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Dryad

Sparsity-constrained wavefront optimization by leveraging complex media

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May 31, 2024 version files 1.02 GB

Abstract

Wavefront shaping gains increasing importance in complex photonics, which can manipulate light spatially and temporally to counter the scattering effect. Important applications include deep-tissue imaging, microendoscopy, optical communications, nanofabrication, and remote sensing. However, high-speed and high-fidelity wavefront shaping is fundamentally hindered by the dimensionality limitation of hardware devices, evinced by the competition between the frame rate, pixel count, and modulation depth. To overcome the speed-fidelity tradeoff, we leverage complex media (e.g., diffusers or multimode fibers) as analogue random multiplexers for pattern compression to address the demand for high-dimensional spatiotemporal control. Sparsity-constrained wavefront optimization is designed to solve the problem by seeking a low-dimensional, robust representation of wavefronts with a carefully designed sparsity constraint. This optimization framework can achieve high-fidelity wavefront shaping through complex media using high-speed, yet relatively low-precision spatial light modulation devices (e.g., digital micromirror devices) without compromising the frame rate.