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 $s$-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$_2$, 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$_2$, 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$_2$ 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

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

Chromosomal mapping, differential origin and evolution of the S100 gene family

S100 proteins are calcium-binding proteins, which exist only in vertebrates and which constitute a large protein family. The origin and evolution of the S100 family in vertebrate lineages remain a challenge. Here, we examined the synteny conservation of mammalian S100A genes by analysing the sequence of available vertebrate S100 genes in databases. Five S100A gene members, unknown previously, were identified by chromosome mapping analysis. Mammalian S100A genes are duplicated and clustered on a single chromosome while two S100A gene clusters are found on separate chromosomes in teleost fish, suggesting that S100A genes existed in fish before the fish-specific genome duplication took place. During speciation, tandem gene duplication events within the cluster of S100A genes of a given chromosome have probably led to the multiple members of the S100A gene family. These duplicated genes have been retained in the genome either by neofunctionalisation and/or subfunctionalisation or have evolved into non-coding sequences. However in vertebrate genomes, other S100 genes are also present i.e. S100P, S100B, S100G and S100Z, which exist as single copy genes distributed on different chromosomes, suggesting that they could have evolved from an ancestor different to that of the S100A genes