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Bibliographic Details
Main Author: Braun, Robert
Format: Preprint
Published: 2025
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Online Access:https://arxiv.org/abs/2508.12869
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author Braun, Robert
author_facet Braun, Robert
contents The "dirty" image made by direct Fourier inversion of visibility data is an important first step in inteferometric imaging. This is where the "deconvolution problem" is defined and the degree to which that problem is either well- or ill-conditioned has direct consequences for the ultimate image fidelity that is achieved in practise. An under-utilised degree of freedom during Fourier imaging is the relative weights that are assigned to the visibility data. We explore the circumstances under which some adjustment of the relative weights might provide improvements to the "dirty" image, and consequently the ultimate post-deconvolution image fidelity. We develop a method to calculate a distinct effective local density estimate for each data point. When used in conjunction with a "uniform" weight correction and the desired clean beam (eg. Gaussian) tapering, it provides a significant improvement in the image quality over that provided by the current pixel-based density estimate. In many cases, particularly spectral-line observations and those with only limited sidereal tracking, this adaptive approach improves the beam quality by a factor of 2 to 10, as measured by the RMS residual relative to the best-fitting clean beam, providing an improvement in final image fidelity that is similar in magnitude.
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publishDate 2025
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spellingShingle Adaptive Uniform Weighting: Pre-conditioning to Improve Image Fidelity
Braun, Robert
Instrumentation and Methods for Astrophysics
The "dirty" image made by direct Fourier inversion of visibility data is an important first step in inteferometric imaging. This is where the "deconvolution problem" is defined and the degree to which that problem is either well- or ill-conditioned has direct consequences for the ultimate image fidelity that is achieved in practise. An under-utilised degree of freedom during Fourier imaging is the relative weights that are assigned to the visibility data. We explore the circumstances under which some adjustment of the relative weights might provide improvements to the "dirty" image, and consequently the ultimate post-deconvolution image fidelity. We develop a method to calculate a distinct effective local density estimate for each data point. When used in conjunction with a "uniform" weight correction and the desired clean beam (eg. Gaussian) tapering, it provides a significant improvement in the image quality over that provided by the current pixel-based density estimate. In many cases, particularly spectral-line observations and those with only limited sidereal tracking, this adaptive approach improves the beam quality by a factor of 2 to 10, as measured by the RMS residual relative to the best-fitting clean beam, providing an improvement in final image fidelity that is similar in magnitude.
title Adaptive Uniform Weighting: Pre-conditioning to Improve Image Fidelity
topic Instrumentation and Methods for Astrophysics
url https://arxiv.org/abs/2508.12869