分类： 物理学 >> 基本粒子与场物理学 提交时间： 2016-05-08
摘要： We design an irreversible Markov chain Monte Carlo algorithm for the self-avoiding walk (SAW). It outperforms the Berretti-Sokal algorithm. The gained efficiency increases with the spatial dimension, from about 10 times in two dimensions to around 40 times in five dimensions. The algorithm violates the widely used detailed balance condition and satisfies the weaker balance condition. We employ the irreversible method to study the finite-size scaling of SAW above the upper critical dimension.
分类： 物理学 提交时间： 2016-05-08
摘要： There are more than eight hundred interest rates published in China bond market every day.Which are the benchmark interest rates that have broad influences on most interest rates is a major concern for economists. In this paper, multi-variable Granger causality test is developed and applied to construct a directed network of interest rates, whose important nodes, regarded as key interest rates, are evaluated with inverse Page Rank scores. The results indicate that some short-term interest rates have larger influences on the most key interest rates, while repo rates are the benchmark of short-term rates. It is also found that central bank bills rates are in the core position of mid-term interest rates network, and treasury bond rates are leading the long-term bonds rates.The evolution of benchmark interest rates is also studied from 2008 to 2014, and it’s found that SHIBOR has generally become the benchmark interest rate in China. In the frequency domain we detect the properties of information flows between interest rates and the result confirms the existence of market segmentation in China bond market.
分类： 物理学 提交时间： 2016-05-08
摘要： We have investigated both site and bond percolation on two-dimensional lattice under the random rule and the product rule respectively. With the random rule, sites or bonds are added randomly into the lattice. From two candidates picked randomly, the site or bond with the smaller size product of two connected clusters is added when the product rule is taken. Not only the size of the largest cluster but also its size jump are studied to characterize the universality class of percolation. The finite-size scaling forms of giant cluster size and size jump are proposed and used to determine the critical exponents of percolation from Monte Carlo data. It is found that the critical exponents of both size and size jump in random site percolation are equal to that in random bond percolation. With the random rule, site and bond percolation belong to the same universality class. We obtain the critical exponents of the site percolation under the product rule, which are different from that of both random percolation and the bond percolation under the product rule. The universality class of site percolation differs different from that of bond percolation when the product rule is used.
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