Speaker
Description
Due to the large number of Swift GRB detections, it has been possible to select sub-samples of long GRBs that are reasonably complete in redshift and with observed prompt and afterglow emission. We perform Bayesian inference to constrain the distributions of burst parameters of the population, in accordance with the observed physical properties of the BAT6 sample. We use the structured jet models in our analysis package Afterglowpy to model the distribution of afterglow observations for the sample. Applying this to observations at key times in the X-ray, optical and radio domains, we create an observationally-calibrated tool for population synthesis modelling. From this, we derive population predictions for afterglow observations including Inverse Compton features in the TeV regime.
