Chaotic Properties of Subshifts Generated by a Non-Periodic Recurrent Orbit

The chaotic properties of some subshift maps are investigated. These subshifts are the orbit closures of certain non-periodic recurrent points of a shift map. We first provide a review of basic concepts for dynamics of continuous maps in metric spaces. These concepts include nonwandering point, recurrent point, eventually periodic point, scrambled set, sensitive dependence on initial conditions, Robinson chaos, and topological entropy. Next we review the notion of shift maps and subshifts. Then we show that the one-sided subshifts generated by a non-periodic recurrent point are chaotic in the sense of Robinson. Moreover, we show that such a subshift has an infinite scrambled set if it has a periodic point. Finally, we give some examples and discuss the topological entropy of these subshifts, and present two open problems on the dynamics of subshifts

Penalized Estimation of Directed Acyclic Graphs From Discrete Data

Bayesian networks, with structure given by a directed acyclic graph (DAG), are a popular class of graphical models. However, learning Bayesian networks from discrete or categorical data is particularly challenging, due to the large parameter space and the difficulty in searching for a sparse structure. In this article, we develop a maximum penalized likelihood method to tackle this problem. Instead of the commonly used multinomial distribution, we model the conditional distribution of a node given its parents by multi-logit regression, in which an edge is parameterized by a set of coefficient vectors with dummy variables encoding the levels of a node. To obtain a sparse DAG, a group norm penalty is employed, and a blockwise coordinate descent algorithm is developed to maximize the penalized likelihood subject to the acyclicity constraint of a DAG. When interventional data are available, our method constructs a causal network, in which a directed edge represents a causal relation. We apply our method to various simulated and real data sets. The results show that our method is very competitive, compared to many existing methods, in DAG estimation from both interventional and high-dimensional observational data.Comment: To appear in Statistics and Computin

High Order Momentum Modes by Resonant Superradiant Scattering

The spatial and time evolutions of superradiant scattering are studied theoretically for a weak pump beam with different frequency components traveling along the long axis of an elongated Bose-Einstein condensate. Resulting from the analysis for mode competition between the different resonant channels and the local depletion of the spatial distribution in the superradiant Rayleigh scattering, a new method of getting a large number of high-order forward modes by resonant frequency components of the pump beam is provided, which is beneficial to a lager momentum transfer in atom manipulation for the atom interferometry and atomic optics.Comment: 7 pages, 7 figure

Theory for superconductivity in alkali chromium arsenides A2Cr3As3 (A=K,Rb,Cs)

We propose an extended Hubbard model with three molecular orbitals on a hexagonal lattice with $D_{3h}$ symmetry to study recently discovered superconductivity in A$_2$Cr$_3$As$_3$ (A=K,Rb,Cs). Effective pairing interactions from paramagnon fluctuations are derived within the random phase approximation, and are found to be most attractive in spin triplet channels. At small Hubbard $U$ and moderate Hund's coupling, the pairing arises from 3-dimensional (3D) $\gamma$ band and has a spatial symmetry $f_{y(3x^{2}-y^{2})}$, which gives line nodes in the gap function. At large $U$, a fully gapped $p$-wave state, $p_{z}\hat{z}$ dominates at the quasi-1D $\alpha$-band