Black hole jets on the scale of the cosmic web
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Cited by 3 publications
References 64 publications
Constraining the giant radio galaxy population with machine learning and Bayesian inference
Large-scale sky surveys at low frequencies, such as the LOFAR Two-metre Sky Survey (LoTSS), allow for the detection and characterisation of unprecedented numbers of giant radio galaxies (GRGs, or `giants', of at least $l_ p,GRG Mpc $ long). This, in turn, enables us to study giants in a cosmological context. A tantalising prospect of such studies is a measurement of the contribution of giants to cosmic magnetogenesis. However, this measurement requires en masse radio--optical association for well-resolved radio galaxies and a statistical framework to infer GRG population properties. By automating the creation of radio--optical catalogues, we aim to significantly expand the census of known giants. With the resulting sample and a forward model that takes into account selection effects, we aim to constrain their intrinsic length distribution, number density, and lobe volume-filling fraction (VFF) in the Cosmic Web. We combined five existing codes into a single machine learning (ML)--driven pipeline that automates radio source component association and optical host identification for well-resolved radio sources. We created a radio--optical catalogue for the entire LoTSS Data Release 2 (DR2) footprint and subsequently selected all sources that qualify as possible giants. We combined the list of ML pipeline GRG candidates with an existing list of LoTSS DR2 crowd-sourced GRG candidates and visually confirmed or rejected all members of the merged sample. To infer intrinsic GRG properties from GRG observations, we developed further a population-based forward model and constrained its parameters using Bayesian inference. Roughly half of all GRG candidates that our ML pipeline identifies indeed turn out to be giants upon visual inspection, whereas the success rate is 1 in 11 for the previous best giant-finding ML technique in the literature. We confirm $5,647$ previously unknown giants from the crowd-sourced LoTSS DR2 catalogue and $2,597$ previously unknown giants from the ML pipeline. Our confirmations and discoveries bring the total number of known giants to at least $11,585$. Our intrinsic GRG population forward model provides a good fit to the data. The posterior indicates that the projected lengths of giants are consistent with a curved power law probability density function whose initial tail index $ p,GRG changes by $ 0.3$ over the interval up to $l_ p Mpc $. We predict a comoving GRG number density $n_ GRG Mpc $, close to a recent estimate of the number density of luminous non-giant radio galaxies. With the projected length distribution, number density, and additional assumptions, we derive a present-day GRG lobe VFF $ V GRG-CW (z=0) = 1.4 $ in clusters and filaments of the Cosmic Web. We present a state-of-the-art ML-accelerated pipeline for finding giants, whose complex morphologies, arcminute extents, and radio-emitting surroundings pose challenges. Our data analysis suggests that giants are more common than previously thought. More work is needed to make GRG lobe VFF estimates reliable, but tentative results imply that it is possible that magnetic fields once contained in giants pervade a significant ($ gtrsim 10<!PCT!>$) fraction of today's Cosmic Web.
Constraining the giant radio galaxy population with machine learning and Bayesian inference
Large-scale sky surveys at low frequencies, such as the LOFAR Two-metre Sky Survey (LoTSS), allow for the detection and characterisation of unprecedented numbers of giant radio galaxies (GRGs, or `giants', of at least $l_ p,GRG Mpc $ long). This, in turn, enables us to study giants in a cosmological context. A tantalising prospect of such studies is a measurement of the contribution of giants to cosmic magnetogenesis. However, this measurement requires en masse radio--optical association for well-resolved radio galaxies and a statistical framework to infer GRG population properties. By automating the creation of radio--optical catalogues, we aim to significantly expand the census of known giants. With the resulting sample and a forward model that takes into account selection effects, we aim to constrain their intrinsic length distribution, number density, and lobe volume-filling fraction (VFF) in the Cosmic Web. We combined five existing codes into a single machine learning (ML)--driven pipeline that automates radio source component association and optical host identification for well-resolved radio sources. We created a radio--optical catalogue for the entire LoTSS Data Release 2 (DR2) footprint and subsequently selected all sources that qualify as possible giants. We combined the list of ML pipeline GRG candidates with an existing list of LoTSS DR2 crowd-sourced GRG candidates and visually confirmed or rejected all members of the merged sample. To infer intrinsic GRG properties from GRG observations, we developed further a population-based forward model and constrained its parameters using Bayesian inference. Roughly half of all GRG candidates that our ML pipeline identifies indeed turn out to be giants upon visual inspection, whereas the success rate is 1 in 11 for the previous best giant-finding ML technique in the literature. We confirm $5,647$ previously unknown giants from the crowd-sourced LoTSS DR2 catalogue and $2,597$ previously unknown giants from the ML pipeline. Our confirmations and discoveries bring the total number of known giants to at least $11,585$. Our intrinsic GRG population forward model provides a good fit to the data. The posterior indicates that the projected lengths of giants are consistent with a curved power law probability density function whose initial tail index $ p,GRG changes by $ 0.3$ over the interval up to $l_ p Mpc $. We predict a comoving GRG number density $n_ GRG Mpc $, close to a recent estimate of the number density of luminous non-giant radio galaxies. With the projected length distribution, number density, and additional assumptions, we derive a present-day GRG lobe VFF $ V GRG-CW (z=0) = 1.4 $ in clusters and filaments of the Cosmic Web. We present a state-of-the-art ML-accelerated pipeline for finding giants, whose complex morphologies, arcminute extents, and radio-emitting surroundings pose challenges. Our data analysis suggests that giants are more common than previously thought. More work is needed to make GRG lobe VFF estimates reliable, but tentative results imply that it is possible that magnetic fields once contained in giants pervade a significant ($ gtrsim 10<!PCT!>$) fraction of today's Cosmic Web.
Ubiquitous radio emission in quasars: Predominant AGN origin and a connection to jets, dust, and winds
We present a comprehensive study of the physical origin of radio emission in optical quasars at redshifts $z<2.5$. We focus particularly on the associations between compact radio emission, dust reddening, and outflows identified in our earlier work. Leveraging the deepest low-frequency radio data available to date (LoTSS Deep DR1), we achieve radio detection fractions of up to 94<!PCT!>, demonstrating the virtual ubiquity of radio emission in quasars, and a continuous distribution in radio loudness. Through our analysis of radio properties, combined with spectral energy distribution modelling of deep multiwavelength photometry, we establish that the primary source of radio emission in quasars is the active galactic nucleus (AGN), rather than star formation. Modelling the dust reddening of the accretion disc emission shows a continuous increase in radio detection in quasars as a function of the reddening parameter E(B-V) suggesting a causal link between radio emission and dust reddening. Confirming previous findings, we observe that the radio excess in red quasars is most pronounced for sources with compact radio morphologies and intermediate radio loudness. We find a significant increase in Oiii and Civ outflow velocities for red quasars not seen in our control sample, with particularly powerful Oiii winds in those around the threshold from radio-quiet to radio-loud. Based on the combined characterisation of radio, reddening, and outflow properties in our sample, we favour a model in which the compact radio emission observed in quasars originates in compact radio jets and their interaction with a dusty, circumnuclear environment. In particular, our results align with the theory that jet-induced winds and shocks resulting from this interaction are the origin of the enhanced radio emission in red quasars. Further investigation of this model is crucial for advancing our understanding of quasar feedback mechanisms and their role in galaxy evolution.
Magnetic Flux Transport in Advection-dominated Accretion Flow toward the Formation of a Magnetically Arrested Disk
Magnetically arrested disks (MADs) have attracted much attention in recent years. The formation of MADs is usually attributed to the accumulation of a sufficient amount of dynamically significant poloidal magnetic flux. In this work, the magnetic flux transport within an advection-dominated accretion flow (ADAF) and the formation of an MAD are investigated. The structure and dynamics of an inner MAD connected with an outer ADAF are derived by solving a set of differential equations with suitable boundary conditions. We find that an inner MAD is eventually formed at a region about several 10 R S outside the horizon. Due to the presence of a strong large-scale magnetic field, the radial velocity of the accretion flow is significantly decreased. The angular velocity of the MAD region is highly sub-Keplerian with Ω ∼ (0.4–0.5)ΩK, and the corresponding ratio of gas to magnetic pressure is about β ≲ 1. Also, we find that an MAD is unlikely to be formed through the inward flux advection process when the external magnetic field strength is weak enough with β out ≳ 100 around R out ∼ 1000 R s. Based on a rough estimate, we find that the jet power of a black hole, with mass M BH and spin a *, surrounded by an ADAF with an inner MAD region is about 2 orders of magnitude larger than that of a black hole surrounded by a normal ADAF. This may account for the powerful jets observed in some Fanaroff–Riley type I galaxies with a very low Eddington ratio.
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