Integrated data analysis on the electron density profile of HL-2A with the Bayesian probability inference method

In fusion research, the diagnostic data are obtained from different diagnostic systems, which are relatively independent (in terms of the response function, noise, calibration, etc…). The consequence is that many measurements providing the same physical quantity could provide different results. In this work, the Bayesian Probability Inference (BPI) has been applied to the Frequency Modulated Continuous Wave reflectometry (FMCW) and the Far-infrared laser interferometer (FIR) diagnostic systems on HL-2A tokamak, offering the Integrated Data Analysis (IDA) for electron density profile reconstruction. With the implementation, it is demonstrated that more comprehensive inference could be delivered from IDA compared to the traditional individual data analysis technique. The data analysis program based on the Bayesian inference model has been developed to reconstruct the two-dimensional electron density profile, which permits to be further implementation of the HL-2A/2M IDA framework in the near future.