Quantum Spin Liquid with Even Ising Gauge Field Structure on Kagome Lattice

Employing large-scale quantum Monte Carlo simulations, we study the extended $XXZ$ model on the kagome lattice. A $\mathbb Z_2$ quantum spin liquid phase with effective even Ising gauge field structure emerges from the delicate balance among three symmetry-breaking phases including stripe solid, staggered solid and ferromagnet. This $\mathbb{Z}_2$ spin liquid is stabilized by an extended interaction related to the Rokhsar-Kivelson potential in the quantum dimer model limit. The phase transitions from the staggered solid to a spin liquid or ferromagnet are found to be first order and so is the transition between the stripe solid and ferromagnet. However, the transition between a spin liquid and ferromagnet is found to be continuous and belongs to the 3D $XY^*$ universality class associated with the condensation of spinons. The transition between a spin liquid and stripe solid appears to be continuous and associated with the condensation of visons.Comment: 7 pages, 8 figure

Generalization Error Analysis of Neural networks with Gradient Based Regularization

We study gradient-based regularization methods for neural networks. We mainly focus on two regularization methods: the total variation and the Tikhonov regularization. Applying these methods is equivalent to using neural networks to solve some partial differential equations, mostly in high dimensions in practical applications. In this work, we introduce a general framework to analyze the generalization error of regularized networks. The error estimate relies on two assumptions on the approximation error and the quadrature error. Moreover, we conduct some experiments on the image classification tasks to show that gradient-based methods can significantly improve the generalization ability and adversarial robustness of neural networks. A graphical extension of the gradient-based methods are also considered in the experiments

Is informational inefficiency priced in stock markets? A comparison between the U.S. and Chinese cases

Using a sample of U.S. and Chinese stocks between July 1999 and June 2016, we investigate the pricing role of informational inefficiency in stock markets. We find that the relations between returns and the informational inefficiency factor statistically change from significantly positive, to insignificant, and further to significantly negative as informational efficiency increases. This finding provides new insights into the common belief that emerging markets are less efficient than developed markets. We propose new factor models for less efficient markets. Our conclusions are robust to alternative ways of sorting portfolios, to various subsample analyses, and to alternative factor models

The charged-current non-standard neutrino interactions at the LHC and HL-LHC

A series of new physics scenarios predict the existence of the extra charged gauge boson $W'$, which can induce the charged-current (CC) non-standard neutrino interactions (NSI). By using the Monte-Carlo (MC) simulation, we discuss the sensitivity and constraints on the CC NSI parameters $\epsilon^{qq'Y}_{\alpha\beta}$ ($\alpha = \beta = e$ or $\mu$) for different $W'$ masses $M_{W'}$ via the process $p p \rightarrow W'\rightarrow \ell\nu$. We find that the interference term plays an important role which was usually neglected in the LHC experiments. We further analyzed the future and high-luminosity (HL) LHC sensitivities to the CC NSI parameters with $\sqrt{s}$ = 14 TeV and $\mathcal{L}$ = $300\;{\rm fb}^{-1}$, $1\;{\rm ab}^{-1}$ and $3\;{\rm ab}^{-1}$.Comment: 22 pages, 38 figures, 4 table