pyEDW

pyEDW runs Exo-Daisy World: a stochastic generalization of Watson & Lovelock’s Daisy World[1], tuned to M-dwarf exoplanets, together with the information-theoretic measures used to read off its information architecture. A planet of habitable fraction f is shared by black and white daisies whose albedos rein the surface temperature; the star’s luminosity drifts as an Ornstein–Uhlenbeck process[2], and because the thermal timescale is comparable to the stellar one the classic model’s instantaneous-equilibrium constraint is broken and the system becomes a genuine stochastic differential equation.

The library ships one environment class and a metrics module. ExoDaisyWorld is the coupled agent (daisies) + environment (temperature, luminosity) SDE, integrated with a strong-order-1 stochastic Runge–Kutta step; pyEDW.metrics turns an endpoint ensemble into viability and the information measures I(A:E), \(\Delta I\), and cooperation \(C(a_1{:}a_2\|E)\).

The model and its informational reading are in Sowinski, Ghoshal & Frank, Exo-Daisy World: Revisiting Gaia Theory through an Informational Architecture Perspective, Planet. Sci. J. 6, 176 (2025), doi:10.3847/PSJ/ade310[3]. If you’re new here, start with Getting started, take the model for a spin in the Applet, then read Theory for the equations. The library ports a set of MATLAB classes, whose interface it keeps.

Guide

Reference

Citing

Sowinski DR. pyEDW [computer software]. Version 0.1.0. 2026. Accessed July 21, 2026. https://github.com/EternalTime/pyEDW

@software{sowinski_pyedw,
  author  = {Sowinski, Damian R.},
  title   = {pyEDW: Exo-Daisy World stochastic simulator and information measures},
  year    = {2026},
  version = {0.1.0},
  url     = {https://github.com/EternalTime/pyEDW}
}

Indices and tables

References