Published August 29, 2024
| Version v1
Dataset
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Large mass hierarchies from strongly-coupled dynamics---Recombined data release
Authors/Creators
Description
This release contains data associated with the publication Large mass hierarchies from strongly-coupled dynamics (JHEP 06 (2016) 114).
Compared to the raw data release, it makes the following changes:
- The two CSV files present in the raw data release are combined, with a common column schema. Since not all data were retained from all steps of the original computation, some of these data have been recomputed.
- The lattice data plotted in Figs. 2 and 3 of the paper are also included, and plotted by the Mathematica notebook.
It comprises five files:
README.md: containing this summary and further details of the contents of each file.su2_adjoint_lattice_data.csv: the data for the points plotted in Figures 2 and 3 of the paper. Masses of the scalar and tensor glueball, extracted from Monte Carlo ensembles of SU(2) with adjoint fermions.sigmamodel.csv: the data shown in Figures 4 and 5 of the paper. The mass of the composite spin-0 and spin-2 states, computed for , as a function of , normalised to the mass of the lightest scalar or tensor.DataRelease.nb: A Mathematica notebook that will take the above three files and generate plots similar to thsoe shown in the paper. This has been tested using Mathematica 14.0.unify_lmh_2016.zip: A Snakemake and Python workflow to take the data from the raw data release, some data released as part of the analysis workflow for arXiv:2408.00171, and some previously unpublished data included in the archive, and generate the two CSV files above. Includes aREADME.mdfile containing more information about how to run the workflow.
Files
README.md
Files
(518.4 kB)
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Additional details
Related works
- Documents
- Journal article: 10.1007/JHEP06(2016)114 (DOI)
- Requires
- Dataset: 10.5281/zenodo.13128485 (DOI)
- Workflow: 10.5281/zenodo.12802810 (DOI)
Funding
- UK Research and Innovation
- Reproducible analysis frameworks in Lattice Field Theory and STFC-enabled computational research in Wales EP/V052489/1
Software
- Repository URL
- https://github.com/edbennett/unify_lmh_2016
- Programming language
- Python , Snakemake , Mathematica