When R2D2 meets Cygnus A

  • Amir Aghabiglou (Creator)
  • Chung San Chu (Creator)
  • Adrian Jackson (Creator)
  • Arwa Dabbech (Creator)
  • Yves Wiaux (Creator)

Dataset

Description

Reconstruction of results of R2D2, a novel AI model for radio interferometric imaging, applied to real S-band observations of the celebrated radio galaxy Cygnus A with the Very Large Array.
The dataset consists of monochromatic images (estimated model images and residual dirty images) obtained by two proposed incarnations of the R2D2 model, and benchmark algorithms.

R2D2 models:
(1) R2D2 series, underpinned by U-Net blocks,
(2) R3D3 series, underpinned by novel R2D2-Net blocks.

Benchmark algorithms:
(1) U-Net, end-to-end DNN (also for term of R2D2 series),
(2) R2D2-Net: proposed by the authors, end-to-end DNN (also first term of R3D3 series),
(3) AIRI, PnP algorithm for RI (Terris et al. 2023),
(4) uSARA, sparsity-based algorithm for RI (Repetti & Wiaux 2020, Terris et al. 2023),
(5) CLEAN, multiscale (Offringa et al. 2014).
Date made available20 Sept 2023
PublisherHeriot-Watt University
Date of data production1 Aug 2023

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