arXivDaily arXiv每日学术速递 周一至周五更新
arXiv 1407.2600astro-ph.COastro-ph.IM
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暗天模拟:早期数据发布

Dark Sky Simulations: Early Data Release

Samuel W. Skillman, Michael S. Warren, Matthew J. Turk, Risa H. Wechsler, Daniel E. Holz, P. M. Sutter

摘要:

暗天模拟是一系列正在进行的宇宙学N体模拟,旨在为大尺度宇宙的演化提供一个定量和可访问的模型。此类模型对于暗物质和暗能量研究的许多方面都至关重要,因为我们缺乏足够准确的非线性引力聚集分析模型。2014年7月,我们向公众提供了我们的早期数据发布,包括超过55 TB的模拟数据产品,包括我们迄今为止最大的模拟,其中使用了$8h^{-1}\mathrm{Gpc}$体积中的$1.07 \times 10^{12}~(10240^3)$粒子。我们的模拟是用2HOT进行的,2HOT是一种纯基于树的自适应N体方法,在Titan超级计算机的20万个处理器上运行,由yt启用数据分析。我们提供了一个概述派生的晕目录,质量函数,功率谱和光锥数据。在粒子质量超过1000的范围内,我们在质量函数和质量功率谱上表现出自洽性。我们还提出了一种新的方法来分发和访问非常大的数据集,基于抽象的万维网(WWW)作为一个文件系统,远程内存映射的文件访问语义,和空间填充曲线索引。这种方法已经实现了我们的数据发布,并提供了一种手段,不仅查询存储的结果,如光环目录,但也设计和部署大型分布式数据集上的新的分析技术。

英文摘要:

The Dark Sky Simulations are an ongoing series of cosmological N-body simulations designed to provide a quantitative and accessible model of the evolution of the large-scale Universe. Such models are essential for many aspects of the study of dark matter and dark energy, since we lack a sufficiently accurate analytic model of non-linear gravitational clustering. In July 2014, we made available to the general community our early data release, consisting of over 55 Terabytes of simulation data products, including our largest simulation to date, which used $1.07 \times 10^{12}~(10240^3)$ particles in a volume $8h^{-1}\mathrm{Gpc}$ across. Our simulations were performed with 2HOT, a purely tree-based adaptive N-body method, running on 200,000 processors of the Titan supercomputer, with data analysis enabled by yt. We provide an overview of the derived halo catalogs, mass function, power spectra and light cone data. We show self-consistency in the mass function and mass power spectrum at the 1% level over a range of more than 1000 in particle mass. We also present a novel method to distribute and access very large datasets, based on an abstraction of the World Wide Web (WWW) as a file system, remote memory-mapped file access semantics, and a space-filling curve index. This method has been implemented for our data release, and provides a means to not only query stored results such as halo catalogs, but also to design and deploy new analysis techniques on large distributed datasets.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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