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<p>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 10<sup>4</sup> 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 <i>N</i><sup>1.5</sup> rather than <i>N</i><sup>2</sup>.</p>

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Arbitrary control over multimode wave propagation for machine learning

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年12月8日

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  • Tatsuhiro Onodera,
  • Martin M. Stein,
  • Benjamin A. Ash,
  • Mandar M. Sohoni,
  • Melissa Bosch,
  • Ryotatsu Yanagimoto,
  • Marc Jankowski,
  • Timothy P. McKenna,
  • Tianyu Wang,
  • Gennady Shvets,
  • Maxim R. Shcherbakov,
  • Logan G. Wright,
  • Peter L. McMahon

摘要

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.