论文标题
在树环放射碳记录中对宇宙辐射事件进行建模
Modelling Cosmic Radiation Events in the Tree-ring Radiocarbon Record
论文作者
论文摘要
树环中的放射性碳含量的每年分辨测量结果显示，碳14的生产中罕见急剧上升。这些“ Miyake事件”可能是由于太阳或其他能量的天体物理来源的宇宙辐射罕见增加而产生的。产生的放射性碳不仅通过地球的大气和海洋循环，而且还被生物圈吸收并锁定在树木的年生长环中。因此，要解释高分辨率的树环放射性碳测量值，就必须对整个全球碳循环进行建模。在这里，我们介绍了“ ticktack”，这是第一个开源python软件包，将碳循环的框型号与现代贝叶斯推理工具连接起来。我们使用它来分析所有公共年度14C树数据，并针对所有六个已知的MIYAKE事件推断后验参数。它们与太阳周期没有一致的关系，并且显示了较长的持续时间，这些持续时间挑战天体物理或地球物理模型。
Annually-resolved measurements of the radiocarbon content in tree-rings have revealed rare sharp rises in carbon-14 production. These 'Miyake events' are likely produced by rare increases in cosmic radiation from the Sun or other energetic astrophysical sources. The radiocarbon produced is not only circulated through the Earth's atmosphere and oceans, but also absorbed by the biosphere and locked in the annual growth rings of trees. To interpret high-resolution tree-ring radiocarbon measurements therefore necessitates modelling the entire global carbon cycle. Here, we introduce 'ticktack', the first open-source Python package that connects box models of the carbon cycle with modern Bayesian inference tools. We use this to analyse all public annual 14C tree data, and infer posterior parameters for all six known Miyake events. They do not show a consistent relationship to the solar cycle, and several display extended durations that challenge either astrophysical or geophysical models.
