A direction-dependent framework for visibility plane mosaicing and primary beam correction

TL;DR

This paper introduces a direction-dependent visibility plane mosaicing framework that enhances sensitivity, fidelity, and flux accuracy in radio interferometric imaging, outperforming traditional image plane methods especially for wide-field and deep surveys.

Contribution

The paper presents a novel joint deconvolution and primary beam correction approach in the visibility plane, improving mosaic depth and accuracy over existing image plane techniques.

Findings

Achieved flux uncertainties within 6% and spectral index uncertainties within 20%.

Produced the deepest high-resolution MeerKAT image with 3.6 μJy/beam sensitivity.

Enhanced dynamic range by approximately 50% compared to image plane methods.

Abstract

With the increasing sensitivity of modern radio interferometers, it has become important to image objects larger than the field of view while optimising sensitivity and image fidelity. We present a coherent visibility plane direction-dependent imaging, calibration and mosaicing framework. Our simulations and application to real MeerKAT data show that this joint deconvolution and primary beam correction approach, coupled with direction-dependent calibration, allows for deeper mosaics with greater fidelity and increased accuracy of recovered flux densities and spectral indices, especially beyond the half-power beam width. Our best-case mosaic produces precise flux values within a 6% uncertainty and spectral indices within 20\% throughout the imaged area, and is fully complete out to twice the radii and half the flux density than the image plane equivalent. The application to archival wideband MeerKAT 1283 MHz data produces the deepest high-resolution image of the Shapley Supercluster Core, with a sensitivity of 3.6 $\mu$Jy/beam within the primary beam at a 7$^{\prime\prime}$ resolution, constituting a $\sim$ 50% increase in dynamic range over the image plane counterpart, and a fluxscale that is consistent within 10% across the entire field of view. The compute time for the direction-dependent visibility plane mosaic was comparable to the sum of the times needed to perform direction-dependent calibration on the individual pointings. Our results suggest that visibility plane mosaicing with its capability for deeper deconvolution could improve the efficiency of deep and wide surveys, particularly for on-the-fly mapping and studies of low surface brightness sources, and could form the basis of future calibration pipelines for SKA-scale instruments.