Localised distributions and criteria for correctness in complex Langevin dynamics
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.
The complex chemical Langevin equation
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.
The complex chemical Langevin equation.
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.
NASA Astrophysics Data System (ADS)
Kong, Wei; Yang, Fang; Liu, Songfen; Shi, Feng
2016-10-01
A Langevin dynamics simulation method is used to study the two-dimensional (2D) equilibrium structure of complex plasmas while considering an external magnetic field. The traditional Yukawa potential and a modified Yukawa potential according to Shukla et al. [Phys. Lett. A 291, 413 (2001); Shukla and Mendonca, Phys. Scr. T113 82 (2004)] and Salimullah et al. [Phys. Plasmas 10, 3047 (2003)] respectively, are employed to account for the interaction of the charged dust particles. It is found that the collisions between neutral gas and charged dust particles have minor effects on the 2D equilibrium structure of the system. Based on the modified Yukawa potential, studies on the 2D equilibrium structure show that the traditional Yukawa potential is still suitable for describing the magnetized complex plasmas, even if the shielding distance of charged dust particles is affected by the strong external magnetic field.
Efficient Algorithms for Langevin and DPD Dynamics.
Goga, N; Rzepiela, A J; de Vries, A H; Marrink, S J; Berendsen, H J C
2012-10-09
In this article, we present several algorithms for stochastic dynamics, including Langevin dynamics and different variants of Dissipative Particle Dynamics (DPD), applicable to systems with or without constraints. The algorithms are based on the impulsive application of friction and noise, thus avoiding the computational complexity of algorithms that apply continuous friction and noise. Simulation results on thermostat strength and diffusion properties for ideal gas, coarse-grained (MARTINI) water, and constrained atomic (SPC/E) water systems are discussed. We show that the measured thermal relaxation rates agree well with theoretical predictions. The influence of various parameters on the diffusion coefficient is discussed.
Applications of Langevin and Molecular Dynamics methods
NASA Astrophysics Data System (ADS)
Lomdahl, P. S.
Computer simulation of complex nonlinear and disordered phenomena from materials science is rapidly becoming an active and new area serving as a guide for experiments and for testing of theoretical concepts. This is especially true when novel massively parallel computer systems and techniques are used on these problems. In particular the Langevin dynamics simulation technique has proven useful in situations where the time evolution of a system in contact with a heat bath is to be studied. The traditional way to study systems in contact with a heat bath has been via the Monte Carlo method. While this method has indeed been used successfully in many applications, it has difficulty addressing true dynamical questions. Large systems of coupled stochastic ODE's (or Langevin equations) are commonly the end result of a theoretical description of higher dimensional nonlinear systems in contact with a heat bath. The coupling is often local in nature, because it reflects local interactions formulated on a lattice, the lattice for example represents the underlying discreteness of a substrate of atoms or discrete k-values in Fourier space. The fundamental unit of parallelism thus has a direct analog in the physical system the authors are interested in. In these lecture notes the authors illustrate the use of Langevin stochastic simulation techniques on a number of nonlinear problems from materials science and condensed matter physics that have attracted attention in recent years. First, the authors review the idea behind the fluctuation-dissipation theorem which forms that basis for the numerical Langevin stochastic simulation scheme. The authors then show applications of the technique to various problems from condensed matter and materials science.
Langevin thermostat for rigid body dynamics.
Davidchack, Ruslan L; Handel, Richard; Tretyakov, M V
2009-06-21
We present a new method for isothermal rigid body simulations using the quaternion representation and Langevin dynamics. It can be combined with the traditional Langevin or gradient (Brownian) dynamics for the translational degrees of freedom to correctly sample the canonical distribution in a simulation of rigid molecules. We propose simple, quasisymplectic second-order numerical integrators and test their performance on the TIP4P model of water. We also investigate the optimal choice of thermostat parameters.
Global Langevin model of multidimensional biomolecular dynamics
NASA Astrophysics Data System (ADS)
Schaudinnus, Norbert; Lickert, Benjamin; Biswas, Mithun; Stock, Gerhard
2016-11-01
Molecular dynamics simulations of biomolecular processes are often discussed in terms of diffusive motion on a low-dimensional free energy landscape F ( 𝒙 ) . To provide a theoretical basis for this interpretation, one may invoke the system-bath ansatz á la Zwanzig. That is, by assuming a time scale separation between the slow motion along the system coordinate x and the fast fluctuations of the bath, a memory-free Langevin equation can be derived that describes the system's motion on the free energy landscape F ( 𝒙 ) , which is damped by a friction field and driven by a stochastic force that is related to the friction via the fluctuation-dissipation theorem. While the theoretical formulation of Zwanzig typically assumes a highly idealized form of the bath Hamiltonian and the system-bath coupling, one would like to extend the approach to realistic data-based biomolecular systems. Here a practical method is proposed to construct an analytically defined global model of structural dynamics. Given a molecular dynamics simulation and adequate collective coordinates, the approach employs an "empirical valence bond"-type model which is suitable to represent multidimensional free energy landscapes as well as an approximate description of the friction field. Adopting alanine dipeptide and a three-dimensional model of heptaalanine as simple examples, the resulting Langevin model is shown to reproduce the results of the underlying all-atom simulations. Because the Langevin equation can also be shown to satisfy the underlying assumptions of the theory (such as a delta-correlated Gaussian-distributed noise), the global model provides a correct, albeit empirical, realization of Zwanzig's formulation. As an application, the model can be used to investigate the dependence of the system on parameter changes and to predict the effect of site-selective mutations on the dynamics.
New Langevin and gradient thermostats for rigid body dynamics.
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.
Parametrizing linear generalized Langevin dynamics from explicit molecular dynamics simulations
NASA Astrophysics Data System (ADS)
Gottwald, Fabian; Karsten, Sven; Ivanov, Sergei D.; Kühn, Oliver
2015-06-01
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.
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.
Complex Langevin method: When can it be trusted?
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.
The notion of error in Langevin dynamics. I. Linear analysis
NASA Astrophysics Data System (ADS)
Mishra, Bimal; Schlick, Tamar
1996-07-01
The notion of error in practical molecular and Langevin dynamics simulations of large biomolecules is far from understood because of the relatively large value of the timestep used, the short simulation length, and the low-order methods employed. We begin to examine this issue with respect to equilibrium and dynamic time-correlation functions by analyzing the behavior of selected implicit and explicit finite-difference algorithms for the Langevin equation. We derive: local stability criteria for these integrators; analytical expressions for the averages of the potential, kinetic, and total energy; and various limiting cases (e.g., timestep and damping constant approaching zero), for a system of coupled harmonic oscillators. These results are then compared to the corresponding exact solutions for the continuous problem, and their implications to molecular dynamics simulations are discussed. New concepts of practical and theoretical importance are introduced: scheme-dependent perturbative damping and perturbative frequency functions. Interesting differences in the asymptotic behavior among the algorithms become apparent through this analysis, and two symplectic algorithms, ``LIM2'' (implicit) and ``BBK'' (explicit), appear most promising on theoretical grounds. One result of theoretical interest is that for the Langevin/implicit-Euler algorithm (``LI'') there exist timesteps for which there is neither numerical damping nor shift in frequency for a harmonic oscillator. However, this idea is not practical for more complex systems because these special timesteps can account only for one frequency of the system, and a large damping constant is required. We therefore devise a more practical, delay-function approach to remove the artificial damping and frequency perturbation from LI. Indeed, a simple MD implementation for a system of coupled harmonic oscillators demonstrates very satisfactory results in comparison with the velocity-Verlet scheme. We also define a
Schrödinger-Langevin equation with quantum trajectories for photodissociation dynamics
NASA Astrophysics Data System (ADS)
Chou, Chia-Chun
2017-02-01
The Schrödinger-Langevin equation is integrated to study the wave packet dynamics of quantum systems subject to frictional effects by propagating an ensemble of quantum trajectories. The equations of motion for the complex action and quantum trajectories are derived from the Schrödinger-Langevin equation. The moving least squares approach is used to evaluate the spatial derivatives of the complex action required for the integration of the equations of motion. Computational results are presented and analyzed for the evolution of a free Gaussian wave packet, a two-dimensional barrier model, and the photodissociation dynamics of NOCl. The absorption spectrum of NOCl obtained from the Schrödinger-Langevin equation displays a redshift when frictional effects increase. This computational result agrees qualitatively with the experimental results in the solution-phase photochemistry of NOCl.
Does the complex Langevin method give unbiased results?
NASA Astrophysics Data System (ADS)
Salcedo, L. L.
2016-12-01
We investigate whether the stationary solution of the Fokker-Planck equation of the complex Langevin algorithm reproduces the correct expectation values. When the complex Langevin algorithm for an action S (x ) is convergent, it produces an equivalent complex probability distribution P (x ) which ideally would coincide with e-S (x ). We show that the projected Fokker-Planck equation fulfilled by P (x ) may contain an anomalous term whose form is made explicit. Such a term spoils the relation P (x )=e-S (x ), introducing a bias in the expectation values. Through the analysis of several periodic and nonperiodic one-dimensional problems, using either exact or numerical solutions of the Fokker-Planck equation on the complex plane, it is shown that the anomaly is present quite generally. In fact, an anomaly is expected whenever the Langevin walker needs only a finite time to go to infinity and come back, and this is the case for typical actions. We conjecture that the anomaly is the rule rather than the exception in the one-dimensional case; however, this could change as the number of variables involved increases.
Accurate Langevin approaches to simulate Markovian channel dynamics
NASA Astrophysics Data System (ADS)
Huang, Yandong; Rüdiger, Sten; Shuai, Jianwei
2015-12-01
The stochasticity of ion-channels dynamic is significant for physiological processes on neuronal cell membranes. Microscopic simulations of the ion-channel gating with Markov chains can be considered to be an accurate standard. However, such Markovian simulations are computationally demanding for membrane areas of physiologically relevant sizes, which makes the noise-approximating or Langevin equation methods advantageous in many cases. In this review, we discuss the Langevin-like approaches, including the channel-based and simplified subunit-based stochastic differential equations proposed by Fox and Lu, and the effective Langevin approaches in which colored noise is added to deterministic differential equations. In the framework of Fox and Lu’s classical models, several variants of numerical algorithms, which have been recently developed to improve accuracy as well as efficiency, are also discussed. Through the comparison of different simulation algorithms of ion-channel noise with the standard Markovian simulation, we aim to reveal the extent to which the existing Langevin-like methods approximate results using Markovian methods. Open questions for future studies are also discussed.
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.
Langevin dynamics of financial systems: A second-order analysis
NASA Astrophysics Data System (ADS)
Canessa, E.
2001-07-01
We address the issue of stock market fluctuations within Langevin Dynamics (LD) and the thermodynamics definitions of multifractality in order to study its second-order characterization given by the analogous specific heat Cq, where q is an analogous temperature relating the moments of the generating partition function for the financial data signals. Due to non-linear and additive noise terms within the LD, we found that Cq can display a shoulder to the right of its main peak as also found in the S&P500 historical data which may resemble a classical phase transition at a critical point.
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.
Langevin Dynamics Simulations of Genome Packing in Bacteriophage
Forrey, Christopher; Muthukumar, M.
2006-01-01
We use Langevin dynamics simulations to study the process by which a coarse-grained DNA chain is packaged within an icosahedral container. We focus our inquiry on three areas of interest in viral packing: the evolving structure of the packaged DNA condensate; the packing velocity; and the internal buildup of energy and resultant forces. Each of these areas has been studied experimentally, and we find that we can qualitatively reproduce experimental results. However, our findings also suggest that the phage genome packing process is fundamentally different than that suggested by the inverse spool model. We suggest that packing in general does not proceed in the deterministic fashion of the inverse-spool model, but rather is stochastic in character. As the chain configuration becomes compressed within the capsid, the structure, energy, and packing velocity all become dependent upon polymer dynamics. That many observed features of the packing process are rooted in condensed-phase polymer dynamics suggests that statistical mechanics, rather than mechanics, should serve as the proper theoretical basis for genome packing. Finally we suggest that, as a result of an internal protein unique to bacteriophage T7, the T7 genome may be significantly more ordered than is true for bacteriophage in general. PMID:16617089
The derivation and approximation of coarse-grained dynamics from Langevin dynamics
NASA Astrophysics Data System (ADS)
Ma, Lina; Li, Xiantao; Liu, Chun
2016-11-01
We present a derivation of a coarse-grained description, in the form of a generalized Langevin equation, from the Langevin dynamics model that describes the dynamics of bio-molecules. The focus is placed on the form of the memory kernel function, the colored noise, and the second fluctuation-dissipation theorem that connects them. Also presented is a hierarchy of approximations for the memory and random noise terms, using rational approximations in the Laplace domain. These approximations offer increasing accuracy. More importantly, they eliminate the need to evaluate the integral associated with the memory term at each time step. Direct sampling of the colored noise can also be avoided within this framework. Therefore, the numerical implementation of the generalized Langevin equation is much more efficient.
Langevin dynamics of a heavy particle and orthogonality effects
NASA Astrophysics Data System (ADS)
Thomas, Mark; Karzig, Torsten; Viola Kusminskiy, Silvia
2015-12-01
The dynamics of a classical heavy particle moving in a quantum environment is determined by a Langevin equation which encapsulates the effect of the environment-induced reaction forces on the particle. For an open quantum system, these include a Born-Oppenheimer force, a dissipative force, and a stochastic force due to shot and thermal noise. Recently, it was shown that these forces can be expressed in terms of the scattering matrix of the system by considering the classical heavy particle as a time-dependent scattering center, allowing to demonstrate interesting features of these forces when the system is driven out of equilibrium. At the same time, it is well known that small changes in a scattering potential can have a profound impact on a fermionic system due to the Anderson orthogonality catastrophe. In this work, by calculating the Loschmidt echo, we relate Anderson orthogonality effects with the mesoscopic reaction forces for an environment that can be taken out of equilibrium. In particular, we show how the decay of the Loschmidt echo is characterized by fluctuations and dissipation in the system and discuss different quench protocols.
Scaling of Langevin and molecular dynamics persistence times of nonhomogeneous fluids.
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.
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.
Argument for justification of the complex Langevin method and the condition for correct convergence
NASA Astrophysics Data System (ADS)
Nagata, Keitaro; Nishimura, Jun; Shimasaki, Shinji
2016-12-01
The complex Langevin method is a promising approach to the complex-action problem based on a fictitious time evolution of complexified dynamical variables under the influence of a Gaussian noise. Although it is known to have a restricted range of applicability, the use of gauge cooling made it applicable to various interesting cases including finite density QCD in certain parameter regions. In this paper we revisit the argument for justification of the method. In particular, we point out a subtlety in the use of time-evolved observables, which play a crucial role in the previous argument. This requires that the probability of the drift term should fall off exponentially or faster at large magnitude. We argue that this is actually a necessary and sufficient condition for the method to be justified. Using two simple examples, we show that our condition tells us clearly whether the results obtained by the method are trustable or not. We also discuss a new possibility for the gauge cooling, which can reduce the magnitude of the drift term directly.
A simple and accurate algorithm for path integral molecular dynamics with the Langevin thermostat.
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.
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.
Langevin dynamics for vector variables driven by multiplicative white noise: A functional formalism.
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.
Dynamics of the solvent around a solute: generalized Langevin theory.
Ishizuka, R; Hirata, F
2010-01-01
The generalized Langevin theory for a solution has been derived as the infinite dilution limit of the theory for a two component mixture. Following a similar formalism, the mode coupling approximations of the memory kernel have been also obtained. We have applied this method for one component bulk liquid of Lennard-Jones spheres and proved this approximation theoretically. The analysis of the space and time pair correlation proposed by Van Hove has been carried out as a function of solute particle sizes. It is found that the size of the solute particle is deeply related to the relaxation process of the solvation structure characterized around a solute particle at equilibrium. We have also investigated the relation between the different thermodynamic environments and relaxation process. From these studies, we have obtained the useful information about the rapidity of the relaxation of the solvation structure around a solute at equilibrium.
Vulnerability in Popular Molecular Dynamics Packages Concerning Langevin and Andersen Dynamics
Cerutti, David S.; Duke, Robert; Freddolino, Peter L.; Fan, Hao; Lybrand, Terry P.
2008-01-01
We report a serious problem associated with a number of current implementations of Andersen and Langevin dynamics algorithms. When long simulations are run in many segments, it is sometimes possible to have a repeating sequence of pseudorandom numbers enter the calcuation. We show that, if the sequence repeats rapidly, the resulting artifacts can quickly denature biomolecules and are then easily detectable. However, if the sequence repeats less frequently, the artifacts become subtle and easily overlooked. We derive a formula for the underlying cause of artifacts in the case of the Langevin thermostat, and find it vanishes slowly as the inverse square root of the number of time steps per simulation segment. Numerous examples of simulation artifacts are presented, including dissociation of a tetrameric protein after 110 ns of dynamics, reductions in atomic fluctuations for a small protein in implicit solvent, altered thermodynamic properties of a box of water molecules, and changes in the transition free energies between dihedral angle conformations. Finally, in the case of strong thermocoupling, we link the observed artifacts to previous work in nonlinear dynamics and show that it is possible to drive a 20-residue, implicitly solvated protein into periodic trajectories if the thermostat is not used properly. Our findings should help other investigators re-evaluate simulations that may have been corrupted and obtain more accurate results. PMID:19180249
Molecular Dynamics, Monte Carlo Simulations, and Langevin Dynamics: A Computational Review
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
NASA Astrophysics Data System (ADS)
Ito, Yuta; Nishimura, Jun
2016-12-01
In many interesting physical systems, the determinant which appears from integrating out fermions becomes complex, and its phase plays a crucial role in the deter-mination of the vacuum. An example of this is QCD at low temperature and high density, where various exotic fermion condensates are conjectured to form. Another example is the Euclidean version of the type IIB matrix model for 10d superstring theory, where spontaneous breaking of the SO(10) rotational symmetry down to SO(4) is expected to occur. When one applies the complex Langevin method to these systems, one encounters the singular-drift problem associated with the appearance of nearly zero eigenvalues of the Dirac operator. Here we propose to avoid this problem by deforming the action with a fermion bilinear term. The results for the original system are obtained by extrapolations with respect to the deformation parameter. We demonstrate the power of this approach by applying it to a simple matrix model, in which spontaneous symmetry breaking from SO(4) to SO(2) is expected to occur due to the phase of the complex fermion determinant. Unlike previous work based on a reweighting-type method, we are able to determine the true vacuum by calculating the order parameters, which agree with the prediction by the Gaussian expansion method.
Dynamical consequences of a constraint on the Langevin thermostat in molecular cluster simulation
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.
A Langevin dynamics study of mobile filler particles in phase-separating binary systems
NASA Astrophysics Data System (ADS)
Laradji, Mohamed
2004-05-01
The dynamics of phase separation in a simple binary mixture containing mobile filler particles that are preferentially wet by one of the two components is investigated systematically via Langevin simulations in two dimensions. We found that while the filler particles reduce the growth rate of spinodal decomposition, the domain growth remains essentially identical to that of the pure binary mixture. The growth rate diminishes as either the filler particles concentration is increased or their diffusivity is decreased.
On extremals of the entropy production by ‘Langevin-Kramers’ dynamics
NASA Astrophysics Data System (ADS)
Muratore-Ginanneschi, Paolo
2014-05-01
We refer as ‘Langevin-Kramers’ dynamics to a class of stochastic differential systems exhibiting a degenerate ‘metriplectic’ structure. This means that the drift field can be decomposed into a symplectic and a gradient-like component with respect to a pseudo-metric tensor associated with random fluctuations affecting increments of only a sub-set of the degrees of freedom. Systems in this class are often encountered in applications as elementary models of Hamiltonian dynamics in a heat bath eventually relaxing to a Boltzmann steady state. Entropy production control in Langevin-Kramers models differs from the now well-understood case of Langevin-Smoluchowski dynamics for two reasons. First, the definition of entropy production stemming from fluctuation theorems specifies a cost functional which does not act coercively on all degrees of freedom of control protocols. Second, the presence of a symplectic structure imposes a non-local constraint on the class of admissible controls. Using Pontryagin control theory and restricting the attention to additive noise, we show that smooth protocols attaining extremal values of the entropy production appear generically in continuous parametric families as a consequence of a trade-off between smoothness of the admissible protocols and non-coercivity of the cost functional. Uniqueness is, however, always recovered in the over-damped limit as extremal equations reduce at leading order to the Monge-Ampère-Kantorovich optimal mass-transport equations.
Langevin model of the temperature and hydration dependence of protein vibrational dynamics.
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.
Quantum Langevin approach for non-Markovian quantum dynamics of the spin-boson model
NASA Astrophysics Data System (ADS)
Zhou, Zheng-Yang; Chen, Mi; Yu, Ting; You, J. Q.
2016-02-01
One longstanding difficult problem in quantum dissipative dynamics is to solve the spin-boson model in a non-Markovian regime where a tractable systematic master equation does not exist. The spin-boson model is particularly important due to its crucial applications in quantum noise control and manipulation as well as its central role in developing quantum theories of open systems. Here we solve this important model by developing a non-Markovian quantum Langevin approach. By projecting the quantum Langevin equation onto the coherent states of the bath, we can derive a set of non-Markovian quantum Bloch equations containing no explicit noise variables. This special feature offers a tremendous advantage over the existing stochastic Schrödinger equations in numerical simulations. The physical significance and generality of our approach are briefly discussed.
A Langevin model for the Dynamic Contact Angle Parameterised Using Molecular Dynamics
NASA Astrophysics Data System (ADS)
Smith, Edward; Muller, Erich; Craster, Richard; Matar, Omar
2016-11-01
An understanding of droplet spreading is essential in a diverse range of applications, including coating processes, dip feed reactors, crop spraying and biomedical treatments such as surfactant replacement theory. The default modelling tools for engineering fluid dynamics assume that the continuum hypothesis is valid. The contact line motion is very difficult to capture in this paradigm and requires some form of closure model, often tuned a priori to experiments. Molecular dynamics (MD), by assuming only an inter-molecular potential, reproduces the full detail of the three-phase contact line with no additional modelling assumptions. This provides an ideal test-bed to understand contact line motion. In this talk, MD results for a sheared liquid bridge are presented. The evolution and fluctuations of the dynamic contact angle are paramterised over a range of wall sliding speeds and temperatures. A Langevin model is proposed to reproduce the fluctuations and evolution of the contact angle. Results from this model are compared to molecular simulation data showing excellent agreement. The potential applications of this model, as well as limitation and possible extensions, are discussed. EPSRC UK platform Grant MACIPh (EP/L020564/1).
Constant pressure and temperature discrete-time Langevin molecular dynamics
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.
Robust and efficient configurational molecular sampling via Langevin dynamics.
Leimkuhler, Benedict; Matthews, Charles
2013-05-07
A wide variety of numerical methods are evaluated and compared for solving the stochastic differential equations encountered in molecular dynamics. The methods are based on the application of deterministic impulses, drifts, and Brownian motions in some combination. The Baker-Campbell-Hausdorff expansion is used to study sampling accuracy following recent work by the authors, which allows determination of the stepsize-dependent bias in configurational averaging. For harmonic oscillators, configurational averaging is exact for certain schemes, which may result in improved performance in the modelling of biomolecules where bond stretches play a prominent role. For general systems, an optimal method can be identified that has very low bias compared to alternatives. In simulations of the alanine dipeptide reported here (both solvated and unsolvated), higher accuracy is obtained without loss of computational efficiency, while allowing large timestep, and with no impairment of the conformational exploration rate (the effective diffusion rate observed in simulation). The optimal scheme is a uniformly better performing algorithm for molecular sampling, with overall efficiency improvements of 25% or more in practical timestep size achievable in vacuum, and with reductions in the error of configurational averages of a factor of ten or more attainable in solvated simulations at large timestep.
Robust and efficient configurational molecular sampling via Langevin dynamics
NASA Astrophysics Data System (ADS)
Leimkuhler, Benedict; Matthews, Charles
2013-05-01
A wide variety of numerical methods are evaluated and compared for solving the stochastic differential equations encountered in molecular dynamics. The methods are based on the application of deterministic impulses, drifts, and Brownian motions in some combination. The Baker-Campbell-Hausdorff expansion is used to study sampling accuracy following recent work by the authors, which allows determination of the stepsize-dependent bias in configurational averaging. For harmonic oscillators, configurational averaging is exact for certain schemes, which may result in improved performance in the modelling of biomolecules where bond stretches play a prominent role. For general systems, an optimal method can be identified that has very low bias compared to alternatives. In simulations of the alanine dipeptide reported here (both solvated and unsolvated), higher accuracy is obtained without loss of computational efficiency, while allowing large timestep, and with no impairment of the conformational exploration rate (the effective diffusion rate observed in simulation). The optimal scheme is a uniformly better performing algorithm for molecular sampling, with overall efficiency improvements of 25% or more in practical timestep size achievable in vacuum, and with reductions in the error of configurational averages of a factor of ten or more attainable in solvated simulations at large timestep.
Chen, Minxin; Li, Xiantao; Liu, Chun
2014-08-14
We present a numerical method to approximate the memory functions in the generalized Langevin models for the collective dynamics of macromolecules. We first derive the exact expressions of the memory functions, obtained from projection to subspaces that correspond to the selection of coarse-grain variables. In particular, the memory functions are expressed in the forms of matrix functions, which will then be approximated by Krylov-subspace methods. It will also be demonstrated that the random noise can be approximated under the same framework, and the second fluctuation-dissipation theorem is automatically satisfied. The accuracy of the method is examined through several numerical examples.
Nonlinear Langevin model for the early-stage dynamics of electrospinning jets
NASA Astrophysics Data System (ADS)
Lauricella, Marco; Pontrelli, Giuseppe; Pisignano, Dario; Succi, Sauro
2015-09-01
We present a nonlinear Langevin model to investigate the early-stage dynamics of electrified polymer jets in electrospinning experiments. In particular, we study the effects of air drag force on the uniaxial elongation of the charged jet, right after ejection from the nozzle. Numerical simulations show that the elongation of the jet filament close to the injection point is significantly affected by the nonlinear drag exerted by the surrounding air. These results provide useful insights for the optimal design of current and future electrospinning experiments.
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:
Boedeker's effective theory: From Langevin dynamics to Dyson-Schwinger equations
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: (
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.
Langevin model for real-time Brownian dynamics of interacting nanodefects in irradiated metals
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.
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
A strong diffusive ion mode in dense ionized matter predicted by Langevin dynamics.
Mabey, P; Richardson, S; White, T G; Fletcher, L B; Glenzer, S H; Hartley, N J; Vorberger, J; Gericke, D O; Gregori, G
2017-01-30
The state and evolution of planets, brown dwarfs and neutron star crusts is determined by the properties of dense and compressed matter. Due to the inherent difficulties in modelling strongly coupled plasmas, however, current predictions of transport coefficients differ by orders of magnitude. Collective modes are a prominent feature, whose spectra may serve as an important tool to validate theoretical predictions for dense matter. With recent advances in free electron laser technology, X-rays with small enough bandwidth have become available, allowing the investigation of the low-frequency ion modes in dense matter. Here, we present numerical predictions for these ion modes and demonstrate significant changes to their strength and dispersion if dissipative processes are included by Langevin dynamics. Notably, a strong diffusive mode around zero frequency arises, which is not present, or much weaker, in standard simulations. Our results have profound consequences in the interpretation of transport coefficients in dense plasmas.
A strong diffusive ion mode in dense ionized matter predicted by Langevin dynamics
Mabey, Paul; Richardson, S.; White, T. G.; ...
2017-01-30
The state and evolution of planets, brown dwarfs and neutron star crusts is determined by the properties of dense and compressed matter. Due to the inherent difficulties in modelling strongly coupled plasmas, however, current predictions of transport coefficients differ by orders of magnitude. Collective modes are a prominent feature, whose spectra may serve as an important tool to validate theoretical predictions for dense matter. With recent advances in free electron laser technology, X-rays with small enough bandwidth have become available, allowing the investigation of the low-frequency ion modes in dense matter. Here, we present numerical predictions for these ion modesmore » and demonstrate significant changes to their strength and dispersion if dissipative processes are included by Langevin dynamics. Notably, a strong diffusive mode around zero frequency arises, which is not present, or much weaker, in standard simulations. Finally, our results have profound consequences in the interpretation of transport coefficients in dense plasmas.« less
Kinetics of formation of bile salt micelles from coarse-grained Langevin dynamics simulations.
Vila Verde, Ana; Frenkel, Daan
2016-06-21
We examine the mechanism of formation of micelles of dihydroxy bile salts using a coarse-grained, implicit solvent model and Langevin dynamics simulations. We find that bile salt micelles primarily form via addition and removal of monomers, similarly to surfactants with typical head-tail molecular structures, and not via a two-stage mechanism - involving formation of oligomers and their subsequent aggregation to form larger micelles - originally proposed for bile salts. The free energy barrier to removal of single bile monomers from micelles is ≈2kBT, much less than what has been observed for head-tail surfactants. Such a low barrier may be biologically relevant: it allows for rapid release of bile monomers into the intestine, possibly enabling the coverage of fat droplets by bile salt monomers and subsequent release of micelles containing fats and bile salts - a mechanism that is not possible for ionic head-tail surfactants of similar critical micellar concentrations.
A strong diffusive ion mode in dense ionized matter predicted by Langevin dynamics
Mabey, P.; Richardson, S.; White, T. G.; Fletcher, L. B.; Glenzer, S. H.; Hartley, N. J.; Vorberger, J.; Gericke, D. O.; Gregori, G.
2017-01-01
The state and evolution of planets, brown dwarfs and neutron star crusts is determined by the properties of dense and compressed matter. Due to the inherent difficulties in modelling strongly coupled plasmas, however, current predictions of transport coefficients differ by orders of magnitude. Collective modes are a prominent feature, whose spectra may serve as an important tool to validate theoretical predictions for dense matter. With recent advances in free electron laser technology, X-rays with small enough bandwidth have become available, allowing the investigation of the low-frequency ion modes in dense matter. Here, we present numerical predictions for these ion modes and demonstrate significant changes to their strength and dispersion if dissipative processes are included by Langevin dynamics. Notably, a strong diffusive mode around zero frequency arises, which is not present, or much weaker, in standard simulations. Our results have profound consequences in the interpretation of transport coefficients in dense plasmas. PMID:28134338
A strong diffusive ion mode in dense ionized matter predicted by Langevin dynamics
Mabey, P.; Richardson, S.; White, T. G.; ...
2017-01-30
We determined the state and evolution of planets, brown dwarfs and neutron star crusts by the properties of dense and compressed matter. Furthermore, due to the inherent difficulties in modelling strongly coupled plasmas, however, current predictions of transport coefficients differ by orders of magnitude. Collective modes are a prominent feature, whose spectra may serve as an important tool to validate theoretical predictions for dense matter. With recent advances in free electron laser technology, X-rays with small enough bandwidth have become available, allowing the investigation of the low-frequency ion modes in dense matter. Here, we present numerical predictions for these ionmore » modes and demonstrate significant changes to their strength and dispersion if dissipative processes are included by Langevin dynamics. Notably, a strong diffusive mode around zero frequency arises, which is not present, or much weaker, in standard simulations. These results have profound consequences in the interpretation of transport coefficients in dense plasmas.« less
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.
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.
A Langevin model for fluctuating contact angle behaviour parametrised using molecular dynamics.
Smith, E R; Müller, E A; Craster, R V; Matar, O K
2016-12-06
Molecular dynamics simulations are employed to develop a theoretical model to predict the fluid-solid contact angle as a function of wall-sliding speed incorporating thermal fluctuations. A liquid bridge between counter-sliding walls is studied, with liquid-vapour interface-tracking, to explore the impact of wall-sliding speed on contact angle. The behaviour of the macroscopic contact angle varies linearly over a range of capillary numbers beyond which the liquid bridge pinches off, a behaviour supported by experimental results. Nonetheless, the liquid bridge provides an ideal test case to study molecular scale thermal fluctuations, which are shown to be well described by Gaussian distributions. A Langevin model for contact angle is parametrised to incorporate the mean, fluctuation and auto-correlations over a range of sliding speeds and temperatures. The resulting equations can be used as a proxy for the fully-detailed molecular dynamics simulation allowing them to be integrated within a continuum-scale solver.
Wu, Xiongwu; Subramaniam, Sriram; Case, David A.; Wu, Katherine W.; Brooks, Bernard R.
2013-01-01
We present a map-restrained self-guided Langevin dynamics (MapSGLD) simulation method for efficient targeted conformational search. The targeted conformational search represents simulations under restraints defined by experimental observations and/or by user specified structural requirements. Through map-restraints, this method provides an efficient way to maintain substructures and to set structure targets during conformational searching. With an enhanced conformational searching ability of self-guided Langevin dynamics, this approach is suitable for simulating large-scale conformational changes, such as the formation of macromolecular assemblies and transitions between different conformational states. Using several examples, we illustrate the application of this method in flexible fitting of atomic structures into density maps from cryo-electron microscopy. PMID:23876978
Langevin dynamics simulations of ds-DNA translocation through synthetic nanopores
NASA Astrophysics Data System (ADS)
Forrey, Christopher; Muthukumar, M.
2007-07-01
We have implemented a coarse-grained model to study voltage-driven as-DNA translocation through nanopores located in synthetic membranes. The simulated trajectory of the DNA through the nanopores was calculated using Langevin dynamics. We present the results based on more than 120 000 individual translocations. We are particularly interested in this work in probing the physical basis of various experimentally observed—yet poorly understood—phenomena. Notably, we observe in our simulations the formation of ds-DNA hairpins, widely suspected to be the basis for quantized blockage. We study the translocation time, a measurable quantity crucially important in polyelectrolyte characterization, as a function of hairpin vertex location along the polymer backbone, finding that this behavior can be tuned to some degree by simulation parameters. We also study the voltage dependence of the tendency of hairpins to serve as the initiators of translocation events. Surprisingly, we find that the resulting probability depends vitally upon whether the events counted are ultimately successful or not. Further details lead us to propose that failed attempts in experimental translocation studies may be more common—and deceptive—than is generally recognized. We find the time taken by successful single file translocations to be directly proportional to the ratio of chain length to the applied voltage. Finally, we address a common yet puzzling phenomenon in translocation experiments: translocation events in which the current through the pore is highly, yet incompletely, blocked. We present the findings that offer a new explanation for such events.
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.
Langevin dynamics simulations of a two-dimensional colloidal crystal under confinement and shear.
Wilms, D; Virnau, P; Sengupta, S; Binder, K
2012-06-01
Langevin dynamics simulations are used to study the effect of shear on a two-dimensional colloidal crystal (with implicit solvent) confined by structured parallel walls. When walls are sheared very slowly, only two or three crystalline layers next to the walls move along with them, while the inner layers of the crystal are only slightly tilted. At higher shear velocities, this inner part of the crystal breaks into several pieces with different orientations. The velocity profile across the slit is reminiscent of shear banding in flowing soft materials, where liquid and solid regions coexist; the difference, however, is that in the latter case the solid regions are glassy while here they are crystalline. At even higher shear velocities, the effect of the shearing becomes smaller again. Also the effective temperature near the walls (deduced from the velocity distributions of the particles) decreases again when the wall velocity gets very large. When the walls are placed closer together, thereby introducing an incommensurability between the periodicity of the confined crystal and the walls, a structure containing a soliton staircase arises in simulations without shear. Introducing shear increases the disorder in these systems until no solitons are visible anymore. Instead, similar structures like in the case without mismatch result. At high shear rates, configurations where the incommensurability of the crystalline structure is compensated by the creation of holes become relevant.
A Langevin dynamics simulation study of the tribology of polymer loop brushes.
Yin, Fang; Bedrov, Dmitry; Smith, Grant D; Kilbey, S Michael
2007-08-28
The tribology of surfaces modified with doubly bound polymer chains (loops) has been investigated in good solvent conditions using Langevin dynamics simulations. The density profiles, brush interpenetration, chain inclination, normal forces, and shear forces for two flat substrates modified by doubly bound bead-necklace polymers and equivalent singly bound polymers (twice as many polymer chains of 12 the molecular weight of the loop chains) were determined and compared as a function of surface separation, grafting density, and shear velocity. The doubly bound polymer layers showed less interpenetration with decreasing separation than the equivalent singly bound layers. Surprisingly, this difference in interpenetration between doubly bound polymer and singly bound polymer did not result in decreased friction at high shear velocity possibly due to the decreased ability of the doubly bound chains to deform in response to the applied shear. However, at lower shear velocity, where deformation of the chains in the flow direction is less pronounced and the difference in interpenetration is greater between the doubly bound and singly bound chains, some reduction in friction was observed.
NASA Astrophysics Data System (ADS)
Sanghi, T.; Aluru, N. R.
2013-03-01
In this work, we combine our earlier proposed empirical potential based quasi-continuum theory, (EQT) [A. V. Raghunathan, J. H. Park, and N. R. Aluru, J. Chem. Phys. 127, 174701 (2007), 10.1063/1.2793070], which is a coarse-grained multiscale framework to predict the static structure of confined fluids, with a phenomenological Langevin equation to simulate the dynamics of confined fluids in thermal equilibrium. An attractive feature of this approach is that all the input parameters to the Langevin equation (mean force profile of the confined fluid and the static friction coefficient) can be determined using the outputs of the EQT and the self-diffusivity data of the corresponding bulk fluid. The potential of mean force profile, which is a direct output from EQT is used to compute the mean force profile of the confined fluid. The density profile, which is also a direct output from EQT, along with the self-diffusivity data of the bulk fluid is used to determine the static friction coefficient of the confined fluid. We use this approach to compute the mean square displacement and survival probabilities of some important fluids such as carbon-dioxide, water, and Lennard-Jones argon confined inside slit pores. The predictions from the model are compared with those obtained using molecular dynamics simulations. This approach of combining EQT with a phenomenological Langevin equation provides a mathematically simple and computationally efficient means to study the impact of structural inhomogeneity on the self-diffusion dynamics of confined fluids.
Finite-Temperature Non-equilibrium Quasicontinuum Method based on Langevin Dynamics
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.
Critical dynamics of self-gravitating Langevin particles and bacterial populations.
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 M
The Langevin Hull: Constant pressure and temperature dynamics for non-periodic systems.
Vardeman, Charles F; Stocker, Kelsey M; Gezelter, J Daniel
2011-04-12
We have developed a new isobaric-isothermal (NPT) algorithm which applies an external pressure to the facets comprising the convex hull surrounding the system. A Langevin thermostat is also applied to the facets to mimic contact with an external heat bath. This new method, the "Langevin Hull", can handle heterogeneous mixtures of materials with different compressibilities. These systems are problematic for traditional affine transform methods. The Langevin Hull does not suffer from the edge effects of boundary potential methods, and allows realistic treatment of both external pressure and thermal conductivity due to the presence of an implicit solvent. We apply this method to several different systems including bare metal nanoparticles, nanoparticles in an explicit solvent, as well as clusters of liquid water. The predicted mechanical properties of these systems are in good agreement with experimental data and previous simulation work.
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.
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.
Wen, Kai; Sakata, Fumihiko; Li, Zhu-Xia; Wu, Xi-Zhen; Zhang, Ying-Xun; Zhou, Shan-Gui
2013-07-05
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.
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.
Langevin dynamics in crossed magnetic and electric fields: Hall and diamagnetic fluctuations.
Roy, Dibyendu; Kumar, N
2008-11-01
Based on the classical Langevin equation, we have revisited the problem of orbital motion of a charged particle in two dimensions for a normal magnetic field crossed with or without an in-plane electric bias. We are led to two interesting fluctuation effects: First, we obtain not only a longitudinal "work-fluctuation" relation as expected for a barotropic type system, but also a transverse work-fluctuation relation perpendicular to the electric bias. This "Hall fluctuation" involves the product of the electric and the magnetic fields. Second, for the case of harmonic confinement without bias, the calculated probability density for the orbital magnetic moment gives nonzero even moments, not derivable as field derivatives of the classical free energy.
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.
NASA Astrophysics Data System (ADS)
Nadtochy, P. N.; Ryabov, E. G.; Cheredov, A. V.; Adeev, G. D.
2016-10-01
A stochastic approach based on four-dimensional Langevin fission dynamics is applied to the calculation of a wide set of experimental observables of excited compound nuclei from 199Pb to 248Cf formed in reactions induced by heavy ions. In the model under investigation, the tilting degree of freedom ( K coordinate) 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 {c,h,α} parametrization. The evolution of the K coordinate is described by means of the Langevin equation in the overdamped regime. The friction tensor for the shape collective coordinates is calculated under the assumption of the modified version of the one-body dissipation mechanism, where the reduction coefficient ks of the contribution from the "wall" formula is introduced. The calculations are performed both for the constant values of the coefficient ks and for the coordinate-dependent reduction coefficient ks(q) which is found on the basis of the "chaos-weighted wall formula". Different possibilities of the deformation-dependent dissipation coefficient (γK) for the K coordinate are investigated. The presented results demonstrate that an impact of the ks and γK parameters on the calculated observable fission characteristics can be selectively probed. It was found that it is possible to describe the experimental data consistently with the deformation-dependent γK(q) coefficient for shapes featuring a neck, which predicts quite small values of γK=0.0077 (MeV zs)-1/2 and constant γK=0.1-0.4 (MeV zs)-1/2 for compact shapes featuring no neck.
NASA Astrophysics Data System (ADS)
Marian, J.; Venturini, G.; Hansen, B. L.; Knap, J.; Ortiz, M.; Campbell, G. H.
2010-01-01
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=\\case{1}{2}) method, which is parametrized to ensure overdamped dynamics. In this fashion, spurious heating due to reflected vibrations is suppressed, leading to stable canonical trajectories. To estimate the errors introduced by the QC reduction in the resulting dynamics, we have quantified the vibrational entropy losses in Al uniform meshes by calculating the thermal expansion coefficient for a number of conditions. We find that the entropic depletion introduced by coarsening varies linearly with the element size and is independent of the nodal cluster diameter. We rationalize the results in terms of the system, mesh and cluster sizes within the framework of the quasiharmonic approximation. The limitations of the method and alternatives to mitigate the errors introduced by coarsening are discussed. This work represents the first of a series of studies aimed at developing a fully non-equilibrium finite-temperature extension of QC.
NASA Astrophysics Data System (ADS)
Bouzat, Sebastián
2016-01-01
One-dimensional models coupling a Langevin equation for the cargo position to stochastic stepping dynamics for the motors constitute a relevant framework for analyzing multiple-motor microtubule transport. In this work we explore the consistence of these models focusing on the effects of the thermal noise. We study how to define consistent stepping and detachment rates for the motors as functions of the local forces acting on them in such a way that the cargo velocity and run-time match previously specified functions of the external load, which are set on the base of experimental results. We show that due to the influence of the thermal fluctuations this is not a trivial problem, even for the single-motor case. As a solution, we propose a motor stepping dynamics which considers memory on the motor force. This model leads to better results for single-motor transport than the approaches previously considered in the literature. Moreover, it gives a much better prediction for the stall force of the two-motor case, highly compatible with the experimental findings. We also analyze the fast fluctuations of the cargo position and the influence of the viscosity, comparing the proposed model to the standard one, and we show how the differences on the single-motor dynamics propagate to the multiple motor situations. Finally, we find that the one-dimensional character of the models impede an appropriate description of the fast fluctuations of the cargo position at small loads. We show how this problem can be solved by considering two-dimensional models.
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.
Haas, Kevin R; Yang, Haw; Chu, Jhih-Wei
2013-12-12
The dynamics of a protein along a well-defined coordinate can be formally projected onto the form of an overdamped Lagevin equation. Here, we present a comprehensive statistical-learning framework for simultaneously quantifying the deterministic force (the potential of mean force, PMF) and the stochastic force (characterized by the diffusion coefficient, D) from single-molecule Förster-type resonance energy transfer (smFRET) experiments. The likelihood functional of the Langevin parameters, PMF and D, is expressed by a path integral of the latent smFRET distance that follows Langevin dynamics and realized by the donor and the acceptor photon emissions. The solution is made possible by an eigen decomposition of the time-symmetrized form of the corresponding Fokker-Planck equation coupled with photon statistics. To extract the Langevin parameters from photon arrival time data, we advance the expectation-maximization algorithm in statistical learning, originally developed for and mostly used in discrete-state systems, to a general form in the continuous space that allows for a variational calculus on the continuous PMF function. We also introduce the regularization of the solution space in this Bayesian inference based on a maximum trajectory-entropy principle. We use a highly nontrivial example with realistically simulated smFRET data to illustrate the application of this new method.
Inferring hidden states in Langevin dynamics on large networks: Average case performance
NASA Astrophysics Data System (ADS)
Bravi, B.; Opper, M.; Sollich, P.
2017-01-01
We present average performance results for dynamical inference problems in large networks, where a set of nodes is hidden while the time trajectories of the others are observed. Examples of this scenario can occur in signal transduction and gene regulation networks. We focus on the linear stochastic dynamics of continuous variables interacting via random Gaussian couplings of generic symmetry. We analyze the inference error, given by the variance of the posterior distribution over hidden paths, in the thermodynamic limit and as a function of the system parameters and the ratio α between the number of hidden and observed nodes. By applying Kalman filter recursions we find that the posterior dynamics is governed by an "effective" drift that incorporates the effect of the observations. We present two approaches for characterizing the posterior variance that allow us to tackle, respectively, equilibrium and nonequilibrium dynamics. The first appeals to Random Matrix Theory and reveals average spectral properties of the inference error and typical posterior relaxation times; the second is based on dynamical functionals and yields the inference error as the solution of an algebraic equation.
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.
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.
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.
Generalized Langevin equation with tempered memory kernel
NASA Astrophysics Data System (ADS)
Liemert, André; Sandev, Trifce; Kantz, Holger
2017-01-01
We study a generalized Langevin equation for a free particle in presence of a truncated power-law and Mittag-Leffler memory kernel. It is shown that in presence of truncation, the particle from subdiffusive behavior in the short time limit, turns to normal diffusion in the long time limit. The case of harmonic oscillator is considered as well, and the relaxation functions and the normalized displacement correlation function are represented in an exact form. By considering external time-dependent periodic force we obtain resonant behavior even in case of a free particle due to the influence of the environment on the particle movement. Additionally, the double-peak phenomenon in the imaginary part of the complex susceptibility is observed. It is obtained that the truncation parameter has a huge influence on the behavior of these quantities, and it is shown how the truncation parameter changes the critical frequencies. The normalized displacement correlation function for a fractional generalized Langevin equation is investigated as well. All the results are exact and given in terms of the three parameter Mittag-Leffler function and the Prabhakar generalized integral operator, which in the kernel contains a three parameter Mittag-Leffler function. Such kind of truncated Langevin equation motion can be of high relevance for the description of lateral diffusion of lipids and proteins in cell membranes.
Langevin simulation of scalar fields: Additive and multiplicative noises and lattice renormalization
NASA Astrophysics Data System (ADS)
Cassol-Seewald, N. C.; Farias, R. L. S.; Fraga, E. S.; Krein, G.; Ramos, Rudnei O.
2012-08-01
We consider the Langevin lattice dynamics for a spontaneously broken λϕ4 scalar field theory where both additive and multiplicative noise terms are incorporated. The lattice renormalization for the corresponding stochastic Ginzburg-Landau-Langevin and the subtleties related to the multiplicative noise are investigated.
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.
Langevin equations from time series.
Racca, E; Porporato, A
2005-02-01
We discuss the link between the approach to obtain the drift and diffusion of one-dimensional Langevin equations from time series, and Pope and Ching's relationship for stationary signals. The two approaches are based on different interpretations of conditional averages of the time derivatives of the time series at given levels. The analysis provides a useful indication for the correct application of Pope and Ching's relationship to obtain stochastic differential equations from time series and shows its validity, in a generalized sense, for nondifferentiable processes originating from Langevin equations.
Data-driven parameterization of the generalized Langevin equation
Lei, Huan; Baker, Nathan A.; Li, Xiantao
2016-11-29
We present a data-driven approach to determine the memory kernel and random noise of the generalized Langevin equation. To facilitate practical implementations, we parameterize the kernel function in the Laplace domain by a rational function, with coefficients directly linked to the equilibrium statistics of the coarse-grain variables. Further, we show that such an approximation can be constructed to arbitrarily high order. Within these approximations, the generalized Langevin dynamics can be embedded in an extended stochastic model without memory. We demonstrate how to introduce the stochastic noise so that the fluctuation-dissipation theorem is exactly satisfied.
Complex dynamics of epileptic EEG.
Kannathal, N; Puthusserypady, Sadasivan K; Choo Min, Lim
2004-01-01
Electroencephalogram (EEG) - the recorded representation of electrical activity of the brain contain useful information about the state of the brain. Recent studies indicate that nonlinear methods can extract valuable information from neuronal dynamics. We compare the dynamical properties of EEG signals of healthy subjects with epileptic subjects using nonlinear time series analysis techniques. Chaotic invariants like correlation dimension (D2) , largest Lyapunov exponent (lambda1), Hurst exponent (H) and Kolmogorov entropy (K) are used to characterize the signal. Our study showed clear differences in dynamical properties of brain electrical activity of the normal and epileptic subjects with a confidence level of more than 90%. Furthermore to support this claim fractal dimension (FD) analysis is performed. The results indicate reduction in value of FD for epileptic EEG indicating reduction in system complexity.
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.
Efficient estimators for likelihood ratio sensitivity indices of complex stochastic dynamics.
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.
Langevin description of nonequilibrium quantum fields
NASA Astrophysics Data System (ADS)
Gautier, F.; Serreau, J.
2012-12-01
We consider the nonequilibrium dynamics of a real quantum scalar field. We show the formal equivalence of the exact evolution equations for the statistical and spectral two-point functions with a fictitious Langevin process and examine the conditions under which a local Markovian dynamics is a valid approximation. In quantum field theory, the memory kernel and the noise correlator typically exhibit long time power laws and are thus highly nonlocal, thereby questioning the possibility of a local description. We show that despite this fact, there is a finite time range during which a local description is accurate. This requires the theory to be (effectively) weakly coupled. We illustrate the use of such a local description for studies of decoherence and entropy production in quantum field theory.
NASA Astrophysics Data System (ADS)
Lemons, Don S.; Gythiel, Anthony
1997-11-01
We present a translation of Paul Langevin's landmark paper. In it Langevin successfully applied Newtonian dynamics to a Brownian particle and so invented an analytical approach to random processes which has remained useful to this day.
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.
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
Quantum Langevin model for nonequilibrium condensation
NASA Astrophysics Data System (ADS)
Chiocchetta, Alessio; Carusotto, Iacopo
2014-08-01
We develop a quantum model for nonequilibrium Bose-Einstein condensation of photons and polaritons in planar microcavity devices. The model builds on laser theory and includes the spatial dynamics of the cavity field, a saturation mechanism, and some frequency dependence of the gain: quantum Langevin equations are written for a cavity field coupled to a continuous distribution of externally pumped two-level emitters with a well-defined frequency. As an example of application, the method is used to study the linearized quantum fluctuations around a steady-state condensed state. In the good-cavity regime, an effective equation for the cavity field only is proposed in terms of a stochastic Gross-Pitaevskii equation. Perspectives in view of a full quantum simulation of the nonequilibrium condensation process are finally sketched.
Cognitive dynamics: complexity and creativity
NASA Astrophysics Data System (ADS)
Tito Arecchi, F.
2007-05-01
A scientific problem described within a given code is mapped by a corresponding computational problem. We call (algorithmic) complexity the bit length of the shortest instruction which solves the problem. Deterministic chaos in general affects a dynamical system making the corresponding problem experimentally and computationally heavy, since one must reset the initial conditions at a rate higher than that of information loss (Kolmogorov entropy). One can control chaos by adding to the system new degrees of freedom (information swapping: information lost by chaos is replaced by that arising from the new degrees of freedom). This implies a change of code, or a new augmented model. Within a single code, changing hypotheses is equivalent to fixing different sets of control parameters, each with a different a-priori probability, to be then confirmed and transformed to an a-posteriori probability via Bayes theorem. Sequential application of Bayes rule is nothing else than the Darwinian strategy in evolutionary biology. The sequence is a steepest ascent algorithm, which stops once maximum probability has been reached. At this point the hypothesis exploration stops. By changing code (and hence the set of relevant variables) one can start again to formulate new classes of hypotheses. We call creativity the action of code changing, which is guided by hints not formalized within the previous code, whence not accessible to a computer. We call semantic complexity the number of different scientific codes, or models, that describe a situation. It is however a fuzzy concept, in so far as this number changes due to interaction of the operator with the context. These considerations are illustrated with reference to a cognitive task, starting from synchronization of neuron arrays in a perceptual area and tracing the putative path towards a model building. Since this is a report on work in progress, we skip technicalities in order to stress the gist of the question, and provide
Analysis of multifragmentation in a Boltzmann-Langevin approach
Zhang, F.; Suraud, E.
1995-06-01
By using the Boltzmann-Langevin equation, which incorporates dynamical fluctuations beyond usual transport theories, we simulate the {sup 40}Ca+{sup 40}Ca reaction system at different beam energies 20, 60, and 90 MeV/nucleon for different impact parameters. Dynamical fluctuations become larger and larger with increasing bombarding energy and the system can reach densities corresponding to the unstable region of the nuclear matter equation of state at energies above 60 MeV/nucleon. By coupling the Boltzmann-Langevin equation with a coalescence model in the late stages of the reaction, we obtain the distribution of the intermediate mass fragments in each event. From the correlation analysis of these fragments, we recover some trends of recent multifragmentation data. A critical behavior analysis is also provided.
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.
Phase-space geometry of the generalized Langevin equation.
Bartsch, Thomas
2009-09-28
The generalized Langevin equation is widely used to model the influence of a heat bath upon a reactive system. This equation will here be studied from a geometric point of view. A dynamical phase space that represents all possible states of the system will be constructed, the generalized Langevin equation will be formally rewritten as a pair of coupled ordinary differential equations, and the fundamental geometric structures in phase space will be described. It will be shown that the phase space itself and its geometric structure depend critically on the preparation of the system: A system that is assumed to have been in existence forever has a larger phase space with a simpler structure than a system that is prepared at a finite time. These differences persist even in the long-time limit, where one might expect the details of preparation to become irrelevant.
NASA Astrophysics Data System (ADS)
Nadtochy, P. N.; Ryabov, E. G.; Gegechkori, A. E.; Anischenko, Yu. A.; Adeev, G. D.
2014-01-01
A four-dimensional dynamical model was developed and applied to study fission characteristics in a wide range of a fissility parameter. Three collective shape coordinates and the K 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 has been used in the study. The inclusion of the K coordinate in the dynamical consideration and use of the "chaos-weighted wall formula" with a deformation-dependent scaling factor ks(q1) lead to fairly good reproduction of the variances of the fission-fragment mass distribution and the prescission neutron multiplicity for a number of fissioning compound nuclei in a wide fissility range. The four-dimensional dynamical calculations describe better experimental prescission neutron multiplicity and variances of fission-fragment mass distribution for heaviest nuclei with respect to a three-dimensional dynamical model, where the K coordinate is assumed to be equal to zero. The estimate of a dissipation coefficient for the orientation degree of freedom, γK≃0.077 (MeVzs)-1/2, is good for heavy nuclei and a larger value of γK≃0.2 (MeVzs)-1/2 is needed for nuclei with mass ACN ≃ 200.
Symbolic Dynamics and Grammatical Complexity
NASA Astrophysics Data System (ADS)
Hao, Bai-Lin; Zheng, Wei-Mou
The following sections are included: * Formal Languages and Their Complexity * Formal Language * Chomsky Hierarchy of Grammatical Complexity * The L-System * Regular Language and Finite Automaton * Finite Automaton * Regular Language * Stefan Matrix as Transfer Function for Automaton * Beyond Regular Languages * Feigenbaum and Generalized Feigenbaum Limiting Sets * Even and Odd Fibonacci Sequences * Odd Maximal Primitive Prefixes and Kneading Map * Even Maximal Primitive Prefixes and Distinct Excluded Blocks * Summary of Results
Dynamics of and on complex networks
NASA Astrophysics Data System (ADS)
Halu, Arda
Complex networks are dynamic, evolving structures that can host a great number of dynamical processes. In this thesis, we address current challenges regarding the dynamics of and dynamical processes on complex networks. First, we study complex network dynamics from the standpoint of network growth. As a quantitative measure of the complexity and information content of networks generated by growing network models, we define and evaluate their entropy rate. We propose stochastic growth models inspired by the duplication-divergence mechanism to generate epistatic interaction networks and find that they exhibit the property of monochromaticity as a result of their dynamical evolution. Second, we explore the dynamics of quantum mechanical processes on complex networks. We investigate the Bose-Hubbard model on annealed and quenched scale-free networks as well as Apollonian networks and show that their phase diagram changes significantly in the presence of complex topologies, depending on the second degree of the degree distribution and the maximal eigenvalue of the adjacency matrix. We then study the Jaynes-Cummings-Hubbard model on various complex topologies and demonstrate the importance of the maximal eigenvalue of the hopping matrix in determining the phase diagram of the model. Third, we investigate dynamical processes on interacting and multiplex networks. We study opinion dynamics in a simulated setting of two antagonistically interacting networks and recover the importance of connectivity and committed agents. We propose a multiplex centrality measure that takes into account the connectivity patterns within and across different layers and find that the dynamics of biased random walks on multiplex networks gives rise to a centrality ranking that is different from univariate centrality measures. Finally, we study the statistical mechanics of multilayered spatial networks and demonstrate the emergence of significant link overlap and improved navigability in
Relativistic Langevin equation for runaway electrons
NASA Astrophysics Data System (ADS)
Mier, J. A.; Martin-Solis, J. R.; Sanchez, R.
2016-10-01
The Langevin approach to the kinetics of a collisional plasma is developed for relativistic electrons such as runaway electrons in tokamak plasmas. In this work, we consider Coulomb collisions between very fast, relativistic electrons and a relatively cool, thermal background plasma. The model is developed using the stochastic equivalence of the Fokker-Planck and Langevin equations. The resulting Langevin model equation for relativistic electrons is an stochastic differential equation, amenable to numerical simulations by means of Monte-Carlo type codes. Results of the simulations will be presented and compared with the non-relativistic Langevin equation for RE electrons used in the past. Supported by MINECO (Spain), Projects ENE2012-31753, ENE2015-66444-R.
An adaptive stepsize method for the chemical Langevin equation.
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.
A Dynamic Testing Complexity Metric
NASA Technical Reports Server (NTRS)
Voas, Jeffrey
1991-01-01
This paper introduces a dynamic metric that is based on the estimated ability of a program to withstand the effects of injected "semantic mutants" during execution by computing the same function as if the semantic mutants had not been injected. Semantic mutants include: (1) syntactic mutants injected into an executing program and (2) randomly selected values injected into an executing program's internal states. The metric is a function of a program, the method used for injecting these two types of mutants, and the program's input distribution; this metric is found through dynamic executions of the program. A program's ability to withstand the effects of injected semantic mutants by computing the same function when executed is then used as a tool for predicting the difficulty that will be incurred during random testing to reveal the existence of faults, i.e., the metric suggests the likelihood that a program will expose the existence of faults during random testing assuming faults were to exist. If the metric is applied to a module rather than to a program, the metric can be used to guide the allocation of testing resources among a program's modules. In this manner the metric acts as a white-box testing tool for determining where to concentrate testing resources. Index Terms: Revealing ability, random testing, input distribution, program, fault, failure.
Amplitude dynamics favors synchronization in complex networks
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
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.
Competitive Dynamics on Complex Networks
NASA Astrophysics Data System (ADS)
Zhao, Jiuhua; Liu, Qipeng; Wang, Xiaofan
2014-07-01
We consider a dynamical network model in which two competitors have fixed and different states, and each normal agent adjusts its state according to a distributed consensus protocol. The state of each normal agent converges to a steady value which is a convex combination of the competitors' states, and is independent of the initial states of agents. This implies that the competition result is fully determined by the network structure and positions of competitors in the network. We compute an Influence Matrix (IM) in which each element characterizing the influence of an agent on another agent in the network. We use the IM to predict the bias of each normal agent and thus predict which competitor will win. Furthermore, we compare the IM criterion with seven node centrality measures to predict the winner. We find that the competitor with higher Katz Centrality in an undirected network or higher PageRank in a directed network is most likely to be the winner. These findings may shed new light on the role of network structure in competition and to what extent could competitors adjust network structure so as to win the competition.
Competitive Dynamics on Complex Networks
Zhao, Jiuhua; Liu, Qipeng; Wang, Xiaofan
2014-01-01
We consider a dynamical network model in which two competitors have fixed and different states, and each normal agent adjusts its state according to a distributed consensus protocol. The state of each normal agent converges to a steady value which is a convex combination of the competitors' states, and is independent of the initial states of agents. This implies that the competition result is fully determined by the network structure and positions of competitors in the network. We compute an Influence Matrix (IM) in which each element characterizing the influence of an agent on another agent in the network. We use the IM to predict the bias of each normal agent and thus predict which competitor will win. Furthermore, we compare the IM criterion with seven node centrality measures to predict the winner. We find that the competitor with higher Katz Centrality in an undirected network or higher PageRank in a directed network is most likely to be the winner. These findings may shed new light on the role of network structure in competition and to what extent could competitors adjust network structure so as to win the competition. PMID:25068622
Complexity, dynamic cellular network, and tumorigenesis.
Waliszewski, P
1997-01-01
A holistic approach to tumorigenesis is proposed. The main element of the model is the existence of dynamic cellular network. This network comprises a molecular and an energetistic structure of a cell connected through the multidirectional flow of information. The interactions within dynamic cellular network are complex, stochastic, nonlinear, and also involve quantum effects. From this non-reductionist perspective, neither tumorigenesis can be limited to the genetic aspect, nor the initial event must be of molecular nature, nor mutations and epigenetic factors are mutually exclusive, nor a link between cause and effect can be established. Due to complexity, an unstable stationary state of dynamic cellular network rather than a group of unrelated genes determines the phenotype of normal and transformed cells. This implies relativity of tumor suppressor genes and oncogenes. A bifurcation point is defined as an unstable state of dynamic cellular network leading to the other phenotype-stationary state. In particular, the bifurcation point may be determined by a change of expression of a single gene. Then, the gene is called bifurcation point gene. The unstable stationary state facilitates the chaotic dynamics. This may result in a fractal dimension of both normal and tumor tissues. The co-existence of chaotic dynamics and complexity is the essence of cellular processes and shapes differentiation, morphogenesis, and tumorigenesis. In consequence, tumorigenesis is a complex, unpredictable process driven by the interplay between self-organisation and selection.
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.
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
Controlling Complex Systems and Developing Dynamic Technology
NASA Astrophysics Data System (ADS)
Avizienis, Audrius Victor
In complex systems, control and understanding become intertwined. Following Ilya Prigogine, we define complex systems as having control parameters which mediate transitions between distinct modes of dynamical behavior. From this perspective, determining the nature of control parameters and demonstrating the associated dynamical phase transitions are practically equivalent and fundamental to engaging with complexity. In the first part of this work, a control parameter is determined for a non-equilibrium electrochemical system by studying a transition in the morphology of structures produced by an electroless deposition reaction. Specifically, changing the size of copper posts used as the substrate for growing metallic silver structures by the reduction of Ag+ from solution under diffusion-limited reaction conditions causes a dynamical phase transition in the crystal growth process. For Cu posts with edge lengths on the order of one micron, local forces promoting anisotropic growth predominate, and the reaction produces interconnected networks of Ag nanowires. As the post size is increased above 10 microns, the local interfacial growth reaction dynamics couple with the macroscopic diffusion field, leading to spatially propagating instabilities in the electrochemical potential which induce periodic branching during crystal growth, producing dendritic deposits. This result is interesting both as an example of control and understanding in a complex system, and as a useful combination of top-down lithography with bottom-up electrochemical self-assembly. The second part of this work focuses on the technological development of devices fabricated using this non-equilibrium electrochemical process, towards a goal of integrating a complex network as a dynamic functional component in a neuromorphic computing device. Self-assembled networks of silver nanowires were reacted with sulfur to produce interfacial "atomic switches": silver-silver sulfide junctions, which exhibit
Chaos synchronization of general complex dynamical networks
NASA Astrophysics Data System (ADS)
Lü, Jinhu; Yu, Xinghuo; Chen, Guanrong
2004-03-01
Recently, it has been demonstrated that many large-scale complex dynamical networks display a collective synchronization motion. Here, we introduce a time-varying complex dynamical network model and further investigate its synchronization phenomenon. Based on this new complex network model, two network chaos synchronization theorems are proved. We show that the chaos synchronization of a time-varying complex network is determined by means of the inner coupled link matrix, the eigenvalues and the corresponding eigenvectors of the coupled configuration matrix, rather than the conventional eigenvalues of the coupled configuration matrix for a uniform network. Especially, we do not assume that the coupled configuration matrix is symmetric and its off-diagonal elements are nonnegative, which in a way generalizes the related results existing in the literature.
Fluctuation theorems for total entropy production in generalized Langevin systems
NASA Astrophysics Data System (ADS)
Ghosh, Bappa; Chaudhury, Srabanti
2017-01-01
The validity of the fluctuation theorems for total entropy production of a colloidal particle embedded in a non-Markovian heat bath driven by a time-dependent force in a harmonic potential is probed here. The dynamics of the system is modeled by the generalized Langevin equation with colored noise. The distribution function of the total entropy production is calculated and the detailed fluctuation theorem contains a renormalized temperature term which arises due to the non-Markovian characteristics of the thermal bath.
Dynamic information routing in complex networks
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
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.
A theory for protein dynamics: Global anisotropy and a normal mode approach to local complexity
NASA Astrophysics Data System (ADS)
Copperman, Jeremy; Romano, Pablo; Guenza, Marina
2014-03-01
We propose a novel Langevin equation description for the dynamics of biological macromolecules by projecting the solvent and all atomic degrees of freedom onto a set of coarse-grained sites at the single residue level. We utilize a multi-scale approach where molecular dynamic simulations are performed to obtain equilibrium structural correlations input to a modified Rouse-Zimm description which can be solved analytically. The normal mode solution provides a minimal basis set to account for important properties of biological polymers such as the anisotropic global structure, and internal motion on a complex free-energy surface. This multi-scale modeling method predicts the dynamics of both global rotational diffusion and constrained internal motion from the picosecond to the nanosecond regime, and is quantitative when compared to both simulation trajectory and NMR relaxation times. Utilizing non-equilibrium sampling techniques and an explicit treatment of the free-energy barriers in the mode coordinates, the model is extended to include biologically important fluctuations in the microsecond regime, such as bubble and fork formation in nucleic acids, and protein domain motion. This work supported by the NSF under the Graduate STEM Fellows in K-12 Education (GK-12) program, grant DGE-0742540 and NSF grant DMR-0804145, computational support from XSEDE and ACISS.
Language Teacher Cognitions: Complex Dynamic Systems?
ERIC Educational Resources Information Center
Feryok, Anne
2010-01-01
Language teacher cognition research is a growing field. In recent years several features of language teacher cognitions have been noted: they can be complex, ranging over a number of different subjects; they can be dynamic, changing over time and under different influences; and they can be systems, forming unified and cohesive personal or…
Design tools for complex dynamic security systems.
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.
Energy spectrum of a Langevin oscillator
NASA Astrophysics Data System (ADS)
Mishin, Y.; Hickman, J.
2016-12-01
We derive analytical solutions for the autocorrelation and cross-correlation functions of the kinetic, potential, and total energy of a Langevin oscillator. These functions are presented in both the time and frequency domains and validated by independent numerical simulations. The results are applied to address the long-standing issue of temperature fluctuations in canonical systems.
Analysis of multifrequency langevin composite ultrasonic transducers.
Lin, Shuyu
2009-09-01
The multimode coupled vibration of Langevin composite ultrasonic transducers with conical metal mass of large cross-section is analyzed. The coupled resonance and anti-resonance frequency equations are derived and the effective electromechanical coupling coefficient is analyzed. The effect of the geometrical dimensions on the resonance frequency, the anti-resonance frequency, and the effective electromechanical coupling coefficient is studied. It is illustrated that when the radial dimension is large compared with the longitudinal dimension, the vibration of the Langevin transducer becomes a multifrequency multimode coupled vibration. Numerical methods are used to simulate the coupled vibration; the simulated results are in good agreement with those from the analytical results. Some Langevin transducers of large cross-section are designed and manufactured and their resonance frequencies are measured. It can be seen that the resonance frequencies obtained from the coupled resonance frequency equations are in good agreement with the measured results. It is expected that by properly choosing the dimensions, multifrequency Langevin transducers can be designed and used in ultrasonic cleaning, ultrasonic sonochemistry, and other applications.
Fractional Langevin model of memory in financial markets.
Picozzi, Sergio; West, Bruce J
2002-10-01
The separation of the microscopic and macroscopic time scales is necessary for the validity of ordinary statistical physics and the dynamical description embodied in the Langevin equation. When the microscopic time scale diverges, the differential equations on the macroscopic level are no longer valid and must be replaced with fractional differential equations of motion; in particular, we obtain a fractional-differential stochastic equation of motion. After decades of statistical analysis of financial time series certain "stylized facts" have emerged, including the statistics of stock price fluctuations having "fat tails" and their linear correlations in time being exceedingly short lived. On the other hand, the magnitude of these fluctuations and other such measures of market volatility possess temporal correlations that decay as an inverse power law. One explanation of this long-term memory is that it is a consequence of the time-scale separation between "microscopic" and "macroscopic" economic variables. We propose a fractional Langevin equation as a dynamical model of the observed memory in financial time series.
Complex reaction noise in a molecular quasispecies model
NASA Astrophysics Data System (ADS)
Hochberg, David; Zorzano, María-Paz; Morán, Federico
2006-05-01
We have derived exact Langevin equations for a model of quasispecies dynamics. The inherent multiplicative reaction noise is complex and its statistical properties are specified completely. The numerical simulation of the complex Langevin equations is carried out using the Cholesky decomposition for the noise covariance matrix. This internal noise, which is due to diffusion-limited reactions, produces unavoidable spatio-temporal density fluctuations about the mean field value. In two dimensions, this noise strictly vanishes only in the perfectly mixed limit, a situation difficult to attain in practice.
Ayik, S. Joint Inst. for Heavy Ion Research, Oak Ridge, TN ); Ivanov, Y.B.; Russkikh, V.N.; Noerenberg, W. )
1993-01-01
A reduction of the relativistic Boltzmann-Langevin Equation (BLE), to a stochastic two-fluid model is presented, and transport coefficients associated with fluid dynamical variables are extracted. The approach is applied to investigate equilibration in a counter-streaming nuclear system.
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.
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.
Complex Filling Dynamics in Mesoporous Thin Films.
Mercuri, Magalí; Pierpauli, Karina; Bellino, Martín G; Berli, Claudio L A
2017-01-10
The fluid-front dynamics resulting from the coexisting infiltration and evaporation phenomena in nanofluidic systems has been investigated. More precisely, water infiltration in both titania and silica mesoporous films was studied through a simple experiment: a sessile drop was deposited over the film and the advancement of the fluid front into the porous structure was optically followed and recorded in time. In the case of titania mesoporous films, capillary infiltration was arrested at a given distance, and a steady annular region of the wetted material was formed. A simple model that combines Lucas-Washburn infiltration and surface evaporation was derived, which appropriately describes the observed filling dynamics and the annulus width in dissimilar mesoporous morphologies. In the case of wormlike mesoporous morphologies, a remarkable phenomenon was found: instead of reaching a steady infiltration-evaporation balance, the fluid front exhibits an oscillating behavior. This complex filling dynamics opens interesting possibilities to study the unusual nanofluidic phenomena and to discover novel applications.
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
NASA Astrophysics Data System (ADS)
West, Bruce J.
The proper methodology for describing the dynamics of certain complex phenomena and fractal time series is the fractional calculus through the fractional Langevin equation discussed herein and applied in a biomedical context. We show that a fractional operator (derivative or integral) acting on a fractal function, yields another fractal function, allowing us to construct a fractional Langevin equation to describe the evolution of a fractal statistical process, for example, human gait and cerebral blood flow. The goal of this talk is to make clear how certain complex phenomena, such as those that are abundantly present in human physiology, can be faithfully described using dynamical models involving fractional differential stochastic equations. These models are tested against existing data sets and shown to describe time series from complex physiologic phenomena quite well.
Automated Design of Complex Dynamic Systems
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
Computing generalized Langevin equations and generalized Fokker-Planck equations.
Darve, Eric; Solomon, Jose; Kia, Amirali
2009-07-07
The Mori-Zwanzig formalism is an effective tool to derive differential equations describing the evolution of a small number of resolved variables. In this paper we present its application to the derivation of generalized Langevin equations and generalized non-Markovian Fokker-Planck equations. We show how long time scales rates and metastable basins can be extracted from these equations. Numerical algorithms are proposed to discretize these equations. An important aspect is the numerical solution of the orthogonal dynamics equation which is a partial differential equation in a high dimensional space. We propose efficient numerical methods to solve this orthogonal dynamics equation. In addition, we present a projection formalism of the Mori-Zwanzig type that is applicable to discrete maps. Numerical applications are presented from the field of Hamiltonian systems.
Stochastic dynamics of complexation reaction in the limit of small numbers.
Ghosh, Kingshuk
2011-05-21
We study stochastic dynamics of the non-linear bimolecular reaction A + B↔AB. These reactions are common in several bio-molecular systems such as binding, complexation, protein multimerization to name a few. We use master equation to compute the full distribution of several stochastic equilibrium properties such as number of complexes formed (N(c)), equilibrium constant (K). We provide exact analytical and simpler approximate expression for equilibrium fluctuation quantities to quickly estimate the amount of noise as a function of reactant molecules and rates. We construct the phase diagram for a fluctuational quantity f, defined as the ratio of standard deviation to average (f=√
PREFACE: Complex Dynamics in Spatially Extended Systems
NASA Astrophysics Data System (ADS)
Mosekilde, Erik; Bohr, Tomas; Rasmussen, Jens Juul; Leth Christiansen, Peter
1996-01-01
Self-organization, or the spontaneous emergence of patterns and structures under far-from-equilibrium conditions, turbulence, and related nonlinear dynamic phenomena in spatially extended systems have developed into one of the most exciting topics of modern science. Phenomena of this type arise in a wide variety of different fields, ranging from the development of chemical and biological patterns in reaction-diffusion systems over vortex formation in connection with chemical, optical, hydrodynamic or magnetohydrodynamic turbulence to technical applications in connection with liquid crystal displays or pulse compression in optical communication systems. Lasers often show interesting patterns produced by self-focusing and other nonlinear phenomena, diffusion limited aggregation is known to generate fractal-like structures, and amazing struc- tures also arise in bacterial growth processes or when a droplet of an oil suspension of finely divided magnetic particles is subject to a magnetic field perpendicular to the surface of the cell in which it is contained. In September 1995 the Niels Bohr Institute in Copenhagen was the venue of an International Conference on Complex Dynamics in Spatially Extended Systems. Organizers of the conference were the three Danish centers for nonlinear dynamics: The Center for Chaos and Turbulence Studies (CATS), located at the Niels Bohr Institute; the Center for Modeling, Nonlinear Dynamics and Irreversible Thermodynamics (MIDIT), located at the Technical University of Denmark, and the Center for Nonlinear Dynamics in Continuum Systems, located at the Risø National Laboratories. In the spirit of the successful NATO Advanced Research Workshops on Spatiotemporal Patterns in Nonequilibrium Systems of which the last was held in Santa Fe, New Mexico in 1993, the conference aimed at stimulating new ideas and providing a forum for the exchange of knowledge between leading practitioners of the field. With its 50 invited speakers and more than
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.
Langevin formulation for single-file diffusion
NASA Astrophysics Data System (ADS)
Taloni, Alessandro; Lomholt, Michael A.
2008-11-01
We introduce a stochastic equation for the microscopic motion of a tagged particle in the single-file model. This equation provides a compact representation of several of the system’s properties such as fluctuation-dissipation and linear-response relations, achieved by means of a diffusion noise approach. Most importantly, the proposed Langevin equation reproduces quantitatively the three temporal regimes and the corresponding time scales: ballistic, diffusive, and subdiffusive.
Markovian dynamics on complex reaction networks
NASA Astrophysics Data System (ADS)
Goutsias, J.; Jenkinson, G.
2013-08-01
Complex networks, comprised of individual elements that interact with each other through reaction channels, are ubiquitous across many scientific and engineering disciplines. Examples include biochemical, pharmacokinetic, epidemiological, ecological, social, neural, and multi-agent networks. A common approach to modeling such networks is by a master equation that governs the dynamic evolution of the joint probability mass function of the underlying population process and naturally leads to Markovian dynamics for such process. Due however to the nonlinear nature of most reactions and the large size of the underlying state-spaces, computation and analysis of the resulting stochastic population dynamics is a difficult task. This review article provides a coherent and comprehensive coverage of recently developed approaches and methods to tackle this problem. After reviewing a general framework for modeling Markovian reaction networks and giving specific examples, the authors present numerical and computational techniques capable of evaluating or approximating the solution of the master equation, discuss a recently developed approach for studying the stationary behavior of Markovian reaction networks using a potential energy landscape perspective, and provide an introduction to the emerging theory of thermodynamic analysis of such networks. Three representative problems of opinion formation, transcription regulation, and neural network dynamics are used as illustrative examples.
BDI-modelling of complex intracellular dynamics.
Jonker, C M; Snoep, J L; Treur, J; Westerhoff, H V; Wijngaards, W C A
2008-03-07
A BDI-based continuous-time modelling approach for intracellular dynamics is presented. It is shown how temporalized BDI-models make it possible to model intracellular biochemical processes as decision processes. By abstracting from some of the details of the biochemical pathways, the model achieves understanding in nearly intuitive terms, without losing veracity: classical intentional state properties such as beliefs, desires and intentions are founded in reality through precise biochemical relations. In an extensive example, the complex regulation of Escherichia coli vis-à-vis lactose, glucose and oxygen is simulated as a discrete-state, continuous-time temporal decision manager. Thus a bridge is introduced between two different scientific areas: the area of BDI-modelling and the area of intracellular dynamics.
Efficient quantum computing of complex dynamics.
Benenti, G; Casati, G; Montangero, S; Shepelyansky, D L
2001-11-26
We propose a quantum algorithm which uses the number of qubits in an optimal way and efficiently simulates a physical model with rich and complex dynamics described by the quantum sawtooth map. The numerical study of the effect of static imperfections in the quantum computer hardware shows that the main elements of the phase space structures are accurately reproduced up to a time scale which is polynomial in the number of qubits. The errors generated by these imperfections are more significant than the errors of random noise in gate operations.
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.
A Constraint Embedding Approach for Complex Vehicle Suspension Dynamics
2015-04-24
Suspension Dynamics ECCOMAS Thematic Conference on Multibody Dynamics 2015 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6...Complex Vehicle Suspension Dynamics ECCOMAS Thematic Conference on Multibody Dynamics 2015 Abhinandan Jain∗, Calvin Kuo#, Paramsothy Jayakumar†, Jonathan...topic of this paper is the de- velopment of computationally efficient and accurate dynamics model for ground vehicles with complex suspension dynamics. In
Complex Dynamics Along One Dimensional Cardiac Fibers
NASA Astrophysics Data System (ADS)
Fox, Jeff; Stubna, Mike; Hua, Fei; Bodenschatz, Eberhard; Gilmour, Robert
2001-03-01
Beat-to-beat alternation of cardiac electrical properties (electrical alternans; EA) may destabilize spiral waves in cardiac tissue, leading to cardiac arrhythmias. Recent studies have suggested that propagation of EA may not be uniform, resulting in concordant (in phase) and discordant (out of phase) EA across spatially distributed systems. In this study we induced EA in canine cardiac Purkinje fibers by pacing at short cycle lengths (CL). At CL between 110-150 ms, discordant EA occurred distal to the site of stimulation, whereas at CL less than 110 ms, complex dynamics (period 4 and higher) appeared. The mechanism for this behavior was studied using a model of a cardiac fiber in which local dynamics were determined by action potential duration (APD) and conduction velocity restitution curves. We investigated the stability of spatially extended EA and observed discordant EA. We also showed that models in which the APD restitution curve has a local minimum exhibited complex activation patterns. The dispersion of electrical properties caused by such patterns may facilitate reentrant excitation.
Copie, Guillaume; Cleri, Fabrizio; Blossey, Ralf; Lensink, Marc F.
2016-01-01
Interfacial waters are increasingly appreciated as playing a key role in protein-protein interactions. We report on a study of the prediction of interfacial water positions by both Molecular Dynamics and explicit solvent-continuum electrostatics based on the Dipolar Poisson-Boltzmann Langevin (DPBL) model, for three test cases: (i) the barnase/barstar complex (ii) the complex between the DNase domain of colicin E2 and its cognate Im2 immunity protein and (iii) the highly unusual anti-freeze protein Maxi which contains a large number of waters in its interior. We characterize the waters at the interface and in the core of the Maxi protein by the statistics of correctly predicted positions with respect to crystallographic water positions in the PDB files as well as the dynamic measures of diffusion constants and position lifetimes. Our approach provides a methodology for the evaluation of predicted interfacial water positions through an investigation of water-mediated inter-chain contacts. While our results show satisfactory behaviour for molecular dynamics simulation, they also highlight the need for improvement of continuum methods. PMID:27905545
The heterogeneous dynamics of economic complexity.
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.
Lattice-Boltzmann-Langevin simulations of binary mixtures.
Thampi, Sumesh P; Pagonabarraga, Ignacio; Adhikari, R
2011-10-01
We report a hybrid numerical method for the solution of the Model H fluctuating hydrodynamic equations for binary mixtures. The momentum conservation equations with Landau-Lifshitz stresses are solved using the fluctuating lattice Boltzmann equation while the order parameter conservation equation with Langevin fluxes is solved using stochastic method of lines. Two methods, based on finite difference and finite volume, are proposed for spatial discretization of the order parameter equation. Special care is taken to ensure that the fluctuation-dissipation theorem is maintained at the lattice level in both cases. The methods are benchmarked by comparing static and dynamic correlations and excellent agreement is found between analytical and numerical results. The Galilean invariance of the model is tested and found to be satisfactory. Thermally induced capillary fluctuations of the interface are captured accurately, indicating that the model can be used to study nonlinear fluctuations.
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.
Complex Dynamics in Nonequilibrium Economics and Chemistry
NASA Astrophysics Data System (ADS)
Wen, Kehong
Complex dynamics provides a new approach in dealing with economic complexity. We study interactively the empirical and theoretical aspects of business cycles. The way of exploring complexity is similar to that in the study of an oscillatory chemical system (BZ system)--a model for modeling complex behavior. We contribute in simulating qualitatively the complex periodic patterns observed from the controlled BZ experiments to narrow the gap between modeling and experiment. The gap between theory and reality is much wider in economics, which involves studies of human expectations and decisions, the essential difference from natural sciences. Our empirical and theoretical studies make substantial progress in closing this gap. With the help from the new development in nonequilibrium physics, i.e., the complex spectral theory, we advance our technique in detecting characteristic time scales from empirical economic data. We obtain correlation resonances, which give oscillating modes with decays for correlation decomposition, from different time series including S&P 500, M2, crude oil spot prices, and GNP. The time scales found are strikingly compatible with business experiences and other studies in business cycles. They reveal the non-Markovian nature of coherent markets. The resonances enhance the evidence of economic chaos obtained by using other tests. The evolving multi-humped distributions produced by the moving-time -window technique reveal the nonequilibrium nature of economic behavior. They reproduce the American economic history of booms and busts. The studies seem to provide a way out of the debate on chaos versus noise and unify the cyclical and stochastic approaches in explaining business fluctuations. Based on these findings and new expectation formulation, we construct a business cycle model which gives qualitatively compatible patterns to those found empirically. The soft-bouncing oscillator model provides a better alternative than the harmonic oscillator
Optimal dynamic bandwidth allocation for complex networks
NASA Astrophysics Data System (ADS)
Jiang, Zhong-Yuan; Liang, Man-Gui; Li, Qian; Guo, Dong-Chao
2013-03-01
Traffic capacity of one network strongly depends on the link’s bandwidth allocation strategy. In previous bandwidth allocation mechanisms, once one link’s bandwidth is allocated, it will be fixed throughout the overall traffic transmission process. However, the traffic load of every link changes from time to time. In this paper, with finite total bandwidth resource of the network, we propose to dynamically allocate the total bandwidth resource in which each link’s bandwidth is proportional to the queue length of the output buffer of the link per time step. With plenty of data packets in the network, the traffic handling ability of all links of the network achieves full utilization. The theoretical analysis and the extensive simulation results on complex networks are consistent. This work is valuable for network service providers to improve network performance or to do reasonable network design efficiently.
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
Major Depression as a Complex Dynamic System
Cramer, Angélique O. J.; van Borkulo, Claudia D.; Giltay, Erik J.; van der Maas, Han L. J.; Kendler, Kenneth S.; Scheffer, Marten; Borsboom, Denny
2016-01-01
In this paper, we characterize major depression (MD) as a complex dynamic system in which symptoms (e.g., insomnia and fatigue) are directly connected to one another in a network structure. We hypothesize that individuals can be characterized by their own network with unique architecture and resulting dynamics. With respect to architecture, we show that individuals vulnerable to developing MD are those with strong connections between symptoms: e.g., only one night of poor sleep suffices to make a particular person feel tired. Such vulnerable networks, when pushed by forces external to the system such as stress, are more likely to end up in a depressed state; whereas networks with weaker connections tend to remain in or return to a non-depressed state. We show this with a simulation in which we model the probability of a symptom becoming ‘active’ as a logistic function of the activity of its neighboring symptoms. Additionally, we show that this model potentially explains some well-known empirical phenomena such as spontaneous recovery as well as accommodates existing theories about the various subtypes of MD. To our knowledge, we offer the first intra-individual, symptom-based, process model with the potential to explain the pathogenesis and maintenance of major depression. PMID:27930698
[The dynamic complex of the temporomandibular meniscus].
Couly, G; Hureau, J; Vaillant, J M
1975-12-01
The existence of meniscocapsular insertions of the temporal, masseter and external pterygoid muscles complicates the scheme of capsulo-meniscal dynamics. Our findings do indeed agree with those of DUBECQ (Bordeaux); but we think that the insertions of the masseter and the temporal are not only fine tracts. In the embryon, the meniscus is the preglossal mekelian conjunctival blastema, which receives the 3 masticatory muscles on its anterior border. In the adult, menisco-capsulo-muscular relationships are not modified; inspite of considerable functional adaptation of the articulation to varied stimuli, the menisco-capsular apparatus seems to be triply controlled by 3 musculo-masticatory bands, owing to the anterior premeniscal tendinous lamina, in histological continuity with the meniscus and rich in corpuscles of deep sensitivity. The resultant of the tridirectional muscular traction of the masseter, external pterygoid and temporal is a force in the postero-anterior oblique direction, downwards and forwards, which allows the meniscus to stretch, as was shown by Pr Delaire, and thus to have a sub-temporal sliding pathway of 8 to 12 mm. The three muscle bundles external pterygoid, temporal and masseter constitute the dynamic complex of the meniscus.
Forest microbiome: diversity, complexity and dynamics.
Baldrian, Petr
2017-03-01
Globally, forests represent highly productive ecosystems that act as carbon sinks where soil organic matter is formed from residuals after biomass decomposition as well as from rhizodeposited carbon. Forests exhibit a high level of spatial heterogeneity and the importance of trees, the dominant primary producers, for their structure and functioning. Fungi, bacteria and archaea inhabit various forest habitats: foliage, the wood of living trees, the bark surface, ground vegetation, roots and the rhizosphere, litter, soil, deadwood, rock surfaces, invertebrates, wetlands or the atmosphere, each of which has its own specific features, such as nutrient availability or temporal dynamicy and specific drivers that affect microbial abundance, the level of dominance of bacteria or fungi as well as the composition of their communities. However, several microorganisms, and in particular fungi, inhabit or even connect multiple habitats, and most ecosystem processes affect multiple habitats. Forests are dynamic on a broad temporal scale with processes ranging from short-term events over seasonal ecosystem dynamics to long-term stand development after disturbances such as fires or insect outbreaks. The understanding of these processes can be only achieved by the exploration of the complex 'ecosystem microbiome' and its functioning using focused, integrative microbiological and ecological research performed across multiple habitats.
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.
Perspective: Dynamics of receptor tyrosine kinase signaling complexes.
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.
Orbital Architectures of Dynamically Complex Exoplanet Systems
NASA Astrophysics Data System (ADS)
Nelson, Benjamin E.
2015-01-01
The most powerful constraints on planet formation will come from characterizing the dynamical state of complex multi-planet systems. Unfortunately, with that complexity comes a number of factors that make analyzing these systems a computationally challenging endeavor: the sheer number of model parameters, a wonky shaped posterior distribution, and hundreds to thousands of time series measurements. We develop a differential evolution Markov chain Monte Carlo (RUN DMC) to tackle these difficult aspects of data analysis. We apply RUN DMC to two classic multi-planet systems from radial velocity surveys, 55 Cancri and GJ 876. For 55 Cancri, we find the inner-most planet "e" must be coplanar to within 40 degrees of the outer planets, otherwise Kozai-like perturbations will cause the planet's orbit to cross the stellar surface. We find the orbits of planets "b" and "c" are apsidally aligned and librating with low to median amplitude (50±610 degrees), but they are not orbiting in a mean-motion resonance. For GJ 876, we can meaningfully constrain the three-dimensional orbital architecture of all the planets based on the radial velocity data alone. By demanding orbital stability, we find the resonant planets have low mutual inclinations (Φ) so they must be roughly coplanar (Φcb = 1.41±0.620.57 degrees and Φbe = 3.87±1.991.86 degrees). The three-dimensional Laplace argument librates with an amplitude of 50.5±7.910.0 degrees, indicating significant past disk migration and ensuring long-term stability. These empirically derived models will provide new challenges for planet formation models and motivate the need for more sophisticated algorithms to analyze exoplanet data.
Trajectory approach to the Schrödinger–Langevin equation with linear dissipation for ground states
Chou, Chia-Chun
2015-11-15
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.
The Complex Dynamics of Sponsored Search Markets
NASA Astrophysics Data System (ADS)
Robu, Valentin; La Poutré, Han; Bohte, Sander
This paper provides a comprehensive study of the structure and dynamics of online advertising markets, mostly based on techniques from the emergent discipline of complex systems analysis. First, we look at how the display rank of a URL link influences its click frequency, for both sponsored search and organic search. Second, we study the market structure that emerges from these queries, especially the market share distribution of different advertisers. We show that the sponsored search market is highly concentrated, with less than 5% of all advertisers receiving over 2/3 of the clicks in the market. Furthermore, we show that both the number of ad impressions and the number of clicks follow power law distributions of approximately the same coefficient. However, we find this result does not hold when studying the same distribution of clicks per rank position, which shows considerable variance, most likely due to the way advertisers divide their budget on different keywords. Finally, we turn our attention to how such sponsored search data could be used to provide decision support tools for bidding for combinations of keywords. We provide a method to visualize keywords of interest in graphical form, as well as a method to partition these graphs to obtain desirable subsets of search terms.
Modeling Structural Dynamics of Biomolecular Complexes by Coarse-Grained Molecular Simulations.
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
Stochastic thermodynamics for delayed Langevin systems.
Jiang, Huijun; Xiao, Tiejun; Hou, Zhonghuai
2011-06-01
We discuss stochastic thermodynamics (ST) for delayed Langevin systems in this paper. By using the general principles of ST, the first-law-like energy balance and trajectory-dependent entropy s(t) can be well defined in a way that is similar to that in a system without delay. Because the presence of time delay brings an additional entropy flux into the system, the conventional second law (Δs(tot))≥0 no longer holds true, where Δs(tot) denotes the total entropy change along a stochastic path and (·) stands for the average over the path ensemble. With the help of a Fokker-Planck description, we introduce a delay-averaged trajectory-dependent dissipation functional η[χ(t)] which involves the work done by a delay-averaged force F(x,t) along the path χ(t) and equals the medium entropy change Δs(m)[x(t)] in the absence of delay. We show that the total dissipation functional R=Δs+η, where Δs denotes the system entropy change along a path, obeys (R)≥0, which could be viewed as the second law in the delayed system. In addition, the integral fluctuation theorem (e(-R))=1 also holds true. We apply these concepts to a linear Langevin system with time delay and periodic external force. Numerical results demonstrate that the total entropy change (Δs(tot)) could indeed be negative when the delay feedback is positive. By using an inversing-mapping approach, we are able to obtain the delay-averaged force F(x,t) from the stationary distribution and then calculate the functional R as well as its distribution. The second law (R)≥0 and the fluctuation theorem are successfully validated.
Langevin model for reactive transport in porous media
NASA Astrophysics Data System (ADS)
Tartakovsky, Alexandre M.
2010-08-01
Existing continuum models for reactive transport in porous media tend to overestimate the extent of solute mixing and mixing-controlled reactions because the continuum models treat both the mechanical and diffusive mixings as an effective Fickian process. Recently, we have proposed a phenomenological Langevin model for flow and transport in porous media [A. M. Tartakovsky, D. M. Tartakovsky, and P. Meakin, Phys. Rev. Lett. 101, 044502 (2008)10.1103/PhysRevLett.101.044502]. In the Langevin model, the fluid flow in a porous continuum is governed by a combination of a Langevin equation and a continuity equation. Pore-scale velocity fluctuations, the source of mechanical dispersion, are represented by the white noise. The advective velocity (the solution of the Langevin flow equation) causes the mechanical dispersion of a solute. Molecular diffusion and sub-pore-scale Taylor-type dispersion are modeled by an effective stochastic advection-diffusion equation. Here, we propose a method for parameterization of the model for a synthetic porous medium, and we use the model to simulate multicomponent reactive transport in the porous medium. The detailed comparison of the results of the Langevin model with pore-scale and continuum (Darcy) simulations shows that: (1) for a wide range of Peclet numbers the Langevin model predicts the mass of reaction product more accurately than the Darcy model; (2) for small Peclet numbers predictions of both the Langevin and the Darcy models agree well with a prediction of the pore-scale model; and (3) the accuracy of the Langevin and Darcy model deteriorates with the increasing Peclet number but the accuracy of the Langevin model decreases more slowly than the accuracy of the Darcy model. These results show that the separate treatment of advective and diffusive mixing in the stochastic transport model is more accurate than the classical advection-dispersion theory, which uses a single effective diffusion coefficient (the dispersion
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.
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.
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.
Hamiltonian dynamics for complex food webs.
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.
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.
Imaging complex nutrient dynamics in mycelial networks.
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
Complex Dynamical Behavior in Hybrid Systems
2012-09-29
multiple mode switching and other high-level supervisory control architectures, give rise to complicated hybrid dynamical systems with behaviors... switching and other high-level supervisory control architectures, give rise to complicated hybrid dynamical systems with behaviors that can be difficult...Teel, ``Analytical and numerical Lyapunov functions for SISO linear control systems with first-order reset elements”, International Journal of
Exponential rise of dynamical complexity in quantum computing through projections.
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.
Exponential rise of dynamical complexity in quantum computing through projections
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
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.
Variable time-stepping in the pathwise numerical solution of the chemical Langevin equation.
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.
Dynamical Baryogenesis in Complex Hybrid Inflation
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.
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.
Complexity and dynamics of topological and community structure in complex networks
NASA Astrophysics Data System (ADS)
Berec, Vesna
2017-01-01
Complexity is highly susceptible to variations in the network dynamics, reflected on its underlying architecture where topological organization of cohesive subsets into clusters, system's modular structure and resulting hierarchical patterns, are cross-linked with functional dynamics of the system. Here we study connection between hierarchical topological scales of the simplicial complexes and the organization of functional clusters - communities in complex networks. The analysis reveals the full dynamics of different combinatorial structures of q-th-dimensional simplicial complexes and their Laplacian spectra, presenting spectral properties of resulting symmetric and positive semidefinite matrices. The emergence of system's collective behavior from inhomogeneous statistical distribution is induced by hierarchically ordered topological structure, which is mapped to simplicial complex where local interactions between the nodes clustered into subcomplexes generate flow of information that characterizes complexity and dynamics of the full system.
Dynamic information routing in complex networks
NASA Astrophysics Data System (ADS)
Kirst, Christoph; Timme, Marc; Battaglia, Demian
2015-03-01
Flexible information routing fundamentally underlies the function of many biological and artificial networks. Yet, how information may be specifically communicated and dynamically routed in these systems is not well understood. Here we demonstrate that collective dynamical states systematically control patterns of information sharing and transfer in networks, as measured by delayed mutual information and transfer entropies between activities of a network's units. For oscillatory networks we analyze how individual unit properties, the connectivity structure and external inputs all provide means to flexibly control information routing. For multi-scale, modular architectures, we resolve communication patterns at all levels and show how local interventions within one sub-network may remotely control the non-local network-wide routing of information. This theory helps understanding information routing patterns across systems where collective dynamics co-occurs with a communication function.
Langevin processes, agent models and socio-economic systems
NASA Astrophysics Data System (ADS)
Richmond, Peter; Sabatelli, Lorenzo
2004-05-01
We review some approaches to the understanding of fluctuations of financial asset prices. Our approach builds on the development of a simple Langevin equation that characterises stochastic processes. This provides a unifying approach that allows first a straightforward description of the early approaches of Bachelier. We generalize the approach to stochastic equations that model interacting agents. The agent models recently advocated by Marsilli and Solomon are motivated. Using a simple change of variable, we show that the peer pressure model of Marsilli and the wealth dynamics model of Solomon are essentially equivalent. The methods are further shown to be consistent with a global free energy functional that invokes an entropy term based on the Boltzmann formula. There follows a brief digression on the Heston model that extends the simple model to one that, in the language of physics, exhibits a temperature this is subject to stochastic fluctuations. Mathematically the model corresponds to a Feller process. Dragulescu and Yakovenko have shown how the model yields some of the stylised features of asset prices. A more recent approach by Michael and Johnson maximised a Tsallis entropy function subject to simple constraints. They obtain a distribution function for financial returns that exhibits power law tails and which can describe the distribution of returns not only over low but also high frequencies (minute by minute) data for the Dow Jones index. We show how this approach can be developed from an agent model, where the simple Langevin process is now conditioned by local rather than global noise. Such local noise may of course be the origin of speculative frenzy or herding in the market place. The approach yields a BBGKY type hierarchy of equations for the system correlation functions. Of especial interest is that the results can be obtained from a new free energy functional similar to that mentioned above except that a Tsallis like entropy term replaces the
Targeting the dynamics of complex networks
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
c -number quantum generalized Langevin equation for an open system
NASA Astrophysics Data System (ADS)
Kantorovich, L.; Ness, H.; Stella, L.; Lorenz, C. D.
2016-11-01
We derive a c -number generalized Langevin equation (GLE) describing the evolution of the expectation values xixit of the atomic position operators xi of an open system. The latter is coupled linearly to a harmonic bath kept at a fixed temperature. The equations of motion contain a non-Markovian friction term with the classical kernel [L. Kantorovich, Phys. Rev. B 78, 094304 (2008), 10.1103/PhysRevB.78.094304] and a zero mean non-Gaussian random force with correlation functions that depend on the initial preparation of the open system. We used a density operator formalism without assuming that initially the combined system was decoupled. The only approximation made in deriving quantum GLE consists of assuming that the Hamiltonian of the open system at time t can be expanded up to the second order with respect to operators of atomic displacements ui=xi-
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.
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.
Dynamics of Affective States during Complex Learning
ERIC Educational Resources Information Center
D'Mello, Sidney; Graesser, Art
2012-01-01
We propose a model to explain the dynamics of affective states that emerge during deep learning activities. The model predicts that learners in a state of engagement/flow will experience cognitive disequilibrium and confusion when they face contradictions, incongruities, anomalies, obstacles to goals, and other impasses. Learners revert into the…
Dynamical origin of complex motor patterns
NASA Astrophysics Data System (ADS)
Alonso, L. M.; Alliende, J. A.; Mindlin, G. B.
2010-11-01
Behavior emerges as the nervous system generates motor patterns in charge of driving a peripheral biomechanical device. For several cases in the animal kingdom, it has been identified that the motor patterns used in order to accomplish a diversity of tasks are the different solutions of a simple, low dimensional nonlinear dynamical system. Yet, motor patterns emerge from the interaction of an enormous number of individual dynamical units. In this work, we study the dynamics of the average activity of a large set of coupled excitable units which are periodically forced. We show that low dimensional, yet non trivial dynamics emerges. As a case study, we analyze the air sac pressure patterns used by domestic canaries during song, which consists of a succession of repetitions of different syllable types. We show that the pressure patterns used to generate different syllables can be approximated by the solutions of the investigated model. In this way, we are capable of integrating different description scales of our problem.
Exact series model of Langevin transducers with internal losses.
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%.
The Structure and Dynamics of Economic Complexity
NASA Astrophysics Data System (ADS)
Hidalgo, Cesar A.
2011-03-01
Can network science help us understand the structure and evolution of the global economy? In this talk I summarize recent research that uses networks and complexity science to describe and explain the evolution of the mix of products that countries, and cities, produce and export. First, I show how to use information on the network connecting industries to locations to measure the complexity of an economy. Using these measures I demonstrate that countries tend to approach a level of income that is dictated by the complexity of their economies. Next, I study the evolution of economic complexity by showing that it is constrained by a coordination problem that countries, and cities, deal with using three different channels: First, they move to products that are close by, in the Product Space, to the products that they already do. Second, they are more likely to develop a product if a geographical neighbor has already developed it. And third, they follow the nestedness of the network connecting industries to locations. Finally, I introduce a simple model to account for the stylized facts uncovered in the previous sections.
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.
Understanding the complexity of human gait dynamics.
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.
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.
Complex dynamics in supervised work groups
NASA Astrophysics Data System (ADS)
Dal Forno, Arianna; Merlone, Ugo
2013-07-01
In supervised work groups many factors concur to determine productivity. Some of them may be economical and some psychological. According to the literature, the heterogeneity in terms of individual capacity seems to be one of the principal causes for chaotic dynamics in a work group. May sorting groups of people with same capacity for effort be a solution? In the organizational psychology literature an important factor is the engagement in the task, while expectations are central in the economics literature. Therefore, we propose a dynamical model which takes into account both engagement in the task and expectations. An important lesson emerges. The intolerance deriving from the exposure to inequity may not be only caused by differences in individual capacities, but also by these factors combined. Consequently, solutions have to be found in this new direction.
Dust Cloud Dynamics in Complex Plasma Afterglow
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.
The Heterogeneous Dynamics of Economic Complexity
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
Complex dynamical aspects of organic electrolyte solutions.
Palombo, Francesca; Sassi, Paola; Paolantoni, Marco; Barontini, Chiara; Morresi, Assunta; Giorgini, Maria Grazia
2014-01-09
Molecular dynamics of acetone-alkali metal halide (LiBr, LiI) solutions were investigated using depolarized Rayleigh scattering (DRS) and low-frequency Raman spectroscopy in the frequency range from ~0.5 to 200 cm(-1) (~20 GHz to 6 THz). These experiments probe fast dynamical fluctuations of the polarizability anisotropy at picosecond and sub-picosecond time scales that are mainly driven by acetone orientational dynamics. Two distinct contributions were revealed: a fast process (units of picosecond, ps) related to the essentially unperturbed bulk solvent and a slow one (tens of ps) assigned to acetone molecules forming Li(+) solvation shells, decelerated by the motional constraint imposed by the cation. The increase of LiBr and LiI concentration significantly slows down the overall solvent relaxation as a consequence of the increased fraction of acetone molecules involved in the ion solvation shells. The global retardation is larger in LiI than LiBr solutions consistently with viscosity trends. This is explained in terms of ion association (at least ion pairing) more favorably promoted by Br(-) than I(-), with reduced Li(+)-acetone interactions in LiBr than LiI solutions. Anion-induced modulation of the Li(+)···O═C contacts, largely responsible for electrostriction phenomena, also affects the reduced THz-Raman spectral density, ascribed to ultrafast librational motions of acetone molecules. Overall, these findings enlighten the interplay between ion-dipole and ion-ion interactions on the fast solvation dynamics in electrolyte solutions of a typical polar aprotic solvent.
Ferrofluids, complex particle dynamics and braid description
NASA Astrophysics Data System (ADS)
Skjeltorp, Arne T.; Clausen, Sigmund; Helgesen, Geir
2001-05-01
Finely divided magnetic matter is important in many areas of science and technology. A special sub-class of systems are made up of freely moving particles suspended in a carrier liquid where the magnetic interactions play an important role in the actual structure formation and dynamical behaviour. These include ferrofluids, which are colloids of magnetic particles dispersed in carrier fluids, magnetic micro-beads, which are micrometer sized plastic beads loaded with iron oxide, and nonmagnetic particles dispersed in ferrofluids, forming the so-called "magnetic holes". How, in a simple and forceful way, is it possible to characterise the dynamics of systems with several moving components like dispersed magnetic particles subjected to external magnetic fields? The methods based on the theory of braids may provide the answer. Braid theory is a sub-field of mathematics known as topology. It involves classifying different ways of tracing curves in space. The topological description of braids thus provides a simple and concise language for describing the dynamics of a system of moving particles as if they perform a complicated dance as they move about one another, and the braid encodes the choreography of this dance.
Two critical issues in Langevin simulation of gas flows
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.
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…
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…
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.
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.
Separating internal and external dynamics of complex systems.
Argollo de Menezes, M; Barabási, A-L
2004-08-06
The observable behavior of a complex system reflects the mechanisms governing the internal interactions between the system's components and the effect of external perturbations. Here we show that by capturing the simultaneous activity of several of the system's components we can separate the internal dynamics from the external fluctuations. The method allows us to systematically determine the origin of fluctuations in various real systems, finding that while the Internet and the computer chip have robust internal dynamics, highway and Web traffic are driven by external demand. As multichannel measurements are becoming the norm in most fields, the method could help uncover the collective dynamics of a wide array of complex systems.
Dynamics of DNA/intercalator complexes
NASA Astrophysics Data System (ADS)
Schurr, J. M.; Wu, Pengguang; Fujimoto, Bryant S.
1990-05-01
Complexes of linear and supercoiled DNAs with different intercalating dyes are studied by time-resolved fluorescence polarization anisotropy using intercalated ethidium as the probe. Existing theory is generalized to take account of excitation transfer between intercalated ethidiums, and Forster theory is shown to be valid in this context. The effects of intercalated ethidium, 9-aminoacridine, and proflavine on the torsional rigidity of linear and supercoiled DNAs are studied up to rather high binding ratios. Evidence is presented that metastable secondary structure persists in dye-relaxed supercoiled DNAs, which contradicts the standard model of supercoiled DNAs.
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
Untangling complex dynamical systems via derivative-variable correlations
NASA Astrophysics Data System (ADS)
Levnaji, Zoran; Pikovsky, Arkady
2014-05-01
Inferring the internal interaction patterns of a complex dynamical system is a challenging problem. Traditional methods often rely on examining the correlations among the dynamical units. However, in systems such as transcription networks, one unit's variable is also correlated with the rate of change of another unit's variable. Inspired by this, we introduce the concept of derivative-variable correlation, and use it to design a new method of reconstructing complex systems (networks) from dynamical time series. Using a tunable observable as a parameter, the reconstruction of any system with known interaction functions is formulated via a simple matrix equation. We suggest a procedure aimed at optimizing the reconstruction from the time series of length comparable to the characteristic dynamical time scale. Our method also provides a reliable precision estimate. We illustrate the method's implementation via elementary dynamical models, and demonstrate its robustness to both model error and observation error.
Dynamical properties of transportation on complex networks
NASA Astrophysics Data System (ADS)
Shen, Bo; Gao, Zi-You
2008-02-01
We study the dynamical properties of transportation considering the topology structure of networks and congestion effects, based on a proposed simple model. We analyze the behavior of the model for finding out the relationship between the properties of transportation and the structure of network. Analysis and numerical results demonstrate that the transition from free flow to congested regime can be observed for both single link load and network load, but it is discontinuous for single link and continuous for network. We also find that networks with large average degree have small average link betweenness and are more tolerant to congestion, and networks with homogeneous structure can hold more vehicles in stationary state at the subcritical region. Furthermore, by allotting capacity with different mode to links, a manner of enhancing the performance of networks is introduced, which should be helpful in the design of traffic networks.
Collective Dynamics of Complex Plasma Bilayers
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.
Dynamics of ranking processes in complex systems.
Blumm, Nicholas; Ghoshal, Gourab; Forró, Zalán; Schich, Maximilian; Bianconi, Ginestra; Bouchaud, Jean-Philippe; Barabási, Albert-László
2012-09-21
The world is addicted to ranking: everything, from the reputation of scientists, journals, and universities to purchasing decisions is driven by measured or perceived differences between them. Here, we analyze empirical data capturing real time ranking in a number of systems, helping to identify the universal characteristics of ranking dynamics. We develop a continuum theory that not only predicts the stability of the ranking process, but shows that a noise-induced phase transition is at the heart of the observed differences in ranking regimes. The key parameters of the continuum theory can be explicitly measured from data, allowing us to predict and experimentally document the existence of three phases that govern ranking stability.
Dynamics of complex fluids in rotary atomization
NASA Astrophysics Data System (ADS)
Keshavarz, Bavand; McKinley, Gareth; MIT, Mechanical Engineering Department Team
2016-11-01
We study the dynamics of fragmentation for different Newtonian and viscoelastic liquids in rotary atomization. In this process, at the rim of a spinning cup, the centripetal acceleration destabilizes the formed liquid torus due to the Rayleigh-Taylor instability. The resulting ligaments leave the liquid torus with a remarkably repeatable spacing that scales linearly with the inverse of the rotation rate. Filaments then follow a well-defined geometrical path-line that is described by the involute of the circle. Knowing the geometry of this phenomenon we derive the detailed kinematics of this process and compare it with the experimental observations. We show that the ligaments elongate tangentially to the involute of the circle and thin radially as they separate from the cup. A theoretical form is derived for the spatial variation of the filament deformation rate. Once the ligaments are far from the cup they breakup into droplets since they are not stretched fast enough (compared to the critical rate of capillary thinning). We couple these derivations with the known properties of Newtonian and viscoelastic liquids to provide a physical analysis for this fragmentation process that is compared in detail with our experiments.
Structure, dynamics and function of nuclear pore complexes
D’Angelo, M. A.; Hetzer, M. W.
2009-01-01
Nuclear pore complexes are large aqueous channels that penetrate the nuclear envelope, connecting the nuclear interior with the cytoplasm. Until recently, these macromolecular complexes were viewed as static structures whose only function was to control the molecular trafficking between the two compartments. It has now become evident that this simplistic scenario is inaccurate and that nuclear pore complexes are highly dynamic multiprotein assemblies involved in diverse cellular processes ranging from the organization of the cytoskeleton to gene expression. In this review, we will discuss the most recent developments in the nuclear pore complex field, focusing in the assembly, disassembly, maintenance and function of this macromolecular structure. PMID:18786826
Dynamics of nanoparticles in complex fluids
NASA Astrophysics Data System (ADS)
Omari, Rami A.
Soft matter is a subfield of condensed matter including polymers, colloidal dispersions, surfactants, and liquid crystals. These materials are familiar from our everyday life- glues, paints, soaps, and plastics are examples of soft materials. Many phenomena in these systems have the same underlying physical mechanics. Moreover, it has been recognized that combinations of these systems, like for example polymers and colloids, exhibit new properties which are not found in each system separately. These mixed systems have a higher degree of complexity than the separate systems. In order to understand their behavior, knowledge from each subfields of soft matter has to be put together. One of these complex systems is the mixture of nanoparticles with macromolecules such as polymers, proteins, etc. Understanding the interactions in these systems is essential for solving various problems in technological and medical fields, such as developing high performance polymeric materials, chromatography, and drug delivery vehicles. The author of this dissertation investigates fundemental soft matter systems, including colloid dispersions in polymer solutions and binary mixture. The diffusion of gold nanoparticles in semidilute and entangled solutions of polystyrene (PS) in toluene were studied using fluorescence correlation spectroscopy (FCS). In our experiments, the particle radius (R ≈ 2.5 nm) was much smaller compared to the radius of gyration of the chain but comparable to the average mesh size of the fluctuating polymer network. The diffusion coefficient (D) of the particles decreased monotonically with polymer concentration and it can be fitted with a stretched exponential function. At high concentration of the polymer, a clear subdiffusive motion of the particles was observed. The results were compared with the diffusion of free dyes, which showed normal diffusive behavior for all concentrations. In another polymer solution, poly ethylene glycol (PEG) in water, the
Traditional Chinese medicine: potential approaches from modern dynamical complexity theories.
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.
NASA Astrophysics Data System (ADS)
Lisin, E. A.; Lisina, I. I.; Vaulina, O. S.; Petrov, O. F.
2015-03-01
Solution of the inverse Langevin problem is presented for open dissipative systems with anisotropic interparticle interaction. Possibility of applying this solution for experimental determining the anisotropic interaction forces between dust particles in complex plasmas with ion flow is considered. For this purpose, we have tested the method on the results of numerical simulation of chain structures of particles with quasidipole-dipole interaction, similar to the one occurring due to effects of ion focusing in gas discharges. Influence of charge spatial inhomogeneity and fluctuations on the results of recovery is also discussed.
NASA Astrophysics Data System (ADS)
Chou, Chia-Chun
2017-02-01
The Schrödinger-Langevin equation is approximately solved by propagating individual quantum trajectories for barrier transmission problems. Equations of motion are derived through use of the derivative propagation method, which leads to a hierarchy of coupled differential equations for the amplitude of the wave function and the spatial derivatives of the complex action along each trajectory. Computational results are presented for a one-dimensional Eckart barrier and a two-dimensional system involving either a thick or thin Eckart barrier along the reaction coordinate coupled to a harmonic oscillator. Frictional effects on the trajectory, the transmitted wave packet, and the transmission probability are analyzed.
Langevin equation model of dispersion in the convective boundary layer
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
Langevin equation approach to diffusion magnetic resonance imaging.
Cooke, Jennie M; Kalmykov, Yuri P; Coffey, William T; Kerskens, Christian M
2009-12-01
The normal phase diffusion problem in magnetic resonance imaging (MRI) is treated by means of the Langevin equation for the phase variable using only the properties of the characteristic function of Gaussian random variables. The calculation may be simply extended to anomalous diffusion using a fractional generalization of the Langevin equation proposed by Lutz [E. Lutz, Phys. Rev. E 64, 051106 (2001)] pertaining to the fractional Brownian motion of a free particle coupled to a fractal heat bath. The results compare favorably with diffusion-weighted experiments acquired in human neuronal tissue using a 3 T MRI scanner.
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.
Coupled disease-behavior dynamics on complex networks: A review.
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.
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.
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.
Dynamic inclusion complexes of metal nanoparticles inside nanocups.
Alarcón-Correa, Mariana; Lee, Tung-Chun; Fischer, Peer
2015-06-01
Host-guest inclusion complexes are abundant in molecular systems and of fundamental importance in living organisms. Realizing a colloidal analogue of a molecular dynamic inclusion complex is challenging because inorganic nanoparticles (NPs) with a well-defined cavity and portal are difficult to synthesize in high yield and with good structural fidelity. Herein, a generic strategy towards the fabrication of dynamic 1:1 inclusion complexes of metal nanoparticles inside oxide nanocups with high yield (>70%) and regiospecificity (>90%) by means of a reactive double Janus nanoparticle intermediate is reported. Experimental evidence confirms that the inclusion complexes are formed by a kinetically controlled mechanism involving a delicate interplay between bipolar galvanic corrosion and alloying-dealloying oxidation. Release of the NP guest from the nanocups can be efficiently triggered by an external stimulus.
Structure, dynamics, assembly, and evolution of protein complexes.
Marsh, Joseph A; Teichmann, Sarah A
2015-01-01
The assembly of individual proteins into functional complexes is fundamental to nearly all biological processes. In recent decades, many thousands of homomeric and heteromeric protein complex structures have been determined, greatly improving our understanding of the fundamental principles that control symmetric and asymmetric quaternary structure organization. Furthermore, our conception of protein complexes has moved beyond static representations to include dynamic aspects of quaternary structure, including conformational changes upon binding, multistep ordered assembly pathways, and structural fluctuations occurring within fully assembled complexes. Finally, major advances have been made in our understanding of protein complex evolution, both in reconstructing evolutionary histories of specific complexes and in elucidating general mechanisms that explain how quaternary structure tends to evolve. The evolution of quaternary structure occurs via changes in self-assembly state or through the gain or loss of protein subunits, and these processes can be driven by both adaptive and nonadaptive influences.
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 identiο¬ed 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.
Investigating dynamical complexity in the magnetosphere using various entropy measures
NASA Astrophysics Data System (ADS)
Balasis, Georgios; Daglis, Ioannis A.; Papadimitriou, Constantinos; Kalimeri, Maria; Anastasiadis, Anastasios; Eftaxias, Konstantinos
2009-09-01
The complex system of the Earth's magnetosphere corresponds to an open spatially extended nonequilibrium (input-output) dynamical system. The nonextensive Tsallis entropy has been recently introduced as an appropriate information measure to investigate dynamical complexity in the magnetosphere. The method has been employed for analyzing Dst time series and gave promising results, detecting the complexity dissimilarity among different physiological and pathological magnetospheric states (i.e., prestorm activity and intense magnetic storms, respectively). This paper explores the applicability and effectiveness of a variety of computable entropy measures (e.g., block entropy, Kolmogorov entropy, T complexity, and approximate entropy) to the investigation of dynamical complexity in the magnetosphere. We show that as the magnetic storm approaches there is clear evidence of significant lower complexity in the magnetosphere. The observed higher degree of organization of the system agrees with that inferred previously, from an independent linear fractal spectral analysis based on wavelet transforms. This convergence between nonlinear and linear analyses provides a more reliable detection of the transition from the quiet time to the storm time magnetosphere, thus showing evidence that the occurrence of an intense magnetic storm is imminent. More precisely, we claim that our results suggest an important principle: significant complexity decrease and accession of persistency in Dst time series can be confirmed as the magnetic storm approaches, which can be used as diagnostic tools for the magnetospheric injury (global instability). Overall, approximate entropy and Tsallis entropy yield superior results for detecting dynamical complexity changes in the magnetosphere in comparison to the other entropy measures presented herein. Ultimately, the analysis tools developed in the course of this study for the treatment of Dst index can provide convenience for space weather
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.
On Chaotic and Hyperchaotic Complex Nonlinear Dynamical Systems
NASA Astrophysics Data System (ADS)
Mahmoud, Gamal M.
Dynamical systems described by real and complex variables are currently one of the most popular areas of scientific research. These systems play an important role in several fields of physics, engineering, and computer sciences, for example, laser systems, control (or chaos suppression), secure communications, and information science. Dynamical basic properties, chaos (hyperchaos) synchronization, chaos control, and generating hyperchaotic behavior of these systems are briefly summarized. The main advantage of introducing complex variables is the reduction of phase space dimensions by a half. They are also used to describe and simulate the physics of detuned laser and thermal convection of liquid flows, where the electric field and the atomic polarization amplitudes are both complex. Clearly, if the variables of the system are complex the equations involve twice as many variables and control parameters, thus making it that much harder for a hostile agent to intercept and decipher the coded message. Chaotic and hyperchaotic complex systems are stated as examples. Finally there are many open problems in the study of chaotic and hyperchaotic complex nonlinear dynamical systems, which need further investigations. Some of these open problems are given.
The complexity of gene expression dynamics revealed by permutation entropy
2010-01-01
Background High complexity is considered a hallmark of living systems. Here we investigate the complexity of temporal gene expression patterns using the concept of Permutation Entropy (PE) first introduced in dynamical systems theory. The analysis of gene expression data has so far focused primarily on the identification of differentially expressed genes, or on the elucidation of pathway and regulatory relationships. We aim to study gene expression time series data from the viewpoint of complexity. Results Applying the PE complexity metric to abiotic stress response time series data in Arabidopsis thaliana, genes involved in stress response and signaling were found to be associated with the highest complexity not only under stress, but surprisingly, also under reference, non-stress conditions. Genes with house-keeping functions exhibited lower PE complexity. Compared to reference conditions, the PE of temporal gene expression patterns generally increased upon stress exposure. High-complexity genes were found to have longer upstream intergenic regions and more cis-regulatory motifs in their promoter regions indicative of a more complex regulatory apparatus needed to orchestrate their expression, and to be associated with higher correlation network connectivity degree. Arabidopsis genes also present in other plant species were observed to exhibit decreased PE complexity compared to Arabidopsis specific genes. Conclusions We show that Permutation Entropy is a simple yet robust and powerful approach to identify temporal gene expression profiles of varying complexity that is equally applicable to other types of molecular profile data. PMID:21176199
Behavioral-independent features of complex heartbeat dynamics.
Nunes Amaral, L A; Ivanov, P C; Aoyagi, N; Hidaka, I; Tomono, S; Goldberger, A L; Stanley, H E; Yamamoto, Y
2001-06-25
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.
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.
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.
Applications of dynamical complexity theory in traditional Chinese medicine.
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.
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.
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…
Structure and Dynamics of Antigenic Peptides in Complex with TAP
Lehnert, Elisa; Tampé, Robert
2017-01-01
The transporter associated with antigen processing (TAP) selectively translocates antigenic peptides into the endoplasmic reticulum. Loading onto major histocompatibility complex class I molecules and proofreading of these bound epitopes are orchestrated within the macromolecular peptide-loading complex, which assembles on TAP. This heterodimeric ABC-binding cassette (ABC) transport complex is therefore a major component in the adaptive immune response against virally or malignantly transformed cells. Its pivotal role predestines TAP as a target for infectious diseases and malignant disorders. The development of therapies or drugs therefore requires a detailed comprehension of structure and function of this ABC transporter, but our knowledge about various aspects is still insufficient. This review highlights recent achievements on the structure and dynamics of antigenic peptides in complex with TAP. Understanding the binding mode of antigenic peptides in the TAP complex will crucially impact rational design of inhibitors, drug development, or vaccination strategies. PMID:28194151
Identification of simple reaction coordinates from complex dynamics
NASA Astrophysics Data System (ADS)
McGibbon, Robert T.; Husic, Brooke E.; Pande, Vijay S.
2017-01-01
Reaction coordinates are widely used throughout chemical physics to model and understand complex chemical transformations. We introduce a definition of the natural reaction coordinate, suitable for condensed phase and biomolecular systems, as a maximally predictive one-dimensional projection. We then show that this criterion is uniquely satisfied by a dominant eigenfunction of an integral operator associated with the ensemble dynamics. We present a new sparse estimator for these eigenfunctions which can search through a large candidate pool of structural order parameters and build simple, interpretable approximations that employ only a small number of these order parameters. Example applications with a small molecule's rotational dynamics and simulations of protein conformational change and folding show that this approach can filter through statistical noise to identify simple reaction coordinates from complex dynamics.
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
On the Generalized Langevin Equation for a Rouse Bead in a Nonequilibrium Bath
NASA Astrophysics Data System (ADS)
Vandebroek, Hans; Vanderzande, Carlo
2017-04-01
We present the reduced dynamics of a bead in a Rouse chain which is submerged in a bath containing a driving agent that renders it out-of-equilibrium. We first review the generalized Langevin equation of the middle bead in an equilibrated bath. Thereafter, we introduce two driving forces. Firstly, we add a constant force that is applied to the first bead of the chain. We investigate how the generalized Langevin equation changes due to this perturbation for which the system evolves towards a steady state after some time. Secondly, we consider the case of stochastic active forces which will drive the system to a nonequilibrium state. Including these active forces results in an extra contribution to the second fluctuation-dissipation relation. The form of this active contribution is analysed for the specific case of Gaussian, exponentially correlated active forces. We also discuss the resulting rich dynamics of the middle bead in which various regimes of normal diffusion, subdiffusion and superdiffusion can be present.
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.
On the Generalized Langevin Equation for a Rouse Bead in a Nonequilibrium Bath
NASA Astrophysics Data System (ADS)
Vandebroek, Hans; Vanderzande, Carlo
2017-02-01
We present the reduced dynamics of a bead in a Rouse chain which is submerged in a bath containing a driving agent that renders it out-of-equilibrium. We first review the generalized Langevin equation of the middle bead in an equilibrated bath. Thereafter, we introduce two driving forces. Firstly, we add a constant force that is applied to the first bead of the chain. We investigate how the generalized Langevin equation changes due to this perturbation for which the system evolves towards a steady state after some time. Secondly, we consider the case of stochastic active forces which will drive the system to a nonequilibrium state. Including these active forces results in an extra contribution to the second fluctuation-dissipation relation. The form of this active contribution is analysed for the specific case of Gaussian, exponentially correlated active forces. We also discuss the resulting rich dynamics of the middle bead in which various regimes of normal diffusion, subdiffusion and superdiffusion can be present.
Polyacrylic acids-bovine serum albumin complexation: Structure and dynamics.
Othman, Mohamed; Aschi, Adel; Gharbi, Abdelhafidh
2016-01-01
The study of the mixture of BSA with polyacrylic acids at different masses versus pH allowed highlighting the existence of two regimes of weak and strong complexation. These complexes were studied in diluted regime concentration, by turbidimetry, dynamic light scattering (DLS), zeta-potential measurements and nuclear magnetic resonance (NMR). We have followed the pH effect on the structure and properties of the complex. This allowed refining the interpretation of the phase diagram and understanding the observed phenomena. The NMR measurements allowed probing the dynamics of the constituents versus the pH. The computational method was used to precisely determine the electrostatic potential of BSA and how the polyelectrolyte binds to it at different pH.
Dynamical complexity of short and noisy time series - Compression-Complexity vs. Shannon entropy
NASA Astrophysics Data System (ADS)
Nagaraj, Nithin; Balasubramanian, Karthi
2017-01-01
Shannon entropy has been extensively used for characterizing complexity of time series arising from chaotic dynamical systems and stochastic processes such as Markov chains. However, for short and noisy time series, Shannon entropy performs poorly. Complexity measures which are based on lossless compression algorithms are a good substitute in such scenarios. We evaluate the performance of two such Compression-Complexity Measures namely Lempel-Ziv complexity (LZ) and Effort-To-Compress (ETC) on short time series from chaotic dynamical systems in the presence of noise. Both LZ and ETC outperform Shannon entropy (H) in accurately characterizing the dynamical complexity of such systems. For very short binary sequences (which arise in neuroscience applications), ETC has higher number of distinct complexity values than LZ and H, thus enabling a finer resolution. For two-state ergodic Markov chains, we empirically show that ETC converges to a steady state value faster than LZ. Compression-Complexity measures are promising for applications which involve short and noisy time series.
Complex dynamics of blackouts in power transmission systems.
Carreras, B A; Lynch, V E; Dobson, I; Newman, D E
2004-09-01
In order to study the complex global dynamics of a series of blackouts in power transmission systems a dynamical model of such a system has been developed. This model includes a simple representation of the dynamical evolution by incorporating the growth of power demand, the engineering response to system failures, and the upgrade of generator capacity. Two types of blackouts have been identified, each having different dynamical properties. One type of blackout involves the loss of load due to transmission lines reaching their load limits but no line outages. The second type of blackout is associated with multiple line outages. The dominance of one type of blackout over the other depends on operational conditions and the proximity of the system to one of its two critical points. The model displays characteristics such as a probability distribution of blackout sizes with power tails similar to that observed in real blackout data from North America.
Universality classes of fluctuation dynamics in hierarchical complex systems
NASA Astrophysics Data System (ADS)
Macêdo, A. M. S.; González, Iván R. Roa; Salazar, D. S. P.; Vasconcelos, G. L.
2017-03-01
A unified approach is proposed to describe the statistics of the short-time dynamics of multiscale complex systems. The probability density function of the relevant time series (signal) is represented as a statistical superposition of a large time-scale distribution weighted by the distribution of certain internal variables that characterize the slowly changing background. The dynamics of the background is formulated as a hierarchical stochastic model whose form is derived from simple physical constraints, which in turn restrict the dynamics to only two possible classes. The probability distributions of both the signal and the background have simple representations in terms of Meijer G functions. The two universality classes for the background dynamics manifest themselves in the signal distribution as two types of tails: power law and stretched exponential, respectively. A detailed analysis of empirical data from classical turbulence and financial markets shows excellent agreement with the theory.
Laser altimetry reveals complex pattern of Greenland Ice Sheet dynamics.
Csatho, Beata M; Schenk, Anton F; van der Veen, Cornelis J; Babonis, Gregory; Duncan, Kyle; Rezvanbehbahani, Soroush; van den Broeke, Michiel R; Simonsen, Sebastian B; Nagarajan, Sudhagar; van Angelen, Jan H
2014-12-30
We present a new record of ice thickness change, reconstructed at nearly 100,000 sites on the Greenland Ice Sheet (GrIS) from laser altimetry measurements spanning the period 1993-2012, partitioned into changes due to surface mass balance (SMB) and ice dynamics. We estimate a mean annual GrIS mass loss of 243 ± 18 Gt ⋅ y(-1), equivalent to 0.68 mm ⋅ y(-1) sea level rise (SLR) for 2003-2009. Dynamic thinning contributed 48%, with the largest rates occurring in 2004-2006, followed by a gradual decrease balanced by accelerating SMB loss. The spatial pattern of dynamic mass loss changed over this time as dynamic thinning rapidly decreased in southeast Greenland but slowly increased in the southwest, north, and northeast regions. Most outlet glaciers have been thinning during the last two decades, interrupted by episodes of decreasing thinning or even thickening. Dynamics of the major outlet glaciers dominated the mass loss from larger drainage basins, and simultaneous changes over distances up to 500 km are detected, indicating climate control. However, the intricate spatiotemporal pattern of dynamic thickness change suggests that, regardless of the forcing responsible for initial glacier acceleration and thinning, the response of individual glaciers is modulated by local conditions. Recent projections of dynamic contributions from the entire GrIS to SLR have been based on the extrapolation of four major outlet glaciers. Considering the observed complexity, we question how well these four glaciers represent all of Greenland's outlet glaciers.
Control of complex networks requires both structure and dynamics
NASA Astrophysics Data System (ADS)
Gates, Alexander J.; Rocha, Luis M.
2016-04-01
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.
Dynamic heteroleptic metal-phenanthroline complexes: from structure to function.
Saha, Manik Lal; Neogi, Subhadip; Schmittel, Michael
2014-03-14
Dynamically heteroligated metal centres are auspicious platforms to access multicomponent supramolecular systems, the latter showing unique structures, amazing properties and even emergent functions. The great potential of heteroleptic complexes has materialised after the development of appropriate strategies that warrant quantitative formation in spite of the dynamic character. In this perspective, we discuss our endeavours at developing various heteroleptic self-assembly protocols based on sterically bulky 2,9-diarylphenanthrolines and our work toward self-sorted multicomponent architectures and assemblies with new and useful functions.
Complexity of controlling quantum many-body dynamics
NASA Astrophysics Data System (ADS)
Caneva, T.; Silva, A.; Fazio, R.; Lloyd, S.; Calarco, T.; Montangero, S.
2014-04-01
We demonstrate that arbitrary time evolutions of many-body quantum systems can be reversed even in cases when only part of the Hamiltonian can be controlled. The reversed dynamics obtained via optimal control—contrary to standard time-reversal procedures—is extremely robust to external sources of noise. We provide a lower bound on the control complexity of a many-body quantum dynamics in terms of the dimension of the manifold supporting it, elucidating the role played by integrability in this context.
Preictal Dynamics of EEG Complexity in Intracranially Recorded Epileptic Seizure
Bob, Petr; Roman, Robert; Svetlak, Miroslav; Kukleta, Miloslav; Chladek, Jan; Brazdil, Milan
2014-01-01
Abstract Recent findings suggest that neural complexity reflecting a number of independent processes in the brain may characterize typical changes during epileptic seizures and may enable to describe preictal dynamics. With respect to previously reported findings suggesting specific changes in neural complexity during preictal period, we have used measure of pointwise correlation dimension (PD2) as a sensitive indicator of nonstationary changes in complexity of the electroencephalogram (EEG) signal. Although this measure of complexity in epileptic patients was previously reported by Feucht et al (Applications of correlation dimension and pointwise dimension for non-linear topographical analysis of focal onset seizures. Med Biol Comput. 1999;37:208–217), it was not used to study changes in preictal dynamics. With this aim to study preictal changes of EEG complexity, we have examined signals from 11 multicontact depth (intracerebral) EEG electrodes located in 108 cortical and subcortical brain sites, and from 3 scalp EEG electrodes in a patient with intractable epilepsy, who underwent preoperative evaluation before epilepsy surgery. From those 108 EEG contacts, records related to 44 electrode contacts implanted into lesional structures and white matter were not included into the experimental analysis. The results show that in comparison to interictal period (at about 8–6 minutes before seizure onset), there was a statistically significant decrease in PD2 complexity in the preictal period at about 2 minutes before seizure onset in all 64 intracranial channels localized in various brain sites that were included into the analysis and in 3 scalp EEG channels as well. Presented results suggest that using PD2 in EEG analysis may have significant implications for research of preictal dynamics and prediction of epileptic seizures. PMID:25415671
Slip complexity in dynamic models of earthquake faults.
Langer, J S; Carlson, J M; Myers, C R; Shaw, B E
1996-01-01
We summarize recent evidence that models of earthquake faults with dynamically unstable friction laws but no externally imposed heterogeneities can exhibit slip complexity. Two models are described here. The first is a one-dimensional model with velocity-weakening stick-slip friction; the second is a two-dimensional elastodynamic model with slip-weakening friction. Both exhibit small-event complexity and chaotic sequences of large characteristic events. The large events in both models are composed of Heaton pulses. We argue that the key ingredients of these models are reasonably accurate representations of the properties of real faults. PMID:11607671
Bernoulli-Langevin Wind Speed Model for Simulation of Storm Events
NASA Astrophysics Data System (ADS)
Fürstenau, Norbert; Mittendorf, Monika
2016-12-01
We present a simple nonlinear dynamics Langevin model for predicting the instationary wind speed profile during storm events typically accompanying extreme low-pressure situations. It is based on a second-degree Bernoulli equation with δ-correlated Gaussian noise and may complement stationary stochastic wind models. Transition between increasing and decreasing wind speed and (quasi) stationary normal wind and storm states are induced by the sign change of the controlling time-dependent rate parameter k(t). This approach corresponds to the simplified nonlinear laser dynamics for the incoherent to coherent transition of light emission that can be understood by a phase transition analogy within equilibrium thermodynamics [H. Haken, Synergetics, 3rd ed., Springer, Berlin, Heidelberg, New York 1983/2004.]. Evidence for the nonlinear dynamics two-state approach is generated by fitting of two historical wind speed profiles (low-pressure situations "Xaver" and "Christian", 2013) taken from Meteorological Terminal Air Report weather data, with a logistic approximation (i.e. constant rate coefficients k) to the solution of our dynamical model using a sum of sigmoid functions. The analytical solution of our dynamical two-state Bernoulli equation as obtained with a sinusoidal rate ansatz k(t) of period T (=storm duration) exhibits reasonable agreement with the logistic fit to the empirical data. Noise parameter estimates of speed fluctuations are derived from empirical fit residuals and by means of a stationary solution of the corresponding Fokker-Planck equation. Numerical simulations with the Bernoulli-Langevin equation demonstrate the potential for stochastic wind speed profile modeling and predictive filtering under extreme storm events that is suggested for applications in anticipative air traffic management.
Practical synchronization on complex dynamical networks via optimal pinning control
NASA Astrophysics Data System (ADS)
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.
Practical synchronization on complex dynamical networks via optimal pinning control.
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.
Structure and dynamics of small van der Waals complexes
Loreau, J.
2014-10-06
We illustrate computational aspects of the calculation of the potential energy surfaces of small (up to five atoms) van der Waals complexes with high-level quantum chemistry techniques such as the CCSD(T) method with extended basis sets. We discuss the compromise between the required accuracy and the computational time. Further, we show how these potential energy surfaces can be fitted and used in dynamical calculations such as non-reactive inelastic scattering.
Concurrency and Complexity in Verifying Dynamic Adaptation: A Case Study
2005-01-01
Concurrency and Complexity in Verifying Dynamic Adaptation: A Case Study ? Karun N. Biyani?? Sandeep S. Kulkarni? ? ? Department of Computer Science...lattice. References 1. Sandeep S. Kulkarni, Karun N. Biyani, and Umamaheswaran Arumugam. Compos- ing distributed fault-tolerance components. In...and Autonomic Computing. PhD thesis, Michigan State University, 2004. 7. Sandeep Kulkarni and Karun Biyani. Correctness of component-based adaptation
Complex noise in diffusion-limited reactions of replicating and competing species
NASA Astrophysics Data System (ADS)
Hochberg, David; Zorzano, M.-P.; Morán, Federico
2006-06-01
We derive exact Langevin-type equations governing quasispecies dynamics. The inherent multiplicative noise has both real and imaginary parts. The numerical simulation of the underlying complex stochastic partial differential equations is carried out employing the Cholesky decomposition for the noise covariance matrix. This noise produces unavoidable spatiotemporal density fluctuations about the mean-field value. In two dimensions, the fluctuations are suppressed only when the diffusion time scale is much smaller than the amplification time scale for the master species.
E-Index for Differentiating Complex Dynamic Traits
Qi, Jiandong; Sun, Jianfeng; Wang, Jianxin
2016-01-01
While it is a daunting challenge in current biology to understand how the underlying network of genes regulates complex dynamic traits, functional mapping, a tool for mapping quantitative trait loci (QTLs) and single nucleotide polymorphisms (SNPs), has been applied in a variety of cases to tackle this challenge. Though useful and powerful, functional mapping performs well only when one or more model parameters are clearly responsible for the developmental trajectory, typically being a logistic curve. Moreover, it does not work when the curves are more complex than that, especially when they are not monotonic. To overcome this inadaptability, we therefore propose a mathematical-biological concept and measurement, E-index (earliness-index), which cumulatively measures the earliness degree to which a variable (or a dynamic trait) increases or decreases its value. Theoretical proofs and simulation studies show that E-index is more general than functional mapping and can be applied to any complex dynamic traits, including those with logistic curves and those with nonmonotonic curves. Meanwhile, E-index vector is proposed as well to capture more subtle differences of developmental patterns. PMID:27064292
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.
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.
Ultrafast fluorescence dynamics of Sybr Green I/DNA complexes
NASA Astrophysics Data System (ADS)
Trantakis, Ioannis A.; Fakis, Mihalis; Tragoulias, Sotirios S.; Christopoulos, Theodore K.; Persephonis, Peter; Giannetas, Vassilis; Ioannou, Penelope
2010-01-01
The ultrafast dynamics of the DNA fluorescent dye Sybr Green I (SG) has been studied in buffer, single-stranded (ssDNA), double-stranded (dsDNA) and triple-stranded DNA (tsDNA). The fluorescence quantum yield of SG increases dramatically when bound to DNA (including tsDNA). The fluorescence dynamics of the free SG has shown two decay components with ˜0.15-0.4 ps and ˜1.3-2.1 ps time constants, depending on the fluorescence wavelength. Upon binding to DNA, the dynamics becomes slower exhibiting four decay components. This is mainly due to the restriction of the internal motions of the dye caused by the relatively rigid environment of the dye complexed with DNA.
Human opinion dynamics: An inspiration to solve complex optimization problems
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
Cooperative dynamics of a DNA polymerase replicating complex.
Moors, Samuel L C; Herdewijn, Piet; Robben, Johan; Ceulemans, Arnout
2013-12-01
Engineered DNA polymerases continue to be the workhorses of many applications in biotechnology, medicine and nanotechnology. However, the dynamic interplay between the enzyme and the DNA remains unclear. In this study, we performed an extensive replica exchange with flexible tempering (REFT) molecular dynamics simulation of the ternary replicating complex of the archaeal family B DNA polymerase from the thermophile Thermococcus gorgonarius, right before the chemical step. The convoluted dynamics of the enzyme are reducible to rigid-body motions of six subdomains. Upon binding to the enzyme, the DNA double helix conformation changes from a twisted state to a partially untwisted state. The twisted state displays strong bending motion, whereby the DNA oscillates between a straight and a bent conformation. The dynamics of double-stranded DNA are strongly correlated with rotations of the thumb toward the palm, which suggests an assisting role of the enzyme during DNA translocation. In the complex, the primer-template duplex displays increased preference for the B-DNA conformation at the n-2 and n-3 dinucleotide steps. Interactions at the primer 3' end indicate that Thr541 and Asp540 are the acceptors of the first proton transfer in the chemical step, whereas in the translocation step both residues hold the primer 3' terminus in the vicinity of the priming site, which is crucial for high processivity.
Molecular dynamics simulations of a membrane protein/amphipol complex.
Perlmutter, Jason D; Popot, Jean-Luc; Sachs, Jonathan N
2014-10-01
Amphipathic polymers known as "amphipols" provide a highly stabilizing environment for handling membrane proteins in aqueous solutions. A8-35, an amphipol with a polyacrylate backbone and hydrophobic grafts, has been extensively characterized and widely employed for structural and functional studies of membrane proteins using biochemical and biophysical approaches. Given the sensitivity of membrane proteins to their environment, it is important to examine what effects amphipols may have on the structure and dynamics of the proteins they complex. Here we present the first molecular dynamics study of an amphipol-stabilized membrane protein, using Escherichia coli OmpX as a model. We begin by describing the structure of the complexes formed by supplementing OmpX with increasing amounts of A8-35, in order to determine how the amphipol interacts with the transmembrane and extramembrane surfaces of the protein. We then compare the dynamics of the protein in either A8-35, a detergent, or a lipid bilayer. We find that protein dynamics on all accessible length scales is restrained by A8-35, which provides a basis to understanding some of the stabilizing and functional effects of amphipols that have been experimentally observed.
SELF-CONSISTENT LANGEVIN SIMULATION OF COULOMB COLLISIONS IN CHARGED-PARTICLE BEAMS
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.
Langevin modelling of high-frequency Hang-Seng index data
NASA Astrophysics Data System (ADS)
Tang, Lei-Han
2003-06-01
Accurate statistical characterization of financial time series, such as compound stock indices, foreign currency exchange rates, etc., is fundamental to investment risk management, pricing of derivative products and financial decision making. Traditionally, such data were analyzed and modeled from a purely statistics point of view, with little concern on the specifics of financial markets. Increasingly, however, attention has been paid to the underlying economic forces and the collective behavior of investors. Here we summarize a novel approach to the statistical modeling of a major stock index (the Hang Seng index). Based on mathematical results previously derived in the fluid turbulence literature, we show that a Langevin equation with a variable noise amplitude correctly reproduces the ubiquitous fat tails in the probability distribution of intra-day price moves. The form of the Langevin equation suggests that, despite the extremely complex nature of financial concerns and investment strategies at the individual's level, there exist simple universal rules governing the high-frequency price move in a stock market.
Architecture and dynamics of the autophagic phosphatidylinositol 3-kinase complex
Baskaran, Sulochanadevi; Carlson, Lars-Anders; Stjepanovic, Goran; Young, Lindsey N; Kim, Do Jin; Grob, Patricia; Stanley, Robin E; Nogales, Eva; Hurley, James H
2014-01-01
The class III phosphatidylinositol 3-kinase complex I (PI3KC3-C1) that functions in early autophagy consists of the lipid kinase VPS34, the scaffolding protein VPS15, the tumor suppressor BECN1, and the autophagy-specific subunit ATG14. The structure of the ATG14-containing PI3KC3-C1 was determined by single-particle EM, revealing a V-shaped architecture. All of the ordered domains of VPS34, VPS15, and BECN1 were mapped by MBP tagging. The dynamics of the complex were defined using hydrogen–deuterium exchange, revealing a novel 20-residue ordered region C-terminal to the VPS34 C2 domain. VPS15 organizes the complex and serves as a bridge between VPS34 and the ATG14:BECN1 subcomplex. Dynamic transitions occur in which the lipid kinase domain is ejected from the complex and VPS15 pivots at the base of the V. The N-terminus of BECN1, the target for signaling inputs, resides near the pivot point. These observations provide a framework for understanding the allosteric regulation of lipid kinase activity. DOI: http://dx.doi.org/10.7554/eLife.05115.001 PMID:25490155
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.
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.
The Complexity of Dynamics in Small Neural Circuits
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
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.
Entropic contributions in Langevin equations for anisotropic driven systems
NASA Astrophysics Data System (ADS)
de los Santos, Francisco; Garrido, Pedro L.; Muñoz, Miguel A.
2001-07-01
We report on analytical results for a series of anisotropic driven systems in the context of a recently proposed Langevin equation approach. In a recent paper (P.L. Garrido et al., Phys. Rev. E 61 (2000) R4683) we have pointed out that entropic contributions, over-looked in previous works, are crucial in order to obtain suitable Langevin descriptions of driven lattice gases. Here, we present a more detailed derivation and justification of the entropic term for the standard driven lattice gas, and also we extend the improved approach to other anisotropic driven systems, namely: (i) the randomly driven lattice gas, (ii) the two-temperature model and, (iii) the bi-layer lattice gas. It is shown that the two-temperature model and the lattice gas driven either by a random field or by an uniform infinite one are members of the same universality class. When the drive is uniform and finite the ‘standard’ theory is recovered. A Langevin equation describing the phenomenology of the bi-layer lattice gas is also presented.
Laser altimetry reveals complex pattern of Greenland Ice Sheet dynamics
Csatho, Beata M.; Schenk, Anton F.; van der Veen, Cornelis J.; Babonis, Gregory; Duncan, Kyle; Rezvanbehbahani, Soroush; van den Broeke, Michiel R.; Simonsen, Sebastian B.; Nagarajan, Sudhagar; van Angelen, Jan H.
2014-01-01
We present a new record of ice thickness change, reconstructed at nearly 100,000 sites on the Greenland Ice Sheet (GrIS) from laser altimetry measurements spanning the period 1993–2012, partitioned into changes due to surface mass balance (SMB) and ice dynamics. We estimate a mean annual GrIS mass loss of 243 ± 18 Gt⋅y−1, equivalent to 0.68 mm⋅y−1 sea level rise (SLR) for 2003–2009. Dynamic thinning contributed 48%, with the largest rates occurring in 2004–2006, followed by a gradual decrease balanced by accelerating SMB loss. The spatial pattern of dynamic mass loss changed over this time as dynamic thinning rapidly decreased in southeast Greenland but slowly increased in the southwest, north, and northeast regions. Most outlet glaciers have been thinning during the last two decades, interrupted by episodes of decreasing thinning or even thickening. Dynamics of the major outlet glaciers dominated the mass loss from larger drainage basins, and simultaneous changes over distances up to 500 km are detected, indicating climate control. However, the intricate spatiotemporal pattern of dynamic thickness change suggests that, regardless of the forcing responsible for initial glacier acceleration and thinning, the response of individual glaciers is modulated by local conditions. Recent projections of dynamic contributions from the entire GrIS to SLR have been based on the extrapolation of four major outlet glaciers. Considering the observed complexity, we question how well these four glaciers represent all of Greenland’s outlet glaciers. PMID:25512537
Studies of Transition Metal Complexes Using Dynamic NMR Techniques.
NASA Astrophysics Data System (ADS)
Coston, Timothy Peter John
Available from UMI in association with The British Library. This Thesis is primarily concerned with the quantitative study of fluxional processes in, predominantly platinum(IV) complexes, with the ligands 1,1,2,2-tetrakis(methylthio)ethane (MeS)_2CHCH(SMe)_2 , and 1,1,2,2-tetrakis(methylthio)ethene (MeS) _2C=C(SMe)_2. Quantitative information relating to the energetics of these processes has been obtained by a combination of one- and two-dimensional NMR techniques. Chapter One provides an introduction to the background of fluxional processes in transition metal complexes together with data concerning the energetics of the processes that have already been studied by NMR techniques. Chapter Two provides a thorough grounding in NMR techniques, in particular those concerned with the quantitative measurement of rates involved in chemical exchange processes. A description of the use of 2D EXSY NMR spectroscopy in obtaining rate data is given. The properties of the magnetic isotope of platinum are given in Chapter Three. A general survey is also given of some additional compounds that have already been studied by platinum-195 spectroscopy. Chapter Four is concerned with the quantitative study of low temperature (<293 K) fluxionality (sulphur inversion) in the complexes (PtXMe_3 (MeS)_2CHCH(SMe) _2) (X = Cl, Br, I). These complexes were studied by dynamic nuclear magnetic resonance and the information regarding the rates of sulphur inversion was obtained by complete band-shape analysis. Chapter Five is concerned with high temperature (>333 K) fluxionality, of the previous complexes, as studied by a combination of one- and two -dimensional NMR techniques. Aside from obtaining thermodynamic parameters for all the processes, a new novel mechanism is proposed. Chapter Six is primarily concerned with the NMR investigation of the new dinuclear complexes ((PtXMe _3)_2(MeS) _2CHCH(SMe)_2) (X = Cl, Br, I). The solution properties have been established and thermo-dynamic parameters
Scaling analysis of Langevin-type equations
NASA Astrophysics Data System (ADS)
Hanfei; Ma, Benkun
1993-05-01
The approach of scaling behavior of open dissipative systems, which was proposed by Hentschel and Family [Phys. Rev. Lett. 66, 1982 (1991)], is developed to analyze several models. The results show there are two scaling regions, a strong-coupling region and a weak-coupling region, in each model. The dynamic renormalization-group results are exactly the same as the results in the weak-coupling region. The scaling exponents in the strong-coupling region and the crossover behavior are also discussed.
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.
Complex population dynamics and the coalescent under neutrality.
Volz, Erik M
2012-01-01
Estimates of the coalescent effective population size N(e) can be poorly correlated with the true population size. The relationship between N(e) and the population size is sensitive to the way in which birth and death rates vary over time. The problem of inference is exacerbated when the mechanisms underlying population dynamics are complex and depend on many parameters. In instances where nonparametric estimators of N(e) such as the skyline struggle to reproduce the correct demographic history, model-based estimators that can draw on prior information about population size and growth rates may be more efficient. A coalescent model is developed for a large class of populations such that the demographic history is described by a deterministic nonlinear dynamical system of arbitrary dimension. This class of demographic model differs from those typically used in population genetics. Birth and death rates are not fixed, and no assumptions are made regarding the fraction of the population sampled. Furthermore, the population may be structured in such a way that gene copies reproduce both within and across demes. For this large class of models, it is shown how to derive the rate of coalescence, as well as the likelihood of a gene genealogy with heterochronous sampling and labeled taxa, and how to simulate a coalescent tree conditional on a complex demographic history. This theoretical framework encapsulates many of the models used by ecologists and epidemiologists and should facilitate the integration of population genetics with the study of mathematical population dynamics.
Clustering determines the dynamics of complex contagions in multiplex networks
NASA Astrophysics Data System (ADS)
Zhuang, Yong; Arenas, Alex; Yaǧan, Osman
2017-01-01
We present the mathematical analysis of generalized complex contagions in a class of clustered multiplex networks. The model is intended to understand spread of influence, or any other spreading process implying a threshold dynamics, in setups of interconnected networks with significant clustering. The contagion is assumed to be general enough to account for a content-dependent linear threshold model, where each link type has a different weight (for spreading influence) that may depend on the content (e.g., product, rumor, political view) that is being spread. Using the generating functions formalism, we determine the conditions, probability, and expected size of the emergent global cascades. This analysis provides a generalization of previous approaches and is especially useful in problems related to spreading and percolation. The results present nontrivial dependencies between the clustering coefficient of the networks and its average degree. In particular, several phase transitions are shown to occur depending on these descriptors. Generally speaking, our findings reveal that increasing clustering decreases the probability of having global cascades and their size, however, this tendency changes with the average degree. There exists a certain average degree from which on clustering favors the probability and size of the contagion. By comparing the dynamics of complex contagions over multiplex networks and their monoplex projections, we demonstrate that ignoring link types and aggregating network layers may lead to inaccurate conclusions about contagion dynamics, particularly when the correlation of degrees between layers is high.
Generalized synchronization of complex dynamical networks via impulsive control.
Chen, Juan; Lu, Jun-An; Wu, Xiaoqun; Zheng, Wei Xing
2009-12-01
This paper investigates the generalized synchronization (GS) of two typical complex dynamical networks, small-world networks and scale-free networks, in terms of impulsive control strategy. By applying the auxiliary-system approach to networks, we demonstrate theoretically that for any given coupling strength, GS can take place in complex dynamical networks consisting of nonidentical systems. Particularly, for Barabasi-Albert scale-free networks, we look into the relations between GS error and topological parameter m, which denotes the number of edges linking to a new node at each time step, and find out that GS speeds up with increasing m. And for Newman-Watts small-world networks, the time needed to achieve GS decreases as the probability of adding random edges increases. We further reveal how node dynamics affects GS speed on both small-world and scale-free networks. Finally, we analyze how the development of GS depends on impulsive control gains. Some abnormal but interesting phenomena regarding the GS process are also found in simulations.
Vibrational energy transfer dynamics in ruthenium polypyridine transition metal complexes.
Fedoseeva, Marina; Delor, Milan; Parker, Simon C; Sazanovich, Igor V; Towrie, Michael; Parker, Anthony W; Weinstein, Julia A
2015-01-21
Understanding the dynamics of the initial stages of vibrational energy transfer in transition metal complexes is a challenging fundamental question which is also of crucial importance for many applications, such as improving the performance of solar devices or photocatalysis. The present study investigates vibrational energy transport in the ground and the electronic excited state of Ru(4,4'-(COOEt)2-2,2-bpy)2(NCS)2, a close relative of the efficient "N3" dye used in dye-sensitized solar cells. Using the emerging technique of ultrafast two-dimensional infrared spectroscopy, we show that, similarly to other transition-metal complexes, the central Ru heavy atom acts as a "bottleneck" making the energy transfer from small ligands with high energy vibrational stretching frequencies less favorable and thereby affecting the efficiency of vibrational energy flow in the complex. Comparison of the vibrational relaxation times in the electronic ground and excited state of Ru(4,4'-(COOEt)2-2,2-bpy)2(NCS)2 shows that it is dramatically faster in the latter. We propose to explain this observation by the intramolecular electrostatic interactions between the thiocyanate group and partially oxidised Ru metal center, which increase the degree of vibrational coupling between CN and Ru-N modes in the excited state thus reducing structural and thermodynamic barriers that slow down vibrational relaxation and energy transport in the electronic ground state. As a very similar behavior was earlier observed in another transition-metal complex, Re(4,4'-(COOEt)2-2,2'-bpy)(CO)3Cl, we suggest that this effect in vibrational energy dynamics might be common for transition-metal complexes with heavy central atoms.
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.
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.
Slip complexity and frictional heterogeneities in dynamic fault models
NASA Astrophysics Data System (ADS)
Bizzarri, A.
2005-12-01
The numerical modeling of earthquake rupture requires the specification of the fault system geometry, the mechanical properties of the media surrounding the fault, the initial conditions and the constitutive law for fault friction. The latter accounts for the fault zone properties and allows for the description of processes of nucleation, propagation, healing and arrest of a spontaneous rupture. In this work I solve the fundamental elasto-dynamic equation for a planar fault, adopting different constitutive equations (slip-dependent and rate- and state-dependent friction laws). We show that the slip patterns may be complicated by different causes. The spatial heterogeneities of constitutive parameters are able to cause the healing of slip, like barrier-healing or slip pulses. Our numerical experiments show that the heterogeneities of the parameter L affect the dynamic rupture propagation and weakly modify the dynamic stress drop and the rupture velocity. The heterogeneity of a and b parameters affects the dynamic rupture propagation in a more complex way: a velocity strengthening area (a > b) can arrest a dynamic rupture, but can be driven to an instability if suddenly loaded by the dynamic rupture front. Our simulations provide a picture of the complex interactions between fault patches having different frictional properties. Moreover, the slip distribution on the fault plane is complicated considering the effects of the rake rotation during the propagation: depending on the position on the fault plane, the orientation of instantaneous total dynamic traction can change with time with respect to the imposed initial stress direction. These temporal rake rotations depend on the amplitude of the initial stress and on its distribution. They also depend on the curvature and direction of the rupture front with respect to the imposed initial stress direction: this explains why rake rotations are mostly located near the rupture front and within the cohesive zone, where the
Chiu, Chih-Chung; Hung, Chih-Chang; Cheng, Po-Yuan
2016-12-08
The charge-transfer (CT) state relaxation dynamics of the binary (1:1) and ternary (2:1) benzene/tetracyanoethylene (BZ/TCNE) complexes are reported. Steady-state and ultrafast time-resolved broadband fluorescence (TRFL) spectra of TCNE dissolved in a series of BZ/CCl4 mixed solvents are measured to elucidate the spectroscopic properties of the BZ/TCNE complexes and their CT-state relaxation dynamics. Both steady-state and TRFL spectra exhibit marked BZ concentration dependences, which can be attributed to the formation of two types of 2:1 complexes in the ground and excited states. By combining with the density functional theory (DFT) calculations, it was concluded that the BZ concentration dependence of the absorption spectra is mainly due to the formation and excitation of the sandwich-type 2:1 ternary complexes, whereas the changes in fluorescence spectra at high BZ concentrations are due to the formation of the asymmetric-type 2:1 ternary complex CT1 state. A unified mechanism involving both direct excitation and secondary formation of the 2:1 complexes CT states are proposed to account for the observations. The equilibrium charge recombination (CR) time constant of the 1:1 CT1 state is determined to be ∼150 ps in CCl4, whereas that of the 2:1 DDA-type CT1 state becomes ∼70 ps in 10% BZ/CCl4 and ∼34 ps in pure BZ. The CR rates and the CT1-S0 energy gap of these complexes in different solvents exhibit a correlation conforming to the Marcus inverted region. It is concluded that partial charge resonance occurring between the two adjacent BZs in the asymmetric-type 2:1 CT1-state reduces the CR reaction exothermicity and increases the CR rate.
Bifurcation Phenomena of Opinion Dynamics in Complex Networks
NASA Astrophysics Data System (ADS)
Guo, Long; Cai, Xu
In this paper, we study the opinion dynamics of Improved Deffuant model (IDM), where the convergence parameter μ is a function of the opposite’s degree K according to the celebrity effect, in small-world network (SWN) and scale-free network (SFN). Generically, the system undergoes a phase transition from the plurality state to the polarization state and to the consensus state as the confidence parameter ɛ increasing. Furthermore, the evolution of the steady opinion s * as a function of ɛ, and the relation between the minority steady opinion s_{*}^{min} and the individual connectivity k also have been analyzed. Our present work shows the crucial role of the confidence parameter and the complex system topology in the opinion dynamics of IDM.
Functional holography analysis: Simplifying the complexity of dynamical networks
NASA Astrophysics Data System (ADS)
Baruchi, Itay; Grossman, Danny; Volman, Vladislav; Shein, Mark; Hunter, John; Towle, Vernon L.; Ben-Jacob, Eshel
2006-03-01
We present a novel functional holography (FH) analysis devised to study the dynamics of task-performing dynamical networks. The latter term refers to networks composed of dynamical systems or elements, like gene networks or neural networks. The new approach is based on the realization that task-performing networks follow some underlying principles that are reflected in their activity. Therefore, the analysis is designed to decipher the existence of simple causal motives that are expected to be embedded in the observed complex activity of the networks under study. First we evaluate the matrix of similarities (correlations) between the activities of the network's components. We then perform collective normalization of the similarities (or affinity transformation) to construct a matrix of functional correlations. Using dimension reduction algorithms on the affinity matrix, the matrix is projected onto a principal three-dimensional space of the leading eigenvectors computed by the algorithm. To retrieve back information that is lost in the dimension reduction, we connect the nodes by colored lines that represent the level of the similarities to construct a holographic network in the principal space. Next we calculate the activity propagation in the network (temporal ordering) using different methods like temporal center of mass and cross correlations. The causal information is superimposed on the holographic network by coloring the nodes locations according to the temporal ordering of their activities. First, we illustrate the analysis for simple, artificially constructed examples. Then we demonstrate that by applying the FH analysis to modeled and real neural networks as well as recorded brain activity, hidden causal manifolds with simple yet characteristic geometrical and topological features are deciphered in the complex activity. The term "functional holography" is used to indicate that the goal of the analysis is to extract the maximum amount of functional
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.
Complex scattering dynamics and the quantum Hall effects
Trugman, S.A.
1994-12-16
We review both classical and quantum potential scattering in two dimensions in a magnetic field, with applications to the quantum Hall effect. Classical scattering is complex, due to the approach of scattering states to an infinite number of dynamically bound states. Quantum scattering follows the classical behavior rather closely, exhibiting sharp resonances in place of the classical bound states. Extended scatterers provide a quantitative explanation for the breakdown of the QHE at a comparatively small Hall voltage as seen by Kawaji et al., and possibly for noise effects.
Nonlinear complex dynamics and Keynesian rigidity: A short introduction
NASA Astrophysics Data System (ADS)
Jovero, Edgardo
2005-09-01
The topic of this paper is to show that the greater acceptance and intense use of complex nonlinear dynamics in macroeconomics makes sense only within the neoKeynesian tradition. An example is presented regarding the behavior of an open-economy two-sector growth model endowed with Keynesian rigidity. The Keynesian view that structural instability globally exists in the aggregate economy is put forward, and therefore the need arises for policy to alleviate this instability in the form of dampened fluctuations is presented as an alternative view for macroeconomic theorizing.
Intelligent Tutoring for Diagnostic Problem Solving in Complex Dynamic Systems
1991-09-01
tre cOllecti0n Of ormtio. n he r n tmt or er e Of this C ,ollectof of inorma o. Icluding suggeiont for reducing tis burden. to Watiington N _dgar i...AND SUBTITLE S. FUNDING NUMBERS Intelligent Tutoring for Diagnostic Problem Solving in Complex Dynamic Systems C : N00014-87-K-0482 6. AUTHOR(S) PE...Chronister, Sally Cohen, Ed Crowther, Kelly Deyoe, Suzanne Dilley, Brenda Downs, Janet Fath, Dick Henneman , Patty Jones, Merrick Kossack, Steve Krosner
Actin dynamics at the Golgi complex in mammalian cells.
Egea, Gustavo; Lázaro-Diéguez, Francisco; Vilella, Montserrat
2006-04-01
Secretion and endocytosis are highly dynamic processes that are sensitive to external stimuli. Thus, in multicellular organisms, different cell types utilize specialised pathways of intracellular membrane traffic to facilitate specific physiological functions. In addition to the complex internal molecular factors that govern sorting functions and fission or fusion of transport carriers, the actin cytoskeleton plays an important role in both the endocytic and secretory pathways. The interaction between the actin cytoskeleton and membrane trafficking is not restricted to transport processes: it also appears to be directly involved in the biogenesis of Golgi-derived transport carriers (budding and fission processes) and in the maintenance of the unique flat shape of Golgi cisternae.
Control of complex dynamics and chaos in distributed parameter systems
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.
3D dynamic holographic display by modulating complex amplitude experimentally.
Li, Xin; Liu, Juan; Jia, Jia; Pan, Yijie; Wang, Yongtian
2013-09-09
Complex amplitude modulation method is presented theoretically and performed experimentally for three-dimensional (3D) dynamic holographic display with reduced speckle using a single phase-only spatial light modulator. The determination of essential factors is discussed based on the basic principle and theory. The numerical simulations and optical experiments are performed, where the static and animated objects without refinement on the surfaces and without random initial phases are reconstructed successfully. The results indicate that this method can reduce the speckle in reconstructed images effectively; furthermore, it will not cause the internal structure in the reconstructed pixels. Since the complex amplitude modulation is based on the principle of phase-only hologram, it does not need the stringent alignment of pixels. This method can be used for high resolution imaging or measurement in various optical areas.
Itô Formula for Subordinated Langevin Equation. A Case of Time Dependent Force
NASA Astrophysics Data System (ADS)
Weron, A.; Orzeł, S.
2009-05-01
A century after Paul Langevin's landmark paper (1908) we derive here an analog of the Itô formula for subordinated Langevin equation. We show that for any subdiffusion process Yt with time-dependent force its image f(t,Yt) by any function f in C1,2(R+×R) is given again by a stochastic differential equation of Langevin type.
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.
Dynamic analysis of the human brain with complex cerebral sulci.
Tseng, Jung-Ge; Huang, Bo-Wun; Ou, Yi-Wen; Yen, Ke-Tien; Wu, Yi-Te
2016-07-03
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.
Computational complexity of ecological and evolutionary spatial dynamics.
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).
Dynamic spin label study of the barstar-barnase complex.
Timofeev, V P; Balandin, T G; Tkachev, Ya V; Novikov, V V; Lapuk, V A; Deev, S M
2007-09-01
The dynamic spin label method was used to study protein-protein interactions in the model complex of the enzyme barnase (Bn) with its inhibitor barstar. The C40A mutant of barstar (Bs) containing a single cysteine residue was modified with two different spin labels varying in length and structure of a flexible linker. Each spin label was selectively bound to the Cys82 residue, located near the Bn-Bs contact site. The formation of the stable protein complex between Bn and spin labeled Bs was accompanied by a substantial restriction of spin label mobility, indicated by remarkable changes in the registered EPR spectra. Order parameter, S, as an estimate of rapid reorientation of spin label relative to protein molecule, was sharply increasing approaching 1. However, the rotational correlation time tau for spin-labeled Bs and its complex with Bn in solution corresponded precisely to their molecular weights. These data indicate that both Bs and its complex with Bn are rigid protein entities. Spin labels attached to Bs in close proximity to an interface of interaction with Bn, regardless of its structure, undergo significant restriction of mobility by the environment of the contact site of the two proteins. The results show that this approach can be used to investigate fusion proteins containing Bn or Bs.
Thresholds and Complex Dynamics of Interdependent Cascading Infrastructure Systems
NASA Astrophysics Data System (ADS)
Carreras, B. A.; Newman, D. E.; Dobson, I.; Lynch, V. E.; Gradney, Paul
Critical infrastructures have a number of the characteristic properties of complex systems. Among these are infrequent large failures through cascading events. These events, though infrequent, often obey a power law distribution in their probability versus size which suggests that conventional risk analysis does not apply to these systems. Real infrastructure systems typically have an additional layer of complexity, namely the heterogeneous coupling to other infrastructure systems that can allow a failure in one system to propagate to the other system. Here, we model the infrastructure systems through a network with complex system dynamics. We use both mean field theory to get analytic results and a numerical complex systems model, Demon, for computational results. An isolated system has bifurcated fixed points and a cascading threshold which is the same as the bifurcation point. When systems are coupled, this is no longer true and the cascading threshold is different from the bifurcation point of the fixed point solutions. This change in the cascading threshold caused by the interdependence of the system can have an impact on the "safe operation" of interdependent infrastructure systems by changing the critical point and even the power law exponent.
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.
Complex Processes from Dynamical Architectures with Time-Scale Hierarchy
Perdikis, Dionysios; Huys, Raoul; Jirsa, Viktor
2011-01-01
The idea that complex motor, perceptual, and cognitive behaviors are composed of smaller units, which are somehow brought into a meaningful relation, permeates the biological and life sciences. However, no principled framework defining the constituent elementary processes has been developed to this date. Consequently, functional configurations (or architectures) relating elementary processes and external influences are mostly piecemeal formulations suitable to particular instances only. Here, we develop a general dynamical framework for distinct functional architectures characterized by the time-scale separation of their constituents and evaluate their efficiency. Thereto, we build on the (phase) flow of a system, which prescribes the temporal evolution of its state variables. The phase flow topology allows for the unambiguous classification of qualitatively distinct processes, which we consider to represent the functional units or modes within the dynamical architecture. Using the example of a composite movement we illustrate how different architectures can be characterized by their degree of time scale separation between the internal elements of the architecture (i.e. the functional modes) and external interventions. We reveal a tradeoff of the interactions between internal and external influences, which offers a theoretical justification for the efficient composition of complex processes out of non-trivial elementary processes or functional modes. PMID:21347363
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..
Complex processes from dynamical architectures with time-scale hierarchy.
Perdikis, Dionysios; Huys, Raoul; Jirsa, Viktor
2011-02-10
The idea that complex motor, perceptual, and cognitive behaviors are composed of smaller units, which are somehow brought into a meaningful relation, permeates the biological and life sciences. However, no principled framework defining the constituent elementary processes has been developed to this date. Consequently, functional configurations (or architectures) relating elementary processes and external influences are mostly piecemeal formulations suitable to particular instances only. Here, we develop a general dynamical framework for distinct functional architectures characterized by the time-scale separation of their constituents and evaluate their efficiency. Thereto, we build on the (phase) flow of a system, which prescribes the temporal evolution of its state variables. The phase flow topology allows for the unambiguous classification of qualitatively distinct processes, which we consider to represent the functional units or modes within the dynamical architecture. Using the example of a composite movement we illustrate how different architectures can be characterized by their degree of time scale separation between the internal elements of the architecture (i.e. the functional modes) and external interventions. We reveal a tradeoff of the interactions between internal and external influences, which offers a theoretical justification for the efficient composition of complex processes out of non-trivial elementary processes or functional modes.
Complex formation dynamics in a single-molecule electronic device
Wen, Huimin; Li, Wengang; Chen, Jiewei; He, Gen; Li, Longhua; Olson, Mark A.; Sue, Andrew C.-H.; Stoddart, J. Fraser; Guo, Xuefeng
2016-01-01
Single-molecule electronic devices offer unique opportunities to investigate the properties of individual molecules that are not accessible in conventional ensemble experiments. However, these investigations remain challenging because they require (i) highly precise device fabrication to incorporate single molecules and (ii) sufficient time resolution to be able to make fast molecular dynamic measurements. We demonstrate a graphene-molecule single-molecule junction that is capable of probing the thermodynamic and kinetic parameters of a host-guest complex. By covalently integrating a conjugated molecular wire with a pendent crown ether into graphene point contacts, we can transduce the physical [2]pseudorotaxane (de)formation processes between the electron-rich crown ether and a dicationic guest into real-time electrical signals. The conductance of the single-molecule junction reveals two-level fluctuations that are highly dependent on temperature and solvent environments, affording a nondestructive means of quantitatively determining the binding and rate constants, as well as the activation energies, for host-guest complexes. The thermodynamic processes reveal the host-guest binding to be enthalpy-driven and are consistent with conventional 1H nuclear magnetic resonance titration experiments. This electronic device opens up a new route to developing single-molecule dynamics investigations with microsecond resolution for a broad range of chemical and biochemical applications. PMID:28138528
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.
Tear Film Dynamics: the roles of complex structure and rheology
NASA Astrophysics Data System (ADS)
Dey, Mohar; Feng, James; Vivek, Atul S.; Dixit, Harish N.; Richhariya, Ashutosh
2016-11-01
Ocular surface infections such as microbial and fungal keratitis are among leading causes of blindness in the world. A thorough understanding of the pre-corneal tear film dynamics is essential to comprehend the role of various tear layer components in the escalation of such ocular infections. The pre-corneal tear film comprises of three layers of complex fluids, viz. the innermost mucin layer, a hydrophilic protective cover over the sensitive corneal epithelium, the intermediate aqueous layer that forms the bulk of the tear film and is often embedded with large number of bio-polymers either in the form of soluble mucins or pathogens, and finally the outermost lipid layer that stabilizes the film by decreasing the air/tear film interfacial tension. We have developed a comprehensive mathematical model to describe such a film by incorporating the effects of the non-uniform mucin distribution along with the complex rheology of the aqueous layer with/without pathogens, Marangoni effects from the lipid layer and the slip effects at the base of the tear film. A detailed linear stability analysis and a fully non-linear solution determine the break up time (BUT) of such a tear film. We also probe the role of the various components of the pre-corneal tear film in the dynamics of rupture.
Fluid Dynamics of Urban Atmospheres in Complex Terrain
NASA Astrophysics Data System (ADS)
Fernando, H. J. S.
2010-01-01
A majority of the world's urban centers are located in complex terrain, in which local airflow patterns are driven by pressure gradients and thermal forcing, while being strongly influenced by topographic effects and human (anthropogenic) activities. A paradigm in this context is a city located in a valley surrounded by mountains, slopes, and escarpments, in which the airflow is determined by terrain-induced perturbations to synoptic (background) flow, mesoscale thermal circulation (valley/slope flows) generated by local heating or cooling, and by their interaction with factitious (e.g., buildings and roads) and natural (e.g., vegetation and terrain) elements. The dynamics of airflows intrinsic to urban areas in complex terrain is reviewed here by employing idealized flow configurations to illustrate fundamental processes. Urban flows span a wide range of space and time scales and the emphasis here is on mesoscales (1-100 km). Basic fluid dynamics plays a central role in explaining observations of urban flow and in developing subgrid parameterizations for predictive models.
Complex Flare Dynamics Initiated by a Filament-Filament Interaction
NASA Astrophysics Data System (ADS)
Zhu, Chunming; Liu, Rui; Alexander, David; Sun, Xudong; McAteer, James
2015-04-01
We report on a filament eruption that led to a relatively rare filament-filament interaction event. The filaments were located at different heights above the same segment of a circular polarity inversion line (PIL) around a condensed leading sunspot. The onset of the eruption of the lower of the two filaments was accompanied by a simultaneous descent of the upper filament resulting in a convergence and direct interaction of the two filaments. The interaction led to the subsequent merger of the filaments into a single magnetically complex structure that erupted to create a large solar flare and an array of complex dynamical activity. A hard X-ray coronal source and an associated enhancement of hot plasma are observed at the interface between the two interacting filaments. These phenomena are related to the production of a small C flare and the subsequent development of a much stronger M flare. Magnetic loop shrinkage and descending dark voids were observed at different locations as part of the large flare energy release giving us a unique insight into these dynamic flare phenomena.
Synchronization in complex delayed dynamical networks with nonsymmetric coupling
NASA Astrophysics Data System (ADS)
Wu, Jianshe; Jiao, Licheng
2007-12-01
A new general complex delayed dynamical network model with nonsymmetric coupling is introduced, and then we investigate its synchronization phenomena. Several synchronization criteria for delay-independent and delay-dependent synchronization are provided which generalize some previous results. The matrix Jordan canonical formalization method is used instead of the matrix diagonalization method, so in our synchronization criteria, the coupling configuration matrix of the network does not required to be diagonalizable and may have complex eigenvalues. Especially, we show clearly that the synchronizability of a delayed dynamical network is not always characterized by the second-largest eigenvalue even though all the eigenvalues of the coupling configuration matrix are real. Furthermore, the effects of time-delay on synchronizability of networks with unidirectional coupling are studied under some typical network structures. The results are illustrated by delayed networks in which each node is a two-dimensional limit cycle oscillator system consisting of a two-cell cellular neural network, numerical simulations show that these networks can realize synchronization with smaller time-delay, and will lose synchronization when the time-delay increase larger than a threshold.
A study of QM/Langevin-MD simulation for oxygen-evolving center of photosystem II
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.
Functional loop dynamics of the streptavidin-biotin complex.
Song, Jianing; Li, Yongle; Ji, Changge; Zhang, John Z H
2015-01-20
Accelerated molecular dynamics (aMD) simulation is employed to study the functional dynamics of the flexible loop(3-4) 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 loop(3-4) 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 loop(3-4) and biotin. (3) The closure of loop(3-4) is concerted to the stable binding of biotin to streptavidin. When the loop(3-4) is in its open-state, biotin moves out of the binding pocket, indicating that the interactions between the loop(3-4) and biotin are essential in trapping biotin in the binding pocket. (4) In the tetrameric streptavidin system, the conformational change of the loop(3-4) 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.
Robust global synchronization of two complex dynamical networks.
Asheghan, Mohammad Mostafa; Míguez, Joaquín
2013-06-01
We investigate the synchronization of two coupled complex dynamical networks, a problem that has been termed outer synchronization in the literature. Our approach relies on (a) a basic lemma on the eigendecomposition of matrices resulting from Kronecker products and (b) a suitable choice of Lyapunov function related to the synchronization error dynamics. Starting from these two ingredients, a theorem that provides a sufficient condition for outer synchronization of the networks is proved. The condition in the theorem is expressed as a linear matrix inequality. When satisfied, synchronization is guaranteed to occur globally, i.e., independently of the initial conditions of the networks. The argument of the proof includes the design of the gain of the synchronizer, which is a constant square matrix with dimension dependent on the number of dynamic variables in a single network node, but independent of the size of the overall network, which can be much larger. This basic result is subsequently elaborated to simplify the design of the synchronizer, to avoid unnecessarily restrictive assumptions (e.g., diffusivity) on the coupling matrix that defines the topology of the networks and, finally, to obtain synchronizers that are robust to model errors in the parameters of the coupled networks. An illustrative numerical example for the outer synchronization of two networks of classical Lorenz nodes with perturbed parameters is presented.
Functional Loop Dynamics of the Streptavidin-Biotin Complex
NASA Astrophysics Data System (ADS)
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.
Dynamics of Natural Variability: Ecological Complexity in a Changing World
NASA Astrophysics Data System (ADS)
Falk, D. A.; Savage, M.; Swetnam, T. W.
2008-12-01
One of the central challenges in ecology, both theoretical and applied, is understanding how complex systems respond to spatial and temporal variability in their environment. In the context of contemporary and near-term climate variation, this issue can be reframed to ask whether future climate represents "no- analogue" conditions compared to the ecologically relevant past. If future ecosystems operate under climatic and landscape conditions that exceed the envelope of past variability, then it could be argued that our characterizations of how ecosystems functioned in the past may no longer be relevant. In this model, reconstruction of paleoecosystems is still essential for assessing whether systems have exceeded the envelope of past variability, but less useful for predicting future system behavior. This view of the relationship between climate variability and ecosystem function is based largely on statistical characterization of the historical range of variability (HRV) over some temporal and spatial frame of reference. We present an alternative way of thinking about this problem, which focuses on the dynamics of natural systems (DNV) rather than simply their statistical characterization. By emphasizing dynamic interactions among ecosystem components, combined with reconstruction of past environmental variability, we focus attention on the inherently time-varying, nonlinear interaction properties of complex systems. When driving factors exceed the range of past observed values, the ecological response may be correspondingly unfamiliar. This may not mean that the system is operating by different rules, but rather that the functional relationships have shifted to new domains. We provide a series of examples illustrating a DNV perspective, including changes in fire regimes and post-fire vegetation response, insect outbreaks, and species geographic movements in response to changing climates and landscapes. We suggest that an emphasis on dynamic interactions will be
Dislocation dynamics during plastic deformations of complex plasma crystals
NASA Astrophysics Data System (ADS)
Durniak, C.; Samsonov, D.; Ralph, J. F.; Zhdanov, S.; Morfill, G.
2013-11-01
The internal structures of most periodic crystalline solids contain defects. This affects various important mechanical and thermal properties of crystals. Since it is very difficult and expensive to track the motion of individual atoms in real solids, macroscopic model systems, such as complex plasmas, are often used. Complex plasmas consist of micrometer-sized grains immersed into an ion-electron plasma. They exist in solidlike, liquidlike, and gaseouslike states and exhibit a range of nonlinear and dynamic effects, most of which have direct analogies in solids and liquids. Slabs of a monolayer hexagonal complex plasma were subjected to a cycle of uniaxial compression and decompression of large amplitudes to achieve plastic deformations, both in experiments and simulations. During the cycle, the internal structure of the lattice exhibited significant rearrangements. Dislocations (point defects) were generated and displaced in the stressed lattice. They tended to glide parallel to their Burgers vectors under load. It was found that the deformation cycle was macroscopically reversible but irreversible at the particle scale.
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.
Multiple-node basin stability in complex dynamical networks
NASA Astrophysics Data System (ADS)
Mitra, Chiranjit; Choudhary, Anshul; Sinha, Sudeshna; Kurths, Jürgen; Donner, Reik V.
2017-03-01
Dynamical entities interacting with each other on complex networks often exhibit multistability. The stability of a desired steady regime (e.g., a synchronized state) to large perturbations is critical in the operation of many real-world networked dynamical systems such as ecosystems, power grids, the human brain, etc. This necessitates the development of appropriate quantifiers of stability of multiple stable states of such systems. Motivated by the concept of basin stability (BS) [P. J. Menck et al., Nat. Phys. 9, 89 (2013), 10.1038/nphys2516], we propose here the general framework of multiple-node basin stability for gauging the global stability and robustness of networked dynamical systems in response to nonlocal perturbations simultaneously affecting multiple nodes of a system. The framework of multiple-node BS provides an estimate of the critical number of nodes that, when simultaneously perturbed, significantly reduce the capacity of the system to return to the desired stable state. Further, this methodology can be applied to estimate the minimum number of nodes of the network to be controlled or safeguarded from external perturbations to ensure proper operation of the system. Multiple-node BS can also be utilized for probing the influence of spatially localized perturbations or targeted attacks to specific parts of a network. We demonstrate the potential of multiple-node BS in assessing the stability of the synchronized state in a deterministic scale-free network of Rössler oscillators and a conceptual model of the power grid of the United Kingdom with second-order Kuramoto-type nodal dynamics.
Dynamic surface tension analysis of dodecyl sulfate association complexes.
Quigley, W W; Nabi, A; Prazen, B J; Lenghor, N; Grudpan, K; Synovec, R E
2001-09-13
First, a novel calibration method is used to expand the current understanding of spherical drop growth and elongation that occurs during on-line measurements of surface pressure using the dynamic surface tension detector (DSTD). Using a novel surface tension calibration method, the drop radius is calculated as a function of time from experimental drop pressure data and compared to the theoretical drop radius calculated from volumetric flow rate. From this comparison, the drop volume at which the drop shape starts to deviate ( approximately 4 mul) from a spherical shape is readily observed and deviates more significantly by approximately 6 mul drop volume (5% deviation in the ideal spherical drop radius) for the capillary sensing tip employed in the DSTD. From this assessment of drop shape, an experimental method for precise drop detachment referred to as pneumatic drop detachment is employed at a drop volume of 2 mul (two second drops at 60 mul/min) in order to provide rapid dynamic surface tension measurements via the novel on-line calibration methodology. Second, the DSTD is used to observe and study kinetic information for surface-active molecules and association complexes adsorbing to an air-liquid drop interface. Dynamic surface tension measurements are made for sodium dodecyl sulfate (SDS) in the absence and presence of either tetra butyl ammonium (TBA) or chromium (III). Sensitive, indirect detection of chromium and other multiply charged metals at low concentrations is also investigated. The DSTD is utilized in examining the dynamic nature of SDS: cation association at the air-liquid interface of a growing drop. Either TBA or Cr(III) were found to substantially enhance the surface tension lowering of dodecyl sulfate (DS), but the surface tension lowering is accompanied by a considerable kinetic dependence. Essentially, the surface tension lowering of these DS: cation complexes is found to be a fairly slow process in the context of the two second DSTD
2007-06-30
fractal dimensions and Lyapunov exponents . Fractal dimensions characterize geometri- cal complexity of dynamics (e.g., spatial distribution of points along...ant classi3ers (e.g., Lyapunov exponents , and fractal dimensions). The 3rst three steps show how chaotic systems may be separated from stochastic...correlated random walk in which a ¼ 2H, where H is the Hurst exponen interval 0pHp1 with the case H ¼ 0:5 corresponding to a simple rando This model has been
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.
Universal relation between skewness and kurtosis in complex dynamics.
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.
Nonlinear problems of complex natural systems: Sun and climate dynamics.
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.
Invariant Multiparameter Sensitivity to Characterize Dynamical Systems on Complex Networks
NASA Astrophysics Data System (ADS)
Fujiwara, Kenzaburo; Tanaka, Takuma; Nakamura, Kiyohiko
2015-02-01
The behavior of systems is determined by the parameters. Because we seldom know the detailed structure of a system, metrics of parameter sensitivity should be independent of how we model the system. We formulate a new parameter sensitivity metric, which we refer to as "invariant multiparameter sensitivity" (IMPS) because it gives the same result for a class of equivalent models of a system. To investigate the property of IMPS, we firstly apply IMPS to resistor circuits and linear dynamical systems. To examine the dependence of IMPS on network structures, we secondly apply IMPS to nonlinear systems on complex networks. We find that the IMPS of networks of phase oscillators is essentially independent of the number of oscillators. We examine the network-structure dependence of IMPS using a simplified solvable model.
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.
Information processing using a single dynamical node as complex system
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
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.
Dynamical complexity in the perception-based network formation model
NASA Astrophysics Data System (ADS)
Jo, Hang-Hyun; Moon, Eunyoung
2016-12-01
Many link formation mechanisms for the evolution of social networks have been successful to reproduce various empirical findings in social networks. However, they have largely ignored the fact that individuals make decisions on whether to create links to other individuals based on cost and benefit of linking, and the fact that individuals may use perception of the network in their decision making. In this paper, we study the evolution of social networks in terms of perception-based strategic link formation. Here each individual has her own perception of the actual network, and uses it to decide whether to create a link to another individual. An individual with the least perception accuracy can benefit from updating her perception using that of the most accurate individual via a new link. This benefit is compared to the cost of linking in decision making. Once a new link is created, it affects the accuracies of other individuals' perceptions, leading to a further evolution of the actual network. As for initial actual networks, we consider both homogeneous and heterogeneous cases. The homogeneous initial actual network is modeled by Erdős-Rényi (ER) random networks, while we take a star network for the heterogeneous case. In any cases, individual perceptions of the actual network are modeled by ER random networks with controllable linking probability. Then the stable link density of the actual network is found to show discontinuous transitions or jumps according to the cost of linking. As the number of jumps is the consequence of the dynamical complexity, we discuss the effect of initial conditions on the number of jumps to find that the dynamical complexity strongly depends on how much individuals initially overestimate or underestimate the link density of the actual network. For the heterogeneous case, the role of the highly connected individual as an information spreader is also discussed.
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
A new algorithm of Langevin simulation and its application to the SU(2) and SU(3) lattice gauge
NASA Astrophysics Data System (ADS)
Nakajima, Hideo; Furui, Sadataka
1998-04-01
The 2nd order Runge-Kutta scheme Langevin simulation of unquenched QCD in pseudofermion method derived from our general theory shows a behaviour as a function of the Langevin step t better than the Fukugita, Oyanagi, Ukawa's scheme.
Langevin Equation for the Morphological Evolution of Strained Epitaxial Films
NASA Astrophysics Data System (ADS)
Vvedensky, Dimitri; Haselwandter, Christoph
2006-03-01
A stochastic partial differential equation for the morphological evolution of strained epitaxial films is derived from an atomistic master equation. The transition rules in this master equation are based on previous kinetic Monte Carlo (KMC) simulations of a model that incorporates the effects of strain through local environment-dependent energy barriers to adatom detachment from step edges. The morphological consequences of these rules are seen in the transition from layer-by-layer growth to the appearance of three-dimensional islands with increasing strain. The regularization of the exact Langevin description of these rules yields a continuum equation whose lowest-order terms provide a coarse-grained theory of this model. The coefficients in this equation are expressed in terms of the parameters of the original lattice model, so a direct comparison between the morphologies produced by KMC simulations and this Langevin equation are meaningful. Comparisons with previous approaches are made to provide an atomistic interpretation of a similar equation derived by Golovin et al. based on classical elasticity.
Methods for simulating the dynamics of complex biological processes.
Schilstra, Maria J; Martin, Stephen R; Keating, Sarah M
2008-01-01
In this chapter, we provide the basic information required to understand the central concepts in the modeling and simulation of complex biochemical processes. We underline the fact that most biochemical processes involve sequences of interactions between distinct entities (molecules, molecular assemblies), and also stress that models must adhere to the laws of thermodynamics. Therefore, we discuss the principles of mass-action reaction kinetics, the dynamics of equilibrium and steady state, and enzyme kinetics, and explain how to assess transition probabilities and reactant lifetime distributions for first-order reactions. Stochastic simulation of reaction systems in well-stirred containers is introduced using a relatively simple, phenomenological model of microtubule dynamic instability in vitro. We demonstrate that deterministic simulation [by numerical integration of coupled ordinary differential equations (ODE)] produces trajectories that would be observed if the results of many rounds of stochastic simulation of the same system were averaged. In Section V, we highlight several practical issues with regard to the assessment of parameter values. We draw some attention to the development of a standard format for model storage and exchange, and provide a list of selected software tools that may facilitate the model building process, and can be used to simulate the modeled systems.
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
Proceedings of "Optical Probes of Dynamics in Complex Environments"
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 ÃÂÃÂÃÂÃÂÃÂÃÂÃÂÃÂresolved 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.
Tidal dynamics in channels: 2. Complex channel networks
NASA Astrophysics Data System (ADS)
Hill, A. E.; Souza, A. J.
2006-11-01
Intricate networks of tidal channels such as those found in fjordic, barrier island, and branching estuarine systems are often at risk from contaminant inputs and can be important as spawning grounds or migration pathways for marine organisms. These intricate systems are rarely spatially resolved in regional-scale numerical tidal models, and setting up a specific detailed numerical model for the purpose of rapidly assessing the likely tidal behavior of such geometrically complex systems carries a high overhead. Here we describe a straightforward algorithm (implemented in MATLAB) which permits rapid assessment of the linear tidal dynamics in an arbitrarily complex network of tidal channels. The method needs only a minimum of input data, namely, (1) the forcing tidal elevation amplitude and phase at the entrances of those channels directly exposed to the open sea and (2) the length, width, and depth of each channel. The performance of the method is tested against results from the finite element regional-scale numerical model of Foreman et al. (1993) in the fjordic region of western Canada.
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.
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
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
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
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
Quantum Dynamical Behaviour in Complex Systems - A Semiclassical Approach
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
Contagion spreading on complex networks with local deterministic dynamics
NASA Astrophysics Data System (ADS)
Manshour, Pouya; Montakhab, Afshin
2014-07-01
Typically, contagion strength is modeled by a transmission rate λ, whereby all nodes in a network are treated uniformly in a mean-field approximation. However, local agents react differently to the same contagion based on their local characteristics. Following our recent work (Montakhab and Manshour, 2012 [42]), we investigate contagion spreading models with local dynamics on complex networks. We therefore quantify contagions by their quality, 0⩽α⩽1, and follow their spreading as their transmission condition (fitness) is evaluated by local agents. Instead of considering stochastic dynamics, here we consider various deterministic local rules. We find that initial spreading with exponential quality-dependent time scales is followed by a stationary state with a prevalence depending on the quality of the contagion. We also observe various interesting phenomena, for example, high prevalence without the participation of the hubs. This special feature of our "threshold rule" provides a mechanism for high prevalence spreading without the participation of "super-spreaders", in sharp contrast with many standard mechanism of spreading where hubs are believed to play the central role. On the other hand, if local nodes act as agents who stop the transmission once a threshold is reached, we find that spreading is severely hindered in a heterogeneous population while in a homogeneous one significant spreading may occur. We further decouple local characteristics from underlying topology in order to study the role of network topology in various models and find that as long as small-world effect exists, the underlying topology does not contribute to the final stationary state but only affects the initial spreading velocity.
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.
Integrated health management and control of complex dynamical systems
NASA Astrophysics Data System (ADS)
Tolani, Devendra K.
2005-11-01
A comprehensive control and health management strategy for human-engineered complex dynamical systems is formulated for achieving high performance and reliability over a wide range of operation. Results from diverse research areas such as Probabilistic Robust Control (PRC), Damage Mitigating/Life Extending Control (DMC), Discrete Event Supervisory (DES) Control, Symbolic Time Series Analysis (STSA) and Health and Usage Monitoring System (HUMS) have been employed to achieve this goal. Continuous-domain control modules at the lower level are synthesized by PRC and DMC theories, whereas the upper-level supervision is based on DES control theory. In the PRC approach, by allowing different levels of risk under different flight conditions, the control system can achieve the desired trade off between stability robustness and nominal performance. In the DMC approach, component damage is incorporated in the control law to reduce the damage rate for enhanced structural durability. The DES controller monitors the system performance and, based on the mission requirements (e.g., performance metrics and level of damage mitigation), switches among various lower-level controllers. The core idea is to design a framework where the DES controller at the upper-level, mimics human intelligence and makes appropriate decisions to satisfy mission requirements, enhance system performance and structural durability. Recently developed tools in STSA have been used for anomaly detection and failure prognosis. The DMC deals with the usage monitoring or operational control part of health management, where as the issue of health monitoring is addressed by the anomaly detection tools. The proposed decision and control architecture has been validated on two test-beds, simulating the operations of rotorcraft dynamics and aircraft propulsion.
Molecular Dynamic Studies of the Complex Polyethylenimine and Glucose Oxidase
Szefler, Beata; Diudea, Mircea V.; Putz, Mihai V.; Grudzinski, Ireneusz P.
2016-01-01
Glucose oxidase (GOx) is an enzyme produced by Aspergillus, Penicillium and other fungi species. It catalyzes the oxidation of β-d-glucose (by the molecular oxygen or other molecules, like quinones, in a higher oxidation state) to form d-glucono-1,5-lactone, which hydrolyses spontaneously to produce gluconic acid. A coproduct of this enzymatic reaction is hydrogen peroxide (H2O2). GOx has found several commercial applications in chemical and pharmaceutical industries including novel biosensors that use the immobilized enzyme on different nanomaterials and/or polymers such as polyethylenimine (PEI). The problem of GOx immobilization on PEI is retaining the enzyme native activity despite its immobilization onto the polymer surface. Therefore, the molecular dynamic (MD) study of the PEI ligand (C14N8_07_B22) and the GOx enzyme (3QVR) was performed to examine the final complex PEI-GOx stabilization and the affinity of the PEI ligand to the docking sites of the GOx enzyme. The docking procedure showed two places/regions of major interaction of the protein with the polymer PEI: (LIG1) of −5.8 kcal/mol and (LIG2) of −4.5 kcal/mol located inside the enzyme and on its surface, respectively. The values of enthalpy for the PEI-enzyme complex, located inside of the protein (LIG1) and on its surface (LIG2) were computed. Docking also discovered domains of the GOx protein that exhibit no interactions with the ligand or have even repulsive characteristics. The structural data clearly indicate some differences in the ligand PEI behavior bound at the two places/regions of glucose oxidase. PMID:27801788
Molecular Dynamic Studies of the Complex Polyethylenimine and Glucose Oxidase.
Szefler, Beata; Diudea, Mircea V; Putz, Mihai V; Grudzinski, Ireneusz P
2016-10-27
Glucose oxidase (GOx) is an enzyme produced by Aspergillus, Penicillium and other fungi species. It catalyzes the oxidation of β-d-glucose (by the molecular oxygen or other molecules, like quinones, in a higher oxidation state) to form d-glucono-1,5-lactone, which hydrolyses spontaneously to produce gluconic acid. A coproduct of this enzymatic reaction is hydrogen peroxide (H₂O₂). GOx has found several commercial applications in chemical and pharmaceutical industries including novel biosensors that use the immobilized enzyme on different nanomaterials and/or polymers such as polyethylenimine (PEI). The problem of GOx immobilization on PEI is retaining the enzyme native activity despite its immobilization onto the polymer surface. Therefore, the molecular dynamic (MD) study of the PEI ligand (C14N8_07_B22) and the GOx enzyme (3QVR) was performed to examine the final complex PEI-GOx stabilization and the affinity of the PEI ligand to the docking sites of the GOx enzyme. The docking procedure showed two places/regions of major interaction of the protein with the polymer PEI: (LIG1) of -5.8 kcal/mol and (LIG2) of -4.5 kcal/mol located inside the enzyme and on its surface, respectively. The values of enthalpy for the PEI-enzyme complex, located inside of the protein (LIG1) and on its surface (LIG2) were computed. Docking also discovered domains of the GOx protein that exhibit no interactions with the ligand or have even repulsive characteristics. The structural data clearly indicate some differences in the ligand PEI behavior bound at the two places/regions of glucose oxidase.
Proofreading of Peptide-MHC Complexes through Dynamic Multivalent Interactions.
Thomas, Christoph; Tampé, Robert
2017-01-01
The adaptive immune system is able to detect and destroy cells that are malignantly transformed or infected by intracellular pathogens. Specific immune responses against these cells are elicited by antigenic peptides that are presented on major histocompatibility complex class I (MHC I) molecules and recognized by cytotoxic T lymphocytes at the cell surface. Since these MHC I-presented peptides are generated in the cytosol by proteasomal protein degradation, they can be metaphorically described as a window providing immune cells with insights into the state of the cellular proteome. A crucial element of MHC I antigen presentation is the peptide-loading complex (PLC), a multisubunit machinery, which contains as key constituents the transporter associated with antigen processing (TAP) and the MHC I-specific chaperone tapasin (Tsn). While TAP recognizes and shuttles the cytosolic antigenic peptides into the endoplasmic reticulum (ER), Tsn samples peptides in the ER for their ability to form stable complexes with MHC I, a process called peptide proofreading or peptide editing. Through its selection of peptides that improve MHC I stability, Tsn contributes to the hierarchy of immunodominant peptide epitopes. Despite the fact that it concerns a key event in adaptive immunity, insights into the catalytic mechanism of peptide proofreading carried out by Tsn have only lately been gained via biochemical, biophysical, and structural studies. Furthermore, a Tsn homolog called TAP-binding protein-related (TAPBPR) has only recently been demonstrated to function as a second MHC I-specific chaperone and peptide proofreader. Although TAPBPR is PLC-independent and has a distinct allomorph specificity, it is likely to share a common catalytic mechanism with Tsn. This review focuses on the current knowledge of the multivalent protein-protein interactions and the concomitant dynamic molecular processes underlying peptide-proofreading catalysis. We do not only derive a model that
Proofreading of Peptide—MHC Complexes through Dynamic Multivalent Interactions
Thomas, Christoph; Tampé, Robert
2017-01-01
The adaptive immune system is able to detect and destroy cells that are malignantly transformed or infected by intracellular pathogens. Specific immune responses against these cells are elicited by antigenic peptides that are presented on major histocompatibility complex class I (MHC I) molecules and recognized by cytotoxic T lymphocytes at the cell surface. Since these MHC I-presented peptides are generated in the cytosol by proteasomal protein degradation, they can be metaphorically described as a window providing immune cells with insights into the state of the cellular proteome. A crucial element of MHC I antigen presentation is the peptide-loading complex (PLC), a multisubunit machinery, which contains as key constituents the transporter associated with antigen processing (TAP) and the MHC I-specific chaperone tapasin (Tsn). While TAP recognizes and shuttles the cytosolic antigenic peptides into the endoplasmic reticulum (ER), Tsn samples peptides in the ER for their ability to form stable complexes with MHC I, a process called peptide proofreading or peptide editing. Through its selection of peptides that improve MHC I stability, Tsn contributes to the hierarchy of immunodominant peptide epitopes. Despite the fact that it concerns a key event in adaptive immunity, insights into the catalytic mechanism of peptide proofreading carried out by Tsn have only lately been gained via biochemical, biophysical, and structural studies. Furthermore, a Tsn homolog called TAP-binding protein-related (TAPBPR) has only recently been demonstrated to function as a second MHC I-specific chaperone and peptide proofreader. Although TAPBPR is PLC-independent and has a distinct allomorph specificity, it is likely to share a common catalytic mechanism with Tsn. This review focuses on the current knowledge of the multivalent protein–protein interactions and the concomitant dynamic molecular processes underlying peptide-proofreading catalysis. We do not only derive a model that
Stochastic Langevin Model for Flow and Transport in Porous Media
Tartakovsky, Alexandre M.; Tartakovsky, Daniel M.; Meakin, Paul
2008-07-25
A new stochastic Lagrangian model for fluid flow and transport in porous media is described. The fluid is represented by particles whose flow and dispersion in a continuous porous medium is governed by a Langevin equation. Changes in the properties of the fluid particles (e.g. the solute concentration) due to molecular diffusion is governed by the advection-diffusion equation. The separate treatment of advective and diffusive mixing in the stochastic model has an advantage over the classical advection-dispersion theory, which uses a single effective diffusion coefficient (the dispersion coefficient) to describe both types of mixing leading to over-prediction of mixing induced effective reaction rates. The stochastic model predicts much lower reaction product concentrations in mixing induced reactions. In addition the dispersion theory predicts more stable fronts (with a higher effective fractal dimension) than the stochastic model during the growth of Rayleigh-Taylor instabilities.
The generalized Schrödinger–Langevin equation
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.
Complex Dynamic Flows in Solar Flare Sheet Structures
NASA Astrophysics Data System (ADS)
McKenzie, David Eugene; Reeves, K. K.; Savage, S. L.
2012-05-01
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. This work is supported by NASA under contract SP02H3901R from Lockheed-Martin to MSU (DMcK), contract SP02H1701R from Lockheed-Martin to SAO (KKR), and contract NNM07AB07C with the Harvard-Smithsonian Astrophysical Observatory. SLS is supported via a NASA/GSFC NPP appointment administered by Oak Ridge Associated Universities and under the mentorship of G. Holman.
Molecular Dynamics of Mouse Acetylcholinesterase Complexed with Huperzine A
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.
Intrinsic Multi-Scale Dynamic Behaviors of Complex Financial Systems.
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.
Dynamics of the Toxoplasma gondii inner membrane complex
Ouologuem, Dinkorma T.; Roos, David S.
2014-01-01
ABSTRACT 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. PMID:24928899
Dynamic Bayesian Testing of Sets of Variants in Complex Diseases
Zhang, Yu; Ghosh, Soumitra; Hakonarson, Hakon
2014-01-01
Rare genetic variants have recently been studied for genome-wide associations with human complex diseases. Existing rare variant methods are based on the hypothesis-testing framework that predefined variant sets need to be tested separately. The power of those methods is contingent upon accurate selection of variants for testing, and frequently, common variants are left out for separate testing. In this article, we present a novel Bayesian method for simultaneous testing of all genome-wide variants across the whole frequency range. The method allows for much more flexible grouping of variants and dynamically combines them for joint testing. The method accounts for correlation among variant sets, such that only direct associations with the disease are reported, whereas indirect associations due to linkage disequilibrium are not. Consequently, the method can obtain much improved power and flexibility and simultaneously pinpoint multiple disease variants with high resolution. Additional covariates of categorical, discrete, and continuous values can also be added. We compared our method with seven existing categories of approaches for rare variant mapping. We demonstrate that our method achieves similar power to the best methods available to date when testing very rare variants in small SNP sets. When moderately rare or common variants are included, or when testing a large collection of variants, however, our method significantly outperforms all existing methods evaluated in this study. We further demonstrate the power and the usage of our method in a whole-genome resequencing study of type 1 diabetes. PMID:25217050
Intrinsic Multi-Scale Dynamic Behaviors of Complex Financial Systems
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
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.
Notes on the Langevin model for turbulent diffusion of ``marked`` particles
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.
Elizondo-Aguilera, L F; Zubieta Rico, P F; Ruiz-Estrada, H; Alarcón-Waess, O
2014-11-01
A self-consistent generalized Langevin-equation theory is proposed to describe the self- and collective dynamics of a liquid of linear Brownian particles. The equations of motion for the spherical harmonics projections of the collective and self-intermediate-scattering functions, F_{lm,lm}(k,t) and F_{lm,lm}^{S}(k,t), are derived as a contraction of the description involving the stochastic equations of the corresponding tensorial one-particle density n_{lm}(k,t) and the translational (α=T) and rotational (α=R) current densities j_{lm}^{α}(k,t). Similar to the spherical case, these dynamic equations require as an external input the equilibrium structural properties of the system contained in the projections of the static structure factor, denoted by S_{lm,lm}(k). Complementing these exact equations with simple (Vineyard-like) approximate relations for the collective and the self-memory functions we propose a closed self-consistent set of equations for the dynamic properties involved. In the long-time asymptotic limit, these equations become the so-called bifurcation equations, whose solutions (the nonergodicity parameters) can be written, extending the spherical case, in terms of one translational and one orientational scalar dynamic order parameter, γ_{T} and γ_{R}, which characterize the possible dynamical arrest transitions of the system. As a concrete illustrative application of this theory we determine the dynamic arrest diagram of the dipolar hard-sphere fluid. In qualitative agreement with mode coupling theory, the present self-consistent equations also predict three different regions in the state space spanned by the macroscopic control parameters η (volume fraction) and T* (scaled temperature): a region of fully ergodic states, a region of mixed states, in which the translational degrees of freedom become arrested while the orientational degrees of freedom remain ergodic, and a region of fully nonergodic states.
Dutta, Priyanka; Botlani, Mohsen; Varma, Sameer
2014-12-26
The dynamical properties of water at protein-water interfaces are unlike those in the bulk. Here we utilize molecular dynamics simulations to study water dynamics in interstitial regions between two proteins. We consider two natural protein-protein complexes, one in which the Nipah virus G protein binds to cellular ephrin B2 and the other in which the same G protein binds to ephrin B3. While the two complexes are structurally similar, the two ephrins share only a modest sequence identity of ∼50%. X-ray crystallography also suggests that these interfaces are fairly extensive and contain exceptionally large amounts of waters. We find that while the interstitial waters tend to occupy crystallographic sites, almost all waters exhibit residence times of less than hundred picoseconds in the interstitial region. We also find that while the differences in the sequence of the two ephrins result in quantitative differences in the dynamics of interstitial waters, the trends in the shifts with respect to bulk values are similar. Despite the high wetness of the protein-protein interfaces, the dynamics of interstitial waters are considerably slower compared to the bulk-the interstitial waters diffuse an order of magnitude slower and have 2-3 fold longer hydrogen bond lifetimes and 2-1000 fold slower dipole relaxation rates. To understand the role of interstitial waters, we examine how implicit solvent models compare against explicit solvent models in producing ephrin-induced shifts in the G conformational density. Ephrin-induced shifts in the G conformational density are critical to the allosteric activation of another viral protein that mediates fusion. We find that in comparison with the explicit solvent model, the implicit solvent model predicts a more compact G-B2 interface, presumably because of the absence of discrete waters at the G-B2 interface. Simultaneously, we find that the two models yield strikingly different induced changes in the G conformational density, even
Epitope flexibility and dynamic footprint revealed by molecular dynamics of a pMHC-TCR complex.
Reboul, Cyril F; Meyer, Grischa R; Porebski, Benjamin T; Borg, Natalie A; Buckle, Ashley M
2012-01-01
The crystal structures of unliganded and liganded pMHC molecules provide a structural basis for TCR recognition yet they represent 'snapshots' and offer limited insight into dynamics that may be important for interaction and T cell activation. MHC molecules HLA-B*3501 and HLA-B*3508 both bind a 13 mer viral peptide (LPEP) yet only HLA-B*3508-LPEP induces a CTL response characterised by the dominant TCR clonetype SB27. HLA-B*3508-LPEP forms a tight and long-lived complex with SB27, but the relatively weak interaction between HLA-B*3501-LPEP and SB27 fails to trigger an immune response. HLA-B*3501 and HLA-B*3508 differ by only one amino acid (L/R156) located on α2-helix, but this does not alter the MHC or peptide structure nor does this polymorphic residue interact with the peptide or SB27. In the absence of a structural rationalisation for the differences in TCR engagement we performed a molecular dynamics study of both pMHC complexes and HLA-B*3508-LPEP in complex with SB27. This reveals that the high flexibility of the peptide in HLA-B*3501 compared to HLA-B*3508, which was not apparent in the crystal structure alone, may have an under-appreciated role in SB27 recognition. The TCR pivots atop peptide residues 6-9 and makes transient MHC contacts that extend those observed in the crystal structure. Thus MD offers an insight into 'scanning' mechanism of SB27 that extends the role of the germline encoded CDR2α and CDR2β loops. Our data are consistent with the vast body of experimental observations for the pMHC-LPEP-SB27 interaction and provide additional insights not accessible using crystallography.
Epitope Flexibility and Dynamic Footprint Revealed by Molecular Dynamics of a pMHC-TCR Complex
Porebski, Benjamin T.; Borg, Natalie A.; Buckle, Ashley M.
2012-01-01
The crystal structures of unliganded and liganded pMHC molecules provide a structural basis for TCR recognition yet they represent ‘snapshots’ and offer limited insight into dynamics that may be important for interaction and T cell activation. MHC molecules HLA-B*3501 and HLA-B*3508 both bind a 13 mer viral peptide (LPEP) yet only HLA-B*3508-LPEP induces a CTL response characterised by the dominant TCR clonetype SB27. HLA-B*3508-LPEP forms a tight and long-lived complex with SB27, but the relatively weak interaction between HLA-B*3501-LPEP and SB27 fails to trigger an immune response. HLA-B*3501 and HLA-B*3508 differ by only one amino acid (L/R156) located on α2-helix, but this does not alter the MHC or peptide structure nor does this polymorphic residue interact with the peptide or SB27. In the absence of a structural rationalisation for the differences in TCR engagement we performed a molecular dynamics study of both pMHC complexes and HLA-B*3508-LPEP in complex with SB27. This reveals that the high flexibility of the peptide in HLA-B*3501 compared to HLA-B*3508, which was not apparent in the crystal structure alone, may have an under-appreciated role in SB27 recognition. The TCR pivots atop peptide residues 6–9 and makes transient MHC contacts that extend those observed in the crystal structure. Thus MD offers an insight into ‘scanning’ mechanism of SB27 that extends the role of the germline encoded CDR2α and CDR2β loops. Our data are consistent with the vast body of experimental observations for the pMHC-LPEP-SB27 interaction and provide additional insights not accessible using crystallography. PMID:22412359
Cherepanov, D A; Krishtalik, L I; Mulkidjanian, A Y
2001-01-01
Relaxation processes in proteins range in time from picoseconds to seconds. Correspondingly, biological electron transfer (ET) could be controlled by slow protein relaxation. We used the Langevin stochastic approach to describe this type of ET dynamics. Two different types of kinetic behavior were revealed, namely: oscillating ET (that could occur at picoseconds) and monotonically relaxing ET. On a longer time scale, the ET dynamics can include two different kinetic components. The faster one reflects the initial, nonadiabatic ET, whereas the slower one is governed by the medium relaxation. We derived a simple relation between the relative extents of these components, the change in the free energy (DeltaG), and the energy of the slow reorganization Lambda. The rate of ET was found to be determined by slow relaxation at -DeltaG < or = Lambda. The application of the developed approach to experimental data on ET in the bacterial photosynthetic reaction centers allowed a quantitative description of the oscillating features in the primary charge separation and yielded values of Lambda for the slower low-exothermic ET reactions. In all cases but one, the obtained estimates of Lambda varied in the range of 70-100 meV. Because the vast majority of the biological ET reactions are only slightly exothermic (DeltaG > or = -100 meV), the relaxationally controlled ET is likely to prevail in proteins. PMID:11222272
Classification of time series patterns from complex dynamic systems
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.
Sinks without borders: Snowshoe hare dynamics in a complex landscape
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.
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.
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.
Study of the structure and dynamics of complex biological networks
NASA Astrophysics Data System (ADS)
Samal, Areejit
2008-12-01
In this thesis, we have studied the large scale structure and system level dynamics of certain biological networks using tools from graph theory, computational biology and dynamical systems. We study the structure and dynamics of large scale metabolic networks inside three organisms, Escherichia coli, Saccharomyces cerevisiae and Staphylococcus aureus. We also study the dynamics of the large scale genetic network controlling E. coli metabolism. We have tried to explain the observed system level dynamical properties of these networks in terms of their underlying structure. Our studies of the system level dynamics of these large scale biological networks provide a different perspective on their functioning compared to that obtained from purely structural studies. Our study also leads to some new insights on features such as robustness, fragility and modularity of these large scale biological networks. We also shed light on how different networks inside the cell such as metabolic networks and genetic networks are interrelated to each other.
Chaotic and Bifurcating Nonlinear Systems Driven by Noise with Applications to Laser Dynamics
1988-12-30
one or a set of Langevin equations . Noise from a noise generator is passed through a linear filter to establish its correlation time and then applied...random potential U(x) which has a non zero correlation length 1, that is, colored spatial noise. The dynamics are given by the Langevin equation , x - -dU...that we are no longer limited to simulations of Langevin equations with polynomials made up of powers or trigonometric functions of x and y, but can
The complex interplay between mitochondrial dynamics and cardiac metabolism
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
Zanatta, M; Sacchetti, F; Guarini, E; Orecchini, A; Paciaroni, A; Sani, L; Petrillo, C
2015-05-08
A detailed inelastic neutron scattering investigation of the THz dynamics of liquid zinc is presented. The observed Q dependence clearly reveals the existence of a complex dynamics made up of two distinct excitations. The highest energy mode is the prolongation of the longitudinal acoustic density fluctuations whereas the comparison with the phonon dynamics of crystalline hcp zinc suggests a transverse acousticlike nature for the second one. This mode seems related to peculiar anisotropic interactions, possibly connected to the behavior of the crystalline phase.
Xiao, Tiejun
2016-11-01
In this paper, stochastic thermodynamics of delayed bistable Langevin systems near coherence resonance is discussed. We calculate the heat dissipation rate and the information flow of a delayed bistable Langevin system under various noise intensities. Both the heat dissipation rate and the information flow are found to be bell-shaped functions of the noise intensity, which implies that coherence resonance manifests itself in the thermodynamic properties.
Complexities of Organization Dynamics and Development: Leaders and Managers
ERIC Educational Resources Information Center
Nderu-Boddington, Eulalee
2008-01-01
This article shows the theoretical framework for understanding organizational dynamics and development - the change theory and subordinate relationships within contemporary organizations. The emphasis is on power strategies and the relationship to organizational dynamics and development. The integrative process broadens the understanding of…
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)…
NASA Astrophysics Data System (ADS)
Vijaykumar, Adithya; Ouldridge, Thomas E.; ten Wolde, Pieter Rein; Bolhuis, Peter G.
2017-03-01
The modeling of complex reaction-diffusion processes in, for instance, cellular biochemical networks or self-assembling soft matter can be tremendously sped up by employing a multiscale algorithm which combines the mesoscopic Green's Function Reaction Dynamics (GFRD) method with explicit stochastic Brownian, Langevin, or deterministic molecular dynamics to treat reactants at the microscopic scale [A. Vijaykumar, P. G. Bolhuis, and P. R. ten Wolde, J. Chem. Phys. 143, 214102 (2015)]. Here we extend this multiscale MD-GFRD approach to include the orientational dynamics that is crucial to describe the anisotropic interactions often prevalent in biomolecular systems. We present the novel algorithm focusing on Brownian dynamics only, although the methodology is generic. We illustrate the novel algorithm using a simple patchy particle model. After validation of the algorithm, we discuss its performance. The rotational Brownian dynamics MD-GFRD multiscale method will open up the possibility for large scale simulations of protein signalling networks.
On fractional Langevin equation involving two fractional orders
NASA Astrophysics Data System (ADS)
Baghani, Omid
2017-01-01
In numerical analysis, it is frequently needed to examine how far a numerical solution is from the exact one. To investigate this issue quantitatively, we need a tool to measure the difference between them and obviously this task is accomplished by the aid of an appropriate norm on a certain space of functions. For example, Sobolev spaces are indispensable part of theoretical analysis of partial differential equations and boundary integral equations, as well as are necessary for the analysis of some numerical methods for the solving of such equations. But most of articles that appear in this field usually use ‖.‖∞ in the space of C[a, b] which is very restrictive. In this paper, we introduce a new norm that is convenient for the fractional and singular differential equations. Using this norm, the existence and uniqueness of initial value problems for nonlinear Langevin equation with two different fractional orders are studied. In fact, the obtained results could be used for the classical cases. Finally, by two examples we show that we cannot always speak about the existence and uniqueness of solutions just by using the previous methods.
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.
SuperADAM: Upgraded polarized neutron reflectometer at the Institut Laue-Langevin
Devishvili, A.; Zhernenkov, K.; Dennison, A. J. C.; Toperverg, B. P.; Wolff, M.; Hjoervarsson, B.; Zabel, H.
2013-02-15
A new neutron reflectometer SuperADAM has recently been built and commissioned at the Institut Laue-Langevin, Grenoble, France. It replaces the previous neutron reflectometer ADAM. The new instrument uses a solid state polarizer/wavelength filter providing a highly polarized (up to 98.6%) monochromatic neutron flux of 8 Multiplication-Sign 10{sup 4} n cm{sup -2} s{sup -1} with monochromatization {Delta}{lambda}/{lambda}= 0.7% and angular divergence {Delta}{alpha}= 0.2 mrad. The instrument includes both single and position sensitive detectors. The position sensitive detector allows simultaneous measurement of specular reflection and off-specular scattering. Polarization analysis for both specular reflection and off-specular scattering is achieved using either mirror analyzers or a {sup 3}He spin filter cell. High efficiency detectors, low background, and high flux provides a dynamic range of up to seven decades in reflectivity. Detailed specifications and the instrument capabilities are illustrated with examples of recently collected data in the fields of thin film magnetism and thin polymer films.
Non-Gaussian statistics, classical field theory, and realizable Langevin models
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.
Langevin-Poisson-EQT: A dipolar solvent based quasi-continuum approach for electric double layers
NASA Astrophysics Data System (ADS)
Mashayak, S. Y.; Aluru, N. R.
2017-01-01
Water is a highly polar solvent. As a result, electrostatic interactions of interfacial water molecules play a dominant role in determining the distribution of ions in electric double layers (EDLs). Near a surface, an inhomogeneous and anisotropic arrangement of water molecules gives rise to pronounced variations in the electrostatic and hydration energies of ions. Therefore, a detailed description of the structural and dielectric properties of water is important to study EDLs. However, most theoretical models ignore the molecular effects of water and treat water as a background continuum with a uniform dielectric permittivity. Explicit consideration of water polarization and hydration of ions is both theoretically and numerically challenging. In this work, we present an empirical potential-based quasi-continuum theory (EQT) for EDL, which incorporates the polarization and hydration effects of water explicitly. In EQT, water molecules are modeled as Langevin point dipoles and a point dipole based coarse-grained model for water is developed systematically. The space dependence of the dielectric permittivity of water is included in the Poisson equation to compute the electrostatic potential. In addition, to reproduce hydration of ions, ion-water coarse-grained potentials are developed. We demonstrate the EQT framework for EDL by simulating NaCl aqueous electrolyte confined inside slit-like capacitor channels at various ion concentrations and surface charge densities. We show that the ion and water density predictions from EQT agree well with the reference molecular dynamics simulations.
Correlation-based characterisation of time-varying dynamical complexity in the Earth's magnetosphere
NASA Astrophysics Data System (ADS)
Donner, Reik V.; Balasis, George; Kurths, Jürgen
2014-05-01
The dynamical behaviour of the magnetosphere is known to be a sensitive indicator for the response of the system to solar wind coupling. Since the solar activity commonly displays very interesting non-stationary and multi-scale dynamics, the magnetospheric response also exhibits a high degree of dynamical complexity associated with fundamentally different characteristics during periods of quiescence and magnetic storms. The resulting temporal complexity profile has been explored regarding several approaches from applied statistics, dynamical systems theory and statistical mechanics. Here, we propose an alternative way of looking at time-varying dynamical complexity of nonlinear geophysical time series utilising subtle but significant changes in the linear auto-correlation structure of the recorded data. Our approach is demonstrated to sensitively trace the dynamic signatures associated with intense magnetic storms, and to display reasonable skills in distinguishing between quiescence and storm periods. The potentials and methodological limitations of this new viewpoint are discussed in some detail.
Correlation-based characterisation of time-varying dynamical complexity in the Earth's magnetosphere
NASA Astrophysics Data System (ADS)
Donner, R. V.; Balasis, G.
2013-11-01
The dynamical behaviour of the magnetosphere is known to be a sensitive indicator for the response of the system to solar wind coupling. Since the solar activity commonly displays very interesting non-stationary and multi-scale dynamics, the magnetospheric response also exhibits a high degree of dynamical complexity associated with fundamentally different characteristics during periods of quiescence and magnetic storms. The resulting temporal complexity profile has been explored using several approaches from applied statistics, dynamical systems theory and statistical mechanics. Here, we propose an alternative way of looking at time-varying dynamical complexity of nonlinear geophysical time series utilising subtle but significant changes in the linear autocorrelation structure of the recorded data. Our approach is demonstrated to sensitively trace the dynamic signatures associated with intense magnetic storms, and to display reasonable skills in distinguishing between quiescence and storm periods. The potentials and methodological limitations of this new viewpoint are discussed in some detail.
Mattos, Sérgio H V L DE; Vicente, Luiz E; Perez, Archimedes; Piqueira, José R C
2016-01-01
The Brazilian Cerrado is a vegetation mosaic composed of different physiognomies. Discussions remain open regarding the factors and processes responsible for the dynamic and spatial organization of the Cerrado - in its different physiognomies. The contributions of the complexity paradigm in this context are still less exploited, despite its great potential for explanations and predictions presented in previous diverse dynamic systems of complex behavior researches, a category in which the Cerrado can be included. This article has the intention of contributing to the construction of this new perspective, discussing - from theoretical concepts - the paradigm of complexity for the understanding of the organization and the dynamics of the Cerrado.
Srihari, Sriganesh; Yong, Chern Han; Patil, Ashwini; Wong, Limsoon
2015-09-14
Complexes of physically interacting proteins constitute fundamental functional units responsible for driving biological processes within cells. A faithful reconstruction of the entire set of complexes is therefore essential to understand the functional organisation of cells. In this review, we discuss the key contributions of computational methods developed till date (approximately between 2003 and 2015) for identifying complexes from the network of interacting proteins (PPI network). We evaluate in depth the performance of these methods on PPI datasets from yeast, and highlight their limitations and challenges, in particular at detecting sparse and small or sub-complexes and discerning overlapping complexes. We describe methods for integrating diverse information including expression profiles and 3D structures of proteins with PPI networks to understand the dynamics of complex formation, for instance, of time-based assembly of complex subunits and formation of fuzzy complexes from intrinsically disordered proteins. Finally, we discuss methods for identifying dysfunctional complexes in human diseases, an application that is proving invaluable to understand disease mechanisms and to discover novel therapeutic targets. We hope this review aptly commemorates a decade of research on computational prediction of complexes and constitutes a valuable reference for further advancements in this exciting area.
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.
Structural dynamics in complex liquids studied with multidimensional vibrational spectroscopy
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.
Predicting the evolution of complex networks via similarity dynamics
NASA Astrophysics Data System (ADS)
Wu, Tao; Chen, Leiting; Zhong, Linfeng; Xian, Xingping
2017-01-01
Almost all real-world networks are subject to constant evolution, and plenty of them have been investigated empirically to uncover the underlying evolution mechanism. However, the evolution prediction of dynamic networks still remains a challenging problem. The crux of this matter is to estimate the future network links of dynamic networks. This paper studies the evolution prediction of dynamic networks with link prediction paradigm. To estimate the likelihood of the existence of links more accurate, an effective and robust similarity index is presented by exploiting network structure adaptively. Moreover, most of the existing link prediction methods do not make a clear distinction between future links and missing links. In order to predict the future links, the networks are regarded as dynamic systems in this paper, and a similarity updating method, spatial-temporal position drift model, is developed to simulate the evolutionary dynamics of node similarity. Then the updated similarities are used as input information for the future links' likelihood estimation. Extensive experiments on real-world networks suggest that the proposed similarity index performs better than baseline methods and the position drift model performs well for evolution prediction in real-world evolving networks.
Asymmetrically interacting spreading dynamics on complex layered networks
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
Evolving enhanced topologies for the synchronization of dynamical complex networks.
Gorochowski, Thomas E; di Bernardo, Mario; Grierson, Claire S
2010-05-01
Enhancing the synchronization of dynamical networks is of great interest to those designing and analyzing many man-made and natural systems. In this work, we investigate how network topology can be evolved to improve this property through the rewiring of edges. A computational tool called NETEVO performs this task using a simulated annealing metaheuristic. In contrast to other work which considers topological attributes when assessing current performance, we instead take a dynamical approach using simulated output from the system to direct the evolution of the network. Resultant topologies are analyzed using standard network measures, B matrices, and motif distributions. These uncover the convergence of many similar features for all our networks, highlighting also significant differences between those evolved using topological rather than dynamical performance measures.
Collisionally induced stochastic dynamics of fast ions in solids
Burgdoerfer, J.
1989-01-01
Recent developments in the theory of excited state formation in collisions of fast highly charged ions with solids are reviewed. We discuss a classical transport theory employing Monte-Carlo sampling of solutions of a microscopic Langevin equation. Dynamical screening by the dielectric medium as well as multiple collisions are incorporated through the drift and stochastic forces in the Langevin equation. The close relationship between the extrinsically stochastic dynamics described by the Langevin and the intrinsic stochasticity in chaotic nonlinear dynamical systems is stressed. Comparison with experimental data and possible modification by quantum corrections are discussed. 49 refs., 11 figs.
Dynamical weights and enhanced synchronization in adaptive complex networks.
Zhou, Changsong; Kurths, Jürgen
2006-04-28
Dynamical organization of connection weights is studied in scale-free networks of chaotic oscillators, where the coupling strength of a node from its neighbors develops adaptively according to the local synchronization property between the node and its neighbors. We find that when complete synchronization is achieved, the coupling strength becomes weighted and correlated with the topology due to a hierarchical transition to synchronization in heterogeneous networks. Importantly, such an adaptive process enhances significantly the synchronizability of the networks, which could have meaningful implications in the manipulation of dynamical networks.
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.
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.
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.
Unraveling the complexity of mitochondrial complex I assembly: A dynamic process.
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.
Understanding and Designing Military Organizations for a Complex Dynamic Environment
2008-03-25
recognize and develop an understanding about the relationships between organizational design, organizational processes, and the attributes of leadership...and are associated with evolution, ecological niches, social process, human behavior, and economies.4 In other words, complex systems can be...and the Environment The rational approach to defining environmental conditions was used in detail because it lays the ground work for developing an
Microbial bebop: creating music from complex dynamics in microbial ecology.
Larsen, Peter; Gilbert, Jack
2013-01-01
In order for society to make effective policy decisions on complex and far-reaching subjects, such as appropriate responses to global climate change, scientists must effectively communicate complex results to the non-scientifically specialized public. However, there are few ways however to transform highly complicated scientific data into formats that are engaging to the general community. Taking inspiration from patterns observed in nature and from some of the principles of jazz bebop improvisation, we have generated Microbial Bebop, a method by which microbial environmental data are transformed into music. Microbial Bebop uses meter, pitch, duration, and harmony to highlight the relationships between multiple data types in complex biological datasets. We use a comprehensive microbial ecology, time course dataset collected at the L4 marine monitoring station in the Western English Channel as an example of microbial ecological data that can be transformed into music. Four compositions were generated (www.bio.anl.gov/MicrobialBebop.htm.) from L4 Station data using Microbial Bebop. Each composition, though deriving from the same dataset, is created to highlight different relationships between environmental conditions and microbial community structure. The approach presented here can be applied to a wide variety of complex biological datasets.
Teachers' Beliefs and Practices: A Dynamic and Complex Relationship
ERIC Educational Resources Information Center
Zheng, Hongying
2013-01-01
Research on teachers' beliefs has provided useful insights into understanding processes of teaching. However, no research has explored teachers' beliefs as a system nor have researchers investigated the substance of interactions between teachers' beliefs, practices and context. Therefore, the author adopts complexity theory to explore the features…
Complex networks: when random walk dynamics equals synchronization
NASA Astrophysics Data System (ADS)
Kriener, Birgit; Anand, Lishma; Timme, Marc
2012-09-01
Synchrony prevalently emerges from the interactions of coupled dynamical units. For simple systems such as networks of phase oscillators, the asymptotic synchronization process is assumed to be equivalent to a Markov process that models standard diffusion or random walks on the same network topology. In this paper, we analytically derive the conditions for such equivalence for networks of pulse-coupled oscillators, which serve as models for neurons and pacemaker cells interacting by exchanging electric pulses or fireflies interacting via light flashes. We find that the pulse synchronization process is less simple, but there are classes of, e.g., network topologies that ensure equivalence. In particular, local dynamical operators are required to be doubly stochastic. These results provide a natural link between stochastic processes and deterministic synchronization on networks. Tools for analyzing diffusion (or, more generally, Markov processes) may now be transferred to pin down features of synchronization in networks of pulse-coupled units such as neural circuits.
Evolving complex dynamics in electronic models of genetic networks
NASA Astrophysics Data System (ADS)
Mason, Jonathan; Linsay, Paul S.; Collins, J. J.; Glass, Leon
2004-09-01
Ordinary differential equations are often used to model the dynamics and interactions in genetic networks. In one particularly simple class of models, the model genes control the production rates of products of other genes by a logical function, resulting in piecewise linear differential equations. In this article, we construct and analyze an electronic circuit that models this class of piecewise linear equations. This circuit combines CMOS logic and RC circuits to model the logical control of the increase and decay of protein concentrations in genetic networks. We use these electronic networks to study the evolution of limit cycle dynamics. By mutating the truth tables giving the logical functions for these networks, we evolve the networks to obtain limit cycle oscillations of desired period. We also investigate the fitness landscapes of our networks to determine the optimal mutation rate for evolution.
Synchronization in complex dynamical networks with nonsymmetric coupling
NASA Astrophysics Data System (ADS)
Wu, Jianshe; Jiao, Licheng
2008-10-01
Based on the work of Nishikawa and Motter, who have extended the well-known master stability framework to include non-diagonalizable cases, we develop another extension of the master stability framework to obtain criteria for global synchronization. Several criteria for global synchronization are provided which generalize some previous results. The Jordan canonical transformation method is used in stead of the matrix diagonalization method. Especially, we show clearly that, the synchronizability of a dynamical network with nonsymmetric coupling is not always characterized by its second-largest eigenvalue, even though all the eigenvalues of the nonsymmetric coupling matrix are real. Furthermore, the effects of the asymmetry of coupling on synchronizability of networks with different structures are analyzed. Numerical simulations are also done to illustrate and verify the theoretical results on networks in which each node is a dynamical limit cycle oscillator consisting of a two-cell cellular neural network.
A Dynamic Ensemble for Second Language Research: Putting Complexity Theory into Practice
ERIC Educational Resources Information Center
Hiver, Phil; Al-Hoorie, Ali H.
2016-01-01
In this article, we introduce a template of methodological considerations, termed "the dynamic ensemble," for scholars doing or evaluating empirical second language development (SLD) research within a complexity/dynamic systems theory (CDST) framework. Given that CDST principles have yielded significant insight into SLD and have become…
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…
Complex dynamics of industrial transferring in a credit-constrained economy
NASA Astrophysics Data System (ADS)
Yu, Tongkui; Yu, Jiefei; Li, Honggang; Lin, Hongxi
2010-08-01
We present a simple industrial transferring macroeconomic model where credit constrained agents may invest projects of different industries. The feedback effect between agent's net worth and credit composition among industries with different productivity gives rise to complex aggregation dynamics including unique equilibrium, multiple-equilibrium, cycle and chaos. These dynamics replicate many industry transferring patterns and provide economic implications for industry policy.
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.
Reducing congestion on complex networks by dynamic relaxation processes
NASA Astrophysics Data System (ADS)
Macri, Pablo A.; Pastore y Piontti, Ana L.; Braunstein, Lidia A.
2007-12-01
We study the effects of relaxational dynamics on the congestion pressure in general transport networks. We show that the congestion pressure is reduced in scale-free networks if a relaxation mechanism is utilized, while this is in general not the case for non-scale-free graphs such as random graphs. We also present evidence supporting the idea that the emergence of scale-free networks arise from optimization mechanisms to balance the load of the networks nodes.
Efficient modelling of droplet dynamics on complex surfaces
NASA Astrophysics Data System (ADS)
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.
SVEN: Informative Visual Representation of Complex Dynamic Structure
2014-12-23
placement of storylines to decrease clutter (line crossings, straightness, and bends) in the drawing . This paper demonstrates SVEN on several different...of storylines to decrease clutter (line crossings, straightness, and bends) in the drawing . This paper demon- strates SVEN on several different flavors...visualization of graphs (i.e., graph drawing ) has been an active area of research for the past several decades. However, the world is a dynamic place, so
Rhythmic Manipulation of Objects with Complex Dynamics: Predictability over Chaos
Nasseroleslami, Bahman; Hasson, Christopher J.; Sternad, Dagmar
2014-01-01
The study of object manipulation has been largely confined to discrete tasks, where accuracy, mechanical effort, or smoothness were examined to explain subjects' preferred movements. This study investigated a rhythmic manipulation task, which involved continuous interaction with a nonlinear object that led to unpredictable object behavior. Using a simplified virtual version of the task of carrying a cup of coffee, we studied how this unpredictable object behavior affected the selected strategies. The experiment was conducted in a virtual set-up, where subjects moved a cup with a ball inside, modeled by cart-and-pendulum dynamics. Inverse dynamics calculations of the system showed that performing the task with different amplitudes and relative phases required different force profiles and rendered the object's dynamics with different degrees of predictability (quantified by Mutual Information between the applied force and the cup kinematics and its sensitivity). Subjects (n = 8) oscillated the virtual cup between two targets via a robotic manipulandum, paced by a metronome at 1 Hz for 50 trials, each lasting 45 s. They were free to choose their movement amplitude and relative phase between the ball and cup. Experimental results showed that subjects increased their movement amplitudes, which rendered the interactions with the object more predictable and with lower sensitivity to the execution variables. These solutions were associated with higher average exerted force and lower object smoothness, contradicting common expectations from studies on discrete object manipulation and unrestrained movements. Instead, the findings showed that humans selected strategies with higher predictability of interaction dynamics. This finding expressed that humans seek movement strategies where force and kinematics synchronize to repeatable patterns that may require less sensorimotor information processing. PMID:25340581
Dynamical symmetries in Kondo tunneling through complex quantum dots.
Kuzmenko, T; Kikoin, K; Avishai, Y
2002-10-07
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).
Efficient modelling of droplet dynamics on complex surfaces.
Karapetsas, George; Chamakos, Nikolaos T; Papathanasiou, Athanasios G
2016-03-02
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.
Cellular automata and complex dynamics of driven elastic media
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.
Evolution and selection of river networks: Statics, dynamics, and complexity
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
Dynamical interplay between epidemics and cascades in complex networks
NASA Astrophysics Data System (ADS)
Ouyang, Bo; Jin, Xinyu; Xia, Yongxiang; Jiang, Lurong; Wu, Duanpo
2014-04-01
Epidemics and cascading failure are extensively investigated. Traditionally, they are independently studied, but in practice, there are many cases where these two dynamics interact with each other and neither of their effects can be ignored. For example, consider that a digital virus is spreading in a communication network, which is transferring data in the meantime. We build a model based on the epidemiological SIR model and a local load sharing cascading failure model to study the interplay between these two dynamics. In this model, when the dynamical process stops at equilibrium, the nodes both uninfected and unfailed form several clusters. We consider the relative size of the largest one, i.e. the giant component. A phenomenon is observed in both Erdős-Rényi (ER) random networks and Barabási-Albert (BA) scale-free networks that when the infection probability is over some critical value, a giant component forms only if the tolerance parameter α is within some interval (\\alpha_l,\\alpha_u) . In this interval, the size of the remained giant component first increases and then decreases. After analyzing the cause of this phenomenon, we then present in ER random networks a theoretical solution of the key values of \\alpha_l and \\alpha_u , which are very important when we evaluate the robustness of the network. Finally, our theory is verified by numerical simulations.
Complex Ginzburg-Landau equation on networks and its non-uniform dynamics
NASA Astrophysics Data System (ADS)
Nakao, Hiroya
2014-10-01
Dynamics of the complex Ginzburg-Landau equation describing networks of diffusively coupled limit-cycle oscillators near the Hopf bifurcation is reviewed. It is shown that the Benjamin-Feir instability destabilizes the uniformly synchronized state and leads to non-uniform pattern dynamics on general networks. Nonlinear dynamics on several network topologies, i.e., local, nonlocal, global, and random networks, are briefly illustrated by numerical simulations.
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
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
A Fisher-gradient complexity in systems with spatio-temporal dynamics
NASA Astrophysics Data System (ADS)
Arbona, A.; Bona, C.; Massó, J.; Miñano, B.; Plastino, A.
2016-04-01
We define a benchmark for definitions of complexity in systems with spatio-temporal dynamics and employ it in the study of Collective Motion. We show that LMC's complexity displays interesting properties in such systems, while a statistical complexity model (SCM) based on autocorrelation reasonably meets our perception of complexity. However this SCM is not as general as desirable, as it does not merely depend on the system's Probability Distribution Function. Inspired by the notion of Fisher information, we develop a SCM candidate, which we call the Fisher-gradient complexity, which exhibits nice properties from the viewpoint of our benchmark.
The Graph Laplacian and the Dynamics of Complex Networks
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.
Shear-stress-controlled dynamics of nematic complex fluids.
Klapp, Sabine H L; Hess, Siegfried
2010-05-01
Based on a mesoscopic theory we investigate the nonequilibrium dynamics of a sheared nematic liquid, with the control parameter being the shear stress σ xy (rather than the usual shear rate, γ). To this end we supplement the equations of motion for the orientational order parameters by an equation for γ, which then becomes time dependent. Shearing the system from an isotropic state, the stress-controlled flow properties turn out to be essentially identical to those at fixed γ. Pronounced differences occur when the equilibrium state is nematic. Here, shearing at controlled γ yields several nonequilibrium transitions between different dynamic states, including chaotic regimes. The corresponding stress-controlled system has only one transition from a regular periodic into a stationary (shear-aligned) state. The position of this transition in the σ xy-γ plane turns out to be tunable by the delay time entering our control scheme for σ xy. Moreover, a sudden change in the control method can stabilize the chaotic states appearing at fixed γ.
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.
Dynamics of Research Team Formation in Complex Networks
NASA Astrophysics Data System (ADS)
Sun, Caihong; Wan, Yuzi; Chen, Yu
Most organizations encourage the formation of teams to accomplish complicated tasks, and vice verse, effective teams could bring lots benefits and profits for organizations. Network structure plays an important role in forming teams. In this paper, we specifically study the dynamics of team formation in large research communities in which knowledge of individuals plays an important role on team performance and individual utility. An agent-based model is proposed, in which heterogeneous agents from research communities are described and empirically tested. Each agent has a knowledge endowment and a preference for both income and leisure. Agents provide a variable input (‘effort’) and their knowledge endowments to production. They could learn from others in their team and those who are not in their team but have private connections in community to adjust their own knowledge endowment. They are allowed to join other teams or work alone when it is welfare maximizing to do so. Various simulation experiments are conducted to examine the impacts of network topology, knowledge diffusion among community network, and team output sharing mechanisms on the dynamics of team formation.
A complex systems analysis of stick-slip dynamics of a laboratory fault
Walker, David M.; Tordesillas, Antoinette; Small, Michael; Behringer, Robert P.; Tse, Chi K.
2014-03-15
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.
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
Safety assessment document for the dynamic test complex (Building 836)
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.
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
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.
Cao, Youfang; Liang, Jie
2016-01-01
Langevin equation is widely used to study the stochastic effects in molecular networks, as it often approximates well the underlying chemical master equation. However, frequently it is not clear when such an approximation is applicable and when it breaks down. This paper studies the simple Schnakenberg model consisting of three reversible reactions and two molecular species whose concentrations vary. To reduce the residual errors from the conventional formulation of the Langevin equation, the authors propose to explicitly model the effective coupling between macroscopic concentrations of different molecular species. The results show that this formulation is effective in correcting residual errors from the original uncoupled Langevin equation and can approximate the underlying chemical master equation very accurately.
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.
Detecting changes in dynamic and complex acoustic environments
Boubenec, Yves; Lawlor, Jennifer; Górska, Urszula; Shamma, Shihab; Englitz, Bernhard
2017-01-01
Natural sounds such as wind or rain, are characterized by the statistical occurrence of their constituents. Despite their complexity, listeners readily detect changes in these contexts. We here address the neural basis of statistical decision-making using a combination of psychophysics, EEG and modelling. In a texture-based, change-detection paradigm, human performance and reaction times improved with longer pre-change exposure, consistent with improved estimation of baseline statistics. Change-locked and decision-related EEG responses were found in a centro-parietal scalp location, whose slope depended on change size, consistent with sensory evidence accumulation. The potential's amplitude scaled with the duration of pre-change exposure, suggesting a time-dependent decision threshold. Auditory cortex-related potentials showed no response to the change. A dual timescale, statistical estimation model accounted for subjects' performance. Furthermore, a decision-augmented auditory cortex model accounted for performance and reaction times, suggesting that the primary cortical representation requires little post-processing to enable change-detection in complex acoustic environments. DOI: http://dx.doi.org/10.7554/eLife.24910.001 PMID:28262095
Multidimensional Large Amplitude Dynamics in the Pyridine-Water Complex.
Mackenzie, Rebecca B; Dewberry, Christopher T; Cornelius, Ryan D; Smith, C J; Leopold, Kenneth R
2017-02-02
Aqueous pyridine plays an important role in a variety of catalytic processes aimed at harnessing solar energy. In this work, the pyridine-water interaction is studied by microwave spectroscopy and density functional theory calculations. Water forms a hydrogen bond to the nitrogen with the oxygen tilted slightly toward either of the ortho-hydrogens of the pyridine, and a tunneling motion involving in-plane rocking of the water interconverts the resulting equivalent structures. A pair of tunneling states with severely perturbed rotational spectra is identified and their energy separation, ΔE, is inferred from the perturbations and confirmed by direct measurement. Curiously, values of ΔE are 10404.45 and 13566.94 MHz for the H2O and D2O complexes, respectively, revealing an inverted isotope effect upon deuteration. Small splittings in some transitions suggest an additional internal motion making this complex an interesting challenge for theoretical treatments of large amplitude motion. The results underscore the significant effect of the ortho-hydrogens on the intermolecular interaction of pyridine.
Multiagent model and mean field theory of complex auction dynamics
NASA Astrophysics Data System (ADS)
Chen, Qinghua; Huang, Zi-Gang; Wang, Yougui; Lai, Ying-Cheng
2015-09-01
Recent years have witnessed a growing interest in analyzing a variety of socio-economic phenomena using methods from statistical and nonlinear physics. We study a class of complex systems arising from economics, the lowest unique bid auction (LUBA) systems, which is a recently emerged class of online auction game systems. Through analyzing large, empirical data sets of LUBA, we identify a general feature of the bid price distribution: an inverted J-shaped function with exponential decay in the large bid price region. To account for the distribution, we propose a multi-agent model in which each agent bids stochastically in the field of winner’s attractiveness, and develop a theoretical framework to obtain analytic solutions of the model based on mean field analysis. The theory produces bid-price distributions that are in excellent agreement with those from the real data. Our model and theory capture the essential features of human behaviors in the competitive environment as exemplified by LUBA, and may provide significant quantitative insights into complex socio-economic phenomena.
Dealing with the complex dynamics of teaching hospitals.
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.
Detecting changes in dynamic and complex acoustic environments.
Boubenec, Yves; Lawlor, Jennifer; Górska, Urszula; Shamma, Shihab; Englitz, Bernhard
2017-03-06
Natural sounds such as wind or rain, are characterized by the statistical occurrence of their constituents. Despite their complexity, listeners readily detect changes in these contexts. We here address the neural basis of statistical decision-making using a combination of psychophysics, EEG and modelling. In a texture-based, change-detection paradigm, human performance and reaction times improved with longer pre-change exposure, consistent with improved estimation of baseline statistics. Change-locked and decision-related EEG responses were found in a centro-parietal scalp location, whose slope depended on change size, consistent with sensory evidence accumulation. The potential's amplitude scaled with the duration of pre-change exposure, suggesting a time-dependent decision threshold. Auditory cortex-related potentials showed no response to the change. A dual timescale, statistical estimation model accounted for subjects' performance. Furthermore, a decision-augmented auditory cortex model accounted for performance and reaction times, suggesting that the primary cortical representation requires little post-processing to enable change-detection in complex acoustic environments.
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.
Spectroscopy and reaction dynamics of collision complexes containing hydroxyl radicals
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.
Distribution of directional change as a signature of complex dynamics
Burov, Stanislav; Tabei, S. M. Ali; Huynh, Toan; Murrell, Michael P.; Philipson, Louis H.; Rice, Stuart A.; Gardel, Margaret L.; Scherer, Norbert F.; Dinner, Aaron R.
2013-01-01
Analyses of random walks traditionally use the mean square displacement (MSD) as an order parameter characterizing dynamics. We show that the distribution of relative angles of motion between successive time intervals of random walks in two or more dimensions provides information about stochastic processes beyond the MSD. We illustrate the behavior of this measure for common models and apply it to experimental particle tracking data. For a colloidal system, the distribution of relative angles reports sensitively on caging as the density varies. For transport mediated by molecular motors on filament networks in vitro and in vivo, we discover self-similar properties that cannot be described by existing models and discuss possible scenarios that can lead to the elucidated statistical features. PMID:24248363
COMPLEX FLARE DYNAMICS INITIATED BY A FILAMENT–FILAMENT INTERACTION
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.
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.
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.
Momentum conserving Brownian dynamics propagator for complex soft matter fluids
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.
Dynamical Crossover in Complex Networks near the Percolation Transition
NASA Astrophysics Data System (ADS)
Kawasaki, Fumiya; Yakubo, Kousuke
2011-10-01
The return probability P0(t) of random walkers is investigated numerically for several scale-free fractal networks. Our results show that P0(t) is proportional to t-ds/2 with the non-integer spectral dimension ds as in the case of non-scale free fractal networks. We also study how the diffusion process is affected by the structural crossover from a fractal to a small-world architecture in a network near the percolation transition. It is elucidated that the corresponding dynamical crossover is scaled only by the unique characteristic time tξ regardless of whether the network is scale free or not. In addition, the scaling relation ds= 2Df/dw is found to be valid even for scale-free fractal networks, where Df and dw are the fractal and the walk dimensions. These results suggest that qualitative properties of P0(t) are irrelevant to the scale-free nature of networks.
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
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.
Dynamics and control of oscillations in a complex crystalline lattice
NASA Astrophysics Data System (ADS)
Aero, Eron; Fradkov, Alexander; Andrievsky, Boris; Vakulenko, Sergey
2006-04-01
A highly nonlinear system of acoustic and optical oscillations in a complex crystalline lattice consisting of two sublattices is analyzed. The system is obtained as a generalization of the linear Carman Born Kun Huang theory. Large displacements of atoms up to structure stability loss and restructuring are admitted. It is shown that the system has nontrivial solutions describing movements of fronts, emergence of periodic structures and defects. Strong interaction of acoustic and optical modes of oscillation for media without center of symmetry is demonstrated. A possibility of energy-excitation of the optical mode by means of controlling torque applied to the ends of the lattice is examined. Control algorithm based on speed-gradient method is proposed and analyzed numerically. Simulation results demonstrate that application of control may eliminate or reduce influence of initial conditions. An easily realizable nonfeedback version of control algorithm is proposed possessing similar properties.
Restricted dynamics of water around a protein-carbohydrate complex: Computer simulation studies
NASA Astrophysics Data System (ADS)
Jana, Madhurima; Bandyopadhyay, Sanjoy
2012-08-01
Water-mediated protein-carbohydrate interaction is a complex phenomenon responsible for different biological processes in cellular environment. One of the unexplored but important issues in this area is the role played by water during the recognition process and also in controlling the microscopic properties of the complex. In this study, we have carried out atomistic molecular dynamics simulations of a protein-carbohydrate complex formed between the hyaluronan binding domain of the murine Cd44 protein and the octasaccharide hyaluronan in explicit water. Efforts have been made to explore the heterogeneous influence of the complex on the dynamic properties of water present in different regions around it. It is revealed from our analyses that the heterogeneous dynamics of water around the complex are coupled with differential time scales of formation and breaking of hydrogen bonds at the interface. Presence of a highly rigid thin layer of motionally restricted water molecules bridging the protein and the carbohydrate in the common region of the complex has been identified. Such water molecules are expected to play a crucial role in controlling properties of the complex. Importantly, it is demonstrated that the formation of the protein-carbohydrate complex affects the transverse and longitudinal degrees of freedom of the interfacial water molecules in a heterogeneous manner.
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.
Basharov, A. M.
2012-09-15
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.
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.
Gaussian Process Model for Collision Dynamics of Complex Molecules.
Cui, Jie; Krems, Roman V
2015-08-14
We show that a Gaussian process model can be combined with a small number (of order 100) of scattering calculations to provide a multidimensional dependence of scattering observables on the experimentally controllable parameters (such as the collision energy or temperature) as well as the potential energy surface (PES) parameters. For the case of Ar-C_{6}H_{6} collisions, we show that 200 classical trajectory calculations are sufficient to provide a ten-dimensional hypersurface, giving the dependence of the collision lifetimes on the collision energy, internal temperature, and eight PES parameters. This can be used for solving the inverse scattering problem, for the efficient calculation of thermally averaged observables, for reducing the error of the molecular dynamics calculations by averaging over the PES variations, and for the analysis of the sensitivity of the observables to individual parameters determining the PES. Trained by a combination of classical and quantum calculations, the model provides an accurate description of the quantum scattering cross sections, even near scattering resonances.
Universal data-based method for reconstructing complex networks with binary-state dynamics
NASA Astrophysics Data System (ADS)
Li, Jingwen; Shen, Zhesi; Wang, Wen-Xu; Grebogi, Celso; Lai, Ying-Cheng
2017-03-01
To understand, predict, and control complex networked systems, a prerequisite is to reconstruct the network structure from observable data. Despite recent progress in network reconstruction, binary-state dynamics that are ubiquitous in nature, technology, and society still present an outstanding challenge in this field. Here we offer a framework for reconstructing complex networks with binary-state dynamics by developing a universal data-based linearization approach that is applicable to systems with linear, nonlinear, discontinuous, or stochastic dynamics governed by monotonic functions. The linearization procedure enables us to convert the network reconstruction into a sparse signal reconstruction problem that can be resolved through convex optimization. We demonstrate generally high reconstruction accuracy for a number of complex networks associated with distinct binary-state dynamics from using binary data contaminated by noise and missing data. Our framework is completely data driven, efficient, and robust, and does not require any a priori knowledge about the detailed dynamical process on the network. The framework represents a general paradigm for reconstructing, understanding, and exploiting complex networked systems with binary-state dynamics.
Interfacial Polymerization on Dynamic Complex Colloids: Creating Stabilized Janus Droplets.
He, Yuan; Savagatrup, Suchol; Zarzar, Lauren D; Swager, Timothy M
2017-03-01
Complex emulsions, including Janus droplets, are becoming increasingly important in pharmaceuticals and medical diagnostics, the fabrication of microcapsules for drug delivery, chemical sensing, E-paper display technologies, and optics. Because fluid Janus droplets are often sensitive to external perturbation, such as unexpected changes in the concentration of the surfactants or surface-active biomolecules in the environment, stabilizing their morphology is critical for many real-world applications. To endow Janus droplets with resistance to external chemical perturbations, we demonstrate a general and robust method of creating polymeric hemispherical shells via interfacial free-radical polymerization on the Janus droplets. The polymeric hemispherical shells were characterized by optical and fluorescence microscopy, scanning electron microscopy, and confocal laser scanning microscopy. By comparing phase diagrams of a regular Janus droplet and a Janus droplet with the hemispherical shell, we show that the formation of the hemispherical shell nearly doubles the range of the Janus morphology and maintains the Janus morphology upon a certain degree of external perturbation (e.g., adding hydrocarbon-water or fluorocarbon-water surfactants). We attribute the increased stability of the Janus droplets to (1) the surfactant nature of polymeric shell formed and (2) increase in interfacial tension between hydrocarbon and fluorocarbon due to polymer shell formation. This finding opens the door of utilizing these stabilized Janus droplets in a demanding environment.
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.
Safety assessment document for the Dynamic Test Complex B854
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.
Ecological dynamics and complex interactions of Agrobacterium megaplasmids
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
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.
Optimizing controllability of edge dynamics in complex networks by perturbing network structure
NASA Astrophysics Data System (ADS)
Pang, Shaopeng; Hao, Fei
2017-03-01
Using the minimum input signals to drive the dynamics in complex networks toward some desired state is a fundamental issue in the field of network controllability. For a complex network with the dynamical process defined on its edges, the controllability of this network is optimal if it can be fully controlled by applying one input signal to an arbitrary non-isolated vertex of it. In this paper, the adding-edge strategy and turning-edge strategy are proposed to optimize the controllability by minimum structural perturbations. Simulations and analyses indicate that the minimum number of adding-edges required for the optimal controllability is equal to the minimum number of turning-edges, and networks with positively correlated in- and out-degrees are easier to achieve optimal controllability. Furthermore, both the strategies have the capacity to reveal the relationship between certain structural properties of a complex network and its controllability of edge dynamics.
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.
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
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.
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
Excited State Energetics and Dynamics of Large Molecules, Complexes and Clusters
1988-07-01
States of Large Molecules 6 .4,,4 7- - . / ,-° - . . - ii - Page No. 7. (cont’d) K) Photoisomerization Dynamics of Trans- Stilbene and 6 of Cis- Stilbene L...Photoisomerization Dynamics of Alkyl Substituted Trans- Stilbene 6 M) Energy-Resolved Photoisomerization Rates 7 N) van der Waals Complexes and... Stilbene andof CisStilbene. Time-resolved fluorescence lifetimes from photoselected states of trans- stilbene were recorded by the techniques of
Sensing Domain Dynamics in Protein Kinase A-Iα Complexes by Solution X-ray Scattering*
Cheng, Cecilia Y.; Yang, Jie; Taylor, Susan S.; Blumenthal, Donald K.
2009-01-01
The catalytic (C) and regulatory (R) subunits of protein kinase A are exceptionally dynamic proteins. Interactions between the R- and C-subunits are regulated by cAMP binding to the two cyclic nucleotide-binding domains in the R-subunit. Mammalian cells express four different isoforms of the R-subunit (RIα, RIβ, RIIα, and RIIβ) that all interact with the C-subunit in different ways. Here, we investigate the dynamic behavior of protein complexes between RIα and C-subunits using small angle x-ray scattering. We show that a single point mutation in RIα, R333K (which alters the cAMP-binding properties of Domain B) results in a compact shape compared with the extended shape of the wild-type R·C complex. A double mutant complex that disrupts the interaction site between the C-subunit and Domain B in RIα, RIαABR333K·C(K285P), results in a broader P(r) curve that more closely resembles the P(r) profiles of wild-type complexes. These results together suggest that interactions between RIα Domain B and the C-subunit in the RIα·C complex involve large scale dynamics that can be disrupted by single point mutations in both proteins. In contrast to RIα·C complexes. Domain B in the RIIβ·C heterodimer is not dynamic and is critical for both inhibition and complex formation. Our study highlights the functional differences of domain dynamics between protein kinase A isoforms, providing a framework for elucidating the global organization of each holoenzyme and the cross-talk between the R- and C-subunits. PMID:19837668
Static and dynamic shear viscosity of a single-layer complex plasma
Hartmann, Peter; Sandor, Mate Csaba; Kovacs, Aniko; Donko, Zoltan
2011-07-15
The static and dynamic (complex) shear viscosity of a single-layer dusty plasma is measured by applying, respectively, a stationary and a periodically modulated shear stress, induced by the light pressure of manipulating laser beams. Under static conditions we observe a decrease of the viscosity with increasing shear rate, the so-called shear-thinning behavior. Under oscillating shear both the magnitude and the ratio of the dissipative and elastic contributions to the complex viscosity show strong frequency dependence, as the system changes from viscous to elastic in nature with increasing excitation frequency. Accompanying molecular dynamics simulations explain and support the experimental observations.
Passivity of Directed and Undirected Complex Dynamical Networks With Adaptive Coupling Weights.
Wang, Jin-Liang; Wu, Huai-Ning; Huang, Tingwen; Ren, Shun-Yan; Wu, Jigang
2016-05-05
A complex dynamical network consisting of $N$ identical neural networks with reaction-diffusion terms is considered in this paper. First, several passivity definitions for the systems with different dimensions of input and output are given. By utilizing some inequality techniques, several criteria are presented, ensuring the passivity of the complex dynamical network under the designed adaptive law. Then, we discuss the relationship between the synchronization and output strict passivity of the proposed network model. Furthermore, these results are extended to the case when the topological structure of the network is undirected. Finally, two examples with numerical simulations are provided to illustrate the correctness and effectiveness of the proposed results.
Moreira-Leite, Flavia; Varga, Vladimir; Gull, Keith
2016-01-01
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
Particle physics with slow neutrons at the institute Laue-Langevin
NASA Astrophysics Data System (ADS)
Dubbers, D.
1988-02-01
We give an overview over the particle and fundamental physics program at the European High Flux Reactor of the Institut Max von Laue-Paul Langevin at Grenoble, France. The experiments on neutron-antineutron oscillations, the neutron electric dipole moment, and on free neutron beta decay are reviewed in more detail.
Finite-temperature phase transitions in lattice QCD with Langevin simulation
Fukugita, M.; Ukawa, A.
1988-09-15
This article presents the result of Langevin simulation studies of finite-temperature behavior of QCD for a various number of flavor species. Most of the simulations employ an 8/sup 3/ x 4 lattice. A full description is made of the data and the identification problem of a first-order phase transition. The systematic bias problem is also investigated.
Langevin simulation of the full QCD hadron mass spectrum on a lattice
Fukugita, M.; Oyanagi, Y.; Ukawa, A.
1987-08-01
Langevin simulation of quantum chromodynamics (QCD) on a lattice is carried out fully taking into account the effect of the quark vacuum polarization. It is shown that the Langevin method works well for full QCD and that simulation on a large lattice is practically feasible. A careful study is made of systematic errors arising from a finite Langevin time-step size. The magnitude of the error is found to be significant for light quarks, but the well-controlled extrapolation allows a separation of the values at the vanishing time-step size. As another important ingredient for the feasibility of Langevin simulation the advantage of the matrix inversion algorithm of the preconditioned conjugate residual method is described, as compared with various other algorithms. The results of a hadron-mass-spectrum calculation on a 9/sup 3/ x 18 lattice at ..beta.. = 5.5 with the Wilson quark action having two flavors are presented. It is shown that the contribution of vacuum quark loops significantly modifies the hadron masses in lattice units, but that the dominant part can be absorbed into a shift of the gauge coupling constant at least for the ground-state hadrons. Some suggestion is also presented for the physical effect of vacuum quark loops for excited hadrons.
Molecular dynamics of protein kinase-inhibitor complexes: a valid structural information.
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.
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.
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.
The topology and dynamics of protein complexes: insights from intra- molecular network theory.
Hu, Guang; Zhou, Jianhong; Yan, Wenying; Chen, Jiajia; Shen, Bairong
2013-03-01
Intra-molecular interactions within complex systems play a pivotal role in the biological function. They form a major challenge to computational structural proteomics. The network paradigm treats any system as a set of nodes linked by edges corresponding to the relations existing between the nodes. It offers a computationally efficient tool to meet this challenge. Here, we review the recent advances in the use of network theory to study the topology and dynamics of protein- ligand and protein-nucleic acid complexes. The study of protein complexes networks not only involves the topological classification in term of network parameters, but also reveals the consistent picture of intrinsic functional dynamics. Current dynamical analysis focuses on a plethora of functional phenomena: the process of allosteric communication, the binding induced conformational changes, prediction and identification of binding sites of protein complexes, which will give insights into intra-protein complexes interactions. Furthermore, such computational results may elucidate a variety of known biological processes and experimental data, and thereby demonstrate a huge potential for applications such as drug design and functional genomics. Finally we describe some web-based resources for protein complexes, as well as protein network servers and related bioinformatics tools.
Control of epidemic spreading on complex networks by local traffic dynamics
NASA Astrophysics Data System (ADS)
Yang, Han-Xin; Wang, Wen-Xu; Lai, Ying-Cheng; Xie, Yan-Bo; Wang, Bing-Hong
2011-10-01
Despite extensive work on traffic dynamics and epidemic spreading on complex networks, the interplay between these two types of dynamical processes has not received adequate attention. We study the effect of local-routing-based traffic dynamics on epidemic spreading. For the case of unbounded node-delivery capacity, where the traffic is free of congestion, we obtain analytic and numerical results indicating that the epidemic threshold can be maximized by an optimal routing protocol. This means that epidemic spreading can be effectively controlled by local traffic dynamics. For the case of bounded delivery capacity, numerical results and qualitative arguments suggest that traffic congestion can suppress epidemic spreading. Our results provide quantitative insight into the nontrivial role of traffic dynamics associated with a local-routing scheme in the epidemic spreading.
Control of epidemic spreading on complex networks by local traffic dynamics.
Yang, Han-Xin; Wang, Wen-Xu; Lai, Ying-Cheng; Xie, Yan-Bo; Wang, Bing-Hong
2011-10-01
Despite extensive work on traffic dynamics and epidemic spreading on complex networks, the interplay between these two types of dynamical processes has not received adequate attention. We study the effect of local-routing-based traffic dynamics on epidemic spreading. For the case of unbounded node-delivery capacity, where the traffic is free of congestion, we obtain analytic and numerical results indicating that the epidemic threshold can be maximized by an optimal routing protocol. This means that epidemic spreading can be effectively controlled by local traffic dynamics. For the case of bounded delivery capacity, numerical results and qualitative arguments suggest that traffic congestion can suppress epidemic spreading. Our results provide quantitative insight into the nontrivial role of traffic dynamics associated with a local-routing scheme in the epidemic spreading.
Hudson, Lawrence N.; Reuman, Daniel C.
2013-01-01
A major goal of ecology is to discover how dynamics and structure of multi-trophic ecological communities are related. This is difficult, because whole-community data are limited and typically comprise only a snapshot of a community instead of a time series of dynamics, and mathematical models of complex system dynamics have a large number of unmeasured parameters and therefore have been only tenuously related to real systems. These are related problems, because long time-series, if they were commonly available, would enable inference of parameters. The resulting ‘plague of parameters’ means most studies of multi-species population dynamics have been very theoretical. Dynamical models parametrized using physiological allometries may offer a partial cure for the plague of parameters, and these models are increasingly used in theoretical studies. However, physiological allometries cannot determine all parameters, and the models have also rarely been directly tested against data. We confronted a model of community dynamics with data from a lake community. Many important empirical patterns were reproducible as outcomes of dynamics, and were not reproducible when parameters did not follow physiological allometries. Results validate the usefulness, when parameters follow physiological allometries, of classic differential-equation models for understanding whole-community dynamics and the structure–dynamics relationship. PMID:24026824
Molecular basis for the dissociation dynamics of protein A-immunoglobulin G1 complex.
Liu, Fu-Feng; Huang, Bo; Dong, Xiao-Yan; Sun, Yan
2013-01-01
Staphylococcus aureus protein A (SpA) is the most popular affinity ligand for immunoglobulin G1 (IgG1). However, the molecular basis for the dissociation dynamics of SpA-IgG1 complex is unclear. Herein, coarse-grained (CG) molecular dynamics (MD) simulations with the Martini force field were used to study the dissociation dynamics of the complex. The CG-MD simulations were first verified by the agreement in the structural and interactional properties of SpA and human IgG1 (hIgG1) in the association process between the CG-MD and all-atom MD at different NaCl concentrations. Then, the CG-MD simulation studies focused on the molecular insight into the dissociation dynamics of SpA-hIgG1 complex at pH 3.0. It is found that there are four steps in the dissociation process of the complex. First, there is a slight conformational adjustment of helix II in SpA. This is followed by the phenomena that the electrostatic interactions provided by the three hot spots (Glu143, Arg146 and Lys154) of helix II of SpA break up, leading to the dissociation of helix II from the binding site of hIgG1. Subsequently, breakup of the hydrophobic interactions between helix I (Phe132, Tyr133 and His137) in SpA and hIgG1 occurs, resulting in the disengagement of helix I from its binding site of hIgG1. Finally, the non-specific interactions between SpA and hIgG1 decrease slowly till disappearance, leading to the complete dissociation of the SpA-hIgG1 complex. This work has revealed that CG-MD coupled with the Martini force field is an effective method for studying the dissociation dynamics of protein-protein complex.
Balance between Noise and Information Flow Maximizes Set Complexity of Network Dynamics
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
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.
Complex dynamics of life at different scales: from genomic to global environmental issues.
Anteneodo, C; da Luz, M G E
2010-12-28
This introduction to the Theme Issue, Complex dynamics of life at different scales: from genomic to global environmental issues, gives a short overview on why the ideas and concepts in complexity and nonlinearity are relevant to the understanding of life in its different manifestations. Also, it discusses how life phenomena can be thought of as composing different scales of organization. Finally, the articles in this thematic publication are briefly commented on in terms of their relevance in helping to understand the complexity of life systems.
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…
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…
Trend Motif: A Graph Mining Approach for Analysis of Dynamic Complex Networks
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.
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.
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…
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…
Fluorescence anisotropy of DNA/DAPI complex: torsional dynamics and geometry of the complex.
Barcellona, M L; Gratton, E
1996-01-01
Fluorescence depolarization of synthetic polydeoxynucleotide/4'-6-diamidino-2-phenylindole dihydrochloride complexes has been investigated as a function of dye/polymer coverage. At low coverage, fluorescence depolarization is due to local torsional motions of the DNA segment where the dye resides. At relatively high coverage, fluorescence depolarization is dominated by energy transfer to other dye molecules along the DNA. The extent of the observed depolarization due to torsional motion depends on the angle the dye molecule forms with the DNA helical axis. A large torsional motion and a small angle produce the same depolarization as a small torsional motion and a large projection angle. Furthermore, the extent of transfer critically depends on the relative orientation of dye molecules along the DNA. The effect of multiple transfer is examined using a Monte Carlo approach. The measurement of depolarization with transfer, at high coverage, allows determination of the dye orientation about the DNA helical axis. The value of the torsional spring constant is then determined, at very low coverage, for few selected polydeoxynucleotides. Images FIGURE 3 PMID:9172758
Dynamics around solutes and solute-solvent complexes in mixed solvents.
Kwak, Kyungwon; Park, Sungnam; Fayer, M D
2007-09-04
Ultrafast 2D-IR vibrational echo experiments, IR pump-probe experiments, and FT-IR spectroscopy of the hydroxyl stretch of phenol-OD in three solvents, CCl4, mesitylene (1, 3, 5 trimethylbenzene), and the mixed solvent of mesitylene and CCl4 (0.83 mole fraction CCl4), are used to study solute-solvent dynamics via observation of spectral diffusion. Phenol forms a complex with Mesitylene. In the mesitylene solution, there is only complexed phenol; in the CCl4 solution, there is only uncomplexed phenol; and in the mixed solvent, both phenol species are present. Dynamics of the free phenol in CCl4 or the mixed solvent are very similar, and dynamics of the complex in mesitylene and in the mixed solvent are very similar. However, there are differences in the slowest time scale dynamics between the pure solvents and the mixed solvents. The mixed solvent produces slower dynamics that are attributed to first solvent shell solvent composition variations. The composition variations require a longer time to randomize than is required in the pure solvents, where only density variations occur. The experimental results and recent MD simulations indicate that the solvent structure around the solute may be different from the mixed solvent's mole fraction.
Game theory and extremal optimization for community detection in complex dynamic networks.
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.
Complex Nonlinear Dynamic System of Oligopolies Price Game with Heterogeneous Players Under Noise
NASA Astrophysics Data System (ADS)
Liu, Feng; Li, Yaguang
A nonlinear four oligopolies price game with heterogeneous players, that are boundedly rational and adaptive, is built using two different special demand costs. Based on the theory of complex discrete dynamical system, the stability and the existing equilibrium point are investigated. The complex dynamic behavior is presented via bifurcation diagrams, the Lyapunov exponents to show equilibrium state, bifurcation and chaos with the variation in parameters. As disturbance is ubiquitous in economic systems, this paper focuses on the analysis of delay feedback control method under noise circumstances. Stable dynamics is confirmed to depend mainly on the low price adjustment speed, and if all four players have limited opportunities to stabilize the market, the new adaptive player facing profits of scale are found to be higher than the incumbents of bounded rational.
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.
NASA Astrophysics Data System (ADS)
Arbona, A.; Bona, C.; Miñano, B.; Plastino, A.
2014-09-01
The definition of complexity through Statistical Complexity Measures (SCM) has recently seen major improvements. Mostly, the effort is concentrated in measures on time series. We propose a SCM definition for spatial dynamical systems. Our definition is in line with the trend to combine entropy with measures of structure (such as disequilibrium). We study the behaviour of our definition against the vectorial noise model of Collective Motion. From a global perspective, we show how our SCM is minimal at both the microscale and macroscale, while it reaches a maximum at the ranges that define the mesoscale in this model. From a local perspective, the SCM is minimum both in highly ordered and disordered areas, while it reaches a maximum at the edges between such areas. These characteristics suggest this is a good candidate for detecting the mesoscale of arbitrary dynamical systems as well as regions where the complexity is maximal in such systems.
Viewing the Extended Mind Hypothesis (clark & Chambers) in Terms of Complex System Dynamics
NASA Astrophysics Data System (ADS)
Werner, Gerhard
In the course of the past 60 years, the brain — and in lockstep with it, Cognition — became liberated from confinement to the skull: the liberation I am referring to consists of the transition from being a distinct physical entity in indirect, mediated contact with the rest of the physical world to being an integral component of it, in a manner envisioned by the Extended Mind Hypothesis of Clark & Chalmers: in current terminology, merging brain, body and world into ONE complex system. As background, I briefly review the progression of steps that culminated in the Extended Mind Hypothesis, and allude to the controversies it raised. Assuming the validity of this hypothesis, I will explore the issues that arise from viewing brain, body and world as ONE complex dynamical system. This will lead me to suggest that interrelations between complex system and fractal dynamics enable the seamless integration of human capabilities and the material world.
Temporal dynamics of eye movements are related to differences in scene complexity and clutter.
Wu, David W-L; Anderson, Nicola C; Bischof, Walter F; Kingstone, Alan
2014-08-11
Recent research has begun to explore not just the spatial distribution of eye fixations but also the temporal dynamics of how we look at the world. In this investigation, we assess how scene characteristics contribute to these fixation dynamics. In a free-viewing task, participants viewed three scene types: fractal, landscape, and social scenes. We used a relatively new method, recurrence quantification analysis (RQA), to quantify eye movement dynamics. RQA revealed that eye movement dynamics were dependent on the scene type viewed. To understand the underlying cause for these differences we applied a technique known as fractal analysis and discovered that complexity and clutter are two scene characteristics that affect fixation dynamics, but only in scenes with meaningful content. Critically, scene primitives-revealed by saliency analysis-had no impact on performance. In addition, we explored how RQA differs from the first half of the trial to the second half, as well as the potential to investigate the precision of fixation targeting by changing RQA radius values. Collectively, our results suggest that eye movement dynamics result from top-down viewing strategies that vary according to the meaning of a scene and its associated visual complexity and clutter.
Matsuzaki, Satoshi
2001-01-01
This thesis contains the candidate's original work on excitonic structure and energy transfer dynamics of two bacterial antenna complexes as studied using spectral hole-burning spectroscopy. The general introduction is divided into two chapters (1 and 2). Chapter 1 provides background material on photosynthesis and bacterial antenna complexes with emphasis on the two bacterial antenna systems related to the thesis research. Chapter 2 reviews the underlying principles and mechanism of persistent nonphotochemical hole-burning (NPHB) spectroscopy. Relevant energy transfer theories are also discussed. Chapters 3 and 4 are papers by the candidate that have been published. Chapter 3 describes the application of NPHB spectroscopy to the Fenna-Matthews-Olson (FMO) complex from the green sulfur bacterium Prosthecochloris aestuarii; emphasis is on determination of the low energy vibrational structure that is important for understanding the energy transfer process associated within three lowest energy Qy-states of the complex. The results are compared with those obtained earlier on the FMO complex from Chlorobium tepidum. In Chapter 4, the energy transfer dynamics of the B800 molecules of intact LH2 and B800-deficient LH2 complexes of the purple bacterium Rhodopseudomonas acidophila are compared. New insights on the additional decay channel of the B800 ring of bacteriochlorophyll a (BChl a) molecules are provided. General conclusions are given in Chapter 5.
NASA Astrophysics Data System (ADS)
Jensen, Henrik Jeldtoft
Recent research on the non-stationary nature of the dynamics of complex systems is reviewed through three specific models. The long time dynamics consists of a slow, decelerating but spasmodic release of generalized intrinsic strain. These events are denoted quakes. Between the quakes weak fluctuations occur but no essential change in properties are induced. The accumulated effect of the quakes, however, is to induce a direct change in the probability density functions characterizing the system. We discuss how the log-Poisson statistics of record dynamics may be an effective description of the long time evolution and describe how an analysis of the times at which the quakes occur enables one to check the applicability of record dynamics.
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.
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.
Schurr, J Michael; Fujimoto, Bryant S
2013-12-01
Extension versus twist data of Koster et al. (Nature 2005, 434, 671-674) are analyzed to obtain C for the main-chain segments and the twist energy parameter (ET ) for the supercoiled pseudocircular (sp) domain(s) from which C is estimated via simulations. The torsional rigidity in the tension-free sp domain(s) (C = 163 fJ fm) is typical of the unstrained DNA and is less than half the value in the main-chain segments under tension (C = 350-410 fJ fm). Tension is suggested to induce a structural transition to a torsionally stiffer state. Data of Koster et al. for the rate of extension owing to unwinding of a covalent complex of DNA with human Topoisomerase Ib (H Topo I) are analyzed to determine the torque and rate of rotation from which an effective friction coefficient is obtained. A Langevin equation for the unwinding motion in a supercoiled DNA:H Topo I complex is solved to obtain the temporal trajectory of the average winding angle and the time-dependent distribution of winding angles. The mean rate constant for the religation reaction is estimated from the measured probability of reaction per turn. We predict that unwinding proceeds rather far during a single-cleavage and religation cycle, and is effectively completely equilibrated during the 3.2 cleavage and religation cycles that occur during each noncovalent binding and dissociation event. H Topo I is predicted to be completely processive as in accord with observations on calf-thymus Topo I (Brewood et al., Biochemistry 2010, 49, 3367-3380).
Gambhir, Manoj; Michael, Edwin
2008-01-01
Background The current global efforts to control the morbidity and mortality caused by infectious diseases affecting developing countries—such as HIV/AIDS, polio, tuberculosis, malaria and the Neglected Tropical Diseases (NTDs)—have led to an increasing focus on the biological controllability or eradicability of disease transmission by management action. Here, we use an age-structured dynamical model of lymphatic filariasis transmission to show how a quantitative understanding of the dynamic processes underlying infection persistence and extinction is key to evaluating the eradicability of this macroparasitic disease. Methodology/Principal Findings We investigated the persistence and extinction dynamics of lymphatic filariasis by undertaking a numerical equilibrium analysis of a deterministic model of parasite transmission, based on varying values of the initial L3 larval density in the system. The results highlighted the likely occurrence of complex dynamics in parasite transmission with three major outcomes for the eradicability of filariasis. First, both vector biting and worm breakpoint thresholds are shown to be complex dynamic entities with values dependent on the nature and magnitude of vector-and host specific density-dependent processes and the degree of host infection aggregation prevailing in endemic communities. Second, these thresholds as well as the potential size of the attractor domains and hence system resilience are strongly dependent on peculiarities of infection dynamics in different vector species. Finally, the existence of multiple stable states indicates the presence of hysteresis nonlinearity in the filariasis system dynamics in which infection thresholds for infection invasion are lower but occur at higher biting rates than do the corresponding thresholds for parasite elimination. Conclusions/Significance The variable dynamic nature of thresholds and parasite system resilience reflecting both initial conditions and vector species
Dynamic Functional Segregation and Integration in Human Brain Network During Complex Tasks.
Ren, Shen; Li, Junhua; Taya, Fumihiko; deSouza, Joshua; Thakor, Nitish; Bezerianos, Anastasios
2016-09-09
The analysis of the topology and organisation of brain networks is known to greatly benefit from network measures in graph theory. However, to evaluate dynamic changes of brain functional connectivity, more sophisticated quantitative metrics characterising temporal evolution of brain topological features are required. To simplify conversion of time-varying brain connectivity to a static graph representation is straightforward but the procedure loses temporal information that could be critical in understanding the brain functions. To extend the understandings of functional segregation and integration to a dynamic fashion, we recommend dynamic graph metrics to characterise temporal changes of topological features of brain networks. This study investigated functional segregation and integration of brain networks over time by dynamic graph metrics derived from EEG signals during an experimental protocol: performance of complex flight simulation tasks with multiple levels of difficulty. We modelled time-varying brain functional connectivity as multilayer networks, in which each layer models brain connectivity at time window t + t. Dynamic graph metrics were calculated to quantify temporal and topological properties of the network. Results show that brain networks under the performance of complex tasks reveal a dynamic small-world architecture with a number of frequently connected nodes or hubs, which supports the balance of information segregation and integration in brain over time. The results also show that greater cognitive workloads caused by more difficult tasks induced a more globally efficient but less clustered dynamic small-world functional network. Our study illustrates that task-related changes of functional brain network segregation and integration can be characterised by dynamic graph metrics.
NASA Astrophysics Data System (ADS)
Iyer, Swami; Killingback, Timothy
2014-10-01
The traveler's dilemma game and the minimum-effort coordination game are social dilemmas that have received significant attention resulting from the fact that the predictions of classical game theory are inconsistent with the results found when the games are studied experimentally. Moreover, both the traveler's dilemma and the minimum-effort coordination games have potentially important applications in evolutionary biology. Interestingly, standard deterministic evolutionary game theory, as represented by the replicator dynamics in a well-mixed population, is also inadequate to account for the behavior observed in these games. Here we study the evolutionary dynamics of both these games in populations with interaction patterns described by a variety of complex network topologies. We investigate the evolutionary dynamics of these games through agent-based simulations on both model and empirical networks. In particular, we study the effects of network clustering and assortativity on the evolutionary dynamics of both games. In general, we show that the evolutionary behavior of the traveler's dilemma and minimum-effort coordination games on complex networks is in good agreement with that observed experimentally. Thus, formulating the traveler's dilemma and the minimum-effort coordination games on complex networks neatly resolves the paradoxical aspects of these games.
Iyer, Swami; Killingback, Timothy
2014-10-01
The traveler's dilemma game and the minimum-effort coordination game are social dilemmas that have received significant attention resulting from the fact that the predictions of classical game theory are inconsistent with the results found when the games are studied experimentally. Moreover, both the traveler's dilemma and the minimum-effort coordination games have potentially important applications in evolutionary biology. Interestingly, standard deterministic evolutionary game theory, as represented by the replicator dynamics in a well-mixed population, is also inadequate to account for the behavior observed in these games. Here we study the evolutionary dynamics of both these games in populations with interaction patterns described by a variety of complex network topologies. We investigate the evolutionary dynamics of these games through agent-based simulations on both model and empirical networks. In particular, we study the effects of network clustering and assortativity on the evolutionary dynamics of both games. In general, we show that the evolutionary behavior of the traveler's dilemma and minimum-effort coordination games on complex networks is in good agreement with that observed experimentally. Thus, formulating the traveler's dilemma and the minimum-effort coordination games on complex networks neatly resolves the paradoxical aspects of these games.
Real-Time Quantum Dynamics Reveals Complex, Many-Body Interactions in Solvated Nanodroplets.
Oviedo, M Belén; Wong, Bryan M
2016-04-12
Electronic excitations in the liquid phase are surprisingly rich and considerably more complex than either gas-phase or solid-state systems. While the majority of physical and biological processes take place in solvent, our understanding of nonequilibrium excited-state processes in these condensed phase environments remains far from complete. A central and long-standing issue in these solvated environments is the assessment of many-body interactions, particularly when the entire system is out of equilibrium and many quantum states participate in the overall process. Here we present a microscopic picture of solute-solvent electron dynamics and solvatochromic effects, which we uncover using a new real-time quantum dynamics approach for extremely large solvated nanodroplets. In particular, we find that a complex interplay of quantum interactions underlies our observations of solute-solvent effects, and simple macroscopic solvatochromic shifts can even be qualitatively different at the microscopic molecular level in these systems. By treating both the solvent and the solute on the same footing at a quantum-mechanical level, we demonstrate that the electron dynamics in these systems are surprisingly complex, and the emergence of many-body interactions underlies the dynamics in these solvated systems.
Sequence-dependent nanometer-scale conformational dynamics of individual RecBCD–DNA complexes
Carter, Ashley R.; Seaberg, Maasa H.; Fan, Hsiu-Fang; Sun, Gang; Wilds, Christopher J.; Li, Hung-Wen; Perkins, Thomas T.
2016-01-01
RecBCD is a multifunctional enzyme that possesses both helicase and nuclease activities. To gain insight into the mechanism of its helicase function, RecBCD unwinding at low adenosine triphosphate (ATP) (2–4 μM) was measured using an optical-trapping assay featuring 1 base-pair (bp) precision. Instead of uniformly sized steps, we observed forward motion convolved with rapid, large-scale (∼4 bp) variations in DNA length. We interpret this motion as conformational dynamics of the RecBCD–DNA complex in an unwinding-competent state, arising, in part, by an enzyme-induced, back-and-forth motion relative to the dsDNA that opens and closes the duplex. Five observations support this interpretation. First, these dynamics were present in the absence of ATP. Second, the onset of the dynamics was coupled to RecBCD entering into an unwinding-competent state that required a sufficiently long 5′ strand to engage the RecD helicase. Third, the dynamics were modulated by the GC-content of the dsDNA. Fourth, the dynamics were suppressed by an engineered interstrand cross-link in the dsDNA that prevented unwinding. Finally, these dynamics were suppressed by binding of a specific non-hydrolyzable ATP analog. Collectively, these observations show that during unwinding, RecBCD binds to DNA in a dynamic mode that is modulated by the nucleotide state of the ATP-binding pocket. PMID:27220465
Dynamic Binding Mode of a Synaptotagmin-1-SNARE Complex in Solution
Brewer, Kyle D.; Bacaj, Taulant; Cavalli, Andrea; Camilloni, Carlo; Swarbrick, James D.; Liu, Jin; Zhou, Amy; Zhou, Peng; Barlow, Nicholas; Xu, Junjie; Seven, Alpay B.; Prinslow, Eric A.; Voleti, Rashmi; Häussinger, Daniel; Bonvin, Alexandre M.J.J.; Tomchick, Diana R.; Vendruscolo, Michele; Graham, Bim; Südhof, Thomas C.; Rizo, Josep
2015-01-01
SUMMARY Rapid neurotransmitter release depends on the Ca2+-sensor Synaptotagmin-1 and the SNARE complex formed by synaptobrevin, syntaxin-1 and SNAP-25. How Synaptotagmin-1 triggers release remains unclear, in part because elucidating high-resolution structures of Synaptotagmin-1-SNARE complexes has been challenging. An NMR approach based on lanthanide-induced pseudocontact shifts now reveals a dynamic binding mode where basic residues in the concave side of the Synaptotagmin-1 C2B domain β-sandwich interact with a polyacidic region of the SNARE complex formed by syntaxin-1 and SNAP-25. The physiological relevance of this dynamic structural model is supported by mutations in basic residues of Synaptotagmin-1 that markedly impair SNARE-complex binding in vitro and Synaptotagmin-1 function in neurons. Mutations with milder effects on binding have correspondingly milder effects on Synaptotagmin-1 function. Our results support a model whereby their dynamic interaction facilitates cooperation between synaptotagmin-1 and the SNAREs in inducing membrane fusion. PMID:26030874
Statistical Techniques Complement UML When Developing Domain Models of Complex Dynamical Biosystems
Timmis, Jon; Qwarnstrom, Eva E.
2016-01-01
Computational modelling and simulation is increasingly being used to complement traditional wet-lab techniques when investigating the mechanistic behaviours of complex biological systems. In order to ensure computational models are fit for purpose, it is essential that the abstracted view of biology captured in the computational model, is clearly and unambiguously defined within a conceptual model of the biological domain (a domain model), that acts to accurately represent the biological system and to document the functional requirements for the resultant computational model. We present a domain model of the IL-1 stimulated NF-κB signalling pathway, which unambiguously defines the spatial, temporal and stochastic requirements for our future computational model. Through the development of this model, we observe that, in isolation, UML is not sufficient for the purpose of creating a domain model, and that a number of descriptive and multivariate statistical techniques provide complementary perspectives, in particular when modelling the heterogeneity of dynamics at the single-cell level. We believe this approach of using UML to define the structure and interactions within a complex system, along with statistics to define the stochastic and dynamic nature of complex systems, is crucial for ensuring that conceptual models of complex dynamical biosystems, which are developed using UML, are fit for purpose, and unambiguously define the functional requirements for the resultant computational model. PMID:27571414
Statistical Techniques Complement UML When Developing Domain Models of Complex Dynamical Biosystems.
Williams, Richard A; Timmis, Jon; Qwarnstrom, Eva E
2016-01-01
Computational modelling and simulation is increasingly being used to complement traditional wet-lab techniques when investigating the mechanistic behaviours of complex biological systems. In order to ensure computational models are fit for purpose, it is essential that the abstracted view of biology captured in the computational model, is clearly and unambiguously defined within a conceptual model of the biological domain (a domain model), that acts to accurately represent the biological system and to document the functional requirements for the resultant computational model. We present a domain model of the IL-1 stimulated NF-κB signalling pathway, which unambiguously defines the spatial, temporal and stochastic requirements for our future computational model. Through the development of this model, we observe that, in isolation, UML is not sufficient for the purpose of creating a domain model, and that a number of descriptive and multivariate statistical techniques provide complementary perspectives, in particular when modelling the heterogeneity of dynamics at the single-cell level. We believe this approach of using UML to define the structure and interactions within a complex system, along with statistics to define the stochastic and dynamic nature of complex systems, is crucial for ensuring that conceptual models of complex dynamical biosystems, which are developed using UML, are fit for purpose, and unambiguously define the functional requirements for the resultant computational model.
Solvation of Co(III)-cysteinato complexes in water: a DFT-based molecular dynamics study.
Spezia, Riccardo; Bresson, Carole; Den Auwer, Christophe; Gaigeot, Marie-Pierre
2008-05-22
Structural, dynamical, and vibrational properties of complexes made of metal cobalt(III) coordinated to different amounts of cysteine molecules were investigated with DFT-based Car-Parrinello molecular dynamics (CPMD) simulations in liquid water solution. The systems are composed of Co(III):3Cys and Co(III):2Cys immersed in liquid water which are modeled by about 110 explicit water molecules, thus one of the biggest molecular systems studied with ab initio molecular simulations so far. In such a way, we were able to investigate structural and dynamical properties of a model of a typical metal binding site used by several proteins. Cobalt, mainly a toxicological agent, can replace the natural binding metal and thus modify the biochemical activity. The structure of the surrounding solvent around the metal-ligands complexes is reported in detail, as well as the metal-ligands coordination bonds, using radial distribution functions and electronic analyses with Mayer bond orders. Structures of the Cocysteine complexes are found in very good agreement with EXAFS experimental data, stressing the importance of considering the surrounding solvent in the modeling. A vibrational analysis is also conducted and compared to experiment, which strengthens the reliability of the solvent interactions with the Cocysteine complexes from our molecular dynamics simulations, as well as the dynamics of the systems. From this preliminary analysis, we could suggest a vibrational fingerprint able to distinguish Co(III):2Cys from Co(III):3Cys. Our simulations also show the importance of considering a quantum explicit solvent, as solute-to-solvent proton transfer events have been observed.