title: Google matrix, dynamical attractors, and Ulam networks.
abstract: We study the properties of the Google matrix generated by a coarse-grained Perron-Frobenius operator of the Chirikov typical map with dissipation. The finite-size matrix approximant of this operator is constructed by the Ulam method. This method applied to the simple dynamical model generates directed Ulam networks with approximate scale-free scaling and characteristics being in certain features similar to those of the world wide web with approximate scale-free degree distributions as well as two characteristics similar to the web: a power-law decay in PageRank that mirrors the decay of PageRank on the world wide web and a sensitivity to the value alpha in PageRank. The simple dynamical attractors play here the role of popular websites with a strong concentration of PageRank. A variation in the Google parameter alpha or other parameters of the dynamical map can drive the PageRank of the Google matrix to a delocalized phase with a strange attractor where the Google search becomes inefficient.
authors.affiliation: Laboratoire de Physique Théorique (IRSAMC), Université de Toulouse-UPS, F-31062 Toulouse, France.
authors.forename: D L
authors.initials: DL
authors.lastname: Shepelyansky
authors.forename: O V
authors.initials: OV
authors.lastname: Zhirov