Metasurface-encoded optical neural network wavefront sensing for high-speed adaptive optics

TL;DR

This paper introduces a hybrid opto-electric neural network wavefront sensor using metasurfaces and a neural network for ultrafast, low-cost adaptive optics, outperforming traditional sensors in dynamic conditions.

Contribution

It presents a novel hybrid sensor combining metasurfaces and neural networks for high-speed wavefront sensing, reducing cost and latency compared to electronic-only systems.

Findings

Achieves >60% Strehl ratio improvement in simulations

Maintains performance under dynamic atmospheric conditions

Outperforms electronic sensors in transient scenarios

Abstract

Free-space optical communications with moving targets, such as satellite terminals, demand ultrafast wavefront sensing and correction. This is typically addressed using a Shack-Hartmann sensor, which pairs a high-speed camera with a lenslet array, but such systems add significant cost, weight, and power demands. In this work, we present a hybrid opto-electric neural network (OENN) wavefront sensor that enables ultra-high-speed operation in a compact, low-cost system. Subwavelength diffractive metasurfaces efficiently encode the incoming wavefront into tailored irradiance patterns, which are then decoded by a lightweight multilayer perceptron (MLP). In simulation and experiment, the hybrid approach achieves average Strehl ratio (SR) improvements exceeding 60% and 45%, respectively, for unseen wavefronts compared to purely electronic sensors with few-pixel inputs. Although larger MLPs allow purely electronic sensors to match the hybrid's SR under static conditions, transient atmosphere modeling shows that their added latency leads to rapid SR degradation with increasing Greenwood frequency, while the hybrid system maintains performance. These results highlight the potential of hybrid OENN architectures to unlock scalable, high-bandwidth free-space communication systems and, more broadly, to advance optical technologies where real-time sensing is constrained by electronic latency.