English

High-Dimensional Bayesian Likelihood Normalisation for CRESST's Background Model

Instrumentation and Detectors 2025-01-10 v2 Instrumentation and Methods for Astrophysics High Energy Physics - Experiment

Abstract

Using CaWO4_4 crystals as cryogenic calorimeters, the CRESST experiment searches for nuclear recoils caused by the scattering of potential Dark Matter particles. A reliable identification of a potential signal crucially depends on an accurate background model. In this work we introduce an improved normalisation method for CRESST's model of the electromagnetic backgrounds. Spectral templates, based on Geant4 simulations, are normalised via a Bayesian likelihood fit to experimental background data. Contrary to our previous work, no assumption of partial secular equilibrium is required, which results in a more robust and versatile applicability. Furthermore, considering the correlation between all background components allows us to explain 82.7% of the experimental background within [1 keV, 40 keV], an improvement of 18.6% compared to our previous method.

Keywords

Cite

@article{arxiv.2307.12991,
  title  = {High-Dimensional Bayesian Likelihood Normalisation for CRESST's Background Model},
  author = {G. Angloher and S. Banik and G. Benato and A. Bento and A. Bertolini and R. Breier and C. Bucci and J. Burkhart and L. Canonica and A. D'Addabbo and S. Di Lorenzo and L. Einfalt and A. Erb and F. v. Feilitzsch and S. Fichtinger and D. Fuchs and A. Garai and V. M. Ghete and P. Gorla and P. V. Guillaumon and S. Gupta and D. Hauff and M. Jeskovsky and J. Jochum and M. Kaznacheeva and A. Kinast and H. Kluck and H. Kraus and S. Kuckuk and A. Langenkaemper and M. Mancuso and L. Marini and L. Meyer and V. Mokina and A. Nilima and M. Olmi and T. Ortmann and C. Pagliarone and L. Pattavina and F. Petricca and W. Potzel and P. Povinec and F. Proebst and F. Pucci and F. Reindl and J. Rothe and K. Schaeffner and J. Schieck and D. Schmiedmayer and S. Schoenert and C. Schwertner and M. Stahlberg and L. Stodolsky and C. Strandhagen and R. Strauss and I. Usherov and F. Wagner and M. Willers and V. Zema and F. Ferella and M. Laubenstein and S. Nisi},
  journal= {arXiv preprint arXiv:2307.12991},
  year   = {2025}
}

Comments

38 pages, 15 figures, accepted version to JINST

R2 v1 2026-06-28T11:38:55.698Z