ZANanoGEN:

Parton-level physics analyses based on event samples produced by matrix-element generators are far from describing the reality of what is observed in any existing detector.

NanoGen is simply a way to produce NanoAOD with only the GEN-related branches.

It is possible to produce NanoGen directly from a gridpack without the need for time consuming SIM and RECOsteps, which makes it convenient for GEN-level studies. It is also possible to produce NanoGen from GEN, AOD, or MINIAOD inputs if you would like to make a gen-only skim.

The automatic building of NanoGen configurations with cmsDriver is supported in CMSSW_10_6_X for X >= 19, and for CMSSW_11_2_X for X >= 0_pre7 or greater (i.e., 11_3 and above).

Setup CMSSW area :

To set up in a new CMSSW area:

cmsrel CMSSW_10_6_19_patch2
cd CMSSW_10_6_19_patch2/src
cmsenv
mkdir Configuration
git clone https://github.com/kjaffel/NanoGenScripts -o Configuration/NanoGenScripts
scram b

or inside an existing CMSSW area

cd $CMSSW_BASE/src
mkdir -p Configuration
git clone https://github.com/kjaffel/NanoGenScripts -o Configuration/NanoGenScripts
scram b

gridpacks -> LHE -> GEN: [slurm submission]

At this stage I am assuming that you manage to generate gridpacks stored by default in :genproductions/bin/MadGraph5_aMCatNLO/

1. Save your gridpacks tarball some where :

bash loadgridpacksfromlxplus.sh

2. Submit jobs to slurm:

python slurmOverallgridpacks.py --path --output

• -p/--path : path to _tarball.tar.xz gridpacks
• -o/--output: output dir by default will be tha same as the output
• --decay_in: need to be madspin or pythia8 accordingly the gen-fragment will be changed.
• --nbrjobs : must be int, default = 2

3. Merge your outputs :

python scripts/mergeOutput.py --path to_slurm_dir 

LHE -> GEN:

If you have lhe files: Go to folderName/Events/run_01. In there should be a file named unweighted_events.lhe.gz . To unzip it, use:

zcat unweighted_events.lhe.gz > unweighted_events.lhe
or gunzip unweighted_events.lhe.gz

You should now have unweighted_events.lhe, which is the file to be used in further analysis.

./Configuration/NanoGenScripts/lheToNanoGen.sh <fragment> <lhe> <output>

where <fragment> is a fragment with an externalLHEProducer and hadronizer settings compatible with the process in the LHE file.

Get gridpack and fragments for a dataset: snippets/1488

python getGenInfo.py --cernSSOcookies=prodcookies.pkl /HToZATo2L2B_MH-500_MA-300_13TeV-madgraph-pythia8/RunIISummer16NanoAODv7-PUMoriond17_Nano02Apr2020_102X_mcRun2_asymptotic_v8-v1/NANOAODSIM

This (python3) script assumes you have a grid proxy (to query DAS) and kerberos token (to get a session cookie for McM - set up with kinit username@CERN.CH). It also depends on cerndb/cern-sso-python with a patch, which can be installed with

pip install git+https://github.com/pieterdavid/cern-sso-python.git@addverifyarg 

Useful Links:

• NanoGen twiki page
• Kenneth Long's repo
• Pieter David repo