Streamlined data analysis in Python

TL;DR

The paper introduces AnalysisToolbox, a Python library that enhances lattice QCD data analysis with specialized modules, parallelization, and JIT compilation, addressing existing library gaps and performance issues.

Contribution

It presents a new Python collection tailored for lattice QCD analysis, integrating advanced routines and performance optimizations not available in standard libraries.

Findings

Includes jackknife and bootstrap routines

Provides modules for gauge configuration handling

Features parallelized and JIT-compiled functions

Abstract

Python is a particularly appealing language to carry out data analysis, owing in part to its user-friendly character as well as its access to well maintained and powerful libraries like NumPy and SciPy. Still, for the purpose of analyzing data in a lattice QCD context, some desirable functionality is missing from these libraries. Moreover, scripting languages tend to be slower than compiled ones. To help address these points we present the AnalysisToolbox, a collection of Python modules to facilitate lattice QCD data analysis. Some highlighted features include general-purpose jackknife and bootstrap routines; modules for reading in and storing gauge configurations; a module to carry out hadron resonance gas model calculations; and convenience wrappers for SciPy integration, curve fitting, and splines. These features are sped up behind the scenes using parallelization and just-in-time compilation.