The Monte Carlo Physarum Machine from UC Santa Cruz is a computational algorithm that accurately predicts cosmic web formation using slime mold growth patterns.


  • Improved accuracy
  • Improved predictability


  • Computer algorithms
  • Space exploration

UN Sustainable Development Goals Addressed

  • Goal 9: Industry Innovation & Infrastructure

The Challenge

The cosmic web connects galaxies together throughout the Universe. It occurred after the Big Bang, as the Universe was expanding and matter became distributed in a web-like network of interconnected filaments. Traditional representations of the cosmic web were created by computer simulations based on the distribution of matter, especially dark matter. Creating an accurate algorithm to predict cosmic web formation will allow us to map more distant galaxies, and eventually the whole Universe.

Innovation Details

The computer algorithm was inspired by the web-like networks a slime mold builds as it searches for food. The algorithm is based on the 2-dimensional Physarum model developed in 2010 by Jeff Jones. It has been modified to work in three dimensions and has been tested on a dataset of 37,000 galaxies from the Sloan Digital Sky Survey (SDSS), where it accurately replicated the results produced by dark matter-based algorithms. It has since been used to model a map of the cosmic web in the local Universe, within 100 million light-years of Earth.

Biological Model

The single-cell organism known as slime mold builds complex web-like filamentary networks in search of food, always finding near-optimal pathways to connect different locations, similar to cosmic webs found in outer space.