Search

Context. The Gaia-ESO Survey (GES) is a large public spectroscopic survey that has collected, over a period of six years, spectra of similar to 10(5) stars. This survey provides not only the reduced spectra, but also the stellar parameters and abundances resulting from the analysis of the spectra.Aims. The GES dataflow is organised in 19 working groups. Working group 13 (WG13) is responsible for the spectral analysis of the hottest stars (O, B, and A type, with a formal cutoff of T-eff > 7000 K) that were observed as part of GES. We present the procedures and techniques that have been applied to the reduced spectra in order to determine the stellar parameters and abundances of these stars.Methods. The procedure used was similar to that of other working groups in GES. A number of groups (called Nodes) each independently analyse the spectra via state-of-the-art techniques and codes. Specific for the analysis in WG13 was the large temperature range covered (T-eff approximate to 7000-50 000 K), requiring the use of different analysis codes. Most Nodes could therefore only handle part of the data. Quality checks were applied to the results of these Nodes by comparing them to benchmark stars, and by comparing them to one another. For each star the Node values were then homogenised into a single result: the recommended parameters and abundances.Results. Eight Nodes each analysed part of the data. In total 17 693 spectra of 6462 stars were analysed, most of them in 37 open star clusters. The homogenisation led to stellar parameters for 5584 stars. Abundances were determined for a more limited number of stars. The elements studied are He, C, N, O, Ne, Mg, Al, Si, and Sc. Abundances for at least one of these elements were determined for 292 stars.Conclusions. The hot-star data analysed here, as well as the GES data in general, will be of considerable use in future studies of stellar evolution and open clusters.

Context. The Gaia-ESO Survey (GES) is a large public spectroscopic survey that has collected, over a period of six years, spectra of similar to 10(5) stars. This survey provides not only the reduced spectra, but also the stellar parameters and abundances resulting from the analysis of the spectra.Aims. The GES dataflow is organised in 19 working groups. Working group 13 (WG13) is responsible for the spectral analysis of the hottest stars (O, B, and A type, with a formal cutoff of T-eff > 7000 K) that were observed as part of GES. We present the procedures and techniques that have been applied to the reduced spectra in order to determine the stellar parameters and abundances of these stars.Methods. The procedure used was similar to that of other working groups in GES. A number of groups (called Nodes) each independently analyse the spectra via state-of-the-art techniques and codes. Specific for the analysis in WG13 was the large temperature range covered (T-eff approximate to 7000-50 000 K), requiring the use of different analysis codes. Most Nodes could therefore only handle part of the data. Quality checks were applied to the results of these Nodes by comparing them to benchmark stars, and by comparing them to one another. For each star the Node values were then homogenised into a single result: the recommended parameters and abundances.Results. Eight Nodes each analysed part of the data. In total 17 693 spectra of 6462 stars were analysed, most of them in 37 open star clusters. The homogenisation led to stellar parameters for 5584 stars. Abundances were determined for a more limited number of stars. The elements studied are He, C, N, O, Ne, Mg, Al, Si, and Sc. Abundances for at least one of these elements were determined for 292 stars.Conclusions. The hot-star data analysed here, as well as the GES data in general, will be of considerable use in future studies of stellar evolution and open clusters.

© ESO 2021. Artículo firmado por 27 autores. We thank Nikola Vitas and Andrew McWilliam for pedagogical discussions on the nature of HFS splitting. We are grateful to our referee Vardan Adibekyan for insightful feedback that helped to improve the quality of this manuscript. CARMENES is an instrument at the Centro Astronómico Hispano-Alemán (CAHA) at Calar Alto (Almeria, Spain), operated jointly by the Junta de Andalucía and the Instituto de Astrofísica de Andalucía (CSIC). CARMENES was funded by the Max-Planck-Gesellschaft (MPG), the Consejo Superior de Investigaciones Científicas (CSIC), the Ministerio de Economía y Competitividad (MINECO) and the European Regional Development Fund (ERDF) through projects FICTS-2011-02, ICTS-2017-07-CAHA-4, and CAHA16-CE-3978, and the members of the CARMENES Consortium (Max-Planck-Institut fur Astronomie, Instituto de Astrofísica de Andalucía, Landessternwarte Konigstuhl, Institut de Ciencies de l'Espai, Institut fur Astrophysik Gottingen, Universidad Complutense de Madrid, Thuringer Landessternwarte Tautenburg, Instituto de Astrofísica de Canarias, Hamburger Sternwarte, Centro de Astrobiología and Centro Astronómico Hispano-Alemán), with additional contributions by the MINECO, the Deutsche Forschungsgemeinschaft (DFG) through the Major Research Instrumentation Programme and Research Unit FOR2544 "Blue Planets around Red Stars", the Klaus Tschira Stiftung, the states of Baden-Wurttemberg and Niedersachsen, and by the Junta de Andalucía. We acknowledge financial support from the Agencia Estatal de Investigación of the Ministerio de Ciencia, Innovación y Universidades and the ERDF through projects PID2019-109522GB-C5[1:4]/AEI/10.13039/501100011033 and the Centre of Excellence "Severo Ochoa" and "María de Maeztu" awards to the Instituto de Astrofísica de Canarias (CEX2019-000920-S), Instituto de Astrofísica de Andalucía (SEV-2017-0709), and Centro de Astrobiología (MDM-2017-0737), the Generalitat de Catalunya/CERCA programme, the Aust, Context. M-dwarf spectra are complex and notoriously difficult to model, posing challenges to understanding their photospheric properties and compositions in depth. Vanadium (V) is an iron-group element whose abundance supposedly closely tracks that of iron, but has origins that are not completely understood. Aims. Our aim is to characterize a series of neutral vanadium atomic absorption lines in the 800-910 nm wavelength region of high signal-to-noise, high-resolution, telluric-corrected M-dwarf spectra from the CARMENES survey. Many of these lines are prominent and exhibit a distinctive broad and flat-bottom shape, which is a result of hyperfine structure (HFS). We investigate the potential and implications of these HFS split lines for abundance analysis of cool stars. Methods. With standard spectral synthesis routines, as provided by the spectroscopy software iSpec and the latest atomic data (including HFS) available from the VALD3 database, we modeled these striking line profiles. We used them to measure V abundances of cool dwarfs. Results. We determined V abundances for 135 early M dwarfs (M0.0 V to M3.5 V) in the CARMENES guaranteed time observations sample. They exhibit a [V/Fe]-[Fe/H] trend consistent with that derived from nearby FG dwarfs. The tight (+/- 0.1 dex) correlation between [V/H] and [Fe/H] suggests the potential application of V as an alternative metallicity indicator in M dwarfs. We also show hints that neglecting to model HFS could partially explain the temperature correlation in V abundance measurements observed in previous studies of samples involving dwarf stars with T-eff less than or similar to 5300 K. Conclusions. Our work suggests that HFS can impact certain absorption lines in cool photospheres more severely than in Sun-like ones. Therefore, we advocate that HFS should be carefully treated in abundance studies in stars cooler than similar to 5000 K. On the other hand, strong HFS split lines in high-resolution spectra present an opportu, Ministerio de Economía y Competitividad (MINECO)/FEDER, Ministerio de Ciencia e Innovación (MICINN)/FEDER, Centro de Excelencia Severo Ochoa, Unidad de Excelencia María de Maeztu, Max-Planck-Gesellschaft (MPG) Max Planck Society, Consejo Superior de Investigaciones Científicas (CSIC), European Regional Development Fund (ERDF) European Commission, Centro de Astrobiología, Generalitat de Catalunya/CERCA programme, Austrian Science Fund, DFG German Research Foundation (DFG) European Commission, NASA National Aeronautics & Space Administration (NASA), Depto. de Física de la Tierra y Astrofísica, Fac. de Ciencias Físicas, TRUE, pub

The consensus in the field is that we have a pretty good understanding of the physics behind star formation and evolution. So far, the models that have been created characterize the different collections of stars in our Milky Way galaxy with decent accuracy, and they have allowed for humanity to obtain insights into how our universe evolved. However, the author believes that our current techniques and theory that go into such models might be biased or slightly flawed. A simulated model of the Milky Way is used to generate virtual stars whose properties are known. These stars are then analysed using the current most up-to-date techniques, and the obtained values for the various stellar properties are compared with the already known values. Non-trivial evidence is obtained that we are indeed systematically over-/underestimating the values of these parameters by almost 1 standard deviation in most cases. Some possible ideas about why this might be the case are explored within this document., Astronomi är ett vetenskapsområde som får allt mer uppmärksamhet varje år, allteftersom vi blickar mot stjärnorna för framtida utforskning och kolonisation. Det är därför väldigt viktigt att mänskligheten fortsätter att arbeta med att förstå hur universum fungerar när det kommer till avlägsna stjärnor. Vi lär oss om detta genom att, bland annat, skapa modeller och simuleringar av vår galax baserade på vad vi vet från observationer och teorier. Det här hjälper oss att förbättra vår dataanalys. Men, vi tror att våra nuvarande tekniker och teorier som krävs för att skapa sådana modeller för att analysera data kan vara vinklade eller bristfälliga. Det skulle vara väldigt problematiskt om det är så, och det är därför viktigt att ta ett steg tillbaka och reflektera över våra nuvarande metoder för att försäkra oss om att de är tillräckligt noggranna. I det här projektet kommer vi därför att testa de här teknikerna och kortfattat förklara de möjliga orsakerna till alla funna systematiska avvikelser. Hur tänker vi testa våra tekniker? Vi skapar en ”simulerad galax”, liknande vår egen Vintergata, med samlingar av virtuella stjärnor fördelade i galaxen enligt nuvarande teorier. Vi samlar sedan in data om de här stjärnorna, egenskaper som vanligtvis mäts i undersökningar (som temperatur, ytgravitation, hur mycket de lyser i olika delar av det elektromagnetiska spektrumet, etcetera). Sen analyserar vi varje stjärna med de senaste analysteknikerna för att beräkna vilka egenskaper som passar den bäst, baserat på de ursprungliga villkoren. Eftersom vi vet allting om de simulerade stjärnorna, kan vi jämföra deras egenskapers faktiska värden med de vi har beräknat. Skillnader mellan de observerade och beräknade värdena informerar oss om systematiska fel i de teknikerna som vi har använt. Vi upprepar processen för olika antaganden om fördelningen av stjärnor för att försäkra oss om att vi inte själva har introducerat ett systematiskt fel. Det visar sig att de flesta huvudseriestjärnor

The consensus in the field is that we have a pretty good understanding of the physics behind star formation and evolution. So far, the models that have been created characterize the different collections of stars in our Milky Way galaxy with decent accuracy, and they have allowed for humanity to obtain insights into how our universe evolved. However, the author believes that our current techniques and theory that go into such models might be biased or slightly flawed. A simulated model of the Milky Way is used to generate virtual stars whose properties are known. These stars are then analysed using the current most up-to-date techniques, and the obtained values for the various stellar properties are compared with the already known values. Non-trivial evidence is obtained that we are indeed systematically over-/underestimating the values of these parameters by almost 1 standard deviation in most cases. Some possible ideas about why this might be the case are explored within this document., Astronomi är ett vetenskapsområde som får allt mer uppmärksamhet varje år, allteftersom vi blickar mot stjärnorna för framtida utforskning och kolonisation. Det är därför väldigt viktigt att mänskligheten fortsätter att arbeta med att förstå hur universum fungerar när det kommer till avlägsna stjärnor. Vi lär oss om detta genom att, bland annat, skapa modeller och simuleringar av vår galax baserade på vad vi vet från observationer och teorier. Det här hjälper oss att förbättra vår dataanalys. Men, vi tror att våra nuvarande tekniker och teorier som krävs för att skapa sådana modeller för att analysera data kan vara vinklade eller bristfälliga. Det skulle vara väldigt problematiskt om det är så, och det är därför viktigt att ta ett steg tillbaka och reflektera över våra nuvarande metoder för att försäkra oss om att de är tillräckligt noggranna. I det här projektet kommer vi därför att testa de här teknikerna och kortfattat förklara de möjliga orsakerna till alla funna systematiska avvikelser. Hur tänker vi testa våra tekniker? Vi skapar en ”simulerad galax”, liknande vår egen Vintergata, med samlingar av virtuella stjärnor fördelade i galaxen enligt nuvarande teorier. Vi samlar sedan in data om de här stjärnorna, egenskaper som vanligtvis mäts i undersökningar (som temperatur, ytgravitation, hur mycket de lyser i olika delar av det elektromagnetiska spektrumet, etcetera). Sen analyserar vi varje stjärna med de senaste analysteknikerna för att beräkna vilka egenskaper som passar den bäst, baserat på de ursprungliga villkoren. Eftersom vi vet allting om de simulerade stjärnorna, kan vi jämföra deras egenskapers faktiska värden med de vi har beräknat. Skillnader mellan de observerade och beräknade värdena informerar oss om systematiska fel i de teknikerna som vi har använt. Vi upprepar processen för olika antaganden om fördelningen av stjärnor för att försäkra oss om att vi inte själva har introducerat ett systematiskt fel. Det visar sig att de flesta huvudseriestjärnor

More than 80% of the stars in the Universe are expected to have initial masses below eight to ten times the mass of our sun. These low mass stars, including our sun, become cool red giants during one of the final evolutionary stages of their life: the Asymptotic Giant Branch (or AGB) phase. AGB stars are among the main producers of carbon and heavy (s-process) elements in the Universe. These elements are synthesized inside the star and mixed to the stellar atmosphere where stellar winds are responsible for the loss of more than 50% of the stellar mass, hence, AGB stars are strong polluters of the interstellar medium. The ejected material can clump together into dusty particles which may serve as ingredients for the birth of new stars and planets. When most of the AGB stellar envelope is lost, the AGB star stops releasing nuclear energy from interior processes and swaps its giant face for a planetary nebulae look, whereafter it fades away as a white dwarf.The dredge-up of carbon and s-process elements into the AGB atmosphere causes an important chemical anomaly among them: initial oxygen-rich stars (M stars) are transformed into carbon-rich stars (C stars). As a consequence, a group of oxygen-rich AGB stars exists which makes the transition between M and C stars. These transition stars are classified as S.Although AGB stars are identified as producers of heavy elements, their nucleosynthesis and mixing processes are weakly constrained due to large uncertainties on their estimated temperature, gravity and chemical composition. Stronger constraints on the atmospheric parameter space, hence interior processes, of AGB stars can be obtained by investigating the atmosphere of S stars. Since they are transition objects on the AGB, they trace the rise of the s-process. S stars are less numerous than C stars, but their optical spectra are brighter making it easier to identify atomic and molecular lines. Therefore, S stars belong to the most interesting objects alo, Doctorat en Sciences, info:eu-repo/semantics/nonPublished