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arXiv · 2112.08396

Emergence of Galactic Morphologies at Cosmic Dawn: Input from Numerical Modeling

Abstract

We employ high-resolution zoom-in cosmological simulations to analyze the emerging morphology of galaxies in dark matter halos at redshifts z > 2. We choose DM halos of similar masses of log (Mvir/Mo) ~11.65 +- 0.05 at the target redshifts of z_f = 6, 4 and 2. The rationale for this choice, among others, allows us to analyze how the different growth rate in these halos propagates down to galaxy scales. Halos were embedded in high or low overdensity regions, and two different versions of a galactic wind feedback have been employed. Our main results are: (1) Although our galaxies evolve in different epochs, their global parameters remain within a narrow range. Their morphology, kinematics and stellar populations differ substantially, yet all of them host sub-kpc stellar bars; (2) The SFRs appear higher for larger z_f, in tandem with their energy and momentum feedback; (3) The stellar kinematics allowed separation of bulge from the stellar spheroid. The existence of disk-like bulges has been revealed based on stellar surface density and photometry, but displayed a mixed disk-like and classical bulges based on their kinematics. The bulge-to-total mass ratios appear independent of the last merger time for all z_f. The stellar spheroid-to-total mass ratios of these galaxies lie in the range of ~0.5-0.8; (4) The synthetic redshifted, pixelized and PSF-degraded JWST images allow to detect stellar disks at all z_f. Some bars disappear in degraded images, but others remain visible; (5) Based on the kinematic decomposition, for stellar disks separated from bulges and spheroids. we observe that rotational support in disks depends on the feedback type, but increases with decreasing z_f; (6) Finally, the ALMA images detect disks at all z_f, but their spiral structure is only detectable in z_f=2 galaxies.

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Da Bi, Isaac Shlosman, Emilio Romano-Diaz. 2021-12-15. Emergence of Galactic Morphologies at Cosmic Dawn: Input from Numerical Modeling. https://doi.org/10.1093/mnras%2Fstac363

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