Research into CUP-VISAR velocity reconstruction based on weighted DRUNet and total variation joint optimization

Area of Science:

• Physics
• Engineering
• Data Science

Background:

• Laser-driven inertial confinement fusion (ICF) research requires advanced diagnostic techniques for accurate data acquisition.
• Current methods for reconstructing CUP-VISAR (Compound-Reflective-Interferometer-VISAR) data face challenges with high compression ratios and aliasing.
• Accurate velocity field calculations are crucial for understanding ICF implosion dynamics.

Purpose of the Study:

• To propose and validate a novel data reconstruction algorithm for CUP-VISAR systems used in ICF research.
• To improve the quality of reconstructed shockwave velocity fringe images and enhance the accuracy of velocity field calculations.
• To address specific challenges in CUP-VISAR data, including high compression ratios and aliasing.

Main Methods:

• Development of a data reconstruction algorithm combining a weighted deep residual U-Net (DRUNet) with joint optimization using total variation (TV).
• Comparative analysis of the proposed algorithm against existing methods like ADMM-TV and enhanced 3D total variation (E-3DTV) using simulation results.
• Evaluation of the algorithm's robustness to noise, specifically Gaussian noise up to a relative intensity of 0.05.

Main Results:

• The proposed DRUNet-TV algorithm significantly outperforms ADMM-TV and E-3DTV in reconstructing CUP-VISAR images.
• Enhanced image quality leads to more accurate velocity field calculations, crucial for ICF diagnostics.
• The algorithm demonstrates robustness against noise, ensuring reliable performance in challenging experimental conditions.

Conclusions:

• The developed DRUNet-TV algorithm offers a superior solution for CUP-VISAR data reconstruction in ICF research.
• This advancement improves diagnostic capabilities in complex environments, supporting the pursuit of controlled thermonuclear fusion.
• The algorithm holds significant theoretical and practical value for the field of fusion energy research.