A new technical paper titled “Arbitrary control over multimode wave propagation for machine learning” was published by researchers at Boston University, UC Irvine, and Yale University.
Abstract
“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.”
Find the technical paper here. December 2025. Related Github info is here.
Onodera, T., Stein, M.M., Ash, B.A. et al. Arbitrary control over multimode wave propagation for machine learning. Nat. Phys. (2025). https://doi.org/10.1038/s41567-025-03094-2. Creative commons license.
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