Type Ia Supernovae

该奖项促进了使用IBM开发的名为Blue Waters的大型新计算资源的科学研究，并计划在伊利诺伊大学部署。它提供旅费以支持主要研究人员、Blue Waters项目团队和供应商技术团队之间的技术协调。目前Ia型超新星的标准模型是钱德拉塞卡质量附近的一颗碳氧白矮星的爆炸。尽管经过了50年的研究，对相关物理学有了很好的定性理解，但科学界仍缺乏一个可以达成一致的关于这些爆炸的定量模型。在Blue Waters上，这个问题将使用三个新的、高度可扩展的代码来解决。白矮星点火后将使用低马赫数代码MAESTRO；湍流核燃烧将使用可压缩AMR代码CASTRO进行模拟；和辐射传输将使用三维隐式蒙特卡罗代码SEDONA进行跟踪。这三种代码都已被证明可以在至少数万个处理器上扩展。美国和欧洲正在投入大量的计算和观测资源，试图发现和理解Ia型超新星。部分原因是它们应用于宇宙学中的暗能量问题。这些超新星也是研究燃烧的实验室，在这种情况下，长时间尺度和大长度尺度允许发展地球上无法观察到的现象。正在开发的用于研究超新星的三个代码中的每一个都有潜在的应用于天体物理学以外的领域，例如燃烧科学和惯性聚变。该项目还将有助于培养下一代计算物理学家。

This award facilitates scientific research using the large new computational resource named Blue Waters being developed by IBM and scheduled to be deployed at the University of Illinois. It provides travel funds to support technical coordination between the principal investigators, the Blue Waters project team and vendor technical team.The current standard model for Type Ia supernovae is the explosion of a carbon-oxygen white dwarf near the Chandrasekhar mass. Despite 50 years of study and a good qualitative understanding of the relevant physics, a quantitative model for these explosions that the community can agree upon is lacking. On Blue Waters, the problem will be solved using three new, highly scalable codes. White dwarf ignition will be followed using the low Mach number code, MAESTRO; turbulent nuclear burning will be simulated using the compressible AMR code, CASTRO; and radiation transport will be followed using the 3D implicit Monte Carlo code, SEDONA. All three codes have been proven to scale on at least tens of thousands of processors.Major resources, both computational and observational, are being invested by the US and Europe in attempts to discover and understand Type Ia supernovae. Part of the reason is their application to the dark energy problem in cosmology. These supernovae are also a laboratory for studying combustion in a situation where long time scales and large length scales allow phenomena to develop that are not terrestrially observable. Each of the three codes being developed to study supernovae has potential application outside of astrophysics, e.g., in combustion science and inertial fusion. The project will also help to train the next generation of computational physicists.