RUI: Harnessing Rubin Observatory Data to Prepare Tomorrow's STEM Leaders: Galaxy Evolution and Large Scale Structure

星系在宇宙中并不是均匀分布的。相反，它们被发现高度集中在称为星团的区域，并沿着连接星团的巨大细丝扩散。这种大规模的结构被称为宇宙网。众所周知，大质量的红色星系通常存在于密集的星系团中，避开了它们之间的细丝和稀疏的空隙。因此，星系的特性与它所处的环境有关。该项目支持的加州州立理工大学的本科生将使用鲁宾天文台的新数据来研究星系的属性，如颜色、大小、形状和方向，如何依赖于它们的环境。星系特性与其宿主环境之间的相关性将有助于推断宇宙网是如何以及何时形成的，以及星系的演化是否取决于其环境。该项目将为来自STEM中代表性不足群体的本科生提供有价值的研究培训。提出建议的团队将使用光谱观测以及鲁宾天文台的预览和早期光度数据来测试各种形成和进化场景，这些场景将星系团与更广泛的环境联系起来。具体来说，该团队将描述和比较星系团核心、外围和细丝中的星系的特性。主要成果包括：(1)对已知超星团中形成恒星的星系进行有效的光谱跟踪，这将提供光度与光谱恒星年龄、颜色和红移的比较，并将为计算星系落秋时间提供可靠的运动学数据；(2)测量灯丝星系、最亮的星团星系（BCG）和灯丝本身之间的排列，以检验星系沿灯丝落入星团核心的重要性；(3)整个大尺度结构和星团核心的星系恒星群测量；(4)在聚类图像中注入簇内光（ICL），以测试ICL恢复方法。恒星的形成速率和落入时间将被计算出来，并用于确定有多少星系通过细丝落入可以合理地促进BCG和ICL的形成。一旦鲁宾天文台上线并获得深度图像，ICL恢复方法将为研究ICL做准备。进行研究的本科生将以包容性的意图招募，并在技术方法以及多样性，公平和包容性教育方面进行培训。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

Galaxies are not found evenly distributed throughout the universe. Rather, they are found to be highly concentrated in regions called clusters and spread along vast filaments that connect the clusters. This large-scale structure is referred to as the cosmic web. It is known that large, massive, red galaxies are generally found in the dense clusters, avoiding the filaments and sparse voids in between. The properties of a galaxy are thus correlated with the environment in which it lives. Undergraduate students at California Polytechnic State University supported by this project will use new data from the Rubin Observatory to study how the properties of galaxies, such as color, size, shape, and orientation, depend on their environment. Correlations between the galaxy properties and their host environment will help deduce how and when the cosmic web formed, and whether the evolution of a galaxy depends on its environment. This project will provide valuable research training to undergraduate students from underrepresented groups in STEM. The proposing team will use spectroscopic observations as well as preview and early photometric data from the Rubin Observatory to test various formation and evolutionary scenarios that connect cluster galaxies to their broader environment. Specifically, the team will characterize and compare the properties of galaxies in cluster cores, outskirts and filaments. The main deliverables include: (1) Efficient spectral follow-up of star-forming galaxies in known supercluster filaments, which will provide a comparison of photometric versus spectroscopic stellar ages, colors and redshifts, and will also provide reliable kinematic data for calculating galaxy in-fall times; (2) A measurement of alignments between filament galaxies, the brightest cluster galaxy (BCG), and the filament itself in order to test the importance of galaxy in-fall along filaments into the cluster core; (3) The measurement of stellar populations of galaxies throughout the large-scale structures and cluster cores; and (4) The injection of intra-cluster light (ICL) into cluster images in order to test ICL recovery methods. Star formation rates and in-fall times will be calculated and used to determine how much galaxy in-fall through filaments can plausibly contribute to the buildup of the BCG and ICL. The ICL recovery methods will prepare the group for studying ICL once the Rubin Observatory comes online and deep images are available. The undergraduate students who perform the research will be recruited with inclusive intent and trained in technical methods alongside diversity, equity and inclusivity education.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.