A distributed algorithm for wide-band radio-interferometry

Abdullah Abdulaziz; Alex Onose; Arwa Dabbech; Yves Wiaux

A distributed algorithm for wide-band radio-interferometry

Abdullah Abdulaziz
, Alex Onose
, Arwa Dabbech
, Yves Wiaux

Research output: Contribution to conference › Paper › peer-review

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Abstract

We propose a scalable, randomised algorithm to solve the inverse imaging problem in wide-band radio- interferometry. In the big-data context of the next- generation radio-telescopes, the scalability is paramount due to the large-scale of the problem to be solved. The proposed method distributes the data measured at each frequency and processes it in parallel. We showcase the algorithm capabilities through realistic simulations.

Original language	English
Number of pages	1
Publication status	Published - 30 Jan 2017
Event	International Biomedical and Astronomical Signal Processing Frontiers Workshop 2017 - Villars-sur-Ollon, Switzerland Duration: 29 Jan 2017 → 3 Feb 2017

Conference

Conference	International Biomedical and Astronomical Signal Processing Frontiers Workshop 2017
Abbreviated title	BASP Frontiers 2017
Country/Territory	Switzerland
City	Villars-sur-Ollon
Period	29/01/17 → 3/02/17

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title = "A distributed algorithm for wide-band radio-interferometry",

abstract = "We propose a scalable, randomised algorithm to solve the inverse imaging problem in wide-band radio- interferometry. In the big-data context of the next- generation radio-telescopes, the scalability is paramount due to the large-scale of the problem to be solved. The proposed method distributes the data measured at each frequency and processes it in parallel. We showcase the algorithm capabilities through realistic simulations.",

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T1 - A distributed algorithm for wide-band radio-interferometry

AU - Abdulaziz, Abdullah

AU - Onose, Alex

AU - Dabbech, Arwa

AU - Wiaux, Yves

PY - 2017/1/30

Y1 - 2017/1/30

N2 - We propose a scalable, randomised algorithm to solve the inverse imaging problem in wide-band radio- interferometry. In the big-data context of the next- generation radio-telescopes, the scalability is paramount due to the large-scale of the problem to be solved. The proposed method distributes the data measured at each frequency and processes it in parallel. We showcase the algorithm capabilities through realistic simulations.

AB - We propose a scalable, randomised algorithm to solve the inverse imaging problem in wide-band radio- interferometry. In the big-data context of the next- generation radio-telescopes, the scalability is paramount due to the large-scale of the problem to be solved. The proposed method distributes the data measured at each frequency and processes it in parallel. We showcase the algorithm capabilities through realistic simulations.

M3 - Paper

T2 - International Biomedical and Astronomical Signal Processing Frontiers Workshop 2017

Y2 - 29 January 2017 through 3 February 2017

ER -

A distributed algorithm for wide-band radio-interferometry

Abstract

Conference

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