Cross-Sector Cascade Resilience Under Quantum Threats: Multilayer Network Theorems and Stress-Testing Algorithms

Abstract: Cascade failures increasingly connect sectors that were once analyzed in isolation—power, finance, health, transport, water, and digital infrastructure— while emerging quantum capabilities reshape the threat landscape through accelerated cryptanalysis, novel sensing, and optimization at scale. This manuscript develops an integrated academic framework for cross-sector cascade resilience under quantum threats by unifying multilayer network theorems with stress-testing algorithms and governance-oriented evaluation designs. The central argument is that resilience is not a single metric but a portfolio of properties—robustness, recoverability, adaptability, and legitimacy—whose trade-offs must be made explicit in research design and in operational decision rules. Across five chapters, the book formalizes uncertainty-aware modeling assumptions, connects explanatory and causal inference strategies to policy-grade claims, and distinguishes predictive generalization from trustworthiness in machine learning pipelines. It then positions reproducibility and MLOps as the mechanisms by which analytic insights become durable institutional capabilities, and it concludes with sectoral horizons that translate theory into governance artifacts, auditing protocols, and stress-test playbooks usable across South Asia, Europe, Africa, and the Americas. The result is a methodologically disciplined blueprint for researchers, practitioners, and policymakers seeking defensible resilience interventions in the quantum transition. Keywords cascade resilience, quantum threats, multilayer networks, interdependent infrastructure, systemic risk, stress testing, uncertainty quantification, causal inference, counterfactual analysis, trustworthy machine learning, generalization, robustness, reproducibility, MLOps, governance, auditability, risk metrics, scenario design, policy evaluation, resilience engineering