A Bayesian Approach to Modelling Multi-Messenger Emission from Blazars using Lepto-Hadronic Kinetic Equations

TL;DR

This paper develops a Bayesian lepto-hadronic kinetic model for blazar emissions, capable of fitting multi-messenger data and revealing parameter correlations, with implications for understanding neutrino production in sources like TXS 0506+056.

Contribution

It introduces a comprehensive Bayesian framework combining kinetic emission modeling with MCMC sampling to analyze multi-messenger data from blazars.

Findings

Best-fit parameters for the model variants.

Strong correlation between proton-electron ratio and neutrino flux.

Reproducing TXS 0506+056 neutrino flux requires extreme proton-electron ratios.

Abstract

Blazar TXS 0506+056 is the main candidate for a coincident neutrino and gamma-ray flare event. In this paper, we present a detailed kinetic lepto-hadronic emission model capable of producing a photon and neutrino spectrum given a set of parameters. Our model includes a range of large-scale geometries and both dynamical and steady-state injection models for electrons and protons. We link this model with a Markov Chain Monte Carlo sampler to obtain a powerful statistical tool that allows us to both fit the Spectral Energy Distribution and study the probability density functions and correlations of the parameters. Assuming a fiducial neutrino flux, we demonstrate how multi-messenger observations can be modelled jointly in a Bayesian framework. We find the best parameters for each of the variants of the model tested and report on their cross-correlations. Additionally, we confirm that reproducing the neutrino flux of TXS 0506+056 requires an extreme proton to electron ratio either in the local acceleration process or from external injection.