Understanding the temperature and the chemical potential using computer simulations

Several Monte Carlo algorithms and applications that are useful for understanding the concepts of temperature and chemical potential are discussed. We then introduce a generalization of the demon algorithm that measures the chemical potential and is suitable for simulating systems with variable particle number.Comment: 23 pages including 6 figure

Teaching statistical physics by thinking about models and algorithms

We discuss several ways of illustrating fundamental concepts in statistical and thermal physics by considering various models and algorithms. We emphasize the importance of replacing students' incomplete mental images by models that are physically accurate. In some cases it is sufficient to discuss the results of an algorithm or the behavior of a model rather than having students write a program.Comment: 21 pages, 4 figures, submitted to the American Journal of Physic

Recognition of Emerging Technology Trends. Class-selective study of citations in the U.S. Patent Citation Network

By adopting a citation-based recursive ranking method for patents the evolution of new fields of technology can be traced. Specifically, it is demonstrated that the laser / inkjet printer technology emerged from the recombination of two existing technologies: sequential printing and static image production. The dynamics of the citations coming from the different "precursor" classes illuminates the mechanism of the emergence of new fields and give the possibility to make predictions about future technological development. For the patent network the optimal value of the PageRank damping factor is close to 0.5; the application of d=0.85 leads to unacceptable ranking results.Comment: 8 pages, 2 tables, 1 figure , (accepted). in Scientometrics 201

Granular Collapse as a Percolation Transition

Inelastic collapse is found in a two-dimensional system of inelastic hard disks confined between two walls which act as an energy source. As the coefficient of restitution is lowered, there is a transition between a state containing small collapsed clusters and a state dominated by a large collapsed cluster. The transition is analogous to that of a percolation transition. At the transition the number of clusters n_s of size s scales as $n_s \sim s^{-\tau}$ with $\tau \approx 2.7$.Comment: 10 pages revtex, 5 figures, accepted by Phys Rev E many changes and corrections from previous submissio

Properties of a random attachment growing network

In this study we introduce and analyze the statistical structural properties of a model of growing networks which may be relevant to social networks. At each step a new node is added which selects 'k' possible partners from the existing network and joins them with probability delta by undirected edges. The 'activity' of the node ends here; it will get new partners only if it is selected by a newcomer. The model produces an infinite-order phase transition when a giant component appears at a specific value of delta, which depends on k. The average component size is discontinuous at the transition. In contrast, the network behaves significantly different for k=1. There is no giant component formed for any delta and thus in this sense there is no phase transition. However, the average component size diverges for delta greater or equal than one half.Comment: LaTeX, 19 pages, 6 figures. Discussion section, comments, a new figure and a new reference are added. Equations simplifie

Non-equilibrium relaxation and interface energy of the Ising model

{}From the non-equilibrium critical relaxation study of the two-dimensional Ising model, the dynamical critical exponent $z$ is estimated to be $2.165 \pm 0.010$ for this model. The relaxation in the ordered phase of this model is consistent with $\exp (-\sqrt{t/\tau })$ behavior. The interface energy of the three-dimensional Ising model is studied and the critical exponent of the correlation length $\nu$ and the critical amplitude of the surface tension $\sigma_0$ are estimated to be $0.6250\pm 0.025$ and $1.42\pm 0.04$, respectively. A dynamic Monte Carlo renormalization group method is applied to the equilibrium properties of the three-dimensional Ising model successfully.Comment: 32pages( 15 figures are not included. Their Postscript file is available. Request the author directly. ), LaTe

New Dynamic Monte Carlo Renormalization Group Method

The dynamical critical exponent of the two-dimensional spin-flip Ising model is evaluated by a Monte Carlo renormalization group method involving a transformation in time. The results agree very well with a finite-size scaling analysis performed on the same data. The value of $z = 2.13 \pm 0.01$ is obtained, which is consistent with most recent estimates