Saved in:
| Main Authors: | , , |
|---|---|
| Format: | Preprint |
| Published: |
2026
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2605.18955 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Table of Contents:
- We present an automated pipeline for the detection of EVPA rotations in blazars, integrating correction of the 180$^\circ$ ambiguity, Bayesian Blocks segmentation, and statistical validation. Applied to RoboPol monitoring data, the method identified 48 rotations across 25 sources, including multiple events in RBPLJ2232+1143, RBPLJ1751+0939, RBPLJ1800+7828, and RBPLJ2253+1608. The rotations span amplitudes from 90.8$^\circ$ to 359.7$^\circ$, durations between 7.0 and 111.3 days, and rotation rates averaging 5.0$^\circ$/day. Comparison with previous catalogs reveals systematic differences: Bayesian Blocks rotations are on average $\sim$10\% larger in amplitude, about twice as long in duration, and roughly two-thirds slower in angular velocity, reflecting systematic biases between adaptive binning and manual segmentation. In addition, we report 27 previously unreported rotations, including 11 from the final 2016--2017 season. A correlation analysis with contemporaneous Fermi--LAT $γ$-ray light curves shows that longer rotations tend to coincide with enhanced $γ$-ray activity, while rotation amplitude alone is not predictive of $γ$-ray brightness. Our pipeline minimizes subjective biases, expands the list of known EVPA rotations, and provides a reproducible framework for future multiwavelength studies of blazar jet dynamics and particle acceleration.