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.
Supported by the JPL Information and Computing Technologies Research Section.
Supported by the NASA/JPL Center for Integrated Space Microsystems and by the JPL Information and Computing Technologies Research Section.
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© 1999 Springer-Verlag Berlin Heidelberg
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Zak, M., Williams, C.P. (1999). Quantum Recurrent Networks for Simulating Stochastic Processes. In: Williams, C.P. (eds) Quantum Computing and Quantum Communications. QCQC 1998. Lecture Notes in Computer Science, vol 1509. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-49208-9_5
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DOI: https://doi.org/10.1007/3-540-49208-9_5
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