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Predicting the emission profile and estimation of model parameters for some nearby LLAGN using accretion and jet models

Authors: Bandyopadhyay, Bidisha; Xie, Fu-Guo; Schleicher, Dominik R. G.; Nagar, Neil M.; Ramakrishnan, Venkatessh; Arevalo, Patricia; Lopez, Elena; +1 Authors

Predicting the emission profile and estimation of model parameters for some nearby LLAGN using accretion and jet models

Abstract

AbstractThe Event Horizon Telescope (EHT) provides a unique opportunity to probe the physics of supermassive black holes through Very Large Baseline Interferometry (VLBI), such as the existence of the event horizon, the accretion processes as well as jet formation in Low Luminosity AGN (LLAGN). We build a theoretical model which includes an Advection Dominated Accretion Flow (ADAF) and a simple radio jet outflow. The predicted spectral energy distribution (SED) of this model can be compared to observations to get the best estimates of the model parameters. The model-predicted radial emission profiles at different frequency bands can be used to predict whether the inflow can be resolved by the EHT or other telescopes. We have applied this method to some nearby LLAGN such as M84, NGC 4594, NGC 4278 and NGC 3998. We also estimate the model parameters for each of them using high resolution data from different surveys.

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Keywords

accretion, accretion disks, Galaxy: nucleus, black hole physics

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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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