Systematically characterizing regions of the First Fermi-LAT SNR Catalog

TL;DR

This study systematically analyzes gamma-ray emissions from all known Galactic supernova remnants using Fermi LAT data, addressing systematic uncertainties and interstellar emission modeling to characterize their properties.

Contribution

It introduces a comprehensive method for analyzing SNR gamma-ray emission and systematically accounts for modeling uncertainties, expanding understanding of SNR characteristics.

Findings

Identified 30 SNRs in the Fermi LAT catalog.

Provided upper limits for non-detected SNRs.

Compared gamma-ray and radio properties of SNRs.

Abstract

While supernova remnants (SNRs) are widely thought to be powerful cosmic-ray accelerators, indirect evidence comes from a small number of well-studied cases. Here we systematically determine the gamma-ray emission detected by the Fermi Large Area Telescope (LAT) from all known Galactic SNRs, disentangling them from the sea of cosmic-ray generated photons in the Galactic plane. Using LAT data we have characterized the 1-100 GeV emission in 279 regions containing SNRs, accounting for systematic uncertainties caused by source confusion and instrumental response. We have also developed a method to explore some systematic effects on SNR properties caused by the modeling of the interstellar emission (IEM). The IEM contributes substantially to gamma-ray emission in the regions where SNRs are located. To explore the systematics we consider different model construction methods, different model input parameters, and independently fit the model components to the gamma-ray data. We will describe this analysis method in detail. In the First Fermi LAT SNR Catalog there are 30 sources classified as SNRs, using spatial overlap with the radio position. For all the remaining regions we evaluated upper limits on SNRs' emission. In this work we will present a study of the aggregate characteristics of SNRs, such as comparisons between GeV and radio sizes as well as fluxes and spectral indexes and with TeV.