Modelling the Impact of Stellar Feedback on Astrochemistry in Molecular Clouds

恒星形成于寒冷、密集的分子气体区域。恒星形成的许多突出问题，包括恒星质量的起源和恒星形成的速度，首先取决于精确地确定有多少分子气体，其次取决于气体的能量有多大。然而，对于所有的气体密度和温度，没有一种完美的示踪剂。分子云中最丰富的分子——氢分子（H2）实际上是看不见的。因此，获得基本信息需要了解H2与其他较少丰度物种的排放之间的关系，这些都是当地环境的复杂功能。这项研究将为理解不同恒星形成环境中的化学分布提供基础，并将重点研究H2与容易观察到的分子（如一氧化碳（CO）和氰化氢（HCN））之间的关系。本研究项目的目标是研究恒星形成分子云中化学丰度和谱线发射的演化作为恒星形成活动的函数。研究人员将对湍流、恒星形成云进行数值模拟，包括磁流体动力学、辐射转移、重力和恒星反馈。该项目将使用完整的化学网络与多物理场分子云模拟相结合，研究观测结果与潜在物理量之间的关系。研究者将定量地探索三个基本问题：原子碳、CO和HCN发射与H2密度之间的关系如何演变为恒星形成活动的函数？示踪剂，如CO和HCN，探测气体能量学和与总恒星形成的关系有多好？原恒星外流的运动学反馈对天体化学的影响是什么？这项工作对估计总分子气体质量、恒星形成效率以及分子云特性（温度、质量、速度色散）与恒星形成速率之间的对应关系具有重要意义。他们计划通过“Dataverse”网站将丰度和发射图存档并与天文学界分享。这将允许与观测结果进行比较，包括阿塔卡马大型毫米波阵列（ALMA）数据，用于广泛的物种，云条件和物理尺度。在这笔资金支持下开发的新数值方法也将公开发布。

Stars form within regions of cold, dense molecular gas. Many outstanding problems in star formation, including the origin of star masses and the rate of star formation, rely on first, accurately determining how much molecular gas there is and, second, how energetic that gas is. However, there is no single perfect tracer for all gas densities and temperatures. The most abundant molecule within molecular clouds, molecular hydrogen (H2), is virtually invisible. Consequently, obtaining fundamental information requires understanding the relation between H2 and the emission of other less abundant species, which are all complex functions of the local environment. This research will provide a basis for understanding chemical distributions in different star-forming environments and will focus on the relationship between H2 and easily observable molecules, such as carbon monoxide (CO) and hydrogen cyanide (HCN).The goal of this research project is to investigate the evolution of chemical abundances and line emission in star-forming molecular clouds as a function of star formation activity. The investigator will perform numerical simulations of turbulent, star-forming clouds that include magneto-hydrodynamics, radiative transfer, gravity and feedback from stars. This project will use full chemical networks coupled with multi-physics molecular cloud simulations to study the relationship between observations and underlying physical quantities. The investigator will quantitatively explore three fundamental questions: How does the relation between atomic carbon, CO, and HCN emission and H2 density evolve as a function of star formation activity? How well do tracers, such as CO and HCN, probe the gas energetics and correlate with total star formation? What is the impact of kinematic feedback due to proto-stellar outflows on astrochemistry? This work has implications for estimating the total molecular gas mass, star formation efficiency, and the correspondence between molecular cloud properties (temperature, mass, velocity dispersion) and the star formation rate. They plan to archive and share the abundance and emission maps with the astronomy community through the website "Dataverse". This will allow comparison with observations, including Atacama Large Millimeter Array (ALMA) data, for a wide range of species, cloud conditions, and physical scales. New numerical methods developed under the auspices of this funding will also be publicly released.