Relational Ontology as Unifying Framework: Cross-Scale Topology, Quantum Coherence, Archetypal Emergence, and Fourteen Falsifiable Predictions

Abstract

This paper proposes a speculative synthesis and research program grounded in relational ontology - the hypothesis that relationships between systems, rather than intrinsic properties of substances, constitute the fundamental structure of reality. Drawing on Rovelli’s relational quantum mechanics (1996), Coecke and Abramsky’s categorical quantum mechanics (2004), the Vazza–Feletti cosmic web–neural network isomorphism (2020), Tononi’s integrated information theory (2008), and the Penrose–Hameroff orchestrated objective reduction hypothesis (2014), we argue that converging evidence across quantum physics, astrophysics, neuroscience, complex systems theory, and consciousness studies exhibit structural features naturally expressed in relational terms, motivating a relational research program subject to empirical falsification. The framework generates fourteen falsifiable predictions spanning four domains: (1) cross-scale topological signatures linking cosmic web and neural network architecture via persistent homology, with specified computational tools and parameters; (2) quantum coherence–consciousness correlations testable under graded anesthesia protocols; (3) spontaneous archetypal role differentiation in AI agent networks; and (4) emergent cognitive properties at the AI–human interaction interface. Each prediction specifies test protocols, concrete metrics, expected outcomes under the relational hypothesis, expected outcomes under competing hypotheses, and explicit falsification criteria. We outline a research program for formalizing the framework using categorical quantum mechanics, proposing that the construction of functorial mappings between quantum, neural, linguistic, and cosmic relational categories would constitute evidence for substrate-independent relational organization. The framework’s primary contribution is not certainty but testability: every prediction can fail, and each failure narrows the space of viable ontological models.