标题： 用引力波约束中子物质的状态方程 显示英文标题

标题： Constraining the neutron-matter equation of state with gravitational waves

摘要： 我们展示如何在未来几年内对双中子星（BNS）并合产生的引力波观测结果与核物理的见解相结合，以获得对致密物质状态方程（EoS）的有用约束，特别是将中子物质状态方程限制在核饱和密度的一到两倍之间，误差不超过20%$n_0\approx 0.16\ {\text{fm}^{-3}}$。 使用费舍尔信息方法，我们将从各种种群模型中抽取的模拟BNS并合事件的观测约束与独立的中子星半径测量结果相结合，这些测量结果预期来自X射线天文学（尤其是中子星内部成分探测器（NICER）的观测），以直接约束核物理参数。 为了参数化核状态方程，我们采用了一种不同的方法，从纯核物质展开，而不是从对称核物质展开，以利用最近的量子蒙特卡洛（QMC）计算。 这种方法避免了需要引入所谓的抛物线近似来从对称核物质外推，使我们能够直接约束中子物质状态方程。 通过主成分分析，我们确定了最受观测数据约束的参数组合。 我们讨论了对各种效应的敏感性，例如通过种群模型敏感性对不同组分质量的敏感性、核心状态方程中的相变以及中心参数值的大幅偏离。 显示英文摘要

摘要： We show how observations of gravitational waves from binary neutron star (BNS) mergers over the next few years can be combined with insights from nuclear physics to obtain useful constraints on the equation of state (EoS) of dense matter, in particular, constraining the neutron-matter EoS to within 20% between one and two times the nuclear saturation density $n_0\approx 0.16\ {\text{fm}^{-3}}$. Using Fisher information methods, we combine observational constraints from simulated BNS merger events drawn from various population models with independent measurements of the neutron star radii expected from x-ray astronomy (the Neutron Star Interior Composition Explorer (NICER) observations in particular) to directly constrain nuclear physics parameters. To parameterize the nuclear EoS, we use a different approach, expanding from pure nuclear matter rather than from symmetric nuclear matter to make use of recent quantum Monte Carlo (QMC) calculations. This method eschews the need to invoke the so-called parabolic approximation to extrapolate from symmetric nuclear matter, allowing us to directly constrain the neutron-matter EoS. Using a principal component analysis, we identify the combination of parameters most tightly constrained by observational data. We discuss sensitivity to various effects such as different component masses through population-model sensitivity, phase transitions in the core EoS, and large deviations from the central parameter values.