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

Oskar Elek, Joseph Burchett, Jason Prochaska, Angus Forbes

External link (DOI)
View presentation:2020-10-29T15:15:00ZGMT-0600Change your timezone on the schedule page
2020-10-29T15:15:00Z
Exemplar figure
This figure depicts the use of the Polyphorm software tool for interactive visualization and data reconstruction during an analysis of the Bolshoi-Planck cosmological simulation dataset, which consists of approximately 840,000 simulated dark matter halos spanning a region of 170 Mpc in each dimension. Here, the entire volume is split into 4 equally sized vertical slabs, each showing a different view that enables the analysis of dark matter filaments: (a) raw data points (red) and agents (white) of our Monte Carlo Physarum Machine (MCPM) reconstruction algorithm, (b) volumetric footprint of the data ('deposit', white) and the reconstructed Cosmic Web filament density field ('trace', purple), (c) density field of the reconstruction mapped using a heatmap color palette, and (d) the same density field, but now segmented instead into three intervals using an alternative color map (‘low' in blue, 'medium' in green, 'high' in red). The filament reconstruction and interactive visualization facilitates new insights into into the structure and composition of the Cosmic Web.
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Direct link to video on YouTube: https://youtu.be/V_JivWRFJKA

Keywords

Astrophysics visualization, agent-based modeling, intergalactic media, Physarum polycephalum, Cosmic Web.

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.