29 citations · 38 across the 2 of their papers we have counts for
2 papers
astro-ph.GA2023★ 9 cited
Finding AGN remnant candidates based on radio morphology with machine learning
Rafael I. J. Mostert, Raffaella Morganti, Marisa Brienza +6
Remnant radio galaxies represent the dying phase of radio-loud active galactic nuclei (AGN). Large samples of remnant radio galaxies are important for quantifying the radio galaxy…
astro-ph.GA2020★ 29 cited
The best of both worlds: Combining LOFAR and Apertif to derive resolved radio spectral index images
R. Morganti, T. A. Oosterloo, M. Brienza +36
Supermassive black holes at the centres of galaxies can cycle through periods of activity and quiescence. Characterising the duty cycle of active galactic nuclei is crucial for und…