Spherical Wavelet Analysis of Geophysical Data

地球物理数据的球面小波分析

• 批准号: 2077701
• 金额: --
• 依托单位: University 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-2077701
• 关键词: Spherical; Wavelet; Analysis; Geophysical; Data

Despite being very distinct research areas, dark matter mapping in cosmology and the imaging of the seismic properties of the Earth's interior (e.g., wave speeds) in geophysics currently face similar technical challenges. For example, with the explosion of big data sets in both disciplines, many maps and images of the same object have been produced by different research groups. There are often substantial differences between them, but fully quantitative, objective analyses of their statistical properties are lacking. In addition, most images and maps do not report uncertainties, which limits their usefulness to understand the fundamental physical processes underneath them. This project addresses these challenges through a two-way transfer of knowledge between cosmology and geophysics by: (i) applying some new methods developed for dark matter mapping in cosmology to the geophysical context, notably wavelet and sparse/compressed sensing approaches, and Bayesian Hierarchical modelling; and, (ii) adapting novel Bayesian trans-dimensional approaches currently used in geophysics to cosmological mapping.

尽管是非常不同的研究领域，宇宙学中的暗物质映射和地球内部地震特性的成像（例如，波速）目前面临类似的技术挑战。例如，随着这两个学科中大数据集的爆炸式增长，不同的研究小组已经制作了同一对象的许多地图和图像。它们之间往往有很大的差异，但缺乏对它们的统计特性进行全面的定量和客观的分析。此外，大多数图像和地图没有报告不确定性，这限制了它们对了解其下的基本物理过程的有用性。该项目通过宇宙学和天体物理学之间的双向知识转移来应对这些挑战：（一）将为宇宙学中的暗物质映射开发的一些新方法应用于地球物理学背景，特别是小波和稀疏/压缩传感方法以及贝叶斯分层建模;以及（二）将目前在天体物理学中使用的新贝叶斯跨维方法应用于宇宙映射。