Publication Date
2026
Document Type
Dissertation/Thesis
First Advisor
de la Torre Perez, Hector
Degree Name
M.S. (Master of Science)
Legacy Department
Department of Physics
Abstract
RNTuple is the new data storage format set to replace TTree at the start of the High-Luminosity LHC. An investigation was conducted to evaluate how analysis workflows for ATLAS researchers will change with RNTuple, using reading speed, writing speed, disk space, and memory consumption as metrics. In this study, all metrics were measured using converted RNTuple inputs from ATLAS Open Data, compared to their TTree equivalents. Additionally, RNTuples produced with the LZ4 compression algorithm were generated and compared with those produced using ZSTD. Finally, two new versions of the Analysis Grand Challenge (AGC) using ATLAS Open Data were completed for TTree and RNTuple inputs with RDataFrame in Python. This constitutes the first implementation of an end-to-end analysis completed using RNTuple.
Recommended Citation
Rodriguez, Fatima Ariana, "RNTuple for ATLAS Analysis Workflow" (2026). Graduate Research Theses & Dissertations. 8238.
https://huskiecommons.lib.niu.edu/allgraduate-thesesdissertations/8238
Extent
67 pages
Language
en
Publisher
Northern Illinois University
Rights Statement
In Copyright
Rights Statement 2
NIU theses are protected by copyright. They may be viewed from Huskie Commons for any purpose, but reproduction or distribution in any format is prohibited without the written permission of the authors.
Media Type
Text
