Predictions for the infrared numbercounts and star formation histories from a semi analytic model of galaxy formation

One of the most fundamental probes of the physics that underpins galaxy evolution is the star formation rate (SFR) as a function of cosmic time. In addition, the statistical prop- erties of galaxy populations are another important key to understand how the universe has been evolving. It is known that the far-infrared emission from galaxies is strongly correlated with obscured star formation and forms a significant part of cosmic infrared background. We thus investigate the variation of the SFR of galaxies over time by com- paring predictions of the L-Galaxies semi-analytic model with observations of the far infrared (FIR) luminosity and number counts. In the first part of this thesis, we follow the star formation histories (SFHs) of galaxies and use these to construct stellar spectra in post-processing. We then contrast model SFHs from the Millennium Simulation with observed ones from the VESPA algorithm as applied to the SDSS-7 catalogue when this has been characterized by mass and colour of galaxies. In order to investigate the SAM model prediction, I extend L-galaxies to predict far infrared fluxes and construct mock catalogues which are fed into SMAP in order to provide simulated maps. LFs have also been estimated for model galaxies at different redshifts. The results are compared with observations from Herschel. To conclude, our model under- estimates the number density of galaxies at bright sources (e.g fluxes above 0.02 Jy) also does not produce high luminosity objects especially at higher redshifts (e.g z > 1) . We show that by fitting the simulated IR luminosity function to observed LIR, our model is able to produce more bright sources at high redshifts and match reasonably well to the observed number counts.