Plasmon-Stimulated Synaptic Transistor

Abstract With the emerging transition from programmed to learning computing, traditional electronic ICs are unlikely to be able to match the massive perceptual data that will need to be processed in real-time. Neuromorphic engineering may surmount the von Neumann bottleneck by creating high-performance hardware for distributed and parallel processing with low power consumption. Nowadays, most of high-efficiency neuromorphic hardware is based on artificial synapsis and neuronal devices, utilizingelectrical or optical platforms and thus correspondingly limited in terms of bandwidth or footprint, respectively. In this work, we introduce a plasmon-stimulated synaptic transistor concept that may combine the high bandwidth of a photonic network with the compactness of electronic circuits. The actual synaptic characteristic, including excitatory postsynaptic current and paired-pulse facilitation, is achieved utilizing charge trapping effects to control the conductivity of a monolithic Al-Ge-Al Schottky barrier field-effect transistor. The population of traps is thereby controlled by hot electrons arising from the non-radiative decay of deliberately applied surface plasmon polariton spikes. The temporal dynamics of the trapping process and thus the plasticity of the synaptic transistor can be set by the geometry and operation mode of the synaptic transistor as well as the intensity and duration of the plasmon spikes.