Measuring the lifecycle of 30,000 molecular clouds across the main sequence of galaxies

测量星系主序中 30,000 个分子云的生命周期

• 批准号: 417450974
• 负责人: Dr. Mélanie Chevance, since 8/2022
• 金额: --
• 依托单位: Astronomisches Rechen-Institut
• 依托单位国家: 德国
• 项目类别: Research Grants
• 财政年份: 2018
• 资助国家: 德国
• 起止时间: 2017-12-31 至 2022-12-31
• 项目状态: 已结题
• 来源: https://gepris.dfg.de/gepris/projekt/417450974?language=en
• 关键词: Measuring; lifecycle; 30; 000; molecular

Star formation and stellar feedback play a critical role in galaxy evolution, but the underlying physical mechanisms are poorly understood. Stars form in a large variety of environments, and the interaction between star formation and the galactic environment is thought to be highly complex. Theories of star formation attempt to describe galactic star formation as the result of processes taking place within molecular clouds, but there exists a crucial lack of observational constraints on these small spatial scales - until recently, these were inaccessible to resolved observations.We will drive major progress in our understanding of star formation and feedback by exploiting our ongoing Large Programme on the Atacama Large Millimeter/submillimeter Array (ALMA), which has the unprecedented resolution and sensitivity needed to achieve detailed observations of molecular clouds in galaxies outside of the Local Group, enabling a statistically representative view of star formation across a wide variety of environments. Our group is world-leading in characterising the lifecycle of star formation and feedback from ALMA + optical observations of galaxies, using a new statistical method that we have developed in-house. Initial applications to a dozen galaxies reveal a great variety of cloud-scale conditions under which stars form (e.g. the molecular cloud lifetime, star formation efficiency, fragmentation scales) and exert stellar feedback (e.g. the timescales, velocities, and efficiencies with which stars dissipate their parent cloud), both between galaxies and within individual ones. The major question is where this variety comes from, and how it plausibly correlates with the galactic environment (e.g. gas surface density, galactic dynamics, morphology). Answering this question requires a statistically representative galaxy sample to probe the variety of environments in which stars formOur currently ongoing ALMA Large Programme provides the ideal opportunity to solve this problem by giving us access to 30,000 giant molecular clouds in 80 star-forming galaxies at the necessary (cloud-scale) resolution. We will apply our new analysis method, derive the above physical quantities describing cloud-scale star formation and feedback, and investigate their connection to the galactic environment. Analysing such a large galaxy sample is an ambitious project, which significantly expands the scope of our research and requires a dedicated researcher. It will provide the definitive observational characterisation of the multi-scale coupling between galaxy properties and cloud-scale star formation and stellar feedback, which is a critical step to identify the physical processes driving galaxy evolution.This project is well-embedded within our group and in the international PHANGS collaboration. It benefits from state-of-the-art in-hand data and a well-tested analysis method, which makes it a perfect project for a PhD student.

星星的形成和恒星反馈在星系演化中起着至关重要的作用，但其潜在的物理机制却知之甚少。恒星形成于各种各样的环境中，星星形成与银河系环境之间的相互作用被认为是高度复杂的。星星形成理论试图将银河系星星的形成描述为分子云内发生的过程的结果，但在这些小的空间尺度上存在着严重缺乏观测约束的问题-直到最近，我们将利用我们正在进行的阿塔卡马大毫米波大计划，推动我们对星星形成和反馈的理解取得重大进展。亚毫米阵列（阿尔马），它具有前所未有的分辨率和灵敏度，需要实现本星系群以外的星系分子云的详细观测，使统计代表性的看法星星形成在各种环境。我们的团队在表征星星形成的生命周期和来自阿尔马+星系光学观测的反馈方面处于世界领先地位，使用我们内部开发的新统计方法。对十几个星系的初步应用揭示了恒星形成的各种云尺度条件（例如分子云寿命，星星形成效率，碎片尺度）和施加恒星反馈（例如恒星消散其母云的时间尺度，速度和效率），无论是在星系之间还是在单个星系内。主要的问题是这种多样性来自哪里，以及它如何与银河系环境（例如气体表面密度，银河系动力学，形态学）相关。解决这个问题需要一个具有统计学代表性的星系样本来探测恒星形成的各种环境。我们目前正在进行的阿尔马大型计划提供了解决这个问题的理想机会，它使我们能够以必要的（云尺度）分辨率访问80个恒星形成星系中的30，000个巨大分子云。我们将应用我们新的分析方法，推导出上述描述云尺度星星形成和反馈的物理量，并研究它们与银河系环境的联系。分析如此大的星系样本是一个雄心勃勃的项目，它大大扩展了我们的研究范围，需要一个专门的研究人员。它将提供星系性质和云尺度星星形成和恒星反馈之间的多尺度耦合的确定性观测表征，这是识别驱动星系演化的物理过程的关键一步。它受益于最先进的手头数据和经过充分测试的分析方法，这使其成为博士生的完美项目。