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Excitable laser processing network node in hybrid silicon: analysis and simulation.

Mitchell A Nahmias, Alexander N Tait, Bhavin J Shastri

|October 20, 2015

Summary

This summary is machine-generated.

We developed a novel optoelectronic circuit model for ultrafast laser neural networks, enabling complex, real-time signal processing on a single chip. This technology promises advancements in areas like cognitive radio and low-latency control systems.

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Area of Science:

Optoelectronics
Photonics
Artificial Intelligence

Background:

Real-time signal processing demands speed and complexity.
Ultrafast laser dynamics and on-chip networking offer potential solutions.

Purpose of the Study:

To present a physically realistic optoelectronic simulation model for dynamical laser neural networks.
To verify the behavior and properties of this novel circuit.

Main Methods:

Developed an optoelectronic simulation model for a laser neural network node.
Described the physics, dynamics, and parasitics of the network node components (filters, photodetector, excitable laser).

Main Results:

Verified the behavior of the proposed laser neural network circuit model.
Demonstrated critical properties for large-scale networking: cascadability and fan-in.
Showcased the potential for on-chip photonic integrated circuit implementation with no off-chip optical I/O.

Conclusions:

The proposed laser neural network circuit is a viable platform for advanced signal processing.
This technology can be integrated into photonic integrated circuits for efficient, on-chip operation.
Potential applications include cognitive radio and low-latency control systems.