Next-Generation Radio Surveys for Cosmic Magnetism Science

宇宙磁学的下一代无线电巡天

• 批准号: 2489010
• 金额: --
• 依托单位: University of Manchester
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2020
• 资助国家: 英国
• 起止时间: 2020 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2489010
• 关键词: Next; Generation; Radio; Surveys; Cosmic

In this project the student will work on spectral data from the MeerKAT MIGHTEE survey, with particular emphasis on the polarisation components, to produce a classified object catalogue with quantitative estimates of bias. In collaboration with the MIGHTEE team, the student will develop the polarisation calibration and imaging processing for MeerKAT survey data to produce a classified object catalogue with quantitative estimates of bias using machine learning methodologies. A key focus within the later part of this project will be understanding the effects of selection bias in the training data for the machine learning classification and the impact of these biases on astrophysical interpretation and parameter estimation.

在这个项目中，学生将工作的光谱数据从MeerKAT MIGHTEE调查，特别强调的偏振组件，以产生一个分类的对象目录与定量估计的偏见。与MIGHTEE团队合作，学生将开发MeerKAT调查数据的偏振校准和成像处理，以使用机器学习方法生成分类对象目录，并对偏差进行定量估计。该项目后期的一个重点是了解机器学习分类训练数据中选择偏差的影响，以及这些偏差对天体物理解释和参数估计的影响。