论文标题
实施有效的贝叶斯搜索引力波爆发，并在PULSAR时正时数组中使用内存
Implementation of an efficient Bayesian search for gravitational wave bursts with memory in pulsar timing array data
论文作者
论文摘要
使用马尔可夫链Monte Carlo（MCMC）采样的标准贝叶斯技术，用于搜索引力波（GW）带有内存（BWMS）的脉冲星定时数据的爆发非常昂贵。在本文中，我们解释了一种有效的贝叶斯技术来搜索BWM的实施。该技术利用了这样一个事实，即地球bwms的信号模型（经过地球）是完全分化的。我们估计该实施将计算复杂性降低了100倍。我们还证明，该技术具有使用标准贝叶斯技术的发布结果一致的上限，并且可以用于执行标准MCMC技术可以执行的所有相同分析。
The standard Bayesian technique for searching pulsar timing data for gravitational wave (GW) bursts with memory (BWMs) using Markov Chain Monte Carlo (MCMC) sampling is very computationally expensive to perform. In this paper, we explain the implementation of an efficient Bayesian technique for searching for BWMs. This technique makes use of the fact that the signal model for Earth-term BWMs (BWMs passing over the Earth) is fully factorizable. We estimate that this implementation reduces the computational complexity by a factor of 100. We also demonstrate that this technique gives upper limits consistent with published results using the standard Bayesian technique, and may be used to perform all of the same analyses that standard MCMC techniques can perform.
