Speaker
Description
This study aimed to assess existing multi-wavelength analysis techniques and identify statistical mea- sures that effectively characterize temporal variability of blazars. The data used in the analysis were retrieved from VizieR consisting of three catalogs (VLBA, Effelsberg, and Fermi–LAT observations). From these, a sample of 15 common blazars was selected and their light curves were generated. Furthermore, statistical measures such as skewness and kurtosis and variability metrics including chi-square tests, variability index, modulation index, fractional index, and de-biased modulation index were calculated to quantify the variability. We performed a correlation analysis of each of the variability metrics using a package linmix. We classified the blazars into three variability categories based on our statistical analysis of their light curves and quantitative variability metrics. These cat- egories are; highly variable, moderately variable, and less variable sources. The sources; J1256-0547, J1229+0203, J1635+3808, and J2202+4216 show high variability, typical of flat-spectrum radio quasars, while the sources; J0738+1742, J1653+3945, J1104+3812, and J1221+2813 showed stable emission with minimal flux variations during the observation period of our analysis. Our study found that the Fermi-LAT γ-ray observations presented the highest variability among all three instruments, with modulation indices reaching 63.85±1.38 and fractional indices achieving 322.62±9.57, more than double the Effelsberg values. This indicates that high-energy emission processes are more variable than extended radio emission detected by single-dish telescopes. Moreover, radio variability indices exhibit stronger and more consistent linear correlations than γ-ray indices, possibly due to advanced radio variability analysis techniques and the higher statistical uncertainties inherent in γ-ray photon data.