Negative Refractive Index in Optics of Metal-Dielectric Composites

Specially designed metal-dielectric composites can have a negative refractive index in the optical range. Specifically, it is shown that arrays of single and paired nanorods can provide such negative refraction. For pairs of metal rods, a negative refractive index has been observed at 1.5 micrometer. The inverted structure of paired voids in metal films may also exhibit a negative refractive index. A similar effect can be accomplished with metal strips in which the refractive index can reach -2. The refractive index retrieval procedure and the critical role of light phases in determining the refractive index is discussed.Comment: 39 pages, 17 figures, 24 equation

Always Keep your Target in Mind: Studying Semantics and Improving Performance of Neural Lexical Substitution

Lexical substitution, i.e. generation of plausible words that can replace a particular target word in a given context, is an extremely powerful technology that can be used as a backbone of various NLP applications, including word sense induction and disambiguation, lexical relation extraction, data augmentation, etc. In this paper, we present a large-scale comparative study of lexical substitution methods employing both rather old and most recent language and masked language models (LMs and MLMs), such as context2vec, ELMo, BERT, RoBERTa, XLNet. We show that already competitive results achieved by SOTA LMs/MLMs can be further substantially improved if information about the target word is injected properly. Several existing and new target word injection methods are compared for each LM/MLM using both intrinsic evaluation on lexical substitution datasets and extrinsic evaluation on word sense induction (WSI) datasets. On two WSI datasets we obtain new SOTA results. Besides, we analyze the types of semantic relations between target words and their substitutes generated by different models or given by annotators.Comment: arXiv admin note: text overlap with arXiv:2006.0003

Sub-diffraction light propagation in fibers with anisotropic dielectric cores

We present a detailed study of light propagation in waveguides with anisotropic metamaterial cores. We demonstrate that in contrast to conventional optical fibers, our structures support free-space-like propagating modes even when the waveguide radius is much smaller than the wavelength. We develop analytical formalism to describe mode structure and propagation in strongly anisotropic systems and study the effects related to waveguide boundaries and material composition

Meta-material photonic funnels for sub-diffraction light compression and propagation

We present waveguides with photonic crystal cores, supporting energy propagation in subwavelength regions with a mode structure similar to that in telecom fibers. We design meta-materials for near-, mid-, and far-IR frequencies, and demonstrate efficient energy transfer to and from regions smaller than 1/25-th of the wavelength. Both positive- and negative-refractive index light transmissions are shown. Our approach, although demonstrated here in circular waveguides for some specific frequencies, is easily scalable from optical to IR to THz frequency ranges, and can be realized in a variety of waveguide geometries. Our design may be used for ultra high-density energy focusing, nm-resolution sensing, near-field microscopy, and high-speed all-optical computing.Comment: 4 pages, 3 figures, texify read

Gain-assisted slow to superluminal group velocity manipulation in nano-waveguides

We study the energy propagation in subwavelength waveguides and demonstrate that the mechanism of material gain, previously suggested for loss compensation, is also a powerful tool to manipulate dispersion and propagation characteristics of electromagnetic pulses at the nanoscale. We show theoretically that the group velocity in lossy nano-waveguides can be controlled from slow to superluminal values by the material gain and waveguide geometry and develop an analytical description of the relevant physics. We utilize the developed formalism to show that gain-assisted dispersion management can be used to control the transition between ``photonic-funnel'' and ``photonic-compressor'' regimes in tapered nano-waveguides. The phenomenon of strong modulation of group velocity in subwavelength structures can be realized in waveguides with different geometries, and is present for both volume and surface-modes.Comment: Some changes in the abstract and Fig.1. No results affecte

Active metamaterials: sign of refraction index and gain-assisted dispersion management

We derive an approach to define the causal direction of the wavevector of modes in optical metamaterials, which in turn, determines signs of refractive index and impedance as a function of {\it real and imaginary} parts of dielectric permittivity and magnetic permeability. We use the developed technique to demonstrate that the interplay between resonant response of constituents of metamaterials can be used to achieve efficient dispersion management. Finally we demonstrate broadband dispersion-less index and impedance matching in active nanowire-based negative index materials. Our work opens new practical applications of negative index composites for broadband lensing, imaging, and pulse-routing

Revisiting Mahalanobis Distance for Transformer-Based Out-of-Domain Detection

Real-life applications, heavily relying on machine learning, such as dialog systems, demand out-of-domain detection methods. Intent classification models should be equipped with a mechanism to distinguish seen intents from unseen ones so that the dialog agent is capable of rejecting the latter and avoiding undesired behavior. However, despite increasing attention paid to the task, the best practices for out-of-domain intent detection have not yet been fully established. This paper conducts a thorough comparison of out-of-domain intent detection methods. We prioritize the methods, not requiring access to out-of-domain data during training, gathering of which is extremely time- and labor-consuming due to lexical and stylistic variation of user utterances. We evaluate multiple contextual encoders and methods, proven to be efficient, on three standard datasets for intent classification, expanded with out-of-domain utterances. Our main findings show that fine-tuning Transformer-based encoders on in-domain data leads to superior results. Mahalanobis distance, together with utterance representations, derived from Transformer-based encoders, outperforms other methods by a wide margin and establishes new state-of-the-art results for all datasets. The broader analysis shows that the reason for success lies in the fact that the fine-tuned Transformer is capable of constructing homogeneous representations of in-domain utterances, revealing geometrical disparity to out of domain utterances. In turn, the Mahalanobis distance captures this disparity easily.Comment: to appear in AAAI 202

GEC-DePenD: Non-Autoregressive Grammatical Error Correction with Decoupled Permutation and Decoding

Grammatical error correction (GEC) is an important NLP task that is currently usually solved with autoregressive sequence-to-sequence models. However, approaches of this class are inherently slow due to one-by-one token generation, so non-autoregressive alternatives are needed. In this work, we propose a novel non-autoregressive approach to GEC that decouples the architecture into a permutation network that outputs a self-attention weight matrix that can be used in beam search to find the best permutation of input tokens (with auxiliary {ins} tokens) and a decoder network based on a step-unrolled denoising autoencoder that fills in specific tokens. This allows us to find the token permutation after only one forward pass of the permutation network, avoiding autoregressive constructions. We show that the resulting network improves over previously known non-autoregressive methods for GEC and reaches the level of autoregressive methods that do not use language-specific synthetic data generation methods. Our results are supported by a comprehensive experimental validation on the ConLL-2014 and Write&Improve+LOCNESS datasets and an extensive ablation study that supports our architectural and algorithmic choices.Comment: ACL 202

Plasmonic Nanolayer Composites: Coupled Plasmon Polaritons, Effective-Medium Response, and Subdiffraction Light Manipulation

We analyze the evolution of the modes in nanoplasmonic multilayered structures and study the transition of the optical properties of these systems to the effective-medium regime. We derive the effective-medium parameters and study the validity of our analytical results with exact numerical solutions of Maxwell equations. Finally, we explore the applications of multilayered systems for subwavelength light confinement in planar and circular waveguides