Antipersistant Effects in the Dynamics of a Competing Population

We consider a population of agents competing for finite resources using strategies based on two channels of signals. The model is applicable to financial markets, ecosystems and computer networks. We find that the dynamics of the system is determined by the correlation between the two channels. In particular, occasional mismatches of the signals induce a series of transitions among numerous attractors. Surprisingly, in contrast to the effects of noises on dynamical systems normally resulting in a large number of attractors, the number of attractors due to the mismatched signals remains finite. Both simulations and analyses show that this can be explained by the antipersistent nature of the dynamics. Antipersistence refers to the response of the system to a given signal being opposite to that of the signal's previous occurrence, and is a consequence of the competition of the agents to make minority decisions. Thus, it is essential for stabilizing the dynamical systems.Comment: 4 pages, 6 figure

Economic Development in China and Its Implications for East Asia

Economic development in China, East Asia, trade adjustment

A gyroscope calibration analysis for the Gamma Ray Observatory (GRO)

Current documentation and software do not adequately address the calculation and use of the optimal weight matrices involved in calibrating inertial reference units (IRU). Several facets of the GRO IRU calibration as it relates to the bias and misalignment weighting matrices are investigated. The physical meaning and use of the bias and misalignment weight matrices in IRU calibration are examined. The relation of the weighting and the final biases, misalignments, and their corrections are pursued. Methods for determining reliable, realistic weighting matrices to be used in the GRO IRU calibration (IRUCAL) utility are determined. Possible correlations among observation uncertainties are also explored. For the undetermined case where the maneuvers are insufficient to identify all calibration parameters, the weighting matrices allow as much information as possible to be extracted from the measurements. Finally, applicable simulated flight data are used, incorporating the appropriate calibration maneuvers, to test the weighting matrices in the IRUCAL utility, and examine correlation effects

Complementary algorithms for graphs and percolation

A pair of complementary algorithms are presented. One of the pair is a fast method for connecting graphs with an edge. The other is a fast method for removing edges from a graph. Both algorithms employ the same tree based graph representation and so, in concert, can arbitrarily modify any graph. Since the clusters of a percolation model may be described as simple connected graphs, an efficient Monte Carlo scheme can be constructed that uses the algorithms to sweep the occupation probability back and forth between two turning points. This approach concentrates computational sampling time within a region of interest. A high precision value of pc = 0.59274603(9) was thus obtained, by Mersenne twister, for the two dimensional square site percolation threshold.Comment: 5 pages, 3 figures, poster version presented at statphys23 (2007

Automatic Dimension Selection for a Non-negative Factorization Approach to Clustering Multiple Random Graphs

We consider a problem of grouping multiple graphs into several clusters using singular value thesholding and non-negative factorization. We derive a model selection information criterion to estimate the number of clusters. We demonstrate our approach using "Swimmer data set" as well as simulated data set, and compare its performance with two standard clustering algorithms.Comment: This paper has been withdrawn by the author due to a newer version with overlapping content