M2P2 à l'école internationale d'ITER

Understanding magnetic confinement fusion plasmas requires accurate interpretation of experimental measurements, which are inherently indirect and influenced by multiple intertwined physical processes. Extracting meaningful insights demands a robust comparison with experiments through an integrated modeling approach that accounts for both core and edge plasma while incorporating transport, turbulence, and impurity physics. This lecture will explore how synthetic diagnostics serve as a crucial link between simulations and experiments, enabling direct comparison of model predictions with measured signals. By replicating real diagnostic observations, synthetic diagnostics help identify the dominant physical mechanisms shaping experimental data. Embedding them within integrated modeling frameworks allows for a systematic assessment of transport assumptions, turbulence characteristics, and impurity contributions, improving the reliability of model validation. We will present case studies from tokamak experiments, illustrating how integrated modeling enhances measurement interpretation while addressing challenges such as diagnostic uncertainties, model fidelity, and computational constraints. The role of synthetic diagnostics in refining measurement interpretations, optimizing diagnostic configurations, and improving predictive capabilities for reactor-scale plasmas will also be examined. The lecture will conclude with perspectives on advancing integration between modeling and diagnostics to support the next generation of fusion research.