James, Robert;
(2024)
Signals, backgrounds and statistical inference for dark matter direct detection experiments.
Doctoral thesis (Ph.D), UCL (University College London).
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Abstract
Astrophysical observations spanning galactic to cosmological scales provide compelling evidence that approximately 85% of matter in the Universe is composed of a non-luminous substance known as dark matter. Despite decades of work, dark matter remains elusive. Weakly interacting massive particles (WIMPs) are a well-motivated candidate for particle dark matter, producing the correct relic abundance whilst requiring minimal extensions to the Standard Model. Dual phase multi tonne liquid xenon time projection chambers (TPCs), operated in deep underground laboratories for background reduction, are the current world-leading technology in the search for WIMP dark matter. This thesis presents a novel statistical inference framework capable of enhancing the physics potential of these instruments. This framework, FlameNEST, incorporates the state-of-the-art set of models for noble element response physics from NEST, the Noble Element Simulation Technique. It eschews the need for computationally expensive Monte Carlo simulation, instead allowing analytical and differentiable likelihood evaluation accelerated on GPUs. FlameNEST allows for the inclusion of additional event observables and nuisance parameters within the likelihood in a computationally efficient manner, increasing both the reach and robustness of results. A number of analyses are presented on first data from the world leading LUX-ZEPLIN (LZ) experiment using FlameNEST. These include a re-analysis of the first WIMP search results of the experiment using a 6D observable space, an analysis placing experimental constraints on fermionic dark matter absorption by nuclei, and work towards a search for the Migdal effect in liquid xenon. Additionally, the framework is used to characterise the sensitivity of a proposed future liquid xenon TPC, the XLZD project, to WIMP dark matter under different design scenarios. The use of FlameNEST to provide rapid sensitivity projections for a wide variety of beyond the Standard Model physics searches using this instrument is also highlighted.
| Type: | Thesis (Doctoral) |
|---|---|
| Qualification: | Ph.D |
| Title: | Signals, backgrounds and statistical inference for dark matter direct detection experiments |
| Open access status: | An open access version is available from UCL Discovery |
| Language: | English |
| Additional information: | Copyright © The Author 2024. Original content in this thesis is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) Licence (https://creativecommons.org/licenses/by-nc/4.0/). Any third-party copyright material present remains the property of its respective owner(s) and is licensed under its existing terms. Access may initially be restricted at the author’s request. |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences > Dept of Physics and Astronomy |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10190030 |
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