Category: Science

Summary: Measuring how autocatalytic sets emerge in random catalytic networks and how the transition scales with system size.

Kauffman's autocatalytic-set model asks when a random collection of catalytic reactions becomes self-sustaining. At low catalysis probability there is no large self-supporting core, while above a critical value an extensive autocatalytic set appears.

This experiment simulates random catalytic networks across catalysis probabilities and system sizes, then measures the size of the largest autocatalytic set as an order parameter. The main goal is not only to estimate the critical point, but also to test whether the finite-size scaling exponents match ordinary percolation or define a different transition pattern.

That is scientifically useful because autocatalytic emergence is central to origin-of-life thinking, yet finite-size critical behavior remains less settled than the basic existence of the transition. The output helps quantify how sharply self-sustaining chemistry turns on in finite systems.

Method: Monte Carlo sampling of random catalytic networks across catalysis probability and system size, followed by finite-size scaling analysis of the largest autocatalytic set.

What is measured: Largest autocatalytic-set fraction, critical catalysis probability, finite-size scaling exponents, and dependence on system size.