Connection between Galaxy Morphology and Dark-matter Halo Structure. II. Predicting Disk Structure from Dark-matter Halo Properties

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Abstract
We investigate how galactic disk structures connect to the detailed properties of their host dark-matter halos using the TNG50 simulation. From the hydrodynamic and matched dark-matter-only runs, we measure a comprehensive list of halo properties describing density structure, angular momentum, shape, assembly history, and environment. Using the morphological decomposition developed in Paper I, we quantify the sizes, scale heights, and mass fractions of the disk components for galaxies at 0 ≤ z ≤ 4. A random forest regression shows that halo properties alone predict disk size and thickness with high accuracy, while a symbolic regression (SR) provides compact empirical relations with slightly lower accuracy. Disk height is consistently easier to predict than disk size, and lower-mass halos yield higher accuracy than massive halos. Predictions based on halo properties measured in the hydro simulations outperform those based on halos matched in the dark-matter-only simulation, reflecting the imprint of baryonic restructuring on the inner halo. The SHAP analysis reveals the most informative halo parameters include concentration, Einasto shape, global and inner spin, and recent mass accretion, although their importance varies across disk properties. We show correlations between disk size and the density–profile shape arise primarily from a disk-induced modification of the inner halo, rather than a primordial connection. Finally, we point out that disks become more extended with respect to their host halos at higher redshift in low-mass halos, while massive high-redshift halos show the opposite trend. We provide SR-based prescriptions that accurately map halo properties to disk structures, offering practical tools for galaxy–halo modeling.
Funding Information
  • National Natural Science Foundation of China (12473007)
  • China Manned Space Program (CMS-CSST-2025-A09)
  • China Manned Space Program (CMS-CSST-2025-A03)
  • National Natural Science Foundation of China (12233001)

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