A Novel Method for Detecting Extended Sources with VERITAS

TL;DR

This paper introduces a new 3D maximum likelihood method for detecting highly extended gamma-ray sources with VERITAS, overcoming limitations of traditional background estimation techniques.

Contribution

The paper develops a novel 3D maximum likelihood analysis incorporating instrument response functions and a gamma-hadron discriminant to improve detection of large extended sources.

Findings

Enhanced sensitivity to extended sources demonstrated

Systematic studies show potential for revealing large gamma-ray sources

Method addresses limitations of traditional background models

Abstract

The most commonly used techniques for estimating the background contribution in IACT data analysis are the ring background model and the reflected region methods. However, these two techniques are poorly suited for analyses of sources with extensions comparable to the detector's field of view (greater than $\sim$1$^{\circ}$). Nearby pulsar wind nebulae, supernova remnants interacting with molecular clouds, and dark matter signatures from galaxy clusters are just a few potentially highly extended source classes. A three dimensional maximum likelihood analysis is in development that seeks to resolve this issue for data from the VERITAS telescopes. The technique incorporates relevant instrument response functions to model the distribution of detected gamma-ray like events in two spatial dimensions. Additionally, we incorporate a third dimension based on a gamma-hadron discriminating parameter. The inclusion of this third dimension significantly improves the sensitivity of the technique to highly extended sources. We present this promising technique as well as systematic studies demonstrating its potential for revealing sources of large extent in VERITAS data.