1,512 research outputs found
Radiation effects on the electronic structure of bilayer graphene
We report on the effects of laser illumination on the electronic properties
of bilayer graphene. By using Floquet theory combined with Green's functions we
unveil the appeareance of laser-induced gaps not only at integer multiples of
but also at the Dirac point with features which are shown to
depend strongly on the laser polarization. Trigonal warping corrections are
shown to lead to important corrections for radiation in the THz range, reducing
the size of the dynamical gaps. Furthermore, our analysis of the topological
properties at low energies reveals that when irradiated with linearly polarized
light, ideal bilayer graphene behaves as a trivial insulator, whereas circular
polarization leads to a non-trivial insulator per valley.Comment: 5 pages 3 figure
Crafting zero-bias one-way transport of charge and spin
We explore the electronic structure and transport properties of a metal on
top of a (weakly coupled) two-dimensional topological insulator. Unlike the
widely studied junctions between topological non-trivial materials, the systems
studied here allow for a unique bandstructure and transport steering. First,
states on the topological insulator layer may coexist with the gapless bulk
and, second, the edge states on one edge can be selectively switched-off,
thereby leading to nearly perfect directional transport of charge and spin even
in the zero bias limit. We illustrate these phenomena for Bernal stacked
bilayer graphene with Haldane or intrinsic spin-orbit terms and a perpendicular
bias voltage. This opens a path for realizing directed transport in materials
such as van der Waals heterostructures, monolayer and ultrathin topological
insulators.Comment: 7 pages, 7 figure
Running Genetic Algorithms in the Edge: A First Analysis
Nowadays, the volume of data produced by different kinds of devices is continuously growing, making even more difficult to solve the
many optimization problems that impact directly on our living quality. For instance, Cisco projected that by 2019 the volume of data will reach 507.5 zettabytes per year, and the cloud traffic will quadruple. This is not sustainable in the long term, so it is a need to move part of the intelligence from the cloud to a highly decentralized computing model. Considering this, we propose a ubiquitous intelligent system which is composed by different kinds of endpoint devices such as smartphones, tablets, routers, wearables, and any other CPU powered device. We want to use this to solve tasks useful for smart cities. In this paper, we analyze if these devices are suitable for this purpose and how we have to adapt the optimization algorithms to be efficient using heterogeneous hardware. To do this, we perform a set of experiments in which we measure the speed, memory usage, and battery consumption of these devices for a set of binary and combinatorial problems. Our conclusions reveal the strong and weak features of each device to run future algorihms in the border of the cyber-physical system.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech.
This research has been partially funded by the Spanish MINECO and FEDER projects TIN2014-57341-R (http://moveon.lcc.uma.es), TIN2016-81766-REDT (http://cirti.es), TIN2017-88213-R (http://6city.lcc.uma.es), the Ministry of Education of Spain (FPU16/02595
Human Pose Detection for Robotic-Assisted and Rehabilitation Environments
Assistance and rehabilitation robotic platforms must have precise sensory systems for human–robot interaction. Therefore, human pose estimation is a current topic of research, especially for the safety of human–robot collaboration and the evaluation of human biomarkers. Within this field of research, the evaluation of the low-cost marker-less human pose estimators of OpenPose and Detectron 2 has received much attention for their diversity of applications, such as surveillance, sports, videogames, and assessment in human motor rehabilitation. This work aimed to evaluate and compare the angles in the elbow and shoulder joints estimated by OpenPose and Detectron 2 during four typical upper-limb rehabilitation exercises: elbow side flexion, elbow flexion, shoulder extension, and shoulder abduction. A setup of two Kinect 2 RGBD cameras was used to obtain the ground truth of the joint and skeleton estimations during the different exercises. Finally, we provided a numerical comparison (RMSE and MAE) among the angle measurements obtained with OpenPose, Detectron 2, and the ground truth. The results showed how OpenPose outperforms Detectron 2 in these types of applications.Óscar G. Hernández holds a grant from the Spanish Fundación Carolina, the University of Alicante, and the National Autonomous University of Honduras
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