Simulation study proposes that weakly rotating, gas-rich cosmic wallflowers at high redshift are natural proto-globular cluster candidates based on kinematics and densities.
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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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Too shy to spin? Cosmic wallflowers as proto-globular clusters
Simulation study proposes that weakly rotating, gas-rich cosmic wallflowers at high redshift are natural proto-globular cluster candidates based on kinematics and densities.
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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.