School of Science Department of Physics 68 Search for Light Dark Matter with Positronium Supervisor: LUK Kam Biu / PHYS Student: LAM Hoi Hang Hiram / PHYS Course: UROP 1000, Summer Positronium is a bounding state consisting of an electron and its anti-particle, positron. Its decay modes are well predicted and described by quantum electrodynamics (QED). However, the existence of rare or invisible decay channels could indicate hidden interactions with dark matter. This project aims to design and implement an experimental setup, to investigate the decay properties of positronium. The current phase focuses on evaluating the performance of various scintillating materials, which emit photons upon interaction with other high energy photons and charged particles, such as positrons and gamma rays. These materials enable the detection of positronium formation and annihilation events. The behavior and response of the Silicon Photomultipliers (SiPM), essential for detecting the photons produced, are being analysed. Search for Light Dark Matter with Positronium Supervisor: LUK Kam Biu / PHYS Student: YIK Wai Ting / PHYS Course: UROP 1000, Summer This report studies the properties of positronium, a bound state of an electron and its antiparticle, the positron, using the Bohr model and the hydrogen atom model. By substituting the proton with a positron, we derive the allowed energy states, the effect of the fine and hyperfine structures of the positronium. We also derive the range of energy the positron, “Orc Gap”, requires to form positronium inside a gas. Additionally, we discuss thermalization and pick-off effects that can distort decay measurements, emphasizing the need for considering these factors in experimental design. This study provides the essential information about positronium behavior, which helps to plan for future experimental investigations. Theoretical Modeling of the Motion of Particles in Energy Walls Supervisor: PARK Hyo Keun / PHYS Student: CHEUNG King Nam / PHYS-IRE Course: UROP 1100, Summer This essay examines the computer simulation of nanoparticle diffusion across a geometrical landscape, with the goal of aligning theoretical predictions with experimental findings by Prof. Park and Prof. Wong. The simulation applies the Gillespie Algorithm to model Brownian motion and interactions with structural obstacles, investigating the impact of geometry on diffusion dynamics. By analyzing various elements of the simulation data, such as nanoparticle reinitialization, ring region analysis and variations in landscape dept, the study reveals observable trends from the dwell time distribution that support both theoretical explanations and experimental outcomes.
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