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Bayesian inference to study a signal with two or more decaying particles in a non-resonant background

2022/10/13 by Ezequiel Álvarez, Alvarez, Ezequiel · 2 citations
Physics and Astronomy · #FOS: Physical sciences #High Energy Physics - Experiment (hep-ex) #High Energy Physics - Phenomenology (hep-ph) #Nuclear Physics and Applications #Radiation Detection and Scintillator Technologies #Scientific Research and Discoveries

paper · pdf · doi:10.48550/arxiv.2210.07358

openalex publication_date 2022/10/13 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

We study the application of a Bayesian method to extract relevant information from data for the case of a signal consisting of two or more decaying particles and its background. The method takes advantage of the dependence that exists in the distributions of the decaying products at the event-by-event level and processes the information for the whole sample to infer the mixture fraction and the relevant parameters for signal and background distributions. The algorithm usually needs a numerical computation of the posterior, which we work out explicitly in a benchmark scenario of a simplified pp→ hh → b b γγ search. We perform a posterior predictive check on the results and we show how the signal fraction is correctly extracted from the sample, as well as many parameters in the signal and background distributions. The presented framework could be used for other searches such as pp→ ZZ, WW, ZW and pair of Leptoquarks, among many others.

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