# A comprehensive real-time analysis model at the LHCb experiment

## TL;DR

The paper presents an advanced real-time data analysis model for the LHCb experiment that enhances trigger efficiency and data preservation, enabling more physics insights with optimized resource use during high-energy physics experiments.

## Contribution

It introduces a reduced event model that allows selective data persistence, improving trigger rates and data mining capabilities compared to traditional full raw data storage methods.

## Key findings

- Higher trigger rates achieved with the new model
- Significant savings in computing resources
- Enhanced physics reach and data analysis flexibility

## Abstract

An evolved real-time data processing strategy is proposed for high-energy physics experiments, and its implementation at the LHCb experiment is presented. The reduced event model allows not only the signal candidate firing the trigger to be persisted, as previously available, but also an arbitrary set of other reconstructed or raw objects from the event. This allows for higher trigger rates for a given output data bandwidth, when compared to the traditional model of saving the full raw detector data for each trigger, whilst accommodating inclusive triggers and preserving data mining capabilities. The gains in physics reach and savings in computing resources already made possible by the model are discussed, along with the prospects of employing it more widely for Run 3 of the Large Hadron Collider.