CDS&E: Machine Learning for Star Cluster Classification

这是一个试点项目，旨在比较和测试人类视觉检查与机器学习(ML)和计算机视觉(CV)方法在高分辨率星系图像中识别年轻星团(YSC)的方法。这是探索和优化ML方法的第一步，以建立一个能够自动搜索、分类和测量YSC形状的工具。这项研究将为整个项目提供一个发射台。ML工具似乎将是处理在天文学中变得普遍的海量“大数据”数据库的唯一可行方法。综合教育部分包括面向本科生的暑期研究，其中包括对大数据问题的有价值的介绍。初步测试将在距离我们银河系最近的两个星系(M31和M33)上进行，然后扩展到距离我们更远的M51和NGC628。这些都是经过充分研究的星系，其高保真星表已经存在，可以进行比较和校准。所选择的测试星系具有非常不同的星系团群体，因此是验证标准(基于人类的)方法和未来正在开发的ML方法的关键试验台。将在这些图像上探索和测试的ML/CV算法包括非常深的卷积神经网络，它将被调整为提供星团的集体分类。以人为本的方法目前是‘行业标准’，它的验证将为未来外部星系恒星形成的物理研究提供更可靠的基础。这一奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

This is a pilot project to compare and test human visual inspection versus machine learning (ML) and computer vision (CV) methods for identifying young star clusters (YSC) in high resolution images of galaxies. It is the first step towards exploring and optimizing the ML methods so as to build a tool capable of automatic search, classification, and shape measurement of YSC. This study will provide a launch-pad for the full project. It seems likely that ML tools will be the only viable way to handle the vast 'Big Data' databases becoming common in astronomy. An integrated educational component includes summer research for undergraduate students, including a valuable introduction to 'Big Data' issues.Initial tests will be performed on the two closest galaxies to our own Milky Way (M31 and M33), and then extended to M51 and NGC628, which are further away from us. These are well-studied galaxies for which high-fidelity catalogs already exist, which are available for comparison and calibration. The chosen test galaxies have very different cluster populations, and thus represent key testbeds to validate both the standard (human-based) approach and the future ML approach being developed. ML/CV algorithms to be explored and tested on these images include very deep convolutional neural networks, which will be adapted to provide collective classifications of star clusters. The human-based approach is currently the 'industry standard', and its validation will provide a more secure footing for future investigations of the physics of star formation in external galaxies.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.