Python code implements a diagnostic framework for precision Higgs measurements, demonstrating reproducible analyses.
Category-Induced Coupling Distortions: Core Diagnostic Code Description: Python implementation of the weight-concentration diagnostic framework described in Blatt (2026), "Category-Induced Coupling Distortions in Precision Higgs Measurements." The code provides four analytic functions and a Monte Carlo validation routine: weight_concentration — computes the weight-concentration factor f and combined statistical uncertainty from category uncertainties rms_combined — analytic RMS of the combined estimator including unresolved category structure thresholds — returns the relevance, action, and combination-limit thresholds for a given category configuration pull_variance — computes the pull variance including category-induced broadening run_pseudoexperiments — Monte Carlo validation of the analytic RMS using pseudo-experiments with fixed random seed for reproducibility Benchmark configurations for current-like and HL-LHC-like H→μμ analyses are included. All numerical results and figures in the companion paper are reproducible from this code. Related publication: https://doi.org/10.5281/zenodo.20583049
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Kate Lynn Blatt (2026) studied this question.
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