Optical neural network for all-optical logic gates solution
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2024
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ENCONTRO DE OUTONO DA SOCIEDADE BRASILEIRA DE FISICA
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With the escalating demand for speed and computational power to meet the ever-growing
requirements of AI algorithms, coupled with the limitations of von Neumann computing, there
is an increasing necessity for alternatives to silicon-based computers. Photonic computers
emerge as a promising solution to this challenge, leveraging the low latency and parallelism of
light to deliver unrivaled capabilities for neuromorphic computing. Notably, they offer
significant reductions in energy consumption and substantial speed enhancements, allowing for
matrix multiplications at the speed of light. These operations are particularly crucial as they
constitute approximately 80% of computer usage in convolutional neural networks.
In this work, we present an optical system capable of performing logic operations, such as
AND, OR, NOT, and XOR, in an all-optical manner. This is made possible by utilizing a spatial
light modulator (SLM), which receives and adjusts the input light according to the desired logic
operation and input binary values. These values are encoded using a metal mask that segments a
collimated light beam from a He-Ne laser. To incorporate not only the binary value of each bit
but also the desired logic operation simultaneously, specific regions within a CCD sensor that
receive the input beam after passing through the mask are defined. In a simplified approach, we
designate the two lower quadrants of the CCD image to represent individual bits (lower left =
bit 1; lower right = bit 2) and by detecting light intensity above a defined threshold, a logic
value of '1' is assigned; otherwise, '0' is interpreted. Similarly, the same intuitive method can be
applied to the upper quadrants to determine the logic operation (upper left = AND; upper right =
OR). Further divisions of the CCD image can be implemented to accommodate additional
operations or to create a bias beam, which is crucial for solving more complex problems.
The analogy between this optical neural network and traditional networks can be drawn
as follows: incident light on each SLM pixel forms the input vector, multiplied by a weight
matrix via programmable phase delays. The resulting light, reflected by the SLM, is focused by
a lens and captured by a CCD camera, effectively summing up the results to produce an output
or new layer. The presented approach is particularly interesting for establishing a basis for
future improvements and characterizations of optical non-linear activation functions.
Como referenciar
PRADO, FELIPE M.; WETTER, NIKLAUS U. Optical neural network for all-optical logic gates solution. In: ENCONTRO DE OUTONO DA SOCIEDADE BRASILEIRA DE FISICA, 19-23 de maio, 2024, Florianópolis, SC. Resumo... São Paulo, SP: Sociedade Brasileira de Física - SBF, 2024. Disponível em: https://repositorio.ipen.br/handle/123456789/49131. Acesso em: 19 Mar 2026.
Esta referência é gerada automaticamente de acordo com as normas do estilo IPEN/SP (ABNT NBR 6023) e recomenda-se uma verificação final e ajustes caso necessário.