Supplementary Data Status of the scalar singlet dark matter model arXiv:1705.07931 The files in this record contain data for the scalar singlet dark matter model considered in the GAMBIT "Round 1" scalar singlet paper. The files consist of Three YAML files, each corresponding to a different parameter range StandardModel_SLHA2_SingletDM_scan_15.yaml, a universal YAML fragment included from the other three YAML files Three hdf5 files. SingletDM.hdf5 contains the combined results of all sampling runs, and is the basis for the profile likelihood plots in the paper. SingletDM_TW_full.hdf5 and SingletDM_TW_lowmass.hdf5 contain the results from T-Walk scans over the full and low-mass parameter ranges, respectively. These are the bases for the marginalised posterior plots in the paper. An example pip file corresponding to each hdf5 file, for producing plots using pippi A tarball best_fits_yaml.tar.gz containing YAML files of the best-fit point in each subregion of the fit. The YAML files corresponding to different parameter ranges follow the naming scheme SingletDM_[slice].yaml, where slice may be full, lowmass or neck. Each of these YAML files contains entries in the Scanners node for running Diver, MultiNest, TWalk and GreAT. A few caveats to keep in mind: 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.

v2 adds YAML benchmark files for the best-fit points in each region of the model.