A combinatorial result with applications to self-interacting random walks

We give a series of combinatorial results that can be obtained from any two collections (both indexed by $\Z\times \N$) of left and right pointing arrows that satisfy some natural relationship. When applied to certain self-interacting random walk couplings, these allow us to reprove some known transience and recurrence results for some simple models. We also obtain new results for one-dimensional multi-excited random walks and for random walks in random environments in all dimensions

A combinatorial result with applications to self-interacting random walks

Abstract We give a series of combinatorial results that can be obtained from any two collections (both indexed by Z×N) of left and right pointing arrows that satisfy some natural relationship. When applied to certain self-interacting random walk couplings, these allow us to reprove some known transience and recurrence results for some simple models. We also obtain new results for one-dimensional multi-excited random walks and for random walks in random environments in all dimensions

Strict monotonicity properties in one-dimensional excited random walks

We consider one-dimensional excited random walks with finitely many cookies at each site. There are certain natural monotonicity results that are known for the excited random walk under some partial orderings of the cookie environments. We improve these monotonicity results to be strictly monotone under a partial ordering of cookie environments introduced by Holmes and Salisbury. While the self-interacting nature of the excited random walk makes a direct coupling proof difficult, we show that there is a very natural coupling of the associated branching process from which the monotonicity results follow

Network harness: bundles of routes in public transport networks

Public transport routes sharing the same grid of streets and tracks are often found to proceed in parallel along shorter or longer sequences of stations. Similar phenomena are observed in other networks built with space consuming links such as cables, vessels, pipes, neurons, etc. In the case of public transport networks (PTNs) this behavior may be easily worked out on the basis of sequences of stations serviced by each route. To quantify this behavior we use the recently introduced notion of network harness. It is described by the harness distribution P(r,s): the number of sequences of s consecutive stations that are serviced by r parallel routes. For certain PTNs that we have analyzed we observe that the harness distribution may be described by power laws. These power laws observed indicate a certain level of organization and planning which may be driven by the need to minimize the costs of infrastructure and secondly by the fact that points of interest tend to be clustered in certain locations of a city. This effect may be seen as a result of the strong interdependence of the evolutions of both the city and its PTN. To further investigate the significance of the empirical results we have studied one- and two-dimensional models of randomly placed routes modeled by different types of walks. While in one dimension an analytic treatment was successful, the two dimensional case was studied by simulations showing that the empirical results for real PTNs deviate significantly from those expected for randomly placed routes.Comment: 12 pages, 24 figures, paper presented at the Conference ``Statistical Physics: Modern Trends and Applications'' (23-25 June 2009, Lviv, Ukaine) dedicated to the 100th anniversary of Mykola Bogolyubov (1909-1992

Fluctuations of the one-dimensional asymmetric exclusion process using random matrix techniques

The studies of fluctuations of the one-dimensional Kardar-Parisi-Zhang universality class using the techniques from random matrix theory are reviewed from the point of view of the asymmetric simple exclusion process. We explain the basics of random matrix techniques, the connections to the polynuclear growth models and a method using the Green's function.Comment: 41 pages, 10 figures, minor corrections, references adde

"Cluster Size Distributions of Heterogeneous Economic Agents: Are there non-self-averaging phenomena in economics?"

This paper outlines the applications of one-and two-parameter Poisson-Dirichlet distributions to describe stationary statistical distributions of clus-ters of agents by types. We discuss how the notion of residudal allocation processes in statistics and population genetics literature also arises as stick-breaking processes in the physics literature. The phenomena of self-(non-) averaging in the physics literature are analogous to long-run non-vanishing of profits or variances of capital sizes in some disequilibrium economic dy-namics. We offer an economic interpretation of the physical notion of non-self-averaging as something that refers to the existence of long-run dise-quilibrium phenomena in economics, rather than thermodynamic limits in statistical physics, since both involve non-vanishing of variances as the size or the time goes to infinity.

Random walks on graphs: ideas, techniques and results

Random walks on graphs are widely used in all sciences to describe a great variety of phenomena where dynamical random processes are affected by topology. In recent years, relevant mathematical results have been obtained in this field, and new ideas have been introduced, which can be fruitfully extended to different areas and disciplines. Here we aim at giving a brief but comprehensive perspective of these progresses, with a particular emphasis on physical aspects.Comment: LateX file, 34 pages, 13 jpeg figures, Topical Revie

"Growth Patterns of Two Types of Macro-Models: Limiting Behavior of One-and Two-Parameter Poisson-Dirichlet Models"

This paper uses novel growth models composed of clusters of heterogeneous agents,and shows that limiting behavior of one-and two-parameter Poisson-Dirichlet models are qualitatively very different. As model sizes grow unboundedly, the coefficients of variations of extensive variables, such as the number of total clusters, and the numbers of clusters of specified sizes all approach zero in the one-parameter models, but not in the two-parameter models. In the calculations of the coefficients of variations Mittag-Le?er distributions arise naturally. We show that the distributions of the numbers of the clusters in the models havepower-lawbehavior.