Related papers: Programmable Superconducting Optoelectronic Single…
The realization of large-scale photonic circuit for quantum optics experiments at telecom wavelengths requires an increasing number of integrated detectors. Superconductive nanowire single photon detectors (SNSPDs) can be easily integrated…
Neuromorphic photonics that aims to process and store information simultaneously like human brains has emerged as a promising alternative for the next generation intelligent computing systems. The implementation of hardware emulating the…
Neuromorphic computing uses brain-inspired principles to design circuits that can perform computational tasks with superior power efficiency to conventional computers. Approaches that use traditional electronic devices to create artificial…
Neural networks and neuromorphic computing play pivotal roles in deep learning and machine vision. Due to their dissipative nature and inherent limitations, traditional semiconductor-based circuits face challenges in realizing ultra-fast…
Interfacing single-photon detectors with active photonic components is a cornerstone photonic quantum technology. We describe how the output signal of commercial superconducting nanowire single-photon detectors can be used in situ to drive…
The circuits comprising superconducting optoelectronic synapses, dendrites, and neurons are described by numerically cumbersome and formally opaque coupled differential equations. Reference 1 showed that a phenomenological model of…
Single-photon detectors and nanoscale superconducting devices are two major candidates for realizing quantum technologies. Superconducting-nanowire single-photon detectors (SNSPDs) comprise these two solid-state and optic aspects enabling…
Artificial neural networks inspired by brain operations can improve the possibilities of solving complex problems more efficiently. Today's computing hardware, on the other hand, is mainly based on von Neumann architecture and CMOS…
Over the past decade Spiking Neural Networks (SNN) have emerged as one of the popular architectures to emulate the brain. In SNN, information is temporally encoded and communication between neurons is accomplished by means of spikes. In…
Highly efficient information processing in brain is based on processing and memory components called synapses, whose output is dependent on the history of the signals passed through them. Here we have developed an artificial synapse with…
Superconducting nanowire single-photon detectors promise efficient (~100%) and fast (~Gcps) detection of light at the single-photon level. They constitute one of the building blocks to realize integrated quantum optical circuits in a…
Mixed-signal analog/digital circuits emulate spiking neurons and synapses with extremely high energy efficiency, an approach known as "neuromorphic engineering". However, analog circuits are sensitive to process-induced variation among…
Single flux quantum (SFQ) circuits form a natural neuromorphic technology with SFQ pulses and superconducting transmission lines simulating action potentials and axons, respectively. Here we present a new component, magnetic Josephson…
Superconducting nanowire single-photon detectors (SNSPDs) are efficient measurement devices used for counting single photons. The field of their applications covers experimental quantum-optical studies, optical quantum computing, quantum…
Superconducting nanowire single photon detectors (SNSPDs) offer high-quantum-efficiency and low-dark-count-rate single photon detection. In a growing number of cases, large magnetic fields are being incorporated into quantum microscopes,…
Spiking neural networks (SNN) provide a new computational paradigm capable of highly parallelized, real-time processing. Photonic devices are ideal for the design of high-bandwidth, parallel architectures matching the SNN computational…
Photonic integrated circuits (PICs) have emerged as a scalable platform for complex quantum technologies using photonic and atomic systems. A central goal has been to integrate photon-resolving detectors to reduce optical losses, latency,…
A neuromorphic chip that combines CMOS analog spiking neurons and memristive synapses offers a promising solution to brain-inspired computing, as it can provide massive neural network parallelism and density. Previous hybrid analog…
Neuromorphic computing is poised to further the success of software-based neural networks by utilizing improved customized hardware. However, the translation of neuromorphic algorithms to hardware specifications is a problem that has been…
We present a novel design of a superconducting nanowire single photon detector (SNSPD) fabricated on a core of a single mode optical fiber. The proposed design allows high overlap between the fiber light mode and the detector, and…