Collaborative Research: A Data Challenge for the Next Generation of Ground-Based Gravitational Wave Detectors

美国国家科学基金会的激光干涉仪引力波天文台（LIGO）开启了探索宇宙的新时代。科学家们现在可以利用引力波——时空结构中的涟漪——来探索遥远的物体，比如黑洞和中子星。随着LIGO继续探索宇宙，科学家们正在为下一代引力波天文台制定计划；天文台可以看到宇宙中每一个黑洞的合并，并有可能揭示支配致密物质行为的物理原理。在美国，科学界一直在设计一种名为“宇宙探索者”（Cosmic Explorer）的探测器，欧洲正在提议建立一个互补的天文台，即爱因斯坦望远镜（Einstein Telescope）。实现这些观测站的科学潜力需要先进的算法和计算技术，这些算法现在就需要开发，所以当探测器在2030年代开始探索引力波天空时，这些算法已经准备好了。学生们将学习开发这些技术的这些技能将提高美国STEM劳动力的竞争力。该奖项还将支持将高性能计算引入宾夕法尼亚州农村学区的努力，并促进K-12学校的STEM教育。为了应对下一代引力波探测器所带来的数据分析障碍，将会出现一系列越来越困难的数据挑战。这些挑战将：(i)告知在开发有效探测和参数推断的新算法方面需要取得的进展，（ii）帮助估计充分利用下一代探测器的科学潜力所需的计算资源，（iii）建立并吸引一个准备用这个新的观测窗口探索宇宙的研究人员社区。该奖项将提供一个机会，以确定从未来探测器的信号丰富数据中是否可以可靠地提取科学结果，并刺激研究新的分析和推理算法的发展，这些算法可以处理重叠的多种信号类型和强度，不同的持续时间和节奏，所有这些都隐藏在具有非平稳性和空白的数据中。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

The National Science Foundation’s Laser Interferometer Gravitational Wave Observatory (LIGO) has begun a new era in the exploration of the Universe. Scientists can now use gravitational waves, ripples in the fabric of spacetime, to explore distant objects like black holes and neutron stars. As LIGO continues to explore the universe, scientists are making plans for the next generation of gravitational-wave observatories; observatories that can see every black hole merger in the universe and have the potential to reveal the physics that governs the behavior of dense matter. In the United States, the community has been developing a design for a detector called Cosmic Explorer and Europe is proposing a complementary observatory known as the Einstein Telescope. Achieving the scientific potential of these observatories requires advanced algorithms and computational techniques that need to be developed now, so these algorithms are ready when the detectors begin exploring the gravitational-wave sky in the 2030s. These skills that students will learn developing these technologies will advance the competitiveness of the U.S. STEM workforce. This award will also support an effort to bring high-performance computing to school districts in rural Pennsylvania and promote STEM education in K-12 schools.A series of progressively more difficult data challenges will be created to confront the data-analysis hurdles presented by the next generation of gravitational-wave detectors. These challenges will: (i) inform the progress that would need to be made in the development of new algorithms for efficient detection and parameter inference, (ii) help estimate the computational resources required to fully exploit the science potential of next-generation detectors and (iii) build and engage a community of researchers that is ready to explore the Universe with this new observational window. This award will provide an opportunity to determine if science results from the signal-rich data of future detectors can be reliably extracted and stimulate research in the development of new analysis and inference algorithms that can deal with overlapping multiple signal types and strengths, of varying duration and cadence, all buried in data with non-stationarities and gaps.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.