Recent years have seen a rapid expansion of research into nanophotonics based on surface plasmon–polaritons. These electromagnetic waves propagate along metal–dielectric interfaces and can be guided by metallic nanostructures beyond the diffraction limit. This remarkable capability has unique prospects for the design of highly integrated photonic signal-processing systems, nanoresolution optical imaging techniques and sensors. This Review summarizes the basic principles and major achievements of plasmon guiding, and details the current state-of-the-art in subwavelength plasmonic waveguides, passive and active nanoplasmonic components for the generation, manipulation and detection of radiation, and configurations for the nanofocusing of light. Potential future developments and applications of nanophotonic devices and circuits are also discussed, such as in optical signals processing, nanoscale optical devices and near-field microscopy with nanoscale resolution.

Plasmonics beyond the diffraction limit

In 1873, Ernst Abbe discovered what was to become a well-known paradigm: the inability of a lens-based optical microscope to discern details that are closer together than half of the wavelength of light. However, for its most popular imaging mode, fluorescence microscopy, the diffraction barrier is crumbling. Here, I discuss the physical concepts that have pushed fluorescence microscopy to the nanoscale, once the prerogative of electron and scanning probe microscopes. Initial applications indicate that emergent far-field optical nanoscopy will have a strong impact in the life sciences and in other areas benefiting from nanoscale visualization.

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Far-Field Optical Nanoscopy

Artificially engineered metamaterials are now demonstrating unprecedented electromagnetic properties that cannot be obtained with naturally occurring materials. In particular, they provide a route to creating materials that possess a negative refractive index and offer exciting new prospects for manipulating light. This review describes the recent progress made in creating nanostructured metamaterials with a negative index at optical wavelengths, and discusses some of the devices that could result from these new materials.

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Optical negative-index metamaterials

Metamaterials, or engineered materials with rationally designed, subwavelength-scale building blocks, allow us to control the behavior of physical fields in optical, microwave, radio, acoustic, heat transfer, and other applications with flexibility and performance that are unattainable with naturally available materials. In turn, metasurfaces-planar, ultrathin metamaterials-extend these capabilities even further. Optical metasurfaces offer the fascinating possibility of controlling light with surface-confined, flat components. In the planar photonics concept, it is the reduced dimensionality of the optical metasurfaces that enables new physics and, therefore, leads to functionalities and applications that are distinctly different from those achievable with bulk, multilayer metamaterials. Here, we review the progress in developing optical metasurfaces that has occurred over the past few years with an eye toward the promising future directions in the field.

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Planar Photonics with Metasurfaces

We present the science and technology roadmap for graphene, related two-dimensional crystals, and hybrid systems, targeting an evolution in technology, that might lead to impacts and benefits reaching into most areas of society. This roadmap was developed within the framework of the European Graphene Flagship and outlines the main targets and research areas as best understood at the start of this ambitious project. We provide an overview of the key aspects of graphene and related materials (GRMs), ranging from fundamental research challenges to a variety of applications in a large number of sectors, highlighting the steps necessary to take GRMs from a state of raw potential to a point where they might revolutionize multiple industries. We also define an extensive list of acronyms in an effort to standardize the nomenclature in this emerging field.

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Science and technology roadmap for graphene, related two-dimensional crystals, and hybrid systems

Metallic films with subwavelength apertures integrated into a semiconductor exhibit broadband enhancement of light coupling into the semiconductor (compared to an unstructured surface) while providing near uniform electrical contact for potential integration into optoelectronic devices.

Buried extraordinary optical transmission

We demonstrate that in lasers with non-integrable resonators, chaos-assisted tunneling leads to dramatic changes in the emission spectrum, removing the near-degeneracy of symmetry-related doublets and changing the lifetimes of high-Q modes by several orders of magnitude. Our theory is in quantitative agreement with numerical simulations.

Chaos-assisted tunneling in microlasers with partially chaotic resonators

Given their ability to effectively learn non-linear mappings and perform fast inference, deep neural networks (NNs) have been proposed as a viable alternative to traditional simulation-driven approaches for solving high-dimensional eigenvalue equations (HDEs), which are the foundation for many scientific applications. Unfortunately, for the learnedmodels in these scientific applications to achieve generalization, a large, diverse, and preferably annotated dataset is typically needed and is computationally expensive to obtain. Furthermore, the learned models tend to be memory– and compute–intensive primarily due to the size of the output layer. While generalization, especially extrapolation, with scarce data has been attempted by imposing physical constraints in the form of physics loss, the problem of model scalability has remained. In this paper, we alleviate the compute bottleneck in the output layer by using physics knowledge to decompose the complex regression task of predicting the high-dimensional eigenvectors into multiple simpler sub-tasks, each of which are learned by a simple “expert" network.We call the resulting architecture of specialized experts Physics-Guided Mixture-of-Experts (PG-MoE). We demonstrate the efficacy of such physics-guided problem decomposition for the case of the Schrödinger Equation in Quantum Mechanics. Our proposed PG-MoE model predicts the ground-state solution, i.e., the eigenvector that corresponds to the smallest possible eigenvalue. The model is 150× smaller than the network trained to learn the complex task while being competitive in generalization. To improve the generalization of the PG-MoE, we also employ a physics-guided loss function based on variational energy, which by quantum mechanics principles is minimized iff the output is the ground-state solution.

Physics-Guided Problem Decomposition for Scaling Deep Learning of High-dimensional Eigen-Solvers: The Case of Schrödinger's Equation

We demonstrate an order of magnitude enhancement of emission from mid-infrared emitters monolithically integrated with semiconductor designer metals relative to the same emitters on dielectric substrates and provide theoretical explanation of the observed phenomena.

Enhanced Emission from Ultra-Thin Long Wavelength Infrared Superlattices on Epitaxial Plasmonic Materials

We present novel "ratchet" resonators. Due to dynamical localization of resonant modes and broken symmetry between positive and negative angular momenta, these devices show increased efficiency of light trapping and can be used for sensing applications.

Viktor A. Podolskiy

Papers

Buried extraordinary optical transmission

Chaos-assisted tunneling in microlasers with partially chaotic resonators

Physics-Guided Problem Decomposition for Scaling Deep Learning of High-dimensional Eigen-Solvers: The Case of Schrödinger's Equation

Enhanced Emission from Ultra-Thin Long Wavelength Infrared Superlattices on Epitaxial Plasmonic Materials

Optical ratchet resonators