4,969 research outputs found
Majorana corner modes and tunable patterns in an altermagnet heterostructure
The mutual competition and synergy of magnetism and superconductivity provide
us with a very valuable opportunity to access topological superconductivity and
Majorana Fermions. Here, we devise a heterostructure consisting of an -wave
superconductor, a 2D topological insulator and an altermagnet, which is
classified as the third magnet and featured by zero magnetization but spin
polarization in both real and reciprocal spaces. We find that the altermagnet
can induce mass terms at the edges that compete with electron pairing, and mass
domains are formed at the corners of sample, resulting in zero-energy Majorana
corner modes (MCMs). The presence or absence of MCMs can be engineered by only
changing the direction of the N\'{e}el vector. Moreover, uniaxial strain can
effectively manipulate the patterns of the MCMs, such as moving and
interchanging MCMs. Experimental realization, remarkable advantages of our
proposal and possible braiding are discussed.Comment: Accepted by PRB, 5 pages main text + 13 pages S
Dielectric Screening by 2D Substrates
Two-dimensional (2D) materials are increasingly being used as active
components in nanoscale devices. Many interesting properties of 2D materials
stem from the reduced and highly non-local electronic screening in two
dimensions. While electronic screening within 2D materials has been studied
extensively, the question still remains of how 2D substrates screen charge
perturbations or electronic excitations adjacent to them. Thickness-dependent
dielectric screening properties have recently been studied using electrostatic
force microscopy (EFM) experiments. However, it was suggested that some of the
thickness-dependent trends were due to extrinsic effects. Similarly, Kelvin
probe measurements (KPM) indicate that charge fluctuations are reduced when BN
slabs are placed on SiO, but it is unclear if this effect is due to
intrinsic screening from BN. In this work, we use first principles calculations
to study the fully non-local dielectric screening properties of 2D material
substrates. Our simulations give results in good qualitative agreement with
those from EFM experiments, for hexagonal boron nitride (BN), graphene and
MoS, indicating that the experimentally observed thickness-dependent
screening effects are intrinsic to the 2D materials. We further investigate
explicitly the role of BN in lowering charge potential fluctuations arising
from charge impurities on an underlying SiO substrate, as observed in the
KPM experiments. 2D material substrates can also dramatically change the
HOMO-LUMO gaps of adsorbates, especially for small molecules, such as benzene.
We propose a reliable and very quick method to predict the HOMO-LUMO gap of
small physisorbed molecules on 2D and 3D substrates, using only the band gap of
the substrate and the gas phase gap of the molecule.Comment: 24 pages, 5 figures, Supplementary Informatio
Investigation and comparison of land cover change patterns in Xuzhou city, China, and Dortmund city region, Germany, using multitemporal Landsat images
Optimal learning rates for least squares regularized regression with unbounded sampling
AbstractA standard assumption in theoretical study of learning algorithms for regression is uniform boundedness of output sample values. This excludes the common case with Gaussian noise. In this paper we investigate the learning algorithm for regression generated by the least squares regularization scheme in reproducing kernel Hilbert spaces without the assumption of uniform boundedness for sampling. By imposing some incremental conditions on moments of the output variable, we derive learning rates in terms of regularity of the regression function and capacity of the hypothesis space. The novelty of our analysis is a new covering number argument for bounding the sample error
Research on Financing Efficiencies of Strategic Emerging Listed Companies by Six-Stage DEA Model
Accounting for the information of input slack variables, as well as the effects of external environment and stochastic factors, a six-stage DEA model was proposed based on four-stage DEA model. It was employed to assess the financing efficiencies of 689 strategic emerging listed companies in 2015. By isolating the environmental and stochastic factors, the final efficiencies can reflect the actual financing level of these companies. The empirical results show that most financing efficiencies are still at a low level relatively. The scales of these strategic emerging companies are the main constraint on their development. And the special technical level also has an impact on these efficiencies. In addition, the efficiency difference among provinces in China gives another support to environmental influence on the strategic emerging industry. Therefore, a strategic emerging company should pay attention to expanding its scale of production and heighten its special technical level and it should improve its financing efficiencies with the help of local government power
A WOA-based optimization approach for task scheduling in cloud Computing systems
Task scheduling in cloud computing can directly
affect the resource usage and operational cost of a system. To
improve the efficiency of task executions in a cloud, various
metaheuristic algorithms, as well as their variations, have been
proposed to optimize the scheduling. In this work, for the
first time, we apply the latest metaheuristics WOA (the whale
optimization algorithm) for cloud task scheduling with a multiobjective optimization model, aiming at improving the performance of a cloud system with given computing resources. On that
basis, we propose an advanced approach called IWC (Improved
WOA for Cloud task scheduling) to further improve the optimal
solution search capability of the WOA-based method. We present
the detailed implementation of IWC and our simulation-based
experiments show that the proposed IWC has better convergence
speed and accuracy in searching for the optimal task scheduling
plans, compared to the current metaheuristic algorithms. Moreover, it can also achieve better performance on system resource
utilization, in the presence of both small and large-scale tasks
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