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Polyphorm: Structural Analysis of Cosmological Datasets via Interactive Physarum Polycephalum Visualization | | Oskar Elek
; Joseph N. Burchett
; J. Xavier Prochaska
; Angus G. Forbes
; | | Date: |
5 Sep 2020 | | Abstract: | 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. | | Source: | arXiv, 2009.02441 | | Services: | Forum | Review | PDF | Favorites | |
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