Speaker
Description
Blazars show variability across the entire electromagnetic spectrum and over a wide range of timescales. In some cases, characteristic emission patterns have been observed, such as the multi-year modulation detected in PG 1553+113. Quasi-periodic oscillations (QPOs) can arise from various astrophysical mechanisms, including jet precession, accretion disk instabilities, and binary supermassive black holes. While the latter is a particularly compelling possibility, potentially linking galaxy mergers to jet physics, the other scenarios also provide valuable information about the physical processes governing blazar variability, which remain poorly understood.
In this work, we present the first application of Singular Spectrum Analysis (SSA) to a large sample of Fermi Large Area Telescope (LAT) blazars in a systematic search for QPO candidates. SSA effectively isolates periodicity by decomposing the signal into trend, oscillatory, and noise components, providing a robust approach for characterizing variability. In addition, we provide forecasting models based on SSA to predict the long-term behavior of blazars. Our analysis identifies 46 blazar candidates for QPOs, including 25 new candidates not previously reported. This constitutes the largest sample of blazar QPO candidates to date, significantly surpassing previous studies and enabling the first steps toward population-level statistical analyses of these phenomena. By identifying promising candidates and highlighting their potential significance within the context of blazar variability, this study provides a foundation for future investigations into their physical origins.
| Collaboration(s) | Fermi-LAT Collaboration |
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