Multispacecraft Study of the Spatio-Temporal Variability of Solar Energetic Particles (SEP) Profiles in the Inner Heliosphere

太阳高能粒子（英语：Solar energetic particles，缩写为SEP）是在太阳耀斑和日冕物质抛射等高能事件中从太阳加速而来的粒子。它们能够以相对论速度移动，并且在指向地球时，可能对人类技术造成与空间天气有关的问题，并对人类造成辐射风险。该项目旨在更好地了解SEP特征-包括强度，通量和内日光层的时空演变。研究成果将公开提供，这项工作由妇女领导。该项目将研究太阳高能粒子（SEP）的近太阳特征及其时空变化如何帮助确定它们在内日光层的起源、加速和传播，并限制它们产生的种子种群的建模。数据集来自美国宇航局的帕克太阳探测器和太阳轨道器将被使用。此外，高能粒子辐射环境模型（EPREM）将用于模拟SEP事件，电流片源表面（CSSS）模型用于将PSP位置映射回太阳，以建立磁连通性。研究的三个目标是：目标1：获得SEP时间廓线（强度，积分通量，通量，光谱指数和成分）在日光层的多个位置，并调查其时间变化。目标2：模型比较-使用目标1中获得的知识来约束稳定太阳风中SEP传输的EPREM模拟参数以及冲击和之字形的启发式模型。目标3：使用人工智能技术开发的算法准备AI就绪数据和数据重建，并遵循Poduval等人2022年关于AI就绪数据的建议。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

Solar energetic particles (SEPs) are particles that are accelerated from the Sun in energetic events, such as solar flares and coronal mass ejections. They can move at relativistic speeds and when directed to the Earth, can cause space weather-related issues for human technology as well as radiation risks to humans. This project aims to gain better insights on SEP characteristics – including intensity, flux, and spatio-temporal evolution in the inner heliosphere. The research products will be made publicly available and the work is led by women. Undergraduate students will be mentored.The project investigates how the near-Sun characteristics of solar energetic particles (SEPs) and their spatio-temporal variability help determine their origin, acceleration and propagation in the inner heliosphere, and constrains modeling of the seed population from which they arise. Data sets from NASA’s Parker Solar Probe and Solar Orbiter will be used. Additionally, the Energetic Particle Radiation Environment Model (EPREM) will be used for simulating the SEP events and the Current Sheet Source Surface (CSSS) model used for mapping the PSP locations back to the Sun for establishing the magnetic connectivity. The three objectives of the study are: Obj 1: Obtain SEP Time Profiles (intensity, integral flux, fluence, spectral index and composition) at multiple locations in the heliosphere and investigate their temporal variability. Obj 2: Model Comparison - use the knowledge gained in Obj 1 to constrain the parameters of EPREM simulations of SEP transport in the steady solar wind and heuristic models of shocks and switchbacks. Obj 3: Preparation of AI-ready Data and Data Reconstruction using algorithms developed using techniques of artificial intelligence and following the recommendations of Poduval et al. 2022 for AI-ready data.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.