Coronal Hole

Coronal holes are dark regions on the Sun characterized by open magnetic field lines and cooler temperatures, leading to enhanced solar wind emissions that can impact Earth's space weather. Current research focuses on automated detection and segmentation of coronal holes in solar images using advanced computer vision techniques, including deep learning models like convolutional neural networks (CNNs) and LSTM networks, as well as quantum-enhanced fuzzy clustering methods. These improved detection methods, coupled with time-series analysis and predictive modeling, aim to enhance forecasting of geomagnetic storms and mitigate their effects on satellites and other technological systems. The ultimate goal is to improve space weather prediction accuracy for better preparedness and risk mitigation.