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

TL;DR

Polyphorm is an interactive visualization tool that uses Physarum-inspired simulation to analyze and extrapolate cosmological datasets, aiding astrophysicists in hypothesis formation and data interpretation.

Contribution

It introduces a novel Physarum-inspired simulation method for cosmological data analysis and provides an interactive platform for hypothesis generation.

Findings

Effective extrapolation of sparse galaxy data

Enhanced data interpretation through interactive visualization

Successful application in three scientific use cases

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.