标题： 从NICER脉冲轮廓得出的系统学方法在中子星状态方程的多信使推断中引起不确定性 显示英文标题

标题： Systematics from NICER Pulse Profiles Drive Uncertainty in Multi-Messenger Inference of the Neutron Star Equation of State

摘要： 我们使用一种统一的贝叶斯推断框架，结合最新的NICER测量数据，包括PSR J0614$-$3329，以及引力波数据、射电脉冲星质量和核理论，对中子星状态方程（EOS）和质量分布提出了新的约束。 通过系统比较四种推断场景——在PSR J0614$-$3329的包含情况以及用于PSR J0030+0451的脉冲轮廓模型上有所不同——我们量化了观测和建模选择对致密物质推断的影响。 我们发现脉冲轮廓系统误差主导了EOS不确定性：PSR J0030+0451热点几何形状的选择导致了推断出的EOS刚度和最大中子星质量的显著变化。 相比之下，PSR J0614$-$3329在低密度下略微软化了EOS，使\(1.4\,M_\odot\)的半径减少了\(\sim 100\)~m。 贝叶斯模型比较得出一个贝叶斯因子为$\log_{10} \mathrm{BF} \approx 1.58$，支持ST+PDT模型优于PDT-U，提供了强有力的证据，表明多信使EOS推断可以统计区分竞争的NICER脉冲轮廓模型。 这些结果突显了NICER系统误差在致密物质推断中的关键作用，以及联合分析在打破建模退化中的强大能力。 显示英文摘要

摘要： We present new constraints on the neutron star equation of state (EOS) and mass distribution using a unified Bayesian inference framework that incorporates latest NICER measurements, including PSR J0614$-$3329, alongside gravitational wave data, radio pulsar masses, and nuclear theory. By systematically comparing four inference scenarios--varying in the inclusion of PSR J0614$-$3329 and in the pulse profile model used for PSR J0030+0451--we quantify the impact of observational and modeling choices on dense matter inference. We find that pulse profile systematics dominate EOS uncertainties: the choice of hot spot geometry for PSR J0030+0451 leads to significant shifts in the inferred stiffness of the EOS and maximum neutron star mass. In contrast, PSR J0614$-$3329 mildly softens the EOS at low densities, reducing the radius at \(1.4\,M_\odot\) by \(\sim 100\)~m. A Bayesian model comparison yields a Bayes factor of $\log_{10} \mathrm{BF} \approx 1.58$ in favor of the ST+PDT model over PDT-U, providing strong evidence that multi-messenger EOS inference can statistically discriminate between competing NICER pulse profile models. These results highlight the critical role of NICER systematics in dense matter inference and the power of joint analyses in breaking modeling degeneracies.