Related papers: On-chip rewritable phase-change metasurface for pr…
Photonic brain-inspired platforms are emerging as novel analog computing devices, enabling fast and energy-efficient operations for machine learning. These artificial neural networks generally require tailored optical elements, such as…
Phase-change materials (PCMs) have emerged as key enablers of non-volatile, ultra-compact photonic switches for energy-efficient deep neural network (DNN) applications. In this work, we investigate the recently discovered…
The proliferation of deep learning applications has intensified the demand for electronic hardware with low energy consumption and fast computing speed. Neuromorphic photonics have emerged as a viable alternative to directly process…
Recently, interest in programmable photonics integrated circuits has grown as a potential hardware framework for deep neural networks, quantum computing, and field programmable arrays (FPGAs). However, these circuits are constrained by the…
Femtosecond laser writing is a powerful technique that allows rapid and cost-effective fabrication of photonic integrated circuits with unique three-dimensional geometries. In particular, the possibility to reconfigure such devices by…
Capping layers are essential for protecting phase change materials (PCMs) used in non-volatile photonics technologies. This work demonstrates how $(ZnS)_{0.8}-(SiO_2)_{0.2}$ caps radically influence the performance of $Sb_{2}S_{3}$ and…
In this letter, a wireless transmitter using the new architecture of programmable metasurface is presented. The proposed transmitter does not require any filter, nor wideband mixer or wideband power amplifier, thereby making it a promising…
Software-defined metasurfaces (SDMs) comprise a dense topology of basic elements called meta-atoms, exerting the highest degree of control over surface currents among intelligent panel technologies. As such, they can transform impinging…
Programmable integrated photonics has evolved into a potent platform for implementing diverse optical functions on a single chip through software-driven reconfiguration. At the core of these processors are the photonic waveguide meshes that…
Reconfigurable memristors featuring neural and synaptic functions hold great potential for neuromorphic circuits by simplifying system architecture, cutting power consumption, and boosting computational efficiency. Their additive…
Silicon photonics has become a key platform for photonic integrated circuits (PICs) due to its high refractive index and compatibility with complementary metal-oxide-semiconductor manufacturing. However, the inherent birefringence in…
Metasurfaces are ultrathin structures which are constituted by an array of subwavelength scatterers with designable scattering responses. They have opened up unprecedented exciting opportunities for extraordinary wave engineering processes.…
Laser-based manufacturing has emerged as a promising alternative to conventional thermal and mechanical processing owing to its precision, versatility, and ability to work across diverse materials. In particular, tailoring the spatial…
With the recent advances in optical phase change material (PCM), photonic in-memory neurocomputing has demonstrated its superiority in optical neural network (ONN) designs with near-zero static power consumption, time-of-light latency, and…
In this paper, we propose a novel fully programmable linear photonic processor, which we call LightPro, with improved scalability, performance, and footprint. At the heart of LightPro are compact, low-loss, and programmable silicon photonic…
Nanophotonics has garnered intensive attention due to its unique capabilities in molding the flow of light in the subwavelength regime. Metasurfaces (MSs) and photonic integrated circuits (PICs) enable the realization of mass-producible,…
Diffractive deep neural network (D2NN), also referred to as reconfigurable intelligent metasurface based deep neural networks (Rb-DNNs) or stacked intelligent metasurfaces (SIMs) in the field of wireless communications, has emerged as a…
Reservoir computing, renowned for its low training cost, has emerged as a promising lightweight paradigm for efficient spatiotemporal processing,it remains challenging to realize deep photonic reservoir computing (DPRC) systems, due to the…
Inverse design of nanoparticles for desired scattering spectra and dynamic switching between the two opposite scattering anomalies, i.e. superscattering and invisibility, is important in realizing cloaking, sensing and functional devices.…
Photonic technologies offer great prospects for novel ultrafast, energy-efficient and hardware-friendly neuromorphic (brain-like) computing platforms. Moreover, neuromorphic photonic approaches based upon ubiquitous, technology-mature and…