论文标题
Pycbc Live的天体物理源分类和距离估计
Astrophysical Source Classification and Distance Estimation for PyCBC Live
论文作者
论文摘要
在晚期Ligo和高级处女座探测器的第三次观察（O3）期间，已经对数十个候选重力波（GW）事件进行了分类。这种观察跑步的挑战是对紧凑型二元合并（CBC）信号的快速识别和公众传播，这是由Pycbc Live等低延迟搜索执行的任务。在O3的后期，我们开发了一种通过Pycbc Live内包含中子星或黑洞成分的概率来对CBC来源进行分类的方法，以促进电磁和中核观测值立即进行后续观察。鉴于难以测量质量比以高度准确性的低质量二进制物测量质量比，这种快速分类使用搜索恢复的chiRP质量。我们还使用从搜索输出中得出的距离估计值来纠正由于宇宙红移而导致的chirp质量偏差。我们提出了模拟信号的结果，以及在O3上低潜伏期中确定的已确认的候选事件。
During the third observing run (O3) of the Advanced LIGO and Advanced Virgo detectors, dozens of candidate gravitational-wave (GW) events have been catalogued. A challenge of this observing run has been the rapid identification and public dissemination of compact binary coalescence (CBC) signals, a task carried out by low-latency searches such as PyCBC Live. During the later part of O3, we developed a method of classifying CBC sources, via their probabilities of containing neutron star or black hole components, within PyCBC Live, in order to facilitate immediate follow-up observations by electromagnetic and neutrino observatories. This fast classification uses the chirp mass recovered by the search as input, given the difficulty of measuring the mass ratio with high accuracy for lower-mass binaries. We also use a distance estimate derived from the search output to correct for the bias in chirp mass due to the cosmological redshift. We present results for simulated signals, and for confirmed candidate events identified in low latency over O3.
