发表机构
China Agricultural University（中国农业大学）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本文提出利用完整脉冲星对协方差联合重建Hellings-Downs曲线，通过全角度最佳线性无偏估计器最小化各箱方差，在NANOGrav 15年数据上标准差最多降低12.9%，未来SKAO类PTA可降低达36.4%。
AI 中文摘要
脉冲星计时阵列（PTAs）通过不同脉冲星计时残差之间的空间相关性探测纳赫兹引力波。对于广义相对论中各向同性、非极化的随机背景，系综平均相关性遵循Hellings-Downs（HD）曲线；测量这一角分布模式可检验信号的引力波起源。标准的分箱逐点重建方法在每个角度箱内分别优化权重。我们利用完整的脉冲星对协方差联合重建该曲线，在每个箱中保留自由振幅。由此得到的全角度最佳线性无偏估计器使每个箱值及箱值的每个线性组合的方差最小化。应用于公开的NANOGrav 15年数据产品时，我们的方法将箱标准差最多降低12.9%，中位数降低9.5%。对于未来类似平方千米阵列天文台（SKAO）的PTA，预计降低幅度可达36.4%，中位数为29.6%，从而能够显著更精确地测量引力波背景。
英文摘要
Pulsar timing arrays (PTAs) detect nanohertz gravitational waves through spatial correlations between the timing residuals of different pulsars. For an isotropic, unpolarized stochastic background in general relativity, the ensemble-mean correlation follows the Hellings--Downs (HD) curve; measuring this angular pattern tests the gravitational-wave origin of the signal. Standard bin-by-bin reconstructions optimize the weights within each angular bin separately. We reconstruct the curve jointly using the full pulsar-pair covariance, retaining a free amplitude in every bin. The resulting all-angle best linear unbiased estimator minimizes the variance of every bin value and every linear combination of bins. Applied to the public NANOGrav 15 yr data products, our method reduces the bin standard deviations by up to 12.9\%, with a median reduction of 9.5\%. For a future Square Kilometre Array Observatory (SKAO)-like PTA, the predicted reduction reaches 36.4\%, with a median of 29.6\%, enabling significantly more precise measurements of the gravitational-wave background.
Comments7 pages, 3 figures
