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◆ The Astrophysical Journal2026-02-05· Physics

The Shape of FIREbox Galaxies and a Potential Tension with Low-mass Disks

Courtney Klein, Jenny D. Wang, Luke Y. Xia, James Bullock, Jorge Moreno, Robert Feldmann, Francisco J. Mercado, Claude-André Faucher-Giguère, Jonathan Stern, N. Nicole Sanchez, Abdelaziz Hussein, Michelle S. Park

原始摘要(英文原文)· Original abstract
Abstract We study the intrinsic and observable shapes of approximately 700 star-forming galaxies with stellar masses of 10 8 –10 11 M ⊙ from the FIREbox simulation at z = 0. We calculate intrinsic axis ratios using inertia tensors weighted by three morphology types: “All Stars,” “Young Stars,” and “Luminosity-weighted Stars.” Young Stars shows mass-dependent 3D configurations, with spheroidal, elongated, and disky shapes dominant at stellar masses of 10 8.5 , 10 9.5 , and 10 10.5 M ⊙ , respectively. Using the radiative transfer code SKIRT , we construct mock images for each galaxy and show that projected short-to-long axis ratios, q , inferred from 2D Sérsic fits are most closely related to Luminosity-weighted Stars tensor shapes and least resemble the All Stars’ shapes. This suggests observed 2D shape distributions should not be compared to predictions based on 3D stellar mass shapes. Next, we construct a sample of mock images projected in random orientations and compare them to observed axis ratio distributions from the GAMA survey. At stellar masses below 10 10 M ⊙ , we produce too few galaxies with observed q < 0.4 and none with q < 0.2, suggesting that FIREbox does not produce enough low-mass disk galaxies. At higher masses, 10 10 –10 11 M ⊙ , we find that the predicted q distribution is sensitive to the dust-to-metal ratio; using our fiducial model, the distribution of q values is formally consistent with observations, but there is tension with our ability to produce enough very thin systems with q < 0.2. Future observational and theoretical programs aimed at understanding disk and thin-disk fractions will provide crucial tests of galaxy formation models.
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