利用相对分箱加速 Bilby 中的参数估计
Accelerated parameter estimation in Bilby with relative binning
AI总结:
本文在开源参数估计软件 Bilby 中实现相对分箱及相位、距离边缘化似然,显著加速引力波参数估计,并通过 GW170817、模拟信号和 p-p 检验验证。
摘要:
我们描述了相对分箱技术的一种实现,用于加速引力波信号的参数估计。我们首先对相对分箱进行教学式概述,并讨论关于相位和距离边缘化后的似然表达式。随后,我们介绍 Bilby 中代码的细节;Bilby 是一个常用于引力波源参数估计的开源软件包。我们的代码能够在单核 CPU 上用 14 小时复现 GW170817 的参数,在模拟信号上表现良好,并通过百分位–百分位(p-p)检验。我们还说明,相对分箱是估计下一代引力波探测器中信号参数的理想技术。
英文摘要:
We describe an implementation of the relative binning technique to speed up parameter estimation of gravitational-wave signals. We first give a pedagogical overview of relative binning, discussing also the expressions for the likelihood marginalized over phase and distance. Then, we describe the details of the code in \texttt{Bilby}, an open-source software package commonly used for parameter estimation of gravitational-wave sources. Our code is able to reproduce the parameters of GW170817 in 14 hours on a single-core CPU, performs well on simulated signals, and passes the percentile-percentile (p-p) tests. We also illustrate that relative binning is an ideal technique to estimate the parameters of signals in next-generation gravitational wave detectors.
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