Inferring the jet parameters of active galactic nuclei using Bayesian analysis of VLBI data with a non-uniform jet model

Pashchenko, I. N.; Plavin, A. V.

doi:10.1093/mnras/stz1677

Cited by 9 publications

(8 citation statements)

References 75 publications

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“…In the general case of arbitrary exponents 𝑚, 𝑛 and optically thin spectral index 𝛼 analytical expressions for the distribution of optical depth and brightness temperature can be found in, e.g. Pashchenko & Plavin (2019). Lobanov (1998) has shown that the relativistic jet model can be used to estimate the jets physical parameters, e.g.…”

Section: Jet Model and Core Shift Measurementsmentioning

confidence: 99%

“…However, this requires some further assumptions because core shift measurements alone do not constrain the parameters of the jet model. More on degeneracies between model parameters can be found in Pashchenko & Plavin (2019). The most widely used is the assumption of an equipartition between emitting particles and magnetic field energy densities (Lobanov 1998;O'Sullivan & Gabuzda 2009;Pushkarev et al 2012).…”

Section: Jet Model and Core Shift Measurementsmentioning

confidence: 99%

“…To find the analytical expression for the position of the maximum intensity at some frequency, one has to differentiate the equation of the brightness temperature radial distribution. The brightness temperature distribution in a general case of arbitrary 𝑛, 𝑚 and 𝛼 is (Pashchenko & Plavin 2019):…”

Section: Bias Due To 𝜏 = 1 Region Being Offset From the Intensity Peakmentioning

confidence: 99%

“…1. The ratio of the distances from the jet apex to the 𝜏 = 1 region 𝑟 𝜏=1 and to the intensity maximum 𝑟 max can be calculated by substituting 𝜏 𝑟 max into the equation for optical depth distribution along the jet axis (Pashchenko & Plavin 2019):…”

Section: Bias Due To 𝜏 = 1 Region Being Offset From the Intensity Peakmentioning

confidence: 99%

“…The brightness distribution of the Blandford & Königl (1979) model depends on several parameters. Only some combinations of these parameters are identifiable on the basis of the VLBI observations (Pashchenko & Plavin 2019). Using a uniform or random grid in the parameter space will result in sample parameter values, which are not typical for the sources observed in flux-density-limited samples (e.g.…”

Section: Creation Of the Artificial Samplementioning

confidence: 99%

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A bias in VLBI measurements of the core shift effect in AGN jets

Pashchenko,

Plavin,

Kutkin

et al. 2020

Preprint

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The Blandford and Königl model of AGN jets predicts that the position of the apparent opaque jet base -the core -changes with frequency. This effect is observed with radio interferometry and is widely used to infer parameters and structure of the innermost jet regions. The position of the radio core is typically estimated by fitting a Gaussian template to the interferometric visibilities. This results in a model approximation error, i.e. a bias that can be detected and evaluated through simulations of observations with a realistic jet model. To assess the bias, we construct an artificial sample of sources based on the AGN jet model evaluated on a grid of the parameters derived from a real VLBI flux-density-limited sample and create simulated VLBI data sets at 2.3, 8.1 and 15.4 GHz. We found that the core position shifts from the true jet apex are generally overestimated. The bias is typically comparable to the core shift random error and can reach a factor of two for jets with large apparent opening angles. This observational bias depends mostly on the ratio between the true core shift and the image resolution. This implies that the magnetic field, the core radial distance and the jet speed inferred from the core shift measurements are overestimated. We present a method to account for the bias.

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Section: Jet Model and Core Shift Measurementsmentioning

confidence: 99%

Section: Jet Model and Core Shift Measurementsmentioning

confidence: 99%

Section: Bias Due To 𝜏 = 1 Region Being Offset From the Intensity Peakmentioning

confidence: 99%

Section: Bias Due To 𝜏 = 1 Region Being Offset From the Intensity Peakmentioning

confidence: 99%

Section: Creation Of the Artificial Samplementioning

confidence: 99%

See 3 more Smart Citations

A bias in VLBI measurements of the core shift effect in AGN jets

Pashchenko,

Plavin,

Kutkin

et al. 2020

Preprint

View full text Add to dashboard Cite

show abstract

Persistent mysteries of jet engines, formation, propagation, and particle acceleration: Have they been addressed experimentally?

Blackman

Lebedev

2022

New Astronomy Reviews

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A bias in VLBI measurements of the core shift effect in AGN jets

Pashchenko

Plavin

Kutkin

et al. 2020

Monthly Notices of the Royal Astronomical Society

View full text Add to dashboard Cite

The Blandford and Königl model of AGN jets predicts that the position of the apparent opaque jet base — the core — changes with frequency. This effect is observed with radio interferometry and is widely used to infer parameters and structure of the innermost jet regions. The position of the radio core is typically estimated by fitting a Gaussian template to the interferometric visibilities. This results in a model approximation error, i.e. a bias that can be detected and evaluated through simulations of observations with a realistic jet model. To assess the bias, we construct an artificial sample of sources based on the AGN jet model evaluated on a grid of the parameters derived from a real VLBI flux-density-limited sample and create simulated VLBI data sets at 2.3, 8.1 and 15.4 GHz. We found that the core position shifts from the true jet apex are generally overestimated. The bias is typically comparable to the core shift random error and can reach a factor of two for jets with large apparent opening angles. This observational bias depends mostly on the ratio between the true core shift and the image resolution. This implies that the magnetic field, the core radial distance and the jet speed inferred from the core shift measurements are overestimated. We present a method to account for the bias.

show abstract

Inferring the jet parameters of active galactic nuclei using Bayesian analysis of VLBI data with a non-uniform jet model

Cited by 9 publications

References 75 publications

A bias in VLBI measurements of the core shift effect in AGN jets

A bias in VLBI measurements of the core shift effect in AGN jets

Persistent mysteries of jet engines, formation, propagation, and particle acceleration: Have they been addressed experimentally?

A bias in VLBI measurements of the core shift effect in AGN jets

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