Analysis Preservation and Reproducibility in Collider Physics: An ADL/CutLang Implementation of ATLAS Open Data Analyses

Abstract

Analysis Description Language (ADL) and the CutLang runtime interpreter offer an innovative and sustainable solution for describing, executing, and preserving the physics content of collider data analyses. In this solution, all physics objects and event selection criteria are expressed in a human-readable form using ADL, a domain-specific language designed for collider physics. ADL descriptions are interpreted directly at runtime by CutLang without translation into a general-purpose programming language, producing event selections that can be readily fed into statistical analysis tools. This approach addresses the long-standing challenge of analysis preservation and analysis reproducibility in high energy physics by decoupling the physics logic from experiment-specific software infrastructures. In this study, several benchmark analyses within ATLAS Open Data C++ Framework are reimplemented in ADL and executed with CutLang using data provided by ATLAS Open Data at a center-of-mass energy of 13 TeV and corresponding to an integrated luminosity of 10 fb$^{-1}$. The reimplemented analyses yield results in good agreement with the original publications, validating the ADL/CutLang workflow as a reliable alternative to traditional analysis frameworks. The study also provides a detailed assessment of CutLang's current capabilities and identifies areas for further development, offering a roadmap toward broader adoption of ADL-based analysis preservation in the LHC community.