Collaborative Research: CDS&E: Renaissance Simulations Laboratory to Model and Explore the First Galaxies in the Universe

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。 为了补充对真实的星系的观测，研究人员使用计算机模拟来模拟早期宇宙并研究结果。 这一过程使人们能够了解这些第一个星系可能是如何形成的。 然而，这种星系模拟的庞大规模和复杂性也带来了挑战，因为单个研究小组缺乏充分探索它们的能力。 因此，最大限度地提高模拟的科学价值需要新的工具和服务，旨在促进合作，多组研究社区的发展。 该项目旨在开发和使用一个新的虚拟实验室，以便对新的和现有的星系模拟进行变革性的科学调查，其中一些模拟是由先前的NSF支持制作的。 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这些模拟的研究小组内外继续具有价值。 该项目解决了国家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方面的领导地位的迫切需要。更技术上，在NSF的支持下，研究人员使用国家超级计算应用中心（NCSA）的Blue沃茨超级计算机进行文艺复兴模拟：迄今为止最大，最详细的第一批星系形成和演化模拟。 文艺复兴时期的模拟产生了超过3,000个高红移（20 z 7）星系的样本，并专门设计用于模拟负责预热星系际介质和再电离的主要来源，其细节达到了前所未有的水平。 该项目计划开展两项相关活动：（1）进一步分析文艺复兴时期的模拟;（2）创建一个开放式数据访问门户网站-文艺复兴时期模拟实验室（RSL），该实验室将为天文学研究界提供对这一独特数据库的开放式访问，同时提供沿着相关的数据分析工具。 推动其设计和实用性，研究人员将使用RSL进行自己的研究调查。 研究者的研究过程将以可执行的“计算机”笔记本的形式成为RSL的一部分。 iPython Notebook的演化版，是RSL的基本组成部分，正在引领开放科学的时代。 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笔记本电脑容器化，研究人员能够将计算带入数据并分享他们如何获得科学结果，这是迈向可重复科学的关键一步。 用户可以选择将笔记本电脑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。

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.