Extending the Li&Ma method to include PSF information

TL;DR

This paper extends the Li&Ma significance estimation method for Imaging Atmospheric Cherenkov Telescopes by incorporating PSF information, improving sensitivity by around 10% based on simulations.

Contribution

It introduces a likelihood ratio approach that utilizes PSF data to enhance the significance calculation for point source observations.

Findings

Inclusion of PSF increases significance by about 10%.

Sensitivity improves with background modeling and finer binning.

Method tested with Monte Carlo simulations based on real data.

Abstract

The so called Li&Ma formula is still the most frequently used method for estimating the significance of observations carried out by Imaging Atmospheric Cherenkov Telescopes. In this work a straightforward extension of the method for point sources that profits from the good imaging capabilities of current instruments is proposed. It is based on a likelihood ratio under the assumption of a well-known PSF and a smooth background. Its performance is tested with Monte Carlo simulations based on real observations and its sensitivity is compared to standard methods which do not incorporate PSF information. The gain of significance that can be attributed to the inclusion of the PSF is around of 10% and can be boosted if a background model is assumed or a finer binning is used.