A Bayesian Search for the Higgs Particle
Applications
2016-05-10 v2
Abstract
The statistical procedure used in the search for the Higgs boson is investigated in this paper. A Bayesian hierarchical model is proposed that uses the information provided by the theory in the analysis of the data generated by the particle detectors. In addition, we develop a Bayesian decision making procedure that combines the two steps of the current method (discovery and exclusion) into one and can be calibrated to satisfy frequency theory error rate requirements. .
Keywords
Cite
@article{arxiv.1501.02226,
title = {A Bayesian Search for the Higgs Particle},
author = {Shirin Golchi and Richard Lockhart},
journal= {arXiv preprint arXiv:1501.02226},
year = {2016}
}