Tidal Disruption of Satellite Galaxies in a Semi-Analytic Model of Galaxy Formation

TL;DR

This paper introduces a tidal stripping process for satellite galaxies into a semi-analytic galaxy formation model, significantly improving its fit to multiple observational data sets and enhancing its physical realism.

Contribution

The paper adds a new tidal disruption mechanism for satellite galaxies into an existing semi-analytic model, improving its likelihood and observational agreement.

Findings

Model likelihood increased fourfold with tidal disruption.

Better match to black hole-bulge mass relation and star formation laws.

Reduced dwarf galaxy excess and improved metal distribution predictions.

Abstract

We introduce a new physical recipe into the De Lucia and Blaizot version of the Munich semi-analytic model built upon the Millennium dark matter simulation: the tidal stripping of stellar material from satellite galaxies during mergers. To test the significance of the new physical process we apply a Monte Carlo Markov Chain parameter estimation technique constraining the model with the $K$-band luminosity function, $B-V$ colours and the black hole-bulge mass relation. The differences in parameter correlations, and in the allowed regions in likelihood space, reveal the impact of the new physics on the basic ingredients of the model, such as the star-formation laws, feedback recipes and the black hole growth model. With satellite disruption in place, we get a model likelihood four times higher than in the original model, indicating that the new process seems to be favoured by observations. This is achieved mainly due to a reduction in black hole growth that produces a better agreement between the properties of central black holes and host galaxies. Compared to the best-fit model without disruption, the new model removes the excess of dwarf galaxies in the original recipe with a more modest supernova heating. The new model is now consistent with the three observational data sets used to constrain it, while significantly improving the agreement with observations for the distribution of metals in stars. Moreover, the model now follows the build up of intra-cluster light.