3D Spectral Synthesis for Large-Scale Stellar Surveys, Asteroseismology and Galactic Archaeology
Abstract
Much of our understanding of our Galaxy's formation and evolution relies on accurate knowledge of stellar abundances of the chemical elements. The general amount of metals, for example, tells us the number of stellar generations between the Big Bang and the formation of a particular star; Particular abundance patterns can reveal the enrichment of star-forming clouds by nearby super novae and stellar winds, or the interior dynamics of stars. The nascent field of Galactic archaeology puts the strongest demands on our knowledge of stellar abundances. This is the pursuit of the history of the Galaxy, including its star formation history, galactic mergers, and coupling to the growth history of our central black hole. Such studies are based on the idea that distinct populations of stars in our Galaxy have kinematic and chemical fingerprints, that uniquely identifies them. We live in an unprecedented era for Galactic Archaeology. For the first time, representative large scale surveys for millions (and even billions) of stars allow a precise probing of the Milky Way structure and evolution. In this respect, ESA's astrometry mission, Gaia, is currently revolutionizing our knowledge of the structure and kinematics of the Milky Way. Gaia has revealed populations of stars with common origins, such as merger events or a shared birth place --- populations that now, after thousands of orbits, are scattered throughout the Galaxy. A special population being searched for, is that of our stellar siblings, born out of the same giant molecular cloud as the Sun. Accurate abundances are crucial for discriminating between such populations, but the accuracy is currently limited by the 1D stellar atmosphere models they are based on. These models employ simplistic prescriptions for convection that has free parameters, adjusted to reproduce the depths and widths of spectral lines, compromising the reliability of abundances based on 1D atmospheres. Furthermore, the assumptions behind 1D prescriptions for convection are known to break down in the exact layers where the light we see from stars, form. In stark contrast, realistic 3D, hydrodynamic, atmosphere simulations, exhibit convection as an emergent property, with large temperature fluctuations and velocities. At the surface, the temperatures and velocities are correlated in a way that produce blue-shifted, slightly C-shaped spectral lines, in robust agreement with observed stellar spectra. With such realistic synthetic lines, blends by other weaker lines become obvious and can be accounted for, whereas in 1D analysis such blends go unnoticed. Missed blends systematically increase inferred abundances. 3D convection simulations are computationally expensive, however, and there is no trivial way of interpolating between simulations in a grid, as can be easily done in grids of 1D atmosphere models. This means a single simulation is both expensive, and also only relevant for the few stars that are similar enough. This project aims at alleviating this obstacle, and make grids of 3D simulations as useful as grids of 1D atmosphere models, but with much higher fidelity and realism. This work will match the wealth of high-quality spectroscopic, ground-based surveys, with an equally high-quality analysis of the observations to produce robust and reliable abundances and surface-temperatures and -gravities. This will apply to major surveys like RAVE, GALAH and SDSS/APOGEE, as well as the targeted SAGA and APOKASC surveys, that support NASA's planet-hunting and asteroseismology mission TESS, and the past Kepler/K2 missions. Combining this with the now ubiquitous Gaia parallaxes will provide unprecedentedly strong constraints on all fundamental parameters of stars, advancing our understanding of stellar structure, the Milky Way's evolution and our place in it.
- Publication:
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NASA ATP Proposal
- Pub Date:
- 2019
- Bibcode:
- 2019atp..prop..217T