发表机构
Department of Physics and Astronomy, East Texas A&M University（东德克萨斯农工大学物理与天文系）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本研究借助贝叶斯框架与元模型物态方程，探究未来高精度中子星半径测量如何编码致密物态方程微观信息及强子-夸克一级相变，构建逆映射分析参数敏感性与拓扑关联，明确半径测量的科学回报层级与局限。
AI 中文摘要
我们探究未来高精度中子星（NS）半径测量如何编码致密物态方程（EOS）的微观信息，重点关注可能的强子-夸克一级相变及由此产生的质量-半径拓扑结构。在贝叶斯框架下，我们采用含9个微观参数的元模型物态方程，分析了典型中子星的模拟半径测量值$R_{1.4}=11.9\pmσ_R$ km（对应$σ_R=0.9$）和$0.1$ km。我们构建了物态方程-半径逆映射，该映射给出每个物态方程参数的后验均值随$R_{1.4}$的变化关系。映射的斜率衡量半径敏感性，而曲率则通过詹森展开决定后验均值的主导精度依赖关系。将映射分解为连通、断开、两者兼有、无夸克物质四种质量-半径拓扑后，可揭示出清晰的信息层级。对称能参数$L$（斜率）和$K_{\rm sym}$（曲率）被强编码于$R_{1.4}$中，且其后验均值随半径精度提升发生显著偏移，而高阶强子参数则表现出更强的拓扑依赖性。在相变参数中，相变密度$ρ_t$在$R_{1.4}$中编码程度最强，而能量密度跃变和夸克物质声速则与完整质量-半径序列的拓扑关联更紧密。由于不同拓扑的$R_{1.4}$分布存在高度重叠，即便精确的半径测量也无法单独识别拓扑结构，或唯一确定高密度相变性质。这些结果为评估未来高精度半径测量的科学回报，以及高密度区的互补探测手段提供了依赖于参数的层级框架。
英文摘要
We investigate how future high-precision neutron star (NS) radius measurements encode microscopic information about the dense-matter equation of state (EOS), focusing on a possible first-order hadron--quark phase transition and the resulting mass--radius topology. Within a Bayesian framework using meta-model EOSs with nine microscopic parameters, we analyze mock radius measurements $R_{1.4}=11.9\pmσ_R$ km with $σ_R=0.9$ and $0.1$ km for canonical NSs. We introduce inverse EOS--radius mappings by studying the conditional mean of each EOS parameter as a function of the model-predicted canonical radius $R_{1.4}$. Their slope measures the sensitivity of an EOS parameter to the radius, while their curvature determines the leading precision dependence of its posterior mean through the Jensen expansion. The symmetry-energy parameters $L$ (slope) and $K_{\rm sym}$ (curvature) are strongly encoded in $R_{1.4}$ and their posterior means shift appreciably with improved radius precision, whereas the higher-order hadronic parameters show stronger topology dependence. Among the transition parameters, the transition density $ρ_t$ is the most strongly encoded in $R_{1.4}$, while the energy-density jump and quark-matter sound speed are more strongly associated with the topology of the full mass--radius sequence. Since the different topologies have strongly overlapping $R_{1.4}$ distributions, even precise radius measurements cannot by themselves identify the topology or uniquely determine the high-density transition properties. These results provide a parameter-dependent hierarchy for assessing the scientific return of future high-precision radius measurements and complementary probes of high-density NS EOS.
CommentsVersion accepted by APJ. More analytical results on inverse EOS-radius mapping, nonlinear filtering and Jensen expansion added
