论文标题
使用机器学习确定卫星输入时间
Determining Satellite Infall Times Using Machine Learning
论文作者
论文摘要
银河系（MW）卫星的一个关键是它们的轨道历史，尤其是它们被吸收到MW系统上的时间，因为它标志着他们经历了许多环境过程。我们提出了一种确定输入时间的新方法，即使用神经网络（NN）算法。 NN在Eagle流体动力学模拟中对MW-Analogues进行了训练，以预测矮星系是最初是Inflal的还是后挡板的银河系，并推断出其输入时间。如果当前在病毒半径以外的星系为后挡板卫星，并且以4.4 Gyrs的典型68 \％的置信区间确定了INSTALS卫星，则最终的NN预测为85 \％的准确性。将NN应用于Gaia EDR3的适当动作到MW矮人，我们发现所有矮人在300 kpc以内的所有矮人都在银河系中。总体MW卫星积聚率与理论预测非常吻合，除了较晚的时间，MW在回顾时间显示了与LMC及其卫星相对应的1.5 Gyrs的第二个峰值。我们还发现，超级矮人的淬火时间与输入时间没有显着相关性，从而支持了在重新定化过程中淬灭它们的假设。相比之下，发现具有恒星质量的矮人$ 10^5〜m_ \ odot $被发现与银河系中的环境淬火一致，平均恒星形态停止为$ 0.5^{+0.9} _ { - 1.2} $ gyrs in Insust in Insustall后。
A key unknown of the Milky Way (MW) satellites is their orbital history, and, in particular, the time they were accreted onto the MW system since it marks the point where they experience a multitude of environmental processes. We present a new methodology for determining infall times, namely using a neural network (NN) algorithm. The NN is trained on MW-analogues in the EAGLE hydrodynamical simulation to predict if a dwarf galaxy is at first infall or a backsplash galaxy and to infer its infall time. The resulting NN predicts with 85\% accuracy if a galaxy currently outside the virial radius is a backsplash satellite and determines the infall times with a typical 68\% confidence interval of 4.4 Gyrs. Applying the NN to MW dwarfs with Gaia EDR3 proper motions, we find that all of the dwarfs within 300 kpc had been inside the Galactic halo. The overall MW satellite accretion rate agrees well with the theoretical prediction except for late times when the MW shows a second peak at a lookback time of 1.5 Gyrs corresponding to the infall of the LMC and its satellites. We also find that the quenching times for ultrafaint dwarfs show no significant correlation with infall time and thus supporting the hypothesis that they were quenched during reionisation. In contrast, dwarfs with stellar masses above $10^5~M_\odot$ are found to be consistent with environmental quenching inside the Galactic halo, with star-formation ceasing on average at $0.5^{+0.9}_{-1.2}$ Gyrs after infall.
