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Sample records for complex langevin dynamics

  1. Controlling complex Langevin dynamics at finite density

    NASA Astrophysics Data System (ADS)

    Aarts, Gert; Bongiovanni, Lorenzo; Seiler, Erhard; Sexty, Dénes; Stamatescu, Ion-Olimpiu

    2013-07-01

    At nonzero chemical potential the numerical sign problem in lattice field theory limits the use of standard algorithms based on importance sampling. Complex Langevin dynamics provides a possible solution, but it has to be applied with care. In this review, we first summarise our current understanding of the approach, combining analytical and numerical insight. In the second part we study SL( C, ℂ) gauge cooling, which was introduced recently as a tool to control complex Langevin dynamics in nonabelian gauge theories. We present new results in Polyakov chain models and in QCD with heavy quarks and compare various adaptive cooling implementations.

  2. Adaptive gauge cooling for complex Langevin dynamics

    NASA Astrophysics Data System (ADS)

    Bongiovanni, L.; Aarts, G.; Seiler, E.; Sexty, D.; Stamatescu, I. O.

    In the case of nonabelian gauge theories with a complex weight, a controlled exploration of the complexified configuration space during a complex Langevin process requires the use of SL(N,C) gauge cooling, in order to minimize the distance from SU(N). Here we show that adaptive gauge cooling can lead to an efficient implementation of this idea. First results for SU(3) Yang-Mills theory in the presence of a nonzero theta-term are presented as well.

  3. Stability of complex Langevin dynamics in effective models

    NASA Astrophysics Data System (ADS)

    Aarts, Gert; James, Frank A.; Pawlowski, Jan M.; Seiler, Erhard; Sexty, Dénes; Stamatescu, Ion-Olimpiu

    2013-03-01

    The sign problem at nonzero chemical potential prohibits the use of importance sampling in lattice simulations. Since complex Langevin dynamics does not rely on importance sampling, it provides a potential solution. Recently it was shown that complex Langevin dynamics fails in the disordered phase in the case of the three-dimensional XY model, while it appears to work in the entire phase diagram in the case of the three-dimensional SU(3) spin model. Here we analyse this difference and argue that it is due to the presence of the nontrivial Haar measure in the SU(3) case, which has a stabilizing effect on the complexified dynamics. The freedom to modify and stabilize the complex Langevin process is discussed in some detail.

  4. Some remarks on Lefschetz thimbles and complex Langevin dynamics

    NASA Astrophysics Data System (ADS)

    Aarts, Gert; Bongiovanni, Lorenzo; Seiler, Erhard; Sexty, Dénes

    2014-10-01

    Lefschetz thimbles and complex Langevin dynamics both provide a means to tackle the numerical sign problem prevalent in theories with a complex weight in the partition function, e.g. due to nonzero chemical potential. Here we collect some findings for the quartic model, and for U(1) and SU(2) models in the presence of a determinant, which have some features not discussed before, due to a singular drift. We find evidence for a relation between classical runaways and stable thimbles, and give an example of a degenerate fixed point. We typically find that the distributions sampled in complex Langevin dynamics are related to the thimble(s), but with some important caveats, for instance due to the presence of unstable fixed points in the Langevin dynamics.

  5. Localised distributions and criteria for correctness in complex Langevin dynamics

    SciTech Connect

    Aarts, Gert; Giudice, Pietro; Seiler, Erhard

    2013-10-15

    Complex Langevin dynamics can solve the sign problem appearing in numerical simulations of theories with a complex action. In order to justify the procedure, it is important to understand the properties of the real and positive distribution, which is effectively sampled during the stochastic process. In the context of a simple model, we study this distribution by solving the Fokker–Planck equation as well as by brute force and relate the results to the recently derived criteria for correctness. We demonstrate analytically that it is possible that the distribution has support in a strip in the complexified configuration space only, in which case correct results are expected. -- Highlights: •Characterisation of the equilibrium distribution sampled in complex Langevin dynamics. •Connection between criteria for correctness and breakdown. •Solution of the Fokker–Planck equation in the case of real noise. •Analytical determination of support in complexified space.

  6. Localised distributions and criteria for correctness in complex Langevin dynamics

    NASA Astrophysics Data System (ADS)

    Aarts, Gert; Giudice, Pietro; Seiler, Erhard

    2013-10-01

    Complex Langevin dynamics can solve the sign problem appearing in numerical simulations of theories with a complex action. In order to justify the procedure, it is important to understand the properties of the real and positive distribution, which is effectively sampled during the stochastic process. In the context of a simple model, we study this distribution by solving the Fokker-Planck equation as well as by brute force and relate the results to the recently derived criteria for correctness. We demonstrate analytically that it is possible that the distribution has support in a strip in the complexified configuration space only, in which case correct results are expected.

  7. Entropy and enthalpy of polyelectrolyte complexation: Langevin dynamics simulations.

    PubMed

    Ou, Zhaoyang; Muthukumar, M

    2006-04-21

    We report a systematic study by Langevin dynamics simulation on the energetics of complexation between two oppositely charged polyelectrolytes of same charge density in dilute solutions of a good solvent with counterions and salt ions explicitly included. The enthalpy of polyelectrolyte complexation is quantified by comparisons of the Coulomb energy before and after complexation. The entropy of polyelectrolyte complexation is determined directly from simulations and compared with that from a mean-field lattice model explicitly accounting for counterion adsorption. At weak Coulomb interaction strengths, e.g., in solvents of high dielectric constant or with weakly charged polyelectrolytes, complexation is driven by a negative enthalpy due to electrostatic attraction between two oppositely charged chains, with counterion release entropy playing only a subsidiary role. In the strong interaction regime, complexation is driven by a large counterion release entropy and opposed by a positive enthalpy change. The addition of salt reduces the enthalpy of polyelectrolyte complexation by screening electrostatic interaction at all Coulomb interaction strengths. The counterion release entropy also decreases in the presence of salt, but the reduction only becomes significant at higher Coulomb interaction strengths. More significantly, in the range of Coulomb interaction strengths appropriate for highly charged polymers in aqueous solutions, complexation enthalpy depends weakly on salt concentration and counterion release entropy exhibits a large variation as a function of salt concentration. Our study quantitatively establishes that polyelectrolyte complexation in highly charged Coulomb systems is of entropic origin.

  8. Improvement in complex Langevin dynamics from a view point of Lefschetz thimbles

    NASA Astrophysics Data System (ADS)

    Tsutsui, Shoichiro; Doi, Takahiro M.

    2016-10-01

    We develop a way of improving complex Langevin dynamics motivated by the Lefschetz-thimble decomposition of integrals. In our method, arbitrary observables of an original model with multiple Lefschetz thimbles are computed by a modified model with a single thimble. We apply our modification method to a one-dimensional integral in which the naive implementation of the complex Langevin dynamics fails to reproduce the exact results due to the severe sign problem. We show that the toy model can be modified so that the new model consists of a single Lefschetz thimble. We find that correct results can be obtained by the improved complex Langevin dynamics.

  9. The complex chemical Langevin equation.

    PubMed

    Schnoerr, David; Sanguinetti, Guido; Grima, Ramon

    2014-07-14

    The chemical Langevin equation (CLE) is a popular simulation method to probe the stochastic dynamics of chemical systems. The CLE's main disadvantage is its break down in finite time due to the problem of evaluating square roots of negative quantities whenever the molecule numbers become sufficiently small. We show that this issue is not a numerical integration problem, rather in many systems it is intrinsic to all representations of the CLE. Various methods of correcting the CLE have been proposed which avoid its break down. We show that these methods introduce undesirable artefacts in the CLE's predictions. In particular, for unimolecular systems, these correction methods lead to CLE predictions for the mean concentrations and variance of fluctuations which disagree with those of the chemical master equation. We show that, by extending the domain of the CLE to complex space, break down is eliminated, and the CLE's accuracy for unimolecular systems is restored. Although the molecule numbers are generally complex, we show that the "complex CLE" predicts real-valued quantities for the mean concentrations, the moments of intrinsic noise, power spectra, and first passage times, hence admitting a physical interpretation. It is also shown to provide a more accurate approximation of the chemical master equation of simple biochemical circuits involving bimolecular reactions than the various corrected forms of the real-valued CLE, the linear-noise approximation and a commonly used two moment-closure approximation.

  10. The complex chemical Langevin equation

    SciTech Connect

    Schnoerr, David; Sanguinetti, Guido; Grima, Ramon

    2014-07-14

    The chemical Langevin equation (CLE) is a popular simulation method to probe the stochastic dynamics of chemical systems. The CLE’s main disadvantage is its break down in finite time due to the problem of evaluating square roots of negative quantities whenever the molecule numbers become sufficiently small. We show that this issue is not a numerical integration problem, rather in many systems it is intrinsic to all representations of the CLE. Various methods of correcting the CLE have been proposed which avoid its break down. We show that these methods introduce undesirable artefacts in the CLE’s predictions. In particular, for unimolecular systems, these correction methods lead to CLE predictions for the mean concentrations and variance of fluctuations which disagree with those of the chemical master equation. We show that, by extending the domain of the CLE to complex space, break down is eliminated, and the CLE’s accuracy for unimolecular systems is restored. Although the molecule numbers are generally complex, we show that the “complex CLE” predicts real-valued quantities for the mean concentrations, the moments of intrinsic noise, power spectra, and first passage times, hence admitting a physical interpretation. It is also shown to provide a more accurate approximation of the chemical master equation of simple biochemical circuits involving bimolecular reactions than the various corrected forms of the real-valued CLE, the linear-noise approximation and a commonly used two moment-closure approximation.

  11. The complex chemical Langevin equation

    NASA Astrophysics Data System (ADS)

    Schnoerr, David; Sanguinetti, Guido; Grima, Ramon

    2014-07-01

    The chemical Langevin equation (CLE) is a popular simulation method to probe the stochastic dynamics of chemical systems. The CLE's main disadvantage is its break down in finite time due to the problem of evaluating square roots of negative quantities whenever the molecule numbers become sufficiently small. We show that this issue is not a numerical integration problem, rather in many systems it is intrinsic to all representations of the CLE. Various methods of correcting the CLE have been proposed which avoid its break down. We show that these methods introduce undesirable artefacts in the CLE's predictions. In particular, for unimolecular systems, these correction methods lead to CLE predictions for the mean concentrations and variance of fluctuations which disagree with those of the chemical master equation. We show that, by extending the domain of the CLE to complex space, break down is eliminated, and the CLE's accuracy for unimolecular systems is restored. Although the molecule numbers are generally complex, we show that the "complex CLE" predicts real-valued quantities for the mean concentrations, the moments of intrinsic noise, power spectra, and first passage times, hence admitting a physical interpretation. It is also shown to provide a more accurate approximation of the chemical master equation of simple biochemical circuits involving bimolecular reactions than the various corrected forms of the real-valued CLE, the linear-noise approximation and a commonly used two moment-closure approximation.

  12. Multidimensional Langevin Modeling of Nonoverdamped Dynamics

    NASA Astrophysics Data System (ADS)

    Schaudinnus, Norbert; Bastian, Björn; Hegger, Rainer; Stock, Gerhard

    2015-07-01

    Based on a given time series, data-driven Langevin modeling aims to construct a low-dimensional dynamical model of the underlying system. When dealing with physical data as provided by, e.g., all-atom molecular dynamics simulations, effects due to small damping may be important to correctly describe the statistics (e.g., the energy landscape) and the dynamics (e.g., transition times). To include these effects in a dynamical model, an algorithm that propagates a second-order Langevin scheme is derived, which facilitates the treatment of multidimensional data. Adopting extensive molecular dynamics simulations of a peptide helix, a five-dimensional model is constructed that successfully forecasts the complex structural dynamics of the system. Neglect of small damping effects, on the other hand, is shown to lead to significant errors and inconsistencies.

  13. Langevin Equation for DNA Dynamics

    NASA Astrophysics Data System (ADS)

    Grych, David; Copperman, Jeremy; Guenza, Marina

    Under physiological conditions, DNA oligomers can contain well-ordered helical regions and also flexible single-stranded regions. We describe the site-specific motion of DNA with a modified Rouse-Zimm Langevin equation formalism that describes DNA as a coarse-grained polymeric chain with global structure and local flexibility. The approach has successfully described the protein dynamics in solution and has been extended to nucleic acids. Our approach provides diffusive mode analytical solutions for the dynamics of global rotational diffusion and internal motion. The internal DNA dynamics present a rich energy landscape that accounts for an interior where hydrogen bonds and base-stacking determine structure and experience limited solvent exposure. We have implemented several models incorporating different coarse-grained sites with anisotropic rotation, energy barrier crossing, and local friction coefficients that include a unique internal viscosity and our models reproduce dynamics predicted by atomistic simulations. The models reproduce bond autocorrelation along the sequence as compared to that directly calculated from atomistic molecular dynamics simulations. The Langevin equation approach captures the essence of DNA dynamics without a cumbersome atomistic representation.

  14. Intermediate dynamics between Newton and Langevin.

    PubMed

    Bao, Jing-Dong; Zhuo, Yi-Zhong; Oliveira, Fernando A; Hänggi, Peter

    2006-12-01

    A dynamics between Newton and Langevin formalisms is elucidated within the framework of the generalized Langevin equation. For thermal noise yielding a vanishing zero-frequency friction the corresponding non-Markovian Brownian dynamics exhibits anomalous behavior which is characterized by ballistic diffusion and accelerated transport. We also investigate the role of a possible initial correlation between the system degrees of freedom and the heat-bath degrees of freedom for the asymptotic long-time behavior of the system dynamics. As two test beds we investigate (i) the anomalous energy relaxation of free non-Markovian Brownian motion that is driven by a harmonic velocity noise and (ii) the phenomenon of a net directed acceleration in noise-induced transport of an inertial rocking Brownian motor.

  15. Error Analysis of Modified Langevin Dynamics

    NASA Astrophysics Data System (ADS)

    Redon, Stephane; Stoltz, Gabriel; Trstanova, Zofia

    2016-08-01

    We consider Langevin dynamics associated with a modified kinetic energy vanishing for small momenta. This allows us to freeze slow particles, and hence avoid the re-computation of inter-particle forces, which leads to computational gains. On the other hand, the statistical error may increase since there are a priori more correlations in time. The aim of this work is first to prove the ergodicity of the modified Langevin dynamics (which fails to be hypoelliptic), and next to analyze how the asymptotic variance on ergodic averages depends on the parameters of the modified kinetic energy. Numerical results illustrate the approach, both for low-dimensional systems where we resort to a Galerkin approximation of the generator, and for more realistic systems using Monte Carlo simulations.

  16. New Langevin and gradient thermostats for rigid body dynamics

    NASA Astrophysics Data System (ADS)

    Davidchack, R. L.; Ouldridge, T. E.; Tretyakov, M. V.

    2015-04-01

    We introduce two new thermostats, one of Langevin type and one of gradient (Brownian) type, for rigid body dynamics. We formulate rotation using the quaternion representation of angular coordinates; both thermostats preserve the unit length of quaternions. The Langevin thermostat also ensures that the conjugate angular momenta stay within the tangent space of the quaternion coordinates, as required by the Hamiltonian dynamics of rigid bodies. We have constructed three geometric numerical integrators for the Langevin thermostat and one for the gradient thermostat. The numerical integrators reflect key properties of the thermostats themselves. Namely, they all preserve the unit length of quaternions, automatically, without the need of a projection onto the unit sphere. The Langevin integrators also ensure that the angular momenta remain within the tangent space of the quaternion coordinates. The Langevin integrators are quasi-symplectic and of weak order two. The numerical method for the gradient thermostat is of weak order one. Its construction exploits ideas of Lie-group type integrators for differential equations on manifolds. We numerically compare the discretization errors of the Langevin integrators, as well as the efficiency of the gradient integrator compared to the Langevin ones when used in the simulation of rigid TIP4P water model with smoothly truncated electrostatic interactions. We observe that the gradient integrator is computationally less efficient than the Langevin integrators. We also compare the relative accuracy of the Langevin integrators in evaluating various static quantities and give recommendations as to the choice of an appropriate integrator.

  17. New Langevin and gradient thermostats for rigid body dynamics.

    PubMed

    Davidchack, R L; Ouldridge, T E; Tretyakov, M V

    2015-04-14

    We introduce two new thermostats, one of Langevin type and one of gradient (Brownian) type, for rigid body dynamics. We formulate rotation using the quaternion representation of angular coordinates; both thermostats preserve the unit length of quaternions. The Langevin thermostat also ensures that the conjugate angular momenta stay within the tangent space of the quaternion coordinates, as required by the Hamiltonian dynamics of rigid bodies. We have constructed three geometric numerical integrators for the Langevin thermostat and one for the gradient thermostat. The numerical integrators reflect key properties of the thermostats themselves. Namely, they all preserve the unit length of quaternions, automatically, without the need of a projection onto the unit sphere. The Langevin integrators also ensure that the angular momenta remain within the tangent space of the quaternion coordinates. The Langevin integrators are quasi-symplectic and of weak order two. The numerical method for the gradient thermostat is of weak order one. Its construction exploits ideas of Lie-group type integrators for differential equations on manifolds. We numerically compare the discretization errors of the Langevin integrators, as well as the efficiency of the gradient integrator compared to the Langevin ones when used in the simulation of rigid TIP4P water model with smoothly truncated electrostatic interactions. We observe that the gradient integrator is computationally less efficient than the Langevin integrators. We also compare the relative accuracy of the Langevin integrators in evaluating various static quantities and give recommendations as to the choice of an appropriate integrator. PMID:25877569

  18. New Langevin and gradient thermostats for rigid body dynamics.

    PubMed

    Davidchack, R L; Ouldridge, T E; Tretyakov, M V

    2015-04-14

    We introduce two new thermostats, one of Langevin type and one of gradient (Brownian) type, for rigid body dynamics. We formulate rotation using the quaternion representation of angular coordinates; both thermostats preserve the unit length of quaternions. The Langevin thermostat also ensures that the conjugate angular momenta stay within the tangent space of the quaternion coordinates, as required by the Hamiltonian dynamics of rigid bodies. We have constructed three geometric numerical integrators for the Langevin thermostat and one for the gradient thermostat. The numerical integrators reflect key properties of the thermostats themselves. Namely, they all preserve the unit length of quaternions, automatically, without the need of a projection onto the unit sphere. The Langevin integrators also ensure that the angular momenta remain within the tangent space of the quaternion coordinates. The Langevin integrators are quasi-symplectic and of weak order two. The numerical method for the gradient thermostat is of weak order one. Its construction exploits ideas of Lie-group type integrators for differential equations on manifolds. We numerically compare the discretization errors of the Langevin integrators, as well as the efficiency of the gradient integrator compared to the Langevin ones when used in the simulation of rigid TIP4P water model with smoothly truncated electrostatic interactions. We observe that the gradient integrator is computationally less efficient than the Langevin integrators. We also compare the relative accuracy of the Langevin integrators in evaluating various static quantities and give recommendations as to the choice of an appropriate integrator.

  19. Parametrizing linear generalized Langevin dynamics from explicit molecular dynamics simulations

    SciTech Connect

    Gottwald, Fabian; Karsten, Sven; Ivanov, Sergei D. Kühn, Oliver

    2015-06-28

    Fundamental understanding of complex dynamics in many-particle systems on the atomistic level is of utmost importance. Often the systems of interest are of macroscopic size but can be partitioned into a few important degrees of freedom which are treated most accurately and others which constitute a thermal bath. Particular attention in this respect attracts the linear generalized Langevin equation, which can be rigorously derived by means of a linear projection technique. Within this framework, a complicated interaction with the bath can be reduced to a single memory kernel. This memory kernel in turn is parametrized for a particular system studied, usually by means of time-domain methods based on explicit molecular dynamics data. Here, we discuss that this task is more naturally achieved in frequency domain and develop a Fourier-based parametrization method that outperforms its time-domain analogues. Very surprisingly, the widely used rigid bond method turns out to be inappropriate in general. Importantly, we show that the rigid bond approach leads to a systematic overestimation of relaxation times, unless the system under study consists of a harmonic bath bi-linearly coupled to the relevant degrees of freedom.

  20. Langevin Dynamics Deciphers the Motility Pattern of Swimming Parasites

    NASA Astrophysics Data System (ADS)

    Zaburdaev, Vasily; Uppaluri, Sravanti; Pfohl, Thomas; Engstler, Markus; Friedrich, Rudolf; Stark, Holger

    2011-05-01

    The parasite African trypanosome swims in the bloodstream of mammals and causes the highly dangerous human sleeping sickness. Cell motility is essential for the parasite’s survival within the mammalian host. We present an analysis of the random-walk pattern of a swimming trypanosome. From experimental time-autocorrelation functions for the direction of motion we identify two relaxation times that differ by an order of magnitude. They originate from the rapid deformations of the cell body and a slower rotational diffusion of the average swimming direction. Velocity fluctuations are athermal and increase for faster cells whose trajectories are also straighter. We demonstrate that such a complex dynamics is captured by two decoupled Langevin equations that decipher the complex trajectory pattern by referring it to the microscopic details of cell behavior.

  1. Complex Langevin method: When can it be trusted?

    SciTech Connect

    Aarts, Gert; Seiler, Erhard; Stamatescu, Ion-Olimpiu

    2010-03-01

    We analyze to what extent the complex Langevin method, which is in principle capable of solving the so-called sign problems, can be considered as reliable. We give a formal derivation of the correctness and then point out various mathematical loopholes. The detailed study of some simple examples leads to practical suggestions about the application of the method.

  2. Protein displacements under external forces: An atomistic Langevin dynamics approach

    NASA Astrophysics Data System (ADS)

    Gnandt, David; Utz, Nadine; Blumen, Alexander; Koslowski, Thorsten

    2009-02-01

    We present a fully atomistic Langevin dynamics approach as a method to simulate biopolymers under external forces. In the harmonic regime, this approach permits the computation of the long-term dynamics using only the eigenvalues and eigenvectors of the Hessian matrix of second derivatives. We apply this scheme to identify polymorphs of model proteins by their mechanical response fingerprint, and we relate the averaged dynamics of proteins to their biological functionality, with the ion channel gramicidin A, a phosphorylase, and neuropeptide Y as examples. In an environment akin to dilute solutions, even small proteins show relaxation times up to 50 ns. Atomically resolved Langevin dynamics computations have been performed for the stretched gramicidin A ion channel.

  3. Temporal breakdown and Borel resummation in the complex Langevin method

    SciTech Connect

    Duncan, A. Niedermaier, M.

    2013-02-15

    We reexamine the Parisi-Klauder conjecture for complex e{sup i{theta}/2}{phi}{sup 4} measures with a Wick rotation angle 0{<=}{theta}/2{<=}{pi}/2 interpolating between Euclidean signature and Lorentzian signature. Our main result is that the asymptotics for short stochastic times t encapsulates information also about the equilibrium aspects. The moments evaluated with the complex measure and with the real measure defined by the stochastic Langevin equation have the same t{yields}0 asymptotic expansion which is shown to be Borel summable. The Borel transform correctly reproduces the time dependent moments of the complex measure for all t, including their t{yields}{infinity} equilibrium values. On the other hand the results of a direct numerical simulation of the Langevin moments are found to disagree from the 'correct' result for t larger than a finite t{sub c}. The breakdown time t{sub c} increases powerlike for decreasing strength of the noise's imaginary part but cannot be excluded to be finite for purely real noise. To ascertain the discrepancy we also compute the real equilibrium distribution for complex noise explicitly and verify that its moments differ from those obtained with the complex measure. - Highlights: Black-Right-Pointing-Pointer The Parisi-Klauder conjecture is reexamined for complex e{sup i{theta}/2}{phi}{sup 4} measures. Black-Right-Pointing-Pointer The time dependent moments are evaluated by temporal Borel resummation. Black-Right-Pointing-Pointer The results disagree with the Langevin simulations beyond a critical time t{sub c}. Black-Right-Pointing-Pointer t{sub c} increases with decreasing strength of the noise's imaginary part. Black-Right-Pointing-Pointer The technical reason for the breakdown is identified.

  4. Langevin dynamics of polymeric manifolds in melts

    NASA Astrophysics Data System (ADS)

    Rostiashvili, V. G.; Rehkopf, M.; Vilgis, T. A.

    1999-03-01

    The Martin-Siggia-Rose generating functional (MSR-GF) technique is used for treating the polymeric D-dimensional-manifold melt dynamics. The one- (test-) manifold dynamics and the collective dynamics are considered separately. The test-manifold dynamics is obtained by integrating out the melt collective variables. This is done within the dynamic random-phase approximation (RPA). The resulting effective-action functional of the test manifold is treated by making use of the self-consistent Hartree approximation. As a consequence, the generalized Rouse equation of the test manifold is derived, and its static and dynamic properties are studied. By making use the MSR-GF technique, the fluctuations around the RPA of the collective variables - mass density and response-field density - are investigated. As a result, the equations for the correlation and response functions are derived. The memory kernel can be specified for the ideal glass transition as a sum of all `water-melon' diagrams.

  5. Langevin Dynamics with Space-Time Periodic Nonequilibrium Forcing

    NASA Astrophysics Data System (ADS)

    Joubaud, R.; Pavliotis, G. A.; Stoltz, G.

    2015-01-01

    We present results on the ballistic and diffusive behavior of the Langevin dynamics in a periodic potential that is driven away from equilibrium by a space-time periodic driving force, extending some of the results obtained by Collet and Martinez in (J Math Biol, 56(6):765-792 2008). In the hyperbolic scaling, a nontrivial average velocity can be observed even if the external forcing vanishes in average. More surprisingly, an average velocity in the direction opposite to the forcing may develop at the linear response level—a phenomenon called negative mobility. The diffusive limit of the non-equilibrium Langevin dynamics is also studied using the general methodology of central limit theorems for additive functionals of Markov processes. To apply this methodology, which is based on the study of appropriate Poisson equations, we extend recent results on pointwise estimates of the resolvent of the generator associated with the Langevin dynamics. Our theoretical results are illustrated by numerical simulations of a two-dimensional system.

  6. Complex saddle points and the sign problem in complex Langevin simulation

    NASA Astrophysics Data System (ADS)

    Hayata, Tomoya; Hidaka, Yoshimasa; Tanizaki, Yuya

    2016-10-01

    We show that complex Langevin simulation converges to a wrong result within the semiclassical analysis, by relating it to the Lefschetz-thimble path integral, when the path-integral weight has different phases among dominant complex saddle points. Equilibrium solution of the complex Langevin equation forms local distributions around complex saddle points. Its ensemble average approximately becomes a direct sum of the average in each local distribution, where relative phases among them are dropped. We propose that by taking these phases into account through reweighting, we can solve the wrong convergence problem. However, this prescription may lead to a recurrence of the sign problem in the complex Langevin method for quantum many-body systems.

  7. Complex Langevin: etiology and diagnostics of its main problem

    NASA Astrophysics Data System (ADS)

    Aarts, Gert; James, Frank A.; Seiler, Erhard; Stamatescu, Ion-Olimpiu

    2011-10-01

    The complex Langevin method is a leading candidate for solving the so-called sign problem occurring in various physical situations. Its most vexing problem is that sometimes it produces `convergence to the wrong limit'. In this paper we carefully revisit the formal justification of the method, identifying points at which it may fail and derive a necessary and sufficient criterion for correctness. This criterion is, however, not practical, since its application requires checking an infinite tower of identities. We propose instead a practical test involving only a check of the first few of those identities; this raises the question of the `sensitivity' of the test. This sensitivity as well as the general insights into the possible reasons of failure (the etiology) are then tested in two toy models where the correct answer is known. At least in those models the test works perfectly.

  8. Bifurcation dynamics of the tempered fractional Langevin equation.

    PubMed

    Zeng, Caibin; Yang, Qigui; Chen, YangQuan

    2016-08-01

    Tempered fractional processes offer a useful extension for turbulence to include low frequencies. In this paper, we investigate the stochastic phenomenological bifurcation, or stochastic P-bifurcation, of the Langevin equation perturbed by tempered fractional Brownian motion. However, most standard tools from the well-studied framework of random dynamical systems cannot be applied to systems driven by non-Markovian noise, so it is desirable to construct possible approaches in a non-Markovian framework. We first derive the spectral density function of the considered system based on the generalized Parseval's formula and the Wiener-Khinchin theorem. Then we show that it enjoys interesting and diverse bifurcation phenomena exchanging between or among explosive-like, unimodal, and bimodal kurtosis. Therefore, our procedures in this paper are not merely comparable in scope to the existing theory of Markovian systems but also provide a possible approach to discern P-bifurcation dynamics in the non-Markovian settings. PMID:27586627

  9. Bifurcation dynamics of the tempered fractional Langevin equation

    NASA Astrophysics Data System (ADS)

    Zeng, Caibin; Yang, Qigui; Chen, YangQuan

    2016-08-01

    Tempered fractional processes offer a useful extension for turbulence to include low frequencies. In this paper, we investigate the stochastic phenomenological bifurcation, or stochastic P-bifurcation, of the Langevin equation perturbed by tempered fractional Brownian motion. However, most standard tools from the well-studied framework of random dynamical systems cannot be applied to systems driven by non-Markovian noise, so it is desirable to construct possible approaches in a non-Markovian framework. We first derive the spectral density function of the considered system based on the generalized Parseval's formula and the Wiener-Khinchin theorem. Then we show that it enjoys interesting and diverse bifurcation phenomena exchanging between or among explosive-like, unimodal, and bimodal kurtosis. Therefore, our procedures in this paper are not merely comparable in scope to the existing theory of Markovian systems but also provide a possible approach to discern P-bifurcation dynamics in the non-Markovian settings.

  10. Recovering hidden dynamical modes from the generalized Langevin equation.

    PubMed

    Kawai, Shinnosuke; Miyazaki, Yusuke

    2016-09-01

    In studying large molecular systems, insights can better be extracted by selecting a limited number of physical quantities for analysis rather than treating every atomic coordinate in detail. Some information may, however, be lost by projecting the total system onto a small number of coordinates. For such problems, the generalized Langevin equation (GLE) is shown to provide a useful framework to examine the interaction between the observed variables and their environment. Starting with the GLE obtained from the time series of the observed quantity, we perform a transformation to introduce a set of variables that describe dynamical modes existing in the environment. The introduced variables are shown to effectively recover the essential information of the total system that appeared to be lost by the projection. PMID:27608984

  11. Recovering hidden dynamical modes from the generalized Langevin equation

    NASA Astrophysics Data System (ADS)

    Kawai, Shinnosuke; Miyazaki, Yusuke

    2016-09-01

    In studying large molecular systems, insights can better be extracted by selecting a limited number of physical quantities for analysis rather than treating every atomic coordinate in detail. Some information may, however, be lost by projecting the total system onto a small number of coordinates. For such problems, the generalized Langevin equation (GLE) is shown to provide a useful framework to examine the interaction between the observed variables and their environment. Starting with the GLE obtained from the time series of the observed quantity, we perform a transformation to introduce a set of variables that describe dynamical modes existing in the environment. The introduced variables are shown to effectively recover the essential information of the total system that appeared to be lost by the projection.

  12. Sampling the isothermal-isobaric ensemble by Langevin dynamics.

    PubMed

    Gao, Xingyu; Fang, Jun; Wang, Han

    2016-03-28

    We present a new method of conducting fully flexible-cell molecular dynamics simulation in isothermal-isobaric ensemble based on Langevin equations of motion. The stochastic coupling to all particle and cell degrees of freedoms is introduced in a correct way, in the sense that the stationary configurational distribution is proved to be consistent with that of the isothermal-isobaric ensemble. In order to apply the proposed method in computer simulations, a second order symmetric numerical integration scheme is developed by Trotter's splitting of the single-step propagator. Moreover, a practical guide of choosing working parameters is suggested for user specified thermo- and baro-coupling time scales. The method and software implementation are carefully validated by a numerical example. PMID:27036433

  13. A Langevin model for low density pedestrian dynamics

    NASA Astrophysics Data System (ADS)

    Corbetta, Alessandro; Lee, Chung-Min; Benzi, Roberto; Muntean, Adrian; Toschi, Federico

    The dynamics of pedestrian crowds shares deep connections with statistical physics and fluid dynamics. Reaching a quantitative understanding, not only of the average behaviours but also of the statistics of (rare) fluctuations would have major impact, for instance, on the design and safety of civil infrastructures. A key feature of pedestrian dynamics is its strong intrinsic variability, that we can already observe at the single individual level. In this work we aim at a quantitative characterisation of this statistical variability by studying individual fluctuations. We consider experimental observations of low-density pedestrian flows in a corridor within a building at Eindhoven University of Technology. Few hundreds of thousands of pedestrian trajectories with high space and time resolutions have been collected via a Microsoft Kinect 3D-range sensor and automatic head tracking techniques. From these observations we model pedestrians as active Brownian particles by means of a generalised Langevin equation. With this model we can quantitatively reproduce the observed dynamics including the statistics of ordinary pedestrian fluctuations and of rarer U-turn events. Low density, pair-wise interactions between pedestrians are also discussed.

  14. Calibrated Langevin-dynamics simulations of intrinsically disordered proteins

    NASA Astrophysics Data System (ADS)

    Smith, W. Wendell; Ho, Po-Yi; O'Hern, Corey S.

    2014-10-01

    We perform extensive coarse-grained (CG) Langevin dynamics simulations of intrinsically disordered proteins (IDPs), which possess fluctuating conformational statistics between that for excluded volume random walks and collapsed globules. Our CG model includes repulsive steric, attractive hydrophobic, and electrostatic interactions between residues and is calibrated to a large collection of single-molecule fluorescence resonance energy transfer data on the interresidue separations for 36 pairs of residues in five IDPs: α-, β-, and γ-synuclein, the microtubule-associated protein τ, and prothymosin α. We find that our CG model is able to recapitulate the average interresidue separations regardless of the choice of the hydrophobicity scale, which shows that our calibrated model can robustly capture the conformational dynamics of IDPs. We then employ our model to study the scaling of the radius of gyration with chemical distance in 11 known IDPs. We identify a strong correlation between the distance to the dividing line between folded proteins and IDPs in the mean charge and hydrophobicity space and the scaling exponent of the radius of gyration with chemical distance along the protein.

  15. Scaling of Langevin and molecular dynamics persistence times of nonhomogeneous fluids.

    PubMed

    Olivares-Rivas, Wilmer; Colmenares, Pedro J

    2012-01-01

    The existing solution for the Langevin equation of an anisotropic fluid allowed the evaluation of the position-dependent perpendicular and parallel diffusion coefficients, using molecular dynamics data. However, the time scale of the Langevin dynamics and molecular dynamics are different and an ansatz for the persistence probability relaxation time was needed. Here we show how the solution for the average persistence probability obtained from the backward Smoluchowski-Fokker-Planck equation (SE), associated to the Langevin dynamics, scales with the corresponding molecular dynamics quantity. Our SE perpendicular persistence time is evaluated in terms of simple integrals over the equilibrium local density. When properly scaled by the perpendicular diffusion coefficient, it gives a good match with that obtained from molecular dynamics. PMID:22400522

  16. Scaling of Langevin and molecular dynamics persistence times of nonhomogeneous fluids.

    PubMed

    Olivares-Rivas, Wilmer; Colmenares, Pedro J

    2012-01-01

    The existing solution for the Langevin equation of an anisotropic fluid allowed the evaluation of the position-dependent perpendicular and parallel diffusion coefficients, using molecular dynamics data. However, the time scale of the Langevin dynamics and molecular dynamics are different and an ansatz for the persistence probability relaxation time was needed. Here we show how the solution for the average persistence probability obtained from the backward Smoluchowski-Fokker-Planck equation (SE), associated to the Langevin dynamics, scales with the corresponding molecular dynamics quantity. Our SE perpendicular persistence time is evaluated in terms of simple integrals over the equilibrium local density. When properly scaled by the perpendicular diffusion coefficient, it gives a good match with that obtained from molecular dynamics.

  17. Complex Langevin simulation of chiral symmetry restoration at finite baryonic density

    NASA Astrophysics Data System (ADS)

    Ilgenfritz, Ernst-Michael

    1986-12-01

    A recently proposed effective SU(3) spin model with chiral order parameter is studied by means of the complex Langevin equation. A first-order chiral symmetry restoring and deconfining transition is observed at sufficiently low temperature at finite baryonic density. Permanent address: Sektion Physik, Karl-Marx Universität, DDR-7010 Leipzig, German Democratic Republic.

  18. Gauge cooling in complex Langevin for lattice QCD with heavy quarks

    NASA Astrophysics Data System (ADS)

    Seiler, Erhard; Sexty, Dénes; Stamatescu, Ion-Olimpiu

    2013-06-01

    We employ a new method, "gauge cooling", to stabilize complex Langevin simulations of QCD with heavy quarks. The results are checked against results obtained with reweighting; we find agreement within the estimated errors, except for strong gauge coupling in the confinement region. The method allows us to go to previously unaccessible high densities.

  19. A simple and accurate algorithm for path integral molecular dynamics with the Langevin thermostat.

    PubMed

    Liu, Jian; Li, Dezhang; Liu, Xinzijian

    2016-07-14

    We introduce a novel simple algorithm for thermostatting path integral molecular dynamics (PIMD) with the Langevin equation. The staging transformation of path integral beads is employed for demonstration. The optimum friction coefficients for the staging modes in the free particle limit are used for all systems. In comparison to the path integral Langevin equation thermostat, the new algorithm exploits a different order of splitting for the phase space propagator associated to the Langevin equation. While the error analysis is made for both algorithms, they are also employed in the PIMD simulations of three realistic systems (the H2O molecule, liquid para-hydrogen, and liquid water) for comparison. It is shown that the new thermostat increases the time interval of PIMD by a factor of 4-6 or more for achieving the same accuracy. In addition, the supplementary material shows the error analysis made for the algorithms when the normal-mode transformation of path integral beads is used.

  20. A simple and accurate algorithm for path integral molecular dynamics with the Langevin thermostat

    NASA Astrophysics Data System (ADS)

    Liu, Jian; Li, Dezhang; Liu, Xinzijian

    2016-07-01

    We introduce a novel simple algorithm for thermostatting path integral molecular dynamics (PIMD) with the Langevin equation. The staging transformation of path integral beads is employed for demonstration. The optimum friction coefficients for the staging modes in the free particle limit are used for all systems. In comparison to the path integral Langevin equation thermostat, the new algorithm exploits a different order of splitting for the phase space propagator associated to the Langevin equation. While the error analysis is made for both algorithms, they are also employed in the PIMD simulations of three realistic systems (the H2O molecule, liquid para-hydrogen, and liquid water) for comparison. It is shown that the new thermostat increases the time interval of PIMD by a factor of 4-6 or more for achieving the same accuracy. In addition, the supplementary material shows the error analysis made for the algorithms when the normal-mode transformation of path integral beads is used.

  1. Langevin dynamics for vector variables driven by multiplicative white noise: A functional formalism.

    PubMed

    Moreno, Miguel Vera; Arenas, Zochil González; Barci, Daniel G

    2015-04-01

    We discuss general multidimensional stochastic processes driven by a system of Langevin equations with multiplicative white noise. In particular, we address the problem of how time reversal diffusion processes are affected by the variety of conventions available to deal with stochastic integrals. We present a functional formalism to build up the generating functional of correlation functions without any type of discretization of the Langevin equations at any intermediate step. The generating functional is characterized by a functional integration over two sets of commuting variables, as well as Grassmann variables. In this representation, time reversal transformation became a linear transformation in the extended variables, simplifying in this way the complexity introduced by the mixture of prescriptions and the associated calculus rules. The stochastic calculus is codified in our formalism in the structure of the Grassmann algebra. We study some examples such as higher order derivative Langevin equations and the functional representation of the micromagnetic stochastic Landau-Lifshitz-Gilbert equation. PMID:25974436

  2. Langevin dynamics for vector variables driven by multiplicative white noise: A functional formalism

    NASA Astrophysics Data System (ADS)

    Moreno, Miguel Vera; Arenas, Zochil González; Barci, Daniel G.

    2015-04-01

    We discuss general multidimensional stochastic processes driven by a system of Langevin equations with multiplicative white noise. In particular, we address the problem of how time reversal diffusion processes are affected by the variety of conventions available to deal with stochastic integrals. We present a functional formalism to build up the generating functional of correlation functions without any type of discretization of the Langevin equations at any intermediate step. The generating functional is characterized by a functional integration over two sets of commuting variables, as well as Grassmann variables. In this representation, time reversal transformation became a linear transformation in the extended variables, simplifying in this way the complexity introduced by the mixture of prescriptions and the associated calculus rules. The stochastic calculus is codified in our formalism in the structure of the Grassmann algebra. We study some examples such as higher order derivative Langevin equations and the functional representation of the micromagnetic stochastic Landau-Lifshitz-Gilbert equation.

  3. A novel Generalized Langevin approach to bridge different timescales of relaxation in Protein Dynamics

    NASA Astrophysics Data System (ADS)

    Caballero Manrique, Esther; Bray, Jenelle; Guenza, Marina

    2006-03-01

    The derivation of a Generalized Langevin Equation (GLE) for the long-time dynamics of biological systems presents several challenges as hydrogen bonding, secondary and tertiary structure, Coulombic interactions, and hydrophobic effects come into play. Here we propose a novel GLE approach where the internal friction is explicitly included in the protein dynamics, allowing the distinction between hydrophobic and hydrophilic effects. The protein is described as a linear chain of beads (centered at the alpha carbons) that are connected by harmonic springs. Input for our theory is short time (ns) molecular dynamics simulations of a single protein (or complex) in solution, in this case the bacterial signal transduction protein CheY. Effective inter-bead potentials and local friction coefficients are obtained from the simulations. A comparison of the bond autocorrelation function predicted from the theory and calculated directly from the simulation affords the test of the theory in the short timescales (ns). In the long timescales (ms), the theory is tested against experimental NMR T1 relaxation values. Our results show a remarkable agreement in both cases, indicating that our GLE correctly bridges from the short- to the long-time scale of protein dynamics.

  4. Molecular Dynamics, Monte Carlo Simulations, and Langevin Dynamics: A Computational Review

    PubMed Central

    Paquet, Eric; Viktor, Herna L.

    2015-01-01

    Macromolecular structures, such as neuraminidases, hemagglutinins, and monoclonal antibodies, are not rigid entities. Rather, they are characterised by their flexibility, which is the result of the interaction and collective motion of their constituent atoms. This conformational diversity has a significant impact on their physicochemical and biological properties. Among these are their structural stability, the transport of ions through the M2 channel, drug resistance, macromolecular docking, binding energy, and rational epitope design. To assess these properties and to calculate the associated thermodynamical observables, the conformational space must be efficiently sampled and the dynamic of the constituent atoms must be simulated. This paper presents algorithms and techniques that address the abovementioned issues. To this end, a computational review of molecular dynamics, Monte Carlo simulations, Langevin dynamics, and free energy calculation is presented. The exposition is made from first principles to promote a better understanding of the potentialities, limitations, applications, and interrelations of these computational methods. PMID:25785262

  5. Dynamic scaling behaviors of linear fractal Langevin-type equation driven by nonconserved and conserved noise

    NASA Astrophysics Data System (ADS)

    Zhang, Zhe; Xun, Zhi-Peng; Wu, Ling; Chen, Yi-Li; Xia, Hui; Hao, Da-Peng; Tang, Gang

    2016-06-01

    In order to study the effects of the microscopic details of fractal substrates on the scaling behavior of the growth model, a generalized linear fractal Langevin-type equation, ∂h / ∂t =(- 1) m + 1 ν∇ mzrw h (zrw is the dynamic exponent of random walk on substrates), driven by nonconserved and conserved noise is proposed and investigated theoretically employing scaling analysis. Corresponding dynamic scaling exponents are obtained.

  6. Dynamical consequences of a constraint on the Langevin thermostat in molecular cluster simulation

    SciTech Connect

    Stinson, Jake L.; Kathmann, Shawn M.; Ford, Ian J.

    2014-11-17

    We investigate some unusual behaviour observed while performing molecular dynamics simulations with the DL_POLY_4.03 code. Under the standard Langevin thermostat, atoms appear to be thermalised to different temperatures, depending on their mass and on the total number of particles in the system. We find that an imposed constraint whereby no thermal noise acts on the centre of mass of the system is the cause of the unexpected behaviour. This is demonstrated by solving the stochastic dynamics for the constrained thermostat and comparing the results with simulation data. The effect of the constraint can be considerable for small systems with disparate masses. By removing the constraint the Langevin thermostat may be restored to its intended behaviour and this has been implemented as an option in DL_POLY_4.05. SMK was supported by the U.S. Department of Energy, Office of Basic Energy Sciences, Division of Chemical Sciences, Geosciences, and Biosciences.

  7. Dynamic correlation functions and Boltzmann-Langevin approach for driven one-dimensional lattice gas.

    PubMed

    Pierobon, Paolo; Parmeggiani, Andrea; von Oppen, Felix; Frey, Erwin

    2005-09-01

    We study the dynamics of the totally asymmetric exclusion process with open boundaries by phenomenological theories complemented by extensive Monte Carlo simulations. Upon combining domain wall theory with a kinetic approach known as Boltzmann-Langevin theory we are able to give a complete qualitative picture of the dynamics in the low- and high-density regimes and at the corresponding phase boundary. At the coexistence line between high- and low-density phases we observe a time scale separation between local density fluctuations and collective domain wall motion, which are well accounted for by the Boltzmann-Langevin and domain wall theory, respectively. We present Monte Carlo data for the correlation functions and power spectra in the full parameter range of the model.

  8. Langevin model of the temperature and hydration dependence of protein vibrational dynamics.

    PubMed

    Moritsugu, Kei; Smith, Jeremy C

    2005-06-23

    The modification of internal vibrational modes in a protein due to intraprotein anharmonicity and solvation effects is determined by performing molecular dynamics (MD) simulations of myoglobin, analyzing them using a Langevin model of the vibrational dynamics and comparing the Langevin results to a harmonic, normal mode model of the protein in vacuum. The diagonal and off-diagonal Langevin friction matrix elements, which model the roughness of the vibrational potential energy surfaces, are determined together with the vibrational potentials of mean force from the MD trajectories at 120 K and 300 K in vacuum and in solution. The frictional properties are found to be describable using simple phenomenological functions of the mode frequency, the accessible surface area, and the intraprotein interaction (the displacement vector overlap of any given mode with the other modes in the protein). The frictional damping of a vibrational mode in vacuum is found to be directly proportional to the intraprotein interaction of the mode, whereas in solution, the friction is proportional to the accessible surface area of the mode. In vacuum, the MD frequencies are lower than those of the normal modes, indicating intramolecular anharmonic broadening of the associated potential energy surfaces. Solvation has the opposite effect, increasing the large-amplitude vibrational frequencies relative to in vacuum and thus vibrationally confining the protein atoms. Frictional damping of the low-frequency modes is highly frequency dependent. In contrast to the damping effect of the solvent, the vibrational frequency increase due to solvation is relatively temperature independent, indicating that it is primarily a structural effect. The MD-derived vibrational dynamic structure factor and density of states are well reproduced by a model in which the Langevin friction and potential of mean force parameters are applied to the harmonic normal modes. PMID:16852503

  9. Isothermal Langevin dynamics in systems with power-law spatially dependent friction

    NASA Astrophysics Data System (ADS)

    Regev, Shaked; Grønbech-Jensen, Niels; Farago, Oded

    2016-07-01

    We study the dynamics of Brownian particles in a heterogeneous one-dimensional medium with a spatially dependent diffusion coefficient of the form D (x ) ˜|x| c , at constant temperature. The particle's probability distribution function (PDF) is calculated both analytically, by solving Fick's diffusion equation, and from numerical simulations of the underdamped Langevin equation. At long times, the PDFs calculated by both approaches yield identical results, corresponding to subdiffusion for c <0 and superdiffusion for 0 1 , the diffusion equation predicts that the particles accelerate. Here we show that this phenomenon, previously considered in several works as an illustration for the possible dramatic effects of spatially dependent thermal noise, is unphysical. We argue that in an isothermal medium, the motion cannot exceed the ballistic limit (˜t2 ). The ballistic limit is reached when the friction coefficient drops sufficiently fast at large distances from the origin and is correctly captured by Langevin's equation.

  10. Constant pressure and temperature discrete-time Langevin molecular dynamics

    SciTech Connect

    Grønbech-Jensen, Niels; Farago, Oded

    2014-11-21

    We present a new and improved method for simultaneous control of temperature and pressure in molecular dynamics simulations with periodic boundary conditions. The thermostat-barostat equations are built on our previously developed stochastic thermostat, which has been shown to provide correct statistical configurational sampling for any time step that yields stable trajectories. Here, we extend the method and develop a set of discrete-time equations of motion for both particle dynamics and system volume in order to seek pressure control that is insensitive to the choice of the numerical time step. The resulting method is simple, practical, and efficient. The method is demonstrated through direct numerical simulations of two characteristic model systems—a one-dimensional particle chain for which exact statistical results can be obtained and used as benchmarks, and a three-dimensional system of Lennard-Jones interacting particles simulated in both solid and liquid phases. The results, which are compared against the method of Kolb and Dünweg [J. Chem. Phys. 111, 4453 (1999)], show that the new method behaves according to the objective, namely that acquired statistical averages and fluctuations of configurational measures are accurate and robust against the chosen time step applied to the simulation.

  11. Mass-energy distribution of fragments within Langevin dynamics of fission induced by heavy ions

    SciTech Connect

    Anischenko, Yu. A. Adeev, G. D.

    2012-08-15

    A stochastic approach based on four-dimensional Langevin fission dynamics is applied to calculating mass-energy distributions of fragments originating from the fission of excited compound nuclei. In the model under investigation, the coordinate K representing the projection of the total angular momentum onto the symmetry axis of the nucleus is taken into account in addition to three collective shape coordinates introduced on the basis of the {l_brace}c, h, {alpha}{r_brace} parametrization. The evolution of the orientation degree of freedom (K mode) is described by means of the Langevin equation in the overdamped regime. The tensor of friction is calculated under the assumption of the reducedmechanismof one-body dissipation in the wall-plus-window model. The calculations are performed for two values of the coefficient that takes into account the reduction of the contribution from the wall formula: k{sub s} 0.25 and k{sub s} = 1.0. Calculations with a modified wall-plus-window formula are also performed, and the quantity measuring the degree to which the single-particle motion of nucleons within the nuclear system being considered is chaotic is used for k{sub s} in this calculation. Fusion-fission reactions leading to the production of compound nuclei are considered for values of the parameter Z{sup 2}/A in the range between 21 and 44. So wide a range is chosen in order to perform a comparative analysis not only for heavy but also for light compound nuclei in the vicinity of the Businaro-Gallone point. For all of the reactions considered in the present study, the calculations performed within four-dimensional Langevin dynamics faithfully reproduce mass-energy and mass distributions obtained experimentally. The inclusion of the K mode in the Langevin equation leads to an increase in the variances of mass and energy distributions in relation to what one obtains from three-dimensional Langevin calculations. The results of the calculations where one associates k{sub s

  12. Langevin dynamics modeling of the water diffusion tensor in partially aligned collagen networks

    NASA Astrophysics Data System (ADS)

    Powell, Sean K.; Momot, Konstantin I.

    2012-09-01

    In this work, a Langevin dynamics model of the diffusion of water in articular cartilage was developed. Numerical simulations of the translational dynamics of water molecules and their interaction with collagen fibers were used to study the quantitative relationship between the organization of the collagen fiber network and the diffusion tensor of water in model cartilage. Langevin dynamics was used to simulate water diffusion in both ordered and partially disordered cartilage models. In addition, an analytical approach was developed to estimate the diffusion tensor for a network comprising a given distribution of fiber orientations. The key findings are that (1) an approximately linear relationship was observed between collagen volume fraction and the fractional anisotropy of the diffusion tensor in fiber networks of a given degree of alignment, (2) for any given fiber volume fraction, fractional anisotropy follows a fiber alignment dependency similar to the square of the second Legendre polynomial of cos(θ), with the minimum anisotropy occurring at approximately the magic angle (θMA), and (3) a decrease in the principal eigenvalue and an increase in the transverse eigenvalues is observed as the fiber orientation angle θ progresses from 0∘ to 90∘. The corresponding diffusion ellipsoids are prolate for θ<θMA, spherical for θ≈θMA, and oblate for θ>θMA. Expansion of the model to include discrimination between the combined effects of alignment disorder and collagen fiber volume fraction on the diffusion tensor is discussed.

  13. Bödeker’s effective theory: From Langevin dynamics to Dyson-Schwinger equations

    NASA Astrophysics Data System (ADS)

    Zahlten, Claus; Hernandez, Andres; Schmidt, Michael G.

    2009-10-01

    The dynamics of weakly coupled, non-abelian gauge fields at high temperature is non-perturbative if the characteristic momentum scale is of order |k|˜g2T. Such a situation is typical for the processes of electroweak baryon number violation in the early Universe. Bödeker has derived an effective theory that describes the dynamics of the soft field modes by means of a Langevin equation. This effective theory has been used for lattice calculations so far [G.D. Moore, Nucl. Phys. B568 (2000) 367. Available from: ; G.D. Moore, Phys. Rev. D62 (2000) 085011. Available from: ]. In this work we provide a complementary, more analytic approach based on Dyson-Schwinger equations. Using methods known from stochastic quantitation, we recast Bödeker's Langevin equation in the form of a field theoretic path integral. We introduce gauge ghosts in order to help control possible gauge artefacts that might appear after truncation, and which leads to a BRST symmetric formulation and to corresponding Ward identities. A second set of Ward identities, reflecting the origin of the theory in a stochastic differential equation, is also obtained. Finally, Dyson-Schwinger equations are derived.

  14. Boedeker's effective theory: From Langevin dynamics to Dyson-Schwinger equations

    SciTech Connect

    Zahlten, Claus Hernandez, Andres Schmidt, Michael G.

    2009-10-15

    The dynamics of weakly coupled, non-abelian gauge fields at high temperature is non-perturbative if the characteristic momentum scale is of order |k|{approx}g{sup 2}T. Such a situation is typical for the processes of electroweak baryon number violation in the early Universe. Boedeker has derived an effective theory that describes the dynamics of the soft field modes by means of a Langevin equation. This effective theory has been used for lattice calculations so far [G.D. Moore, Nucl. Phys. B568 (2000) 367. Available from: (); G.D. Moore, Phys. Rev. D62 (2000) 085011. Available from: ()]. In this work we provide a complementary, more analytic approach based on Dyson-Schwinger equations. Using methods known from stochastic quantitation, we recast Boedeker's Langevin equation in the form of a field theoretic path integral. We introduce gauge ghosts in order to help control possible gauge artefacts that might appear after truncation, and which leads to a BRST symmetric formulation and to corresponding Ward identities. A second set of Ward identities, reflecting the origin of the theory in a stochastic differential equation, is also obtained. Finally, Dyson-Schwinger equations are derived.

  15. Applications of Path Integral Langevin Dynamics to Weakly Bound Clusters and Biological Molecules

    NASA Astrophysics Data System (ADS)

    Ing, Christopher; Hinsen, Conrad; Yang, Jing; Roy, Pierre-Nicholas

    2011-06-01

    We present the use of path integral molecular dynamics (PIMD) in conjunction with the path integral Langevin equation thermostat for sampling systems that exhibit nuclear quantum effects, notably those at low temperatures or those consisting mainly of hydrogen or helium. To test this approach, the internal energy of doped helium clusters are compared with white-noise Langevin thermostatting and high precision path integral monte carlo (PIMC) simulations. We comment on the structural evolution of these clusters in the absence of rotation and exchange as a function of cluster size. To quantify the importance of both rotation and exchange in our PIMD simulation, we compute band origin shifts for (He)_N-CO_2 as a function of cluster size and compare to previously published experimental and theoretical shifts. A convergence study is presented to confirm the systematic error reduction introduced by increasing path integral beads for our implementation in the Molecular Modelling Toolkit (MMTK) software package. Applications to carbohydrates are explored at biological temperatures by calculating both equilibrium and dynamical properties using the methods presented. M. Ceriotti, M. Parrinello, and D. E. Manolopoulos, J Chem Phys 133, 124104. H. Li, N. Blinov, P.-N. Roy, and R. J. L. Roy, J Chem Phys 130, 144305.

  16. Four-dimensional Langevin dynamics of heavy-ion-induced fission

    NASA Astrophysics Data System (ADS)

    Nadtochy, P. N.; Ryabov, E. G.; Gegechkori, A. E.; Anischenko, Yu. A.; Adeev, G. D.

    2012-06-01

    A four-dimensional dynamical model based on Langevin equations was developed and applied to calculate a wide set of experimental observables for the reactions 16O+208Pb→224Th and 16O+232Th→248Cf over a wide range of excitation energy. The fusion-fission and evaporation residue cross sections, fission fragment mass-energy distribution parameters, prescission neutron multiplicities, and anisotropy of angular distribution of fission fragments could be reasonably reproduced using a modified one-body mechanism for nuclear friction with a reduction coefficient of the contribution from a wall formula ks≃0.25 and a dissipation coefficient for the orientation degree of freedom (K coordinate) γK≃ 0.077 (MeVzs)-1/2. Inclusion of the K coordinate into calculation of potential energy changes the stiffness of the nucleus with respect to mass asymmetry coordinate for the values of K≠0 and results in a shift of the Businaro-Gallone point towards larger Z2/A values. The experimental data on the fission fragment mass-energy distribution parameters together with mean prescission neutron multiplicity for heavy fissioning nuclei are reproduced through the four-dimensional Langevin calculations more accurately than through three-dimensional calculations.

  17. Heavy quark diffusion with relativistic Langevin dynamics in the quark-gluon fluid

    SciTech Connect

    Akamatsu, Yukinao; Hatsuda, Tetsuo; Hirano, Tetsufumi

    2009-05-15

    The relativistic diffusion process of heavy quarks is formulated on the basis of the relativistic Langevin equation in Ito discretization scheme. The drag force inside the quark-gluon plasma (QGP) is parametrized according to the formula for the strongly coupled plasma obtained by the anti-de-Sitter space/conformal field theory (AdS/CFT) correspondence. The diffusion dynamics of charm and bottom quarks in QGP is described by combining the Langevin simulation under the background matter described by the relativistic hydrodynamics. Theoretical calculations of the nuclear modification factor R{sub AA} and the elliptic flow v{sub 2} for the single electrons from the charm and bottom decays are compared with the experimental data from the relativistic heavy-ion collisions. The R{sub AA} for electrons with large transverse momentum (p{sub T}>3 GeV) indicates that the drag force from the QGP is as strong as the AdS/CFT prediction.

  18. Isothermal Langevin dynamics in systems with power-law spatially dependent friction.

    PubMed

    Regev, Shaked; Grønbech-Jensen, Niels; Farago, Oded

    2016-07-01

    We study the dynamics of Brownian particles in a heterogeneous one-dimensional medium with a spatially dependent diffusion coefficient of the form D(x)∼|x|^{c}, at constant temperature. The particle's probability distribution function (PDF) is calculated both analytically, by solving Fick's diffusion equation, and from numerical simulations of the underdamped Langevin equation. At long times, the PDFs calculated by both approaches yield identical results, corresponding to subdiffusion for c<0 and superdiffusion for 01, the diffusion equation predicts that the particles accelerate. Here we show that this phenomenon, previously considered in several works as an illustration for the possible dramatic effects of spatially dependent thermal noise, is unphysical. We argue that in an isothermal medium, the motion cannot exceed the ballistic limit (〈x^{2}〉∼t^{2}). The ballistic limit is reached when the friction coefficient drops sufficiently fast at large distances from the origin and is correctly captured by Langevin's equation.

  19. Thermodynamically consistent Langevin dynamics with spatially correlated noise predicting frictionless regime and transient attraction effect

    NASA Astrophysics Data System (ADS)

    Majka, M.; Góra, P. F.

    2016-10-01

    While the origins of temporal correlations in Langevin dynamics have been thoroughly researched, the understanding of spatially correlated noise (SCN) is rather incomplete. In particular, very little is known about the relation between friction and SCN. In this article, starting from the microscopic, deterministic model, we derive the analytical formula for the spatial correlation function in the particle-bath interactions. This expression shows that SCN is the inherent component of binary mixtures, originating from the effective (entropic) interactions. Further, employing this spatial correlation function, we postulate the thermodynamically consistent Langevin equation driven by the Gaussian SCN and calculate the adequate fluctuation-dissipation relation. The thermodynamical consistency is achieved by introducing the spatially variant friction coefficient, which can be also derived analytically. This coefficient exhibits a number of intriguing properties, e.g., the singular behavior for certain types of interactions. Eventually, we apply this new theory to the system of two charged particles in the presence of counter-ions. Such particles interact via the screened-charge Yukawa potential and the inclusion of SCN leads to the emergence of the anomalous frictionless regime. In this regime the particles can experience active propulsion leading to the transient attraction effect. This effect suggests a nonequilibrium mechanism facilitating the molecular binding of the like-charged particles.

  20. Isothermal Langevin dynamics in systems with power-law spatially dependent friction.

    PubMed

    Regev, Shaked; Grønbech-Jensen, Niels; Farago, Oded

    2016-07-01

    We study the dynamics of Brownian particles in a heterogeneous one-dimensional medium with a spatially dependent diffusion coefficient of the form D(x)∼|x|^{c}, at constant temperature. The particle's probability distribution function (PDF) is calculated both analytically, by solving Fick's diffusion equation, and from numerical simulations of the underdamped Langevin equation. At long times, the PDFs calculated by both approaches yield identical results, corresponding to subdiffusion for c<0 and superdiffusion for 01, the diffusion equation predicts that the particles accelerate. Here we show that this phenomenon, previously considered in several works as an illustration for the possible dramatic effects of spatially dependent thermal noise, is unphysical. We argue that in an isothermal medium, the motion cannot exceed the ballistic limit (〈x^{2}〉∼t^{2}). The ballistic limit is reached when the friction coefficient drops sufficiently fast at large distances from the origin and is correctly captured by Langevin's equation. PMID:27575086

  1. Langevin model for real-time Brownian dynamics of interacting nanodefects in irradiated metals

    SciTech Connect

    Dudarev, S. L.; Arakawa, K.; Mori, H.; Yao, Z.; Jenkins, M. L.; Derlet, P. M.

    2010-06-01

    In situ real-time electron microscope observations of metals irradiated with ultrahigh-energy electrons or energetic ions show that the dynamics of microstructural evolution in these materials is strongly influenced by long-range elastic interactions between mobile nanoscale radiation defects. Treating long-range interactions is also necessary for modeling microstructures formed in ex situ high-dose-rate ion-beam irradiation experiments, and for interpolating the ion-beam irradiation data to the low-dose-rate limit characterizing the neutron irradiation environments of fission or fusion power plants. We show that simulations, performed using an algorithm where nanoscale radiation defects are treated as interacting Langevin particles, are able to match and explain the real-time dynamics of nanodefects observed in in situ electron microscope experiments.

  2. Langevin dynamics of the choline head group in a membrane environment.

    PubMed Central

    Konstant, P H; Pearce, L L; Harvey, S C

    1994-01-01

    Computer simulations of dipalmitoylphosphatidylcholine (DPPC) have been performed using Langevin dynamics and a Marcelja-type mean field. This work has focused on the dynamics of the choline head group to parameterize the empirical constraints against phosphorus-carbon dipolar couplings (Dp-c) as measured by nuclear magnetic resonance (13C-NMR). The results show good agreement with experimental values at constraints equivalent to the choline tilt observed in joint refinement of x-ray diffraction and neutron diffraction scatterings. Quadrupolar splittings for the alpha and beta positions are also calculated and compared with 2H-NMR experiments. The model predicts torsional transition rates around the alpha-beta bonds and for the two C-O-P-O torsions. It also predicts T1 relaxation times for the alpha and beta carbons. PMID:7948684

  3. Generalized Langevin models of molecular dynamics simulations with applications to ion channels

    NASA Astrophysics Data System (ADS)

    Gordon, Dan; Krishnamurthy, Vikram; Chung, Shin-Ho

    2009-10-01

    We present a new methodology, which combines molecular dynamics and stochastic dynamics, for modeling the permeation of ions across biological ion channels. Using molecular dynamics, a free energy profile is determined for the ion(s) in the channel, and the distribution of random and frictional forces is measured over discrete segments of the ion channel. The parameters thus determined are used in stochastic dynamics simulations based on the nonlinear generalized Langevin equation. We first provide the theoretical basis of this procedure, which we refer to as "distributional molecular dynamics," and detail the methods for estimating the parameters from molecular dynamics to be used in stochastic dynamics. We test the technique by applying it to study the dynamics of ion permeation across the gramicidin pore. Given the known difficulty in modeling the conduction of ions in gramicidin using classical molecular dynamics, there is a degree of uncertainty regarding the validity of the MD-derived potential of mean force (PMF) for gramicidin. Using our techniques and systematically changing the PMF, we are able to reverse engineer a modified PMF which gives a current-voltage curve closely matching experimental results.

  4. Time Step Rescaling Recovers Continuous-Time Dynamical Properties for Discrete-Time Langevin Integration of Nonequilibrium Systems

    PubMed Central

    2015-01-01

    When simulating molecular systems using deterministic equations of motion (e.g., Newtonian dynamics), such equations are generally numerically integrated according to a well-developed set of algorithms that share commonly agreed-upon desirable properties. However, for stochastic equations of motion (e.g., Langevin dynamics), there is still broad disagreement over which integration algorithms are most appropriate. While multiple desiderata have been proposed throughout the literature, consensus on which criteria are important is absent, and no published integration scheme satisfies all desiderata simultaneously. Additional nontrivial complications stem from simulating systems driven out of equilibrium using existing stochastic integration schemes in conjunction with recently developed nonequilibrium fluctuation theorems. Here, we examine a family of discrete time integration schemes for Langevin dynamics, assessing how each member satisfies a variety of desiderata that have been enumerated in prior efforts to construct suitable Langevin integrators. We show that the incorporation of a novel time step rescaling in the deterministic updates of position and velocity can correct a number of dynamical defects in these integrators. Finally, we identify a particular splitting (related to the velocity Verlet discretization) that has essentially universally appropriate properties for the simulation of Langevin dynamics for molecular systems in equilibrium, nonequilibrium, and path sampling contexts. PMID:24555448

  5. Langevin Formalism as the Basis for the Unification of Population Dynamics

    NASA Astrophysics Data System (ADS)

    de Vladar, Harold P.

    2005-03-01

    We are presenting a simple reformulation to population dynamics that generalizes many growth functions. The reformulation consists of two equations, one for population size, and one for the growth rate. The model shows that even when a population is density-dependent the dynamics of its growth rate does not depend explicitly neither on population size nor on the carrying capacity. Actually, the growth rate is uncoupled from the population size equation. The model has only two parameters: a Malthusian parameter ρ and an interaction coefficient θ. Distinct values of these parameters reproduce the family of θ-logistics, the van Bertalanffy, Gompertz and Potential Growth equations, among other possibilities. Stochastic perturbations to the Malthusian parameter leads to a Langevin form of stochastic differential equation consisting of a family of cubic potentials perturbed with multiplicative noise. Using these equtions, we derive the stationary Fokker Plank distribution which which shows that in the stationary dynamics, density dependent populations fluctuate around a mean size that is shifted from the carrying capacity proportionally to the noise intensity. We also study which kinds of populations are susceptible to noise induced transitions.

  6. Many-particle Brownian and Langevin Dynamics Simulations with the Brownmove package

    PubMed Central

    2011-01-01

    Background Brownian Dynamics (BD) is a coarse-grained implicit-solvent simulation method that is routinely used to investigate binary protein association dynamics, but due to its efficiency in handling large simulation volumes and particle numbers it is well suited to also describe many-protein scenarios as they often occur in biological cells. Results Here we introduce our "brownmove" simulation package which was designed to handle many-particle problems with varying particle numbers and allows for a very flexible definition of rigid and flexible protein and polymer models. Both a Brownian and a Langevin dynamics (LD) propagation scheme can be used and hydrodynamic interactions are treated efficiently with our recently introduced TEA-HI ansatz [Geyer, Winter, JCP 130 (2009) 114905]. With simulations of constrained polymers and flexible models of spherical proteins we demonstrate that it is crucial to include hydrodynamics when multi-bead models are used in BD or LD simulations. Only then both the translational and the rotational diffusion coefficients and the timescales of the internal dynamics can be reproduced correctly. In the third example project we show how constant density boundary conditions [Geyer et al, JCP 120 (2004) 4573] can be used to set up a non-equilibrium simulation of diffusional transport across an array of fixed obstacles. Finally, we demonstrate how the agglomeration dynamics of multiple particles with attractive patches can be analysed conveniently with the help of a dynamic interaction network. Conclusions Combining BD and LD propagation, fast hydrodynamics, a flexible protein model, and interfaces for "open" simulation settings, our freely available "brownmove" simulation package constitutes a new platform for coarse-grained many-particle simulations of biologically relevant diffusion and transport processes. PMID:21596002

  7. Solvated molecular dynamics of LiCN isomerization: All-atom argon solvent versus a generalized Langevin bath.

    PubMed

    Junginger, Andrej; Garcia-Muller, Pablo L; Borondo, F; Benito, R M; Hernandez, Rigoberto

    2016-01-14

    The reaction rate rises and falls with increasing density or friction when a molecule is activated by collisions with the solvent particles. This so-called Kramers turnover has recently been observed in the isomerization reaction of LiCN in an argon bath. In this paper, we demonstrate by direct comparison with those results that a reduced-dimensional (generalized) Langevin description gives rise to similar reaction dynamics as the corresponding (computationally expensive) full molecular dynamics calculations. We show that the density distributions within the Langevin description are in direct agreement with the full molecular dynamics results and that the turnover in the reaction rates is reproduced qualitatively and quantitatively at different temperatures. PMID:26772551

  8. Perturbative treatment of anharmonic vibrational effects on bond distances: an extended Langevin dynamics method.

    PubMed

    Shen, Tonghao; Su, Neil Qiang; Wu, Anan; Xu, Xin

    2014-03-01

    In this work, we first review the perturbative treatment of an oscillator with cubic anharmonicity. It is shown that there is a quantum-classical correspondence in terms of mean displacement, mean-squared displacement, and the corresponding variance in the first-order perturbation theory, provided that the amplitude of the classical oscillator is fixed at the zeroth-order energy of quantum mechanics EQM (0). This correspondence condition is realized by proposing the extended Langevin dynamics (XLD), where the key is to construct a proper driving force. It is assumed that the driving force adopts a simple harmonic form with its amplitude chosen according to EQM (0), while the driving frequency chosen as the harmonic frequency. The latter can be improved by using the natural frequency of the system in response to the potential if its anharmonicity is strong. By comparing to the accurate numeric results from discrete variable representation calculations for a set of diatomic species, it is shown that the present method is able to capture the large part of anharmonicity, being competitive with the wave function-based vibrational second-order perturbation theory, for the whole frequency range from ∼4400 cm(-1) (H2 ) to ∼160 cm(-1) (Na2 ). XLD shows a substantial improvement over the classical molecular dynamics which ceases to work for hard mode when zero-point energy effects are significant. PMID:24375394

  9. An electrodynamics-Langevin dynamics (ED-LD) approach to simulate metal nanoparticle interactions and motion.

    PubMed

    Sule, N; Rice, S A; Gray, S K; Scherer, N F

    2015-11-16

    Understanding the formation of electrodynamically interacting assemblies of metal nanoparticles requires accurate computational methods for determining the forces and propagating trajectories. However, since computation of electromagnetic forces occurs on attosecond to femtosecond timescales, simulating the motion of colloidal nanoparticles on milliseconds to seconds timescales is a challenging multi-scale computational problem. Here, we present a computational technique for performing accurate simulations of laser-illuminated metal nanoparticles. In the simulation, we self-consistently combine the finite-difference time-domain method for electrodynamics (ED) with Langevin dynamics (LD) for the particle motions. We demonstrate the ED-LD method by calculating the 3D trajectories of a single 100-nm-diameter Ag nanoparticle and optical trapping and optical binding of two and three 150-nm-diameter Ag nanoparticles in simulated optical tweezers. We show that surface charge on the colloidal metal nanoparticles plays an important role in their optically driven self-organization. In fact, these simulations provide a more complete understanding of the assembly of different structures of two and three Ag nanoparticles that have been observed experimentally, demonstrating that the ED-LD method will be a very useful tool for understanding the self-organization of optical matter.

  10. Langevin dynamics simulation of polymer-assisted virus-like assembly

    NASA Astrophysics Data System (ADS)

    Mahalik, J. P.; Muthukumar, M.

    2012-04-01

    Starting from a coarse grained representation of the building units of the minute virus of mice and a flexible polyelectrolyte molecule, we have explored the mechanism of assembly into icosahedral structures with the help of Langevin dynamics simulations and the parallel tempering technique. Regular icosahedra with appropriate symmetry form only in a narrow range of temperature and polymer length. Within this region of parameters where successful assembly would proceed, we have systematically investigated the growth kinetics. The assembly of icosahedra is found to follow the classical nucleation and growth mechanism in the absence of the polymer, with the three regimes of nucleation, linear growth, and slowing down in the later stage. The calculated average nucleation time obeys the laws expected from the classical nucleation theory. The linear growth rate is found to obey the laws of secondary nucleation as in the case of lamellar growth in polymer crystallization. The same mechanism is seen in the simulations of the assembly of icosahedra in the presence of the polymer as well. The polymer reduces the nucleation barrier significantly by enhancing the local concentration of subunits via adsorbing them on their backbone. The details of growth in the presence of the polymer are also found to be consistent with the classical nucleation theory, despite the smallness of the assembled structures.

  11. Generalized Langevin equation: An efficient approach to nonequilibrium molecular dynamics of open systems

    NASA Astrophysics Data System (ADS)

    Stella, L.; Lorenz, C. D.; Kantorovich, L.

    2014-04-01

    The generalized Langevin equation (GLE) has been recently suggested to simulate the time evolution of classical solid and molecular systems when considering general nonequilibrium processes. In this approach, a part of the whole system (an open system), which interacts and exchanges energy with its dissipative environment, is studied. Because the GLE is derived by projecting out exactly the harmonic environment, the coupling to it is realistic, while the equations of motion are non-Markovian. Although the GLE formalism has already found promising applications, e.g., in nanotribology and as a powerful thermostat for equilibration in classical molecular dynamics simulations, efficient algorithms to solve the GLE for realistic memory kernels are highly nontrivial, especially if the memory kernels decay nonexponentially. This is due to the fact that one has to generate a colored noise and take account of the memory effects in a consistent manner. In this paper, we present a simple, yet efficient, algorithm for solving the GLE for practical memory kernels and we demonstrate its capability for the exactly solvable case of a harmonic oscillator coupled to a Debye bath.

  12. An electrodynamics-Langevin dynamics (ED-LD) approach to simulate metal nanoparticle interactions and motion.

    PubMed

    Sule, N; Rice, S A; Gray, S K; Scherer, N F

    2015-11-16

    Understanding the formation of electrodynamically interacting assemblies of metal nanoparticles requires accurate computational methods for determining the forces and propagating trajectories. However, since computation of electromagnetic forces occurs on attosecond to femtosecond timescales, simulating the motion of colloidal nanoparticles on milliseconds to seconds timescales is a challenging multi-scale computational problem. Here, we present a computational technique for performing accurate simulations of laser-illuminated metal nanoparticles. In the simulation, we self-consistently combine the finite-difference time-domain method for electrodynamics (ED) with Langevin dynamics (LD) for the particle motions. We demonstrate the ED-LD method by calculating the 3D trajectories of a single 100-nm-diameter Ag nanoparticle and optical trapping and optical binding of two and three 150-nm-diameter Ag nanoparticles in simulated optical tweezers. We show that surface charge on the colloidal metal nanoparticles plays an important role in their optically driven self-organization. In fact, these simulations provide a more complete understanding of the assembly of different structures of two and three Ag nanoparticles that have been observed experimentally, demonstrating that the ED-LD method will be a very useful tool for understanding the self-organization of optical matter. PMID:26698479

  13. Finite-Temperature Non-equilibrium Quasicontinuum Method based on Langevin Dynamics

    SciTech Connect

    Marian, J; Venturini, G; Hansen, B; Knap, J; Ortiz, M; Campbell, G

    2009-05-08

    The concurrent bridging of molecular dynamics and continuum thermodynamics presents a number of challenges, mostly associated with energy transmission and changes in the constitutive description of a material across domain boundaries. In this paper, we propose a framework for simulating coarse dynamic systems in the canonical ensemble using the Quasicontinuum method (QC). The equations of motion are expressed in reduced QC coordinates and are strictly derived from dissipative Lagrangian mechanics. The derivation naturally leads to a classical Langevin implementation where the timescale is governed by vibrations emanating from the finest length scale occurring in the computational cell. The equations of motion are integrated explicitly via Newmark's ({beta} = 0; {gamma} = 1/2) method, leading to a robust numerical behavior and energy conservation. In its current form, the method only allows for wave propagations supported by the less compliant of the two meshes across a heterogeneous boundary, which requires the use of overdamped dynamics to avoid spurious heating due to reflected vibrations. We have applied the method to two independent crystallographic systems characterized by different interatomic potentials (Al and Ta) and have measured thermal expansion in order to quantify the vibrational entropy loss due to homogenization. We rationalize the results in terms of system size, mesh coarseness, and nodal cluster diameter within the framework of the quasiharmonic approximation. For Al, we find that the entropy loss introduced by mesh coarsening varies linearly with the element size, and that volumetric effects are not critical in driving the anharmonic behavior of the simulated systems. In Ta, the anomalies of the interatomic potential employed result in negative and zero thermal expansion at low and high temperatures, respectively.

  14. Critical dynamics of self-gravitating Langevin particles and bacterial populations.

    PubMed

    Sire, Clément; Chavanis, Pierre-Henri

    2008-12-01

    We study the critical dynamics of the generalized Smoluchowski-Poisson system (for self-gravitating Langevin particles) or generalized Keller-Segel model (for the chemotaxis of bacterial populations). These models [P. H. Chavanis and C. Sire, Phys. Rev. E 69, 016116 (2004)] are based on generalized stochastic processes leading to the Tsallis statistics. The equilibrium states correspond to polytropic configurations with index n similar to polytropic stars in astrophysics. At the critical index n_{3}=d(d-2) (where d>or=2 is the dimension of space), there exists a critical temperature Theta_{c} (for a given mass) or a critical mass M_{c} (for a given temperature). For Theta>Theta_{c} or MM_{c} the system collapses and forms, in a finite time, a Dirac peak containing a finite fraction M_{c} of the total mass surrounded by a halo. We study these regimes numerically and, when possible, analytically by looking for self-similar or pseudo-self-similar solutions. This study extends the critical dynamics of the ordinary Smoluchowski-Poisson system and Keller-Segel model in d=2 corresponding to isothermal configurations with n_{3}-->+infinity . We also stress the analogy between the limiting mass of white dwarf stars (Chandrasekhar's limit) and the critical mass of bacterial populations in the generalized Keller-Segel model of chemotaxis. PMID:19256806

  15. Critical dynamics of self-gravitating Langevin particles and bacterial populations.

    PubMed

    Sire, Clément; Chavanis, Pierre-Henri

    2008-12-01

    We study the critical dynamics of the generalized Smoluchowski-Poisson system (for self-gravitating Langevin particles) or generalized Keller-Segel model (for the chemotaxis of bacterial populations). These models [P. H. Chavanis and C. Sire, Phys. Rev. E 69, 016116 (2004)] are based on generalized stochastic processes leading to the Tsallis statistics. The equilibrium states correspond to polytropic configurations with index n similar to polytropic stars in astrophysics. At the critical index n_{3}=d(d-2) (where d>or=2 is the dimension of space), there exists a critical temperature Theta_{c} (for a given mass) or a critical mass M_{c} (for a given temperature). For Theta>Theta_{c} or MM_{c} the system collapses and forms, in a finite time, a Dirac peak containing a finite fraction M_{c} of the total mass surrounded by a halo. We study these regimes numerically and, when possible, analytically by looking for self-similar or pseudo-self-similar solutions. This study extends the critical dynamics of the ordinary Smoluchowski-Poisson system and Keller-Segel model in d=2 corresponding to isothermal configurations with n_{3}-->+infinity . We also stress the analogy between the limiting mass of white dwarf stars (Chandrasekhar's limit) and the critical mass of bacterial populations in the generalized Keller-Segel model of chemotaxis.

  16. The Small-Mass Limit for Langevin Dynamics with Unbounded Coefficients and Positive Friction

    NASA Astrophysics Data System (ADS)

    Herzog, David P.; Hottovy, Scott; Volpe, Giovanni

    2016-05-01

    A class of Langevin stochastic differential equations is shown to converge in the small-mass limit under very weak assumptions on the coefficients defining the equation. The convergence result is applied to three physically realizable examples where the coefficients defining the Langevin equation for these examples grow unboundedly either at a boundary, such as a wall, and/or at the point at infinity. This unboundedness violates the assumptions of previous limit theorems in the literature. The main result of this paper proves convergence for such examples.

  17. Two-dimensional Langevin modeling of fission dynamics of the excited compound nuclei 188Pt, 227Pa and 251Es

    NASA Astrophysics Data System (ADS)

    Eslamizadeh, H.

    2016-02-01

    A stochastic approach based on one- and two-dimensional Langevin equations is applied to calculate the pre-scission neutron multiplicity, fission probability, anisotropy of fission fragment angular distribution, fission cross section and the evaporation cross section for the compound nuclei 188Pt, 227Pa and 251Es in an intermediate range of excitation energies. The chaos weighted wall and window friction formula are used in the Langevin equations. The elongation parameter, c, is used as the first dimension and projection of the total spin of the compound nucleus onto the symmetry axis, K, considered as the second dimension in Langevin dynamical calculations. A constant dissipation coefficient of K, γK = 0.077(MeV zs)-1/2, is used in two-dimensional calculations to reproduce the above mentioned experimental data. Comparison of the theoretical results of the pre-scission neutron multiplicity, fission probability, fission cross section and the evaporation cross section with the experimental data shows that the results of two-dimensional calculations are in better agreement with the experimental data. Furthermore, it is shown that the two-dimensional Langevin equations together with a dissipation coefficient of K, γK = 0.077(MeV zs)-1/2, can satisfactorily reproduce the anisotropy of fission fragment angular distribution for the heavy compound nucleus 251Es. However, a larger value of γK = 0.250(MeV zs)-1/2 is needed to reproduce the anisotropy of fission fragment angular distribution for the lighter compound nucleus 227Pa.

  18. Non-Gaussian fluctuations and non-Markovian effects in the nuclear fusion process: Langevin dynamics emerging from quantum molecular dynamics simulations.

    PubMed

    Wen, Kai; Sakata, Fumihiko; Li, Zhu-Xia; Wu, Xi-Zhen; Zhang, Ying-Xun; Zhou, Shan-Gui

    2013-07-01

    Macroscopic parameters as well as precise information on the random force characterizing the Langevin-type description of the nuclear fusion process around the Coulomb barrier are extracted from the microscopic dynamics of individual nucleons by exploiting the numerical simulation of the improved quantum molecular dynamics. It turns out that the dissipation dynamics of the relative motion between two fusing nuclei is caused by a non-Gaussian distribution of the random force. We find that the friction coefficient as well as the time correlation function of the random force takes particularly large values in a region a little bit inside of the Coulomb barrier. A clear non-Markovian effect is observed in the time correlation function of the random force. It is further shown that an emergent dynamics of the fusion process can be described by the generalized Langevin equation with memory effects by appropriately incorporating the microscopic information of individual nucleons through the random force and its time correlation function.

  19. Molecular dynamics and analytical Langevin equation approach for the self-diffusion constant of an anisotropic fluid.

    PubMed

    Colmenares, Pedro J; López, Floralba; Olivares-Rivas, Wilmer

    2009-12-01

    We carried out a molecular-dynamics (MD) study of the self-diffusion tensor of a Lennard-Jones-type fluid, confined in a slit pore with attractive walls. We developed Bayesian equations, which modify the virtual layer sampling method proposed by Liu, Harder, and Berne (LHB) [P. Liu, E. Harder, and B. J. Berne, J. Phys. Chem. B 108, 6595 (2004)]. Additionally, we obtained an analytical solution for the corresponding nonhomogeneous Langevin equation. The expressions found for the mean-squared displacement in the layers contain naturally a modification due to the mean force in the transverse component in terms of the anisotropic diffusion constants and mean exit time. Instead of running a time consuming dual MD-Langevin simulation dynamics, as proposed by LHB, our expression was used to fit the MD data in the entire survival time interval not only for the parallel but also for the perpendicular direction. The only fitting parameter was the diffusion constant in each layer. PMID:20365134

  20. Molecular dynamics and analytical Langevin equation approach for the self-diffusion constant of an anisotropic fluid

    NASA Astrophysics Data System (ADS)

    Colmenares, Pedro J.; López, Floralba; Olivares-Rivas, Wilmer

    2009-12-01

    We carried out a molecular-dynamics (MD) study of the self-diffusion tensor of a Lennard-Jones-type fluid, confined in a slit pore with attractive walls. We developed Bayesian equations, which modify the virtual layer sampling method proposed by Liu, Harder, and Berne (LHB) [P. Liu, E. Harder, and B. J. Berne, J. Phys. Chem. B 108, 6595 (2004)]. Additionally, we obtained an analytical solution for the corresponding nonhomogeneous Langevin equation. The expressions found for the mean-squared displacement in the layers contain naturally a modification due to the mean force in the transverse component in terms of the anisotropic diffusion constants and mean exit time. Instead of running a time consuming dual MD-Langevin simulation dynamics, as proposed by LHB, our expression was used to fit the MD data in the entire survival time interval not only for the parallel but also for the perpendicular direction. The only fitting parameter was the diffusion constant in each layer.

  1. Molecular dynamics and analytical Langevin equation approach for the self-diffusion constant of an anisotropic fluid.

    PubMed

    Colmenares, Pedro J; López, Floralba; Olivares-Rivas, Wilmer

    2009-12-01

    We carried out a molecular-dynamics (MD) study of the self-diffusion tensor of a Lennard-Jones-type fluid, confined in a slit pore with attractive walls. We developed Bayesian equations, which modify the virtual layer sampling method proposed by Liu, Harder, and Berne (LHB) [P. Liu, E. Harder, and B. J. Berne, J. Phys. Chem. B 108, 6595 (2004)]. Additionally, we obtained an analytical solution for the corresponding nonhomogeneous Langevin equation. The expressions found for the mean-squared displacement in the layers contain naturally a modification due to the mean force in the transverse component in terms of the anisotropic diffusion constants and mean exit time. Instead of running a time consuming dual MD-Langevin simulation dynamics, as proposed by LHB, our expression was used to fit the MD data in the entire survival time interval not only for the parallel but also for the perpendicular direction. The only fitting parameter was the diffusion constant in each layer.

  2. Combined Néel and Brown rotational Langevin dynamics in magnetic particle imaging, sensing, and therapy

    SciTech Connect

    Reeves, Daniel B.; Weaver, John B.

    2015-11-30

    Magnetic nanoparticles have been studied intensely because of their possible uses in biomedical applications. Biosensing using the rotational freedom of particles has been used to detect biomarkers for cancer, hyperthermia therapy has been used to treat tumors, and magnetic particle imaging is a promising new imaging modality that can spatially resolve the concentration of nanoparticles. There are two mechanisms by which the magnetization of a nanoparticle can rotate, a fact that poses a challenge for applications that rely on precisely one mechanism. The challenge is exacerbated by the high sensitivity of the dominant mechanism to applied fields. Here, we demonstrate stochastic Langevin equation simulations for the combined rotation in magnetic nanoparticles exposed to oscillating applied fields typical to these applications to both highlight the existing relevant theory and quantify which mechanism should occur in various parameter ranges.

  3. Multiple time scale dynamics of distance fluctuations in a semiflexible polymer: a one-dimensional generalized Langevin equation treatment.

    PubMed

    Debnath, Pallavi; Min, Wei; Xie, X Sunney; Cherayil, Binny J

    2005-11-22

    Time-dependent fluctuations in the distance x(t) between two segments along a polymer are one measure of its overall conformational dynamics. The dynamics of x(t), modeled as the coordinate of a particle moving in a one-dimensional potential well in thermal contact with a reservoir, is treated with a generalized Langevin equation whose memory kernel K(t) can be calculated from the time-correlation function of distance fluctuations C(t) identical with x(0)x(t). We compute C(t) for a semiflexible continuum model of the polymer and use it to determine K(t) via the GLE. The calculations demonstrate that C(t) is well approximated by a Mittag-Leffler function and K(t) by a power-law decay on time scales of several decades. Both functions depend on a number of parameters characterizing the polymer, including chain length, degree of stiffness, and the number of intervening residues between the two segments. The calculations are compared with the recent observation of a nonexponential C(t) and a power law K(t) in the conformational dynamics within single molecule proteins [Min et al., Phys. Rev. Lett. 94, 198302 (2005)].

  4. Dynamics of Lane Formation in Driven Binary Complex Plasmas

    SciTech Connect

    Suetterlin, K. R.; Ivlev, A. V.; Raeth, C.; Thomas, H. M.; Rubin-Zuzic, M.; Morfill, G. E.; Wysocki, A.; Loewen, H.; Goedheer, W. J.; Fortov, V. E.; Lipaev, A. M.; Molotkov, V. I.; Petrov, O. F.

    2009-02-27

    The dynamical onset of lane formation is studied in experiments with binary complex plasmas under microgravity conditions. Small microparticles are driven and penetrate into a cloud of big particles, revealing a strong tendency towards lane formation. The observed time-resolved lane-formation process is in good agreement with computer simulations of a binary Yukawa model with Langevin dynamics. The laning is quantified in terms of the anisotropic scaling index, leading to a universal order parameter for driven systems.

  5. The generalized Langevin equation revisited: Analytical expressions for the persistence dynamics of a viscous fluid under a time dependent external force

    NASA Astrophysics Data System (ADS)

    Olivares-Rivas, Wilmer; Colmenares, Pedro J.

    2016-09-01

    The non-static generalized Langevin equation and its corresponding Fokker-Planck equation for the position of a viscous fluid particle were solved in closed form for a time dependent external force. Its solution for a constant external force was obtained analytically. The non-Markovian stochastic differential equation, associated to the dynamics of the position under a colored noise, was then applied to the description of the dynamics and persistence time of particles constrained within absorbing barriers. Comparisons with molecular dynamics were very satisfactory.

  6. Computing Freidlin's Cycles for the Overdamped Langevin Dynamics. Application to the Lennard-Jones-38 Cluster

    NASA Astrophysics Data System (ADS)

    Cameron, M. K.

    2013-08-01

    The large time behavior of a stochastic system with infinitesimally small noise can be described in terms of Freidlin's cycles. We show that if the system is gradient and the potential satisfies certain non-restrictive conditions, the hierarchy of cycles has a structure of a full binary tree, and each cycle is exited via the lowest saddle adjacent to it. Exploiting this property, we propose an algorithm for computing the asymptotic zero-temperature path and building a hierarchy of Freidlin's cycles associated with the transition process between two given local equilibria. This algorithm is suitable for systems with a complex potential energy landscape with numerous minima. We apply it to find the asymptotic zero-temperature path and Freidlin's cycles involved into the transition process between the two lowest minima of the Lennard-Jones cluster of 38 atoms. D. Wales's stochastic network of minima and transition states of this cluster is used as an input.

  7. Gauge cooling for the singular-drift problem in the complex Langevin method — a test in Random Matrix Theory for finite density QCD

    NASA Astrophysics Data System (ADS)

    Nagata, Keitaro; Nishimura, Jun; Shimasaki, Shinji

    2016-07-01

    Recently, the complex Langevin method has been applied successfully to finite density QCD either in the deconfinement phase or in the heavy dense limit with the aid of a new technique called the gauge cooling. In the confinement phase with light quarks, however, convergence to wrong limits occurs due to the singularity in the drift term caused by small eigenvalues of the Dirac operator including the mass term. We propose that this singular-drift problem should also be overcome by the gauge cooling with different criteria for choosing the complexified gauge transformation. The idea is tested in chiral Random Matrix Theory for finite density QCD, where exact results are reproduced at zero temperature with light quarks. It is shown that the gauge cooling indeed changes drastically the eigenvalue distribution of the Dirac operator measured during the Langevin process. Despite its non-holomorphic nature, this eigenvalue distribution has a universal diverging behavior at the origin in the chiral limit due to a generalized Banks-Casher relation as we confirm explicitly.

  8. Investigation of dissipation in the tilting degree of freedom from four-dimensional Langevin dynamics of heavy-ion-induced fission

    NASA Astrophysics Data System (ADS)

    Nadtochy, P. N.; Ryabov, E. G.; Adeev, G. D.

    2015-04-01

    A four-dimensional dynamical model based on Langevin equations was applied to calculate a wide set of experimental observables for heavy fissioning compound nuclei. Three collective shape coordinates plus the tilting coordinate were considered dynamically from the ground state deformation to the scission into fission fragments. A modified one-body mechanism for nuclear dissipation with a reduction coefficient ks of the contribution from a ‘wall’ formula was used for shapes parameters. Different possibilities of deformation-dependent dissipation coefficient for the tilting coordinate ({{γ }K}) were investigated. Presented results demonstrate that the influence of the ks and γK parameters on the calculated quantities can be selectively probed. The nuclear viscosity with respect to the nuclear shape parameters influences the \\lt {{n}pre}\\gt , the fission fragment mass-energy distribution parameters, and the angular distribution of fission fragments. At the same time the viscosity coefficient γK affects the angular distribution of fission fragments only. The independence of anisotropy on the fission fragment mass is found at both Langevin calculations performed with deformation-dependent and constant γK coefficients.

  9. Elastic Vibrations in the Photosynthetic Bacterial Reaction Center Coupled to the Primary Charge Separation: Implications from Molecular Dynamics Simulations and Stochastic Langevin Approach.

    PubMed

    Milanovsky, Georgy E; Shuvalov, Vladimir A; Semenov, Alexey Yu; Cherepanov, Dmitry A

    2015-10-29

    Primary electron transfer reactions in the bacterial reaction center are difficult for theoretical explication: the reaction kinetics, almost unalterable over a wide range of temperature and free energy changes, revealed oscillatory features observed initially by Shuvalov and coauthors (1997, 2002). Here the reaction mechanism was studied by molecular dynamics and analyzed within a phenomenological Langevin approach. The spectral function of polarization around the bacteriochlorophyll special pair PLPM and the dielectric response upon the formation of PL(+)PM(-) dipole within the special pair were calculated. The system response was approximated by Langevin oscillators; the respective frequencies, friction, and energy coupling coefficients were determined. The protein dynamics around PL and PM were distinctly asymmetric. The polarization around PL included slow modes with the frequency 30-80 cm(-1) and the total amplitude of 130 mV. Two main low-frequency modes of protein response around PM had frequencies of 95 and 155 cm(-1) and the total amplitude of 30 mV. In addition, a slowly damping mode with the frequency of 118 cm(-1) and the damping time >1.1 ps was coupled to the formation of PL(+)PM(-) dipole. It was attributed to elastic vibrations of α-helices in the vicinity of PLPM. The proposed trapping of P excitation energy in the form of the elastic vibrations can rationalize the observed properties of the primary electron transfer reactions, namely, the unusual temperature and ΔG dependences, the oscillating phenomena in kinetics, and the asymmetry of the charge separation reactions. PMID:26148224

  10. Calculations of the anisotropy of the fission fragment angular distribution and neutron emission multiplicities prescission from Langevin dynamics

    SciTech Connect

    Jia Ying; Bao Jingdong

    2007-03-15

    The anisotropy of the fission fragment angular distribution defined at the saddle point and the neutron multiplicities emitted prior to scission for fissioning nuclei {sup 224}Th, {sup 229}Np, {sup 248}Cf, and {sup 254}Fm are calculated simultaneously by using a set of realistic coupled two-dimensional Langevin equations, where the (c,h,{alpha}=0) nuclear parametrization is employed. In comparison with the one-dimensional stochastic model without neck variation, our two-dimensional model produces results that are in better agreement with the experimental data, and the one-dimensional model is available only for low excitation energies. Indeed, to determine the temperature of the nucleus at the saddle point, we investigate the neutron emission during nucleus oscillation around the saddle point for different friction mechanisms. It is shown that the neutrons emitted during the saddle oscillation cause the temperature of a fissioning nuclear system at the saddle point to decrease and influence the fission fragment angular distribution.

  11. Complexity in Dynamical Systems

    NASA Astrophysics Data System (ADS)

    Moore, Cristopher David

    The study of chaos has shown us that deterministic systems can have a kind of unpredictability, based on a limited knowledge of their initial conditions; after a finite time, the motion appears essentially random. This observation has inspired a general interest in the subject of unpredictability, and more generally, complexity; how can we characterize how "complex" a dynamical system is?. In this thesis, we attempt to answer this question with a paradigm of complexity that comes from computer science, we extract sets of symbol sequences, or languages, from a dynamical system using standard methods of symbolic dynamics; we then ask what kinds of grammars or automata are needed a generate these languages. This places them in the Chomsky heirarchy, which in turn tells us something about how subtle and complex the dynamical system's behavior is. This gives us insight into the question of unpredictability, since these automata can also be thought of as computers attempting to predict the system. In the culmination of the thesis, we find a class of smooth, two-dimensional maps which are equivalent to the highest class in the Chomsky heirarchy, the turning machine; they are capable of universal computation. Therefore, these systems possess a kind of unpredictability qualitatively different from the usual "chaos": even if the initial conditions are known exactly, questions about the system's long-term dynamics are undecidable. No algorithm exists to answer them. Although this kind of unpredictability has been discussed in the context of distributed, many-degree-of -freedom systems (for instance, cellular automata) we believe this is the first example of such phenomena in a smooth, finite-degree-of-freedom system.

  12. Modeling surface motion effects in N2 dissociation on W(110): Ab initio molecular dynamics calculations and generalized Langevin oscillator model

    NASA Astrophysics Data System (ADS)

    Nattino, Francesco; Galparsoro, Oihana; Costanzo, Francesca; Díez Muiño, Ricardo; Alducin, Maite; Kroes, Geert-Jan

    2016-06-01

    Accurately modeling surface temperature and surface motion effects is necessary to study molecule-surface reactions in which the energy dissipation to surface phonons can largely affect the observables of interest. We present here a critical comparison of two methods that allow to model such effects, namely, the ab initio molecular dynamics (AIMD) method and the generalized Langevin oscillator (GLO) model, using the dissociation of N2 on W(110) as a benchmark. AIMD is highly accurate as the surface atoms are explicitly part of the dynamics, but this advantage comes with a large computational cost. The GLO model is much more computationally convenient, but accounts for lattice motion effects in a very approximate way. Results show that, despite its simplicity, the GLO model is able to capture the physics of the system to a large extent, returning dissociation probabilities which are in better agreement with AIMD than static-surface results. Furthermore, the GLO model and the AIMD method predict very similar energy transfer to the lattice degrees of freedom in the non-reactive events, and similar dissociation dynamics.

  13. Modeling surface motion effects in N2 dissociation on W(110): Ab initio molecular dynamics calculations and generalized Langevin oscillator model.

    PubMed

    Nattino, Francesco; Galparsoro, Oihana; Costanzo, Francesca; Díez Muiño, Ricardo; Alducin, Maite; Kroes, Geert-Jan

    2016-06-28

    Accurately modeling surface temperature and surface motion effects is necessary to study molecule-surface reactions in which the energy dissipation to surface phonons can largely affect the observables of interest. We present here a critical comparison of two methods that allow to model such effects, namely, the ab initio molecular dynamics (AIMD) method and the generalized Langevin oscillator (GLO) model, using the dissociation of N2 on W(110) as a benchmark. AIMD is highly accurate as the surface atoms are explicitly part of the dynamics, but this advantage comes with a large computational cost. The GLO model is much more computationally convenient, but accounts for lattice motion effects in a very approximate way. Results show that, despite its simplicity, the GLO model is able to capture the physics of the system to a large extent, returning dissociation probabilities which are in better agreement with AIMD than static-surface results. Furthermore, the GLO model and the AIMD method predict very similar energy transfer to the lattice degrees of freedom in the non-reactive events, and similar dissociation dynamics.

  14. Beyond complex Langevin equations: from simple examples to positive representation of Feynman path integrals directly in the Minkowski time

    NASA Astrophysics Data System (ADS)

    Wosiek, Jacek

    2016-04-01

    A positive representation for an arbitrary complex, gaussian weight is derived and used to construct a statistical formulation of gaussian path integrals directly in the Minkowski time. The positivity of Minkowski weights is achieved by doubling the number of real variables. The continuum limit of the new representation exists only if some of the additional couplings tend to infinity and are tuned in a specific way. The construction is then successfully applied to three quantum mechanical examples including a particle in a constant magnetic field — a simplest prototype of a Wilson line. Further generalizations are shortly discussed and an intriguing interpretation of new variables is alluded to.

  15. Interpretation of surface diffusion data with Langevin simulations: a quantitative assessment.

    PubMed

    Diamant, M; Rahav, S; Ferrando, R; Alexandrowicz, G

    2015-04-01

    Diffusion studies of adsorbates moving on a surface are often analyzed using 2D Langevin simulations. These simulations are computationally cheap and offer valuable insight into the dynamics, however, they simplify the complex interactions between the substrate and adsorbate atoms, neglecting correlations in the motion of the two species. The effect of this simplification on the accuracy of observables extracted using Langevin simulations was previously unquantified. Here we report a numerical study aimed at assessing the validity of this approach. We compared experimentally accessible observables which were calculated using a Langevin simulation with those obtained from explicit molecular dynamics simulations. Our results show that within the range of parameters we explored Langevin simulations provide a good alternative for calculating the diffusion procress, i.e. the effect of correlations is too small to be observed within the numerical accuracy of this study and most likely would not have a significant effect on the interpretation of experimental data. Our comparison of the two numerical approaches also demonstrates the effect temperature dependent friction has on the calculated observables, illustrating the importance of accounting for such a temperature dependence when interpreting experimental data. PMID:25743627

  16. Steady-State Thermodynamics of Langevin Systems

    NASA Astrophysics Data System (ADS)

    Hatano, Takahiro; Sasa, Shin-Ichi

    2001-04-01

    We study Langevin dynamics describing nonequilibirum steady states. Employing the phenomenological framework of steady-state thermodynamics constructed by Oono and Paniconi [Prog. Theor. Phys. Suppl. 130, 29 (1998)], we find that the extended form of the second law which they proposed holds for transitions between steady states and that the Shannon entropy difference is related to the excess heat produced in an infinitely slow operation. A generalized version of the Jarzynski work relation plays an important role in our theory.

  17. Probability Density Function Method for Langevin Equations with Colored Noise

    SciTech Connect

    Wang, Peng; Tartakovsky, Alexandre M.; Tartakovsky, Daniel M.

    2013-04-05

    We present a novel method to derive closed-form, computable PDF equations for Langevin systems with colored noise. The derived equations govern the dynamics of joint or marginal probability density functions (PDFs) of state variables, and rely on a so-called Large-Eddy-Diffusivity (LED) closure. We demonstrate the accuracy of the proposed PDF method for linear and nonlinear Langevin equations, describing the classical Brownian displacement and dispersion in porous media.

  18. Langevin Equation on Fractal Curves

    NASA Astrophysics Data System (ADS)

    Satin, Seema; Gangal, A. D.

    2016-07-01

    We analyze random motion of a particle on a fractal curve, using Langevin approach. This involves defining a new velocity in terms of mass of the fractal curve, as defined in recent work. The geometry of the fractal curve, plays an important role in this analysis. A Langevin equation with a particular model of noise is proposed and solved using techniques of the Fα-Calculus.

  19. The Dynamics of Polycomb Complexes.

    PubMed

    Palacios, Daniela

    2016-01-01

    Polycomb complexes are essential regulators of embryonic and adult stem cells, highly conserved from flies to mammals. Traditionally, their study was based on biochemical and genetic approaches. More recently, the development of novel technologies and the improvement and standardization of existing ones has allowed to address previously unexplored aspects of Polycomb biology, such as dynamics and regulation. In this chapter, relevant researchers in the field discuss novel technologies aimed at dissecting the dynamics of Polycomb complexes in normal and pathological conditions. PMID:27659981

  20. Managing Complex Dynamical Systems

    ERIC Educational Resources Information Center

    Cox, John C.; Webster, Robert L.; Curry, Jeanie A.; Hammond, Kevin L.

    2011-01-01

    Management commonly engages in a variety of research designed to provide insight into the motivation and relationships of individuals, departments, organizations, etc. This paper demonstrates how the application of concepts associated with the analysis of complex systems applied to such data sets can yield enhanced insights for managerial action.

  1. From Langevin to generalized Langevin equations for the nonequilibrium Rouse model.

    PubMed

    Maes, Christian; Thomas, Simi R

    2013-02-01

    We investigate the nature of the effective dynamics and statistical forces obtained after integrating out nonequilibrium degrees of freedom. To be explicit, we consider the Rouse model for the conformational dynamics of an ideal polymer chain subject to steady driving. We compute the effective dynamics for one of the many monomers by integrating out the rest of the chain. The result is a generalized Langevin dynamics for which we give the memory and noise kernels and the effective force, and we discuss the inherited nonequilibrium aspects.

  2. Functional characterization of linear delay Langevin equations

    NASA Astrophysics Data System (ADS)

    Budini, Adrián A.; Cáceres, Manuel O.

    2004-10-01

    We present an exact functional characterization of linear delay Langevin equations driven by any noise structure defined through its characteristic functional. This method relies on the possibility of finding an explicitly analytical expression for each realization of the delayed stochastic process in terms of those of the driving noise. General properties of the transient dissipative dynamics are analyzed. The corresponding interplay with a color Gaussian noise is presented. As a full application of our functional method we study a model for population growth with non-Gaussian fluctuations: the Gompertz model driven by multiplicative white shot noise.

  3. Experimenting with Langevin lattice QCD

    SciTech Connect

    Gavai, R.V.; Potvin, J.; Sanielevici, S.

    1987-05-01

    We report on the status of our investigations of the effects of systematic errors upon the practical merits of Langevin updating in full lattice QCD. We formulate some rules for the safe use of this updating procedure and some observations on problems which may be common to all approximate fermion algorithms.

  4. Synchronization Dynamics in Complex Networks

    NASA Astrophysics Data System (ADS)

    Zhou, Changsong; Zemanová, Lucia; Kurths, Jürgen

    Previous chapters have discussed tools from graph theory and their contribution to our understanding of the structural organization of mammalian brains and its functional implications. The brain functions are mediated by complicated dynamical processes which arise from the underlying complex neural networks, and synchronization has been proposed as an important mechanism for neural information processing. In this chapter, we discuss synchronization dynamics on complex networks. We first present a general theory and tools to characterize the relationship of some structural measures of networks to their synchronizability (the ability of the networks to achieve complete synchronization) and to the organization of effective synchronization patterns on the networks. Then, we study synchronization in a realistic network of cat cortical connectivity by modeling the nodes (which are cortical areas composed of large ensembles of neurons) by a neural mass model or a subnetwork of interacting neurons. We show that if the dynamics is characterized by well-defined oscillations (neural mass model and subnetworks with strong couplings), the synchronization patterns can be understood by the general principles discussed in the first part of the chapter. With weak couplings, the model with subnetworks displays biologically plausible dynamics and the synchronization pattern reveals a hierarchically clustered organization in the network structure. Thus, the study of synchronization of complex networks can provide insights into the relationship between network topology and functional organization of complex brain networks.

  5. Modeling wildfire incident complexity dynamics.

    PubMed

    Thompson, Matthew P

    2013-01-01

    Wildfire management in the United States and elsewhere is challenged by substantial uncertainty regarding the location and timing of fire events, the socioeconomic and ecological consequences of these events, and the costs of suppression. Escalating U.S. Forest Service suppression expenditures is of particular concern at a time of fiscal austerity as swelling fire management budgets lead to decreases for non-fire programs, and as the likelihood of disruptive within-season borrowing potentially increases. Thus there is a strong interest in better understanding factors influencing suppression decisions and in turn their influence on suppression costs. As a step in that direction, this paper presents a probabilistic analysis of geographic and temporal variation in incident management team response to wildfires. The specific focus is incident complexity dynamics through time for fires managed by the U.S. Forest Service. The modeling framework is based on the recognition that large wildfire management entails recurrent decisions across time in response to changing conditions, which can be represented as a stochastic dynamic system. Daily incident complexity dynamics are modeled according to a first-order Markov chain, with containment represented as an absorbing state. A statistically significant difference in complexity dynamics between Forest Service Regions is demonstrated. Incident complexity probability transition matrices and expected times until containment are presented at national and regional levels. Results of this analysis can help improve understanding of geographic variation in incident management and associated cost structures, and can be incorporated into future analyses examining the economic efficiency of wildfire management.

  6. Unidirectional Flux In Brownian And Langevin Simulations Of Diffusion

    NASA Astrophysics Data System (ADS)

    Singer, A.; Schuss, Z.; Nadler, B.

    2005-11-01

    Brownian and Langevin simulations of ions in solution require the maintenance of average fixed concentrations at the interface between the simulation volume and the surrounding continuum. This requires the injection of new trajectories into the simulation, which creates a unidirectional flux at the interface. The Wiener path integral splits the net diffusion flux into infinite unidirectional fluxes, whose difference is finite, as in classical diffusion theory. The infinite unidirectional flux is an artifact of the diffusion approximation to Langevin's equation, which fails on time scales shorter than the relaxation time 1/γ. The probability of Brownian trajectories that cross a point in one direction per unit time Δt equals that of Langevin trajectories if γΔt = 2. This result is relevant to Brownian dynamics simulation of particles in a finite volume inside a large bath.

  7. Langevin equations for competitive growth models

    NASA Astrophysics Data System (ADS)

    Silveira, F. A.; Aarão Reis, F. D. A.

    2012-01-01

    Langevin equations for several competitive growth models in one dimension are derived. For models with crossover from random deposition (RD) to some correlated deposition (CD) dynamics, with small probability p of CD, the surface tension ν and the nonlinear coefficient λ of the associated equations have linear dependence on p due solely to this random choice. However, they also depend on the regularized step functions present in the analytical representations of the CD, whose expansion coefficients scale with p according to the divergence of local height differences when p→0. The superposition of those scaling factors gives ν˜p2 for random deposition with surface relaxation (RDSR) as the CD, and ν˜p, λ˜p3/2 for ballistic deposition (BD) as the CD, in agreement with simulation and other scaling approaches. For bidisperse ballistic deposition (BBD), the same scaling of RD-BD model is found. The Langevin equation for the model with competing RDSR and BD, with probability p for the latter, is also constructed. It shows linear p dependence of λ, while the quadratic dependence observed in previous simulations is explained by an additional crossover before the asymptotic regime. The results highlight the relevance of scaling of the coefficients of step function expansions in systems with steep surfaces, which is responsible for noninteger exponents in some p-dependent stochastic equations, and the importance of the physical correspondence of aggregation rules and equation coefficients.

  8. Modeling Wildfire Incident Complexity Dynamics

    PubMed Central

    Thompson, Matthew P.

    2013-01-01

    Wildfire management in the United States and elsewhere is challenged by substantial uncertainty regarding the location and timing of fire events, the socioeconomic and ecological consequences of these events, and the costs of suppression. Escalating U.S. Forest Service suppression expenditures is of particular concern at a time of fiscal austerity as swelling fire management budgets lead to decreases for non-fire programs, and as the likelihood of disruptive within-season borrowing potentially increases. Thus there is a strong interest in better understanding factors influencing suppression decisions and in turn their influence on suppression costs. As a step in that direction, this paper presents a probabilistic analysis of geographic and temporal variation in incident management team response to wildfires. The specific focus is incident complexity dynamics through time for fires managed by the U.S. Forest Service. The modeling framework is based on the recognition that large wildfire management entails recurrent decisions across time in response to changing conditions, which can be represented as a stochastic dynamic system. Daily incident complexity dynamics are modeled according to a first-order Markov chain, with containment represented as an absorbing state. A statistically significant difference in complexity dynamics between Forest Service Regions is demonstrated. Incident complexity probability transition matrices and expected times until containment are presented at national and regional levels. Results of this analysis can help improve understanding of geographic variation in incident management and associated cost structures, and can be incorporated into future analyses examining the economic efficiency of wildfire management. PMID:23691014

  9. Efficient estimators for likelihood ratio sensitivity indices of complex stochastic dynamics

    NASA Astrophysics Data System (ADS)

    Arampatzis, Georgios; Katsoulakis, Markos A.; Rey-Bellet, Luc

    2016-03-01

    We demonstrate that centered likelihood ratio estimators for the sensitivity indices of complex stochastic dynamics are highly efficient with low, constant in time variance and consequently they are suitable for sensitivity analysis in long-time and steady-state regimes. These estimators rely on a new covariance formulation of the likelihood ratio that includes as a submatrix a Fisher information matrix for stochastic dynamics and can also be used for fast screening of insensitive parameters and parameter combinations. The proposed methods are applicable to broad classes of stochastic dynamics such as chemical reaction networks, Langevin-type equations and stochastic models in finance, including systems with a high dimensional parameter space and/or disparate decorrelation times between different observables. Furthermore, they are simple to implement as a standard observable in any existing simulation algorithm without additional modifications.

  10. Efficient estimators for likelihood ratio sensitivity indices of complex stochastic dynamics.

    PubMed

    Arampatzis, Georgios; Katsoulakis, Markos A; Rey-Bellet, Luc

    2016-03-14

    We demonstrate that centered likelihood ratio estimators for the sensitivity indices of complex stochastic dynamics are highly efficient with low, constant in time variance and consequently they are suitable for sensitivity analysis in long-time and steady-state regimes. These estimators rely on a new covariance formulation of the likelihood ratio that includes as a submatrix a Fisher information matrix for stochastic dynamics and can also be used for fast screening of insensitive parameters and parameter combinations. The proposed methods are applicable to broad classes of stochastic dynamics such as chemical reaction networks, Langevin-type equations and stochastic models in finance, including systems with a high dimensional parameter space and/or disparate decorrelation times between different observables. Furthermore, they are simple to implement as a standard observable in any existing simulation algorithm without additional modifications.

  11. Complex dynamics of text analysis

    NASA Astrophysics Data System (ADS)

    Ke, Xiaohua; Zeng, Yongqiang; Ma, Qinghua; Zhu, Lin

    2014-12-01

    This paper presents a novel method for the analysis of nonlinear text quality in Chinese language. Texts produced by university students in China were represented as scale-free networks (word adjacency model), from which typical network features such as the in/outdegree, clustering coefficient and network dynamics were obtained. The method integrates the classical concepts of network feature representation and text quality series variation. The analytical and numerical scheme leads to a parameter space representation that constitutes a valid alternative to represent the network features. The results reveal that complex network features of different text qualities can be clearly revealed and applied to potential applications in other instances of text analysis.

  12. LANGEVIN DYNAMICS OF THE TWO STAGE MELTING TRANSITION OF VORTEX MATTER IN Bi{sub 2}Sr{sub 2}CaCu{sub 2}O{sub 8+{delta}} IN THE PRESENCE OF STRAIGHT AND OF TILTED COLUMNAR DEFECTS

    SciTech Connect

    GOLDSCHMIDT, YADIN Y.; LIU, Jin-Tao

    2007-08-07

    In this paper we use London Langevin molecular dynamics simulations to investigate the vortex matter melting transition in the highly anisotropic high-temperature superconductor material Bi{sub 2}Sr{sub 2}CaCu{sub 2}O{sub 8+{delta}} in the presence of low concentration of columnar defects (CDs). We reproduce with further details our previous results obtained by using Multilevel Monte Carlo simulations that showed that the melting of the nanocrystalline vortex matter occurs in two stages: a first stage melting into nanoliquid vortex matter and a second stage delocalization transition into a homogeneous liquid. Furthermore, we report on new dynamical measurements in the presence of a current that identifies clearly the irreversibility line and the second stage delocalization transition. In addition to CDs aligned along the c-axis we also simulate the case of tilted CDs which are aligned at an angle with respect to the applied magnetic field. Results for CDs tilted by 45{degree} with respect to c-axis show that the locations of the melting and delocalization transitions are not affected by the tilt when the ratio of flux lines to CDs remains constant. On the other hand we argue that some dynamical properties and in particular the position of the irreversibility line should be affected.

  13. Generalized Langevin equation for tracer diffusion in atomic liquids

    NASA Astrophysics Data System (ADS)

    Mendoza-Méndez, Patricia; López-Flores, Leticia; Vizcarra-Rendón, Alejandro; Sánchez-Díaz, Luis E.; Medina-Noyola, Magdaleno

    2014-01-01

    We derive the time-evolution equation that describes the Brownian motion of labeled individual tracer particles in a simple model atomic liquid (i.e., a system of N particles whose motion is governed by Newton’s second law, and interacting through spherically symmetric pairwise potentials). We base our derivation on the generalized Langevin equation formalism, and find that the resulting time evolution equation is formally identical to the generalized Langevin equation that describes the Brownian motion of individual tracer particles in a colloidal suspension in the absence of hydrodynamic interactions. This formal dynamic equivalence implies the long-time indistinguishability of some dynamic properties of both systems, such as their mean squared displacement, upon a well-defined time scaling. This prediction is tested here by comparing the results of molecular and Brownian dynamics simulations performed on the hard sphere system.

  14. Dynamic and interacting complex networks

    NASA Astrophysics Data System (ADS)

    Dickison, Mark E.

    This thesis employs methods of statistical mechanics and numerical simulations to study some aspects of dynamic and interacting complex networks. The mapping of various social and physical phenomena to complex networks has been a rich field in the past few decades. Subjects as broad as petroleum engineering, scientific collaborations, and the structure of the internet have all been analyzed in a network physics context, with useful and universal results. In the first chapter we introduce basic concepts in networks, including the two types of network configurations that are studied and the statistical physics and epidemiological models that form the framework of the network research, as well as covering various previously-derived results in network theory that are used in the work in the following chapters. In the second chapter we introduce a model for dynamic networks, where the links or the strengths of the links change over time. We solve the model by mapping dynamic networks to the problem of directed percolation, where the direction corresponds to the time evolution of the network. We show that the dynamic network undergoes a percolation phase transition at a critical concentration pc, that decreases with the rate r at which the network links are changed. The behavior near criticality is universal and independent of r. We find that for dynamic random networks fundamental laws are changed: i) The size of the giant component at criticality scales with the network size N for all values of r, rather than as N2/3 in static network, ii) In the presence of a broad distribution of disorder, the optimal path length between two nodes in a dynamic network scales as N1/2, compared to N1/3 in a static network. The third chapter consists of a study of the effect of quarantine on the propagation of epidemics on an adaptive network of social contacts. For this purpose, we analyze the susceptible-infected-recovered model in the presence of quarantine, where susceptible

  15. Modelling platelet–blood flow interaction using the subcellular element Langevin method

    PubMed Central

    Sweet, Christopher R.; Chatterjee, Santanu; Xu, Zhiliang; Bisordi, Katharine; Rosen, Elliot D.; Alber, Mark

    2011-01-01

    In this paper, a new three-dimensional modelling approach is described for studying fluid–viscoelastic cell interaction, the subcellular element Langevin (SCEL) method, with cells modelled by subcellular elements (SCEs) and SCE cells coupled with fluid flow and substrate models by using the Langevin equation. It is demonstrated that: (i) the new method is computationally efficient, scaling as 𝒪(N) for N SCEs; (ii) cell geometry, stiffness and adhesivity can be modelled by directly relating parameters to experimentally measured values; (iii) modelling the fluid–platelet interface as a surface leads to a very good correlation with experimentally observed platelet flow interactions. Using this method, the three-dimensional motion of a viscoelastic platelet in a shear blood flow was simulated and compared with experiments on tracking platelets in a blood chamber. It is shown that the complex platelet-flipping dynamics under linear shear flows can be accurately recovered with the SCEL model when compared with the experiments. All experimental details and electronic supplementary material are archived at http://biomath.math.nd.edu/scelsupplementaryinformation/. PMID:21593027

  16. Aging and the complexity of cardiovascular dynamics

    NASA Technical Reports Server (NTRS)

    Kaplan, D. T.; Furman, M. I.; Pincus, S. M.; Ryan, S. M.; Lipsitz, L. A.; Goldberger, A. L.

    1991-01-01

    Biomedical signals often vary in a complex and irregular manner. Analysis of variability in such signals generally does not address directly their complexity, and so may miss potentially useful information. We analyze the complexity of heart rate and beat-to-beat blood pressure using two methods motivated by nonlinear dynamics (chaos theory). A comparison of a group of healthy elderly subjects with healthy young adults indicates that the complexity of cardiovascular dynamics is reduced with aging. This suggests that complexity of variability may be a useful physiological marker.

  17. An adaptive stepsize method for the chemical Langevin equation.

    PubMed

    Ilie, Silvana; Teslya, Alexandra

    2012-05-14

    Mathematical and computational modeling are key tools in analyzing important biological processes in cells and living organisms. In particular, stochastic models are essential to accurately describe the cellular dynamics, when the assumption of the thermodynamic limit can no longer be applied. However, stochastic models are computationally much more challenging than the traditional deterministic models. Moreover, many biochemical systems arising in applications have multiple time-scales, which lead to mathematical stiffness. In this paper we investigate the numerical solution of a stochastic continuous model of well-stirred biochemical systems, the chemical Langevin equation. The chemical Langevin equation is a stochastic differential equation with multiplicative, non-commutative noise. We propose an adaptive stepsize algorithm for approximating the solution of models of biochemical systems in the Langevin regime, with small noise, based on estimates of the local error. The underlying numerical method is the Milstein scheme. The proposed adaptive method is tested on several examples arising in applications and it is shown to have improved efficiency and accuracy compared to the existing fixed stepsize schemes.

  18. Langevin model for a Brownian system with directed motion

    NASA Astrophysics Data System (ADS)

    Ambía, Francisco; Híjar, Humberto

    2016-08-01

    We propose a model for an active Brownian system that exhibits one-dimensional directed motion. This system consists of two Brownian spherical particles that interact through an elastic potential and have time-dependent radii. We suggest an algorithm by which the sizes of the particles can be varied, such that the center of mass of the system is able to move at an average constant speed in one direction. The dynamics of the system is studied theoretically using a Langevin model, as well as from Brownian Dynamics simulations.

  19. Dynamics on Complex Networks and Applications

    NASA Astrophysics Data System (ADS)

    Motter, Adilson E.; Matías, Manuel A.; Kurths, Jürgen; Ott, Edward

    2006-12-01

    At the eight-year anniversary of Watts and Strogatz’s work on the collective dynamics of small-world networks and seven years after Barabási and Albert’s discovery of scale-free networks, the area of dynamical processes on complex networks is at the forefront of the current research on nonlinear dynamics and complex systems. This volume brings together a selection of original contributions in complementary topics of statistical physics, nonlinear dynamics and biological sciences, and is expected to provide the reader with a comprehensive up-to-date representation of this rapidly developing area.

  20. Generalized Langevin Theory for Inhomogeneous Fluids.

    NASA Astrophysics Data System (ADS)

    Grant, Martin Garth

    This thesis presents a molecular theory of the dynamics of inhomogeneous fluids. Dynamical correlations in a nonuniform system are studied through the generalized Langevin approach. The equations of motion (formally exact) are obtained for the number density, momentum density, energy density, stress tensor and heat flux. We evaluate all the relevant sum rules appearing in the frequency matrix exactly in terms of microscopic pair potentials and an external field. We show using functional derivatives how these microscopic sum rules relate to more familiar, though now nonlocal, hydrodynamic-like quantities. The set of equations is closed by a Markov approximation in the equations for stress tensor and heat flux. As a result, these equations become analogous to Grad's 13-moment equations for low density fluids and constitute a generalization to inhomogeneous fluids of the work of Schofield and Akcasu-Daniels. We apply this formalism to several problems. We study the correlation of currents orthogonal to a diffuse planar, liquid-vapour, interface, introducing new nonlocal elastic moduli and new nonlocal, frequency dependent, viscosities. Novel symmetry breaking contributions are obtained, which are related to the Young-Laplace equation for pressure balance. The normal modes, associated with the symmetry breaking interface in the liquid-vapour system, are analyzed, taking into account the nonlocal nature of the diffuse planar interface. We obtain the classical dispersion relation for capillary waves, observed in light scattering experiments, from an adiabatic (molecular) approach. We consider the 'capillary wave model' (CWM) of the equilibrium liquid-vapour interface. CWM is reformulated to be consistent with capillary waves; corrections to the standard CWM results, due to self-consistent long range coupling, are obtained for finite surface area and nonzero gravitational acceleration. Finally, we obtain the Landau-Lifshitz theory of fluctuating hydrodynamics from the

  1. Collinearly improved JIMWLK evolution in Langevin form

    NASA Astrophysics Data System (ADS)

    Hatta, Yoshitaka; Iancu, Edmond

    2016-08-01

    The high-energy evolution of Wilson line operators, which at leading order is described by the Balitsky-JIMWLK equations, receives large radiative corrections en-hanced by single and double collinear logarithms at next-to-leading order and beyond. We propose a method for resumming such logarithmic corrections to all orders, at the level of the Langevin formulation of the JIMWLK equation. The ensuing, collinearly-improved Langevin equation features generalized Wilson line operators, which depend not only upon rapidity (the logarithm of the longitudinal momentum), but also upon the transverse size of the color neutral projectile to which the Wilson lines belong. This additional scale dependence is built up during the evolution, via the condition that the successive emissions of soft gluons be ordered in time. The presence of this transverse scale in the Langevin equation furthermore allows for the resummation of the one-loop running coupling corrections.

  2. Dynamics of complex multibody systems

    NASA Astrophysics Data System (ADS)

    Schiehlen, W. O.

    The analysis of multibody-system (MBS) dynamics is discussed and demonstrated in a review of recent work. The early history of MBS studies is traced; the kinematic equations are derived for free, holonomic, and nonholonomic systems in both inertial and moving reference frames; the Newton-Euler equations are obtained by replacing the rigid bearings and supports by constraint forces and torques; equations of motion are found by means of D'Alembert's and Jourdain's principles; and generalized constraint forces and bearing and support clearances are considered. The computer derivation of equations of motion is demonstrated on a four-body moving-vehicle problem. The approach described is shown to use less computation time and memory space than techniques based on the Lagrange or Gibbs-Appell equations, while permitting the inclusion of contact and friction forces.

  3. Amplitude dynamics favors synchronization in complex networks

    NASA Astrophysics Data System (ADS)

    Gambuzza, Lucia Valentina; Gómez-Gardeñes, Jesus; Frasca, Mattia

    2016-04-01

    In this paper we study phase synchronization in random complex networks of coupled periodic oscillators. In particular, we show that, when amplitude dynamics is not negligible, phase synchronization may be enhanced. To illustrate this, we compare the behavior of heterogeneous units with both amplitude and phase dynamics and pure (Kuramoto) phase oscillators. We find that in small network motifs the behavior crucially depends on the topology and on the node frequency distribution. Surprisingly, the microscopic structures for which the amplitude dynamics improves synchronization are those that are statistically more abundant in random complex networks. Thus, amplitude dynamics leads to a general lowering of the synchronization threshold in arbitrary random topologies. Finally, we show that this synchronization enhancement is generic of oscillators close to Hopf bifurcations. To this aim we consider coupled FitzHugh-Nagumo units modeling neuron dynamics.

  4. Amplitude dynamics favors synchronization in complex networks

    PubMed Central

    Gambuzza, Lucia Valentina; Gómez-Gardeñes, Jesus; Frasca, Mattia

    2016-01-01

    In this paper we study phase synchronization in random complex networks of coupled periodic oscillators. In particular, we show that, when amplitude dynamics is not negligible, phase synchronization may be enhanced. To illustrate this, we compare the behavior of heterogeneous units with both amplitude and phase dynamics and pure (Kuramoto) phase oscillators. We find that in small network motifs the behavior crucially depends on the topology and on the node frequency distribution. Surprisingly, the microscopic structures for which the amplitude dynamics improves synchronization are those that are statistically more abundant in random complex networks. Thus, amplitude dynamics leads to a general lowering of the synchronization threshold in arbitrary random topologies. Finally, we show that this synchronization enhancement is generic of oscillators close to Hopf bifurcations. To this aim we consider coupled FitzHugh-Nagumo units modeling neuron dynamics. PMID:27108847

  5. Role of the Charge-Transfer State in Reduced Langevin Recombination in Organic Solar Cells: A Theoretical Study

    PubMed Central

    2015-01-01

    Reduced Langevin recombination has been observed in organic solar cells (OSCs) for many years, but its origin is still unclear. A recent work by Burke et al. (Adv. Energy Mater.2015, 5, 1500123-1) was inspired by this reduced Langevin recombination, and they proposed an equilibrium model of charge-transfer (CT) states that correlates the open-circuit voltage of OSCs with experimentally available device parameters. In this work, we extend Burke et al.’s CT model further and for the first time directly correlate the reduced Langevin recombination with the energetic and dynamic behavior of the CT state. Recombination through CT states leads in a straightforward manner to a decrease in the Langevin reduction factor with increasing temperature, without explicit consideration of the temperature dependence of the mobility. To verify the correlation between the CT states and reduced Langevin recombination, we incorporated this CT model and the reduced Langevin model into drift-diffusion simulations of a bilayer OSC. The simulations not only successfully reproduced realistic current–voltage (J–V) characteristics of the bilayer OSC, but also demonstrate that the two models consistently lead to same value of the apparent Langevin reduction factor. PMID:26640611

  6. Spreading dynamics in complex networks

    NASA Astrophysics Data System (ADS)

    Pei, Sen; Makse, Hernán A.

    2013-12-01

    Searching for influential spreaders in complex networks is an issue of great significance for applications across various domains, ranging from epidemic control, innovation diffusion, viral marketing, and social movement to idea propagation. In this paper, we first display some of the most important theoretical models that describe spreading processes, and then discuss the problem of locating both the individual and multiple influential spreaders respectively. Recent approaches in these two topics are presented. For the identification of privileged single spreaders, we summarize several widely used centralities, such as degree, betweenness centrality, PageRank, k-shell, etc. We investigate the empirical diffusion data in a large scale online social community—LiveJournal. With this extensive dataset, we find that various measures can convey very distinct information of nodes. Of all the users in the LiveJournal social network, only a small fraction of them are involved in spreading. For the spreading processes in LiveJournal, while degree can locate nodes participating in information diffusion with higher probability, k-shell is more effective in finding nodes with a large influence. Our results should provide useful information for designing efficient spreading strategies in reality.

  7. Constructing minimal models for complex system dynamics

    NASA Astrophysics Data System (ADS)

    Barzel, Baruch; Liu, Yang-Yu; Barabási, Albert-László

    2015-05-01

    One of the strengths of statistical physics is the ability to reduce macroscopic observations into microscopic models, offering a mechanistic description of a system's dynamics. This paradigm, rooted in Boltzmann's gas theory, has found applications from magnetic phenomena to subcellular processes and epidemic spreading. Yet, each of these advances were the result of decades of meticulous model building and validation, which are impossible to replicate in most complex biological, social or technological systems that lack accurate microscopic models. Here we develop a method to infer the microscopic dynamics of a complex system from observations of its response to external perturbations, allowing us to construct the most general class of nonlinear pairwise dynamics that are guaranteed to recover the observed behaviour. The result, which we test against both numerical and empirical data, is an effective dynamic model that can predict the system's behaviour and provide crucial insights into its inner workings.

  8. Collective dynamics of active filament complexes

    NASA Astrophysics Data System (ADS)

    Nogucci, Hironobu; Ishihara, Shuji

    2016-05-01

    Networks of biofilaments are essential for the formation of cellular structures that support various biological functions. For the most part, previous studies have investigated the collective dynamics of rodlike biofilaments; however, the shapes of the actual subcellular components are often more elaborate. In this study, we considered an active object composed of two active filaments, which represents the progression from rodlike biofilaments to complex-shaped biofilaments. Specifically, we numerically assessed the collective behaviors of these active objects in two dimensions and observed several types of dynamics, depending on the density and the angle of the two filaments as shape parameters of the object. Among the observed collective dynamics, a moving density band that we named a "moving smectic" is introduced here for the first time. By analyzing the trajectories of individual objects and the interactions among them, this study demonstrated how interactions among active biofilaments with complex shapes could produce collective dynamics in a nontrivial manner.

  9. Better Decision Making in Complex, Dynamic Tasks

    NASA Astrophysics Data System (ADS)

    Qudrat-Ullah, Hassan

    Complex managerial problems abound. For instance, project costs continue to overrun, friendly fire events, where a fighter plane bombs its own troops on ground, appear unavoidable, and overexploitation of renewables continues unabated. In essence, managers and policymakers today face problems that are increasingly complex, and dynamic. Therefore, the need for effective and efficient decisional aids is always on the rise.

  10. Dynamic information routing in complex networks

    NASA Astrophysics Data System (ADS)

    Kirst, Christoph; Timme, Marc; Battaglia, Demian

    2016-04-01

    Flexible information routing fundamentally underlies the function of many biological and artificial networks. Yet, how such systems may specifically communicate and dynamically route information is not well understood. Here we identify a generic mechanism to route information on top of collective dynamical reference states in complex networks. Switching between collective dynamics induces flexible reorganization of information sharing and routing patterns, as quantified by delayed mutual information and transfer entropy measures between activities of a network's units. We demonstrate the power of this mechanism specifically for oscillatory dynamics and analyse how individual unit properties, the network topology and external inputs co-act to systematically organize information routing. For multi-scale, modular architectures, we resolve routing patterns at all levels. Interestingly, local interventions within one sub-network may remotely determine nonlocal network-wide communication. These results help understanding and designing information routing patterns across systems where collective dynamics co-occurs with a communication function.

  11. Dynamic information routing in complex networks

    PubMed Central

    Kirst, Christoph; Timme, Marc; Battaglia, Demian

    2016-01-01

    Flexible information routing fundamentally underlies the function of many biological and artificial networks. Yet, how such systems may specifically communicate and dynamically route information is not well understood. Here we identify a generic mechanism to route information on top of collective dynamical reference states in complex networks. Switching between collective dynamics induces flexible reorganization of information sharing and routing patterns, as quantified by delayed mutual information and transfer entropy measures between activities of a network's units. We demonstrate the power of this mechanism specifically for oscillatory dynamics and analyse how individual unit properties, the network topology and external inputs co-act to systematically organize information routing. For multi-scale, modular architectures, we resolve routing patterns at all levels. Interestingly, local interventions within one sub-network may remotely determine nonlocal network-wide communication. These results help understanding and designing information routing patterns across systems where collective dynamics co-occurs with a communication function. PMID:27067257

  12. Design tools for complex dynamic security systems.

    SciTech Connect

    Byrne, Raymond Harry; Rigdon, James Brian; Rohrer, Brandon Robinson; Laguna, Glenn A.; Robinett, Rush D. III; Groom, Kenneth Neal; Wilson, David Gerald; Bickerstaff, Robert J.; Harrington, John J.

    2007-01-01

    The development of tools for complex dynamic security systems is not a straight forward engineering task but, rather, a scientific task where discovery of new scientific principles and math is necessary. For years, scientists have observed complex behavior but have had difficulty understanding it. Prominent examples include: insect colony organization, the stock market, molecular interactions, fractals, and emergent behavior. Engineering such systems will be an even greater challenge. This report explores four tools for engineered complex dynamic security systems: Partially Observable Markov Decision Process, Percolation Theory, Graph Theory, and Exergy/Entropy Theory. Additionally, enabling hardware technology for next generation security systems are described: a 100 node wireless sensor network, unmanned ground vehicle and unmanned aerial vehicle.

  13. Molecular dynamics simulations of large macromolecular complexes

    PubMed Central

    Perilla, Juan R.; Goh, Boon Chong; Cassidy, C. Keith; Liu, Bo; Bernardi, Rafael C.; Rudack, Till; Yu, Hang; Wu, Zhe; Schulten, Klaus

    2015-01-01

    Connecting dynamics to structural data from diverse experimental sources, molecular dynamics simulations permit the exploration of biological phenomena in unparalleled detail. Advances in simulations are moving the atomic resolution descriptions of biological systems into the million-to-billion atom regime, in which numerous cell functions reside. In this opinion, we review the progress, driven by large-scale molecular dynamics simulations, in the study of viruses, ribosomes, bioenergetic systems, and other diverse applications. These examples highlight the utility of molecular dynamics simulations in the critical task of relating atomic detail to the function of supramolecular complexes, a task that cannot be achieved by smaller-scale simulations or existing experimental approaches alone. PMID:25845770

  14. Fokker-Planck description for a linear delayed Langevin equation with additive Gaussian noise

    NASA Astrophysics Data System (ADS)

    Giuggioli, Luca; McKetterick, Thomas John; Kenkre, V. M.; Chase, Matthew

    2016-09-01

    We construct an equivalent probability description of linear multi-delay Langevin equations subject to additive Gaussian white noise. By exploiting the time-convolutionless transform and a time variable transformation we are able to write a Fokker-Planck equation (FPE) for the 1-time and for the 2-time probability distributions valid irrespective of the regime of stability of the Langevin equations. We solve exactly the derived FPEs and analyze the aging dynamics by studying analytically the conditional probability distribution. We discuss explicitly why the initially conditioned distribution is not sufficient to describe fully out a non-Markov process as both preparation and observation times have bearing on its dynamics. As our analytic procedure can also be applied to linear Langevin equations with memory kernels, we compare the non-Markov dynamics of a one-delay system with that of a generalized Langevin equation with an exponential as well as a power law memory. Application to a generalization of the Green-Kubo formula is also presented.

  15. Fokker–Planck description for a linear delayed Langevin equation with additive Gaussian noise

    NASA Astrophysics Data System (ADS)

    Giuggioli, Luca; McKetterick, Thomas John; Kenkre, V. M.; Chase, Matthew

    2016-09-01

    We construct an equivalent probability description of linear multi-delay Langevin equations subject to additive Gaussian white noise. By exploiting the time-convolutionless transform and a time variable transformation we are able to write a Fokker–Planck equation (FPE) for the 1-time and for the 2-time probability distributions valid irrespective of the regime of stability of the Langevin equations. We solve exactly the derived FPEs and analyze the aging dynamics by studying analytically the conditional probability distribution. We discuss explicitly why the initially conditioned distribution is not sufficient to describe fully out a non-Markov process as both preparation and observation times have bearing on its dynamics. As our analytic procedure can also be applied to linear Langevin equations with memory kernels, we compare the non-Markov dynamics of a one-delay system with that of a generalized Langevin equation with an exponential as well as a power law memory. Application to a generalization of the Green–Kubo formula is also presented.

  16. Langevin Equations for Reaction-Diffusion Processes.

    PubMed

    Benitez, Federico; Duclut, Charlie; Chaté, Hugues; Delamotte, Bertrand; Dornic, Ivan; Muñoz, Miguel A

    2016-09-01

    For reaction-diffusion processes with at most bimolecular reactants, we derive well-behaved, numerically tractable, exact Langevin equations that govern a stochastic variable related to the response field in field theory. Using duality relations, we show how the particle number and other quantities of interest can be computed. Our work clarifies long-standing conceptual issues encountered in field-theoretical approaches and paves the way for systematic numerical and theoretical analyses of reaction-diffusion problems. PMID:27636462

  17. Langevin Equations for Reaction-Diffusion Processes

    NASA Astrophysics Data System (ADS)

    Benitez, Federico; Duclut, Charlie; Chaté, Hugues; Delamotte, Bertrand; Dornic, Ivan; Muñoz, Miguel A.

    2016-09-01

    For reaction-diffusion processes with at most bimolecular reactants, we derive well-behaved, numerically tractable, exact Langevin equations that govern a stochastic variable related to the response field in field theory. Using duality relations, we show how the particle number and other quantities of interest can be computed. Our work clarifies long-standing conceptual issues encountered in field-theoretical approaches and paves the way for systematic numerical and theoretical analyses of reaction-diffusion problems.

  18. Supplementary analyses regarding Langevin, Langevin, and Curnoe's (2007) findings on fraternal birth order in homosexual men.

    PubMed

    Blanchard, Ray

    2007-08-01

    A recent article by Langevin, Langevin, and Curnoe (2007) reported mixed results regarding the fraternal birth order effect, that is, the repeatedly observed finding that older brothers correlate with homosexuality in later-born males. Using a fraternal birth order index computed as older brothers minus younger brothers, Langevin et al. found that the "homoerotic" probands were born later among their brothers than were the "heteroerotic" probands in their full sample (N = 1194) and in their subsample over age 19 (N = 1122), but not in their subsample over age 31 (N = 698) or in their subsample with mothers over age 46 at the proband's birth (N = 727). The present writer concluded that the results obtained with the larger samples are more reliable, based on analyses demonstrating that (1) the larger samples are unlikely to be seriously affected by incomplete sibships, and (2) the smaller samples have poor statistical power. A separate analysis, based on an approximate reconstruction of Langevin et al.'s raw data, indicated that their heteroerotic probands reported a ratio of 104 older brothers per 100 older sisters, which is close to the normative population value of 106, whereas their homoerotic probands reported a ratio of 137, indicating a statistically significant excess of older brothers. These results suggest that Langevin et al.'s data showed significant evidence of a fraternal birth order effect and that their data were consistent with previous studies of this phenomenon.

  19. Structure and dynamics of complex liquid water: Molecular dynamics simulation

    NASA Astrophysics Data System (ADS)

    S, Indrajith V.; Natesan, Baskaran

    2015-06-01

    We have carried out detailed structure and dynamical studies of complex liquid water using molecular dynamics simulations. Three different model potentials, namely, TIP3P, TIP4P and SPC-E have been used in the simulations, in order to arrive at the best possible potential function that could reproduce the structure of experimental bulk water. All the simulations were performed in the NVE micro canonical ensemble using LAMMPS. The radial distribution functions, gOO, gOH and gHH and the self diffusion coefficient, Ds, were calculated for all three models. We conclude from our results that the structure and dynamical parameters obtained for SPC-E model matched well with the experimental values, suggesting that among the models studied here, the SPC-E model gives the best structure and dynamics of bulk water.

  20. Stability threshold approach for complex dynamical systems

    NASA Astrophysics Data System (ADS)

    Klinshov, Vladimir V.; Nekorkin, Vladimir I.; Kurths, Jürgen

    2016-01-01

    A new measure to characterize the stability of complex dynamical systems against large perturbations is suggested, the stability threshold (ST). It quantifies the magnitude of the weakest perturbation capable of disrupting the system and switch it to an undesired dynamical regime. In the phase space, the ST corresponds to the ‘thinnest site’ of the attraction basin and therefore indicates the most ‘dangerous’ direction of perturbations. We introduce a computational algorithm for quantification of the ST and demonstrate that the suggested approach is effective and provides important insights. The generality of the obtained results defines their vast potential for application in such fields as engineering, neuroscience, power grids, Earth science and many others where the robustness of complex systems is studied.

  1. Stability, complexity and robustness in population dynamics.

    PubMed

    Demongeot, J; Hazgui, H; Ben Amor, H; Waku, J

    2014-09-01

    The problem of stability in population dynamics concerns many domains of application in demography, biology, mechanics and mathematics. The problem is highly generic and independent of the population considered (human, animals, molecules,…). We give in this paper some examples of population dynamics concerning nucleic acids interacting through direct nucleic binding with small or cyclic RNAs acting on mRNAs or tRNAs as translation factors or through protein complexes expressed by genes and linked to DNA as transcription factors. The networks made of these interactions between nucleic acids (considered respectively as edges and nodes of their interaction graph) are complex, but exhibit simple emergent asymptotic behaviours, when time tends to infinity, called attractors. We show that the quantity called attractor entropy plays a crucial role in the study of the stability and robustness of such genetic networks. PMID:25107273

  2. Nonlinear dynamics, chaos and complex cardiac arrhythmias

    NASA Technical Reports Server (NTRS)

    Glass, L.; Courtemanche, M.; Shrier, A.; Goldberger, A. L.

    1987-01-01

    Periodic stimulation of a nonlinear cardiac oscillator in vitro gives rise to complex dynamics that is well described by one-dimensional finite difference equations. As stimulation parameters are varied, a large number of different phase-locked and chaotic rhythms is observed. Similar rhythms can be observed in the intact human heart when there is interaction between two pacemaker sites. Simplified models are analyzed, which show some correspondence to clinical observations.

  3. Species Abundance Patterns in Complex Evolutionary Dynamics

    NASA Astrophysics Data System (ADS)

    Tokita, Kei

    2004-10-01

    An analytic theory of species abundance patterns (SAPs) in biological networks is presented. The theory is based on multispecies replicator dynamics equivalent to the Lotka-Volterra equation, with diverse interspecies interactions. Various SAPs observed in nature are derived from a single parameter. The abundance distribution is formed like a widely observed left-skewed lognormal distribution. As the model has a general form, the result can be applied to similar patterns in other complex biological networks, e.g., gene expression.

  4. Nonlinear Dynamics, Chaotic and Complex Systems

    NASA Astrophysics Data System (ADS)

    Infeld, E.; Zelazny, R.; Galkowski, A.

    2011-04-01

    Part I. Dynamic Systems Bifurcation Theory and Chaos: 1. Chaos in random dynamical systems V. M. Gunldach; 2. Controlling chaos using embedded unstable periodic orbits: the problem of optimal periodic orbits B. R. Hunt and E. Ott; 3. Chaotic tracer dynamics in open hydrodynamical flows G. Karolyi, A. Pentek, T. Tel and Z. Toroczkai; 4. Homoclinic chaos L. P. Shilnikov; Part II. Spatially Extended Systems: 5. Hydrodynamics of relativistic probability flows I. Bialynicki-Birula; 6. Waves in ionic reaction-diffusion-migration systems P. Hasal, V. Nevoral, I. Schreiber, H. Sevcikova, D. Snita, and M. Marek; 7. Anomalous scaling in turbulence: a field theoretical approach V. Lvov and I. Procaccia; 8. Abelian sandpile cellular automata M. Markosova; 9. Transport in an incompletely chaotic magnetic field F. Spineanu; Part III. Dynamical Chaos Quantum Physics and Foundations Of Statistical Mechanics: 10. Non-equilibrium statistical mechanics and ergodic theory L. A. Bunimovich; 11. Pseudochaos in statistical physics B. Chirikov; 12. Foundations of non-equilibrium statistical mechanics J. P. Dougherty; 13. Thermomechanical particle simulations W. G. Hoover, H. A. Posch, C. H. Dellago, O. Kum, C. G. Hoover, A. J. De Groot and B. L. Holian; 14. Quantum dynamics on a Markov background and irreversibility B. Pavlov; 15. Time chaos and the laws of nature I. Prigogine and D. J. Driebe; 16. Evolutionary Q and cognitive systems: dynamic entropies and predictability of evolutionary processes W. Ebeling; 17. Spatiotemporal chaos information processing in neural networks H. Szu; 18. Phase transitions and learning in neural networks C. Van den Broeck; 19. Synthesis of chaos A. Vanecek and S. Celikovsky; 20. Computational complexity of continuous problems H. Wozniakowski; Part IV. Complex Systems As An Interface Between Natural Sciences and Environmental Social and Economic Sciences: 21. Stochastic differential geometry in finance studies V. G. Makhankov; Part V. Conference Banquet

  5. Random complex dynamics and devil's coliseums

    NASA Astrophysics Data System (ADS)

    Sumi, Hiroki

    2015-04-01

    We investigate the random dynamics of polynomial maps on the Riemann sphere \\hat{\\Bbb{C}} and the dynamics of semigroups of polynomial maps on \\hat{\\Bbb{C}} . In particular, the dynamics of a semigroup G of polynomials whose planar postcritical set is bounded and the associated random dynamics are studied. In general, the Julia set of such a G may be disconnected. We show that if G is such a semigroup, then regarding the associated random dynamics, the chaos of the averaged system disappears in the C0 sense, and the function T∞ of probability of tending to ∞ \\in \\hat{\\Bbb{C}} is Hölder continuous on \\hat{\\Bbb{C}} and varies only on the Julia set of G. Moreover, the function T∞ has a kind of monotonicity. It turns out that T∞ is a complex analogue of the devil's staircase, and we call T∞ a ‘devil’s coliseum'. We investigate the details of T∞ when G is generated by two polynomials. In this case, T∞ varies precisely on the Julia set of G, which is a thin fractal set. Moreover, under this condition, we investigate the pointwise Hölder exponents of T∞.

  6. Modular interdependency in complex dynamical systems.

    PubMed

    Watson, Richard A; Pollack, Jordan B

    2005-01-01

    Herbert A. Simon's characterization of modularity in dynamical systems describes subsystems as having dynamics that are approximately independent of those of other subsystems (in the short term). This fits with the general intuition that modules must, by definition, be approximately independent. In the evolution of complex systems, such modularity may enable subsystems to be modified and adapted independently of other subsystems, whereas in a nonmodular system, modifications to one part of the system may result in deleterious side effects elsewhere in the system. But this notion of modularity and its effect on evolvability is not well quantified and is rather simplistic. In particular, modularity need not imply that intermodule dependences are weak or unimportant. In dynamical systems this is acknowledged by Simon's suggestion that, in the long term, the dynamical behaviors of subsystems do interact with one another, albeit in an "aggregate" manner--but this kind of intermodule interaction is omitted in models of modularity for evolvability. In this brief discussion we seek to unify notions of modularity in dynamical systems with notions of how modularity affects evolvability. This leads to a quantifiable measure of modularity and a different understanding of its effect on evolvability. PMID:16197673

  7. Automated Design of Complex Dynamic Systems

    PubMed Central

    Hermans, Michiel; Schrauwen, Benjamin; Bienstman, Peter; Dambre, Joni

    2014-01-01

    Several fields of study are concerned with uniting the concept of computation with that of the design of physical systems. For example, a recent trend in robotics is to design robots in such a way that they require a minimal control effort. Another example is found in the domain of photonics, where recent efforts try to benefit directly from the complex nonlinear dynamics to achieve more efficient signal processing. The underlying goal of these and similar research efforts is to internalize a large part of the necessary computations within the physical system itself by exploiting its inherent non-linear dynamics. This, however, often requires the optimization of large numbers of system parameters, related to both the system's structure as well as its material properties. In addition, many of these parameters are subject to fabrication variability or to variations through time. In this paper we apply a machine learning algorithm to optimize physical dynamic systems. We show that such algorithms, which are normally applied on abstract computational entities, can be extended to the field of differential equations and used to optimize an associated set of parameters which determine their behavior. We show that machine learning training methodologies are highly useful in designing robust systems, and we provide a set of both simple and complex examples using models of physical dynamical systems. Interestingly, the derived optimization method is intimately related to direct collocation a method known in the field of optimal control. Our work suggests that the application domains of both machine learning and optimal control have a largely unexplored overlapping area which envelopes a novel design methodology of smart and highly complex physical systems. PMID:24497969

  8. Generalized Langevin theory for inhomogeneous fluids: The equations of motion

    NASA Astrophysics Data System (ADS)

    Grant, Martin; Desai, Rashmi C.

    1982-05-01

    We use the generalized Langevin approach to study the dynamical correlations in an inhomogeneous system. The equations of motion (formally exact) are obtained for the number density, momentum density, energy density, stress tensor, and heat flux. We evaluate all the relevant sum rules appearing in the frequency matrix exactly in terms of microscopic pair potentials and an external field. We show using functional derivatives how these microscopic sum rules relate to more familiar, though now nonlocal, hydrodynamiclike quantities. The set of equations is closed by a Markov approximation in the equations for stress tensor and heat flux. As a result, these equations become analogous to Grad's 13-moment equations for low-density fluids and constitute a generalization to inhomogeneous fluids of the work of Schofield and Akcasu-Daniels. We also indicate how the resulting general set of equations would simplify for systems in which the inhomogeneity is unidirectional, e.g., a liquid-vapor interface.

  9. Complex Dynamics in Information Sharing Networks

    NASA Astrophysics Data System (ADS)

    Cronin, Bruce

    This study examines the roll-out of an electronic knowledge base in a medium-sized professional services firm over a six year period. The efficiency of such implementation is a key business problem in IT systems of this type. Data from usage logs provides the basis for analysis of the dynamic evolution of social networks around the depository during this time. The adoption pattern follows an "s-curve" and usage exhibits something of a power law distribution, both attributable to network effects, and network position is associated with organisational performance on a number of indicators. But periodicity in usage is evident and the usage distribution displays an exponential cut-off. Further analysis provides some evidence of mathematical complexity in the periodicity. Some implications of complex patterns in social network data for research and management are discussed. The study provides a case study demonstrating the utility of the broad methodological approach.

  10. Structural relaxation in complex liquids: non-Markovian dynamics in a bistable potential.

    PubMed

    Chaudhury, Srabanti; Cherayil, Binny J

    2006-11-14

    The time correlation function C(t) identical with of the distance fluctuations of a particle moving in a bistable potential under the action of fractional Gaussian noise (fGn) is calculated from a Smoluchowski-type equation derived from a generalized Langevin equation (GLE). The time derivative of this function, dC(t)dt, is compared with data from optical Kerr effect measurements of liquid crystal dynamics in the vicinity of the isotropic-to-nematic transition, which are related to the time derivative of an orientational correlation function. A number of characteristic features of the experimental decay curves, including short and intermediate time power law behavior and long time exponential relaxation, are qualitatively reproduced by the analytical calculations, even though the latter do not explicitly treat orientational degrees of freedom. The GLE formalism with fGn was, in fact, originally proposed as a model of protein conformational fluctuations, so the present results suggest that it may also serve more generally as a model of structural relaxation in complex condensed phase media.

  11. Langevin power curve analysis for numerical wind energy converter models with new insights on high frequency power performance

    NASA Astrophysics Data System (ADS)

    Mücke, Tanja A.; Wächter, Matthias; Milan, Patrick; Peinke, Joachim

    2015-11-01

    Based on the Langevin equation it has been proposed to obtain power curves for wind turbines from high frequency data of wind speed measurements u(t) and power output P (t). The two parts of the Langevin approach, power curve and drift field, give a comprehensive description of the conversion dynamic over the whole operating range of the wind turbine. The method deals with high frequent data instead of 10 min means. It is therefore possible to gain a reliable power curve already from a small amount of data per wind speed. Furthermore, the method is able to visualize multiple fixed points, which is e.g. characteristic for the transition from partial to full load or in case the conversion process deviates from the standard procedures. In order to gain a deeper knowledge it is essential that the method works not only for measured data but also for numerical wind turbine models and synthetic wind fields. Here, we characterize the dynamics of a detailed numerical wind turbine model and calculate the Langevin power curve for different data samplings. We show, how to get reliable results from synthetic data and verify the applicability of the method for field measurements with ultra-sonic, cup and Lidar measurements. The independence of the fixed points on site specific turbulence effects is also confirmed with the numerical model. Furthermore, we demonstrate the potential of the Langevin approach to detect failures in the conversion process and thus show the potential of the Langevin approach for a condition monitoring system.

  12. Hybrid function projective synchronization in complex dynamical networks

    SciTech Connect

    Wei, Qiang; Wang, Xing-yuan Hu, Xiao-peng

    2014-02-15

    This paper investigates hybrid function projective synchronization in complex dynamical networks. When the complex dynamical networks could be synchronized up to an equilibrium or periodic orbit, a hybrid feedback controller is designed to realize the different component of vector of node could be synchronized up to different desired scaling function in complex dynamical networks with time delay. Hybrid function projective synchronization (HFPS) in complex dynamical networks with constant delay and HFPS in complex dynamical networks with time-varying coupling delay are researched, respectively. Finally, the numerical simulations show the effectiveness of theoretical analysis.

  13. Langevin representation of Coulomb collisions for bi-Maxwellian plasmas

    SciTech Connect

    Hellinger, Petr

    2010-07-20

    Langevin model corresponding to the Fokker-Planck equation for bi-Maxwellian particle distribution functions is developed. Rosenbluth potentials and their derivatives are derived in the form of triple hypergeometric functions. The Langevin model is tested in the case of relaxation of the proton temperature anisotropy and implemented into the hybrid expanding box model. First results of this code are presented and discussed.

  14. The heterogeneous dynamics of economic complexity.

    PubMed

    Cristelli, Matthieu; Tacchella, Andrea; Pietronero, Luciano

    2015-01-01

    What will be the growth of the Gross Domestic Product (GDP) or the competitiveness of China, United States, and Vietnam in the next 3, 5 or 10 years? Despite this kind of questions has a large societal impact and an extreme value for economic policy making, providing a scientific basis for economic predictability is still a very challenging problem. Recent results of a new branch--Economic Complexity--have set the basis for a framework to approach such a challenge and to provide new perspectives to cast economic prediction into the conceptual scheme of forecasting the evolution of a dynamical system as in the case of weather dynamics. We argue that a recently introduced non-monetary metrics for country competitiveness (fitness) allows for quantifying the hidden growth potential of countries by the means of the comparison of this measure for intangible assets with monetary figures, such as GDP per capita. This comparison defines the fitness-income plane where we observe that country dynamics presents strongly heterogeneous patterns of evolution. The flow in some zones is found to be laminar while in others a chaotic behavior is instead observed. These two regimes correspond to very different predictability features for the evolution of countries: in the former regime, we find strong predictable pattern while the latter scenario exhibits a very low predictability. In such a framework, regressions, the usual tool used in economics, are no more the appropriate strategy to deal with such a heterogeneous scenario and new concepts, borrowed from dynamical systems theory, are mandatory. We therefore propose a data-driven method--the selective predictability scheme--in which we adopt a strategy similar to the methods of analogues, firstly introduced by Lorenz, to assess future evolution of countries.

  15. The heterogeneous dynamics of economic complexity.

    PubMed

    Cristelli, Matthieu; Tacchella, Andrea; Pietronero, Luciano

    2015-01-01

    What will be the growth of the Gross Domestic Product (GDP) or the competitiveness of China, United States, and Vietnam in the next 3, 5 or 10 years? Despite this kind of questions has a large societal impact and an extreme value for economic policy making, providing a scientific basis for economic predictability is still a very challenging problem. Recent results of a new branch--Economic Complexity--have set the basis for a framework to approach such a challenge and to provide new perspectives to cast economic prediction into the conceptual scheme of forecasting the evolution of a dynamical system as in the case of weather dynamics. We argue that a recently introduced non-monetary metrics for country competitiveness (fitness) allows for quantifying the hidden growth potential of countries by the means of the comparison of this measure for intangible assets with monetary figures, such as GDP per capita. This comparison defines the fitness-income plane where we observe that country dynamics presents strongly heterogeneous patterns of evolution. The flow in some zones is found to be laminar while in others a chaotic behavior is instead observed. These two regimes correspond to very different predictability features for the evolution of countries: in the former regime, we find strong predictable pattern while the latter scenario exhibits a very low predictability. In such a framework, regressions, the usual tool used in economics, are no more the appropriate strategy to deal with such a heterogeneous scenario and new concepts, borrowed from dynamical systems theory, are mandatory. We therefore propose a data-driven method--the selective predictability scheme--in which we adopt a strategy similar to the methods of analogues, firstly introduced by Lorenz, to assess future evolution of countries. PMID:25671312

  16. Complex mode dynamics of coupled wave oscillators.

    PubMed

    Alexander, T J; Yan, D; Kevrekidis, P G

    2013-12-01

    We explore how nonlinear coherent waves localized in a few wells of a periodic potential can act analogously to a chain of coupled oscillators. We identify the small-amplitude oscillation modes of these "coupled wave oscillators" and find that they can be extended into the large amplitude regime, where some "ring" for long times. We also reveal the appearance of complex behavior such as the breakdown of Josephson-like oscillations, the destabilization of fundamental oscillation modes, and the emergence of chaotic oscillations for large amplitude excitations. We show that the dynamics may be accurately described by a discrete model with nearest-neighbor coupling, in which the lattice oscillators bear an effective mass.

  17. Phase transitions in complex network dynamics

    NASA Astrophysics Data System (ADS)

    Squires, Shane

    Two phase transitions in complex networks are analyzed. The first of these is a percolation transition, in which the network develops a macroscopic connected component as edges are added to it. Recent work has shown that if edges are added "competitively" to an undirected network, the onset of percolation is abrupt or "explosive." A new variant of explosive percolation is introduced here for directed networks, whose critical behavior is explored using numerical simulations and finite-size scaling theory. This process is also characterized by a very rapid percolation transition, but it is not as sudden as in undirected networks. The second phase transition considered here is the emergence of instability in Boolean networks, a class of dynamical systems that are widely used to model gene regulation. The dynamics, which are determined by the network topology and a set of update rules, may be either stable or unstable, meaning that small perturbations to the state of the network either die out or grow to become macroscopic. Here, this transition is analytically mapped onto a well-studied percolation problem, which can be used to predict the average steady-state distance between perturbed and unperturbed trajectories. This map applies to specific Boolean networks with few restrictions on network topology, but can only be applied to two commonly used types of update rules. Finally, a method is introduced for predicting the stability of Boolean networks with a much broader range of update rules. The network is assumed to have a given complex topology, subject only to a locally tree-like condition, and the update rules may be correlated with topological features of the network. While past work has addressed the separate effects of topology and update rules on stability, the present results are the first widely applicable approach to studying how these effects interact. Numerical simulations agree with the theory and show that such correlations between topology and update

  18. Trajectory approach to the Schrödinger-Langevin equation with linear dissipation for ground states

    NASA Astrophysics Data System (ADS)

    Chou, Chia-Chun

    2015-11-01

    The Schrödinger-Langevin equation with linear dissipation is integrated by propagating an ensemble of Bohmian trajectories for the ground state of quantum systems. Substituting the wave function expressed in terms of the complex action into the Schrödinger-Langevin equation yields the complex quantum Hamilton-Jacobi equation with linear dissipation. We transform this equation into the arbitrary Lagrangian-Eulerian version with the grid velocity matching the flow velocity of the probability fluid. The resulting equation is simultaneously integrated with the trajectory guidance equation. Then, the computational method is applied to the harmonic oscillator, the double well potential, and the ground vibrational state of methyl iodide. The excellent agreement between the computational and the exact results for the ground state energies and wave functions shows that this study provides a synthetic trajectory approach to the ground state of quantum systems.

  19. Dynamics of swimming bacteria at complex interfaces

    NASA Astrophysics Data System (ADS)

    Lopez, Diego; Lauga, Eric

    2014-07-01

    Flagellated bacteria exploiting helical propulsion are known to swim along circular trajectories near surfaces. Fluid dynamics predicts this circular motion to be clockwise (CW) above a rigid surface (when viewed from inside the fluid) and counter-clockwise (CCW) below a free surface. Recent experimental investigations showed that complex physicochemical processes at the nearby surface could lead to a change in the direction of rotation, both at solid surfaces absorbing slip-inducing polymers and interfaces covered with surfactants. Motivated by these results, we use a far-field hydrodynamic model to predict the kinematics of swimming near three types of interfaces: clean fluid-fluid interface, slipping rigid wall, and a fluid interface covered by incompressible surfactants. Representing the helical swimmer by a superposition of hydrodynamic singularities, we first show that in all cases the surfaces reorient the swimmer parallel to the surface and attract it, both of which are a consequence of the Stokes dipole component of the swimmer flow field. We then show that circular motion is induced by a higher-order singularity, namely, a rotlet dipole, and that its rotation direction (CW vs. CCW) is strongly affected by the boundary conditions at the interface and the bacteria shape. Our results suggest thus that the hydrodynamics of complex interfaces provide a mechanism to selectively stir bacteria.

  20. Numerical integration of the extended variable generalized Langevin equation with a positive Prony representable memory kernel.

    PubMed

    Baczewski, Andrew D; Bond, Stephen D

    2013-07-28

    Generalized Langevin dynamics (GLD) arise in the modeling of a number of systems, ranging from structured fluids that exhibit a viscoelastic mechanical response, to biological systems, and other media that exhibit anomalous diffusive phenomena. Molecular dynamics (MD) simulations that include GLD in conjunction with external and/or pairwise forces require the development of numerical integrators that are efficient, stable, and have known convergence properties. In this article, we derive a family of extended variable integrators for the Generalized Langevin equation with a positive Prony series memory kernel. Using stability and error analysis, we identify a superlative choice of parameters and implement the corresponding numerical algorithm in the LAMMPS MD software package. Salient features of the algorithm include exact conservation of the first and second moments of the equilibrium velocity distribution in some important cases, stable behavior in the limit of conventional Langevin dynamics, and the use of a convolution-free formalism that obviates the need for explicit storage of the time history of particle velocities. Capability is demonstrated with respect to accuracy in numerous canonical examples, stability in certain limits, and an exemplary application in which the effect of a harmonic confining potential is mapped onto a memory kernel.

  1. Numerical integration of the extended variable generalized Langevin equation with a positive Prony representable memory kernel

    NASA Astrophysics Data System (ADS)

    Baczewski, Andrew D.; Bond, Stephen D.

    2013-07-01

    Generalized Langevin dynamics (GLD) arise in the modeling of a number of systems, ranging from structured fluids that exhibit a viscoelastic mechanical response, to biological systems, and other media that exhibit anomalous diffusive phenomena. Molecular dynamics (MD) simulations that include GLD in conjunction with external and/or pairwise forces require the development of numerical integrators that are efficient, stable, and have known convergence properties. In this article, we derive a family of extended variable integrators for the Generalized Langevin equation with a positive Prony series memory kernel. Using stability and error analysis, we identify a superlative choice of parameters and implement the corresponding numerical algorithm in the LAMMPS MD software package. Salient features of the algorithm include exact conservation of the first and second moments of the equilibrium velocity distribution in some important cases, stable behavior in the limit of conventional Langevin dynamics, and the use of a convolution-free formalism that obviates the need for explicit storage of the time history of particle velocities. Capability is demonstrated with respect to accuracy in numerous canonical examples, stability in certain limits, and an exemplary application in which the effect of a harmonic confining potential is mapped onto a memory kernel.

  2. Dynamic interactions of proteins in complex networks

    SciTech Connect

    Appella, E.; Anderson, C.

    2009-10-01

    Recent advances in techniques such as NMR and EPR spectroscopy have enabled the elucidation of how proteins undergo structural changes to act in concert in complex networks. The three minireviews in this series highlight current findings and the capabilities of new methodologies for unraveling the dynamic changes controlling diverse cellular functions. They represent a sampling of the cutting-edge research presented at the 17th Meeting of Methods in Protein Structure Analysis, MPSA2008, in Sapporo, Japan, 26-29 August, 2008 (http://www.iapsap.bnl.gov). The first minireview, by Christensen and Klevit, reports on a structure-based yeast two-hybrid method for identifying E2 ubiquitin-conjugating enzymes that interact with the E3 BRCA1/BARD1 heterodimer ligase to generate either mono- or polyubiquitinated products. This method demonstrated for the first time that the BRCA1/BARD1 E3 can interact with 10 different E2 enzymes. Interestingly, the interaction with multiple E2 enzymes displayed unique ubiquitin-transfer properties, a feature expected to be common among other RING and U-box E3s. Further characterization of new E3 ligases and the E2 enzymes that interact with them will greatly enhance our understanding of ubiquitin transfer and facilitate studies of roles of ubiquitin and ubiquitin-like proteins in protein processing and trafficking. Stein et al., in the second minireview, describe recent progress in defining the binding specificity of different peptide-binding domains. The authors clearly point out that transient peptide interactions mediated by both post-translational modifications and disordered regions ensure a high level of specificity. They postulate that a regulatory code may dictate the number of combinations of domains and post-translational modifications needed to achieve the required level of interaction specificity. Moreover, recognition alone is not enough to obtain a stable complex, especially in a complex cellular environment. Increasing

  3. Guiding locomotion in complex, dynamic environments

    PubMed Central

    Fajen, Brett R.

    2013-01-01

    Locomotion in complex, dynamic environments is an integral part of many daily activities, including walking in crowded spaces, driving on busy roadways, and playing sports. Many of the tasks that humans perform in such environments involve interactions with moving objects—that is, they require people to coordinate their own movement with the movements of other objects. A widely adopted framework for research on the detection, avoidance, and interception of moving objects is the bearing angle model, according to which observers move so as to keep the bearing angle of the object constant for interception and varying for obstacle avoidance. The bearing angle model offers a simple, parsimonious account of visual control but has several significant limitations and does not easily scale up to more complex tasks. In this paper, I introduce an alternative account of how humans choose actions and guide locomotion in the presence of moving objects. I show how the new approach addresses the limitations of the bearing angle model and accounts for a variety of behaviors involving moving objects, including (1) choosing whether to pass in front of or behind a moving obstacle, (2) perceiving whether a gap between a pair of moving obstacles is passable, (3) avoiding a collision while passing through single or multiple lanes of traffic, (4) coordinating speed and direction of locomotion during interception, (5) simultaneously intercepting a moving target while avoiding a stationary or moving obstacle, and (6) knowing whether to abandon the chase of a moving target. I also summarize data from recent studies that support the new approach. PMID:23885238

  4. Guiding locomotion in complex, dynamic environments.

    PubMed

    Fajen, Brett R

    2013-01-01

    Locomotion in complex, dynamic environments is an integral part of many daily activities, including walking in crowded spaces, driving on busy roadways, and playing sports. Many of the tasks that humans perform in such environments involve interactions with moving objects-that is, they require people to coordinate their own movement with the movements of other objects. A widely adopted framework for research on the detection, avoidance, and interception of moving objects is the bearing angle model, according to which observers move so as to keep the bearing angle of the object constant for interception and varying for obstacle avoidance. The bearing angle model offers a simple, parsimonious account of visual control but has several significant limitations and does not easily scale up to more complex tasks. In this paper, I introduce an alternative account of how humans choose actions and guide locomotion in the presence of moving objects. I show how the new approach addresses the limitations of the bearing angle model and accounts for a variety of behaviors involving moving objects, including (1) choosing whether to pass in front of or behind a moving obstacle, (2) perceiving whether a gap between a pair of moving obstacles is passable, (3) avoiding a collision while passing through single or multiple lanes of traffic, (4) coordinating speed and direction of locomotion during interception, (5) simultaneously intercepting a moving target while avoiding a stationary or moving obstacle, and (6) knowing whether to abandon the chase of a moving target. I also summarize data from recent studies that support the new approach. PMID:23885238

  5. Perspective: Dynamics of receptor tyrosine kinase signaling complexes.

    PubMed

    Mayer, Bruce J

    2012-08-14

    Textbook descriptions of signal transduction complexes provide a static snapshot view of highly dynamic events. Despite enormous strides in identifying the key components of signaling complexes and the underlying mechanisms of signal transduction, our understanding of the dynamic behavior of these complexes has lagged behind. Using the example of receptor tyrosine kinases, this perspective takes a fresh look at the dynamics of the system and their potential impact on signal processing. PMID:22584051

  6. Gaussian approximations for stochastic systems with delay: Chemical Langevin equation and application to a Brusselator system

    NASA Astrophysics Data System (ADS)

    Brett, Tobias; Galla, Tobias

    2014-03-01

    We present a heuristic derivation of Gaussian approximations for stochastic chemical reaction systems with distributed delay. In particular, we derive the corresponding chemical Langevin equation. Due to the non-Markovian character of the underlying dynamics, these equations are integro-differential equations, and the noise in the Gaussian approximation is coloured. Following on from the chemical Langevin equation, a further reduction leads to the linear-noise approximation. We apply the formalism to a delay variant of the celebrated Brusselator model, and show how it can be used to characterise noise-driven quasi-cycles, as well as noise-triggered spiking. We find surprisingly intricate dependence of the typical frequency of quasi-cycles on the delay period.

  7. Gaussian approximations for stochastic systems with delay: chemical Langevin equation and application to a Brusselator system.

    PubMed

    Brett, Tobias; Galla, Tobias

    2014-03-28

    We present a heuristic derivation of Gaussian approximations for stochastic chemical reaction systems with distributed delay. In particular, we derive the corresponding chemical Langevin equation. Due to the non-Markovian character of the underlying dynamics, these equations are integro-differential equations, and the noise in the Gaussian approximation is coloured. Following on from the chemical Langevin equation, a further reduction leads to the linear-noise approximation. We apply the formalism to a delay variant of the celebrated Brusselator model, and show how it can be used to characterise noise-driven quasi-cycles, as well as noise-triggered spiking. We find surprisingly intricate dependence of the typical frequency of quasi-cycles on the delay period. PMID:24697429

  8. Gaussian approximations for stochastic systems with delay: Chemical Langevin equation and application to a Brusselator system

    SciTech Connect

    Brett, Tobias Galla, Tobias

    2014-03-28

    We present a heuristic derivation of Gaussian approximations for stochastic chemical reaction systems with distributed delay. In particular, we derive the corresponding chemical Langevin equation. Due to the non-Markovian character of the underlying dynamics, these equations are integro-differential equations, and the noise in the Gaussian approximation is coloured. Following on from the chemical Langevin equation, a further reduction leads to the linear-noise approximation. We apply the formalism to a delay variant of the celebrated Brusselator model, and show how it can be used to characterise noise-driven quasi-cycles, as well as noise-triggered spiking. We find surprisingly intricate dependence of the typical frequency of quasi-cycles on the delay period.

  9. Gaussian approximations for stochastic systems with delay: chemical Langevin equation and application to a Brusselator system.

    PubMed

    Brett, Tobias; Galla, Tobias

    2014-03-28

    We present a heuristic derivation of Gaussian approximations for stochastic chemical reaction systems with distributed delay. In particular, we derive the corresponding chemical Langevin equation. Due to the non-Markovian character of the underlying dynamics, these equations are integro-differential equations, and the noise in the Gaussian approximation is coloured. Following on from the chemical Langevin equation, a further reduction leads to the linear-noise approximation. We apply the formalism to a delay variant of the celebrated Brusselator model, and show how it can be used to characterise noise-driven quasi-cycles, as well as noise-triggered spiking. We find surprisingly intricate dependence of the typical frequency of quasi-cycles on the delay period.

  10. A path-integral Langevin equation treatment of low-temperature doped helium clusters

    NASA Astrophysics Data System (ADS)

    Ing, Christopher; Hinsen, Konrad; Yang, Jing; Zeng, Toby; Li, Hui; Roy, Pierre-Nicholas

    2012-06-01

    We present an implementation of path integral molecular dynamics for sampling low temperature properties of doped helium clusters using Langevin dynamics. The robustness of the path integral Langevin equation and white-noise Langevin equation [M. Ceriotti, M. Parrinello, T. E. Markland, and D. E. Manolopoulos, J. Chem. Phys. 133, 124104 (2010)], 10.1063/1.3489925 sampling methods are considered for those weakly bound systems with comparison to path integral Monte Carlo (PIMC) in terms of efficiency and accuracy. Using these techniques, convergence studies are performed to confirm the systematic error reduction introduced by increasing the number of discretization steps of the path integral. We comment on the structural and energetic evolution of HeN-CO2 clusters from N = 1 to 20. To quantify the importance of both rotations and exchange in our simulations, we present a chemical potential and calculated band origin shifts as a function of cluster size utilizing PIMC sampling that includes these effects. This work also serves to showcase the implementation of path integral simulation techniques within the molecular modelling toolkit [K. Hinsen, J. Comp. Chem. 21, 79 (2000)], 10.1002/(SICI)1096-987X(20000130)21:2<79::AID-JCC1>3.0.CO;2-B, an open-source molecular simulation package.

  11. The dynamic nature of the Golgi complex

    PubMed Central

    1989-01-01

    The intracellular transport of newly synthesized G protein of vesicular stomatitis virus is blocked at 20 degrees C and this spanning membrane glycoprotein accumulates in the last Golgi compartment, the trans Golgi- network (TGN). Previous morphological evidence suggested that the TGN enlarged significantly under this condition. In the present study we have used stereological procedures to estimate the volume and surface area of the Golgi stack and the TGN of baby hamster kidney cells under different conditions. The results indicate that the increase in the size of the TGN at 20 degrees C is accompanied by a significant decrease in the surface area and volume of the preceding Golgi compartments. A similar effect is also seen in uninfected cells at 20 degrees C, as well as during normal (37 degrees C) infection with Semliki Forest virus. In the latter case, however, the decrease in the size of the Golgi stack and the increase in that of the TGN is not accompanied by inhibition of transport from the Golgi complex to the cell surface. The results indicate that the Golgi stack and the TGN are dynamic and interrelated structures that are capable of rapid alteration in total surface area in response to changes in the rates of membrane transport. PMID:2537312

  12. Modeling Structural Dynamics of Biomolecular Complexes by Coarse-Grained Molecular Simulations.

    PubMed

    Takada, Shoji; Kanada, Ryo; Tan, Cheng; Terakawa, Tsuyoshi; Li, Wenfei; Kenzaki, Hiroo

    2015-12-15

    Due to hierarchic nature of biomolecular systems, their computational modeling calls for multiscale approaches, in which coarse-grained (CG) simulations are used to address long-time dynamics of large systems. Here, we review recent developments and applications of CG modeling methods, focusing on our methods primarily for proteins, DNA, and their complexes. These methods have been implemented in the CG biomolecular simulator, CafeMol. Our CG model has resolution such that ∼10 non-hydrogen atoms are grouped into one CG particle on average. For proteins, each amino acid is represented by one CG particle. For DNA, one nucleotide is simplified by three CG particles, representing sugar, phosphate, and base. The protein modeling is based on the idea that proteins have a globally funnel-like energy landscape, which is encoded in the structure-based potential energy function. We first describe two representative minimal models of proteins, called the elastic network model and the classic Go̅ model. We then present a more elaborate protein model, which extends the minimal model to incorporate sequence and context dependent local flexibility and nonlocal contacts. For DNA, we describe a model developed by de Pablo's group that was tuned to well reproduce sequence-dependent structural and thermodynamic experimental data for single- and double-stranded DNAs. Protein-DNA interactions are modeled either by the structure-based term for specific cases or by electrostatic and excluded volume terms for nonspecific cases. We also discuss the time scale mapping in CG molecular dynamics simulations. While the apparent single time step of our CGMD is about 10 times larger than that in the fully atomistic molecular dynamics for small-scale dynamics, large-scale motions can be further accelerated by two-orders of magnitude with the use of CG model and a low friction constant in Langevin dynamics. Next, we present four examples of applications. First, the classic Go̅ model was used to

  13. Boltzmann-Langevin theory of Coulomb drag

    NASA Astrophysics Data System (ADS)

    Chen, W.; Andreev, A. V.; Levchenko, A.

    2015-06-01

    We develop a Boltzmann-Langevin description of the Coulomb drag effect in clean double-layer systems with large interlayer separation d as compared to the average interelectron distance λF. Coulomb drag arises from density fluctuations with spatial scales of order d . At low temperatures, their characteristic frequencies exceed the intralayer equilibration rate of the electron liquid, and Coulomb drag may be treated in the collisionless approximation. As temperature is raised, the electron mean free path becomes short due to electron-electron scattering. This leads to local equilibration of electron liquid, and consequently drag is determined by hydrodynamic density modes. Our theory applies to both the collisionless and the hydrodynamic regimes, and it enables us to describe the crossover between them. We find that drag resistivity exhibits a nonmonotonic temperature dependence with multiple crossovers at distinct energy scales. At the lowest temperatures, Coulomb drag is dominated by the particle-hole continuum, whereas at higher temperatures of the collision-dominated regime it is governed by the plasmon modes. We observe that fast intralayer equilibration mediated by electron-electron collisions ultimately renders a stronger drag effect.

  14. Fractional Langevin model of gait variability

    PubMed Central

    West, Bruce J; Latka, Miroslaw

    2005-01-01

    The stride interval in healthy human gait fluctuates from step to step in a random manner and scaling of the interstride interval time series motivated previous investigators to conclude that this time series is fractal. Early studies suggested that gait is a monofractal process, but more recent work indicates the time series is weakly multifractal. Herein we present additional evidence for the weakly multifractal nature of gait. We use the stride interval time series obtained from ten healthy adults walking at a normal relaxed pace for approximately fifteen minutes each as our data set. A fractional Langevin equation is constructed to model the underlying motor control system in which the order of the fractional derivative is itself a stochastic quantity. Using this model we find the fractal dimension for each of the ten data sets to be in agreement with earlier analyses. However, with the present model we are able to draw additional conclusions regarding the nature of the control system guiding walking. The analysis presented herein suggests that the observed scaling in interstride interval data may not be due to long-term memory alone, but may, in fact, be due partly to the statistics. PMID:16076394

  15. Multiple Cancer Cell Population Dynamics in a Complex Ecology

    NASA Astrophysics Data System (ADS)

    Lin, Ke-Chih; Targa, Gonzalo; Pienta, Kenneth; Sturm, James; Austin, Robert

    We have developed a technology for study of complex ecology cancer population dynamics. The technology includes complex drug gradients, full bright field/dark field/fluorescence imaging of areas of several square millimeters and thin gas-permable membranes which allow single cell extraction and analysis. We will present results of studies of prostate cancer cell dynamics.

  16. Variable time-stepping in the pathwise numerical solution of the chemical Langevin equation.

    PubMed

    Ilie, Silvana

    2012-12-21

    Stochastic modeling is essential for an accurate description of the biochemical network dynamics at the level of a single cell. Biochemically reacting systems often evolve on multiple time-scales, thus their stochastic mathematical models manifest stiffness. Stochastic models which, in addition, are stiff and computationally very challenging, therefore the need for developing effective and accurate numerical methods for approximating their solution. An important stochastic model of well-stirred biochemical systems is the chemical Langevin Equation. The chemical Langevin equation is a system of stochastic differential equation with multidimensional non-commutative noise. This model is valid in the regime of large molecular populations, far from the thermodynamic limit. In this paper, we propose a variable time-stepping strategy for the numerical solution of a general chemical Langevin equation, which applies for any level of randomness in the system. Our variable stepsize method allows arbitrary values of the time-step. Numerical results on several models arising in applications show significant improvement in accuracy and efficiency of the proposed adaptive scheme over the existing methods, the strategies based on halving/doubling of the stepsize and the fixed step-size ones.

  17. Hamiltonian dynamics for complex food webs.

    PubMed

    Kozlov, Vladimir; Vakulenko, Sergey; Wennergren, Uno

    2016-03-01

    We investigate stability and dynamics of large ecological networks by introducing classical methods of dynamical system theory from physics, including Hamiltonian and averaging methods. Our analysis exploits the topological structure of the network, namely the existence of strongly connected nodes (hubs) in the networks. We reveal new relations between topology, interaction structure, and network dynamics. We describe mechanisms of catastrophic phenomena leading to sharp changes of dynamics and hence completely altering the ecosystem. We also show how these phenomena depend on the structure of interaction between species. We can conclude that a Hamiltonian structure of biological interactions leads to stability and large biodiversity. PMID:27078396

  18. Hamiltonian dynamics for complex food webs.

    PubMed

    Kozlov, Vladimir; Vakulenko, Sergey; Wennergren, Uno

    2016-03-01

    We investigate stability and dynamics of large ecological networks by introducing classical methods of dynamical system theory from physics, including Hamiltonian and averaging methods. Our analysis exploits the topological structure of the network, namely the existence of strongly connected nodes (hubs) in the networks. We reveal new relations between topology, interaction structure, and network dynamics. We describe mechanisms of catastrophic phenomena leading to sharp changes of dynamics and hence completely altering the ecosystem. We also show how these phenomena depend on the structure of interaction between species. We can conclude that a Hamiltonian structure of biological interactions leads to stability and large biodiversity.

  19. Hamiltonian dynamics for complex food webs

    NASA Astrophysics Data System (ADS)

    Kozlov, Vladimir; Vakulenko, Sergey; Wennergren, Uno

    2016-03-01

    We investigate stability and dynamics of large ecological networks by introducing classical methods of dynamical system theory from physics, including Hamiltonian and averaging methods. Our analysis exploits the topological structure of the network, namely the existence of strongly connected nodes (hubs) in the networks. We reveal new relations between topology, interaction structure, and network dynamics. We describe mechanisms of catastrophic phenomena leading to sharp changes of dynamics and hence completely altering the ecosystem. We also show how these phenomena depend on the structure of interaction between species. We can conclude that a Hamiltonian structure of biological interactions leads to stability and large biodiversity.

  20. Description of quantum noise by a Langevin equation

    NASA Technical Reports Server (NTRS)

    Metiu, H.; Schon, G.

    1984-01-01

    General features of the quantum noise problem expressed as the equations of motion for a particle coupled to a set of oscillators are investigated analytically. Account is taken of the properties of the companion oscillators by formulating quantum statistical correlation Langevin equations (QSLE). The frequency of the oscillators is then retained as a natural cut-off for the quantum noise. The QSLE is further extended to encompass the particle trajectory and is bounded by initial and final states of the oscillator. The states are expressed as the probability of existence at the moment of particle collision that takes the oscillator into a final state. Two noise sources then exist: a statistical uncertainty of the initial state and the quantum dynamical uncertainty associated with a transition from the initial to final state. Feynman's path-integral formulation is used to characterize the functional of the particle trajectory, which slows the particle. It is shown that the energy loss may be attributed to friction, which satisfies energy conservation laws.

  1. Stochastic processes with distributed delays: chemical Langevin equation and linear-noise approximation.

    PubMed

    Brett, Tobias; Galla, Tobias

    2013-06-21

    We develop a systematic approach to the linear-noise approximation for stochastic reaction systems with distributed delays. Unlike most existing work our formalism does not rely on a master equation; instead it is based upon a dynamical generating functional describing the probability measure over all possible paths of the dynamics. We derive general expressions for the chemical Langevin equation for a broad class of non-Markovian systems with distributed delay. Exemplars of a model of gene regulation with delayed autoinhibition and a model of epidemic spread with delayed recovery provide evidence of the applicability of our results.

  2. Interacting Single-File System: Fractional Langevin Formulation Versus Diffusion-Noise Approach

    NASA Astrophysics Data System (ADS)

    Taloni, Alessandro; Marchesoni, Fabio

    2014-07-01

    We review the latest advances in the analytical modelling of single file diffusion. We focus first on the derivation of the fractional Langevin equation that describes the motion of a tagged file particle. We then propose an alternative derivation of the very same stochastic equation by starting from the diffusion-noise formalism for the time evolution of the file density. Special Issue Comments: This article presents mathematical formulations and results on the dynamics in files with applied potential, yet also general files. This article is connected to the Special Issue articles about the zig zag phenomenon,72 advanced statistical properties in single file dynamics,73 and expanding files.74

  3. Imaging complex nutrient dynamics in mycelial networks.

    PubMed

    Fricker, M D; Lee, J A; Bebber, D P; Tlalka, M; Hynes, J; Darrah, P R; Watkinson, S C; Boddy, L

    2008-08-01

    Transport networks are vital components of multi-cellular organisms, distributing nutrients and removing waste products. Animal cardiovascular and respiratory systems, and plant vasculature, are branching trees whose architecture is thought to determine universal scaling laws in these organisms. In contrast, the transport systems of many multi-cellular fungi do not fit into this conceptual framework, as they have evolved to explore a patchy environment in search of new resources, rather than ramify through a three-dimensional organism. These fungi grow as a foraging mycelium, formed by the branching and fusion of threadlike hyphae, that gives rise to a complex network. To function efficiently, the mycelial network must both transport nutrients between spatially separated source and sink regions and also maintain its integrity in the face of continuous attack by mycophagous insects or random damage. Here we review the development of novel imaging approaches and software tools that we have used to characterise nutrient transport and network formation in foraging mycelia over a range of spatial scales. On a millimetre scale, we have used a combination of time-lapse confocal imaging and fluorescence recovery after photobleaching to quantify the rate of diffusive transport through the unique vacuole system in individual hyphae. These data then form the basis of a simulation model to predict the impact of such diffusion-based movement on a scale of several millimetres. On a centimetre scale, we have used novel photon-counting scintillation imaging techniques to visualize radiolabel movement in small microcosms. This approach has revealed novel N-transport phenomena, including rapid, preferential N-resource allocation to C-rich sinks, induction of simultaneous bi-directional transport, abrupt switching between different pre-existing transport routes, and a strong pulsatile component to transport in some species. Analysis of the pulsatile transport component using Fourier

  4. Exact series model of Langevin transducers with internal losses.

    PubMed

    Nishamol, P A; Ebenezer, D D

    2014-03-01

    An exact series method is presented to analyze classical Langevin transducers with arbitrary boundary conditions. The transducers consist of an axially polarized piezoelectric solid cylinder sandwiched between two elastic solid cylinders. All three cylinders are of the same diameter. The length to diameter ratio is arbitrary. Complex piezoelectric and elastic coefficients are used to model internal losses. Solutions to the exact linearized governing equations for each cylinder include four series. Each term in each series is an exact solution to the governing equations. Bessel and trigonometric functions that form complete and orthogonal sets in the radial and axial directions, respectively, are used in the series. Asymmetric transducers and boundary conditions are modeled by using axially symmetric and anti-symmetric sets of functions. All interface and boundary conditions are satisfied in a weighted-average sense. The computed input electrical admittance, displacement, and stress in transducers are presented in tables and figures, and are in very good agreement with those obtained using atila-a finite element package for the analysis of sonar transducers. For all the transducers considered in the analysis, the maximum difference between the first three resonance frequencies calculated using the present method and atila is less than 0.03%.

  5. Dynamics-based scalability of complex networks.

    PubMed

    Huang, Liang; Lai, Ying-Cheng; Gatenby, Robert A

    2008-10-01

    We address the fundamental issue of network scalability in terms of dynamics and topology. In particular, we consider different network topologies and investigate, for every given topology, the dependence of certain dynamical properties on the network size. By focusing on network synchronizability, we find both analytically and numerically that globally coupled networks and random networks are scalable, but locally coupled regular networks are not. Scale-free networks are scalable for certain types of node dynamics. We expect our findings to provide insights into the ubiquity and workings of networks arising in nature and to be potentially useful for designing technological networks as well. PMID:18999478

  6. Exponential rise of dynamical complexity in quantum computing through projections.

    PubMed

    Burgarth, Daniel Klaus; Facchi, Paolo; Giovannetti, Vittorio; Nakazato, Hiromichi; Pascazio, Saverio; Yuasa, Kazuya

    2014-10-10

    The ability of quantum systems to host exponentially complex dynamics has the potential to revolutionize science and technology. Therefore, much effort has been devoted to developing of protocols for computation, communication and metrology, which exploit this scaling, despite formidable technical difficulties. Here we show that the mere frequent observation of a small part of a quantum system can turn its dynamics from a very simple one into an exponentially complex one, capable of universal quantum computation. After discussing examples, we go on to show that this effect is generally to be expected: almost any quantum dynamics becomes universal once 'observed' as outlined above. Conversely, we show that any complex quantum dynamics can be 'purified' into a simpler one in larger dimensions. We conclude by demonstrating that even local noise can lead to an exponentially complex dynamics.

  7. Emergence of dynamical complexity related to human heart rate variability

    NASA Astrophysics Data System (ADS)

    Chang, Mei-Chu; Peng, C.-K.; Stanley, H. Eugene

    2014-12-01

    We apply the refined composite multiscale entropy (MSE) method to a one-dimensional directed small-world network composed of nodes whose states are binary and whose dynamics obey the majority rule. We find that the resulting fluctuating signal becomes dynamically complex. This dynamical complexity is caused (i) by the presence of both short-range connections and long-range shortcuts and (ii) by how well the system can adapt to the noisy environment. By tuning the adaptability of the environment and the long-range shortcuts we can increase or decrease the dynamical complexity, thereby modeling trends found in the MSE of a healthy human heart rate in different physiological states. When the shortcut and adaptability values increase, the complexity in the system dynamics becomes uncorrelated.

  8. Exponential rise of dynamical complexity in quantum computing through projections

    PubMed Central

    Burgarth, Daniel Klaus; Facchi, Paolo; Giovannetti, Vittorio; Nakazato, Hiromichi; Pascazio, Saverio; Yuasa, Kazuya

    2014-01-01

    The ability of quantum systems to host exponentially complex dynamics has the potential to revolutionize science and technology. Therefore, much effort has been devoted to developing of protocols for computation, communication and metrology, which exploit this scaling, despite formidable technical difficulties. Here we show that the mere frequent observation of a small part of a quantum system can turn its dynamics from a very simple one into an exponentially complex one, capable of universal quantum computation. After discussing examples, we go on to show that this effect is generally to be expected: almost any quantum dynamics becomes universal once ‘observed’ as outlined above. Conversely, we show that any complex quantum dynamics can be ‘purified’ into a simpler one in larger dimensions. We conclude by demonstrating that even local noise can lead to an exponentially complex dynamics. PMID:25300692

  9. Two critical issues in Langevin simulation of gas flows

    SciTech Connect

    Zhang, Jun; Fan, Jing

    2014-12-09

    A stochastic algorithm based on the Langevin equation has been recently proposed to simulate rarefied gas flows. Compared with the direct simulation Monte Carlo (DSMC) method, the Langevin method is more efficient in simulating small Knudsen number flows. While it is well-known that the cell sizes and time steps should be smaller than the mean free path and the mean collision time, respectively, in DSMC simulations, the Langevin equation uses a drift term and a diffusion term to describe molecule movements, so no direct molecular collisions have to be modeled. This enables the Langevin simulation to proceed with a much larger time step than that in the DSMC method. Two critical issues in Langevin simulation are addressed in this paper. The first issue is how to reproduce the transport properties as that described by kinetic theory. Transport coefficients predicted by Langevin equation are obtained by using Green-Kubo formulae. The second issue is numerical scheme with boundary conditions. We present two schemes corresponding to small time step and large time step, respectively. For small time step, the scheme is similar to DSMC method as the update of positions and velocities are uncoupled; for large time step, we present an analytical solution of the hitting time, which is the crucial factor for accurate simulation. Velocity-Couette flow, thermal-Couette flow, Rayleigh-Bénard flow and wall-confined problem are simulated by using these two schemes. Our study shows that Langevin simulation is a promising tool to investigate small Knudsen number flows.

  10. Discovering independent parameters in complex dynamical systems

    PubMed Central

    Lainscsek, Claudia; Weyhenmeyer, Jonathan; Sejnowski, Terrence J.; Letellier, Christophe

    2015-01-01

    The transformation of a nonlinear dynamical system into a standard form by using one of its variables and its successive derivatives can be used to identify the relationships that may exist between the parameters of the original system such as the subset of the parameter space over which the dynamics is left invariant. We show how the size of the attractor or the time scale (the pseudo-period) can be varied without affecting the underlying dynamics. This is demonstrated for the Rössler and the Lorenz systems. We also consider the case when two Rössler systems are unidirectionally coupled and when a Lorenz system is driven by a Rössler system. In both cases, the dynamics of the coupled system is affected. PMID:25983399

  11. Dynamical complexity changes during two forms of meditation

    NASA Astrophysics Data System (ADS)

    Li, Jin; Hu, Jing; Zhang, Yinhong; Zhang, Xiaofeng

    2011-06-01

    Detection of dynamical complexity changes in natural and man-made systems has deep scientific and practical meaning. We use the base-scale entropy method to analyze dynamical complexity changes for heart rate variability (HRV) series during specific traditional forms of Chinese Chi and Kundalini Yoga meditation techniques in healthy young adults. The results show that dynamical complexity decreases in meditation states for two forms of meditation. Meanwhile, we detected changes in probability distribution of m-words during meditation and explained this changes using probability distribution of sine function. The base-scale entropy method may be used on a wider range of physiologic signals.

  12. Dynamical Baryogenesis in Complex Hybrid Inflation

    SciTech Connect

    Delepine, David; Martinez, Carlos; Urena-Lopez, L. Arturo

    2008-07-02

    We propose a hybrid inflation model with a complex waterfall field which contains an interaction term that breaks the U (1) global symmetry associated to the waterfall field charge. We show that the asymmetric evolution of the real and imaginary parts of the complex field during the phase transition at the end of inflation translates into a charge asymmetry. The latter strongly depends on the vev of the waterfall field, which is well constrained by diverse cosmological observations.

  13. Complex dynamics of cellular automata rule 119

    NASA Astrophysics Data System (ADS)

    Chen, Fang-Fang; Chen, Fang-Yue

    2009-03-01

    In this paper, the dynamical behaviors of cellular automata rule 119 are studied from the viewpoint of symbolic dynamics in the bi-infinite symbolic sequence space Σ2. It is shown that there exists one Bernoulli-measure global attractor of rule 119, which is also the nonwandering set of the rule. Moreover, it is demonstrated that rule 119 is topologically mixing on the global attractor and possesses the positive topological entropy. Therefore, rule 119 is chaotic in the sense of both Li-Yorke and Devaney on the global attractor. It is interesting that rule 119, a member of Wolfram’s class II which was said to be simple as periodic before, actually possesses a chaotic global attractor in Σ2. Finally, it is noted that the method presented in this work is also applicable to studying the dynamics of other rules, especially the 112 Bernoulli-shift rules therein.

  14. Targeting the dynamics of complex networks

    PubMed Central

    Gutiérrez, Ricardo; Sendiña-Nadal, Irene; Zanin, Massimiliano; Papo, David; Boccaletti, Stefano

    2012-01-01

    We report on a generic procedure to steer (target) a network's dynamics towards a given, desired evolution. The problem is here tackled through a Master Stability Function approach, assessing the stability of the aimed dynamics, and through a selection of nodes to be targeted. We show that the degree of a node is a crucial element in this selection process, and that the targeting mechanism is most effective in heterogeneous scale-free architectures. This makes the proposed approach applicable to the large majority of natural and man-made networked systems. PMID:22563525

  15. Targeting the dynamics of complex networks

    NASA Astrophysics Data System (ADS)

    Gutiérrez, Ricardo; Sendiña-Nadal, Irene; Zanin, Massimiliano; Papo, David; Boccaletti, Stefano

    2012-05-01

    We report on a generic procedure to steer (target) a network's dynamics towards a given, desired evolution. The problem is here tackled through a Master Stability Function approach, assessing the stability of the aimed dynamics, and through a selection of nodes to be targeted. We show that the degree of a node is a crucial element in this selection process, and that the targeting mechanism is most effective in heterogeneous scale-free architectures. This makes the proposed approach applicable to the large majority of natural and man-made networked systems.

  16. Nonlinear Dynamics of the Perceived Pitch of Complex Sounds

    NASA Astrophysics Data System (ADS)

    Cartwright, Julyan H. E.; González, Diego L.; Piro, Oreste

    1999-06-01

    We apply results from nonlinear dynamics to an old problem in acoustical physics: the mechanism of the perception of the pitch of sounds, especially the sounds known as complex tones that are important for music and speech intelligibility.

  17. Mapping complex traits as a dynamic system

    NASA Astrophysics Data System (ADS)

    Sun, Lidan; Wu, Rongling

    2015-06-01

    Despite increasing emphasis on the genetic study of quantitative traits, we are still far from being able to chart a clear picture of their genetic architecture, given an inherent complexity involved in trait formation. A competing theory for studying such complex traits has emerged by viewing their phenotypic formation as a "system" in which a high-dimensional group of interconnected components act and interact across different levels of biological organization from molecules through cells to whole organisms. This system is initiated by a machinery of DNA sequences that regulate a cascade of biochemical pathways to synthesize endophenotypes and further assemble these endophenotypes toward the end-point phenotype in virtue of various developmental changes. This review focuses on a conceptual framework for genetic mapping of complex traits by which to delineate the underlying components, interactions and mechanisms that govern the system according to biological principles and understand how these components function synergistically under the control of quantitative trait loci (QTLs) to comprise a unified whole. This framework is built by a system of differential equations that quantifies how alterations of different components lead to the global change of trait development and function, and provides a quantitative and testable platform for assessing the multiscale interplay between QTLs and development. The method will enable geneticists to shed light on the genetic complexity of any biological system and predict, alter or engineer its physiological and pathological states.

  18. Sum rule for response function in nonequilibrium Langevin systems

    NASA Astrophysics Data System (ADS)

    Yuge, Tatsuro

    2010-11-01

    We derive general properties of the linear-response functions of nonequilibrium steady states in Langevin systems. These correspond to extension of the results which were recently found in Hamiltonian systems [A. Shimizu and T. Yuge, J. Phys. Soc. Jpn. 79, 013002 (2010)10.1143/JPSJ.79.013002]. We discuss one of the properties, the sum rule for the response function, in particular detail. We show that the sum rule for the response function of the velocity holds in the underdamped case, whereas it is violated in the overdamped case. This implies that the overdamped Langevin models should be used with great care. We also investigate the relation of the sum rule to an equality on the energy dissipation in nonequilibrium Langevin systems, which was derived by Harada and Sasa.

  19. Metapopulation dynamics in a complex ecological landscape

    NASA Astrophysics Data System (ADS)

    Colombo, E. H.; Anteneodo, C.

    2015-08-01

    We propose a general model to study the interplay between spatial dispersal and environment spatiotemporal fluctuations in metapopulation dynamics. An ecological landscape of favorable patches is generated like a Lévy dust, which allows to build a range of patterns, from dispersed to clustered ones. Locally, the dynamics is driven by a canonical model for the time evolution of the population density, consisting of a logistic expression plus multiplicative noises. Spatial coupling is introduced by means of two spreading mechanisms: diffusion and selective dispersal driven by patch suitability. We focus on the long-time population size as a function of habitat configurations, environment fluctuations, and coupling schemes. We obtain the conditions, that the spatial distribution of favorable patches and the coupling mechanisms must fulfill, to grant population survival. The fundamental phenomenon that we observe is the positive feedback between environment fluctuations and spatial spread preventing extinction.

  20. Metapopulation dynamics in a complex ecological landscape.

    PubMed

    Colombo, E H; Anteneodo, C

    2015-08-01

    We propose a general model to study the interplay between spatial dispersal and environment spatiotemporal fluctuations in metapopulation dynamics. An ecological landscape of favorable patches is generated like a Lévy dust, which allows to build a range of patterns, from dispersed to clustered ones. Locally, the dynamics is driven by a canonical model for the time evolution of the population density, consisting of a logistic expression plus multiplicative noises. Spatial coupling is introduced by means of two spreading mechanisms: diffusion and selective dispersal driven by patch suitability. We focus on the long-time population size as a function of habitat configurations, environment fluctuations, and coupling schemes. We obtain the conditions, that the spatial distribution of favorable patches and the coupling mechanisms must fulfill, to grant population survival. The fundamental phenomenon that we observe is the positive feedback between environment fluctuations and spatial spread preventing extinction. PMID:26382439

  1. Understanding the complexity of human gait dynamics

    NASA Astrophysics Data System (ADS)

    Scafetta, Nicola; Marchi, Damiano; West, Bruce J.

    2009-06-01

    Time series of human gait stride intervals exhibit fractal and multifractal properties under several conditions. Records from subjects walking at normal, slow, and fast pace speed are analyzed to determine changes in the fractal scalings as a function of the stress condition of the system. Records from subjects with different age from children to elderly and patients suffering from neurodegenerative disease are analyzed to determine changes in the fractal scalings as a function of the physical maturation or degeneration of the system. A supercentral pattern generator model is presented to simulate the above two properties that are typically found in dynamical network performance: that is, how a dynamical network responds to stress and to evolution.

  2. Understanding the complexity of human gait dynamics.

    PubMed

    Scafetta, Nicola; Marchi, Damiano; West, Bruce J

    2009-06-01

    Time series of human gait stride intervals exhibit fractal and multifractal properties under several conditions. Records from subjects walking at normal, slow, and fast pace speed are analyzed to determine changes in the fractal scalings as a function of the stress condition of the system. Records from subjects with different age from children to elderly and patients suffering from neurodegenerative disease are analyzed to determine changes in the fractal scalings as a function of the physical maturation or degeneration of the system. A supercentral pattern generator model is presented to simulate the above two properties that are typically found in dynamical network performance: that is, how a dynamical network responds to stress and to evolution. PMID:19566268

  3. Dust Cloud Dynamics in Complex Plasma Afterglow

    SciTech Connect

    Layden, B.; Samarian, A. A.; Vladimirov, S. V.; Coueedel, L.

    2008-09-07

    Experimental observations of dust cloud dynamics in a RF discharge afterglow are presented. Image analysis is used to extract information from videos taken of the plasma. Estimations of the mean confining electric field have been made for different experimental conditions using a model for the contraction of the dust cloud. Dust particle trajectories in the late afterglow evidence the co-existence of positively and negatively charged dust particles.

  4. The Heterogeneous Dynamics of Economic Complexity

    PubMed Central

    Cristelli, Matthieu; Tacchella, Andrea; Pietronero, Luciano

    2015-01-01

    What will be the growth of the Gross Domestic Product (GDP) or the competitiveness of China, United States, and Vietnam in the next 3, 5 or 10 years? Despite this kind of questions has a large societal impact and an extreme value for economic policy making, providing a scientific basis for economic predictability is still a very challenging problem. Recent results of a new branch—Economic Complexity—have set the basis for a framework to approach such a challenge and to provide new perspectives to cast economic prediction into the conceptual scheme of forecasting the evolution of a dynamical system as in the case of weather dynamics. We argue that a recently introduced non-monetary metrics for country competitiveness (fitness) allows for quantifying the hidden growth potential of countries by the means of the comparison of this measure for intangible assets with monetary figures, such as GDP per capita. This comparison defines the fitness-income plane where we observe that country dynamics presents strongly heterogeneous patterns of evolution. The flow in some zones is found to be laminar while in others a chaotic behavior is instead observed. These two regimes correspond to very different predictability features for the evolution of countries: in the former regime, we find strong predictable pattern while the latter scenario exhibits a very low predictability. In such a framework, regressions, the usual tool used in economics, are no more the appropriate strategy to deal with such a heterogeneous scenario and new concepts, borrowed from dynamical systems theory, are mandatory. We therefore propose a data-driven method—the selective predictability scheme—in which we adopt a strategy similar to the methods of analogues, firstly introduced by Lorenz, to assess future evolution of countries. PMID:25671312

  5. Complex dynamics in learning complicated games.

    PubMed

    Galla, Tobias; Farmer, J Doyne

    2013-01-22

    Game theory is the standard tool used to model strategic interactions in evolutionary biology and social science. Traditionally, game theory studies the equilibria of simple games. However, is this useful if the game is complicated, and if not, what is? We define a complicated game as one with many possible moves, and therefore many possible payoffs conditional on those moves. We investigate two-person games in which the players learn based on a type of reinforcement learning called experience-weighted attraction (EWA). By generating games at random, we characterize the learning dynamics under EWA and show that there are three clearly separated regimes: (i) convergence to a unique fixed point, (ii) a huge multiplicity of stable fixed points, and (iii) chaotic behavior. In case (iii), the dimension of the chaotic attractors can be very high, implying that the learning dynamics are effectively random. In the chaotic regime, the total payoffs fluctuate intermittently, showing bursts of rapid change punctuated by periods of quiescence, with heavy tails similar to what is observed in fluid turbulence and financial markets. Our results suggest that, at least for some learning algorithms, there is a large parameter regime for which complicated strategic interactions generate inherently unpredictable behavior that is best described in the language of dynamical systems theory.

  6. Managing Multiple Tasks in Complex, Dynamic Environments

    NASA Technical Reports Server (NTRS)

    Freed, Michael; Null, Cynthia H. (Technical Monitor)

    1998-01-01

    Sketchy planners are designed to achieve goals in realistically complex, time-pressured, and uncertain task environments. However, the ability to manage multiple, potentially interacting tasks in such environments requires extensions to the functionality these systems typically provide. This paper identifies a number of factors affecting how interacting tasks should be prioritized, interrupted, and resumed, and then describes a sketchy planner called APEX that takes account of these factors when managing multiple tasks.

  7. Langevin equation for systems with a preferred spatial direction

    NASA Astrophysics Data System (ADS)

    Belousov, Roman; Cohen, E. G. D.; Rondoni, Lamberto

    2016-09-01

    In this paper, we generalize the theory of Brownian motion and the Onsager-Machlup theory of fluctuations for spatially symmetric systems to equilibrium and nonequilibrium steady-state systems with a preferred spatial direction, due to an external force. To do this, we extend the Langevin equation to include a bias, which is introduced by an external force and alters the Gaussian structure of the system's fluctuations. In addition, by solving this extended equation, we provide a physical interpretation for the statistical properties of the fluctuations in these systems. Connections of the extended Langevin equation with the theory of active Brownian motion are discussed as well.

  8. Langevin equation model of dispersion in the convective boundary layer

    SciTech Connect

    Nasstrom, J S

    1998-08-01

    This dissertation presents the development and evaluation of a Lagrangian stochastic model of vertical dispersion of trace material in the convective boundary layer (CBL). This model is based on a Langevin equation of motion for a fluid particle, and assumes the fluid vertical velocity probability distribution is skewed and spatially homogeneous. This approach can account for the effect of large-scale, long-lived turbulent structures and skewed vertical velocity distributions found in the CBL. The form of the Langevin equation used has a linear (in velocity) deterministic acceleration and a skewed randomacceleration. For the case of homogeneous fluid velocity statistics, this ""linear-skewed" Langevin equation can be integrated explicitly, resulting in a relatively efficient numerical simulation method. It is shown that this approach is more efficient than an alternative using a "nonlinear-Gaussian" Langevin equation (with a nonlinear deterministic acceleration and a Gaussian random acceleration) assuming homogeneous turbulence, and much more efficient than alternative approaches using Langevin equation models assuming inhomogeneous turbulence. "Reflection" boundary conditions for selecting a new velocity for a particle that encounters a boundary at the top or bottom of the CBL were investigated. These include one method using the standard assumption that the magnitudes of the particle incident and reflected velocities are positively correlated, and two alternatives in which the magnitudes of these velocities are negatively correlated and uncorrelated. The constraint that spatial and velocity distributions of a well-mixed tracer must be the same as those of the fluid, was used to develop the Langevin equation models and the reflection boundary conditions. The two Langevin equation models and three reflection methods were successfully tested using cases for which exact, analytic statistical properties of particle velocity and position are known, including well

  9. Scaling of ballistic deposition from a Langevin equation.

    PubMed

    Haselwandter, Christoph A; Vvedensky, Dimitri D

    2006-04-01

    An exact lattice Langevin equation is derived for the ballistic deposition model of surface growth. The continuum limit of this equation is dominated by the Kardar-Parisi-Zhang (KPZ) equation at all length and time scales. For a one-dimensional substrate the solution of the exact lattice Langevin equation yields the KPZ scaling exponents without any extrapolation. For a two-dimensional substrate the scaling exponents are different from those found from computer simulations. This discrepancy is discussed in relation to analytic approaches to the KPZ equation in higher dimensions. PMID:16711773

  10. Complex, Dynamic Systems: A New Transdisciplinary Theme for Applied Linguistics?

    ERIC Educational Resources Information Center

    Larsen-Freeman, Diane

    2012-01-01

    In this plenary address, I suggest that Complexity Theory has the potential to contribute a transdisciplinary theme to applied linguistics. Transdisciplinary themes supersede disciplines and spur new kinds of creative activity (Halliday 2001 [1990]). Investigating complex systems requires researchers to pay attention to system dynamics. Since…

  11. Understanding Learner Agency as a Complex Dynamic System

    ERIC Educational Resources Information Center

    Mercer, Sarah

    2011-01-01

    This paper attempts to contribute to a fuller understanding of the nature of language learner agency by considering it as a complex dynamic system. The purpose of the study was to explore detailed situated data to examine to what extent it is feasible to view learner agency through the lens of complexity theory. Data were generated through a…

  12. Parameter Estimation in Epidemiology: from Simple to Complex Dynamics

    NASA Astrophysics Data System (ADS)

    Aguiar, Maíra; Ballesteros, Sebastién; Boto, João Pedro; Kooi, Bob W.; Mateus, Luís; Stollenwerk, Nico

    2011-09-01

    We revisit the parameter estimation framework for population biological dynamical systems, and apply it to calibrate various models in epidemiology with empirical time series, namely influenza and dengue fever. When it comes to more complex models like multi-strain dynamics to describe the virus-host interaction in dengue fever, even most recently developed parameter estimation techniques, like maximum likelihood iterated filtering, come to their computational limits. However, the first results of parameter estimation with data on dengue fever from Thailand indicate a subtle interplay between stochasticity and deterministic skeleton. The deterministic system on its own already displays complex dynamics up to deterministic chaos and coexistence of multiple attractors.

  13. Ground state energy from the single trajectory propagation of the Schrödinger-Langevin equation

    NASA Astrophysics Data System (ADS)

    Chou, Chia-Chun

    2015-07-01

    The Schrödinger-Langevin equation is approximately solved for the ground state energy of quantum systems by propagating one single trajectory at a fixed point. Equations of motion for the amplitude of the wave function and the spatial derivatives of the complex action are derived through use of the derivative propagation method. The ground state energy is calculated from the amplitude of the wave function propagated along the single trajectory. Excellent ground state energies are obtained for the Morse potential, the strongly anharmonic potential, the coupled Morse oscillator-harmonic oscillator system, and the ground vibrational state of methyl iodide.

  14. Nonequilibrium processes from generalized Langevin equations: Realistic nanoscale systems connected to two thermal baths

    NASA Astrophysics Data System (ADS)

    Ness, H.; Genina, A.; Stella, L.; Lorenz, C. D.; Kantorovich, L.

    2016-05-01

    We extend the generalized Langevin equation (GLE) method [L. Stella, C. D. Lorenz, and L. Kantorovich, Phys. Rev. B 89, 134303 (2014), 10.1103/PhysRevB.89.134303] to model a central classical region connected to two realistic thermal baths at two different temperatures. In such nonequilibrium conditions a heat flow is established, via the central system, in between the two baths. The GLE-2B (GLE two baths) scheme permits us to have a realistic description of both the dissipative central system and its surrounding baths. Following the original GLE approach, the extended Langevin dynamics scheme is modified to take into account two sets of auxiliary degrees of freedom corresponding to the mapping of the vibrational properties of each bath. These auxiliary variables are then used to solve the non-Markovian dissipative dynamics of the central region. The resulting algorithm is used to study a model of a short Al nanowire connected to two baths. The results of the simulations using the GLE-2B approach are compared to the results of other simulations that were carried out using standard thermostatting approaches (based on Markovian Langevin and Nosé-Hoover thermostats). We concentrate on the steady-state regime and study the establishment of a local temperature profile within the system. The conditions for obtaining a flat profile or a temperature gradient are examined in detail, in agreement with earlier studies. The results show that the GLE-2B approach is able to treat, within a single scheme, two widely different thermal transport regimes, i.e., ballistic systems, with no temperature gradient, and diffusive systems with a temperature gradient.

  15. Structural and dynamical properties of complex networks

    NASA Astrophysics Data System (ADS)

    Ghoshal, Gourab

    Recent years have witnessed a substantial amount of interest within the physics community in the properties of networks. Techniques from statistical physics coupled with the widespread availability of computing resources have facilitated studies ranging from large scale empirical analysis of the worldwide web, social networks, biological systems, to the development of theoretical models and tools to explore the various properties of these systems. Following these developments, in this dissertation, we present and solve for a diverse set of new problems, investigating the structural and dynamical properties of both model and real world networks. We start by defining a new metric to measure the stability of network structure to disruptions, and then using a combination of theory and simulation study its properties in detail on artificially generated networks; we then compare our results to a selection of networks from the real world and find good agreement in most cases. In the following chapter, we propose a mathematical model that mimics the structure of popular file-sharing websites such as Flickr and CiteULike and demonstrate that many of its properties can solved exactly in the limit of large network size. The remaining part of the dissertation primarily focuses on the dynamical properties of networks. We first formulate a model of a network that evolves under the addition and deletion of vertices and edges, and solve for the equilibrium degree distribution for a variety of cases of interest. We then consider networks whose structure can be manipulated by adjusting the rules by which vertices enter and leave the network. We focus in particular on degree distributions and show that, with some mild constraints, it is possible by a suitable choice of rules to arrange for the network to have any degree distribution we desire. In addition we define a simple local algorithm by which appropriate rules can be implemented in practice. Finally, we conclude our

  16. Topological and Dynamical Complexity of Random Neural Networks

    NASA Astrophysics Data System (ADS)

    Wainrib, Gilles; Touboul, Jonathan

    2013-03-01

    Random neural networks are dynamical descriptions of randomly interconnected neural units. These show a phase transition to chaos as a disorder parameter is increased. The microscopic mechanisms underlying this phase transition are unknown and, similar to spin glasses, shall be fundamentally related to the behavior of the system. In this Letter, we investigate the explosion of complexity arising near that phase transition. We show that the mean number of equilibria undergoes a sharp transition from one equilibrium to a very large number scaling exponentially with the dimension on the system. Near criticality, we compute the exponential rate of divergence, called topological complexity. Strikingly, we show that it behaves exactly as the maximal Lyapunov exponent, a classical measure of dynamical complexity. This relationship unravels a microscopic mechanism leading to chaos which we further demonstrate on a simpler disordered system, suggesting a deep and underexplored link between topological and dynamical complexity.

  17. Collective Dynamics of Complex Plasma Bilayers

    SciTech Connect

    Hartmann, P.; Donko, Z.; Kalman, G. J.; Kyrkos, S.; Golden, K. I.; Rosenberg, M.

    2009-12-11

    A classical dusty plasma experiment was performed using two different dust grain sizes to form a strongly coupled asymmetric bilayer (two closely spaced interacting monolayers) of two species of charged dust particles. The observation and analysis of the thermally excited particle oscillations revealed the collective mode structure and dispersion (wave propagation) in this system; in particular, the existence of the theoretically predicted k=0 energy (frequency) gap was verified. Equilibrium molecular-dynamics simulations were performed to emulate the experiment, assuming Yukawa-type interparticle interaction. The simulations and analytic calculations based both on lattice summation and on the quasilocalized charge approximation approach are in good agreement with the experimental findings and help in identifying and characterizing the observed phenomena.

  18. Conceptualizing Teacher Identity as a Complex Dynamic System: The Inner Dynamics of Transformations during a Practicum

    ERIC Educational Resources Information Center

    Henry, Alastair

    2016-01-01

    Currently, the inner dynamics of teacher identity transformations remain a "black box." Conceptualizing preservice teacher identity as a complex dynamic system, and the notion of "being someone who teaches" in dialogical terms as involving shifts between different teacher voices, the study investigates the dynamical processes…

  19. Visualization of chemical reaction dynamics: Toward understanding complex polyatomic reactions

    PubMed Central

    SUZUKI, Toshinori

    2013-01-01

    Polyatomic molecules have several electronic states that have similar energies. Consequently, their chemical dynamics often involve nonadiabatic transitions between multiple potential energy surfaces. Elucidating the complex reactions of polyatomic molecules is one of the most important tasks of theoretical and experimental studies of chemical dynamics. This paper describes our recent experimental studies of the multidimensional multisurface dynamics of polyatomic molecules based on two-dimensional ion/electron imaging. It also discusses ultrafast photoelectron spectroscopy of liquids for elucidating nonadiabatic electronic dynamics in aqueous solutions. PMID:23318678

  20. Dynamics of a complex streamer structure

    NASA Astrophysics Data System (ADS)

    Lehtinen, N. G.; Ostgaard, N.; Inan, U.

    2014-12-01

    Streamer corona formation and propagation is an important process in the development of lightning. In order to understand its dynamics, the streamer front velocity is calculated in a 1D model with curvature. We show that streamers may only propagate only the presence of mechanisms such as electron drift, electron diffusion and photoionization. The results indicate, in particular, that: (1) the effect of photoionization on the streamer velocity for both positive and negative streamers is mostly determined by the photoionization length, with a weaker dependence on the amount of photoionization; (2) the electron drift may increase the velocity of the negative streamers but has an opposite effect on the positive streamers; (3) the contributions of photoionization and electron diffusion to the velocity are decreased for positive curvature, i.e., convex fronts, while the contribution of electron drift is independent of curvature. These results are used in a fractal model in which the front propagation velocity is simulated as the cluster growth probability [Niemeyer et al, 1984, doi:10.1103/PhysRevLett.52.1033]. In the case when the photoionization is the main mechanism which determines the streamer propagation, the emerging transverse size of the streamers is of the order of the photoionization length, and at the larger scale the streamer structure is a fractal similar to the one obtained in a diffusion-limited aggregation system.

  1. Langevin Theory of Anomalous Brownian Motion Made Simple

    ERIC Educational Resources Information Center

    Tothova, Jana; Vasziova, Gabriela; Glod, Lukas; Lisy, Vladimir

    2011-01-01

    During the century from the publication of the work by Einstein (1905 "Ann. Phys." 17 549) Brownian motion has become an important paradigm in many fields of modern science. An essential impulse for the development of Brownian motion theory was given by the work of Langevin (1908 "C. R. Acad. Sci.", Paris 146 530), in which he proposed an…

  2. Crossover behavior of multiscale fluctuations in Big Data: Langevin model and substorm time-scales in Earth's magnetosphere

    NASA Astrophysics Data System (ADS)

    Sharma, A. S.; Setty, V. A.

    2015-12-01

    Multiscale fluctuations in large and complex data are usually characterized by a power law with a scaling exponent but many systems require more than one exponent and thus exhibit crossover behavior. The scaling exponents, such as Hurst exponents, represent the nature of correlation in the system and the crossover shows the presence of more than one type of correlation. An accurate characterization of the crossover behavior is thus needed for a better understanding of the inherent correlations in the system, and is an important method of Big Data analysis. A multi-step process is developed for accurate computation of the crossover behavior. First the detrended fluctuation analysis is used to remove the trends in the data and the scaling exponents are computed. The crossover point is then computed by a Hyperbolic regression technique, with no prior assumptions. The time series data of the magnetic field variations during substorms in the Earth's magnetosphere is analyzed with these techniques and yields a crossover behavior with a time scale of ~4 hrs. A Langevin model derived from the data provides an excellent fit to the crossover in the scaling exponents and a good model of magnetospheric dynamics. The combination of fluctuation analysis and mathematical modeling thus yields a comprehensive approach in the analysis of Big Data.

  3. Temporal properties of dynamic processes on complex networks

    NASA Astrophysics Data System (ADS)

    Turalska, Malgorzata A.

    Many social, biological and technological systems can be viewed as complex networks with a large number of interacting components. However despite recent advancements in network theory, a satisfactory description of dynamic processes arising in such cooperative systems is a subject of ongoing research. In this dissertation the emergence of dynamical complexity in networks of interacting stochastic oscillators is investigated. In particular I demonstrate that networks of two and three state stochastic oscillators present a second-order phase transition with respect to the strength of coupling between individual units. I show that at the critical point fluctuations of the global order parameter are characterized by an inverse-power law distribution and I assess their renewal properties. Additionally, I study the effect that different types of perturbation have on dynamical properties of the model. I discuss the relevance of those observations for the transmission of information between complex systems.

  4. Interplay between collective behavior and spreading dynamics on complex networks

    NASA Astrophysics Data System (ADS)

    Li, Kezan; Ma, Zhongjun; Jia, Zhen; Small, Michael; Fu, Xinchu

    2012-12-01

    There are certain correlations between collective behavior and spreading dynamics on some real complex networks. Based on the dynamical characteristics and traditional physical models, we construct several new bidirectional network models of spreading phenomena. By theoretical and numerical analysis of these models, we find that the collective behavior can inhibit spreading behavior, but, conversely, this spreading behavior can accelerate collective behavior. The spread threshold of spreading network is obtained by using the Lyapunov function method. The results show that an effective spreading control method is to enhance the individual awareness to collective behavior. Many real-world complex networks can be thought of in terms of both collective behavior and spreading dynamics and therefore to better understand and control such complex networks systems, our work may provide a basic framework.

  5. Traditional Chinese medicine: potential approaches from modern dynamical complexity theories.

    PubMed

    Ma, Yan; Zhou, Kehua; Fan, Jing; Sun, Shuchen

    2016-03-01

    Despite the widespread use of traditional Chinese medicine (TCM) in clinical settings, proving its effectiveness via scientific trials is still a challenge. TCM views the human body as a complex dynamical system, and focuses on the balance of the human body, both internally and with its external environment. Such fundamental concepts require investigations using system-level quantification approaches, which are beyond conventional reductionism. Only methods that quantify dynamical complexity can bring new insights into the evaluation of TCM. In a previous article, we briefly introduced the potential value of Multiscale Entropy (MSE) analysis in TCM. This article aims to explain the existing challenges in TCM quantification, to introduce the consistency of dynamical complexity theories and TCM theories, and to inspire future system-level research on health and disease.

  6. Effects of microscopic transport coefficients on fission observables calculated by the Langevin equation

    NASA Astrophysics Data System (ADS)

    Usang, M. D.; Ivanyuk, F. A.; Ishizuka, C.; Chiba, S.

    2016-10-01

    Nuclear fission is treated by using the Langevin dynamical description with macroscopic and microscopic transport coefficients (mass and friction tensors), and it is elucidated how the microscopic (shell and pairing) effects in the transport coefficients, especially their dependence on temperature, affects various fission observables. We found that the microscopic transport coefficients, calculated by linear response theory, change drastically as a function of temperature: in general, the friction increases with growing temperature while the mass tensor decreases. This temperature dependence brings a noticeable change in the mass distribution and kinetic energies of fission fragments from nuclei around 236U at an excitation energy of 20 MeV. The prescission kinetic energy decreases from 25 MeV at low temperature to about 2.5 MeV at high temperature. In contrast, the Coulomb kinetic energy increases as the temperature increases. Interpolating the microscopic transport coefficients among the various temperatures enabled our Langevin equation to use the microscopic transport coefficients at a deformation-dependent local temperature of the dynamical evolution. This allowed us to compare directly the fission observables of both macroscopic and microscopic calculations, and we found almost identical results under the conditions considered in this work.

  7. Generalized Langevin equation with colored noise description of the stochastic oscillations of accretion disks

    NASA Astrophysics Data System (ADS)

    Harko, Tiberiu; Leung, Chun Sing; Mocanu, Gabriela

    2014-05-01

    We consider a description of the stochastic oscillations of the general relativistic accretion disks around compact astrophysical objects interacting with their external medium based on a generalized Langevin equation with colored noise and on the fluctuation-dissipation theorems. The former accounts for the general memory and retarded effects of the frictional force. The presence of the memory effects influences the response of the disk to external random interactions, and it modifies the dynamical behavior of the disk, as well as the energy dissipation processes. The generalized Langevin equation of the motion of the disk in the vertical direction is studied numerically, and the vertical displacements, velocities, and luminosities of the stochastically perturbed disks are explicitly obtained for both the Schwarzschild and the Kerr cases. The power spectral distribution of the disk luminosity is also obtained. As a possible astrophysical application of the formalism we investigate the possibility that the intra-day variability of the active galactic nuclei may be due to the stochastic disk instabilities. The perturbations due to colored/nontrivially correlated noise induce a complicated disk dynamics, which could explain some astrophysical observational features related to disk variability.

  8. Complex dynamics in the Oregonator model with linear delayed feedback

    NASA Astrophysics Data System (ADS)

    Sriram, K.; Bernard, S.

    2008-06-01

    The Belousov-Zhabotinsky (BZ) reaction can display a rich dynamics when a delayed feedback is applied. We used the Oregonator model of the oscillating BZ reaction to explore the dynamics brought about by a linear delayed feedback. The time-delayed feedback can generate a succession of complex dynamics: period-doubling bifurcation route to chaos; amplitude death; fat, wrinkled, fractal, and broken tori; and mixed-mode oscillations. We observed that this dynamics arises due to a delay-driven transition, or toggling of the system between large and small amplitude oscillations, through a canard bifurcation. We used a combination of numerical bifurcation continuation techniques and other numerical methods to explore the dynamics in the strength of feedback-delay space. We observed that the period-doubling and quasiperiodic route to chaos span a low-dimensional subspace, perhaps due to the trapping of the trajectories in the small amplitude regime near the canard; and the trapped chaotic trajectories get ejected from the small amplitude regime due to a crowding effect to generate chaotic-excitable spikes. We also qualitatively explained the observed dynamics by projecting a three-dimensional phase portrait of the delayed dynamics on the two-dimensional nullclines. This is the first instance in which it is shown that the interaction of delay and canard can bring about complex dynamics.

  9. Probability in Theories With Complex Dynamics and Hardy's Fifth Axiom

    NASA Astrophysics Data System (ADS)

    Burić, Nikola

    2010-08-01

    L. Hardy has formulated an axiomatization program of quantum mechanics and generalized probability theories that has been quite influential. In this paper, properties of typical Hamiltonian dynamical systems are used to argue that there are applications of probability in physical theories of systems with dynamical complexity that require continuous spaces of pure states. Hardy’s axiomatization program does not deal with such theories. In particular Hardy’s fifth axiom does not differentiate between such applications of classical probability and quantum probability.

  10. Coupled disease-behavior dynamics on complex networks: A review

    NASA Astrophysics Data System (ADS)

    Wang, Zhen; Andrews, Michael A.; Wu, Zhi-Xi; Wang, Lin; Bauch, Chris T.

    2015-12-01

    It is increasingly recognized that a key component of successful infection control efforts is understanding the complex, two-way interaction between disease dynamics and human behavioral and social dynamics. Human behavior such as contact precautions and social distancing clearly influence disease prevalence, but disease prevalence can in turn alter human behavior, forming a coupled, nonlinear system. Moreover, in many cases, the spatial structure of the population cannot be ignored, such that social and behavioral processes and/or transmission of infection must be represented with complex networks. Research on studying coupled disease-behavior dynamics in complex networks in particular is growing rapidly, and frequently makes use of analysis methods and concepts from statistical physics. Here, we review some of the growing literature in this area. We contrast network-based approaches to homogeneous-mixing approaches, point out how their predictions differ, and describe the rich and often surprising behavior of disease-behavior dynamics on complex networks, and compare them to processes in statistical physics. We discuss how these models can capture the dynamics that characterize many real-world scenarios, thereby suggesting ways that policy makers can better design effective prevention strategies. We also describe the growing sources of digital data that are facilitating research in this area. Finally, we suggest pitfalls which might be faced by researchers in the field, and we suggest several ways in which the field could move forward in the coming years.

  11. 2D pattern evolution constrained by complex network dynamics

    NASA Astrophysics Data System (ADS)

    da Rocha, L. E. C.; Costa, L. da F.

    2007-03-01

    Complex networks have established themselves in recent years as being particularly suitable and flexible for representing and modelling several complex natural and artificial systems. In the same time in which the structural intricacies of such networks are being revealed and understood, efforts have also been directed at investigating how such connectivity properties define and constrain the dynamics of systems unfolding on such structures. However, less attention has been focused on hybrid systems, i.e. involving more than one type of network and/or dynamics. Several real systems present such an organization, e.g. the dynamics of a disease coexisting with the dynamics of the immune system. The current paper investigates a specific system involving diffusive (linear and nonlinear) dynamics taking place in a regular network while interacting with a complex network of defensive agents following Erdös Rényi (ER) and Barabási Albert (BA) graph models with moveable nodes. More specifically, the complex network is expected to control, and if possible, to extinguish the diffusion of some given unwanted process (e.g. fire, oil spilling, pest dissemination, and virus or bacteria reproduction during an infection). Two types of pattern evolution are considered: Fick and Gray Scott. The nodes of the defensive network then interact with the diffusing patterns and communicate between themselves in order to control the diffusion. The main findings include the identification of higher efficiency for the BA control networks and the presence of relapses in the case of the ER model.

  12. Coupled disease-behavior dynamics on complex networks: A review.

    PubMed

    Wang, Zhen; Andrews, Michael A; Wu, Zhi-Xi; Wang, Lin; Bauch, Chris T

    2015-12-01

    It is increasingly recognized that a key component of successful infection control efforts is understanding the complex, two-way interaction between disease dynamics and human behavioral and social dynamics. Human behavior such as contact precautions and social distancing clearly influence disease prevalence, but disease prevalence can in turn alter human behavior, forming a coupled, nonlinear system. Moreover, in many cases, the spatial structure of the population cannot be ignored, such that social and behavioral processes and/or transmission of infection must be represented with complex networks. Research on studying coupled disease-behavior dynamics in complex networks in particular is growing rapidly, and frequently makes use of analysis methods and concepts from statistical physics. Here, we review some of the growing literature in this area. We contrast network-based approaches to homogeneous-mixing approaches, point out how their predictions differ, and describe the rich and often surprising behavior of disease-behavior dynamics on complex networks, and compare them to processes in statistical physics. We discuss how these models can capture the dynamics that characterize many real-world scenarios, thereby suggesting ways that policy makers can better design effective prevention strategies. We also describe the growing sources of digital data that are facilitating research in this area. Finally, we suggest pitfalls which might be faced by researchers in the field, and we suggest several ways in which the field could move forward in the coming years.

  13. Investigating dynamical complexity of geomagnetic jerks using various entropy measures

    NASA Astrophysics Data System (ADS)

    Balasis, Georgios; Potirakis, Stelios; Mandea, Mioara

    2016-06-01

    Recently, many novel concepts originated in dynamical systems or information theory have been developed, partly motivated by specific research questions linked to geosciences, and found a variety of different applications. This continuously extending toolbox of nonlinear time series analysis highlights the importance of the dynamical complexity to understand the behavior of the complex Earth's system and its components. Here, we propose to apply such new approaches, mainly a series of entropy methods to the time series of the geomagnetic field. Two datasets provided by Chambon la Foret (France) and Niemegk (Germany) observatories are considered for analysis to detect dynamical complexity changes associated with geomagnetic jerks, the abrupt changes in the second temporal derivative of the Earth's magnetic field. The results clearly demonstrate the ability of Shannon and Tsallis entropies as well as Fisher information to detect events in a regional manner having identified complexities lower than the background in time intervals when geomagnetic jerks have already been reported in the literature. Additionally, these information measures are directly applicable to the original data without having to derive the secular variation or acceleration from the observatory monthly means. The strength of the proposed analysis to reveal dynamical complexity features associated with geomagnetic jerks can be utilized for analyzing not only ground measurements, but also satellite data, as those provided by the current magnetic field mission of Swarm.

  14. Converting PSO dynamics into complex network - Initial study

    NASA Astrophysics Data System (ADS)

    Pluhacek, Michal; Janostik, Jakub; Senkerik, Roman; Zelinka, Ivan

    2016-06-01

    In this paper it is presented the initial study on the possibility of capturing the inner dynamic of Particle Swarm Optimization algorithm into a complex network structure. Inspired in previous works there are two different approaches for creating the complex network presented in this paper. Visualizations of the networks are presented and commented. The possibilities for future applications of the proposed design are given in detail.

  15. Minimal model for complex dynamics in cellular processes.

    PubMed

    Suguna, C; Chowdhury, K K; Sinha, S

    1999-11-01

    Cellular functions are controlled and coordinated by the complex circuitry of biochemical pathways regulated by genetic and metabolic feedback processes. This paper aims to show, with the help of a minimal model of a regulated biochemical pathway, that the common nonlinearities and control structures present in biomolecular interactions are capable of eliciting a variety of functional dynamics, such as homeostasis, periodic, complex, and chaotic oscillations, including transients, that are observed in various cellular processes.

  16. Complexity and dynamism from an urban health perspective: a rationale for a system dynamics approach.

    PubMed

    Tozan, Yesim; Ompad, Danielle C

    2015-06-01

    In a variety of urban health frameworks, cities are conceptualized as complex and dynamic yet commonly used epidemiological methods have failed to address this complexity and dynamism head on due to their narrow problem definitions and linear analytical representations. Scholars from a variety of disciplines have also long conceptualized cities as systems, but few have modeled urban health issues as problems within a system. Systems thinking in general and system dynamics in particular are relatively new approaches in public health, but ones that hold immense promise as methodologies to model and analyze the complexity underlying urban processes to effectively inform policy actions in dynamic environments. This conceptual essay reviews the utility of applying the concepts, principles, and methods of systems thinking to the study of complex urban health phenomena as a complementary approach to standard epidemiological methods using specific examples and provides recommendations on how to better incorporate systems thinking methods in urban health research and practice. PMID:25952137

  17. Complexity and dynamism from an urban health perspective: a rationale for a system dynamics approach.

    PubMed

    Tozan, Yesim; Ompad, Danielle C

    2015-06-01

    In a variety of urban health frameworks, cities are conceptualized as complex and dynamic yet commonly used epidemiological methods have failed to address this complexity and dynamism head on due to their narrow problem definitions and linear analytical representations. Scholars from a variety of disciplines have also long conceptualized cities as systems, but few have modeled urban health issues as problems within a system. Systems thinking in general and system dynamics in particular are relatively new approaches in public health, but ones that hold immense promise as methodologies to model and analyze the complexity underlying urban processes to effectively inform policy actions in dynamic environments. This conceptual essay reviews the utility of applying the concepts, principles, and methods of systems thinking to the study of complex urban health phenomena as a complementary approach to standard epidemiological methods using specific examples and provides recommendations on how to better incorporate systems thinking methods in urban health research and practice.

  18. Behavioral-Independent Features of Complex Heartbeat Dynamics

    NASA Astrophysics Data System (ADS)

    Nunes Amaral, Luís A.; Ivanov, Plamen Ch.; Aoyagi, Naoko; Hidaka, Ichiro; Tomono, Shinji; Goldberger, Ary L.; Stanley, H. Eugene; Yamamoto, Yoshiharu

    2001-06-01

    We test whether the complexity of the cardiac interbeat interval time series is simply a consequence of the wide range of scales characterizing human behavior, especially physical activity, by analyzing data taken from healthy adult subjects under three conditions with controls: (i) a ``constant routine'' protocol where physical activity and postural changes are kept to a minimum, (ii) sympathetic blockade, and (iii) parasympathetic blockade. We find that when fluctuations in physical activity and other behavioral modifiers are minimized, a remarkable level of complexity of heartbeat dynamics remains, while for neuroautonomic blockade the multifractal complexity decreases.

  19. Nonlinear Synergies and Multiscale Structural Dynamics in Complex Systems: Theoretical Advances and Applications to Hydroclimate Dynamics

    NASA Astrophysics Data System (ADS)

    Perdigão, R. A. P.

    2015-12-01

    The dynamical evolution of complex coevolving systems is assessed in a novel nonlinear statistical-dynamical framework formally linking nonlinear statistical measures of codependence and emergence with fundamental dynamical interaction laws. The methodological developments are then used to shed light onto fundamental interactions underlying complex behaviour in hydroclimate dynamics. For that purpose, a dynamical model is presented predicting evolving hydroclimatic quantities and their distributions under nonlinearly coevolving geophysical processes. The functional model is based on first principles regulating the dynamics of each system constituent and their synergies, therefore its applicability is general and data-independent, not requiring local calibrations. Moreover, it enables the dynamical estimation of hydroclimatic variations in space and time from the given knowledge at different spatiotemporal conditions. This paves the way for a robust physically based prediction of hydroclimatic changes in unmonitored areas. Validation is achieved by producing, with the dynamical model, a comprehensive spatiotemporal legacy consistent with the observed distributions along with their dynamical and statistical properties and relations. The similarity between simulated and observed distributions is further assessed with robust information-theoretic diagnostics. This study ultimately brings to light emerging signatures of structural change in hydroclimate dynamics arising from nonlinear synergies across spatiotemporal scales, and contributes to a better dynamical understanding and prediction of spatiotemporal regimes, transitions and extremes. The study further sheds light onto a diversity of emerging properties from harmonic to hyper-chaotic dynamics in hydroclimatic systems.

  20. Applications of dynamical complexity theory in traditional Chinese medicine.

    PubMed

    Ma, Yan; Sun, Shuchen; Peng, Chung-Kang

    2014-09-01

    Traditional Chinese medicine (TCM) has been gradually accepted by the world. Despite its widespread use in clinical settings, a major challenge in TCM is to study it scientifically. This difficulty arises from the fact that TCM views human body as a complex dynamical system, and focuses on the balance of the human body, both internally and with its external environment. As a result, conventional tools that are based on reductionist approach are not adequate. Methods that can quantify the dynamics of complex integrative systems may bring new insights and utilities about the clinical practice and evaluation of efficacy of TCM. The dynamical complexity theory recently proposed and its computational algorithm, Multiscale Entropy (MSE) analysis, are consistent with TCM concepts. This new system level analysis has been successfully applied to many health and disease related topics in medicine. We believe that there could be many promising applications of this dynamical complexity concept in TCM. In this article, we propose some promising applications and research areas that TCM practitioners and researchers can pursue.

  1. Complex and unexpected dynamics in simple genetic regulatory networks

    NASA Astrophysics Data System (ADS)

    Borg, Yanika; Ullner, Ekkehard; Alagha, Afnan; Alsaedi, Ahmed; Nesbeth, Darren; Zaikin, Alexey

    2014-03-01

    One aim of synthetic biology is to construct increasingly complex genetic networks from interconnected simpler ones to address challenges in medicine and biotechnology. However, as systems increase in size and complexity, emergent properties lead to unexpected and complex dynamics due to nonlinear and nonequilibrium properties from component interactions. We focus on four different studies of biological systems which exhibit complex and unexpected dynamics. Using simple synthetic genetic networks, small and large populations of phase-coupled quorum sensing repressilators, Goodwin oscillators, and bistable switches, we review how coupled and stochastic components can result in clustering, chaos, noise-induced coherence and speed-dependent decision making. A system of repressilators exhibits oscillations, limit cycles, steady states or chaos depending on the nature and strength of the coupling mechanism. In large repressilator networks, rich dynamics can also be exhibited, such as clustering and chaos. In populations of Goodwin oscillators, noise can induce coherent oscillations. In bistable systems, the speed with which incoming external signals reach steady state can bias the network towards particular attractors. These studies showcase the range of dynamical behavior that simple synthetic genetic networks can exhibit. In addition, they demonstrate the ability of mathematical modeling to analyze nonlinearity and inhomogeneity within these systems.

  2. Nonlinear Dynamics of Complex Coevolutionary Systems in Historical Times

    NASA Astrophysics Data System (ADS)

    Perdigão, Rui A. P.

    2016-04-01

    A new theoretical paradigm for statistical-dynamical modeling of complex coevolutionary systems is introduced, with the aim to provide historical geoscientists with a practical tool to analyse historical data and its underlying phenomenology. Historical data is assumed to represent the history of dynamical processes of physical and socio-economic nature. If processes and their governing laws are well understood, they are often treated with traditional dynamical equations: deterministic approach. If the governing laws are unknown or impracticable, the process is often treated as if being random (even if it is not): statistical approach. Although single eventful details - such as the exact spatiotemporal structure of a particular hydro-meteorological incident - may often be elusive to a detailed analysis, the overall dynamics exhibit group properties summarized by a simple set of categories or dynamical regimes at multiple scales - from local short-lived convection patterns to large-scale hydro-climatic regimes. The overwhelming microscale complexity is thus conveniently wrapped into a manageable group entity, such as a statistical distribution. In a stationary setting whereby the distribution is assumed to be invariant, alternating regimes are approachable as dynamical intermittence. For instance, in the context of bimodal climatic oscillations such as NAO and ENSO, each mode corresponds to a dynamical regime or phase. However, given external forcings or longer-term internal variability and multiscale coevolution, the structural properties of the system may change. These changes in the dynamical structure bring about a new distribution and associated regimes. The modes of yesteryear may no longer exist as such in the new structural order of the system. In this context, aside from regime intermittence, the system exhibits structural regime change. New oscillations may emerge whilst others fade into the annals of history, e.g. particular climate fluctuations during

  3. Complex systems dynamics in aging: new evidence, continuing questions.

    PubMed

    Cohen, Alan A

    2016-02-01

    There have long been suggestions that aging is tightly linked to the complex dynamics of the physiological systems that maintain homeostasis, and in particular to dysregulation of regulatory networks of molecules. This review synthesizes recent work that is starting to provide evidence for the importance of such complex systems dynamics in aging. There is now clear evidence that physiological dysregulation--the gradual breakdown in the capacity of complex regulatory networks to maintain homeostasis--is an emergent property of these regulatory networks, and that it plays an important role in aging. It can be measured simply using small numbers of biomarkers. Additionally, there are indications of the importance during aging of emergent physiological processes, functional processes that cannot be easily understood through clear metabolic pathways, but can nonetheless be precisely quantified and studied. The overall role of such complex systems dynamics in aging remains an important open question, and to understand it future studies will need to distinguish and integrate related aspects of aging research, including multi-factorial theories of aging, systems biology, bioinformatics, network approaches, robustness, and loss of complexity.

  4. Molecular dynamics studies of U1A-RNA complexes.

    PubMed Central

    Reyes, C M; Kollman, P A

    1999-01-01

    The U1A protein binds to a hairpin RNA and an internal-loop RNA with picomolar affinities. To probe the molecular basis of U1A binding, we performed state-of-the-art nanosecond molecular dynamics simulations on both complexes. The good agreement with experimental structures supports the protocols used in the simulations. We compare the dynamics, hydrogen-bonding occupancies, and interfacial flexibility of both complexes and also describe a rigid-body motion in the U1A-internal loop complex that is not observed in the U1A-hairpin simulation. We relate these observations to experimental mutational studies and highlight their significance in U1A binding affinity and specificity. PMID:10024175

  5. Dynamic liquid association: complex learning without implausible guidance.

    PubMed

    Morse, Anthony; Aktius, Malin

    2009-09-01

    Simple associative networks have many desirable properties, but are fundamentally limited by their inability to accurately capture complex relationships. This paper presents a solution significantly extending the abilities of associative networks by using an untrained dynamic reservoir as an input filter. The untrained reservoir provides complex dynamic transformations, and temporal integration, and can be viewed as a complex non-linear feature detector from which the associative network can learn. Typically reservoir systems utilize trained single layer perceptrons to produce desired output responses. However given that both single layer perceptions and simple associative learning have the same computational limitations, i.e. linear separation, they should perform similarly in terms of pattern recognition ability. Further to this the extensive psychological properties of simple associative networks and the lack of explicit supervision required for associative learning motivates this extension overcoming previous limitations. Finally, we demonstrate the resulting model in a robotic embodiment, learning sensorimotor contingencies, and matching a variety of psychological data.

  6. Complexity Analysis and Parameter Estimation of Dynamic Metabolic Systems

    PubMed Central

    Tian, Li-Ping; Shi, Zhong-Ke; Wu, Fang-Xiang

    2013-01-01

    A metabolic system consists of a number of reactions transforming molecules of one kind into another to provide the energy that living cells need. Based on the biochemical reaction principles, dynamic metabolic systems can be modeled by a group of coupled differential equations which consists of parameters, states (concentration of molecules involved), and reaction rates. Reaction rates are typically either polynomials or rational functions in states and constant parameters. As a result, dynamic metabolic systems are a group of differential equations nonlinear and coupled in both parameters and states. Therefore, it is challenging to estimate parameters in complex dynamic metabolic systems. In this paper, we propose a method to analyze the complexity of dynamic metabolic systems for parameter estimation. As a result, the estimation of parameters in dynamic metabolic systems is reduced to the estimation of parameters in a group of decoupled rational functions plus polynomials (which we call improper rational functions) or in polynomials. Furthermore, by taking its special structure of improper rational functions, we develop an efficient algorithm to estimate parameters in improper rational functions. The proposed method is applied to the estimation of parameters in a dynamic metabolic system. The simulation results show the superior performance of the proposed method. PMID:24233242

  7. SELF-CONSISTENT LANGEVIN SIMULATION OF COULOMB COLLISIONS IN CHARGED-PARTICLE BEAMS

    SciTech Connect

    J. QIANG; R. RYNE; S. HABIB

    2000-05-01

    In many plasma physics and charged-particle beam dynamics problems, Coulomb collisions are modeled by a Fokker-Planck equation. In order to incorporate these collisions, we present a three-dimensional parallel Langevin simulation method using a Particle-In-Cell (PIC) approach implemented on high-performance parallel computers. We perform, for the first time, a fully self-consistent simulation, in which the friction and diffusion coefficients are computed from first principles. We employ a two-dimensional domain decomposition approach within a message passing programming paradigm along with dynamic load balancing. Object oriented programming is used to encapsulate details of the communication syntax as well as to enhance reusability and extensibility. Performance tests on the SGI Origin 2000 and the Cray T3E-900 have demonstrated good scalability. Work is in progress to apply our technique to intrabeam scattering in accelerators.

  8. Langevin theory of anomalous Brownian motion made simple

    NASA Astrophysics Data System (ADS)

    Tóthová, Jana; Vasziová, Gabriela; Glod, Lukáš; Lisý, Vladimír

    2011-05-01

    During the century from the publication of the work by Einstein (1905 Ann. Phys. 17 549) Brownian motion has become an important paradigm in many fields of modern science. An essential impulse for the development of Brownian motion theory was given by the work of Langevin (1908 C. R. Acad. Sci., Paris 146 530), in which he proposed an 'infinitely more simple' description of Brownian motion than that by Einstein. The original Langevin approach has however strong limitations, which were rigorously stated after the creation of the hydrodynamic theory of Brownian motion (1945). Hydrodynamic Brownian motion is a special case of 'anomalous Brownian motion', now intensively studied both theoretically and in experiments. We show how some general properties of anomalous Brownian motion can be easily derived using an effective method that allows one to convert the stochastic generalized Langevin equation into a deterministic Volterra-type integro-differential equation for the mean square displacement of the particle. Within the Gibbs statistics, the method is applicable to linear equations of motion with any kind of memory during the evolution of the system. We apply it to memoryless Brownian motion in a harmonic potential well and to Brownian motion in fluids, taking into account the effects of hydrodynamic memory. Exploring the mathematical analogy between Brownian motion and electric circuits, which are at nanoscales also described by the generalized Langevin equation, we calculate the fluctuations of charge and current in RLC circuits that are in contact with the thermal bath. Due to the simplicity of our approach it could be incorporated into graduate courses of statistical physics. Once the method is established, it allows bringing to the attention of students and effectively solving a number of attractive problems related to Brownian motion.

  9. Complex Dynamics of Compound Vesicles in Linear Flow

    NASA Astrophysics Data System (ADS)

    Levant, Michael; Steinberg, Victor

    2014-04-01

    We report first experimental observations of dynamics of compound vesicles in linear flow realized in a microfluidic four-roll mill. We show that while a compound vesicle undergoes the same main tank-treading, trembling (TR), and tumbling regimes, its dynamics are far richer and more complex than that of unilamellar vesicles. A new swinging motion of the inner vesicle is found in TR in accord with simulations. The inner and outer vesicles can exist simultaneously in different dynamical regimes and can undergo either synchronized or unsynchronized motions depending on the filling factor. A compound vesicle can be used as a physical model to study white blood cell dynamics in flow similar to a unilamellar vesicle used successfully to model anucleate cells.

  10. Complex dynamics of compound vesicles in linear flow.

    PubMed

    Levant, Michael; Steinberg, Victor

    2014-04-01

    We report first experimental observations of dynamics of compound vesicles in linear flow realized in a microfluidic four-roll mill. We show that while a compound vesicle undergoes the same main tank-treading, trembling (TR), and tumbling regimes, its dynamics are far richer and more complex than that of unilamellar vesicles. A new swinging motion of the inner vesicle is found in TR in accord with simulations. The inner and outer vesicles can exist simultaneously in different dynamical regimes and can undergo either synchronized or unsynchronized motions depending on the filling factor. A compound vesicle can be used as a physical model to study white blood cell dynamics in flow similar to a unilamellar vesicle used successfully to model anucleate cells.

  11. Langevin and diffusion equation of turbulent fluid flow

    NASA Astrophysics Data System (ADS)

    Brouwers, J. J. H.

    2010-08-01

    A derivation of the Langevin and diffusion equations describing the statistics of fluid particle displacement and passive admixture in turbulent flow is presented. Use is made of perturbation expansions. The small parameter is the inverse of the Kolmogorov constant C 0 , which arises from Lagrangian similarity theory. The value of C 0 in high Reynolds number turbulence is 5-6. To achieve sufficient accuracy, formulations are not limited to terms of leading order in C0 - 1 including terms next to leading order in C0 - 1 as well. Results of turbulence theory and statistical mechanics are invoked to arrive at the descriptions of the Langevin and diffusion equations, which are unique up to truncated terms of O ( C0 - 2 ) in displacement statistics. Errors due to truncation are indicated to amount to a few percent. The coefficients of the presented Langevin and diffusion equations are specified by fixed-point averages of the Eulerian velocity field. The equations apply to general turbulent flow in which fixed-point Eulerian velocity statistics are non-Gaussian to a degree of O ( C0 - 1 ) . The equations provide the means to calculate and analyze turbulent dispersion of passive or almost passive admixture such as fumes, smoke, and aerosols in areas ranging from atmospheric fluid motion to flows in engineering devices.

  12. Dynamic ionic clusters with flowing electron bubbles from warm to hot dense iron along the Hugoniot curve.

    PubMed

    Dai, Jiayu; Kang, Dongdong; Zhao, Zengxiu; Wu, Yanqun; Yuan, Jianmin

    2012-10-26

    Complex structures of warm and hot dense matter are essential to understanding the behavior of materials in high energy density processes and provide new features of matter constitutions. Here, around a new unified first-principles determined Hugoniot curve of iron from the normal condensed condition up to 1 Gbar, the novel structures characterized by the ionic clusters with electron bubbles are found using quantum Langevin molecular dynamics. Subsistence of complex clusters can persist in the time scale of 50 fs dynamically with quantum flowing bubbles, which are produced by the interplay of Fermi electron degeneracy, the ionic coupling, and the dynamical nature. With the inclusion of those complicated features in quantum Langevin molecular dynamics, the present equation of states could serve as a first-principles based database in a wide range of temperatures and densities.

  13. Dynamic modeling of structures from measured complex modes

    NASA Technical Reports Server (NTRS)

    Ibrahim, s. R.

    1982-01-01

    A technique is presented to use a set of identified complex modes together with an analytical mathematical model of a structure under test to compute improved mass, stiffness and damping matrices. A set of identified normal modes, computed from the measured complex modes, is used in the mass orthogonality equation to compute an improved mass matrix. This eliminates possible errors that may result from using approximated complex modes as normal modes. The improved mass matrix, the measured complex modes and the higher analytical modes are then used to compute the improved stiffness and damping matrices. The number of degrees-of-freedom of the improved model is limited to equal the number of elements in the measured modal vectors. A simulated experiment shows considerable improvements, in the system's analytical dynamic model, over the frequency range of the given measured modal information.

  14. Control of complex networks requires both structure and dynamics

    PubMed Central

    Gates, Alexander J.; Rocha, Luis M.

    2016-01-01

    The study of network structure has uncovered signatures of the organization of complex systems. However, there is also a need to understand how to control them; for example, identifying strategies to revert a diseased cell to a healthy state, or a mature cell to a pluripotent state. Two recent methodologies suggest that the controllability of complex systems can be predicted solely from the graph of interactions between variables, without considering their dynamics: structural controllability and minimum dominating sets. We demonstrate that such structure-only methods fail to characterize controllability when dynamics are introduced. We study Boolean network ensembles of network motifs as well as three models of biochemical regulation: the segment polarity network in Drosophila melanogaster, the cell cycle of budding yeast Saccharomyces cerevisiae, and the floral organ arrangement in Arabidopsis thaliana. We demonstrate that structure-only methods both undershoot and overshoot the number and which sets of critical variables best control the dynamics of these models, highlighting the importance of the actual system dynamics in determining control. Our analysis further shows that the logic of automata transition functions, namely how canalizing they are, plays an important role in the extent to which structure predicts dynamics. PMID:27087469

  15. How vegetation patterning affects sediment dynamics in complex landscapes

    NASA Astrophysics Data System (ADS)

    Baartman, Jantiene; Temme, Arnaud; Saco, Patricia

    2016-04-01

    Semi-arid ecosystems are often spatially self-organized in typical patterns of vegetation bands with high plant cover interspersed with bare soil areas, also known as 'tigerbush'. Tigerbush dynamics have been studied using model simulations on flat synthetic landscapes, although in some cases straight slopes were used. The feedbacks between vegetation and more realistic and complex landscapes have not been studied yet, even though these landscapes are much more prevalent. Hence, our objective was to determine the effect of landform variation on vegetation patterning and sediment dynamics. We linked two existing models that simulate (a) plant growth, death and dispersal of vegetation, and (b) erosion and sedimentation. The model was calibrated on a straight planar hillslope and then applied to (i) a set of synthetic but more complex topographies and (ii) three real-world landscapes. Furthermore, sediment dynamics were evaluated by comparing simulated sediment output with and without vegetation dynamics. Results show banded vegetation patterning on all synthetic topographies, always perpendicular to the slope gradient. For real topographies, banded vegetation was simulated in the relatively flat, rolling landscape and in the dissected landscape when slopes were gentle. In the steep dissected landscape and the alluvial fan, vegetation was simulated to grow in local depressions where moisture is present whereas hilltops were bare. Including vegetation dynamics resulted in significantly less simulated erosion and relatively more deposition compared to simulations with uniformly distributed vegetation.

  16. Langevin Simulation of Microstructure in Martensitic Transformations

    NASA Astrophysics Data System (ADS)

    Wu, Y.; Lookman, T.; Shenoy, S. R.; Saxena, A.; Bishop, A. R.

    1996-03-01

    We present a dynamical model to simulate microstructure in martensitic transformations within the context of shape memory alloys. The Hamiltonian of the system includes a triple-well potential (φ^6 model) in local shear strain, (2) strain gradient terms up to second order in strain and fourth order in gradient, and (3) all symmetry allowed compositional fluctuation induced strain gradient terms. We show the formation of twinned martensite below the transformation temperature and tweed precursors above the transformation temperature, as well as indications of hierarchical structures near the habit plane. These phases result from a competition between short range attraction and long range elastic repulsive forces. The long range interaction is incorporated via Fourier spectral methods as discussed by C. Roland and R.C.Desai [Phys. Rev. B 42, 6658 (1990)].

  17. Impedance control complements incomplete internal models under complex external dynamics.

    PubMed

    Tomi, Naoki; Gouko, Manabu; Ito, Koji

    2008-01-01

    In this paper, we investigate motor adaptation of human arm movements to external dynamics. In an experiment, we tried to determine whether humans can learn an internal model of a mixed force field (V+P) that was the sum of a velocity-dependent force field (V) and a position-dependent force field (P). The experimental results show that the subjects did not learn the internal model of V+P accurately and they compensated for the loads by using impedance control. Our results suggest that humans use impedance control when internal models become inaccurate because of the complexity of the external dynamics.

  18. Dynamic subcellular localization of a respiratory complex controls bacterial respiration.

    PubMed

    Alberge, François; Espinosa, Leon; Seduk, Farida; Sylvi, Léa; Toci, René; Walburger, Anne; Magalon, Axel

    2015-01-01

    Respiration, an essential process for most organisms, has to optimally respond to changes in the metabolic demand or the environmental conditions. The branched character of their respiratory chains allows bacteria to do so by providing a great metabolic and regulatory flexibility. Here, we show that the native localization of the nitrate reductase, a major respiratory complex under anaerobiosis in Escherichia coli, is submitted to tight spatiotemporal regulation in response to metabolic conditions via a mechanism using the transmembrane proton gradient as a cue for polar localization. These dynamics are critical for controlling the activity of nitrate reductase, as the formation of polar assemblies potentiates the electron flux through the complex. Thus, dynamic subcellular localization emerges as a critical factor in the control of respiration in bacteria.

  19. Dynamic subcellular localization of a respiratory complex controls bacterial respiration

    PubMed Central

    Alberge, François; Espinosa, Leon; Seduk, Farida; Sylvi, Léa; Toci, René; Walburger, Anne; Magalon, Axel

    2015-01-01

    Respiration, an essential process for most organisms, has to optimally respond to changes in the metabolic demand or the environmental conditions. The branched character of their respiratory chains allows bacteria to do so by providing a great metabolic and regulatory flexibility. Here, we show that the native localization of the nitrate reductase, a major respiratory complex under anaerobiosis in Escherichia coli, is submitted to tight spatiotemporal regulation in response to metabolic conditions via a mechanism using the transmembrane proton gradient as a cue for polar localization. These dynamics are critical for controlling the activity of nitrate reductase, as the formation of polar assemblies potentiates the electron flux through the complex. Thus, dynamic subcellular localization emerges as a critical factor in the control of respiration in bacteria. DOI: http://dx.doi.org/10.7554/eLife.05357.001 PMID:26077726

  20. Practical synchronization on complex dynamical networks via optimal pinning control.

    PubMed

    Li, Kezan; Sun, Weigang; Small, Michael; Fu, Xinchu

    2015-07-01

    We consider practical synchronization on complex dynamical networks under linear feedback control designed by optimal control theory. The control goal is to minimize global synchronization error and control strength over a given finite time interval, and synchronization error at terminal time. By utilizing the Pontryagin's minimum principle, and based on a general complex dynamical network, we obtain an optimal system to achieve the control goal. The result is verified by performing some numerical simulations on Star networks, Watts-Strogatz networks, and Barabási-Albert networks. Moreover, by combining optimal control and traditional pinning control, we propose an optimal pinning control strategy which depends on the network's topological structure. Obtained results show that optimal pinning control is very effective for synchronization control in real applications. PMID:26274112

  1. Complex Network from Pseudoperiodic Time Series: Topology versus Dynamics

    NASA Astrophysics Data System (ADS)

    Zhang, J.; Small, M.

    2006-06-01

    We construct complex networks from pseudoperiodic time series, with each cycle represented by a single node in the network. We investigate the statistical properties of these networks for various time series and find that time series with different dynamics exhibit distinct topological structures. Specifically, noisy periodic signals correspond to random networks, and chaotic time series generate networks that exhibit small world and scale free features. We show that this distinction in topological structure results from the hierarchy of unstable periodic orbits embedded in the chaotic attractor. Standard measures of structure in complex networks can therefore be applied to distinguish different dynamic regimes in time series. Application to human electrocardiograms shows that such statistical properties are able to differentiate between the sinus rhythm cardiograms of healthy volunteers and those of coronary care patients.

  2. Topics in Complexity: Dynamical Patterns in the Cyberworld

    NASA Astrophysics Data System (ADS)

    Qi, Hong

    Quantitative understanding of mechanism in complex systems is a common "difficult" problem across many fields such as physical, biological, social and economic sciences. Investigation on underlying dynamics of complex systems and building individual-based models have recently been fueled by big data resulted from advancing information technology. This thesis investigates complex systems in social science, focusing on civil unrests on streets and relevant activities online. Investigation consists of collecting data of unrests from open digital source, featuring dynamical patterns underlying, making predictions and constructing models. A simple law governing the progress of two-sided confrontations is proposed with data of activities at micro-level. Unraveling the connections between activity of organizing online and outburst of unrests on streets gives rise to a further meso-level pattern of human behavior, through which adversarial groups evolve online and hyper-escalate ahead of real-world uprisings. Based on the patterns found, noticeable improvement of prediction of civil unrests is achieved. Meanwhile, novel model created from combination of mobility dynamics in the cyberworld and a traditional contagion model can better capture the characteristics of modern civil unrests and other contagion-like phenomena than the original one.

  3. Quantifying spatiotemporal complexity of cardiac dynamics using ordinal patterns.

    PubMed

    Schlemmer, Alexander; Berg, Sebastian; Shajahan, T K; Luther, Stefan; Parlitz, Ulrich

    2015-08-01

    Analyzing the dynamics of complex excitation wave patterns in cardiac tissue plays a key role for understanding the origin of life-threatening arrhythmias and for devising novel approaches to control them. The quantification of spatiotemporal complexity, however, remains a challenging task. This holds in particular for the analysis of data from fluorescence imaging (optical mapping), which allows for the measurement of membrane potential and intracellular calcium at high spatial and temporal resolution. Hitherto methods, like dominant frequency maps and the analysis of phase singularities, address important aspects of cardiac dynamics, but they consider very specific properties of excitable media, only. This article focuses on the benchmark of spatial complexity measures over time in the context of cardiac cell cultures. Standard Shannon Entropy and Spatial Permutation Entropy, an adaption of [1], have been implemented and applied to optical mapping data from embryonic chicken cell culture experiments. We introduce spatial separation of samples when generating ordinal patterns and show its importance for Spatial Permutation Entropy. Results suggest that Spatial Permutation Entropies provide a robust and interpretable measure for detecting qualitative changes in the dynamics of this excitable medium. PMID:26737183

  4. Human opinion dynamics: an inspiration to solve complex optimization problems.

    PubMed

    Kaur, Rishemjit; Kumar, Ritesh; Bhondekar, Amol P; Kapur, Pawan

    2013-01-01

    Human interactions give rise to the formation of different kinds of opinions in a society. The study of formations and dynamics of opinions has been one of the most important areas in social physics. The opinion dynamics and associated social structure leads to decision making or so called opinion consensus. Opinion formation is a process of collective intelligence evolving from the integrative tendencies of social influence with the disintegrative effects of individualisation, and therefore could be exploited for developing search strategies. Here, we demonstrate that human opinion dynamics can be utilised to solve complex mathematical optimization problems. The results have been compared with a standard algorithm inspired from bird flocking behaviour and the comparison proves the efficacy of the proposed approach in general. Our investigation may open new avenues towards understanding the collective decision making. PMID:24141795

  5. Human opinion dynamics: An inspiration to solve complex optimization problems

    PubMed Central

    Kaur, Rishemjit; Kumar, Ritesh; Bhondekar, Amol P.; Kapur, Pawan

    2013-01-01

    Human interactions give rise to the formation of different kinds of opinions in a society. The study of formations and dynamics of opinions has been one of the most important areas in social physics. The opinion dynamics and associated social structure leads to decision making or so called opinion consensus. Opinion formation is a process of collective intelligence evolving from the integrative tendencies of social influence with the disintegrative effects of individualisation, and therefore could be exploited for developing search strategies. Here, we demonstrate that human opinion dynamics can be utilised to solve complex mathematical optimization problems. The results have been compared with a standard algorithm inspired from bird flocking behaviour and the comparison proves the efficacy of the proposed approach in general. Our investigation may open new avenues towards understanding the collective decision making. PMID:24141795

  6. Dynamical complexity in the C.elegans neural network

    NASA Astrophysics Data System (ADS)

    Antonopoulos, C. G.; Fokas, A. S.; Bountis, T. C.

    2016-09-01

    We model the neuronal circuit of the C.elegans soil worm in terms of a Hindmarsh-Rose system of ordinary differential equations, dividing its circuit into six communities which are determined via the Walktrap and Louvain methods. Using the numerical solution of these equations, we analyze important measures of dynamical complexity, namely synchronicity, the largest Lyapunov exponent, and the ΦAR auto-regressive integrated information theory measure. We show that ΦAR provides a useful measure of the information contained in the C.elegans brain dynamic network. Our analysis reveals that the C.elegans brain dynamic network generates more information than the sum of its constituent parts, and that attains higher levels of integrated information for couplings for which either all its communities are highly synchronized, or there is a mixed state of highly synchronized and desynchronized communities.

  7. Human opinion dynamics: An inspiration to solve complex optimization problems

    NASA Astrophysics Data System (ADS)

    Kaur, Rishemjit; Kumar, Ritesh; Bhondekar, Amol P.; Kapur, Pawan

    2013-10-01

    Human interactions give rise to the formation of different kinds of opinions in a society. The study of formations and dynamics of opinions has been one of the most important areas in social physics. The opinion dynamics and associated social structure leads to decision making or so called opinion consensus. Opinion formation is a process of collective intelligence evolving from the integrative tendencies of social influence with the disintegrative effects of individualisation, and therefore could be exploited for developing search strategies. Here, we demonstrate that human opinion dynamics can be utilised to solve complex mathematical optimization problems. The results have been compared with a standard algorithm inspired from bird flocking behaviour and the comparison proves the efficacy of the proposed approach in general. Our investigation may open new avenues towards understanding the collective decision making.

  8. Is the Langevin phase equation an efficient model for oscillating neurons?

    NASA Astrophysics Data System (ADS)

    Ota, Keisuke; Tsunoda, Takamasa; Omori, Toshiaki; Watanabe, Shigeo; Miyakawa, Hiroyoshi; Okada, Masato; Aonishi, Toru

    2009-12-01

    The Langevin phase model is an important canonical model for capturing coherent oscillations of neural populations. However, little attention has been given to verifying its applicability. In this paper, we demonstrate that the Langevin phase equation is an efficient model for neural oscillators by using the machine learning method in two steps: (a) Learning of the Langevin phase model. We estimated the parameters of the Langevin phase equation, i.e., a phase response curve and the intensity of white noise from physiological data measured in the hippocampal CA1 pyramidal neurons. (b) Test of the estimated model. We verified whether a Fokker-Planck equation derived from the Langevin phase equation with the estimated parameters could capture the stochastic oscillatory behavior of the same neurons disturbed by periodic perturbations. The estimated model could predict the neural behavior, so we can say that the Langevin phase equation is an efficient model for oscillating neurons.

  9. Complex elaboration: making sense of meiotic cohesin dynamics

    PubMed Central

    Rankin, Susannah

    2015-01-01

    In mitotically dividing cells, the cohesin complex tethers sister chromatids, the products of DNA replication, together from the time they are generated during S phase until anaphase. Cohesion between sister chromatids ensures accurate chromosome segregation, and promotes normal gene regulation and certain kinds of DNA repair. In somatic cells, the core cohesin complex is composed of four subunits: Smc1, Smc3, Rad21 and an SA subunit. During meiotic cell divisions meiosis-specific isoforms of several of the cohesin subunits are also expressed and incorporated into distinct meiotic cohesin complexes. The relative contributions of these meiosis-specific forms of cohesin to chromosome dynamics during meiotic progression have not been fully worked out. However, the localization of these proteins during chromosome pairing and synapsis, and their unique loss-of-function phenotypes, suggest non-overlapping roles in controlling meiotic chromosome behavior. Many of the proteins that regulate cohesin function during mitosis also appear to regulate cohesin during meiosis. Here we review how cohesin contributes to meiotic chromosome dynamics, and explore similarities and differences between cohesin regulation during the mitotic cell cycle and meiotic progression. A deeper understanding of the regulation and function of cohesin in meiosis will provide important new insights into how the cohesin complex is able to promote distinct kinds of chromosome interactions under diverse conditions. PMID:25895170

  10. Intranuclear dynamics of the Nup107-160 complex

    PubMed Central

    Morchoisne-Bolhy, Stéphanie; Geoffroy, Marie-Claude; Bouhlel, Imène B.; Alves, Annabelle; Audugé, Nicolas; Baudin, Xavier; Van Bortle, Kevin; Powers, Maureen A.; Doye, Valérie

    2015-01-01

    Nup98 is a glycine-leucine-phenylalanine-glycine (GLFG) repeat–containing nucleoporin that, in addition to nuclear transport, contributes to multiple aspects of gene regulation. Previous studies revealed its dynamic localization within intranuclear structures known as GLFG bodies. Here we show that the mammalian Nup107-160 complex (Y-complex), a major scaffold module of the nuclear pore, together with its partner Elys, colocalizes with Nup98 in GLFG bodies. The frequency and size of GLFG bodies vary among HeLa sublines, and we find that an increased level of Nup98 is associated with the presence of bodies. Recruitment of the Y-complex and Elys into GLFG bodies requires the C-terminal domain of Nup98. During cell division, Y-Nup–containing GLFG bodies are disassembled in mitotic prophase, significantly ahead of nuclear pore disassembly. FRAP studies revealed that, unlike at nuclear pores, the Y-complex shuttles into and out of GLFG bodies. Finally, we show that within the nucleoplasm, a fraction of Nup107, a key component of the Y-complex, displays reduced mobility, suggesting interaction with other nuclear components. Together our data uncover a previously neglected intranuclear pool of the Y-complex that may underscore a yet-uncharacterized function of these nucleoporins inside the nucleus, even in cells that contain no detectable GLFG bodies. PMID:25904327

  11. Intranuclear dynamics of the Nup107-160 complex.

    PubMed

    Morchoisne-Bolhy, Stéphanie; Geoffroy, Marie-Claude; Bouhlel, Imène B; Alves, Annabelle; Audugé, Nicolas; Baudin, Xavier; Van Bortle, Kevin; Powers, Maureen A; Doye, Valérie

    2015-06-15

    Nup98 is a glycine-leucine-phenylalanine-glycine (GLFG) repeat-containing nucleoporin that, in addition to nuclear transport, contributes to multiple aspects of gene regulation. Previous studies revealed its dynamic localization within intranuclear structures known as GLFG bodies. Here we show that the mammalian Nup107-160 complex (Y-complex), a major scaffold module of the nuclear pore, together with its partner Elys, colocalizes with Nup98 in GLFG bodies. The frequency and size of GLFG bodies vary among HeLa sublines, and we find that an increased level of Nup98 is associated with the presence of bodies. Recruitment of the Y-complex and Elys into GLFG bodies requires the C-terminal domain of Nup98. During cell division, Y-Nup-containing GLFG bodies are disassembled in mitotic prophase, significantly ahead of nuclear pore disassembly. FRAP studies revealed that, unlike at nuclear pores, the Y-complex shuttles into and out of GLFG bodies. Finally, we show that within the nucleoplasm, a fraction of Nup107, a key component of the Y-complex, displays reduced mobility, suggesting interaction with other nuclear components. Together our data uncover a previously neglected intranuclear pool of the Y-complex that may underscore a yet-uncharacterized function of these nucleoporins inside the nucleus, even in cells that contain no detectable GLFG bodies.

  12. Universality of flux-fluctuation law in complex dynamical systems

    NASA Astrophysics Data System (ADS)

    Zhou, Zhao; Huang, Zi-Gang; Huang, Liang; Lai, Ying-Cheng; Yang, Lei; Xue, De-Sheng

    2013-01-01

    Recent work has revealed a law governing flux fluctuation and the average flux in complex dynamical systems. We establish the universality of this flux-fluctuation law through the following steps: (i) We derive the law in a more general setting, showing that it depends on a single parameter characterizing the external driving; (ii) we conduct extensive numerical computations using distinct external driving, different network topologies, and multiple traffic routing strategies; and (iii) we analyze data from an actual vehicle traffic system in a major city in China to lend more credence to the universality of the flux-fluctuation law. Additional factors considered include flux fluctuation on links, window size effect, and hidden topological structures such as nodal degree correlation. Besides its fundamental importance in complex systems, the flux-fluctuation law can be used to infer certain intrinsic property of the system for potential applications such as control of complex systems for improved performance.

  13. Dynamically reconfigurable complex emulsions via tunable interfacial tensions.

    PubMed

    Zarzar, Lauren D; Sresht, Vishnu; Sletten, Ellen M; Kalow, Julia A; Blankschtein, Daniel; Swager, Timothy M

    2015-02-26

    Emulsification is a powerful, well-known technique for mixing and dispersing immiscible components within a continuous liquid phase. Consequently, emulsions are central components of medicine, food and performance materials. Complex emulsions, including Janus droplets (that is, droplets with faces of differing chemistries) and multiple emulsions, are of increasing importance in pharmaceuticals and medical diagnostics, in the fabrication of microparticles and capsules for food, in chemical separations, in cosmetics, and in dynamic optics. Because complex emulsion properties and functions are related to the droplet geometry and composition, the development of rapid, simple fabrication approaches allowing precise control over the droplets' physical and chemical characteristics is critical. Significant advances in the fabrication of complex emulsions have been made using a number of procedures, ranging from large-scale, less precise techniques that give compositional heterogeneity using high-shear mixers and membranes, to small-volume but more precise microfluidic methods. However, such approaches have yet to create droplet morphologies that can be controllably altered after emulsification. Reconfigurable complex liquids potentially have great utility as dynamically tunable materials. Here we describe an approach to the one-step fabrication of three- and four-phase complex emulsions with highly controllable and reconfigurable morphologies. The fabrication makes use of the temperature-sensitive miscibility of hydrocarbon, silicone and fluorocarbon liquids, and is applied to both the microfluidic and the scalable batch production of complex droplets. We demonstrate that droplet geometries can be alternated between encapsulated and Janus configurations by varying the interfacial tensions using hydrocarbon and fluorinated surfactants including stimuli-responsive and cleavable surfactants. This yields a generalizable strategy for the fabrication of multiphase emulsions with

  14. Dynamically reconfigurable complex emulsions via tunable interfacial tensions

    PubMed Central

    Zarzar, Lauren D.; Sresht, Vishnu; Sletten, Ellen M.; Kalow, Julia A.; Blankschtein, Daniel; Swager, Timothy M.

    2015-01-01

    Emulsification is a powerful, well-known technique for mixing and dispersing immiscible components within a continuous liquid phase. Consequently, emulsions are central components of medicine, food and performance materials. Complex emulsions, including multiple emulsions and Janus droplets which contain hemispheres of differing material, are of increasing importance1 in pharmaceuticals and medical diagnostics2, in the fabrication of microparticles and capsules3–5 for food6, in chemical separations7, in cosmetics8, and in dynamic optics9. Because complex emulsion properties and functions are related to the droplet geometry and composition, the development of rapid, simple fabrication approaches allowing precise control over the droplets’ physical and chemical characteristics is critical. Significant advances in the fabrication of complex emulsions have been made using a number of procedures, ranging from large-scale, less precise techniques that give compositional heterogeneity using high-shear mixers and membranes10, to small-volume but more precise microfluidic methods11,12. However, such approaches have yet to create droplet morphologies that can be controllably altered after emulsification. Reconfigurable complex liquids potentially have greatly increased utility as dynamically tunable materials. Here we describe an approach to the one-step fabrication of three- and four-phase complex emulsions with highly controllable and reconfigurable morphologies. The fabrication makes use of the temperature-sensitive miscibility of hydrocarbon, silicone and fluorocarbon liquids, and is applied to both the microfluidic and the scalable batch production of complex droplets. We demonstrate that droplet geometries can be alternated between encapsulated and Janus configurations by varying the interfacial tensions using hydrocarbon and fluorinated surfactants including stimuli-responsive and cleavable surfactants. This yields a generalizable strategy for the fabrication of

  15. Dynamically reconfigurable complex emulsions via tunable interfacial tensions

    NASA Astrophysics Data System (ADS)

    Zarzar, Lauren D.; Sresht, Vishnu; Sletten, Ellen M.; Kalow, Julia A.; Blankschtein, Daniel; Swager, Timothy M.

    2015-02-01

    Emulsification is a powerful, well-known technique for mixing and dispersing immiscible components within a continuous liquid phase. Consequently, emulsions are central components of medicine, food and performance materials. Complex emulsions, including Janus droplets (that is, droplets with faces of differing chemistries) and multiple emulsions, are of increasing importance in pharmaceuticals and medical diagnostics, in the fabrication of microparticles and capsules for food, in chemical separations, in cosmetics, and in dynamic optics. Because complex emulsion properties and functions are related to the droplet geometry and composition, the development of rapid, simple fabrication approaches allowing precise control over the droplets' physical and chemical characteristics is critical. Significant advances in the fabrication of complex emulsions have been made using a number of procedures, ranging from large-scale, less precise techniques that give compositional heterogeneity using high-shear mixers and membranes, to small-volume but more precise microfluidic methods. However, such approaches have yet to create droplet morphologies that can be controllably altered after emulsification. Reconfigurable complex liquids potentially have great utility as dynamically tunable materials. Here we describe an approach to the one-step fabrication of three- and four-phase complex emulsions with highly controllable and reconfigurable morphologies. The fabrication makes use of the temperature-sensitive miscibility of hydrocarbon, silicone and fluorocarbon liquids, and is applied to both the microfluidic and the scalable batch production of complex droplets. We demonstrate that droplet geometries can be alternated between encapsulated and Janus configurations by varying the interfacial tensions using hydrocarbon and fluorinated surfactants including stimuli-responsive and cleavable surfactants. This yields a generalizable strategy for the fabrication of multiphase emulsions with

  16. The Complexity of Dynamics in Small Neural Circuits

    PubMed Central

    Panzeri, Stefano

    2016-01-01

    Mean-field approximations are a powerful tool for studying large neural networks. However, they do not describe well the behavior of networks composed of a small number of neurons. In this case, major differences between the mean-field approximation and the real behavior of the network can arise. Yet, many interesting problems in neuroscience involve the study of mesoscopic networks composed of a few tens of neurons. Nonetheless, mathematical methods that correctly describe networks of small size are still rare, and this prevents us to make progress in understanding neural dynamics at these intermediate scales. Here we develop a novel systematic analysis of the dynamics of arbitrarily small networks composed of homogeneous populations of excitatory and inhibitory firing-rate neurons. We study the local bifurcations of their neural activity with an approach that is largely analytically tractable, and we numerically determine the global bifurcations. We find that for strong inhibition these networks give rise to very complex dynamics, caused by the formation of multiple branching solutions of the neural dynamics equations that emerge through spontaneous symmetry-breaking. This qualitative change of the neural dynamics is a finite-size effect of the network, that reveals qualitative and previously unexplored differences between mesoscopic cortical circuits and their mean-field approximation. The most important consequence of spontaneous symmetry-breaking is the ability of mesoscopic networks to regulate their degree of functional heterogeneity, which is thought to help reducing the detrimental effect of noise correlations on cortical information processing. PMID:27494737

  17. Modularity and the spread of perturbations in complex dynamical systems

    NASA Astrophysics Data System (ADS)

    Kolchinsky, Artemy; Gates, Alexander J.; Rocha, Luis M.

    2015-12-01

    We propose a method to decompose dynamical systems based on the idea that modules constrain the spread of perturbations. We find partitions of system variables that maximize "perturbation modularity," defined as the autocovariance of coarse-grained perturbed trajectories. The measure effectively separates the fast intramodular from the slow intermodular dynamics of perturbation spreading (in this respect, it is a generalization of the "Markov stability" method of network community detection). Our approach captures variation of modular organization across different system states, time scales, and in response to different kinds of perturbations: aspects of modularity which are all relevant to real-world dynamical systems. It offers a principled alternative to detecting communities in networks of statistical dependencies between system variables (e.g., "relevance networks" or "functional networks"). Using coupled logistic maps, we demonstrate that the method uncovers hierarchical modular organization planted in a system's coupling matrix. Additionally, in homogeneously coupled map lattices, it identifies the presence of self-organized modularity that depends on the initial state, dynamical parameters, and type of perturbations. Our approach offers a powerful tool for exploring the modular organization of complex dynamical systems.

  18. The Complexity of Dynamics in Small Neural Circuits.

    PubMed

    Fasoli, Diego; Cattani, Anna; Panzeri, Stefano

    2016-08-01

    Mean-field approximations are a powerful tool for studying large neural networks. However, they do not describe well the behavior of networks composed of a small number of neurons. In this case, major differences between the mean-field approximation and the real behavior of the network can arise. Yet, many interesting problems in neuroscience involve the study of mesoscopic networks composed of a few tens of neurons. Nonetheless, mathematical methods that correctly describe networks of small size are still rare, and this prevents us to make progress in understanding neural dynamics at these intermediate scales. Here we develop a novel systematic analysis of the dynamics of arbitrarily small networks composed of homogeneous populations of excitatory and inhibitory firing-rate neurons. We study the local bifurcations of their neural activity with an approach that is largely analytically tractable, and we numerically determine the global bifurcations. We find that for strong inhibition these networks give rise to very complex dynamics, caused by the formation of multiple branching solutions of the neural dynamics equations that emerge through spontaneous symmetry-breaking. This qualitative change of the neural dynamics is a finite-size effect of the network, that reveals qualitative and previously unexplored differences between mesoscopic cortical circuits and their mean-field approximation. The most important consequence of spontaneous symmetry-breaking is the ability of mesoscopic networks to regulate their degree of functional heterogeneity, which is thought to help reducing the detrimental effect of noise correlations on cortical information processing. PMID:27494737

  19. Composite generalized Langevin equation for Brownian motion in different hydrodynamic and adhesion regimes.

    PubMed

    Yu, Hsiu-Yu; Eckmann, David M; Ayyaswamy, Portonovo S; Radhakrishnan, Ravi

    2015-05-01

    We present a composite generalized Langevin equation as a unified framework for bridging the hydrodynamic, Brownian, and adhesive spring forces associated with a nanoparticle at different positions from a wall, namely, a bulklike regime, a near-wall regime, and a lubrication regime. The particle velocity autocorrelation function dictates the dynamical interplay between the aforementioned forces, and our proposed methodology successfully captures the well-known hydrodynamic long-time tail with context-dependent scaling exponents and oscillatory behavior due to the binding interaction. Employing the reactive flux formalism, we analyze the effect of hydrodynamic variables on the particle trajectory and characterize the transient kinetics of a particle crossing a predefined milestone. The results suggest that both wall-hydrodynamic interactions and adhesion strength impact the particle kinetics.

  20. Time-local Heisenberg-Langevin equations and the driven qubit

    NASA Astrophysics Data System (ADS)

    Whalen, S. J.; Carmichael, H. J.

    2016-06-01

    The time-local master equation for a driven boson system interacting with a boson environment is derived by way of a time-local Heisenberg-Langevin equation. Extension to the driven qubit fails—except for weak excitation—due to the lost linearity of the system-environment interaction. We show that a reported time-local master equation for the driven qubit is incorrect. As a corollary to our demonstration, we also uncover odd asymptotic behavior in the "repackaged" time-local dynamics of a system driven to a far-from-equilibrium steady state: the density operator becomes steady while time-dependent coefficients oscillate (with periodic singularities) forever.

  1. A Langevin Approach to a Classical Brownian Oscillator in an Electromagnetic Field

    NASA Astrophysics Data System (ADS)

    Espinoza Ortiz, J. S.; Bauke, F. C.; Lagos, R. E.

    2016-08-01

    We consider a charged Brownian particle bounded by an harmonic potential, embedded in a Markovian heat bath and driven from equilibrium by external electric and magnetic fields. We develop a quaternionic-like (or Pauli spinor-like) representation, hitherto exploited in classical Lorentz related dynamics. Within this formalism, in a very straight forward and elegant fashion, we compute the exact solution for the resulting generalized Langevin equation, for the case of a constant magnetic field. For the case the source electromagnetic fields satisfy Maxwell's equations, yielding spinor-like Mathieu equations, we compute the solutions within the JWKB approximation. With the solutions at hand we further compute spatial, velocities and crossed time correlations. In particular we study the (kinetically defined) nonequilbrium temperature. Therefore, we can display the system's time evolution towards equilibrium or towards non equilibrium (steady or not) states.

  2. Inferring Dynamic Signatures of Microbes in Complex Host Ecosystems

    PubMed Central

    Gerber, Georg K.; Onderdonk, Andrew B.; Bry, Lynn

    2012-01-01

    The human gut microbiota comprise a complex and dynamic ecosystem that profoundly affects host development and physiology. Standard approaches for analyzing time-series data of the microbiota involve computation of measures of ecological community diversity at each time-point, or measures of dissimilarity between pairs of time-points. Although these approaches, which treat data as static snapshots of microbial communities, can identify shifts in overall community structure, they fail to capture the dynamic properties of individual members of the microbiota and their contributions to the underlying time-varying behavior of host ecosystems. To address the limitations of current methods, we present a computational framework that uses continuous-time dynamical models coupled with Bayesian dimensionality adaptation methods to identify time-dependent signatures of individual microbial taxa within a host as well as across multiple hosts. We apply our framework to a publicly available dataset of 16S rRNA gene sequences from stool samples collected over ten months from multiple human subjects, each of whom received repeated courses of oral antibiotics. Using new diversity measures enabled by our framework, we discover groups of both phylogenetically close and distant bacterial taxa that exhibit consensus responses to antibiotic exposure across multiple human subjects. These consensus responses reveal a timeline for equilibration of sub-communities of micro-organisms with distinct physiologies, yielding insights into the successive changes that occur in microbial populations in the human gut after antibiotic treatments. Additionally, our framework leverages microbial signatures shared among human subjects to automatically design optimal experiments to interrogate dynamic properties of the microbiota in new studies. Overall, our approach provides a powerful, general-purpose framework for understanding the dynamic behaviors of complex microbial ecosystems, which we believe

  3. Outlier-resilient complexity analysis of heartbeat dynamics

    NASA Astrophysics Data System (ADS)

    Lo, Men-Tzung; Chang, Yi-Chung; Lin, Chen; Young, Hsu-Wen Vincent; Lin, Yen-Hung; Ho, Yi-Lwun; Peng, Chung-Kang; Hu, Kun

    2015-03-01

    Complexity in physiological outputs is believed to be a hallmark of healthy physiological control. How to accurately quantify the degree of complexity in physiological signals with outliers remains a major barrier for translating this novel concept of nonlinear dynamic theory to clinical practice. Here we propose a new approach to estimate the complexity in a signal by analyzing the irregularity of the sign time series of its coarse-grained time series at different time scales. Using surrogate data, we show that the method can reliably assess the complexity in noisy data while being highly resilient to outliers. We further apply this method to the analysis of human heartbeat recordings. Without removing any outliers due to ectopic beats, the method is able to detect a degradation of cardiac control in patients with congestive heart failure and a more degradation in critically ill patients whose life continuation relies on extracorporeal membrane oxygenator (ECMO). Moreover, the derived complexity measures can predict the mortality of ECMO patients. These results indicate that the proposed method may serve as a promising tool for monitoring cardiac function of patients in clinical settings.

  4. Outlier-resilient complexity analysis of heartbeat dynamics

    PubMed Central

    Lo, Men-Tzung; Chang, Yi-Chung; Lin, Chen; Young, Hsu-Wen Vincent; Lin, Yen-Hung; Ho, Yi-Lwun; Peng, Chung-Kang; Hu, Kun

    2015-01-01

    Complexity in physiological outputs is believed to be a hallmark of healthy physiological control. How to accurately quantify the degree of complexity in physiological signals with outliers remains a major barrier for translating this novel concept of nonlinear dynamic theory to clinical practice. Here we propose a new approach to estimate the complexity in a signal by analyzing the irregularity of the sign time series of its coarse-grained time series at different time scales. Using surrogate data, we show that the method can reliably assess the complexity in noisy data while being highly resilient to outliers. We further apply this method to the analysis of human heartbeat recordings. Without removing any outliers due to ectopic beats, the method is able to detect a degradation of cardiac control in patients with congestive heart failure and a more degradation in critically ill patients whose life continuation relies on extracorporeal membrane oxygenator (ECMO). Moreover, the derived complexity measures can predict the mortality of ECMO patients. These results indicate that the proposed method may serve as a promising tool for monitoring cardiac function of patients in clinical settings. PMID:25744292

  5. Outlier-resilient complexity analysis of heartbeat dynamics.

    PubMed

    Lo, Men-Tzung; Chang, Yi-Chung; Lin, Chen; Young, Hsu-Wen Vincent; Lin, Yen-Hung; Ho, Yi-Lwun; Peng, Chung-Kang; Hu, Kun

    2015-01-01

    Complexity in physiological outputs is believed to be a hallmark of healthy physiological control. How to accurately quantify the degree of complexity in physiological signals with outliers remains a major barrier for translating this novel concept of nonlinear dynamic theory to clinical practice. Here we propose a new approach to estimate the complexity in a signal by analyzing the irregularity of the sign time series of its coarse-grained time series at different time scales. Using surrogate data, we show that the method can reliably assess the complexity in noisy data while being highly resilient to outliers. We further apply this method to the analysis of human heartbeat recordings. Without removing any outliers due to ectopic beats, the method is able to detect a degradation of cardiac control in patients with congestive heart failure and a more degradation in critically ill patients whose life continuation relies on extracorporeal membrane oxygenator (ECMO). Moreover, the derived complexity measures can predict the mortality of ECMO patients. These results indicate that the proposed method may serve as a promising tool for monitoring cardiac function of patients in clinical settings. PMID:25744292

  6. A study of QM/Langevin-MD simulation for oxygen-evolving center of photosystem II

    SciTech Connect

    Uchida, Waka; Kimura, Yoshiro; Wakabayashi, Masamitsu; Hatakeyama, Makoto; Ogata, Koji; Nakamura, Shinichiro; Yokojima, Satoshi

    2013-12-10

    We have performed three QM/Langevin-MD simulations for oxygen-evolving complex (OEC) and surrounding residues, which are different configurations of the oxidation numbers on Mn atoms in the Mn{sub 4}O{sub 5}Ca cluster. By analyzing these trajectories, we have observed sensitivity of the change to the configuration of Mn oxidation state on O atoms of carboxyl on three amino acids, Glu354, Ala344, and Glu333. The distances from Mn to O atoms in residues contacting with the Mn{sub 4}O{sub 5}Ca cluster were analyzed for the three trajectories. We found the good correlation of the distances among the simulations. However, the distances with Glu354, Ala344, and Glu333 have not shown the correlation. These residues can be sensitive index of the changes of Mn oxidation numbers.

  7. Solving the generalized Langevin equation with the algebraically correlated noise

    NASA Astrophysics Data System (ADS)

    Srokowski, T.; Płoszajczak, M.

    1998-04-01

    We solve the Langevin equation with the memory kernel. The stochastic force possesses algebraic correlations, proportional to 1/t. The velocity autocorrelation function and related quantities characterizing transport properties are calculated with the assumption that the system is in thermal equilibrium. Stochastic trajectories are simulated numerically, using the kangaroo process as a noise generator. Results of this simulation resemble Lévy walks with divergent moments of the velocity distribution. We consider motion of a Brownian particle, both without any external potential and in the harmonic oscillator field, in particular the escape from a potential well. The results are compared with memory-free calculations for the Brownian particle.

  8. The Dynamics of Coalition Formation on Complex Networks

    PubMed Central

    Auer, S.; Heitzig, J.; Kornek, U.; Schöll, E.; Kurths, J.

    2015-01-01

    Complex networks describe the structure of many socio-economic systems. However, in studies of decision-making processes the evolution of the underlying social relations are disregarded. In this report, we aim to understand the formation of self-organizing domains of cooperation (“coalitions”) on an acquaintance network. We include both the network’s influence on the formation of coalitions and vice versa how the network adapts to the current coalition structure, thus forming a social feedback loop. We increase complexity from simple opinion adaptation processes studied in earlier research to more complex decision-making determined by costs and benefits, and from bilateral to multilateral cooperation. We show how phase transitions emerge from such coevolutionary dynamics, which can be interpreted as processes of great transformations. If the network adaptation rate is high, the social dynamics prevent the formation of a grand coalition and therefore full cooperation. We find some empirical support for our main results: Our model develops a bimodal coalition size distribution over time similar to those found in social structures. Our detection and distinguishing of phase transitions may be exemplary for other models of socio-economic systems with low agent numbers and therefore strong finite-size effects. PMID:26303622

  9. The Dynamics of Coalition Formation on Complex Networks

    NASA Astrophysics Data System (ADS)

    Auer, S.; Heitzig, J.; Kornek, U.; Schöll, E.; Kurths, J.

    2015-08-01

    Complex networks describe the structure of many socio-economic systems. However, in studies of decision-making processes the evolution of the underlying social relations are disregarded. In this report, we aim to understand the formation of self-organizing domains of cooperation (“coalitions”) on an acquaintance network. We include both the network’s influence on the formation of coalitions and vice versa how the network adapts to the current coalition structure, thus forming a social feedback loop. We increase complexity from simple opinion adaptation processes studied in earlier research to more complex decision-making determined by costs and benefits, and from bilateral to multilateral cooperation. We show how phase transitions emerge from such coevolutionary dynamics, which can be interpreted as processes of great transformations. If the network adaptation rate is high, the social dynamics prevent the formation of a grand coalition and therefore full cooperation. We find some empirical support for our main results: Our model develops a bimodal coalition size distribution over time similar to those found in social structures. Our detection and distinguishing of phase transitions may be exemplary for other models of socio-economic systems with low agent numbers and therefore strong finite-size effects.

  10. Young Children's Knowledge About the Moon: A Complex Dynamic System

    NASA Astrophysics Data System (ADS)

    Venville, Grady J.; Louisell, Robert D.; Wilhelm, Jennifer A.

    2012-08-01

    The purpose of this research was to use a multidimensional theoretical framework to examine young children's knowledge about the Moon. The research was conducted in the interpretive paradigm and the design was a multiple case study of ten children between the ages of three and eight from the USA and Australia. A detailed, semi-structured interview was conducted with each child. In addition, each child's parents were interviewed to determine possible social and cultural influences on the child's knowledge. We sought evidence about how the social and cultural experiences of the children might have influenced the development of their ideas. From a cognitive perspective we were interested in whether the children's ideas were constructed in a theory like form or whether the knowledge was the result of gradual accumulation of fragments of isolated cultural information. Findings reflected the strong and complex relationship between individual children, their social and cultural milieu, and the way they construct ideas about the Moon and astronomy. Findings are presented around four themes including ontology, creatures and artefacts, animism, and permanence. The findings support a complex dynamic system view of students' knowledge that integrates the framework theory perspective and the knowledge in fragments perspective. An initial model of a complex dynamic system of young children's knowledge about the Moon is presented.

  11. MADS-complexes regulate transcriptome dynamics during pollen maturation

    PubMed Central

    Verelst, Wim; Twell, David; de Folter, Stefan; Immink, Richard; Saedler, Heinz; Münster, Thomas

    2007-01-01

    Background Differentiation processes are responsible for the diversity and functional specialization of the cell types that compose an organism. The outcome of these processes can be studied at molecular, physiologic, and biochemical levels by comparing different cell types, but the complexity and dynamics of the regulatory processes that specify the differentiation are largely unexplored. Results Here we identified the pollen-specific MIKC* class of MADS-domain transcription factors as major regulators of transcriptome dynamics during male reproductive cell development in Arabidopsis thaliana. Pollen transcript profiling of mutants deficient in different MIKC* protein complexes revealed that they control a transcriptional switch that directs pollen maturation and that is essential for pollen competitive ability. We resolved the functional redundancy among the MIKC* proteins and uncovered part of the underlying network by identifying the non-MIKC* MADS-box genes AGL18 and AGL29 as downstream regulators of a subset of the MIKC* MADS-controlled genes. Conclusion Our results provide a first, unique, and compelling insight into the complexity of a transcription factor network that directs cellular differentiation during pollen maturation, a process that is essential for male reproductive fitness in flowering plants. PMID:18034896

  12. Large scale molecular dynamics study of polymer-surfactant complex

    NASA Astrophysics Data System (ADS)

    Goswami, Monojoy; Sumpter, Bobby

    2012-02-01

    In this work, we study the self-assembly of cationic polyelectrolytes mediated by anionic surfactants in dilute or semi-dilute and gel states. The understanding of the dilute system is a requirement for the understanding of gel states. The importance of polyelectrolyte with oppositely charged colloidal particles can be found in biological systems, such as immobilization of enzymes in polyelectrolyte complexes or nonspecific association of DNA with protein. With the same understanding, interaction of surfactants with polyelectrolytes shows intriguing phenomena that are important for both in academic research as well as industrial applications. Many useful properties of PE surfactant complexes come from the highly ordered structures of surfactant self-assembly inside the PE aggregate. We do large scale molecular dynamics simulation using LAMMPS to understand the structure and dynamics of PE-surfactant systems. Our investigation shows highly ordered ring-string structures that have been observed experimentally in biological systems. We will investigate many different properties of PE-surfactant complexation which will be helpful for pharmaceutical, engineering and biological applications.

  13. Ultrafast excited-state dynamics of copper(I) complexes.

    PubMed

    Iwamura, Munetaka; Takeuchi, Satoshi; Tahara, Tahei

    2015-03-17

    Bis-diimine Cu(I) complexes exhibit strong absorption in the visible region owing to the metal-to-ligand charge transfer (MLCT) transitions, and the triplet MLCT ((3)MLCT) states have long lifetimes. Because these characteristics are highly suitable for photosensitizers and photocatalysts, bis-diimine Cu(I) complexes have been attracting much interest. An intriguing feature of the Cu(I) complexes is the photoinduced structural change called "flattening". Bis-diimine Cu(I) complexes usually have tetrahedron-like D2d structures in the ground (S0) state, in which two ligands are perpendicularly attached to the Cu(I) ion. With MLCT excitation, the central Cu(I) ion is formally oxidized to Cu(II), which induces the structural change to the "flattened" square-planar-like structure that is seen for usual Cu(II) complexes. In this Account, we review our recent studies on ultrafast excited-state dynamics of bis-diimine Cu(I) complexes carried out using femtosecond time-resolved optical spectroscopy. Focusing on three prototypical bis-diimine Cu(I) complexes that have 1,10-phenanthroline ligands with different substituents at the 2,9-positions, i.e., [Cu(phen)2](+) (phen = 1,10-phenanthroline), [Cu(dmphen)2](+) (dmphen = 2,9-dimethyl-1,10-phenanthroline), and [Cu(dpphen)2](+) (dpphen = 2,9-diphenyl-1,10-phenanthroline), we examined their excited-state dynamics by time-resolved emission and absorption spectroscopies with 200 fs time resolution, observed the excited-state coherent nuclear motion with 30 fs time resolution and performed complementary theoretical calculations. This combined approach vividly visualizes excited-state processes in the MLCT state of bis-diimine Cu(I) complexes. It was demonstrated that flattening distortion, internal conversion, and intersystem crossing occur on the femtosecond-early picosecond time scale, and their dynamics is clearly identified separately. The flattening distortion predominantly occurs in the S1 state on the subpicosecond time

  14. Disrupted coarsening in complex Cahn-Hilliard dynamics.

    PubMed

    Simeone, David; Demange, Gilles; Luneville, Laurence

    2013-09-01

    Predicting the pattern formation in a system maintained far from equilibrium is a complex task. For a given dynamics governed by the evolution of a conservative order parameter, recent investigations have demonstrated that the knowledge of the long time expression of the order parameter is sufficient to predict the existence of disrupted coarsening, i.e., the pinning of the inhomogeneities wavelength to a well defined value. However, there exists some dynamics for which the asymptotic form of the order parameter remains unknown. The Cahn-Hilliard-like equation used to describe the stability of solids under irradiation belongs to this class of equations. In this paper, we present an alternative to predict the patterning induced by this equation. Based on a simple ansatz, we calculated the form factor and proved that a disrupted coarsening takes place in such dynamics. This disrupted coarsening results from the bifurcation of the implicit equation linking the characteristic length of the dynamics (k_{m}^{∞})^{-1} to a control parameter describing the irradiation. This analysis is supported by direct simulations. From this paper, it clearly appears that the bifurcation of k_{m}^{∞} is a criterion for disrupted coarsening. PMID:24125222

  15. Ultrafast internal dynamics of flexible hydrogen-bonded supramolecular complexes.

    PubMed

    Olschewski, Martin; Knop, Stephan; Seehusen, Jaane; Lindner, Jörg; Vöhringer, Peter

    2011-02-24

    Supramolecular chemistry is intimately linked to the dynamical interplay between intermolecular forces and intramolecular flexibility. Here, we studied the ultrafast equilibrium dynamics of a supramolecular hydrogen-bonded receptor-substrate complex, 18-crown-6 monohydrate, using Fourier transform infrared (FTIR) and two-dimensional infrared (2DIR) spectroscopy in combination with numerical simulations based on molecular mechanics, density functional theory, and transition state theory. The theoretical calculations suggest that the flexibility of the macrocyclic crown ether receptor is related to an ultrafast crankshaft isomerization occurring on a time scale of several picoseconds and that the OH stretching vibrations of the substrate can serve as internal probes for the receptor's flexibility. The importance of population transfer among the vibrational modes of a given binding motif and of chemical exchange between spectroscopically distinguishable binding motifs for shaping the two-dimensional infrared spectrum and its temporal evolution is discussed. PMID:21271721

  16. Kinetics of the Dynamical Information Shannon Entropy for Complex Systems

    NASA Astrophysics Data System (ADS)

    Yulmetyev, R. M.; Yulmetyeva, D. G.

    1999-08-01

    Kinetic behaviour of dynamical information Shannon entropy is discussed for complex systems: physical systems with non-Markovian property and memory in correlation approximation, and biological and physiological systems with sequences of the Markovian and non-Markovian random noises. For the stochastic processes, a description of the information entropy in terms of normalized time correlation functions is given. The influence and important role of two mutually dependent channels of the entropy change, correlation (creation or generation of correlations) and anti-correlation (decay or annihilation of correlation) is discussed. The method developed here is also used in analysis of the density fluctuations in liquid cesium obtained from slow neutron scattering data, fractal kinetics of the long-range fluctuation in the short-time human memory and chaotic dynamics of R-R intervals of human ECG.

  17. WATERWAVES: wave particles dynamics on a complex triatomic potential

    NASA Astrophysics Data System (ADS)

    Taioli, Simone; Tennyson, Jonathan

    2006-07-01

    The WATERWAVES program suite performs complex scattering calculations by propagating a wave packet in a complex, full-dimensional potential for non-rotating ( J=0) but vibrating triatomic molecules. Potential energy and decay probability surfaces must be provided. Expectation values of geometric quantities can be calculated, which are useful for following the wave packet motion. The programs use a local complex potential approximation (LCP) for the Hamiltonian and Jacobi coordinates. The bottleneck of the calculation is the application of each term of the Hamiltonian to the wave packet. To solve this problem the programs use a different representation for each term: normalized associated Legendre polynomials PjK(x) as a functional basis for the angular kinetic term and an evenly spaced grid for the radial kinetic term yielding a fully point-wise representation of the wave functions. The potential term is treated using an efficient Discrete Variable Representation (DVR) being diagonal in the coordinate representation. The radial kinetic term uses a fast Fourier transform (FFT) to obtain an operator which is diagonal in the momentum space. To avoid artificial reflection at the boundaries of the grid a complex absorbing potential is included for calculating continuum quantities. Asymptotic analysis is performed to obtain scattering observables such as cross sections and other dynamical properties. Program summaryProgram title: WATERWAVES Catalogue identifier:ADXT_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/ADXT_v1_0 Program obtainable from: CPC Program Library, Queen's University of Belfast, N. Ireland Licensing provisions: Freely available from CPC Programming language: Fortran 77 Computer(s) for which the program has been designed: PC Operating system(s) for which the program has been designed: Linux RAM required to execute with typical data: case dependent: test run requires 976 024 kB No. of bytes in distributed program, including test data, etc.:11

  18. Universal nonexponential relaxation: Complex dynamics in simple liquids.

    PubMed

    Turton, David A; Wynne, Klaas

    2009-11-28

    The dynamics of the noble-gas liquids underlies that of all liquids making them an important prototypical model system. Using optical Kerr-effect spectroscopy we show that for argon, krypton, and xenon, both the librational and diffusional contributions to the spectrum are surprisingly complex. The diffusional relaxation appears as a stretched-exponential, such as widely found in studies of structured (e.g., glass-forming) liquids and as predicted by mode-coupling theory. We show that this behavior is remarkably similar to that measured in water and suggest that it is a fundamental or universal property.

  19. A Simple Model for Complex Dynamical Transitions in Epidemics

    NASA Astrophysics Data System (ADS)

    Earn, David J. D.; Rohani, Pejman; Bolker, Benjamin M.; Grenfell, Bryan T.

    2000-01-01

    Dramatic changes in patterns of epidemics have been observed throughout this century. For childhood infectious diseases such as measles, the major transitions are between regular cycles and irregular, possibly chaotic epidemics, and from regionally synchronized oscillations to complex, spatially incoherent epidemics. A simple model can explain both kinds of transitions as the consequences of changes in birth and vaccination rates. Measles is a natural ecological system that exhibits different dynamical transitions at different times and places, yet all of these transitions can be predicted as bifurcations of a single nonlinear model.

  20. Vibrational dynamics of the CH4·F- complex.

    PubMed

    Wodraszka, Robert; Palma, Juliana; Manthe, Uwe

    2012-11-26

    Motivated by recent photodetachment experiments studying resonance structures in the transition-state region of the F + CH(4) → HF + CH(3) reaction, the vibrational dynamics of the precursor complex CH(4)·F(-) is investigated. Delocalized vibrational eigenstates of CH(4)·F(-) are computed in full dimensionality employing the multiconfigurational time-dependent Hartree (MCTDH) approach and a recently developed iterative diagonalization approach for general multiwell systems. Different types of stereographic coordinates are used, and a corresponding general N-body kinetic energy operator is given. The calculated tunneling splittings of the ground and the lower vibrational excited states of the CH(4)·F(-) complex do not significantly exceed 1 cm(-1). Comparing the converged MCTDH results for localized vibrational excitations with existing results obtained by normal-mode-based (truncated) vibrational configuration interaction calculations, significantly lower frequencies are found for excitations in the intermolecular modes. PMID:22731911

  1. Control of complex dynamics and chaos in distributed parameter systems

    SciTech Connect

    Chakravarti, S.; Marek, M.; Ray, W.H.

    1995-12-31

    This paper discusses a methodology for controlling complex dynamics and chaos in distributed parameter systems. The reaction-diffusion system with Brusselator kinetics, where the torus-doubling or quasi-periodic (two characteristic incommensurate frequencies) route to chaos exists in a defined range of parameter values, is used as an example. Poincare maps are used for characterization of quasi-periodic and chaotic attractors. The dominant modes or topos, which are inherent properties of the system, are identified by means of the Singular Value Decomposition. Tested modal feedback control schemas based on identified dominant spatial modes confirm the possibility of stabilization of simple quasi-periodic trajectories in the complex quasi-periodic or chaotic spatiotemporal patterns.

  2. Molecular dynamics simulations of DNA-polycation complexes

    NASA Astrophysics Data System (ADS)

    Ziebarth, Jesse; Wang, Yongmei

    2008-03-01

    A necessary step in the preparation of DNA for use in gene therapy is the packaging of DNA with a vector that can condense DNA and provide protection from degrading enzymes. Because of the immunoresponses caused by viral vectors, there has been interest in developing synthetic gene therapy vectors, with polycations emerging as promising candidates. Molecular dynamics simulations of the DNA duplex CGCGAATTCGCG in the presence of 20 monomer long sequences of the polycations, poly-L-lysine (PLL) and polyethyleneimine (PEI), with explicit counterions and TIP3P water, are performed to provide insight into the structure and formation of DNA polyplexes. After an initial separation of approximately 50 å, the DNA and polycation come together and form a stable complex within 10 ns. The DNA does not undergo any major structural changes upon complexation and remains in the B-form. In the formed complex, the charged amine groups of the polycation mainly interact with DNA phosphate groups, and rarely occupy electronegative sites in either the major or minor grooves. Differences between complexation with PEI and PLL will be discussed.

  3. Dynamic analysis of the human brain with complex cerebral sulci.

    PubMed

    Tseng, Jung-Ge; Huang, Bo-Wun; Ou, Yi-Wen; Yen, Ke-Tien; Wu, Yi-Te

    2016-07-01

    The brain is one of the most vulnerable organs inside the human body. Head accidents often appear in daily life and are easy to cause different level of brain damage inside the skull. Once the brain suffered intense locomotive impact, external injuries, falls, or other accidents, it will result in different degrees of concussion. This study employs finite element analysis to compare the dynamic characteristics between the geometric models of an assumed simple brain tissue and a brain tissue with complex cerebral sulci. It is aimed to understand the free vibration of the internal brain tissue and then to protect the brain from injury caused by external influences. Reverse engineering method is used for a Classic 5-Part Brain (C18) model produced by 3B Scientific Corporation. 3D optical scanner is employed to scan the human brain structure model with complex cerebral sulci and imported into 3D graphics software to construct a solid brain model to simulate the real complex brain tissue. Obtaining the normal mode analysis by inputting the material properties of the true human brain into finite element analysis software, and then to compare the simplified and the complex of brain models. PMID:27459595

  4. Computational complexity of ecological and evolutionary spatial dynamics.

    PubMed

    Ibsen-Jensen, Rasmus; Chatterjee, Krishnendu; Nowak, Martin A

    2015-12-22

    There are deep, yet largely unexplored, connections between computer science and biology. Both disciplines examine how information proliferates in time and space. Central results in computer science describe the complexity of algorithms that solve certain classes of problems. An algorithm is deemed efficient if it can solve a problem in polynomial time, which means the running time of the algorithm is a polynomial function of the length of the input. There are classes of harder problems for which the fastest possible algorithm requires exponential time. Another criterion is the space requirement of the algorithm. There is a crucial distinction between algorithms that can find a solution, verify a solution, or list several distinct solutions in given time and space. The complexity hierarchy that is generated in this way is the foundation of theoretical computer science. Precise complexity results can be notoriously difficult. The famous question whether polynomial time equals nondeterministic polynomial time (i.e., P = NP) is one of the hardest open problems in computer science and all of mathematics. Here, we consider simple processes of ecological and evolutionary spatial dynamics. The basic question is: What is the probability that a new invader (or a new mutant) will take over a resident population? We derive precise complexity results for a variety of scenarios. We therefore show that some fundamental questions in this area cannot be answered by simple equations (assuming that P is not equal to NP).

  5. Computational complexity of ecological and evolutionary spatial dynamics

    PubMed Central

    Ibsen-Jensen, Rasmus; Chatterjee, Krishnendu; Nowak, Martin A.

    2015-01-01

    There are deep, yet largely unexplored, connections between computer science and biology. Both disciplines examine how information proliferates in time and space. Central results in computer science describe the complexity of algorithms that solve certain classes of problems. An algorithm is deemed efficient if it can solve a problem in polynomial time, which means the running time of the algorithm is a polynomial function of the length of the input. There are classes of harder problems for which the fastest possible algorithm requires exponential time. Another criterion is the space requirement of the algorithm. There is a crucial distinction between algorithms that can find a solution, verify a solution, or list several distinct solutions in given time and space. The complexity hierarchy that is generated in this way is the foundation of theoretical computer science. Precise complexity results can be notoriously difficult. The famous question whether polynomial time equals nondeterministic polynomial time (i.e., P = NP) is one of the hardest open problems in computer science and all of mathematics. Here, we consider simple processes of ecological and evolutionary spatial dynamics. The basic question is: What is the probability that a new invader (or a new mutant) will take over a resident population? We derive precise complexity results for a variety of scenarios. We therefore show that some fundamental questions in this area cannot be answered by simple equations (assuming that P is not equal to NP). PMID:26644569

  6. Reprint of : The Boltzmann--Langevin approach: A simple quantum-mechanical derivation

    NASA Astrophysics Data System (ADS)

    Nagaev, K. E.

    2016-08-01

    We present a simple quantum-mechanical derivation of correlation function of Langevin sources in the semiclassical Boltzmann-Langevin equation. The specific case of electron-phonon scattering is considered. It is shown that the assumption of weak scattering leads to the Poisson nature of the scattering fluxes.

  7. Complex Dynamic Behavior in Simple Gene Regulatory Networks

    NASA Astrophysics Data System (ADS)

    Santillán Zerón, Moisés

    2007-02-01

    Knowing the complete genome of a given species is just a piece of the puzzle. To fully unveil the systems behavior of an organism, an organ, or even a single cell, we need to understand the underlying gene regulatory dynamics. Given the complexity of the whole system, the ultimate goal is unattainable for the moment. But perhaps, by analyzing the most simple genetic systems, we may be able to develop the mathematical techniques and procedures required to tackle more complex genetic networks in the near future. In the present work, the techniques for developing mathematical models of simple bacterial gene networks, like the tryptophan and lactose operons are introduced. Despite all of the underlying assumptions, such models can provide valuable information regarding gene regulation dynamics. Here, we pay special attention to robustness as an emergent property. These notes are organized as follows. In the first section, the long historical relation between mathematics, physics, and biology is briefly reviewed. Recently, the multidisciplinary work in biology has received great attention in the form of systems biology. The main concepts of this novel science are discussed in the second section. A very slim introduction to the essential concepts of molecular biology is given in the third section. In the fourth section, a brief introduction to chemical kinetics is presented. Finally, in the fifth section, a mathematical model for the lactose operon is developed and analyzed..

  8. GPU-enabled molecular dynamics simulations of ankyrin kinase complex

    NASA Astrophysics Data System (ADS)

    Gautam, Vertika; Chong, Wei Lim; Wisitponchai, Tanchanok; Nimmanpipug, Piyarat; Zain, Sharifuddin M.; Rahman, Noorsaadah Abd.; Tayapiwatana, Chatchai; Lee, Vannajan Sanghiran

    2014-10-01

    The ankyrin repeat (AR) protein can be used as a versatile scaffold for protein-protein interactions. It has been found that the heterotrimeric complex between integrin-linked kinase (ILK), PINCH, and parvin is an essential signaling platform, serving as a convergence point for integrin and growth-factor signaling and regulating cell adhesion, spreading, and migration. Using ILK-AR with high affinity for the PINCH1 as our model system, we explored a structure-based computational protocol to probe and characterize binding affinity hot spots at protein-protein interfaces. In this study, the long time scale dynamics simulations with GPU accelerated molecular dynamics (MD) simulations in AMBER12 have been performed to locate the hot spots of protein-protein interaction by the analysis of the Molecular Mechanics-Poisson-Boltzmann Surface Area/Generalized Born Solvent Area (MM-PBSA/GBSA) of the MD trajectories. Our calculations suggest good binding affinity of the complex and also the residues critical in the binding.

  9. Dynamic of astrophysical jets in the complex octonion space

    NASA Astrophysics Data System (ADS)

    Weng, Zi-Hua

    2015-06-01

    The paper aims to consider the strength gradient force as the dynamic of astrophysical jets, explaining the movement phenomena of astrophysical jets. J. C. Maxwell applied the quaternion analysis to describe the electromagnetic theory. This encourages others to adopt the complex quaternion and octonion to depict the electromagnetic and gravitational theories. In the complex octonion space, it is capable of deducing the field potential, field strength, field source, angular momentum, torque, force and so forth. As one component of the force, the strength gradient force relates to the gradient of the norm of field strength only, and is independent of not only the direction of field strength but also the mass and electric charge for the test particle. When the strength gradient force is considered as the thrust of the astrophysical jets, one can deduce some movement features of astrophysical jets, including the bipolarity, matter ingredient, precession, symmetric distribution, emitting, collimation, stability, continuing acceleration and so forth. The above results reveal that the strength gradient force is able to be applied to explain the main mechanical features of astrophysical jets, and is the competitive candidate of the dynamic of astrophysical jets.

  10. Generalized Langevin equation for solids. I. Rigorous derivation and main properties

    NASA Astrophysics Data System (ADS)

    Kantorovich, L.

    2008-09-01

    We demonstrate explicitly that the derivation by Adelman and Doll (AD) [J. Chem. Phys. 64, 2375 (1976)] of the generalized Langevin equation (GLE) to describe dynamics of an extended solid system by considering its finite subsystem is inconsistent because it relies on performing statistical averages over the entire system when establishing properties of the random force. This results in the random force representing a nonstationary process opposite to one of the main assumptions made in AD that the random force corresponds to a stationary stochastic process. This invalidates the derivation of the Brownian (or Langevin) form of the GLE in AD. Here we present a different and more general approach in deriving the GLE. Our method generalizes that of AD in two main aspects: (i) the structure of the finite region can be arbitrary (e.g., anharmonic), and (ii) ways are indicated in which the method can be implemented exactly if the phonon Green’s function of the harmonic environment region surrounding the anharmonic region is known, which is, e.g., the case when the environment region represents a part of a periodic solid (the bulk or a surface). We also show that in general after the local perturbation has ceased, the system returns to thermodynamic equilibrium with the distribution function for region 1 being canonical with respect to an effective interaction between atoms, which includes instantaneous response of the surrounding region. Note that our method does not rely on the assumption made in AD that the stochastic force correlation function depends on the times difference only (i.e., the random force corresponds to a stationary random process). In fact, we demonstrate explicitly that generally this is not the case. Still, the correct GLE can be obtained, which satisfies exactly the fluctuation-dissipation theorem.

  11. Functional Loop Dynamics of the Streptavidin-Biotin Complex

    PubMed Central

    Song, Jianing; Li, Yongle; Ji, Changge; Zhang, John Z. H.

    2015-01-01

    Accelerated molecular dynamics (aMD) simulation is employed to study the functional dynamics of the flexible loop3-4 in the strong-binding streptavidin-biotin complex system. Conventional molecular (cMD) simulation is also performed for comparison. The present study reveals the following important properties of the loop dynamics: (1) The transition of loop3-4 from open to closed state is observed in 200 ns aMD simulation. (2) In the absence of biotin binding, the open-state streptavidin is more stable, which is consistent with experimental evidences. The free energy (ΔG) difference is about 5 kcal/mol between two states. But with biotin binding, the closed state is more stable due to electrostatic and hydrophobic interactions between the loop3-4 and biotin. (3) The closure of loop3-4 is concerted to the stable binding of biotin to streptavidin. When the loop3-4 is in its open-state, biotin moves out of the binding pocket, indicating that the interactions between the loop3-4 and biotin are essential in trapping biotin in the binding pocket. (4) In the tetrameric streptavidin system, the conformational change of the loop3-4 in each monomer is independent of each other. That is, there is no cooperative binding for biotin bound to the four subunits of the tetramer. PMID:25601277

  12. Dynamical complexity of the Brans-Dicke cosmology

    SciTech Connect

    Hrycyna, Orest; Szydłowski, Marek E-mail: marek.szydlowski@uj.edu.pl

    2013-12-01

    The dynamics of the Brans-Dicke theory with a quadratic scalar field potential function and barotropic matter is investigated. The dynamical system methods are used to reveal complexity of dynamical evolution in homogeneous and isotropic cosmological models. The structure of phase space crucially depends on the parameter of the theory ω{sub BD} as well as barotropic matter index w{sub m}. In our analysis these parameters are treated as bifurcation parameters. We found sets of values of these parameters which lead to generic evolutional scenarios. We show that in isotropic and homogeneous models in the Brans-Dicke theory with a quadratic potential function the de Sitter state appears naturally. Stability conditions of this state are fully investigated. It is shown that these models can explain accelerated expansion of the Universe without the assumption of the substantial form of dark matter and dark energy. The Poincare construction of compactified phase space with a circle at infinity is used to show that phase space trajectories in a physical region can be equipped with a structure of a vector field on nontrivial topological closed space. For ω{sub BD} < −3/2 we show new types of early and late time evolution leading from the anti-de Sitter to the de Sitter state through an asymmetric bounce. In the theory without a ghost we find bouncing solutions and the coexistence of the bounces and the singularity. Following the Peixoto theorem some conclusions about structural stability are drawn.

  13. Development of metal-bonded Langevin transducer using LiNbO3

    NASA Astrophysics Data System (ADS)

    Ito, Hiroshi; Jimbo, Hikaru; Shiotani, Koichi; Sakai, Nagahide

    2016-07-01

    We newly developed a metal-bonded Langevin transducer using LiNbO3 in order to realize a practical high-power LiNbO3 Langevin transducer. It utilizes metal bonding with a lead-free solder as an assembly method for a Langevin transducer, instead of a bolt as used in a conventional bolt-clamped Langevin transducer. The newly developed metal-bonded LiNbO3 Langevin transducer achieved a high vibration velocity of over 1.5 m/s and stable operation. Because of rigid metal bonding, it does not show nonlinear phenomena such as a jump phenomenon and/or a resonant frequency shift.

  14. PREFACE: Complex dynamics of fluids in disordered and crowded environments Complex dynamics of fluids in disordered and crowded environments

    NASA Astrophysics Data System (ADS)

    Coslovich, Daniele; Kahl, Gerhard; Krakoviack, Vincent

    2011-06-01

    Over the past two decades, the dynamics of fluids under nanoscale confinement has attracted much attention. Motivation for this rapidly increasing interest is based on both practical and fundamental reasons. On the practical and rather applied side, problems in a wide range of scientific topics, such as polymer and colloidal sciences, rheology, geology, or biophysics, benefit from a profound understanding of the dynamical behaviour of confined fluids. Further, effects similar to those observed in confinement are expected in fluids whose constituents have strong size or mass asymmetry, and in biological systems where crowding and obstruction phenomena in the cytosol are responsible for clear separations of time scales for macromolecular transport in the cell. In fundamental research, on the other hand, the interest focuses on the complex interplay between confinement and structural relaxation, which is responsible for the emergence of new phenomena in the dynamics of the system: in confinement, geometric constraints associated with the pore shape are imposed to the adsorbed fluids and an additional characteristic length scale, i.e. the pore size, comes into play. For many years, the topic has been mostly experimentally driven. Indeed, a broad spectrum of systems has been investigated by sophisticated experimental techniques, while theoretical and simulation studies were rather scarce due to conceptual and computational issues. In the past few years, however, theory and simulations could largely catch up with experiments. On one side, new theories have been put forward that duly take into account the porosity, the connectivity, and the randomness of the confinement. On the other side, the ever increasing available computational power now allows investigations that were far out of reach a few years ago. Nowadays, instead of isolated state points, systematic investigations on the dynamics of confined fluids, covering a wide range of system parameters, can be realized

  15. Collaborative Research. Damage and Burst Dynamics in Failure of Complex Geomaterials. A Statistical Physics Approach to Understanding the Complex Emergent Dynamics in Near Mean-Field Geological Materials

    SciTech Connect

    Rundle, John B.; Klein, William

    2015-09-29

    We have carried out research to determine the dynamics of failure in complex geomaterials, specifically focusing on the role of defects, damage and asperities in the catastrophic failure processes (now popularly termed “Black Swan events”). We have examined fracture branching and flow processes using models for invasion percolation, focusing particularly on the dynamics of bursts in the branching process. We have achieved a fundamental understanding of the dynamics of nucleation in complex geomaterials, specifically in the presence of inhomogeneous structures.

  16. Complex dynamical behaviors of daily data series in stock exchange

    NASA Astrophysics Data System (ADS)

    Wang, Hongchun; Chen, Guanrong; Lü, Jinhu

    2004-12-01

    It is well known that many economic data series show chaotic behaviors. In this Letter, we further investigate the complex dynamical behaviors of the daily data series, including opening quotation, closing quotation, maximum price, minimum price, and total exchange quantum, in Shenzhen stock exchange and Shanghai stock exchange, which are two representative stock exchanges in mainland China. The maximum Lyapunov exponents, correlation dimensions, and frequency spectra are calculated for these time series. Our results indicate that some daily data series of stock exchanges display low-dimensional chaotic behaviors, and some other daily data series do not show any chaotic behavior. Moreover, we introduce a weighted one-rank local-region approach for predicting short-term daily data series of stock exchange.

  17. Information processing using a single dynamical node as complex system

    PubMed Central

    Appeltant, L.; Soriano, M.C.; Van der Sande, G.; Danckaert, J.; Massar, S.; Dambre, J.; Schrauwen, B.; Mirasso, C.R.; Fischer, I.

    2011-01-01

    Novel methods for information processing are highly desired in our information-driven society. Inspired by the brain's ability to process information, the recently introduced paradigm known as 'reservoir computing' shows that complex networks can efficiently perform computation. Here we introduce a novel architecture that reduces the usually required large number of elements to a single nonlinear node with delayed feedback. Through an electronic implementation, we experimentally and numerically demonstrate excellent performance in a speech recognition benchmark. Complementary numerical studies also show excellent performance for a time series prediction benchmark. These results prove that delay-dynamical systems, even in their simplest manifestation, can perform efficient information processing. This finding paves the way to feasible and resource-efficient technological implementations of reservoir computing. PMID:21915110

  18. Crystallization Dynamics of a Single Layer Complex Plasma

    SciTech Connect

    Hartmann, Peter; Kovacs, Aniko; Donko, Zoltan; Douglass, Angela; Reyes, Jorge C.; Matthews, Lorin S.; Hyde, Truell W.

    2010-09-10

    We report a series of complex (dusty) plasma experiments, aimed at the study of the detailed time evolution of the recrystallization process following a rapid quench of a two-dimensional dust liquid. The experiments were accompanied by large-scale (million-particle) molecular dynamics simulations, assuming Yukawa-type interparticle interaction. Both experiment and simulation show a {proportional_to}t{sup {alpha}} (power-law) dependence of the linear crystallite domain size as measured by the bond-order correlation length, translational correlation length, dislocation (defect) density, and a direct size measurement algorithm. The results show two stages of order formation. On short time scales, individual particle motion dominates; this is a fast process characterized by {alpha}=0.93{+-}0.1. At longer time scales, small crystallites undergo collective rearrangement, merging into bigger ones, resulting in a smaller exponent {alpha}=0.38{+-}0.06.

  19. Reduced complexity turbo equalization using a dynamic Bayesian network

    NASA Astrophysics Data System (ADS)

    Myburgh, Hermanus C.; Olivier, Jan C.; van Zyl, Augustinus J.

    2012-12-01

    It is proposed that a dynamic Bayesian network (DBN) is used to perform turbo equalization in a system transmitting information over a Rayleigh fading multipath channel. The DBN turbo equalizer (DBN-TE) is modeled on a single directed acyclic graph by relaxing the Markov assumption and allowing weak connections to past and future states. Its complexity is exponential in encoder constraint length and approximately linear in the channel memory length. Results show that the performance of the DBN-TE closely matches that of a traditional turbo equalizer that uses a maximum a posteriori equalizer and decoder pair. The DBN-TE achieves full convergence and near-optimal performance after small number of iterations.

  20. Computational complexity of symbolic dynamics at the onset of chaos

    NASA Astrophysics Data System (ADS)

    Lakdawala, Porus

    1996-05-01

    In a variety of studies of dynamical systems, the edge of order and chaos has been singled out as a region of complexity. It was suggested by Wolfram, on the basis of qualitative behavior of cellular automata, that the computational basis for modeling this region is the universal Turing machine. In this paper, following a suggestion of Crutchfield, we try to show that the Turing machine model may often be too powerful as a computational model to describe the boundary of order and chaos. In particular we study the region of the first accumulation of period doubling in unimodal and bimodal maps of the interval, from the point of view of language theory. We show that in relation to the ``extended'' Chomsky hierarchy, the relevant computational model in the unimodal case is the nested stack automaton or the related indexed languages, while the bimodal case is modeled by the linear bounded automaton or the related context-sensitive languages.

  1. Complex Dynamic Flows in Solar Flare Sheet Structures

    NASA Technical Reports Server (NTRS)

    McKenzie, David E.; Reeves, Katharine K.; Savage, Sabrina

    2012-01-01

    Observations of high-energy emission from solar flares often reveal the presence of large sheet-like structures, sometimes extending over a space comparable to the Sun's radius. Given that these structures are found between a departing coronal mass ejection and the post-eruption flare arcade, it is natural to associate the structure with a current sheet; though the relationship is unclear. Moreover, recent high-resolution observations have begun to reveal that the motions in this region are highly complex, including reconnection outflows, oscillations, and apparent wakes and eddies. We present a detailed first look at the complicated dynamics within this supra-arcade plasma, and consider implications for the interrelationship between the plasma and its embedded magnetic field.

  2. Complex flow dynamics around 3D microbot prototypes.

    PubMed

    Martínez-Aranda, Sergio; Galindo-Rosales, Francisco J; Campo-Deaño, Laura

    2016-02-28

    A new experimental setup for the study of the complex flow dynamics around 3D microbot prototypes in a straight microchannel has been developed and assessed. The ultimate aim of this work is focused on the analysis of the morphology of different microbot prototypes to get a better insight into their efficiency when they swim through the main conduits of the human circulatory system. The setup consists of a fused silica straight microchannel with a 3D microbot prototype fastened in the center of the channel cross-section by an extremely thin support. Four different prototypes were considered: a cube, a sphere and two ellipsoids with aspect ratios of 1 : 2 and 1 : 4, respectively. Flow visualization and micro-particle image velocimetry (μPIV) measurements were performed using Newtonian and viscoelastic blood analogue fluids. An efficiency parameter, ℑ, to discriminate the prototypes in terms of flow disturbance has been proposed.

  3. Nonlinear problems of complex natural systems: Sun and climate dynamics.

    PubMed

    Bershadskii, A

    2013-01-13

    The universal role of the nonlinear one-third subharmonic resonance mechanism in generation of strong fluctuations in complex natural dynamical systems related to global climate is discussed using wavelet regression detrended data. The role of the oceanic Rossby waves in the year-scale global temperature fluctuations and the nonlinear resonance contribution to the El Niño phenomenon have been discussed in detail. The large fluctuations in the reconstructed temperature on millennial time scales (Antarctic ice core data for the past 400,000 years) are also shown to be dominated by the one-third subharmonic resonance, presumably related to the Earth's precession effect on the energy that the intertropical regions receive from the Sun. The effects of galactic turbulence on the temperature fluctuations are also discussed. PMID:23185052

  4. Universal relation between skewness and kurtosis in complex dynamics

    NASA Astrophysics Data System (ADS)

    Cristelli, Matthieu; Zaccaria, Andrea; Pietronero, Luciano

    2012-06-01

    We identify an important correlation between skewness and kurtosis for a broad class of complex dynamic systems and present a specific analysis of earthquake and financial time series. Two regimes of non-Gaussianity can be identified: a parabolic one, which is common in various fields of physics, and a power law one, with exponent 4/3, which at the moment appears to be specific of earthquakes and financial markets. For this property we propose a model and an interpretation in terms of very rare events dominating the statistics independently on the nature of the events considered. The predicted scaling relation between skewness and kurtosis matches very well the experimental pattern of the second regime. Regarding price fluctuations, this situation characterizes a universal stylized fact.

  5. Fluctuation analysis of time-averaged mean-square displacement for the Langevin equation with time-dependent and fluctuating diffusivity

    NASA Astrophysics Data System (ADS)

    Uneyama, Takashi; Miyaguchi, Tomoshige; Akimoto, Takuma

    2015-09-01

    The mean-square displacement (MSD) is widely utilized to study the dynamical properties of stochastic processes. The time-averaged MSD (TAMSD) provides some information on the dynamics which cannot be extracted from the ensemble-averaged MSD. In particular, the relative standard deviation (RSD) of the TAMSD can be utilized to study the long-time relaxation behavior. In this work, we consider a class of Langevin equations which are multiplicatively coupled to time-dependent and fluctuating diffusivities. Various interesting dynamics models such as entangled polymers and supercooled liquids can be interpreted as the Langevin equations with time-dependent and fluctuating diffusivities. We derive a general formula for the RSD of the TAMSD for the Langevin equation with the time-dependent and fluctuating diffusivity. We show that the RSD can be expressed in terms of the correlation function of the diffusivity. The RSD exhibits the crossover at the long time region. The crossover time is related to a weighted average relaxation time for the diffusivity. Thus the crossover time gives some information on the relaxation time of fluctuating diffusivity which cannot be extracted from the ensemble-averaged MSD. We discuss the universality and possible applications of the formula via some simple examples.

  6. The generalized Schrödinger–Langevin equation

    SciTech Connect

    Bargueño, Pedro; Miret-Artés, Salvador

    2014-07-15

    In this work, for a Brownian particle interacting with a heat bath, we derive a generalization of the so-called Schrödinger–Langevin or Kostin equation. This generalization is based on a nonlinear interaction model providing a state-dependent dissipation process exhibiting multiplicative noise. Two straightforward applications to the measurement process are then analyzed, continuous and weak measurements in terms of the quantum Bohmian trajectory formalism. Finally, it is also shown that the generalized uncertainty principle, which appears in some approaches to quantum gravity, can be expressed in terms of this generalized equation. -- Highlights: •We generalize the Kostin equation for arbitrary system–bath coupling. •This generalization is developed both in the Schrödinger and Bohmian formalisms. •We write the generalized Kostin equation for two measurement problems. •We reformulate the generalized uncertainty principle in terms of this equation.

  7. PREFACE: Complex dynamics of fluids in disordered and crowded environments Complex dynamics of fluids in disordered and crowded environments

    NASA Astrophysics Data System (ADS)

    Coslovich, Daniele; Kahl, Gerhard; Krakoviack, Vincent

    2011-06-01

    Over the past two decades, the dynamics of fluids under nanoscale confinement has attracted much attention. Motivation for this rapidly increasing interest is based on both practical and fundamental reasons. On the practical and rather applied side, problems in a wide range of scientific topics, such as polymer and colloidal sciences, rheology, geology, or biophysics, benefit from a profound understanding of the dynamical behaviour of confined fluids. Further, effects similar to those observed in confinement are expected in fluids whose constituents have strong size or mass asymmetry, and in biological systems where crowding and obstruction phenomena in the cytosol are responsible for clear separations of time scales for macromolecular transport in the cell. In fundamental research, on the other hand, the interest focuses on the complex interplay between confinement and structural relaxation, which is responsible for the emergence of new phenomena in the dynamics of the system: in confinement, geometric constraints associated with the pore shape are imposed to the adsorbed fluids and an additional characteristic length scale, i.e. the pore size, comes into play. For many years, the topic has been mostly experimentally driven. Indeed, a broad spectrum of systems has been investigated by sophisticated experimental techniques, while theoretical and simulation studies were rather scarce due to conceptual and computational issues. In the past few years, however, theory and simulations could largely catch up with experiments. On one side, new theories have been put forward that duly take into account the porosity, the connectivity, and the randomness of the confinement. On the other side, the ever increasing available computational power now allows investigations that were far out of reach a few years ago. Nowadays, instead of isolated state points, systematic investigations on the dynamics of confined fluids, covering a wide range of system parameters, can be realized

  8. Coherent amplification and noise in gain-enhanced nanoplasmonic metamaterials: a Maxwell-Bloch Langevin approach.

    PubMed

    Pusch, Andreas; Wuestner, Sebastian; Hamm, Joachim M; Tsakmakidis, Kosmas L; Hess, Ortwin

    2012-03-27

    Nanoplasmonic metamaterials are an exciting new class of engineered media that promise a range of important applications, such as subwavelength focusing, cloaking, and slowing/stopping of light. At optical frequencies, using gain to overcome potentially not insignificant losses has recently emerged as a viable solution to ultra-low-loss operation that may lead to next-generation active metamaterials. Maxwell-Bloch models for active nanoplasmonic metamaterials are able to describe the coherent spatiotemporal and nonlinear gain-plasmon dynamics. Here, we extend the Maxwell-Bloch theory to a Maxwell-Bloch Langevin approach-a spatially resolved model that describes the light field and noise dynamics in gain-enhanced nanoplasmonic structures. Using the example of an optically pumped nanofishnet metamaterial with an embedded laser dye (four-level) medium exhibiting a negative refractive index, we demonstrate the transition from loss-compensation to amplification and to nanolasing. We observe ultrafast relaxation oscillations of the bright negative-index mode with frequencies just below the THz regime. The influence of noise on mode competition and the onset and magnitude of the relaxation oscillations is elucidated, and the dynamics and spectra of the emitted light indicate that coherent amplification and lasing are maintained even in the presence of noise and amplified spontaneous emission.

  9. Path-wise versus kinetic modeling for equilibrating non-Langevin jump-type processes

    NASA Astrophysics Data System (ADS)

    Żaba, Mariusz; Garbaczewski, Piotr; Stephanovich, Vladimir

    2014-03-01

    We discuss two independent methods of solution of a master equation whose biased jump transition rates account for long jumps of Lévy-stable type and admit a Boltzmannian (thermal) equilibrium to arise in the large time asymptotics of a probability density function ρ(x, t). Our main goal is to demonstrate a compatibility of a direct solution method (an explicit, albeit numerically assisted, integration of the master equation) with an indirect pathwise procedure, recently proposed in [Physica A 392, 3485, (2013)] as a valid tool for a dynamical analysis of non-Langevin jump-type processes. The path-wise method heavily relies on an accumulation of large sample path data, that are generated by means of a properly tailored Gillespie's algorithm. Their statistical analysis in turn allows to infer the dynamics of ρ(x, t). However, no consistency check has been completed so far to demonstrate that both methods are fully compatible and indeed provide a solution of the same dynamical problem. Presently we remove this gap, with a focus on potential deficiencies (various cutoffs, including those upon the jump size) of approximations involved in simulation routines and solutions protocols.

  10. Path-wise versus kinetic modeling for equilibrating non-Langevin jump-type processes

    NASA Astrophysics Data System (ADS)

    Żaba, Mariusz; Garbaczewski, Piotr; Stephanovich, Vladimir A.

    2014-03-01

    We discuss two independent methods of solution of a master equation whose biased jump transition rates account for long jumps of Lévy-stable type and admit a Boltzmannian (thermal) equilibrium to arise in the large time asymptotics of a probability density function ρ( x, t). Our main goal is to demonstrate a compatibility of a direct solution method (an explicit, albeit numerically assisted, integration of the master equation) with an indirect pathwise procedure, recently proposed in [Physica A 392, 3485, (2013)] as a valid tool for a dynamical analysis of non-Langevin jump-type processes. The path-wise method heavily relies on an accumulation of large sample path data, that are generated by means of a properly tailored Gillespie's algorithm. Their statistical analysis in turn allows to infer the dynamics of ρ( x, t). However, no consistency check has been completed so far to demonstrate that both methods are fully compatible and indeed provide a solution of the same dynamical problem. Presently we remove this gap, with a focus on potential deficiencies (various cutoffs, including those upon the jump size) of approximations involved in simulation routines and solutions protocols.

  11. Harmonically bound Brownian motion in fluids under shear: Fokker-Planck and generalized Langevin descriptions.

    PubMed

    Híjar, Humberto

    2015-02-01

    We study the Brownian motion of a particle bound by a harmonic potential and immersed in a fluid with a uniform shear flow. We describe this problem first in terms of a linear Fokker-Planck equation which is solved to obtain the probability distribution function for finding the particle in a volume element of its associated phase space. We find the explicit form of this distribution in the stationary limit and use this result to show that both the equipartition law and the equation of state of the trapped particle are modified from their equilibrium form by terms increasing as the square of the imposed shear rate. Subsequently, we propose an alternative description of this problem in terms of a generalized Langevin equation that takes into account the effects of hydrodynamic correlations and sound propagation on the dynamics of the trapped particle. We show that these effects produce significant changes, manifested as long-time tails and resonant peaks, in the equilibrium and nonequilibrium correlation functions for the velocity of the Brownian particle. We implement numerical simulations based on molecular dynamics and multiparticle collision dynamics, and observe a very good quantitative agreement between the predictions of the model and the numerical results, thus suggesting that this kind of numerical simulations could be used as complement of current experimental techniques. PMID:25768490

  12. A Qualitative Model of Human Interaction with Complex Dynamic Systems

    NASA Technical Reports Server (NTRS)

    Hess, Ronald A.

    1987-01-01

    A qualitative model describing human interaction with complex dynamic systems is developed. The model is hierarchical in nature and consists of three parts: a behavior generator, an internal model, and a sensory information processor. The behavior generator is responsible for action decomposition, turning higher level goals or missions into physical action at the human-machine interface. The internal model is an internal representation of the environment which the human is assumed to possess and is divided into four submodel categories. The sensory information processor is responsible for sensory composition. All three parts of the model act in consort to allow anticipatory behavior on the part of the human in goal-directed interaction with dynamic systems. Human workload and error are interpreted in this framework, and the familiar example of an automobile commute is used to illustrate the nature of the activity in the three model elements. Finally, with the qualitative model as a guide, verbal protocols from a manned simulation study of a helicopter instrument landing task are analyzed with particular emphasis on the effect of automation on human-machine performance.

  13. A qualitative model of human interaction with complex dynamic systems

    NASA Technical Reports Server (NTRS)

    Hess, Ronald A.

    1987-01-01

    A qualitative model describing human interaction with complex dynamic systems is developed. The model is hierarchical in nature and consists of three parts: a behavior generator, an internal model, and a sensory information processor. The behavior generator is responsible for action decomposition, turning higher level goals or missions into physical action at the human-machine interface. The internal model is an internal representation of the environment which the human is assumed to possess and is divided into four submodel categories. The sensory information processor is responsible for sensory composition. All three parts of the model act in consort to allow anticipatory behavior on the part of the human in goal-directed interaction with dynamic systems. Human workload and error are interpreted in this framework, and the familiar example of an automobile commute is used to illustrate the nature of the activity in the three model elements. Finally, with the qualitative model as a guide, verbal protocols from a manned simulation study of a helicopter instrument landing task are analyzed with particular emphasis on the effect of automation on human-machine performance.

  14. Complex dynamics of semantic memory access in reading.

    PubMed

    Baggio, Giosué; Fonseca, André

    2012-02-01

    Understanding a word in context relies on a cascade of perceptual and conceptual processes, starting with modality-specific input decoding, and leading to the unification of the word's meaning into a discourse model. One critical cognitive event, turning a sensory stimulus into a meaningful linguistic sign, is the access of a semantic representation from memory. Little is known about the changes that activating a word's meaning brings about in cortical dynamics. We recorded the electroencephalogram (EEG) while participants read sentences that could contain a contextually unexpected word, such as 'cold' in 'In July it is very cold outside'. We reconstructed trajectories in phase space from single-trial EEG time series, and we applied three nonlinear measures of predictability and complexity to each side of the semantic access boundary, estimated as the onset time of the N400 effect evoked by critical words. Relative to controls, unexpected words were associated with larger prediction errors preceding the onset of the N400. Accessing the meaning of such words produced a phase transition to lower entropy states, in which cortical processing becomes more predictable and more regular. Our study sheds new light on the dynamics of information flow through interfaces between sensory and memory systems during language processing.

  15. Dynamic hysteresis in the rheology of complex fluids.

    PubMed

    Puisto, Antti; Mohtaschemi, Mikael; Alava, Mikko J; Illa, Xavier

    2015-04-01

    Recently, rheological hysteresis has been studied systematically in a wide range of complex fluids combining global rheology and time-resolved velocimetry. In this paper we present an analysis of the roles of the three most fundamental mechanisms in simple-yield-stress fluids: structure dynamics, viscoelastic response, and spatial flow heterogeneities, i.e., time-dependent shear bands. Dynamical hysteresis simulations are done analogously to rheological ramp-up and -down experiments on a coupled model which incorporates viscoelasticity and time-dependent structure evolution. Based on experimental data, a coupling between hysteresis measured from the local velocity profiles and that measured from the global flow curve has been suggested. According to the present model, even if transient shear banding appears during the shear ramps, in typical narrow-gap devices, only a small part of the hysteretic response can be attributed to heterogeneous flow. This results in decoupling of the hysteresis measured from the local velocity profiles and the global flow curve, demonstrating that for an arbitrary time-dependent rheological response this proposed coupling can be very weak.

  16. Proceedings of "Optical Probes of Dynamics in Complex Environments"

    SciTech Connect

    Sension, R; Tokmakoff, A

    2008-04-01

    This document contains the proceedings from the symposium on Optical Probes of Dynamics in Complex Environments, which organized as part of the 235th National Meeting of the American Chemical Society in New Orleans, LA from April 6 to 10, 2008. The study of molecular dynamics in chemical reaction and biological processes using time ƒresolved spectroscopy plays an important role in our understanding of energy conversion, storage, and utilization problems. Fundamental studies of chemical reactivity, molecular rearrangements, and charge transport are broadly supported by the DOE Office of Science because of their role in the development of alternative energy sources, the understanding of biological energy conversion processes, the efficient utilization of existing energy resources, and the mitigation of reactive intermediates in radiation chemistry. In addition, time resolved spectroscopy is central to all of DOEs grand challenges for fundamental energy science. This symposium brought together leaders in the field of ultrafast spectroscopy, including experimentalists, theoretical chemists, and simulators, to discuss the most recent scientific and technological advances. DOE support for this conference was used to help young US and international scientists travel to the meeting. The latest technology in ultrafast infrared, optical, and xray spectroscopy and the scientific advances that these methods enable were covered. Particular emphasis was placed on new experimental methods used to probe molecular dynamics in liquids, solids, interfaces, nanostructured materials, and biomolecules.

  17. Measurement and Information Extraction in Complex Dynamics Quantum Computation

    NASA Astrophysics Data System (ADS)

    Casati, Giulio; Montangero, Simone

    Quantum Information processing has several di.erent applications: some of them can be performed controlling only few qubits simultaneously (e.g. quantum teleportation or quantum cryptography) [1]. Usually, the transmission of large amount of information is performed repeating several times the scheme implemented for few qubits. However, to exploit the advantages of quantum computation, the simultaneous control of many qubits is unavoidable [2]. This situation increases the experimental di.culties of quantum computing: maintaining quantum coherence in a large quantum system is a di.cult task. Indeed a quantum computer is a many-body complex system and decoherence, due to the interaction with the external world, will eventually corrupt any quantum computation. Moreover, internal static imperfections can lead to quantum chaos in the quantum register thus destroying computer operability [3]. Indeed, as it has been shown in [4], a critical imperfection strength exists above which the quantum register thermalizes and quantum computation becomes impossible. We showed such e.ects on a quantum computer performing an e.cient algorithm to simulate complex quantum dynamics [5,6].

  18. Dynamics of Crowd Behaviors: From Complex Plane to Quantum Random Fields

    NASA Astrophysics Data System (ADS)

    Ivancevic, Vladimir G.; Reid, Darryn J.

    2015-11-01

    The following sections are included: * Complex Plane Dynamics of Crowds and Groups * Introduction * Complex-Valued Dynamics of Crowd and Group Behaviors * Kähler Geometry of Crowd and Group Dynamics * Computer Simulations of Crowds and Croups Dynamics * Braids of Agents' Behaviors in the Complex Plane * Hilbert-Space Control of Crowds and Groups Dynamics * Quantum Random Fields: A Unique Framework for Simulation, Optimization, Control and Learning * Introduction * Adaptive Quantum Oscillator * Optimization and Learning on Banach and Hilbert Spaces * Appendix * Complex-Valued Image Processing * Linear Integral Equations * Riemann-Liouville Fractional Calculus * Rigorous Geometric Quantization * Supervised Machine-Learning Methods * First-Order Logic and Quantum Random Fields

  19. Notes on the Langevin model for turbulent diffusion of ``marked`` particles

    SciTech Connect

    Rodean, H.C.

    1994-01-26

    Three models for scalar diffusion in turbulent flow (eddy diffusivity, random displacement, and on the Langevin equation) are briefly described. These models random velocity increment based Fokker-Planck equation is introduced as are then examined in more detail in the reverse order. The Fokker-Planck equation is the Eulerian equivalent of the Lagrangian Langevin equation, and the derivation of e outlined. The procedure for obtaining the deterministic and stochastic components of the Langevin equation from Kolmogorov`s 1941 inertial range theory and the Fokker-Planck equation is described. it is noted that a unique form of the Langevin equation can be determined for diffusion in one dimension but not in two or three. The Langevin equation for vertical diffusion in the non-Gaussian convective boundary layer is presented and successively simplified for Gaussian inhomogeneous turbulence and Gaussian homogeneous turbulence in turn. The Langevin equation for Gaussian inhomogeneous turbulence is mathematically transformed into the random displacement model. It is shown how the Fokker-Planck equation for the random displacement model is identical in form to the partial differential equation for the eddy diffusivity model. It is noted that the Langevin model is applicable in two cases in which the other two are not valid: (1) very close in time and distance to the point of scalar release and (2) the non-Gaussian convective boundary layer. The two- and three-dimensional cases are considered in Part III.

  20. Studying microstructural dynamics of complex fluids with particle tracking microrheology

    NASA Astrophysics Data System (ADS)

    Breedveld, Victor

    2004-11-01

    Over the last decade, particle tracking microrheology has matured as a new tool for complex fluids research. The main advantages of microrheology over traditional macroscopic rheometry are: the required sample size is extremely small ( ˜ 1 microliter); local viscoelastic properties in a sample can be probed with high spatial resolution ( ˜1-10 micrometer); and the sample is not disturbed by moving rheometer parts. I will present two examples of recent work in my group that highlight how these characteristics can be exploited to acquire unique information about the microstructure of complex fluids. First, we have studied protein unfolding. Traditionally, protein unfolding is studied with spectroscopic techniques (circular dichroism, NMR, fluorescence). Although viscosity has been listed in textbooks as a suitable technique, few -if any- quantitative rheological studies of unfolding have been reported, mainly due to technical difficulties. With microrheology, we have been able to quantify the size of the folded and unfolded protein, as well as the Gibbs free energy of unfolding, for aqueous bovine serum albumine solutions upon addition of urea as a denaturant. The results are in excellent agreement with literature data. Secondly, we have developed new technology for studying the microstructural dynamics of solvent-responsive complex fluids. In macroscopic rheometry it is virtually impossible to change solvent composition and measure the rheological response of a sample. By integrating microfluidics and microrheology we have been able to overcome this barrier: due to the micrometer lengthscales in microfluidiv devices, diffusive timescales in a dialysis set-up become short enough to achieve rapid and reversible changes in sample composition, without affecting the concentration of macromolecular components. Our dialysis cell for microrheology is a unique tool for studying the dynamics of structural and rheological changes induced by solvent composition. I will

  1. A complex-valued neural dynamical optimization approach and its stability analysis.

    PubMed

    Zhang, Songchuan; Xia, Youshen; Zheng, Weixing

    2015-01-01

    In this paper, we propose a complex-valued neural dynamical method for solving a complex-valued nonlinear convex programming problem. Theoretically, we prove that the proposed complex-valued neural dynamical approach is globally stable and convergent to the optimal solution. The proposed neural dynamical approach significantly generalizes the real-valued nonlinear Lagrange network completely in the complex domain. Compared with existing real-valued neural networks and numerical optimization methods for solving complex-valued quadratic convex programming problems, the proposed complex-valued neural dynamical approach can avoid redundant computation in a double real-valued space and thus has a low model complexity and storage capacity. Numerical simulations are presented to show the effectiveness of the proposed complex-valued neural dynamical approach.

  2. Complex systems approach to fire dynamics and climate change impacts

    NASA Astrophysics Data System (ADS)

    Pueyo, S.

    2012-04-01

    I present some recent advances in complex systems theory as a contribution to understanding fire regimes and forecasting their response to a changing climate, qualitatively and quantitatively. In many regions of the world, fire sizes have been found to follow, approximately, a power-law frequency distribution. As noted by several authors, this distribution also arises in the "forest fire" model used by physicists to study mechanisms that give rise to scale invariance (the power law is a scale-invariant distribution). However, this model does not give and does not pretend to give a realistic description of fire dynamics. For example, it gives no role to weather and climate. Pueyo (2007) developed a variant of the "forest fire" model that is also simple but attempts to be more realistic. It also results into a power law, but the parameters of this distribution change through time as a function of weather and climate. Pueyo (2007) observed similar patterns of response to weather in data from boreal forest fires, and used the fitted response functions to forecast fire size distributions in a possible climate change scenario, including the upper extreme of the distribution. For some parameter values, the model in Pueyo (2007) displays a qualitatively different behavior, consisting of simple percolation. In this case, fire is virtually absent, but megafires sweep through the ecosystem a soon as environmental forcings exceed a critical threshold. Evidence gathered by Pueyo et al. (2010) suggests that this is realistic for tropical rainforests (specifically, well-conserved upland rainforests). Some climate models suggest that major tropical rainforest regions are going to become hotter and drier if climate change goes ahead unchecked, which could cause such abrupt shifts. Not all fire regimes are well described by this model. Using data from a tropical savanna region, Pueyo et al. (2010) found that the dynamics in this area do not match its assumptions, even though fire

  3. Estimation of Instantaneous Complex Dynamics through Lyapunov Exponents: A Study on Heartbeat Dynamics

    PubMed Central

    Valenza, Gaetano; Citi, Luca; Barbieri, Riccardo

    2014-01-01

    Measures of nonlinearity and complexity, and in particular the study of Lyapunov exponents, have been increasingly used to characterize dynamical properties of a wide range of biological nonlinear systems, including cardiovascular control. In this work, we present a novel methodology able to effectively estimate the Lyapunov spectrum of a series of stochastic events in an instantaneous fashion. The paradigm relies on a novel point-process high-order nonlinear model of the event series dynamics. The long-term information is taken into account by expanding the linear, quadratic, and cubic Wiener-Volterra kernels with the orthonormal Laguerre basis functions. Applications to synthetic data such as the Hénon map and Rössler attractor, as well as two experimental heartbeat interval datasets (i.e., healthy subjects undergoing postural changes and patients with severe cardiac heart failure), focus on estimation and tracking of the Instantaneous Dominant Lyapunov Exponent (IDLE). The novel cardiovascular assessment demonstrates that our method is able to effectively and instantaneously track the nonlinear autonomic control dynamics, allowing for complexity variability estimations. PMID:25170911

  4. Incorporating geometrically complex vegetation in a computational fluid dynamic framework

    NASA Astrophysics Data System (ADS)

    Boothroyd, Richard; Hardy, Richard; Warburton, Jeff; Rosser, Nick

    2015-04-01

    Vegetation is known to have a significant influence on the hydraulic, geomorphological, and ecological functioning of river systems. Vegetation acts as a blockage to flow, thereby causing additional flow resistance and influencing flow dynamics, in particular flow conveyance. These processes need to be incorporated into flood models to improve predictions used in river management. However, the current practice in representing vegetation in hydraulic models is either through roughness parameterisation or process understanding derived experimentally from flow through highly simplified configurations of fixed, rigid cylinders. It is suggested that such simplifications inadequately describe the geometric complexity that characterises vegetation, and therefore the modelled flow dynamics may be oversimplified. This paper addresses this issue by using an approach combining field and numerical modelling techniques. Terrestrial Laser Scanning (TLS) with waveform processing has been applied to collect a sub-mm, 3-dimensional representation of Prunus laurocerasus, an invasive species to the UK that has been increasingly recorded in riparian zones. Multiple scan perspectives produce a highly detailed point cloud (>5,000,000 individual data points) which is reduced in post processing using an octree-based voxelisation technique. The method retains the geometric complexity of the vegetation by subdividing the point cloud into 0.01 m3 cubic voxels. The voxelised representation is subsequently read into a computational fluid dynamic (CFD) model using a Mass Flux Scaling Algorithm, allowing the vegetation to be directly represented in the modelling framework. Results demonstrate the development of a complex flow field around the vegetation. The downstream velocity profile is characterised by two distinct inflection points. A high velocity zone in the near-bed (plant-stem) region is apparent due to the lack of significant near-bed foliage. Above this, a zone of reduced velocity is

  5. Wake Dynamics in the Atmospheric Boundary Layer Over Complex Terrain

    NASA Astrophysics Data System (ADS)

    Markfort, Corey D.

    The goal of this research is to advance our understanding of atmospheric boundary layer processes over heterogeneous landscapes and complex terrain. The atmospheric boundary layer (ABL) is a relatively thin (˜ 1 km) turbulent layer of air near the earth's surface, in which most human activities and engineered systems are concentrated. Its dynamics are crucially important for biosphere-atmosphere couplings and for global atmospheric dynamics, with significant implications on our ability to predict and mitigate adverse impacts of land use and climate change. In models of the ABL, land surface heterogeneity is typically represented, in the context of Monin-Obukhov similarity theory, as changes in aerodynamic roughness length and surface heat and moisture fluxes. However, many real landscapes are more complex, often leading to massive boundary layer separation and wake turbulence, for which standard models fail. Trees, building clusters, and steep topography produce extensive wake regions currently not accounted for in models of the ABL. Wind turbines and wind farms also generate wakes that combine in complex ways to modify the ABL. Wind farms are covering an increasingly significant area of the globe and the effects of large wind farms must be included in regional and global scale models. Research presented in this thesis demonstrates that wakes caused by landscape heterogeneity must be included in flux parameterizations for momentum, heat, and mass (water vapor and trace gases, e.g. CO2 and CH4) in ABL simulation and prediction models in order to accurately represent land-atmosphere interactions. Accurate representation of these processes is crucial for the predictions of weather, air quality, lake processes, and ecosystems response to climate change. Objectives of the research reported in this thesis are: 1) to investigate turbulent boundary layer adjustment, turbulent transport and scalar flux in wind farms of varying configurations and develop an improved

  6. Quantum Dynamical Behaviour in Complex Systems - A Semiclassical Approach

    SciTech Connect

    Ananth, Nandini

    2008-01-01

    One of the biggest challenges in Chemical Dynamics is describing the behavior of complex systems accurately. Classical MD simulations have evolved to a point where calculations involving thousands of atoms are routinely carried out. Capturing coherence, tunneling and other such quantum effects for these systems, however, has proven considerably harder. Semiclassical methods such as the Initial Value Representation (SC-IVR) provide a practical way to include quantum effects while still utilizing only classical trajectory information. For smaller systems, this method has been proven to be most effective, encouraging the hope that it can be extended to deal with a large number of degrees of freedom. Several variations upon the original idea of the SCIVR have been developed to help make these larger calculations more tractable; these range from the simplest, classical limit form, the Linearized IVR (LSC-IVR) to the quantum limit form, the Exact Forward-Backward version (EFB-IVR). In this thesis a method to tune between these limits is described which allows us to choose exactly which degrees of freedom we wish to treat in a more quantum mechanical fashion and to what extent. This formulation is called the Tuning IVR (TIVR). We further describe methodology being developed to evaluate the prefactor term that appears in the IVR formalism. The regular prefactor is composed of the Monodromy matrices (jacobians of the transformation from initial to finial coordinates and momenta) which are time evolved using the Hessian. Standard MD simulations require the potential surfaces and their gradients, but very rarely is there any information on the second derivative. We would like to be able to carry out the SC-IVR calculation without this information too. With this in mind a finite difference scheme to obtain the Hessian on-the-fly is proposed. Wealso apply the IVR formalism to a few problems of current interest. A method to obtain energy eigenvalues accurately for complex

  7. Stochastic thermodynamics of Langevin systems under time-delayed feedback control: Second-law-like inequalities.

    PubMed

    Rosinberg, M L; Munakata, T; Tarjus, G

    2015-04-01

    Response lags are generic to almost any physical system and often play a crucial role in the feedback loops present in artificial nanodevices and biological molecular machines. In this paper, we perform a comprehensive study of small stochastic systems governed by an underdamped Langevin equation and driven out of equilibrium by a time-delayed continuous feedback control. In their normal operating regime, these systems settle in a nonequilibrium steady state in which work is permanently extracted from the surrounding heat bath. By using the Fokker-Planck representation of the dynamics, we derive a set of second-law-like inequalities that provide bounds to the rate of extracted work. These inequalities involve additional contributions characterizing the reduction of entropy production due to the continuous measurement process. We also show that the non-Markovian nature of the dynamics requires a modification of the basic relation linking dissipation to the breaking of time-reversal symmetry at the level of trajectories. The modified relation includes a contribution arising from the acausal character of the reverse process. This, in turn, leads to another second-law-like inequality. We illustrate the general formalism with a detailed analytical and numerical study of a harmonic oscillator driven by a linear feedback, which describes actual experimental setups.

  8. Complexity and Dynamic Heterogeneity of the Process of Cancer Metastasis

    NASA Astrophysics Data System (ADS)

    Chambers, Ann

    2010-03-01

    Cancer metastasis -- the spread of cancer from a primary tumor to distant parts of the body -- is responsible for most cancer deaths. If cancer is detected early, before it has spread, it can often be treated with local therapies like surgery and radiation. If cancer is detected after it has already spread, it is much harder to treat successfully. Cancer cells may be distributed to many organs, may be present as tiny micrometastases that are hard to detect, and cancer cells can be in a dormant state that may be resistant to treatment that is directed against actively dividing cells. A better understanding of the process of metastasis thus is needed in order to improve survival from cancer. Cancer is not a static disease, but one that can undergo stepwise evolution and progression from early, treatable cancer to aggressive cancer that is harder to treat. Furthermore, cancers are made up of many cells, and there is considerable heterogeneity among the cells in a tumor. Thus, cancer is ``plastic,'' with heterogeneity among cancer cells and changes over time. Understanding this ``dynamic heterogeneity'' has proven to be difficult. Input from physical sciences disciplines may help to shed light on this complex aspect of cancer biology. Here the process of cancer metastasis will be discussed, and experimental models for imaging the process described. The concept of ``dynamic heterogeneity'' of the metastatic process will be discussed, and some of the questions that need to be addressed for better understanding of metastasis will be outlined. An evolving dialogue between cancer biologists and physical scientists may lead to new ways of studying and understanding this lethal aspect of cancer.

  9. Modeling of complex systems using nonlinear, flexible multibody dynamics

    NASA Astrophysics Data System (ADS)

    Rodriguez, Jesus Diaz

    Finite element based multibody dynamics formulations extend the applicability of classical finite element methods to the modeling of flexible mechanisms. A general computer code will include rigid and flexible bodies, such as beams, joints, and active elements. These procedures are designed to overcome the modeling limitations of conventional multibody formulations that are often restricted to the analysis of rigid systems or use a modal representation to model the flexibility of elastic components. As multibody formulations become more widely accepted, the need to model a wider array of phenomena increases. The goal of this work is to present a methodology for the analysis of complex systems that may require the modeling of new joints and elements, or include the effects of clearance, freeplay or friction in the joints. Joints are essential components of multibody systems, rigid or flexible. Usually, joints are modeled as perfect components. In actual joints, clearance, freeplay, friction, lubrication and impact forces will can have a significant effect on the dynamic response of the system. Certain systems require the formulation of new joints for their analysis. Among one of them is the curve sliding joint which enforces the sliding of a body on a rigid curve connected to another body. The curve sliding joint is especially useful when modeling a vibration absorber device mounted on the rotor hub of rotorcraft: the bifilar pendulum. The formulation of a new modal based element is also presented. A modal based element is a model of an elastic substructure that includes a modal representation of elastic effects together with large rigid body motions. The proposed approach makes use of a component mode synthesis technique that allows the analyst to choose any type of modal basis and simplifies the connection to other multibody elements. The formulation is independent of the finite element analysis package used to compute the modes of the elastic component.

  10. Structuring and sampling complex conformation space: Weighted ensemble dynamics simulations.

    PubMed

    Gong, Linchen; Zhou, Xin

    2009-08-01

    Based on multiple simulation trajectories, which started from dispersively selected initial conformations, the weighted ensemble dynamics method is designed to robustly and systematically explore the hierarchical structure of complex conformational space through the spectral analysis of the variance-covariance matrix of trajectory-mapped vectors. The nondegenerate ground state of the matrix directly predicts the ergodicity of simulation data. The ground state could be adopted as statistical weights of trajectories to correctly reconstruct the equilibrium properties, even though each trajectory only explores part of the conformational space. Otherwise, the degree of degeneracy simply gives the number of metastable states of the system under the time scale of individual trajectory. Manipulation on the eigenvectors leads to the classification of trajectories into nontransition ones within the states and transition ones between them. The transition states may also be predicted without a priori knowledge of the system. We demonstrate the application of the general method both to the system with a one-dimensional glassy potential and with the one of alanine dipeptide in explicit solvent.

  11. Structuring and sampling complex conformation space: Weighted ensemble dynamics simulations

    NASA Astrophysics Data System (ADS)

    Gong, Linchen; Zhou, Xin

    2009-08-01

    Based on multiple simulation trajectories, which started from dispersively selected initial conformations, the weighted ensemble dynamics method is designed to robustly and systematically explore the hierarchical structure of complex conformational space through the spectral analysis of the variance-covariance matrix of trajectory-mapped vectors. The nondegenerate ground state of the matrix directly predicts the ergodicity of simulation data. The ground state could be adopted as statistical weights of trajectories to correctly reconstruct the equilibrium properties, even though each trajectory only explores part of the conformational space. Otherwise, the degree of degeneracy simply gives the number of metastable states of the system under the time scale of individual trajectory. Manipulation on the eigenvectors leads to the classification of trajectories into nontransition ones within the states and transition ones between them. The transition states may also be predicted without a priori knowledge of the system. We demonstrate the application of the general method both to the system with a one-dimensional glassy potential and with the one of alanine dipeptide in explicit solvent.

  12. Intrinsic Multi-Scale Dynamic Behaviors of Complex Financial Systems.

    PubMed

    Ouyang, Fang-Yan; Zheng, Bo; Jiang, Xiong-Fei

    2015-01-01

    The empirical mode decomposition is applied to analyze the intrinsic multi-scale dynamic behaviors of complex financial systems. In this approach, the time series of the price returns of each stock is decomposed into a small number of intrinsic mode functions, which represent the price motion from high frequency to low frequency. These intrinsic mode functions are then grouped into three modes, i.e., the fast mode, medium mode and slow mode. The probability distribution of returns and auto-correlation of volatilities for the fast and medium modes exhibit similar behaviors as those of the full time series, i.e., these characteristics are rather robust in multi time scale. However, the cross-correlation between individual stocks and the return-volatility correlation are time scale dependent. The structure of business sectors is mainly governed by the fast mode when returns are sampled at a couple of days, while by the medium mode when returns are sampled at dozens of days. More importantly, the leverage and anti-leverage effects are dominated by the medium mode. PMID:26427063

  13. Molecular Dynamics of Mouse Acetylcholinesterase Complexed with Huperzine A

    SciTech Connect

    Tara, Sylvia; Helms, Volkhard H.; Straatsma, TP; Mccammon, J Andrew A.

    1999-03-16

    Two molecular dynamics simulations were performed for a modeled complex of mouse acetylcholinesterase liganded with huperzine A (HupA). Analysis of these simulations shows that HupA shifts in the active site toward Tyr 337 and Phe 338, and that several residues in the active site area reach out to make hydrogen bonds with the inhibitor. Rapid fluctuations of the gorge width are observed, ranging from widths that allow substrate access to the active site, to pinched structures that do not allow access of molecules as small as water. Additional openings or channels to the active site are found. One opening is formed in the side wall of the active site gorge by residues Val 73, Asp 74, Thr 83, Glu 84, and Asn 87. Another opening is formed at the base of the gorge by residues Trp 86, Val 132, Glu 202, Gly 448, and Ile 451. Both of these openings have been observed separately in the Torpedo californica form of the enzyme. These channels could allow transport of waters and ions to and from the bulk solution.

  14. An ICAI architecture for troubleshooting in complex, dynamic systems

    NASA Technical Reports Server (NTRS)

    Fath, Janet L.; Mitchell, Christine M.; Govindaraj, T.

    1990-01-01

    Ahab, an intelligent computer-aided instruction (ICAI) program, illustrates an architecture for simulator-based ICAI programs to teach troubleshooting in complex, dynamic environments. The architecture posits three elements of a computerized instructor: the task model, the student model, and the instructional module. The task model is a prescriptive model of expert performance that uses symptomatic and topographic search strategies to provide students with directed problem-solving aids. The student model is a descriptive model of student performance in the context of the task model. This student model compares the student and task models, critiques student performance, and provides interactive performance feedback. The instructional module coordinates information presented by the instructional media, the task model, and the student model so that each student receives individualized instruction. Concept and metaconcept knowledge that supports these elements is contained in frames and production rules, respectively. The results of an experimental evaluation are discussed. They support the hypothesis that training with an adaptive online system built using the Ahab architecture produces better performance than training using simulator practice alone, at least with unfamiliar problems. It is not sufficient to develop an expert strategy and present it to students using offline materials. The training is most effective if it adapts to individual student needs.

  15. Intrinsic Multi-Scale Dynamic Behaviors of Complex Financial Systems

    PubMed Central

    Ouyang, Fang-Yan; Zheng, Bo; Jiang, Xiong-Fei

    2015-01-01

    The empirical mode decomposition is applied to analyze the intrinsic multi-scale dynamic behaviors of complex financial systems. In this approach, the time series of the price returns of each stock is decomposed into a small number of intrinsic mode functions, which represent the price motion from high frequency to low frequency. These intrinsic mode functions are then grouped into three modes, i.e., the fast mode, medium mode and slow mode. The probability distribution of returns and auto-correlation of volatilities for the fast and medium modes exhibit similar behaviors as those of the full time series, i.e., these characteristics are rather robust in multi time scale. However, the cross-correlation between individual stocks and the return-volatility correlation are time scale dependent. The structure of business sectors is mainly governed by the fast mode when returns are sampled at a couple of days, while by the medium mode when returns are sampled at dozens of days. More importantly, the leverage and anti-leverage effects are dominated by the medium mode. PMID:26427063

  16. Dynamics of the Toxoplasma gondii inner membrane complex.

    PubMed

    Ouologuem, Dinkorma T; Roos, David S

    2014-08-01

    Unlike most cells, protozoa in the phylum Apicomplexa divide by a distinctive process in which multiple daughters are assembled within the mother (schizogony or endodyogeny), using scaffolding known as the inner membrane complex (IMC). The IMC underlies the plasma membrane during interphase, but new daughters develop in the cytoplasm, as cytoskeletal filaments associate with flattened membrane cisternae (alveolae), which elongate rapidly to encapsulate subcellular organelles. Newly assembled daughters acquire their plasma membrane as they emerge from the mother, leaving behind vestiges of the maternal cell. Although the maternal plasma membrane remains intact throughout this process, the maternal IMC disappears - is it degraded, or recycled to form the daughter IMC? Exploiting fluorescently tagged IMC markers, we have used live-cell imaging, fluorescence recovery after photobleaching (FRAP) and mEos2 photoactivation to monitor the dynamics of IMC biogenesis and turnover during the replication of Toxoplasma gondii tachyzoites. These studies reveal that the formation of the T. gondii IMC involves two distinct steps - de novo assembly during daughter IMC elongation within the mother cell, followed by recycling of maternal IMC membranes after the emergence of daughters from the mother cell.

  17. Inclusion of trial functions in the Langevin equation path integral ground state method: Application to parahydrogen clusters and their isotopologues

    SciTech Connect

    Schmidt, Matthew; Constable, Steve; Ing, Christopher; Roy, Pierre-Nicholas

    2014-06-21

    We developed and studied the implementation of trial wavefunctions in the newly proposed Langevin equation Path Integral Ground State (LePIGS) method [S. Constable, M. Schmidt, C. Ing, T. Zeng, and P.-N. Roy, J. Phys. Chem. A 117, 7461 (2013)]. The LePIGS method is based on the Path Integral Ground State (PIGS) formalism combined with Path Integral Molecular Dynamics sampling using a Langevin equation based sampling of the canonical distribution. This LePIGS method originally incorporated a trivial trial wavefunction, ψ{sub T}, equal to unity. The present paper assesses the effectiveness of three different trial wavefunctions on three isotopes of hydrogen for cluster sizes N = 4, 8, and 13. The trial wavefunctions of interest are the unity trial wavefunction used in the original LePIGS work, a Jastrow trial wavefunction that includes correlations due to hard-core repulsions, and a normal mode trial wavefunction that includes information on the equilibrium geometry. Based on this analysis, we opt for the Jastrow wavefunction to calculate energetic and structural properties for parahydrogen, orthodeuterium, and paratritium clusters of size N = 4 − 19, 33. Energetic and structural properties are obtained and compared to earlier work based on Monte Carlo PIGS simulations to study the accuracy of the proposed approach. The new results for paratritium clusters will serve as benchmark for future studies. This paper provides a detailed, yet general method for optimizing the necessary parameters required for the study of the ground state of a large variety of systems.

  18. Dynamics of Major Histocompatibility Complex Class I Association with the Human Peptide-loading Complex*

    PubMed Central

    Panter, Michaela S.; Jain, Ankur; Leonhardt, Ralf M.; Ha, Taekjip; Cresswell, Peter

    2012-01-01

    Although the human peptide-loading complex (PLC) is required for optimal major histocompatibility complex class I (MHC I) antigen presentation, its composition is still incompletely understood. The ratio of the transporter associated with antigen processing (TAP) and MHC I to tapasin, which is responsible for MHC I recruitment and peptide binding optimization, is particularly critical for modeling of the PLC. Here, we characterized the stoichiometry of the human PLC using both biophysical and biochemical approaches. By means of single-molecule pulldown (SiMPull), we determined a TAP/tapasin ratio of 1:2, consistent with previous studies of insect-cell microsomes, rat-human chimeric cells, and HeLa cells expressing truncated TAP subunits. We also report that the tapasin/MHC I ratio varies, with the PLC population comprising both 2:1 and 2:2 complexes, based on mutational and co-precipitation studies. The MHC I-saturated PLC may be particularly prevalent among peptide-selective alleles, such as HLA-C4. Additionally, MHC I association with the PLC increases when its peptide supply is reduced by inhibiting the proteasome or by blocking TAP-mediated peptide transport using viral inhibitors. Taken together, our results indicate that the composition of the human PLC varies under normal conditions and dynamically adapts to alterations in peptide supply that may arise during viral infection. These findings improve our understanding of the quality control of MHC I peptide loading and may aid the structural and functional modeling of the human PLC. PMID:22829594

  19. Energetic modeling and single-molecule verification of dynamic regulation on receptor complexes by actin corrals and lipid raft domains

    NASA Astrophysics Data System (ADS)

    Lin, Chien Y.; Huang, Jung Y.; Lo, Leu-Wei

    2014-12-01

    We developed an energetic model by integrating the generalized Langevin equation with the Cahn-Hilliard equation to simulate the diffusive behaviors of receptor proteins in the plasma membrane of a living cell. Simulation results are presented to elaborate the confinement effects from actin corrals and protein-induced lipid domains. Single-molecule tracking data of epidermal growth factor receptors (EGFR) acquired on live HeLa cells agree with the simulation results and the mechanism that controls the diffusion of single-molecule receptors is clarified. We discovered that after ligand binding, EGFR molecules move into lipid nanodomains. The transition rates between different diffusion states of liganded EGFR molecules are regulated by the lipid domains. Our method successfully captures dynamic interactions of receptors at the single-molecule level and provides insight into the functional architecture of both the diffusing EGFR molecules and their local cellular environment.

  20. Energetic modeling and single-molecule verification of dynamic regulation on receptor complexes by actin corrals and lipid raft domains.

    PubMed

    Lin, Chien Y; Huang, Jung Y; Lo, Leu-Wei

    2014-12-01

    We developed an energetic model by integrating the generalized Langevin equation with the Cahn-Hilliard equation to simulate the diffusive behaviors of receptor proteins in the plasma membrane of a living cell. Simulation results are presented to elaborate the confinement effects from actin corrals and protein-induced lipid domains. Single-molecule tracking data of epidermal growth factor receptors (EGFR) acquired on live HeLa cells agree with the simulation results and the mechanism that controls the diffusion of single-molecule receptors is clarified. We discovered that after ligand binding, EGFR molecules move into lipid nanodomains. The transition rates between different diffusion states of liganded EGFR molecules are regulated by the lipid domains. Our method successfully captures dynamic interactions of receptors at the single-molecule level and provides insight into the functional architecture of both the diffusing EGFR molecules and their local cellular environment. PMID:25481171

  1. Irreversible Langevin samplers and variance reduction: a large deviations approach

    NASA Astrophysics Data System (ADS)

    Rey-Bellet, Luc; Spiliopoulos, Konstantinos

    2015-07-01

    In order to sample from a given target distribution (often of Gibbs type), the Monte Carlo Markov chain method consists of constructing an ergodic Markov process whose invariant measure is the target distribution. By sampling the Markov process one can then compute, approximately, expectations of observables with respect to the target distribution. Often the Markov processes used in practice are time-reversible (i.e. they satisfy detailed balance), but our main goal here is to assess and quantify how the addition of a non-reversible part to the process can be used to improve the sampling properties. We focus on the diffusion setting (overdamped Langevin equations) where the drift consists of a gradient vector field as well as another drift which breaks the reversibility of the process but is chosen to preserve the Gibbs measure. In this paper we use the large deviation rate function for the empirical measure as a tool to analyze the speed of convergence to the invariant measure. We show that the addition of an irreversible drift leads to a larger rate function and it strictly improves the speed of convergence of ergodic average for (generic smooth) observables. We also deduce from this result that the asymptotic variance decreases under the addition of the irreversible drift and we give an explicit characterization of the observables whose variance is not reduced reduced, in terms of a nonlinear Poisson equation. Our theoretical results are illustrated and supplemented by numerical simulations.

  2. Ergodic properties of fractional Brownian-Langevin motion.

    PubMed

    Deng, Weihua; Barkai, Eli

    2009-01-01

    We investigate the time average mean-square displacement delta;{2}[over ](x(t))=integral_{0};{t-Delta}[x(t;{'}+Delta)-x(t;{'})];{2}dt;{'}(t-Delta) for fractional Brownian-Langevin motion where x(t) is the stochastic trajectory and Delta is the lag time. Unlike the previously investigated continuous-time random-walk model, delta;{2}[over ] converges to the ensemble average x;{2} approximately t;{2H} in the long measurement time limit. The convergence to ergodic behavior is slow, however, and surprisingly the Hurst exponent H=3/4 marks the critical point of the speed of convergence. When H<3/4 , the ergodicity breaking parameter E_{B}=[[delta;{2}[over ](x(t))];{2}-delta;{2}[over ](x(t));{2}]/delta;{2}[over ](x(t));{2} approximately k(H)Deltat;{-1} , when H=3/4 , E_{B} approximately (9/16)(lnt)Deltat;{-1} , and when 3/41 ergodicity is broken and E_{B} approximately 2 . The critical point H=3/4 is marked by the divergence of the coefficient k(H) . Fractional Brownian motion as a model for recent experiments of subdiffusion of mRNA in the cell is briefly discussed, and a comparison with the continuous-time random-walk model is made. PMID:19257006

  3. Classification of time series patterns from complex dynamic systems

    SciTech Connect

    Schryver, J.C.; Rao, N.

    1998-07-01

    An increasing availability of high-performance computing and data storage media at decreasing cost is making possible the proliferation of large-scale numerical databases and data warehouses. Numeric warehousing enterprises on the order of hundreds of gigabytes to terabytes are a reality in many fields such as finance, retail sales, process systems monitoring, biomedical monitoring, surveillance and transportation. Large-scale databases are becoming more accessible to larger user communities through the internet, web-based applications and database connectivity. Consequently, most researchers now have access to a variety of massive datasets. This trend will probably only continue to grow over the next several years. Unfortunately, the availability of integrated tools to explore, analyze and understand the data warehoused in these archives is lagging far behind the ability to gain access to the same data. In particular, locating and identifying patterns of interest in numerical time series data is an increasingly important problem for which there are few available techniques. Temporal pattern recognition poses many interesting problems in classification, segmentation, prediction, diagnosis and anomaly detection. This research focuses on the problem of classification or characterization of numerical time series data. Highway vehicles and their drivers are examples of complex dynamic systems (CDS) which are being used by transportation agencies for field testing to generate large-scale time series datasets. Tools for effective analysis of numerical time series in databases generated by highway vehicle systems are not yet available, or have not been adapted to the target problem domain. However, analysis tools from similar domains may be adapted to the problem of classification of numerical time series data.

  4. Sinks without borders: Snowshoe hare dynamics in a complex landscape

    USGS Publications Warehouse

    Griffin, P.C.; Scott, Mills L.

    2009-01-01

    A full understanding of population dynamics of wide-ranging animals should account for the effects that movement and habitat use have on individual contributions to population growth or decline. Quantifying the per-capita, habitat-specific contribution to population growth can clarify the value of different patch types, and help to differentiate population sources from population sinks. Snowshoe hares, Lepus americanus, routinely use various habitat types in the landscapes they inhabit in the contiguous US, where managing forests for high snowshoe hare density is a priority for conservation of Canada lynx, Lynx canadensis. We estimated density and demographic rates via mark-recapture live trapping and radio-telemetry within four forest stand structure (FSS) types at three study areas within heterogeneous managed forests in western Montana. We found support for known fate survival models with time-varying individual covariates representing the proportion of locations in each of the FSS types, with survival rates decreasing as use of open young and open mature FSS types increased. The per-capita contribution to overall population growth increased with use of the dense mature or dense young FSS types and decreased with use of the open young or open mature FSS types, and relatively high levels of immigration appear to be necessary to sustain hares in the open FSS types. Our results support a conceptual model for snowshoe hares in the southern range in which sink habitats (open areas) prevent the buildup of high hare densities. More broadly, we use this system to develop a novel approach to quantify demographic sources and sinks for animals making routine movements through complex fragmented landscapes. ?? 2009 Oikos.

  5. Non-Gaussian statistics, classical field theory, and realizable Langevin models

    SciTech Connect

    Krommes, J.A.

    1995-11-01

    The direct-interaction approximation (DIA) to the fourth-order statistic Z {approximately}{l_angle}{lambda}{psi}{sup 2}){sup 2}{r_angle}, where {lambda} is a specified operator and {psi} is a random field, is discussed from several points of view distinct from that of Chen et al. [Phys. Fluids A 1, 1844 (1989)]. It is shown that the formula for Z{sub DIA} already appeared in the seminal work of Martin, Siggia, and Rose (Phys. Rev. A 8, 423 (1973)] on the functional approach to classical statistical dynamics. It does not follow from the original generalized Langevin equation (GLE) of Leith [J. Atmos. Sd. 28, 145 (1971)] and Kraichnan [J. Fluid Mech. 41, 189 (1970)] (frequently described as an amplitude representation for the DIA), in which the random forcing is realized by a particular superposition of products of random variables. The relationship of that GLE to renormalized field theories with non-Gaussian corrections (``spurious vertices``) is described. It is shown how to derive an improved representation, that realizes cumulants through O({psi}{sup 4}), by adding to the GLE a particular non-Gaussian correction. A Markovian approximation Z{sub DIA}{sup M} to Z{sub DIA} is derived. Both Z{sub DIA} and Z{sub DIA}{sup M} incorrectly predict a Gaussian kurtosis for the steady state of a solvable three-mode example.

  6. Pre- and post- scission particle emission in 3D Langevin calculations with various macroscopic potentials

    NASA Astrophysics Data System (ADS)

    Mazurek, K.; Nadtochy, P. N.; Schmitt, C.; Wasiak, P.; Kmiecik, M.; Maj, A.; Bonnet, E.; Chbihi, A.; Frankland, J.; Gruyer, D.; Wieleczko, J.-P.

    2013-12-01

    The fission dynamics described by solving differential equations of the Langevin type in three dimensional space of the deformation parameters is very sensitive on the choice of the macroscopic components such as potential energy models. The mass or charge distribution or total kinetic energy has been already shown to be different when one uses the Finite Range Liquid Drop Model or Lublin - Strasbourg Drop model. Also the shape-dependent congruence or shape-dependent Wigner energy and A0 terms are important especially for the fission of medium mass nuclei. We would like to make step forward and answer the question about the varying of the post-scission multiplicity by including different PES. Up to now there are only few experimental data for the medium mass nuclei where the pre- and post- scission emission has been estimated and isotopic distributions have been shown. The isotopic distributions of the fission products for light compound nucleus such as 111 In with two beam energies (Ebeam = 10.6 AMeV and 5.9 AMeV) and two heavy systems: 229Np with Ebeam = 7.4 AMeV and 260 No (Ebeam = 6 AMeV and 7.5 AMeV) have been studied theoretically. The agreement with the experimental data is discussed.

  7. A smart pinless ejection mechanism using dual-resonance excitation Langevin piezoelectric transducers

    NASA Astrophysics Data System (ADS)

    Wang, Yu-Jen; Fu, Kuo-Chieh; Wang, Chun-Chieh

    2016-01-01

    This study investigated a smart pinless ejection mechanism comprising two dual-resonance excitation Langevin piezoelectric transducers (DRELPTs) for keeping the injection parts intact and protecting their top and bottom surfaces from scarring during plastic injection molding. The dimensions of each DRELPT were determined using longitudinal vibration models, and an optimization method was used to set the frequency ratio of the first to the second longitudinal mode to 1:2. This concept enables the driving of DRELPT in its two longitudinal modes consistent with the ejection direction in resonant-type smooth impact drive mechanisms. During the ejection process, DRELPT provides an ejection force, which is applied on the sidewalls of the injection parts to protect their top and bottom surfaces from scarring. Considering individual differences in the resonance frequencies of DRELPTs, a resonance frequency tracking circuit based on a phase-locked loop was designed to keep DRELPT actuating in resonance. The ejection velocity of the injection part was estimated using the kinetic models derived from the dynamic behavior of the mold cavity and injection parameters. A characteristic number S was defined to evaluate the average velocity of the injection part during ejection. Proof-of-concept experimental results of the pinless ejection mechanism are presented. The ejection time, that is, the time from triggering the composite wave to the full departure of the injection part from the mold cavity, was 72 ms.

  8. The Spatial Chemical Langevin and Reaction Diffusion Master Equations: Moments and Qualitative Solutions

    NASA Astrophysics Data System (ADS)

    Ghosh, Atiyo; Leier, Andre; Marquez-Lago, Tatiana

    2014-03-01

    Spatial stochastic effects are prevalent in many biological systems spanning a variety of scales, from intracellular (e.g. gene expression) to ecological (plankton aggregation). The most common ways of simulating such systems involve drawing sample paths from either the Reaction Diffusion Master Equation (RDME) or the Smoluchowski Equation, using methods such as Gillespie's Simulation Algorithm, Green's Function Reaction Dynamics and Single Particle Tracking. The simulation times of such techniques scale with the number of simulated particles, leading to much computational expense when considering large systems. The Spatial Chemical Langevin Equation (SCLE) can be simulated with fixed time intervals, independent of the number of particles, and can thus provide significant computational savings. However, very little work has been done to investigate the behavior of the SCLE. In this talk we summarize our findings on comparing the SCLE to the well-studied RDME. We use both analytical and numerical procedures to show when one should expect the moments of the SCLE to be close to the RDME, and also when they should differ.

  9. BDO-RFQ Program Complex of Modelling and Optimization of Charged Particle Dynamics

    NASA Astrophysics Data System (ADS)

    Ovsyannikov, D. A.; Ovsyannikov, A. D.; Antropov, I. V.; Kozynchenko, V. A.

    2016-09-01

    The article is dedicated to BDO Code program complex used for modelling and optimization of charged particle dynamics with consideration of interaction in RFQ accelerating structures. The structure of the program complex and its functionality are described; mathematical models of charged particle dynamics, interaction models and methods of optimization are given.

  10. Dynamics of Complexity and Accuracy: A Longitudinal Case Study of Advanced Untutored Development

    ERIC Educational Resources Information Center

    Polat, Brittany; Kim, Youjin

    2014-01-01

    This longitudinal case study follows a dynamic systems approach to investigate an under-studied research area in second language acquisition, the development of complexity and accuracy for an advanced untutored learner of English. Using the analytical tools of dynamic systems theory (Verspoor et al. 2011) within the framework of complexity,…

  11. Understanding the complexity of temperature dynamics in Xinjiang, China, from multitemporal scale and spatial perspectives.

    PubMed

    Xu, Jianhua; Chen, Yaning; Li, Weihong; Liu, Zuhan; Wei, Chunmeng; Tang, Jie

    2013-01-01

    Based on the observed data from 51 meteorological stations during the period from 1958 to 2012 in Xinjiang, China, we investigated the complexity of temperature dynamics from the temporal and spatial perspectives by using a comprehensive approach including the correlation dimension (CD), classical statistics, and geostatistics. The main conclusions are as follows (1) The integer CD values indicate that the temperature dynamics are a complex and chaotic system, which is sensitive to the initial conditions. (2) The complexity of temperature dynamics decreases along with the increase of temporal scale. To describe the temperature dynamics, at least 3 independent variables are needed at daily scale, whereas at least 2 independent variables are needed at monthly, seasonal, and annual scales. (3) The spatial patterns of CD values at different temporal scales indicate that the complex temperature dynamics are derived from the complex landform.

  12. Theoretical Studies on Docking Dynamics and Electronic Structure in Metalloprotein Complexes

    NASA Astrophysics Data System (ADS)

    Sugiyama, Ayumu; Nishikawa, Keigo; Yamamoto, Tetsunori; Purqon, Acep; Nishikawa, Kiyoshi; Nagao, Hidemi

    2007-12-01

    An investigating of docking structure and dynamics between metalloprotein is interested from the viewpoint of searching the function of protein. We investigate the cytochrome c551 and azurin complexes by three computational methods, quantum mechanical calculation, docking searching algorism and molecular dynamics simulation. At first we present the docking structure of the cytochrome c551-azurin complexes expected by ZDOCK searching algorism. Quantum chemical calculation is tools to estimate the charge distrubution around the active site for each protein and force field parameters. From these parameters, we reproduce the protein docking dynamics by molecular dynamics simulation. We analyze some physical properties of complex system such as binding free energy, dynamical cross correlation map, and so on. We discuss the docking stability and dynamical effect of the cytochrome c551-azurin complexes.

  13. The complex interplay between mitochondrial dynamics and cardiac metabolism

    PubMed Central

    Parra, Valentina; Verdejo, Hugo; del Campo, Andrea; Pennanen, Christian; Kuzmicic, Jovan; Iglewski, Myriam; Hill, Joseph A.; Rothermel, Beverly A.

    2012-01-01

    Mitochondria are highly dynamic organelles, capable of undergoing constant fission and fusion events, forming networks. These dynamic events allow the transmission of chemical and physical messengers and the exchange of metabolites within the cell. In this article we review the signaling mechanisms controlling mitochondrial fission and fusion, and its relationship with cell bioenergetics, especially in the heart. Furthermore we also discuss how defects in mitochondrial dynamics might be involved in the pathogenesis of metabolic cardiac diseases. PMID:21258852

  14. Langevin equation with fluctuating diffusivity: A two-state model.

    PubMed

    Miyaguchi, Tomoshige; Akimoto, Takuma; Yamamoto, Eiji

    2016-07-01

    Recently, anomalous subdiffusion, aging, and scatter of the diffusion coefficient have been reported in many single-particle-tracking experiments, though the origins of these behaviors are still elusive. Here, as a model to describe such phenomena, we investigate a Langevin equation with diffusivity fluctuating between a fast and a slow state. Namely, the diffusivity follows a dichotomous stochastic process. We assume that the sojourn time distributions of these two states are given by power laws. It is shown that, for a nonequilibrium ensemble, the ensemble-averaged mean-square displacement (MSD) shows transient subdiffusion. In contrast, the time-averaged MSD shows normal diffusion, but an effective diffusion coefficient transiently shows aging behavior. The propagator is non-Gaussian for short time and converges to a Gaussian distribution in a long-time limit; this convergence to Gaussian is extremely slow for some parameter values. For equilibrium ensembles, both ensemble-averaged and time-averaged MSDs show only normal diffusion and thus we cannot detect any traces of the fluctuating diffusivity with these MSDs. Therefore, as an alternative approach to characterizing the fluctuating diffusivity, the relative standard deviation (RSD) of the time-averaged MSD is utilized and it is shown that the RSD exhibits slow relaxation as a signature of the long-time correlation in the fluctuating diffusivity. Furthermore, it is shown that the RSD is related to a non-Gaussian parameter of the propagator. To obtain these theoretical results, we develop a two-state renewal theory as an analytical tool. PMID:27575079

  15. Langevin equation with fluctuating diffusivity: A two-state model

    NASA Astrophysics Data System (ADS)

    Miyaguchi, Tomoshige; Akimoto, Takuma; Yamamoto, Eiji

    2016-07-01

    Recently, anomalous subdiffusion, aging, and scatter of the diffusion coefficient have been reported in many single-particle-tracking experiments, though the origins of these behaviors are still elusive. Here, as a model to describe such phenomena, we investigate a Langevin equation with diffusivity fluctuating between a fast and a slow state. Namely, the diffusivity follows a dichotomous stochastic process. We assume that the sojourn time distributions of these two states are given by power laws. It is shown that, for a nonequilibrium ensemble, the ensemble-averaged mean-square displacement (MSD) shows transient subdiffusion. In contrast, the time-averaged MSD shows normal diffusion, but an effective diffusion coefficient transiently shows aging behavior. The propagator is non-Gaussian for short time and converges to a Gaussian distribution in a long-time limit; this convergence to Gaussian is extremely slow for some parameter values. For equilibrium ensembles, both ensemble-averaged and time-averaged MSDs show only normal diffusion and thus we cannot detect any traces of the fluctuating diffusivity with these MSDs. Therefore, as an alternative approach to characterizing the fluctuating diffusivity, the relative standard deviation (RSD) of the time-averaged MSD is utilized and it is shown that the RSD exhibits slow relaxation as a signature of the long-time correlation in the fluctuating diffusivity. Furthermore, it is shown that the RSD is related to a non-Gaussian parameter of the propagator. To obtain these theoretical results, we develop a two-state renewal theory as an analytical tool.

  16. Stochastic Cascade Dynamical Downscaling of Precipitation over Complex Terrain

    NASA Astrophysics Data System (ADS)

    Posadas, A.; Duffaut, L. E.; Jones, C.; Carvalho, L. V.; Carbajal, M.; Heidinger, H.; Quiroz, R.

    2013-12-01

    spatial and temporal variability of rainfall between the rainfall fields obtained from the rain gauge network and those generated by the simulation model. The potential advantages of this methodology are discussed.Stochastic Cascade Dynamical Downscaling of Precipitation over Complex Terrain

  17. Complexity, Chaos, and Nonlinear Dynamics: A New Perspective on Career Development Theory

    ERIC Educational Resources Information Center

    Bloch, Deborah P.

    2005-01-01

    The author presents a theory of career development drawing on nonlinear dynamics and chaos and complexity theories. Career is presented as a complex adaptive entity, a fractal of the human entity. Characteristics of complex adaptive entities, including (a) autopiesis, or self-regeneration; (b) open exchange; (c) participation in networks; (d)…

  18. Ultraprecision XY stage using a hybrid bolt-clamped Langevin-type ultrasonic linear motor for continuous motion

    NASA Astrophysics Data System (ADS)

    Lee, Dong-Jin; Lee, Sun-Kyu

    2015-01-01

    This paper presents a design and control system for an XY stage driven by an ultrasonic linear motor. In this study, a hybrid bolt-clamped Langevin-type ultrasonic linear motor was manufactured and then operated at the resonance frequency of the third longitudinal and the sixth lateral modes. These two modes were matched through the preload adjustment and precisely tuned by the frequency matching method based on the impedance matching method with consideration of the different moving weights. The XY stage was evaluated in terms of position and circular motion. To achieve both fine and stable motion, the controller consisted of a nominal characteristics trajectory following (NCTF) control for continuous motion, dead zone compensation, and a switching controller based on the different NCTFs for the macro- and micro-dynamics regimes. The experimental results showed that the developed stage enables positioning and continuous motion with nanometer-level accuracy.

  19. Ultraprecision XY stage using a hybrid bolt-clamped Langevin-type ultrasonic linear motor for continuous motion.

    PubMed

    Lee, Dong-Jin; Lee, Sun-Kyu

    2015-01-01

    This paper presents a design and control system for an XY stage driven by an ultrasonic linear motor. In this study, a hybrid bolt-clamped Langevin-type ultrasonic linear motor was manufactured and then operated at the resonance frequency of the third longitudinal and the sixth lateral modes. These two modes were matched through the preload adjustment and precisely tuned by the frequency matching method based on the impedance matching method with consideration of the different moving weights. The XY stage was evaluated in terms of position and circular motion. To achieve both fine and stable motion, the controller consisted of a nominal characteristics trajectory following (NCTF) control for continuous motion, dead zone compensation, and a switching controller based on the different NCTFs for the macro- and micro-dynamics regimes. The experimental results showed that the developed stage enables positioning and continuous motion with nanometer-level accuracy.

  20. Ultraprecision XY stage using a hybrid bolt-clamped Langevin-type ultrasonic linear motor for continuous motion

    SciTech Connect

    Lee, Dong-Jin; Lee, Sun-Kyu

    2015-01-15

    This paper presents a design and control system for an XY stage driven by an ultrasonic linear motor. In this study, a hybrid bolt-clamped Langevin-type ultrasonic linear motor was manufactured and then operated at the resonance frequency of the third longitudinal and the sixth lateral modes. These two modes were matched through the preload adjustment and precisely tuned by the frequency matching method based on the impedance matching method with consideration of the different moving weights. The XY stage was evaluated in terms of position and circular motion. To achieve both fine and stable motion, the controller consisted of a nominal characteristics trajectory following (NCTF) control for continuous motion, dead zone compensation, and a switching controller based on the different NCTFs for the macro- and micro-dynamics regimes. The experimental results showed that the developed stage enables positioning and continuous motion with nanometer-level accuracy.

  1. COMBINED DELAY AND GRAPH EMBEDDING OF EPILEPTIC DISCHARGES IN EEG REVEALS COMPLEX AND RECURRENT NONLINEAR DYNAMICS

    PubMed Central

    Erem, B.; Hyde, D.E.; Peters, J.M.; Duffy, F.H.; Brooks, D.H.; Warfield, S.K.

    2015-01-01

    The dynamical structure of the brain’s electrical signals contains valuable information about its physiology. Here we combine techniques for nonlinear dynamical analysis and manifold identification to reveal complex and recurrent dynamics in interictal epileptiform discharges (IEDs). Our results suggest that recurrent IEDs exhibit some consistent dynamics, which may only last briefly, and so individual IED dynamics may need to be considered in order to understand their genesis. This could potentially serve to constrain the dynamics of the inverse source localization problem. PMID:26366250

  2. Comparison of reflection boundary conditions for langevin equation modeling of convective boundary layer dispersion

    SciTech Connect

    Nasstrom, J.S.; Ermak, D.L.

    1997-04-01

    Lagrangian stochastic modeling based on the Langevin equation has been shown to be useful for simulating vertical dispersion of trace material in the convective boundary layer or CBL. This modeling approach can account for the effects of the long velocity correlation time scales, skewed vertical velocity distributions, and vertically inhomogeneous turbulent properties found in the CBL. It has been recognized that Langevin equation models assuming skewed but homogenous velocity statistics can capture the important aspects of diffusion from sources in the CBL, especially elevated sources. We compare three reflection boundary conditions using two different Langevin-equation-based numerical models for vertical dispersion in skewed, homogeneous turbulence. One model, described by Ermak and Nasstrom (1995) is based on a Langevin equation with a skewed random force and a linear deterministic force. The second model, used by Hurley and Physick (1993) is based on a Langevin equation with a Gaussian random force and a non-linear deterministic force. The reflection boundary conditions are all based on the approach described by Thompson and Montgomery (1994).

  3. Identifying dynamic protein complexes based on gene expression profiles and PPI networks.

    PubMed

    Li, Min; Chen, Weijie; Wang, Jianxin; Wu, Fang-Xiang; Pan, Yi

    2014-01-01

    Identification of protein complexes from protein-protein interaction networks has become a key problem for understanding cellular life in postgenomic era. Many computational methods have been proposed for identifying protein complexes. Up to now, the existing computational methods are mostly applied on static PPI networks. However, proteins and their interactions are dynamic in reality. Identifying dynamic protein complexes is more meaningful and challenging. In this paper, a novel algorithm, named DPC, is proposed to identify dynamic protein complexes by integrating PPI data and gene expression profiles. According to Core-Attachment assumption, these proteins which are always active in the molecular cycle are regarded as core proteins. The protein-complex cores are identified from these always active proteins by detecting dense subgraphs. Final protein complexes are extended from the protein-complex cores by adding attachments based on a topological character of "closeness" and dynamic meaning. The protein complexes produced by our algorithm DPC contain two parts: static core expressed in all the molecular cycle and dynamic attachments short-lived. The proposed algorithm DPC was applied on the data of Saccharomyces cerevisiae and the experimental results show that DPC outperforms CMC, MCL, SPICi, HC-PIN, COACH, and Core-Attachment based on the validation of matching with known complexes and hF-measures. PMID:24963481

  4. Structural dynamics in complex liquids studied with multidimensional vibrational spectroscopy

    SciTech Connect

    Tokmakoff, Andrei

    2013-08-31

    The development of new sustainable energy sources is linked to our understanding of the molecular properties of water and aqueous solutions. Energy conversion, storage, and transduction processes, particularly those that occur in biology, fuel cells, and batteries, make use of water for the purpose of moving energy in the form of charges and mediating the redox chemistry that allows this energy to be stored as and released from chemical bonds. To build our fundamental knowledge in this area, this project supports work in the Tokmakoff group to investigate the molecular dynamics of water’s hydrogen bond network, and how these dynamics influence its solutes and the mechanism of proton transport in water. To reach the goals of this grant, we developed experiments to observe molecular dynamics in water as directly as possible, using ultrafast multidimensional vibrational spectroscopy. We excite and probe broad vibrational resonances of water, molecular solutes, and protons in water. By correlating how molecules evolve from an initial excitation frequency to a final frequency, we can describe the underlying molecular dynamics. Theoretical modeling of the data with the help of computational spectroscopy coupled with molecular dynamics simulations provided the atomistic insight in these studies.

  5. The Influence of Information Acquisition on the Complex Dynamics of Market Competition

    NASA Astrophysics Data System (ADS)

    Guo, Zhanbing; Ma, Junhai

    In this paper, we build a dynamical game model with three bounded rational players (firms) to study the influence of information on the complex dynamics of market competition, where useful information is about rival’s real decision. In this dynamical game model, one information-sharing team is composed of two firms, they acquire and share the information about their common competitor, however, they make their own decisions separately, where the amount of information acquired by this information-sharing team will determine the estimation accuracy about the rival’s real decision. Based on this dynamical game model and some creative 3D diagrams, the influence of the amount of information on the complex dynamics of market competition such as local dynamics, global dynamics and profits is studied. These results have significant theoretical and practical values to realize the influence of information.

  6. Detecting protein complexes from active protein interaction networks constructed with dynamic gene expression profiles

    PubMed Central

    2013-01-01

    Background Protein interaction networks (PINs) are known to be useful to detect protein complexes. However, most available PINs are static, which cannot reflect the dynamic changes in real networks. At present, some researchers have tried to construct dynamic networks by incorporating time-course (dynamic) gene expression data with PINs. However, the inevitable background noise exists in the gene expression array, which could degrade the quality of dynamic networkds. Therefore, it is needed to filter out contaminated gene expression data before further data integration and analysis. Results Firstly, we adopt a dynamic model-based method to filter noisy data from dynamic expression profiles. Then a new method is proposed for identifying active proteins from dynamic gene expression profiles. An active protein at a time point is defined as the protein the expression level of whose corresponding gene at that time point is higher than a threshold determined by a standard variance involved threshold function. Furthermore, a noise-filtered active protein interaction network (NF-APIN) is constructed. To demonstrate the efficiency of our method, we detect protein complexes from the NF-APIN, compared with those from other dynamic PINs. Conclusion A dynamic model based method can effectively filter out noises in dynamic gene expression data. Our method to compute a threshold for determining the active time points of noise-filtered genes can make the dynamic construction more accuracy and provide a high quality framework for network analysis, such as protein complex prediction. PMID:24565281

  7. Asymmetrically interacting spreading dynamics on complex layered networks

    PubMed Central

    Wang, Wei; Tang, Ming; Yang, Hui; Younghae Do; Lai, Ying-Cheng; Lee, GyuWon

    2014-01-01

    The spread of disease through a physical-contact network and the spread of information about the disease on a communication network are two intimately related dynamical processes. We investigate the asymmetrical interplay between the two types of spreading dynamics, each occurring on its own layer, by focusing on the two fundamental quantities underlying any spreading process: epidemic threshold and the final infection ratio. We find that an epidemic outbreak on the contact layer can induce an outbreak on the communication layer, and information spreading can effectively raise the epidemic threshold. When structural correlation exists between the two layers, the information threshold remains unchanged but the epidemic threshold can be enhanced, making the contact layer more resilient to epidemic outbreak. We develop a physical theory to understand the intricate interplay between the two types of spreading dynamics. PMID:24872257

  8. Complex dynamics of the biological rhythms: gallbladder and heart cases

    NASA Astrophysics Data System (ADS)

    Imponente, Giovanni

    2004-07-01

    A theoretical analysis of the mechanisms underlying the dynamics of gallbladder and heart pulsation could clarify the question regarding the classification as chaotic of the associated behaviour, eventually related to a normal and healthy beat; this analysis is particularly relevant in view of the control of dynamic bifurcations arising in situations of disease. In this work a summary of the DFA method applied to gallbladder volume data for a modest number of healthy and ill patients is presented: the presence of signal correlation is found in both cases, but the fit shapes differ from some critical values.

  9. Conformally related Einstein-Langevin equations for metric fluctuations in stochastic gravity

    NASA Astrophysics Data System (ADS)

    Satin, Seema; Cho, H. T.; Hu, Bei Lok

    2016-09-01

    For a conformally coupled scalar field we obtain the conformally related Einstein-Langevin equations, using appropriate transformations for all the quantities in the equations between two conformally related spacetimes. In particular, we analyze the transformations of the influence action, the stress energy tensor, the noise kernel and the dissipation kernel. In due course the fluctuation-dissipation relation is also discussed. The analysis in this paper thereby facilitates a general solution to the Einstein-Langevin equation once the solution of the equation in a simpler, conformally related spacetime is known. For example, from the Minkowski solution of Martín and Verdaguer, those of the Einstein-Langevin equations in conformally flat spacetimes, especially for spatially flat Friedmann-Robertson-Walker models, can be readily obtained.

  10. Positive Affect and the Complex Dynamics of Human Flourishing

    ERIC Educational Resources Information Center

    Fredrickson, Barbara L.; Losada, Marcial F.

    2005-01-01

    Extending B. L. Fredrickson's (1998) broaden-and-build theory of positive emotions and M. Losada's (1999) nonlinear dynamics model of team performance, the authors predict that a ratio of positive to negative affect at or above 2.9 will characterize individuals in flourishing mental health. Participants (N=188) completed an initial survey to…

  11. Evolution and selection of river networks: statics, dynamics, and complexity.

    PubMed

    Rinaldo, Andrea; Rigon, Riccardo; Banavar, Jayanth R; Maritan, Amos; Rodriguez-Iturbe, Ignacio

    2014-02-18

    Moving from the exact result that drainage network configurations minimizing total energy dissipation are stationary solutions of the general equation describing landscape evolution, we review the static properties and the dynamic origins of the scale-invariant structure of optimal river patterns. Optimal channel networks (OCNs) are feasible optimal configurations of a spanning network mimicking landscape evolution and network selection through imperfect searches for dynamically accessible states. OCNs are spanning loopless configurations, however, only under precise physical requirements that arise under the constraints imposed by river dynamics--every spanning tree is exactly a local minimum of total energy dissipation. It is remarkable that dynamically accessible configurations, the local optima, stabilize into diverse metastable forms that are nevertheless characterized by universal statistical features. Such universal features explain very well the statistics of, and the linkages among, the scaling features measured for fluvial landforms across a broad range of scales regardless of geology, exposed lithology, vegetation, or climate, and differ significantly from those of the ground state, known exactly. Results are provided on the emergence of criticality through adaptative evolution and on the yet-unexplored range of applications of the OCN concept. PMID:24550264

  12. Unraveling the complexity of mitochondrial complex I assembly: A dynamic process.

    PubMed

    Sánchez-Caballero, Laura; Guerrero-Castillo, Sergio; Nijtmans, Leo

    2016-07-01

    Mammalian complex I is composed of 44 different subunits and its assembly requires at least 13 specific assembly factors. Proper function of the mitochondrial respiratory chain enzyme is of crucial importance for cell survival due to its major participation in energy production and cell signaling. Complex I assembly depends on the coordination of several crucial processes that need to be tightly interconnected and orchestrated by a number of assembly factors. The understanding of complex I assembly evolved from simple sequential concept to the more sophisticated modular assembly model describing a convoluted process. According to this model, the different modules assemble independently and associate afterwards with each other to form the final enzyme. In this review, we aim to unravel the complexity of complex I assembly and provide the latest insights in this fundamental and fascinating process. This article is part of a Special Issue entitled Respiratory complex I, edited by Volker Zickermann and Ulrich Brandt.

  13. A dynamic [1]catenane with pH-responsiveness formed via threading-followed-by-complexation.

    PubMed

    Yan, Xuzhou; Wei, Peifa; Li, Zhengtao; Zheng, Bo; Dong, Shengyi; Huang, Feihe; Zhou, Qizhong

    2013-03-28

    Driven by orthogonal pillar[5]arene-based and crown ether-based molecular recognitions, a dynamic [1]catenane with pH-responsiveness was constructed via threading-followed-by-complexation. PMID:23423220

  14. Cationic Dihydrogen/Dihydride Complexes of Osmium: Structure and Dynamics

    SciTech Connect

    Egbert, Jonathan D.; Bullock, R. Morris; Heinekey, D. M.

    2007-03-22

    Reaction of Cp*Os(CO)2Cl with (Et3Si )(BArF4) under hydrogen gas affords the cationic hydrogen complex [Cp*Os(CO)2(H2)][BArF4] (1), (Cp* = C5Me5; ArF = C6F5). When this reaction is carried out with HD gas, complex 1-d1 results, with JHD = 24.5 Hz. When solutions of complex 1 are monitored by 1H NMR spectroscopy over several days, the gradual formation of a trans dihydride species is observed. Similarly, reaction of CpOs(dppm)Br with NaBArF*4 (ArF* = 3,5-(CF3)2C6H3) under hydrogen affords the cationic dihydride complex [CpOs(dppm)H2]BArF*4 (2). At 295 K, complex 2 exists as a 10:1 mixture of cis and trans isomers. The 1H NMR spectrum of the cis form in the hydride region exhibits a triplet with JHP = 6.5 Hz, due to rapid exchange of the hydrogen atoms. At low temperature, static spectra of the HH'PP' spin system can be obtained, revealing quantum mechanical exchange coupling between the two hydride ligands. The observed JHH' is temperature dependent, varying from 133 Hz at 141 K to 176 Hz at 198 K. This is the first report of detectable exchange coupling between pairs of chemically equivalent hydrogen atoms. Research at the University of Washington was supported by the National Science Foundation. Research at Brookhaven National Laboratory was carried out under contract DE-AC02-98CH10886 with the U.S. Department of Energy and was supported by its Division of Chemical Sciences, Office of Basic Energy Sciences. Research at Pacific Northwest National Laboratory (PNNL) was funded by LDRD funds. PNNL is operated by Battelle for the US Department of Energy.

  15. Thermodynamic aspects of information transfer in complex dynamical systems.

    PubMed

    Cafaro, Carlo; Ali, Sean Alan; Giffin, Adom

    2016-02-01

    From the Horowitz-Esposito stochastic thermodynamical description of information flows in dynamical systems [J. M. Horowitz and M. Esposito, Phys. Rev. X 4, 031015 (2014)], it is known that while the second law of thermodynamics is satisfied by a joint system, the entropic balance for the subsystems is adjusted by a term related to the mutual information exchange rate between the two subsystems. In this article, we present a quantitative discussion of the conceptual link between the Horowitz-Esposito analysis and the Liang-Kleeman work on information transfer between dynamical system components [X. S. Liang and R. Kleeman, Phys. Rev. Lett. 95, 244101 (2005)]. In particular, the entropic balance arguments employed in the two approaches are compared. Notwithstanding all differences between the two formalisms, our work strengthens the Liang-Kleeman heuristic balance reasoning by showing its formal analogy with the recent Horowitz-Esposito thermodynamic balance arguments. PMID:26986295

  16. Complex brain networks: From topological communities to clustered dynamics

    NASA Astrophysics Data System (ADS)

    Zemanova, Lucia; Zamora-Lopez, Gorka; Zhou, Changsong; Kurths, Jurgen

    2008-06-01

    Recent research has revealed a rich and complicated network topology in the cortical connectivity of mammalian brains. A challenging task is to understand the implications of such network structures on the functional organisation of the brain activities. We investigate synchronisation dynamics on the corticocortical network of the cat by modelling each node of the network (cortical area) with a subnetwork of interacting excitable neurons. We find that this network of networks displays clustered synchronisation behaviour and the dynamical clusters closely coincide with the topological community structures observed in the anatomical network. The correlation between the firing rate of the areas and the areal intensity is additionally examined. Our results provide insights into the relationship between the global organisation and the functional specialisation of the brain cortex.

  17. RG-Whitham dynamics and complex Hamiltonian systems

    NASA Astrophysics Data System (ADS)

    Gorsky, A.; Milekhin, A.

    2015-06-01

    Inspired by the Seiberg-Witten exact solution, we consider some aspects of the Hamiltonian dynamics with the complexified phase space focusing at the renormalization group (RG)-like Whitham behavior. We show that at the Argyres-Douglas (AD) point the number of degrees of freedom in Hamiltonian system effectively reduces and argue that anomalous dimensions at AD point coincide with the Berry indexes in classical mechanics. In the framework of Whitham dynamics AD point turns out to be a fixed point. We demonstrate that recently discovered Dunne-Ünsal relation in quantum mechanics relevant for the exact quantization condition exactly coincides with the Whitham equation of motion in the Ω-deformed theory.

  18. Dynamical symmetries in Kondo tunneling through complex quantum dots.

    PubMed

    Kuzmenko, T; Kikoin, K; Avishai, Y

    2002-10-01

    Kondo tunneling reveals hidden SO(n) dynamical symmetries of evenly occupied quantum dots. As is exemplified for an experimentally realizable triple quantum dot in parallel geometry, the possible values n=3,4,5,7 can be easily tuned by gate voltages. Following construction of the corresponding o(n) algebras, scaling equations are derived and Kondo temperatures are calculated. The symmetry group for a magnetic field induced anisotropic Kondo tunneling is SU(2) or SO(4).

  19. Efficient modelling of droplet dynamics on complex surfaces.

    PubMed

    Karapetsas, George; Chamakos, Nikolaos T; Papathanasiou, Athanasios G

    2016-03-01

    This work investigates the dynamics of droplet interaction with smooth or structured solid surfaces using a novel sharp-interface scheme which allows the efficient modelling of multiple dynamic contact lines. The liquid-gas and liquid-solid interfaces are treated in a unified context and the dynamic contact angle emerges simply due to the combined action of the disjoining and capillary pressure, and viscous stresses without the need of an explicit boundary condition or any requirement for the predefinition of the number and position of the contact lines. The latter, as it is shown, renders the model able to handle interfacial flows with topological changes, e.g. in the case of an impinging droplet on a structured surface. Then it is possible to predict, depending on the impact velocity, whether the droplet will fully or partially impregnate the structures of the solid, or will result in a 'fakir', i.e. suspended, state. In the case of a droplet sliding on an inclined substrate, we also demonstrate the built-in capability of our model to provide a prediction for either static or dynamic contact angle hysteresis. We focus our study on hydrophobic surfaces and examine the effect of the geometrical characteristics of the solid surface. It is shown that the presence of air inclusions trapped in the micro-structure of a hydrophobic substrate (Cassie-Baxter state) result in the decrease of contact angle hysteresis and in the increase of the droplet migration velocity in agreement with experimental observations for super-hydrophobic surfaces. Moreover, we perform 3D simulations which are in line with the 2D ones regarding the droplet mobility and also indicate that the contact angle hysteresis may be significantly affected by the directionality of the structures with respect to the droplet motion. PMID:26828706

  20. Diffusion of Single layer Clusters: Langevin Analysis and Monte Carlo Simulations^*

    NASA Astrophysics Data System (ADS)

    Khare, S. V.

    1996-03-01

    In recent observations of Brownian motion of islands of adsorbed atoms and of vacancies with mean radius R, the cluster diffusion constant Dc is found to vary as R-1 and R-2 in studies by Wen et al. ( J. M. Wen, S. -L. Chang, J. W. Burnett, J. W. Evans and P. A. Thiel, Phys. Rev. Lett. 73), 2591 (1994). and Morgenstern et al. (K. Morgenstern, G. Rosenfeld, B. Poelsema, and G. Comsa, Phys. Rev. Lett. 74), 2058 (1995)., repectively. From an analytical continuum description of the cluster's step-like boundary, we find a single Langevin equation for the motion of the cluster boundary. From this we determine the cluster diffusion constant and the fluctuations of the shape around an assumed equilibrium circular shape. In three limiting cases this leads to the scaling of the diffusion constant with the radius as Dc ~ R^-α and the scaling of a shape fluctuations correlation function with the elapsed time as t^1/(1+α ). These three cases correspond to the three microscopic surface mass-transport mechanisms of straight steps, namely: evaporation condensation (EC) giving α=1, terrace diffusion (TD) implying α=2 and periphery diffusion (PD) yielding α = 3. We thereby provide a unified treatment of the dynamics of steps and of clusters ( S. V. Khare, N. C. Bartelt, and T. L. Einstein, Phys. Rev. Lett. 75), 2148 (1995); in preparation.. To check how well the continuum results apply to real systems with finite lattice constants, we perform Monte Carlo simulations of simple lattice gas models for these three cases. We also relate the the experimentally measured diffusion coefficients of the clusters to atomic diffusion parameters. ^* This work was done in collaboration with N. C. Bartelt and T. L. Einstein and was supported in part by NSF DMR-MRG 91-03031.

  1. Evolution and selection of river networks: Statics, dynamics, and complexity

    PubMed Central

    Rinaldo, Andrea; Rigon, Riccardo; Banavar, Jayanth R.; Maritan, Amos; Rodriguez-Iturbe, Ignacio

    2014-01-01

    Moving from the exact result that drainage network configurations minimizing total energy dissipation are stationary solutions of the general equation describing landscape evolution, we review the static properties and the dynamic origins of the scale-invariant structure of optimal river patterns. Optimal channel networks (OCNs) are feasible optimal configurations of a spanning network mimicking landscape evolution and network selection through imperfect searches for dynamically accessible states. OCNs are spanning loopless configurations, however, only under precise physical requirements that arise under the constraints imposed by river dynamics—every spanning tree is exactly a local minimum of total energy dissipation. It is remarkable that dynamically accessible configurations, the local optima, stabilize into diverse metastable forms that are nevertheless characterized by universal statistical features. Such universal features explain very well the statistics of, and the linkages among, the scaling features measured for fluvial landforms across a broad range of scales regardless of geology, exposed lithology, vegetation, or climate, and differ significantly from those of the ground state, known exactly. Results are provided on the emergence of criticality through adaptative evolution and on the yet-unexplored range of applications of the OCN concept. PMID:24550264

  2. Cellular automata and complex dynamics of driven elastic media

    SciTech Connect

    Coppersmith, S.N.; Littlewodd, P.B.; Sibani, P.

    1995-12-01

    Several systems of importance in condensed matter physics can be modelled as an elastic medium in a disordered environment and driven by an external force. In the simplest cases, the equation of motion involves competition between a local non-linear potential (fluctuating in space) and elastic coupling, as well as relaxational (inertialess) dynamics. Despite a simple mathematical description, the interactions between many degrees of freedom lead to the emergence of time and length scales much longer than those set by the microscopic dynamics. Extensive computations have improved the understanding of the behavior of such models, but full solutions of the equations of motion for very large systems are time-consuming and may obscure important physical principles in a massive volume of output. The development of cellular automata models has been crucial, both in conceptual simplification and in allowing the collection of data on many replicas of very large systems. We will discuss how the marriage of cellular automata models and parallel computation on a MasPar MP-1216 computer has helped to elucidate the dynamical properties of these many-degree-of-freedom systems.

  3. Networks as complex dynamic systems: applications to clinical and developmental psychology and psychopathology.

    PubMed

    van Geert, Paul L C; Steenbeek, Henderien W

    2010-06-01

    Cramer et al.'s article is an example of the fruitful application of complex dynamic systems theory. We extend their approach with examples from our own work on development and developmental psychopathology and address three issues: (1) the level of aggregation of the network, (2) the required research methodology, and (3) the clinical and educational application of dynamic network thinking.

  4. Plenary Speech: Researching Complex Dynamic Systems--"Retrodictive Qualitative Modelling" in the Language Classroom

    ERIC Educational Resources Information Center

    Dörnyei, Zoltán

    2014-01-01

    While approaching second language acquisition from a complex dynamic systems perspective makes a lot of intuitive sense, it is difficult for a number of reasons to operationalise such a dynamic approach in research terms. For example, the most common research paradigms in the social sciences tend to examine variables in relative isolation rather…

  5. High Dynamic Range Complex Impedance Measurement System for Petrophysical Usage

    NASA Astrophysics Data System (ADS)

    Chen, R.; He, X.; Yao, H.; Tan, S.; Shi, H.; Shen, R.; Yan, C.; Zeng, P.; He, L.; Qiao, N.; Xi, F.; Zhang, H.; Xie, J.

    2015-12-01

    Spectral induced polarization method (SIP) or complex resistivity method is increasing its application in metalliferous ore exploration, hydrocarbon exploration, underground water exploration, monitoring of environment pollution, and the evaluation of environment remediation. And the measurement of complex resistivity or complex impedance of rock/ore sample and polluted water plays a fundamental role in improving the application effect of SIP and the application scope of SIP. However, current instruments can't guaranty the accuracy of measurement when the resistance of sample is less than 10Ω or great than 100kΩ. A lot of samples, such as liquid, polluted sea water, igneous rock, limestone, and sandstone, can't be measured with reliable complex resistivity result. Therefore, this problem projects a shadow in the basic research and application research of SIP. We design a high precision measurement system from the study of measurement principle, sample holder, and measurement instrument. We design input buffers in a single board. We adopt operation amplifier AD549 in this system because of its ultra-high input impedance and ultra-low current noise. This buffer is good in acquiring potential signal across high impedance sample. By analyzing the sources of measurement error and errors generated by the measurement system, we propose a correction method to remove the error in order to achieve high quality complex impedance measurement for rock and ore samples. This measurement system can improve the measurement range of the complex impedance to 0.1 Ω ~ 10 GΩ with amplitude error less than 0.1% and phase error less than 0.1mrad when frequency ranges as 0.01 Hz ~ 1 kHz. We tested our system on resistors with resistance as 0.1Ω ~ 10 GΩ in frequency range as 1 Hz ~ 1000 Hz, and the measurement error is less than 0.1 mrad. We also compared the result with LCR bridge and SCIP, we can find that the bridge's measuring range only reaches 100 MΩ, SCIP's measuring range

  6. Excited state dynamics and isomerization in ruthenium sulfoxide complexes.

    PubMed

    King, Albert W; Wang, Lei; Rack, Jeffrey J

    2015-04-21

    Molecular photochromic compounds are those that interconvert between two isomeric forms with light. The two isomeric forms display distinct electronic and molecular structures and must not be in equilibrium with one another. These light-activated molecular switch compounds have found wide application in areas of study ranging from chemical biology to materials science, where conversion from one isomeric form to another by light prompts a response in the environment (e.g., protein or polymeric material). Certain ruthenium and osmium polypyridine sulfoxide complexes are photochromic. The mode of action is a phototriggered isomerization of the sulfoxide from S- to O-bonded. The change in ligation drastically alters both the spectroscopic and electrochemical properties of the metal complex. Our laboratory has pioneered the preparation and study of these complexes. In particular, we have applied femtosecond pump-probe spectroscopy to reveal excited state details of the isomerization mechanism. The data from numerous complexes allowed us to predict that the isomerization was nonadiabatic in nature, defined as occurring from a S-bonded triplet excited state (primarily metal-to-ligand charge transfer in character) to an O-bonded singlet ground state potential energy surface. This prediction was corroborated by high-level density functional theory calculations. An intriguing aspect of this reactivity is the coupling of nuclear motion to the electronic wave function and how this coupling affects motions productive for isomerization. In an effort to learn more about this coupling, we designed a project to examine phototriggered isomerization in bis-sulfoxide complexes. The goal of these studies was to determine whether certain complexes could be designed in which a single photon excitation event would prompt two sulfoxide isomerizations. We employed chelating sulfoxides in this study and found that both the nature of the chelate ring and the R group on the sulfoxide affect

  7. Dynamics of Social Complex Networks: Some Insights into Recent Research

    NASA Astrophysics Data System (ADS)

    Lozano, Sergi

    Social networks analysis (that is, the study of interactions among social actors from a structural viewpoint) has a long tradition covering several decades [1, 2, 3]. This sort of study has usually been performed over small social networks, and the limitation of size has conditioned the visibility of complexity [4, 5]. However, the situation has changed significantly in recent times due to basically two reasons. First, there is an increasing availability of larger social datasets (obtained in most cases from information and communication technologies). Secondly, a large number of physicists and other scholars from complexity science have started to take active interest in the field. New perspectives and tools have been provided by these ‘newcomers’, which in combination with the expertise and knowledge accumulated by ‘classical’ social network analysts, has formed the basis of a multidisciplinary field suitably termed the science of networks [6, 7].

  8. Dynamics and recognition within a protein–DNA complex: a molecular dynamics study of the SKN-1/DNA interaction

    PubMed Central

    Etheve, Loïc; Martin, Juliette; Lavery, Richard

    2016-01-01

    Molecular dynamics simulations of the Caenorhabditis elegans transcription factor SKN-1 bound to its cognate DNA site show that the protein–DNA interface undergoes significant dynamics on the microsecond timescale. A detailed analysis of the simulation shows that movements of two key arginine side chains between the major groove and the backbone of DNA generate distinct conformational sub-states that each recognize only part of the consensus binding sequence of SKN-1, while the experimentally observed binding specificity results from a time-averaged view of the dynamic recognition occurring within this complex. PMID:26721385

  9. Quantum theory of open systems based on stochastic differential equations of generalized Langevin (non-Wiener) type

    NASA Astrophysics Data System (ADS)

    Basharov, A. M.

    2012-09-01

    It is shown that the effective Hamiltonian representation, as it is formulated in author's papers, serves as a basis for distinguishing, in a broadband environment of an open quantum system, independent noise sources that determine, in terms of the stationary quantum Wiener and Poisson processes in the Markov approximation, the effective Hamiltonian and the equation for the evolution operator of the open system and its environment. General stochastic differential equations of generalized Langevin (non-Wiener) type for the evolution operator and the kinetic equation for the density matrix of an open system are obtained, which allow one to analyze the dynamics of a wide class of localized open systems in the Markov approximation. The main distinctive features of the dynamics of open quantum systems described in this way are the stabilization of excited states with respect to collective processes and an additional frequency shift of the spectrum of the open system. As an illustration of the general approach developed, the photon dynamics in a single-mode cavity without losses on the mirrors is considered, which contains identical intracavity atoms coupled to the external vacuum electromagnetic field. For some atomic densities, the photons of the cavity mode are "locked" inside the cavity, thus exhibiting a new phenomenon of radiation trapping and non-Wiener dynamics.

  10. Approximate method for stochastic chemical kinetics with two-time scales by chemical Langevin equations.

    PubMed

    Wu, Fuke; Tian, Tianhai; Rawlings, James B; Yin, George

    2016-05-01

    The frequently used reduction technique is based on the chemical master equation for stochastic chemical kinetics with two-time scales, which yields the modified stochastic simulation algorithm (SSA). For the chemical reaction processes involving a large number of molecular species and reactions, the collection of slow reactions may still include a large number of molecular species and reactions. Consequently, the SSA is still computationally expensive. Because the chemical Langevin equations (CLEs) can effectively work for a large number of molecular species and reactions, this paper develops a reduction method based on the CLE by the stochastic averaging principle developed in the work of Khasminskii and Yin [SIAM J. Appl. Math. 56, 1766-1793 (1996); ibid. 56, 1794-1819 (1996)] to average out the fast-reacting variables. This reduction method leads to a limit averaging system, which is an approximation of the slow reactions. Because in the stochastic chemical kinetics, the CLE is seen as the approximation of the SSA, the limit averaging system can be treated as the approximation of the slow reactions. As an application, we examine the reduction of computation complexity for the gene regulatory networks with two-time scales driven by intrinsic noise. For linear and nonlinear protein production functions, the simulations show that the sample average (expectation) of the limit averaging system is close to that of the slow-reaction process based on the SSA. It demonstrates that the limit averaging system is an efficient approximation of the slow-reaction process in the sense of the weak convergence. PMID:27155630

  11. Approximate method for stochastic chemical kinetics with two-time scales by chemical Langevin equations.

    PubMed

    Wu, Fuke; Tian, Tianhai; Rawlings, James B; Yin, George

    2016-05-01

    The frequently used reduction technique is based on the chemical master equation for stochastic chemical kinetics with two-time scales, which yields the modified stochastic simulation algorithm (SSA). For the chemical reaction processes involving a large number of molecular species and reactions, the collection of slow reactions may still include a large number of molecular species and reactions. Consequently, the SSA is still computationally expensive. Because the chemical Langevin equations (CLEs) can effectively work for a large number of molecular species and reactions, this paper develops a reduction method based on the CLE by the stochastic averaging principle developed in the work of Khasminskii and Yin [SIAM J. Appl. Math. 56, 1766-1793 (1996); ibid. 56, 1794-1819 (1996)] to average out the fast-reacting variables. This reduction method leads to a limit averaging system, which is an approximation of the slow reactions. Because in the stochastic chemical kinetics, the CLE is seen as the approximation of the SSA, the limit averaging system can be treated as the approximation of the slow reactions. As an application, we examine the reduction of computation complexity for the gene regulatory networks with two-time scales driven by intrinsic noise. For linear and nonlinear protein production functions, the simulations show that the sample average (expectation) of the limit averaging system is close to that of the slow-reaction process based on the SSA. It demonstrates that the limit averaging system is an efficient approximation of the slow-reaction process in the sense of the weak convergence.

  12. Approximate method for stochastic chemical kinetics with two-time scales by chemical Langevin equations

    NASA Astrophysics Data System (ADS)

    Wu, Fuke; Tian, Tianhai; Rawlings, James B.; Yin, George

    2016-05-01

    The frequently used reduction technique is based on the chemical master equation for stochastic chemical kinetics with two-time scales, which yields the modified stochastic simulation algorithm (SSA). For the chemical reaction processes involving a large number of molecular species and reactions, the collection of slow reactions may still include a large number of molecular species and reactions. Consequently, the SSA is still computationally expensive. Because the chemical Langevin equations (CLEs) can effectively work for a large number of molecular species and reactions, this paper develops a reduction method based on the CLE by the stochastic averaging principle developed in the work of Khasminskii and Yin [SIAM J. Appl. Math. 56, 1766-1793 (1996); ibid. 56, 1794-1819 (1996)] to average out the fast-reacting variables. This reduction method leads to a limit averaging system, which is an approximation of the slow reactions. Because in the stochastic chemical kinetics, the CLE is seen as the approximation of the SSA, the limit averaging system can be treated as the approximation of the slow reactions. As an application, we examine the reduction of computation complexity for the gene regulatory networks with two-time scales driven by intrinsic noise. For linear and nonlinear protein production functions, the simulations show that the sample average (expectation) of the limit averaging system is close to that of the slow-reaction process based on the SSA. It demonstrates that the limit averaging system is an efficient approximation of the slow-reaction process in the sense of the weak convergence.

  13. The Graph Laplacian and the Dynamics of Complex Networks

    SciTech Connect

    Thulasidasan, Sunil

    2012-06-11

    In this talk, we explore the structure of networks from a spectral graph-theoretic perspective by analyzing the properties of the Laplacian matrix associated with the graph induced by a network. We will see how the eigenvalues of the graph Laplacian relate to the underlying network structure and dynamics and provides insight into a phenomenon frequently observed in real world networks - the emergence of collective behavior from purely local interactions seen in the coordinated motion of animals and phase transitions in biological networks, to name a few.

  14. Control of Complex Dynamic Systems by Neural Networks

    NASA Technical Reports Server (NTRS)

    Spall, James C.; Cristion, John A.

    1993-01-01

    This paper considers the use of neural networks (NN's) in controlling a nonlinear, stochastic system with unknown process equations. The NN is used to model the resulting unknown control law. The approach here is based on using the output error of the system to train the NN controller without the need to construct a separate model (NN or other type) for the unknown process dynamics. To implement such a direct adaptive control approach, it is required that connection weights in the NN be estimated while the system is being controlled. As a result of the feedback of the unknown process dynamics, however, it is not possible to determine the gradient of the loss function for use in standard (back-propagation-type) weight estimation algorithms. Therefore, this paper considers the use of a new stochastic approximation algorithm for this weight estimation, which is based on a 'simultaneous perturbation' gradient approximation that only requires the system output error. It is shown that this algorithm can greatly enhance the efficiency over more standard stochastic approximation algorithms based on finite-difference gradient approximations.

  15. Safety assessment document for the dynamic test complex (Building 836)

    SciTech Connect

    Odell, B.N.; Pfeifer, H.E.

    1981-11-24

    A safety assessment was performed to determine if potential accidents at the 836 Complex at Site 300 could present undue hazards to the general public, personnel at Site 300, or have an adverse effect on the environment. The credible accidents that might have an effect on these facilities or have off-site consequences were considered. These were earthquake, extreme wind (including missiles), lightning, flood, criticality, high explosive (H) detonation that disperses uranium and beryllium, spontaneous oxidation of plutonium, explosions due to finely divided particles, and a fire.

  16. Two-Proton Phototautomerization Dynamics of 7-AZAINDOLE Complexes

    NASA Astrophysics Data System (ADS)

    Chakraborty, T.; Mukherjee, M.; Karmakar, S.

    2013-06-01

    Light-induced tautomerization of 7-azaindole in doubly hydrogen-bonded dimeric complexes is one of the extensively investigated photoisomerization processes in recent years. The reaction, in the case of homodimer, takes place with equal ease in non-polar liquids at room temperature as well as in a cold supersonic jet expansion. A lot of studies were devoted arguing whether the double proton transfer occurs sequentially or in a concerted manner. Over the past three decades it has been assumed, on the basis of the observations of some low-temperature photophysical measurements, the double proton exchange barrier of the dimer is ˜ 2 kcal/mol. However, we notice that such measurements are flawed by artifact; the apparent barrier depends on sample concentration in the solutions. The tautomerization of the isolated dimer is found stopped at 10 K in an argon matrix, and we propose that the double proton exchange is coupled with the large amplitude hydrogen bond vibrations. Furthermore, the process in several 1:1 complexes of the molecule with pyrazole and amides displays remarkable contrasts with that of the homodimer. While the tautomerization in the former cases occurs extremely efficiently in hydrocarbon solutions, is hindered fully in supersonic jet expansion condition.The observations also imply that the effective barrier of phototautomerization in the 1:1 complexes is intimately correlated with the details of double proton transfer mechanism. The details of our findings along with the predictions of some electronic structure calculations will be presented in the talk. References: ``Ultraviolet and infrared spectroscopy of matrix-isolated 7-azaindole dimer: Matrix effect on excited state tautomerization", M. Mukherjee, B. Bandyopadhyay and T. Chakraborty, Chem. Phys. Lett. 546, 74-79 (2012). ``Excited State Tautomerization of 7-Azaindole in a 1:1 Complex with δ-Valerolactam: A Comparative Study with the Homodimer", M. Mukherjee, S. Karmakar and T. Chakraborty, J

  17. A complex systems analysis of stick-slip dynamics of a laboratory fault.

    PubMed

    Walker, David M; Tordesillas, Antoinette; Small, Michael; Behringer, Robert P; Tse, Chi K

    2014-03-01

    We study the stick-slip behavior of a granular bed of photoelastic disks sheared by a rough slider pulled along the surface. Time series of a proxy for granular friction are examined using complex systems methods to characterize the observed stick-slip dynamics of this laboratory fault. Nonlinear surrogate time series methods show that the stick-slip behavior appears more complex than a periodic dynamics description. Phase space embedding methods show that the dynamics can be locally captured within a four to six dimensional subspace. These slider time series also provide an experimental test for recent complex network methods. Phase space networks, constructed by connecting nearby phase space points, proved useful in capturing the key features of the dynamics. In particular, network communities could be associated to slip events and the ranking of small network subgraphs exhibited a heretofore unreported ordering.

  18. Volterra representation enables modeling of complex synaptic nonlinear dynamics in large-scale simulations

    PubMed Central

    Hu, Eric Y.; Bouteiller, Jean-Marie C.; Song, Dong; Baudry, Michel; Berger, Theodore W.

    2015-01-01

    Chemical synapses are comprised of a wide collection of intricate signaling pathways involving complex dynamics. These mechanisms are often reduced to simple spikes or exponential representations in order to enable computer simulations at higher spatial levels of complexity. However, these representations cannot capture important nonlinear dynamics found in synaptic transmission. Here, we propose an input-output (IO) synapse model capable of generating complex nonlinear dynamics while maintaining low computational complexity. This IO synapse model is an extension of a detailed mechanistic glutamatergic synapse model capable of capturing the input-output relationships of the mechanistic model using the Volterra functional power series. We demonstrate that the IO synapse model is able to successfully track the nonlinear dynamics of the synapse up to the third order with high accuracy. We also evaluate the accuracy of the IO synapse model at different input frequencies and compared its performance with that of kinetic models in compartmental neuron models. Our results demonstrate that the IO synapse model is capable of efficiently replicating complex nonlinear dynamics that were represented in the original mechanistic model and provide a method to replicate complex and diverse synaptic transmission within neuron network simulations. PMID:26441622

  19. Dealing with the complex dynamics of teaching hospitals.

    PubMed

    van Rossum, Tiuri R; Scheele, Fedde; Scherpbier, Albert J J A; Sluiter, Henk E; Heyligers, Ide C

    2016-04-05

    Innovation and change in postgraduate medical education programs affects teaching hospital organizations, since medical education and clinical service are interrelated.Recent trends towards flexible, time-independent and individualized educational programs put pressure on this relationship. This pressure may lead to organizational uncertainty, unbalance and friction making it an important issue to analyze.The last decade was marked by a transition towards outcome-based postgraduate medical education. During this transition competency-based programs made their appearance. Although competency-based medical education has the potential to make medical education more efficient, the effects are still under debate. And while this debate continues, the field of medical education is already introducing next level innovations: flexible and individualized training programs. Major organizational change, like the transition to flexible education programs, can easily lead to friction and conflict in teaching hospital organizations.This article analyses the organizational impact of postgraduate medical education innovations, with a particular focus on flexible training and competency based medical education. The characteristics of teaching hospital organizations are compared with elements of innovation and complexity theory.With this comparison the article argues that teaching hospital organizations have complex characteristics and behave in a non-linear way. This perspective forms the basis for further discussion and analysis of this unexplored aspect of flexible and competency based education.

  20. Dealing with the complex dynamics of teaching hospitals.

    PubMed

    van Rossum, Tiuri R; Scheele, Fedde; Scherpbier, Albert J J A; Sluiter, Henk E; Heyligers, Ide C

    2016-01-01

    Innovation and change in postgraduate medical education programs affects teaching hospital organizations, since medical education and clinical service are interrelated.Recent trends towards flexible, time-independent and individualized educational programs put pressure on this relationship. This pressure may lead to organizational uncertainty, unbalance and friction making it an important issue to analyze.The last decade was marked by a transition towards outcome-based postgraduate medical education. During this transition competency-based programs made their appearance. Although competency-based medical education has the potential to make medical education more efficient, the effects are still under debate. And while this debate continues, the field of medical education is already introducing next level innovations: flexible and individualized training programs. Major organizational change, like the transition to flexible education programs, can easily lead to friction and conflict in teaching hospital organizations.This article analyses the organizational impact of postgraduate medical education innovations, with a particular focus on flexible training and competency based medical education. The characteristics of teaching hospital organizations are compared with elements of innovation and complexity theory.With this comparison the article argues that teaching hospital organizations have complex characteristics and behave in a non-linear way. This perspective forms the basis for further discussion and analysis of this unexplored aspect of flexible and competency based education. PMID:27048264

  1. Dynamic Regulation of AP-1 Transcriptional Complexes Directs Trophoblast Differentiation

    PubMed Central

    Kent, Lindsey N.; Rumi, M. A. Karim; Roby, Katherine F.

    2015-01-01

    Placentation is a process that establishes the maternal-fetal interface and is required for successful pregnancy. The epithelial component of the placenta consists of trophoblast cells, which possess the capacity for multilineage differentiation and are responsible for placenta-specific functions. FOS-like antigen 1 (FOSL1), a component of AP-1 transcription factor complexes, contributes to the regulation of placental development. FOSL1 expression is restricted to trophoblast giant cells and invasive trophoblast cells. In the present study, we characterized the FOSL1 regulatory pathway in rat trophoblast cells. Transcriptome profiling in control and FOSL1 knockdown cells identified FOSL1-dependent gene sets linked to endocrine and invasive functions. FOSL1 was shown to occupy AP-1 binding sites within these gene loci, as determined by chromatin immunoprecipitation (ChIP). Complementary in vivo experiments using trophoblast-specific lentiviral delivery of FOSL1 short hairpin RNAs (shRNAs) provided in vivo validation of FOSL1 targets. FOSL1 actions require a dimerization partner. Coimmunoprecipitation, coimmunolocalization, and ChIP analyses showed that FOSL1 interacts with JUNB and, to a lesser extent, JUN in differentiating trophoblast cells. Knockdown of FOSL1 and JUNB expression inhibited both endocrine and invasive properties of trophoblast cells. In summary, FOSL1 recruits JUNB to form AP-1 transcriptional complexes that specifically regulate the endocrine and invasive trophoblast phenotypes. PMID:26149388

  2. Adaptive representation for dynamic environment, vehicle, and mission complexity

    NASA Astrophysics Data System (ADS)

    Collier, Jack A.; Ricard, Benoit; Digney, Bruce L.; Cheng, David; Trentini, Michael; Beckman, Blake

    2004-09-01

    In order for an Unmanned Ground Vehicle (UGV) to operate effectively it must be able to perceive its environment in an accurate, robust and effective manner. This is done by creating a world representation which encompasses all the perceptual information necessary for the UGV to understand its surroundings. These perceptual needs are a function of the robots mobility characteristics, the complexity of the environment in which it operates, and the mission with which the UGV has been tasked. Most perceptual systems are designed with predefined vehicle, environmental, and mission complexity in mind. This can lead the robot to fail when it encounters a situation which it was not designed for since its internal representation is insufficient for effective navigation. This paper presents a research framework currently being investigated by Defence R&D Canada (DRDC), which will ultimately relieve robotic vehicles of this problem by allowing the UGV to recognize representational deficiencies, and change its perceptual strategy to alleviate these deficiencies. This will allow the UGV to move in and out of a wide variety of environments, such as outdoor rural to indoor urban, at run time without reprogramming. We present sensor and perception work currently being done and outline our research in this area for the future.

  3. Dynamical properties and complexity in fractional-order diffusionless Lorenz system

    NASA Astrophysics Data System (ADS)

    He, Shaobo; Sun, Kehui; Banerjee, Santo

    2016-08-01

    In this paper, dynamics and complexity of the fractional-order diffusionless Lorenz system which is solved by the developed discrete Adomian decomposition method are investigated numerically. Dynamical properties of the fractional-order diffusionless Lorenz system with the control parameter and derivative order varying is analyzed by using bifurcation diagrams, and period-doubling route to chaos in different cases is observed. The complexity of the system is investigated by means of Lyapunov characteristic exponents, multi-scale spectral entropy algorithm and multiscale Renyi permutation entropy algorithm. It can be observed that the three methods illustrate consistent results and the system has rich complex dynamics. Interestingly, complexity decreases with the increase of derivative order. It shows that the fractional-order diffusionless Lorenz system is a good model for real applications such as information encryption and secure communication.

  4. Positive Affect and the Complex Dynamics of Human Flourishing

    PubMed Central

    Fredrickson, Barbara L.; Losada, Marcial F.

    2011-01-01

    Extending B. L. Fredrickson’s (1998) broaden-and-build theory of positive emotions and M. Losada’s (1999) nonlinear dynamics model of team performance, the authors predict that a ratio of positive to negative affect at or above 2.9 will characterize individuals in flourishing mental health. Participants (N = 188) completed an initial survey to identify flourishing mental health and then provided daily reports of experienced positive and negative emotions over 28 days. Results showed that the mean ratio of positive to negative affect was above 2.9 for individuals classified as flourishing and below that threshold for those not flourishing. Together with other evidence, these findings suggest that a set of general mathematical principles may describe the relations between positive affect and human flourishing. PMID:16221001

  5. Positive affect and the complex dynamics of human flourishing.

    PubMed

    Fredrickson, Barbara L; Losada, Marcial F

    2005-10-01

    Extending B. L. Fredrickson's (1998) broaden-and-build theory of positive emotions and M. Losada's (1999) nonlinear dynamics model of team performance, the authors predict that a ratio of positive to negative affect at or above 2.9 will characterize individuals in flourishing mental health. Participants (N=188) completed an initial survey to identify flourishing mental health and then provided daily reports of experienced positive and negative emotions over 28 days. Results showed that the mean ratio of positive to negative affect was above 2.9 for individuals classified as flourishing and below that threshold for those not flourishing. Together with other evidence, these findings suggest that a set of general mathematical principles may describe the relations between positive affect and human flourishing. PMID:16221001

  6. Spectroscopy and reaction dynamics of collision complexes containing hydroxyl radicals

    SciTech Connect

    Lester, M.I.

    1993-12-01

    The DOE supported work in this laboratory has focused on the spectroscopic characterization of the interaction potential between an argon atom and a hydroxyl radical in the ground X{sup 2}II and excited A {sup 2}{summation}{sup +} electronic states. The OH-Ar system has proven to be a test case for examining the interaction potential in an open-shell system since it is amenable to experimental investigation and theoretically tractable from first principles. Experimental identification of the bound states supported by the Ar + OH (X {sup 2}II) and Ar + OH(A {sup 2}{summation}{sup +}) potentials makes it feasible to derive realistic potential energy surfaces for these systems. The experimentally derived intermolecular potentials provide a rigorous test of ab initio theory and a basis for understanding the dramatically different collision dynamics taking place on the ground and excited electronic state surfaces.

  7. Complex dynamics of a nonlinear voter model with contrarian agents

    SciTech Connect

    Tanabe, Shoma; Masuda, Naoki

    2013-12-15

    We investigate mean-field dynamics of a nonlinear opinion formation model with congregator and contrarian agents. Each agent assumes one of the two possible states. Congregators imitate the state of other agents with a rate that increases with the number of other agents in the opposite state, as in the linear voter model and nonlinear majority voting models. Contrarians flip the state with a rate that increases with the number of other agents in the same state. The nonlinearity controls the strength of the majority voting and is used as a main bifurcation parameter. We show that the model undergoes a rich bifurcation scenario comprising the egalitarian equilibrium, two symmetric lopsided equilibria, limit cycle, and coexistence of different types of stable equilibria with intertwining attractive basins.

  8. Galectin-9: From cell biology to complex disease dynamics.

    PubMed

    John, Sebastian; Mishra, Rashmi

    2016-09-01

    Galectins is a family of non-classically secreted, beta-galactoside-binding proteins that has recently received considerable attention in the spatio-temporal regulation of surface 'signal lattice' organization, membrane dynamics, cell-adhesion and disease therapeutics. Galectin-9 is a unique member of this family, with two non-homologous carbohydrate recognition domains joined by a linker peptide sequence of variable lengths, generating isoforms with distinct properties and functions in both physiological and pathological settings, such as during development, immune reaction, neoplastic transformations and metastasis. In this review, we summarize the latest knowledge on the structure, receptors, cellular targets, trafficking pathways and functional properties of galectin-9 and discuss how galectin-9-mediated signalling cascades can be exploited in cancers and immunotherapies.

  9. Galectin-9: From cell biology to complex disease dynamics.

    PubMed

    John, Sebastian; Mishra, Rashmi

    2016-09-01

    Galectins is a family of non-classically secreted, beta-galactoside-binding proteins that has recently received considerable attention in the spatio-temporal regulation of surface 'signal lattice' organization, membrane dynamics, cell-adhesion and disease therapeutics. Galectin-9 is a unique member of this family, with two non-homologous carbohydrate recognition domains joined by a linker peptide sequence of variable lengths, generating isoforms with distinct properties and functions in both physiological and pathological settings, such as during development, immune reaction, neoplastic transformations and metastasis. In this review, we summarize the latest knowledge on the structure, receptors, cellular targets, trafficking pathways and functional properties of galectin-9 and discuss how galectin-9-mediated signalling cascades can be exploited in cancers and immunotherapies. PMID:27581941

  10. Railway faults spreading model based on dynamics of complex network

    NASA Astrophysics Data System (ADS)

    Zhou, Jin; Xu, Weixiang; Guo, Xin; Ma, Xin

    2015-12-01

    In this paper, we propose a railway faults spreading model which improved the SIR model and made it suitable for analyzing the dynamic process of faults spreading. To apply our model into a real network, the accident causation network of "7.23" China Yongwen high-speed railway accident is employed. This network is improved into a directed network, which more clearly reflects the causation relationships among the accident factors and provides help for our studies. Simulation results quantitatively show that the influence of failures can be diminished via choosing the appropriate initial recovery factors, reducing the time of the failure detected, decreasing the transmission rate of faults and increasing the propagating rate of corrected information. The model is useful to simulate the railway faults spreading and quantitatively analyze the influence of failures.

  11. Momentum conserving Brownian dynamics propagator for complex soft matter fluids

    SciTech Connect

    Padding, J. T.; Briels, W. J.

    2014-12-28

    We present a Galilean invariant, momentum conserving first order Brownian dynamics scheme for coarse-grained simulations of highly frictional soft matter systems. Friction forces are taken to be with respect to moving background material. The motion of the background material is described by locally averaged velocities in the neighborhood of the dissolved coarse coordinates. The velocity variables are updated by a momentum conserving scheme. The properties of the stochastic updates are derived through the Chapman-Kolmogorov and Fokker-Planck equations for the evolution of the probability distribution of coarse-grained position and velocity variables, by requiring the equilibrium distribution to be a stationary solution. We test our new scheme on concentrated star polymer solutions and find that the transverse current and velocity time auto-correlation functions behave as expected from hydrodynamics. In particular, the velocity auto-correlation functions display a long time tail in complete agreement with hydrodynamics.

  12. Complexity multiscale asynchrony measure and behavior for interacting financial dynamics

    NASA Astrophysics Data System (ADS)

    Yang, Ge; Wang, Jun; Niu, Hongli

    2016-08-01

    A stochastic financial price process is proposed and investigated by the finite-range multitype contact dynamical system, in an attempt to study the nonlinear behaviors of real asset markets. The viruses spreading process in a finite-range multitype system is used to imitate the interacting behaviors of diverse investment attitudes in a financial market, and the empirical research on descriptive statistics and autocorrelation behaviors of return time series is performed for different values of propagation rates. Then the multiscale entropy analysis is adopted to study several different shuffled return series, including the original return series, the corresponding reversal series, the random shuffled series, the volatility shuffled series and the Zipf-type shuffled series. Furthermore, we propose and compare the multiscale cross-sample entropy and its modification algorithm called composite multiscale cross-sample entropy. We apply them to study the asynchrony of pairs of time series under different time scales.

  13. Dynamically­ Reconfigurable Complex Emulsions via Tunable Interfacial Tensions

    NASA Astrophysics Data System (ADS)

    Swager, Timothy

    This lecture will focus on the design of systems wherein a reconfiguration of the materials can be triggered chemically of mechanically. The utility of these methods is to generate transduction mechanisms by which chemical and biological sensors can be developed. Three different types of systems will be discussed. (1) Particles wherein a protease enzyme releases strain in the particle by breaking crosslinks. (2) Assemblies of polymers at air water interfaces and the demonstration of a luminescence strain response upon compression. (3) Dynamic colloids produced from immiscible fluorocarbon/hydrocarbon mixtures and ability to convert the core and shell layers of the particles as well as the conversion to Janus particles. The latter system's morphology changes can be triggered chemically or optically.

  14. COMPLEX FLARE DYNAMICS INITIATED BY A FILAMENT–FILAMENT INTERACTION

    SciTech Connect

    Zhu, Chunming; McAteer, R. T. James; Liu, Rui; Alexander, David; Sun, Xudong

    2015-11-01

    We report on an eruption involving a relatively rare filament–filament interaction on 2013 June 21, observed by SDO and STEREO-B. The two filaments were separated in height with a “double-decker” configuration. The eruption of the lower filament began simultaneously with a descent of the upper filament, resulting in a convergence and direct interaction of the two filaments. The interaction was accompanied by the heating of surrounding plasma and an apparent crossing of a loop-like structure through the upper filament. The subsequent coalescence of the filaments drove a bright front ahead of the erupting structures. The whole process was associated with a C3.0 flare followed immediately by an M2.9 flare. Shrinking loops and descending dark voids were observed during the M2.9 flare at different locations above a C-shaped flare arcade as part of the energy release, giving us unique insight into the flare dynamics.

  15. Langevin equation with stochastic damping - Possible application to critical binary fluid

    NASA Technical Reports Server (NTRS)

    Jasnow, D.; Gerjuoy, E.

    1975-01-01

    We solve the familiar Langevin equation with stochastic damping to represent the motion of a Brownian particle in a fluctuating medium. A connection between the damping and the random driving forces is proposed which preserves quite generally the Einstein relation between the diffusion and mobility coefficients. We present an application to the case of a Brownian particle in a critical binary mixture.

  16. Critical comparison of Kramers' fission width with the stationary width from the Langevin equation

    SciTech Connect

    Sadhukhan, Jhilam; Pal, Santanu

    2009-06-15

    It is shown that Kramers' fission width, originally derived for a system with constant inertia, can be extended to systems with a deformation-dependent collective inertia, which is the case for nuclear fission. The predictions of Kramers' width for systems with variable inertia are found to be in very good agreement with the stationary fission widths obtained by solving the corresponding Langevin equations.

  17. A Statistical Physics Characterization of the Complex Systems Dynamics: Quantifying Complexity from Spatio-Temporal Interactions

    NASA Astrophysics Data System (ADS)

    Koorehdavoudi, Hana; Bogdan, Paul

    2016-06-01

    Biological systems are frequently categorized as complex systems due to their capabilities of generating spatio-temporal structures from apparent random decisions. In spite of research on analyzing biological systems, we lack a quantifiable framework for measuring their complexity. To fill this gap, in this paper, we develop a new paradigm to study a collective group of N agents moving and interacting in a three-dimensional space. Our paradigm helps to identify the spatio-temporal states of the motion of the group and their associated transition probabilities. This framework enables the estimation of the free energy landscape corresponding to the identified states. Based on the energy landscape, we quantify missing information, emergence, self-organization and complexity for a collective motion. We show that the collective motion of the group of agents evolves to reach the most probable state with relatively lowest energy level and lowest missing information compared to other possible states. Our analysis demonstrates that the natural group of animals exhibit a higher degree of emergence, self-organization and complexity over time. Consequently, this algorithm can be integrated into new frameworks to engineer collective motions to achieve certain degrees of emergence, self-organization and complexity.

  18. A Statistical Physics Characterization of the Complex Systems Dynamics: Quantifying Complexity from Spatio-Temporal Interactions

    PubMed Central

    Koorehdavoudi, Hana; Bogdan, Paul

    2016-01-01

    Biological systems are frequently categorized as complex systems due to their capabilities of generating spatio-temporal structures from apparent random decisions. In spite of research on analyzing biological systems, we lack a quantifiable framework for measuring their complexity. To fill this gap, in this paper, we develop a new paradigm to study a collective group of N agents moving and interacting in a three-dimensional space. Our paradigm helps to identify the spatio-temporal states of the motion of the group and their associated transition probabilities. This framework enables the estimation of the free energy landscape corresponding to the identified states. Based on the energy landscape, we quantify missing information, emergence, self-organization and complexity for a collective motion. We show that the collective motion of the group of agents evolves to reach the most probable state with relatively lowest energy level and lowest missing information compared to other possible states. Our analysis demonstrates that the natural group of animals exhibit a higher degree of emergence, self-organization and complexity over time. Consequently, this algorithm can be integrated into new frameworks to engineer collective motions to achieve certain degrees of emergence, self-organization and complexity. PMID:27297496

  19. Complexity and Control: Towards a Rigorous Behavioral Theory of Complex Dynamical Systems

    NASA Astrophysics Data System (ADS)

    Ivancevic, Vladimir G.; Reid, Darryn J.

    We introduce our motive for writing this book on complexity and control with a popular "complexity myth," which seems to be quite wide spread among chaos and complexity theory fashionistas: Low-dimensional systems usually exhibit complex behaviours (which we know fromMay's studies of the Logisticmap), while high-dimensional systems usually exhibit simple behaviours (which we know from synchronisation studies of the Kuramoto model)... We admit that this naive view on complex (e.g., human) systems versus simple (e.g., physical) systems might seem compelling to various technocratic managers and politicians; indeed, the idea makes for appealing sound-bites. However, it is enough to see both in the equations and computer simulations of pendula of various degree - (i) a single pendulum, (ii) a double pendulum, and (iii) a triple pendulum - that this popular myth is plain nonsense. The only thing that we can learn from it is what every tyrant already knows: by using force as a strong means of control, it is possible to effectively synchronise even hundreds of millions of people, at least for a while.

  20. BiCAMWI: A Genetic-Based Biclustering Algorithm for Detecting Dynamic Protein Complexes

    PubMed Central

    Lakizadeh, Amir; Jalili, Saeed

    2016-01-01

    Considering the roles of protein complexes in many biological processes in the cell, detection of protein complexes from available protein-protein interaction (PPI) networks is a key challenge in the post genome era. Despite high dynamicity of cellular systems and dynamic interaction between proteins in a cell, most computational methods have focused on static networks which cannot represent the inherent dynamicity of protein interactions. Recently, some researchers try to exploit the dynamicity of PPI networks by constructing a set of dynamic PPI subnetworks correspondent to each time-point (column) in a gene expression data. However, many genes can participate in multiple biological processes and cellular processes are not necessarily related to every sample, but they might be relevant only for a subset of samples. So, it is more interesting to explore each subnetwork based on a subset of genes and conditions (i.e., biclusters) in a gene expression data. Here, we present a new method, called BiCAMWI to employ dynamicity in detecting protein complexes. The preprocessing phase of the proposed method is based on a novel genetic algorithm that extracts some sets of genes that are co-regulated under some conditions from input gene expression data. Each extracted gene set is called bicluster. In the detection phase of the proposed method, then, based on the biclusters, some dynamic PPI subnetworks are extracted from input static PPI network. Protein complexes are identified by applying a detection method on each dynamic PPI subnetwork and aggregating the results. Experimental results confirm that BiCAMWI effectively models the dynamicity inherent in static PPI networks and achieves significantly better results than state-of-the-art methods. So, we suggest BiCAMWI as a more reliable method for protein complex detection. PMID:27462706

  1. BiCAMWI: A Genetic-Based Biclustering Algorithm for Detecting Dynamic Protein Complexes.

    PubMed

    Lakizadeh, Amir; Jalili, Saeed

    2016-01-01

    Considering the roles of protein complexes in many biological processes in the cell, detection of protein complexes from available protein-protein interaction (PPI) networks is a key challenge in the post genome era. Despite high dynamicity of cellular systems and dynamic interaction between proteins in a cell, most computational methods have focused on static networks which cannot represent the inherent dynamicity of protein interactions. Recently, some researchers try to exploit the dynamicity of PPI networks by constructing a set of dynamic PPI subnetworks correspondent to each time-point (column) in a gene expression data. However, many genes can participate in multiple biological processes and cellular processes are not necessarily related to every sample, but they might be relevant only for a subset of samples. So, it is more interesting to explore each subnetwork based on a subset of genes and conditions (i.e., biclusters) in a gene expression data. Here, we present a new method, called BiCAMWI to employ dynamicity in detecting protein complexes. The preprocessing phase of the proposed method is based on a novel genetic algorithm that extracts some sets of genes that are co-regulated under some conditions from input gene expression data. Each extracted gene set is called bicluster. In the detection phase of the proposed method, then, based on the biclusters, some dynamic PPI subnetworks are extracted from input static PPI network. Protein complexes are identified by applying a detection method on each dynamic PPI subnetwork and aggregating the results. Experimental results confirm that BiCAMWI effectively models the dynamicity inherent in static PPI networks and achieves significantly better results than state-of-the-art methods. So, we suggest BiCAMWI as a more reliable method for protein complex detection. PMID:27462706

  2. Dynamic Simulation of VEGA SRM Bench Firing By Using Propellant Complex Characterization

    NASA Astrophysics Data System (ADS)

    Di Trapani, C. D.; Mastrella, E.; Bartoccini, D.; Squeo, E. A.; Mastroddi, F.; Coppotelli, G.; Linari, M.

    2012-07-01

    During the VEGA launcher development, from the 2004 up to now, 8 firing tests have been performed at Salto di Quirra (Sardinia, Italy) and Kourou (Guyana, Fr) with the objective to characterize and qualify of the Zefiros and P80 Solid Rocket Motors (SRM). In fact the VEGA launcher configuration foreseen 3 solid stages based on P80, Z23 and Z9 Solid Rocket Motors respectively. One of the primary objectives of the firing test is to correctly characterize the dynamic response of the SRM in order to apply such a characterization to the predictions and simulations of the VEGA launch dynamic environment. Considering that the solid propellant is around 90% of the SRM mass, it is very important to dynamically characterize it, and to increase the confidence in the simulation of the dynamic levels transmitted to the LV upper part from the SRMs. The activity is articulated in three parts: • consolidation of an experimental method for the dynamic characterization of the complex dynamic elasticity modulus of elasticity of visco-elastic materials applicable to the SRM propellant operative conditions • introduction of the complex dynamic elasticity modulus in a numerical FEM benchmark based on MSC NASTRAN solver • analysis of the effect of the introduction of the complex dynamic elasticity modulus in the Zefiros FEM focusing on experimental firing test data reproduction with numerical approach.

  3. Epidemic spreading model of complex dynamical network with the heterogeneity of nodes

    NASA Astrophysics Data System (ADS)

    Hong, Sheng; Yang, Hongqi; Zhao, Tingdi; Ma, Xiaomin

    2016-08-01

    In this paper, we model epidemic spreading by considering the mobility of nodes in complex dynamical network based on mean field theory using differential equations. Moreover, a resistance factor which can characterise the impact of individual's difference on the propagation dynamics in complex dynamical network is proposed by considering the influence of total number of connections and the continuous time to remain in contact. The effect of heterogeneity on the evolution process of propagation dynamics is explored by simulation. Extensive simulations are conducted to study the key influence parameters and the influence of them on the spreading dynamics, which are helpful to the understanding of epidemic spreading mechanism and the designing of effective control strategies.

  4. Linear Superposition and Prediction of Bacterial Promoter Activity Dynamics in Complex Conditions

    PubMed Central

    Rothschild, Daphna; Dekel, Erez; Hausser, Jean; Bren, Anat; Aidelberg, Guy; Szekely, Pablo; Alon, Uri

    2014-01-01

    Bacteria often face complex environments. We asked how gene expression in complex conditions relates to expression in simpler conditions. To address this, we obtained accurate promoter activity dynamical measurements on 94 genes in E. coli in environments made up of all possible combinations of four nutrients and stresses. We find that the dynamics across conditions is well described by two principal component curves specific to each promoter. As a result, the promoter activity dynamics in a combination of conditions is a weighted average of the dynamics in each condition alone. The weights tend to sum up to approximately one. This weighted-average property, called linear superposition, allows predicting the promoter activity dynamics in a combination of conditions based on measurements of pairs of conditions. If these findings apply more generally, they can vastly reduce the number of experiments needed to understand how E. coli responds to the combinatorially huge space of possible environments. PMID:24809350

  5. Distributed parameter approach to the dynamics of complex biological processes

    SciTech Connect

    Lee, T.T.; Wang, F.Y.; Newell, R.B.

    1999-10-01

    Modeling and simulation of a complex biological process for the removal of nutrients (nitrogen and phosphorus) from municipal wastewater are addressed. The model developed in this work employs a distributed-parameter approach to describe the behavior of components within three different bioreaction zones and the behavior of sludge in the anaerobic zone and soluble phosphate in the aerobic zone in two experiments. Good results are achieved despite the apparent plant-model mismatch, such as uncertainties with the behavior of phosphorus-accumulating organisms. Validation of the proposed secondary-settler model shows that it is superior to two state-of-the-art models in terms of the sum of the square relative errors.

  6. A perspective on modeling and simulation of complex dynamical systems

    NASA Astrophysics Data System (ADS)

    Åström, K. J.

    2011-09-01

    There has been an amazing development of modeling and simulation from its beginning in the 1920s, when the technology was available only at a handful of University groups who had access to a mechanical differential analyzer. Today, tools for modeling and simulation are available for every student and engineer. This paper gives a perspective on the development with particular emphasis on technology and paradigm shifts. Modeling is increasingly important for design and operation of complex natural and man-made systems. Because of the increased use of model based control such as Kalman filters and model predictive control, models are also appearing as components of feedback systems. Modeling and simulation are multidisciplinary, it is used in a wide variety of fields and their development have been strongly influenced by mathematics, numerics, computer science and computer technology.

  7. Morphological dynamics of cumulus-oocyte complex during oocyte maturation.

    PubMed

    Sato, E

    1998-01-01

    The recent advances on the cytoplasmic regulators of the induction of germinal vesicle break down, maturation and degeneration of oocytes, and glycosaminoglycan composition during cumulus expansion of cumulus-oocyte complexes are discussed. A) Inactive mitogen-activated protein kinases (MAPKs) are present in the oocytes at germinal vesicle (GV) stage, and are activated with germinal vesicle breakdown (GVBD), and remain highly active throughout maturation in porcine oocytes. Inactive MAPKs are localized in the cytoplasm of GV-arrested oocytes and active MAPKs were detected in the GV just before GVBD. B) Cumulus expansion of porcine cumulus-oocyte complexes (COCs) was reduced by oocy tectomy. The profile of total glycosaminoglycan synthesis was attributed to hyaluronic acid rather than chondroitin sulfate in intact COCs and oocytectomy reduced hyaluronic acid synthesis. C) The abnormalities of chromosomes and alpha-tubulin morphology were observed in the oocytes of c-mos deficient mice. MAPK activity of c-mos deficient oocytes did not significantly fluctuate throughout maturation and was clearly lower than that of wild-type oocytes. One of the most drastic abnormalities in c-mos knockout mouse oocytes was their entrance into the interphase instead of second meiosis after first polar body emission. D) Reverse transcriptase/polymerase chain reaction-Southern blot hybridization demonstrated positive expression of Fas in intraovarian mouse oocytes. In contrast, expression of Fas ligand was detected in granulosa cells. These findings were histologically confirmed by in situ hybridization with Fas- and FasL-specific probes. Co-culture of intact and zona-free eggs and granulosa cells demonstrated positive TUNEL staining only zona-free eggs.

  8. Characterization and dynamic properties for the solid inclusion complexes of β-cyclodextrin and perfluorooctanoic acid.

    PubMed

    Karoyo, Abdalla H; Sidhu, Paul; Wilson, Lee D; Hazendonk, Paul

    2013-07-11

    The structural characterization and dynamic properties of solid-state inclusion complexes (ICs) formed between β-cyclodextrin (β-CD; host) and perfluorooctanoic acid (PFOA; guest) were investigated using (13)C NMR spectroscopy. The 1:1 and 2:1 host/guest solid-state complexes were prepared using a modified dissolution method to obtain complexes with high phase purity. These complexes were further characterized using differential scanning calorimetry (DSC), FT-IR spectroscopy, powder X-ray diffraction (PXRD), (19)F directpolarization (DP), and (13)C cross-polarization (CP) with magic-angle spinning (MAS) NMR spectroscopy. The (19)F → (13)C CP results provided unequivocal support for the formation of well-defined inclusion compounds. The phase purity of the complexes formed between β-CD and PFOA were assessed using the (19)F DP NMR technique at variable temperature (VT) and MAS at 20 kHz. The complexes were found to be of high phase purity when prepared in accordance with the modified dissolution method. The motional dynamics of the guest in the solid complexes were assessed using T1/T2/T1ρ relaxation NMR methods at ambient and VT conditions. The relaxation data revealed reliable and variable guest dynamics for the 1:1 versus 2:1 complexes at the VTs investigated. The motional dynamics of the guest molecules involve an ensemble of axial motions of the whole chain and 120° rotational jumps of the methyl (CF3) group at the termini of the perfluorocarbon chain. The axial and rotational dynamics of the guest in the 1:1 and 2:1 complexes differ in distribution and magnitude in accordance with the binding geometry of the guest within the host. PMID:23713518

  9. Fault diagnosis of time-delay complex dynamical networks using output signals

    NASA Astrophysics Data System (ADS)

    Liu, Hao; Song, Yu-Rong; Fan, Chun-Xia; Jiang, Guo-Ping

    2010-07-01

    This paper proposes a novel approach for fault diagnosis of a time-delay complex dynamical network. Unlike the other methods, assuming that the dynamics of the network can be described by a linear stochastic model, or using the state variables of nodes in the network to design an adaptive observer, it only uses the output variable of the nodes to design an observer and an adaptive law of topology matrix in the observer of a complex network, leading to simple design of the observer and easy realisation of topology monitoring for the complex networks in real engineering. The proposed scheme can monitor any changes of the topology structure of a time-delay complex network. The effectiveness of this method is successfully demonstrated by virtue of a complex networks with Lorenz model.

  10. Complexity Science Applications to Dynamic Trajectory Management: Research Strategies

    NASA Technical Reports Server (NTRS)

    Sawhill, Bruce; Herriot, James; Holmes, Bruce J.; Alexandrov, Natalia

    2009-01-01

    The promise of the Next Generation Air Transportation System (NextGen) is strongly tied to the concept of trajectory-based operations in the national airspace system. Existing efforts to develop trajectory management concepts are largely focused on individual trajectories, optimized independently, then de-conflicted among each other, and individually re-optimized, as possible. The benefits in capacity, fuel, and time are valuable, though perhaps could be greater through alternative strategies. The concept of agent-based trajectories offers a strategy for automation of simultaneous multiple trajectory management. The anticipated result of the strategy would be dynamic management of multiple trajectories with interacting and interdependent outcomes that satisfy multiple, conflicting constraints. These constraints would include the business case for operators, the capacity case for the Air Navigation Service Provider (ANSP), and the environmental case for noise and emissions. The benefits in capacity, fuel, and time might be improved over those possible under individual trajectory management approaches. The proposed approach relies on computational agent-based modeling (ABM), combinatorial mathematics, as well as application of "traffic physics" concepts to the challenge, and modeling and simulation capabilities. The proposed strategy could support transforming air traffic control from managing individual aircraft behaviors to managing systemic behavior of air traffic in the NAS. A system built on the approach could provide the ability to know when regions of airspace approach being "full," that is, having non-viable local solution space for optimizing trajectories in advance.

  11. Dynamics and complexity of the Schelling segregation model

    NASA Astrophysics Data System (ADS)

    Domic, Nicolás Goles; Goles, Eric; Rica, Sergio

    2011-05-01

    In this paper we consider the Schelling social segregation model for two different populations. In Schelling’s model, segregation appears as a consequence of discrimination, measured by the local difference between two populations. For that, the model defines a tolerance criterion on the neighborhood of an individual, indicating wether the individual is able to move to a new place or not. Next, the model chooses which of the available unhappy individuals really moves. In our work, we study the patterns generated by the dynamical evolution of the Schelling model in terms of various parameters or the initial condition, such as the size of the neighborhood of an inhabitant, the tolerance, and the initial number of individuals. As a general rule we observe that segregation patterns minimize the interface of zones of different people. In this context we introduce an energy functional associated with the configuration which is a strictly decreasing function for the tolerant people case. Moreover, as far as we know, we are the first to notice that in the case of a non-strictly-decreasing energy functional, the system may segregate very efficiently.

  12. Dynamics and complexity of the Schelling segregation model.

    PubMed

    Domic, Nicolás Goles; Goles, Eric; Rica, Sergio

    2011-05-01

    In this paper we consider the Schelling social segregation model for two different populations. In Schelling's model, segregation appears as a consequence of discrimination, measured by the local difference between two populations. For that, the model defines a tolerance criterion on the neighborhood of an individual, indicating wether the individual is able to move to a new place or not. Next, the model chooses which of the available unhappy individuals really moves. In our work, we study the patterns generated by the dynamical evolution of the Schelling model in terms of various parameters or the initial condition, such as the size of the neighborhood of an inhabitant, the tolerance, and the initial number of individuals. As a general rule we observe that segregation patterns minimize the interface of zones of different people. In this context we introduce an energy functional associated with the configuration which is a strictly decreasing function for the tolerant people case. Moreover, as far as we know, we are the first to notice that in the case of a non-strictly-decreasing energy functional, the system may segregate very efficiently.

  13. Complex Rotation Quantum Dynamic Neural Networks (CRQDNN) using Complex Quantum Neuron (CQN): Applications to time series prediction.

    PubMed

    Cui, Yiqian; Shi, Junyou; Wang, Zili

    2015-11-01

    Quantum Neural Networks (QNN) models have attracted great attention since it innovates a new neural computing manner based on quantum entanglement. However, the existing QNN models are mainly based on the real quantum operations, and the potential of quantum entanglement is not fully exploited. In this paper, we proposes a novel quantum neuron model called Complex Quantum Neuron (CQN) that realizes a deep quantum entanglement. Also, a novel hybrid networks model Complex Rotation Quantum Dynamic Neural Networks (CRQDNN) is proposed based on Complex Quantum Neuron (CQN). CRQDNN is a three layer model with both CQN and classical neurons. An infinite impulse response (IIR) filter is embedded in the Networks model to enable the memory function to process time series inputs. The Levenberg-Marquardt (LM) algorithm is used for fast parameter learning. The networks model is developed to conduct time series predictions. Two application studies are done in this paper, including the chaotic time series prediction and electronic remaining useful life (RUL) prediction.

  14. Ecological dynamics and complex interactions of Agrobacterium megaplasmids.

    PubMed

    Platt, Thomas G; Morton, Elise R; Barton, Ian S; Bever, James D; Fuqua, Clay

    2014-01-01

    As with many pathogenic bacteria, agrobacterial plant pathogens carry most of their virulence functions on a horizontally transmissible genetic element. The tumor-inducing (Ti) plasmid encodes the majority of virulence functions for the crown gall agent Agrobacterium tumefaciens. This includes the vir genes which drive genetic transformation of host cells and the catabolic genes needed to utilize the opines produced by infected plants. The Ti plasmid also encodes, an opine-dependent quorum sensing system that tightly regulates Ti plasmid copy number and its conjugal transfer to other agrobacteria. Many natural agrobacteria are avirulent, lacking the Ti plasmid. The burden of harboring the Ti plasmid depends on the environmental context. Away from diseased hosts, plasmid costs are low but the benefit of the plasmid is also absent. Consequently, plasmidless genotypes are favored. On infected plants the costs of the Ti plasmid can be very high, but balanced by the opine benefits, locally favoring plasmid bearing cells. Cheating derivatives which do not incur virulence costs but can benefit from opines are favored on infected plants and in most other environments, and these are frequently isolated from nature. Many agrobacteria also harbor an At plasmid which can stably coexist with a Ti plasmid. At plasmid genes are less well characterized but in general facilitate metabolic activities in the rhizosphere and bulk soil, such as the ability to breakdown plant exudates. Examination of A. tumefaciens C58, revealed that harboring its At plasmid is much more costly than harboring it's Ti plasmid, but conversely the At plasmid is extremely difficult to cure. The interactions between these co-resident plasmids are complex, and depend on environmental context. However, the presence of a Ti plasmid appears to mitigate At plasmid costs, consistent with the high frequency with which they are found together. PMID:25452760

  15. Safety assessment document for the Dynamic Test Complex B854

    SciTech Connect

    Odell, B.N.; Pfeifer, H.E.

    1981-12-11

    A safety assessment was performed to determine if potential accidents at the 854 Complex at Site 300 could present undue hazards to the general public, personnel at Site 300, or have an adverse effect on the environment. The credible accidents that might have an effect on these facilities or have off-site consequences were considered. These were earthquake, extreme wind (including missiles), lightning, flood, criticality, high explosive (HE) detonation that disperses uranium and beryllium, spontaneous oxidation of plutonium, explosions due to finely divided particles, and a fire. Seismic and extreme wind (including missiles) analyses indicate that the buildings are basically sound. The lightning protection system is in the process of being upgraded to meet AMCR 385-100. These buildings are located high above the dry creek bed so that a flood is improbable. The probability of high explosive detonation involving plutonium is very remote since the radioactive materials are encased and plutonium and HE are not permitted concurrently in the same area at Site 300. (The exception to this policy is that explosive actuating devices are sometimes located in assemblies containing fissile materials. However, an accidental actuation will not affect the safe containment of the plutonium within the assembly.) There is a remote possibility of an HE explosion involving uranium and beryllium since these are permitted in the same area.The possibility of a criticality accident is very remote since the fissile materials are doubly encased in stout metal containers. All operations involving these materials are independently reviewed and inspected by the Criticality Safety Office. It was determined that a fire was unlikely due to the low fire loading and the absence of ignition sources. It was also determined that the consequences of any accidents were reduced by the remote location of these facilities, their design, and by administrative controls.

  16. Ecological dynamics and complex interactions of Agrobacterium megaplasmids

    PubMed Central

    Platt, Thomas G.; Morton, Elise R.; Barton, Ian S.; Bever, James D.; Fuqua, Clay

    2014-01-01

    As with many pathogenic bacteria, agrobacterial plant pathogens carry most of their virulence functions on a horizontally transmissible genetic element. The tumor-inducing (Ti) plasmid encodes the majority of virulence functions for the crown gall agent Agrobacterium tumefaciens. This includes the vir genes which drive genetic transformation of host cells and the catabolic genes needed to utilize the opines produced by infected plants. The Ti plasmid also encodes, an opine-dependent quorum sensing system that tightly regulates Ti plasmid copy number and its conjugal transfer to other agrobacteria. Many natural agrobacteria are avirulent, lacking the Ti plasmid. The burden of harboring the Ti plasmid depends on the environmental context. Away from diseased hosts, plasmid costs are low but the benefit of the plasmid is also absent. Consequently, plasmidless genotypes are favored. On infected plants the costs of the Ti plasmid can be very high, but balanced by the opine benefits, locally favoring plasmid bearing cells. Cheating derivatives which do not incur virulence costs but can benefit from opines are favored on infected plants and in most other environments, and these are frequently isolated from nature. Many agrobacteria also harbor an At plasmid which can stably coexist with a Ti plasmid. At plasmid genes are less well characterized but in general facilitate metabolic activities in the rhizosphere and bulk soil, such as the ability to breakdown plant exudates. Examination of A. tumefaciens C58, revealed that harboring its At plasmid is much more costly than harboring it’s Ti plasmid, but conversely the At plasmid is extremely difficult to cure. The interactions between these co-resident plasmids are complex, and depend on environmental context. However, the presence of a Ti plasmid appears to mitigate At plasmid costs, consistent with the high frequency with which they are found together. PMID:25452760

  17. Understanding Life : The Evolutionary Dynamics of Complexity and Semiosis

    NASA Astrophysics Data System (ADS)

    Loeckenhoff, Helmut K.

    2010-11-01

    Post-Renaissance sciences created different cultures. To establish an epistemological base, Physics were separated from the Mental domain. Consciousness was excluded from science. Life Sciences were left in between e.g. LaMettrie's `man—machine' (1748) and 'vitalism' [e.g. Bergson 4]. Causative thinking versus intuitive arguing limited strictly comprehensive concepts. First ethology established a potential shared base for science, proclaiming the `biology paradigm' in the middle of the 20th century. Initially procured by Cybernetics and Systems sciences, `constructivist' models prepared a new view on human perception and thus also of scientific `objectivity when introducing the `observer'. In sequel Computer sciences triggered the ICT revolution. In turn ICT helped to develop Chaos and Complexity sciences, Non-linear Mathematics and its spin-offs in the formal sciences [Spencer-Brown 49] as e.g. (proto-)logics. Models of life systems, as e.g. Anticipatory Systems, integrated epistemology with mathematics and Anticipatory Computing [Dubois 11, 12, 13, 14] connecting them with Semiotics. Seminal ideas laid in the turn of the 19th to the 20th century [J. v. Uexküll 53] detected the co-action and co-evolvement of environments and life systems. Bio-Semiotics ascribed purpose, intent and meaning as essential qualities of life. The concepts of Systems Biology and Qualitative Research enriched and develop also anthropologies and humanities. Brain research added models of (higher) consciousness. An avant-garde is contemplating a science including consciousness as one additional base. New insights from the extended qualitative approach led to re-conciliation of basic assumptions of scientific inquiry, creating the `epistemological turn'. Paradigmatically, resting on macro- micro- and recently on nano-biology, evolution biology sired fresh scripts of evolution [W. Wieser 60,61]. Its results tie to hypotheses describing the emergence of language, of the human mind and of

  18. Dynamic analysis of traffic time series at different temporal scales: A complex networks approach

    NASA Astrophysics Data System (ADS)

    Tang, Jinjun; Wang, Yinhai; Wang, Hua; Zhang, Shen; Liu, Fang

    2014-07-01

    The analysis of dynamics in traffic flow is an important step to achieve advanced traffic management and control in Intelligent Transportation System (ITS). Complexity and periodicity are definitely two fundamental properties in traffic dynamics. In this study, we first measure the complexity of traffic flow data by Lempel-Ziv algorithm at different temporal scales, and the data are collected from loop detectors on freeway. Second, to obtain more insight into the complexity and periodicity in traffic time series, we then construct complex networks from traffic time series by considering each day as a cycle and each cycle as a single node. The optimal threshold value of complex networks is estimated by the distribution of density and its derivative. In addition, the complex networks are subsequently analyzed in terms of some statistical properties, such as average path length, clustering coefficient, density, average degree and betweenness. Finally, take 2 min aggregation data as example, we use the correlation coefficient matrix, adjacent matrix and closeness to exploit the periodicity of weekdays and weekends in traffic flow data. The findings in this paper indicate that complex network is a practical tool for exploring dynamics in traffic time series.

  19. Function and dynamics of macromolecular complexes explored by integrative structural and computational biology.

    PubMed

    Purdy, Michael D; Bennett, Brad C; McIntire, William E; Khan, Ali K; Kasson, Peter M; Yeager, Mark

    2014-08-01

    Three vignettes exemplify the potential of combining EM and X-ray crystallographic data with molecular dynamics (MD) simulation to explore the architecture, dynamics and functional properties of multicomponent, macromolecular complexes. The first two describe how EM and X-ray crystallography were used to solve structures of the ribosome and the Arp2/3-actin complex, which enabled MD simulations that elucidated functional dynamics. The third describes how EM, X-ray crystallography, and microsecond MD simulations of a GPCR:G protein complex were used to explore transmembrane signaling by the β-adrenergic receptor. Recent technical advancements in EM, X-ray crystallography and computational simulation create unprecedented synergies for integrative structural biology to reveal new insights into heretofore intractable biological systems.

  20. Dynamical complexity of multipoint geospace observations related to magnetosphere-ionosphere coupling

    NASA Astrophysics Data System (ADS)

    Balasis, Georgios; Daglis, Ioannis A.; Papadimitriou, Constantinos; Donner, Reik; Runge, Jakob

    2016-07-01

    We explore, evaluate and compare the applicability, effectiveness and interdisciplinary character of a variety of modern and sophisticated methods, from complex systems sciences, for the investigation of dynamical complexity of the near-Earth electromagnetic environment. We identify and inter-compare complementary analysis concepts, allowing for a systematic study of geospace magnetic storms and magnetospheric substorms and regime shifts between normal and abnormal states of the Earth's magnetic field, based on observational data from both ground and space. We expect these concepts to allow identifying previously unrecognized precursory structures in the dynamical complexity and, thus, contribute to a better understanding of dynamical processes manifested in observable magnetic field fluctuations prior to possible space weather-related hazards.

  1. An integrative and practical evolutionary optimization for a complex, dynamic model of biological networks.

    PubMed

    Maeda, Kazuhiro; Fukano, Yuya; Yamamichi, Shunsuke; Nitta, Daichi; Kurata, Hiroyuki

    2011-05-01

    Computer simulation is an important technique to capture the dynamics of biochemical networks. Numerical optimization is the key to estimate the values of kinetic parameters so that the dynamic model reproduces the behaviors of the existing experimental data. It is required to develop general strategies for the optimization of complex biochemical networks with a huge space of search parameters, under the condition that kinetic and quantitative data are hardly available. We propose an integrative and practical strategy for optimizing a complex dynamic model by using qualitative and incomplete experimental data. The key technologies are the divide and conquer method for reducing the search space, handling of multiple objective functions representing different types of biological behaviors, and design of rule-based objective functions that are suitable for qualitative and error-prone experimental data. This strategy is applied to optimizing a dynamic model of the yeast cell cycle to demonstrate the feasibility of it.

  2. Markov and non-Markov processes in complex systems by the dynamical information entropy

    NASA Astrophysics Data System (ADS)

    Yulmetyev, R. M.; Gafarov, F. M.

    1999-12-01

    We consider the Markov and non-Markov processes in complex systems by the dynamical information Shannon entropy (DISE) method. The influence and important role of the two mutually dependent channels of entropy alternation (creation or generation of correlation) and anti-correlation (destroying or annihilation of correlation) have been discussed. The developed method has been used for the analysis of the complex systems of various natures: slow neutron scattering in liquid cesium, psychology (short-time numeral and pattern human memory and effect of stress on the dynamical taping-test), random dynamics of RR-intervals in human ECG (problem of diagnosis of various disease of the human cardio-vascular systems), chaotic dynamics of the parameters of financial markets and ecological systems.

  3. Data based identification and prediction of nonlinear and complex dynamical systems

    NASA Astrophysics Data System (ADS)

    Wang, Wen-Xu; Lai, Ying-Cheng; Grebogi, Celso

    2016-07-01

    The problem of reconstructing nonlinear and complex dynamical systems from measured data or time series is central to many scientific disciplines including physical, biological, computer, and social sciences, as well as engineering and economics. The classic approach to phase-space reconstruction through the methodology of delay-coordinate embedding has been practiced for more than three decades, but the paradigm is effective mostly for low-dimensional dynamical systems. Often, the methodology yields only a topological correspondence of the original system. There are situations in various fields of science and engineering where the systems of interest are complex and high dimensional with many interacting components. A complex system typically exhibits a rich variety of collective dynamics, and it is of great interest to be able to detect, classify, understand, predict, and control the dynamics using data that are becoming increasingly accessible due to the advances of modern information technology. To accomplish these goals, especially prediction and control, an accurate reconstruction of the original system is required. Nonlinear and complex systems identification aims at inferring, from data, the mathematical equations that govern the dynamical evolution and the complex interaction patterns, or topology, among the various components of the system. With successful reconstruction of the system equations and the connecting topology, it may be possible to address challenging and significant problems such as identification of causal relations among the interacting components and detection of hidden nodes. The "inverse" problem thus presents a grand challenge, requiring new paradigms beyond the traditional delay-coordinate embedding methodology. The past fifteen years have witnessed rapid development of contemporary complex graph theory with broad applications in interdisciplinary science and engineering. The combination of graph, information, and nonlinear dynamical

  4. Coarse-Grained Molecular Dynamics: Dissipation Due to Internal Modes

    SciTech Connect

    Rudd, R E

    2001-12-21

    We describe progress on the issue of pathological elastic wave reflection in atomistic and multiscale simulation. First we briefly review Coarse-Grained Molecular Dynamics (CGMD). Originally CGMD was formulated as a Hamiltonian system in which energy is conserved. This formulation is useful for many applications, but recently CGMD has been extended to include generalized Langevin forces. Here we describe how Langevin dynamics arise naturally in CGMD, and we examine the implication for elastic wave scattering.

  5. Cilium transition zone proteome reveals compartmentalization and differential dynamics of ciliopathy complexes.

    PubMed

    Dean, Samuel; Moreira-Leite, Flavia; Varga, Vladimir; Gull, Keith

    2016-08-30

    The transition zone (TZ) of eukaryotic cilia and flagella is a structural intermediate between the basal body and the axoneme that regulates ciliary traffic. Mutations in genes encoding TZ proteins (TZPs) cause human inherited diseases (ciliopathies). Here, we use the trypanosome to identify TZ components and localize them to TZ subdomains, showing that the Bardet-Biedl syndrome complex (BBSome) is more distal in the TZ than the Meckel syndrome (MKS) complex. Several of the TZPs identified here have human orthologs. Functional analysis shows essential roles for TZPs in motility, in building the axoneme central pair apparatus and in flagellum biogenesis. Analysis using RNAi and HaloTag fusion protein approaches reveals that most TZPs (including the MKS ciliopathy complex) show long-term stable association with the TZ, whereas the BBSome is dynamic. We propose that some Bardet-Biedl syndrome and MKS pleiotropy may be caused by mutations that impact TZP complex dynamics. PMID:27519801

  6. Molecular dynamics of protein kinase-inhibitor complexes: a valid structural information.

    PubMed

    Caballero, Julio; Alzate-Morales, Jans H

    2012-01-01

    Protein kinases (PKs) are key components of protein phosphorylation based signaling networks in eukaryotic cells. They have been identified as being implicated in many diseases. High-resolution X-ray crystallographic data exist for many PKs and, in many cases, these structures are co-complexed with inhibitors. Although this valuable information confirms the precise structure of PKs and their complexes, it ignores the dynamic movements of the structures which are relevant to explain the affinities and selectivity of the ligands, to characterize the thermodynamics of the solvated complexes, and to derive predictive models. Atomistic molecular dynamics (MD) simulations present a convenient way to study PK-inhibitor complexes and have been increasingly used in recent years in structure-based drug design. MD is a very useful computational method and a great counterpart for experimentalists, which helps them to derive important additional molecular information. That enables them to follow and understand structure and dynamics of protein-ligand systems with extreme molecular detail on scales where motion of individual atoms can be tracked. MD can be used to sample dynamic molecular processes, and can be complemented with more advanced computational methods (e.g., free energy calculations, structure-activity relationship analysis). This review focuses on the most commonly applications to study PK-inhibitor complexes using MD simulations. Our aim is that researchers working in the design of PK inhibitors be aware of the benefits of this powerful tool in the design of potent and selective PK inhibitors. PMID:22571663

  7. Complex dynamics in a cross-catalytic self-replication mechanism

    NASA Astrophysics Data System (ADS)

    Beutel, Kathleen M.; Peacock-López, Enrique

    2007-03-01

    The authors consider a minimal cross-catalytic self-replicating system of only two cross-catalytic templates that mimics the R3C ligase ribozyme system of Dong-Eu and Joyce [Chem. Biol. 11, 1505 (2004)]. This system displays considerably more complex dynamics than its self-replicating counterpart. In particular, the authors discuss the Poincaré-Andronov-Hopf bifurcation, canard transitions, excitability, and hysteresis that yield birhythmicity between simple and complex oscillations.

  8. Mathematical Physics of Complex Coevolutionary Systems: Theoretical Advances and Applications to Multiscale Hydroclimate Dynamics

    NASA Astrophysics Data System (ADS)

    Perdigão, Rui A. P.

    2016-04-01

    The fundamental stochastic-dynamic coevolution laws governing complex coevolutionary systems are introduced in a mathematical physics framework formally unifying nonlinear stochastic physics with fundamental deterministic interaction laws among spatiotemporally distributed processes. The methodological developments are then used to shed light onto fundamental interactions underlying complex spatiotemporal behaviour and emergence in multiscale hydroclimate dynamics. For this purpose, a mathematical physics framework is presented predicting evolving distributions of hydrologic quantities under nonlinearly coevolving geophysical processes. The functional formulation is grounded on first principles regulating the dynamics of each system constituent and their interactions, therefore its applicability is general and data-independent, not requiring local calibrations. Moreover, it enables the dynamical estimation of hydroclimatic variations in space and time from knowledge at different spatiotemporal conditions, along with the associated uncertainties. This paves the way for a robust physically based prediction of hydroclimatic changes in unsupervised areas (e.g. ungauged basins). Validation is achieved by producing, with the mathematical physics framework, a comprehensive spatiotemporal legacy consistent with the observed distributions along with their statistic-dynamic relations. The similarity between simulated and observed distributions is further assessed with novel robust nonlinear information-theoretic diagnostics. The present study brings to light emerging signatures of structural change in hydroclimate dynamics arising from nonlinear synergies across multiple spatiotemporal scales, and contributes to a better dynamical understanding and prediction of spatiotemporal regimes, transitions, structural changes and extremes in complex coevolutionary systems. This study further sheds light onto a diversity of emerging properties from harmonic to hyper-chaotic in general

  9. Complex quantum Hamilton-Jacobi equation with Bohmian trajectories: Application to the photodissociation dynamics of NOCl

    SciTech Connect

    Chou, Chia-Chun

    2014-03-14

    The complex quantum Hamilton-Jacobi equation-Bohmian trajectories (CQHJE-BT) method is introduced as a synthetic trajectory method for integrating the complex quantum Hamilton-Jacobi equation for the complex action function by propagating an ensemble of real-valued correlated Bohmian trajectories. Substituting the wave function expressed in exponential form in terms of the complex action into the time-dependent Schrödinger equation yields the complex quantum Hamilton-Jacobi equation. We transform this equation into the arbitrary Lagrangian-Eulerian version with the grid velocity matching the flow velocity of the probability fluid. The resulting equation describing the rate of change in the complex action transported along Bohmian trajectories is simultaneously integrated with the guidance equation for Bohmian trajectories, and the time-dependent wave function is readily synthesized. The spatial derivatives of the complex action required for the integration scheme are obtained by solving one moving least squares matrix equation. In addition, the method is applied to the photodissociation of NOCl. The photodissociation dynamics of NOCl can be accurately described by propagating a small ensemble of trajectories. This study demonstrates that the CQHJE-BT method combines the considerable advantages of both the real and the complex quantum trajectory methods previously developed for wave packet dynamics.

  10. Complex quantum Hamilton-Jacobi equation with Bohmian trajectories: application to the photodissociation dynamics of NOCl.

    PubMed

    Chou, Chia-Chun

    2014-03-14

    The complex quantum Hamilton-Jacobi equation-Bohmian trajectories (CQHJE-BT) method is introduced as a synthetic trajectory method for integrating the complex quantum Hamilton-Jacobi equation for the complex action function by propagating an ensemble of real-valued correlated Bohmian trajectories. Substituting the wave function expressed in exponential form in terms of the complex action into the time-dependent Schrödinger equation yields the complex quantum Hamilton-Jacobi equation. We transform this equation into the arbitrary Lagrangian-Eulerian version with the grid velocity matching the flow velocity of the probability fluid. The resulting equation describing the rate of change in the complex action transported along Bohmian trajectories is simultaneously integrated with the guidance equation for Bohmian trajectories, and the time-dependent wave function is readily synthesized. The spatial derivatives of the complex action required for the integration scheme are obtained by solving one moving least squares matrix equation. In addition, the method is applied to the photodissociation of NOCl. The photodissociation dynamics of NOCl can be accurately described by propagating a small ensemble of trajectories. This study demonstrates that the CQHJE-BT method combines the considerable advantages of both the real and the complex quantum trajectory methods previously developed for wave packet dynamics. PMID:24628169

  11. Clustering of time-evolving scaling dynamics in a complex signal.

    PubMed

    Saghir, Hamidreza; Chau, Tom; Kushki, Azadeh

    2016-07-01

    Complex time series are widespread in physics and physiology. Multifractal analysis provides a tool to study the scaling dynamics of such time series. However, the temporal evolution of scaling dynamics has been ignored by traditional tools such as the multifractal spectrum. We present scaling maps that add the time dimension to the study of scaling dynamics. This is particularly important in cases in which the dynamics of the underlying processes change in time or in applications that necessitate real-time detection of scaling dynamics. In addition, we present a methodology for automatic clustering of existing scaling regimes in a signal. We demonstrate the methodology on time-evolving correlated and uncorrelated noise and the output of a physiological control system (i.e., cardiac interbeat intervals) in healthy and pathological states. PMID:27575136

  12. Clustering of time-evolving scaling dynamics in a complex signal

    NASA Astrophysics Data System (ADS)

    Saghir, Hamidreza; Chau, Tom; Kushki, Azadeh

    2016-07-01

    Complex time series are widespread in physics and physiology. Multifractal analysis provides a tool to study the scaling dynamics of such time series. However, the temporal evolution of scaling dynamics has been ignored by traditional tools such as the multifractal spectrum. We present scaling maps that add the time dimension to the study of scaling dynamics. This is particularly important in cases in which the dynamics of the underlying processes change in time or in applications that necessitate real-time detection of scaling dynamics. In addition, we present a methodology for automatic clustering of existing scaling regimes in a signal. We demonstrate the methodology on time-evolving correlated and uncorrelated noise and the output of a physiological control system (i.e., cardiac interbeat intervals) in healthy and pathological states.

  13. Data based identification and prediction of nonlinear and complex dynamical systems

    NASA Astrophysics Data System (ADS)

    Wang, Wen-Xu; Lai, Ying-Cheng; Grebogi, Celso

    2016-07-01

    The problem of reconstructing nonlinear and complex dynamical systems from measured data or time series is central to many scientific disciplines including physical, biological, computer, and social sciences, as well as engineering and economics. The classic approach to phase-space reconstruction through the methodology of delay-coordinate embedding has been practiced for more than three decades, but the paradigm is effective mostly for low-dimensional dynamical systems. Often, the methodology yields only a topological correspondence of the original system. There are situations in various fields of science and engineering where the systems of interest are complex and high dimensional with many interacting components. A complex system typically exhibits a rich variety of collective dynamics, and it is of great interest to be able to detect, classify, understand, predict, and control the dynamics using data that are becoming increasingly accessible due to the advances of modern information technology. To accomplish these goals, especially prediction and control, an accurate reconstruction of the original system is required. Nonlinear and complex systems identification aims at inferring, from data, the mathematical equations that govern the dynamical evolution and the complex interaction patterns, or topology, among the various components of the system. With successful reconstruction of the system equations and the connecting topology, it may be possible to address challenging and significant problems such as identification of causal relations among the interacting components and detection of hidden nodes. The "inverse" problem thus presents a grand challenge, requiring new paradigms beyond the traditional delay-coordinate embedding methodology. The past fifteen years have witnessed rapid development of contemporary complex graph theory with broad applications in interdisciplinary science and engineering. The combination of graph, information, and nonlinear dynamical

  14. Solving the Langevin equation with stochastic algebraically correlated noise

    NASA Astrophysics Data System (ADS)

    Płoszajczak, M.; Srokowski, T.

    1997-05-01

    The long time tail in the velocity and force autocorrelation function has been found recently in molecular dynamics simulations of peripheral collisions of ions. Simulation of those slowly decaying correlations in the stochastic transport theory requires the development of new methods of generating stochastic force of arbitrarily long correlation times. In this paper we propose a Markovian process, the multidimensional kangaroo process, which permits the description of various algebraically correlated stochastic processes.

  15. Balance between Noise and Information Flow Maximizes Set Complexity of Network Dynamics

    PubMed Central

    Mäki-Marttunen, Tuomo; Kesseli, Juha; Nykter, Matti

    2013-01-01

    Boolean networks have been used as a discrete model for several biological systems, including metabolic and genetic regulatory networks. Due to their simplicity they offer a firm foundation for generic studies of physical systems. In this work we show, using a measure of context-dependent information, set complexity, that prior to reaching an attractor, random Boolean networks pass through a transient state characterized by high complexity. We justify this finding with a use of another measure of complexity, namely, the statistical complexity. We show that the networks can be tuned to the regime of maximal complexity by adding a suitable amount of noise to the deterministic Boolean dynamics. In fact, we show that for networks with Poisson degree distributions, all networks ranging from subcritical to slightly supercritical can be tuned with noise to reach maximal set complexity in their dynamics. For networks with a fixed number of inputs this is true for near-to-critical networks. This increase in complexity is obtained at the expense of disruption in information flow. For a large ensemble of networks showing maximal complexity, there exists a balance between noise and contracting dynamics in the state space. In networks that are close to critical the intrinsic noise required for the tuning is smaller and thus also has the smallest effect in terms of the information processing in the system. Our results suggest that the maximization of complexity near to the state transition might be a more general phenomenon in physical systems, and that noise present in a system may in fact be useful in retaining the system in a state with high information content. PMID:23516395

  16. Molecular dynamics of the P450cam-Pdx complex reveals complex stability and novel interface contacts.

    PubMed

    Hollingsworth, Scott A; Poulos, Thomas L

    2015-01-01

    Cytochrome P450cam catalyzes the stereo and regiospecific hydroxylation of camphor to 5-exo-hydroxylcamphor. The two electrons for the oxidation of camphor are provided by putidaredoxin (Pdx), a Fe2 S2 containing protein. Two recent crystal structures of the P450cam-Pdx complex, one solved with the aid of covalent cross-linking and one without, have provided a structural picture of the redox partner interaction. To study the stability of the complex structure and the minor differences between the recent crystal structures, a 100 nanosecond molecular dynamics (MD) simulation of the cross-linked structure, mutated in silico to wild type and the linker molecule removed, was performed. The complex was stable over the course of the simulation though conformational changes including the movement of the C helix of P450cam further toward Pdx allowed for the formation of a number of new contacts at the complex interface that remained stable throughout the simulation. While several minor crystal contacts were lost in the simulation, all major contacts that had been experimentally studied previously were maintained. The equilibrated MD structure contained a mixture of contacts resembling both the cross-linked and noncovalent structures and the newly identified interactions. Finally, the reformation of the P450cam Asp251-Arg186 ion pair in the MD simulation mirrors the ion pair observed in the more promiscuous CYP101D1 and suggests that the Asp251-Arg186 ion pair may be important.

  17. Mood states modulate complexity in heartbeat dynamics: A multiscale entropy analysis

    NASA Astrophysics Data System (ADS)

    Valenza, G.; Nardelli, M.; Bertschy, G.; Lanata, A.; Scilingo, E. P.

    2014-07-01

    This paper demonstrates that heartbeat complex dynamics is modulated by different pathological mental states. Multiscale entropy analysis was performed on R-R interval series gathered from the electrocardiogram of eight bipolar patients who exhibited mood states among depression, hypomania, and euthymia, i.e., good affective balance. Three different methodologies for the choice of the sample entropy radius value were also compared. We show that the complexity level can be used as a marker of mental states being able to discriminate among the three pathological mood states, suggesting to use heartbeat complexity as a more objective clinical biomarker for mental disorders.

  18. Fractional Brownian motion and motion governed by the fractional Langevin equation in confined geometries.

    PubMed

    Jeon, Jae-Hyung; Metzler, Ralf

    2010-02-01

    Motivated by subdiffusive motion of biomolecules observed in living cells, we study the stochastic properties of a non-Brownian particle whose motion is governed by either fractional Brownian motion or the fractional Langevin equation and restricted to a finite domain. We investigate by analytic calculations and simulations how time-averaged observables (e.g., the time-averaged mean-squared displacement and displacement correlation) are affected by spatial confinement and dimensionality. In particular, we study the degree of weak ergodicity breaking and scatter between different single trajectories for this confined motion in the subdiffusive domain. The general trend is that deviations from ergodicity are decreased with decreasing size of the movement volume and with increasing dimensionality. We define the displacement correlation function and find that this quantity shows distinct features for fractional Brownian motion, fractional Langevin equation, and continuous time subdiffusion, such that it appears an efficient measure to distinguish these different processes based on single-particle trajectory data.

  19. Diffusion length and Langevin recombination of singlet and triplet excitons in organic heterojunction solar cells.

    PubMed

    Ompong, David; Singh, Jai

    2015-04-27

    We derived new expressions for the diffusion length of singlet and triplet excitons by using the Föster and Dexter transfer mechanisms, respectively, and have found that the diffusion lengths of singlet and triplet excitons are comparable. By using the Langevin recombination theory, we derived the rate of recombination of dissociated free charges into their excitonic states. We found that in some organic polymers the probabilities of recombination of free charge carriers back into the singlet and triplet states are approximately 65.6 and 34.4 %, respectively, indicating that Langevin-type recombination into triplet excitons in organic semiconductors is less likely. This implies that the creation of triplet excitons may be advantageous in organic solar cells, because this may lead to dissociated free charge carriers that can be collected at their respective electrodes, which should result in better conversion efficiency.

  20. Fast Ice Detection for Wind Turbine Blades via the Langevin Equation

    NASA Astrophysics Data System (ADS)

    Fang, Haijun; Wang, Linpeng

    2016-09-01

    In this paper, a software-based algorithm for fast detection of ice on wind turbine blades is developed. The Langevin equation is used to create an entire or partial power curve with the high frequency data of wind speed and electrical power. Such a power curve is called the Langevin Power Curve (LPC). The LPC is obtained periodically. The period can be adjusted to be from 1 minute to 1 hour. For our application, the period is set to 5 minutes to allow enough data to generate an entire or partial LPC and then ice may be detected within a short period of time. The obtained LPC is compared to a reference power curve and then an ice index is calculated given that the condition for ice accretion is met. If the ice index is much higher or lower than 1, it may be concluded that there is ice on the anemometer or the blades of a wind turbine.

  1. Controlling Uncertainty: A Review of Human Behavior in Complex Dynamic Environments

    ERIC Educational Resources Information Center

    Osman, Magda

    2010-01-01

    Complex dynamic control (CDC) tasks are a type of problem-solving environment used for examining many cognitive activities (e.g., attention, control, decision making, hypothesis testing, implicit learning, memory, monitoring, planning, and problem solving). Because of their popularity, there have been many findings from diverse domains of research…

  2. Focusing on the Complexity of Emotion Issues in Academic Learning: A Dynamical Component Systems Approach

    ERIC Educational Resources Information Center

    Eynde, Peter Op 't; Turner, Jeannine E.

    2006-01-01

    Understanding the interrelations among students' cognitive, emotional, motivational, and volitional processes is an emergening focus in educational psychology. A dynamical, component systems theory of emotions is presented as a promising framework to further unravel these complex interrelations. This framework considers emotions to be a process…

  3. Detection of NAD(P)H-dependent enzyme activity with dynamic luminescence quenching of terbium complexes.

    PubMed

    Ito, Hiroki; Terai, Takuya; Hanaoka, Kenjiro; Ueno, Tasuku; Komatsu, Toru; Nagano, Tetsuo; Urano, Yasuteru

    2015-05-14

    We discovered that positively charged terbium complexes bearing 1,4,7,10-tetraazacyclododecane functionalized with amide ligands are highly sensitive to dynamic luminescence quenching by NAD(P)H. We exploited this phenomenon to establish a general time-resolved luminescence-based assay platform for sensitive detection of NAD(P)H-dependent enzyme activities.

  4. Trend Motif: A Graph Mining Approach for Analysis of Dynamic Complex Networks

    SciTech Connect

    Jin, R; McCallen, S; Almaas, E

    2007-05-28

    Complex networks have been used successfully in scientific disciplines ranging from sociology to microbiology to describe systems of interacting units. Until recently, studies of complex networks have mainly focused on their network topology. However, in many real world applications, the edges and vertices have associated attributes that are frequently represented as vertex or edge weights. Furthermore, these weights are often not static, instead changing with time and forming a time series. Hence, to fully understand the dynamics of the complex network, we have to consider both network topology and related time series data. In this work, we propose a motif mining approach to identify trend motifs for such purposes. Simply stated, a trend motif describes a recurring subgraph where each of its vertices or edges displays similar dynamics over a userdefined period. Given this, each trend motif occurrence can help reveal significant events in a complex system; frequent trend motifs may aid in uncovering dynamic rules of change for the system, and the distribution of trend motifs may characterize the global dynamics of the system. Here, we have developed efficient mining algorithms to extract trend motifs. Our experimental validation using three disparate empirical datasets, ranging from the stock market, world trade, to a protein interaction network, has demonstrated the efficiency and effectiveness of our approach.

  5. Embracing Connectedness and Change: A Complex Dynamic Systems Perspective for Applied Linguistic Research

    ERIC Educational Resources Information Center

    Cameron, Lynne

    2015-01-01

    Complex dynamic systems (CDS) theory offers a powerful metaphorical model of applied linguistic processes, allowing holistic descriptions of situated phenomena, and addressing the connectedness and change that often characterise issues in our field. A recent study of Kenyan conflict transformation illustrates application of a CDS perspective. Key…

  6. Phase Transitions in Development of Writing Fluency from a Complex Dynamic Systems Perspective

    ERIC Educational Resources Information Center

    Baba, Kyoko; Nitta, Ryo

    2014-01-01

    This study explored patterns in L2 writing development by focusing on one of the linguistic features of texts (fluency) from a complex dynamic systems perspective. It investigated whether two English-as-a-foreign-language university students would experience discontinuous change (phase transition) in their writing fluency through repetition of a…

  7. Environmental Factors Affecting Computer Assisted Language Learning Success: A Complex Dynamic Systems Conceptual Model

    ERIC Educational Resources Information Center

    Marek, Michael W.; Wu, Wen-Chi Vivian

    2014-01-01

    This conceptual, interdisciplinary inquiry explores Complex Dynamic Systems as the concept relates to the internal and external environmental factors affecting computer assisted language learning (CALL). Based on the results obtained by de Rosnay ["World Futures: The Journal of General Evolution", 67(4/5), 304-315 (2011)], who observed…

  8. Dynamical analysis of tRNA Gln-GlnRS complex using normal mode calculation

    NASA Astrophysics Data System (ADS)

    Nakamura, Shugo; Ikeguchi, Mitsunori; Shimizu, Kentaro

    2003-04-01

    We applied normal mode calculation in internal coordinates to a complex of glutamine transfer RNA (tRNA Gln) and glutaminyl-tRNA synthetase (GlnRS). Calculated deviations of atoms agreed well with those obtained from X-ray data. The differences of motions corresponding to low mode frequencies between the free state and the complex state were analyzed. For GlnRS, many motions in the free state were conserved in the complex state, while the dynamics of tRNA Gln was largely affected by the complex formation. Superimposed images of the conserved and non-conserved motions of tRNA Gln clearly indicated the restricted direction of motions in the complex.

  9. Game theory and extremal optimization for community detection in complex dynamic networks.

    PubMed

    Lung, Rodica Ioana; Chira, Camelia; Andreica, Anca

    2014-01-01

    The detection of evolving communities in dynamic complex networks is a challenging problem that recently received attention from the research community. Dynamics clearly add another complexity dimension to the difficult task of community detection. Methods should be able to detect changes in the network structure and produce a set of community structures corresponding to different timestamps and reflecting the evolution in time of network data. We propose a novel approach based on game theory elements and extremal optimization to address dynamic communities detection. Thus, the problem is formulated as a mathematical game in which nodes take the role of players that seek to choose a community that maximizes their profit viewed as a fitness function. Numerical results obtained for both synthetic and real-world networks illustrate the competitive performance of this game theoretical approach.

  10. Probing excited state charge transfer dynamics in a heteroleptic ruthenium complex.

    PubMed

    Ghosh, Rajib; Palit, Dipak K

    2014-01-01

    Dynamics of metal to ligand charge transfer in the excited states of ruthenium polypyridyl complexes, which have shown promise as materials for artificial solar energy harvesting, has been of immense interest recently. Mixed ligand complexes are especially important for broader absorption in the visible region. Dynamics of ultrafast vibrational energy relaxation and inter-ligand charge transfer processes in the excited states of a heteroleptic ruthenium complex, [Ru(bpy)2(pap)](ClO4)2 (where bpy is 2,2'-bipyridine and pap is 2-(phenylazo)pyridine) have been investigated using femtosecond to nanosecond time-resolved transient absorption spectroscopic techniques. A good agreement between the TA spectrum of the lowest excited (3)MLCT state of [Ru(bpy)2(pap)](ClO4)2 complex and the anion radical spectrum of the pap ligand, which has been generated using the pulse radiolysis technique, confirmed the charge localization at the pap ligand. While the lifetime of the inter-ligand charge transfer from the bpy to the pap ligand in the (3)MLCT state is about 2.5 ps, vibrational cooling of the pap-localized(3)MLCT state occurs over a much longer time scale with a lifetime of about 35 ps. Ultrafast charge localization dynamics observed here may have important consequences in artificial solar energy harvesting systems, which employ heteroleptic ruthenium complexes. PMID:24247908

  11. Deciphering deterioration mechanisms of complex diseases based on the construction of dynamic networks and systems analysis

    NASA Astrophysics Data System (ADS)

    Li, Yuanyuan; Jin, Suoqin; Lei, Lei; Pan, Zishu; Zou, Xiufen

    2015-03-01

    The early diagnosis and investigation of the pathogenic mechanisms of complex diseases are the most challenging problems in the fields of biology and medicine. Network-based systems biology is an important technique for the study of complex diseases. The present study constructed dynamic protein-protein interaction (PPI) networks to identify dynamical network biomarkers (DNBs) and analyze the underlying mechanisms of complex diseases from a systems level. We developed a model-based framework for the construction of a series of time-sequenced networks by integrating high-throughput gene expression data into PPI data. By combining the dynamic networks and molecular modules, we identified significant DNBs for four complex diseases, including influenza caused by either H3N2 or H1N1, acute lung injury and type 2 diabetes mellitus, which can serve as warning signals for disease deterioration. Function and pathway analyses revealed that the identified DNBs were significantly enriched during key events in early disease development. Correlation and information flow analyses revealed that DNBs effectively discriminated between different disease processes and that dysfunctional regulation and disproportional information flow may contribute to the increased disease severity. This study provides a general paradigm for revealing the deterioration mechanisms of complex diseases and offers new insights into their early diagnoses.

  12. The influence of piezoceramic stack location on nonlinear behavior of Langevin transducers.

    PubMed

    Mathieson, Andrew; Cardoni, Andrea; Cerisola, Niccolò; Lucas, Margaret

    2013-06-01

    Power ultrasonic applications such as cutting, welding, and sonochemistry often use Langevin transducers to generate power ultrasound. Traditionally, it has been proposed that the piezoceramic stack of a Langevin transducer should be located in the nodal plane of the longitudinal mode of vibration, ensuring that the piezoceramic elements are positioned under a uniform stress during transducer operation, maximizing element efficiency and minimizing piezoceramic aging. However, this general design rule is often partially broken during the design phase if features such as a support flange or multiple piezoceramic stacks are incorporated into the transducer architecture. Meanwhile, it has also been well documented in the literature that power ultrasonic devices driven at high excitation levels exhibit nonlinear behaviors similar to those observed in Duffing-type systems, such as resonant frequency shifts, the jump phenomenon, and hysteretic regions. This study investigates three Langevin transducers with different piezoceramic stack locations by characterizing their linear and nonlinear vibrational responses to understand how the stack location influences nonlinear behavior. PMID:25004475

  13. The influence of piezoceramic stack location on nonlinear behavior of Langevin transducers.

    PubMed

    Mathieson, Andrew; Cardoni, Andrea; Cerisola, Niccolò; Lucas, Margaret

    2013-06-01

    Power ultrasonic applications such as cutting, welding, and sonochemistry often use Langevin transducers to generate power ultrasound. Traditionally, it has been proposed that the piezoceramic stack of a Langevin transducer should be located in the nodal plane of the longitudinal mode of vibration, ensuring that the piezoceramic elements are positioned under a uniform stress during transducer operation, maximizing element efficiency and minimizing piezoceramic aging. However, this general design rule is often partially broken during the design phase if features such as a support flange or multiple piezoceramic stacks are incorporated into the transducer architecture. Meanwhile, it has also been well documented in the literature that power ultrasonic devices driven at high excitation levels exhibit nonlinear behaviors similar to those observed in Duffing-type systems, such as resonant frequency shifts, the jump phenomenon, and hysteretic regions. This study investigates three Langevin transducers with different piezoceramic stack locations by characterizing their linear and nonlinear vibrational responses to understand how the stack location influences nonlinear behavior.

  14. Langevin equation modeling of convective boundary layer dispersion assuming homogeneous, skewed turbulence

    SciTech Connect

    Hasstrom, J.S.; Ermak, D.L.

    1997-10-01

    Vertical dispersion of material in the convective boundary layer, CBL, is dramatically different than in natural or stable boundary layers, as has been shown by field and laboratory experiments. Lagrangian stochastic modeling based on the Langevin equation has been shown to be useful for simulating vertical dispersion in the CBL. This modeling approach can account for the effects of the long Lagrangian time scales (associated with large-scale turbulent structures), skewed vertical velocity distributions, and vertically inhomogeneous turbulent properties found in the CBL. It has been recognized that simplified Langevin equation models that assume skewed but homogeneous velocity statistics can capture the important aspects of dispersion from sources the the CBL. The assumption of homogeneous turbulence has a significant practical advantage, specifically, longer time steps can be used in numerical simulations. In this paper, we compare two Langevin equations models that use the homogeneous turbulence assumption. We also compare and evaluate three reflection boundary conditions, the method for determining a new velocity for a particle that encounters a boundary. Model results are evaluated using data from Willis and Deardorff`s laboratory experiments for three different source heights.

  15. Escaping the flatlands: new approaches for studying the dynamic assembly and activation of GPCR signaling complexes.

    PubMed

    Huber, Thomas; Sakmar, Thomas P

    2011-07-01

    Despite significant recent advances in molecular and structural studies of G protein-coupled receptors (GPCRs), an understanding of transmembrane signal transduction with chemical precision requires new approaches. Simple binary receptor-ligand or receptor-G protein complex models cannot adequately describe the relevant macromolecular signaling machineries. GPCR signalosomes undergo complex dynamic assembly-disassembly reactions to create allosteric signaling conduits whose properties cannot necessarily be predicted from individual elements alone. The combinatorial possibilities inherent in a system with hundreds of potential components suggest that high-content miniaturized experimental platforms and computational approaches will be required. To study allosteric effects involved in signalosome reaction pathways, a bottom-up approach using multicolor single-molecule detection fluorescence experiments in biochemically defined systems and complemented by molecular dynamics models of macromolecular complexes is proposed. In bridging the gap between molecular and systems biology, this synthetic approach suggests a way forward from the flatlands to multi-dimensional data collection.

  16. Dissociation of a Dynamic Protein Complex Studied by All-Atom Molecular Simulations.

    PubMed

    Zhang, Liqun; Borthakur, Susmita; Buck, Matthias

    2016-02-23

    The process of protein complex dissociation remains to be understood at the atomic level of detail. Computers now allow microsecond timescale molecular-dynamics simulations, which make the visualization of such processes possible. Here, we investigated the dissociation process of the EphA2-SHIP2 SAM-SAM domain heterodimer complex using unrestrained all-atom molecular-dynamics simulations. Previous studies on this system have shown that alternate configurations are sampled, that their interconversion can be fast, and that the complex is dynamic by nature. Starting from different NMR-derived structures, mutants were designed to stabilize a subset of configurations by swapping ion pairs across the protein-protein interface. We focused on two mutants, K956D/D1235K and R957D/D1223R, with attenuated binding affinity compared with the wild-type proteins. In contrast to calculations on the wild-type complexes, the majority of simulations of these mutants showed protein dissociation within 2.4 μs. During the separation process, we observed domain rotation and pivoting as well as a translation and simultaneous rolling, typically to alternate and weaker binding interfaces. Several unsuccessful recapturing attempts occurred once the domains were moderately separated. An analysis of protein solvation suggests that the dissociation process correlates with a progressive loss of protein-protein contacts. Furthermore, an evaluation of internal protein dynamics using quasi-harmonic and order parameter analyses indicates that changes in protein internal motions are expected to contribute significantly to the thermodynamics of protein dissociation. Considering protein association as the reverse of the separation process, the initial role of charged/polar interactions is emphasized, followed by changes in protein and solvent dynamics. The trajectories show that protein separation does not follow a single distinct pathway, but suggest that the mechanism of dissociation is common in

  17. Characteristics of crystallization of complex plasmas in narrow channels

    SciTech Connect

    Klumov, B. A. Morfill, G. E.

    2008-11-15

    Molecular dynamics simulations are performed to analyze the dependence of the behavior of complex (dusty) plasmas in narrow three-dimensional channels on the confining potential. Dynamics of micrometer-sized particles is modeled by using Langevin thermostat and Yukawa (screened Coulomb) pair interaction potential. A detailed analysis shows that confinement strongly affects plasma crystallization characteristics and local ordering of dust grains. In particular, the formation of a new, quasi-crystalline phase induced by hard-wall confinement is revealed. Transitions between different lattice symmetries induced by changes in channel width are examined. Strong dependence of the transverse dust density profile on the shielding parameter (ratio between mean interparticle distance and screening length) can be used to manipulate the dust-grain flux in such a system.

  18. Complex Rotation Quantum Dynamic Neural Networks (CRQDNN) using Complex Quantum Neuron (CQN): Applications to time series prediction.

    PubMed

    Cui, Yiqian; Shi, Junyou; Wang, Zili

    2015-11-01

    Quantum Neural Networks (QNN) models have attracted great attention since it innovates a new neural computing manner based on quantum entanglement. However, the existing QNN models are mainly based on the real quantum operations, and the potential of quantum entanglement is not fully exploited. In this paper, we proposes a novel quantum neuron model called Complex Quantum Neuron (CQN) that realizes a deep quantum entanglement. Also, a novel hybrid networks model Complex Rotation Quantum Dynamic Neural Networks (CRQDNN) is proposed based on Complex Quantum Neuron (CQN). CRQDNN is a three layer model with both CQN and classical neurons. An infinite impulse response (IIR) filter is embedded in the Networks model to enable the memory function to process time series inputs. The Levenberg-Marquardt (LM) algorithm is used for fast parameter learning. The networks model is developed to conduct time series predictions. Two application studies are done in this paper, including the chaotic time series prediction and electronic remaining useful life (RUL) prediction. PMID:26277609

  19. Extending and expanding the Darwinian synthesis: the role of complex systems dynamics.

    PubMed

    Weber, Bruce H

    2011-03-01

    Darwinism is defined here as an evolving research tradition based upon the concepts of natural selection acting upon heritable variation articulated via background assumptions about systems dynamics. Darwin's theory of evolution was developed within a context of the background assumptions of Newtonian systems dynamics. The Modern Evolutionary Synthesis, or neo-Darwinism, successfully joined Darwinian selection and Mendelian genetics by developing population genetics informed by background assumptions of Boltzmannian systems dynamics. Currently the Darwinian Research Tradition is changing as it incorporates new information and ideas from molecular biology, paleontology, developmental biology, and systems ecology. This putative expanded and extended synthesis is most perspicuously deployed using background assumptions from complex systems dynamics. Such attempts seek to not only broaden the range of phenomena encompassed by the Darwinian Research Tradition, such as neutral molecular evolution, punctuated equilibrium, as well as developmental biology, and systems ecology more generally, but to also address issues of the emergence of evolutionary novelties as well as of life itself.

  20. Optimal dimensionality reduction of complex dynamics: The chess game as diffusion on a free-energy landscape

    NASA Astrophysics Data System (ADS)

    Krivov, Sergei V.

    2011-07-01

    Dimensionality reduction is ubiquitous in the analysis of complex dynamics. The conventional dimensionality reduction techniques, however, focus on reproducing the underlying configuration space, rather than the dynamics itself. The constructed low-dimensional space does not provide a complete and accurate description of the dynamics. Here I describe how to perform dimensionality reduction while preserving the essential properties of the dynamics. The approach is illustrated by analyzing the chess game—the archetype of complex dynamics. A variable that provides complete and accurate description of chess dynamics is constructed. The winning probability is predicted by describing the game as a random walk on the free-energy landscape associated with the variable. The approach suggests a possible way of obtaining a simple yet accurate description of many important complex phenomena. The analysis of the chess game shows that the approach can quantitatively describe the dynamics of processes where human decision-making plays a central role, e.g., financial and social dynamics.