Simulations of Stochastic Long-Term Variability in Leptonic Models for External-Compton and Synchrotron Self-Compton Dominated Blazars

TL;DR

This study uses numerical simulations with stochastic parameter variations to analyze multi-wavelength variability in blazars, revealing how different emission mechanisms influence variability patterns and correlations.

Contribution

It introduces a Monte Carlo-based stochastic modeling approach to simulate and analyze blazar variability across multiple wavelengths, distinguishing between different blazar types.

Findings

Power spectral densities follow a -2 slope for stochastic variations.

Distinct multi-wavelength cross-correlation patterns differentiate blazar types.

Variability is closely linked to underlying stochastic parameter changes.

Abstract

In this work we investigate the nature of multi-wavelength variability of blazars from a purely numerical approach. We use a time-dependent one-zone leptonic blazar emission model to simulate multi-wavelength variability by introducing stochastic parameter variations in the emission region. These stochastic parameter variations are generated by Monte Carlo methods and have a characteristic power law index of $\alpha=-2$ in their power spectral densities. We include representative blazar test cases for a flat spectrum radio quasar and a high synchrotron peaked BL Lacertae object for which the high energy component of the Spectral Energy Distribution is dominated by external Compton and synchrotron self-Compton emission, respectively. The simulated variability is analyzed in order to characterise the distinctions between the two blazar cases and the physical parameters driving the variability. We show that the variability's power spectrum is closely related to underlying stochastic parameter variations for both cases. Distinct differences between the different progenitor variations are present in the multi-wavelength cross-correlation functions.