Improving Radio Interferometry Imaging by Explicitly Modeling Cross-Domain Consistency in Reconstruction

TL;DR

This paper introduces CDCRec, a multimodal reconstruction method for radio interferometry that explicitly models cross-domain consistency, improving imaging quality by leveraging mutual dependencies between visibility and image domains.

Contribution

The paper presents CDCRec, a novel hierarchical multi-task, multi-stage framework that enhances cross-domain correlation modeling in radio interferometric image reconstruction.

Findings

CDCRec outperforms existing methods in imaging quality.

Self-supervised strategy improves dense information recovery.

Enhanced cross-domain correlation extraction leads to better reconstructions.

Abstract

Radio astronomy plays a crucial role in understanding the universe, particularly within the realm of non-thermal astrophysics. Images of celestial objects are derived from the signals (called visibility) measured by radio telescopes. Such imaging results, called dirty images, contain artifacts due to factors such as sparsity and therefore require reconstruction to improve imaging quality. Existing methods typically restrict reconstruction to a unimodal domain, either to the dirty image after imaging or to the sparse visibility prior to imaging. Focusing solely on each unimodal reconstruction results in the loss of complementary in-context information in either the visibility or image domain, leading to an incomplete modeling of mutual dependency and consistency. To address these challenges, we propose CDCRec, a multimodal radio interferometric data reconstruction method that explicitly models cross-domain consistency. We design a hierarchical multi-task and multi-stage framework to enhance the exploration of interplays between domains during reconstruction. Our experimental results demonstrate that CDCRec improves imaging performance through enhanced cross-domain correlation extraction. In particular, our self-supervised complementary modeling strategy is better than current methods at interferometric domain translations that rely heavily on recovering dense information from constrained source-domain data.