The HST view of the FR I / FR II dichotomy
Marco Chiaberge, Alessandro Capetti, Annalisa Celotti

TL;DR
This study uses HST images to analyze the nuclear properties of FR I and FR II radio galaxies, revealing diverse behaviors and challenging the traditional dichotomy between their morphologies and nuclear characteristics.
Contribution
It provides a detailed comparison of nuclear properties of FR I and FR II galaxies, highlighting the heterogeneity within FR II and implications for AGN unification models.
Findings
FR I nuclei follow a tight radio-optical luminosity correlation.
FR II galaxies show varied nuclear properties related to spectral classification.
Some FR II nuclei resemble FR I, especially in cluster environments.
Abstract
In order to explore how the FR I / FR II dichotomy is related to the nuclear properties of radio galaxies, we studied a complete sample of 26 nearby FR II radio galaxies using Hubble Space Telescope (HST) images and compared them with a sample of FR I previously analyzed. FR I nuclei lie in the radio-optical luminosity plane along a tight linear correlation, which argues for a common synchrotron origin. FR II show a more complex behavior, which is however clearly related to their optical spectral classification. Broad line FR II radio galaxies (BLRG) are located overall well above the FR I correlation, suggesting that a contribution from thermal (disc) emission is present. Three narrow line (NLRG) and one weak line radio galaxy (WLRG), in which no nuclear source is seen, can be interpreted as the obscured counter-parts of BLRG, in agreement with the current unification schemes.…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsMagnetic confinement fusion research · Advanced Frequency and Time Standards · Scientific Measurement and Uncertainty Evaluation
