Quality over quantity: Optimizing pulsar timing array analysis for stochastic and continuous gravitational wave signals
Quality over quantity: Optimizing pulsar timing array analysis for stochastic and continuous gravitational wave signals
复制标题
质量重于数量：优化随机和连续引力波信号的脉冲星定时阵列分析
DOI：
10.1093/mnras/stac3237
复制
发表时间：
2022
影响因子：
4.8
通讯作者：
Taylor, Stephen R.
中科院分区：
文献类型：
--
作者：
Speri, Lorenzo;Porayko, Nataliya K.;Falxa, Mikel;Chen, Siyuan;Gair, Jonathan R.;Sesana, Alberto;Taylor, Stephen R.
使用脉冲星定时阵列(PTA)搜索引力波是一项计算昂贵的复杂分析，涉及特定来源的噪声研究。随着更多的脉冲星加入阵列，这一阶段的PTA分析将变得越来越具有挑战性。因此，优化包含脉冲星的数量对于减少数据分析的计算负担至关重要。在这里，我们提出了一套在PTA分析范围内使用的脉冲星排名方法。首先，我们用信噪比最大化作为选择脉冲星的指标。利用这种方法，我们的目标是检测随机和连续的引力波信号。接下来，我们给出一个排名，它最小化空间相关特征之间的耦合，即单极、偶极和Hellings&Down相关性。最后，我们还探讨了如何将这两种方法结合起来。我们使用频率统计法和贝叶斯假设检验法对这些方法进行测试。对于等噪声脉冲星，我们发现，对于引力波背景的假设检验，最佳选择导致对数贝叶斯因子的增加是随机选择的两倍，而不是常见的不相关红色噪声过程。对于相同的测试，但对于现实的欧洲PTA数据集，从40个脉冲星中选择的25个脉冲星的子集可以提供总的89 %的对数似然比，这意味着最佳选择的脉冲星子集可以产生与从整个阵列获得的结果相当的结果。我们预计这些选择方法将在未来的PTA数据组合中发挥关键作用。
The search for gravitational waves using Pulsar Timing Arrays (PTAs) is a computationally expensive complex analysis that involves source-specific noise studies. As more pulsars are added to the arrays, this stage of PTA analysis will become increasingly challenging. Therefore, optimizing the number of included pulsars is crucial to reduce the computational burden of data analysis. Here, we present a suite of methods to rank pulsars for use within the scope of PTA analysis. First, we use the maximization of the signal-to-noise ratio as a proxy to select pulsars. With this method, we target the detection of stochastic and continuous gravitational wave signals. Next, we present a ranking that minimizes the coupling between spatial correlation signatures, namely monopolar, dipolar, and Hellings & Downs correlations. Finally, we also explore how to combine these two methods. We test these approaches against mock data using frequentist and Bayesian hypothesis testing. For equal-noise pulsars, we find that an optimal selection leads to an increase in the log-Bayes factor two times steeper than a random selection for the hypothesis test of a gravitational wave background versus a common uncorrelated red noise process. For the same test but for a realistic European PTA (EPTA) data set, a subset of 25 pulsars selected out of 40 can provide a log-likelihood ratio that is 89 % of the total, implying that an optimally selected subset of pulsars can yield results comparable to those obtained from the whole array. We expect these selection methods to play a crucial role in future PTA data combinations.