12,769 research outputs found
Surrogate time series
Before we apply nonlinear techniques, for example those inspired by chaos
theory, to dynamical phenomena occurring in nature, it is necessary to first
ask if the use of such advanced techniques is justified "by the data". While
many processes in nature seem very unlikely a priori to be linear, the possible
nonlinear nature might not be evident in specific aspects of their dynamics.
The method of surrogate data has become a very popular tool to address such a
question. However, while it was meant to provide a statistically rigorous,
foolproof framework, some limitations and caveats have shown up in its
practical use. In this paper, recent efforts to understand the caveats, avoid
the pitfalls, and to overcome some of the limitations, are reviewed and
augmented by new material. In particular, we will discuss specific as well as
more general approaches to constrained randomisation, providing a full range of
examples. New algorithms will be introduced for unevenly sampled and
multivariate data and for surrogate spike trains. The main limitation, which
lies in the interpretability of the test results, will be illustrated through
instructive case studies. We will also discuss some implementational aspects of
the realisation of these methods in the TISEAN
(http://www.mpipks-dresden.mpg.de/~tisean) software package.Comment: 28 pages, 23 figures, software at
http://www.mpipks-dresden.mpg.de/~tisea
Optimal Energy Estimation in Path-Integral Monte Carlo Simulations
We investigate the properties of two standard energy estimators used in
path-integral Monte Carlo simulations. By disentangling the variance of the
estimators and their autocorrelation times we analyse the dependence of the
performance on the update algorithm and present a detailed comparison of
refined update schemes such as multigrid and staging techniques. We show that a
proper combination of the two estimators leads to a further reduction of the
statistical error of the estimated energy with respect to the better of the two
without extra cost.Comment: 45 pp. LaTeX, 22 Postscript Figure
Reliability-based design optimization using kriging surrogates and subset simulation
The aim of the present paper is to develop a strategy for solving
reliability-based design optimization (RBDO) problems that remains applicable
when the performance models are expensive to evaluate. Starting with the
premise that simulation-based approaches are not affordable for such problems,
and that the most-probable-failure-point-based approaches do not permit to
quantify the error on the estimation of the failure probability, an approach
based on both metamodels and advanced simulation techniques is explored. The
kriging metamodeling technique is chosen in order to surrogate the performance
functions because it allows one to genuinely quantify the surrogate error. The
surrogate error onto the limit-state surfaces is propagated to the failure
probabilities estimates in order to provide an empirical error measure. This
error is then sequentially reduced by means of a population-based adaptive
refinement technique until the kriging surrogates are accurate enough for
reliability analysis. This original refinement strategy makes it possible to
add several observations in the design of experiments at the same time.
Reliability and reliability sensitivity analyses are performed by means of the
subset simulation technique for the sake of numerical efficiency. The adaptive
surrogate-based strategy for reliability estimation is finally involved into a
classical gradient-based optimization algorithm in order to solve the RBDO
problem. The kriging surrogates are built in a so-called augmented reliability
space thus making them reusable from one nested RBDO iteration to the other.
The strategy is compared to other approaches available in the literature on
three academic examples in the field of structural mechanics.Comment: 20 pages, 6 figures, 5 tables. Preprint submitted to Springer-Verla
Velocity gradients statistics along particle trajectories in turbulent flows: the refined similarity hypothesis in the Lagrangian frame
We present an investigation of the statistics of velocity gradient related
quantities, in particluar energy dissipation rate and enstrophy, along the
trajectories of fluid tracers and of heavy/light particles advected by a
homogeneous and isotropic turbulent flow. The Refined Similarity Hypothesis
(RSH) proposed by Kolmogorov and Oboukhov in 1962 is rephrased in the
Lagrangian context and then tested along the particle trajectories. The study
is performed on state-of-the-art numerical data resulting from numerical
simulations up to Re~400 with 2048^3 collocation points. When particles have
small inertia, we show that the Lagrangian formulation of the RSH is well
verified for time lags larger than the typical response time of the particle.
In contrast, in the large inertia limit when the particle response time
approaches the integral-time-scale of the flow, particles behave nearly
ballistic, and the Eulerian formulation of RSH holds in the inertial-range.Comment: 7 pages, 7 figures; Physical Review E (accepted Dec 7, 2009
Spectral Simplicity of Apparent Complexity, Part I: The Nondiagonalizable Metadynamics of Prediction
Virtually all questions that one can ask about the behavioral and structural
complexity of a stochastic process reduce to a linear algebraic framing of a
time evolution governed by an appropriate hidden-Markov process generator. Each
type of question---correlation, predictability, predictive cost, observer
synchronization, and the like---induces a distinct generator class. Answers are
then functions of the class-appropriate transition dynamic. Unfortunately,
these dynamics are generically nonnormal, nondiagonalizable, singular, and so
on. Tractably analyzing these dynamics relies on adapting the recently
introduced meromorphic functional calculus, which specifies the spectral
decomposition of functions of nondiagonalizable linear operators, even when the
function poles and zeros coincide with the operator's spectrum. Along the way,
we establish special properties of the projection operators that demonstrate
how they capture the organization of subprocesses within a complex system.
Circumventing the spurious infinities of alternative calculi, this leads in the
sequel, Part II, to the first closed-form expressions for complexity measures,
couched either in terms of the Drazin inverse (negative-one power of a singular
operator) or the eigenvalues and projection operators of the appropriate
transition dynamic.Comment: 24 pages, 3 figures, 4 tables; current version always at
http://csc.ucdavis.edu/~cmg/compmech/pubs/sdscpt1.ht
Intermolecular correlations are necessary to explain diffuse scattering from protein crystals
Conformational changes drive protein function, including catalysis,
allostery, and signaling. X-ray diffuse scattering from protein crystals has
frequently been cited as a probe of these correlated motions, with significant
potential to advance our understanding of biological dynamics. However, recent
work challenged this prevailing view, suggesting instead that diffuse
scattering primarily originates from rigid body motions and could therefore be
applied to improve structure determination. To investigate the nature of the
disorder giving rise to diffuse scattering, and thus the potential applications
of this signal, a diverse repertoire of disorder models was assessed for its
ability to reproduce the diffuse signal reconstructed from three protein
crystals. This comparison revealed that multiple models of intramolecular
conformational dynamics, including ensemble models inferred from the Bragg
data, could not explain the signal. Models of rigid body or short-range
liquid-like motions, in which dynamics are confined to the biological unit,
showed modest agreement with the diffuse maps, but were unable to reproduce
experimental features indicative of long-range correlations. Extending a model
of liquid-like motions to include disorder across neighboring proteins in the
crystal significantly improved agreement with all three systems and highlighted
the contribution of intermolecular correlations to the observed signal. These
findings anticipate a need to account for intermolecular disorder in order to
advance the interpretation of diffuse scattering to either extract biological
motions or aid structural inference.Comment: 12 pages, 5 figures (not including Supplementary Information
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