Holographic three flavor baryon in the Witten-Sakai-Sugimoto model with the D0-D4 background

With the construction of the Witten-Sakai-Sugimoto model in the D0-D4 background, we systematically investigate the holographic baryon spectrum in the case of three flavors. The background geometry in this model is holographically dual to $U\left(N_{c}\right)$ Yang-Mills theory in large $N_{c}$ limit involving an excited state with a nonzero $\theta$ angle or glue condensate $\left\langle \mathrm{Tr}\mathcal{F}\wedge\mathcal{F}\right\rangle =8\pi^{2}N_{c}\tilde{\kappa}$, which is proportional to the charge density of the smeared D0-branes through a parameter $b$ or $\tilde{\kappa}$. The classical solution of baryon in this model can be modified by embedding the Belavin-Polyakov-Schwarz-Tyupkin (BPST) instanton and we carry out the quantization of the collective modes with this solution. Then we extend the analysis to include the heavy flavor and find that the heavy meson is always bound in the form of the zero mode of the flavor instanton in strong coupling limit. The mass spectrum of heavy-light baryons in the situation with single- and double-heavy baryon is derived by solving the eigen equation of the quantized collective Hamiltonian. Afterwards we obtain that the constraint of stable baryon states has to be $1<b<3$ and the difference in the baryon spectrum becomes smaller as the D0 charge increases. It indicates that quarks or mesons can not form stable baryons if the $\theta$ angle or glue condensate is sufficiently large. Our work is an extension of the previous study of this model and also agrees with those conclusions.Comment: 35 pages, 2 figures, 1 table, this version includes the acknowledgement and some revision

Matrix Completion via Max-Norm Constrained Optimization

Matrix completion has been well studied under the uniform sampling model and the trace-norm regularized methods perform well both theoretically and numerically in such a setting. However, the uniform sampling model is unrealistic for a range of applications and the standard trace-norm relaxation can behave very poorly when the underlying sampling scheme is non-uniform. In this paper we propose and analyze a max-norm constrained empirical risk minimization method for noisy matrix completion under a general sampling model. The optimal rate of convergence is established under the Frobenius norm loss in the context of approximately low-rank matrix reconstruction. It is shown that the max-norm constrained method is minimax rate-optimal and yields a unified and robust approximate recovery guarantee, with respect to the sampling distributions. The computational effectiveness of this method is also discussed, based on first-order algorithms for solving convex optimizations involving max-norm regularization.Comment: 33 page

A Max-Norm Constrained Minimization Approach to 1-Bit Matrix Completion

We consider in this paper the problem of noisy 1-bit matrix completion under a general non-uniform sampling distribution using the max-norm as a convex relaxation for the rank. A max-norm constrained maximum likelihood estimate is introduced and studied. The rate of convergence for the estimate is obtained. Information-theoretical methods are used to establish a minimax lower bound under the general sampling model. The minimax upper and lower bounds together yield the optimal rate of convergence for the Frobenius norm loss. Computational algorithms and numerical performance are also discussed.Comment: 33 pages, 3 figure