The Conscious Universe Hypothesis: Scale-Invariant Information Integration in Cosmic and Neural Networks

We present a comparative network-theoretic analysis of the universe’s large-scale structure and biological neural systems. Using publicly available galaxy survey data and human connectome networks, we demonstrate that both systems converge under identical information-integration invariants, including degree distributions, clustering coefficients, path-length scaling, and spectral measures such as algebraic connectivity.

Across more than 29 orders of magnitude in scale, these shared invariants suggest that integrated information is a scale-invariant property of sufficiently complex networks, independent of physical substrate. We do not claim anthropomorphic consciousness at cosmic scales; rather, we show that the universe satisfies necessary structural conditions associated with conscious systems in biology.

All methods are containerized for reproducibility, with cryptographic hash verification of inputs and outputs. The hypothesis is falsifiable and yields testable predictions for future cosmological observations and cross-scale network analyses.