论文标题
贝叶斯堆栈中的针头：一种层次的贝叶斯方法，用于用二元中子星的合奏来限制状态的中子星方程
Needle in a Bayes Stack: a Hierarchical Bayesian Method for Constraining the Neutron Star Equation of State with an Ensemble of Binary Neutron Star Post-merger Remnants
论文作者
论文摘要
二进制中子星（BNS）合并后引力波发射可以在BNS合并后发生 - 前提是系统避免了迅速崩溃到黑洞中 - 作为可抗性的高质量残留经历四极性振荡和非轴对称性变形。合并后的重力波谱具有特征性的峰值频率，该峰频率已被证明取决于二进制chirp质量和状态的中子星方程（EOS），使合并后的引力波成为约束中子星组成的强大工具。不幸的是，BNS后合并信号以高（$ \ gtrsim 1.5 $ kHz）的频率发射，基于地面的重力波检测器的灵敏度降低。因此，直到下一代探测器出现，结合后信号不太可能以足够的信噪比（SNR）检测到。但是，通过采用源自数值相对性模拟的经验关系，我们可以在BNS合并的集合中结合信息，从而使我们能够获得具有许多低SNR信号的EOS约束。我们提出了一种分层贝叶斯方法，用于在$ r_ {1.6} $上得出约束，这是1.6 $ \ mathrm {m _ {\ odot}} $中子星的半径，通过二元中性恒星合并的集合分析。我们将此方法应用于接下来的两个Ligo-Virgo-Kagra观察跑步，即O4和O5，以及以A+敏感性的延长的4年运行，这表明了我们从与电流生成检测器的通道后信号中产生EOS信息的方法。 The A+ 4-year scenario is predicted to improve the constraint on $R_{1.6}$ from the currently available multimessenger-based 95\% credible interval (C.I.) uncertainty of $R_{1.6}=12.07^{+0.98}_{-0.77}$ km to $ r_ {1.6} = 11.91^{+0.80} _ { - 0.56} $ km，减少95％C.I.宽度。
Binary neutron star (BNS) post-merger gravitational-wave emission can occur in the aftermath of a BNS merger -- provided the system avoids prompt collapse to a black hole -- as a quasistable hypermassive remnant experiences quadrupolar oscillations and non-axisymmetric deformations. The post-merger gravitational-wave spectrum possesses a characteristic peak frequency that has been shown to be dependent on the binary chirp mass and the neutron star equation of state (EoS), rendering post-merger gravitational waves a powerful tool for constraining neutron star composition. Unfortunately, the BNS post-merger signal is emitted at high ($\gtrsim 1.5$ kHz) frequencies, where ground-based gravitational wave detectors suffer from reduced sensitivity. It is therefore unlikely that post-merger signals will be detected with sufficient signal-to-noise ratio (SNR) until the advent of next-generation detectors. However, by employing empirical relations derived from numerical relativity simulations, we can combine information across an ensemble of BNS mergers, allowing us to obtain EoS constraints with many low-SNR signals. We present a hierarchical Bayesian method for deriving constraints on $R_{1.6}$, the radius of a 1.6$\mathrm{M_{\odot}}$ neutron star, through an ensemble analysis of binary neutron star mergers. We apply this method to simulations of the next two LIGO-Virgo-KAGRA observing runs, O4 and O5, as well as an extended 4-year run at A+ sensitivity, demonstrating the potential of our approach to yield EoS information from the post-merger signal with current-generation detectors. The A+ 4-year scenario is predicted to improve the constraint on $R_{1.6}$ from the currently available multimessenger-based 95\% credible interval (C.I.) uncertainty of $R_{1.6}=12.07^{+0.98}_{-0.77}$ km to $R_{1.6}=11.91^{+0.80}_{-0.56}$ km, a 22% reduction of the 95% C.I. width.
