Self-consistent Modeling of the Dynamics and Chemistry of Molecular Clouds in Different Evolutionary Stages

恒星的形成过程涵盖了各种物理条件和大小尺度。它还涉及到各种动力学过程。由于很难直接观测到最丰富的分子H2，我们被迫通过观察不一定与分子氢很好混合的痕量物种来评估恒星形成区域的动力学状态。因此，为了充分解释观测结果，需要动力学和化学演化的自洽模型。我们打算创建这样一个模型，其中考虑了所有相关过程，包括关于化学反应速度、冷却和加热速度、扩散和颗粒表面反应的最新信息。该模型将与一维和二维流体动力学模型相耦合，并与其他化学代码和观测数据进行比较。

The process of star formation covers a tremendous range of physical conditions and size scales. It also involves a variety of dynamical processes. Due to the difficulty of direct observations of the most abundant molecule H2, we are forced to assess the dynamical state of star-forming regions through observations of trace species that are not necessarily well mixed with molecular hydrogen. Thus, to interpret adequately results of observations, self-consistent models of the dynamical and chemical evolution are required. We intend to create such a model in which all relevant processes are taken into account, including up-to-date information about the chemical reaction rates, cooling and heating rates, diffusion, and grain surface reactions. This model will be coupled with 1D- and 2D-hydrodynamical models and compared with other chemical codes and observational data.