Speaker
Description
With the projected background reductions through cryogenic distillation systems and material selection, the XLZD detector aims for an internal radioactive isotope background an order of magnitude lower than the solar $pp$ neutrino-electron scattering rate. Given a target mass of $O(10)\,$tonnes of liquid xenon (LXe), XLZD will have sufficient statistics to measure the solar $pp$ flux with sub-percent accuracy. To realize this potential, a dedicated effort to characterize the measurement uncertainties for each radioactive background component is just as critical.
This DFG-funded project focuses on investigating, improving, and standardizing the measurement sensitivities for krypton ($^{85}\mathrm{Kr}$), radon ($^{222}\mathrm{Rn}$ and $^{220}\mathrm{Rn}$), and detector-material-induced backgrounds. For krypton, the project introduces the Xenon Filter for Krypton detection Enhancement (XeFKrE) system. Integrated into the LowRAD krypton distillation column and utilizing the Automatic Rare Gas Mass Spectrometer (Auto-RGMS), XeFKrE is designed to produce a well-defined $^{\mathrm{nat}}\mathrm{Kr}$ calibration source at the $O(10)\,$ppq level with better than 10% accuracy. For radon, the project plans to establish a full decay-chain analysis framework to constrain the rates of the beta-emitting progeny, $^{214}\mathrm{Pb}$ and $^{212}\mathrm{Pb}$, to within 1%. This framework leverages existing data from $^{222}\mathrm{Rn}$ and $^{220}\mathrm{Rn}$ calibrations, incorporating continuous source injection, algebraic Bateman equations for decay chains, and empirical modeling of loss mechanisms such as the plate-out effect. Finally, for material backgrounds, the project explores machine learning techniques that optimize the Monte Carlo simulation performance in the solar $pp$ region of interest (ROI). The ultimate goal of this work is to provide a realistic error budget reference for the electron-recoil detection channel in XLZD.
This work is supported by DFG under project number 565663248 and ERC AdG LowRad under project number 101055063.