Iliana Cortes (Mexico)
Iliana.cortes @ h-its.org
Galaxies that host in their centre a Supermassive Black Hole (SMBH) with a mass larger than 10^8 solar masses, and a high accretion rate are known as Active Galactic Nuclei (AGNs). AGNs are variable sources and their variability carries the footprint of the underlying latent activity of the central engine. The continuum emission from the accretion disk (AD) and the emission lines from the Broad Line Region (BLR) dominate the optical spectrum of AGNs. AD and BLR exhibit delayed emissions that depend on their physical properties. In contrast to the abundance of multi-band photometry from surveys, such as SDSS, spectroscopic observations of AGNs over long periods are not common, for being too time consuming. We aim to implement Machine Learning techniques to provide a robust framework for reconstructing detailed spectral information and variability characteristics from photometry alone.
tbd
Supervisor: Kai Polsterer (HITS)
