Abstract
X-ray-like background has the ability to introduce significant systematic and statistical errors to astronomical measurements from space-based X-ray observatories. Statistical errors from radiation-induced X-ray-like background can dominate the noise in images produced by space-based X-ray telescopes and can severely reduce scientific output. However, the composition and quantity of radiation-induced X-ray-like background events that will be present in a space-based X-ray observatory is not well understood. The work presented in this thesis has investigated several key research areas. The results of two experimental campaigns are presented, which are used to assess the accuracy of Geant4 at simulating low energy radiation to mimic the space-based environment. Geant4 simulations are then used to predict the particle composition of radiation-induced background in the environment of space. The composition of background for a detector in a spherical shell spacecraft model is characterised through Geant4 simulations, and it is found that on-chip filters could significantly reduce the background due to electrons and low energy photons. It is also found that for the purposes of maximising signal-to-noise ratio in an ideal detector, there exists an optimal detector thickness for a given particle composition of background. Finally, key results for investigations into shielding methods include the creation of a mathematical model for the determination of optimal graded-Z shielding locations, and the demonstration that a Helmholtz coil magnetic field structure could be used to significantly reduce the background induced by both low energy fully absorbed electrons, and backscattering electrons. Much of the simulation work in this thesis was performed on geometries similar to the expected geometry of the Wide Field Imager (WFI) in the European Space Agency's ATHENA mission as an example of a general X-ray astronomy mission, and to predict the background that will be present in images from the WFI when ATHENA launches in the 2030s.