From Nearby Low Luminosity AGN to High Redshift Radio Galaxies: Science Interests with Square Kilometre Array

Kharb, P.; Lal, D.; Singh, Veeresh; Chandra, C. H. Ishwara; Hota, Ananda; Konar, C.; Wadadekar, Yogesh; Shastri, P.; Das, Mousumi; Baliyan, K. S.; Nath, Biman B.; Pandey-Pommier, M.

doi:10.1007/s12036-016-9411-z

Cited by 3 publications

(3 citation statements)

References 161 publications

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“…The key science drivers of the SKA encompass many important areas of research related to AGN physics and the connection between MBHs and galaxies in the context of galaxy formation and evolution. As detailed in numerous recent white papers, the SKA will directly probe jet-ISM feedback through observations of neutral hydrogen absorption against radio jets, constrain radio AGN duty cycles through spectral aging studies, and provide a census of the radio AGN population at low luminosities and high redshifts (Agudo et al 2015;Kapinska et al 2015;Kharb et al 2016;McAlpine et al 2015;Orienti et al 2015;Prandoni & Seymour 2015;Smolcic et al 2015). Thus, there is indeed significant overlap between the scientific questions that the SKA and the ngVLA will address regarding AGNs (see Section 2), but we emphasize that this overlap is synergistic in nature.…”

Section: Skamentioning

confidence: 99%

Revolutionizing Our Understanding of AGN Feedback and its Importance to Galaxy Evolution in the Era of the Next Generation Very Large Array

Nyland

Harwood

Mukherjee

et al. 2018

ApJ

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Energetic feedback by Active Galactic Nuclei (AGNs) plays an important evolutionary role in the regulation of star formation (SF) on galactic scales. However, the effects of this feedback as a function of redshift and galaxy properties such as mass, environment and cold gas content remain poorly understood. The broad frequency coverage (1 to 116 GHz), high sensitivity (up to ten times higher than the Karl G. Jansky Very Large Array), and superb angular resolution (maximum baselines of at least a few hundred km) of the proposed next generation Very Large Array (ngVLA) are uniquely poised to revolutionize our understanding of AGNs and their role in galaxy evolution. Here, we provide an overview of the science related to AGN feedback that will be possible in the ngVLA era and present new continuum ngVLA imaging simulations of resolved radio jets spanning a wide range of intrinsic extents. We also consider key computational challenges and discuss exciting opportunities for multi-wavelength synergy with other next-generation instruments, such as the Square Kilometer Array and the James Webb Space Telescope. The unique combination of high-resolution, large collecting area, and wide frequency range will enable significant advancements in our understanding of the effects of jet-driven feedback on sub-galactic scales, particularly for sources with extents of a few pc to a few kpc such as young and/or lower-power radio AGNs, AGNs hosted by low-mass galaxies, radio jets that are interacting strongly with the interstellar medium of the host galaxy, and AGNs at high redshift.

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Section: Skamentioning

confidence: 99%

Revolutionizing Our Understanding of AGN Feedback and its Importance to Galaxy Evolution in the Era of the Next Generation Very Large Array

Nyland

Harwood

Mukherjee

et al. 2018

ApJ

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“…An issue in the latter studies is the relatively small fraction of FRI sources found in current all-sky surveys -due to their relatively high detection and completeness threshold, high redshift and/or low luminosity, low-surface brightness source populations are not probed well. Upcoming all-sky surveys with SKA will probe FRI populations to high redshifts (Kapinska et al 2015) and would be able to answer these questions (Kharb et al 2016).…”

Section: Introductionmentioning

confidence: 99%

Classifying Radio Galaxies with the Convolutional Neural Network

Aniyan

Thorat

2017

ApJS

161

176

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We present the application of deep machine learning technique to classify radio images of extended sources on a morphological basis using convolutional neural networks. In this study, we have taken the case of Fanaroff-Riley (FR) class of radio galaxies as well as radio galaxies with bent-tailed morphology. We have used archival data from the Very Large Array (VLA) -Faint Images of the Radio Sky at Twenty Centimeters (FIRST) survey and existing visually classified samples available in literature to train a neural network for morphological classification of these categories of radio sources. Our training sample size for each of these categories is ∼200 sources, which has been augmented by rotated versions of the same. Our study shows that convolutional neural networks can classify images of the FRI and FRII and bent-tailed radio galaxies with high accuracy (maximum precision at 95%) using well-defined samples and "fusion classifier", which combines the results of binary classifications, while allowing for a mechanism to find sources with unusual morphologies. The individual precision is highest for bent-tailed radio galaxies at 95% and is 91% and 75% for the FRI and FRII classes, respectively, whereas the recall is highest for FRI and FRIIs at 91% each, while bent-tailed class has a recall of 79%. These results show that our results are comparable to that of manual classification while being much faster. Finally, we discuss the computational and data-related challenges associated with morphological classification of radio galaxies with convolutional neural networks.

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“…In addition, optical spectra provided by the WEAVE-LOFAR survey (Smith et al 2016) will be beneficial in identifying LDR2 counterparts to unidentified γ-ray sources. In the long term, surveys with the Square Kilometre Array (SKA) will also be key in studying this population (Kharb et al 2016). This table is available in its entirety in machine-readable form.…”

Section: Conclusion and Future Prospectsmentioning

confidence: 99%

Characterising the Extended Morphologies of BL Lacertae Objects at 144 MHz with LOFAR

Mooney

Massaro

Quinn

et al. 2021

ApJS

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We present a morphological and spectral study of a sample of 99 BL Lac objects using the LOFAR Two-Metre Sky Survey Second Data Release (LDR2). Extended emission has been identified at gigahertz frequencies around BL Lac objects, but with LDR2 it is now possible to systematically study their morphologies at 144 MHz, where more diffuse emission is expected. LDR2 reveals the presence of extended radio structures around 66/99 of the BL Lac nuclei, with angular extents ranging up to 115″, corresponding to spatial extents of 410 kpc. The extended emission is likely to be both unbeamed diffuse emission and beamed emission associated with relativistic bulk motion in jets. The spatial extents and luminosities of the extended emission are consistent with the unification scheme for active galactic nuclei, where BL Lac objects correspond to low-excitation radio galaxies with the jet axis aligned along the line of sight. While extended emission is detected around the majority of BL Lac objects, the median 144–1400 MHz spectral index and core dominance at 144 MHz indicate that the core component contributes ∼42% on average to the total low-frequency flux density. A stronger correlation was found between the 144 MHz core flux density and the γ-ray photon flux (r = 0.69) than between the 144 MHz extended flux density and the γ-ray photon flux (r = 0.42). This suggests that the radio-to-γ-ray connection weakens at low radio frequencies because the population of particles that give rise to the γ-ray flux are distinct from the electrons producing the diffuse synchrotron emission associated with spatially extended features.

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From Nearby Low Luminosity AGN to High Redshift Radio Galaxies: Science Interests with Square Kilometre Array

Cited by 3 publications

References 161 publications

Revolutionizing Our Understanding of AGN Feedback and its Importance to Galaxy Evolution in the Era of the Next Generation Very Large Array

Revolutionizing Our Understanding of AGN Feedback and its Importance to Galaxy Evolution in the Era of the Next Generation Very Large Array

Classifying Radio Galaxies with the Convolutional Neural Network

Characterising the Extended Morphologies of BL Lacertae Objects at 144 MHz with LOFAR

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