Real-time wavefront measurement based on GPU-accelerated parallel algorithm using phase diversity images

• Published in: IEEE transactions on instrumentation and measurement 2024-01, Vol.73, p.1-1
• Main Authors: Kim, Jinsung, Lee, Kye-Sung, Lee, Sang-Chul, Kim, Dong Uk, Kim, I Jong, Chang, Ki Soo, Hur, Hwan
• Format: Article
• Language: English
• Subjects: Aberration; Acceleration; Adaptive optics; Algorithms; Astigmatism; Computational modeling; Diversity methods; Global optimization; GPU acceleration; gradient-based optimization algorithm; Graphics processing units; image-based wavefront sensing; Linear quadratic regulator; Measurement; Optimization; Phase diversity; phase diversity method; point spread function; Point spread functions; Pupils; Real time; real-time aberration measurement; Real-time systems; Time measurement; Wave fronts
• ISSN: 0018-9456; 1557-9662
• DOI: 10.1109/TIM.2023.3341104

In this study, we introduce a novel real-time measurement and correction method for time-varying wavefront aberrations. Central to this method is a GPU-accelerated parallel algorithm based on phase diversity images. We apply an approximate model for the point spread function to reduce the computational load of error metric minimization. We forge a parallel framework that independently measures each aberration mode by deriving an object-independent error metric and its gradient. Numerical experiments with actual Kolmogorov model-based data were conducted to assess the measurement performance and real-time feasibility of the proposed method. When juxtaposed with the global optimization algorithm, the proposed method improved the computation speed by up to 1300 times, while maintaining measurement accuracy. Moreover, we executed benchmark tests on diverse hardware configurations, thereby verifying the real-time viability of GPU acceleration. The GPU achieved a 6.8x improvement in computational speed compared to the CPU. Seamlessly integrating a LQR controller into the adaptive optics system, we zeroed in on the real-time correction of dynamic aberrations. The empirical results exhibited an operational speed of 90 [Hz] in a realistic environment for correcting only three types of aberrations (astigmatism, defocus, and coma). Furthermore, we demonstrated the correction capability for large-scale aberrations, proving that the proposed method is scalable relative to the intensity of aberrations. In conclusion, this study paves the way for a combination of real-time execution and precise wavefront aberration correction in a sensorless AO, establishing a novel standard for future development and enhancements in wavefront sensing technology.