Accelerating parameter estimation of gravitational waves from compact binary coalescence using adaptive frequency resolutions
Accelerating parameter estimation of gravitational waves from compact binary coalescence using adaptive frequency resolutions
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DOI：
10.1103/physrevd.104.044062
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发表时间：
2021-04
影响因子：
5
通讯作者：
S. Morisaki
中科院分区：
文献类型：
--
作者：
S. Morisaki
从致密的双星合并(CBC)中估计引力波的贝叶斯参数通常需要对计算昂贵的模板波形进行数百万次以上的评估。我们提出了一种利用CBC信号的线性调频特性来降低波形产生成本的技术。我们的技术不需要在分析中使用的频率范围内的所有频率上的波形，也不会因为波形的上采样而受到固定成本的影响。我们的方法将典型双星中子星信号的参数估计速度提高了一个数学量{O}(10)$，当低频截止值为$20，mHZ时，提高了数学量{O}(10^2)$，对于$5，mHZ}$，提高了数学量{O}(10^2)$。它不需要任何离线准备或由检测管道提供的源参数的准确估计。
Bayesian parameter estimation of gravitational waves from compact binary coalescence (CBC) typically requires more than millions of evaluations of computationally expensive template waveforms. We propose a technique to reduce the cost of waveform generation by exploiting the chirping behavior of CBC signal. Our technique does not require waveforms at all frequencies in the frequency range used in the analysis, and does not suffer from the fixed cost due to the upsampling of waveforms. Our technique speeds up the parameter estimation of typical binary neutron star signal by a factor of $\mathcal{O}(10)$ for the low-frequency cutoff of $20\,\mathrm{Hz}$, and $\mathcal{O}(10^2)$ for $5\,\mathrm{Hz}$. It does not require any offline preparations or accurate estimates of source parameters provided by detection pipelines.