Date of Thesis
Spring 2026
Description
XENONnT is a physics experiment designed with the goal of detecting dark matter particles. The detector is a time projection chamber; a series of charged electrodes creates an electric field, surrounding a central body filled with liquid and gaseous xenon. Photomultiplier tubes (PMTs), positioned on either end of the chamber, serve to detect light signals. We seek to minimize the root mean square of the electric field norms experienced by the PMTs. This quantity corresponds to the variance in the electric field observed by the PMTs. Establishing a consistent electric field is important to maintaining these sensitive components. The electric field's distribution can be modulated via two screening rings positioned near the PMTs, one on either end of the detector. Using the simulation software COMSOL we adapted a pre-existing model of the detector to evaluate this quantity. We determined the ideal voltage for each of these screening rings based on the voltage of the other components within the chamber, finding a linear relationship between the voltage of the Anode and Cathode to the ideal voltage of the screening rings. We also determined the average electric field magnitude on the PMTs for a specific Anode or Cathode voltage. Additional factors were also evaluated, including a comparison of the simulated XENONnT in its current state to a past iteration of the detector. While the old setup led to lower field magnitudes on the PMTs, the performance from preliminary tests suggests that the conditions for the PMTs with the screening ring are acceptable.
Keywords
Physics, Computer Science, Dark Matter, Particle Physics, Experiment, Xenon, COMSOL, Electrostatics, Simulation
Access Type
Honors Thesis
Degree Type
Bachelor of Science in Computer Science and Engineering
Major
Computer Science & Engineering
Minor, Emphasis, or Concentration
Physics
First Advisor
Abby Kopec
Second Advisor
Chris Mitsch
Recommended Citation
Meloni, Miles, "Utilizing computer modeling to optimize electric fields within XENON time projection chambers" (2026). Honors Theses. 744.
https://digitalcommons.bucknell.edu/honors_theses/744
Included in
Data Science Commons, Elementary Particles and Fields and String Theory Commons, Engineering Physics Commons, Numerical Analysis and Scientific Computing Commons
