306 research outputs found
The influence of boundaries on high pressure melting experiments
At low pressure, free surfaces play a crucial role in the melting transition.
Under pressure, the surface of the sample is acted upon by some pressure
transmitting medium. To examine the effect of this medium on melting, we
performed Monte Carlo simulations of a system of argon atoms in the form of a
slab with two boundaries. We examined two cases, one with a soft and the other
with a rigid medium at the boundaries. We found that in the presence of a rigid
medium, melting resembles the mechanical lattice instability found in a
surface-free solid. With a soft medium at the boundary, melting begins at the
surface and at a lower temperature. The relevance of these results to
experiment is discussed.Comment: 4 pages, 5 figure
Accurate modeling approach for the structural comparison between monolayer polymer tubes and single-walled nanotubes
In a recent computational study, we found highly structured ground states for
coarse-grained polymers adsorbed to ultrathin nanowires in a certain model
parameter region. Those tubelike configurations show, even at a first glance,
exciting morphological similarities to known atomistic nanotubes such as
single-walled carbon nanotubes. In order to explain those similarities in a
systematic way, we performed additional detailed and extensive simulations of
coarse-grained polymer models with various parameter settings.
We show this here and explain why standard geometrical models for atomistic
nanotubes are not suited to interpret the results of those studies. In fact,
the general structural behavior of polymer nanotubes, as well as specific
previous observations, can only be explained by applying recently developed
polyhedral tube models.Comment: Proceedings of the 24th Workshop on Recent Developments in Computer
Simulation Studies in Condensed Matter Physics, Feb 21-25, 2011, Athens,
Georgia, US
Efficient Hopfield pattern recognition on a scale-free neural network
Neural networks are supposed to recognise blurred images (or patterns) of
pixels (bits) each. Application of the network to an initial blurred version of
one of pre-assigned patterns should converge to the correct pattern. In the
"standard" Hopfield model, the "neurons'' are connected to each other via
bonds which contain the information on the stored patterns. Thus computer
time and memory in general grow with . The Hebb rule assigns synaptic
coupling strengths proportional to the overlap of the stored patterns at the
two coupled neurons. Here we simulate the Hopfield model on the Barabasi-Albert
scale-free network, in which each newly added neuron is connected to only
other neurons, and at the end the number of neurons with neighbours decays
as . Although the quality of retrieval decreases for small , we find
good associative memory for . Hence, these networks gain a
factor in the computer memory and time.Comment: 8 pages including 4 figure
High-Temperature Series Analyses of the Classical Heisenberg and XY Model
Although there is now a good measure of agreement between Monte Carlo and
high-temperature series expansion estimates for Ising () models, published
results for the critical temperature from series expansions up to 12{\em th}
order for the three-dimensional classical Heisenberg () and XY ()
model do not agree very well with recent high-precision Monte Carlo estimates.
In order to clarify this discrepancy we have analyzed extended high-temperature
series expansions of the susceptibility, the second correlation moment, and the
second field derivative of the susceptibility, which have been derived a few
years ago by L\"uscher and Weisz for general vector spin models on
-dimensional hypercubic lattices up to 14{\em th} order in . By analyzing these series expansions in three dimensions with two different
methods that allow for confluent correction terms, we obtain good agreement
with the standard field theory exponent estimates and with the critical
temperature estimates from the new high-precision MC simulations. Furthermore,
for the Heisenberg model we reanalyze existing series for the susceptibility on
the BCC lattice up to 11{\em th} order and on the FCC lattice up to 12{\em th}
order.Comment: 15 pages, Latex, 2 PS figures not included. FUB-HEP 18/92 and HLRZ
76/9
Series Approach to the Randomly Diluted Elastic Network
Series expansions in powers of the concentration p for elastic and other susceptibilities of randomly diluted elastic networks have been generated for a bond-bending model on a honeycomb lattice up to 13th order, and for the central-force model on a triangular lattice up to 22nd order, in p. Critical exponents for both models and the critical threshold of the central-force problem have been estimated by Padé-approximant-analysis techniques. We obtain exponent estimates that are consistent with scaling relations and other calculations. For the bond-bending model, the effective splay elastic constant scales like L−φsp/ν with φsp=1.20±0.015. For central-force elastic percolation, we find β+γ=1.9±0.2 and ν=1.1±0.2
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