Capacity and Energy Efficiency of TeraHertz Surface Wave Interconnects

The potential of geometrically induced terahertz surface wave technology for communications can only be realized if communication links based on them are studied and benchmarked. The frequency-dependent transmission characteristics of interconnects based on three different archetypal textured surfaces (namely, gratings, dominos, nails) are analyzed numerically and the impact of the geometry and realistic surface roughness on the maximum capacity and energy efficiency is quantified. Unlike conventional hollow waveguides, the analysis shows that the capacity of uncoated corrugated surfaces is limited by loss and not dispersion. This work provides the guidelines for the design of terahertz surface wave interconnects

A Computationally-Inexpensive Strategy in CT Image Data Augmentation for Robust Deep Learning Classification in the Early Stages of an Outbreak

Coronavirus disease 2019 (COVID-19) has spread globally for over three years, and chest computed tomography (CT) has been used to diagnose COVID-19 and identify lung damage in COVID-19 patients. Given its widespread, CT will remain a common diagnostic tool in future pandemics, but its effectiveness at the beginning of any pandemic will depend strongly on the ability to classify CT scans quickly and correctly when only limited resources are available, as it will happen inevitably again in future pandemics. Here, we resort into the transfer learning procedure and limited hyperparameters to use as few computing resources as possible for COVID-19 CT images classification. Advanced Normalisation Tools (ANTs) are used to synthesise images as augmented/independent data and trained on EfficientNet to investigate the effect of synthetic images. On the COVID-CT dataset, classification accuracy increases from 91.15% to 95.50% and Area Under the Receiver Operating Characteristic (AUC) from 96.40% to 98.54%. We also customise a small dataset to simulate data collected in the early stages of the outbreak and report an improvement in accuracy from 85.95% to 94.32% and AUC from 93.21% to 98.61%. This study provides a feasible Low-Threshold, Easy-To-Deploy and Ready-To-Use solution with a relatively low computational cost for medical image classification at an early stage of an outbreak in which scarce data are available and traditional data augmentation may fail. Hence, it would be most suitable for low-resource settings

Conformal transformation in bowtie nanoantennas and nanocavities: unveiling hidden symmetries

In this work, bowtie nanoantennas and nanocavities are analyzed using the conformal transformation technique. Their performance is studied in terms of the non-radiative Purcell enhancement and self-induced optical forces experienced by quantum emitters. It is demonstrated how these two geometrically different plasmonic nanoparticles can share the same non-radiative Purcell spectra. This hidden symmetric response is unveiled by properly applying the conformal transformation technique, demonstrating that both nanoparticles share the same transformed geometry

Bridging the hydrodynamic Drude model and local transformation optics theory

The recent ability of plasmonic nanostructures to probe subnanometer and even atomic scales demands theories that can account for the nonlocal dynamics of the electron gas. The hydrodynamic Drude model (HDM) captures much of the microscopic dynamics of the quantum mechanical effects when additional boundary conditions are considered. Here, we revisit the HDM under the Madelung formalism to reexpress its coupled system of equations as a single nonlinear Schrödinger equation in order to have a natural quantum mechanical description of plasmonics. Specifically, we study the response of two overlapping nanowires with this formalism. We ensure that an proposed frame concurs with classical electrodynamics when the local response approximation holds in the plasmonic system by finding the correction needed

Impact of plasmonic bowtie nanoantennas and nanocavities on the dynamics of nearby nanoemitters

Metallic nanoparticles exert a strong influence on the electrodynamics and mechanical dynamics of nanoemitters in their vicinity. Transformation optics can provide analytical descriptions and physical insight on these scenarios. As a case of study, we discuss the use of conformal transformation to understand the nonradiative Purcell enhancement and the optical forces experienced by nanoemitters nearby bowtie nanocavities and nanoantennas

Low Sidelobe Level Millimeter-Wave Asymmetric Bull’s Eye Antenna with Minimal Profile Feeding

Bull’s eye antennas exhibit remarkable directivity considering their low profile, albeit accompanied by high sidelobes. This undesirable radiation characteristic is tackled here by reporting a complementary split ring feeding whereby the broadside space-wave partially responsible for the high sidelobes is cancelled while the leaky-wave is excited effectively. This feeding results into an asymmetric bull’s eye antenna with minimal profile (∼0.73λ0) and no protrusions on the radiating interface. The fabricated 10 period antenna operating in the Ka band shows a directivity of 23.5 dBi, a sidelobe level of -22.9 dB (>6 dB improvement compared to other bull’s eye antennas) and a beamwidth of 3.7◦ and 6.7◦ in the E- and H-plane, respectively