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Neuromorphic computing would benefit from the utilization of improved customized hardware. However, the translation of neuromorphic algorithms to hardware is not easily accomplished. In particular, building superconducting neuromorphic systems requires expertise in both supercon- ducting physics and theoretical neuroscience, which makes such design particularly challenging. In this work, we aim to bridge this gap by presenting a tool and methodology to translate algorith- mic parameters into circuit specifications. We first show the correspondence between theoretical neuroscience models and the dynamics of our circuit topologies. We then apply this tool to solve a linear system and implement Boolean logic gates by creating spiking neural networks with our superconducting nanowire-based hardware. 

Neuromorphic computing would benefit from the utilization of improved customized hardware. However, the translation of neuromorphic algorithms to hardware is not easily accomplished. In particular, building superconducting neuromorphic systems requires expertise in both superconducting physics and theoretical neuroscience, which makes such design particularly challenging. In this work, we aim to bridge this gap by presenting a tool and methodology to translate algorithmic parameters into circuit specifications. We first show the correspondence between theoretical neuroscience models and the dynamics of our circuit topologies. We then apply this tool to solve a linear system and implement Boolean logic gates by creating spiking neural networks with our superconducting nanowire-based hardware. 

In this work, we investigate multiphoton and optical field tunneling emission from metallic surfaces with nanoscale vacuum gaps. Using time-dependent Schrödinger equation (TDSE) simulations, we find that the properties of the emitted photocurrent in such systems can be greatly altered by the application of only a few-volt direct current (DC) bias. We find that when coupled with expected plasmonic enhancements within the nanometer-scale metallic gaps, the application of this DC bias significantly reduces the threshold for the transition to optical-field-driven tunneling from the metal surface, and could sufficiently enhance the emitted photocurrents, to make it feasible to electronically tag fJ ultrafast pulses at room temperature. Given the petahertz-scale instantaneous response of the photocurrents, and the low effective capacitance of thin-film nanoantenna devices that enables$<<\#comment/>1\mathrm{f}\mathrm{s}$response time, detectors that exploit this bias-enhanced surface emission from nanoscale vacuum gaps could prove to be useful for communication, petahertz electronics, and ultrafast optical-field-resolved metrology.