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Neural networks are one of the disruptive computing concepts of our time. However, they fundamentally differ from classical, algorithmic computing in a number of fundamental aspects. These differences result in equally fundamental, severe…

Neural and Evolutionary Computing · Computer Science 2020-12-22 Xavier Porte , Anas Skalli , Nasibeh Haghighi , Stephan Reitzenstein , James A. Lott , Daniel Brunner

Structural coloration is commonly modeled using wave optics for reliable and photorealistic rendering of natural, quasi-periodic and complex nanostructures. Such models often rely on dense, preliminary or preprocessed data to accurately…

Graphics · Computer Science 2025-07-03 Narayan Kandel , Daljit Singh J. S. Dhillon

Diffractive neural networks hold great promise for applications requiring intensive computational processing. Considerable attention has focused on diffractive networks for either spatially coherent or spatially incoherent illumination.…

Optics · Physics 2025-03-25 Matan Kleiner , Lior Michaeli , Tomer Michaeli

All-dielectric metasurfaces consisting of arrays of nanostructured high-refractive-index materials, typically Si, are re-writing what is achievable in terms of the manipulation of light. Such devices support very strong magnetic, as well as…

Modern nanofabrication techniques have enabled us to manipulate the wavefront of light with sub-wavelength-scale structures, offering the potential to replace bulky refractive surfaces in conventional optics with ultrathin metasurfaces. In…

Emerging immersive visual communication technologies require light sources with complex functionality for dynamic control of polarization, directivity, wavefront, spectrum, and intensity of light. Currently, this is mostly achieved by free…

Flexible control light field across multiple parameters is the cornerstone of versatile and miniaturized optical devices. Metasurfaces, comprising subwavelength scatterers, offer a potent platform for executing such precise manipulations.…

High-quality flat optical elements require efficient light deflection to large angles and over a wide wavelength spectrum. Although phase gradient metasurfaces achieve this by continuously adding phase shifts in the range of 0 to 2{\pi} to…

Optics · Physics 2018-10-26 Claudio U. Hail , Dimos Poulikakos , Hadi Eghlidi

The recent progress of artificial intelligence (AI) has boosted the computational possibilities in fields where standard computers are not able to perform. The AI paradigm is to emulate human intelligence and therefore breaks the familiar…

Nonlinear metasurfaces are multifunctional photonic elements that generate and control light, enabling multiple proof-of-principle applications, such as in nonlinear holography, beam shaping, and nanoscale sources of entangled photon pairs.…

Optically levitated multiple nanoparticles has emerged as a platform for studying complex fundamental physics such as non-equilibrium phenomena, quantum entanglement, and light-matter interaction, which could be applied for sensing weak…

Optical neural networks (ONNs) perform extensive computations using photons instead of electrons, resulting in passively energy-efficient and low-latency computing. Among various ONNs, the diffractive optical neural networks (DONNs)…

Optically resonant dielectric metasurfaces offer unique capability to fully control the wavefront, polarisation, intensity or spectral content of light based on the excitation and interference of different electric and magnetic Mie…

Classification of features in a scene typically requires conversion of the incoming photonic field into the electronic domain. Recently, an alternative approach has emerged whereby passive structured materials can perform classification…

Nonlinear computation is essential for a wide range of information processing tasks, yet implementing nonlinear functions using optical systems remains a challenge due to the weak and power-intensive nature of optical nonlinearities.…

Optics · Physics 2025-11-10 Md Sadman Sakib Rahman , Yuhang Li , Xilin Yang , Shiqi Chen , Aydogan Ozcan

Nonlinear computation is essential for various information processing tasks. Optical implementations are attractive because passive light propagation can manipulate high-dimensional signals with extreme throughput and parallelism; yet…

Diffractive deep neural networks have been introduced earlier as an optical machine learning framework that uses task-specific diffractive surfaces designed by deep learning to all-optically perform inference, achieving promising…

Neural and Evolutionary Computing · Computer Science 2019-08-14 Jingxi Li , Deniz Mengu , Yi Luo , Yair Rivenson , Aydogan Ozcan

With its unique parallel processing capability, optical neural network has shown low-power consumption in image recognition and speech processing. At present, the manufacturing technology of programmable photonic chip is not mature, and the…

Emerging Technologies · Computer Science 2021-10-13 Qiuhao Wu , Jia Liu , Xiubao Sui , Liping Wang , Qian Chen

Metasurfaces are planar structures that can manipulate the amplitude, phase and polarization (APP) of light at subwavelength scale. Although various functionalities have been proposed based on metasurface, a most general optical control,…

Optics · Physics 2021-05-31 Yanjun Bao , Ying Yu , Shang Sun , Yang Chen , Qing-Hua Xu , Cheng-Wei Qiu

Computer-automated design and discovery have led to high-performance nanophotonic devices with diverse functionalities. However, massively multi-channel systems such as metasurfaces controlling many incident angles and photonic-circuit…

Applied Physics · Physics 2024-06-05 Shiyu Li , Ho-Chun Lin , Chia Wei Hsu
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