Collaborative project to find the Higgs Boson from muon muon decay in ATLAS data
Each line of the data file contains 7 columns:
- Transverse momentum pT of the first muon
- Azimuthal angle of the first muon
- The pseudo-rapidity of the first muon
- Transverse moment pT of the second muon
- Azimuthal angle of the second muon
- The pseudo-rapidity of the second muon
- The effective mass of the dimuon system
- higgs.data: Monte-Carlo data for the Higgs Boson
- MC-Z0.data: Monte-Carlo data for the Z Boson
- real-dimuon-4M.data: Real data containing 4 million dimuon events from ATLAS at the CERN LHC
- real-dimuon-400k.data: Real data containing 400,000 dimuon events from ATLAS at the CERN LHC
- real-dimuon-small-1.data: Real data containing 1000 dimuon events from ATLAS at the CERN LHC
- load.py: loads data files and returns a pandas dataframe.
- plot.py: plots the input data in a histogram.
- crystalball.py: plots a histogram of input data and fits aa crystal ball function.
- fit_higgs.py: plots a histogram of higgs.data and fits a voigt curve.
- fit_MCZ0.py: plots a histogram of MC-Z0.data, fits a voigt curve and a power law curve.
- angular_distance.py: Calculates and plots the angular distance of the dimuon pair.
- Z0_processing.py: Takes the ratio of the real dimuon data and the MC-Z0 data to remove the Z0 background.
- summed_fit.py: Sums the power law background model and the crystal ball Higgs model and fits it to the input real dimuon data file.
- interpolate.py: Fits the power law background model to the data, but excludes data in a given "gap region" at the location of the Higgs. Calculates integral under the background curve in the gap region and sums the number of bins in the region. This gives the expected and real number of bins respectively.
- higgs_range_errors.py: Finding percentage of points contained in a range their associated errors. Dataframe at the end tabulates errors and percentages to be sorted and compared.