Quantum Recurrent Networks for Simulating Stochastic Processes

Michail Zak, Colin P. Williams

Published Apr 2, 2008• 1 citation

Abstract

Abstract. We introduce the concept of quantum recurrent networks by incorporating classical feedback loops into conventional quantum networks. We show that the dynamical evolution of such networks, which interleave quantum evolution with measurement and reset operations, exhibit novel dynamical properties finding application in pattern recognition, optimization and simulation. Moreover, decoherence in quantum recurrent networks is less problematic than in conventional quantum network architectures due to the modest phase coherence times needed for network operation.

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