发表机构
ETH Zurich; Universitat de les Illes Balears; University of Trento; INFN-TIFPA, Trento Institute for Fundamental Physics and Applications（苏黎世联邦理工学院; 巴利阿里群岛大学; 特伦托大学; 意大利国家核物理研究所-特伦托基础物理与应用研究所）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本文提出cWB-space时频瞬变搜索流水线，无需波形模板即可识别LISA数据中的引力波候选信号，并在Sangria模拟数据中成功恢复全部六个注入的大质量黑洞双星系统。
AI 中文摘要
引力波观测可以揭示信号事先未知的源。因此，不需要预测波形模板的搜索是对特定源类别搜索的重要补充。对于激光干涉空间天线（LISA），挑战在于从重叠的天体物理源和仪器扰动中找出此类信号。我们提出\ exttt{cWB-space}，它通过跟踪信号功率在时间和频率上的分布来识别候选信号，然后在不施加源模型的情况下重建其波形的一部分。对并合大质量黑洞、其他爆发信号以及仪器扰动的模拟测试，既检验了候选识别能力，也检验了探测器响应所携带的信息。响应比较方法从观测数据中估计其背景。对多个激光测量中扰动的测试，考察了在何处可能产生来自仪器来源的类似响应。在搜索Sangria模拟LISA数据时，我们将所有六个注入的大质量黑洞双星系统恢复为排名最高的六个候选体。其重建波形在所研究的区间内与注入信号吻合良好。这些结果展示了研究瞬变信号的另一条途径，而误报率和仪器扰动的一般性判别则留待未来验证。
英文摘要
Gravitational-wave observations can reveal sources whose signals are not known in advance. Searches that do not require a predicted waveform are therefore an important complement to searches for specific source classes. For the Laser Interferometer Space Antenna (LISA), the challenge is to find such signals among overlapping astrophysical sources and disturbances in the instrument. We present \texttt{cWB-space}, which identifies candidate signals by following how their power is distributed in time and frequency, and then reconstructs parts of their waveforms without imposing a source model. Simulations of merging massive black holes, other burst signals, and instrumental disturbances test both candidate identification and the information carried by the detector's response. The response comparison estimates its background from the observed data. Tests of disturbances in several laser measurements examine where a similar response can arise from an instrumental origin. Searching the Sangria simulated LISA data, we recover all six injected massive-black-hole binaries as the six highest-ranked candidates. Their reconstructed waveforms agree well with the injected signals over the intervals studied. The results demonstrate another route to investigating transients, while leaving the rate of false detections and general discrimination of instrumental disturbances to future validation.
Comments19 Pages, 10 figures
