Investigating the faint radio population in the Lockman Hole with novel Machine Learning techniques

这个项目将利用新的机器学习技术来分解活动星系核和恒星形成星系在亚mJy通量密度范围内对微弱射电源的相对贡献。这项研究将利用e-Merlin和VLA对洛克曼洞的联合观测进行。结果是目标区域的高分辨率地图，由于e-Merlin的长基线，加上VLA的出色灵敏度。利用这些观测在这个流量范围内从形态上识别这两个源将提供宇宙的全球恒星形成速率历史的证据，并补充在Goods-N领域进行的类似工作的结果。

This project will utilise new machine learning techniques to decompose the relative contributions of Active Galactic Nuclei and Star Forming Galaxies to faint radio sources in the sub-mJy flux density range. This study will be carried out using joint e-MERLIN and VLA observations of the Lockman Hole. The result is a high resolution map of the target field, due to the long baselines of e-MERLIN, augmented by the excellent sensitivity of the VLA. Using these observations to morphologically identify these two sources in this flux range will provide evidence indicative of the global star formation rate history of the universe, as well as complimenting the results of similar work conducted in the GOODS-N field.