Collaborative Research: CDS&E: Renaissance Simulations Laboratory to Model and Explore the First Galaxies in the Universe
Collaborative Research: CDS&E: Renaissance Simulations Laboratory to Model and Explore the First Galaxies in the Universe
批准号:
1615848
负责人:
Michael Norman
金额:
$37.06万
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
项目状态:
已结题
起止时间:
2016-08-01 至 2019-07-31
中文摘要
天体物理学的一个巨大挑战是详细了解早期宇宙中物质的初始平滑分布是如何形成第一个星系的。为了补充对真实星系的观测,研究人员使用计算机模拟来模拟早期宇宙并研究结果。这个过程可以让我们了解这些最初的星系是如何形成的。然而,这种星系模拟的庞大规模和复杂性给它们带来了挑战,因为单个研究小组缺乏对它们进行全面探索的能力。因此,最大化模拟的科学价值需要新的工具和服务,旨在促进合作,多小组研究社区的发展。该项目旨在开发和使用一个新的虚拟实验室,对新的和现有的星系模拟进行变革性的科学研究,其中一些是由NSF先前支持的。允许公众访问和不受限制的分析,并促进共享技术和结果的协作环境,将确保星系模拟在最初进行它们的研究小组内外继续具有价值。该项目解决了发展美国网络基础设施和发展美国在天体物理学科学研究中的领导地位的国家迫切需要。从技术上讲,在美国国家科学基金会的事先支持下,研究人员使用国家超级计算应用中心(NCSA)的蓝水超级计算机进行了文艺复兴模拟:这是迄今为止对第一批星系形成和演化的最大、最详细的模拟之一。文艺复兴模拟产生了超过3000个高红移(20z7)星系的样本,并专门设计以前所未有的细节水平模拟负责预热星系间介质和再电离的主要来源。本项目计划开展两项相关活动:(1)进一步分析文艺复兴模拟;(2)创建开放数据访问门户,文艺复兴模拟实验室(RSL),该实验室将为天文研究界提供对这一独特数据语料库以及相关数据分析工具的开放访问。推动其设计和效用,研究人员将使用RSL进行自己的研究调查。调查人员的研究过程将以可执行的“木星”笔记本的形式成为RSL的一部分。Jupyter Notebook是iPython Notebook的进化版,是RSL的基础部分,正在引领开放科学时代。调查人员对Docker容器的使用同样引人注目。通过将执行预编程数据分析工作流程的Jupyter Notebooks容器化,研究人员能够对数据进行计算,并分享他们如何获得科学结果,这是迈向可复制科学的关键一步。用户可以选择将笔记本和相关数据下载到自己的平台上,或者在圣地亚哥超级计算机中心和NCSA高性能平台上执行。
英文摘要
A great challenge in astrophysics is to understand in detail how the initial smooth distribution of matter in the early Universe formed the first galaxies. Complementing observations of real galaxies, researchers use computational simulations to model the early Universe and study the results. This process allows one to learn how these first galaxies might have formed. However, the sheer size and complexity of such galaxy simulations present their own challenge as a single research group lacks the capacity to explore them fully. As a result, maximizing the scientific value of simulations demands new tools and services designed to foster the growth of a collaborative, multi-group research community. This project aims to develop and use a new virtual laboratory to enable transformative scientific inquiry on new and existing galaxy simulations, some of which were produced by prior NSF support. Enabling public access and unrestricted analysis and fostering a collaborative environment for sharing technology and results will ensure that galaxy simulations continue to be valuable within and beyond the research group that originally conducted them. This project addresses the national imperative to develop US cyber infrastructure and to develop US leadership in scientific research in astrophysics.More technically, with prior NSF support the investigators used the Blue Waters supercomputer at the National Center for Supercomputing Applications (NCSA) to perform the Renaissance Simulations: among the largest, most detailed simulations of the formation and evolution of the first galaxies to date. The Renaissance Simulations yielded a sample of over 3,000 high redshift (20 z 7) galaxies and were specifically designed to simulate the dominant sources responsible for preheating the intergalactic medium and reionization at an unprecedented level of detail. This project plans two related activities: (1) further analysis of the Renaissance Simulations; and (2) the creation of an open-data access portal, the Renaissance Simulation Laboratory (RSL), which will provide open access to this unique data corpus along with associated data analysis tools for the astronomical research community. Driving its design and utility, the investigators will use the RSL to carry out their own research investigations. The investigators' research processes will become part of the RSL in the form of executable "Jupyter" notebooks. The Jupyter Notebook, an evolution of the iPython Notebook, is a fundamental part of the RSL and is ushering in the era of open science. The investigators' use of Docker containers is equally compelling. By containerizing Jupyter Notebooks which execute pre-programmed data analysis workflows the investigators are able to bring computation to the data and share how they obtain their scientific results, a key step toward reproducible science. Users will have the option of downloading notebooks and associated data to their own platforms or executing them on San Diego Supercomputer Center and NCSA high performance platforms.
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