Z' Bosons at Colliders: a Bayesian Viewpoint
Jens Erler, Paul Langacker, Shoaib Munir, Eduardo Rojas

TL;DR
This paper employs a Bayesian statistical framework to analyze collider data for Z' bosons, allowing flexible parameter variation and interference effects, leading to refined mass limits and model discrimination capabilities.
Contribution
It introduces a Bayesian method for Z' boson analysis that incorporates interference, parameter variation, and combines multiple data sources, improving upon previous approaches.
Findings
Bayesian approach yields Z' mass limits similar to CDF but with more flexibility.
Interference effects are crucial for model discrimination.
Method reduces reliance on arbitrary event count assumptions.
Abstract
We revisit the CDF data on di-muon production to impose constraints on a large class of Z' bosons occurring in a variety of E_6 GUT based models. We analyze the dependence of these limits on various factors contributing to the production cross-section, showing that currently systematic and theoretical uncertainties play a relatively minor role. Driven by this observation, we emphasize the use of the Bayesian statistical method, which allows us to straightforwardly (i) vary the gauge coupling strength, g', of the underlying U(1)'; (ii) include interference effects with the Z' amplitude (which are especially important for large g'); (iii) smoothly vary the U(1)' charges; (iv) combine these data with the electroweak precision constraints as well as with other observables obtained from colliders such as LEP 2 and the LHC; and (v) find preferred regions in parameter space once an excess is…
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