Gas-Phase Ultrafast Electron Diffraction (GUED) is a technique used for analyzing the molecular dynamics of molecules using electrons. The purpose of this research is to develop a computational model that consolidates all adjustable parameters in GUED to optimize the tracking of electrons in a program called General Particle Tracer (GPT). This involves creating a customizable input system within GPT based on a laboratory setup that includes variables such as electron beam size, intensity, duration, and all the parameters that the beam interacts with. The laboratory setup involves a photoemission source, acceleration gradients, lenses, and compression cavities. These components will be programmed into GPT with user-defined boundaries. The output of the GPT model will depict the beam spread, duration, and orientation as it travels through the apparatus. The results of the simulation will be directly compared to the laboratory setup of the GUED experiment. We will compare any discrepancies between the simulation and the experiment and continually optimize the code to fit the real-world results. This project will create an efficient diagnostic and verification tool to use when performing GUED experiments as described by Dr. Centurion’s group.

A convolutional neural network (CNN) model was previously trained to identify electromagnetic ion cyclotron (EMIC) waves from spectrograms from Halley magnetometer station in Antarctica. The model was trained on three years of data spanning from 2015 to 2017. When tested, it identified all spectrograms manually labelled as having EMIC wave events. Antarctica is fairly far from human interventions so the data set is less noisy compared to stations at eastern Arctic Canada. Therefore, this research project aims to train the model on a relatively more noisy data set from Nain, Halley’s magnetically conjugate station in the northern hemisphere. The training data set includes 2022 and 2023 spectrograms from Nain. If successful, less time will be spent on identifying and cataloguing EMIC waves from spectrograms and comparing the wave activity during solar maximum and minimum years.

Muons, charged particles that are heavier than the electron, can be useful for achieving tera-electron volt energy levels and for enabling more precise measurements of other fundamental particles. However, a significant obstacle in creating muon collisions is their microsecond lifetime, which is too short to allow quality collisions. Ionization cooling enables high-quality beam manipulation within the muon’s short lifetime, allowing high-energy collisions. For my research, I will analyze how the designed ionization cooling system for a future muon collider will affect parameters such as emittance, momentum, and the position of muons moving through the cooling system by creating simulations through a software called G4Beamline. Research in muon colliders and accelerators can have applications such as muon tomography for non-invasive imaging and future possibilities in cancer treatment.

YBCO (YBa2Cu3O7-x) are a class of high temperature superconductors, consisting of planes and chains of copper and oxygen atoms. To date, most research has focused on under- and optimally-doped YBCO, demonstrating properties such as higher critical temperatures and interesting electron/superconducting behaviors. Our focus is to study an overdoped YBCO. Doping is achieved by synthesizing crystals in a well-controlled oxygen environment, which changes the overall electronic structure of the material. These changes affect the superconducting properties, such as critical temperatures and relaxation rates. Conventional wisdom suggests that with sufficiently high doping, the superconducting transition temperature will decrease and eventually reach zero. However, preliminary experiments have suggested otherwise. To further understand these properties and determine whether this behavior is a common occurrence in overdoped YBCO, we use nuclear quadrupole resonance (NQR) to investigate the local charge environment of the different Cu sites through the electron field gradient (EFG). We measure the spectra, which gives direct information about the doping, and the spin-lattice relaxation and decoherence rates. From this sample we can compare the critical temperature and relaxation rates to the lower and optimally doped cuprates.