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)

Edit environment.yml

Deactivate conda environment with conda deactivate

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