No Arabic abstract
Topological photonics has emerged as a novel paradigm for the design of electromagnetic systems from microwaves to nanophotonics. Studies to date have largely focused on the demonstration of fundamental concepts, such as non-reciprocity and waveguiding protected against fabrication disorder. Moving forward, there is a pressing need to identify applications where topological designs can lead to useful improvements in device performance. Here we review applications of topological photonics to ring resonator-based systems, including one- and two-dimensional resonator arrays, and dynamically-modulated resonators. We evaluate potential applications such as quantum light generation, disorder-robust delay lines, and optical isolation, as well as future research directions and open problems that need to be addressed.
We present a detailed study of electrical and optical generated free carrier on the spectral characteristics of a silicon microring modulator. The spectral distortion generated due to thermal and free carriers is presented, and the mechanism for mitigation is also presented. We observed that two-photon induced nonlinearity could be addressed by operating the modulator at suitable bias points. Furthermore, by applying small-signal drive the spectral distortion can be restored. We also present the effect of optical power and drive signal limit on the spectral characteristics. The study allows one to identify suitable device performance and operating conditions to utilize silicon ring modulator for optical signal processing.
Unidirectional photonic edge states arise at the interface between two topologically-distinct photonic crystals. Here, we demonstrate a micron-scale GaAs photonic ring resonator, created using a spin Hall-type topological photonic crystal waveguide. Embedded InGaAs quantum dots are used to probe the mode structure of the device. We map the spatial profile of the resonator modes, and demonstrate control of the mode confinement through tuning of the photonic crystal lattice parameters. The intrinsic chirality of the edge states makes them of interest for applications in integrated quantum photonics, and the resonator represents an important building block towards the development of such devices with embedded quantum emitters.
The Low Frequency Array (LOFAR) is under construction in the Netherlands and in several surrounding European countries. In this contribution, we describe the layout and design of the telescope, with a particular emphasis on the imaging characteristics of the array when used in its standard imaging mode. After briefly reviewing the calibration and imaging software used for LOFAR image processing, we show some recent results from the ongoing imaging commissioning efforts. We conclude by summarizing future prospects for the use of LOFAR in observing the little-explored low frequency Universe.
To enhance transmission efficiency of Pancharatnam-Berry (PB) phase metasurfaces, multilayer split-ring resonators were proposed to develop encoding sequences. As per the generalized Snell law, the deflection angle of the PB phase encoding metasurfaces depends on the metasurface period size. Therefore, it is impossible to design an infinitesimal metasurface unit.Consequently, the continuous transmission scattering angle cannot be obtained. In digital signal processing, this study introduces the Fourier convolution principle on encoding metasurface sequences to freely control the transmitted scattering angles. Both addition and subtraction operations between two different encoding sequences were then performed to achieve the continuous variation of the scattering angle. Furthermore, we established that the Fourier convolution principle can be applied to the checkerboard coded metasurfaces.
Most of our lives are conducted in the cyberspace. The human notion of privacy translates into a cyber notion of privacy on many functions that take place in the cyberspace. This article focuses on three such functions: how to privately retrieve information from cyberspace (privacy in information retrieval), how to privately leverage large-scale distributed/parallel processing (privacy in distributed computing), and how to learn/train machine learning models from private data spread across multiple users (privacy in distributed (federated) learning). The article motivates each privacy setting, describes the problem formulation, summarizes breakthrough results in the history of each problem, and gives recent results and discusses some of the major ideas that emerged in each field. In addition, the cross-cutting techniques and interconnections between the three topics are discussed along with a set of open problems and challenges.