Kavli Affiliate: Luis Ho
| Summary:
Understanding the physical processes that regulate galaxy quenching is a key challenge in galaxy formation and evolution. The VariableTNG (VTNG) project provides a laboratory to investigate these processes, as it systematically varies eight parameters of galaxy formation while keeping the initial conditions fixed, allowing the effects of individual feedback prescriptions to be isolated. We use interpretable machine-learning techniques as a tool to identify the parameters that most strongly regulate the quenched galaxy fraction. Our goal is to quantify the relative importance of the galaxy formation and feedback parameters that regulate the quenched galaxy fraction at z=0, determine how their influence changes across stellar mass and environment. We compute the quenched galaxy fraction for 26 VTNG boxes as a function of stellar mass, black hole mass, and gas mass, considering both the total galaxy population and separate samples of central and satellite galaxies. We train Random Forest regressors to predict the variation of the quenched fraction relative to the TNG100-1 model and use SHAP values to quantify both the magnitude and direction of the influence of each parameter. Our analysis reveals that only a small subset of the VTNG parameters dominates the variance of the quenched fraction. The stellar feedback wind parameter is the primary driver at low stellar masses, while its importance gradually shifts toward AGN-related parameters at higher masses. The supernova temperature also plays an important role at both extremes of the stellar-mass range. This transition persists when the galaxy population is divided into central and satellite systems. Comparisons with observational measurements further suggest that variations in these feedback parameters may contribute to the discrepancies between the fiducial TNG100-1 model and the observed passive galaxy population.
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