Twelve flavor SU(3) gradient flow data for the continuous beta-function

Data:

Raw gradient flow data for calculating the continuous beta-function of the massless SU(3) gauge-fermion system with twelve fermions in the fundamental representation of SU(3). Each file corresponds to a particular ensemble, with volume "lxlx" and bare gauge coupling "by": "lxlxby.txt". Bare gauge couplings are "920: 9.2", "940: 9.4", "960: 9.6", "980: 9.8", "100: 10.0", "102: 10.2", "104: 10.4", "110: 11.0", "114: 11.4", "120: 12.0", "128: 12.8", "136: 13.6", "146: 14.6". In each file, there is data for the Yang-Mills energy density E(t) calculated from the Wilson and clover discretization. The columns of each file are laid out as follows.

meas #        flow_time          E_Wilson          E_clover

n                    t/a^2                   E(t)                     E(t)

"meas #" is an identifier for the gradient flow measurement on a particular configuration.

Code:

This data was generated using a combination of a modified MILC library and Curtis Taylor Peterson's fork of the Quantum EXpressions (QEX) library. Fits that we performed using this dataset utilize the SwissFit and GVar Python libraries. Links are provided down below.

Modified MILC: https://github.com/daschaich/KS_nHYP_FA

Quantum EXpressions fork: https://github.com/ctpeterson/qex_staghmc

SwissFit: https://github.com/ctpeterson/SwissFit

GVar: https://github.com/gplepage/gvar

Statement about use (PLEASE READ):

If you use this data, please cite arXiv:2402.18038 and acknowledge both USQCD and CU Boulder resources by adding the following statement to your acknowledgements. 

"The data used in this work was generated using the computing and long-term storage facilities of the USQCD Collaboration, which are funded by the Office of Science of the U.S. Department of Energy, and the Alpine high performance computing resource at the University of Colorado Boulder. Alpine is jointly funded by the University of Colorado Boulder, the University of Colorado Anschutz, and Colorado State University."

ACKNOWLEDGEMENTS:

Both authors acknowledge support by DOE Grant No. DE-SC0010005. This material is based upon work supported by the National Science Foundation Graduate Research Fellowship Program under Grant No. DGE 2040434. The research reported in this work made use of computing and long-term storage facilities of the USQCD Collaboration, which are funded by the Office of Science of the U.S. Department of Energy.  This work utilized the Alpine high performance computing resource at the University of Colorado Boulder. Alpine is jointly funded by the University of Colorado Boulder, the University of Colorado Anschutz, and Colorado State University. We thank James Osborn and Xiaoyong Jin for writing Quantum EXpressions (QEX) and helping us develop our QEX-based hybrid Monte Carlo and gradient flow codes.