Bayesian Inference of High-density Nuclear Symmetry Energy from Radii of Canonical Neutron Stars
Bayesian Inference of High-density Nuclear Symmetry Energy from Radii of Canonical Neutron Stars
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DOI：
10.3847/1538-4357/ab3f37
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发表时间：
2019-07
期刊：
影响因子：
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通讯作者：
Wen-Jie Xie;Bao-An Li
中科院分区：
文献类型：
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作者：
Wen-Jie Xie;Bao-An Li
质量为1.4 M的中子星半径R1.4在最近的许多研究文献中一直被提取。利用代表性的R1.4实验数据，利用核物质的参数状态方程（EOS），采用贝叶斯统计方法，推导了对称核物质（SNM）的高密度核对称能Esym（ρ）和核子比能E0（ρ）.我们发现了以下内容。(1)现有的天体物理学数据已经可以大大提高我们目前对ρ0 − 2.5ρ0密度范围内物态方程的认识。特别地，在68%的置信水平下，在核物质饱和密度ρ0的两倍处的对称能被确定为Esym（2ρ0）= MeV。(2)与我们从现有半径数据中提取的结果相比，仅精确测量R1.4，1σ统计误差为4%，但没有系统误差，不会大大改善对致密丰中子核子物质的物态方程的约束。(3)R1.4半径数据和其他一般条件，如观测到的NS最大质量和因果关系条件，为高阶EOS参数引入了强相关性。因此，推断的Esym（ρ）的高密度行为强烈依赖于高密度SNM EOS E0（ρ）的参数化方式，反之亦然。(4)观测到的最大NS质量的值以及它是否被用作最小最大质量的急剧截止值或通过高斯分布显著影响E0（ρ）和Esym（ρ）的下边界，仅在密度高于约2.5ρ0时。
The radius R1.4 of neutron stars (NSs) with a mass of 1.4 M⊙ has been extracted consistently in many recent studies in the literature. Using representative R1.4 data, we infer high-density nuclear symmetry energy Esym(ρ) and the associated nucleon specific energy E0(ρ) in symmetric nuclear matter (SNM) within a Bayesian statistical approach using an explicitly isospin-dependent parametric equation of state (EOS) for nucleonic matter. We found the following. (1) The available astrophysical data can already significantly improve our current knowledge about the EOS in the density range of ρ0 − 2.5ρ0. In particular, the symmetry energy at twice the saturation density ρ0 of nuclear matter is determined to be Esym(2ρ0)= MeV at a 68% confidence level. (2) A precise measurement of R1.4 alone with a 4% 1σ statistical error but no systematic error will not greatly improve the constraints on the EOS of dense neutron-rich nucleonic matter compared to what we extracted from using the available radius data. (3) The R1.4 radius data and other general conditions, such as the observed NS maximum mass and causality condition, introduce strong correlations for the high-order EOS parameters. Consequently, the high-density behavior of Esym(ρ) inferred depends strongly on how the high-density SNM EOS E0(ρ) is parameterized, and vice versa. (4) The value of the observed maximum NS mass and whether it is used as a sharp cutoff for the minimum maximum mass or through a Gaussian distribution significantly affects the lower boundaries of both E0(ρ) and Esym(ρ) only at densities higher than about 2.5ρ0.