Radio Transients and Machine Learning

亚历克斯·安德森（Alex Andersson）将从事一个项目，寻找、分类和调查MeerKAT射电望远镜射电数据中的共场瞬变。在此过程中，他将开发机器学习技术，并通过Zooniverse与公民科学家合作，开发将人类和机器分类相结合的技术。这项工作的动机是在我们的数据中发现了大量新的无线电变量和瞬变，并且需要开发新的工具来最大限度地从他们的研究中获得科学回报。MeerKAT的数据分析和新工具的开发与英国对平方公里阵列的关键战略投资是一致的，MeerKAT是两个官方先驱之一。新的工具将被开发出来，影响可能非常大。

Alex Andersson will work on a project to look find, classify and investigate commensal field transients in radio data from the MeerKAT radio telescope. In the process he will develop machine learning techniques and work with citizen scientists via Zooniverse, developing techniques for combining human and machine classifications. The work is motivated by the flood of new radio variables and transients being discovered in our data, and the need to develop new tools to maximise the scientific reward from their study. The MeerKAT data analysis and development of new tools for this and future radio telescopes aligns well with the UK's key strategic investment in the Square Kilometre Array, for which MeerKAT is one of two official precursors. Novel tools will be developed, and impact is potentially very high.