Preprint Short Note Version 1 Preserved in Portico This version is not peer-reviewed

Optima and Simplicity in Nature

Version 1 : Received: 18 August 2022 / Approved: 18 August 2022 / Online: 18 August 2022 (03:51:21 CEST)

How to cite: Dingle, K. Optima and Simplicity in Nature. Preprints 2022, 2022080330. Dingle, K. Optima and Simplicity in Nature. Preprints 2022, 2022080330.


Why are simple, regular, and symmetric shapes common in nature? Many natural shapes arise as solutions to energy minimisation or other optimisation problems, but is there a general relation between optima and simple, regular shapes and geometries? Here we argue from algorithmic information theory that for objective functions common in nature --- based on physics and engineering laws --- optimal geometries will be simple, regular, and symmetric. Further, we derive a null model prediction that if a given geometry is an optimal solution for one natural objective function, then it is a priori more likely to be optimal or close to optimal for another objective function.


Optimisation; simplicity; Kolmogorov complexity; physics


Computer Science and Mathematics, Computer Science

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