Authors: Antony Orth, Oliver Pitts, Costel Flueraru, Terrence Stewart, Hamed Akhlaghi, Mohamadreza Pashazanoosi, Michael Taylor, Steve Hranilovic

Published on: February 05, 2024

Impact Score: 8.22

Arxiv code: Arxiv:2402.02752

Summary

• What is new: A new wavefront sensing technique that uses a single photodiode and a fast mirror for phase-diverse intensity measurements, trained with neural networks to estimate input phase.
• Why this is important: Dynamic wavefront aberrations negatively impact optical applications like astronomy and SatCom, with existing wavefront sensing techniques being inadequate for SatCom wavelengths.
• What the research proposes: A novel wavefront sensing approach utilizing a single photodiode, fast mirror, and neural networks for phase estimation under strong turbulence and rapid satellite movements.
• Results: Achieves 99% of the optimal Strehl ratio from a 50-mode correction at a 2kHz sensing rate, proving robust against strong turbulence and modal crosstalk.

Technical Details

Technological frameworks used: Neural network training for phase estimation

Models used: Simulations of typical turbulence, sensing speed, and noise cases

Data used: Phase-diverse sub-millisecond intensity trace data

Potential Impact

Astronomy, satellite optical communications, optical free-space telecommunications, and bio-imaging sectors

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