32,143 research outputs found
Efficient configurational-bias Monte-Carlo simulations of chain molecules with `swarms' of trial configurations
Proposed here is a dynamic Monte-Carlo algorithm that is efficient in
simulating dense systems of long flexible chain molecules. It expands on the
configurational-bias Monte-Carlo method through the simultaneous generation of
a large set of trial configurations. This process is directed by attempting to
terminate unfinished chains with a low statistical weight, and replacing these
chains with clones (enrichments) of stronger chains. The efficiency of the
resulting method is explored by simulating dense polymer brushes. A gain in
efficiency of at least three orders of magnitude is observed with respect to
the configurational-bias approach, and almost one order of magnitude with
respect to recoil-growth Monte-Carlo. Furthermore, the inclusion of `waste
recycling' is observed to be a powerful method for extracting meaningful
statistics from the discarded configurations
Threshold effects for two pathogens spreading on a network
Diseases spread through host populations over the networks of contacts
between individuals, and a number of results about this process have been
derived in recent years by exploiting connections between epidemic processes
and bond percolation on networks. Here we investigate the case of two pathogens
in a single population, which has been the subject of recent interest among
epidemiologists. We demonstrate that two pathogens competing for the same hosts
can both spread through a population only for intermediate values of the bond
occupation probability that lie above the classic epidemic threshold and below
a second higher value, which we call the coexistence threshold, corresponding
to a distinct topological phase transition in networked systems.Comment: 5 pages, 2 figure
A user's manual for the Loaded Microstrip Antenna Code (LMAC)
The use of the Loaded Microstrip Antenna Code is described. The geometry of this antenna is shown and its dimensions are described in terms of the program outputs. The READ statements for the inputs are detailed and typical values are given where applicable. The inputs of four example problems are displayed with the corresponding output of the code given in the appendices
Radiation and scattering from loaded microstrip antennas over a wide bandwidth
The integral equation and moment method solution is developed for two different antennas in the presence of an infinite grounded dielectric substrate. The first antenna is a rectangular microstrip patch antenna. This antenna is analyzed for excitation by an incident plane wave in free space and a vertical filament of uniform current in the dielectric. This antenna can be loaded by a lumped impedance in a vertical filament of uniform current extending from the patch through the dielectric to the ground plane. The radar cross section of the microstrip antenna is found from the plane wave excitation and shows good agreement to measurement for both an unloaded and loaded antenna. The input impedance is found from the current filament excitation. This is compared to the measured input impedance of a coaxially fed microstrip antenna and shows good agreement for both unloaded and loaded antennas when the dielectric substrate is much less than a wavelength. The second antenna is a vertical thin wire extending from the ground plane into or through the dielectric substrate. The mutual impedance between two imbedded monopoles is compared to a previous calculation
Random graphs with clustering
We offer a solution to a long-standing problem in the physics of networks,
the creation of a plausible, solvable model of a network that displays
clustering or transitivity -- the propensity for two neighbors of a network
node also to be neighbors of one another. We show how standard random graph
models can be generalized to incorporate clustering and give exact solutions
for various properties of the resulting networks, including sizes of network
components, size of the giant component if there is one, position of the phase
transition at which the giant component forms, and position of the phase
transition for percolation on the network.Comment: 5 pages, 2 figure
Wang-Landau Algorithm: a Theoretical Analysis of the Saturation of the Error
In this work we present a theoretical analysis of the convergence of the
Wang-Landau algorithm [Phys. Rev. Lett. 86, 2050 (2001)] which was introduced
years ago to calculate the density of states in statistical models. We study
the dynamical behavior of the error in the calculation of the density of
states.We conclude that the source of the saturation of the error is due to the
decreasing variations of the refinement parameter. To overcome this limitation,
we present an analytical treatment in which the refinement parameter is scaled
down as a power law instead of exponentially. An extension of the analysis to
the N-fold way variation of the method is also discussed.Comment: 7 pages, 5 figure
Mean-field solution of the small-world network model
The small-world network model is a simple model of the structure of social
networks, which simultaneously possesses characteristics of both regular
lattices and random graphs. The model consists of a one-dimensional lattice
with a low density of shortcuts added between randomly selected pairs of
points. These shortcuts greatly reduce the typical path length between any two
points on the lattice. We present a mean-field solution for the average path
length and for the distribution of path lengths in the model. This solution is
exact in the limit of large system size and either large or small number of
shortcuts.Comment: 14 pages, 2 postscript figure
Temperature-stable Gunn-diode oscillator
Oscillator consisting of Gunn diode embedded in coaxial circuit has excellent temperature stability and low fabrication costs as compared with automatic-frequency-control crystal oscillators
Clustering and preferential attachment in growing networks
We study empirically the time evolution of scientific collaboration networks
in physics and biology. In these networks, two scientists are considered
connected if they have coauthored one or more papers together. We show that the
probability of scientists collaborating increases with the number of other
collaborators they have in common, and that the probability of a particular
scientist acquiring new collaborators increases with the number of his or her
past collaborators. These results provide experimental evidence in favor of
previously conjectured mechanisms for clustering and power-law degree
distributions in networks.Comment: 13 pages, 2 figure
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