KN and KbarN Elastic Scattering in the Quark Potential Model

The KN and KbarN low-energy elastic scattering is consistently studied in the framework of the QCD-inspired quark potential model. The model is composed of the t-channel one-gluon exchange potential, the s-channel one-gluon exchange potential and the harmonic oscillator confinement potential. By means of the resonating group method, nonlocal effective interaction potentials for the KN and KbarN systems are derived and used to calculate the KN and KbarN elastic scattering phase shifts. By considering the effect of QCD renormalization, the contribution of the color octet of the clusters (qqbar) and (qqq) and the suppression of the spin-orbital coupling, the numerical results are in fairly good agreement with the experimental data.Comment: 20 pages, 8 figure

Renormalization of the Sigma-Omega model within the framework of U(1) gauge symmetry

It is shown that the Sigma-Omega model which is widely used in the study of nuclear relativistic many-body problem can exactly be treated as an Abelian massive gauge field theory. The quantization of this theory can perfectly be performed by means of the general methods described in the quantum gauge field theory. Especially, the local U(1) gauge symmetry of the theory leads to a series of Ward-Takahashi identities satisfied by Green's functions and proper vertices. These identities form an uniquely correct basis for the renormalization of the theory. The renormalization is carried out in the mass-dependent momentum space subtraction scheme and by the renormalization group approach. With the aid of the renormalization boundary conditions, the solutions to the renormalization group equations are given in definite expressions without any ambiguity and renormalized S-matrix elememts are exactly formulated in forms as given in a series of tree diagrams provided that the physical parameters are replaced by the running ones. As an illustration of the renormalization procedure, the one-loop renormalization is concretely carried out and the results are given in rigorous forms which are suitable in the whole energy region. The effect of the one-loop renormalization is examined by the two-nucleon elastic scattering.Comment: 32 pages, 17 figure

Gate voltage controlled electronic transport through a ferromagnet/normal/ferromagnet junction on the surface of a topological insulator

We investigate the electronic transport properties of a ferromagnet/normal/ferromagnet junction on the surface of a topological insulator with a gate voltage exerted on the normal segment. It is found that the conductance oscillates with the width of normal segment and gate voltage, and the maximum of conductance gradually decreases while the minimum of conductance approaches zero as the width increases. The conductance can be controlled by tuning the gate voltage like a spin field-effect transistor. It is found that the magnetoresistance ratio can be very large, and can also be negative owing to the anomalous transport. In addition, when there exists a magnetization component in the surface plane, it is shown that only the component parallel to the junction interface has an influence on the conductance.Comment: 7 pages,8 figure

Duration distributions for different softness groups of gamma-ray bursts

Gamma-ray bursts (GRBs) are divided into two classes according to their durations. We investigate if the softness of bursts plays a role in the conventional classification of the objects. We employ the BATSE (Burst and Transient Source Experiment) catalog and analyze the duration distributions of different groups of GRBs associated with distinct softness. Our analysis reveals that the conventional classification of GRBs with the duration of bursts is influenced by the softness of the objects. There exits a bimodality in the duration distribution of GRBs for each group of bursts and the time position of the dip in the bimodality histogram shifts with the softness parameter. Our findings suggest that the conventional classification scheme should be modified by separating the two well-known populations in different softness groups, which would be more reasonable than doing so with a single sample. According to the relation between the dip position and the softness parameter, we get an empirical function that can roughly set apart the short-hard and long-soft bursts: $SP = (0.100 \pm 0.028) T_{90}^{-(0.85 \pm 0.18)}$, where $SP$ is the softness parameter adopted in this paper.Comment: 20 pages, 10 figure

On indecomposable modules over the Virasoro algebra

It is proved that an indecomposable Harish-Chandra module over the Virasoro algebra must be (i) a uniformly bounded module, or (ii) a module in Category $\cal O$, or (iii) a module in Category ${\cal O}^-$, or (iv) a module which contains the trivial module as one of its composition factors.Comment: 5 pages, Latex, to appear in Science in China

Space Shuttle/TDRSS communication and tracking systems analysis

In order to evaluate the technical and operational problem areas and provide a recommendation, the enhancements to the Tracking and Data Delay Satellite System (TDRSS) and Shuttle must be evaluated through simulation and analysis. These enhancement techniques must first be characterized, then modeled mathematically, and finally updated into LinCsim (analytical simulation package). The LinCsim package can then be used as an evaluation tool. Three areas of potential enhancements were identified: shuttle payload accommodations, TDRSS SSA and KSA services, and shuttle tracking system and navigation sensors. Recommendations for each area were discussed

Absence of Localization in Disordered Two Dimensional Electron Gas at Weak Magnetic Field and Strong Spin-Orbit Coupling

The one-parameter scaling theory of localization predicts that all states in a disordered two-dimensional system with broken time reversal symmetry are localized even in the presence of strong spin-orbit coupling. While at constant strong magnetic fields this paradigm fails (recall quantum Hall effect), it is believed to hold at weak magnetic fields. Here we explore the nature of quantum states at weak magnetic field and strongly fluctuating spin-orbit coupling, employing highly accurate numerical procedure based on level spacing distribution and transfer matrix technique combined with finite-size one-parameter scaling hypothesis. Remarkably, the metallic phase, (known to exist at zero magnetic field), persists also at finite (albeit weak) magnetic fields, and eventually crosses over into a critical phase, which has already been confirmed at high magnetic fields. A schematic phase diagram drawn in the energy-magnetic field plane elucidates the occurrence of localized, metallic and critical phases. In addition, it is shown that nearest-level statistics is determined solely by the symmetry parameter $\beta$ and follows the Wigner surmise irrespective of whether states are metallic or critical.Comment: 4 pages, 3 figure

Exploiting Cognitive Structure for Adaptive Learning

Adaptive learning, also known as adaptive teaching, relies on learning path recommendation, which sequentially recommends personalized learning items (e.g., lectures, exercises) to satisfy the unique needs of each learner. Although it is well known that modeling the cognitive structure including knowledge level of learners and knowledge structure (e.g., the prerequisite relations) of learning items is important for learning path recommendation, existing methods for adaptive learning often separately focus on either knowledge levels of learners or knowledge structure of learning items. To fully exploit the multifaceted cognitive structure for learning path recommendation, we propose a Cognitive Structure Enhanced framework for Adaptive Learning, named CSEAL. By viewing path recommendation as a Markov Decision Process and applying an actor-critic algorithm, CSEAL can sequentially identify the right learning items to different learners. Specifically, we first utilize a recurrent neural network to trace the evolving knowledge levels of learners at each learning step. Then, we design a navigation algorithm on the knowledge structure to ensure the logicality of learning paths, which reduces the search space in the decision process. Finally, the actor-critic algorithm is used to determine what to learn next and whose parameters are dynamically updated along the learning path. Extensive experiments on real-world data demonstrate the effectiveness and robustness of CSEAL.Comment: Accepted by KDD 2019 Research Track. In Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining (KDD'19