Non-classical computation has tended to consider only single computational models: neural, analog, quantum, etc. However, combined computational models can both have more computational power, and more natural programming approaches, than such 'pure' models alone. Here we outline a proposed new approach, which we term heterotic computing. We discuss how this might be incorporated in an accessible refinement-based computational framework for combining diverse computational models, and describe a range of physical exemplars (combinations of classical discrete, quantum discrete, classical analog, and quantum analog) that could be used to demonstrate the capability. © 2011 Springer-Verlag Berlin Heidelberg.
CITATION STYLE
Kendon, V., Sebald, A., Stepney, S., Bechmann, M., Hines, P., & Wagner, R. C. (2011). Heterotic computing. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6714 LNCS, pp. 113–124). https://doi.org/10.1007/978-3-642-21341-0_16
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