A.A. was supported by the Horizon 2020 European research infrastructures programme “NI4OS-Europe” with grant agreement no. 85764, by “SimEA" project funded by the European Union’s Horizon 2020 research and innovation programme under grant agreement No 810660, as well as by the “EuroCC" project funded by the “Deputy Ministry of Research, Innovation and Digital Policy and the Cyprus Research and Innovation Foundation" as well as by the European High-Performance Computing Joint Undertaking (JU) under grant agreement No. 101101903. P.B. acknowledges support by the project H2020- MSCAITN-2018-813942 (EuroPLEx) and the EU Horizon 2020 research and innovation programme and by the Grant DGA-FSE grant 2020-E21-17R Aragon Government and the European Union - NextGenerationEU Recovery and Resilience Program on “Astrofísica y Física de Altas Energías" CEFCA-CAPA-ITAINNOVA. The work of E.B. and J.L. has been supported by the UKRI Science and Technology Facilities Council (STFC) Research Software Engineering Fellowship EP/V052489/1. The work of E.B., J.L., and B.L. has been supported in part by the EPSRC ExCALIBUR programme ExaTEPP (project EP/X017168/1). E.B. and B.L. have been partly supported by the STFC Consolidated Grant No. ST/T000813/1. B.L. received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation program under Grant Agreement No. 813942. G.B. is funded by the Deutsche Forschungsgemeinschaft (DFG) under Grant No. 432299911 and 431842497. This work used the DiRAC Extreme Scaling service Tursa at the University of Edinburgh, managed by the Edinburgh Parallel Computing Centre on behalf of the STFC DiRAC HPC Facility (www.dirac.ac.uk). The DiRAC service at Edinburgh was funded by BEIS, UKRI and STFC capital funding and STFC operations grants. DiRAC is part of the UKRI Digital Research Infrastructure. We acknowledge the support of the Supercomputing Wales project, which is part-funded by the European Regional Development Fund (ERDF) via Welsh Government.

This package contains all data generated in preparing the publication SU(2) gauge theory with one and two adjoint fermions towards the continuum limit. It includes four classes of data: Raw data, as generated from the measurement code running on HPC, in their native formats (raw_data.zip). Metadata around the analysis of the ensembles, in YAML format (ensembles.yaml). Data obtained by analysing the above data and presented in arXiv:2408.00171, for specific ensembles, in sqlite3 format (su2.sqlite). The above data in (3), and additional data obtained by further analysing them, in CSV format (ensemble_results.csv and gammastar_results.csv). For convenience, the data in (1) above, repackaged in HDF5 format (package.h5). Each of these is documented in more detail in the file README.md. Due to their size, raw gauge configurations are not included in this package.