DOI: 10.1063/5.0350411 ISSN: 0034-6748

Development of Korea Superconducting Tokamak Advanced Researches (KSTAR) Lyman alpha diagnostics and its synthetic data algorithm

Jae-seok Lee, K. C. Lee, Jayhyun Kim, Taeuk Moon, Yong-Seon Kim, Jae-Min Kwon, E. S. Yoon, Y.-c. Ghim

Characterizing the neutral density in the edge region of the magnetically confined plasma is critical for understanding power exhaust, fuel recycling, and the L–H transition. Lyman-α emission can offer two advantages over Balmer-α: higher emission intensity where the edge electron density is below 1019/m3, and simpler data analysis because the emissivity is directly tied to the ground-state atomic density, with a smaller molecular contribution at low temperatures near a divertor and the magnetic X-point. We report the Korea Superconducting Tokamak Advanced Research (KSTAR) Lyman Alpha Measuring Apparatus (KLAMA), a radial 20-channel system viewing the region near the magnetic X-point and lower divertor, with a radial channel separation of up to 1.3 cm. KLAMA uses three notch reflective filters designed to provide 13.02% transmission while suppressing the neighboring C-III line by a factor of ∼14. We have developed a synthetic data algorithm utilizing the Virtual KSTAR platform to optimize the optical design, quantify noise propagation, and build the transfer matrix. The synthetic data algorithm is also used for a Gaussian-process-regularized 2D reconstruction of the neutral density and is expected to be used to generate a forward model for a Bayesian inference analysis in future work. KLAMA has been manufactured and installed on KSTAR, and preliminary data acquired during a disruption are presented.