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Using Metal-Poor Stars in the Inner Galaxy to Uncover the Ancient Milky Way

Published online by Cambridge University Press:  13 February 2024

Madeline Lucey*
Affiliation:
Department of Astronomy, The University of Texas at Austin, 2515 Speedway Boulevard, Austin, TX 78712, USA.
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Abstract

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The chemo-dynamics of the stellar populations in the Galactic Bulge inform and constrain the Milky Way’s formation and evolution. The metal-poor population is particularly important in light of cosmological simulations, which predict that some of the oldest stars in the Galaxy now reside in its center. The metal-poor bulge appears to consist of multiple stellar populations that require chemo-dynamical analyses to disentangle. In this paper, I describe the detailed chemo-dynamical study of the metal-poor stars in the inner Galaxy, named The COMBS Survey which uses VLT/FLAMES spectra of 350 metal-poor stars. I discuss the results and the implications for early Milky Way formation and chemical evolution. In addition, I preview results from an ongoing survey of carbon-enhanced metal-poor stars, which are thought to be solely enriched by the first generation of stars.

Type
Contributed Paper
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution and reproduction, provided the original article is properly cited.
Copyright
© The Author(s), 2024. Published by Cambridge University Press on behalf of International Astronomical Union

References

Adibekyan, V. Z., Sousa, S. G., Santos, N. C., et al. 2012, A&A, 545, A32 Google Scholar
Arentsen, A., et al. 2020, MNRAS, 491, L11 CrossRefGoogle Scholar
Arentsen, A., et al. 2021, MNRAS, 505, 1239 CrossRefGoogle Scholar
Battistini, C., Bensby, T., 2015, A&A, 577, A9 Google Scholar
Bensby, T., Feltzing, S., Oey, M. S. 2014, A&A, 562, A71 Google Scholar
Casagrande, L., Wolf, C., Mackey., A. D., et al.2019, MNRAS, 482, 2770Google Scholar
Da Costa, G. S., et al. 2019, MNRAS, 489, 5900 CrossRefGoogle Scholar
Debattista, V. P., Ness, M., Gonzalez, O. A., et al. 2017, MNRAS, 469, 1587 CrossRefGoogle Scholar
Duong, L., Asplund, M., Nataf, D. M., et al. 2019, MNRAS, 486, 3586 CrossRefGoogle Scholar
El-Badry, K., Bland-Hawthorn, J., Wetzel, A., et al. 2018, MNRAS, 480, 652 CrossRefGoogle Scholar
Frebel, A., Norris, J. E. 2015, ARA&A, 53, 631 Google Scholar
Heger., A., Fryer, C. L., Woosley, S. E., et al. 2003, ApJ, 591, 288 CrossRefGoogle Scholar
Hirano, S., Hosokawa, T., Yoshida, N., et al. 2014, ApJ, 781, 60 CrossRefGoogle Scholar
Howes, L. M., et al. 2015, Nature, 527, 484 CrossRefGoogle Scholar
Howes, L. M., et al. 2016, MNRAS, 460, 884 CrossRefGoogle Scholar
Lucey, M., et al. 2019, MNRAS, 488, 2283 CrossRefGoogle Scholar
Lucey, M., et al. 2021, MNRAS, 501, 5981 CrossRefGoogle Scholar
Lucey, M., et al. 2022, MNRAS, 509, 122 CrossRefGoogle Scholar
Meynet, G., Hirschim, R., Ekstrom, S., et al. 2010, A&A, 521, A30 Google Scholar
Nomoto, K., Kobayashim, C., Tominaga, N. 2013, ARA&A, 51, 457 Google Scholar
Roederer, I. U., Preston, G. W., Thompson, I. B., et al. 2014, AJ, 147, 136 CrossRefGoogle Scholar
Takahashi, K., Yoshida, T., Umeda, H. 2018, ApJ, 857, 111 CrossRefGoogle Scholar
Tumlinson, J. 2010, ApJ, 708, 1398 CrossRefGoogle Scholar
Van der Swaelmen, M., Hill, V., Primas, F., et al. 2013, A&A, 560, A44 Google Scholar
Yong, D., et al. 2013, ApJ, 762, 26 CrossRefGoogle Scholar
Zoccali, M., et al. 2014, A&A, 562, A66 Google Scholar