Morphological Identification of Dynamical Regimes in MHD Turbulence with ScaleAware-JEPA

Abstract

The morphology of turbulent interstellar gas reflects the coupled action of turbulence, magnetic fields, and self-gravity, but density amplitude alone does not uniquely specify dynamical state. We use ScaleAware-JEPA to learn multiscale structural coordinates from density alone and test whether these learned coordinates organize dynamical states more clearly than density-based conditioning. Clump-like, filament-like, and diffuse-like latent neighborhoods show an ordered progression in turbulent velocity scaling that is not reproduced by density-selected populations. Velocity and magnetic fields are withheld during training and used afterward as post-training physical diagnostics: MHD states occupy ordered but overlapping regions of the learned representation, and dimensionless dynamical balances vary coherently across the full latent atlas. These results show that a representation learned from density morphology can acquire a geometry that is systematically organized by established MHD diagnostics. Multiscale morphology therefore provides a useful coordinate for dynamical state beyond density amplitude alone.