Speaker
Description
Blazars are highly variable sources that emit light across the entire electromagnetic spectrum. The period of their variability can range from intra-night minute/hour long timescales, day/week timescales, and have even been known to vary over the course of years. This makes high cadence observations key to understanding the processes producing the observed radiation. This is no more apparent than with polarimetric data. Large gaps between subsequent data points allow for multiwavelength flares to go unobserved, as well as linear polarisation flares and position angle rotations. Data taken in the middle or at the end of an event does not provide the timescale or magnitude of the rapidly changing variability.
I will present data from the long-term photo-polarimetric blazar monitoring program using the RINGO3 and MOPTOP polarimeters on the Liverpool Telescope. We have conducted correlation analysis between the different photo-polarimetric components and Fermi data, and I will discuss the issues presented by interrupted monitoring and poorly sampled data over various timescales. I will also present the application of machine learning techniques for interpreting activity phases in blazars giving us the potential to understand the source behaviour during periods where they cannot be observed with ground-based optical telescopes.