Rank-frequency relation for Chinese characters

We show that the Zipf's law for Chinese characters perfectly holds for sufficiently short texts (few thousand different characters). The scenario of its validity is similar to the Zipf's law for words in short English texts. For long Chinese texts (or for mixtures of short Chinese texts), rank-frequency relations for Chinese characters display a two-layer, hierarchic structure that combines a Zipfian power-law regime for frequent characters (first layer) with an exponential-like regime for less frequent characters (second layer). For these two layers we provide different (though related) theoretical descriptions that include the range of low-frequency characters (hapax legomena). The comparative analysis of rank-frequency relations for Chinese characters versus English words illustrates the extent to which the characters play for Chinese writers the same role as the words for those writing within alphabetical systems.Comment: To appear in European Physical Journal B (EPJ B), 2014 (22 pages, 7 figures

Environmental implications of privatised public space in gated residential neighbourhood: case study of China's small residential district

Gated neighbourhood is well-defined by enclosed walls and gates with clear physical boundaries. The most distinctive feature of gated neighbourhoods is that their public spaces are normally privatised. The construction and operation of the public space within a gated neighbourhood consumes energy and resources, and sequentially has impacts on the environment. This paper argues such environmental impacts from the construction and operation of the public space should be also “privatised”, i.e. it should be jointly owned by all property owners of a gated neighbourhood. Through examining a case study neighbourhood in China, this research indicates the environmental outcomes due to the privatisation of the public space cannot be ignored. De-privatising the public space from gated neighbourhoods through sound urban planning can help to improve environmental sustainability as well as social sustainability in tandem

Disorderless quasi-localization of polar gases in one-dimensional lattices

One-dimensional polar gases in deep optical lattices present a severely constrained dynamics due to the interplay between dipolar interactions, energy conservation, and finite bandwidth. The appearance of dynamically-bound nearest-neighbor dimers enhances the role of the $1/r^3$ dipolar tail, resulting, in the absence of external disorder, in quasi-localization via dimer clustering for very low densities and moderate dipole strengths. Furthermore, even weak dipoles allow for the formation of self-bound superfluid lattice droplets with a finite doping of mobile, but confined, holons. Our results, which can be extrapolated to other power-law interactions, are directly relevant for current and future lattice experiments with magnetic atoms and polar molecules.Comment: 5 + 2 Page

Evidence for the Collective Nature of the Reentrant Integer Quantum Hall States of the Second Landau Level

We report an unexpected sharp peak in the temperature dependence of the magnetoresistance of the reentrant integer quantum Hall states in the second Landau level. This peak defines the onset temperature of these states. We find that in different spin branches the onset temperatures of the reentrant states scale with the Coulomb energy. This scaling provides direct evidence that Coulomb interactions play an important role in the formation of these reentrant states evincing their collective nature

On the Light Curve and Spectrum of SN 2003dh Separated from the Optical Afterglow of GRB 030329

The net optical light curves and spectra of the supernova (SN) 2003dh are obtained from the published spectra of GRB 030329, covering about 6 days before SN maximum to about 60 days after. The bulk of the U-band flux is subtracted from the observed spectra using early-time afterglow templates, because strong line blanketing greatly depresses the UV and U-band SN flux in a metal-rich, fast-moving SN atmosphere. The blue-end spectra of the gamma-ray burst (GRB)connected hypernova SN 1998bw is used to determine the amount of subtraction. The subtraction of a host galaxy template affects the late-time results. The derived SN 2003dh light curves are narrower than those of SN 1998bw, rising as fast before maximum, reaching a possibly fainter maximum, and then declining ~ 1.2-1.4 times faster. We then build UVOIR bolometric SN light curve. Allowing for uncertainties, it can be reproduced with a spherical ejecta model of Mej ~ 7+/-3 Msun, KE ~ (3.5+/-1.5)E52 ergs, with KE/Mej ~ 5 following previous spectrum modelling, and M(Ni56) ~ (0.4 +0.15/-0.1) Msun. This suggests a progenitor main-sequence mass of about 25-40 Msun, lower than SN 1998bw but significantly higher than normal Type Ic SNe and the GRB-unrelated hypernova SN 2002ap.Comment: 18 pages, 7 figures, published by Ap

Dynamics of an inhomogeneous quantum phase transition

We argue that in a second order quantum phase transition driven by an inhomogeneous quench density of quasiparticle excitations is suppressed when velocity at which a critical point propagates across a system falls below a threshold velocity equal to the Kibble-Zurek correlation length times the energy gap at freeze-out divided by $\hbar$. This general prediction is supported by an analytic solution in the quantum Ising chain. Our results suggest, in particular, that adiabatic quantum computers can be made more adiabatic when operated in an "inhomogeneous" way.Comment: 7 pages; version to appear in a special issue of New J. Phy

Blur-Robust Face Recognition via Transformation Learning

Abstract. This paper introduces a new method for recognizing faces degraded by blur using transformation learning on the image feature. The basic idea is to transform both the sharp images and blurred im-ages to a same feature subspace by the method of multidimensional s-caling. Different from the method of finding blur-invariant descriptors, our method learns the transformation which both preserves the mani-fold structure of the original shape images and, at the same time, en-hances the class separability, resulting in a wide applications to various descriptors. Furthermore, we combine our method with subspace-based point spread function (PSF) estimation method to handle cases of un-known blur degree, by applying the feature transformation correspond-ing to the best matched PSF, where the transformation for each PSF is learned in the training stage. Experimental results on the FERET database show the proposed method achieve comparable performance a-gainst the state-of-the-art blur-invariant face recognition methods, such as LPQ and FADEIN.