A 6–12 GHz analogue lag-correlator for radio interferometry

Holler, C. M.; Kaneko, T.; Jones, Michael E.; Grainge, Keith; Scott, P. F.

doi:10.1051/0004-6361:20066879

Cited by 18 publications

(25 citation statements)

References 12 publications

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“…The SA data were checked for systematics using two jackknife tests. In test (a), calibrated visibilities from ‘plus’ correlator boards are subtracted from those obtained from ‘minus’ correlator boards – the signal is the same for both correlations but the latter inserts an additional 180° phase shift into the signal from one antenna (see Holler et al 2007 for a full description of the AMI correlator). For test (b), data obtained before the weighted median date of the visibilities are subtracted from data obtained afterwards.…”

Section: Instrument Observations Data Reduction and Mappingmentioning

confidence: 99%

A blind detection of a large, complex, Sunyaev-Zel’dovich structure★

Shimwell¹,

Barker²,

Biddulph³

et al. 2012

Monthly Notices of the Royal Astronomical Society

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We present an interesting Sunyaev–Zel’dovich (SZ) detection in the first of the Arcminute Microkelvin Imager (AMI) ‘blind’, degree‐square fields to have been observed down to our target sensitivity of . In follow‐up deep pointed observations the SZ effect is detected with a maximum peak decrement greater than eight times the thermal noise. No corresponding emission is visible in the ROSAT all‐sky X‐ray survey and no cluster is evident in the Palomar all‐sky optical survey. Compared with existing SZ images of distant clusters, the extent is large (≈10 arcmin) and complex; our analysis favours a model containing two clusters rather than a single cluster. Our Bayesian analysis is currently limited to modelling each cluster with an ellipsoidal or spherical β model, which does not do justice to this decrement. Fitting an ellipsoid to the deeper candidate we find the following. (a) Assuming that the Evrard et al. approximation to Press & Schechter correctly gives the number density of clusters as a function of mass and redshift, then, in the search area, the formal Bayesian probability ratio of the AMI detection of this cluster is 7.9 × 104:1; alternatively assuming Jenkins et al. as the true prior, the formal Bayesian probability ratio of detection is 2.1 × 105:1. (b) The cluster mass is . (c) Abandoning a physical model with number density prior and instead simply modelling the SZ decrement using a phenomenological β model of temperature decrement as a function of angular distance, we find a central SZ temperature decrement of K – this allows for cosmic microwave background primary anisotropies, receiver noise and radio sources. We are unsure if the cluster system we observe is a merging system or two separate clusters.

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Section: Instrument Observations Data Reduction and Mappingmentioning

confidence: 99%

A blind detection of a large, complex, Sunyaev-Zel’dovich structure★

Shimwell¹,

Barker²,

Biddulph³

et al. 2012

Monthly Notices of the Royal Astronomical Society

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“…The operation of a lag correlator, and comparison against an FX architecture are discussed in Holler et al (2007). He we restrict our discussion to details specific to the WBAC.…”

Section: Assemblymentioning

confidence: 99%

“…To avoid correlated noise signals, the calibration and data reduction of the scanning interleaves was carried out in the lag domain. Calibration of the lag response can be done using monochromatic signals (Harris & Zmuidzinas, 2001), or in situ using astronomical sources (Holler et al, 2007). The AT20G survey had already adopted the approach independently described by Holler et al (2007).…”

Section: Survey Calibrationmentioning

confidence: 99%

“…Calibration of the lag response can be done using monochromatic signals (Harris & Zmuidzinas, 2001), or in situ using astronomical sources (Holler et al, 2007). The AT20G survey had already adopted the approach independently described by Holler et al (2007). It is necessary to be able to deduce the location of a source in delay space from the signal distribution of the 16 lag channels of the correlator.…”

Section: Survey Calibrationmentioning

confidence: 99%

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The Australia telescope 20 GHz survey: hardware, observing strategy, and scanning survey catalog

et al. 2011

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The Australia Telescope 20GHz (AT20G) survey is a large area (2π sr), sensitive (40 mJy), high frequency (20 GHz) survey of the southern sky. The survey was conducted in two parts: an initial fast scanning survey, and a series of more accurate follow-up observations. The follow-up survey catalog has been presented by Murphy et al. (2010). In this paper we discuss the hardware setup and scanning survey strategy as well as the production of the scanning survey catalog.

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“…The discrepancy between the flux densities measured using the phase‐self‐calibrated pointed observations and the raster observations is instead attributed to phase errors in AMI data resulting from the uneven spacings of the time‐delays in the telescope’s lag correlator. Holler et al (2007) explain this problem in detail and propose a solution. In practice, however, further work is required to analyse the data from the correlator correctly.…”

Section: The 10c Source Cataloguementioning

confidence: 99%

10C survey of radio sources at 15.7 GHz - II. First results★

Davies¹,

Franzen²,

Waldram³

et al. 2011

Monthly Notices of the Royal Astronomical Society

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In a previous paper (Paper I), the observational, mapping and source‐extraction techniques used for the Tenth Cambridge (10C) Survey of Radio Sources were described. Here, the first results from the survey, carried out using the Arcminute Microkelvin Imager Large Array (LA) at an observing frequency of 15.7 GHz, are presented. The survey fields cover an area of ≈27 deg2 to a flux‐density completeness of 1 mJy. Results for some deeper areas, covering ≈12 deg2, wholly contained within the total areas and complete to 0.5 mJy, are also presented. The completeness for both areas is estimated to be at least 93 per cent. The 10C survey is the deepest radio survey of any significant extent (≳0.2 deg2) above 1.4 GHz. The 10C source catalogue contains 1897 entries and is available online. The source catalogue has been combined with that of the Ninth Cambridge Survey to calculate the 15.7‐GHz source counts. A broken power law is found to provide a good parametrization of the differential count between 0.5 mJy and 1 Jy. The measured source count has been compared with that predicted by de Zotti et al. – the model is found to display good agreement with the data at the highest flux densities. However, over the entire flux‐density range of the measured count (0.5 mJy to 1 Jy), the model is found to underpredict the integrated count by ≈30 per cent. Entries from the source catalogue have been matched with those contained in the catalogues of the NRAO VLA Sky Survey and the Faint Images of the Radio Sky at Twenty‐cm survey (both of which have observing frequencies of 1.4 GHz). This matching provides evidence for a shift in the typical 1.4‐GHz spectral index to 15.7‐GHz spectral index of the 15.7‐GHz‐selected source population with decreasing flux density towards sub‐mJy levels – the spectra tend to become less steep. Automated methods for detecting extended sources, developed in Paper I, have been applied to the data; ≈5 per cent of the sources are found to be extended relative to the LA‐synthesized beam of ≈30 arcsec. Investigations using higher resolution data showed that most of the genuinely extended sources at 15.7 GHz are classical doubles, although some nearby galaxies and twin‐jet sources were also identified.

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A 6–12 GHz analogue lag-correlator for radio interferometry

Cited by 18 publications

References 12 publications

A blind detection of a large, complex, Sunyaev-Zel’dovich structure★

A blind detection of a large, complex, Sunyaev-Zel’dovich structure★

The Australia telescope 20 GHz survey: hardware, observing strategy, and scanning survey catalog

10C survey of radio sources at 15.7 GHz - II. First results★

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