On the algorithmic behaviour of complex physical systems

TL;DR

This paper explores the idea that natural processes are driven by underlying algorithms, demonstrating this through examples of oxidation complexity and shape-memory alloy deformations exhibiting LIFO behavior.

Contribution

It introduces a novel perspective that natural phenomena can be understood as computational processes with intrinsic optimization mechanisms.

Findings

Oxidation processes analyzed through algorithm complexity.

Shape-memory alloy deformations exhibit LIFO behavior.

Natural systems may operate as self-optimizing computational entities.

Abstract

Starting from the idea that the underlying mechanisms driving the observable processes in nature are algorithmic, we exemplify this in two ways: nature works as a computing machine and thus the processes running on it optimize themselves in an intrinsic manner so as to save time. As a first example we will place the empirical analysis of oxidation in the context of algorithm complexity analysis. Second, we will show that deformations suffered by a shape-memory alloy may be produced by nature showing a LIFO (Last In First Out) behaviour.