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.
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Simulations of accreting black holes in standard and complex spacetimes indicate that magnetic geometry, quantum corrections, and binary dynamics influence flares, precession, photon rings, and multi-wavelength variability, with potential EHT constraints.
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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.
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GRMHD and GRRT Simulations of Black Hole Accretion: Flares, Precession, and Complex Spacetimes
Simulations of accreting black holes in standard and complex spacetimes indicate that magnetic geometry, quantum corrections, and binary dynamics influence flares, precession, photon rings, and multi-wavelength variability, with potential EHT constraints.