Statistical resampling as a tool for radio-interferometric imaging fidelity assessment

本项目将开发一种定量统计技术来评估无线电干涉图像的像素级保真度，该图像是通过解决复杂的校准和逆成像问题而形成的。相依数据的统计重采样技术的最新理论进展，以及高性能计算资源的几何增长，使得使用现代Bootstrap方法的创新方法成为可能。这项研究将纳入更完整的统计技术，推导出使用该方法的量化指南，并探索重抽样的理论性质。如果成功，这些方法可以应用于任何天文干涉测量，以及物理科学中的其他逆成像问题。由于校准和成像需要专门的技术知识，这是新用户进入的障碍，开发强大的统计技术是建立自动管道减少系统所需的关键因素，该系统能够生产出具有定量不确定性的科学产品，供更广泛的用户社区直接使用。因此，这项工作将是对研究基础设施的重要贡献。

AST-0506745KemballThis project will develop a quantitative statistical technique to assess the pixel-level fidelity of radio-interferometric images, which are formed by solving a complex calibration and inverse imaging problem. Recent theoretical advances in statistical resampling techniques for dependent data, and geometric increases in high performance computing resources, allow an innovative approach using modern bootstrap methods. This research will incorporate more complete statistical techniques, derive quantitative guidelines for the use of this method, and explore the theoretical properties of resampling. If successful, these methods can be applied to any astronomical interferometry, as well as to other inverse imaging problems in the physical sciences.Because calibration and imaging requires specialized technical knowledge, which acts as an entry barrier for new users, the development of robust statistical techniques is a vital ingredient required to build automated pipeline reduction systems capable of producing science products with quantitative uncertainties ready for direct use by a far broader user community. This work will therefore be an important contribution to research infrastructure.