Structural Emergence of Intelligence (SEI) v1.1: Observational Mapping and Temporal Evolution of the Spatial Distribution of Intelligent Life

We present SEI v1. 1 (Structural Emergence of Intelligence), a minimal and falsifiable framework that predicts the spatial and temporal distribution of intelligent life in the universe based on structural differentiation. In SEI, intelligence is not treated as a biological accident, but as an emergent phenomenon arising from the self-referential stabilization of structured information under persistent differentiation. The framework is defined by three key variables: - structural density C (x, t) - information fixation rate Γ (x, t) - structural persistence dSC/dt Intelligence is proposed to emerge when these variables simultaneously exceed critical thresholds. In SEI v1. 0, this led to a direct spatial prediction: intelligent life is most likely to arise in intermediate structural regions of spiral galaxies, approximately within the range: 0. 3 < r / Rgalaxy < 0. 6 In SEI v1. 1, we introduce two major extensions: (1) Observational Mapping The spatial prediction is translated into a direct target selection strategy for technosignature searches. Instead of treating galaxies as observationally uniform, SEI restricts the search to structurally favorable regions, significantly reducing the effective search space. (2) Temporal Evolution The emergence band is not static, but shifts over cosmic time as galactic structure evolves. Early galaxies favor outer regions, intermediate galaxies match the v1. 0 prediction, and late-stage galaxies shift inward or narrow the emergence zone. These extensions establish a direct bridge between structural theory, observational strategy, and time-dependent intelligence emergence. SEI therefore provides: - a minimal structural definition of intelligence, - a testable spatial prediction, - an observational prioritization strategy, - a temporal evolution model of intelligence emergence. The framework is explicitly falsifiable if observed technosignatures do not follow the predicted spatial or temporal distributions. This work proposes that intelligence is neither random nor purely contingent, but structurally constrained in both space and time. A testable structural framework predicting where and when intelligence emerges in the universe