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Spiking Flip-Flop Memory in Resonant Tunneling Diode Neurons.

Giovanni Donati¹, Dafydd Owen-Newns¹, Joshua Robertson¹

¹University of Strathclyde, Institute of Photonics, SUPA Dept of Physics, Glasgow, United Kingdom.

Physical Review Letters

|January 29, 2025

Summary

Researchers developed a novel flip-flop memory mechanism in resonant tunneling diode (RTD) neurons. This breakthrough enables controllable switching between neural-like firing and quiescent states using precise, high-speed signals for advanced AI hardware.

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Area of Science:

* Solid-state physics
* Neuroscience
* Computer engineering

Background:

* Resonant tunneling diodes (RTDs) exhibit unique electrical properties.
* Developing efficient memory mechanisms is crucial for neuromorphic computing.
* Mimicking neural dynamics in electronic circuits is a key challenge.

Purpose of the Study:

* To demonstrate a spiking flip-flop memory mechanism in RTD neurons.
* To investigate the role of input pulse timing in controlling neural dynamics.
* To explore the potential for RTD-based neuromorphic computing.

Main Methods:

* Utilized low-amplitude (<150 mV) and high-speed (ns rate) input pulses.
* Applied set-reset pulse sequences to RTD neurons.
* Analyzed switching dynamics between excitable and quiescent states.

Main Results:

* Successfully demonstrated controllable switching between spiking and quiescent dynamics.
* Established the critical role of input pulse timing for state switching.
* Achieved flip-flop memory behavior in RTD neurons.

Conclusions:

* The developed flip-flop spiking memory offers a promising approach for RTD-based neural networks.
* This mechanism can be controllably excited, stored, and inhibited.
* Potential for extension to optoelectronic implementations for photonic-electronic neuromorphic computing and AI hardware.