A Physical Theory of National Resilience

This dataset contains all synthetic and processed empirical data, along with the core Python code, necessary to fully replicate every key finding and figure​ in the manuscript “A Physical Theory of National Resilience” (submitted to Nature Communications). The repository serves as the complete, auditable computational backbone of the theory. It enables independent verification of both the theoretical framework​ (phase diagrams, synthetic trajectories) and its empirical validation​ (pre-crisis early-warning signals). Core Contents: generate_nrs_dataset.py: Implements the stochastic differential equations of the National Resilience Surplus (NRS) theory. Generates the global synthetic dataset (2000-2023) for the Sovereignty Strength Index (SSI), Wealth-Guardian Entropy (H_g), and the Resilience Surplus (W) and its dynamic derivatives (W′, W′′). This data underpins the SSI-H_g Diagnostic Phase Diagram (Fig. 2)​ and the synthetic nation trajectory plots (Fig. 3). analysis_fig4.py: Contains the code to reproduce the empirical analysis of the 2008 financial crisis (Fig. 4). It processes real-world data to calculate the acceleration (W′′) of U.S. household debt-to-GDP and the S&P 500 index, demonstrating the synchronized “silent deceleration” prior to the collapse. Corresponding processed data files for all figures are included in the data/directory. This is the archival, versioned release under the Global Thought Laboratory Protocol, ensuring full transparency and reproducibility. The active development repository, featuring continuous updates and expanded diagnostic tools, is available on GitHub: [https://github.com/NRS-Research/NRS-Framework].