Dataset Open Access
The GAMBIT Collaboration
Supplementary Data
A global fit of the MSSM with GAMBIT
arXiv:1705.07917
The files in this record contain data for the MSSM7 model considered in the GAMBIT “Round 1” weak-scale SUSY paper.
The files consist of
The different YAML files corresponding to different samplers and/or priors follow the naming scheme MSSM7_[scanner]_[prior]_[slice]_[special].yaml , where
A few caveats to keep in mind:
The final hdf5 results file included here was generated in the following way:
It is not necessary to repeat the steps listed in point 1 when running new scans; the LHC Run II likelihoods can be included in the original YAML file, so that no postprocessing step is required.
The YAML files that we give here are updated compared to the ones that we used when generating the hdf5 file, in order to match the set of available options in the release version of GAMBIT 1.0.0. The included physics and numerics are however identical.
The YAML files are designed to work with the tagged release of GAMBIT 1.0.0, and the pip file is tested with pippi 2.0, commit 2ab061a8. They may or may not work with later versions of either software (but you can of course always obtain the version that they do work with via the git history).
The pip file is an example only. Users wishing to reproduce the more advanced plots in any of the GAMBIT papers should contact us for tips or scripts, or experiment for themselves. Many of these scripts are in multiple parts and require undocumented manual interventions and steps in order to implement various plot-specific customisations, so please don’t expect the same level of polish as for files provided here or in the GAMBIT repo.
Name | Size | |
---|---|---|
best_fits_SLHA.tar.gz
md5:a2943a2828b820047c3da1e96c618beb |
116.0 kB | Download |
gambit_preamble.py
md5:836f4aae006b11761523f5b5f92b78aa |
1.5 kB | Download |
MSSM7.hdf5.tar.gz
md5:c19061a02a43a02c32bec648e328bda4 |
35.6 GB | Download |
MSSM7.pip
md5:8ac032eb95a9cd6081a9454bcc6f02f0 |
14.5 kB | Download |
MSSM7.yaml
md5:dada82f479f529703bffdf22e7248889 |
7.6 kB | Download |
MSSM7_Diver_flat_nM2.yaml
md5:86d17a69061712e67e7c215b1b1e8fe7 |
11.7 kB | Download |
MSSM7_Diver_flat_nM2_jDE.yaml
md5:9bf9f2c00b9a6e57f2c54b744f250dda |
11.8 kB | Download |
MSSM7_Diver_flat_pM2.yaml
md5:08dbdf3cb8d559b9e6c25ca14c4467fa |
11.7 kB | Download |
MSSM7_Diver_flat_pM2_jDE.yaml
md5:3b3b830b2105e8503f4430d3d70f01dc |
11.8 kB | Download |
MSSM7_Diver_log_Afunnel_jDE.yaml
md5:7cd9e5b629d15385a3a5f7266a7559b5 |
12.2 kB | Download |
MSSM7_Diver_log_hZfunnel_jDE.yaml
md5:887f7c920b1067037d3db0bbfffed841 |
12.0 kB | Download |
MSSM7_Diver_log_nM2.yaml
md5:5a08d8c04af32ed2ad66395c7f361e9b |
11.9 kB | Download |
MSSM7_Diver_log_nM2_jDE.yaml
md5:9518e08a1f3d08ef8b71b70ba6fc72b6 |
11.9 kB | Download |
MSSM7_Diver_log_pM2.yaml
md5:0c04595dee4c13dd355fdaff307f33ab |
11.9 kB | Download |
MSSM7_Diver_log_pM2_jDE.yaml
md5:aea983d5f9328b953229a5c76463cef1 |
11.9 kB | Download |
MSSM7_Diver_log_slcoann_jDE.yaml
md5:d6ca37399cd2073dd89026fc6f9f57c7 |
12.3 kB | Download |
MSSM7_Diver_log_sqcoann_jDE.yaml
md5:05048b658cf31b99eb3cdf7f4ef680d8 |
12.3 kB | Download |
MSSM7_MN_flat_nM2.yaml
md5:1d36fb98a3e591753e56df4e595b9a78 |
11.6 kB | Download |
MSSM7_MN_flat_pM2.yaml
md5:539f4995ace96e064ddc675a9c204a21 |
11.6 kB | Download |
MSSM7_MN_log_nM2.yaml
md5:2520a2a417eb114cdc44e302f58e8f88 |
11.9 kB | Download |
MSSM7_MN_log_pM2.yaml
md5:e54c3812e6ea5a58982f03bc49a5f8a5 |
11.9 kB | Download |
README_MSSM7.md
md5:1bda59e7963cf5980654109f6099b050 |
3.4 kB | Download |
StandardModel_SLHA2_postprocessing.yaml
md5:84fa3f0c3a2f9ec3cab8179138dcf7d1 |
948 Bytes | Download |
StandardModel_SLHA2_scan.yaml
md5:0dd9947f80c9c2c441d19df1057fc9bf |
3.0 kB | Download |
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