Constraints of the equation of state of dark energy from current and future observational data by piecewise parametrizations

The model-independent piecewise parametrizations (0-spline, linear-spline and cubic-spline) are used to estimate constraints of equation of state of dark energy ($w_{de}$) from current observational data (including SNIa, BAO and Hubble parameter) and the simulated future data. A combination of fitting results of $w_{de}$ from these three spline methods reveal essential properties of real equation of state $w_{de}$. It is shown that $w_{de}$ beyond redshift $z\sim0.5$ is poorly constrained from current data, and the mock future $\sim2300$ supernovae data give poor constraints of $w_{de}$ beyond $z\sim1$. The fitting results also indicate that there might exist a rapid transition of $w_{de}$ around $z\sim0.5$. The difference between three spline methods in reconstructing and constraining $w_{de}$ has also been discussed.Comment: 16 pages, 2 figures, 5 table

Dirac series for E6(−14)E_{6(-14)}

Up to equivalence, this paper classifies all the irreducible unitary representations with non-zero Dirac cohomology for the simple Lie group $E_{6(-14)}$, which is of Hermitian symmetric type. Each FS-scattered Dirac series of $E_{6(-14)}$ is realized as a composition factor of certain $A_{\mathfrak{q}}(\lambda)$ module. Along the way, we have also obtained all the fully supported irreducible unitary representations of $E_{6(-14)}$ with integral infinitesimal characters.Comment: 32 pages, some strings are folde

Hierarchical Codebook Design for Beamforming Training in Millimeter-Wave Communication

In millimeter-wave communication, large antenna arrays are required to achieve high power gain by steering towards each other with narrow beams, which poses the problem to efficiently search the best beam direction in the angle domain at both Tx and Rx sides. As the exhaustive search is time consuming, hierarchical search has been widely accepted to reduce the complexity, and its performance is highly dependent on the codebook design. In this paper, we propose two basic criteria for the hierarchical codebook design, and devise an efficient hierarchical codebook by jointly exploiting sub-array and deactivation (turning-off) antenna processing techniques, where closed-form expressions are provided to generate the codebook. Performance evaluations are conducted under different system and channel models. Results show superiority of the proposed codebook over the existing alternatives.Comment: 13 pages, 11 figures. To appear in IEEE Trans. Wireless Commn. This paper proposes the BMW-SS approach to design a fully-hierarchical codebook for mmWave communication

IRCI Free Colocated MIMO Radar Based on Sufficient Cyclic Prefix OFDM Waveforms

In this paper, we propose a cyclic prefix (CP) based MIMO-OFDM range reconstruction method and its corresponding MIMO-OFDM waveform design for co-located MIMO radar systems. Our proposed MIMO-OFDM waveform design achieves the maximum signal-to-noise ratio (SNR) gain after the range reconstruction and its peak-to-average power ratio (PAPR) in the discrete time domain is also optimal, i.e., 0dB, when Zadoff-Chu sequences are used in the discrete frequency domain as the weighting coefficients for the subcarriers. We also investigate the performance when there are transmit and receive digital beamforming (DBF) pointing errors. It is shown that our proposed CP based MIMO-OFDM range reconstruction is inter-range-cell interference (IRCI) free no matter whether there are transmit and receive DBF pointing errors or not. Simulation results are presented to verify the theory and compare it with the conventional OFDM and LFM co-located MIMO radars.Comment: 27 pages, 11 figure

A wavelet frame coefficient total variational model for image restoration

In this paper, we propose a vector total variation (VTV) of feature image model for image restoration. The VTV imposes different smoothing powers on different features (e.g. edges and cartoons) based on choosing various regularization parameters. Thus, the model can simultaneously preserve edges and remove noises. Next, the existence of solution for the model is proved and the split Bregman algorithm is used to solve the model. At last, we use the wavelet filter banks to explicitly define the feature operator and present some experimental results to show its advantage over the related methods in both quality and efficiency.Comment: 19 pages, 8 figures, 2 table

Some aspects of QGP phase in a hQCD model

We continue to study the holographic QCD (hQCD) model, proposed in a previous paper, in an Einstein-Maxwell-Dilaton (EMD) system. In this paper we discuss some aspects of quark gluon plasma (QGP) in the hQCD model, such as drag force, jet quenching parameter and screening length. The results turn out to be consistent with those as expected in QCD qualitatively. By calculating free energy of the background black hole solution, we find that there exists a Hawking-Page phase transition between small black hole and big black hole when chemical potential $\mu$ is less than a critical one $\mu_c$, and the phase transition is absent when chemical potential is beyond the critical one.Comment: 31 pages,15 figures, LaTeX, Statements and figures have been improved. Accepted by JHE

A Holographic Study on Vector Condensate Induced by a Magnetic Field

We study a holographic model with vector condensate by coupling the anti-de Sitter gravity to an Abelian gauge field and a charged vector field in $(3+1)$ dimensional spacetime. In this model there exists a non-minimal coupling of the vector filed to the gauge field. We find that there is a critical temperature below which the charged vector condenses via a second order phase transition. The DC conductivity becomes infinite and the AC conductivity develops a gap in the condensed phase. We study the effect of a background magnetic field on the system. It is found that the background magnetic field can induce the condensate of the vector field even in the case without chemical potential/charge density. In the case with non-vanishing charge density, the transition temperature raises with the applied magnetic field, and the condensate of the charged vector operator forms a vortex lattice structure in the spatial directions perpendicular to the magnetic field.Comment: v3: minor changes, references added, to appear in JHE

Holographic Entanglement Entropy in Insulator/Superconductor Transition

We investigate the behaviors of entanglement entropy in the holographical insulator/superconductor phase transition. We calculate the holographic entanglement entropy for two kinds of geometry configurations in a completely back-reacted gravitational background describing the insulator/superconductor phase transition. The non-monotonic behavior of the entanglement entropy is found in this system. In the belt geometry case, there exist four phases characterized by the chemical potential and belt width.Comment: v2: 18 pages, 12 figures, references and figures added, minor corrections mad

OPARC: Optimal and Precise Array Response Control Algorithm -- Part II: Multi-points and Applications

In this paper, the optimal and precise array response control (OPARC) algorithm proposed in Part I of this two paper series is extended from single point to multi-points. Two computationally attractive parameter determination approaches are provided to maximize the array gain under certain constraints. In addition, the applications of the multi-point OPARC algorithm to array signal processing are studied. It is applied to realize array pattern synthesis (including the general array case and the large array case), multi-constraint adaptive beamforming and quiescent pattern control, where an innovative concept of normalized covariance matrix loading (NCL) is proposed. Finally, simulation results are presented to validate the superiority and effectiveness of the multi-point OPARC algorithm.Comment: submitted to TS

Locality Constraint Dictionary Learning with Support Vector for Pattern Classification

Discriminative dictionary learning (DDL) has recently gained significant attention due to its impressive performance in various pattern classification tasks. However, the locality of atoms is not fully explored in conventional DDL approaches which hampers their classification performance. In this paper, we propose a locality constraint dictionary learning with support vector discriminative term (LCDL-SV), in which the locality information is preserved by employing the graph Laplacian matrix of the learned dictionary. To jointly learn a classifier during the training phase, a support vector discriminative term is incorporated into the proposed objective function. Moreover, in the classification stage, the identity of test data is jointly determined by the regularized residual and the learned multi-class support vector machine. Finally, the resulting optimization problem is solved by utilizing the alternative strategy. Experimental results on benchmark databases demonstrate the superiority of our proposed method over previous dictionary learning approaches on both hand-crafted and deep features. The source code of our proposed LCDL-SV is accessible at https://github.com/yinhefeng/LCDL-SVComment: submitted to IEEE Acces