Advancing foreground removal techniques and calibration methods for the next generation of radio telescopes

推进下一代射电望远镜的前景去除技术和校准方法

• 批准号: 2118888
• 金额: --
• 依托单位: Imperial College London
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2018
• 资助国家: 英国
• 起止时间: 2018 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2118888
• 关键词: Advancing; foreground; removal; techniques; calibration

The current generation of radio telescopes aiming to make a first detection of the Epoch of Reionisation have each come across unforeseen obstacles, particularly when it comes to the conspiracy of foregrounds removal and calibration of the telescope. These obstacles have all largely been overcome though advanced methods of foreground removal which take into account the calibration step would advance this further. This project will explore developing those methods, using current LOFAR data to assess obstacles and solutions and embedding any successes within the SKA EoR Key Science Project data pipeline. This project will result in a broad knowledge of simulation, instrumentation and data analysis. The first part of this project will focus on developing an understanding of the reionisation signal and sufficient coding and HPC skills, through producing various simulations and understanding the parameterisations behind them. These simulations will be used to test various foreground methods (new methods to be determined). The second part of this project will assess the validity of the methods on LOFAR data, possibly incorporating a calibration-foreground removal feedback loop in order to couple the two approaches more robustly. The use of LOFAR data and the application of different foreground removal methods will allow further early science to be extracted from the data, for example the overall topology of reionisation. Any instrumental effects which appear within the LOFAR data will be incorporated into SKA instrument simulation software OSKAR in order to make the SKA simulations as accurate as possible.The third part of this project will involve developing the successful methods/pipeline routes into a modular data pipeline within the SKA EoR working group in order to both design the Key Science Project and eventually process the early commissioning data. The application of these methods on early SKA commissioning data will ideally result in some extremely early science results, namely a deeper redshift and lower noise signal detection.

旨在对Reionisation时代进行首次探测的当前一代射电望远镜都遇到了不可预见的障碍，特别是当涉及到前景移除和望远镜校准的阴谋时。这些障碍已经在很大程度上被克服，尽管考虑到校准步骤的前景去除的先进方法将进一步推进这一点。该项目将探索开发这些方法，使用当前的LOFAR数据评估障碍和解决方案，并将任何成功嵌入SKA EoR关键科学项目数据管道。该项目将导致模拟，仪器和数据分析的广泛知识。该项目的第一部分将侧重于通过制作各种模拟并了解其背后的参数化来了解再电离信号以及足够的编码和HPC技能。这些模拟将用于测试各种前景方法（新方法待定）。该项目的第二部分将评估LOFAR数据的方法的有效性，可能纳入校准前景去除反馈回路，以更稳健地耦合两种方法。LOFAR数据的使用和不同前景去除方法的应用将允许从数据中提取进一步的早期科学，例如再电离的整体拓扑结构。LOFAR数据中出现的任何仪器效应都将被纳入SKA仪器模拟软件OSKAR，以使SKA模拟尽可能准确。该项目的第三部分将涉及在SKA EoR工作组内将成功的方法/管道路线开发成模块化数据管道，以便设计关键科学项目并最终处理早期调试数据。这些方法在早期SKA调试数据上的应用将理想地导致一些非常早期的科学结果，即更深的红移和更低的噪声信号检测。