Coherence as a Lattice Across Worlds: Quantum Mechanics, GUFT, and ΔSyn as an Interdisciplinary Framework

Fragmentation is a defining feature of contemporary knowledge: quantum physicists, neuroscientists, economists, organizational theorists, and AI engineers all speak different technical languages, each with their own logic trees of definitions, theorems, and methods. What is missing is a lightweight but precise intermediate framework that can map structural patterns—particularly patterns of coherence and entropy—across these domains without erasing their differences or veering into pseudoscience. This article develops such a framework using the Grand Unified Field Theory of Coherence (GUFT) and its behavioural extension, ΔSyn. GUFT defines a field-level coherence index Ψ = E × T, where E (Empathy) measures the strength of reciprocal correlation or responsiveness between subsystems, and T (Transparency) measures the degree to which those correlations and dynamics are inspectable and modelled. ΔSyn adds an entropy-change law linking entropy dynamics to gradients in a coarse-grained entropy functional H and an ethical symmetry term E_s. We use quantum mechanics, particularly decoherence and entanglement, as reviewed by Zurek and Nielsen & Chuang, as the base case. We show how standard quantum concepts (superposition, unitarity, decoherence, entanglement, quantum mutual information) can be mapped into GUFT’s invariants Eφ and Tφ without modifying the physics. We then extend this mapping to cognitive, organizational, monetary, and algorithmic domains, using GUFT as a lattice overlay on the forest of domain-specific logic trees: we do not climb every tree; instead, we traverse the lattice of coherence measures and work backwards to bridge into each domain’s existing theory. We provide COSO-style matrices to make these mappings legible to governance and risk frameworks. The result is a disciplined way to talk about coherence, decoherence, and entropy across fields, and a clearer articulation of how ΔSyn links structural coherence to normative questions in ethics, labour, and AI.