Democratizing LHC Data Analysis with ADL/CutLang
Sezen Sekmen, Gokhan Unel, Harrison B. Prosper, Aytul Adiguzel, Burak, Sen

TL;DR
The paper introduces ADL, a human-readable language for LHC data analysis, and CutLang, a runtime interpreter, to make high-energy physics data analysis more accessible for researchers, students, and the public.
Contribution
It presents ADL and CutLang as novel tools that simplify LHC data analysis by eliminating complex programming requirements and promoting broader accessibility.
Findings
ADL enables analysis description in plain English.
CutLang allows execution of analyses without programming.
Tools have been used in educational settings for students and teachers.
Abstract
Data analysis at the LHC has a very steep learning curve, which erects a formidable barrier between data and anyone who wishes to analyze data, either to study an idea or to simply understand how data analysis is performed. To make analysis more accessible, we designed the so-called Analysis Description Language (ADL), a domain specific language capable of describing the contents of an LHC analysis in a standard and unambiguous way, independent of any computing frameworks. ADL has an English-like highly human-readable syntax and directly employs concepts relevant to HEP. Therefore it eliminates the need to learn complex analysis frameworks written based on general purpose languages such as C++ or Python, and shifts the focus directly to physics. Analyses written in ADL can be run on data using a runtime interpreter called CutLang, without the necessity of programming. ADL and CutLang…
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Taxonomy
TopicsDistributed and Parallel Computing Systems · Scientific Computing and Data Management · Computational Physics and Python Applications
