Speaker
Description
We present ongoing work on a Bayesian integrated data analysis (IDA) framework for multi-diagnostic equilibrium reconstruction at the WEST tokamak. The approach builds on previously validated Bayesian current tomography using external magnetic diagnostics and extends it toward a unified inference of equilibrium-relevant plasma quantities using magnetic, density, and temperature information [1].
Within a single probabilistic framework, we infer the two-dimensional plasma current density and poloidal magnetic flux, together with electron density and electron temperature profiles. External magnetic measurements from pick-up coils and flux loops are combined with interferometry for electron density, polarimetry for internal magnetic field constraints, and electron cyclotron emission (ECE) for electron temperature, through physics-based forward models, allowing all quantities to be estimated self-consistently with quantified uncertainties.
The methodology is designed to remain as close as possible to existing Bayesian IDA formulations developed for WEST impurity tomography, enabling methodological consistency and facilitating future integration of additional diagnostics [2]. At the same time, the framework is being extended to incorporate equilibrium constraints through probabilistic force-balance formulations, inspired by Bayesian equilibrium inference approaches applied at JET [3].
This work represents a step toward fully integrated, multi-diagnostic Bayesian equilibrium reconstruction at WEST and provides a scalable basis for future applications to real-time plasma monitoring and control in next-step devices.
J. De Rycke acknowledges the Research Foundation - Flanders (FWO) via PhD grant 1SH6424N
[1] J. De Rycke, et al., J. Instrum. 21 (2026).
[2] H. Wu, et al., Plasma Phys. Control. Fusion. 67 (2025).
[3] S. Kwak, et al., Nucl. Fusion. 62 (2022).