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.
MHD and GRMHD simulations of magnetized accretion flows around rotating black holes show distinct bolometric luminosities and synchrotron-to-SSC peak ratios between SANE and MAD states that can distinguish magnetic field properties.
citing papers explorer
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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.
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Spectral analysis of magnetized advective accretion flows around rotating black holes
MHD and GRMHD simulations of magnetized accretion flows around rotating black holes show distinct bolometric luminosities and synchrotron-to-SSC peak ratios between SANE and MAD states that can distinguish magnetic field properties.