Related papers: Surface nanoscale axial photonics
There exists a significant scale gap between photonic neural network integrated chips and neural networks, which hinders the deployment and application of photonic neural network. Here, we propose hardware-aware lightweight spiking neural…
Optical neural networks (ONNs) enable high speed parallel and energy efficient processing compared to conventional digital electronic counterparts. However, realizing large scale systems is an open problem. Among various integrated and…
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…
On-chip nanophotonics serves as the foundation for the new generation of information technology, but it is challenged by the diffraction limit of light. With the capabilities of confining light into (deep) subwavelength volumes, plasmonics…
Silicon has long been the foundational semiconductor material for a broad range of electronic devices, owing to its numerous advantages: wide natural availability, ease of synthesis in both crystalline and amorphous forms, and relatively…
The SuperNovae Analysis aPplication (SNAP) is a new tool for the analysis of SN observations and validation of SN models. SNAP consists of an open source relational database with (a) observational light curve, (b) theoretical light curve,…
Atomic-layer and two-dimensional (2D) materials have emerged as essential building blocks for next-generation quantum and semiconductor technologies, where atomic-scale control over light-matter interactions is critical. However, their…
On-chip quantum information processing requires controllable quantum light sources that can be operated on-demand at high-speeds and with the possibility of in-situ control of the photon emission wavelength and its optical polarization…
With high integration density and excellent optical properties, silicon photonics is becoming a promising platform for complete integration and large-scale optical quantum information processing. Scalable quantum information applications…
Surface plasmon resonances (SPRs) are crucial for confining light beyond the diffraction limit, yet heavy metal losses often limit their spectral localization. Here, we propose a practical strategy for enabling the spectral localization of…
Neuromorphic engineering has emerged as a promising avenue for developing brain-inspired computational systems. However, conventional electronic AI-based processors often encounter challenges related to processing speed and thermal…
Image enhancement is a critical task in computer vision and photography that is often entangled with noise. This renders the traditional Image Signal Processing (ISP) ineffective compared to the advances in deep learning. However, the…
Due to the large surface-to-volume ratio, surface trap states play a dominant role in the optoelectronic properties of nanoscale devices(1-6). Understanding the surface trap states allows us to properly engineer the device surfaces for…
Optimization-based filtering smoothes an image by minimizing a fidelity function and simultaneously preserves edges by exploiting a sparse norm penalty over gradients. It has obtained promising performance in practical problems, such as…
The successful development of future photonic quantum technologies heavily depends on the possibility of realizing robust, reliable and, crucially, scalable nanophotonic devices. In integrated networks, quantum emitters can be deployed as…
The study of optical phenomena on the subwavelength scale is becoming increasingly important in photonics, particularly in the fields of nanoemitters, photonic crystals and plasmonics. Subwavelength field patterns are evanescent and must…
Optical nanofibers confine light to subwavelength scales, and are of interest for the design, integration, and interconnection of nanophotonic devices. Here we demonstrate high transmission (> 97%) of the first family of excited modes…
We present a detailed investigation of the near-field optical response of core-shell nanoparticles using Fourier-demodulated full-wave simulations, revealing significant modifications to established contrast mechanisms in scattering-type…
Detecting non-classical light is a central requirement for photonics-based quantum technologies. Unrivaled high efficiencies and low dark counts have positioned superconducting nanowire single photon detectors (SNSPDs) as the leading…
As computing resource demands continue to escalate in the face of big data, cloud-connectivity and the internet of things, it has become imperative to develop new low-power, scalable architectures. Neuromorphic photonics, or photonic neural…