The gamma-ray emission from Radio Galaxies and their contribution to the Isotropic Gamma-Ray Background

TL;DR

This paper addresses the RG contribution to the IGRB by leveraging a gamma-ray–radio core luminosity correlation to translate the well-measured radio core luminosity function into a gamma-ray luminosity function. Using two RG samples (26 LAT-detected and 210 subthreshold RGs) and stacking analyses, the authors robustly constrain the L_gamma–L_{C,5GHz} relation and propagate its uncertainty to estimate the RG GLF and IGRB contribution, accounting for EBL attenuation. Their main finding is that RGs contribute about $\sim 21\%$ of the IGRB, with a wide but informative uncertainty range, and that including subthreshold RGs reduces previous overestimates that neglected the faint population. This work sharpens the RGs’ role relative to other contributors (e.g., blazars, star-forming galaxies) and demonstrates the value of deep population studies in gamma-ray background synthesis.

Abstract

We evaluate the contribution to the Isotropic Gamma-Ray Background (IGRB) coming from Radio Galaxies (RGs), the subclass of radio-loud Active Galactic Nuclei (AGN) with the highest misalignment from the line of sight (l.o.s.). Since only a small number of RGs are detected in gamma rays compared to the largest known radio population, the correlation between radio and gamma-ray emission serves as a crucial tool to characterize the gamma-ray properties of these sources. We analyse the population of RGs using two samples. The first sample contains 26 sources individually detected by the Large Area Telescope (LAT) on board the Fermi Gamma-ray Space Telescope at gamma rays. The second sample contains 210 RGs for which the gamma-ray emission is not significantly detected by the LAT. We use a stacking analysis to characterize the average properties of the gamma-ray emission of the two samples, separately at first and then combined. We then evaluate the correlation between their gamma-ray emission and the emission from their radio core at 5 GHz, and we use it to determine their contribution to the IGRB. Due to the limited number of RGs detected at the gamma-rays, information on the gamma-ray luminosity function is limited. The correlation between the gamma-ray emission and the emission of the radio core allows us to characterize it starting from the luminosity function of the radio cores, which is modeled with greater accuracy due to the larger number of sources detected at these frequencies. We find that the diffuse emission as extrapolated from the properties of the subthreshold RGs is lower than the one inferred from detected RGs, showing that the contribution of the population of RGs to the IGRB is lower than the previous estimates and it is around the 30% level of the IGRB intensity.

Figures (6)

• Figure 1: 5 GHz core luminosity versus redshift for the sample of detected RGs at $\gamma$-rays (green circles) and for the sample of subthreshold RGs (gray circles) presented in Sect. \ref{['sec:data_sample']}.
• Figure 2: Stacked TS profile for the subthreshold RG sample. The coordinates of the black cross indicate the best estimates for the average integrated flux and photon index of the population. The green contours are the uncertainties at the $1\sigma$, $2\sigma$, and $3\sigma$ levels respectively.
• Figure 3: Correlation between the 1 -- 800 GeV $\gamma$-ray luminosity and the luminosity of the radio core at 5 GHz for the RGs analysed in this paper. The green points are the individually detected RGs. The values for the $\gamma$-ray luminosity are obtained through their individual TS profiles obtained in this analysis, while the core luminosities come from Khatiya+23. The green band is the $L_\gamma - L_{C,5\textrm{GHz}}$ correlation for the detected RGs with its $1\sigma$ uncertainty. The gray band is the $1\sigma$ band on the $L_\gamma - L_{C,5\textrm{GHz}}$ correlation derived from the analysis of the subthreshold sample. The red band represents the $L_\gamma - L_{C,5\textrm{GHz}}$ correlation from the combination of the detected and undetected samples, with its $1\sigma$ uncertainty. We also include the results from DiMauro+2014 and Stecker+2019, the dashed blue and yellow lines, respectively, with their $1\sigma$ uncertainties.
• Figure 4: Core dominance (see eq. \ref{['eq:core_dom']}) versus redshift for the sample of detected RGs at $\gamma$-rays (green circles) and for the sample of subthreshold RGs (gray circles). The subsample of undetected RGs chosen to have R $>0.15$is highlighted with red contours. The green, gray and red lines represent the average R of the detected RGs, the undetected RGs, and the subsample of undetected RGs, respectively.
• Figure 5: Integrated $\gamma$-ray emission from RGs. The green band is the predicted contribution from the detected RG population, with its $1\sigma$ uncertainty. The gray band is the predicted contribution from the subthreshold RG population with its $1\sigma$ uncertainty. The red band is the contribution obtained combining the results of both samples of RGs, with its $1\sigma$ uncertainty. The dashed blue, orange and purple lines are the contributions from DiMauro+2014, Hooper+2016, and Stecker+2019, respectively. The black dot-dashed line is the contribution from Fukazawa+2022. The black datapoints are the LAT evaluation of the IGRB Ackermann2015