A Likelihood Ratio Framework for Highly Motivated Subdominant Signals
This paper proposes a robust likelihood ratio framework designed to evaluate the compatibility of highly motivated theoretical models with experimental residuals, specifically addressing the challenge of detecting subtle new physics signals that manifest as small deviations from established background predictions.