ARPES insights on the metallic states of YbB6(001): E(k) dispersion, temporal changes and spatial variation

We report high resolution Angle Resolved PhotoElectron Spectroscopy (ARPES) results on the (001) cleavage surface of YbB$_{6}$, a rare-earth compound which has been recently predicted to host surface electronic states with topological character. We observe two types of well-resolved metallic states, whose Fermi contours encircle the time-reversal invariant momenta of the YbB$_{6}$(001) surface Brillouin zone, and whose full (E,$k$)-dispersion relation can be measured wholly unmasked by states from the rest of the electronic structure. Although the two-dimensional character of these metallic states is confirmed by their lack of out-of-plane dispersion, two new aspects are revealed in these experiments. Firstly, these states do not resemble two branches of opposite, linear velocity that cross at a Dirac point, but rather straightforward parabolas which terminate to high binding energy with a clear band bottom. Secondly, these states are sensitive to time-dependent changes of the YbB$_{6}$ surface under ultrahigh vacuum conditions. Adding the fact that these data from cleaved YbB$_{6}$ surfaces also display spatial variations in the electronic structure, it appears there is little in common between the theoretical expectations for an idealized YbB$_{6}$(001) crystal truncation on the one hand, and these ARPES data from real cleavage surfaces on the other.Comment: 8 pages, 4 figures (accepted in Physical Review B

A Cloud-Computing-Based Data Placement Strategy in High-Speed Railway

As an important component of China’s transportation data sharing system, high-speed railway data sharing is a typical application of data-intensive computing. Currently, most high-speed railway data is shared in cloud computing environment. Thus, there is an urgent need for an effective cloud-computing-based data placement strategy in high-speed railway. In this paper, a new data placement strategy named hierarchical structure data placement strategy is proposed. The proposed method combines the semidefinite programming algorithm with the dynamic interval mapping algorithm. The semi-definite programming algorithm is suitable for the placement of files with various replications, ensuring that different replications of a file are placed on different storage devices, while the dynamic interval mapping algorithm ensures better self-adaptability of the data storage system. A hierarchical data placement strategy is proposed for large-scale networks. In this paper, a new theoretical analysis is provided, which is put in comparison with several other previous data placement approaches, showing the efficacy of the new analysis in several experiments