Nathan M. Thornhill

Institute for Complexity Science and Advanced Computing

Nathan M. Thornhill is a complexity science researcher working in information theory, pattern persistence, AI, and neuroscience. His work circles one deceptively simple question: what separates the systems that persist from the ones that dissolve? His Existence Threshold framework attacks it through measurable information dynamics: integration, differentiation, and the balance between them.

Early work found the numbers. A persistence criterion sorted ten cellular automata without a miss, and crossing a dimensional boundary cost roughly 86% of a pattern's information, measured over 1,500 patterns and again in GPT-2 and Gemma-2. That figure is…

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