# Bimodal radio variability in OVRO-40m-monitored blazars

## TL;DR

This paper introduces a new maximum likelihood method to analyze bimodal radio variability in blazars, distinguishing quiescent and flaring states to better understand their behavior and link to gamma-ray emission.

## Contribution

The novel approach models blazar flux-density as 'off' and 'on' states, enabling detailed analysis of variability characteristics and their relation to gamma-ray detection.

## Key findings

- BL Lacs are more variable with larger outbursts than FSRQs.
- Gamma-ray detected blazars show different variability properties from non-detected ones.
- Flaring ratios, duty cycles, and modulation indices distributions are fitted for population studies.

## Abstract

Blazars are known to show periods of quiescence followed by outbursts visible throughout the electromagnetic spectrum. We present a novel maximum likelihood approach to capture this bimodal behavior by examining blazar radio variability in the flux-density domain. We separate quiescent and flaring components of a source's light curve by modeling its flux-density distribution as a series of "off" and "on" states. Our modeling allows us to extract information regarding the flaring ratio, duty cycle, and the modulation index in the "off"-state, in the "on"-state, as well as throughout the monitoring period of each blazar. We apply our method to a flux-density-limited subsample from the Owens Valley Radio observatory's 15 GHz blazar monitoring program, and explore differences in the variability characteristics between BL Lacs and FSRQs as well as between $\gamma$-ray detected and non-detected sources. We find that: (1) BL Lacs are more variable and have relatively larger outbursts than the FSRQs, (2) unclassified blazar candidates in our sample show similar variability characteristics as the FSRQs, and (3) $\gamma$-ray detected differ from the $\gamma$-ray non-detected sources in all their variability properties, suggesting a link between the production of $\gamma$-rays and the mechanism responsible for the radio variability. Finally, we fit distributions for blazar flaring ratios, duty cycles, and on- and off- modulation indices that can be used in population studies of variability-dependent blazar properties.