SIMAI 2025

IS034 - Recent Trends in Models and Algorithms for Astronomical Imaging

Organized by: P. Massa (Fachhochschule Nordwestschweiz (FHNW), Switzerland) and S. Tozza (ALMA MATER STUDIORUM - Università di Bologna, Italy)
Keywords: Approximation theory, Astronomical imaging, Inverse problems, Machine learning, PDE-based methods, Solar X-ray imaging
The intersection of mathematics and astronomy has long been a fertile ground for innovation, driving advancements in both theoretical and observational sciences. With the latest generation of astronomical instruments producing increasingly complex and voluminous datasets, the need for precise and efficient mathematical techniques has never been greater. In fact, handling vast amounts of data and ensuring precise, self-consistent image analysis across varying depths and resolutions brings significant challenges. Developing new and efficient methodologies for image restoration, segmentation, super-resolution, and analysis is therefore a crucial and demanding task. This Minisymposium aims to explore the critical role of mathematical modeling, computational methods, and statistical analysis in addressing key challenges in modern astronomy. One of the central issues in astronomical imaging is the reconstruction and interpretation of indirect or incomplete observations, as seen, for example, in solar X-ray imaging. Advanced mathematical techniques, such as inverse problems, compressed sensing, and machine learning, offer powerful tools to extract meaningful information from noisy or sparse data. Additionally, new methods in data assimilation, numerical simulations, and topological data analysis provide innovative ways to study astrophysical structures and dynamics. This Minisymposium will bring together researchers from both the fields of mathematics and astronomy to discuss recent developments, exchange ideas, and foster collaborations. Topics of interest include, but are not limited to, novel approaches to image reconstruction and segmentation, deep learning applications in astrophysics, state-of-the-art interpolation techniques and PDE-based methods for the analysis of astrophysical data. By bridging these two disciplines, we aim to develop robust methodologies that enhance our ability to process and interpret astronomical data. This interdisciplinary approach will not only improve the accuracy of scientific results but also contribute to the design of next-generation telescopes and observational strategies. Ultimately, this Minisymposium seeks to highlight how mathematical innovations can propel our understanding of the universe forward, ensuring that we make the most of the unprecedented opportunities provided by modern astronomical observations.