Silicon Tracking and a Search for Long-lived Particles

The ATLAS Detector, below the surface of the Swiss-French border, measures the remnants of high-energy proton- proton collisions, accelerated by the Large Hadron Collider (LHC) at CERN. Recently the LHC paused operations, having delivered an integrated luminosity corresponding to 150 fb−1 of data at a centre-of-mass energy of 13 TeV. This thesis describes a search for physics beyond the Standard Model using that dataset as well as the charged particle tracking detector technology that renders it possible. The analysis searches for long-lived, massive particles identified by a characteristic decay displaced from the interaction point and produced in association with high momentum jets. Searching for rare processes requires sifting through a large amount of data, which stresses the ATLAS computing infrastructure. As such, measures are taken to reduce unnecessary computations and supplement our existing resources with, for example, inherently parallel computing architectures. Early adoption of these new architectures is necessary to understand the feasibility of their potential integration, including porting existing algorithms. A popular algorithm used in track reconstruction, the Kalman filter, has been implemented in a neuromorphic architecture: IBM’s TrueNorth. The limits of using such an architecture for tracking, as well as how its performance compares to a non-spiking Kalman filter implementation, are explored in this thesis. In 2026 the LHC will enter a High Luminosity phase (HL-LHC), increasing the instantaneous luminosity by a factor of five and delivering 4000 fb-1 within twelve years. This will impose significant technical challenges on all aspects of the ATLAS detector, resulting in the entire ATLAS Inner Detector being replaced by an all-silicon tracker. ITk (the new “Inner TracKer”) will be comprised of Strip and Pixel detectors. The layout of the Pixel and Strip detectors was optimised for the upgrade to extend their forward coverage. To cope with the increased number of hits per chip per event and explore novel techniques for dealing with the conditions in HL-LHC, an inter-experiment collaboration, RD53, was formed, tasked with producing a front-end readout chip used in Pixel detectors. This thesis will briefly outline the author’s contribution to both of these projects. ITk silicon sensors will undergo significant damage over their lifetime due to non-ionising energy loss (NIEL). This damage must be incorporated into the detector simulation both to predict the detector performance and to understand the effects of radiation damage on data taking. The implementation of NIEL radiation damage in the ATLAS simulation framework is discussed in this thesis.