Topological analytics for large-scale scientific dataMS16

This talk presents the application of a discrete topological framework for the representation and analysis of large-scale scientific data. The inherent robustness of the approach allows addressing effectively the high complexity of the feature extraction and tracking of high-resolution scientific data. This approach has enabled the successful analysis of several massively parallel simulations including turbulent hydrodynamic instabilities, porous material under stress, energy transport of eddies in ocean data, and lifted flames for clean energy production.

This presentation is part of Minisymposium “MS16 - Topological Image Analysis: Methods, Algorithms, Applications (3 parts)
organized by: Patrizio Frosini (University of Bologna) , Massimo Ferri (University of Bologna) , Claudia Landi (University of Modena and Reggio Emilia) .

Valerio Pascucci (University of Utah)
discrete morse theory, feature extraction and tracking, scientific data analysis, visualization