Causal Entropy Divergence as an Early Warning Signal for Critical Infrastructure Failure - The Karimov-Alekberli Framework

Critical infrastructure systems -- power grids, water networks, transportation -- exhibit phase-transition behaviour prior to catastrophic failure. We introduce the Karimov-Alekberli (KA) framework: a thermodynamic early-warning system monitoring the Causal Entropic Response (CER), defined as the deviation of per-channel sliding-window entropy (Freedman-Diaconis binning) from an adaptive exponentially weighted moving-average (EWMA) baseline, combined with a cross-channel structural coupling covariance term. We state Proposition 1 (Entropy Divergence Precedes Failure) with a proof sketch; the full formal proof is deferred to Appendix B. Synthetic validation on the IEEE 39-bus cascade benchmark (50 Monte Carlo trials, reproducible seeds) yields: median lead time 22 steps (IQR 21-23) before visible state deterioration; detection rate 100%; false positive rate 6% at persistence k=3. An ablation study establishes the structural necessity of the coupling term: removing it (=0) collapses detection rate from 100% to 2%. Variance-based detection completely fails on this coupling-driven cascade type (DR = 0%), a genuine negative result establishing failure-mode specificity. CSD autocorrelation achieves comparable lead time (22 steps, DR = 98%) but at 62% FPR. The Granger causality connection is stated as a conceptual motivation, not a formal derivation. This position paper invites empirical replication on real SCADA/PMU data (ERCOT, ENTSO-E, NREL Wind Toolkit)