tokens: sample size of TNG50. For star-forming galaxies the Δ〈LLR〉 is the lowest for TNG50, followed by TNG100 and Illustris, indicating that TNG50 is the simulation that best models star-forming galaxies. Instead, all simulations struggle to accurately model quiescent galaxies, for which the Δ〈LLR〉 remains low in all cases. These trends are robust across the stellar mass bins considered. The left-hand top panel of Fig. 3 shows how the mean of the LLR distribution for simulated star-forming galaxies is the closest to SDSS for TNG50, followed by TNG100 and with Illustris being the furthest away from it. The higher LLR of TNG100 with respect to Illustris is suggestive that the improved physical model for galaxy formation adopted in the IllustrisTNG framework is overall an improvement compared to the original Illustris implementation (Pillepich et al. 2018 ). Furthermore, the unprecedented agreement with observations reached by TNG50 star-forming galaxies is also a sign that a higher resolution is key to effectively model star formation. We note, however, that all simulated data sets are still inconsistent at the 1σ level with SDSS. On the other hand, it can be seen that the improvement noted for star-forming galaxies does not seem to propagate to quiescent galaxies as well (the top right-hand panel of Fig. 3 ). We start by noting that in this case Illustris galaxies show a tail of high LLR that is consistent with IllustrisTNG at the 1σ level. However, the large variance suggests that this tail is very scarcely populated, whereas the very small variance found for the spike at low LLR is indicative that the bulk of the population of Illustris quiescent galaxies lies there, i.e. they are very far from reproducing SDSS. Yet, while there seems to be an overall improvement from the original Illustris framework to IllustrisTNG, the better resolution offered by TNG50 over TNG100 does not appear to significantly modify the overall LLR distribution for quiescent galaxies. Indeed, the distributions of the two IllustrisTNG volumes are practically consistent but at very high LLR, where the probability density of TNG50 is slightly higher. In short, what the top of Fig. 3 is telling us is that there has been a clear amelioration from the Illustris to the IllustrisTNG framework, in both the modelling of star formation regulation and of quenching, yet IllustrisTNG still produces small-scale stellar morphological details that differ from those in SDSS, and especially so for quiescent galaxies. Most importantly, while the higher resolution featured by TNG50 generates a sizeable improvement in the morphology of star-forming galaxies, this is not the case for quiescent galaxies. This is suggestive that the physics that couples small-scale stellar morphological details to star-formation quenching in the IllustrisTNG simulations warrants improvement, or that an even higher resolution is needed to accurately model the processes that lead to quiescence. 5.2 Mass dependence The
ner_tags: O O O B-Model O O O O O O O O O B-Model O O B-Model O B-Model O O B-Model O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-Survey O B-Model O O B-Model O O B-Model O O O O O O O O O O B-Model O O O B-Model O O O O O O O O O O O O O B-Model I-Model O O O O O O O O B-Model O B-Citation I-Citation I-Citation I-Citation O O O O O O O O O B-Model O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-Survey O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-Model O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-Model O O O O O O O O O O O B-Survey O O O O O O O O O O O O O O O B-Model O O O O O B-Model O B-Model O O O O O O O O O O O O O O O O O O O B-Model O O O O O O O O O O O O O O B-Model O O O O O O O O O O O O O O O O O O O O O O O O O O O B-Model I-Model O O O O O O O O O O O O B-Model O O O O O O O O O O O B-Survey O O O O O O O O O O O O O O B-Model O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-Model O O O O O O O O O O O O O O O O O O O O O O O O