APOGEE-2 is a high-resolution, near-infrared spectroscopic survey observing similar to 3. x. 10(5) stars across the entire sky. It is the successor to APOGEE and is part of the Sloan Digital Sky Survey IV (SDSS-IV). APOGEE-2 is expanding on APOGEE's goals of addressing critical questions of stellar astrophysics, stellar populations, and Galactic chemodynamical evolution using (1) an enhanced set of target types and (2) a second spectrograph at Las Campanas Observatory in Chile. APOGEE-2 is targeting red giant branch and red clump stars, RR Lyrae, lowmass dwarf stars, young stellar objects, and numerous other Milky Way and Local Group sources across the entire sky from both hemispheres. In this paper, we describe the APOGEE-2 observational design, target selection catalogs and algorithms, and the targeting-related documentation included in the SDSS data releases.

The Magellanic System at a distance of 50 kpc from the Milky Way (MW), is a prime target in the study of stellar populations, star formation histories and galactic dynamics in low metallicity environments. The Large Magellanic Cloud (LMC) and Small Magellanic Cloud (SMC) have been observed in great depth, however there has been somewhat less interest in the Magellanic Bridge connecting the two and only more recently has the interest surged in the Magellanic Stream, which trails the Clouds between them and the MW. The Magellanic Bridge has a known younger stellar population dating back to Irwin’s observations (Irwin et al., 1990), only more recently has an older population been confirmed in the Bridge by Bagheri et al. (2013) and No¨el et al. (2013), while the Magellanic Stream is known to contain gas only with no stellar component. The estimated ages of the Bridge and Stream are 200 Myr (Bekki, 2007) and 2 Gyr (Diaz and Bekki, 2012) respectively, with the postulated Bridge formation from a tidal interaction between the Clouds. The formation of the Stream is less well understood with different models using varying assumptions and parameters such as Besla et al. (2012) and Nidever et al. (2010), including possibilities that the Clouds were historically bound or un-bound, and that the MW may or may not have been involved in the Stream formation. The work in this thesis makes use of different methods of removing the Galactic foreground population in the direction of the Magellanic Bridge and Stream to create cleaned catalogues of these regions. Various methods of analysis are applied to the cleaned catalogues in this work to identify stellar populations in the Bridge and Stream and density variations in the Bridge, including the production of CMDs and two-colour diagrams, fitting isochrones to the observational data, creating stellar density maps and studying spatial variations. This work contains the first published confirmation that the Bridge contains an older population of stars from public catalogues, which is supported with observations of the older population in recent deeper surveys, and confirmed with spectroscopic follow up observations. The young population has ages within the age of the Bridge ( 200 − 500 Myr) and are likely to have formed in-situ, in regions of high density gas closest to the SMC. The number of young blue objects in the Bridge tiles is greater towards the SMC and decreases towards the LMC. Populations identified here reach ages up to 3 Gyr are likely to have been drawn into the Bridge from the Clouds at formation. The key results from this work are that an older Bridge stellar population has been identified and confirmed, indicating that stars as well as gas were drawn into the Bridge at its creation. The fact that the younger population has the highest density away from the main concentration of hydrogen show that the gas within the Bridge has been displaced by ram pressure, most likely due to the Clouds moving through the Galactic halo. Less concrete results in this work reveal a puzzling populetion of objects within the Magellanic Stream, which could be stellar in nature and with follow up work, could be the first observation of Stream objects. This work contributes to our understanding of the interaction between the LMC and SMC via the Stellar populations between them.

Nos encontramos em uma localização vantajosa para o estudo da formação e evolução de galáxias espirais. Situados no disco da Via-Láctea, somos capazes de fazer observações detalhadas sobre as estrelas individuais que a compõem. Com o avanço tecnológico das últimas décadas, foi possível coletar um grande conjunto de informações, (e.g. composição química, cinemática, astrometria e parâmetros atmosféricos), com alta resolução para uma vasta parte do volume Galáctico. Com o objetivo de compreender melhor a nossa Galáxia, desenvolvemos uma ferramenta, chamada StarHorse, que estima parâmetros como distâncias, idades, massas e avermelhamento utilizando informação disponível em levantamentos espectroscópicos, fotométricos e astrométricos. O código StarHorse estima os parâmetros através de um método Bayesiano, que constrói uma distribuição de probabilidade a partir do cálculo de verossimilhança entre observações e modelos de evolução teórica e a partir de priores Galácticos bem conhecidos. Os parâmetros que o StarHorse estima são cruciais para estudos de arqueologia Galáctica. Com eles é possível investigar a estrutura, o histórico de formação estelar, a função de massa inicial, o mapa tridimensional da nossa Galáxia e também adicionar vínculos a modelos quemodinâmicos da Via Láctea Neste trabalho, focaremos na descrição e validação do método, testando sua aplicabilidade em levantamentos recentes de espectroscópica, astrometria e fotometria. Também disponibilizamos catálogos com distâncias e extinção para comunidade astronômica. As nossas distâncias e extinções se tornaram referência dentro da colaboração APOGEE e foram liberadas junto com o seu Data Release 14. Ademais, catálogos foram liberados para os surveys RAVE, Gaia-ESO e GALAH. Neste trabalho, exploramos os resultados do StarHorse, especialmente os resultados APOGEE, em um contexto amplo de arqueologia Galáctica. / We are in an advantageous position to study the formation and evolution of disk galaxies. By being inside the Milky Way, we are able to make detailed observations about the individual stars that compose it. With the technological revolution of the latest years, it has been possible to collect a massive set of information, (e.g. chemical composition, kinematics, astrometry, and atmospheric parameters), with high resolution for a large portion of the Galactic volume. With the goal to understand better our Galaxy, we developed a tool, called StarHorse, that can estimate distances, ages, masses, and extinction from the available spectroscopic, astrometric, and photometric information. StarHorse makes these estimates through a Bayesian method, that builds a probability distribution over the models by calculating a likelihood function between observation and stellar evolution models, and by using common knowledge about our Galaxy as priors. The parameters that StarHorse estimates are crucial to Galactic archaeology studies. With them, we can investigate the structure, the star formation history, the initial mass function, the three-dimensional dust map of our Galaxy, and provide constraints to chemodynamical models of the Milky Way. In this work, we focus on the description and validation of the method, testing its applicability in recent spectroscopic and astrometric surveys. We also make available catalogs with distances and extinctions to the astronomy community. Our distances and extinctions became a reference inside the APOGEE-team and were released as part of the SDSS Data Release 14. Moreover, we made available catalogs also to other spectroscopic surveys such as Gaia-ESO, RAVE, and GALAH. In this work, we also explore these results, especially for APOGEE, in a broad Galactic archaeology context.

Nos encontramos em uma localização vantajosa para o estudo da formação e evolução de galáxias espirais. Situados no disco da Via-Láctea, somos capazes de fazer observações detalhadas sobre as estrelas individuais que a compõem. Com o avanço tecnológico das últimas décadas, foi possível coletar um grande conjunto de informações, (e.g. composição química, cinemática, astrometria e parâmetros atmosféricos), com alta resolução para uma vasta parte do volume Galáctico. Com o objetivo de compreender melhor a nossa Galáxia, desenvolvemos uma ferramenta, chamada StarHorse, que estima parâmetros como distâncias, idades, massas e avermelhamento utilizando informação disponível em levantamentos espectroscópicos, fotométricos e astrométricos. O código StarHorse estima os parâmetros através de um método Bayesiano, que constrói uma distribuição de probabilidade a partir do cálculo de verossimilhança entre observações e modelos de evolução teórica e a partir de priores Galácticos bem conhecidos. Os parâmetros que o StarHorse estima são cruciais para estudos de arqueologia Galáctica. Com eles é possível investigar a estrutura, o histórico de formação estelar, a função de massa inicial, o mapa tridimensional da nossa Galáxia e também adicionar vínculos a modelos quemodinâmicos da Via Láctea Neste trabalho, focaremos na descrição e validação do método, testando sua aplicabilidade em levantamentos recentes de espectroscópica, astrometria e fotometria. Também disponibilizamos catálogos com distâncias e extinção para comunidade astronômica. As nossas distâncias e extinções se tornaram referência dentro da colaboração APOGEE e foram liberadas junto com o seu Data Release 14. Ademais, catálogos foram liberados para os surveys RAVE, Gaia-ESO e GALAH. Neste trabalho, exploramos os resultados do StarHorse, especialmente os resultados APOGEE, em um contexto amplo de arqueologia Galáctica. / We are in an advantageous position to study the formation and evolution of disk galaxies. By being inside the Milky Way, we are able to make detailed observations about the individual stars that compose it. With the technological revolution of the latest years, it has been possible to collect a massive set of information, (e.g. chemical composition, kinematics, astrometry, and atmospheric parameters), with high resolution for a large portion of the Galactic volume. With the goal to understand better our Galaxy, we developed a tool, called StarHorse, that can estimate distances, ages, masses, and extinction from the available spectroscopic, astrometric, and photometric information. StarHorse makes these estimates through a Bayesian method, that builds a probability distribution over the models by calculating a likelihood function between observation and stellar evolution models, and by using common knowledge about our Galaxy as priors. The parameters that StarHorse estimates are crucial to Galactic archaeology studies. With them, we can investigate the structure, the star formation history, the initial mass function, the three-dimensional dust map of our Galaxy, and provide constraints to chemodynamical models of the Milky Way. In this work, we focus on the description and validation of the method, testing its applicability in recent spectroscopic and astrometric surveys. We also make available catalogs with distances and extinctions to the astronomy community. Our distances and extinctions became a reference inside the APOGEE-team and were released as part of the SDSS Data Release 14. Moreover, we made available catalogs also to other spectroscopic surveys such as Gaia-ESO, RAVE, and GALAH. In this work, we also explore these results, especially for APOGEE, in a broad Galactic archaeology context.

The Apache Point Observatory Galactic Evolution Experiment (APOGEE), one of the programs in the Sloan Digital Sky Survey III (SDSS-III), has now completed its systematic, homogeneous spectroscopic survey sampling all major populations of the Milky Way. After a three-year observing campaign on the Sloan 2.5 m Telescope, APOGEE has collected a half million high-resolution (R similar to 22,500), high signal-to-noise ratio (>100), infrared (1.51-1.70 mu m) spectra for 146,000 stars, with time series information via repeat visits to most of these stars. This paper describes the motivations for the survey and its overall design-hardware, field placement, target selection, operations-and gives an overview of these aspects as well as the data reduction, analysis, and products. An index is also given to the complement of technical papers that describe various critical survey components in detail. Finally, we discuss the achieved survey performance and illustrate the variety of potential uses of the data products by way of a number of science demonstrations, which span from time series analysis of stellar spectral variations and radial velocity variations from stellar companions, to spatial maps of kinematics, metallicity, and abundance patterns across the Galaxy and as a function of age, to new views of the interstellar medium, the chemistry of star clusters, and the discovery of rare stellar species. As part of SDSS-III Data Release 12 and later releases, all of the APOGEE data products are publicly available.

Here, we present the results from our analysis of 6 yr of optical photometry taken by the Siding Spring Survey (SSS). This completes a search for periodic variable stars within the 30 000 deg(2) of the sky covered by the Catalina Surveys. The current analysis covers 81 million sources with declinations between -20 degrees. and -75 degrees. with median magnitudes in the range 11 < V < 19.5. We find approximately 34 000 new periodic variable stars in addition to the similar to 9000 RR Lyrae that we previously discovered in SSS data. This brings the total number of periodic variables identified in Catalina data to similar to 110 000. The new SSS periodic variable stars mainly consist of eclipsing binaries, RR Lyrae, LPVs, RS CVn stars, delta Scutis, and Anomalous Cepheids. By cross-matching these variable stars with those from prior surveys, we find that similar to 90 per cent of the sources are new discoveries and recover similar to 95 per cent of the known periodic variables in the survey region. For the known sources, we find excellent agreement between our catalogue and prior values of luminosity, period, and amplitude. However, we find many variable stars that had previously been misclassified. Examining the distribution of RR Lyrae, we find a population associated with the Large Magellanic Cloud (LMC) that extends more than 20 degrees from its centre confirming recent evidence for the existence of a very extended stellar halo in the LMC. By combining SSS photometry with Dark Energy Survey data, we identify additional LMC halo RR Lyrae, thus confirming the significance of the population.

Nos encontramos em uma localização vantajosa para o estudo da formação e evolução de galáxias espirais. Situados no disco da Via-Láctea, somos capazes de fazer observações detalhadas sobre as estrelas individuais que a compõem. Com o avanço tecnológico das últimas décadas, foi possível coletar um grande conjunto de informações, (e.g. composição química, cinemática, astrometria e parâmetros atmosféricos), com alta resolução para uma vasta parte do volume Galáctico. Com o objetivo de compreender melhor a nossa Galáxia, desenvolvemos uma ferramenta, chamada StarHorse, que estima parâmetros como distâncias, idades, massas e avermelhamento utilizando informação disponível em levantamentos espectroscópicos, fotométricos e astrométricos. O código StarHorse estima os parâmetros através de um método Bayesiano, que constrói uma distribuição de probabilidade a partir do cálculo de verossimilhança entre observações e modelos de evolução teórica e a partir de priores Galácticos bem conhecidos. Os parâmetros que o StarHorse estima são cruciais para estudos de arqueologia Galáctica. Com eles é possível investigar a estrutura, o histórico de formação estelar, a função de massa inicial, o mapa tridimensional da nossa Galáxia e também adicionar vínculos a modelos quemodinâmicos da Via Láctea Neste trabalho, focaremos na descrição e validação do método, testando sua aplicabilidade em levantamentos recentes de espectroscópica, astrometria e fotometria. Também disponibilizamos catálogos com distâncias e extinção para comunidade astronômica. As nossas distâncias e extinções se tornaram referência dentro da colaboração APOGEE e foram liberadas junto com o seu Data Release 14. Ademais, catálogos foram liberados para os surveys RAVE, Gaia-ESO e GALAH. Neste trabalho, exploramos os resultados do StarHorse, especialmente os resultados APOGEE, em um contexto amplo de arqueologia Galáctica. / We are in an advantageous position to study the formation and evolution of disk galaxies. By being inside the Milky Way, we are able to make detailed observations about the individual stars that compose it. With the technological revolution of the latest years, it has been possible to collect a massive set of information, (e.g. chemical composition, kinematics, astrometry, and atmospheric parameters), with high resolution for a large portion of the Galactic volume. With the goal to understand better our Galaxy, we developed a tool, called StarHorse, that can estimate distances, ages, masses, and extinction from the available spectroscopic, astrometric, and photometric information. StarHorse makes these estimates through a Bayesian method, that builds a probability distribution over the models by calculating a likelihood function between observation and stellar evolution models, and by using common knowledge about our Galaxy as priors. The parameters that StarHorse estimates are crucial to Galactic archaeology studies. With them, we can investigate the structure, the star formation history, the initial mass function, the three-dimensional dust map of our Galaxy, and provide constraints to chemodynamical models of the Milky Way. In this work, we focus on the description and validation of the method, testing its applicability in recent spectroscopic and astrometric surveys. We also make available catalogs with distances and extinctions to the astronomy community. Our distances and extinctions became a reference inside the APOGEE-team and were released as part of the SDSS Data Release 14. Moreover, we made available catalogs also to other spectroscopic surveys such as Gaia-ESO, RAVE, and GALAH. In this work, we also explore these results, especially for APOGEE, in a broad Galactic archaeology context.