论文标题
模拟驱动的深度学习方法，用于分离合并和星系星系：所有烛台中块状星系的形成历史
A Simulation Driven Deep Learning Approach for Separating Mergers and Star Forming Galaxies: The Formation Histories of Clumpy Galaxies in all the CANDELS Fields
论文作者
论文摘要
能够区分最近发生重大合并事件或正在经历强烈恒星形成的星系对于在我们对星系的形成和演变的理解中取得进展至关重要。因此，我们使用卷积神经网络（CNN）开发了一个机器学习框架，以使用来自Illaberistng100的160,000张模拟图像的数据集将星系组与后的恒星分离，该数据集类似于观察到的与Hubble的星系的深度成像。我们通过开发一种新的方法来应对拥挤领域中相邻来源污染的复杂性，并根据重叠源和背景通量定义质量控制限制，从而改善了以前的机器学习方法，并通过成像进行了成像。我们的管道成功地将邮政在Illustristng $ 80 \％$的恒星形成星系中分离出来，与使用银河系的不对称（$ a $）进行分类相比，这是至少25 \％的改进。与测得的Sérsic曲线相比，我们表明烛台中的星形形成星系主要是圆盘主导的系统，而后螺旋体则显示了过渡光盘的分布，以膨胀为主导的星系。通过这些新的测量结果，我们追踪宇宙中非对称星系中的邮政在邮政库的速度，发现从$ z = 0.5 $的$ 20 \％$ $ z = 0.5 $ to $ z = 2 $的$ 50 \％$。此外，我们没有发现有力的证据表明，恒星形成主序列（SFM）上方的散射可以归因于主要的后培养剂。最后，我们使用新方法来更新我们先前对星系合并费率的测量$ \ MATHCAL {r} = 0.022 \ pm 0.006 \ times（1+z）^{2.71 \ pm0.31} $
Being able to distinguish between galaxies that have recently undergone major merger events, or are experiencing intense star formation, is crucial for making progress in our understanding of the formation and evolution of galaxies. As such, we have developed a machine learning framework based on a convolutional neural network (CNN) to separate star forming galaxies from post-mergers using a dataset of 160,000 simulated images from IllustrisTNG100 that resemble observed deep imaging of galaxies with Hubble. We improve upon previous methods of machine learning with imaging by developing a new approach to deal with the complexities of contamination from neighbouring sources in crowded fields and define a quality control limit based on overlapping sources and background flux. Our pipeline successfully separates post-mergers from star forming galaxies in IllustrisTNG $80\%$ of the time, which is an improvement by at least 25\% in comparison to a classification using the asymmetry ($A$) of the galaxy. Compared with measured Sérsic profiles, we show that star forming galaxies in the CANDELS fields are predominantly disc-dominated systems while post-mergers show distributions of transitioning discs to bulge-dominated galaxies. With these new measurements, we trace the rate of post-mergers among asymmetric galaxies in the universe finding an increase from $20\%$ at $z=0.5$ to $50\%$ at $z=2$. Additionally, we do not find strong evidence that the scattering above the Star Forming Main Sequence (SFMS) can be attributed to major post-mergers. Finally, we use our new approach to update our previous measurements of galaxy merger rates $\mathcal{R} = 0.022 \pm 0.006 \times (1+z)^{2.71\pm0.31}$
