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Abstract One of the main theories for heating of the solar corona is based on the idea that solar convection shuffles and tangles magnetic field lines to make many small-scale current sheets that, via reconnection, heat coronal loops. S. K. Tiwari et al. present evidence that, besides depending on loop length and other factors, the brightness of a coronal loop depends on the field strength in the loop’s feet and the freedom of convection in the feet. While it is known that strong solar magnetic fields suppress convection, the decrease in the speed of horizontal advection of magnetic flux with increasing field strength has not been quantified before. We quantify that trend by analyzing 24 hr of Helioseismic Magnetic Imager-SHARP vector magnetograms of each of six sunspot-active regions and their surroundings. Using Fourier local correlation tracking, we estimate the horizontal advection speed of the magnetic flux at each pixel in which the vertical component of the magnetic field strength (Bz) is well above (≥150 G) noise level. We find that the average horizontal advection speed of magnetic flux steadily decreases asBzincreases, from 110 ± 3 m s−1for 150 G (in network and plage) to 10 ± 4 m s−1for 2500 G (in sunspot umbra). The trend is well fit by a fourth-degree polynomial. These results quantitatively confirm the expectation that magnetic flux advection is suppressed by increasing magnetic field strength. The presented quantitative relation should be useful for future MHD simulations of coronal heating.more » « lessFree, publicly-accessible full text available July 1, 2026
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Ahmadzadeh, Azim; Adhyapak, Rohan; Chaurasiya, Kartik; Nagubandi, Laxmi Alekhya; Aparna, V; Martens, Petrus C; Pevtsov, Alexei; Bertello, Luca; Pevtsov, Alexander; Douglas, Naomi; et al (, Harvard Dataverse)MAGFiLO is a dataset of manually annotated solar filaments from H-Alpha observations captured by the Global Oscillation Network Group (GONG). This dataset includes over ten thousand annotated filaments, spanning the years 2011 through 2022. Each annotation details one filament's segmentation, minimum bounding box, spine, and magnetic field chirality. MAGFiLO is the first dataset of its size, enabling advanced deep learning models to identify filaments and their features with unprecedented precision. It also provides a testbed for solar physicists interested in large-scale analysis of filaments.more » « less
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