Theoretical simulation study demonstrates that relational state formation constrained by local consistency enforces Tsirelson bounds, suggesting quantum correlations emerge from context.
Relational Formation and the Bell Bound investigates an alternative structural reading of Bell-type correlations. Rather than assuming that alternative measurement settings reveal values attributable to a single pre-existing complete state, the paper introduces a minimal Relational Formation Algebra (RFA) in which a definite relational state is formed under the realized context. The framework is developed through four stages, R0–R3, describing a pre-relational possibility space, contextual relational formation, intrinsic compatibility through composition, and subsequent observational projection. A further condition, R4 (local substructure consistency), requires globally context-dependent relational states to retain locally consistent marginal structure. Two reproducible blind numerical experiments explore the resulting correlation domain. An unrestricted R0–R3 ensemble produces Bell violations but also permits CHSH values above the Tsirelson bound. In a structured bipartite realization satisfying R4 to numerical precision, Bell violations remain common while none of 30,000 randomized trials exceeds 2√2. The paper then examines the corresponding binary, cross-compatible operator algebra and the elementary origin of the 2√2 norm bound. The proposal is not presented as a refutation of Bell’s theorem or CHSH, nor as an independent derivation of quantum mechanics. Instead, it asks whether the assumption of a pre-existing jointly attributable order can be replaced by a framework in which complete order is formed relationally while local consistency is retained. The conceptual distinction is summarized by the proposition: “Relation does not select an order. Relation forms the order.” The work includes the numerical parameters and fixed random seeds required to reproduce the reported simulations and references the original EPR (1935), Bell (1964), and CHSH (1969) papers. AI assistance: ChatGPT (OpenAI) was used as a collaborative tool for mathematical exploration, numerical simulation, structural analysis, and preparation of the manuscript. The conceptual direction, interpretation, selection of hypotheses, and responsibility for the published content remain with the human author.
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