21 research outputs found
Gaia FGK Benchmark Stars and their reference parameters
In this article we summarise on-going work on the so-called Gaia FGK
Benchmark Stars. This work consists of the determination of their atmospheric
parameters and of the construction of a high-resolution spectral library. The
definition of such a set of reference stars has become crucial in the current
era of large spectroscopic surveys. Only with homogeneous and well documented
stellar parameters can one exploit these surveys consistently and understand
the structure and history of the Milky Way and therefore other of galaxies in
the Universe.Comment: to appear in ASI Conference Series, 2014, Vol. 10 for the Workshop of
Spectral Libraries held in Lyon, Oct. 201
Test de la technique de marquage chimique avec des amas ouverts
Context. Stars are born together from giant molecular clouds and, if weassume that they were chemically homogeneous and well-mixed, we expect them toshare the same chemical composition.Most of the stellar aggregates are disrupted while orbiting the Galaxy and thedynamic information is lost, thus the only possibility to reconstruct the stellarformation history is to analyze the chemical abundances that we observe today.Aims. The chemical tagging technique aims to recover disrupted stellarclusters based merely on their chemical composition. We evaluate the viability of thistechnique to recover conatal stars that are not gravitationally bound anymore.Methods. We built a high-quality stellar spectra library to facilitate theassessment of spectral analyses. We developed our own spectral analysisframework, named iSpec, capable of homogeneizing stellar spectra and derivingatmospheric parameters/chemical abundances. Finally, we compiled stellar spectrafrom 32 Open Clusters, homogeneously derived atmospheric parameters and 17abundance species, and applied machine learning algorithms to group the starsbased on their chemical composition. This approach allows us to evaluate theviability of the chemical tagging technique.Results. We found that stars in different evolutionary stages havedistinguished chemical patterns may be due to NLTE effects, atomic diffusion, mixingand correlations from atmospheric parameter determinations. When separating starsper evolutionary stage, we observed a high degree of overlapping among OpenClusterâs chemical signatures, making it difficult to recover conatal aggregates byapplying the chemical tagging technique.Contexte. Les Ă©toiles naissent ensemble dans des nuages molĂ©culaires gĂ©ants. Si nous faisons lâhypothĂšse quâils Ă©taient Ă lâorigine chimiquement homogĂšnes et bien mĂ©langĂ©s, nous nous attendrions Ă ce que les Ă©toiles issues dâun mĂȘme nuage aient la mĂȘme composition chimique. La plupart des groupes dâĂ©toiles sont perturbĂ©s lors de leur Ă©volution dans la galaxie et lâinformation dynamique est perdue. Ainsi la seule possibilitĂ© que nous ayons de reconstruire lâhistoire de la formation stellaire est dâanalyser les abondances chimiques que lâon observe aujourdâhui.But. La technique de marquage chimique a pour but de retrouver les amas dâĂ©toiles dissociĂ©s en se basant uniquement sur leur composition chimique. Nous Ă©valuons la viabilitĂ© de cette technique pour retrouver les Ă©toiles qui sont nĂ©es dans un mĂȘme amas mais qui ne sont plus gravitationnellement liĂ©es.MĂ©thodes. Nous avons crĂ©Ă© une librairie de spectres stellaires de haute qualitĂ© afin de faciliter lâĂ©valuation des analyses spectrales. Nous avons dĂ©veloppĂ© notre propre outil dâanalyse spectrale, nommĂ©e iSpec, capable dâhomogĂ©nĂ©iser les spectres stellaires venant de tous types dâinstruments et de dĂ©river les paramĂštres atmosphĂ©riques et les abondances chimiques. Finalement, nous avons compilĂ© des spectres stellaires dâĂ©toiles de 32 amas ouverts, nous avons dĂ©rivĂ© de façon homogĂšne les paramĂštres atmosphĂ©riques et les abondances de 17 espĂšces, et nous avons utilisĂ© des algorithmes dâapprentissage automatique pour grouper les Ă©toiles en se basant sur leur composition chimique.RĂ©sultats. Nous avons trouvĂ© que les Ă©toiles Ă des Ă©tapes dâĂ©volution diffĂ©rentes ont des motifs chimiques distincts qui peuvent ĂȘtre dus Ă des effets NLTE,de diffusion atomique, de mĂ©lange et de corrĂ©lation Ă partir des dĂ©terminations de paramĂštres atmosphĂ©riques. Quand nous sĂ©parons les Ă©toiles suivant leur stade dâĂ©volution, nous observons quâil y a un important degrĂ© de recouvrement dans la dĂ©termination des signatures chimiques des amas ouverts. Ceci rend difficile de retrouver les groupes dâĂ©toiles nĂ©es ensemble en utilisant la technique de marquage chimique
On the influence of equilibrium tides on transit-timing variations of close-in super-Earths. I. Application to single-planet systems and the case of K2-265 b
In this work, we investigate the influence of planetary tidal interactions on
the transit-timing variations of short-period low-mass rocky exoplanets. For
such purpose, we employ the recently-developed creep tide theory to compute
tidally-induced TTVs. We implement the creep tide in the recently-developed
Posidonius N-body code, thus allowing for a high-precision evolution of the
coupled spin-orbit dynamics of planetary systems. As a working example for the
analyses of tidally-induced TTVs, we apply our version of the code to the
K2-265 b planet. We analyse the dependence of tidally-induced TTVs with the
planetary rotation rate, uniform viscosity coefficient and eccentricity. Our
results show that the tidally-induced TTVs are more significant in the case
where the planet is trapped in non-synchronous spin-orbit resonances, in
particular the 3/2 and 2/1 spin-orbit resonant states. An analysis of the TTVs
induced separately by apsidal precession and tidally-induced orbital decay has
allowed for the conclusion that the latter effect is much more efficient at
causing high-amplitude TTVs than the former effect by 2 - 3 orders of
magnitude. We compare our findings for the tidally-induced TTVs obtained with
Posidonius with analytical formulations for the transit timings used in
previous works, and verified that the results for the TTVs coming from
Posidonius are in excellent agreement with the analytical formulations. These
results show that the new version of Posidonius containing the creep tide
theory implementation can be used to study more complex cases in the future.
For instance, the code can be used to study multiplanetary systems, in which
case planet-planet gravitational perturbations must be taken into account
additionally to tidal interactions to obtain the TTVs.Comment: 12 pages, 9 figures. Accepted with minor revisions in Astronomy and
Astrophysics (A&A
New ADS Functionality for the Curator
In this paper we provide an update concerning the operations of the NASA
Astrophysics Data System (ADS), its services and user interface, and the
content currently indexed in its database. As the primary information system
used by researchers in Astronomy, the ADS aims to provide a comprehensive index
of all scholarly resources appearing in the literature. With the current effort
in our community to support data and software citations, we discuss what steps
the ADS is taking to provide the needed infrastructure in collaboration with
publishers and data providers. A new API provides access to the ADS search
interface, metrics, and libraries allowing users to programmatically automate
discovery and curation tasks. The new ADS interface supports a greater
integration of content and services with a variety of partners, including ORCID
claiming, indexing of SIMBAD objects, and article graphics from a variety of
publishers. Finally, we highlight how librarians can facilitate the ingest of
gray literature that they curate into our system.Comment: Submitted to the Proceedings of Library and Information Services in
Astronomy VIII, Strasbourg, Franc
TOI-257b (HD 19916b): a warm sub-saturn orbiting an evolved F-type star
ABSTRACT
We report the discovery of a warm sub-Saturn, TOI-257b (HD 19916b), based on data from NASAâs Transiting Exoplanet Survey Satellite (TESS). The transit signal was detected by TESS and confirmed to be of planetary origin based on radial velocity observations. An analysis of the TESS photometry, the Minerva-Australis, FEROS, and HARPS radial velocities, and the asteroseismic data of the stellar oscillations reveals that TOI-257b has a mass of MP = 0.138 ± 0.023 (43.9 ± 7.3 ), a radius of RP = 0.639 ± 0.013 (7.16 ± 0.15 ), bulk density of (cgs), and period . TOI-257b orbits a bright (V = 7.612 mag) somewhat evolved late F-type star with M* = 1.390 ± 0.046 , R* = 1.888 ± 0.033 , Teff = 6075 ± 90 , and vsin i = 11.3 ± 0.5 km sâ1. Additionally, we find hints for a second non-transiting sub-Saturn mass planet on a âŒ71 day orbit using the radial velocity data. This system joins the ranks of a small number of exoplanet host stars (âŒ100) that have been characterized with asteroseismology. Warm sub-Saturns are rare in the known sample of exoplanets, and thus the discovery of TOI-257b is important in the context of future work studying the formation and migration history of similar planetary systems
Testing the chemical tagging technique with open clusters
Contexte. Les Ă©toiles naissent ensemble dans des nuages molĂ©culaires gĂ©ants. Si nous faisons lâhypothĂšse quâils Ă©taient Ă lâorigine chimiquement homogĂšnes et bien mĂ©langĂ©s, nous nous attendrions Ă ce que les Ă©toiles issues dâun mĂȘme nuage aient la mĂȘme composition chimique. La plupart des groupes dâĂ©toiles sont perturbĂ©s lors de leur Ă©volution dans la galaxie et lâinformation dynamique est perdue. Ainsi la seule possibilitĂ© que nous ayons de reconstruire lâhistoire de la formation stellaire est dâanalyser les abondances chimiques que lâon observe aujourdâhui.But. La technique de marquage chimique a pour but de retrouver les amas dâĂ©toiles dissociĂ©s en se basant uniquement sur leur composition chimique. Nous Ă©valuons la viabilitĂ© de cette technique pour retrouver les Ă©toiles qui sont nĂ©es dans un mĂȘme amas mais qui ne sont plus gravitationnellement liĂ©es.MĂ©thodes. Nous avons crĂ©Ă© une librairie de spectres stellaires de haute qualitĂ© afin de faciliter lâĂ©valuation des analyses spectrales. Nous avons dĂ©veloppĂ© notre propre outil dâanalyse spectrale, nommĂ©e iSpec, capable dâhomogĂ©nĂ©iser les spectres stellaires venant de tous types dâinstruments et de dĂ©river les paramĂštres atmosphĂ©riques et les abondances chimiques. Finalement, nous avons compilĂ© des spectres stellaires dâĂ©toiles de 32 amas ouverts, nous avons dĂ©rivĂ© de façon homogĂšne les paramĂštres atmosphĂ©riques et les abondances de 17 espĂšces, et nous avons utilisĂ© des algorithmes dâapprentissage automatique pour grouper les Ă©toiles en se basant sur leur composition chimique.RĂ©sultats. Nous avons trouvĂ© que les Ă©toiles Ă des Ă©tapes dâĂ©volution diffĂ©rentes ont des motifs chimiques distincts qui peuvent ĂȘtre dus Ă des effets NLTE,de diffusion atomique, de mĂ©lange et de corrĂ©lation Ă partir des dĂ©terminations de paramĂštres atmosphĂ©riques. Quand nous sĂ©parons les Ă©toiles suivant leur stade dâĂ©volution, nous observons quâil y a un important degrĂ© de recouvrement dans la dĂ©termination des signatures chimiques des amas ouverts. Ceci rend difficile de retrouver les groupes dâĂ©toiles nĂ©es ensemble en utilisant la technique de marquage chimique.Context. Stars are born together from giant molecular clouds and, if weassume that they were chemically homogeneous and well-mixed, we expect them toshare the same chemical composition.Most of the stellar aggregates are disrupted while orbiting the Galaxy and thedynamic information is lost, thus the only possibility to reconstruct the stellarformation history is to analyze the chemical abundances that we observe today.Aims. The chemical tagging technique aims to recover disrupted stellarclusters based merely on their chemical composition. We evaluate the viability of thistechnique to recover conatal stars that are not gravitationally bound anymore.Methods. We built a high-quality stellar spectra library to facilitate theassessment of spectral analyses. We developed our own spectral analysisframework, named iSpec, capable of homogeneizing stellar spectra and derivingatmospheric parameters/chemical abundances. Finally, we compiled stellar spectrafrom 32 Open Clusters, homogeneously derived atmospheric parameters and 17abundance species, and applied machine learning algorithms to group the starsbased on their chemical composition. This approach allows us to evaluate theviability of the chemical tagging technique.Results. We found that stars in different evolutionary stages havedistinguished chemical patterns may be due to NLTE effects, atomic diffusion, mixingand correlations from atmospheric parameter determinations. When separating starsper evolutionary stage, we observed a high degree of overlapping among OpenClusterâs chemical signatures, making it difficult to recover conatal aggregates byapplying the chemical tagging technique
Testing the chemical tagging technique with open clusters
Contexte. Les Ă©toiles naissent ensemble dans des nuages molĂ©culaires gĂ©ants. Si nous faisons lâhypothĂšse quâils Ă©taient Ă lâorigine chimiquement homogĂšnes et bien mĂ©langĂ©s, nous nous attendrions Ă ce que les Ă©toiles issues dâun mĂȘme nuage aient la mĂȘme composition chimique. La plupart des groupes dâĂ©toiles sont perturbĂ©s lors de leur Ă©volution dans la galaxie et lâinformation dynamique est perdue. Ainsi la seule possibilitĂ© que nous ayons de reconstruire lâhistoire de la formation stellaire est dâanalyser les abondances chimiques que lâon observe aujourdâhui.But. La technique de marquage chimique a pour but de retrouver les amas dâĂ©toiles dissociĂ©s en se basant uniquement sur leur composition chimique. Nous Ă©valuons la viabilitĂ© de cette technique pour retrouver les Ă©toiles qui sont nĂ©es dans un mĂȘme amas mais qui ne sont plus gravitationnellement liĂ©es.MĂ©thodes. Nous avons crĂ©Ă© une librairie de spectres stellaires de haute qualitĂ© afin de faciliter lâĂ©valuation des analyses spectrales. Nous avons dĂ©veloppĂ© notre propre outil dâanalyse spectrale, nommĂ©e iSpec, capable dâhomogĂ©nĂ©iser les spectres stellaires venant de tous types dâinstruments et de dĂ©river les paramĂštres atmosphĂ©riques et les abondances chimiques. Finalement, nous avons compilĂ© des spectres stellaires dâĂ©toiles de 32 amas ouverts, nous avons dĂ©rivĂ© de façon homogĂšne les paramĂštres atmosphĂ©riques et les abondances de 17 espĂšces, et nous avons utilisĂ© des algorithmes dâapprentissage automatique pour grouper les Ă©toiles en se basant sur leur composition chimique.RĂ©sultats. Nous avons trouvĂ© que les Ă©toiles Ă des Ă©tapes dâĂ©volution diffĂ©rentes ont des motifs chimiques distincts qui peuvent ĂȘtre dus Ă des effets NLTE,de diffusion atomique, de mĂ©lange et de corrĂ©lation Ă partir des dĂ©terminations de paramĂštres atmosphĂ©riques. Quand nous sĂ©parons les Ă©toiles suivant leur stade dâĂ©volution, nous observons quâil y a un important degrĂ© de recouvrement dans la dĂ©termination des signatures chimiques des amas ouverts. Ceci rend difficile de retrouver les groupes dâĂ©toiles nĂ©es ensemble en utilisant la technique de marquage chimique.Context. Stars are born together from giant molecular clouds and, if weassume that they were chemically homogeneous and well-mixed, we expect them toshare the same chemical composition.Most of the stellar aggregates are disrupted while orbiting the Galaxy and thedynamic information is lost, thus the only possibility to reconstruct the stellarformation history is to analyze the chemical abundances that we observe today.Aims. The chemical tagging technique aims to recover disrupted stellarclusters based merely on their chemical composition. We evaluate the viability of thistechnique to recover conatal stars that are not gravitationally bound anymore.Methods. We built a high-quality stellar spectra library to facilitate theassessment of spectral analyses. We developed our own spectral analysisframework, named iSpec, capable of homogeneizing stellar spectra and derivingatmospheric parameters/chemical abundances. Finally, we compiled stellar spectrafrom 32 Open Clusters, homogeneously derived atmospheric parameters and 17abundance species, and applied machine learning algorithms to group the starsbased on their chemical composition. This approach allows us to evaluate theviability of the chemical tagging technique.Results. We found that stars in different evolutionary stages havedistinguished chemical patterns may be due to NLTE effects, atomic diffusion, mixingand correlations from atmospheric parameter determinations. When separating starsper evolutionary stage, we observed a high degree of overlapping among OpenClusterâs chemical signatures, making it difficult to recover conatal aggregates byapplying the chemical tagging technique