccio, L.; Guerrier, A.; Heiter, U.; Masana, E.; Messineo, R.; Mowlavi, N.; Nicolas, C.; Nienartowicz, K.; Pailler, F.; Panuzzo, P.; Riclet, F.; Roux, W.; Seabroke, G.M.; Sordo, R.; Thévenin, F.; Gracia-Abril, G.; Altmann, M.; Andrae, R.; Audard, M.; Bellas-Velidis, I.; Benson, K.; Berthier, J.; Blomme, R.; Burgess, P.W.; Busonero, D.; Busso, G.; Cánovas, H.; Carry, B.; Cellino, A.; Cheek, N.; Clementini, G.; Damerdji, Y.; De Teodoro, P.; Nuñez Campos, M.; Delchambre, L.; Dell'Oro, A.; Esquej, P.; Fernández-Hernández, J.Context. Gaia-CRF3 is the celestial reference frame for positions and proper motions in the third release of data from the Gaia mission, Gaia DR3 (and for the early third release, Gaia EDR3, which contains identical astrometric results). The reference frame is defined by the positions and proper motions at epoch 2016.0 for a specific set of extragalactic sources in the (E)DR3 catalogue. Aims. We describe the construction of Gaia-CRF3 and its properties in terms of the distributions in magnitude, colour, and astrometric quality. Methods. Compact extragalactic sources in Gaia DR3 were identified by positional cross-matching with 17 external catalogues of quasi-stellar objects (QSO) and active galactic nuclei (AGN), followed by astrometric filtering designed to remove stellar contaminants. Selecting a clean sample was favoured over including a higher number of extragalactic sources. For the final sample, the random and systematic errors in the proper motions are analysed, as well as the radio-optical offsets in position for sources in the third realisation of the International Celestial Reference Frame (ICRF3). Results. Gaia-CRF3 comprises about 1.6 million QSO-like sources, of which 1.2 million have five-parameter astrometric solutions in Gaia DR3 and 0.4 million have six-parameter solutions. The sources span the magnitude range G = 13-21 with a peak density at 20.6 mag, at which the typical positional uncertainty is about 1 mas. The proper motions show systematic errors on the level of 12 μas yr-1 on angular scales greater than 15 deg. For the 3142 optical counterparts of ICRF3 sources in the S/X frequency bands, the median offset from the radio positions is about 0.5 mas, but it exceeds 4 mas in either coordinate for 127 sources. We outline the future of Gaia-CRF in the next Gaia data releases. Appendices give further details on the external catalogues used, how to extract information about the Gaia-CRF3 sources, potential (Galactic) confusion sources, and the estimation of the spin and orientation of an astrometric solution.
- ItemGaia Data Release 2 : Processing the spectroscopic data(Les Ulis : EDP Sciences, 2018) Sartoretti, P.; Katz, D.; Cropper, M.; Panuzzo, P.; Seabroke, G. M.; Viala, Y.; Benson, K.; Blomme, R.; Jasniewicz, G.; Jean-Antoine, A.; Huckle, H.; Smith, M.; Baker, S.; Crifo, F.; Damerdji, Y.; David, M.; Dolding, C.; Frémat, Y.; Gosset, E.; Guerrier, A.; Guy, L. P.; Haigron, R.; Janßen, K.; Marchal, O.; Plum, G.; Soubiran, C.; Thévenin, F.; Ajaj, M.; Allende Prieto, C.; Babusiaux, C.; Boudreault, S.; Chemin, L.; Delle Luche, C.; Fabre, C.; Gueguen, A.; Hambly, N. C.; Lasne, Y.; Meynadier, F.; Pailler, F.; Panem, C.; Riclet, F.; Royer, F.; Tauran, G.; Zurbach, C.; Zwitter, T.; Arenou, F.; Gomez, A.; Lemaitre, V.; Leclerc, N.; Morel, T.; Munari, U.; Turon, C.; Žerjal, M.Context. The Gaia Data Release 2 (DR2 ) contains the first release of radial velocities complementing the kinematic data of a sample of about 7 million relatively bright, late-type stars. Aims. This paper provides a detailed description of the Gaia spectroscopic data processing pipeline, and of the approach adopted to derive the radial velocities presented in DR2 . Methods. The pipeline must perform four main tasks: (i) clean and reduce the spectra observed with the Radial Velocity Spectrometer (RVS); (ii) calibrate the RVS instrument, including wavelength, straylight, line-spread function, bias non-uniformity, and photometric zeropoint; (iii) extract the radial velocities; and (iv) verify the accuracy and precision of the results. The radial velocity of a star is obtained through a fit of the RVS spectrum relative to an appropriate synthetic template spectrum. An additional task of the spectroscopic pipeline was to provide first-order estimates of the stellar atmospheric parameters required to select such template spectra. We describe the pipeline features and present the detailed calibration algorithms and software solutions we used to produce the radial velocities published in DR2 . Results. The spectroscopic processing pipeline produced median radial velocities for Gaia stars with narrow-band near-IR magnitude GRVS ≤ 12 (i.e. brighter than V ∼ 13). Stars identified as double-lined spectroscopic binaries were removed from the pipeline, while variable stars, single-lined, and non-detected double-lined spectroscopic binaries were treated as single stars. The scatter in radial velocity among different observations of a same star, also published in Gaia DR2, provides information about radial velocity variability. For the hottest (Te≥ 7000 K) and coolest (Te≤ 3500 K) stars, the accuracy and precision of the stellar parameter estimates are not sufficient to allow selection of appropriate templates. The radial velocities obtained for these stars were removed from DR2 . The pipeline also provides a first-order estimate of the performance obtained. The overall accuracy of radial velocity measurements is around ∼200-300 m s-1, and the overall precision is ∼1 km s-1; it reaches ∼200 m s-1 for the brightest stars.
- ItemThe MUSE Hubble Ultra Deep Field surveys: Data release II(Les Ulis : EDP Sciences, 2023) Bacon, Roland; Brinchmann, Jarle; Conseil, Simon; Maseda, Michael; Nanayakkara, Themiya; Wendt, Martin; Bacher, Raphael; Mary, David; Weilbacher, Peter M.; Krajnović, Davor; Boogaard, Leindert; Bouché, Nicolas; Contini, Thierry; Epinat, Benoît; Feltre, Anna; Guo, Yucheng; Herenz, Christian; Kollatschny, Wolfram; Kusakabe, Haruka; Leclercq, Floriane; Michel-Dansac, Léo; Pello, Roser; Richard, Johan; Roth, Martin; Salvignol, Gregory; Schaye, Joop; Steinmetz, Matthias; Tresse, Laurence; Urrutia, Tanya; Verhamme, Anne; Vitte, Eloise; Wisotzki, Lutz; Zoutendijk, Sebastiaan L.We present the second data release of the MUSE Hubble Ultra-Deep Field surveys, which includes the deepest spectroscopic survey ever performed. The MUSE data, with their 3D content, amazing depth, wide spectral range, and excellent spatial and medium spectral resolution, are rich in information. Their location in the Hubble ultra-deep field area, which benefits from an exquisite collection of ancillary panchromatic information, is a major asset. This update of the first release incorporates a new 141-h adaptive-optics-assisted MUSE eXtremely Deep Field (MXDF; 1 arcmin diameter field of view) in addition to the reprocessed 10-h mosaic (3 × 3 arcmin2) and the single 31-h deep field (1 × 1 arcmin2). All three data sets were processed and analyzed homogeneously using advanced data reduction and analysis methods. The 3σ point-source flux limit of an unresolved emission line reaches 3.1 × 10-19 and 6.3 × 10-20 erg s-1 cm-2 at 10-and 141-h depths, respectively. We have securely identified and measured the redshift of 2221 sources, an increase of 41% compared to the first release. With the exception of eight stars, the collected sample consists of 25 nearby galaxies (z < 0.25), 677 [O II] emitters (z = 0.25-1.5), 201 galaxies in the MUSE redshift desert range (z = 1.5-2.8), and 1308 Lyα emitters (z = 2.8-6.7). This represents an order of magnitude more redshifts than the collection of all spectroscopic redshifts obtained before MUSE in the Hubble ultra-deep field area (i.e., 2221 versus 292). At high redshift (z > 3), the difference is even more striking, with a factor of 65 increase (1308 versus 20). We compared the measured redshifts against three published photometric redshift catalogs and find the photo-z accuracy to be lower than the constraints provided by photo-z fitting codes. Eighty percent of the galaxies in our final catalog have an HST counterpart. These galaxies are on average faint, with a median AB F775W magnitude of 25.7 and 28.7 for the [O II] and Lyα emitters, respectively. Fits of their spectral energy distribution show that these galaxies tend to be low-mass star-forming galaxies, with a median stellar mass of 6.2 × 108 M· and a median star-formation rate of 0.4 M· yr-1. We measured the completeness of our catalog with respect to HST and found that, in the deepest 141-h area, 50% completeness is achieved for an AB magnitude of 27.6 and 28.7 (F775W) at z = 0.8-1.6 and z = 3.2-4.5, respectively. Twenty percent of our catalog, or 424 galaxies, have no HST counterpart. The vast majority of these new sources are high equivalent-width z > 2.8 Lyα emitters that are detected by MUSE thanks to their bright and asymmetric broad Lyα line. We release advanced data products, specific software, and a web interface to select and download data sets.
- ItemDistance of Hi-GAL sources(Les Ulis : EDP Sciences, 2021) Mège, P.; Russeil, D.; Zavagno, A.; Elia, D.; Molinari, S.; Brunt, C.M.; Butora, R.; Cambresy, L.; Di Giorgio, A.M.; Fenouillet, T.; Fukui, Y.; Lambert, J.C.; Makai, Z.; Merello, M.; Meunier, J.C.; Molinaro, M.; Moreau, C.; Pezzuto, S.; Poulin, Y.; Schisano, E.; Schuller, F.Aims. Distances are key to determining the physical properties of sources. In the Galaxy, large (> 10 000) homogeneous samples of sources for which distance are available, covering the whole Galactic distance range, are still missing. Here we present a catalog of velocity and distance for a large sample (> 100 000) of Hi-GAL compact sources. Methods. We developed a fully automatic Python package to extract the velocity and determine the distance. To assign a velocity to a Hi-GAL compact source, the code uses all the available spectroscopic data complemented by a morphological analysis. Once the velocity is determined, if no stellar or maser parallax distance is known, the kinematic distance is calculated and the distance ambiguity (for sources located inside the Solar circle) is solved with the H I self-absorption method or from distance-extinction data. Results. Among the 150 223 compact sources of the Hi-GAL catalog, we obtained a distance for 124 069 sources for the 5σ catalog (and 128 351 sources for the 3σ catalog), where σ represents the noise level of each molecular spectrum used for the line detections made at 5σ and 3σ to produce the respective catalogs. © P. Mège et al. 2021.