Algorithms for Embedding Quantum-Dot Cellular Automata Networks onto a Quantum Annealing Processor
Abstract
Advancements in computing based on qubit networks, and in particular the flux-qubit processor architecture developed by D-Wave System's Inc., have enabled the physical simulation of quantum-dot cellular automata (QCA) networks beyond the limit of classical methods. However, the embedding of QCA networks onto the available processor architecture is a key challenge in preparing such simulations. In this work, two approaches to embedding QCA circuits are characterized: a dense placement algorithm that uses a routing method based on negotiated congestion; and a heuristic method implemented in D-Wave's Solver API package. A set of benchmark QCA networks is used to characterise the algorithms and a stochastic circuit generator is employed to investigate the performance for different processor sizes and active flux-qubit yields.
Cite
@article{arxiv.1709.04972,
title = {Algorithms for Embedding Quantum-Dot Cellular Automata Networks onto a Quantum Annealing Processor},
author = {Jacob Retallick and Michael Babcock and Miguel Aroca-Ouellette and Shane McNamara and Steve Wilton and Aidan Roy and Mark Johnson and Konrad Walus},
journal= {arXiv preprint arXiv:1709.04972},
year = {2017}
}