Polyphorm: Structural Analysis of Cosmological Datasets via Interactive Physarum Polycephalum Visualization

This paper introduces Polyphorm, an interactive visualization and model fitting tool that provides a novel approach for investigating cosmological datasets. Through a fast computational simulation method inspired by the behavior of Physarum polycephalum, an unicellular slime mold organism that effic...

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Bibliographic Details
Published in:IEEE transactions on visualization and computer graphics 2021-02, Vol.27 (2), p.806-816
Main Authors: Elek, Oskar, Burchett, Joseph N., Prochaska, J. Xavier, Forbes, Angus G.
Format: Article
Language:English
Subjects:
agent-based modeling
Analytical models
Astrophysics visualization
Computational modeling
Computer Graphics
Computer Simulation
Cosmic Web
Data models
Data visualization
Datasets
Galaxies
Hubble Space Telescope
intergalactic media
Nutrients
Physarum polycephalum
Simulation
Sky surveys (astronomy)
Slime
Space telescopes
Structural analysis
Task analysis
Three-dimensional displays
Visualization
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Summary:This paper introduces Polyphorm, an interactive visualization and model fitting tool that provides a novel approach for investigating cosmological datasets. Through a fast computational simulation method inspired by the behavior of Physarum polycephalum, an unicellular slime mold organism that efficiently forages for nutrients, astrophysicists are able to extrapolate from sparse datasets, such as galaxy maps archived in the Sloan Digital Sky Survey, and then use these extrapolations to inform analyses of a wide range of other data, such as spectroscopic observations captured by the Hubble Space Telescope. Researchers can interactively update the simulation by adjusting model parameters, and then investigate the resulting visual output to form hypotheses about the data. We describe details of Polyphorm's simulation model and its interaction and visualization modalities, and we evaluate Polyphorm through three scientific use cases that demonstrate the effectiveness of our approach.
ISSN:1077-2626
1941-0506
DOI:10.1109/TVCG.2020.3030407