On the Algorithmic Nature of the World

TL;DR

This paper investigates whether the world is fundamentally algorithmic by comparing real-world data distributions with those generated by abstract computational models, using a novel statistical approach based on algorithmic complexity.

Contribution

It introduces a new test leveraging algorithmic complexity theory and applies it to compare physical data with algorithmic data, providing evidence for or against the world's algorithmic nature.

Findings

Statistical correlations found between physical data and algorithmic models.

Evidence supports the hypothesis that the world exhibits algorithmic patterns.

Method demonstrates potential for analyzing the computational nature of physical phenomena.

Abstract

We propose a test based on the theory of algorithmic complexity and an experimental evaluation of Levin's universal distribution to identify evidence in support of or in contravention of the claim that the world is algorithmic in nature. To this end we have undertaken a statistical comparison of the frequency distributions of data from physical sources on the one hand--repositories of information such as images, data stored in a hard drive, computer programs and DNA sequences--and the frequency distributions generated by purely algorithmic means on the other--by running abstract computing devices such as Turing machines, cellular automata and Post Tag systems. Statistical correlations were found and their significance measured.