NANOGrav 12.5 年数据集：各向同性随机引力波背景的搜寻
高能天体物理现象
2021-01-11 v2 星系天体物理
广义相对论与量子宇宙学
摘要
我们在北美纳赫兹引力波天文台收集的 年脉冲星计时数据集中搜寻各向同性随机引力波背景(GWB)。我们的分析发现了强证据表明存在一个随机过程，建模为幂律，且在各脉冲星间具有共同振幅和谱斜率。对于 幂律谱，以特征引力波应变表示的振幅贝叶斯后验在中位数 处，且在参考频率 处的 -- 分位数为 --。支持共同谱过程相对于各脉冲星独立红噪声过程的贝叶斯因子超过 。然而，我们发现该过程具有四极空间相关性的统计显著证据不足，而我们将此视为宣称与广义相对论一致的 GWB 探测所必需的。我们发现该过程既无单极也无偶极相关性，这可能分别源于参考钟或太阳系星历的系统误差。振幅后验在先前报道的上限之上有显著支撑；我们用为脉冲星内禀红噪声所假设的贝叶斯先验来解释这一点。我们在该信号确为天体物理起源的假设下，考察了对超大质量黑洞双星群体的潜在含义。
引用
@article{arxiv.2009.04496,
title = {The NANOGrav 12.5-year Data Set: Search For An Isotropic Stochastic Gravitational-Wave Background},
author = {Zaven Arzoumanian and Paul T. Baker and Harsha Blumer and Bence Becsy and Adam Brazier and Paul R. Brook and Sarah Burke-Spolaor and Shami Chatterjee and Siyuan Chen and James M. Cordes and Neil J. Cornish and Fronefield Crawford and H. Thankful Cromartie and Megan E. DeCesar and Paul B. Demorest and Timothy Dolch and Justin A. Ellis and Elizabeth C. Ferrara and William Fiore and Emmanuel Fonseca and Nathan Garver-Daniels and Peter A. Gentile and Deborah C. Good and Jeffrey S. Hazboun and A. Miguel Holgado and Kristina Islo and Ross J. Jennings and Megan L. Jones and Andrew R. Kaiser and David L. Kaplan and Luke Zoltan Kelley and Joey Shapiro Key and Nima Laal and Michael T. Lam and T. Joseph W. Lazio and Duncan R. Lorimer and Jing Luo and Ryan S. Lynch and Dustin R. Madison and Maura A. McLaughlin and Chiara M. F. Mingarelli and Cherry Ng and David J. Nice and Timothy T. Pennucci and Nihan S. Pol and Scott M. Ransom and Paul S. Ray and Brent J. Shapiro-Albert and Xavier Siemens and Joseph Simon and Renee Spiewak and Ingrid H. Stairs and Daniel R. Stinebring and Kevin Stovall and Jerry P. Sun and Joseph K. Swiggum and Stephen R. Taylor and Jacob E. Turner and Michele Vallisneri and Sarah J. Vigeland and Caitlin A. Witt},
journal= {arXiv preprint arXiv:2009.04496},
year = {2021}
}
备注
25 pages, 14 figures, 5 tables, 3 appendices. Published in The Astrophysical Journal Letters. Please send any comments/questions to Joseph Simon ([email protected]). Jupyter notebook tutorials and some MCMC chain files are available at https://github.com/nanograv/12p5yr_stochastic_analysis