Modelling the Impact of Stellar Feedback on Astrochemistry in Molecular Clouds

模拟恒星反馈对分子云中天体化学的影响

• 批准号: 1510021
• 负责人: Stella Offner
• 金额: $ 29.99万
• 依托单位: University of Massachusetts Amherst
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-08-15 至 2019-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1510021&HistoricalAwards=false
• 关键词: Modelling; Impact; Stellar; Feedback; Astrochemistry

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.

恒星在寒冷，密集的分子气体区域内形成。恒星形成中的许多出色问题，包括恒星质量的起源和恒星形成的速率，都依赖于首先确定有多少分子气体，其次，该气体的能量如何。但是，对于所有气体密度和温度，没有一个完美的示踪剂。分子云中最丰富的分子分子氢（H2）几乎是看不见的。因此，获得基本信息需要了解H2与其他较少丰富物种的发射之间的关系，这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，并将重点介绍H2和易于观察到的分子之间的关系，例如一氧化碳（CO）和氰化氢（HCN）。该研究项目的目的是研究化学丰度的演变和线形成的分子云中的化学物质和线发射的变化，以此为星形成所做的星体形成。研究者将对湍流的恒星形成云进行数值模拟，包括磁动力学，辐射转移，重力和恒星的反馈。该项目将使用完整的化学网络，再加上多物理分子云模拟，以研究观测和潜在物理量之间的关系。研究者将定量探讨三个基本问题：原子碳，CO和HCN发射与H2密度之间的关系如何随恒星形成活性的函数而演变？示踪剂（例如CO和HCN）如何探测气体能量并与恒星总形成相关？由于原版流出对天文学的影响，运动学反馈对运动的影响是什么？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，速度分散剂）与恒星形成速率之间的对应关系有影响。他们计划通过网站“数据”与天文学界共享并共享丰度和排放图。这将允许与观测值（包括Atacama大毫米阵列（ALMA）数据）进行比较，这些数据范围广泛，云条件和物理尺度。在此资金的主持下开发的新数值方法也将公开发布。