ND^(*) and NB^(*) interactions in a chiral quark model

ND and ND^* interactions become a hot topic after the observation of new charmed hadrons \Sigma_c(2800) and \Lambda_c(2940)^+. In this letter, we have preliminary investigated S-wave ND and ND^* interactions with possible quantum numbers in the chiral SU(3) quark model and the extended chiral SU(3) quark model by solving the resonating group method equation. The numerical results show that the interactions between N and D or N and D^* are both attractive, which are mainly from \sigma exchanges between light quarks. Further bound-state studies indicate the attractions are strong enough to form ND or ND^* molecules, except for (ND)_{J=3/2} and (ND^*)_{J=3/2} in the chiral SU(3) quark model. In consequence ND system with J=1/2 and ND^* system with J=3/2 in the extended SU(3) quark model could correspond to the observed \Sigma_c(2800) and \Lambda_c(2940)^+, respectively. Naturally, the same method can be applied to research NB and NB^* interactions, and similar conclusions obtained, i.e. NB and NB^* attractive forces may achieve bound states, except for (NB^*)_{J=3/2} in the chiral SU(3) quark model. Meanwhile, S partial wave phase shifts of ND^{(*)} and NB^{(*)} elastic scattering are illustrated, which are qualitatively consistent with results from bound state problem.Comment: 5 pages, 3 figure

First principles study of the vibronic coupling in positively charged C60+_{60}^+

Vibronic coupling parameters for C$_{60}^{+}$ were derived via DFT calculations with hybrid B3LYP and CAM-B3LYP functional, based on which the static Jahn-Teller effect were analyzed. The global minima of adiabatic potential energy surface (APES) shows a D$_{5d}$ Jahn-Teller deformation, with stabilization energies of 110 and 129 meV (with B3LYP and CAM-B3LYP respectively), which are two times larger than that in C$_{60}^-$, suggesting the crucial role of the dynamical Jahn-Teller effect. Present results enable us to assess the actual situation of dynamical Jahn-Teller effect in C$_{60}^{+}$ and excited C$_{60}$ in combination with the established parameters for C$_{60}^{-}$.Comment: 19 pages, 25 figures and 2 table

Dynamical Jahn-Teller effect in the first excited C60−_{60}^-

The Jahn-Teller effect of C$_{60}$ anions in the first electronically excited states was theoretically investigated. The orbital vibronic coupling parameters for the $t_{1g}$ next lowest unoccupied molecular orbitals were derived from the Kohn-Sham orbital levels with hybrid B3LYP functional by using the frozen phonon approach. With the use of these coupling parameters, the vibronic states of the first excited C$_{60}^-$ were derived by exactly diagonalizing the dynamical Jahn-Teller Hamiltonian. The dynamical Jahn-Teller stabilization energy of the first excited C$_{60}^-$ is stronger than that of the ground electronic states.Comment: 10 pages, 10 figures, 3 table

Geographic Trough Filling for Internet Datacenters

To reduce datacenter energy consumption and cost, current practice has considered demand-proportional resource provisioning schemes, where servers are turned on/off according to the load of requests. Most existing work considers instantaneous (Internet) requests only, which are explicitly or implicitly assumed to be delay-sensitive. On the other hand, in datacenters, there exist a vast amount of delay-tolerant jobs, such as background/maintainance jobs. In this paper, we explicitly differentiate delay-sensitive jobs and delay tolerant jobs. We focus on the problem of using delay-tolerant jobs to fill the extra capacity of datacenters, referred to as trough/valley filling. Giving a higher priority to delay-sensitive jobs, our schemes complement to most existing demand-proportional resource provisioning schemes. Our goal is to design intelligent trough filling mechanisms that are energy efficient and also achieve good delay performance. Specifically, we propose two joint dynamic speed scaling and traffic shifting schemes, one subgradient-based and the other queue-based. Our schemes assume little statistical information of the system, which is usually difficult to obtain in practice. In both schemes, energy cost saving comes from dynamic speed scaling, statistical multiplexing, electricity price diversity, and service efficiency diversity. In addition, good delay performance is achieved in the queue-based scheme via load shifting and capacity allocation based on queue conditions. Practical issues that may arise in datacenter networks are considered, including capacity and bandwidth constraint, service agility constraint, and load shifting cost. We use both artificial and real datacenter traces to evaluate the proposed schemes

Effect of Net Charge on the Relative Stability of 2D Boron Allotropes

We study the effect of electron doping on the bonding character and stability of two-dimensional (2D) structures of elemental boron, called borophene, which is known to form many stable allotropes. Our {\em ab initio} calculations for the neutral system reveal previously unknown stable 2D $\epsilon$-B and $\omega$-B structures. We find that the chemical bonding characteristic in this and other boron structures is strongly affected by extra charge. Beyond a critical degree of electron doping, the most stable allotrope changes from $\epsilon$-B to a buckled honeycomb structure. Additional electron doping, mimicking a transformation of boron to carbon, causes a gradual decrease in the degree of buckling of the honeycomb lattice that can be interpreted as piezoelectric response. Net electron doping can be achieved by placing borophene in direct contact with layered electrides such as Ca$_{2}$N. We find that electron doping can be doubled by changing from the B/Ca$_{2}$N bilayer to the Ca$_{2}$N/B/Ca$_{2}$N sandwich geometry.Comment: accepted by Nano Letter

Joint Face Alignment and 3D Face Reconstruction with Application to Face Recognition

Face alignment and 3D face reconstruction are traditionally accomplished as separated tasks. By exploring the strong correlation between 2D landmarks and 3D shapes, in contrast, we propose a joint face alignment and 3D face reconstruction method to simultaneously solve these two problems for 2D face images of arbitrary poses and expressions. This method, based on a summation model of 3D faces and cascaded regression in 2D and 3D shape spaces, iteratively and alternately applies two cascaded regressors, one for updating 2D landmarks and the other for 3D shape. The 3D shape and the landmarks are correlated via a 3D-to-2D mapping matrix, which is updated in each iteration to refine the location and visibility of 2D landmarks. Unlike existing methods, the proposed method can fully automatically generate both pose-and-expression-normalized (PEN) and expressive 3D faces and localize both visible and invisible 2D landmarks. Based on the PEN 3D faces, we devise a method to enhance face recognition accuracy across poses and expressions. Both linear and nonlinear implementations of the proposed method are presented and evaluated in this paper. Extensive experiments show that the proposed method can achieve the state-of-the-art accuracy in both face alignment and 3D face reconstruction, and benefit face recognition owing to its reconstructed PEN 3D face.Comment: IEEE Transactions on Pattern Analysis and Machine Intelligence, Nov. 201

Super-pixel cloud detection using Hierarchical Fusion CNN

Cloud detection plays a very important role in the process of remote sensing images. This paper designs a super-pixel level cloud detection method based on convolutional neural network (CNN) and deep forest. Firstly, remote sensing images are segmented into super-pixels through the combination of SLIC and SEEDS. Structured forests is carried out to compute edge probability of each pixel, based on which super-pixels are segmented more precisely. Segmented super-pixels compose a super-pixel level remote sensing database. Though cloud detection is essentially a binary classification problem, our database is labeled into four categories: thick cloud, cirrus cloud, building and other culture, to improve the generalization ability of our proposed models. Secondly, super-pixel level database is used to train our cloud detection models based on CNN and deep forest. Considering super-pixel level remote sensing images contain less semantic information compared with general object classification database, we propose a Hierarchical Fusion CNN (HFCNN). It takes full advantage of low-level features like color and texture information and is more applicable to cloud detection task. In test phase, every super-pixel in remote sensing images is classified by our proposed models and then combined to recover final binary mask by our proposed distance metric, which is used to determine ambiguous super-pixels. Experimental results show that, compared with conventional methods, HFCNN can achieve better precision and recall

Is Twisted Bilayer Graphene Stable under Shear?

In twisted bilayer graphene (TBLG), extremely small deviations from the magic twist angle $\theta_m{\approx}1.08^\circ$ change its electronic structure near the Fermi level drastically, causing a meV-wide flat band to appear or disappear. In view of such sensitivity to minute structural deformations, we investigate the combined effect of shear and atomic relaxation on the electronic structure. Using precise experimental data for monolayer and bilayer graphene as input in a simplified formalism for the electronic structure and elastic energy, we find TBLG near $\theta_m$ to be unstable with respect to global shear by the angle $\alpha{\approx}0.08^\circ$. In TBLG, the effect of shear on the electronic structure is as important as that of atomic relaxation. Under optimum global shear, calculated $\theta_m$ is reduced by $0.04^\circ$ and agrees with the observed value.Comment: Phys. Rev. B 98 (2018) (in press). 8 pages, 6 figure

Two-dimensional Mechanical Metamaterials with Unusual Poisson Ratio Behavior

We design two-dimensional (2D) mechanical metamaterials that may be deformed substantially at little or no energy cost. Examples of such deformable structures are assemblies of rigid isosceles triangles hinged in their corners on the macro-scale, or polymerized phenanthrene molecules forming porous graphene on the nano-scale. In these and in a large class of related structures, the Poisson ratio $\nu$ diverges for particular strain values. $\nu$ also changes its magnitude and sign, and displays a shape memory effect.Comment: Accepted by Phys. Rev. Applied 10 (2018

Asynchronous Transmission of Wireless Multicast System with Genetic Joint Antennas Selection

Optimal antenna selection algorithm of multicast transmission can significantly reduce the number of antennas and can acquire lower complexity and high performance which is close to that of exhaustive search. An asynchronous multicast transmission mechanism based on genetic antenna selection is proposed. The computational complexity of genetic antenna selection algorithm remains moderate while the total number of antennas increases comparing with optimum searching algorithm. Symbol error rate (SER) and capacity of our mechanism are analyzed and simulated, and the simulation results demonstrate that our proposed mechanism can achieve better SER and sub-maximum channel capacity in wireless multicast systems.Comment: 5 pages, 3 figures. A downlink multicast scenario with genetic antenna selection is presented. The sender equipped with multi-antennas broadcasts successive data packets in groups to several multi-antenna users over a common bandwidth. Select appropriate weight vectors to maximize the minimum SINR under a power constraint. Proposed algorithm can improve system capacity with lower complexit