Robust Independent Validation of Experiment and Theory: Rivet version 4 release note

TL;DR

Rivet version 4 introduces significant improvements in data handling, analysis tools, and machine-learning integration, enhancing the preservation and reproducibility of collider-physics measurements.

Contribution

This release of Rivet provides a more coherent data model, cleans up legacy tools, and adds support for machine-learning models and high-performance computing serialization.

Findings

Enhanced histogram and data object models

Updated analysis routines for backward compatibility

New systems for machine-learning model integration

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.