This repository contains the software implementation for our paper A Novel Approach to Higgs Coupling Measurements (Cranmer, Kreiss, Lopez-Val, Plehn), arXiv:1401.0080 [hep-ph]. It contains tools to apply the discussed methods to new models and contains a Makefile to recreate the plots in the paper.

A demo for the recoupling stage where the effective likelihood and template parametrization are readily provided is at decoupledDemo.

Clone the repository. Then create a virtualenv (which usually comes with your python environment or can be insalled) and install this package and all requirements with pip:

virtualenv venv
source venv/bin/activate
pip install -r requirements.txt

For development and to use the latest versions of all dependencies, use requirements_dev.txt.

You can create your own model and run decouple and recouple on them. decouple takes root files with a RooWorkspace, containing the model as input and produces the effective Likelihood and eta files. recouple takes eta files and effective Likelihoods (also from multiple channels to do a combination) and produces coupling results.

Example models are in the module ModelGenerators.

A fully working example that recouples a model that someone else decoupled is implemented in the decoupledDemo project.

Run everything with

make -j8

This tells make to use parallel builds with 8 jobs in parallel. All profiled effective scans are implemented using the multiprocessing python module which will use as many jobs as there are CPUs. So this can lead to 8 make jobs where each runs 8 multiprocessing jobs.

For finer control, the framework can also be run step-by-step:

1. make models: runs the makefile inside the ModelGenerators module
2. make decouple: runs Decouple/decouple.py on all the models generated with ModelGenerators. For finer control, make decoupleTwoBin and make decoupleAtlasCounting runs the two sets individually.
3. make recouple: runs Decouple/recouple.py on all decouple outputs. Also here, there are make recoupleTwoBin and make recoupleAtlasCounting.
4. make plots

The above chain can be used as a best-practice example to setup your own models. The Makefile is just a guide so that you can see how to run Decouple/decouple.py and Decouple/recouple.py yourself on your own models.

This package depends on a few related Python packages that are generally useful. For this package, they are installed automatically by pip with the install instructions above.

• LHCHiggsCouplings: Interface to cross sections and branching ratios published by the LHC Higgs Cross Section Working Group with interpolation in Higgs mass.
• BatchLikelihoodScan: Powerful tool for likelihood scans and easily runs on batch clusters.
• PyROOTUtils: Collection of useful tools for working with TGraphs and generally plotting with ROOT.

Please cite K. Cranmer, S. Kreiss, D. Lopez-Val and T. Plehn (2014) <http://arxiv.org/abs/1401.0080> if you find this code useful in your research.

Copyright 2013-2014 Sven Kreiss, Kyle Cranmer

decouple is free software made available under the MIT License. For details see the LICENSE file.