Astrophysical Source Classification and Distance Estimation for PyCBC Live
arXiv (Cornell University)(2022)
摘要
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.
更多查看译文
关键词
pycbc
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要