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J. G. Liu

Publications and source records attributed to J. G. Liu.

4 recordsLinked to original sources

Quantum impurities in channel mixing baths

We propose a versatile strategy for numerical renormalization group solution of general channel-mixing Kondo and Anderson models beyond previous reach, opening the door toward broad applications in protocol non-perturbative machineries, such as dynamical cluster approximation and cluster dynamical mean field theory, for strongly correlated electron systems. We illustrate the strategy by investigating the quantum phase transitions in two quantum impurity models with cases untouched before.

cond-mat.str-el

Fluctuation of the download network

The scaling behavior of fluctuation for a download network which we have investigated a few years ago based upon Zhang's Encophysics web page has been presented. A power law scaling, namely $σ\sim < f> ^ α$ exists between the dispersion $σ$ and average flux $ $ of the download rates. The fluctuation exponent $α$ is neither 1/2 nor 1 which was claimed as two universal fluctuation classes in previous publication, instead it varies from 1/2 to 1 with the time window in which the download data were accumulated. The crossover behavior of fluctuation exponents can be qualitatively understood by the external driving fluctuation model for a small-size system or a network traffic model which suggests congestion as the origin.

physics.soc-ph

Network Topology of the Austrian Airline Flights

The information of the Austrian airline flights was collected and quantitatively analyzed by the concepts of complex network. It displays some features of small-world networks, namely large clustering coefficient and small average shortest-path length. The degree distributions of the networks reveal power law behavior with exponent value of 2 $\sim$ 3 for the small degree branch but a flat tail for the large degree branch. Similarly, the flight weight distributions show power-law behavior for the small weight branch. Furthermore, we found that the clustering coefficient $C$, 0.206, of this flight network is greatly larger than that of a random network, 0.01, which has the same numbers of the airports ($N$) and mean degree ($ $), and the diameter $D$, 2.383, of the flight network is significantly smaller than the value of the same random network, 18.67. In addition, the degree-degree correlation analysis shows the network has disassortative behavior, i.e. the large airports are likely to link to smaller airports. Furthermore, the clustering coefficient analysis indicates that the large airports reveal the hierarchical organization.

physics.soc-ph

Scale-free download network for publications

The scale-free power-law behavior of the statistics of the download frequency of publications has been, for the first time, reported. The data of the download frequency of publications are taken from a well-constructed web page in the field of economic physics (http://www.unifr.ch/econophysics/). The Zipf-law analysis and the Tsallis entropy method were used to fit the download frequency. It was found that the power-law exponent of rank-ordered frequency distribution is $γ\sim 0.38 \pm 0.04$ which is consistent with the power-law exponent $α\sim 3.37 \pm 0.45$ for the cumulated frequency distributions. Preferential attachment model of Barabasi and Albert network has been used to explain the download network.

cond-mat.dis-nn