A CMS analysis with paper-ready plots¶

The goal of this example is to show how to use fasthep-flow to perform a full HEP analysis with paper-ready plots and tables. This includes more complex tasks such as:

systematic uncertainties for MC samples and/or physics objects
control regions for background estimation
scale factors for data/MC comparison
statistical analysis of the results
provenance tracking for reproducibility and accountability

Note

Looking for volunteers and public data to create this example!

Control regions¶

Control regions are used to estimate the background in the signal region or verify procedures outside the signal region (e.g. for searches). From a workflow perspecite, they are effectively independent branches. To split a workflow, you will need to use the needs keyword:

stages:
  - name: Data Input Stage
    ...
  - name: Common selection
    ...
  - name: signal selection
    needs: [Common selection]
    ...
  - name: control selection
    needs: ["Common selection"]
    ...
  - name: Create histograms for signal region
    needs: ["signal selection"]
    ...
    - name: Create histograms for control region
    needs: ["control selection"]
    ...
  - name: Output
    needs: ["Create histograms for signal region", "Create histograms for control region"]
    ...

This will create a DAG like this:

flowchart TD A[Data Input Stage] --> B(Common selection) B --> C[signal selection] B --> D[control selection] C --> E[Create histograms for signal region] D --> F[Create histograms for control region] E --> G[Output] F --> G