1,080 research outputs found
Map equation for link community
Community structure exists in many real-world networks and has been reported
being related to several functional properties of the networks. The
conventional approach was partitioning nodes into communities, while some
recent studies start partitioning links instead of nodes to find overlapping
communities of nodes efficiently. We extended the map equation method, which
was originally developed for node communities, to find link communities in
networks. This method is tested on various kinds of networks and compared with
the metadata of the networks, and the results show that our method can identify
the overlapping role of nodes effectively. The advantage of this method is that
the node community scheme and link community scheme can be compared
quantitatively by measuring the unknown information left in the networks
besides the community structure. It can be used to decide quantitatively
whether or not the link community scheme should be used instead of the node
community scheme. Furthermore, this method can be easily extended to the
directed and weighted networks since it is based on the random walk.Comment: 9 pages,5 figure
Statistical significance of communities in networks
Nodes in real-world networks are usually organized in local modules. These
groups, called communities, are intuitively defined as sub-graphs with a larger
density of internal connections than of external links. In this work, we
introduce a new measure aimed at quantifying the statistical significance of
single communities. Extreme and Order Statistics are used to predict the
statistics associated with individual clusters in random graphs. These
distributions allows us to define one community significance as the probability
that a generic clustering algorithm finds such a group in a random graph. The
method is successfully applied in the case of real-world networks for the
evaluation of the significance of their communities.Comment: 9 pages, 8 figures, 2 tables. The software to calculate the C-score
can be found at http://filrad.homelinux.org/cscor
Information Storage and Retrieval for Probe Storage using Optical Diffraction Patterns
A novel method for fast information retrieval from a probe storage device is
considered. It is shown that information can be stored and retrieved using the
optical diffraction patterns obtained by the illumination of a large array of
cantilevers by a monochromatic light source. In thermo-mechanical probe
storage, the information is stored as a sequence of indentations on the polymer
medium. To retrieve the information, the array of probes is actuated by
applying a bending force to the cantilevers. Probes positioned over
indentations experience deflection by the depth of the indentation, probes over
the flat media remain un-deflected. Thus the array of actuated probes can be
viewed as an irregular optical grating, which creates a data-dependent
diffraction pattern when illuminated by laser light. We develop a low
complexity modulation scheme, which allows the extraction of information stored
in the pattern of indentations on the media from Fourier coefficients of the
intensity of the diffraction pattern. We then derive a low-complexity maximum
likelihood sequence detection algorithm for retrieving the user information
from the Fourier coefficients. The derivation of both the modulation and the
detection schemes is based on the Fraunhofer formula for data-dependent
diffraction patterns. We show that for as long as the Fresnel number F<0.1, the
optimal channel detector derived from Fraunhofer diffraction theory does not
suffer any significant performance degradation.Comment: 14 pages, 11 figures. Version 2: minor misprints corrected,
experimental section expande
Supergravity Higgs Inflation and Shift Symmetry in Electroweak Theory
We present a model of inflation in a supergravity framework in the Einstein
frame where the Higgs field of the next to minimal supersymmetric standard
model (NMSSM) plays the role of the inflaton. Previous attempts which assumed
non-minimal coupling to gravity failed due to a tachyonic instability of the
singlet field during inflation. A canonical K\"{a}hler potential with
\textit{minimal coupling} to gravity can resolve the tachyonic instability but
runs into the -problem. We suggest a model which is free of the
-problem due to an additional coupling in the K\"{a}hler potential which
is allowed by the Standard Model gauge group. This induces directions in the
potential which we call K-flat. For a certain value of the new coupling in the
(N)MSSM, the K\"{a}hler potential is special, because it can be associated with
a certain shift symmetry for the Higgs doublets, a generalization of the shift
symmetry for singlets in earlier models. We find that K-flat direction has
This shift symmetry is broken by interactions coming from
the superpotential and gauge fields. This direction fails to produce successful
inflation in the MSSM but produces a viable model in the NMSSM. The model is
specifically interesting in the Peccei-Quinn (PQ) limit of the NMSSM. In this
limit the model can be confirmed or ruled-out not just by cosmic microwave
background observations but also by axion searches.Comment: matches the published version at JCA
Self-avoiding walks crossing a square
We study a restricted class of self-avoiding walks (SAW) which start at the
origin (0, 0), end at , and are entirely contained in the square on the square lattice . The number of distinct
walks is known to grow as . We estimate as well as obtaining strict upper and lower bounds,
We give exact results for the number of SAW of
length for and asymptotic results for .
We also consider the model in which a weight or {\em fugacity} is
associated with each step of the walk. This gives rise to a canonical model of
a phase transition. For the average length of a SAW grows as ,
while for it grows as
. Here is the growth constant of unconstrained SAW in . For we provide numerical evidence, but no proof, that the
average walk length grows as .
We also consider Hamiltonian walks under the same restriction. They are known
to grow as on the same lattice. We give
precise estimates for as well as upper and lower bounds, and prove that
Comment: 27 pages, 9 figures. Paper updated and reorganised following
refereein
Leadership Statistics in Random Structures
The largest component (``the leader'') in evolving random structures often
exhibits universal statistical properties. This phenomenon is demonstrated
analytically for two ubiquitous structures: random trees and random graphs. In
both cases, lead changes are rare as the average number of lead changes
increases quadratically with logarithm of the system size. As a function of
time, the number of lead changes is self-similar. Additionally, the probability
that no lead change ever occurs decays exponentially with the average number of
lead changes.Comment: 5 pages, 3 figure
Periodic orbits of the ensemble of Sinai-Arnold cat maps and pseudorandom number generation
We propose methods for constructing high-quality pseudorandom number
generators (RNGs) based on an ensemble of hyperbolic automorphisms of the unit
two-dimensional torus (Sinai-Arnold map or cat map) while keeping a part of the
information hidden. The single cat map provides the random properties expected
from a good RNG and is hence an appropriate building block for an RNG, although
unnecessary correlations are always present in practice. We show that
introducing hidden variables and introducing rotation in the RNG output,
accompanied with the proper initialization, dramatically suppress these
correlations. We analyze the mechanisms of the single-cat-map correlations
analytically and show how to diminish them. We generalize the Percival-Vivaldi
theory in the case of the ensemble of maps, find the period of the proposed RNG
analytically, and also analyze its properties. We present efficient practical
realizations for the RNGs and check our predictions numerically. We also test
our RNGs using the known stringent batteries of statistical tests and find that
the statistical properties of our best generators are not worse than those of
other best modern generators.Comment: 18 pages, 3 figures, 9 table
Fast Quantum Modular Exponentiation
We present a detailed analysis of the impact on modular exponentiation of
architectural features and possible concurrent gate execution. Various
arithmetic algorithms are evaluated for execution time, potential concurrency,
and space tradeoffs. We find that, to exponentiate an n-bit number, for storage
space 100n (twenty times the minimum 5n), we can execute modular exponentiation
two hundred to seven hundred times faster than optimized versions of the basic
algorithms, depending on architecture, for n=128. Addition on a neighbor-only
architecture is limited to O(n) time when non-neighbor architectures can reach
O(log n), demonstrating that physical characteristics of a computing device
have an important impact on both real-world running time and asymptotic
behavior. Our results will help guide experimental implementations of quantum
algorithms and devices.Comment: to appear in PRA 71(5); RevTeX, 12 pages, 12 figures; v2 revision is
substantial, with new algorithmic variants, much shorter and clearer text,
and revised equation formattin
Implementing Shor's algorithm on Josephson Charge Qubits
We investigate the physical implementation of Shor's factorization algorithm
on a Josephson charge qubit register. While we pursue a universal method to
factor a composite integer of any size, the scheme is demonstrated for the
number 21. We consider both the physical and algorithmic requirements for an
optimal implementation when only a small number of qubits is available. These
aspects of quantum computation are usually the topics of separate research
communities; we present a unifying discussion of both of these fundamental
features bridging Shor's algorithm to its physical realization using Josephson
junction qubits. In order to meet the stringent requirements set by a short
decoherence time, we accelerate the algorithm by decomposing the quantum
circuit into tailored two- and three-qubit gates and we find their physical
realizations through numerical optimization.Comment: 12 pages, submitted to Phys. Rev.
Sampling properties of directed networks
For many real-world networks only a small "sampled" version of the original
network may be investigated; those results are then used to draw conclusions
about the actual system. Variants of breadth-first search (BFS) sampling, which
are based on epidemic processes, are widely used. Although it is well
established that BFS sampling fails, in most cases, to capture the
IN-component(s) of directed networks, a description of the effects of BFS
sampling on other topological properties are all but absent from the
literature. To systematically study the effects of sampling biases on directed
networks, we compare BFS sampling to random sampling on complete large-scale
directed networks. We present new results and a thorough analysis of the
topological properties of seven different complete directed networks (prior to
sampling), including three versions of Wikipedia, three different sources of
sampled World Wide Web data, and an Internet-based social network. We detail
the differences that sampling method and coverage can make to the structural
properties of sampled versions of these seven networks. Most notably, we find
that sampling method and coverage affect both the bow-tie structure, as well as
the number and structure of strongly connected components in sampled networks.
In addition, at low sampling coverage (i.e. less than 40%), the values of
average degree, variance of out-degree, degree auto-correlation, and link
reciprocity are overestimated by 30% or more in BFS-sampled networks, and only
attain values within 10% of the corresponding values in the complete networks
when sampling coverage is in excess of 65%. These results may cause us to
rethink what we know about the structure, function, and evolution of real-world
directed networks.Comment: 21 pages, 11 figure
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