Speaker
Description
Observations and models indicate that the fraction of active galaxies
in the local Universe is about 10% . As most large galaxies host a
supermassive black hole (SMBH), this can be interpreted as a duty
cycle, where 10% of galaxies are active at any given time. Estimating
this activation rate is important to constrain central black hole
feeding mechanisms in galaxy evolution models. Black hole ignition
events, which involve a galaxy transitioning from a quiescent or
star-forming state to a an AGN are, however, exceptionally challenging
to detect. For our work, we took advantage of the very large public
photometric monitorings that are currently ongoing (ZTF) together with
machine-learning algorithms for selecting interesting objects. Black
hole ignition event candidates were selected form a parent sample of
spectrally classified non-active galaxies (> 2.300.000 objects), that
currently show optical flux variability indicative of a type I AGN,
according to the ALeRCE light curve classifier. In this talk I will
present spectral results for the most convincing case of new AGN
activity, for a galaxy with a previous star-forming optical
classification, where the confirmation spectrum shows the appearance
of prominent, broad Balmer lines without significant changes in the
narrow line flux ratios. MIR colors have also evolved from typical non
active galaxy colors to AGN-like colors and current X-ray detections
are consitent with typical AGN emission. This work is presented in
Arévalo et al. 2024(A&A letters 683, L8). In this talk I will present
the selection strategy, statistics, and predictions for similar studies
with the Vera Rubin LSST.
