Dynamics of opinion formation in a small-world network

The dynamical process of opinion formation within a model using a local majority opinion updating rule is studied numerically in networks with the small-world geometrical property. The network is one in which shortcuts are added to randomly chosen pairs of nodes in an underlying regular lattice. The presence of a small number of shortcuts is found to shorten the time to reach a consensus significantly. The effects of having shortcuts in a lattice of fixed spatial dimension are shown to be analogous to that of increasing the spatial dimension in regular lattices. The shortening of the consensus time is shown to be related to the shortening of the mean shortest path as shortcuts are added. Results can also be translated into that of the dynamics of a spin system in a small-world network.Comment: 10 pages, 5 figure

Detection of K+ mesons in segmented electromagnetic calorimeters

The combination of the CrystalBall and TAPS electromagnetic calorimeters were installed in the MAMI A2 hall in 2003. Here they are able to detect the reaction products from photo-induced reactions in combination with the Glasgow photon tagger. In the last two years the MAMI facility was upgraded from 885 MeV to 1.5 GeV, the A2 photon tagger underwent a similar upgrade crossing the threshold for strangeness photoproduction. For the CrystalBall this created a new challenge, to identify K+ mesons above the large background from other charged hadrons, in a situation where the detector setup does not benefit from a magnetic field to help separate particle species. These proceedings outline a novel technique which uses the decay products of the K+ as a strangeness tag

Phase transitions in Ising model on a Euclidean network

A one dimensional network on which there are long range bonds at lattice distances $l>1$ with the probability $P(l) \propto l^{-\delta}$ has been taken under consideration. We investigate the critical behavior of the Ising model on such a network where spins interact with these extra neighbours apart from their nearest neighbours for $0 \leq \delta < 2$. It is observed that there is a finite temperature phase transition in the entire range. For $0 \leq \delta < 1$, finite size scaling behaviour of various quantities are consistent with mean field exponents while for $1\leq \delta\leq 2$, the exponents depend on $\delta$. The results are discussed in the context of earlier observations on the topology of the underlying network.Comment: 7 pages, revtex4, 7 figures; to appear in Physical Review E, minor changes mad

Scale-free networks with tunable degree distribution exponents

We propose and study a model of scale-free growing networks that gives a degree distribution dominated by a power-law behavior with a model-dependent, hence tunable, exponent. The model represents a hybrid of the growing networks based on popularity-driven and fitness-driven preferential attachments. As the network grows, a newly added node establishes $m$ new links to existing nodes with a probability $p$ based on popularity of the existing nodes and a probability $1-p$ based on fitness of the existing nodes. An explicit form of the degree distribution $P(p,k)$ is derived within a mean field approach. For reasonably large $k$, $P(p,k) \sim k^{-\gamma(p)}{\cal F}(k,p)$, where the function ${\cal F}$ is dominated by the behavior of $1/\ln(k/m)$ for small values of $p$ and becomes $k$-independent as $p \to 1$, and $\gamma(p)$ is a model-dependent exponent. The degree distribution and the exponent $\gamma(p)$ are found to be in good agreement with results obtained by extensive numerical simulations.Comment: 12 pages, 2 figures, submitted to PR

Identity and Search in Social Networks

Social networks have the surprising property of being "searchable": Ordinary people are capable of directing messages through their network of acquaintances to reach a specific but distant target person in only a few steps. We present a model that offers an explanation of social network searchability in terms of recognizable personal identities: sets of characteristics measured along a number of social dimensions. Our model defines a class of searchable networks and a method for searching them that may be applicable to many network search problems, including the location of data files in peer-to-peer networks, pages on the World Wide Web, and information in distributed databases.Comment: 4 page, 3 figures, revte

A network-based threshold model for the spreading of fads in society and markets

We investigate the behavior of a threshold model for the spreading of fads and similar phenomena in society. The model is giving the fad dynamics and is intended to be confined to an underlying network structure. We investigate the whole parameter space of the fad dynamics on three types of network models. The dynamics we discover is rich and highly dependent on the underlying network structure. For some range of the parameter space, for all types of substrate networks, there are a great variety of sizes and life-lengths of the fads -- what one see in real-world social and economical systems

A method for predicting full scale buffet response with rigid wind tunnel model fluctuating pressure data. Volume 1: Prediction method development and assessment

The method requires unsteady aerodynamic forces, natural airplane modes, and the measured pressure data as input. A gust response computer program is used to calculate buffet response due to the forcing function posed by the measured pressure data. By calculating both symmetric and antisymmetric solutions, upper and lower bounds on full-scale buffet response are formed. Comparisons of predictions with flight test results are made and the effects of horizontal tail loads and static aeroelasticity are shown. Discussions are also presented on the effects of primary wing torsion modes, chordwise and spanwise phase angles, and altitude

Evolving Network With Different Edges

We proposed an evolving network model constituted by the same nodes but different edges. The competition between nodes and different links were introduced. Scale free properties have been found in this model by continuum theory. Different network topologies can be generated by some tunable parameters. Simulation results consolidate the prediction.Comment: 14 pages, 9 figures, some contents revised, fluctuation of x degree adde

A new possibility for light-quark Dark Matter

Despite many decades of study the physical origin of "dark matter" in the Universe remains elusive. In this letter we calculate the properties of a completely new dark matter candidate - Bose-Einstein condensates formed from a recently discovered bosonic particle in the light-quark sector, the $\mathbf{ d^*(2380)}$ hexaquark. In this first study, we show stable $\mathbf{ d^*(2380)}$ Bose-Einstein condensates could form in the primordial early universe, with a production rate sufficiently large that they are a plausible new candidate for dark matter. Some possible astronomical signatures of such dark matter are also presented