Schur indices for N=4\mathcal{N}=4 super-Yang-Mills with more general gauge groups

We study the unflavored Schur indices in the $\mathcal{N}=4$ super-Yang-Mills theory for the $B_n,C_n,D_n, G_2$ gauge groups. We explore two methods, namely the character expansion method and the Fermi gas method, to efficiently compute the $q$-series expansion of the Schur indices to some high orders. Using the available data and the modular properties, we are able to fix the exact formulas for the general gauge groups up to some high ranks and discover some interesting new features. We also identify some empirical modular anomaly equations, but unlike the case of $A_n$ groups, they are quite complicated and not sufficiently useful to fix exact formulas for gauge groups of arbitrary rank.Comment: 30 page

Statistical analysis for a penalized EM algorithm in high-dimensional mixture linear regression model

The expectation-maximization (EM) algorithm and its variants are widely used in statistics. In high-dimensional mixture linear regression, the model is assumed to be a finite mixture of linear regression and the number of predictors is much larger than the sample size. The standard EM algorithm, which attempts to find the maximum likelihood estimator, becomes infeasible for such model. We devise a group lasso penalized EM algorithm and study its statistical properties. Existing theoretical results of regularized EM algorithms often rely on dividing the sample into many independent batches and employing a fresh batch of sample in each iteration of the algorithm. Our algorithm and theoretical analysis do not require sample-splitting, and can be extended to multivariate response cases. The proposed methods also have encouraging performances in numerical studies

Authenticated Multiparty Quantum Key Agreement Protocol Based on Grover's Algorithm

In the quantum key agreement protocols, some attackers can impersonate legal participant to participate in the negotiation process and steal the agreement key easily. This is often overlooked for most quantum key agreement protocols, which makes them insecure. In this paper, an authenticated multiparty quantum key agreement protocol based on quantum search algorithm is proposed. In the protocol, combining classical hash function with identity information, the authentication operation conforming to the characteristics of search algorithm is designed. In addition, we give a detailed security analysis, which proves that the protocol is secure against common attacks and impersonation attacks. Meanwhile, single particles, which are used as information carries, and single-particle measurement make our protocol feasible with existing technology

Can Class-Priors Help Single-Positive Multi-Label Learning?

Single-positive multi-label learning (SPMLL) is a typical weakly supervised multi-label learning problem, where each training example is annotated with only one positive label. Existing SPMLL methods typically assign pseudo-labels to unannotated labels with the assumption that prior probabilities of all classes are identical. However, the class-prior of each category may differ significantly in real-world scenarios, which makes the predictive model not perform as well as expected due to the unrealistic assumption on real-world application. To alleviate this issue, a novel framework named {\proposed}, i.e., Class-pRiors Induced Single-Positive multi-label learning, is proposed. Specifically, a class-priors estimator is introduced, which could estimate the class-priors that are theoretically guaranteed to converge to the ground-truth class-priors. In addition, based on the estimated class-priors, an unbiased risk estimator for classification is derived, and the corresponding risk minimizer could be guaranteed to approximately converge to the optimal risk minimizer on fully supervised data. Experimental results on ten MLL benchmark datasets demonstrate the effectiveness and superiority of our method over existing SPMLL approaches

Nonlinear flutter wind tunnel test and numerical analysis of folding fins with freeplay nonlinearities

AbstractThe flutter characteristics of folding control fins with freeplay are investigated by numerical simulation and flutter wind tunnel tests. Based on the characteristics of the structures, fins with different freeplay angles are designed. For a 0° angle of attack, wind tunnel tests of these fins are conducted, and vibration is observed by accelerometers and a high-speed camera. By the expansion of the connected relationships, the governing equations of fit for the nonlinear aeroelastic analysis are established by the free-interface component mode synthesis method. Based on the results of the wind tunnel tests, the flutter characteristics of fins with different freeplay angles are analyzed. The results show that the vibration divergent speed is increased, and the divergent speed is higher than the flutter speed of the nominal linear system. The vibration divergent speed is increased along with an increase in the freeplay angle. The developed free-interface component mode synthesis method could be used to establish governing equations and to analyze the characteristics of nonlinear aeroelastic systems. The results of the numerical simulations and the wind tunnel tests indicate the same trends and critical velocities

(Sr3La2O5)(Zn1-xMnx)2As2: A Bulk Form Diluted Magnetic Semiconductor isostructural to the "32522" Fe-based Superconductors

A new diluted magnetic semiconductor system, (Sr3La2O5)(Zn1-xMnx)2As2, has been synthesized and characterized. 10% Mn substitution for Zn in bulk form (Sr3La2O5)Zn2As2 results in a ferromagnetic ordering below Curie temperature, TC ~ 40 K. (Sr3La2O5)(Zn1-xMnx)2As2 has a layered crystal structure identical to that of 32522-type Fe based superconductors, and represents the fifth DMS family that has a direct counterpart among the FeAs high temperature superconductor families.Comment: Accepted for publication in EP