从10个高能物理卫星上寻找连续的引力波。使用隐马尔可夫模型的源
Search for continuous gravitational waves from ten H.E.S.S. sources using a hidden Markov model
摘要：
孤立的中子星是地面引力$-$波干涉仪进行连续波（CW）搜索的主要目标。结果是从CW搜索针对十个卫星。搜索使用半相干算法，该算法结合了最大似然$\mathcal{F}$ -统计与隐马尔可夫模型（HMM），以有效地检测和跟踪准$-$单色信号随机漂移的频率。高能立体系统（H.E.S.S.）探测到的TeV源相关目标，被选择来测试具有强$\mathrmγ$射线发射的年轻的高能恒星的引力辐射，并且与其他CW搜索算法相比，最大限度地利用HMM的频率跟踪能力。这次搜索使用了高级激光干涉引力波天文台（aLIGO）第二次观测运行的数据。它扫描$f_*$周围的1个$-$ Hz子带、4个$f_*$ /3和2个$f_*$，其中$f_*$表示恒星的旋转频率，以适应电磁波和引力波发射之间物理上合理的频率失配。在本研究中搜索的24个子带返回高于高斯阈值的5，256个候选者，每个目标每个子带的虚警概率为1 $\%$。只有12个候选人幸存的三个数据质量否决，适用于分离非$-$高斯伪影从真正的天体物理信号。使用后续观测运行的数据进行CW搜索将澄清剩余候选者的状态。
英文摘要：
Isolated neutron stars are prime targets for continuous-wave (CW) searches by ground-based gravitational$-$wave interferometers. Results are presented from a CW search targeting ten pulsars. The search uses a semicoherent algorithm, which combines the maximum-likelihood $\mathcal{F}$-statistic with a hidden Markov model (HMM) to efficiently detect and track quasi$-$monochromatic signals which wander randomly in frequency. The targets, which are associated with TeV sources detected by the High Energy Stereoscopic System (H.E.S.S.), are chosen to test for gravitational radiation from young, energetic pulsars with strong $\mathrmγ$-ray emission, and take maximum advantage of the frequency tracking capabilities of HMM compared to other CW search algorithms. The search uses data from the second observing run of the Advanced Laser Interferometer Gravitational-Wave Observatory (aLIGO). It scans 1$-$Hz sub-bands around $f_*$, 4$f_*$/3, and 2$f_*$, where $f_*$ denotes the star's rotation frequency, in order to accommodate a physically plausible frequency mismatch between the electromagnetic and gravitational-wave emission. The 24 sub-bands searched in this study return 5,256 candidates above the Gaussian threshold with a false alarm probability of 1$\%$ per sub-band per target. Only 12 candidates survive the three data quality vetoes which are applied to separate non$-$Gaussian artifacts from true astrophysical signals. CW searches using the data from subsequent observing runs will clarify the status of the remaining candidates.
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