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Wang, Kaijie

The evidence of dark matter indicates the incompleteness of the Standard Model (SM), suggesting the existence of new physics beyond the SM that is associated with dark matter. One of the dark matter theories, the dark sector theory, proposes the existence of both a dark force and dark sector particles. A dark sector model, dark shower, hypothesizes that multiple dark sector particles are produced during e+e− collisions. One specific dark sector particle, named 𝜌0d meson in this model, is theorized to decay into SM particles. Searching for low-mass 𝜌0d involves analyzing its decay products e+e−. Specifically, we aim to search for 𝜌0d by studying the particles produced from e+e− collision using the Belle II detector at SuperKEKB. A critical aspect is to distinguish potential 𝜌0d decay events from the background events created by photon conversion to e+e− pairs. To achieve this, an analysis of the characteristics of photon conversion and 𝜌0d decay through Monte Carlo simulation is performed. Additionally, I trained two machine-learning models, with carefully chosen training variables, to effectively filter out background events. Notably, one of the algorithms, XGBoost, achieves a remarkable accuracy of 96.1% on the test dataset. This high efficiency demonstrates that the XGBoost model is exceptionally effective at eliminating photon conversion background noise in 𝜌0d decay studies, and shows the strong potential for other low-mass signal searches with photon conversion background.

Text

University of British Columbia. PHYS 449

Vancouver : University of British Columbia Library

10.14288/1.0443763

Science, Faculty of; Physics and Astronomy, Department of

Undergraduate

http://creativecommons.org/licenses/by-nc-nd/4.0/