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EPINOVA Research Signals

Daily Official Communication Outputs During the First Week of the 2026 U.S.–Israel–Iran War (February 28–March 6, 2026)


Working Paper | EPINOVA–WP–F–2026–04 

Losing the Narrative:

Communication Tempo, Expectation Asymmetry, and Perception Effects in the First Week of the 2026 U.S.–Israel–Iran War

    Research Updates

    Policy Brief | EPINOVA–2026–PB–12

    Narrative Underperformance in the First Week of the U.S.–Israel–Iran War


    This policy brief examines information competition during the first week of the 2026 U.S.–Israel–Iran war. Despite substantial U.S. communication activity, differences in communication tempo, narrative continuity, media-format compatibility, and expectation dynamics shaped perceptions of momentum. A best-effort estimate suggests visible communication tempo approximated 1.2 : 1 : 2.1 (United States : Israel : Iran), highlighting the advantage of continuous, feed-compatible messaging in early-stage conflicts. 

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    Working Paper | EPINOVA–WP–F–2026–04

    Losing the Narrative:

    Communication Tempo, Expectation Asymmetry, and Perception Effects in the First Week of the 2026 U.S.–Israel–Iran War


    This working paper analyzes why the United States appeared to lose narrative momentum in the information environment during the first week of the 2026 U.S.–Israel–Iran war despite contested battlefield outcomes. Using a best-effort estimate of visible official communication outputs (Feb 28–Mar 6, 2026), it argues that differences in disclosure tempo, narrative continuity, media-format compatibility, and expectation asymmetry significantly shaped early-phase perception dynamics. 

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    Policy Brief | EPINOVA–2026–PB–11

    The First Week of the U.S.–Israel–Iran War:

    Battlefield Assessment and Next-Phase Risks


    This policy brief assesses the first seven days of the 2026 U.S.–Israel–Iran war. It argues that the conflict has moved beyond the level of a limited punitive exchange but remains below the threshold of full-scale regional war. The central finding is that the war has entered an unstable intermediate condition characterized by sustained missile-UAV exchange, widening maritime and economic spillover, and growing allied operational integration. The brief finds that the most important driver of next-phase escalation is not average strike performance, but the risk of a threshold-crossing event, including a successful strike on a critical node, a major civilian-casualty incident, sustained deterioration in interception performance, or explicit expansion of war aims. It concludes that the conflict remains under constrained escalation, but the margin of stability is narrowing. 

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    Policy Brief | EPINOVA–2026–PB–10

    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. 

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    Working Paper | EPINOVA–WP–F–2026–03

    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. 

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    Policy Brief | EPINOVA–2026–PB–09

    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. 

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    Policy Brief | EPINOVA–2026–PB–08

    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. 

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    Policy Brief | EPINOVA–2026–PB–07

    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.

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    Policy Brief | EPINOVA–2026–PB–06

    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. 

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    Policy Brief | EPINOVA–2026–PB–05

    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. 

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    Working Paper | EPINOVA–WP–F–2026–02

    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.

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    Policy Brief | EPINOVA–2026–PB–04

    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. 

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