Unpacking Merger Jets: A Bayesian Analysis of GW170817, GW190425 and Electromagnetic Observations of Short Gamma-Ray Bursts
Unpacking Merger Jets: A Bayesian Analysis of GW170817, GW190425 and Electromagnetic Observations of Short Gamma-Ray Bursts
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拆开合并喷气机：GW170817、GW190425 的贝叶斯分析和短伽马射线爆发的电磁观测
DOI：
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发表时间：
2023
影响因子：
4.9
通讯作者：
Michael J. Williams
中科院分区：
文献类型：
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作者：
F. Hayes;I. Heng;G. Lamb;E. Lin;J. Veitch;Michael J. Williams
我们提出了一种新颖的完全贝叶斯分析，以约束与茧、广角和简单顶帽喷流模型相关的短伽马射线爆发（sGRB）喷流结构，以及双中子星（BNS）合并率。这些约束是根据 GW170817 的距离和倾角信息、GRB 170817A 的观测通量、Swift 检测到的 sGRB 的观测速率以及从 LIGO 第一次和第二次观测运行推断出的中子星合并速率而制定的。进行了单独的分析，其中包括拟合的 sGRB 光度函数以提供进一步的约束。使用 GW190425 的观测进一步约束喷流结构模型，我们发现它产生了类似 GRB 170817 的 sGRB（由于喷流几何形状而未被检测到）的假设与之前的观测结果一致。我们发现并量化了 sGRB 群中低光度和广角喷流结构的证据，独立于余辉观测，与经典的顶帽喷流相比，此类模型的对数贝叶斯因子为 0.45-0.55。当提供拟合的光度函数时，发现高斯射流结构模型优于所有其他模型的少量证据，与其他模型相比，产生 0.25-0.9 ± 0.05 的对数贝叶斯因子。然而，在不考虑 GW190425 或拟合的光度函数的情况下，证据倾向于采用对数贝叶斯因子为 0.14 ± 0.05 的茧状模型，而不是高斯射流结构。当假设拟合光度函数时，我们对 BNS 合并率提供新的约束，即 1–1300 Gpc−3 yr−1 或 2–680 Gpc−3 yr−1。
We present a novel fully Bayesian analysis to constrain short gamma-ray burst (sGRB) jet structures associated with cocoon, wide-angle, and simple top-hat jet models, as well as the binary neutron star (BNS) merger rate. These constraints are made given the distance and inclination information from GW170817, observed flux of GRB 170817A, observed rate of sGRBs detected by Swift, and the neutron star merger rate inferred from LIGO’s first and second observing runs. A separate analysis is conducted where a fitted sGRB luminosity function is included to provide further constraints. The jet structure models are further constrained using the observation of GW190425, and we find that the assumption that it produced a GRB 170817–like sGRB which went undetected due to the jet geometry is consistent with previous observations. We find and quantify evidence for low-luminosity and wide-angle jet structuring in the sGRB population, independently from afterglow observations, with log Bayes factors of 0.45–0.55 for such models when compared to a classical top-hat jet. Slight evidence is found for a Gaussian jet structure model over all others when the fitted luminosity function is provided, producing log Bayes factors of 0.25–0.9 ± 0.05 when compared to the other models. However, without considering GW190425 or the fitted luminosity function, the evidence favors a cocoon-like model with log Bayes factors of 0.14 ± 0.05 over the Gaussian jet structure. We provide new constraints to the BNS merger rates of 1–1300 Gpc−3 yr−1 or 2–680 Gpc−3 yr−1 when a fitted luminosity function is assumed.