EPINOVA Research Signals

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The U.S.–Iran War and East Asia’s Next Strategic Test:

Why the Middle East Conflict May Reshape Risk in the Western Pacific

This policy brief argues that the U.S.–Iran war could reshape deterrence dynamics beyond the Middle East by straining U.S. assets, alliance decision space, and perceptions of American resolve. It identifies East Asia as the most plausible next strategic test, with a Taiwan-centered coercive crisis as the most likely serious pathway, the South China Sea as the most likely limited-clash pathway, and the Korean Peninsula as the fastest escalation theater. Based on qualitative analysis of open-source materials, the brief contributes to research on strategic risk, alliance strain, and cross-regional deterrence under missile-intensive conflict conditions. 

The Global Strategic Chain Reactions of the U.S.–Iran War:

East Asia as the Next Plausible Capability-Revealing Theater

This working paper argues that the U.S.–Iran war should be understood not only as a regional conflict, but also as a source of wider strategic chain reactions across other theaters. It identifies East Asia as the most plausible next capability-revealing theater and assesses Taiwan-centered coercive confrontation as the most likely pathway. The paper contributes to the study of strategic risk, alliance strain, and AI-mediated conflict by examining how contemporary wars reveal the limits of military power and multi-theater coherence under operational stress. 

Escalation Dynamics in IRGC’s Operation True Promise: 

Interpreting the Conflict through an Escalation Ladder Framework

This policy brief analyzes escalation dynamics in the U.S.–Israel–Iran confrontation using an escalation ladder framework derived from IRGC Operation True Promise. The framework identifies nine escalation levels from shadow competition to potential large-scale ground conflict. Current indicators suggest the conflict lies between Levels 4 and 6, marked by sustained missile–UAV exchanges and maritime spillover. The study argues that escalation risk is driven less by average strike intensity than by the cumulative probability of threshold-crossing events involving critical strategic nodes. 

Escalation Risk in Protracted Missile Exchanges: 

Assessing Low-Probability, High-Impact Dynamics in the U.S.–Israel–Iran Conflict Based on IRGC Operation True Promise 4 (Waves 1–13)

This policy brief analyzes escalation risk in protracted missile exchanges using a probabilistic accumulation framework, with IRGC Operation True Promise 4 (Waves 1–13) as a bounded case. Drawing on open-source reporting and scenario-based cost modeling, it examines launch tempo, interception effectiveness, critical-node exposure, and political reaction multipliers. The study argues that escalation risk stems less from average strike performance than from the cumulative probability of a single high-impact event. Findings indicate the conflict remains contained but structurally unstable under sustained high-tempo conditions. 

Assessing AI Capabilities Across Six Major Countries and Economic Blocs: An Eight-Dimensional Comparative Framework

This policy brief evaluates AI capabilities across six major countries and economic blocs using an eight-dimensional comparative framework. In addition to traditional structural metrics, such as compute, models, data, industry, chips, and military integration, it incorporates Domestic Task Competence (DTC) and Foreign Task Competence (FTC) to assess real-world execution capacity. The findings suggest that sustainable AI competitiveness depends not only on frontier innovation but also on institutional integration, cross-border operability, and semiconductor resilience.

Lifecycle Cost Parity Between Human Personnel and AI-Enabled Systems: 

Implications for U.S. and Chinese Force Structure Transition (2026–2060)

This policy brief analyzes when AI-enabled military systems reach lifecycle cost parity with human personnel in the United States and China across major services (2026–2060). Findings show earlier crossover in most U.S. roles due to higher personnel liabilities, with China following under different industrial conditions. Information and maintenance roles transition first, maneuver forces in the 2030s, while strategic domains remain human-anchored into the 2040s–2050s. 

The Fiscal Implications of Recent U.S. Force Posture Adjustments in the Middle East: 

An Event-Driven Estimate (Jan 26 – Feb 15, 2026)

This policy brief presents an event-driven estimate of the incremental fiscal impact of recent U.S. force posture adjustments in the Middle East (Jan 26–Feb 15, 2026). Using publicly reported milestones and open-source cost anchors, it models surge-only expenditures at an estimated USD 0.25–0.58 billion, enhancing fiscal transparency in escalation scenarios. 

Derivative-State Drift: 

A Continuous-Time Model of Constraint Erosion in Elite and Artificial Optimization Systems

This paper introduces the Derivative-State Drift (DSD) framework, a continuous-time model explaining structural constraint erosion in both elite institutional systems and artificial optimization architectures. It demonstrates how derivative-based decision rules under soft enforcement conditions generate cumulative misalignment through endogenous threshold decay. The framework offers a unified analytical account of elite moral deformation and AI alignment failure dynamics.

Where Data Centers Get Built?

Institutional Friction and the Spatial Logic of Compute Infrastructure in the United States

This policy brief analyzes U.S. data center development through institutional feasibility, arguing that large-scale compute infrastructure is built where governance capacity, permitting, and utility coordination enable low-friction deployment. It introduces the Infrastructure Friction Boundary (IFB) to diagnose such jurisdictions and highlights governance risks including energy lock-in and infrastructure–governance asymmetry. 

Why the South?

Institutional Friction and the Spatial Reorganization of Data Center Infrastructure in the United States

This working paper examines the spatial reorganization of U.S. data center infrastructure in the AI and hyperscale era. Contrary to explanations emphasizing agglomeration, energy costs, or fiscal incentives, recent expansion has concentrated in the American South and interior regions. The paper advances an institutional feasibility framework and introduces the Infrastructure Friction Boundary (IFB) to explain corridor-based expansion patterns. 

When AI Infrastructure Is Optional but Governance Lock-In Is Not: 

An AI-SNI Local Governance Diagnostic of the Temple (GA) Data Center Proposal

This working paper applies the AI-Strategic Node Index (AI-SNI) to assess whether a proposed large-scale data center constitutes a structurally necessary node within AI-mediated systems. Using the Temple, Georgia “Project Bus” case, the analysis finds that the facility does not meet criteria for structural necessity or non-substitutability under current evidence, and primarily introduces governance burden and long-term path-dependency risk. 

Governing Structural Centrality: 

Greenland as an AI-Strategic Node under the AI-SNI Framework

This policy brief applies the AI-Strategic Node Index (AI-SNI) to examine Greenland as a structurally significant node in Arctic great-power interaction. AI-SNI diagnostics place Greenland in a Tier 3 exposure regime, reflecting high sensing and decision-loop centrality and latent optionality, constrained primarily by infrastructure–governance asymmetry. Designed for Track-2 dialogue, the brief is diagnostic and non-prescriptive.