RJaBi/charmBaryonData: Version 1, Draft 1

Charm Baryon Data

This repository contains the data and plot-input files required to reproduce the figures in the charm parity paper

Conda instructions: Install Environment

conda env create -f environment.yml

Activate/Use

conda activate charm

Update (w. new packages)

1. Edit environment.yml
2. Deactivate conda environment with conda deactivate
3. Update conda environment with conda env update -f=environment.yml

Run Instructions:

• change the scriptDir variable in main.sh and parityRatioRun.sho to where you have cloned the script repository https://github.com/RJaBi/charmBaryonScripts
• ensure that main.sh is executable (i.e. chmod o+x main.sh)
  • This is neccessary for the subscript that runs the fits to work
• activate the charm conda environment
• Run Figures 1, 5-14 via ./main.sh
  • This will likely take up to ~12 hours as it does all the fits
  • Once the fits are made, the process is much quicker as the fits are saved
• Run Figures 2-4 via running parityRatioRun.sh
  • This will likely take 12+ hours
  • running the parityRatio plots off is slow, the inflection points are quick
  • If you are doing this without running main.sh, you will need to make sure parityRatioRun unzip's the correlators

The output will be in output/ but the figures actually used in the paper will be copied into paperPlots/

The input files for the fits are in baseToml. They are copied and modified by the run_fits script such that all combinations of operator, quarks and temperatures are done from the smaller subset of template toml files.

Other input files are complete, based upon the relative paths defined. These are in completeToml

Figure Details

• Figure 1
  • Plots the correlators
  • plotG.py
• Figures 2-4
  • Does the parity-doubling R-ratio analysis
  • gvarParityRatio.py
  • plotInflectionPoints.py
• Figures 5-8
  • Does fits to the correlators and model averages
  • simpleFit.py
• Figure 9
  • Plots the spectrum of masses against experiment
  • plotSpectrum.py
• Figures 10-13
  • Plots the spectrum of masses as a function of temperature
  • simplePlotEMP.py
• Figure 14
  • Considers the Gell-Mann-Okubo relation
  • GellMannOkubo.py