Data-driven background model for the CUORE experiment

We present the model we developed to reconstruct the CUORE radioactive background based on the analysis of an experimental exposure of 1038.4 kg yr. The data reconstruction relies on a simultaneous Bayesian fit applied to energy spectra over a broad energy range. The high granularity of the CUORE detector, together with the large exposure and extended stable operations, allow for an in-depth exploration of both spatial and time dependence of backgrounds. We achieve high sensitivity to both bulk and surface activities of the materials of the setup, detecting levels as low as $10\text{ }\text{ }\mathrm{nBq}\text{ }{\mathrm{kg}}^{\ensuremath{-}1}$ and $0.1\text{ }\text{ }\mathrm{nBq}\text{ }{\mathrm{cm}}^{\ensuremath{-}2}$, respectively. We compare the contamination levels we extract from the background model with prior radio-assay data, which informs future background risk mitigation strategies. The results of this background model play a crucial role in constructing the background budget for the CUPID experiment as it will exploit the same CUORE infrastructure.