The Physics of Solar Prominences: an AI/ML approach

日珥是由于大量冷物质悬浮在太阳大气中而被观察到的。有各种各样的结构和演化，从短暂的爆发性连续性到安静的连续性。日珥是在太阳边缘观测到的，通过日冕物质抛射（CME）向太阳系注入物质。您将使用NASA太阳动力学天文台（SDO）大气成像组件（AIA）的功能来观察和分析时间上的连续性。SDO/AIA的观测现在已经覆盖了一个完整的太阳周期（大约11年），提供了大量的数据（100 TB/年）。您将解决人工智能（AI）和机器学习（ML）方法可以帮助回答的以下科学问题：什么是磁结构？日珥爆发是否有一个单一的机制？日珥爆发的起源及其后果是什么？其目的是对太阳辐射进行全面调查，将其物理特性纳入一个开放式数据库。该项目有两个方面：开发一种基于AI/ML方法的算法，使用NASA SDO/AIA数据提取爆发属性，并建立一个开放访问的数据库;对爆发属性进行统计分析，以确定爆发机制以及太阳周期期间的变化。

Solar prominences are observed as large amount of cool material suspended into the solar atmosphere. There is a large variety of structures and evolution from short-lived erupting prominences to quiet prominences. Prominences are observed on the limb of the Sun and are injecting mass in the solar system through Coronal Mass Ejections (CMEs). You will use the capabilities of the NASA Solar Dynamics Observatory (SDO) Atmospheric Imaging Assembly (AIA) to observe and analyse the properties of prominences in time. SDO/AIA observations have now covered a full solar cycle (about 11 years) providing a huge amount of data (100 TB/year). You will address the following scientific questions that Artificial Intelligence (AI) and Machine Learning (ML) approaches could help to answer:What is the magnetic structure of prominences?Is there a single mechanism characterising prominence eruptions? What is the origin of prominence eruption and their consequences?The aim is to produce a comprehensive survey of solar prominences, assimilating their physical properties into an open-access database. The project is two-fold:Developing an algorithm based on AI/ML methods to extract the properties of prominences using NASA SDO/AIA data, and building an open-access database;Performing a statistical analysis of prominences properties to determine the mechanism(s) of eruptions, and the variations during the solar cycle.