Collaborative Research: Elements: Software: Accelerating Discovery of the First Stars through a Robust Software Testing Infrastructure

130亿年前第一批恒星和星系的诞生--我们的“宇宙黎明”--是宇宙历史上最后一个未被观测到的时期之一。科学家们正在努力观测第一批恒星形成时由原始中性氢雾发出的21厘米射电光。这些观测被认为是现代天体物理学的重大挑战之一。该项目将为21厘米宇宙学领域提供关键的软件基础设施，能够快速审查为这些观测开发的新分析和技术，并提高它们的稳健性、精确性和重复性。在这个项目中，研究人员将培训学生进行软件和代码开发的最佳实践，为他们自己的研究开发强大的、可重复使用的软件做好准备，为大型开放源码项目做出贡献，并在专业环境中开发软件。探测再电离时代的最大挑战之一是存在明亮的天体物理前景，它掩盖了感兴趣的信号，需要对执行这些观测的射电望远镜进行非常精确的建模和校准。21厘米宇宙学社区正在迅速开发用于仪器校准、前景移除和分析的新技术，但彻底测试和整合到现有数据分析管道中的速度一直很慢。该项目将提供一个软件基础设施，能够在统一的框架内对新的算法开发进行严格、无缝的测试。该基础设施将确保现有工具无法达到的可靠性和重现性，并加快将开发集成到生产级代码中的速度，为将我们的领域带入下一个十年以及利用当前NSF在这些实验中的投资提供宝贵的基础。该项目得到了计算机与信息科学与工程局的高级网络基础设施办公室和数学和物理科学局的天文科学部的支持。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

The birth of the first stars and galaxies 13 billions years ago -- our "Cosmic Dawn" -- is one of the last unobserved periods in the history of the Universe. Scientists are working to observe the 21 cm radio light emitted by the primeval neutral hydrogen fog as the first stars formed. These observations are considered one of the grand challenges of modern astrophysics. This project will provide critical software infrastructure for the field of 21 cm cosmology, enabling rapid vetting of the new analyses and techniques developed for these observations and increasing their robustness, rigor, and reproducibility. Under this project The investigators will train students in the best practices for software and code development, preparing them to develop robust, reproducible software for their own research, contribute to large open source projects, and develop software in a professional setting.One of the biggest challenges for the detection of the Epoch of Reionization is the presence of bright astrophysical foregrounds that obscures the signal of interest, requiring extraordinarily precise modeling and calibration of the radio telescopes performing these observations. The 21 cm cosmology community is rapidly developing new techniques for instrument calibration, foreground removal, and analysis, but thorough testing and integration into existing data analysis pipelines has been slow. This project will provide a software infrastructure that can enable rigorous, seamless testing of novel algorithmic developments within a unified framework. This infrastructure will ensure a level of reliability and reproducibility not possible with current tools and accelerate the speed at which developments become integrated into production level code, providing an invaluable foundation for bringing our field into the next decade and for leveraging the current NSF investments in these experiments.This project is supported by the Office of Advanced Cyberinfrastructure in the Directorate for Computer & Information Science & Engineering and the Division of Astronomical Sciences in the Directorate of Mathematical and Physical Sciences.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.