366 research outputs found

    Broken axisymmetry phase of a spin-1 ferromagnetic Bose-Einstein condensate

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    A spin-1 ferromagnetic Bose-Einstein condensate subject to a certain magnetic field exhibits a broken-axisymmetry phase in which the magnetization tilts against the applied magnetic field due to the competition between ferromagnetism and linear and quadratic Zeeman effects. The Bogoliubov analysis shows that in this phase two Goldstone modes associated with U(1) and SO(2) symmetry breakings exist, in which phonons and magnons are coupled to restore the two broken symmetries.Comment: 11 pages, 6 figure

    Hadronic decays of Ba1(1260)b1(1235)B \to a_1(1260) b_1(1235) in the perturbative QCD approach

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    We calculate the branching ratios and polarization fractions of the Ba1b1B \to a_1 b_1 decays in the perturbative QCD(pQCD) approach at leading order, where a1a_1(b1b_1) stands for the axial-vector a1(1260)[b1(1235)]a_1(1260)[b_1(1235)] state. By combining the phenomenological analyses with the perturbative calculations, we find the following results: (a) the large decay rates around 10510^{-5} to 10610^{-6} of the Ba1b1B \to a_1 b_1 decays dominated by the longitudinal polarization(except for the B+b1+a10B^+ \to b_1^+ a_1^0 mode) are predicted and basically consistent with those in the QCD factorization(QCDF) within errors, which are expected to be tested by the Large Hadron Collider and Belle-II experiments. The large B0a10b10B^0 \to a_1^0 b_1^0 branching ratio could provide hints to help explore the mechanism of the color-suppressed decays. (b) the rather different QCD behaviors between the a1a_1 and b1b_1 mesons result in the destructive(constructive) contributions in the nonfactorizable spectator diagrams with a1(b1)a_1(b_1) emission. Therefore, an interesting pattern of the branching ratios appears for the color-suppressed B0a10a10,a10b10,B^0 \to a_1^0 a_1^0, a_1^0 b_1^0, and b10b10b_1^0 b_1^0 modes in the pQCD approach, Br(B0b10b10)>Br(B0a10b10)Br(B0a10a10)Br(B^0 \to b_1^0 b_1^0) > Br(B^0 \to a_1^0 b_1^0) \gtrsim Br(B^0 \to a_1^0 a_1^0), which is different from Br(B0b10b10)Br(B0a10b10)Br(B0a10a10)Br(B^0 \to b_1^0 b_1^0) \sim Br(B^0 \to a_1^0 b_1^0) \gtrsim Br(B^0 \to a_1^0 a_1^0) in the QCDF and would be verified at future experiments. (c) the large naive factorization breaking effects are observed in these Ba1b1B \to a_1 b_1 decays. Specifically, the large nonfactorizable spectator(weak annihilation) amplitudes contribute to the B0b1+a1(B+a1+b10  and  B+b1+a10)B^0 \to b_1^+ a_1^-(B^+ \to a_1^+ b_1^0\; {\rm and}\; B^+ \to b_1^+ a_1^0) mode(s), which demand confirmations via the precise measurements.Comment: 13 pages, 1 figure, 5 tables, revtex fil

    Topological defect formation in quenched ferromagnetic Bose-Einstein condensates

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    We study the dynamics of the quantum phase transition of a ferromagnetic spin-1 Bose-Einstein condensate from the polar phase to the broken-axisymmetry phase by changing magnetic field, and find the spontaneous formation of spinor domain walls followed by the creation of polar-core spin vortices. We also find that the spin textures depend very sensitively on the initial noise distribution, and that an anisotropic and colored initial noise is needed to reproduce the Berkeley experiment [Sadler et al., Nature 443, 312 (2006)]. The dynamics of vortex nucleation and the number of created vortices depend also on the manner in which the magnetic field is changed. We point out an analogy between the formation of spin vortices from domain walls in a spinor BEC and that of vortex-antivortex pairs from dark solitons in a scalar BEC.Comment: 10 pages, 11 figure

    Correlation between morphology and transport properties of quasi-free-standing monolayer graphene

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    We investigate the morphology of quasi-free-standing monolayer graphene (QFMLG) formed at several temperatures by hydrogen intercalation and discuss its relationship with transport properties. Features corresponding to incomplete hydrogen intercalation at the graphene-substrate interface are observed by scanning tunneling microscopy on QFMLG formed at 600 and 800{\deg}C. They contribute to carrier scattering as charged impurities. Voids in the SiC substrate and wrinkling of graphene appear at 1000{\deg}C, and they decrease the carrier mobility significantly

    The A-VEDAM Model For Approaching Vehicle Exterior Design

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    The exterior design of a vehicle is an important subjective factor in customer purchase decisions today, and it is critical that designs match customer lifestyles. This paper introduces A-VEDAM (Amasakalab’s Vehicle Exterior design Approach Model), a model for approaching exterior design in a way that harmonizes the external form (profile) and color of the vehicle to meet the demands of the coming years. The development of the A-VEDAM focuses on the fact that more young women are getting driver’s licenses and purchasing cars

    Tool-Use Model to Reproduce the Goal Situations Considering Relationship Among Tools, Objects, Actions and Effects Using Multimodal Deep Neural Networks

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    We propose a tool-use model that enables a robot to act toward a provided goal. It is important to consider features of the four factors; tools, objects actions, and effects at the same time because they are related to each other and one factor can influence the others. The tool-use model is constructed with deep neural networks (DNNs) using multimodal sensorimotor data; image, force, and joint angle information. To allow the robot to learn tool-use, we collect training data by controlling the robot to perform various object operations using several tools with multiple actions that leads different effects. Then the tool-use model is thereby trained and learns sensorimotor coordination and acquires relationships among tools, objects, actions and effects in its latent space. We can give the robot a task goal by providing an image showing the target placement and orientation of the object. Using the goal image with the tool-use model, the robot detects the features of tools and objects, and determines how to act to reproduce the target effects automatically. Then the robot generates actions adjusting to the real time situations even though the tools and objects are unknown and more complicated than trained ones
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