Dynamical laser spike processing
Bhavin J. Shastri, Mitchell A. Nahmias, Alexander N. Tait, Alejandro, W. Rodriguez, Ben Wu, Paul R. Prucnal

TL;DR
This paper introduces a graphene-coupled laser system capable of complex spike-based optical processing, including logic restoration, cascadability, and pattern detection, promising advancements in speed and efficiency for optical information processing.
Contribution
It presents a novel graphene-enhanced laser platform that exhibits advanced spike dynamics and processing capabilities beyond traditional laser systems.
Findings
Demonstrated logic-level restoration and cascadability in the laser system
Implemented temporal pattern detection and recurrent memory tasks
Showed advantages of graphene properties for high-speed, efficient processing
Abstract
Novel materials and devices in photonics have the potential to revolutionize optical information processing, beyond conventional binary-logic approaches. Laser systems offer a rich repertoire of useful dynamical behaviors, including the excitable dynamics also found in the time-resolved "spiking" of neurons. Spiking reconciles the expressiveness and efficiency of analog processing with the robustness and scalability of digital processing. We demonstrate that graphene-coupled laser systems offer a unified low-level spike optical processing paradigm that goes well beyond previously studied laser dynamics. We show that this platform can simultaneously exhibit logic-level restoration, cascadability and input-output isolation---fundamental challenges in optical information processing. We also implement low-level spike-processing tasks that are critical for higher level processing: temporal…
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Taxonomy
TopicsNeural Networks and Reservoir Computing · Photoreceptor and optogenetics research · Advanced Memory and Neural Computing
