CAREER: Simulating Cosmological Galaxy Formation with Adaptive-Mesh Refinement

职业：用自适应网格细化模拟宇宙星系的形成[j]。哥伦比亚大学的Greg Bryan将应用自适应网格细化（AMR）方法来研究星系形成的问题，以研究暗物质晕内形成重子分布的实际物理过程。来自恒星形成的反馈和自我调节将包括在三维流体动力学模拟中，该模拟将研究大范围星系大小和类型的形成。还将包括其他物理过程，包括磁流体动力学（MHD）和辐射转移的简化处理。Bryan博士的教育工作将包括：(1)让天文学和物理学的本科生参与到科学可视化的生成中，并制作包含这些可视化的短片；(2)在哥伦比亚大学天文系建设立体可视化系统（AstroWall），促进多维数据集的可视化；(3)邀请纽约当地的高中学生和教师到天体物理实验室进行短期研究项目，包括对大维度数据集的分析

CAREER: Simulating cosmological galaxy formation with adaptive-mesh refinementABSTRACTAST 0547823 Greg BryanDr. Greg Bryan, at Columbia University, will apply the Adaptive Mesh Refinement (AMR) method to the problem of galaxy formation to investigate the actual physical processes that shape the distribution of baryons inside dark matter halos. Feedback and self-regulation from star formation will be included in the three-dimensional hydrodynamical simulations that will investigate the formation of a wide range of galaxy sizes and types. Additional physical processes will also be included, including magneto-hydrodynamics (MHD) and a simplified treatment of radiative transfer. Dr. Bryan's educational effort will include: (1) the involvement of astronomy and physics undergraduates in the generation of scientific visualizations, and the creation of short movies that incorporate these visualizations; (2) the construction of a stereoscopic visualization system (the "AstroWall") in the Astronomy Department at Columbia University, to facilitate visualization of multi-dimensional datasets; and (3) bringing local New York high-school students and teachers into the Astrophysics Lab to do short-term research projects involving the analysis of large-dimensional datasets