论文标题
优化的统计方法，用于比较多通间的中子星数据
Optimized Statistical Approach for Comparing Multi-Messenger Neutron Star Data
论文作者
论文摘要
现在，状态的中子星方程正在受到各种多通信器数据的限制，包括来自二进制中子星星合并的重力波，中子星形半径的X射线观察以及许多类型的实验室核实验。这些测量通常被映射到一个共同的域，以相互比较，或用于限制状态理论方程的预测。我们在这里探索当比较或组合不同域时，可能会出现的统计偏差。我们发现，将贝叶斯先验分别放置在每个测量领域都会导致偏见的约束。我们提出了一种新的处方，用于在不同的实验中始终定义贝叶斯先验，这将允许进行鲁棒的跨域比较。以前两个二元中子星合并为例，我们表明潮汐变形性的均匀先验可以产生大较大半径的膨胀证据，而半径的均匀先验则指向较小的半径。最后，使用此新处方，我们在中子星半径上提供了多通间子约束的状态更新。
The neutron star equation of state is now being constrained from a diverse set of multi-messenger data, including gravitational waves from binary neutron star mergers, X-ray observations of the neutron star radius, and many types of laboratory nuclear experiments. These measurements are often mapped to a common domain for comparison with one another or are used to constrain the predictions of theoretical equations of state. We explore here the statistical biases that can arise when such multi-messenger data are compared or combined across different domains. We find that placing Bayesian priors individually in each domain of measurement can lead to biased constraints. We present a new prescription for defining Bayesian priors consistently across different experiments, which will allow for robust cross-domain comparisons. Using the first two binary neutron star mergers as an example, we show that a uniform prior in the tidal deformability can produce inflated evidence for large radii, while a uniform prior in the radius points towards smaller radii. Finally, using this new prescription, we provide a status update on multi-messenger constraints on the neutron star radius.
