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.

了解星系和星团形成的历史从根本上影响我们对整个宇宙的认识，并为我们在宇宙中的位置奠定基础。该项目将使用 Blue Waters 模拟后发星系团中星系群的形成和演化，包括它们对星团内介质 (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恒星形成过程控制，该过程发生在小于一百万个太阳质量的分子云尺度上。另一方面，星团总质量超过 10^15 太阳质量；因此，要在这种情况下对星系进行一致的建模，需要超过十亿的动态质量范围。 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，该项目将向科学专业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。现在已经取得了几项进展，使建模成为可能这些系统。首先是像 Blue Waters 这样的超级计算机的可用性，它可以对现实世界的问题进行千万亿次计算。其次是拉格朗日代码中水动力建模的改进。这些改进包括更好地对多相介质和由此产生的不稳定性进行建模、更准确地处理高马赫数冲击，以及更好地对亚网格物理进行建模，包括超大质量黑洞的生长和反馈。最后，这些算法改进已在代码中实现，即使对于非常集群的数据集，也可以扩展到 Blue Waters 的很大一部分。 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。该模型将与星团星系的观测进行比较，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底层气体之间的关系特性。最后，整体质量分布将用于更好地了解这些星团如何通过引力透镜影响背景星系。