Up close and personal: galaxy evolution at high resolution in the Milky Way

近距离观察：银河系中高分辨率的星系演化

• 批准号: RGPIN-2020-04712
• 负责人: Bovy, Jo
• 金额: $ 4.44万
• 依托单位: University of Toronto
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2022
• 资助国家: 加拿大
• 起止时间: 2022-01-01 至 2023-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=743961
• 关键词: Up; close; personal; galaxy; evolution

Ever since the dawn of galaxy-formation studies, the Milky Way has been one of the best places in the Universe to learn about the physics of galaxy evolution. This is especially true today, when new space- and ground-based surveys are providing positions, velocities, and basic stellar parameters for a billion stars and detailed chemical abundances and ages for millions of stars. These new large data sets represent an enormous opportunity to learn about the detailed evolutionary history of the Milky Way, but analyzing the data and deducing the important elements of galaxy evolution from this presents a novel set of challenges as well. The work in this proposal will make the next leap in our understanding of the evolution of disk galaxies like the Milky Way, by analysis and modeling of the astrometric Gaia data and spectroscopic SDSS data. This proposal will focus on the following areas. Firstly, next-generation photometric and spectroscopic data analysis using machine learning: we will develop new machine-learning and in particular artificial-intelligence methods to determine precise stellar parameters, abundances, distances, and ages for the SDSS-V data set of millions of high-resolution stellar spectra, the TESS data set of lightcurves of millions of stars, and the billion-star spectrophotometric data set from Gaia. This will provide a large, high-quality data sample. Secondly, we will use this new data set to study the detailed structure, dynamics, and evolution of the currently-sparsely-sampled central bar/bulge region of the Milky Way. Finally, we will investigate the vertical structure of the Milky Way's disk near the Sun and towards the outer edge of the disk with the new data and with simulations to understand the origin of perturbations in the vertical structure that we and other groups have recently found and how these perturbations affect the recent evolution of the Milky Way. The combination of these investigations will provide new insights into the evolution of the Milky Way, from its earliest beginnings until the present day.

自从星系形成研究开始以来，银河系一直是宇宙中了解星系演化物理学的最佳地点之一。今天尤其如此，新的空间和地面调查提供了10亿颗恒星的位置、速度和基本恒星参数，以及数百万颗恒星的详细化学丰度和年龄。这些新的大型数据集代表了了解银河系详细演化历史的巨大机会，但分析数据并从中推断星系演化的重要元素也带来了一系列新的挑战。这项提案中的工作将使我们对银河系等盘状星系演化的理解发生下一次飞跃，通过分析和建模天体测量盖亚数据和光谱SDSS数据。这项建议将侧重于以下领域。首先，使用机器学习的下一代光度和光谱数据分析：我们将开发新的机器学习，特别是人工智能方法，以确定数百万高分辨率恒星光谱的SDSS-V数据集，数百万恒星光变曲线的TESS数据集以及来自盖亚的十亿星分光光度数据集的精确恒星参数，丰度，距离和年龄。这将提供大量高质量的数据样本。其次，我们将使用这个新的数据集来研究银河系目前稀疏采样的中央棒/凸起区域的详细结构，动力学和演化。 最后，我们将调查银河系的磁盘在太阳附近的垂直结构，并对磁盘的外边缘与新的数据和模拟，以了解我们和其他团体最近发现的垂直结构中的扰动的起源，以及这些扰动如何影响银河系最近的演变。这些研究的结合将为银河系从最早的起源到现在的演变提供新的见解。