257 research outputs found
Transport properties of a modified Lorentz gas
We present a detailed study of the first simple mechanical system that shows
fully realistic transport behavior while still being exactly solvable at the
level of equilibrium statistical mechanics. The system under consideration is a
Lorentz gas with fixed freely-rotating circular scatterers interacting with
point particles via perfectly rough collisions. Upon imposing a temperature
and/or a chemical potential gradient, a stationary state is attained for which
local thermal equilibrium holds for low values of the imposed gradients.
Transport in this system is normal, in the sense that the transport
coefficients which characterize the flow of heat and matter are finite in the
thermodynamic limit. Moreover, the two flows are non-trivially coupled,
satisfying Onsager's reciprocity relations to within numerical accuracy as well
as the Green-Kubo relations . We further show numerically that an applied
electric field causes the same currents as the corresponding chemical potential
gradient in first order of the applied field. Puzzling discrepancies in higher
order effects (Joule heating) are also observed. Finally, the role of entropy
production in this purely Hamiltonian system is shortly discussed.Comment: 16 pages, 16 figures, submitted to J. Stat. Phy
Metastability in Markov processes
We present a formalism to describe slowly decaying systems in the context of
finite Markov chains obeying detailed balance. We show that phase space can be
partitioned into approximately decoupled regions, in which one may introduce
restricted Markov chains which are close to the original process but do not
leave these regions. Within this context, we identify the conditions under
which the decaying system can be considered to be in a metastable state.
Furthermore, we show that such metastable states can be described in
thermodynamic terms and define their free energy. This is accomplished showing
that the probability distribution describing the metastable state is indeed
proportional to the equilibrium distribution, as is commonly assumed. We test
the formalism numerically in the case of the two-dimensional kinetic Ising
model, using the Wang--Landau algorithm to show this proportionality
explicitly, and confirm that the proportionality constant is as derived in the
theory. Finally, we extend the formalism to situations in which a system can
have several metastable states.Comment: 30 pages, 5 figures; version with one higher quality figure available
at http://www.fis.unam.mx/~dsanders
Phase transitions in systems of self-propelled agents and related network models
An important characteristic of flocks of birds, school of fish, and many
similar assemblies of self-propelled particles is the emergence of states of
collective order in which the particles move in the same direction. When noise
is added into the system, the onset of such collective order occurs through a
dynamical phase transition controlled by the noise intensity. While originally
thought to be continuous, the phase transition has been claimed to be
discontinuous on the basis of recently reported numerical evidence. We address
this issue by analyzing two representative network models closely related to
systems of self-propelled particles. We present analytical as well as numerical
results showing that the nature of the phase transition depends crucially on
the way in which noise is introduced into the system.Comment: Four pages, four figures. Submitted to PR
Occurrence of normal and anomalous diffusion in polygonal billiard channels
From extensive numerical simulations, we find that periodic polygonal
billiard channels with angles which are irrational multiples of pi generically
exhibit normal diffusion (linear growth of the mean squared displacement) when
they have a finite horizon, i.e. when no particle can travel arbitrarily far
without colliding. For the infinite horizon case we present numerical tests
showing that the mean squared displacement instead grows asymptotically as t
log t. When the unit cell contains accessible parallel scatterers, however, we
always find anomalous super-diffusion, i.e. power-law growth with an exponent
larger than 1. This behavior cannot be accounted for quantitatively by a simple
continuous-time random walk model. Instead, we argue that anomalous diffusion
correlates with the existence of families of propagating periodic orbits.
Finally we show that when a configuration with parallel scatterers is
approached there is a crossover from normal to anomalous diffusion, with the
diffusion coefficient exhibiting a power-law divergence.Comment: 9 pages, 15 figures. Revised after referee reports: redrawn figures,
additional comments. Some higher quality figures available at
http://www.fis.unam.mx/~dsander
L\'evy-like behavior in deterministic models of intelligent agents exploring heterogeneous environments
Many studies on animal and human movement patterns report the existence of
scaling laws and power-law distributions. Whereas a number of random walk
models have been proposed to explain observations, in many situations
individuals actually rely on mental maps to explore strongly heterogeneous
environments. In this work we study a model of a deterministic walker, visiting
sites randomly distributed on the plane and with varying weight or
attractiveness. At each step, the walker minimizes a function that depends on
the distance to the next unvisited target (cost) and on the weight of that
target (gain). If the target weight distribution is a power-law, , in some range of the exponent , the foraging medium induces
movements that are similar to L\'evy flights and are characterized by
non-trivial exponents. We explore variations of the choice rule in order to
test the robustness of the model and argue that the addition of noise has a
limited impact on the dynamics in strongly disordered media.Comment: 15 pages, 7 figures. One section adde
Refined Simulations of the Reaction Front for Diffusion-Limited Two-Species Annihilation in One Dimension
Extensive simulations are performed of the diffusion-limited reaction
AB in one dimension, with initially separated reagents. The reaction
rate profile, and the probability distributions of the separation and midpoint
of the nearest-neighbour pair of A and B particles, are all shown to exhibit
dynamic scaling, independently of the presence of fluctuations in the initial
state and of an exclusion principle in the model. The data is consistent with
all lengthscales behaving as as . Evidence of
multiscaling, found by other authors, is discussed in the light of these
findings.Comment: Resubmitted as TeX rather than Postscript file. RevTeX version 3.0,
10 pages with 16 Encapsulated Postscript figures (need epsf). University of
Geneva preprint UGVA/DPT 1994/10-85
The Reaction-Diffusion Front for in One Dimension
We study theoretically and numerically the steady state diffusion controlled
reaction , where currents of and particles
are applied at opposite boundaries. For a reaction rate , and equal
diffusion constants , we find that when the
reaction front is well described by mean field theory. However, for , the front acquires a Gaussian profile - a result of
noise induced wandering of the reaction front center. We make a theoretical
prediction for this profile which is in good agreement with simulation.
Finally, we investigate the intrinsic (non-wandering) front width and find
results consistent with scaling and field theoretic predictions.Comment: 11 pages, revtex, 4 separate PostScript figure
Static Pairwise Annihilation in Complex Networks
We study static annihilation on complex networks, in which pairs of connected
particles annihilate at a constant rate during time. Through a mean-field
formalism, we compute the temporal evolution of the distribution of surviving
sites with an arbitrary number of connections. This general formalism, which is
exact for disordered networks, is applied to Kronecker, Erd\"os-R\'enyi (i.e.
Poisson) and scale-free networks. We compare our theoretical results with
extensive numerical simulations obtaining excellent agreement. Although the
mean-field approach applies in an exact way neither to ordered lattices nor to
small-world networks, it qualitatively describes the annihilation dynamics in
such structures. Our results indicate that the higher the connectivity of a
given network element, the faster it annihilates. This fact has dramatic
consequences in scale-free networks, for which, once the ``hubs'' have been
annihilated, the network disintegrates and only isolated sites are left.Comment: 7 Figures, 10 page
- …