Point Source Detection and Flux Determination with PGWave

TL;DR

This paper evaluates PGWave, a background-independent wavelet-based method, for detecting gamma-ray point sources and estimating their flux without relying on diffuse background models, using Monte Carlo simulations.

Contribution

It demonstrates the application of PGWave for flux estimation of gamma-ray sources independently of background modeling, which is a novel approach in Fermi-LAT data analysis.

Findings

PGWave effectively detects point sources in simulated data.

Flux estimation with PGWave shows promising accuracy.

Background-independent method reduces reliance on diffuse background models.

Abstract

One of the largest uncertainties in the Point Source (PS) studies, at Fermi-LAT energies, is the uncertainty in the diffuse background. In general there are two approaches for PS analysis: background-dependent methods, that include modeling of the diffuse background, and background-independent methods. In this work we study PGWave, which is one of the background-independent methods, based on wavelet filtering to find significant clusters of gamma rays. PGWave is already used in the Fermi-LAT catalog pipeline for finding candidate sources. We test PGWave, not only for source detection, but especially to estimate the flux without the need of a background model. We use Monte Carlo (MC) simulation to study the accuracy of PS detection and estimation of the flux. We present preliminary results of these MC studies.