Dual-spacecraft observations of a November 2021 CME confirm that the CAAP method reliably estimates instantaneous expansion speed from single-point data while revealing unexpected evolution in shock strength and magnetic flux.
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An automated pipeline forecasts CME magnetic fields at L1 using initial magnetic obstacle data, achieving errors of roughly 5 hours in timing and 10 nT in strength comparable to full-event reconstructions.
SuNeRF-CME uses physics-informed NeRFs with ray-tracing for Thomson scattering and constraints on plasma continuity, direction, and speed to enable tomographic 3D reconstruction of CMEs from as few as two viewpoints, validated on synthetic data with low parameter errors.
A CNN-based fusion model trained on multi-instrument solar observations predicts geoeffective CMEs, achieving mean TSS of 0.703 and Brier score of 0.095 via five-fold cross-validation.
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SuNeRF-CME: Physics-Informed Neural Radiance Fields for Tomographic Reconstruction of Coronal Mass Ejections
SuNeRF-CME uses physics-informed NeRFs with ray-tracing for Thomson scattering and constraints on plasma continuity, direction, and speed to enable tomographic 3D reconstruction of CMEs from as few as two viewpoints, validated on synthetic data with low parameter errors.