论文标题
利用网络拓扑来加速贝叶斯的推断晶粒表面反应网络
Exploiting Network Topology for Accelerated Bayesian Inference of Grain Surface Reaction Networks
论文作者
论文摘要
在对星际介质中晶粒表面化学的研究中，关于反应机制的不确定性很少，几乎没有限制的晶粒表面分子的限制。可以进行贝叶斯推断以确定可能的反应速率。在这项工作中，我们考虑通过查看网络的几何形状来减少在反应网络上进行贝叶斯推断的计算费用的方法。提出了利用反应网络拓扑的两种方法。其中一个涉及将反应网络减少到对反应链的限制。此后，将新的约束添加到反应网络中，并表明可以将这个新的反应网络分为子网络。可以将网络分为子网络的事实对于星际复合有机分子的反应网络尤其重要，该反应网络的表面反应网络可能具有数百个反应。两种方法都允许以最小偏置恢复最大的后方反应速率。
In the study of grain-surface chemistry in the interstellar medium, there exists much uncertainty regarding the reaction mechanisms with few constraints on the abundances of grain-surface molecules. Bayesian inference can be performed to determine the likely reaction rates. In this work, we consider methods for reducing the computational expense of performing Bayesian inference on a reaction network by looking at the geometry of the network. Two methods of exploiting the topology of the reaction network are presented. One involves reducing a reaction network to just the reaction chains with constraints on them. After this, new constraints are added to the reaction network and it is shown that one can separate this new reaction network into sub-networks. The fact that networks can be separated into sub-networks is particularly important for the reaction networks of interstellar complex organic molecules, whose surface reaction networks may have hundreds of reactions. Both methods allow the maximum-posterior reaction rate to be recovered with minimal bias.
