cosmic-ray传播的贝叶斯分析：反对均匀扩散的证据
Bayesian analysis of cosmic-ray propagation: evidence against homogeneous diffusion
摘要：
我们提出了有史以来最完整的扫描宇宙射线（CR）注入和传播的参数空间的结果。我们执行贝叶斯搜索的主要GALPROP参数，使用MultiNest嵌套采样算法，增强BAMBI神经网络机器学习包。这是第一次将低质量同位素（$p$，$\bar p$和He）从常见的轻元素（Be，B，C，N，O）中分离出来的研究。我们发现，最适合$p$，$\bar p$，他的数据的传播参数是显着不同的那些适合轻元素，包括B/C和$^{10}$ Be/ $^9$ Be的次级到初级的比率通常用于校准传播参数。这表明每一组物种都在探测一种非常不同的星际介质，而使用B/C校准传播参数的标准方法可能会导致错误的结果。我们提出了后验分布和最佳拟合参数的两套核的传播，以及从H到Si的元素注入丰度。具有这些新参数的输入GALDEF文件将包含在即将发布的公共GALPROP更新中。
英文摘要：
We present the results of the most complete ever scan of the parameter space for cosmic ray (CR) injection and propagation. We perform a Bayesian search of the main GALPROP parameters, using the MultiNest nested sampling algorithm, augmented by the BAMBI neural network machine learning package. This is the first such study to separate out low-mass isotopes ($p$, $\bar p$ and He) from the usual light elements (Be, B, C, N, O). We find that the propagation parameters that best fit $p$, $\bar p$, He data are significantly different from those that fit light elements, including the B/C and $^{10}$Be/$^9$Be secondary-to-primary ratios normally used to calibrate propagation parameters. This suggests each set of species is probing a very different interstellar medium, and that the standard approach of calibrating propagation parameters using B/C can lead to incorrect results. We present posterior distributions and best fit parameters for propagation of both sets of nuclei, as well as for the injection abundances of elements from H to Si. The input GALDEF files with these new parameters will be included in an upcoming public GALPROP update.
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