Acceleration of autofocusing algorithms for fielding solid targets at high-repetition-rates

High-energy-density science experiments utilizing high-power laser systems increasingly operate at high repetition rates (HRRs), demanding automated and rapid target focusing to maintain data throughput. We present a robust autofocusing framework and a direct experimental validation of its performance. The system utilizes a dichroic mirror to collinearly align a continuous-wave 532 nm probe laser with the main beam, focusing both via an off-axis parabola to a <10 μm spot. A focal spot monitor positioned along the optical path captures back-reflected images of the probe light as a target is scanned through the focal axis. We compare seven distinct image-based focus metrics by correlating their chosen focal position with a direct physics-based performance indicator: the resulting x-ray flux produced when the laser is shot into a 34 μm copper flat foil target. Among the metrics tested, the Sobel Tenengrad operator provides the strongest combined high-yield and low-variability performance in the Si-diode measurements. Acceleration is evaluated through two coupled contributions: millisecond-scale metric computation and a dynamic gradient-skip search that reduces the number of acquired images and commanded motor positions relative to a 30-image full focal scan. For Sobel Tenengrad at a patience value of 5, the gradient-skip search retains 96.7% accuracy within ±1 image of the full-scan best focus while reducing the mean number of evaluated images from 30 to 22.93. These results support its use in practical HRR feedback loops where both metric reliability and scan efficiency are required.