Examinando por Autor "Alanis, Juan Arturo"

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Resonant Tunneling Diode Nano-Optoelectronic Excitable Nodes for Neuromorphic Spike-Based Information Processing
(American Physical Society, 2022-02-02) Hejda, Matěj; Alanis, Juan Arturo; Ortega-Piwonka, Ignacio; Lourenço, João; Figueiredo, José; Javaloyes, Julien J. P.; Romeira, Bruno; Hurtado, Antonio
n this work, we introduce an interconnected nano-optoelectronic spiking artificial neuron emitter-receiver system capable of operating at ultrafast rates (about 100 ps/optical spike) and with low-energy consumption (< pJ/spike). The proposed system combines an excitable resonant tunneling diode (RTD) element exhibiting negative differential conductance, coupled to a nanoscale light source (forming a master node) or a photodetector (forming a receiver node). We study numerically the spiking dynamical responses and information propagation functionality of an interconnected master-receiver RTD node system. Using the key functionality of pulse thresholding and integration, we utilize a single node to classify sequential pulse patterns and perform convolutional functionality for image feature (edge) recognition. We also demonstrate an optically interconnected spiking neural network model for processing of spatiotemporal data at over 10 Gbit/s with high inference accuracy. Finally, we demonstrate an off-chip supervised learning approach utilizing spike-timing-dependent plasticity for the RTD-enabled photonic spiking neural network. These results demonstrate the potential and viability of RTD spiking nodes for low footprint, low-energy, high-speed optoelectronic realization of spike-based neuromorphic hardware.
Spike propagation in a nanolaser-based optoelectronic neuron
(Optica Publishing Group, 2022-07-01) Ortega-Piwonka, Ignacio; Hejda, Matěj; Alanis, Juan Arturo; Lourenço, João; Hurtado, Antonio; Figueiredo, José; Romeira, Bruno; Javaloyes, Julien J. P.
With the recent development of artificial intelligence and deep neural networks, alternatives to the Von Neumann architecture are in demand to run these algorithms efficiently in terms of speed, power and component size. In this theoretical study, a neuromorphic, optoelectronic nanopillar metal-cavity consisting of a resonant tunneling diode (RTD) and a nanolaser diode (LD) is demonstrated as an excitable pulse generator. With the proper configuration, the RTD behaves as an excitable system while the LD translates its electronic output into optical pulses, which can be interpreted as bits of information. The optical pulses are characterized in terms of their width, amplitude, response delay, distortion and jitter times. Finally, two RTD-LD units are integrated via a photodetector and their feasibility to generate and propagate optical pulses is demonstrated. Given its low energy consumption per pulse and high spiking rate, this device has potential applications as building blocks in neuromorphic processors and spiking neural networks. © 2022 Optica Publishing Group under the terms of the Optica Open Access Publishing Agreement