发表机构
Laboratoire de Physique de l’École Normale Supérieure, ENS, Université PSL, CNRS, Sorbonne Université, Université Paris Cité, Observatoire de Paris; Research School of Astronomy & Astrophysics, The Australian National University; College of Sciences and Engineering, Universidad San Francisco de Quito; School of Natural Sciences, University of Tasmania; Max-Planck-Institut für Radioastronomie（巴黎高等师范学院物理实验室; 澳大利亚国立大学天文学与天体物理学研究学院; 基多圣弗朗西斯科大学科学与工程学院; 塔斯马尼亚大学自然科学学院; 马克斯·普朗克射电天文研究所）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
IViS是一个GPU加速的Python框架，通过可见度域联合反卷积处理宽视场HI成像，能恢复更多大尺度功率并减少旁瓣，优于传统方法。
AI 中文摘要
当发射是延展的、多尺度的且分布在许多重叠指向中时，使用现代射电干涉仪进行宽视场谱线成像仍然具有挑战性。准确的图像重建需要对校准后的可见度进行联合处理、控制图像域的规则性，并从单碟数据中恢复缺失的短间距信息。我们提出了IViS（干涉测量可见度域反演软件），这是一个用于可见度域联合反卷积的GPU加速Python框架，并评估了其用于澳大利亚平方千米阵列探路者（ASKAP）宽视场HI成像的性能。当前模型Classic3D通过最小化正则化最小二乘准则，直接从校准后的可见度重建非参数天空立方体。前向模型依赖于非均匀快速傅里叶变换（NUFFT），支持跨马赛克指向的联合反卷积和正性约束，并可通过融合项纳入单碟数据。我们使用点源、纯噪声和多尺度弥散发射模拟验证了该方法，并将其应用于对大麦哲伦云（LMC）的ASKAP观测。模拟表明，IViS在没有正则化的情况下能准确恢复点源通量，而正则化设定了噪声抑制与有效分辨率之间的权衡。联合反卷积能比独立反卷积指向的线性马赛克恢复更多大尺度功率。在加入单碟信息后，重建的功率谱能紧密再现输入的天空统计。应用于ASKAP数据时，IViS生成了有效分辨率为22角秒的10小时马赛克，并减少了残余旁瓣结构。与针对单个观测块的ASKAPSoft多尺度CLEAN相比，Classic3D表现出更少的残余旁瓣，并在低空间频率处恢复了显著更多的功率。
英文摘要
Wide-field spectral-line imaging with modern radio interferometers remains challenging when the emission is extended, multiscale, and distributed over many overlapping pointings. Accurate reconstruction requires joint treatment of the calibrated visibilities, control of image-domain regularity, and recovery of missing short spacings from single-dish data. We present IViS (Interferometric Visibility-domain Inversion Software), a GPU-accelerated Python framework for visibility-domain joint deconvolution, and assess its performance for wide-field HI imaging with the Australian Square Kilometre Array Pathfinder (ASKAP). The current model, Classic3D, reconstructs a non-parametric sky cube directly from calibrated visibilities by minimizing a regularized least-squares criterion. The forward model relies on a non-uniform fast Fourier transform (NUFFT), supports joint deconvolution across mosaic pointings and positivity constraints, and can incorporate single-dish data through a fusion term. We validate the method using point-source, noise-only, and multiscale diffuse-emission simulations, and apply it to ASKAP observations toward the Large Magellanic Cloud (LMC). The simulations show that IViS recovers point-source flux accurately without regularization and that regularization sets the trade-off between noise suppression and effective resolution. Joint deconvolution can recover more large-scale power than linear mosaicking of independently deconvolved pointings. With single-dish information, the reconstructed power spectra closely reproduce the input sky statistics. Applied to ASKAP data, IViS yields 10h mosaics with an effective resolution of 22'' and reduced residual side-lobe structure. Compared with ASKAPSoft multi-scale CLEAN for a single observing block, Classic3D exhibits fewer residual side-lobes and recovers substantially more power at low spatial frequencies.
Comments20 pages, 21 figures; Accepted for publication in A&A
