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We analyse a suite of 29 high-resolution zoom-in cosmological hydrodynamic simulations of massive galaxies with stellar masses $M_{\rm star} \gt 10^{10.9} \, \mathrm{M}_\odot$, with the goal of better understanding merger activity among active galactic nuclei (AGN), AGN activity in merging systems, SMBH growth during mergers, and the role of gas content in triggering AGN. Using the radiative transfer code Powderday, we generate HST-WFC3 F160W mock observations of central galaxies at redshift 0.5 < z < 3; convolve each image with a CANDELS-like point spread function; stitch each image into a real CANDELS image; and identify mergers within the synthetic images using commonly adopted non-parametric statistics. We study the connection between mergers and AGN activity in both the simulations and synthetic images and find reasonable agreement with observations from CANDELS. We find that AGN activity is not primarily driven by major mergers (stellar mass ratio > 1:4) except in a select few cases of gas-rich mergers at low redshifts (0.5 < z < 0.9). We also find that major mergers do not significantly grow the central SMBHs, indicating major mergers do not sustain long-term accretion. Moreover, the most luminous AGN in our simulations (Lbol > 1045 erg s−1) are no more likely than inactive galaxies (Lbol < 1043 erg s−1) to be found in merging systems. We conclude that mergers are not the primary drivers of AGN activity in the simulated massive galaxies studied here.

The evolution of star-forming galaxies at high redshifts is very sensitive to the strength and nature of stellar feedback. Using two sets of cosmological, zoom-in simulations from the VELA suite, we compare the effects of two different models of feedback: with and without kinetic feedback from the expansion of supernovae shells and stellar winds. At a fixed halo mass and redshift, the stellar mass is reduced by a factor of ∼1–3 in the models with stronger feedback, so the stellar mass–halo mass relation is in better agreement with abundance matching results. On the other hand, the three-dimensional shape of low-mass galaxies is elongated along a major axis in both models. At a fixed stellar mass, M* < 1010 M⊙, galaxies are more elongated in the strong-feedback case. More massive, star-forming discs with high surface densities form giant clumps. However, the population of round, compact, old (agec > 300 Myr), quenched, stellar (or gas-poor) clumps is absent in the model with strong feedback. On the other hand, giant star-forming clumps with intermediate ages (agec = 100–300 Myr) can survive for several disc dynamical times, independently of feedback strength. The evolution through compaction followed by quenching in the plane of central surface density and specific star formation rate is similar under the two feedback models.

Using the TNG50 cosmological simulation and observations from the Kilo-Degree Survey (KiDS), we investigate the connection between galaxy mergers and optical morphology in the local Universe over a wide range of galaxy stellar masses (8.5 ≤ log (M*/M⊙) ≤ 11). To this end, we have generated over 16 000 synthetic images of TNG50 galaxies designed to match KiDS observations, including the effects of dust attenuation and scattering, and used the statmorph code to measure various image-based morphological diagnostics in the r-band for both data sets. Such measurements include the Gini–M20 and concentration–asymmetry–smoothness statistics. Overall, we find good agreement between the optical morphologies of TNG50 and KiDS galaxies, although the former are slightly more concentrated and asymmetric than their observational counterparts. Afterwards, we trained a random forest classifier to identify merging galaxies in the simulation (including major and minor mergers) using the morphological diagnostics as the model features, along with merger statistics from the merger trees as the ground truth. We find that the asymmetry statistic exhibits the highest feature importance of all the morphological parameters considered. Thus, the performance of our algorithm is comparable to that of the more traditional method of selecting highly asymmetric galaxies. Finally, using our trained model, we estimate the galaxy merger fraction in both our synthetic and observational galaxy samples, finding in both cases that the galaxy merger fraction increases steadily as a function of stellar mass.