Intrinsic coherence in assisted sub-state discrimination

We study intrinsic coherence in the tripartite process to unambiguously discriminate two nonorthogonal states of a qubit, entangled with another one, and assisted by an auxiliary system. The optimal success probability is found to be benefited by initial intrinsic coherence, but no extra one is required. The transformations among different contributions of intrinsic coherence are necessary in this procedure, which increase with the overlap between the states to recognize. Such state discrimination is a key step of the probabilistic teleportation protocol. Entanglement of the quantum channel decreases the coherence characterizing the reliance on an ancilla.Comment: 6 pages with 4 figure

Quantum Entanglement transfer between spin-pairs

We investigate the transfer of entanglement from source particles (SP) to target particles (TP) in the Heisenberg interaction $H=\vec s_{1} \cdot \vec s_{2}$. In our research, TP are two qubits and SP are two qubits or qutrits. When TP are two qubits, we find that no matter what state the TP is initially prepared in, at the specific time $t=\pi$, the entanglement of TP can attain to 1 after interaction with SP which stay on the maximally entangled state. For the TP are two qutrits, we find that the maximal entanglement of TP after interaction is relative to the initial state of TP and always cannot attain to 1 to almost all of initial states of TP. But we discuss an iterated operation which can make the TP to the maximal entangled state.Comment: 6 pages; 4 figs. Accepted for publication in International Journal of Quantum Informatio

Fe alloy slurry and a compacting cumulate pile across Earth's inner-core boundary

Seismic observations show a reduced compressional-wave gradient at the base of the outer core relative to the preliminary reference Earth model and seismic wave asymmetry between the east-west hemispheres at the top of the inner core. Here, we propose a model for the inner core boundary (ICB), where a slurry layer forms through fractional crystallization of an Fe alloy at the base of the outer core (F layer) above a compacting cumulate pile at the top of the inner core (F' layer). Using recent mineral physics data, we show that fractional crystallization of an Fe alloy (e.g., Fe-Si-O) with light element partitioning can explain the observed reduced velocity gradient in the F layer, in cases with a solid fraction of ~15(5)% in liquid with a compositional gradient due to preferential light element partitioning into liquid. The compacting cumulate pile in the F' layer may exhibit lateral variations in thickness between the east-west hemispheres due to lateral variations of large-scale heat flow in the outer core, which may explain the east-west asymmetry observed in the seismic velocity. Our interpretations suggest that the inner core with solid Fe alloy has a high shear viscosity of ~10^23 Pa s.Comment: v2, 39 pages with 10 figure

Dynamical symmetries of the Klein-Gordon equation

The dynamical symmetries of the two-dimensional Klein-Gordon equations with equal scalar and vector potentials (ESVP) are studied. The dynamical symmetries are considered in the plane and the sphere respectively. The generators of the SO(3) group corresponding to the Coulomb potential, and the SU(2) group corresponding to the harmonic oscillator potential are derived. Moreover, the generators in the sphere construct the Higgs algebra. With the help of the Casimir operators, the energy levels of the Klein-Gordon systems are yielded naturally.Comment: 4

Structure propagation for zero-shot learning

The key of zero-shot learning (ZSL) is how to find the information transfer model for bridging the gap between images and semantic information (texts or attributes). Existing ZSL methods usually construct the compatibility function between images and class labels with the consideration of the relevance on the semantic classes (the manifold structure of semantic classes). However, the relationship of image classes (the manifold structure of image classes) is also very important for the compatibility model construction. It is difficult to capture the relationship among image classes due to unseen classes, so that the manifold structure of image classes often is ignored in ZSL. To complement each other between the manifold structure of image classes and that of semantic classes information, we propose structure propagation (SP) for improving the performance of ZSL for classification. SP can jointly consider the manifold structure of image classes and that of semantic classes for approximating to the intrinsic structure of object classes. Moreover, the SP can describe the constrain condition between the compatibility function and these manifold structures for balancing the influence of the structure propagation iteration. The SP solution provides not only unseen class labels but also the relationship of two manifold structures that encode the positive transfer in structure propagation. Experimental results demonstrate that SP can attain the promising results on the AwA, CUB, Dogs and SUN databases