261,274 research outputs found
Quantum-disordered slave-boson theory of underdoped cuprates
We study the stability of the spin gap phase in the U(1) slave-boson theory
of the t-J model in connection to the underdoped cuprates. We approach the spin
gap phase from the superconducting state and consider the quantum phase
transition of the slave-bosons at zero temperature by introducing vortices in
the boson superfluid. At finite temperatures, the properties of the bosons are
different from those of the strange metal phase and lead to modified gauge
field fluctuations. As a result, the spin gap phase can be stabilized in the
quantum critical and quantum disordered regime of the boson system. We also
show that the regime of quantum disordered bosons with the paired fermions can
be regarded as the strong coupling version of the recently proposed nodal
liquid theory.Comment: 5 pages, Replaced by the published versio
Disassortativity of random critical branching trees
Random critical branching trees (CBTs) are generated by the multiplicative
branching process, where the branching number is determined stochastically,
independent of the degree of their ancestor. Here we show analytically that
despite this stochastic independence, there exists the degree-degree
correlation (DDC) in the CBT and it is disassortative. Moreover, the skeletons
of fractal networks, the maximum spanning trees formed by the edge betweenness
centrality, behave similarly to the CBT in the DDC. This analytic solution and
observation support the argument that the fractal scaling in complex networks
originates from the disassortativity in the DDC.Comment: 3 pages, 2 figure
The q-component static model : modeling social networks
We generalize the static model by assigning a q-component weight on each
vertex. We first choose a component among the q components at random
and a pair of vertices is linked with a color according to their weights
of the component as in the static model. A (1-f) fraction of the entire
edges is connected following this way. The remaining fraction f is added with
(q+1)-th color as in the static model but using the maximum weights among the q
components each individual has. This model is motivated by social networks. It
exhibits similar topological features to real social networks in that: (i) the
degree distribution has a highly skewed form, (ii) the diameter is as small as
and (iii) the assortativity coefficient r is as positive and large as those in
real social networks with r reaching a maximum around .Comment: 5 pages, 6 figure
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Self-organized Model for Modular Complex Networks: Division and Independence
We introduce a minimal network model which generates a modular structure in a self-organized way. To this end, we modify the Barabasi-Albert model into the one evolving under the principle of division and independence as well as growth and preferential attachment (PA). A newly added vertex chooses one of the modules composed of existing vertices, and attaches edges to vertices belonging to that module following the PA rule. When the module size reaches a proper size, the module is divided into two, and a new module is created. The karate club network studied by Zachary is a prototypical example. We find that the model can reproduce successfully the behavior of the hierarchical clustering coefficient of a vertex with degree k, C(k), in good agreement with empirical measurements of real world networks
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