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The co-location of memory and processing is a core principle of neuromorphiccomputing. A local memory device for synaptic weight storage has long beenrecognized as an enabling element for large-scale, high-performanceneuromorphic hardware. In this work, we demonstrate programmablesuperconducting synapses with integrated memories for use in superconductingoptoelectronic neural systems. Superconducting nanowire single-photon detectorsand Josephson junctions are combined into programmable synaptic circuits thatexhibit single-photon sensitivity, memory cells with more than 400 internalstates, leaky integration of input spike events, and 0.4 fJ programmingenergies (including cooling power). These results are attractive forimplementing a variety of supervised and unsupervised learning algorithms andlay the foundation for a new hardware platform optimized for large-scalespiking network accelerators.

Programmable Superconducting Optoelectronic Single-Photon Synapses with Integrated Multi-State Memory