Plasma profile tomography for EAST based on integrated data analysis

Abstract

In this study, a plasma profile reconstruction algorithm based on integrated data analysis (IDA) is proposed, which incorporates various diagnostics and can provide two-dimensional distributions of plasma current and electron density. The IDA algorithm based on Bayesian inference combines limited data from multiple diagnostics and builds models in a probabilistic manner, overcoming the limitations of models based on just external magnetic diagnostics and providing more accurate results. To reduce the probability of unreasonable solutions, two Gaussian priors are established: conditional autoregressive prior and squared exponential kernel function prior, which constrain the plasma current and electron density, respectively. Compared to the models based on only magnetic diagnostics, the IDA model improves the current distribution in the core and increases the accuracy of plasma profile reconstruction.