Single-shot deep-turbulence wavefront sensing and digital adaptive optics

Abstract

Despite recent progress, our ability to sense and correct deep atmospheric turbulence remains limited. Such turbulence arises from distributed-volume aberrations that produce strong blur, scintillation, and severe anisoplanatism. Conventional approaches typically require a point-source beacon and are limited to sensing two-dimensional aberrations, which restricts their practical utility. More recently, digital holographic (DH) sensors, combined with iterative computational algorithms, have shown promise for sensing and correcting deep turbulence; however, existing algorithms generally fail when only a single measurement is available. In this work, we review the evolution of DH algorithms performance in deep turbulence, starting with the multi-plane iterative reconstruction algorithm validated experimentally in 2020 and ending with our newest framework, Coherent Plug and Play 2 (CPnP2), which uses a model-based estimation framework with multiple plug-and-play priors. We compare all four algorithms using the same single-shot DH measurement from a calibrated deep-turbulence laboratory experiment. While the previous algorithms fail to focus the image, CPnP2 recovers a high-contrast, speckle-free image along with an estimate of the distributed-volume phase errors. These results represent the first demonstration of single-shot sensing and digital correction of deep atmospheric turbulence using experimental DH data, a major milestone.