论文标题
小N碰撞动力学V:超越不太小的N的领域
Small-N Collisional Dynamics V: Beyond the Realm of Not-So-Small-N
论文作者
论文摘要
有限大小的颗粒之间的直接碰撞通常发生在许多天体物理学领域。这种碰撞通常是由涉及少量颗粒的混沌,结合重力相互作用介导的。一个重要的应用是恒星碰撞,通常发生在密集的恒星簇中,以及它们与形成各种类型的恒星外来的相关性。在本文中,我们回到了小型混乱的引力相互作用($ n $ $ \ lissim $ 10)期间的碰撞率和概率的研究,超越了小数量的粒子限制,并进入了较大的粒子数量($ n $ \ gtrsim $ 10 $ $ 10 $^3 $),以测试我们分析模型的粒子属性和数字的粒子属性和数量的数字和数量的粒子范围。这是使用密集星团中恒星碰撞的直接$ n $体模拟来完成的,这是通过改变不同粒子和半径的颗粒的相对数量来完成的。我们使用平均自由路径近似,采用点粒子极限,并将粘性星近似作为我们的碰撞标准计算预测的碰撞率。我们在将理论速率与数值模拟进行比较来评估了其在重力焦点很重要的状态下的功效。使用本系列之前论文中开发的工具,尤其是碰撞率图,我们说明我们的预测和模拟速率非常吻合,通常彼此一致,在一个标准偏差之内。
Direct collisions between finite-sized particles occur commonly in many areas of astrophysics. Such collisions are typically mediated by chaotic, bound gravitational interactions involving small numbers of particles. An important application is stellar collisions, which occur commonly in dense star clusters, and their relevance for the formation of various types of stellar exotica. In this paper, we return to our study of the collision rates and probabilities during small-number chaotic gravitational interactions ($N$ $\lesssim$ 10), moving beyond the small-number particle limit and into the realm of larger particle numbers ($N$ $\gtrsim$ 10$^3$) to test the extent of validity of our analytic model as a function of the particle properties and the number of interacting particles. This is done using direct $N$-body simulations of stellar collisions in dense star clusters, by varying the relative numbers of particles with different particle masses and radii. We compute the predicted rate of collisions using the mean free path approximation, adopting the point-particle limit and using the sticky-star approximation as our collision criterion. We evaluate its efficacy in the regime where gravitational-focusing is important by comparing the theoretical rates to numerical simulations. Using the tools developed in previous papers in this series, in particular Collision Rate Diagrams, we illustrate that our predicted and simulated rates are in excellent agreement, typically consistent with each other to within one standard deviation.