HEP-EXSENov 3, 2015

ARTUS - A Framework for Event-based Data Analysis in High Energy Physics

arXiv:1511.00852v13 citations
Originality Synthesis-oriented
AI Analysis

This addresses data processing challenges for researchers in high energy physics, but it is incremental as it builds on existing experiences and similar applications.

The paper introduces ARTUS, an event-based data-processing framework for high energy physics experiments, designed to handle large-scale data analysis in collaborative settings, and it is reported to be well-tested and successfully used by multiple analysis groups.

ARTUS is an event-based data-processing framework for high energy physics experiments. It is designed for large-scale data analysis in a collaborative environment. The architecture design choices take into account typical challenges and are based on experiences with similar applications. The structure of the framework and its advantages are described. An example use case and performance measurements are presented. The framework is well-tested and successfully used by several analysis groups.

Code Implementations1 repo
Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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