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Photoluminescence: Applications01:14

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  3. Lightpro: A Linear Photonic Processor With Full Programmability.
  1. Home
  3. Lightpro: A Linear Photonic Processor With Full Programmability.

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LightPro: a linear photonic processor with full programmability.

Amin Shafiee1, Zahra Ghanaatian2, Benoit Charbonnier3

  • 1Department of Electrical and Computer Engineering, Colorado State University, Fort Collins, CO, USA. amin.shafiee@colostate.edu.

Communications Engineering
|June 17, 2026

View abstract on PubMed

Summary
This summary is machine-generated.

We developed LightPro, a programmable photonic processor for deep neural networks. It significantly reduces footprint and power consumption while maintaining high accuracy, overcoming limitations of current hardware.

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Area of Science:

  • Photonics
  • Artificial Intelligence
  • Hardware Acceleration

Background:

  • Conventional photonic hardware for deep neural networks faces limitations in scalability, optical losses, and footprint.
  • Mach-Zehnder interferometers are commonly used but contribute to these limitations.

Purpose of the Study:

  • To present LightPro, a novel programmable linear photonic processor.
  • To optimize scalability, power efficiency, and area footprint for deep neural network acceleration.

Main Methods:

  • Integrated a neural architecture search and pruning framework with tunable phase-change material directional couplers.
  • Dynamically adjusted coupling coefficients by thermally modulating phase-change material states.
  • Validated phase-change material devices using multiphysics simulations and compact models against experimental data.

Main Results:

  • LightPro architectures achieved up to 85% footprint reduction and over 50% decrease in power consumption.
  • Network scaling evaluations showed less than 5% inference accuracy degradation.
  • Experimental prototyping validated the computational accuracy and scalability of LightPro.

Conclusions:

  • LightPro offers a scalable and efficient pathway for next-generation photonic artificial intelligence accelerators.
  • The architecture overcomes fundamental physical scaling limitations of current photonic hardware.