A BRAIN study to tackle imaging in the ALMA 2030 era
Year: 2024
Type: article
Abstract: The ESO internal ALMA development study, BRAIN, utilizes Artificial Intelligence imaging algorithms for ALMA data. Employing both astrostatistics and astroinformatics techniques, this study integrates interdisciplinary approaches spanning observational astronomy, statistics, algorithm development, and data science. We offer compelling evidence of the benefits of these data driven methodologies in ALMA image analysis for operational and scientific purposes. Specifically, RESOLVE and DeepFocus show significant advantages, including improvements in data product quality and processing time reduction. These approaches pave the way for addressing the data analysis revolution expected by ALMA2030. Additionally, we introduce ALMASim, a new package aimed at advancing these fields by providing a refined ALMA simulator accessible to a wide audience. As of 2024, this study is nearing its end of term.
Author: Guglielmetti, Fabrizia
Language: English
Subfield: Astronomy and Astrophysics
Field: Physics and Astronomy
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W6893011669