Codebase release 4.0 for RIVET

The Rivet toolkit is the primary mechanism for phenomenological preservation of collider-physics measurements, containing both a computational core and API for analysis implementation, and a large collection of more than a thousand preserved analyses. In this note we summarise the main changes in the new Rivet 4 major release series. These include a major generalisation and more semantically coherent model for histograms and related data objects, a thorough clean-up of inelegant and legacy observable-computation tools, and new systems for extended analysis-data, incorporation of preserved machine-learning models, and serialization for high-performance computing applications. Where these changes introduce backward-incompatible interface changes, existing analyses have been updated and indications are given on how to update new analysis routines and workflows.

Authors

Institutions

Publication Details

Journal
SciPost Physics Codebases
Published
2024-11-04
DOI
https://doi.org/10.21468/scipostphyscodeb.36-r4.0
Citations
3
Primary Topic
Software Testing and Debugging Techniques
Type
article
Field-Weighted Citation Impact
1.46

Funders

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

Codebase release 4.0 for RIVET

T. Procter, Christian Bierlich, Y. Yeh, Leif Lönnblad et al.
3 citations
SciPost Physics Codebases
Software Testing and Debugging Techniques
1.46
article

Codebase release 4.0 for RIVET

T. Procter, Christian Bierlich, Y. Yeh, Leif Lönnblad, A. G. Buckley, Jonathan Mark Butterworth, Christian Gutschow, Peter Richardson
article en
3 citations

Abstract

The Rivet toolkit is the primary mechanism for phenomenological preservation of collider-physics measurements, containing both a computational core and API for analysis implementation, and a large collection of more than a thousand preserved analyses. In this note we summarise the main changes in the new Rivet 4 major release series. These include a major generalisation and more semantically coherent model for histograms and related data objects, a thorough clean-up of inelegant and legacy observable-computation tools, and new systems for extended analysis-data, incorporation of preserved machine-learning models, and serialization for high-performance computing applications. Where these changes introduce backward-incompatible interface changes, existing analyses have been updated and indications are given on how to update new analysis routines and workflows.

SciPost Physics Codebases
Lund University (SE), Durham University (GB), University College London (GB), University of Glasgow (GB)
University College London, Science and Technology Facilities Council, Horizon 2020
Industry, innovation and infrastructure
Openalex Percentile: Top 15%
Software Testing and Debugging Techniques
1.46
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.