LineFit delivers more stable line-core intensity and Doppler velocity time series from complex multi-line solar spectra by combining adaptive windowing, asymmetric Voigt options, and split-core handling, outperforming standard fast estimators on synthetic benchmarks.
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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.
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Adaptive multi-line fitting for stable line-core intensity and Doppler velocity
LineFit delivers more stable line-core intensity and Doppler velocity time series from complex multi-line solar spectra by combining adaptive windowing, asymmetric Voigt options, and split-core handling, outperforming standard fast estimators on synthetic benchmarks.
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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.