论文标题
确定最限制的冰观测到推断分子结合能
Identifying the most constraining ice observations to infer molecular binding energies
论文作者
论文摘要
为了理解晶曲面化学，必须对反应速率参数有很好的了解。对于基于扩散的反应，这些参数是反应物种的结合能。但是，由于缺乏足够的约束数据，使用贝叶斯推断从晶状表面丰度中估算这些值的尝试抑制了这些值。在这项工作中，我们使用大量优化的参数估计和数据（MOPED）压缩算法来确定应优先考虑哪些物种以使将来的ICE观测值更好地约束分子结合能。利用该算法的结果，我们提出建议将来应该关注的物种未来的观察结果。
In order to understand grain-surface chemistry, one must have a good understanding of the reaction rate parameters. For diffusion-based reactions, these parameters are binding energies of the reacting species. However, attempts to estimate these values from grain-surface abundances using Bayesian inference are inhibited by a lack of enough sufficiently constraining data. In this work, we use the Massive Optimised Parameter Estimation and Data (MOPED) compression algorithm to determine which species should be prioritised for future ice observations to better constrain molecular binding energies. Using the results from this algorithm, we make recommendations for which species future observations should focus on.
