We present a hybrid gyromagnetic photonic crystal (GPC) waveguide composed of different GPC waveguide segments possessing various cylinder radii and waveguide widths but biased by a uniform external magnetic field. We demonstrate in frequency and time domains that based on the strong coupling of two counter-propagating topologically protected one-way edge states, the intriguing slow light rainbow trapping (SLRT) of electromagnetic (EM) waves can be achieved, that is, EM waves of different frequencies can be slowed down and trapped at different positions without cross talk and overlap. More importantly, due to the existence of one-way edge states, external EM waves can be non-reciprocally coupled to the SLRT waveguide channel, although the incident position of the EM wave is far away from the waveguide channel. Besides, the frequency range of the slow light states can also be easily regulated by tuning the intensity of an external magnetic field, which is very beneficial to solve the contradiction between slow light and broad bandwidth. Our results can be applied to the design of high-performance photonic devices, such as an optical buffer, optical switch, and optical filter.
Recent developments in topological photonics have shown that the introduction of disorders can yield the innovative and striking transport phenomena. Here, we theoretically investigate topological one-way edge states in radius-fluctuated photonic Chern topological insulators (PCTIs), which are composed of two-dimensional gyromagnetic photonic crystals with cylinder site fixed but with cylinder radius fluctuated. We use a fluctuation index to characterize the degree of radius fluctuation, employ two empirical parameters to inspect the evolution of topological one-way edge states, and verify the stability of topological one-way edge states by calculating massive samples with various random numbers. We find that as the radius-fluctuation strength increases, there arises a competition between topological one-way edge state, Anderson localization state and trivial bulk state. We reveal that the Anderson localization state appears far more easily in the radius-fluctuation PCTI with even a weak strength compared with the position-perturbed PCTI with a strong randomness. We also demonstrate that the topological one-way edge states are protected against a strong fluctuation much larger than the fabrication errors in practical experiments. Our results show that the PCTIs consisting of gyromagnetic photonic crystals have a high-tolerance for the material and sample fabrication errors, and this would provide a deeper understanding of fundamental topology physics.
Topological one-way edge states have attracted increasing attention because of their intriguing fundamental physics and potential applications, particularly in the realm of photonics. In this paper, we present a theoretical and numerical demonstration of topological one-way edge states in an air-hole honeycomb gyromagnetic photonic crystal biased by an external magnetic field. Localized horizontally to the edge and confined in vertical direction by two parallel metallic plates, these unique states possess robust one-way propagation characteristics. They are strongly robust against various types of defects, imperfections and sharp corners on the path, and even can unidirectionally transport along the irregular edges of arbitrary geometries. We further utilize the one-way property of edge states to overcome entirely the issue of back-reflections and show the design of topological leaky wave antennas. Our results open a new door towards the observation of nontrivial edge states in air-hole topological photonic crystal systems, and offer useful prototype of robust topological photonic devices, such as geometry-independent topological energy flux loops and topological leaky wave antennas.
Mobile edge computing (MEC) deploys computing and storage resources close to mobile devices, enabling resource demanding applications to run on mobile devices with short network latency. In the past few years, large numbers of research works focused on the research hotspots in MEC, such as computation offloading and energy efficiency. However, few researchers have investigated the deployment of edge servers. On the one hand, blindly deploying numerous edge servers will result in a large amount of capital expenditure. On the other hand, the deployment of edge servers is a multimodal problem that should provide decision makers with multiple deployment options to deal with the impact of unmeasured real-world factors. Considering these factors, we study the multimodal optimization problem of edge server placement (MESP) with the goal of minimizing the average system response time in this work. Regarding the difficulty of the MESP problem, we propose a heuristic algorithm that combines particle swarm optimization and niching technology to obtain a set of competitive placement solutions. Extensive experiments over a real-world dataset show that the proposed algorithm can significantly reduce the system response time.
We theoretically propose and experimentally realize a new configuration of a photonic Chern topological insulator (PCTI) composed of a two-dimensional square-hexagon lattice gyromagnetic photonic crystal immersed in an external magnetic field. This PCTI possesses five distinct types of edges and all of them allowed the propagation of truly one-way edge states. We proceeded to utilize this special PCTI to design topological transmission lines of various configurations with sharp turns. Although the wave impedances of the edge states on both sides of the intersections in these transmission lines were very different, definitely no back reflection occurred and no mode-mixing problems and impedance-mismatching issues at the intersections were present, leading to topological resistance-free one-way transport in the whole transmission line network. Our results enrich the geometric and physical means and infrastructure to construct one-way transport and bring about novel platforms for developing topology-driven resistance-free photonic devices.
Spatial crowdsourcing (SC) is a popular distributed problem-solving paradigm that harnesses the power of mobile workers (e.g., smartphone users) to perform location-based tasks (e.g., checking product placement or taking landmark photos). Typically, a worker needs to travel physically to the target location to finish the assigned task. Hence, the worker’s familiarity level on the target location directly influences the completion quality of the task. In addition, from the perspective of the SC server, it is desirable to finish all tasks with a low recruitment cost. Combining these issues, we propose a Bi-Objective Task Planning (BOTP) problem in SC, where the server makes a task assignment and schedule for the workers to jointly optimize the workers’ familiarity levels on the locations of assigned tasks and the total cost of worker recruitment. The BOTP problem is proved to be NP-hard and thus intractable. To solve this challenging problem, we propose two algorithms: a divide-and-conquer algorithm based on the constraint method and a heuristic algorithm based on the multi-objective simulated annealing algorithm. The extensive evaluations on a real-world dataset demonstrate the effectiveness of the proposed algorithms.
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