arXiv:1810.07815physics.optics
Nanophotonic Media for Artificial Neural Inference
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Abstract
We show optical waves passing through a nanophotonic medium can perform artificial neural computing. Complex information, is encoded in the wave front of an input light. The medium transforms the wave front to realize sophisticated computing tasks such as image recognition. At the output, the optical energy is concentrated to well-defined locations, which for example can be interpreted as the identity of the object in the image. These computing media can be as small as tens of wavelengths and offer ultra-high computing density. They exploit sub-wavelength scatterers to realize complex input output mapping beyond the capabilities of traditional nanophotonic devices.
They implement a trained dense multilayer neural net wit ReLU activations in silicon photonics. They evaluate it on MNIST. They use graphene to approximate the ReLUs. The device is a few microns on each side. The 2D image is first converted to a 1D wavefront by some external…
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