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The fields of machine learning and artificial intelligence drive researchers to explore energy-efficient, brain-inspired new hardware. Reservoir computing encompasses recurrent neural networks for sequential data processing and matches the…
The lack of interactions between single photons prohibits direct nonlinear operations in quantum optical circuits, representing a central obstacle in photonic quantum technologies. Here, we demonstrate multi-mode nonlinear photonic circuits…
Programmable photonic integrated circuits (PICs) are emerging as powerful tools for the precise manipulation of light, with applications in quantum information processing, optical range finding, and artificial intelligence. The leading…
The manipulation of geometrically constrained magnetic domain walls (DWs) in nanoscale magnetic strips has attracted much interest recently, with proposals for prospective memory and logic devices. Here we propose to use the high…
Deep learning is one of the most advancing technologies in various fields. Facing the limits of the current electronics platform, optical neural networks (ONNs) based on Si programmable photonic integrated circuits (PICs) have attracted…
Deep 'Analog Artificial Neural Networks' (ANNs) perform complex classification problems with remarkably high accuracy. However, they rely on humongous amount of power to perform the calculations, veiling the accuracy benefits. The…
Optical isolation is a long pursued object with fundamental difficulty in integrated photonics. As a step towards this goal, we demonstrate the design, fabrication, and characterization of on-chip wavelength-scale optical diodes that are…
As deep neural network (DNN) models grow ever-larger, they can achieve higher accuracy and solve more complex problems. This trend has been enabled by an increase in available compute power; however, efforts to continue to scale electronic…
Miniatured computational spectrometers, distinguished by their compact size and lightweight, have shown great promise for on-chip and portable applications in the fields of healthcare, environmental monitoring, food safety, and industrial…
Microwave photonics uses light to carry and process microwave signals over a photonic link. However, light can instead be used as a stimulus to microwave devices that directly control microwave signals. Such optically controlled amplitude…
Solid-state quantum emitters are excellent sources of on-demand indistinguishable or entangled photons and can host long-lived spin memories, crucial resources for photonic quantum information applications. However, their scalability…
The efficiency of photo-conductive switches, which continue to be used for the generation and detection of THz waves, has been overlooked for a long time. The so far 'optics-dominated' devices are making their way through to new and…
The miniaturization of diagnostic devices that exploit optical detection schemes requires the design of light-sources combining small size, high performance for effective excitation of chromophores, and mechanical flexibility for easy…
Emerging applications of photonics in computing, sensing, and security increasingly demand complex input-output behaviors, including highly nonlinear transformations of optical signals. Traditional photonic systems rely on highly structured…
Reconfigurable photonic devices capable of routing the flow of light enable flexible integrated-optic circuits that are not hard-wired but can be externally controlled. Analogous to free-space spatial light modulators, we demonstrate…
Silicon-organic hybrid (SOH) platforms exhibit exceptional electro-optic (EO) properties, including high-speed operation, low energy consumption, and compact footprints. However, the absence of a scalable poling method for EO polymers,…
Optical modulators are one of the most important elements of photonic circuits. Here, we designed, fabricated and characterized a nanophotonic all optical modulator (NOM) in silicon that is an order of magnitude smaller than any previous…
Adaptive optics in combination with multi-photon techniques is a powerful approach to image deep into a specimen. Remarkably, virtually all adaptive optics schemes today rely on wavefront modulators which are reflective, diffractive, or…
Numerous applications in quantum and classical optics require scalable, high-speed modulators that cover visible-NIR wavelengths with low footprint, drive voltage (V) and power dissipation. A critical figure of merit for electro-optic (EO)…
Software-implementation, via neural networks, of brain-inspired computing approaches underlie many important modern-day computational tasks, from image processing to speech recognition, artificial intelligence and deep learning…