Incorporating magnetic equilibrium information in Gaussian process tomography for soft X-ray spectroscopy at WEST

Area of Science:

• Plasma physics
• Tomography
• Fusion energy research

Background:

• Gaussian Process Tomography (GPT) is a novel method for plasma diagnostics.
• GPT has been applied to soft X-ray spectroscopy on the WEST tokamak.
• Existing GPT methods can reconstruct plasma profiles without magnetic equilibrium information.

Purpose of the Study:

• To integrate magnetic flux surface geometry into the GPT method.
• To enhance the regularization of GPT solutions using equilibrium information.
• To validate the improved GPT method with synthetic data.

Main Methods:

• Constructing a covariance matrix for the Gaussian Process prior that depends on flux surface geometry.
• Validating the method using synthetic soft X-ray (SXR) emissivity profiles relevant to WEST plasmas.
• Comparing the performance against classical tomography algorithms.

Main Results:

• The developed GPT method successfully incorporates magnetic equilibrium information.
• The enhanced GPT method shows favorable comparison with the classical Fisher information minimization algorithm.
• The integration of equilibrium geometry improves the regularization of the tomography solution.

Conclusions:

• Incorporating magnetic equilibrium information into GPT enhances its capability for plasma diagnostics.
• The improved GPT method is a valuable tool for real-time impurity transport analysis and MHD control.
• This approach offers a more robust solution for plasma tomography in fusion devices.