Running the analysis¶

The pipeline — anaTuples, observables, histograms, plots — is the standard FLAF chain; follow the FLAF full-workflow walkthrough for the commands (InputFileTask → … → HistPlotTask). This page collects what is specific to H→μμ.

ERA=Run3_2022
VER=dev

law run FLAF.Analysis.tasks.HistPlotTask \
  --period $ERA --version $VER --workflow local --branches 0 --test 1000

No statistical-inference stage here¶

Unlike the HH analyses, H→μμ does not include a statistical-inference step in this repository — there is no StatInference/inference submodule, and the pipeline ends at histograms/plots. Any interpretation is done with separate tooling outside this repository.

Categories¶

H→μμ is split into production-mode categories (e.g. VBF- and ggH-enriched selections). Category and channel selection is driven by config/global.yaml; adjust it there or via your user_custom.yaml.

Running all eras¶

H→μμ targets every Run 3 era. Run a stage per era, or — in CI — set H_mumu_eras: ALL (see FLAF → Integration pipeline). Remember that one law run processes one --period at a time.

Choosing which variables to histogram¶

As for any FLAF analysis, the variable set is controlled by the variables: list in user_custom.yaml (or --variables):

variables:
  - mu1_pt
  - m_mumu

Lower-case CI process names

H→μμ's CI process names are lower-case (custom_CI_signal, custom_CI_background, custom_CI_data) — unlike the capitalised names in the HH analyses. Use the exact name from config/processes.yaml when passing --process.