Abstract
A scalable optical computer based on free-space optics and Koehler illumination was proposed to obtain optical parallelism in an artificial neural network. The Koehler illumination scheme can provide more uniform illumination and less crosstalk compared with the previous systems based on Abbe illumination. The proposed design was realised in hardware with 2 × 2 inputs and 2 × 2 outputs using light-emitting diodes, a liquid crystal display, lens arrays, and a detector array assembled in an optical cage system with subsidiary electronics. The feasibility of the constructed optical computer was demonstrated by achieving the expected results of the NAND and NOR logics in parallel in the nondifference mode. Additionally, a simple pattern-checking function in the difference mode was shown. In addition, the limit of the scalability and the effect of geometric aberration was discussed. Furthermore, a clustering technique was suggested to overcome the limitations of scalability. Clustering can continue to increase the array size and throughput by creating a new block of doubled input and output arrays from multistacks of basic optical modules. The proposed architecture and clustering method have the potential to realise massive optical parallelism if large-array components and high-speed electronics are used in the future.
Original language | English |
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Article number | 220 |
Journal | Optical and Quantum Electronics |
Volume | 55 |
Issue number | 3 |
DOIs | |
State | Published - Mar 2023 |
Keywords
- Clustering
- Free-space optics
- Koehler illumination
- Optical computer
- Optical neural network
- Scalability
- Smart pixels