论文标题
freckll：蒸馏蒸馏的全部和减少系外行星化学动力学
FRECKLL: Full and Reduced Exoplanet Chemical Kinetics distiLLed
论文作者
论文摘要
我们引入了一种新的Python 1D化学动力学代码FRECKLL（蒸馏蒸馏型外系化学动力学），以有效地发展大型化学网络。 Freckll在计算反应速率中采用“蒸馏”，从而将误差界限最小化至双精度值（$ε\ leq 10^{ - 15} $）允许的最小值。与传统算法（如成对求和）的速率求和相比，蒸馏为完整和减少网络的求解时间降低了十倍。完整的和减少的Venot2020网络都包装在Freckll中，以及用于向前建模和系外行星大气检索的Taurex 3.1插件。我们介绍使用完整和减少的Venot2020化学网络在模拟的HD189733 JWST光谱上进行的TAUREX检索，并证明了总不平衡化学检索的可行性以及JWST检测不平衡过程的能力。
We introduce a new Python 1D chemical kinetic code FRECKLL (Full and Reduced Exoplanet Chemical Kinetics distiLLed) to evolve large chemical networks efficiently. FRECKLL employs `distillation' in computing the reaction rates, which minimizes the error bounds to the minimum allowed by double precision values ($ε\leq 10^{-15}$). Compared to summation of rates with traditional algorithms like pairwise summation, distillation provides a tenfold reduction in solver time for both full and reduced networks. Both the full and reduced Venot2020 networks are packaged in FRECKLL as well as a TauREx 3.1 plugin for usage in forward modelling and retrievals of exoplanet atmospheres. We present TauREx retrievals performed on a simulated HD189733 JWST spectra using the full and reduced Venot2020 chemical networks and demonstrate the viability of total disequilibrium chemistry retrievals and the ability for JWST to detect disequilibrium processes.
