The radio time delay in the double quasar 0957 + 561

Lehár, Joseph; Hewitt, J. N.; Roberts, D. H.; Burke, B. F.

doi:10.1086/170887

Cited by 68 publications

(74 citation statements)

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“…For example, in Fig. 12, we plot the locally normalized discrete correlation function (DCF, Lehar et al 1992;Edelson & Krolik 1988) between the m c light curves of two randomly chosen bright sources in our sample, namely 4C +38.41 and CTA 102, before and after the instrumental polarization correction. For the uncorrected data, the most prominent maxima appear at zero time lag where the correlation factor is 0.8 ± 0.2 and 0.7 ± 0.2 for the 4.85 GHz and 8.35 GHz data, respectively.…”

Section: Correcting For Instrumental Circular Polarizationmentioning

confidence: 99%

Full-Stokes polarimetry with circularly polarized feeds

Myserlis

Angelakis

Kraus

et al. 2018

A&A

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We present an analysis pipeline that enables the recovery of reliable information for all four Stokes parameters with high accuracy. Its novelty relies on the effective treatment of the instrumental effects even before the computation of the Stokes parameters, contrary to conventionally used methods such as that based on the Müller matrix. For instance, instrumental linear polarization is corrected across the whole telescope beam and significant Stokes Q and U can be recovered even when the recorded signals are severely corrupted by instrumental effects. The accuracy we reach in terms of polarization degree is of the order of 0.1-0.2%. The polarization angles are determined with an accuracy of almost 1 • . The presented methodology was applied to recover the linear and circular polarization of around 150 active galactic nuclei, which were monitored between July 2010 and April 2016 with the Effelsberg 100-m telescope at 4.85 GHz and 8.35 GHz with a median cadence of 1.2 months. The polarized emission of the Moon was used to calibrate the polarization angle measurements. Our analysis showed a small system-induced rotation of about 1 • at both observing frequencies. Over the examined period, five sources have significant and stable linear polarization; three sources remain constantly linearly unpolarized; and a total of 11 sources have stable circular polarization degree m c , four of them with non-zero m c . We also identify eight sources that maintain a stable polarization angle. All this is provided to the community for future polarization observations reference. We finally show that our analysis method is conceptually different from those traditionally used and performs better than the Müller matrix method. Although it has been developed for a system equipped with circularly polarized feeds, it can easily be generalized to systems with linearly polarized feeds as well.

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Section: Correcting For Instrumental Circular Polarizationmentioning

confidence: 99%

Full-Stokes polarimetry with circularly polarized feeds

Myserlis

Angelakis

Kraus

et al. 2018

A&A

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“…Since the data can be normalised as a preprocessing step, we can use a moderate value of σ 2 s = 10 2 . On the surface, it might seem that the delay has no role in Equations (1) and (2). It of course does, but the effect is of structural nature as it affects the combined time instants t i and consequently the order in which the data samples appear in the model.…”

Section: Modelling Assumptionsmentioning

confidence: 99%

“…We compare the proposed approach to the following three widely used methods: discrete correlation function (DCF) [1], locally normalised discrete correlation function (LNDCF) [2], and linear interpolation followed by standard cross correlation (similar scheme used e.g. in [6]).…”

Section: Controlled Comparisonsmentioning

confidence: 99%

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Bayesian estimation of time delays between unevenly sampled signals

Harva¹,

Raychaudhury

2008

Neurocomputing

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A method for estimating time delays between signals that are irregularly sampled is presented. The approach is based on postulating a latent variable model from which the observed signals have been generated and computing the posterior distribution of the delay. This is achieved partly by exact marginalisation and partly by using MCMC methods. Experiments with artificial data show the effectiveness of the proposed approach while results with real-world gravitational lens data provide the main motivation for this work.

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“…Both calculate correlations directly on discrete pairs of light curves (Edelson & Krolik 1988;Lehar et al 1992). These methods avoid interpolation in the observational gaps.…”

Section: Cross Correlationmentioning

confidence: 99%

How accurate are the time delay estimates in gravitational lensing?

Cuevas-Tello

Tiňo²,

Raychaudhury³

2006

A&A

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We present a novel approach to estimate the time delay between light curves of multiple images in a gravitationally lensed system, based on Kernel methods in the context of machine learning. We perform various experiments with artificially generated irregularlysampled data sets to study the effect of the various levels of noise and the presence of gaps of various size in the monitoring data. We compare the performance of our method with various other popular methods of estimating the time delay and conclude, from experiments with artificial data, that our method is least vulnerable to missing data and irregular sampling, within reasonable bounds of Gaussian noise. Thereafter, we use our method to determine the time delays between the two images of quasar Q0957+561 from radio monitoring data at 4 cm and 6 cm, and conclude that if only the observations at epochs common to both wavelengths are used, the time delay gives consistent estimates, which can be combined to yield 408 ± 12 days. The full 6 cm dataset, which covers a longer monitoring period, yields a value which is 10% larger, but this can be attributed to differences in sampling and missing data.

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The radio time delay in the double quasar 0957 + 561

Cited by 68 publications

References 0 publications

Full-Stokes polarimetry with circularly polarized feeds

Full-Stokes polarimetry with circularly polarized feeds

Bayesian estimation of time delays between unevenly sampled signals

How accurate are the time delay estimates in gravitational lensing?

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