Related papers: High-resolution and ultra-low power nonlinear imag…
This paper introduces a method based on a deep neural network (DNN) that is perfectly capable of processing radar data from extremely thinned radar apertures. The proposed DNN processing can provide both aliasing-free radar imaging and…
High resolution image sensors require electrical access to each individual pixel for signal readout. Such access is especially challenging for ultra-miniaturized pixels, for heterogeneously integrated sensing and readout layers in…
High-transmissivity all-dielectric metasurfaces have recently attracted attention towards the realization of ultra-compact optical devices and systems. Silicon based metasurfaces, in particular, are highly promising considering the…
Metasurfaces are planar structures that locally modify the polarization, phase, and amplitude of light in reflection or transmission, thus enabling lithographically patterned flat optical components with functionalities controlled by…
The aim of this communication is to investigate and demonstrate the possibility to overcome the fundamental limitations of mantle cloaking for antennas by exploiting nonlinear metasurfaces. First, we recap and give additional physical…
In this work we present an ultra low energy, 'on-sensor' image processing architecture, based on cellular array of spin based neurons. The 'neuron' constitutes of a lateral spin valve (LSV) with multiple input magnets, connected to an…
Metasurfaces provide a versatile and compact approach to free-space optical manipulation and wavefront shaping. Comprised of arrays of judiciously-arranged dipolar resonators, metasurfaces precisely control the amplitude, polarization, and…
This work presents a non-local terahertz metasurface integrated into a leaky-wave antenna for robust, wide-angle beam steering. The metasurface encodes a holographic pattern by explicitly inducing tangential and normal susceptibilities,…
Neuromorphic Computing implemented in photonic hardware is one of the most promising routes towards achieving machine learning processing at the picosecond scale, with minimum power consumption. In this work, we present a new concept for…
Nonreciprocity is important for optical information processing, full-duplex communications, and protection of sensitive laser equipment from unwanted reflections. However, it is very challenging to obtain strong nonreciprocal response in…
We report on the development of transmission-line reflectionless filters operating with passbands at 100 GHz and 230 GHz, and stopband absorption up to 500 GHz, the highest operating frequencies yet recorded for such filters. The designs…
Quantum imaging employs the nonclassical correlation of photons to break through the noise limitation of classical imaging, realizing high sensitivity, high SNR imaging and multifunctional image processing. To enhance the flexibility and…
Metasurfaces represent a new frontier in materials science paving for unprecedented methods of controlling electromagnetic waves, with a range of applications spanning from sensing to imaging and communications. For pulsed terahertz…
The development of responsive metamaterials has enabled the realization of compact tunable photonic devices capable of manipulating the amplitude, polarization, wave vector, and frequency of light. Integration of semiconductors into the…
Plasmonic nanolasers have ultrahigh lasing thresholds, especially those devices for which all three dimensions are truly subwavelength. Because of a momentum mismatch between the propagating light and localized optical field of the…
Fourier optical processing underpins optical information manipulation, yet extending such operations to short wavelengths within compact platforms remains challenging. Here, we address this challenge by embedding reconfigurable…
Nowadays, many applications rely on images of high quality to ensure good performance in conducting their tasks. However, noise goes against this objective as it is an unavoidable issue in most applications. Therefore, it is essential to…
Neural networks have proven effective for solving many difficult computational problems. Implementing complex neural networks in software is very computationally expensive. To explore the limits of information processing, it will be…
The physical implementation of artificial intelligence requires mapping computational processes onto the dynamic physical processes of the underlying computing platform. The photonic processors offer an intrinsically parallel and low energy…
Blur was naturally analyzed in the frequency domain, by estimating the latent sharp image and the blur kernel given a blurry image. Recent progress on image deblurring always designs end-to-end architectures and aims at learning the…