论文标题
超新星对分子云的湍流和扩散的影响
The Effect of Supernovae on the Turbulence and Dispersal of Molecular Clouds
论文作者
论文摘要
尽管超新星反馈在星系中的重要性已经确定,但它在分子云规模上的作用仍在争论中。在这项工作中,我们使用高分辨率的磁性磁通动力模拟对250 pc的区域的高分辨率磁动力模拟的重点,我们可以解决单个大型恒星的形成。超新星的反馈是用真正的超新星实现的,这些超新星是已解决的巨星的自然演变,因此它们的位置和时机是自吻的。我们从模拟中选择大量的分子云样本,以研究超新星能量注入和分子云的产生特性。我们发现,分子云的寿命为几个动态时间,其中一半的收缩到重力结合的位置,并且绑定云的分散时间(一个动态时间)比未结合云的云较短。我们强调了内部超新星的重要性,即在其母云中爆炸,设置云分散时间,以及与超新星随机分布的模型相比,它们的巨大恒星。我们还量化了超新星的能量注入效率,这是超新星距离与云的距离的函数。我们得出的结论是,超新星的间歇性驾驶可以维持分子云的湍流,并且可能是云扩散的主要过程。如果没有自一致的反馈实施,超新星在分子云进化中的作用就无法完全解释。
While the importance of supernova feedback in galaxies is well established, its role on the scale of molecular clouds is still debated. In this work, we focus on the impact of supernovae on individual clouds, using a high-resolution magneto-hydrodynamic simulation of a region of 250 pc where we resolve the formation of individual massive stars. The supernova feedback is implemented with real supernovae that are the natural evolution of the resolved massive stars, so their position and timing are self-consistent. We select a large sample of molecular clouds from the simulation to investigate the supernova energy injection and the resulting properties of molecular clouds. We find that molecular clouds have a lifetime of a few dynamical times, less then half of them contract to the point of becoming gravitationally bound, and the dispersal time of bound clouds, of order one dynamical time, is a factor of two shorter than that of unbound clouds. We stress the importance of internal supernovae, that is massive stars that explode inside their parent cloud, in setting the cloud dispersal time, and their huge overdensity compared to models where the supernovae are randomly distributed. We also quantify the energy injection efficiency of supernovae as a function of supernova distance to the clouds. We conclude that intermittent driving by supernovae can maintain molecular-cloud turbulence and may be the main process of cloud dispersal. The role of supernovae in the evolution of molecular clouds cannot be fully accounted for without a self-consistent implementation of their feedback.