Carbon nanotube-based programmable devices for adaptive architectures

We show that optic ally-gated carbon nanotube field effect transistors can be used as 2-terminal like devices with light sensitivity and memory capabilities. In particular, their channel resistivity can be adjusted precisely, within a large range and memorized. These devices can thus be used as synapses in neural network type of circuits. We demonstrate experimentally these properties, build a device model and propose a circuit architecture, which allows very efficient parallel learning.