Fig. 1: A snapshot from a fly by movie showing the distribution of SDSS stars compared to a model of the Milky Way disk. In blue are dwarf stars. Credit: The RAVE Collaboration
Fig. 2: Heliocentric spatial distribution of stars in the studied sample. Left and right panels respectively show results obtained using the standard LTE and new NLTE approach. Colours depict the stellar surface gravity as indicated in the plots.
Fig. 3: Distribution of stars in the studied sample as a function of metallicity (left) and distances. The shape of the distributions is clearly different, when more realistic models including NLTE (red) are used to determine the metallicities and distances of stars (compare to LTE black).
One of the major problems in modern astrophysics is to determine metallicities of stars and their kinematics. While various methods exist, most of them are not suitable for large stellar samples - these, however, are necessary in studies of Galactic structure. Scientists from MPA, Spain, and Sweden developed a novel method to accurately determine various stellar parameters as well as distances using a given stellar spectrum. Applying the new method to a sample of stars that are within 10 kpc of the Sun, they found significantly higher metallicities and shorter distances compared to previous results. This has major consequences for any study based on spectrophotometric distances to determine the stellar kinematics in our Milky Way.
Metallicities and the kinematics of low-mass stars are key parameters when studying the structure and evolution of our Galaxy. The most accurate way to determine metallicity is through spectroscopy, while the most precise way to get distances is astrometry. Parallaxes from the Hipparcos mission are available for many thousands of stars, but their accuracy rapidly deteriorates beyond 0.1 - 0.2 kpc away from the Sun. For large-scale stellar surveys, such as SDSS/SEGUE, APOGEE, and RAVE, which aim to observe the Galaxy from its innermost bulge regions to the outer halo at distances larger than 50 kpc (Fig. 1), scientists have to find another solution.
The only alternative is to use the information in a stellar spectrum, combining the luminosity data with photometry and stellar evolution models. A prerequisite for this approach are physically realistic models of radiative transfer in stellar atmospheres. Then researchers obtain accurate physical parameters of a star when applying them to observed spectra.
In the past decades, spectroscopy of low-mass stars relied on simplified models that were based on the assumptions of both local thermodynamic (LTE) and 1D hydrostatic equilibrium. Because the models are very widely used for the analysis of large datasets, including SDSS and RAVE, the principal question is whether such an 1D LTE approach is accurate.
Recently, scientists at MPA worked together with researchers in Spain and Sweden to devise a new method for computing stellar parameters and distances. This method includes new physical effects (such as non-LTE radiative transfer) in stellar models, which so far have not been included in a single calculation to date.
The scientists found that with the new method, the parameters obtained from the stellar spectra change: the metal-poor stars become warmer, more metal-rich and less evolved, i.e., their surface gravities increase, accompanied by a decrease in luminosity. As a consequence, the stars become fainter and this in turn leads to much shorter distances. For most of the stars, the distance thus decreases by 10-50%. That has a major impact on the volume distribution of stars (a comparison of previous with the new accurate results is shown in Fig. 2).
These improvements in the physics of radiative transfer models have a large impact on the distribution functions of stellar samples. In a magnitude-limited survey (such as RAVE), where more metal-rich unevolved stars dominate the nearby sample and metal-poor luminous giants are predominantly observed at larger distances, classical LTE analysis will systematically over-estimate distances, placing stars progressively further than they are. This would cause the unphysical smearing of the metallicity distribution function (Fig. 3, black area), as well as the stretching of the distance scale. Clearly, the effects will be more prominent in lower-metallicity stars.
Having verified the new method, the team is now ready to analyse much larger stellar samples, such as e.g., SDSS/SEGUE. These will provide radically new information about the properties of stellar populations in the Milky Way. In particular, they will shed new light on the controversy about the origin of our Galactic halo that is currently being debated.
Maria Bergemann (MPA), Aldo Serenelli (ICE/CSIC, Barcelona), Greg Ruchti (MPA/Lund Observatory, Sweden)
References
The only alternative is to use the information in a stellar spectrum, combining the luminosity data with photometry and stellar evolution models. A prerequisite for this approach are physically realistic models of radiative transfer in stellar atmospheres. Then researchers obtain accurate physical parameters of a star when applying them to observed spectra.
In the past decades, spectroscopy of low-mass stars relied on simplified models that were based on the assumptions of both local thermodynamic (LTE) and 1D hydrostatic equilibrium. Because the models are very widely used for the analysis of large datasets, including SDSS and RAVE, the principal question is whether such an 1D LTE approach is accurate.
Recently, scientists at MPA worked together with researchers in Spain and Sweden to devise a new method for computing stellar parameters and distances. This method includes new physical effects (such as non-LTE radiative transfer) in stellar models, which so far have not been included in a single calculation to date.
The scientists found that with the new method, the parameters obtained from the stellar spectra change: the metal-poor stars become warmer, more metal-rich and less evolved, i.e., their surface gravities increase, accompanied by a decrease in luminosity. As a consequence, the stars become fainter and this in turn leads to much shorter distances. For most of the stars, the distance thus decreases by 10-50%. That has a major impact on the volume distribution of stars (a comparison of previous with the new accurate results is shown in Fig. 2).
These improvements in the physics of radiative transfer models have a large impact on the distribution functions of stellar samples. In a magnitude-limited survey (such as RAVE), where more metal-rich unevolved stars dominate the nearby sample and metal-poor luminous giants are predominantly observed at larger distances, classical LTE analysis will systematically over-estimate distances, placing stars progressively further than they are. This would cause the unphysical smearing of the metallicity distribution function (Fig. 3, black area), as well as the stretching of the distance scale. Clearly, the effects will be more prominent in lower-metallicity stars.
Having verified the new method, the team is now ready to analyse much larger stellar samples, such as e.g., SDSS/SEGUE. These will provide radically new information about the properties of stellar populations in the Milky Way. In particular, they will shed new light on the controversy about the origin of our Galactic halo that is currently being debated.
Maria Bergemann (MPA), Aldo Serenelli (ICE/CSIC, Barcelona), Greg Ruchti (MPA/Lund Observatory, Sweden)
References
Aldo Serenelli, Maria Bergemann, Gregory Ruchti, Luca Casagrande, 2013, accepted for publication in MNRAS, arXiv:1212.4497
Maria Bergemann, Aldo Serenelli, Gregory Ruchti, 2013, proceedings IAUS289, Cambridge University Press
Gregory Ruchti, Maria Bergemann, Aldo Serenelli, Luca Casagrande, Karin Lind, MNRAS, 2012, doi:10.1093/mnras/sts319, arXiv:1210.7998
