Enhancing associative memory recall and storage capacity using confocal cavity QED

We introduce a near-term experimental platform for realizing an associative memory that outperforms the standard Hopfield neural network. It can simultaneously store many memories by using spinful bosons coupled to a degenerate multimode optical cavity. The associative memory is realized by a confocal cavity QED neural network, with the cavity modes serving as the synapses, connecting a network of superradiant atomic spin ensembles, which serve as the neurons. Memories are encoded in the connectivity matrix between the spins, and can be accessed through the input and output of patterns of light. Each aspect of the scheme is based on recently demonstrated technology using a confocal cavity and Bose-condensed atoms. The platform represents a new form of random spin system that can be controllably tuned between a ferromagnetic and a spin-glass regime. We find that the native spin dynamics, a form of discrete steepest descent, enhance the network's ability to store and recall memories beyond that of the standard Hopfield model. Surprisingly, the cavity QED dynamics can retrieve memories even when the system is deep in the spin glass phase, a regime in which associative memory was not thought to be possible.