Monte Carlo Simulation Variance Reduction Techniques for Photon Transport in Liquid Xenon Detectors

Monte Carlo simulations are a crucial tool for the analysis and prediction of various background components in liquid xenon (LXe) detectors. With improving shielding in new experiments, the simulation of external backgrounds, such as induced by gamma rays from detector materials, gets more computationally expensive. We introduce and validate an accelerated Monte Carlo simulation technique for photon transport in liquid xenon detectors. The method simulates photon-induced interactions within a defined geometry and energy range with high statistics while interactions outside of the region of interest are not simulated directly but are taken into account by means of probability weights. For a simulation of gamma induced backgrounds in an exemplary detector geometry we achieve a three orders of magnitude acceleration compared to a standard simulation of a current ton-scale LXe dark matter experiment

Radon daughter removal from PTFE surfaces and its application in liquid xenon detectors

Long-lived radon daughters are a critical background source in experiments searching for low-energy rare events. Originating from radon in ambient air, radioactive polonium, bismuth and lead isotopes plate-out on materials that are later employed in the experiment. In this paper, we examine cleaning procedures for their capability to remove radon daughters from PTFE surfaces, a material often used in liquid xenon TPCs. We found a large difference between the removal efficiency obtained for the decay chains of $^{222}$Rn and $^{220}$Rn, respectively. This indicates that the plate-out mechanism has an effect on the cleaning success. While the long-lived $^{222}$Rn daughters could be reduced by a factor of ~2, the removal of $^{220}$Rn daughters was up to 10 times more efficient depending on the treatment. Furthermore, the impact of a nitric acid based PTFE cleaning on the liquid xenon purity is investigated in a small-scale liquid xenon TPC