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Advancements in computing based on qubit networks, and in particular theflux-qubit processor architecture developed by D-Wave System's Inc., haveenabled the physical simulation of quantum-dot cellular automata (QCA) networksbeyond the limit of classical methods. However, the embedding of QCA networksonto the available processor architecture is a key challenge in preparing suchsimulations. In this work, two approaches to embedding QCA circuits arecharacterized: a dense placement algorithm that uses a routing method based onnegotiated congestion; and a heuristic method implemented in D-Wave's SolverAPI package. A set of benchmark QCA networks is used to characterise thealgorithms and a stochastic circuit generator is employed to investigate theperformance for different processor sizes and active flux-qubit yields.

Algorithms for Embedding Quantum-Dot Cellular Automata Networks onto a Quantum Annealing Processor