发表机构
Loyola University Chicago; Northwestern University; Allegheny College（芝加哥洛约拉大学; 西北大学; 阿勒格尼学院）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本研究利用机器学习工具collAIder模拟银河系中心恒星碰撞，发现约10%恒星被剥离质量，5%发生并合，并估计碰撞注入大量气体，部分可能被超大质量黑洞吸积。
AI 中文摘要
银河系中心内部秒差距内的直接碰撞可以改变恒星的轨道和性质。碰撞的结果取决于多个参数，包括恒星的质量和年龄、碰撞参数以及初始相对速度。我们利用新开发的collAIder——一种用于预测恒星碰撞结果的机器学习工具，将恒星碰撞的三维流体动力学模拟与银河系中心的动力学模型连接起来。我们的结果显示，存在大量被剥离的恒星，约占初始恒星群的10%，这些恒星是由高速碰撞过程中的质量损失产生的。恒星并合则较少发生，约有5%的恒星经历碰撞引发的并合。我们还发现，高速、几乎正面的碰撞可以完全瓦解恒星。这些破坏性碰撞通常在此之前发生10次或更多次碰撞，这些碰撞逐渐减少恒星的质量，直至最终被摧毁。我们估计，恒星碰撞期间的质量损失向周围环境注入了大约(2.5-8)×10^5太阳质量的气体。这些气体大部分被注入到内部0.1秒差距内，其中约90%保留在星团内，并可能被吸积到超大质量黑洞上。
英文摘要
Direct collisions in the inner pc of the Galactic center can alter the orbits and properties of stars. The outcome of a collision depends on a number of parameters, including the masses and ages of the stars, the impact parameter, and the initial relative velocity. We utilize the newly developed $\verb|collAIder|$, a machine learning tool developed to predict the outcomes of stellar collisions, to bridge 3D hydrodynamic simulations of stellar collisions with a dynamical model of the Galactic center. Our results show a substantial population of stripped stars, $\sim$$10\%$ of the initial stellar population, produced by mass loss during high-speed collisions. Stellar mergers are less frequent, with about $5\%$ of the stars experiencing a collision-induced merger. We also find that high-speed, nearly head-on collisions can completely disrupt the stars. These destructive collisions are usually preceded by 10 or more collisions, which gradually reduce the mass of the star before it is ultimately destroyed. We estimate that mass loss during stellar collisions injects roughly $(2.5-8)\times 10^5$ M$_\odot$ of gas into the surrounding environment. Most of this gas is injected into the inner $0.1$ pc and about $90\%$ is retained within the cluster and may be accreted onto the supermassive black hole.
Comments21 pages and 10 figures (Including Appendix). Comments welcome
