{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/high-dynamic-range-wide-field-imaging-method","title":"High accuracy wide field imaging method in radio interferometry","arxiv_id":"2101.11172","date":"2021-01-27","proceeding":null,"authors":["Haoyang Ye","Steve F. Gull","Sze M. Tan","Bojan Nikolic"],"abstract":"With the development of modern radio interferometers, wide-field continuum surveys have been planned and undertaken, for which accurate wide-field imaging methods are essential. Based on the widely-used W-stacking method, we propose a new wide-field imaging algorithm that can synthesize visibility data from a model of the sky brightness via degridding, able to construct dirty maps from measured visibility data via gridding. Results carry the smallest approximation error yet achieved relative to the exact calculation involving the direct Fourier transform. In contrast to the original W-stacking method, the new algorithm performs least-misfit optimal gridding (and degridding) in all three directions, and is capable of achieving much higher accuracy than is feasible with the original algorithm. In particular, accuracy at the level of single precision arithmetic is readily achieved by choosing a least-misfit convolution function of width W=7 and an image cropping parameter of x0=0.25. If the accuracy required is only that attained by the original W-stacking method, the computational cost for both the gridding and FFT steps can be substantially reduced using the proposed method by making an appropriate choice of the width and image cropping parameters.","url_abs":"https://arxiv.org/abs/2101.11172v4","url_pdf":"https://arxiv.org/pdf/2101.11172v4.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"links_only","authors_date_abstract":"arXiv metadata, CC0 1.0 (https://info.arxiv.org/help/license), from the Kaggle arXiv metadata snapshot of 2026-09-12"},"code_links":[{"paper_slug":"high-dynamic-range-wide-field-imaging-method","repo_url":"https://github.com/astronomical-data-processing/CuRIG","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":null},{"paper_slug":"high-dynamic-range-wide-field-imaging-method","repo_url":"https://github.com/astronomical-data-processing/cugridder","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":null}],"tasks":[],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":null,"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}