一种新的通用Gamma-Ray蒙特卡罗辐射转移程序
A New Versatile Code for Gamma-Ray Monte-Carlo Radiative Transfer
摘要：
正在进行的MeV望远镜，如INTEGRAL/SPI和Fermi/GBM，以及拟议中的望远镜，包括最近接受的COSI和e-ASTROGAM和AMEGO任务，为理解瞬变提供了另一个窗口。它们的信号包含有关恒星爆炸机制及其相应的短寿命放射性同位素核合成的信息。这就需要一个辐射转移代码，可以有效地探索不同类型的天体物理$γ$射线源和它们的依赖模型参数和输入物理。鉴于此，我们提出了新的蒙特卡罗辐射转移的Python代码。该代码综合了适用于模拟超新星喷出物的$γ$射线光谱和光变曲线，包括C+O新星，O+Ne新星，Ia型和核心塌陷超新星。我们广泛测试的代码再现结果与分析模型一致。我们还将我们的结果与文献中的类似模型进行了比较，并讨论了我们的代码如何依赖于选定的输入物理和设置。
英文摘要：
Ongoing MeV telescopes such as INTEGRAL/SPI and Fermi/GBM, and proposed telescopes including the recently accepted COSI and the e-ASTROGAM and AMEGO missions, provide another window in understanding transients. Their signals contain information about the stellar explosion mechanisms and their corresponding nucleosynthesis of short-lived radioactive isotopes. This raises the need of a radiative transfer code which may efficiently explore different types of astrophysical $γ$-ray sources and their dependence on model parameters and input physics. In view of this, we present our new Monte-Carlo Radiative Transfer code in Python. The code synthesizes the $γ$-ray spectra and light curves suitable for modeling supernova ejecta, including C+O novae, O+Ne novae, Type Ia and core-collapse supernovae. We test the code extensively for reproducing results consistent with analytic models. We also compare our results with similar models in the literature and discuss how our code depends on selected input physics and setting.
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。
