Machine learning on simulated images identifies that flux eruption events cause more diffuse, polarized, lower-flux millimeter emission with decreased Q-U loop rotation rate, achieving ~80% accuracy with random forests on summary statistics.
Accretion disk radiation dynamics and the cosmic battery
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abstract
We investigate the dynamics of radiation in an astrophysical accretion disk around a Kerr black hole. The source of the radiation is the accretion disk itself, and not a central object as in previous studies of the Poynting-Robertson effect. We generate numerical sky maps from photon trajectories that originate on the surface of the disk as seen from the inner edge of the disk at the position of the innermost stable circular orbit (ISCO). We investigate several accretion disk morphologies with a Shakura-Sunyaev surface temperature distribution. Finally, we calculate the electromotive source of the Cosmic Battery mechanism around the inner edge of the accretion disk and obtain characteristic timescales for the generation of astrophysical magnetic fields.
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astro-ph.HE 1years
2026 1verdicts
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Identifying Observational Signatures of Flux Eruption Events in Supermassive Black Hole Accretion Flows with Machine Learning
Machine learning on simulated images identifies that flux eruption events cause more diffuse, polarized, lower-flux millimeter emission with decreased Q-U loop rotation rate, achieving ~80% accuracy with random forests on summary statistics.