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Storage capacity of "quantum" neural networks.

We study the properties of quantum neural networks based on a two-state model a neuron, in which the two neural states correspond to an excited and a deexcited state. Transitions from the excited to the deexcited state are associated with emission of spikes, in analogy to photon-emission models in quantum optics. We consider strongly diluted networks with low firing rates and sparse encoding. We present simple analytic estimations of critical storage capacity of quantum neural networks