Combining Triggers in HEP Data Analysis

TL;DR

This paper presents methods for calculating offline corrections in high-energy physics data analysis, addressing inefficiencies and statistical losses caused by complex trigger systems, especially when combining multiple triggers.

Contribution

It introduces new methods for offline correction calculations and evaluates their statistical performance in the context of multi-trigger data samples.

Findings

Methods effectively correct for trigger inefficiencies.

Statistical performance of correction methods is thoroughly studied.

Implications for trigger system design are discussed.

Abstract

Modern high-energy physics experiments collect data using dedicated complex multi-level trigger systems which perform an online selection of potentially interesting events. In general, this selection suffers from inefficiencies. A further loss of statistics occurs when the rate of accepted events is artificially scaled down in order to meet bandwidth constraints. An offline analysis of the recorded data must correct for the resulting losses in order to determine the original statistics of the analysed data sample. This is particularly challenging when data samples recorded by several triggers are combined. In this paper we present methods for the calculation of the offline corrections and study their statistical performance. Implications on building and operating trigger systems are discussed.