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Browsing School of Physics (ETDs) by SDG "SDG-15: Life on land"
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Item The application of weakly supervised learning in the search for heavy resonances at the LHC(University of the Witwatersrand, Johannesburg, 2023-06) Choma, Nalamotse Joshua; Ruan, Xifeng; Mellado, BruceThe discovery of the Higgs boson at the Large Hadron Collider by the ATLAS and CMS experiments has made the search for new physics beyond the Standard Model a priority in the field of High Energy Particle Physics. New resonances have yet to be discovered using inclusive and model-dependent searches, which means they may be driven by subtle topologies. Rapid improvements in Machine Learning techniques have led to their increasing application in High Energy Particle physics. Unlike supervised learning, which is known to assume full knowledge of the underlying model, semi-supervised learning, in particular weakly supervised learning, allows the extraction of new information from data with partial knowledge. The goal of this study is to set up searches for heavy resonances at the electroweak scale with topological requirements performed in both inclusive and exclusive regions of phase-space tailored to a particular production mode. These resonances could be generated with different production mechanisms. In this work, we describe search procedures based on weakly supervised learning applied to mixed samples and used to search for resonances with little or no prior knowledge of the production mechanism. This approach has the advantage that sidebands or control regions can be used to effectively model backgrounds without relying on models. The effectiveness of this method is measured by the production of the Standard Model Higgs boson, which decays into a pair of photons in both inclusive and exclusive regions of phase-space at the LHC. Having confirmed the ability of the method to extract various Standard Model Higgs boson signal processes, the search for new phenomena in high mass final states will be set up at the LHC. Subsequently, the approach is used in the search for new resonances in the Zγ final state with Z → e +e − or Z → µ +µ −, using the Monte Carlo simulated signal samples for 139 fb−1 of integrated luminosity for Run 2 collected at the LHC. The weakly supervised learning approach is implemented and compared to the performance of the fully supervised approach, which is then used to calculate the production limit for Higgs-like particles for Zγ where the significance of the signal is maximal.Item The culprit for the termination of Mars’ magnetic field: Dark Matter(University of the Witwatersrand, Johannesburg, 2024) Makda, JaveriaThe reason for a significant change in the heat flux of the interior of Mars, leading to the termination of its magnetic dynamo, is not yet known. We present the idea that interaction of dark matter particles with the elements constituting the core of Mars is the cause for this significant heat flux change. We include resonant enhancements in the determining of the capture rate of dark matter particles by a planet, using more recent formulations. The exclusion limits for the interaction cross-sections in our work are more stringent than previous limits. We demonstrate, using Xenon1T limits, that the density of dark matter in our solar neighbourhood is insufficient to induce significant heating. However, encounters with low-mass ultra-compact mini-halos or very massive conventional sub-halos could both produce significant heating effects within terrestrial planets. We find that in 1 Gyr, there is a possibility of up to ∼ 860 interactions of Mars with an ultra-compact mini-halo, that would have the sufficient density and mass to alter the workings of the convective core of Mars, such that it would lead to the cessation of the Martian geodynamo. The interaction of Earth with these halos would not result in the cessation of its magnetic field due to mechanisms such as tectonic activity, crust recycling and the subsequent motion of molten iron in its outer core, which result in the continuous functioning of the geodynamo