Dataset Open Access

Supplementary Data: Global fits of GUT-scale SUSY models with GAMBIT (arXiv:1705.07935)

The GAMBIT Collaboration

Supplementary Data

Global fits of GUT-scale SUSY models with GAMBIT
arXiv:1705.07935

The files in this record contain data for the CMSSM, NUHM1 and NUHM2 models considered in the GAMBIT "Round 1" GUT-scale SUSY paper.

For each model, there are

  • A number of YAML files, each corresponding to a different set of sampling parameters and/or priors
  • A set of YAML files used for postprocessing: CMSSM_intermediate.yaml, CMSSM.yaml, NUHM1.yaml and NUHM2.yaml
  • A final hdf5 file, containing the combined results of all sampling runs
  • An example pip file, for producing plots from the hdf5 file using pippi

The record also contains

  • StandardModel_SLHA2_scan.yaml and StandardModel_SLHA2_postprocessing.yaml, two universal YAML fragments included from other yaml files
  • gambit_preamble.py, a collection of python functions used for in-line data processing in the pip files

The different YAML files corresponding to different samplers and/or priors follow the naming scheme [model]_[scanner]_[prior]_[slice]_[special].yaml, where

  • model = CMSSM, NUHM1, NUHM2
  • scanner = Diver, MN
  • prior = log, flat
  • slice = pmu, nmu (positive or negative mu)
  • special = sqcoann, slcoann, [blank] (squark co-annihilation, slepton co-annihilation, or bulk)

A few caveats to keep in mind:

  1. For each model, the final hdf5 results file included here was generated in the following way:

    • carry out initial runs using YAML files following the naming scheme above
    • combine the resulting hdf5 output files into a single file, using gambit/Printers/scripts/combine_hdf5.py
    • postprocess the samples to remove all points more than 5 sigma from the current best fit, using [model]_strip.yaml
    • postprocess the samples to include a new likelihood term for LHC Run II searches, and to recompute the FlavBit likelihoods (these were buggy in a pre-release version of GAMBIT). For the CMSSM, this happened in two steps, due to persistent flavour bugs, using CMSSM_intermediate.yaml and CMSSM.yaml. For the NUHM1 and NUHM2, this was done in a single step each, using NUHM1.yaml and NUHM2.yaml.
  2. 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.

  3. 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.

  4. The YAML files are designed to work with the tagged release of GAMBIT 1.0.0, and the pip files are 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).

  5. The pip file for each model 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.

Files (48.8 GB)
Name Size
CMSSM.hdf5.tar.gz
md5:337e038e1f13a2de0b6752449a2ab603
10.9 GB Download
CMSSM.pip
md5:45e61058ee1781b7fa3e7a4f17c79057
14.9 kB Download
CMSSM.yaml
md5:78e4e15215763819685df70f5238e0b5
4.0 kB Download
CMSSM_Diver_flat_nmu.yaml
md5:246a8799e2e313dff69f918bb37cadb8
11.2 kB Download
CMSSM_Diver_flat_pmu.yaml
md5:5a65153cb2ad0f1549241a42b41b79e9
11.2 kB Download
CMSSM_Diver_log_nmu.yaml
md5:3a5243f10e60db9228ea329f0860617a
11.4 kB Download
CMSSM_Diver_log_nmu_slcoann.yaml
md5:82959a9260411a881a1f8b0432303c7e
11.8 kB Download
CMSSM_Diver_log_nmu_sqcoann.yaml
md5:7b630d2dc9d204c838acafb2650cf411
11.8 kB Download
CMSSM_Diver_log_pmu.yaml
md5:9afea5155e766d6f5a18ccbad4c8da73
11.4 kB Download
CMSSM_Diver_log_pmu_slcoann.yaml
md5:2d68e20a09f322b63eb9e9fa50d24dc3
11.8 kB Download
CMSSM_Diver_log_pmu_sqcoann.yaml
md5:df688b66c7e316312f25a5dd797d9f16
11.8 kB Download
CMSSM_intermediate.yaml
md5:8f93bebb4e0be1dc76a0cd86c76e9a09
7.4 kB Download
CMSSM_MN_flat_nmu.yaml
md5:1090e5b5087037d511af3ecb39e4fedc
11.2 kB Download
CMSSM_MN_flat_pmu.yaml
md5:e689132a4f5515db88ae43e7f8f2b0bb
11.2 kB Download
CMSSM_MN_log_nmu.yaml
md5:d08def2f0d6b8a801c881bf5d9c3a893
11.4 kB Download
CMSSM_MN_log_pmu.yaml
md5:ce706a4030194bc9b5a6388430ea7c9f
11.4 kB Download
gambit_preamble.py
md5:836f4aae006b11761523f5b5f92b78aa
1.5 kB Download
NUHM1.hdf5.tar.gz
md5:d93df62875013cb3cc0d20bb9c004611
14.6 GB Download
NUHM1.pip
md5:858082575f44a30b075989e118dfbc93
14.9 kB Download
NUHM1.yaml
md5:01ca12c1781a1291f6f4f6a7a88c980e
7.4 kB Download
NUHM1_Diver_flat_nmu.yaml
md5:1decff68cbb3ea7f94103386119fa372
11.3 kB Download
NUHM1_Diver_flat_pmu.yaml
md5:5226ca9bdef847a9bf3c3c9703ba28b3
11.3 kB Download
NUHM1_Diver_log_nmu.yaml
md5:b28b65b1f0ea594ce22a3111470c193c
11.5 kB Download
NUHM1_Diver_log_nmu_slcoann.yaml
md5:bfad2cadf34b4af5e64561505d0e1aa2
11.9 kB Download
NUHM1_Diver_log_nmu_sqcoann.yaml
md5:75405618604828f5a7b59156714fe094
11.9 kB Download
NUHM1_Diver_log_pmu.yaml
md5:b0e98469603ec04d95fc78b44d5ef392
11.4 kB Download
NUHM1_Diver_log_pmu_slcoann.yaml
md5:4e45b3b0fc37f6e556104685fe3eee26
11.9 kB Download
NUHM1_Diver_log_pmu_sqcoann.yaml
md5:9079978a876174c4430c3c34a1357799
11.9 kB Download
NUHM1_MN_flat_nmu.yaml
md5:f7d39d5835da1c4c08a2072ba7f83f1c
11.3 kB Download
NUHM1_MN_flat_pmu.yaml
md5:5faecc751e3dc714710a7b999ade42c6
11.3 kB Download
NUHM1_MN_log_nmu.yaml
md5:af76794689397b9a4159a20706b9108a
11.4 kB Download
NUHM1_MN_log_pmu.yaml
md5:3a39c3ce3893e0b8da5186f7c3d79a8e
11.4 kB Download
NUHM2.hdf5.tar.gz
md5:6706750339362e6122d5b627c09aa7e5
23.2 GB Download
NUHM2.pip
md5:ac5a2a8cbe678088469572fc60b484e1
15.0 kB Download
NUHM2.yaml
md5:702cc7c2cfa5972bfc3488ffc288ffe4
7.4 kB Download
NUHM2_Diver_flat_nmu.yaml
md5:333df172d8c1b71f90a9c0d66778f9de
11.4 kB Download
NUHM2_Diver_flat_pmu.yaml
md5:942deac92a377c7f63a535eb52f34058
11.4 kB Download
NUHM2_Diver_log_nmu.yaml
md5:c32e71e47ecbfb21c581e254712949f2
11.7 kB Download
NUHM2_Diver_log_nmu_slcoann.yaml
md5:4b343c2454257c931c580c41c9b3abd7
12.1 kB Download
NUHM2_Diver_log_nmu_sqcoann.yaml
md5:61059c6d48a233545877492d7847cb3a
12.1 kB Download
NUHM2_Diver_log_pmu.yaml
md5:c9f664edad1d752b87a50af3cbc482bc
11.5 kB Download
NUHM2_Diver_log_pmu_slcoann.yaml
md5:0992edcd7e34b97498a6b23e4d672094
12.1 kB Download
NUHM2_Diver_log_pmu_sqcoann.yaml
md5:0c7659a8f3477cf6555cc315051e1e60
12.1 kB Download
NUHM2_MN_flat_nmu.yaml
md5:ee56bdd86747ef517e81b56ff739a586
11.3 kB Download
NUHM2_MN_flat_pmu.yaml
md5:771b56521f7313c71958cdc95748089f
11.3 kB Download
NUHM2_MN_log_nmu.yaml
md5:86056c4fe091791866d0ff65a263c298
11.5 kB Download
NUHM2_MN_log_pmu.yaml
md5:64c6c46aa0776edfa17309f1dfe0a121
11.5 kB Download
README_GUT.md
md5:a1231b60695040e89432693f5327790a
3.6 kB Download
StandardModel_SLHA2_postprocessing.yaml
md5:84fa3f0c3a2f9ec3cab8179138dcf7d1
948 Bytes Download
StandardModel_SLHA2_scan.yaml
md5:0dd9947f80c9c2c441d19df1057fc9bf
3.0 kB Download

Share

Cite as