Abstract
Researches in natural neuron dynamics have shown that phase transition and chaos provide optimal behaviour for information processing. In artificial neural models that behavior is expected also to maximize the neuron learnability. By employing an open quantum systems approach, we propose a new quantum information extraction method in the quantum RAM node dynamics where complex values are iterated. We experimentally show bifurcation and chaos emergence by varying their parameters.
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