SciPost Submission Page
Consistent, multidimensional differential histogramming and summary statistics with YODA 2
by Andy Buckley, Louie Corpe, Matthew Filipovich, Christian Gutschow, Nick Rozinsky, Simon Thor, Yoran Yeh, Jamie Yellen
Submission summary
| Authors (as registered SciPost users): | Andy Buckley · Christian Gutschow |
| Submission information | |
|---|---|
| Preprint Link: | https://arxiv.org/abs/2312.15070v4 (pdf) |
| Code repository: | https://gitlab.com/hepcedar/yoda |
| Date accepted: | 2024-11-21 |
| Date submitted: | 2024-11-12 10:05 |
| Submitted by: | Gutschow, Christian |
| Submitted to: | SciPost Physics Codebases |
| Ontological classification | |
|---|---|
| Academic field: | Physics |
| Specialties: |
|
| Approaches: | Computational, Phenomenological |
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.
Author comments upon resubmission
We addressed the feedback in this resubmission (v4 on the arXiv).
List of changes
1. Replaced the SciPost style template
2. Added a short summary of timing tests
Current status:
Editorial decision:
For Journal SciPost Physics Codebases: Publish
(status: Editorial decision fixed and (if required) accepted by authors)