Codebase release 2.0 for YODA

Histogramming is often taken for granted, but the power and compactness of partially aggregated, multidimensional summary statistics, and their fundamental connection to differential and integral calculus make them formidable statistical objects, especially when very large data volumes are involved. But expressing these concepts robustly and efficiently in high-dimensional parameter spaces and for large data samples is a highly non-trivial challenge – doubly so if the resulting library is to remain usable by scientists as opposed to software engineers. In this paper we summarise the core principles required for consistent generalised histogramming, and use them to motivate the design principles and implementation mechanics of the re-engineered YODA histogramming library, a key component of physics data–model comparison and statistical interpretation in collider physics.

Authors

Institutions

Publication Details

Journal
SciPost Physics Codebases
Published
2025-01-16
DOI
https://doi.org/10.21468/scipostphyscodeb.45-r2.0
Citations
2
Primary Topic
Software System Performance and Reliability
Type
article
Field-Weighted Citation Impact
2.97

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Codebase release 2.0 for YODA

Simon Thor, L. D. Corpe, Matthew J. Filipovich, Y. Yeh et al.
2 citations
SciPost Physics Codebases
Software System Performance and Reliability
2.97
article

Codebase release 2.0 for YODA

Simon Thor, L. D. Corpe, Matthew J. Filipovich, Y. Yeh, Jamie Yellen, Nick Rozinsky, A. G. Buckley, Christian Gutschow
article en
2 citations

Abstract

Histogramming is often taken for granted, but the power and compactness of partially aggregated, multidimensional summary statistics, and their fundamental connection to differential and integral calculus make them formidable statistical objects, especially when very large data volumes are involved. But expressing these concepts robustly and efficiently in high-dimensional parameter spaces and for large data samples is a highly non-trivial challenge – doubly so if the resulting library is to remain usable by scientists as opposed to software engineers. In this paper we summarise the core principles required for consistent generalised histogramming, and use them to motivate the design principles and implementation mechanics of the re-engineered YODA histogramming library, a key component of physics data–model comparison and statistical interpretation in collider physics.

SciPost Physics Codebases
Centre National de la Recherche Scientifique (FR), Université Clermont Auvergne (FR), University of Oxford (GB), Institut National de Physique Nucléaire et de Physique des Particules (FR), University College London (GB), University of Glasgow (GB), KTH Royal Institute of Technology (SE)
University College London, Science and Technology Facilities Council, Horizon 2020
Openalex Percentile: Top 11%
Software System Performance and Reliability
2.97
DOIOpen Access PDFOpenAlex
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.