The Physics of Solar Prominences: an AI/ML approach

太阳日珥被观测到是大量的冷物质悬浮在太阳大气中。从短暂的喷发日珥到平静日珥，有各种各样的结构和进化。日珥在太阳的边缘被观测到，并通过日冕物质抛射（cme）向太阳系注入质量。您将使用美国宇航局太阳动力学观测站（SDO）大气成像组件（AIA）的能力及时观察和分析日珥的特性。SDO/AIA的观测现在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）。您将解决以下人工智能（AI）和机器学习（ML）方法可以帮助回答的科学问题：日珥的磁性结构是什么？日珥爆发是否有单一的机制？日珥喷发的起源及其后果是什么？其目的是对太阳日珥进行全面调查，并将其物理特性纳入一个开放访问的数据库。该项目分为两部分：开发一种基于AI/ML方法的算法，利用NASA SDO/AIA数据提取日珥的属性，并建立一个开放访问的数据库；对日珥的特性进行统计分析，以确定喷发的机制和太阳活动周期中的变化。

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.