F-GAMMA: Variability Doppler factors of blazars from multiwavelength monitoring

TL;DR

This paper presents a new method to accurately estimate variability Doppler factors in blazars using multiwavelength radio data, improving precision over previous techniques.

Contribution

The study introduces a novel algorithmic approach to model and track individual flare events across multiple frequencies, enhancing the accuracy of Doppler factor estimates.

Findings

Estimated Doppler factors for 58 blazars, 20 of which are new.

Achieved an average error of 16% in Doppler factor estimation.

Provided detailed flare evolution models across 10 radio frequencies.

Abstract

Recent population studies have shown that the variability Doppler factors can adequately describe blazars as a population. We use the flux density variations found within the extensive radio multi-wavelength datasets of the F-GAMMA program, a total of 10 frequencies from 2.64 up to 142.33 GHz, in order to estimate the variability Doppler factors for 58 $\gamma$-ray bright sources, for 20 of which no variability Doppler factor has been estimated before. We employ specifically designed algorithms in order to obtain a model for each flare at each frequency. We then identify each event and track its evolution through all the available frequencies for each source. This approach allows us to distinguish significant events producing flares from stochastic variability in blazar jets. It also allows us to effectively constrain the variability brightness temperature and hence the variability Doppler factor as well as provide error estimates. Our method can produce the most accurate (16\% error on average) estimates in the literature to date.