Simulation-based modelling of gamma-ray burst afterglows from SKA to CTA

The PhD project involves simulating gamma ray burst (thereafter referred to as GRB) afterglows, and in particular working on relevant phenomena that were previously not studied in depth. GRBs are the most powerful emissions in the universe, and the science of GRBs have seen rapid development in the recent years due to increasing sample sizes. However, there are still many open questions about GRBs, such as the conditions of their progenitors, and how the angle of emission impacts our observed spectra.

The afterglow of GRBs contain ample information on the structure and origin of these emissions, but they are encoded by the observation angle and jet structure, which need to be modelled with care. This project will build on previous efforts to model GRBs, but include new information regarding inverse Compton scattering, and model a wider range of wavelengths especially at higher energies.

This is timely as multi-messenger observations are bringing new possibilities of breakthroughs to the science of GRBs: The Cherenkov Telescope Array, CTA, will provide observations of Compton emission instead of synchrotron emission, which can be used to put a constraint on the magnetisation of jets; the Square Kilometre Array, on the other hand, will significantly increase the sample size of radio observations, which will reveal more information on the original ejecta. The project also involves synthetic population analysis, which can help with assessing the possibility of joint detections.

Joint detections in the radio band and of high-energy gamma ray burst afterglows can help constraining certain parameters, or even eliminate model degeneracies.

The project also involves the development of an existing Python package for modelling gamma ray burst afterglows, Afterglowpy, to include the above mentioned features associated with GRB afterglows. There are mainly two ways of modelling GRB afterglows. There are highly resolute numerical simulations that model the details of specific jets, which are particularly helpful for examining the detailed structure of on- and off-axis jets; however, these approaches are computationally expensive, and there is a need for faster, synthetic simulations of GRB afterglows, albeit coarser.

Compared to GAMMA and KATU, the existing numerical simulations that fall into the former category, Afterglowpy allows for Bayesian inference and quick analysis of large datasets. The former can serve as a calibration for the latter, while the latter has been successful in producing coarse fittings for larger samples. However, Afterglowpy also has a few important omissions that will be helpful to take into consideration going forward.

Namely, spatially resolved imaging, inverse Compton emission, and ejecta emission based on reverse shock crossing and long-term energy emission. These will be addressed as more observational data become available.

Apart from adding new physics into the Afterglowpy package, the project also aims to pre-package the currently independent Python package so that it can be integrated into more generic inference software, such as Multinest.

Although the project primarily focuses on the theoretical aspects of gamma ray bursts, there is a chance that it can take on a more observational approach as more data become available from observational collaborations. For example, the project may lean towards direct analysis of raw data, or making direct observations.