234 research outputs found
The azimuth structure of nuclear collisions -- I
We describe azimuth structure commonly associated with elliptic and directed
flow in the context of 2D angular autocorrelations for the purpose of precise
separation of so-called nonflow (mainly minijets) from flow. We extend the
Fourier-transform description of azimuth structure to include power spectra and
autocorrelations related by the Wiener-Khintchine theorem. We analyze several
examples of conventional flow analysis in that context and question the
relevance of reaction plane estimation to flow analysis. We introduce the 2D
angular autocorrelation with examples from data analysis and describe a
simulation exercise which demonstrates precise separation of flow and nonflow
using the 2D autocorrelation method. We show that an alternative correlation
measure based on Pearson's normalized covariance provides a more intuitive
measure of azimuth structure.Comment: 27 pages, 12 figure
Persistent random walk on a one-dimensional lattice with random asymmetric transmittances
We study the persistent random walk of photons on a one-dimensional lattice
of random asymmetric transmittances. Each site is characterized by its
intensity transmittance t (t') for photons moving to the right (left)
direction. Transmittances at different sites are assumed independent,
distributed according to a given probability density Distribution. We use the
effective medium approximation and identify two classes of probability density
distribution of transmittances which lead to the normal diffusion of photons.
Monte Carlo simulations confirm our predictions.Comment: 7 pages, submitted to Phys. Rev.
Diffusive transport of light in three-dimensional disordered Voronoi structures
The origin of diffusive transport of light in dry foams is still under
debate. In this paper, we consider the random walks of photons as they are
reflected or transmitted by liquid films according to the rules of ray optics.
The foams are approximately modeled by three-dimensional Voronoi tessellations
with varying degree of disorder. We study two cases: a constant intensity
reflectance and the reflectance of thin films. Especially in the second case,
we find that in the experimentally important regime for the film thicknesses,
the transport-mean-free path does not significantly depend on the topological
and geometrical disorder of the Voronoi foams including the periodic Kelvin
foam. This may indicate that the detailed structure of foams is not crucial for
understanding the diffusive transport of light. Furthermore, our theoretical
values for transport-mean-free path fall in the same range as the experimental
values observed in dry foams. One can therefore argue that liquid films
contribute substantially to the diffusive transport of light in {dry} foams.Comment: 8 pages, 8 figure
Relativistic diffusion processes and random walk models
The nonrelativistic standard model for a continuous, one-parameter diffusion
process in position space is the Wiener process. As well-known, the Gaussian
transition probability density function (PDF) of this process is in conflict
with special relativity, as it permits particles to propagate faster than the
speed of light. A frequently considered alternative is provided by the
telegraph equation, whose solutions avoid superluminal propagation speeds but
suffer from singular (non-continuous) diffusion fronts on the light cone, which
are unlikely to exist for massive particles. It is therefore advisable to
explore other alternatives as well. In this paper, a generalized Wiener process
is proposed that is continuous, avoids superluminal propagation, and reduces to
the standard Wiener process in the non-relativistic limit. The corresponding
relativistic diffusion propagator is obtained directly from the nonrelativistic
Wiener propagator, by rewriting the latter in terms of an integral over
actions. The resulting relativistic process is non-Markovian, in accordance
with the known fact that nontrivial continuous, relativistic Markov processes
in position space cannot exist. Hence, the proposed process defines a
consistent relativistic diffusion model for massive particles and provides a
viable alternative to the solutions of the telegraph equation.Comment: v3: final, shortened version to appear in Phys. Rev.
Information dynamics: Temporal behavior of uncertainty measures
We carry out a systematic study of uncertainty measures that are generic to
dynamical processes of varied origins, provided they induce suitable continuous
probability distributions. The major technical tool are the information theory
methods and inequalities satisfied by Fisher and Shannon information measures.
We focus on a compatibility of these inequalities with the prescribed
(deterministic, random or quantum) temporal behavior of pertinent probability
densities.Comment: Incorporates cond-mat/0604538, title, abstract changed, text
modified, to appear in Cent. Eur. J. Phy
Statistical Mechanics of Glass Formation in Molecular Liquids with OTP as an Example
We extend our statistical mechanical theory of the glass transition from
examples consisting of point particles to molecular liquids with internal
degrees of freedom. As before, the fundamental assertion is that super-cooled
liquids are ergodic, although becoming very viscous at lower temperatures, and
are therefore describable in principle by statistical mechanics. The theory is
based on analyzing the local neighborhoods of each molecule, and a statistical
mechanical weight is assigned to every possible local organization. This
results in an approximate theory that is in very good agreement with
simulations regarding both thermodynamical and dynamical properties
Diffusive transport of light in a two-dimensional disordered packing of disks: Analytical approach to transport-mean-free path
We study photon diffusion in a two-dimensional random packing of monodisperse
disks as a simple model of granular media and wet foams. We assume that the
intensity reflectance of disks is a constant. We present an analytic expression
for the transport-mean-free path in terms of the velocity of light in the disks
and host medium, radius and packing fraction of the disks, and the intensity
reflectance. For the glass beads immersed in the air or water, we estimate
transport-mean-free paths about half the experimental ones. For the air bubbles
immersed in the water, transport-mean-free paths is an inverse function of
liquid volume fraction of the model wet foam. This throws new light on the
empirical law of Vera et. al, and promotes more realistic models.Comment: 9 pages, 6 figure
Active Brownian Particles. From Individual to Collective Stochastic Dynamics
We review theoretical models of individual motility as well as collective
dynamics and pattern formation of active particles. We focus on simple models
of active dynamics with a particular emphasis on nonlinear and stochastic
dynamics of such self-propelled entities in the framework of statistical
mechanics. Examples of such active units in complex physico-chemical and
biological systems are chemically powered nano-rods, localized patterns in
reaction-diffusion system, motile cells or macroscopic animals. Based on the
description of individual motion of point-like active particles by stochastic
differential equations, we discuss different velocity-dependent friction
functions, the impact of various types of fluctuations and calculate
characteristic observables such as stationary velocity distributions or
diffusion coefficients. Finally, we consider not only the free and confined
individual active dynamics but also different types of interaction between
active particles. The resulting collective dynamical behavior of large
assemblies and aggregates of active units is discussed and an overview over
some recent results on spatiotemporal pattern formation in such systems is
given.Comment: 161 pages, Review, Eur Phys J Special-Topics, accepte
Collective Motion of Cells Mediates Segregation and Pattern Formation in Co-Cultures
Pattern formation by segregation of cell types is an important process during embryonic development. We show that an experimentally yet unexplored mechanism based on collective motility of segregating cells enhances the effects of known pattern formation mechanisms such as differential adhesion, mechanochemical interactions or cell migration directed by morphogens. To study in vitro cell segregation we use time-lapse videomicroscopy and quantitative analysis of the main features of the motion of individual cells or groups. Our observations have been extensive, typically involving the investigation of the development of patterns containing up to 200,000 cells. By either comparing keratocyte types with different collective motility characteristics or increasing cells' directional persistence by the inhibition of Rac1 GTP-ase we demonstrate that enhanced collective cell motility results in faster cell segregation leading to the formation of more extensive patterns. The growth of the characteristic scale of patterns generally follows an algebraic scaling law with exponent values up to 0.74 in the presence of collective motion, compared to significantly smaller exponents in case of diffusive motion
A Stochastic Description of Dictyostelium Chemotaxis
Chemotaxis, the directed motion of a cell toward a chemical source, plays a key role in many essential biological processes. Here, we derive a statistical model that quantitatively describes the chemotactic motion of eukaryotic cells in a chemical gradient. Our model is based on observations of the chemotactic motion of the social ameba Dictyostelium discoideum, a model organism for eukaryotic chemotaxis. A large number of cell trajectories in stationary, linear chemoattractant gradients is measured, using microfluidic tools in combination with automated cell tracking. We describe the directional motion as the interplay between deterministic and stochastic contributions based on a Langevin equation. The functional form of this equation is directly extracted from experimental data by angle-resolved conditional averages. It contains quadratic deterministic damping and multiplicative noise. In the presence of an external gradient, the deterministic part shows a clear angular dependence that takes the form of a force pointing in gradient direction. With increasing gradient steepness, this force passes through a maximum that coincides with maxima in both speed and directionality of the cells. The stochastic part, on the other hand, does not depend on the orientation of the directional cue and remains independent of the gradient magnitude. Numerical simulations of our probabilistic model yield quantitative agreement with the experimental distribution functions. Thus our model captures well the dynamics of chemotactic cells and can serve to quantify differences and similarities of different chemotactic eukaryotes. Finally, on the basis of our model, we can characterize the heterogeneity within a population of chemotactic cells
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