English
 
Help Privacy Policy Disclaimer
  Advanced SearchBrowse

Item

ITEM ACTIONSEXPORT
  Comparison of classical and Bayesian imaging in radio interferometry - Cygnus A with CLEAN and resolve

Arras, P., Bester, H. L., Perley, R. A., Leike, R., Smirnov, O., Westermann, R., et al. (2021). Comparison of classical and Bayesian imaging in radio interferometry - Cygnus A with CLEAN and resolve. Astronomy and Astrophysics, 646: A84. doi:10.1051/0004-6361/202039258.

Item is

Basic

show hide
Genre: Journal Article

Files

show Files
hide Files
:
HOLISMOKES IV. Efficient mass modeling of strong lenses through deep learning.pdf (Any fulltext), 955KB
 
File Permalink:
-
Name:
HOLISMOKES IV. Efficient mass modeling of strong lenses through deep learning.pdf
Description:
-
Visibility:
Private
MIME-Type / Checksum:
application/pdf
Technical Metadata:
Copyright Date:
-
Copyright Info:
-
License:
-

Locators

show

Creators

show
hide
 Creators:
Arras, Philipp1, Author              
Bester, Hertzog L., Author
Perley, Richard A., Author
Leike, Reimar2, Author              
Smirnov, Oleg, Author
Westermann, Rüdiger, Author
Enßlin, Torsten A.1, Author              
Affiliations:
1Computational Structure Formation, MPI for Astrophysics, Max Planck Society, ou_2205642              
2Physical Cosmology, MPI for Astrophysics, Max Planck Society, ou_2205644              

Content

show
hide
Free keywords: -
 Abstract: CLEAN, the commonly employed imaging algorithm in radio interferometry, suffers from a number of shortcomings: In its basic version, it does not have the concept of diffuse flux, and the common practice of convolving the CLEAN components with the CLEAN beam erases the potential for super-resolution; it does not output uncertainty information; it produces images with unphysical negative flux regions; and its results are highly dependent on the so-called weighting scheme as well as on any human choice of CLEAN masks for guiding the imaging. Here, we present the Bayesian imaging algorithm resolve , which solves the above problems and naturally leads to super-resolution. We take a VLA observation of Cygnus A at four different frequencies and image it with single-scale CLEAN, multi-scale CLEAN, and resolve. Alongside the sky brightness distribution, resolve estimates a baseline-dependent correction function for the noise budget, the Bayesian equivalent of a weighting scheme. We report noise correction factors between 0.4 and 429. The enhancements achieved by resolve come at the cost of higher computational effort.

Details

show
hide
Language(s):
 Dates: 2021-02-12
 Publication Status: Published online
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: -
 Identifiers: DOI: 10.1051/0004-6361/202039258
 Degree: -

Event

show

Legal Case

show

Project information

show

Source 1

show
hide
Title: Astronomy and Astrophysics
  Other : Astron. Astrophys.
Source Genre: Journal
 Creator(s):
Affiliations:
Publ. Info: France : EDP Sciences S A
Pages: - Volume / Issue: 646 Sequence Number: A84 Start / End Page: - Identifier: ISSN: 1432-0746
CoNE: https://pure.mpg.de/cone/journals/resource/954922828219_1