Bayesian inference of galaxy formation from the K-band luminosity function of galaxies: tensions between theory and observation
Yu Lu, H.J. Mo, Neal Katz, Martin D. Weinberg

TL;DR
This paper uses Bayesian inference with a semi-analytic galaxy formation model to compare predictions against observed K-band luminosity functions, revealing tensions and missing physics in current models.
Contribution
It introduces a Bayesian framework to constrain galaxy formation model parameters and assesses their predictive power against multiple observational relations.
Findings
Predicts a curved Tully-Fisher relation
Overestimates satellite galaxy fractions
Vastly overpredicts the HI mass function
Abstract
We conduct Bayesian model inferences from the observed K-band luminosity function of galaxies in the local Universe, using the semi-analytic model (SAM) of galaxy formation introduced in Lu et al (2011). The prior distributions for the 14 free parameters include a large range of possible models. We find that some of the free parameters, e.g. the characteristic scales for quenching star formation in both high-mass and low-mass halos, are already tightly constrained by the single data set. The posterior distribution includes the model parameters adopted in other SAMs. By marginalising over the posterior distribution, we make predictions that include the full inferential uncertainties for the colour-magnitude relation, the Tully-Fisher relation, the conditional stellar mass function of galaxies in halos of different masses, the HI mass function, the redshift evolution of the stellar mass…
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