论文标题
三百个模拟中的星系对:关于观察成对找到技术性能的研究
Galaxy pairs in The Three Hundred simulations: a study on the performance of observational pair-finding techniques
论文作者
论文摘要
在文献中广泛研究了一对星系,作为了解星系相互作用和合并的一种方式。在观察中,它们通常是通过在视线沿着天空和速度设置最大分离并在这些范围内找到星系的定义来定义的。但是,在观察天空时,投影效应会通过创建不近距离物理距离的虚假对来影响结果。在这项工作中,我们模仿了这些观察性技术,以在三百个星系簇模拟中找到对。星系的3D坐标投影成2D,其视线速度包括哈勃流。发现的对分为“好”或“坏”,具体取决于它们的3D分离是否在2D空间极限之内。我们发现,根据观测中使用的阈值,好对的比例可以在30%至60%之间。研究配对成员星系之间可观察的特性的比率,我们发现,如果给定对分别具有低于0.8的金属比以上0.8或0.8的颜色比,则一对“良好”的可能性可以增加40%,20%和30%。此外,形状和恒星质量比分别低于0.4和0.2,可能会增加50%至100%。这些结果表明,这些特性可用于增加在观察星系簇及其环境中找到良好对的机会。
Close pairs of galaxies have been broadly studied in the literature as a way to understand galaxy interactions and mergers. In observations they are usually defined by setting a maximum separation in the sky and in velocity along the line of sight, and finding galaxies within these ranges. However, when observing the sky, projection effects can affect the results, by creating spurious pairs that are not close in physical distance. In this work we mimic these observational techniques to find pairs in The Three Hundred simulations of clusters of galaxies. The galaxies' 3D coordinates are projected into 2D, with Hubble flow included for their line-of-sight velocities. The pairs found are classified into "good" or "bad" depending on whether their 3D separations are within the 2D spatial limit or not. We find that the fraction of good pairs can be between 30 and 60 per cent depending on the thresholds used in observations. Studying the ratios of observable properties between the pair member galaxies, we find that the likelihood of a pair being "good" can be increased by around 40, 20 and 30 per cent if the given pair has, respectively, a mass ratio below 0.2, metallicity ratio above 0.8, or colour ratio below 0.8. Moreover, shape and stellar-to-halo mass ratios respectively below 0.4 and 0.2 can increase the likelihood by 50 to 100 per cent. These results suggest that these properties can be used to increase the chance of finding good pairs in observations of galaxy clusters and their environment.