Integrated Information Theory: Consciousness as Mathematical Causal Power — E8 Intelligence Research

FINDING: IIT formalizes consciousness as integrated information Φ, computed via system partitioning and effective information — a purely mathematical quantity, not a substance. | MATH: Φ = min over partitions of (effective information), where effective information = H(X0|MIP) — entropy reduction over the minimum information partition; IIT 3.0/4.0 uses causal power (cause-effect repertoires) with state-space geometry; PyPhi implements exact Φ computation for small systems; no closed-form constant emerges — Φ is system-dependent, discrete, and scales with network complexity. | CONNECTION: The state-space geometry of IIT invokes a "qualia space" with a metric (Earth mover's distance) — this is a lattice-like structure (the power set of system states) with a distance function, but no golden-ratio or base-60 harmonics appear in the formalism; the only ratio-like feature is the threshold for consciousness (Φ > 0), which is binary, not continuous. | DEPTH: 6 — mathematically rigorous and fals Author: Andrew Stewart Caldin, Independent Researcher, UK. Part of the E8 Intelligence Research series. Platform: e8intelligence.com

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-10-14
DOI
https://doi.org/10.5281/zenodo.23358364
Primary Topic
Philosophy and Theoretical Science
Type
preprint
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Integrated Information Theory: Consciousness as Mathematical Causal Power — E8 Intelligence Research

Andrew Stewart Caldin
Zenodo (CERN European Organization for Nuclear Research)
Philosophy and Theoretical Science
preprint

Integrated Information Theory: Consciousness as Mathematical Causal Power — E8 Intelligence Research

Andrew Stewart Caldin
preprint en

Abstract

FINDING: IIT formalizes consciousness as integrated information Φ, computed via system partitioning and effective information — a purely mathematical quantity, not a substance. | MATH: Φ = min over partitions of (effective information), where effective information = H(X0|MIP) — entropy reduction over the minimum information partition; IIT 3.0/4.0 uses causal power (cause-effect repertoires) with state-space geometry; PyPhi implements exact Φ computation for small systems; no closed-form constant emerges — Φ is system-dependent, discrete, and scales with network complexity. | CONNECTION: The state-space geometry of IIT invokes a "qualia space" with a metric (Earth mover's distance) — this is a lattice-like structure (the power set of system states) with a distance function, but no golden-ratio or base-60 harmonics appear in the formalism; the only ratio-like feature is the threshold for consciousness (Φ > 0), which is binary, not continuous. | DEPTH: 6 — mathematically rigorous and fals Author: Andrew Stewart Caldin, Independent Researcher, UK. Part of the E8 Intelligence Research series. Platform: e8intelligence.com

Zenodo (CERN European Organization for Nuclear Research)
Philosophy and Theoretical Science
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