Example code to produce the di-muon spectrum from a CMS 2010 primary dataset

Description

This simple analysis example is set up at Research level, i.e. it requires university-student-level programming experience. Minimal acquaintance with Linux and the ROOT analysis package (https://root.cern.ch/) as well as a basic text editor is needed.

System details

CMS VM Image, for 2010 CMS open data

Validation

Only the list of validated runs are accepted:

CMS list of validated runs Cert_136033-149442_7TeV_Apr21ReReco_Collisions10_JSON_v2.txt

How can you use this?

If you do not have the CERN Virtual Machine for 2010 CMS data installed, follow the instructions in step 1 at How to install a CERN Virtual Machine. Then install and run the Demo (demo analyzer) program following the instructions at How to Test & Validate.

To run the "di-muon spectrum" demo:

1. Create directory datasets under Demo/DemoAnalyzer.
2. Download the index files for the /Mu/Run2010B-Apr21ReReco-v1/AOD primary datasets and store them in Demo/DemoAnalyzer/datasets/.
3. Download the JSON file from CMS Validated Runs and save it to the Demo/DemoAnalyzer/datasets directory.
4. Replace the three files BuildFile.xml, demoanalyzer_cfg.py, src/DemoAnalyzer.cc with the ones from this record and read the comments in DemoAnalyzer.cc if you want to understand what the program does.
5. Recompile (scram b) and rerun (cmsRun ...) exactly as shown before in How to Test & Validate.
6. You should get an output file Mu.root, which contains histograms for 10000 input events (a small subset of the data). These can be looked at using a ROOT Browser (see above, under Description). The most interesting histogram is GM_mass_log. In order to compare it with the invariant-mass spectrum of di-muons in MUO-10-004, it should be viewed with the logy option. Of course with 10000 events the comparison is poor, but the J/ψ (at log10(mass)=0.5), Υ (at log10(mass=0.98)) and Z (at log10(mass)=1.95, one event only) peaks should be visible.
7. Finally, to run over more or even the full data, edit the relevant parts of the Python file demoanalyzer_cfg.py (see comments therein) and rerun. Add up the output histograms from different (non-overlapping) input index files using ROOT tools.

Disclaimer

GNU General Public License (GPL) version 3