Photons to axion-like particles conversion in Active Galactic Nuclei

TL;DR

This paper evaluates the photon to axion-like particle conversion probability in blazars, revealing unpredictable results for BL Lacs but clear predictions for FSRQs, impacting future high-energy photon detection efforts.

Contribution

It provides the first detailed estimation of ALP-photon conversion probabilities in different classes of blazars based on current knowledge.

Findings

Conversion probability in BL Lacs is highly uncertain due to jet magnetic field variability.

Clear predictions are made for FSRQs, enabling better interpretation of future observations.

Results are significant for upcoming gamma-ray detectors like CTA and HAWK.

Abstract

The idea that photons can convert into axion-like particles (ALPs) $\gamma \to a$ in or around an AGN and reconvert back into photons $a \to \gamma$ in the Milky Way magnetic field has been put forward in 2008 and has recently attracted growing interest. Yet, so far nobody has estimated the conversion probability $\gamma \to a$ as carefully as allowed by present-day knowledge. Our aim is to fill this gap. We first remark that AGN that can be detected above 100 GeV are blazars, namely AGN with jets, with one of them pointing towards us. Moreover, blazars fall into two well defined classes: BL Lac objects (BL Lacs) and Flat Spectrum Radio Quasars (FSRQs), with drastically different properties. In this Letter we report a preliminary evaluation of the $\gamma \to a$ conversion probability inside these two classes of blazars. Our findings are surprising. Indeed, while in the case of BL Lacs the conversion probability turns out to be totally unpredictable due to the strong dependence on the values of the somewhat uncertain position of the emission region along the jet and strength of the magnetic field therein, for FSRQs we are able to make a clear-cut prediction. Our results are of paramount importance in view of the planned very-high-energy photon detectors like the CTA, HAWK, GAMMA-400 and HISCORE.