Blazars are among the most energetic and luminous sources in the Universe. They are a subclass of active galactic nuclei (AGN) that exhibit extreme variability and emission across the entire electromagnetic spectrum, from radio waves to gamma rays. Powered by supermassive black holes at the centers of galaxies, blazars launch relativistic jets oriented close to our line of sight, making them prime targets for studying jet physics, particle acceleration, and high-energy astrophysical processes.
Current multi-wavelength (MWL) studies of blazars rely heavily on coordinated observations across different instruments and energy bands. These efforts have revealed complex variability patterns, meaning rapid and often unpredictable changes in flux and spectral properties observed across different timescales and across multiple wavelengths. However, interpreting these variations remains challenging due to the diversity of blazar types and behaviors, as well as the complexity of the data.
This internship will support the exploration of how unsupervised machine learning techniques can be used to characterize MWL data from blazars. By applying clustering and/or dimensionality reduction methods, the project aims to uncover underlying patterns in the data that may reveal new insights into blazar physics. This approach offers a novel pathway to characterize blazar behavior without relying on prior assumptions, potentially leading to a more nuanced understanding of their emission mechanisms and variability.
In details, the student will:
- Become familiar with AGN and blazar physics
- Get accustomed to MWL data (lightcurves) of blazars
- Apply dimensionality reduction/clustering methods on MWL lightcurves of blazars
- Analyze and interpret the results of unsupervised learning methods in the context of blazar variability
This internship is open to M1 students following astrophysics programmes/lectures. Prior knowledge from data science and machine learning courses (e.g. “Modélisation et Machine-Learning” at Université Paris Cité) is beneficial. English will be used as the main language for communication during the internship.