Advanced LIGO data contains numerous noise transients, or "glitches", that have been shown to reduce the sensitivity of matched filter searches for gravitational waves from compact binaries by increasing the rate at which random coincidences occur. The presence of these transients has precipitated extensive work to establish that observed gravitational wave events are astrophysical in nature. We discuss the response of the PyCBC search for gravitational waves from stellar mass binaries to various common glitches that were observed during Advanced LIGO's first and second observing runs. We show how these transients can mimic waveforms from compact binary coalescences and quantify the likelihood that a given class of glitches will create a trigger in the search pipeline. We explore the specific waveform parameters that are most similar to different glitch classes and demonstrate how knowledge of these similarities can be used when evaluating the significance of gravitational-wave candidates.

中文翻译：

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利用 aLIGO 故障分类来验证引力波候选者

先进的 LIGO 数据包含大量噪声瞬变或“毛刺”，已被证明可以通过增加随机巧合发生的速率来降低匹配滤波器搜索来自紧凑双星引力波的灵敏度。这些瞬变的存在促成了广泛的工作，以确定观察到的引力波事件本质上是天体物理学的。我们讨论了 PyCBC 搜索从恒星质量双星引力波到高级 LIGO 第一次和第二次观测运行期间观察到的各种常见故障的响应。我们展示了这些瞬态如何模拟来自紧凑二进制合并的波形，并量化给定类别的毛刺在搜索管道中创建触发器的可能性。