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

被引：0

作者：

Buske, Paul ^{[1
]}

Janssen, Fynn ^{[1
]}

Hofmann, Oskar ^{[1
]}

Stollenwerk, Jochen ^{[1
,2
]}

Holly, Carlo ^{[1
,2
]}

机构：

[1] Rhein Westfal TH Aachen, Chair Technol Opt Syst TOS, Steinbachstr 15, D-52074 Aachen, Germany

[2] Fraunhofer Inst Laser Technol ILT, Steinbachstr 15, D-52074 Aachen, Germany

来源：

COMPUTATIONAL OPTICS 2024 | 2024年 / 13023卷

关键词：

diffractive neural networks; laser beam shaping; spatial light modulator; liquid crystal on silicon; LASER; DESIGN; SYSTEM; ZERO;

D O I：

10.1117/12.3023102

中图分类号：

O29 [应用数学];

学科分类号：

070104 ;

摘要：

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.

引用

页数：8