Fan-out constraints in quantum dot cellular automata circuit design

In this paper, fan-out constraints are demonstrated for robust and reliable quantum dot cellular automata (QCA) device design. These QCA devices can be used to implement large and complex circuits without affecting the expected result. The tile-based QCA nanostructures are more robust and reliable. In this paper, the Hopfield artificial neural network (HANN) model is proposed to find out the robustness and the reliability of QCA nanostructure devices. This proposed HANN model demonstrates that the tile nanostructures of QCA devices are more robust and reliable for driving multiple fan-outs from a particular QCA device. The Kink energy was used in computing the polarity when considering multiple fan-outs. The tile three-input majority voter, the triple fan-out butterfly tile, the multiple fan-out tile structure and the five-input majority voter are the most robust and reliable structures for solving the fan-out problem in QCA and are described in this paper by the proposed HANN model.