A time multiplexed architecture for neural networks using quantum devices

An architecture is proposed which addresses the interconnection problem associated with large scale hardware-based neural networks. A design using silicon based quantum devices with MOS/CMOS devices is described and compared to a design based on conventional devices. The time multiplexed architecture sequentially connects each of the inputs to the next layer in a fully connected neural network.