SHF: Small: Fusion of Quantum Dot/Nanowire Based Sensors and Processors in Ultra-low-energy, Distributed-Intelligence Sensing Network

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The purpose of the award is to develop a new nano-circuit architecture, novel circuit realization using quantum-electronic devices, and a comprehensive, vertically integrated design methodology for real-time electronic vision applications. The architecture integrates nano-optical sensors and active quantum dot processing elements into hybrid, ultra efficient, distributed intelligence systems with meta-level decision making agents. This is in contrast with conventional electronic vision systems where all decision related processing is done by an algorithmic agent only after digitization of the input from nanowire sensors. The approach employs a smooth analog-to-digital processing transition to allow en-route, hierarchical transformation of the input into simpler, digital representations of multidimensional, abstract input characteristics while the signal is on its way to the central decision making agent. A more rapid decision-making can be achieved because the agent can now directly correlate just the key features without first identifying and extracting these features or filtering out extraneous details. Such close-to-source processing also includes all other desirable benefits like high energy-efficiency, low signal degradation and small area requirement for chip implementation, in addition to high speed. Specifically, fanning-out the input to a cellular-neural-network-like architecture of active quantum-electronic analog functional units will extract and encode the key features that can then be fanned in to one or more decision agents. These units include spatio-temporal filters, velocity estimators, and image processing elements. The intellectual merits of this research include the construction of nanoscale quantum dots based cellular logic arrays capable of performing neuromorphic computation like spatiotemporal signal processing, video and image processing; and the design of a new CAD tool for optimizing the 3D nanostructures of quantum tunneling devices while performing the system-level optimization in an augmented circuit simulator developed by the principal investigator's research group. The broader impacts include development of pedagogical interdisciplinary training to the next generation of circuit engineers and supplementary didactic material---two new, definitive textbooks on nanoelectronics.