论文标题
射流结构的全球测试和短期伽马射线爆发的延迟时间分布
A global test of jet structure and delay time distribution of short-duration gamma-ray bursts
论文作者
论文摘要
GW170817和GRB170817A的多通信剂联合观察为短期伽马射线爆发(SGRB)的研究提供了新的启示。它不仅证实了SGRB源自二进制中子星(BNS)合并的假设,而且还证实了由这种合并产生的射流必须是结构的,因此SGRB的观察到的能量取决于观察者的视角。但是,喷气机的确切结构仍可能存在争论。此外,尚不清楚是否可以将单个统一的喷气模型应用于所有SGRB。另一个不确定性是BNS合并有关宇宙恒星形成历史的延迟时间尺度。在本文中,我们对跨广泛的参数空间进行了模拟SGRB的延迟和JET模型进行全球测试。我们将模拟峰通量,红移和光度分布与观察到的峰值进行比较,并测试一组模型和参数组合的拟合优度。我们的模拟表明,GW170817/GRB 170817A和所有SGRB都可以在以不同的视角查看的通用结构喷射的框架内理解。此外,最有利的模型调用带有对数正态延迟时间尺度的Jet Plus Cocoon结构。也可以接受其他一些组合(例如使用幂律喷气机模型的高斯延迟)。但是,使用高斯喷气机模型的高斯延迟以及整个幂律延迟模型均不利。
The multi-messenger joint observations of GW170817 and GRB170817A shed new light on the study of short-duration gamma-ray bursts (SGRBs). Not only did it substantiate the assumption that SGRBs originate from binary neutron star (BNS) mergers, but it also confirms that the jet generated by this type of merger must be structured, hence the observed energy of an SGRB depends on the viewing angle from the observer. However, the precise structure of the jet is still subject to debate. Moreover, whether a single unified jet model can be applied to all SGRBs is not known. Another uncertainty is the delay timescale of BNS mergers with respect to star formation history of the Universe. In this paper, we conduct a global test of both delay and jet models of BNS mergers across a wide parameter space with simulated SGRBs. We compare the simulated peak flux, redshift and luminosity distributions with the observed ones and test the goodness-of-fit for a set of models and parameter combinations. Our simulations suggest that GW170817/GRB 170817A and all SGRBs can be understood within the framework of a universal structured jet viewed at different viewing angles. Furthermore, models invoking a jet plus cocoon structure with a lognormal delay timescale is most favored. Some other combinations (e.g. a Gaussian delay with a power-law jet model) are also acceptable. However, the Gaussian delay with Gaussian jet model and the entire set of power-law delay models are disfavored.