Pupil Design for Computational Wavefront Estimation

2026-03-31

AI Summary

This study addresses the challenge of accurately recovering incident wavefronts from a single intensity measurement by optimizing pupil design in optical systems. The work proposes the first quantitative metric for pupil asymmetry tailored to wavefront estimation and systematically investigates its impact on wavefront recoverability. Through extensive simulations and experimental validation, the authors establish a positive correlation between pupil asymmetry and wavefront reconstruction performance. The results demonstrate that highly asymmetric pupils significantly enhance estimation accuracy while effectively balancing photon throughput and robustness to noise. These findings yield a general design principle applicable to computational imaging, adaptive optics, and related fields requiring precise wavefront sensing from limited measurements.

Abstract

Establishing a precise connection between imaged intensity and the incident wavefront is essential for emerging applications in adaptive optics, holography, computational microscopy, and non-line-of-sight imaging. While prior work has shown that breaking symmetries in pupil design enables wavefront recovery from a single intensity measurement, there is little guidance on how to design a pupil that improves wavefront estimation. In this work we introduce a quantitative asymmetry metric to bridge this gap and, through an extensive empirical study and supporting analysis, demonstrate that increasing asymmetry enhances wavefront recoverability. We analyze the trade-offs in pupil design, and the impact on light throughput along with performance in noise. Both large-scale simulations and optical bench experiments are carried out to support our findings.

Problem

• pupil design
• wavefront estimation
• asymmetry
• computational imaging
• adaptive optics

Innovation

• pupil design
• wavefront estimation
• asymmetry metric
• computational imaging
• single-shot measurement