arXivDaily arXiv每日学术速递 周一至周五更新
arXiv 1503.05308astro-ph.HE
收藏

基于模拟和物理模型的伽马射线暴余辉分析

Simulation and physical model based gamma-ray burst afterglow analysis

Hendrik van Eerten

摘要:

在我们对伽马射线暴余辉过程的数值和理论理解方面取得的进展使我们能够构建能够处理复杂的相对论性喷流动力学和非热发射的模型,这些模型可以直接与Swift等仪器的数据进行比较。由于余辉爆炸波和幂律谱在爆炸能量和介质密度变化下具有固有的尺度不变性,因此可以从大尺度流体动力学模拟中生成模板。这允许使用物理模型参数(量化爆发器、发射和观测器的特性)直接作为拟合变量进行基于迭代模板的模型拟合。在这里,我回顾了这种余辉分析方法在实践中是如何工作的,特别注意这种类型的分析的基本模型假设,可能性,警告和限制。因为一些模型参数可以在参数空间的某些区域中退化,或者如果有限数量的a带中的数据可用则不受约束,所以贝叶斯方法是自然的拟合。详细介绍了标准余辉模型的主要特点。

英文摘要:

Advances in our numerical and theoretical understanding of gamma-ray burst afterglow processes allow us to construct models capable of dealing with complex relativistic jet dynamics and non-thermal emission, that can be compared directly to data from instruments such as Swift. Because afterglow blast waves and power law spectra are intrinsically scale-invariant under changes of explosion energy and medium density, templates can be generated from large-scale hydrodynamics simulations. This allows for iterative template-based model fitting using the physical model parameters (quantifying the properties of the burster, emission and observer) directly as fit variables. Here I review how such an approach to afterglow analysis works in practice, paying special attention to the underlying model assumptions, possibilities, caveats and limitations of this type of analysis. Because some model parameters can be degenerate in certain regions of parameter space, or unconstrained if data in a limited number of a bands is available, a Bayesian approach is a natural fit. The main features of the standard afterglow model are reviewed in detail.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

↑