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.

恒星形成于寒冷、致密的分子气体区域。星星形成中的许多突出问题，包括星星质量的起源和星星形成的速率，首先依赖于精确确定分子气体的数量，其次依赖于气体的能量。然而，没有一个单一的完美的示踪剂的所有气体密度和温度。分子云中最丰富的分子，分子氢（H2），几乎是不可见的。因此，获得基本信息需要了解H2和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。该研究将为理解不同恒星形成环境中的化学分布提供基础，并将重点关注H2与容易观测到的分子（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与星星形成活动的关系。研究人员将对湍流、恒星形成云进行数值模拟，包括磁流体力学、辐射传输、重力和恒星反馈。该项目将使用全化学网络结合多物理场分子云模拟来研究观测与基础物理量之间的关系。研究人员将定量探索三个基本问题：原子碳，CO和HCN排放和H2密度之间的关系如何演变为星星形成活动的函数？示踪剂，如CO和HCN，探测气体能量学和与总星星形成的相关性如何？什么是运动反馈的影响，由于原恒星外流天体化学？这项工作的影响，估计总分子气体质量，星星形成效率，和分子云的性质（温度，质量，速度色散）和星星形成率之间的对应关系。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（阿尔马）数据，用于广泛的物种，云条件和物理尺度。在这笔资金的支持下开发的新数值方法也将公开发布。