Persona:
Sarro Baro, Luis Manuel

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0000-0002-5622-5191
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Sarro Baro
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Luis Manuel
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Autor: Bailer Jones, C. A. L. × search.filters.applied.f.itemFacultad: E.T.S. de Ingeniería Informática ×

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Mostrando 1 - 5 de 5
  • Miniatura
    Publicación
    Ultracool dwarfs in Gaia DR3
    (EDP Sciences, 2023-01-26) Sarro Baro, Luis Manuel; Berihuete, Ángel; Smart, R. L.; Reylé, Céline; Barrado, David; Garcia Torres, Miguel; Cooper, W. J.; Jones, H. R. A.; Marocco, Federico; Creevey, Orlagh; Sordo, Rosanna; Bailer Jones, C. A. L.; Montegriffo, P.; Ruth Carballo; Andrae, Rene; Fouesneau, Morgan; Lanzafame, Alessandro; Pailler, Fred; Thévenin, F.; Lobel, A.; Delchambre, L.; Korn, Andreas J.; Recio Blanco, Alejandra; Schultheis, M.; Angeli, Francesca De; Brouillet, Nathalie; Casamiquela, Laia; Contursi, Gabriele; Laverny, P. de; Garcia Lario, Pedro; Kordopatis, G.; Lebreton, Y.; Livanou, E.; Lorca, Alejandro; Palicio, Pedro Alonso; Slezak Oreshina, I.; Contursi, Gabriele; Ulla, A.; Zhao, He; https://orcid.org/0000-0002-8589-4423; https://orcid.org/0000-0002-4424-4766; https://orcid.org/0000-0003-2258-2403; https://orcid.org/0000-0002-5971-9242; https://orcid.org/0000-0002-6867-7080; https://orcid.org/0000-0003-3501-8967; https://orcid.org/0000-0003-0433-3665; https://orcid.org/0000-0001-7519-1700; https://orcid.org/0000-0003-1853-6631; https://orcid.org/0000-0003-4979-0659; https://orcid.org/0000-0001-5013-5948; https://orcid.org/0000-0001-7412-2498; https://orcid.org/0000-0001-8006-6365; https://orcid.org/0000-0001-9256-5516; https://orcid.org/0000-0002-2697-3607; https://orcid.org/0000-0002-6855-2050; https://orcid.org/0000-0001-5030-019X; https://orcid.org/0000-0003-2559-408X; https://orcid.org/0000-0002-3881-6756; https://orcid.org/0000-0002-6590-1657; https://orcid.org/0000-0003-1879-0488; https://orcid.org/0000-0002-3274-7024; https://orcid.org/0000-0001-5238-8674; https://orcid.org/0000-0001-5370-1511; https://orcid.org/0000-0002-2817-4104; https://orcid.org/0000-0003-4039-8212; https://orcid.org/0000-0002-9035-3920; https://orcid.org/0000-0002-7985-250X; https://orcid.org/0000-0002-7432-8709; https://orcid.org/0000-0001-5370-1511; https://orcid.org/0000-0003-2645-6869
    Context. Previous Gaia data releases offered the opportunity to uncover ultracool dwarfs (UCDs) through astrometric, rather than purely photometric, selection. The most recent, the third data release (DR3), offers in addition the opportunity to use low-resolution spectra to refine and widen the selection. Aims. In this work we use the Gaia DR3 set of UCD candidates and complement the Gaia spectrophotometry with additional photometry in order to characterise the global properties of the set. This includes the inference of the distances, their locus in the Gaia colour-absolute magnitude diagram, and the (biased through selection) luminosity function at the faint end of the main sequence. We study the overall changes in the Gaia RP spectra as a function of spectral type. We study the UCDs in binary systems, we attempt to identify low-mass members of nearby young associations, star-forming regions, and clusters, and we analyse their variability properties. Methods. We used a forward model and the Bayesian inference framework to produce posterior probabilities for the distribution parameters and a calibration of the colour index as a function of the absolute magnitude in the form of a Gaussian process. Additionally, we applied the hierarchical mode association clustering (HMAC) unsupervised classification algorithm for the detection and characterisation of overdensities in the space of celestial coordinates, projected velocities, and parallaxes. Results. We detect 57 young, kinematically homogeneous groups, some of which are identified as well-known star-forming regions, associations, and clusters of different ages. We find that the primary members of the 880 binary systems with a UCD belong to the thin and thick disc components of the Milky Way. We identify 1109 variable UCDs using the variability tables in the Gaia archive, 728 of which belong to the star-forming regions defined by HMAC. We define two groups of variable UCDs with extreme bright or faint outliers. Conclusions. The set of sources identified as UCDs in the Gaia archive contains a wealth of information that will require focused follow-up studies and observations. It will help advance our understanding of the nature of the faint end of the main sequence and the stellar-substellar transition.
  • Miniatura
    Publicación
    Gaia Focused Product Release: Spatial distribution of two diffuse interstellar bands
    (EDP Sciences, 2023-09-05) Schultheis, M.; Zhao, He; Zwitter, Tomaž; Bailer Jones, C. A. L.; Sarro Baro, Luis Manuel
    Diffuse interstellar bands (DIBs) are absorption features seen in optical and infrared spectra of stars and extragalactic objects that are probably caused by large and complex molecules in the galactic interstellar medium (ISM). Here we investigate the Galactic distribution and properties of two DIBs identified in almost six million stellar spectra collected by the Gaia Radial Velocity Spectrometer. These measurements constitute a part of the Gaia Focused Product Release to be made public between the Gaia DR3 and DR4 data releases. In order to isolate the DIB signal from the stellar features in each individual spectrum, we identified a set of 160 000 spectra at high Galactic latitudes (|b| ⩾ 65◦) covering a range of stellar parameters which we consider to be the DIB-free reference sample. Matching each target spectrum to its closest reference spectra in stellar parameter space allowed us to remove the stellar spectrum empirically, without reference to stellar models, leaving a set of six million ISM spectra. Using the star’s parallax and sky coordinates, we then allocated each ISM spectrum to a voxel (VOlume piXEL) on a contiguous three-dimensional grid with an angular size of 1.8◦ (level 5 HEALPix) and 29 unequally sized distance bins. Identifying the two DIBs at 862.1 nm (λ862.1) and 864.8 nm (λ864.8) in the stacked spectra, we modelled their shapes and report the depth, central wavelength, width, and equivalent width (EW) for each, along with confidence bounds on these measurements. We then explored the properties and distributions of these quantities and compared them with similar measurements from other surveys. Our main results are as follows: (1) the strength and spatial distribution of the DIB λ862.1 are very consistent with what was found in Gaia DR3, but for this work we attained a higher signal-to-noise ratio in the stacked spectra to larger distances, which allowed us to trace DIBs in the outer spiral arm and beyond the Scutum–Centaurus spiral arm; (2) we produced an all-sky map below ±65◦ of Galactic latitude to ∼4000 pc of both DIB features and their correlations; (3) we detected the signals of DIB λ862.1 inside the Local Bubble (≲200 pc); and (4) there is a reasonable correlation with the dust reddening found from stellar absorption and EWs of both DIBs with a correlation coefficient of 0.90 for λ862.1 and 0.77 for λ864.8.
  • Miniatura
    Publicación
    Gaia Data Release 3. Non-stellar content and source classification
    (EDP Sciences, 2023-06-16) Delchambre, L.; Bailer Jones, C. A. L.; Bellas Velidis, I.; Sarro Baro, Luis Manuel
    Context. As part of the third Gaia Data Release, we present the contributions of the non-stellar and classifcation modules from the eighth coordination unit (CU8) of the Data Processing and Analysis Consortium, which is responsible for the determination of source astrophysical parameters using Gaia data. This is the third in a series of three papers describing the work done within CU8 for this release. Aims. For each of the five relevant modules from CU8, we summarise their objectives, the methods they employ, their performance, and the results they produce for Gaia DR3. We further advise how to use these data products and highlight some limitations. Methods. The Discrete Source Classier (DSC) module provides classification probabilities associated with five types of sources: quasars, galaxies, stars, white dwarfs, and physical binary stars. A subset of these sources are processed by the Outlier Analysis (OA) module, which performs an unsupervised clustering analysis, and then associates labels with the clusters to complement the DSC classfication. The Quasi Stellar Object Classifier (QSOC) and the Unresolved Galaxy Classfier (UGC) determine the redshifts of the sources classfied as quasar and galaxy by the DSC module. Finally, the Total Galactic Extinction (TGE) module uses the extinctions of individual stars determined by another CU8 module to determine the asymptotic extinction along all lines of sight for Galactic latitudes |b| > 5◦. Results. Gaia DR3 includes 1591 million sources with DSC classications; 56 million sources to which the OA clustering is applied; 1.4 million sources with redshift estimates from UGC; 6.4 million sources with QSOC redshift; and 3.1 million level 9 HEALPixes of size 0.013 deg2 where the extinction is evaluated by TGE. Conclusions. Validation shows that results are in good agreement with values from external catalogues; for example 90% of the QSOC redshifts have absolute error lower than 0.1 for sources with empty warning flags, while UGC redshifts have a mean error of 0.008 ± 0.037 if evaluated on a clean set of spectra. An internal validation of the OA results further shows that 30 million sources are located in high confidence regions of the clustering map.
  • Miniatura
    Publicación
    Gaia Data Release 3. Apsis. III. Non-stellar content and source classification
    (EDP Sciences, 2023-06-16) Delchambre, L.; Bailer Jones, C. A. L.; Bellas Velidis, I.; Drimmel, R.; Garabato, D.; Sarro Baro, Luis Manuel; https://orcid.org/0000-0003-2559-408X; https://orcid.org/0009-0004-7385-9198; https://orcid.org/0000-0002-1777-5502; https://orcid.org/0000-0002-7133-6623
    Context. As part of the third Gaia Data Release, we present the contributions of the non-stellar and classification modules from the eighth coordination unit (CU8) of the Data Processing and Analysis Consortium, which is responsible for the determination of source astrophysical parameters using Gaia data. This is the third in a series of three papers describing the work done within CU8 for this release. Aims. For each of the five relevant modules from CU8, we summarise their objectives, the methods they employ, their performance, and the results they produce for Gaia DR3. We further advise how to use these data products and highlight some limitations. Methods. The Discrete Source Classifier (DSC) module provides classification probabilities associated with five types of sources: quasars, galaxies, stars, white dwarfs, and physical binary stars. A subset of these sources are processed by the Outlier Analysis (OA) module, which performs an unsupervised clustering analysis, and then associates labels with the clusters to complement the DSC classification. The Quasi Stellar Object Classifier (QSOC) and the Unresolved Galaxy Classifier (UGC) determine the redshifts of the sources classified as quasar and galaxy by the DSC module. Finally, the Total Galactic Extinction (TGE) module uses the extinctions of individual stars determined by another CU8 module to determine the asymptotic extinction along all lines of sight for Galactic latitudes |b|> 5°. Results.Gaia DR3 includes 1591 million sources with DSC classifications; 56 million sources to which the OA clustering is applied; 1.4 million sources with redshift estimates from UGC; 6.4 million sources with QSOC redshift; and 3.1 million level 9 HEALPixes of size 0.013 deg2 where the extinction is evaluated by TGE. Conclusions. Validation shows that results are in good agreement with values from external catalogues; for example 90% of the QSOC redshifts have absolute error lower than 0.1 for sources with empty warning flags, while UGC redshifts have a mean error of 0.008 ± 0.037 if evaluated on a clean set of spectra. An internal validation of the OA results further shows that 30 million sources are located in high confidence regions of the clustering map.
  • Miniatura
    Publicación
    Gaia Data Release 3. The extragalactic content
    (EDP Sciences, 2023-06-16) Bailer Jones, C. A. L.; Teyssier, D.; Delchambre, L.; Ducourant, C.; Sarro Baro, Luis Manuel
    The Gaia Galactic survey mission is designed and optimized to obtain astrometry, photometry, and spectroscopy of nearly two billion stars in our Galaxy. Yet as an all-sky multi-epoch survey, Gaia also observes several million extragalactic objects down to a magnitude of G ∼ 21 mag. Due to the nature of the Gaia onboard-selection algorithms, these are mostly point-source-like objects. Using data provided by the satellite, we have identified quasar and galaxy candidates via supervised machine learning methods, and estimate their redshifts using the low resolution BP/RP spectra. We further characterise the surface brightness profiles of host galaxies of quasars and of galaxies from pre-defined input lists. Here we give an overview of the processing of extragalactic bjects, describe the data products in Gaia DR3, and analyse their properties. Two integrated tables contain the main results for a high completeness, but low purity (50−70%), set of 6.6 million candidate quasars and 4.8 million candidate galaxies. We provide queries that select purer sub-samples of these containing 1.9 million probable quasars and 2.9 million probable galaxies (both ∼95% purity). We also use high quality BP/RP spectra of 43 thousand high probability quasars over the redshift range 0.05−4.36 to construct a composite quasar spectrum spanning restframe wavelengths from 72−1000 nm.