187,402 research outputs found
First-Principles Study of Integer Quantum Hall Transitions in Mesoscopic Samples
We perform first principles numerical simulations to investigate resistance
fluctuations in mesoscopic samples, near the transition between consecutive
Quantum Hall plateaus. We use six-terminal geometry and sample sizes similar to
those of real devices. The Hall and longitudinal resistances extracted from the
generalized Landauer formula reproduce all the experimental features uncovered
recently. We then use a simple generalization of the Landauer-B\"uttiker model,
based on the interplay between tunneling and chiral currents -- the co-existing
mechanisms for transport -- to explain the three distinct types of fluctuations
observed, and identify the central region as the critical region.Comment: changes to acknowledgements onl
Spin-one bosons in low dimensional Mott insulating states
We analyze the strong coupling limit of spin-one bosons in low dimensional
Mott insulating states. In 1D lattices, for an odd number of bosons per site
(), the ground state is a dimerized valence bond crystal state with a
two-fold degeneracy; the low lying elementary spin excitations carry spin one.
For an even number of bosons per site, the ground state is a nondegenerate spin
singlet Mott state. We also argue that in a square lattice in a quantum
disordered limit the ground states should be dimerized valence bond crystals
for an odd integer . Finally, we briefly report results for non-integer
numbers of bosons per site in one-dimensional lattices.Comment: 5 pages; discussions on non-integer case have been shortene
Random Networks with given Rich-club Coefficient
In complex networks it is common to model a network or generate a surrogate
network based on the conservation of the network's degree distribution. We
provide an alternative network model based on the conservation of connection
density within a set of nodes. This density is measure by the rich-club
coefficient. We present a method to generate surrogates networks with a given
rich-club coefficient. We show that by choosing a suitable local linking term,
the generated random networks can reproduce the degree distribution and the
mixing pattern of real networks. The method is easy to implement and produces
good models of real networks.Comment: revised version, new figure
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