Effects of disabled neurons in classical and quantum networks information processing

In this study, the effects of missing or broken elements on the memory preservation in classical and quantum neural networks are analyzed. The networks were built by considering each node as a bit or qubit neuron-like processing unit. The qubit-neurons are analyzed from two perspectives, one that involves consideration of quantum coupling between them alongside with specific network connections and another that uses only non quantum network connections between them. The same classical architecture and learning are applied to both networks that contain classical and quantum nodes. The analysis of memory preservation in such networks consists in monitoring changes in memory states as results of interruption of different connections between nodes. From this perspective, the comparative classical and quantum network response to broken or missing elements are analyzed, compared and contextualized.