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Arbitrary control over multimode wave propagation for machine learning
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DOI：10.1038/s41567-025-03094-2.png)
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Abstract
En 中文
Controlled multimode wave propagation can enable more space-efficient photonic processors than architectures based on discrete components connected by single-mode waveguides. Instead of defining discrete elements, one can sculpt the continuous substrate of a photonic processor to perform computations through multimode interference in two dimensions. Here we designed and demonstrated a device with a refractive index that can be rapidly reprogrammed across space, allowing arbitrary control of wave propagation. The device, a two-dimensional programmable waveguide, uses parallel electro-optic modulation of the refractive index of a slab waveguide with about 104 programmable spatial degrees of freedom. We implemented neural network inference on benchmark tasks with up to 49-dimensional vectors in a single pass, without digital pre-processing or post-processing. Theoretical and numerical analyses further indicated that two-dimensional programmable waveguides may offer not only a constant-factor reduction in device area but also a scaling benefit, with the area required growing as N1.5 rather than N2. Photonic processors are limited by the bulkiness of discrete components and wiring complexity. An experiment now demonstrates a reprogrammable two-dimensional waveguide that performs neural network inference through multimode wave propagation.
Keywords:
multimode wave propagation
photonic processors
neural network inference
programmable waveguide
electro-optic modulation
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