IMT Institutional Repository: No conditions. Results ordered -Date Deposited. 2019-10-23T16:06:00ZEPrintshttp://eprints.imtlucca.it/images/logowhite.pnghttp://eprints.imtlucca.it/2012-02-01T11:39:20Z2018-03-08T17:06:00Zhttp://eprints.imtlucca.it/id/eprint/1095This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/10952012-02-01T11:39:20ZQuantifying the taxonomic diversity in real species communitiesWe analyze several florae (collections of plant species populating specific areas) in different geographic and climatic regions. For every list of species we produce a taxonomic classification tree and we consider its statistical properties. We find that regardless of the geographical location, the climate and the environment all species collections have universal statistical properties that we show to be also robust in time. We then compare observed data sets with simulated communities obtained by randomly sampling a large pool of species from all over the world. We find differences in the behavior of the statistical properties of the corresponding taxonomic trees. Our results suggest that it is possible to distinguish quantitatively real species assemblages from random collections and thus demonstrate the existence of correlations between species.Cécile Caretta CartozoDiego Garlaschellidiego.garlaschelli@imtlucca.itCarlo RicottaMarc BarthélemyGuido Caldarelliguido.caldarelli@imtlucca.it2012-02-01T11:07:59Z2018-03-08T17:06:15Zhttp://eprints.imtlucca.it/id/eprint/1092This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/10922012-02-01T11:07:59ZA self-organized model for network evolutionHere we provide a detailed analysis, along with some extensions and additonal investigations, of a recently proposed [1] self-organized model for the evolution of complex networks. Vertices of the network are characterized by a fitness variable evolving through an extremal dynamics process, as in the Bak-Sneppen [2] model representing a prototype of Self-Organized Criticality. The network topology is in turn shaped by the fitness variable itself, as in the fitness network model [3]. The system self-organizes to a nontrivial state, characterized by a power-law decay of dynamical and topological quantities above a critical threshold. The interplay between topology and dynamics in the system is the key ingredient leading to an unexpected behaviour of these quantities. Guido Caldarelliguido.caldarelli@imtlucca.itAndrea CapocciDiego Garlaschellidiego.garlaschelli@imtlucca.it2012-01-26T14:23:51Z2014-12-18T15:38:41Zhttp://eprints.imtlucca.it/id/eprint/1087This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/10872012-01-26T14:23:51ZInvasion percolation on a tree and queueing modelsWe study the properties of the Barabási model of queuing [ A.-L. Barabási Nature (London) 435 207 (2005); J. G. Oliveira and A.-L. Barabási Nature (London) 437 1251 (2005)] in the hypothesis that the number of tasks grows with time steadily. Our analytical approach is based on two ingredients. First we map exactly this model into an invasion percolation dynamics on a Cayley tree. Second we use the theory of biased random walks. In this way we obtain the following results: the stationary-state dynamics is a sequence of causally and geometrically connected bursts of execution activities with scale-invariant size distribution. We recover the correct waiting-time distribution PW(τ)∼τ−3/2 at the stationary state (as observed in different realistic data). Finally we describe quantitatively the dynamics out of the stationary state quantifying the power-law slow approach to stationarity both in single dynamical realization and in average. These results can be generalized to the case of a stochastic increase in the queue length in time with limited fluctuations. As a limit case we recover the situation in which the queue length fluctuates around a constant average value.Andrea GabrielliGuido Caldarelliguido.caldarelli@imtlucca.it2012-01-26T14:19:40Z2014-12-05T09:24:53Zhttp://eprints.imtlucca.it/id/eprint/1086This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/10862012-01-26T14:19:40ZInvasion percolation and critical transient in the Barabási Model of human dynamicsWe introduce an exact probabilistic description for L=2 of the Barabási model for the dynamics of a list of L tasks. This permits us to study the problem out of the stationary state and to solve explicitly the extremal limit case where a critical behavior for the waiting time distribution is observed. This behavior deviates at any finite time from that of the stationary state. We study also the characteristic relaxation time for finite time deviations from stationarity in all cases showing that it diverges in the extremal limit, confirming that these deviations are important at all time.Andrea GabrielliGuido Caldarelliguido.caldarelli@imtlucca.it