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arXiv:1012.2864 · Nature Communications

Scalable architecture for a room temperature solid-state quantum information processor

Norman Y. Yao, Liang Jiang, Alexey Vyacheslavovich Gorshkov, Peter C. Maurer, G. Giedke, J. I. Cirac, Mikhail D. Lukin

Published Apr 24, 2012• 250 citations
arXivHTMLPDF
DOI
10.1038/ncomms1788

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This paper presents a modular hardware / software architecture suited to scalable, configurable quantum processors based upon room-temperature quantum materials and control devices. The principle of operation and salient features of the quantum materials and devices are discussed. Further, we propose to apply this architecture for implementation in a quantum probabilistic learning machine as well as a quantum probabilistic decision engine, both of which are well suited to learning unknown correlations in uncertain or stochastic dynamic processes/systems from operational data and support decision-making under uncertainty. As an example, case studies of quantum algorithms are presented to illustrate the modular software design options and demonstrate the potential of moving quantum algorithms to quantum processors. A plan for future work is also identified.
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