Free‐space Optical Computing Systems

Abstract Free‐space optical systems are emerging as a hardware platform for high‐throughput and energy‐efficient computing. In this review, the pioneering works are first introduced to lay the foundation for the principles and architectures of systems. The modern hardware implementations of two types of optical computing systems, matrix, and vector multiplication systems and diffractive optical neural network systems, are covered from material, device, and system perspectives. Further, the system deployment to various applications is also discussed. This review serves as an introduction and guideline to the current progress of developing and utilizing free‐space optical computing systems in various domains.

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Institutions

Publication Details

Journal
Annalen der Physik
Published
2025-03-22
DOI
https://doi.org/10.1002/andp.202400390
Citations
2
Primary Topic
Neural Networks and Reservoir Computing
Type
article
Field-Weighted Citation Impact
4.96

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article

Free‐space Optical Computing Systems

Weilu Gao, Ruiyang Chen
2 citations
Annalen der Physik
Neural Networks and Reservoir Computing
4.96
article

Free‐space Optical Computing Systems

Weilu Gao, Ruiyang Chen
article en
2 citations

Abstract

Abstract Free‐space optical systems are emerging as a hardware platform for high‐throughput and energy‐efficient computing. In this review, the pioneering works are first introduced to lay the foundation for the principles and architectures of systems. The modern hardware implementations of two types of optical computing systems, matrix, and vector multiplication systems and diffractive optical neural network systems, are covered from material, device, and system perspectives. Further, the system deployment to various applications is also discussed. This review serves as an introduction and guideline to the current progress of developing and utilizing free‐space optical computing systems in various domains.

Annalen der PhysikVol. 537(6)
University of Utah (US)
National Science Foundation
Openalex Percentile: Top 6%
Neural Networks and Reservoir Computing
4.96
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