An assay-based background projection for the MAJORANA DEMONSTRATOR using Monte Carlo Uncertainty Propagation
Abstract
The background index is an important quantity which is used in projecting and calculating the half-life sensitivity of neutrinoless double-beta decay () experiments. A novel analysis framework is presented to calculate the background index using the specific activities, masses and simulated efficiencies of an experiment's components as distributions. This Bayesian framework includes a unified approach to combine specific activities from assay. Monte Carlo uncertainty propagation is used to build a background index distribution from the specific activity, mass and efficiency distributions. This analysis method is applied to the MAJORANA DEMONSTRATOR, which deployed arrays of high-purity Ge detectors enriched in Ge to search for . The framework projects a mean background index of cts/(keV kg yr) from Th and U in the DEMONSTRATOR's components.
Keywords
Cite
@article{arxiv.2408.06786,
title = {An assay-based background projection for the MAJORANA DEMONSTRATOR using Monte Carlo Uncertainty Propagation},
author = {I. J. Arnquist and F. T. Avignone and A. S. Barabash and C. J. Barton and K. H. Bhimani and E. Blalock and B. Bos and M. Busch and T. S. Caldwell and Y. -D. Chan and C. D. Christofferson and P. -H. Chu and M. L. Clark and C. Cuesta and J. A. Detwiler and Yu. Efremenko and H. Ejiri and S. R. Elliott and N. Fuad and G. K. Giovanetti and M. P. Green and J. Gruszko and I. S. Guinn and V. E. Guiseppe and C. R. Haufe and R. Henning and D. Hervas Aguilar and E. W. Hoppe and A. Hostiuc and M. F. Kidd and I. Kim and R. T. Kouzes and T. E. Lannen and A. Li and J. M. López-Castaño and R. D. Martin and R. Massarczyk and S. J. Meijer and T. K. Oli and L. S. Paudel and W. Pettus and A. W. P. Poon and D. C. Radford and A. L. Reine and K. Rielage and N. W. Ruof and D. C. Schaper and S. J. Schleich and D. Tedeschi and R. L. Varner and S. Vasilyev and S. L. Watkins and J. F. Wilkerson and C. Wiseman and W. Xu and C. -H. Yu},
journal= {arXiv preprint arXiv:2408.06786},
year = {2026}
}
Comments
9 pages, 3 figures