GWCloud: A Searchable Repository for the Creation and Curation of Gravitational-wave Inference Results
GWCloud: A Searchable Repository for the Creation and Curation of Gravitational-wave Inference Results
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DOI：
10.3847/1538-4365/acc938
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发表时间：
2022-04
期刊：
影响因子：
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通讯作者：
A. M. Baker;P. Lasky;E. Thrane;G. Ashton;Jesmigel Cantos;Lewis Lakerink;Asher Leslie;G. Poole-G.
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文献类型：
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作者：
A. M. Baker;P. Lasky;E. Thrane;G. Ashton;Jesmigel Cantos;Lewis Lakerink;Asher Leslie;G. Poole-G.
目前天文学文献中已经报道了致密双星合并产生的100个引力波候选者。随着探测器灵敏度的提高，星表的规模将扩大：首先是A+时代的1000个事件，然后是第三代天文台（如宇宙探索者和爱因斯坦望远镜）时代的106个事件。使用贝叶斯推断来分析每个事件以确定源的属性，包括组件质量、自旋、潮汐参数和到源的距离。这些推论的结果是一些最令人兴奋的引力波科学的素材，使我们能够用标准的塞壬来测量宇宙的膨胀，描述中子星状态方程，并揭示引力波源是如何以及在哪里组装的。为了最大限度地利用即将到来的探测洪水的科学，我们引入了GWCloud，一个用于创建和管理引力波推断产品的可搜索存储库。它的设计考虑到五个支柱：结果的一致性，结果的可重复性，结果的稳定性，访问天文学界，以及计算资源的有效利用。我们通过示例描述了如何使用GWCloud，读者可以使用本文的配套代码复制这些示例。我们描述了我们对GWCloud的长期愿景。
There are at present (100) gravitational-wave candidates from compact binary mergers reported in the astronomical literature. As detector sensitivities are improved, the catalog will swell in size: first to (1000) events in the A+ era and then to (106) events in the era of third-generation observatories like Cosmic Explorer and the Einstein Telescope. Each event is analyzed using Bayesian inference to determine properties of the source including component masses, spins, tidal parameters, and the distance to the source. These inference products are the fodder for some of the most exciting gravitational-wave science, enabling us to measure the expansion of the universe with standard sirens, to characterize the neutron-star equation of state, and to unveil how and where gravitational-wave sources are assembled. In order to maximize the science from the coming deluge of detections, we introduce GWCloud, a searchable repository for the creation and curation of gravitational-wave inference products. It is designed with five pillars in mind: uniformity of results, reproducibility of results, stability of results, access to the astronomical community, and efficient use of computing resources. We describe how to use GWCloud with examples, which readers can replicate using the companion code to this paper. We describe our long-term vision for GWCloud.