Modelling the Impact of Stellar Feedback on Astrochemistry in Molecular Clouds

恒星形成于寒冷、致密的分子气体区域。恒星形成中的许多突出问题，包括恒星质量的起源和恒星形成的速度，首先依赖于准确确定有多少分子气体，其次依赖于这种气体的能量有多高。然而，没有一个单一的完美示踪剂可以测量所有的气体密度和温度。分子云中最丰富的分子，分子氢(H2)，实际上是看不见的。因此，获取基本信息需要了解氢与其他不太丰富的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，并将重点放在H2与一氧化碳(CO)和氰化氢(HCN)等容易观察到的分子之间的关系上。这项研究的目标是研究恒星形成分子云中化学丰度和谱线发射随恒星形成活动的演化。研究人员将对湍流的恒星形成云进行数值模拟，其中包括磁流体动力学、辐射传输、重力和恒星反馈。这个项目将使用全化学网络和多物理分子云模拟来研究观测和潜在物理量之间的关系。研究人员将定量探索三个基本问题：原子碳、CO和HCN排放与氢密度之间的关系是如何作为恒星形成活动的函数而演变的？像CO和HCN这样的示踪剂探测气体能量学并与整个恒星形成相关联的情况如何？原恒星外流产生的运动学反馈对天体化学有什么影响？这项工作对估算分子气体总质量、恒星形成效率以及分子云性质(温度、质量、速度弥散)与恒星形成率之间的对应关系具有重要意义。他们计划将丰度和排放地图存档，并通过网站“Datverse”与天文学团体共享。这将允许与包括阿塔卡马大毫米阵列(ALMA)数据在内的各种物种、云条件和物理尺度的观测数据进行比较。在该基金的支持下开发的新的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.