My PhD research within the ATLAS experiment focused on two main topics: the search for top squark pair production, and the ATLAS High-Level Trigger (HLT). Top squark searches have always been a crucial component of the ATLAS supersymmetry programme. A light Higgs boson is a natural feature of many supersymmetric models if the mass of the top squark is relatively low, making it a good candidate for discovery at the LHC. I was the main analyser for the search for top squark pair production in the dileptonic final state, using Run 2 and early Run 3 data. A highlight of my work is the development of a new event selection strategy based on a neural network, to enhance the analysis sensitivity. This search aims to be public in early 2026, and will be one of the first ATLAS supersymmetry results based on Run 3 data.
Since the start of Run 3, ATLAS is recording up to 3 kHz of fully built physics events out of an LHC collision rate of 40 MHz, with additional rate allocated to partial event readout. The two-level trigger system is responsible for selecting in real time events of interest for the broad ATLAS physics programme, while rejecting a high rate of background events. One of the main challenges of the ATLAS trigger system is to maximise the physics outcome of the recorded dataset while operating within strict constraints on bandwidth and CPU resources. During my PhD, I contributed to the ATLAS HLT software, focusing primarily on the trigger menu. I am the main maintainer of the software framework used daily by menu experts to prepare the trigger configuration for data-taking, and I also worked on trigger performance monitoring tools and software performance studies. Additionally, I had the opportunity to take on the crucial role of trigger menu and online on-call expert, covering more than 100 days of shifts, and directly contribute to the successful collection of the Run 3 dataset.
