Signal discovery in sparse spectra: a Bayesian analysis

Abstract

A Bayesian analysis of the probability of a signal in the presence of background is developed, and criteria are proposed for claiming evidence for, or the discovery of a signal. The method is general and in particular applicable to sparsely populated spectra. Monte Carlo techniques to evaluate the sensitivity of an experiment are described. As an example, the method is used to calculate the sensitivity of the GERDA experiment to neutrinoless double beta decay.

15 pages, 5 figures

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Cited by in corpus (11)

• Results on neutrinoless double beta decay of 76Ge from GERDA Phase I
• Toward the discovery of matter creation with neutrinoless double-beta decay
• Measurement of the half-life of the two-neutrino double beta decay of Ge-76 with the Gerda experiment
• A novel approach to quantifying the sensitivity of current and future cosmological datasets to the neutrino mass ordering through Bayesian hierarchical modeling
• CUORE Sensitivity to $0\nu \beta \beta$ Decay
• p-Values for Model Evaluation
• Impact of Coherent Neutrino Nucleus Scattering on Direct Dark Matter Searches based on CaWO${}_4$ Crystals
• Dark-Photon Search using Data from CRESST-II Phase 2
• Results on neutrinoless double beta decay from GERDA Phase I
• JUNO sensitivity to the annihilation of MeV dark matter in the galactic halo
• Determination of neutrino mass ordering in future ${}^{76}$Ge-based neutrinoless double-beta decay experiments