Unified Modeling of Galaxy Populations in Clusters

星系团中星系群的统一建模

• 批准号: 1613674
• 负责人: Thomas Quinn
• 金额: $ 2万
• 依托单位: University of Washington
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-09-01 至 2019-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1613674&HistoricalAwards=false
• 关键词: Unified; Modeling; Galaxy; Populations; Clusters

Understanding the history of galaxy and cluster formation fundamentally affects our knowledgeof the Universe as a whole, and sets the context for our place within the Universe. This project will use Blue Waters to model the formation and evolution of a population of galaxies in a Coma-sized galaxy cluster, including their contribution to and interaction with the Intra-Cluster Medium (ICM). Modeling galaxies and the ICM in galaxy clusters is a formidable challenge. The morphology of the galaxies, and the energy and metal content of the gas is ultimately controlled by star formation processes that happen on molecular cloud scales of less than a million solar masses. On the other hand, total cluster masses exceed 10^15 solar masses; hence a dynamic range in mass of over a billion is necessary for consistently modeling galaxies within this context. The investigation of such issues is appealing to many interested in science and even in society at large. In particular, the results of the project will be used in a program that will introduce the use of computer simulations in astrophysics to science pre-majors, in the hope of ultimately attracting underrepresented students into a STEM major.Several advancements have now enabled the modeling of these systems. First is the availabilityof supercomputers like Blue Waters that can sustained petaflop calculations on real worldproblems. Second is the improvement of hydrodynamic modeling in Lagrangian codes. These improvementsinclude better modeling of multiphase medium and the resulting instabilities, more accuratehandling of high Mach number shocks, and better modeling of the subgrid physics includinggrowth and feedback from supermassive black holes. Finally these algorithm improvements havebeen implemented in codes that can scale to a large fraction of Blue Waters even with veryclustered datasets. This project will use the highly scalable N-body/hydrodynamics code, ChaNGa, to model theformation and evolution of a population of galaxies in a Coma-sized galaxy cluster, includingtheir contribution to and interaction with the ICM. This model will be compared to observationsof cluster galaxies to understand the physical and temporal origin of their morphologies.The model ICM will be compared to X-ray and microwave (via the Sunyaev-Zeldovich effect) tounderstand the relation between these observables and the underlying gas properties. Finally,the overall mass distribution will be used to better understand how these clusters gravitationallylens background galaxies.

了解星系和星系团形成的历史从根本上影响了我们对整个宇宙的认识，并为我们在宇宙中的位置设定了背景。该项目将使用Blue沃茨模拟后发座大小的星系团中星系群的形成和演化，包括它们对星系团内介质（ICM）的贡献和相互作用。 对星系和星系团中的ICM进行建模是一项艰巨的挑战。 星系的形态以及气体的能量和金属含量最终由发生在小于一百万太阳质量的分子云尺度上的星星形成过程控制。另一方面，星系团的总质量超过10^15太阳质量;因此，在这个背景下，要对星系进行一致的建模，就必须有一个超过10亿的质量动态范围。 对这些问题的调查吸引了许多对科学甚至整个社会感兴趣的人。特别是，该项目的结果将用于一个项目，该项目将向科学预科生介绍天体物理学中计算机模拟的使用，希望最终吸引代表性不足的学生进入STEM专业。一些进步现在已经使这些系统的建模成为可能。首先是像Blue沃茨这样的超级计算机的可用性，它可以支持对真实的世界问题的千万亿次计算。二是拉格朗日程序中水动力模型的改进。这些改进包括更好地模拟多相介质和由此产生的不稳定性，更准确地处理高马赫数激波，以及更好地模拟次网格物理，包括超大质量黑洞的生长和反馈。最后，这些算法的改进已经在代码中实现，这些代码可以扩展到Blue沃茨的很大一部分，即使是非常集群的数据集。 该项目将使用高度可扩展的N体/流体动力学代码ChaNGa来模拟后发座大小的星系团中星系群的形成和演化，包括它们对ICM的贡献以及与ICM的相互作用。这个模型将与星系团的观测结果进行比较，以了解其形态的物理和时间起源。ICM模型将与X射线和微波（通过Sunyaev-Zeldovich效应）进行比较，以了解这些观测值与基础气体性质之间的关系。最后，总的质量分布将被用来更好地理解这些星系团是如何引力作用于背景星系的.