FOXES: A Framework For Operational X-ray Emission Synthesis

TL;DR

This paper introduces a Vision Transformer-based framework that converts EUV observations into soft X-ray flux predictions, enhancing solar flare detection and localization beyond Earth's perspective for improved space weather forecasting.

Contribution

The novel use of a Vision Transformer model to translate EUV data into X-ray flux estimates and estimate flare locations, expanding flare detection capabilities beyond Earth's line of sight.

Findings

Accurate flux predictions across flare classes.

Framework enables EUV-based flare detection beyond Earth's view.

Lays groundwork for comprehensive solar flare cataloging.

Abstract

Understanding solar flares is critical for predicting space weather, as their activity shapes how the Sun influences Earth and its environment. The development of reliable forecasting methodologies of these events depends on robust flare catalogs, but current methods are limited to flare classification using integrated soft X-ray emission that are available only from Earth's perspective. This reduces accuracy in pinpointing the location and strength of farside flares and their connection to geoeffective events. In this work, we introduce a Vision Transformer (ViT)-based approach that translates Extreme Ultraviolet (EUV) observations into soft x-ray flux while also setting the groundwork for estimating flare locations in the future. The model achieves accurate flux predictions across flare classes using quantitative metrics. This paves the way for EUV-based flare detection to be extended beyond Earth's line of sight, which allows for a more comprehensive and complete solar flare catalog.