Confidence Level Computation for Combining Searches with Small Statistics

TL;DR

This paper presents an efficient method to compute approximate confidence levels for small-statistics particle searches, enabling the combination of multiple independent searches and incorporating systematic uncertainties.

Contribution

It introduces a new procedure for calculating confidence levels in low-statistics scenarios, facilitating the combination of multiple searches with systematic uncertainty considerations.

Findings

Efficient computation of confidence levels for small signals.

Ability to combine multiple independent searches.

Inclusion of systematic uncertainties in confidence calculations.

Abstract

This article describes an efficient procedure for computing approximate confidence levels for searches for new particles where the expected signal and background levels are small enough to require the use of Poisson statistics. The results of many independent searches for the same particle may be combined easily, regardless of the discriminating variables which may be measured for the candidate events. The effects of systematic uncertainty in the signal and background models are incorporated in the confidence levels. The procedure described allows efficient computation of expected confidence levels.