Skip to Main content Skip to Navigation
New interface
Journal articles

Probabilistic image reconstruction for radio interferometers

Abstract : We present a novel, general-purpose method for deconvolving and denoizing images from gridded radio interferometric visibilities using Bayesian inference based on a Gaussian process model. The method automatically takes into account incomplete coverage of the uv-plane, signal mode coupling due to the primary beam and noise mode coupling due to uv sampling. Our method uses Gibbs sampling to efficiently explore the full posterior distribution of the underlying signal image given the data. We use a set of widely diverse mock images with a realistic interferometer set-up and level of noise to assess the method. Compared to results from a proxy for point source-based CLEAN method we find that in terms of rms error and signal-to-noise ratio our approach performs better than traditional deconvolution techniques, regardless of the structure of the source image in our test suite. Our implementation scales as O(n_p log n_p) provides full statistical and uncertainty information of the reconstructed image, requires no supervision and provides a robust, consistent framework for incorporating noise and parameter marginalizations and foreground removal.
Complete list of metadata

https://hal-insu.archives-ouvertes.fr/insu-03645706
Contributor : Hal Sorbonne Université Gestionnaire Connect in order to contact the contributor
Submitted on : Friday, April 22, 2022 - 4:49:04 PM
Last modification on : Thursday, May 12, 2022 - 6:22:03 PM
Long-term archiving on: : Saturday, July 23, 2022 - 7:16:10 PM

File

stt2244.pdf
Publisher files allowed on an open archive

Identifiers

Citation

P. M. Sutter, Benjamin D. Wandelt, Jason D. Mcewen, Emory F. Bunn, Ata Karakci, et al.. Probabilistic image reconstruction for radio interferometers. Monthly Notices of the Royal Astronomical Society, 2014, 438, pp.768-778. ⟨10.1093/mnras/stt2244⟩. ⟨insu-03645706⟩

Share

Metrics

Record views

21

Files downloads

7