Uncertainty Visualization of 2D Morse Complex Ensembles Using Statistical Summary Maps

• Published in: IEEE transactions on visualization and computer graphics 2022-04, Vol.28 (4), p.1955-1966
• Main Authors: Athawale, Tushar M., Maljovec, Dan, Yan, Lin, Johnson, Chris R., Pascucci, Valerio, Wang, Bei
• Format: Article
• Language: English
• Subjects: Color; Computer Science; Data visualization; Eddy simulation; Entropy; Gradient flow; Morse complexes; Probabilistic logic; Scalars; Scientific visualization; Statistical analysis; topological data analysis; Topology; Two dimensional displays; Uncertainty; uncertainty visualization; Visualization
• ISSN: 1077-2626; 1941-0506; 1941-0506
• DOI: 10.1109/TVCG.2020.3022359

Morse complexes are gradient-based topological descriptors with close connections to Morse theory. They are widely applicable in scientific visualization as they serve as important abstractions for gaining insights into the topology of scalar fields. Data uncertainty inherent to scalar fields due to randomness in their acquisition and processing, however, limits our understanding of Morse complexes as structural abstractions. We, therefore, explore uncertainty visualization of an ensemble of 2D Morse complexes that arises from scalar fields coupled with data uncertainty. We propose several statistical summary maps as new entities for quantifying structural variations and visualizing positional uncertainties of Morse complexes in ensembles. Specifically, we introduce three types of statistical summary maps - the probabilistic map , the significance map , and the survival map - to characterize the uncertain behaviors of gradient flows. We demonstrate the utility of our proposed approach using wind, flow, and ocean eddy simulation datasets.