Iterative time-domain method for resolving multiple gravitational wave sources in pulsar timing array data
Iterative time-domain method for resolving multiple gravitational wave sources in pulsar timing array data
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DOI：
10.1103/physrevd.106.023016
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发表时间：
2021-10
影响因子：
5
通讯作者：
Yi-Qian Qian-Yi-Qian-Qian-102813016;S. Mohanty;Yan Wang
中科院分区：
文献类型：
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作者：
Yi-Qian Qian-Yi-Qian-Qian-102813016;S. Mohanty;Yan Wang
使用脉冲星定时阵列（PTAs）在超低频范围（10 − 9 Hz至10 − 7 Hz）中进行引力波（GW）源搜索的灵敏度将在未来继续增加，因为更多的定时器将被添加到阵列中。预计下一代射电望远镜，即500米口径球面射电望远镜（FAST）和平方公里阵列（SKA），将使适时射电望远镜的数量增加到O（10 3）。更高的灵敏度将导致GW源的更大距离，除了未解决的群体之外，还可以发现多个可解决的GW源。因此，需要数据分析技术，可以搜索和解决PTA数据中同时存在的多个信号。PTA数据分析中的多分辨率问题带来了一系列独特的挑战，例如非均匀采样数据，大量所谓的脉冲星相位参数，这些参数来自于到脉冲星的不准确测量距离，以及由于观测波形中的少量周期而导致傅立叶域中信号分离不良。我们提出了一种方法，可以解决这些挑战，并证明其性能与10 2至10 3 pathars从PTA的模拟数据。该方法使用多个细化阶段迭代地估计并从数据中减去来源，然后通过比较两种不同算法的输出来减少虚假识别的艾德来源。该方法的性能与迄今为止提出的全局拟合方法相比毫不逊色。在所有的情况下，在这项工作中测试的方法，对应于模拟数据中的真实源的比例超过78%和93%的大规模（10 - 3个源和200个源）和中等规模（10 - 2个源和100个源）PTA，分别。恢复出的真实源的网络信噪比可达16。43为大规模和9。07对于中等规模的PTA。
The sensitivity of ongoing searches for gravitational wave (GW) sources in the ultra-low frequency regime (10 − 9 Hz to 10 − 7 Hz) using Pulsar Timing Arrays (PTAs) will continue to increase in the future as more well-timed pulsars are added to the arrays. It is expected that next-generation radio telescopes, namely, the Five-hundred-meter Aperture Spherical radio Telescope (FAST) and the Square Kilometer Array (SKA), will grow the number of well-timed pulsars to O (10 3 ). The higher sensitivity will result in greater distance reach for GW sources, uncovering multiple resolvable GW sources in addition to an unresolved population. Data analysis techniques are, therefore, required that can search for and resolve multiple signals present simultaneously in PTA data. The multisource resolution problem in PTA data analysis poses a unique set of challenges such as non-uniformly sampled data, a large number of so-called pulsar phase parameters that arise from the inaccurately measured distances to the pulsars, and poor separation of signals in the Fourier domain due to a small number of cycles in the observed waveforms. We present a method that can address these challenges and demonstrate its performance on simulated data from PTAs with 10 2 to 10 3 pulsars. The method estimates and subtracts sources from the data iteratively using multiple stages of refinement, followed by a step that mitigates spurious identified sources by comparing the outputs from two different algorithms. The performance of the method compares favorably with the global fit approaches that have been proposed so far. In all the cases tested in this work, the fraction of sources found by the method that correspond to true sources in the simulated data exceeds 78% and 93% for a large-scale (with 10 3 pulsars and 200 sources) and a mid-scale (with 10 2 pulsars and 100 sources) PTA, respectively. The network signal to noise ratio of the recovered true sources reaches down to 16 . 43 for the large-scale and 9 . 07 for the mid-scale PTA.