arXiv:2606.08258v1 Announce Type: cross Abstract: Understanding and comparing structures in scalar fields is a central challenge in scientific visualization, with applications ranging from feature analysis to temporal and structural comparison. The Morse-Smale (MS) complex provides a natural representation by decomposing a scalar field into regions induced by gradient flow. However, existing approaches typically rely on graph-based representations, capturing relationships between critical points while discarding region-level structure. In this work, we represent the MS complex as a hypergraph,
This research is published as AI and scientific visualization continue to advance, necessitating more sophisticated methods for data analysis and comparison.
Improved methods for comparing complex data structures could enhance feature analysis and temporal comparisons across various scientific domains, potentially accelerating research and development.
The proposed 'MS-COOT' method offers a new way to represent and compare Morse-Smale complexes, moving beyond traditional graph-based approaches by utilizing a hypergraph representation.
- · Scientific visualization researchers
- · Data scientists
- · AI/ML model developers
More precise comparison of scalar field structures in scientific data becomes possible.
This could lead to faster insights in fields like materials science, climate modeling, or medical imaging.
New tools and software might emerge that leverage hypergraph-based representations for complex data analysis, influencing advanced AI applications.
This signal links to a primary source. Continuum Brief monitors and indexes it as part of the live intelligence stream — we do not republish source content.
Read at arXiv cs.LG