双中子星并合后引力波信号中体粘滞效应的可探测性
Detectability of bulk viscosity effects on post-merger gravitational wave signals from binary neutron star mergers
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中文总结 AI 辅助
本文研究双中子星并合后引力波中体粘滞效应的可探测性，发现仅对对称能量斜率大的状态方程模型可探测，且效应较弱，难以精确测量对称能量。
中文摘要 AI 辅助
我们研究了体粘滞（BV）效应对双中子星（BNS）并合后引力波（PMGW）信号的影响及其可探测性，使用了由近期引力波（GW）和X射线观测以及中子皮厚度测量所约束的、基于现实状态方程（EoS）的后验样本。我们采用一个基于近期含体粘滞的BNS模拟的线性拟合公式来估算由体粘滞效应引起的PMGW峰值频率偏移。随后，我们针对我们的EoS后验样本集评估了这一峰值频率偏移。我们利用Fisher信息矩阵以及ET和CE探测器网络在乐观情景下的模拟可观测事件数据集，来估算峰值频率的测量精度。我们发现，仅对于具有较大对称能量斜率（$L_{\ m sym}$）值的EoS模型（如中子皮厚度测量所青睐的），体粘滞效应对PMGW的影响才可能是可探测的。因此，对PMGW上体粘滞效应的探测本身可以提供关于对称能量及其斜率的丰富信息。然而，体粘滞效应对PMGW的影响通常较弱，可能仅在某些极端且乐观的情况下被观测到。因此，对PMGW的观测及其分析可能无法通过体粘滞效应提供非常精确的对称能量测量。
英文摘要
We investigate bulk viscosity (BV) effects on post-merger gravitational wave (PMGW) signals from binary neutron star (BNS) mergers and their detectability using realistic equation of state (EoS) posteriors constrained by recent progress in gravitational-wave (GW) and X-ray observations, as well as neutron skin thickness measurements. A linear fitting formula based on recent BNS simulations with BV is used to estimate the peak frequency shift of the PMGWs caused by BV effects. Subsequently, we evaluate this peak frequency shift for our set of EoS posterior samples. We use the Fisher information matrix and the dataset of simulated observable events from the ET and CE detector network in an optimistic scenario to estimate the measurement accuracy of the peak frequency. We find that BV effects on PMGWs may be detectable only for EoS models with large values of the symmetry energy slope ($L_{\rm sym}$), as favored by neutron-skin thickness measurements. Thus, the detection of BV effects on PMGWs itself can provide abundant information about the symmetry energy and its slope. However, BV effects on PMGWs are generally weak and may be observed only in some extreme and optimistic cases. Therefore, observations of PMGWs and their analyses may not be able to provide very accurate measurements of the symmetry energy through BV effects.
发表机构
- Rochester Institute of Technology（罗切斯特理工学院）
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