The Theory of the Universal Attention Field: A Unified Framework for Interaction

This paper introduces the Theory of the Universal Attention Field. Building on process philosophy (e.g., Whitehead) and relational physics (e.g., Rovelli), it adopts the view that reality is dynamically constituted by interactions rather than static, independent entities. We posit as a central axiom that any interaction transforms abstract potential data (undifferentiated, pre-metric possibilities) into concrete, manifested information (a defined, relational state). This is inspired by information-theoretic insights, re-contextualized here as a universal principle independent of consciousness. Rather than merely describing intra-interaction processes, the theory focuses on the prerequisites for interaction to occur at all. Its core contribution is a rigorous conceptualization of demeasurement (at) as the necessary counterpart to measurement (bt). Demeasurement is not a passive reversion to potential but an active, non-metric 'referential background' (relational openness) that enables any distinction, and thus any measurement. We formalize this within an axiomatic system and model it with Soft Logic. From this framework, a super-equation, Δ†, is derived to quantitatively model the measurement–demeasurement dynamic. The validity and utility of this theory are demonstrated through a multi-pronged approach: (1) The core principles are illustrated via formal case studies that clarify the role of demeasurement as the enabling condition for observation. (2) The super-equation is shown to successfully and consistently model results from simulations across sixteen disparate phenomena—from quantum entanglement and neural activity to classical mechanics, epidemic dynamics, nonlinear chaos, and phase transitions—demonstrating its potential as a unifying framework. A formal mapping protocol (Definition 5.1) is introduced that provides a reproducible procedure for applying the theory to new domains. (3) Five explicit falsifiability tests are formulated and passed, including out-of-sample validations on the 2D Ising model, site percolation, an SIR epidemic model, and the logistic map—four domains that played no role in parameter calibration. We report both successful and failed mapping attempts transparently, demonstrating that the theory discriminates between correct and incorrect physical proxies. (4) A practical optimizer (Mobiu-Q) derived from the theory achieves a 100% win rate across 23 optimization domains, with a controlled ablation study proving that the nilpotent property ε²=0 is necessary, not merely convenient. Ultimately, the Theory of the Universal Attention Field offers a unified, rigorous, and empirically testable lens for understanding systemic change and the very nature of interaction.