Rachael O’Sullivan

My name is Rachael O’Sullivan and I hold an MPhys degree in Physics with Astrophysics from the University of Leicester. During my degree I completed projects including simulating compact binary merger populations and producing temperature maps of Jupiter’s poles to investigate atmospheric structure and weather. These experiences developed my interest in computational physics, which I will now apply to the field of nuclear fusion through my PhD project “AI-Assisted High Repetition Rate Development at the European XFEL” at the University of York, supervised by Dr Andy Higginbotham and Dr Andy Comley (AWE).

Fusion has the potential to provide an abundant and clean source of energy, and achieving this in inertial confinement experiments requires rapidly firing powerful lasers in order to compress fuel targets. At these high repetition rates, vast amounts of experimental data are generated, and rapid analysis is essential to keep the system optimised. This creates a challenge, as conventional analysis methods are too slow to provide feedback on the required timescales.

My project will investigate the application of neural networks to this problem, focusing on how AI can be used to rapidly interpret experimental data and feed this back into experimental control systems. I will also explore whether AI can play a more active role by suggesting laser parameters and shot timings, and by identifying new areas of physics that may emerge during experiments.