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.
The impact of Faraday effects on polarized black hole images of Sagittarius A*
1 Pith paper cite this work. Polarity classification is still indexing.
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abstract
We study model images and polarization maps of Sagittarius A* at 230 GHz. We post-process GRMHD simulations and perform a fully relativistic radiative transfer calculation of the emitted synchrotron radiation to obtain polarized images for a range of mass accretion rates and electron temperatures. At low accretion rates, the polarization map traces the underlying toroidal magnetic field geometry. At high accretion rates, we find that Faraday rotation internal to the emission region can depolarize and scramble the map. We measure the net linear polarization fraction and find that high accretion rate "jet-disc" models are heavily depolarized and are therefore disfavoured. We show how Event Horizon Telescope measurements of the polarized "correlation length" over the image provide a model-independent upper limit on the strength of these Faraday effects, and constrain plasma properties like the electron temperature and magnetic field strength.
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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.