466 research outputs found
Levy Flights in Inhomogeneous Media
We investigate the impact of external periodic potentials on superdiffusive
random walks known as Levy flights and show that even strongly superdiffusive
transport is substantially affected by the external field. Unlike ordinary
random walks, Levy flights are surprisingly sensitive to the shape of the
potential while their asymptotic behavior ceases to depend on the Levy index
. Our analysis is based on a novel generalization of the Fokker-Planck
equation suitable for systems in thermal equilibrium. Thus, the results
presented are applicable to the large class of situations in which
superdiffusion is caused by topological complexity, such as diffusion on folded
polymers and scale-free networks.Comment: 4 pages, 4 figure
Sequential Desynchronization in Networks of Spiking Neurons with Partial Reset
The response of a neuron to synaptic input strongly depends on whether or not
it has just emitted a spike. We propose a neuron model that after spike
emission exhibits a partial response to residual input charges and study its
collective network dynamics analytically. We uncover a novel desynchronization
mechanism that causes a sequential desynchronization transition: In globally
coupled neurons an increase in the strength of the partial response induces a
sequence of bifurcations from states with large clusters of synchronously
firing neurons, through states with smaller clusters to completely asynchronous
spiking. We briefly discuss key consequences of this mechanism for more general
networks of biophysical neurons
Metal-insulator transitions in cyclotron resonance of periodic nanostructures due to avoided band crossings
A recently found metal-insulator transition in a model for cyclotron
resonance in a two-dimensional periodic potential is investigated by means of
spectral properties of the time evolution operator. The previously found
dynamical signatures of the transition are explained in terms of avoided band
crossings due to the change of the external electric field. The occurrence of a
cross-like transport is predicted and numerically confirmed
Evolutionary optimization of an experimental apparatus
In recent decades, cold atom experiments have become increasingly complex.
While computers control most parameters, optimization is mostly done manually.
This is a time-consuming task for a high-dimensional parameter space with
unknown correlations. Here we automate this process using a genetic algorithm
based on Differential Evolution. We demonstrate that this algorithm optimizes
21 correlated parameters and that it is robust against local maxima and
experimental noise. The algorithm is flexible and easy to implement. Thus, the
presented scheme can be applied to a wide range of experimental optimization
tasks.Comment: minor revisio
Scaling detection in time series: diffusion entropy analysis
The methods currently used to determine the scaling exponent of a complex
dynamic process described by a time series are based on the numerical
evaluation of variance. This means that all of them can be safely applied only
to the case where ordinary statistical properties hold true even if strange
kinetics are involved. We illustrate a method of statistical analysis based on
the Shannon entropy of the diffusion process generated by the time series,
called Diffusion Entropy Analysis (DEA). We adopt artificial Gauss and L\'{e}vy
time series, as prototypes of ordinary and anomalus statistics, respectively,
and we analyse them with the DEA and four ordinary methods of analysis, some of
which are very popular. We show that the DEA determines the correct scaling
exponent even when the statistical properties, as well as the dynamic
properties, are anomalous. The other four methods produce correct results in
the Gauss case but fail to detect the correct scaling in the case of L\'{e}vy
statistics.Comment: 21 pages,10 figures, 1 tabl
What determines the spreading of a wave packet?
The multifractal dimensions D2^mu and D2^psi of the energy spectrum and
eigenfunctions, resp., are shown to determine the asymptotic scaling of the
width of a spreading wave packet. For systems where the shape of the wave
packet is preserved the k-th moment increases as t^(k*beta) with
beta=D2^mu/D2^psi, while in general t^(k*beta) is an optimal lower bound.
Furthermore, we show that in d dimensions asymptotically in time the center of
any wave packet decreases spatially as a power law with exponent D_2^psi - d
and present numerical support for these results.Comment: Physical Review Letters to appear, 4 pages postscript with figure
Speed of synchronization in complex networks of neural oscillators Analytic results based on Random Matrix Theory
We analyze the dynamics of networks of spiking neural oscillators. First, we
present an exact linear stability theory of the synchronous state for networks
of arbitrary connectivity. For general neuron rise functions, stability is
determined by multiple operators, for which standard analysis is not suitable.
We describe a general non-standard solution to the multi-operator problem.
Subsequently, we derive a class of rise functions for which all stability
operators become degenerate and standard eigenvalue analysis becomes a suitable
tool. Interestingly, this class is found to consist of networks of leaky
integrate and fire neurons. For random networks of inhibitory
integrate-and-fire neurons, we then develop an analytical approach, based on
the theory of random matrices, to precisely determine the eigenvalue
distribution. This yields the asymptotic relaxation time for perturbations to
the synchronous state which provides the characteristic time scale on which
neurons can coordinate their activity in such networks. For networks with
finite in-degree, i.e. finite number of presynaptic inputs per neuron, we find
a speed limit to coordinating spiking activity: Even with arbitrarily strong
interaction strengths neurons cannot synchronize faster than at a certain
maximal speed determined by the typical in-degree.Comment: 17 pages, 12 figures, submitted to Chao
Fractal Conductance Fluctuations in a Soft Wall Stadium and a Sinai Billiard
Conductance fluctuations have been studied in a soft wall stadium and a Sinai
billiard defined by electrostatic gates on a high mobility semiconductor
heterojunction. These reproducible magnetoconductance fluctuations are found to
be fractal confirming recent theoretical predictions of quantum signatures in
classically mixed (regular and chaotic) systems. The fractal character of the
fluctuations provides direct evidence for a hierarchical phase space structure
at the boundary between regular and chaotic motion.Comment: 4 pages, 4 figures, data on Sinai geometry added to Fig.1, minor
change
Experimental evidence for the role of cantori as barriers in a quantum system
We investigate the effect of cantori on momentum diffusion in a quantum
system. Ultracold caesium atoms are subjected to a specifically designed
periodically pulsed standing wave. A cantorus separates two chaotic regions of
the classical phase space. Diffusion through the cantorus is classically
predicted. Quantum diffusion is only significant when the classical phase-space
area escaping through the cantorus per period greatly exceeds Planck's
constant. Experimental data and a quantum analysis confirm that the cantori act
as barriers.Comment: 19 pages including 9 figures, Accepted for publication in Physical
Review E in March 199
Statistics of resonances and of delay times in quasiperiodic Schr"odinger equations
We study the statistical distributions of the resonance widths , and of delay times in one dimensional
quasi-periodic tight-binding systems with one open channel. Both quantities are
found to decay algebraically as , and on
small and large scales respectively. The exponents , and are
related to the fractal dimension of the spectrum of the closed system
as and . Our results are verified for the
Harper model at the metal-insulator transition and for Fibonacci lattices.Comment: 4 pages, 3 figures, submitted to Phys. Rev. Let
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