Franco's PhD was completed under supervision of Dr Joe Walding as a member of the Particle Astrophysics group.
Left : Simon Peeters, external examiner, Centre : Franco La Zia, PhD candidate, Right : Dr Joseph Walding, Supervisor
Franco's thesis titled " Neutron Calibration and Characterisation of the DEAP-3600 Experiment Using a 74MBq AmBe Neutron Source" continues the search for dark matter. This AmBe source, during calibration runs, populates the detector with nuclear recoils, allowing to calibrate it to WIMP-like nuclear recoils.
Franco's contribution was to develop a methodology to simulate AmBe interactions in the detector in an efficient way in order to reach a significant statistics in a short amount of time. He used these simulations to train machine learning algorithms that were able to isolate single scatter (WIMP-like) events in the AmBe calibration data, from multiple scatter events which were actually the majority in the simulated sample (thus in data as well once was proved that monte-carlo and data were matching).
A clean sample of single scatters isolated with this method can then be used to determine the nuclear recoil acceptance in DEAP-3600.
Franco has gone on to work as a data scientist for Accenture in Milan.