Bayesian modeling of quantum-dot-cellular-automata circuits

The goal of this work is to develop a fast, Bayesian Prob-abilistic Computing model [1], [2] that exploits the induced causality of clocking to arrive at a model with the minimum possible complexity. The probabilities directly model the quantum-mechanical steady-state probabilities (density ma-trix) or equivalently, the cell polarizations. The attractive fea-ture of this model is that not only does it model the strong dependencies among the cells, but it can be used to compute the steady state cell polarizations, without iterations or the need for temporal simulation of quantum mechanical equa-tions. The impact of our proposed modeling is that it is based on density matrix-based quantum modeling, takes into ac-count dependency patterns induced by clocking, and is non-iterative. It allows for quick estimation and comparison of quantum-mechanical quantities for a QCA circuit, such as QCA-state occupancy probabilities or polarizations at any cell, thus enable one to quickly compare, contrast, and ne tune clocked QCA circuit designs, before performing costly full quantum-mechanical simulation of the temporal dynam-ics