CAREER: Building the Merger Tree of the Milky Way with Machine Learning

职业：用机器学习构建银河系的合并树

• 批准号: 2337864
• 负责人: Lina Necib
• 金额: $ 83.51万
• 依托单位: Massachusetts Institute of Technology
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2024
• 资助国家: 美国
• 起止时间: 2024-07-01 至 2029-06-30
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2337864&HistoricalAwards=false
• 关键词: CAREER; Building; Merger; Tree; Milky; CAREER; Building; Merger; Tree; Milky

Principal Investigator (PI) Necib and her team will search for stellar debris in our galaxy. These stellar structures were formed when galaxies collided with the Milky Way. The team will use artificial intelligence to develop an automated process to complete the difficult task of analyzing observations of more than 1.5 billion stars from the European Space Agency (ESA) mission Gaia. The team will compare their data to simulations to chart the history of the formation of the Milky Way. The PI is committed to broadening participation. Building on her successful Tunisian Podcast Ga3da Falakia, the PI will work with her graduate students to produce a series of podcasts in a range of languages. The PI will also host a series of Gaia Hackathons for undergraduate and high school students. The PI aims to build the merger tree of the Milky Way using both supervised and unsupervised machine learning techniques. The PI will build a clustering algorithm that integrates measurement uncertainties and scales with the increase in data size, as well as an interpretable equivariant graph neural network that predicts the merging times and infall masses of mergers into the Milky Way, trained on Illustris-TNG50, and applied to Gaia DR3/4 data.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

首席调查员（PI）Necib和她的团队将在我们的银河系中寻找恒星碎片。当星系与银河系相撞时，这些恒星结构形成。该团队将使用人工智能来开发自动化过程，以完成分析欧洲航天局（ESA）Mission Gaia的15亿颗恒星观察的艰巨任务。该团队将将他们的数据与模拟进行比较，以绘制银河系形成的历史。 PI致力于扩大参与。 PI以成功的突尼斯播客Ga3da Falakia为基础，将与她的研究生合作，以各种语言制作一系列播客。 PI还将为本科生和高中生举办一系列Gaia Hackathon。 PI旨在使用监督和无监督的机器学习技术来建造银河系的合并树。 PI将构建一种聚类算法，该算法将测量不确定性和缩放范围与数据大小的增加以及可解释的模棱两可的图形神经网络相结合在一起，该图表可预测合并的时间和群体的合并质量，并通过对GAIA DR3/4数据进行了培训。利用基金会的知识分子和更广泛的影响审查标准。