A Gauge Model of Data Selection, Acquisition and Analysis for LHC

TL;DR

This paper introduces a gauge-inspired model for data selection, acquisition, and analysis in complex high-energy physics experiments, enabling independent yet coordinated sub-experiments with shared resources.

Contribution

It proposes a novel gauge model framework that allows physics groups to optimize configurations on an event-by-event basis within a multi-purpose experiment.

Findings

Model facilitates independent sub-experiments sharing resources

Enables event-by-event optimization of detector configurations

Provides a unified scheme for data handling in complex experiments

Abstract

A novel model of the data selection, acquisition and analysis for a multi-purpose and multi-component high-energy-physics experiment is presented. Its departure point is the freedom and the responsibility given to the different physics groups of the experiment to impose, on the {\it event-by-event basis}, their physics-goal-optimal configurations of (i) the sub-detectors, (ii) the trigger and data acquisition system, and (iii) the reconstruction and analysis framework. Its target is to develop, in a close analogy to the construction of the gauge models in particle physics, the overall data handling scheme, in which a multi-purpose experiment becomes an association of coexistent, yet largely independent, physics-group-based sub-experiments sharing common hardware maintenance, data-acquisition, and data reconstruction resources.