This project performs the chiral, continuum, infinite volume extrapolation of the g_A values computed with MDWF on HISQ lattice action, as described in Nature 558, 91–94 (2018) or arXiv:1805.12130. To perform the extrapolation, we have created a Jupyter notebook and an accompanying Python library:

• ga_workbook.ipynb: Jupyter notebook for chiral-continuum extrapolation analysis used in the final analysis
• callat_ga_lib: Library for extrapolation
  • correlator data formatting for lsqfit
  • fit function definitions
  • systematic error breakdown definitions
  • matplotlib routines The bootstrap results of our correlation function analysis are contained in the data folder along with other input parameters from the HISQ ensembles needed in the analysis:
• data: Directory of data
  • github_ga_v2.csv: Bootstrapped correlation function analysis results in csv format
    • Correlator data is made easily accessible from Jupyter with pandas and summarized in a dataframe
  • hisq_params.csv: a/w₀ and α_s for HISQ ensembles used for this work in csv format
    • HISQ parameters are displayed in pandas dataframe

In addition, the raw correlation functions computed for this project are included in correlation_functions:

• correlation_functions: Directory of data
  • callat_gA.h5 We provide a sample correlation function fitter that performs the same analysis performed for our project in sample_corr_fit. This sample fitter uses iminuit v1.1.1 (our main analysis was performed with lsqfit):
• sample_corr_fit
  • fh_fit.py: main library for performing fit
  • ga_sample_corr_fitter.ipynb: Jupyter notebook that uses the library
  • fit_params.py: an input file generated through our Bayes constrained fit to pre-condition the frequentist least squares minimization.

You can run the $g_A$ notebook in this repository by clinking the Binder badge at the top of this README. Or by clicking here

If you want to run the example correlator fitter notebook instead, you can click here.

Download Anaconda and follow installation instructions.

conda create --name pyqcd3 python=3 anaconda
source activate pyqcd3

Key libraries from gplepage GitHub.

• gvar version 8.3.2
• lsqfit version 9.1.3

Exit conda environment with

source deactivate

jupyter notebook ga_workbook.ipynb

python version: 3.6.1 |Anaconda 4.4.0 (x86_64)| (default, May 11 2017, 13:04:09)
[GCC 4.2.1 Compatible Apple LLVM 6.0 (clang-600.0.57)]
pandas version: 0.20.1
numpy  version: 1.12.1
scipy  version: 0.19.0
mpl    version: 2.0.2
lsqfit version: 9.1.3
gvar   version: 8.3.2

and

python version: 2.7.13 (default, Jul 29 2017, 11:08:07)
[GCC 4.2.1 Compatible Apple LLVM 8.1.0 (clang-802.0.42)]
pandas version: 0.20.3
numpy  version: 1.13.1
scipy  version: 0.19.0
mpl    version: 2.0.2
lsqfit version: 9.1.3
gvar   version: 8.2.2

python version: 3.6.1 |Anaconda 4.4.0 (x86_64)| (default, May 11 2017, 13:04:09)
[GCC 4.2.1 Compatible Apple LLVM 6.0 (clang-600.0.57)]
numpy  version: 1.12.1
scipy  version: 0.19.0
mpl    version: 2.0.2
iminuit version: 1.1.1

python  version: 2.7.14 (default, Sep 25 2017, 09:53:22)
[GCC 4.2.1 Compatible Apple LLVM 9.0.0 (clang-900.0.37)]
numpy   version: 1.14.2
scipy   version: 1.0.1
mpl    version: 2.0.2
iminuit version: 1.1.1

project_gA Copyright (c) 2018, The Regents of the University of California (UC), through Lawrence Berkeley National Laboratory, and the UC Berkeley campus (subject to receipt of any required approvals from the U.S. Dept. of Energy). All rights reserved.

If you have questions about your rights to use or distribute this software, please contact Berkeley Lab's Innovation & Partnerships Office at IPO@lbl.gov.

NOTICE. This Software was developed under funding from the U.S. Department of Energy and the U.S. Government consequently retains certain rights. As such, the U.S. Government has been granted for itself and others acting on its behalf a paid-up, nonexclusive, irrevocable, worldwide license in the Software to reproduce, distribute copies to the public, prepare derivative works, and perform publicly and display publicly, and to permit other to do so.