Spiking flip-flop memory in resonant tunnelling diode neurons

Giovanni Donati*, Dafydd Owen-Newns, Joshua Robertson, Ekaterina Malysheva, Andrew Adair, Jose Figueiredo, Bruno Romeira, Victor Dolores-Calzadilla, Antonio Hurtado

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)
18 Downloads (Pure)

Abstract

We report a spiking flip-flop memory mechanism allowing to controllably switch between neural-like excitable spike-firing and quiescent dynamics in a resonant tunneling diode (RTD) neuron under low-amplitude (<150 mV pulses) and high-speed (ns-rates) inputs pulses. We also show that the timing of the set-reset input pulses is critical to elicit switching responses between spiking and quiescent regimes in the system. The demonstrated flip-flop spiking memory, in which spiking regimes can be controllably excited, stored and inhibited in RTD-neurons, via specific low-amplitude, high speed signals (delivered at proper time instants) offers high promise for RTD-based spiking neural networks, with potentials to extend further to optoelectronic implementations where RTD neurons and RTD memory elements are deployed alongside for fast and efficient photonic-electronic neuromorphic computing and Artificial Intelligence (AI) hardware.
Original languageEnglish
Article number267301
Number of pages7
JournalPhysical Review Letters
Volume133
Issue number26
DOIs
Publication statusPublished - 24 Dec 2024

Funding

The authors acknowledge support from the UKRI Turing AI Acceleration Fellowships Programme (EP/V025198/1), from the EU Pathfinder Open project “SpikePro,” from the Fraunhofer Centre for Applied Photonics, FCAP, and from the Fundação para a Ciência e a Tecnologia (FCT) project 2022.03392.PTDC–META-LED.

Keywords

  • memory
  • neuromorphic computing
  • neuronal dynamics
  • tunnel diode resonance

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