引力波数据分析:无模板搜索  

Gravitational wave data analysis:Unmodeled search

作　　者：许雨蒙 刘玉孝 胡彬[4] 王刚 XU YuMeng;LIU YuXiao;HU Bin;WANG Gang(Physik-Institut,University of Zurich,Zurich 8057,Switzerland;Lanzhou Center for Theoretical Physics,Key Laboratory for Quantum Theory and Applications of the Ministry of Education,Key Laboratory of Theoretical Physics of Gansu Province,Lanzhou University,Lanzhou 730000,China;School of Physics Science and Technology,Lanzhou University,Lanzhou 730000,China;School of Physics and Astronomy,Beijing Normal University,Beijing 100875,China;Shanghai Astronomical Observatory,Chinese Academy of Sciences,Shanghai 200030,China)

机构地区：[1]苏黎世大学物理学院,瑞士苏黎世8057 [2]兰州理论物理中心,量子理论及应用基础教育部重点实验室,甘肃省理论物理重点实验室,兰州大学,兰州730000 [3]兰州大学物理科学与技术学院,兰州730000 [4]北京师范大学物理与天文学院,北京100875 [5]中国科学院上海天文台,上海200030

出　　处：《中国科学:物理学、力学、天文学》2025年第3期95-109,共15页Scientia Sinica Physica,Mechanica & Astronomica

基　　金：国家重点研发计划(编号:2021YFC2203003,2021YFC2203001);国家自然科学基金(编号:12247101,12333001);111计划(编号:B20063)资助项目。

摘　　要：自2015年Advanced LIGO首次探测到双黑洞并合事件GW150914以来,引力波天文学取得了快速发展.截至第三阶段运行,已成功探测到93个引力波事件.随着引力波探测器的不断改进和新一代探测器的出现,我们的宇宙观测能力将进一步拓宽.本文以相干瞬态波管线cWB为例,探讨引力波无模板搜索的核心算法及事件置信度的计算,并简要分析其在高离心率致密双星并合、核塌缩超新星、双曲轨道相遇、脉冲星自转突变、微引力透镜及引力波回声等各种引力波源中的应用.最后,本文展望机器学习在引力波无模板搜索中的未来应用,以及模块化、Python化的PycWB搜索管线在未来空间引力波探测中的扩展.Since the first detection of the binary black hole merger event GW150914 in 2015,gravitational wave astronomy has rapidly advanced,with 93 gravitational wave events detected until O3.The continuous improvement of gravitational wave detectors and the emergence of a new generation of detectors will expand our ability to observe the universe.This study uses the cWB pipeline as an example to explore the core algorithms of unmodeled gravitational wave searches and the computation of background and event significance.Furthermore,we briefly review its applications for various gravitational wave sources,including high-eccentricity compact binary mergers,core-collapse supernovae,hyperbolic encounters,pulsar glitches,microlensing,and echoes.Finally,this study discusses the future applications of machine learning in unmodeled gravitational wave searches and the possible adaption of the modular,Python-based PycWB pipeline for future space-based gravitational wave detectors.

关 键 词：引力波数据分析 无模板搜索 相干瞬态波 

分 类 号：P142.84[天文地球—天体物理]