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Using baseline-dependent window functions for data compression and field-of-interest shaping in radio interferometry
by
Jonas, J
, Smirnov, O M
, Tasse, C
, Foster, G
, Atemkeng, M T
in
Amplitudes
/ Attenuation
/ Computer simulation
/ Convolution
/ Data compression
/ Freight cars
/ Galling
/ Interferometers
/ Interferometry
/ Sensitivity
/ Tradeoffs
/ Very long base interferometry
/ Visibility
/ Window functions
2016
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Using baseline-dependent window functions for data compression and field-of-interest shaping in radio interferometry
by
Jonas, J
, Smirnov, O M
, Tasse, C
, Foster, G
, Atemkeng, M T
in
Amplitudes
/ Attenuation
/ Computer simulation
/ Convolution
/ Data compression
/ Freight cars
/ Galling
/ Interferometers
/ Interferometry
/ Sensitivity
/ Tradeoffs
/ Very long base interferometry
/ Visibility
/ Window functions
2016
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While trying to remove the title from your shelf something went wrong :( Kindly try again later!
Do you wish to request the book?
Using baseline-dependent window functions for data compression and field-of-interest shaping in radio interferometry
by
Jonas, J
, Smirnov, O M
, Tasse, C
, Foster, G
, Atemkeng, M T
in
Amplitudes
/ Attenuation
/ Computer simulation
/ Convolution
/ Data compression
/ Freight cars
/ Galling
/ Interferometers
/ Interferometry
/ Sensitivity
/ Tradeoffs
/ Very long base interferometry
/ Visibility
/ Window functions
2016
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Using baseline-dependent window functions for data compression and field-of-interest shaping in radio interferometry
Paper
Using baseline-dependent window functions for data compression and field-of-interest shaping in radio interferometry
2016
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Overview
In radio interferometry, observed visibilities are intrinsically sampled at some interval in time and frequency. Modern interferometers are capable of producing data at very high time and frequency resolution; practical limits on storage and computation costs require that some form of data compression be imposed. The traditional form of compression is a simple averaging of the visibilities over coarser time and frequency bins. This has an undesired side effect: the resulting averaged visibilities \"decorrelate\", and do so differently depending on the baseline length and averaging interval. This translates into a non-trivial signature in the image domain known as \"smearing\", which manifests itself as an attenuation in amplitude towards off-centre sources. With the increasing fields of view and/or longer baselines employed in modern and future instruments, the trade-off between data rate and smearing becomes increasingly unfavourable. In this work we investigate alternative approaches to low-loss data compression. We show that averaging of the visibility data can be treated as a form of convolution by a boxcar-like window function, and that by employing alternative baseline-dependent window functions a more optimal interferometer smearing response may be induced. In particular, we show improved amplitude response over a chosen field of interest, and better attenuation of sources outside the field of interest. The main cost of this technique is a reduction in nominal sensitivity; we investigate the smearing vs. sensitivity trade-off, and show that in certain regimes a favourable compromise can be achieved. We show the application of this technique to simulated data from the Karl G. Jansky Very Large Array (VLA) and the European Very-long-baseline interferometry Network (EVN).
Publisher
Cornell University Library, arXiv.org
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