Development of topographical data analysis methods for AGATA

This project entails the investigation and optimisation of gamma localisation algorithms used to analyse data from the Advanced Gamma Tracking Array (AGATA), in particular the method of pulse shape analysis (PSA) through machine learning was used to find comparable matches between experimental signal data and reference pulses stored in a pre-existing library. The main aim of this project is to develop novel approaches to PSA that will hopefully lead to a more accurate and efficient method of gamma localisation within the detector array. With a more efficient gamma localisation algorithm understanding the interactions of gamma rays happening inside the tracking array and individual gamma ray tracking should be significantly easier. These improvements will in turn lead to a better peak/total ratio by eliminating a large portion of the continuum of a spectrum and advancements in the field of gamma spectroscopy.