Enhancing three-dimensional beam shaping accuracy through cascaded spatial light modulators using diffractive neural networks

Paul Buske; Fynn Janssen; Oskar Hofmann; Jochen Stollenwerk; Carlo Holly

doi:10.1117/12.3023102

17 June 2024 Enhancing three-dimensional beam shaping accuracy through cascaded spatial light modulators using diffractive neural networks

Paul Buske, Fynn Janssen, Oskar Hofmann, Jochen Stollenwerk, Carlo Holly

Author Affiliations +

Proceedings Volume 13023, Computational Optics 2024; 130230A (2024) https://doi.org/10.1117/12.3023102
Event: SPIE Optical Systems Design, 2024, Strasbourg, France

Abstract

Diffractive neural networks (DNNs) are an emerging design method for systems of cascaded phase masks, where the optical system is treated as an all-optical neural network. In previous work, we have demonstrated how this method can be used to design highly flexible beam shaping systems. We have also shown that DNNs can be used to correct pixel crosstalk and direct reflection in a spatial light modulator based on liquid crystal on silicon. Here, we extend the correction of these effects to two cascaded spatial light modulators and demonstrate the resulting increase in accuracy of the three-dimensional beam shaping capabilities of DNNs.

Conference Presentation

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Paul Buske, Fynn Janssen, Oskar Hofmann, Jochen Stollenwerk, and Carlo Holly "Enhancing three-dimensional beam shaping accuracy through cascaded spatial light modulators using diffractive neural networks", Proc. SPIE 13023, Computational Optics 2024, 130230A (17 June 2024); https://doi.org/10.1117/12.3023102

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