Deep physical neural networks trained with backpropagation

Nature, Journal Year: 2022, Volume and Issue: 601(7894), P. 549 - 555

Published: Jan. 26, 2022

Deep neural networks have become a pervasive tool in science and engineering. However, modern deep networks' growing energy requirements now increasingly limit their scaling broader use. We propose radical alternative for implementing network models: Physical Neural Networks. introduce hybrid physical-digital algorithm called Physics-Aware Training to efficiently train sequences of controllable physical systems act as networks. This method automatically trains the functionality any sequence real systems, directly, using backpropagation, same technique used To illustrate generality, we demonstrate with three diverse systems-optical, mechanical, electrical. may facilitate unconventional machine learning hardware that is orders magnitude faster more efficient than conventional electronic processors.

Language: Английский

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Polarisation optics for biomedical and clinical applications: a review

Light Science & Applications, Journal Year: 2021, Volume and Issue: 10(1)

Published: Sept. 22, 2021

Abstract Many polarisation techniques have been harnessed for decades in biological and clinical research, each based upon measurement of the vectorial properties light or transformations imposed on by objects. Various advanced vector measurement/sensing techniques, physical interpretation methods, approaches to analyse biomedically relevant information developed harnessed. In this review, we focus mainly summarising methodologies applications related tissue polarimetry, with an emphasis adoption Stokes–Mueller formalism. Several recent breakthroughs, development trends, potential multimodal uses conjunction other are also presented. The primary goal review is give reader a general overview use that can be obtained optics biomedical research.

Language: Английский

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Photonic matrix multiplication lights up photonic accelerator and beyond

Light Science & Applications, Journal Year: 2022, Volume and Issue: 11(1)

Published: Feb. 3, 2022

Abstract Matrix computation, as a fundamental building block of information processing in science and technology, contributes most the computational overheads modern signal artificial intelligence algorithms. Photonic accelerators are designed to accelerate specific categories computing optical domain, especially matrix multiplication, address growing demand for resources capacity. multiplication has much potential expand domain telecommunication, benefiting from its superior performance. Recent research photonic flourished may provide opportunities develop applications that unachievable at present by conventional electronic processors. In this review, we first introduce methods mainly including plane light conversion method, Mach–Zehnder interferometer method wavelength division multiplexing method. We also summarize developmental milestones related applications. Then, review their detailed advances neural networks recent years. Finally, comment on challenges perspectives acceleration.

Language: Английский

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Optical meta-waveguides for integrated photonics and beyond

Light Science & Applications, Journal Year: 2021, Volume and Issue: 10(1)

Published: Nov. 22, 2021

Abstract The growing maturity of nanofabrication has ushered massive sophisticated optical structures available on a photonic chip. integration subwavelength-structured metasurfaces and metamaterials the canonical building block waveguides is gradually reshaping landscape integrated circuits, giving rise to numerous meta-waveguides with unprecedented strength in controlling guided electromagnetic waves. Here, we review recent advances meta-structured that synergize various functional subwavelength architectures diverse waveguide platforms, such as dielectric or plasmonic fibers. Foundational results representative applications are comprehensively summarized. Brief physical models explicit design tutorials, either intuition-based methods computer algorithms-based inverse designs, cataloged well. We highlight how meta-optics can infuse new degrees freedom waveguide-based devices systems, by enhancing light-matter interaction drastically boost device performance, offering versatile designer media for manipulating light nanoscale enable novel functionalities. further discuss current challenges outline emerging opportunities this vibrant field biomedical sensing, artificial intelligence beyond.

Language: Английский

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Highlighting photonics: looking into the next decade

eLight, Journal Year: 2021, Volume and Issue: 1(1)

Published: June 7, 2021

Abstract Let there be light –to change the world we want to be! Over past several decades, and ever since birth of first laser, mankind has witnessed development science light, as light-based technologies have revolutionarily changed our lives. Needless say, photonics now penetrated into many aspects technology, turning an important dynamically changing field increasing interdisciplinary interest. In this inaugural issue eLight , highlight a few emerging trends in that think are likely major impact at least upcoming decade, spanning from integrated quantum computing, through topological/non-Hermitian topological insulator lasers, AI-empowered nanophotonics photonic machine learning. This Perspective is by no means attempt summarize all latest advances photonics, yet wish subjective vision could fuel inspiration foster excitement scientific research especially for young researchers who love .

Language: Английский

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Intelligent metasurfaces: control, communication and computing

eLight, Journal Year: 2022, Volume and Issue: 2(1)

Published: May 6, 2022

Abstract Controlling electromagnetic waves and information simultaneously by metasurfaces is of central importance in modern society. Intelligent are smart platforms to manipulate the wave–information–matter interactions without manual intervention synergizing engineered ultrathin structures with active devices algorithms, which evolve from passive composite materials for tailoring wave–matter that cannot be achieved nature. Here, we review recent progress intelligent controls providing historical background underlying physical mechanisms. Then explore application developing novel wireless communication architectures, particular emphasis on metasurface-modulated backscatter communications. We also wave-based computing using metasurfaces, focusing emerging research direction sensing. Finally, comment challenges highlight potential routes further developments controls, communications computing.

Language: Английский

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Quantum networks based on color centers in diamond

Journal of Applied Physics, Journal Year: 2021, Volume and Issue: 130(7)

Published: Aug. 16, 2021

With the ability to transfer and process quantum information, large-scale networks will enable a suite of fundamentally new applications, from communications distributed sensing, metrology, computing. This Perspective reviews requirements for network nodes color centers in diamond as suitable node candidates. We give brief overview state-of-the-art experiments employing discuss future research directions, focusing, particular, on control coherence qubits that distribute store entangled states, efficient spin–photon interfaces. route toward integrated devices combining with other photonic materials an outlook realistic protocol implementations applications.

Language: Английский

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Space-efficient optical computing with an integrated chip diffractive neural network

Nature Communications, Journal Year: 2022, Volume and Issue: 13(1)

Published: Feb. 24, 2022

Abstract Large-scale, highly integrated and low-power-consuming hardware is becoming progressively more important for realizing optical neural networks (ONNs) capable of advanced computing. Traditional experimental implementations need N 2 units such as Mach-Zehnder interferometers (MZIs) an input dimension to realize typical computing operations (convolutions matrix multiplication), resulting in limited scalability consuming excessive power. Here, we propose the diffractive network implementing parallel Fourier transforms, convolution application-specific using two ultracompact cells (Fourier transform operation) only MZIs. The footprint energy consumption scales linearly with data dimension, instead quadratic scaling traditional ONN framework. A ~10-fold reduction both consumption, well equal high accuracy previous MZI-based ONNs was experimentally achieved computations performed on MNIST Fashion-MNIST datasets. (IDNN) chip demonstrates a promising avenue towards scalable low-power-consumption computational chips optical-artificial-intelligence.

Language: Английский

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Quo Vadis, Metasurfaces?

Nano Letters, Journal Year: 2021, Volume and Issue: 21(13), P. 5461 - 5474

Published: June 23, 2021

The full manipulation of intrinsic properties electromagnetic waves has become the central target in various modern optical technologies. Optical metasurfaces have been suggested for a complete control light–matter interaction with subwavelength structures, and they explored widely past decade creating next-generation multifunctional flat-optics devices. current studies reached mature stage where common materials, basic physics, conventional engineering tools extensively applications such as light bending, metalenses, metaholograms, many others. A natural question is future research on will be going: Quo vadis, metasurfaces? In this Mini Review, we provide perspectives developments metasurfaces. Specifically, highlight recent progresses hybrid employing low-dimensional materials discuss biomedical, computational, quantum metasurfaces, followed by discussions challenges foreseeing metasurface physics engineering.

Language: Английский

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Metasurface-enabled on-chip multiplexed diffractive neural networks in the visible

Light Science & Applications, Journal Year: 2022, Volume and Issue: 11(1)

Published: May 27, 2022

Replacing electrons with photons is a compelling route toward high-speed, massively parallel, and low-power artificial intelligence computing. Recently, diffractive networks composed of phase surfaces were trained to perform machine learning tasks through linear optical transformations. However, the existing architectures often comprise bulky components and, most critically, they cannot mimic human brain for multitasking. Here, we demonstrate multi-skilled neural network based on metasurface device, which can on-chip multi-channel sensing multitasking in visible. The polarization multiplexing scheme subwavelength nanostructures applied construct classifier framework simultaneous recognition digital fashionable items. areal density neurons reach up 6.25 × 106 mm-2 multiplied by number channels. integrated mature complementary metal-oxide semiconductor imaging sensor, providing chip-scale architecture process information directly at physical layers energy-efficient ultra-fast image processing vision, autonomous driving, precision medicine.

Language: Английский

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