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This study establishes a rigorous upper bound for the computational capacity of *Physarum polycephalum*, an organism without neurons, by analyzing its morphological dynamics against fundamental physical limits like the Margolus-Levitin bound. The research quantifies how this slime mold processes information through hydromechanical, chemical, and potentially quantum-optical degrees of freedom, offering a new framework for comparing biological computation in non-equilibrium steady states.
Morphological computational capacity of Physarum polycephalum
arXiv:2510.19976v2 Announce Type: replace 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.
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.
Quantum Physics (quant-ph); Biological Physics (physics.bio-ph)
arXiv:2510.19976 [quant-ph]
(or arXiv:2510.19976v2 [quant-ph] for this version)
https://doi.org/10.48550/arXiv.2510.19976 Focus to learn more arXiv-issued DOI via DataCite
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