Complexity and ultradiffusion

p-Adic mathematics and theoretical biology

The principal objective of this article is a brief overview of the main parts of p-adic mathematics, which have already had valuable applications and may have a significant impact in the near future on the further development of some fields of theoretical and mathematical biology. In particular, we present the basics of ultrametrics, p-adic numbers and p-adic analysis, as well as insight into their applications for modeling some cognitive processes, genetic code and protein dynamics. We also argue that ultrametric concepts and p-adic mathematics are natural tools for the viable description of biological systems and phenomena with a hierarchical structure.

Optimization by trees on simple adaptive landscapes

We evaluate the optimizing ability (rate of adaptation) of trees on simple adaptive landscapes. At points away from a peak, there is a strong negative relationship between rate of adaptation and tree precision P, a relationship that is independent of the size of the tree. P measures the variability among trial solutions generated by the tree: high precision trees have low variability, low precision trees have high variability. Near a peak, the situation reverses, with high precision trees showing higher rates of adaptation than low precision trees; however, for all trees, the absolute rate of adaptation is uniformly low. On multiple-peak landscapes, the probability of crossing an adaptive valley from a lower peak to a higher peak is also negatively correlated with tree precision. These results suggest that under a wide range of conditions, trees with low precision are, on average, the best optimizers.

The stability of ecosystems

Stability criteria and phase boundaries for complex ecosystems are obtained and contrasted with previously studied scenarios. The stability of such systems is determined by the behaviour of the largest eigenvalue of matrices governing the response of the system to small perturbations. As a result we show that ecosystems with unstructured cooperative interactions between arbitary species can be less stable than had been previously determined. We also examine hierarchical ecologies, and demonstrate their increased stability under certain conditions.