A stacking method to study the gamma-ray emission of source samples based on the co-adding of Fermi LAT count maps

TL;DR

This paper introduces a stacking method using co-added Fermi LAT gamma-ray count maps to detect faint sources by increasing the combined detection significance, applicable to various astrophysical objects.

Contribution

The paper presents a novel stacking technique that co-adds gamma-ray count maps to enhance detection of faint sources, accounting for background and point sources with a maximum likelihood analysis.

Findings

Stacking increases detection significance for faint gamma-ray sources.

Method successfully applied to simulated and real Fermi LAT data.

Potential to detect gamma-ray emission from galaxy clusters.

Abstract

We present a stacking method that makes use of co-added maps of gamma-ray counts produced from data taken with the Fermi Large Area Telescope. Sources with low integrated gamma-ray fluxes that are not detected individually may become detectable when their corresponding count maps are added. The combined data set is analyzed with a maximum likelihood method taking into account the contribution from point-like and diffuse background sources. For both simulated and real data, detection significance and integrated gamma-ray flux are investigated for different numbers of stacked sources using the public Fermi Science Tools for analysis and data preparation. The co-adding is done such that potential source signals add constructively, in contrast to the signals from background sources, which allows the stacked data to be described with simply structured models. We show, for different scenarios, that the stacking method can be used to increase the cumulative significance of a sample of sources and to characterize the corresponding gamma-ray emission. The method can, for instance, help to search for gamma-ray emission from galaxy clusters.