The increasing sensitivity of gravitational-wave detectors has brought about an increase in the rate of astrophysical signal detections as well as the rate of “glitches”; transient and non-Gaussian detector noise. Temporal overlap of signals and glitches in the detector presents a challenge for inference analyses that typically assume the presence of only Gaussian detector noise. In this study we perform an extensive exploration of the efficacy of a recently proposed method that models the glitch with sine-Gaussian wavelets while simultaneously modeling the signal with compact-binary waveform templates. We explore a wide range of glitch families and signal morphologies and demonstrate that the joint modeling of glitches and signals (with wavelets and templates respectively) can reliably separate the two. We find that the glitches that most affect parameter estimation are also the glitches that are well modeled by such wavelets due to their compact time-frequency signature. As a further test, we investigate the robustness of this analysis against waveform systematics like those arising from the exclusion of higher-order modes and spin-precession effects. Our analysis provides an estimate of the signal parameters; the glitch waveform to be subtracted from the data and an assessment of whether some detected excess power consists of a glitch, signal, or both. We analyze the low-significance triggers (191225_215715 and 200114_020818) and find that they are both consistent with glitches overlapping high-mass signals.

中文翻译：

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引力波数据中重叠信号和毛刺的精确建模和缓解

引力波探测器灵敏度的提高带来了天体物理信号探测率和“故障”率的提高；瞬态和非高斯检测器噪声。检测器中信号和毛刺的时间重叠对通常假设仅存在高斯检测器噪声的推理分析提出了挑战。在这项研究中，我们对最近提出的一种方法的功效进行了广泛的探索，该方法使用正弦高斯小波对毛刺进行建模，同时使用紧凑二进制波形模板对信号进行建模。我们探索了广泛的毛刺家族和信号形态，并证明毛刺和信号的联合建模（分别使用小波和模板）可以可靠地将两者分开。我们发现，最影响参数估计的毛刺也是由此类小波很好地建模的毛刺，因为它们具有紧凑的时频特征。作为进一步的测试，我们研究了这种分析对波形系统的稳健性，例如排除高阶模式和自旋进动效应所产生的波形系统。我们的分析提供了信号参数的估计；要从数据中减去的毛刺波形，并评估检测到的某些多余功率是否由毛刺、信号或两者组成。我们分析了低显着性触发（191225_215715 和 200114_020818），发现它们都与重叠高质量信号的毛刺一致。作为进一步的测试，我们研究了这种分析对波形系统的稳健性，例如排除高阶模式和自旋进动效应所产生的波形系统。我们的分析提供了信号参数的估计；要从数据中减去的毛刺波形，并评估检测到的某些多余功率是否由毛刺、信号或两者组成。我们分析了低显着性触发（191225_215715 和 200114_020818），发现它们都与重叠高质量信号的毛刺一致。作为进一步的测试，我们研究了这种分析对波形系统的稳健性，例如排除高阶模式和自旋进动效应所产生的波形系统。我们的分析提供了信号参数的估计；要从数据中减去的毛刺波形，并评估检测到的某些多余功率是否由毛刺、信号或两者组成。我们分析了低显着性触发（191225_215715 和 200114_020818），发现它们都与重叠高质量信号的毛刺一致。要从数据中减去的毛刺波形，并评估检测到的某些多余功率是否由毛刺、信号或两者组成。我们分析了低显着性触发（191225_215715 和 200114_020818），发现它们都与重叠高质量信号的毛刺一致。要从数据中减去的毛刺波形，并评估检测到的某些多余功率是否由毛刺、信号或两者组成。我们分析了低显着性触发（191225_215715 和 200114_020818），发现它们都与重叠高质量信号的毛刺一致。