Morphological computational capacity of Physarum polycephalum

Abstract

While computational capacity limits of the universe and carbon-based life have been estimated, a stricter bound for aneural organisms has not been established. Physarum polycephalum, a unicellular, multinucleated amoeba, is capable of complex problem-solving despite lacking neurons. By analyzing growth dynamics from high-throughput imaging data-more than 500 samples tracked every 30 minutes for one to three days-across two distinct Physarum strains under diverse biological conditions, we map morphological evolution to information processing. We revisit the Margolus-Levitin bound that constrains maximum computation rates, deriving a correction for these driven-dissipative living systems. Time-series data of Physarum's morphology-quantified through area, perimeter, circularity, and fractal dimension-enable the determination of upper bounds on the number of logical operations achievable through its hydromechanical, chemical, kinetic, and quantum-optical degrees of freedom. The time-series trends of these morphological quantities remain statistically robust across 100,000 bootstrap resamples at both 95% and 99.5% confidence intervals. Based on the organism's explored areas and characteristic values of ATP available for work, the computational capacity of Physarum is upper bounded by ${\sim}10^{33}$ logical operations in 24 hours, scaling linearly in the non-equilibrium steady state. This framework enables comparison of the computational capacities of life, exploiting either classical or quantum degrees of freedom.