Tyler Rolfe’s Post

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MSc Machine Learning in Science

Following on from my previous post, I am delighted to share my final undergraduate project: Dark Matter Direct Detection. This project combined elements from many of my undergraduate modules, including Atomic Physics, Particle Physics, Cosmology, Astrophysics, and Scientific Computing. I am thrilled to have received a first-class mark for this project, as well as for the module overall, which also included several report writing and presentation tasks. The abstract for this project is included at the bottom of this post, and the PDF of my final submission is attached for those interested in learning more. If anyone has any questions regarding any elements of this project, please don't hesitate to get in touch. I will do my best to answer them for you. Abstract: The search for dark matter remains one of the most compelling topics in physics. Despite decades of searching, conclusive evidence of a direct detection remains elusive. We explore the factors that contribute to a model for the expected number of events for different hypothetical Weakly Interacting Massive Particle (WIMP) masses, considering factors from nuclear physics, particle physics and astrophysics. This model is then examined for a number of different detector nuclei, establishing and exploring the relationship of heavier nuclei being superior for heavier WIMP masses, and vice-versa. The assumptions made in this model are examined and a brief overview of other experiments is given. Finally, the investigation delves into the importance of the WIMP-Proton cross section and its continuously diminishing threshold, which casts doubt on the WIMP's status as the primary dark matter candidate.

Courtney Layzell

Graduate intern at MHR

6mo

Informative read! Congratulations on your success.

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