6,966 research outputs found
The 3D structure of the Lagrangian acceleration in turbulent flows
We report experimental results on the three dimensional Lagrangian
acceleration in highly turbulent flows. Tracer particles are tracked optically
using four silicon strip detectors from high energy physics that provide high
temporal and spatial resolution. The components of the acceleration are shown
to be statistically dependent. The probability density function (PDF) of the
acceleration magnitude is comparable to a log-normal distribution. Assuming
isotropy, a log-normal distribution of the magnitude can account for the
observed dependency of the components. The time dynamics of the acceleration
components is found to be typical of the dissipation scales whereas the
magnitude evolves over longer times, possibly close to the integral time scale.Comment: accepted for publication in Physical Review Letter
Coarsening Dynamics of a One-Dimensional Driven Cahn-Hilliard System
We study the one-dimensional Cahn-Hilliard equation with an additional
driving term representing, say, the effect of gravity. We find that the driving
field has an asymmetric effect on the solution for a single stationary
domain wall (or `kink'), the direction of the field determining whether the
analytic solutions found by Leung [J.Stat.Phys.{\bf 61}, 345 (1990)] are
unique. The dynamics of a kink-antikink pair (`bubble') is then studied. The
behaviour of a bubble is dependent on the relative sizes of a characteristic
length scale , where is the driving field, and the separation, ,
of the interfaces. For the velocities of the interfaces are
negligible, while in the opposite limit a travelling-wave solution is found
with a velocity . For this latter case () a set of
reduced equations, describing the evolution of the domain lengths, is obtained
for a system with a large number of interfaces, and implies a characteristic
length scale growing as . Numerical results for the domain-size
distribution and structure factor confirm this behavior, and show that the
system exhibits dynamical scaling from very early times.Comment: 20 pages, revtex, 10 figures, submitted to Phys. Rev.
Dynamics of Ordering of Heisenberg Spins with Torque --- Nonconserved Case. I
We study the dynamics of ordering of a nonconserved Heisenberg magnet. The
dynamics consists of two parts --- an irreversible dissipation into a heat bath
and a reversible precession induced by a torque due to the local molecular
field. For quenches to zero temperature, we provide convincing arguments, both
numerically (Langevin simulation) and analytically (approximate closure scheme
due to Mazenko), that the torque is irrelevant at late times. We subject the
Mazenko closure scheme to systematic numerical tests. Such an analysis, carried
out for the first time on a vector order parameter, shows that the closure
scheme performs respectably well. For quenches to , we show, to , that the torque is irrelevant at the Wilson-Fisher fixed
point.Comment: 13 pages, REVTEX, and 19 .eps figures, compressed, Submitted to Phys.
Rev.
Macrorealism from entropic Leggett-Garg inequalities
We formulate entropic Leggett-Garg inequalities, which place constraints on
the statistical outcomes of temporal correlations of observables. The
information theoretic inequalities are satisfied if macrorealism holds. We show
that the quantum statistics underlying correlations between time-separated spin
component of a quantum rotor mimics that of spin correlations in two spatially
separated spin- particles sharing a state of zero total spin. This brings
forth the violation of the entropic Leggett-Garg inequality by a rotating
quantum spin- system in similar manner as does the entropic Bell inequality
(Phys. Rev. Lett. 61, 662 (1988)) by a pair of spin- particles forming a
composite spin singlet state.Comment: 5 pages, RevTeX, 2 eps figures, Accepted for publication in Phys.
Rev.
Computational models for inferring biochemical networks
Biochemical networks are of great practical importance. The interaction of biological compounds in cells has been enforced to a proper understanding by the numerous bioinformatics projects, which contributed to a vast amount of biological information. The construction of biochemical systems (systems of chemical reactions), which include both topology and kinetic constants of the chemical reactions, is NP-hard and is a well-studied system biology problem. In this paper, we propose a hybrid architecture, which combines genetic programming and simulated annealing in order to generate and optimize both the topology (the network) and the reaction rates of a biochemical system. Simulations and analysis of an artificial model and three real models (two models and the noisy version of one of them) show promising results for the proposed method.The Romanian National Authority for Scientific Research, CNDI–UEFISCDI,
Project No. PN-II-PT-PCCA-2011-3.2-0917
The reinforcing influence of recommendations on global diversification
Recommender systems are promising ways to filter the overabundant information
in modern society. Their algorithms help individuals to explore decent items,
but it is unclear how they allocate popularity among items. In this paper, we
simulate successive recommendations and measure their influence on the
dispersion of item popularity by Gini coefficient. Our result indicates that
local diffusion and collaborative filtering reinforce the popularity of hot
items, widening the popularity dispersion. On the other hand, the heat
conduction algorithm increases the popularity of the niche items and generates
smaller dispersion of item popularity. Simulations are compared to mean-field
predictions. Our results suggest that recommender systems have reinforcing
influence on global diversification.Comment: 6 pages, 6 figure
Measurement of Lagrangian velocity in fully developed turbulence
We have developed a new experimental technique to measure the Lagrangian
velocity of tracer particles in a turbulent flow, based on ultrasonic Doppler
tracking. This method yields a direct access to the velocity of a single
particule at a turbulent Reynolds number . Its dynamics is
analyzed with two decades of time resolution, below the Lagrangian correlation
time. We observe that the Lagrangian velocity spectrum has a Lorentzian form
, in agreement
with a Kolmogorov-like scaling in the inertial range. The probability density
function (PDF) of the velocity time increments displays a change of shape from
quasi-Gaussian a integral time scale to stretched exponential tails at the
smallest time increments. This intermittency, when measured from relative
scaling exponents of structure functions, is more pronounced than in the
Eulerian framework.Comment: 4 pages, 5 figures. to appear in PR
The imprint of large-scale flows on turbulence
We investigate the locality of interactions in hydrodynamic turbulence using
data from a direct numerical simulation on a grid of 1024^3 points; the flow is
forced with the Taylor-Green vortex. An inertial range for the energy is
obtained in which the flux is constant and the spectrum follows an approximate
Kolmogorov law. Nonlinear triadic interactions are dominated by their non-local
components, involving widely separated scales. The resulting nonlinear transfer
itself is local at each scale but the step in the energy cascade is independent
of that scale and directly related to the integral scale of the flow.
Interactions with large scales represent 20% of the total energy flux. Possible
explanations for the deviation from self-similar models, the link between these
findings and intermittency, and their consequences for modeling of turbulent
flows are briefly discussed
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