Using Monte Carlo Simulations to Tag and Predict Mobilities of ²²²Rn Daughters

Author: Samuel Schleich, Department of Physics

Mentor: Dr. Richard Schnee, Department of Physics

In the search for dark matter, detectors using tanks of liquid xenon (LXe) experience their dominant source of radiation as radon that has emanated out of the materials used to construct the detector and into the LXe, where dark matter interactions are searched for. Radon’s ability to emanate out of the material and into the detector stems from its nature as a chemically inert element. ²²²Rn and its polonium daughters have easily identifiable alpha decay events, whereas ²²²Rn’s granddaughter, ²¹⁴Pb, has a decay that can look identical to a predicted dark matter interaction, posing the largest threat as a false positive.

The emanation of ²²²Rn into the LXe and its effect on background interference can be modeled and studied using Monte Carlo simulations. The simulation produces random values and applies them to a set of equations to determine when and where each atom will decay. This data is then sent to a “tagging” algorithm, which sorts decay events based on time and location within the detector. The ²¹⁴Pb parent decays can be easily tagged, but tagging a ²¹⁴Pb decay event due to its half-life and uncertain energy released will pose a challenge. The movement due to the convection of the LXe, the random motion of the atoms, and the mobility of charged daughters in the electric field complicate this process further.

Specifically, the mobility of charged ²²²Rn daughters through the LXe impacts the tagging process greatly, as it changes based on two main factors: the combination of a daughter ion with another ion, and its neutralization as it acquires a free electron. Both processes and their probabilities can also be calculated similarly using a Monte Carlo simulation. Ultimately, the goal of this work is to accurately predict the positions of ²²²Rn daughters to eliminate false positives.