Beyond Entropy Magnitude: Directional Symmetry Breaking, Temporal Memory, and Entropy Production Rate as Early Warning Signals in Complex System Collapse

The Kerimov-Alekberli (KA) framework [Karimov and Alekberli, 2026] detects imminent collapse in complex systems by monitoring KL-divergence accumulation relative to a stable reference distribution via a rst-passage time (FPT) trigger. Prior work established that incorporating directional asymmetry accelerates detection fourfold. The present paper extends the KA model with three additional structural components: (1) directional asymmetry A(t); (2) temporal memory M(t) via lag-1 autocorrelation deviation; and (3) a symmetrized entropy production rate proxy ˆσ(t). A multi-scale detection architecture is introduced, separating wide-window (Φ, WΦ = 40) and narrow-window (A, ˆσ, Wfast = 12) components to ensure mechanistic independence. Monte Carlo validation across three collapse scenarios (N = 200 each, FAR = 5%) yields scenario-dependent gains: 15.9×in Hopf bifurcation, 1.02×in 3-phase drift, 0.98×in TAR model. A 300-sample Dirichlet weight search identies optimal weights w∗ = [Φ : 0.220, A : 0.425, M : 0.269,ˆσ : 0.086], with default weights achieving 98.7% of optimal. Ablation study conrms M(t) provides the largest marginal gain (+41.1 steps in Hopf). Phase-randomized surrogate testing conrms the Hopf memory gain is not a calibration artifact (Mann-Whitney p < 0.0001, rank-biserial r = 0.952). Bootstrap 95% CI for composite lead time: [50.1, 59.3] steps. Cohen's d = 2.65 (very large) for the memory extension. Empirically-calibrated real-domain validation demonstrates: BTC ash crash composite achieves 24.7 days lead (1.08×, 100% DR); ICU sepsis onset composite achieves 12.1 hours lead (+2.0 h absolute gain, 82% DR). The central nding is that gain is mechanism-dependent: memory M(t) is most valuable in oscillatory/CSD systems; KL divergence is near-sucient for distributional-shift collapses. The EPRproxy ˆσ(t) is grounded as a symmetrized KL rate with O(∆t) relative error to true Onsager EPR.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-05-11
DOI
https://doi.org/10.5281/zenodo.20115804
Primary Topic
Earthquake Detection and Analysis
Type
preprint
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preprint

Beyond Entropy Magnitude: Directional Symmetry Breaking, Temporal Memory, and Entropy Production Rate as Early Warning Signals in Complex System Collapse

Rahid Alekberli, Hikmat Karimov
Zenodo (CERN European Organization for Nuclear Research)
Earthquake Detection and Analysis
preprint

Beyond Entropy Magnitude: Directional Symmetry Breaking, Temporal Memory, and Entropy Production Rate as Early Warning Signals in Complex System Collapse

Rahid Alekberli, Hikmat Karimov
preprint en

Abstract

The Kerimov-Alekberli (KA) framework [Karimov and Alekberli, 2026] detects imminent collapse in complex systems by monitoring KL-divergence accumulation relative to a stable reference distribution via a rst-passage time (FPT) trigger. Prior work established that incorporating directional asymmetry accelerates detection fourfold. The present paper extends the KA model with three additional structural components: (1) directional asymmetry A(t); (2) temporal memory M(t) via lag-1 autocorrelation deviation; and (3) a symmetrized entropy production rate proxy ˆσ(t). A multi-scale detection architecture is introduced, separating wide-window (Φ, WΦ = 40) and narrow-window (A, ˆσ, Wfast = 12) components to ensure mechanistic independence. Monte Carlo validation across three collapse scenarios (N = 200 each, FAR = 5%) yields scenario-dependent gains: 15.9×in Hopf bifurcation, 1.02×in 3-phase drift, 0.98×in TAR model. A 300-sample Dirichlet weight search identies optimal weights w∗ = [Φ : 0.220, A : 0.425, M : 0.269,ˆσ : 0.086], with default weights achieving 98.7% of optimal. Ablation study conrms M(t) provides the largest marginal gain (+41.1 steps in Hopf). Phase-randomized surrogate testing conrms the Hopf memory gain is not a calibration artifact (Mann-Whitney p < 0.0001, rank-biserial r = 0.952). Bootstrap 95% CI for composite lead time: [50.1, 59.3] steps. Cohen's d = 2.65 (very large) for the memory extension. Empirically-calibrated real-domain validation demonstrates: BTC ash crash composite achieves 24.7 days lead (1.08×, 100% DR); ICU sepsis onset composite achieves 12.1 hours lead (+2.0 h absolute gain, 82% DR). The central nding is that gain is mechanism-dependent: memory M(t) is most valuable in oscillatory/CSD systems; KL divergence is near-sucient for distributional-shift collapses. The EPRproxy ˆσ(t) is grounded as a symmetrized KL rate with O(∆t) relative error to true Onsager EPR.

Zenodo (CERN European Organization for Nuclear Research)
Azerbaijan Technical University (AZ)
Earthquake Detection and Analysis
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Beyond Entropy Magnitude: Directional Symmetry Breaking, Temporal Memory, and Entropy Production Rate as Early Warning Signals in Complex System Collapse — Rahid Alekberli, Hikmat Karimov · Zenodo (CERN European Organization for Nuclear Research) (2026) | TGRS Research Map | TGRS