2011/08/30 by Niklaus Berger, Berger, Niklaus
Physics and Astronomy · #Data Analysis #FOS: Physical sciences #High Energy Physics - Experiment (hep-ex) #High-Energy Particle Collisions Research #Particle physics theoretical and experimental studies #Quantum Chromodynamics and Particle Interactions #Statistics and Probability (physics.data-an) #hep-ex #physics.data-an
paper · pdf · doi:10.48550/arxiv.1108.5882
7 pages, proceedings of Hadron 2011, Munich
arxiv created 2011/08/30 · openalex publication_date 2011/08/30 · arxiv updated 2011/08/31 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Partial wave analysis is a key technique in hadron spectroscopy. The use of unbinned likelihood fits on large statistics data samples and ever more complex physics models makes this analysis technique computationally very expensive. Parallel computing techniques, in particular the use of graphics processing units, are a powerful means to speed up analyses; in the contexts of the BES III, Compass and GlueX experiments, parallel analysis frameworks have been created. They provide both fits that are faster by more than two orders of magnitude than legacy code and environments to quickly program and run an analysis. This in turn allows the physicists to focus on the many difficult open problems pertaining to partial wave analysis.