Monte Carlo simulations of the X/Gamma-ray Imaging Spectrometer instrument onboard the THESEUS mission

Gamma-Ray Bursts are among the most studied high-energy transient phenomena in the last few decades. Their prompt emission, rapid and energetic, peaking in the gamma-ray band, is followed by the afterglow emission, which spans a broad energy range. This characteristic has allowed for the investigation of their nature and properties. The extreme luminosity of GRBs makes them invaluable tools for investigating the Early Universe and advancing Multi-Messenger Astrophysics. The ESA M7 THESEUS mission, currently in Phase A, has been proposed for the detection and localization of GRBs. Its innovative capabilities, are expected to significantly advance our understanding of GRBs. Its payload includes two wide-field instruments both operating in the X-ray and gamma-ray energy bands, SXI and XGIS, as well as a high-resolution InfraRed Telescope. The combined capabilities of these instruments will enable THESEUS to continuously scan the sky for high-energy transients and to rapidly re-point at them with the telescope, allowing for onboard redshift estimation. In this thesis, a study has been conducted on the performance of the XGIS instrument, which works both as an imager and as a spectrometer. The focus of my study is on evaluating XGIS effective area, instrumental response, and estimates of the background noise count rate in the Low Earth Orbit where it will operate. The performance has been assessed using a Monte Carlo simulation software built upon the CERN Geant4 toolkit, which allows for the study of the passage of particles through matter. In particular, this work implements several improvements and upgrades to the simulations carried out during the previous M5 Phase A study, by introducing a more accurate mass model for XGIS compared to the original design. A random-pattern realistic coded mask and various passive layers have been included. Simulations with both the simple and upgraded mass models will then be compared.