scholarly journals Scattering Analysis and Efficiency Optimization of Dielectric Pancharatnam–Berry-Phase Metasurfaces

Nanomaterials ◽  
2021 ◽  
Vol 11 (3) ◽  
pp. 586
Author(s):  
Chen-Yi Yu ◽  
Qiu-Chun Zeng ◽  
Chih-Jen Yu ◽  
Chien-Yuan Han ◽  
Chih-Ming Wang
Keyword(s):  
Phase Modulation ◽  
Rotation Angle ◽  
Berry Phase ◽  
Fine Tuning ◽  
Design Rule ◽  
Polarization Conversion ◽  
Swarm Optimization ◽  
Efficiency Optimization ◽  
Phase Type ◽  
Gradient Phase

In this study, the phase modulation ability of a dielectric Pancharatnam–Berry (PB) phase metasurface, consisting of nanofins, is theoretically analyzed. It is generally considered that the optical thickness of the unit cell of a PB-phase metasurface is λ/2, i.e., a half-waveplate for polarization conversion. It is found that the λ/2 is not essential for achieving a full 2π modulation. Nevertheless, a λ/2 thickness is still needed for a high polarization conversion efficiency. Moreover, a gradient phase metasurface is designed. With the help of the particle swarm optimization (PSO) method, the wavefront errors of the gradient phase metasurface are reduced by fine-tuning the rotation angle of the nanofins. The diffraction efficiency of the gradient phase metasurface is thus improved from 73.4% to 87.3%. This design rule can be utilized to optimize the efficiency of phase-type meta-devices, such as meta-deflectors and metalenses.

Experimental realization to efficiently sort vector beams by polarization topological charge via Pancharatnam–Berry phase modulation

2018 ◽  
Vol 6 (5) ◽  
pp. 385 ◽  
Author(s):  
Shuiqin Zheng ◽  
Ying Li ◽  
Qinggang Lin ◽  
Xuanke Zeng ◽  
Guoliang Zheng ◽  
...  
Keyword(s):  
Phase Modulation ◽  
Topological Charge ◽  
Berry Phase ◽  
Experimental Realization ◽  
Vector Beams

scholarly journals Multifunctional Plasmonic Grating Based on the Phase Modulation of Excitation Light

Nanomaterials ◽  
2021 ◽  
Vol 11 (11) ◽  
pp. 2941
Author(s):  
Sen Wang ◽  
Jing Zhang ◽  
Maixia Fu ◽  
Jingwen He ◽  
Xing Li
Keyword(s):  
Phase Modulation ◽  
High Efficiency ◽  
Bessel Beam ◽  
Excitation Light ◽  
Linear Gradient ◽  
Practical Applications ◽  
Plasmonic Grating ◽  
The Cost ◽  
Plasmon Polaritons ◽  
Gradient Phase

Multifunctional optical devices are desirable at all times due to their features of flexibility and high efficiency. Based on the principle that the phase of excitation light can be transferred to the generated surface plasmon polaritons (SPPs), a plasmonic grating with three functions is proposed and numerically demonstrated. The Cherenkov SPPs wake or nondiffracting SPPs Bessel beam or focusing SPPs field can be correspondingly excited for the excitation light, which is modulated by a linear gradient phase or a symmetrical phase or a spherical phase, respectively. Moreover, the features of these functions such as the propagation direction of SPPs wake, the size and direction of the SPPs Bessel beam, and the position of SPPs focus can be dynamically manipulated. In consideration of the fact that no extra fabrication is required to obtain the different SPPs fields, the proposed approach can effectively reduce the cost in practical applications.

scholarly journals Particle Swarm Optimization Algorithms with Applications to Wave Scattering Problems

2021 ◽  
Author(s):  
Alkmini Michaloglou ◽  
Nikolaos L. Tsitsas
Keyword(s):  
Particle Swarm Optimization ◽  
Wave Scattering ◽  
Optimization Problems ◽  
Particle Swarm ◽  
Pso Algorithm ◽  
Fine Tuning ◽  
Geometrical Parameters ◽  
Scattering Problems ◽  
Swarm Optimization ◽  
Feasible Solutions

Particle Swarm Optimization (PSO) algorithms are widely used in a plethora of optimization problems. In this chapter, we focus on applications of PSO algorithms to optimization problems arising in the theory of wave scattering by inhomogeneous media. More precisely, we consider scattering problems concerning the excitation of a layered spherical medium by an external dipole. The goal is to optimize the physical and geometrical parameters of the medium’s internal composition for varying numbers of layers (spherical shells) so that the core of the medium is substantially cloaked. For the solution of the associated optimization problem, PSO algorithms have been specifically applied to effectively search for optimal solutions corresponding to realizable parameters values. We performed rounds of simulations for the the basic version of the original PSO algorithm, as well as a newer variant of the Accelerated PSO (known as “Chaos Enhanced APSO”/ “Chaotic APSO”). Feasible solutions were found leading to significantly reduced values of the employed objective function, which is the normalized total scattering cross section of the layered medium. Remarks regarding the differences and particularities among the different PSO algorithms as well as the fine-tuning of their parameters are also pointed out.

Phase modulation of metasurfaces for polarization conversion and RCS reduction

2021 ◽  
Vol 119 ◽  
pp. 111374
Author(s):  
Jiaji Yang ◽  
Zhangqi Liao ◽  
Yinrui Li ◽  
Dongmeng Li ◽  
Zhongkang Wang ◽  
...  
Keyword(s):  
Phase Modulation ◽  
Polarization Conversion

scholarly journals Impedance Controller Tuned by Particle Swarm Optimization for Robotic Arms

10.5772/45692 ◽  
2011 ◽  
Vol 8 (5) ◽  
pp. 57 ◽  
Author(s):  
Haifa Mehdi ◽  
Olfa Boubaker
Keyword(s):  
Particle Swarm Optimization ◽  
Particle Swarm ◽  
Pso Algorithm ◽  
Fine Tuning ◽  
Fast Method ◽  
Constrained Motion ◽  
Circular Trajectory ◽  
Swarm Optimization ◽  
Robotic Arms ◽  
The Stability

This paper presents an efficient and fast method for fine tuning the controller parameters of robot manipulators in constrained motion. The stability of the robotic system is proved using a Lyapunov-based impedance approach whereas the optimal design of the controller parameters are tuned, in offline, by a Particle Swarm Optimization (PSO) algorithm. For designing the PSO method, different index performances are considered in both joint and Cartesian spaces. A 3DOF manipulator constrained to a circular trajectory is finally used to validate the performances of the proposed approach. The simulation results show the stability and the performances of the proposed approach.

Routing algorithm with QoS constraints for real time multicast communications using particle swarm optimization and genetic meta-optimizer

2016 ◽  
Vol 33 (2) ◽  
Author(s):  
YEISON JULIAN CAMARGO ◽  
Leonardo Juan Ramirez ◽  
Ana Karina Martinez
Keyword(s):  
Particle Swarm Optimization ◽  
Design Methodology ◽  
Multicast Routing ◽  
Routing Algorithm ◽  
Particle Swarm ◽  
Minimum Cost ◽  
Fine Tuning ◽  
Steiner Tree Problem ◽  
Swarm Optimization ◽  
Routing Problem

Purpose The current work shows an approach to solve the QoS multicast routing problem by using Particle Swarm Optimization (PSO). The problem of finding a route from a source node to multiple destination nodes (multicast) at a minimum cost is an NP-Complete problem (Steiner tree problem) and is even greater if Quality of Service -QoS- constraints are taken into account. Thus, approximation algorithms are necessary to solve this problem. This work presents a routing algorithm with two QoS constraints (delay and delay variation) for solving the routing problem based on a modified version of particle swarm optimization. Design/methodology/approach This work involved the following methodology: 1. Literature Review 2. Routing algorithm design 3. Implementation of the designed routing algorithm by java programming. 4. Simulations and results. Findings In this work we compared our routing algorithm against the exhaustive search approach. The results showed that our algorithm improves the execution times in about 40% with different topologies. Research limitations/implications The algorithm was tested in three different topologies with 30, 40 and 50 nodes with and a dense graph topology. Originality/value Our algorithm implements a novel technique for fine tuning the parameters of the implemented bio-inspired model (Particles Swarm Optimization) by using a Genetic Meta-Optimizer. We also present a simple and multi implementation approach by using an encoding system that fits multiple bio-inspired models.

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