Quantum confined Stark effect of excitonic transitions in GaAs/AIGaAs MQW structures for implementation of neural networks: basic device requirements

We examine theoretically and experimentally the properties of two electrooptic devices based on quantum confined Stark effect of excitonic transitions. These two devices are shown to be critical in implementation of the Hopfield model as well as other neural type networks for associative memories. P-i(multiquantum wells)-n structures using GaAs/AlGaAs provide a controller-modulator device which has integrating-thresholding properties required of neurons. The p-i-n structures also provide programmable modulators which can serve as a synaptic mask. Using Monte Carlo techniques we examine an all-optical architecture to implement the Hopfield network. No external feedback-thresholding circuitry is required in this implementation due to special design of the controller-modulator device. Speed and stability issues of this architecture are also addressed. The computer simulation results provide valuable insight into how the controllermodulator device should be improved for better network implementation.