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arXiv 1707.02879astro-ph.GA
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演化中分子云的恒星形成

Star formation in evolving molecular clouds

M. Völschow, R. Banerjee, B. Körtgen

摘要:

分子云是我们宇宙的主要恒星摇篮,使它们成为观测和理论研究的焦点。从观测结果来看,分子云的一些关键性质是众所周知的,但关于它们的演化和恒星形成活动的许多问题仍然是开放的。虽然数值模拟涉及大量复杂的物理过程,但这些大量的影响可能隐藏了决定分子云演化和恒星形成的基本原理。另一方面,Pestrian分析模型往往受到粗略近似或缺乏完整性的影响,限制了它们的预测能力。在本文中,我们提出了一个模型,结合了天体物理学的核心概念,以及可靠的结果,从最近的分子云模拟及其演化路径。在此基础上,我们构建了一个自洽的半分析框架,描述了分子云的形成,演化和恒星形成活动,包括一些反馈效应来解释这些物体内部的复杂过程。最终的方程组是数值求解的,但计算费用比,例如,可比较系统的流体动力学描述。本文提出的模型与广泛的观测结果一致,表明分子云演化可以理解为吸积,全球崩溃,恒星形成和恒星反馈之间的相互作用。

英文摘要:

Molecular clouds are the principle stellar nurseries of our universe, keeping them in the focus of both observational and theoretical studies. From observations, some of the key properties of molecular clouds are well known but many questions regarding their evolution and star formation activity remain open. While numerical simulations feature a large number and complexity of involved physical processes, this plenty of effects may hide the fundamentals that determine the evolution of molecular clouds and enable the formation of stars. Purely analytical models, on the other hand, tend to suffer from rough approximations or a lack of completeness, limiting their predictive power. In this paper, we present a model that incorporates central concepts of astrophysics as well as reliable results from recent simulations of molecular clouds and their evolutionary paths. Based on that, we construct a self-consistent semi-analytical framework that describes the formation, evolution and star formation activity of molecular clouds, including a number of feedback effects to account for the complex processes inside those objects. The final equation system is solved numerically but at much lower computational expense than, e.g., hydrodynamical descriptions of comparable systems. The model presented in this paper agrees well with a broad range of observational results, showing that molecular cloud evolution can be understood as an interplay between accretion, global collapse, star formation and stellar feedback.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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