28,230 research outputs found

    Some Issues in a Gauge Model of Unparticles

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    We address in a recent gauge model of unparticles the issues that are important for consistency of a gauge theory, i.e., unitarity and Ward identity of physical amplitudes. We find that non-integrable singularities arise in physical quantities like cross section and decay rate from gauge interactions of unparticles. We also show that Ward identity is violated due to the lack of a dispersion relation for charged unparticles although the Ward-Takahashi identity for general Green functions is incorporated in the model. A previous observation that the unparticle's (with scaling dimension d) contribution to the gauge boson self-energy is a factor (2-d) of the particle's has been extended to the Green function of triple gauge bosons. This (2-d) rule may be generally true for any point Green functions of gauge bosons. This implies that the model would be trivial even as one that mimics certain dynamical effects on gauge bosons in which unparticles serve as an interpolating field.Comment: v1:16 pages, 3 figures. v2: some clarifications made and presentation improved, calculation and conclusion not modified; refs added and updated. Version to appear in EPJ

    Bounds on Unparticles from the Higgs Sector

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    We study supersymmetric QCD in the conformal window as a laboratory for unparticle physics, and analyze couplings between the unparticle sector and the Higgs sector. These couplings can lead to the unparticle sector being pushed away from its scale invariant fixed point. We show that this implies that low energy experiments will not be able to see unparticle physics, and the best hope of seeing unparticles is in high energy collider experiments such as the Tevatron and the LHC. We also demonstrate how the breaking of scale invariance could be observed at these experiments.Comment: 9 pages, 3 figure

    The Application of Predictor Feedback in Designing a Preview Controller for Discrete-Time Systems with Input Delay

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    © 2016 Fucheng Liao et al.This paper presents a method for designing a type one servomechanism for a discrete-time linear system with input delay subject to a previewable desired output and a nonmeasurable constant disturbance. The tracking problem of a delay system is transformed into a regulation problem of a delay-free system via constructing an augmented error system and a variable substitution. A controller is obtained with delay compensation and preview compensation based on preview control theory and the predictor method. When the state vector is not directly measurable, a full-dimensional observer is offered. The effectiveness of the design method is demonstrated by numerical simulations

    From the chiral magnetic wave to the charge dependence of elliptic flow

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    The quark-gluon plasma formed in heavy ion collisions contains charged chiral fermions evolving in an external magnetic field. At finite density of electric charge or baryon number (resulting either from nuclear stopping or from fluctuations), the triangle anomaly induces in the plasma the Chiral Magnetic Wave (CMW). The CMW first induces a separation of the right and left chiral charges along the magnetic field; the resulting dipolar axial charge density in turn induces the oppositely directed vector charge currents leading to an electric quadrupole moment of the quark-gluon plasma. Boosted by the strong collective flow, the electric quadrupole moment translates into the charge dependence of the elliptic flow coefficients, so that v2(π+)<v2(π−)v_2(\pi^+) < v_2(\pi^-) (at positive net charge). Using the latest quantitative simulations of the produced magnetic field and solving the CMW equation, we make further quantitative estimates of the produced v2v_2 splitting and its centrality dependence. We compare the results with the available experimental data.Comment: Contains 12 pages, 6 figures, written as a proceeding for the talk of Y. Burnier at the conference "P and CP-odd Effects in Hot and Dense Matter 2012" held in BN

    Metal-Insulator Transition of the LaAlO3-SrTiO3 Interface Electron System

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    We report on a metal-insulator transition in the LaAlO3-SrTiO3 interface electron system, of which the carrier density is tuned by an electric gate field. Below a critical carrier density n_c ranging from 0.5-1.5 * 10^13/cm^2, LaAlO3-SrTiO3 interfaces, forming drain-source channels in field-effect devices are non-ohmic. The differential resistance at zero channel bias diverges within a 2% variation of the carrier density. Above n_c, the conductivity of the ohmic channels has a metal-like temperature dependence, while below n_c conductivity sets in only above a threshold electric field. For a given thickness of the LaAlO3 layer, the conductivity follows a sigma_0 ~(n - n_c)/n_c characteristic. The metal-insulator transition is found to be distinct from that of the semiconductor 2D systems.Comment: 4 figure

    Deep Learning for Single Image Super-Resolution: A Brief Review

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    Single image super-resolution (SISR) is a notoriously challenging ill-posed problem, which aims to obtain a high-resolution (HR) output from one of its low-resolution (LR) versions. To solve the SISR problem, recently powerful deep learning algorithms have been employed and achieved the state-of-the-art performance. In this survey, we review representative deep learning-based SISR methods, and group them into two categories according to their major contributions to two essential aspects of SISR: the exploration of efficient neural network architectures for SISR, and the development of effective optimization objectives for deep SISR learning. For each category, a baseline is firstly established and several critical limitations of the baseline are summarized. Then representative works on overcoming these limitations are presented based on their original contents as well as our critical understandings and analyses, and relevant comparisons are conducted from a variety of perspectives. Finally we conclude this review with some vital current challenges and future trends in SISR leveraging deep learning algorithms.Comment: Accepted by IEEE Transactions on Multimedia (TMM
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