Google matrix of the world trade network

Using the United Nations Commodity Trade Statistics Database [http://comtrade.un.org/db/] we construct the Google matrix of the world trade network and analyze its properties for various trade commodities for all countries and all available years from 1962 to 2009. The trade flows on this network are classified with the help of PageRank and CheiRank algorithms developed for the World Wide Web and other large scale directed networks. For the world trade this ranking treats all countries on equal democratic grounds independent of country richness. Still this method puts at the top a group of industrially developed countries for trade in {\it all commodities}. Our study establishes the existence of two solid state like domains of rich and poor countries which remain stable in time, while the majority of countries are shown to be in a gas like phase with strong rank fluctuations. A simple random matrix model provides a good description of statistical distribution of countries in two-dimensional rank plane. The comparison with usual ranking by export and import highlights new features and possibilities of our approach.Comment: 14 pages, 13 figures. More detailed data and high definition figures are available on the website: http://www.quantware.ups-tlse.fr/QWLIB/tradecheirank/index.htm

Enhancement of localization length for two interacting kicked rotators

We study the effect of coherent propagation of two interacting particles in a disordered potential. The dependence of the enhancement factor for coherent localization length due to interaction is investigated numerically in the model of quantum chaos. The effect of interaction for two particles in many dimensions is also discussed.Comment: 17 pages in revtex, 9 figures (postscript obtained upon request via e-mail at [email protected]) submitted to Nonlinearit

Disorder and superconductivity : a new phase of bi-particle localized states

We study the two-dimensional, disordered, attractive Hubbard model by the projector quantum Monte Carlo method and Bogoliubov - de Gennes mean-field theory. Our results for the ground state show the appearance of a new phase with charge localization in the metallic regime of the non-interacting model. Contrary to the common lore, we demonstrate that mean-field theory fails to predict this phase and is unable to describe the correct physical picture in this regime.Comment: revtex, 4 pages, 3 figure

Google matrix analysis of DNA sequences

For DNA sequences of various species we construct the Google matrix G of Markov transitions between nearby words composed of several letters. The statistical distribution of matrix elements of this matrix is shown to be described by a power law with the exponent being close to those of outgoing links in such scale-free networks as the World Wide Web (WWW). At the same time the sum of ingoing matrix elements is characterized by the exponent being significantly larger than those typical for WWW networks. This results in a slow algebraic decay of the PageRank probability determined by the distribution of ingoing elements. The spectrum of G is characterized by a large gap leading to a rapid relaxation process on the DNA sequence networks. We introduce the PageRank proximity correlator between different species which determines their statistical similarity from the view point of Markov chains. The properties of other eigenstates of the Google matrix are also discussed. Our results establish scale-free features of DNA sequence networks showing their similarities and distinctions with the WWW and linguistic networks.Comment: latex, 11 fig

Google matrix analysis of the multiproduct world trade network

Using the United Nations COMTRADE database \cite{comtrade} we construct the Google matrix $G$ of multiproduct world trade between the UN countries and analyze the properties of trade flows on this network for years 1962 - 2010. This construction, based on Markov chains, treats all countries on equal democratic grounds independently of their richness and at the same time it considers the contributions of trade products proportionally to their trade volume. We consider the trade with 61 products for up to 227 countries. The obtained results show that the trade contribution of products is asymmetric: some of them are export oriented while others are import oriented even if the ranking by their trade volume is symmetric in respect to export and import after averaging over all world countries. The construction of the Google matrix allows to investigate the sensitivity of trade balance in respect to price variations of products, e.g. petroleum and gas, taking into account the world connectivity of trade links. The trade balance based on PageRank and CheiRank probabilities highlights the leading role of China and other BRICS countries in the world trade in recent years. We also show that the eigenstates of $G$ with large eigenvalues select specific trade communities.Comment: 19 pages, 25 figure

Destruction of Anderson localization by nonlinearity in kicked rotator at different effective dimensions

We study numerically the frequency modulated kicked nonlinear rotator with effective dimension $d=1,2,3,4$. We follow the time evolution of the model up to $10^9$ kicks and determine the exponent $\alpha$ of subdiffusive spreading which changes from $0.35$ to $0.5$ when the dimension changes from $d=1$ to $4$. All results are obtained in a regime of relatively strong Anderson localization well below the Anderson transition point existing for $d=3,4$. We explain that this variation of the exponent is different from the usual $d-$dimensional Anderson models with local nonlinearity where $\alpha$ drops with increasing $d$. We also argue that the renormalization arguments proposed by Cherroret N et al. arXiv:1401.1038 are not valid.Comment: 8 pages, 3 figure

Quantum Gibbs distribution from dynamical thermalization in classical nonlinear lattices

We study numerically time evolution in classical lattices with weak or moderate nonlinearity which leads to interactions between linear modes. Our results show that in a certain strength range a moderate nonlinearity generates a dynamical thermalization process which drives the system to the quantum Gibbs distribution of probabilities, or average oscillation amplitudes. The effective dynamical temperature of the lattice varies from large positive to large negative values depending on energy of initially excited modes. This quantum Gibbs distribution is drastically different from usually expected energy equipartition over linear modes corresponding to a regime of classical thermalization. Possible experimental observations of this dynamical thermalization are discussed for cold atoms in optical lattices, nonlinear photonic lattices and optical fiber arrays.Comment: 15 pages, 12 figures. Small modifs., video abstract 107MB at http://www.quantware.ups-tlse.fr/dima/video/gibbs2013.mp

Opinion formation driven by PageRank node influence on directed networks

We study a two states opinion formation model driven by PageRank node influence and report an extensive numerical study on how PageRank affects collective opinion formations in large-scale empirical directed networks. In our model the opinion of a node can be updated by the sum of its neighbor nodes' opinions weighted by the node influence of the neighbor nodes at each step. We consider PageRank probability and its sublinear power as node influence measures and investigate evolution of opinion under various conditions. First, we observe that all networks reach steady state opinion after a certain relaxation time. This time scale is decreasing with the heterogeneity of node influence in the networks. Second, we find that our model shows consensus and non-consensus behavior in steady state depending on types of networks: Web graph, citation network of physics articles, and LiveJournal social network show non-consensus behavior while Wikipedia article network shows consensus behavior. Third, we find that a more heterogeneous influence distribution leads to a more uniform opinion state in the cases of Web graph, Wikipedia, and Livejournal. However, the opposite behavior is observed in the citation network. Finally we identify that a small number of influential nodes can impose their own opinion on significant fraction of other nodes in all considered networks. Our study shows that the effects of heterogeneity of node influence on opinion formation can be significant and suggests further investigations on the interplay between node influence and collective opinion in networks.Comment: 10 pages, 6 figures. Published in Physica A 436, 707-715 (2015