arXivDaily arXiv每日学术速递 周一至周五更新
arXiv 2201.07814astro-ph.GA
收藏

自宇宙正午以来星系、凸起和盘的淬火:一种用于识别天文数据中因果关系的机器学习方法

The quenching of galaxies, bulges, and disks since cosmic noon: A machine learning approach for identifying causality in astronomical data

Asa F. L. Bluck, Roberto Maiolino, Simcha Brownson, Christopher J. Conselice, Sara L. Ellison, Joanna M. Piotrowska, Mallory D. Thorp

摘要:

我们从$z=2-0$出发,分析了在宇宙历史的大部分时间里,星系、星系球和星系盘中恒星形成的猝灭现象。我们利用观测从SDSS和MANGA在低红移。我们补充这些数据与观测从坎德尔在高红移。此外,我们将观测结果与LGalerkin半解析模型的详细预测进行了比较。为了分析数据,我们开发了一种利用随机森林分类器的机器学习方法。我们首先证明了这种技术在从高度复杂和相互关联的模型数据中提取因果洞察力方面非常有效,然后将其应用于各种观测调查。我们的主要观测结果如下:在所有的红移研究在这项工作中,我们发现球的质量是最具预测性的参数淬火,出的光度参数集(包括球的质量,盘质量,恒星总质量,和$B/T$结构)。此外,我们还发现,无论是凸起和磁盘结构,单独处理的凸起质量是淬火的最具预测性的参数。因此,内在的星系淬火必须是由于一个稳定的机制在宇宙时间内运作,相同的淬火机制必须是有效的在两个凸起和磁盘区域。尽管成功的隆起质量在预测淬火,我们发现,中央速度分散更具有预测性(当光谱数据集)。在比较的LGalerkin模型,我们发现,所有这些观测结果可以一致地解释通过淬火通过预防性的“无线电模式”的活动星系核(AGN)的反馈。此外,许多替代淬火机制(包括维里冲击,超新星反馈,和形态稳定)被发现与我们的观测结果和文献中的不一致。

英文摘要:

We present an analysis of the quenching of star formation in galaxies, bulges, and disks throughout the bulk of cosmic history, from $z=2-0$. We utilise observations from the SDSS and MaNGA at low redshifts. We complement these data with observations from CANDELS at high redshifts. Additionally, we compare the observations to detailed predictions from the LGalaxies semi-analytic model. To analyse the data, we developed a machine learning approach utilising a Random Forest classifier. We first demonstrate that this technique is extremely effective at extracting causal insight from highly complex and inter-correlated model data, before applying it to various observational surveys. Our primary observational results are as follows: At all redshifts studied in this work, we find bulge mass to be the most predictive parameter of quenching, out of the photometric parameter set (incorporating bulge mass, disk mass, total stellar mass, and $B/T$ structure). Moreover, we also find bulge mass to be the most predictive parameter of quenching in both bulge and disk structures, treated separately. Hence, intrinsic galaxy quenching must be due to a stable mechanism operating over cosmic time, and the same quenching mechanism must be effective in both bulge and disk regions. Despite the success of bulge mass in predicting quenching, we find that central velocity dispersion is even more predictive (when available in spectroscopic data sets). In comparison to the LGalaxies model, we find that all of these observational results may be consistently explained through quenching via preventative `radio-mode' active galactic nucleus (AGN) feedback. Furthermore, many alternative quenching mechanisms (including virial shocks, supernova feedback, and morphological stabilisation) are found to be inconsistent with our observational results and those from the literature.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

↑