ruizli / ml_hadron_structure_lqcd

Machine learning application to LQCD data

ML_hadron_structure_LQCD

Machine learning application to LQCD data

Python 3.7 version

Dependencies: numpy, pandas, matplotlib, seaborn, scikit-learn. See the instruction of each package for installation information

Wrapper of regression algorithms to apply to hadron correlators (.ipynb):

ML : Main file to read in the parameters and perform data fits, call to machine learning algorithm kernels

io : Database and I/O, read in data files and generate outputs; select fitting data

data_anal : Post-fit data analysis routines, estimate effective masses, 3pt v.s. 2pt data ratios, etc.

statistic : Estimate and visualize data statistic, e.g., autocorrelations, histogram and KDE plots, correlations, etc.

input : sample input file