Predicting Results from Scintillating Bubble Chambers Through the Use of Molecular Dynamic Simulations to Replicate Conditions Needed for Bubble Nucleation
Session Number
PHYS 04
Advisor(s)
Prof. Eric Dahl, Northwestern University
Discipline
Physical Science
Start Date
17-4-2024 10:45 AM
End Date
17-4-2024 11:00 AM
Abstract
Scintillating bubble chambers detect particle interactions between ionizing radiation and molecules in superheated liquids—liquids maintaining their state of matter despite being heated past their boiling point. These particle interactions can generate nuclear recoils, causing hot spikes experienced by small groups of the liquid’s molecules, which lead to bubblenucleation in the chamber. Interactions with dark matter may also produce nuclear recoils; thus, identifying these bubble formations and understanding the conditions needed for bubbles to form is key to further understanding dark matter particle interactions. Using the HOOMD-Blue Python library, we created a molecular dynamics simulation that models particle interactions in such superheated liquids by creating hot spikes in the centers of simulated Lennard-Jones fluids in superheated liquid states. From the subsequent time the environments and visualizations of the particles’ positions at different time intervals. We used this information to determine whether or not a given hot spike in a given superheated state resulted in a bubble. Several of these simulations did result in bubble formation, confirming that with the given tools, we can successfully model the bubble nucleation process.
Predicting Results from Scintillating Bubble Chambers Through the Use of Molecular Dynamic Simulations to Replicate Conditions Needed for Bubble Nucleation
Scintillating bubble chambers detect particle interactions between ionizing radiation and molecules in superheated liquids—liquids maintaining their state of matter despite being heated past their boiling point. These particle interactions can generate nuclear recoils, causing hot spikes experienced by small groups of the liquid’s molecules, which lead to bubblenucleation in the chamber. Interactions with dark matter may also produce nuclear recoils; thus, identifying these bubble formations and understanding the conditions needed for bubbles to form is key to further understanding dark matter particle interactions. Using the HOOMD-Blue Python library, we created a molecular dynamics simulation that models particle interactions in such superheated liquids by creating hot spikes in the centers of simulated Lennard-Jones fluids in superheated liquid states. From the subsequent time the environments and visualizations of the particles’ positions at different time intervals. We used this information to determine whether or not a given hot spike in a given superheated state resulted in a bubble. Several of these simulations did result in bubble formation, confirming that with the given tools, we can successfully model the bubble nucleation process.