Computation of confidence intervals for Poisson processes

TL;DR

This paper introduces a fast numerical algorithm for computing Feldman-Cousins confidence intervals for Poisson processes, effectively handling large background events and the singularities due to discreteness.

Contribution

The paper presents a novel algorithm that efficiently computes confidence intervals for Poisson processes, addressing challenges with large background counts and variable singularities.

Findings

Algorithm achieves faster computation times

Handles large background event counts effectively

Accurately manages singularities from discreteness

Abstract

We present an algorithm which allows a fast numerical computation of Feldman-Cousins confidence intervals for Poisson processes, even when the number of background events is relatively large. This algorithm incorporates an appropriate treatment of the singularities that arise as a consequence of the discreteness of the variable.