Star Formation in the Turbulent ISM with Realistic Large-Scale Forcing

该奖项是根据2009年美国复苏和再投资法案（公法111-5）资助的。本研究的目的是约束星星形成模型与高动态范围的模拟。目前的星星形成模拟是基于非物理的初始条件或人工驱动力，模拟能量注入从一个大规模的湍流级联。在这个项目中，Paolo Padoan博士（加州大学圣地亚哥分校）将通过开发星星形成模拟来克服这一限制，这种模拟将解决单个原恒星核心的坍塌问题，同时包括驱动湍流和控制恒星形成云生命周期的大规模物理过程。该项目将通过嵌入恒星形成模拟来包括大规模物理学，在垂直于银河系盘的1 × 1 × 20千秒差距区域内，在坍缩核心中达到200天文单位的分辨率。在这个区域的星际介质将使用三维，可压缩，理想磁流体动力学（MHD）模拟，包括密度分层在银河系引力场，气体自引力，辐射冷却，光电和宇宙射线加热，大规模的银河系剪切，星星的形成，和热和机械反馈的Ia型，Ib+c型和II型超新星爆炸。 这些模拟产生的恒星形成云的大样本将与辐射传输代码进行处理，以产生模拟尘埃连续体和线发射观测数据集。 星星的形成是天体物理学和宇宙学的核心。该项目的成果将与星系形成和演化的研究以及宇宙星星形成史有关。它们将被用来制定星系形成的宇宙学模拟的子网格模型，其中恒星反馈是重要的。辐射传输计算将产生大量的恒星形成云的模拟观测数据集，这将有助于解释真实的观测。由于该项目将产生一些迄今为止最大的超音速湍流模拟，它也将允许对超新星驱动的MHD湍流的统计特性进行高分辨率研究。 Padoan博士与圣地亚哥超级计算机中心合作，最近启动了计算天体物理数据分析中心（CADAC），这是一项收集，共享和分析数值模拟数据集的新服务。 CADAC为天体物理学界提供了强大的数据存储和数据分析资源，鼓励数值数据集和数据分析工具的早期出版。通过CADAC，该项目的数据和计算资源将提供给科学界，包括研究生。

This award is funded under the American Recovery and Reinvestment Act of 2009 (Public Law 111-5). The objective of this research is to constrain star formation models with high dynamic range simulations. Current star formation simulations are based on unphysical initial conditions or artificial driving forces that mimic the energy injection from a large-scale turbulent cascade. In this project, Dr. Paolo Padoan (University of California - San Diego) will overcome this limitation by developing star formation simulations that resolve the collapse of individual protostellar cores, while including the large-scale physical processes that drive the turbulence and control the life cycle of star-forming clouds. The project will include the large-scale physics by embedding the star-formation simulations, reaching a resolution of 200 astronomical units in collapsing cores, in a 1 × 1 × 20 Kiloparsec region perpendicular to the Galactic disk. The interstellar medium in this region will be modeled using three-dimensional, compressible, ideal magneto-hydrodynamic (MHD) simulations, including density stratification in the Galactic gravitational field, gas self-gravity, radiative cooling, photoelectric and cosmic-ray heating, large-scale Galactic shear, star formation, and thermal and mechanical feedback from Type Ia, Ib+c, and Type II supernova explosions. The large samples of star-forming clouds generated by these simulations will be processed with radiative transfer codes to produce datasets of simulated dust-continuum and line emission observations. Star formation is central to much of astrophysics and cosmology. Results from this project will be relevant to studies of the formation and evolution of galaxies and to the star formation history of the universe. They will be used to formulate sub-grid models for cosmological simulations of galaxy formation, where stellar feedback is important. The radiative transfer calculations will result in large datasets of simulated observations of star-forming clouds that will be helpful in the interpretation of real observations. Because this project will generate some of the largest simulations of supersonic turbulence to date, it will also allow high resolution studies of the statistical properties of supernova-driven MHD turbulence. Dr. Padoan, in collaboration with the San Diego Supercomputer Center, has recently started the Computational Astrophysics Data Analysis Center (CADAC), a new service to collect, share, and analyze datasets from numerical simulations. CADAC provides powerful data-storage and data-analysis resources to the astrophysical community, encouraging the early publication of numerical datasets and data-analysis tools. Through CADAC, data from this project and computational resources will be available to the scientific community, including graduate students.