246 research outputs found

    The Shape of Unlabeled Rooted Random Trees

    Get PDF
    We consider the number of nodes in the levels of unlabelled rooted random trees and show that the stochastic process given by the properly scaled level sizes weakly converges to the local time of a standard Brownian excursion. Furthermore we compute the average and the distribution of the height of such trees. These results extend existing results for conditioned Galton-Watson trees and forests to the case of unlabelled rooted trees and show that they behave in this respect essentially like a conditioned Galton-Watson process.Comment: 34 pages, 1 figur

    Applications of uniformly distributed functions and sequences in statistic ergodic measuring techniques

    Get PDF
    AbstractThe stochastic ergodic measuring technique is used to measure voltages and mean values by a stochastic principle. After describing this principle it is shown how to estimate the measuring error deterministically with the discrepancy of functions and sequences

    Degree distribution in random planar graphs

    Full text link
    We prove that for each k≥0k\ge0, the probability that a root vertex in a random planar graph has degree kk tends to a computable constant dkd_k, so that the expected number of vertices of degree kk is asymptotically dknd_k n, and moreover that ∑kdk=1\sum_k d_k =1. The proof uses the tools developed by Gimenez and Noy in their solution to the problem of the asymptotic enumeration of planar graphs, and is based on a detailed analysis of the generating functions involved in counting planar graphs. However, in order to keep track of the degree of the root, new technical difficulties arise. We obtain explicit, although quite involved expressions, for the coefficients in the singular expansions of the generating functions of interest, which allow us to use transfer theorems in order to get an explicit expression for the probability generating function p(w)=∑kdkwkp(w)=\sum_k d_k w^k. From this we can compute the dkd_k to any degree of accuracy, and derive the asymptotic estimate dk∼c⋅k−1/2qkd_k \sim c\cdot k^{-1/2} q^k for large values of kk, where q≈0.67q \approx 0.67 is a constant defined analytically
    • …
    corecore