Complex Langevin dynamics for chiral random matrix theory
NASA Astrophysics Data System (ADS)
Mollgaard, A.; Splittorff, K.
2013-12-01
We apply complex Langevin dynamics to chiral random matrix theory at nonzero chemical potential. At large quark mass, the simulations agree with the analytical results while incorrect convergence is found for small quark masses. The region of quark masses for which the complex Langevin dynamics converges incorrectly is identified as the region where the fermion determinant frequently traces out a path surrounding the origin of the complex plane during the Langevin flow. This links the incorrect convergence to an ambiguity in the Langevin force due to the presence of the logarithm of the fermion determinant in the action.
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.
Complex Langevin dynamics and zeroes of the fermion determinant
NASA Astrophysics Data System (ADS)
Aarts, Gert; Seiler, Erhard; Sexty, Dénes; Stamatescu, Ion-Olimpiu
2017-05-01
QCD at nonzero baryon chemical potential suffers from the sign problem, due to the complex quark determinant. Complex Langevin dynamics can provide a solution, provided certain conditions are met. One of these conditions, holomorphicity of the Langevin drift, is absent in QCD since zeroes of the determinant result in a meromorphic drift. We first derive how poles in the drift affect the formal justification of the approach and then explore the various possibilities in simple models. The lessons from these are subsequently applied to both heavy dense QCD and full QCD, and we find that the results obtained show a consistent picture. We conclude that with careful monitoring, the method can be justified a posteriori, even in the presence of meromorphicity.
Entropy and enthalpy of polyelectrolyte complexation: Langevin dynamics simulations.
Ou, Zhaoyang; Muthukumar, M
2006-04-21
We report a systematic study by Langevin dynamics simulation on the energetics of complexation between two oppositely charged polyelectrolytes of same charge density in dilute solutions of a good solvent with counterions and salt ions explicitly included. The enthalpy of polyelectrolyte complexation is quantified by comparisons of the Coulomb energy before and after complexation. The entropy of polyelectrolyte complexation is determined directly from simulations and compared with that from a mean-field lattice model explicitly accounting for counterion adsorption. At weak Coulomb interaction strengths, e.g., in solvents of high dielectric constant or with weakly charged polyelectrolytes, complexation is driven by a negative enthalpy due to electrostatic attraction between two oppositely charged chains, with counterion release entropy playing only a subsidiary role. In the strong interaction regime, complexation is driven by a large counterion release entropy and opposed by a positive enthalpy change. The addition of salt reduces the enthalpy of polyelectrolyte complexation by screening electrostatic interaction at all Coulomb interaction strengths. The counterion release entropy also decreases in the presence of salt, but the reduction only becomes significant at higher Coulomb interaction strengths. More significantly, in the range of Coulomb interaction strengths appropriate for highly charged polymers in aqueous solutions, complexation enthalpy depends weakly on salt concentration and counterion release entropy exhibits a large variation as a function of salt concentration. Our study quantitatively establishes that polyelectrolyte complexation in highly charged Coulomb systems is of entropic origin.
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.
Langevin dynamics for ramified structures
NASA Astrophysics Data System (ADS)
Méndez, Vicenç; Iomin, Alexander; Horsthemke, Werner; Campos, Daniel
2017-06-01
We propose a generalized Langevin formalism to describe transport in combs and similar ramified structures. Our approach consists of a Langevin equation without drift for the motion along the backbone. The motion along the secondary branches may be described either by a Langevin equation or by other types of random processes. The mean square displacement (MSD) along the backbone characterizes the transport through the ramified structure. We derive a general analytical expression for this observable in terms of the probability distribution function of the motion along the secondary branches. We apply our result to various types of motion along the secondary branches of finite or infinite length, such as subdiffusion, superdiffusion, and Langevin dynamics with colored Gaussian noise and with non-Gaussian white noise. Monte Carlo simulations show excellent agreement with the analytical results. The MSD for the case of Gaussian noise is shown to be independent of the noise color. We conclude by generalizing our analytical expression for the MSD to the case where each secondary branch is n dimensional.
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.
Entropy production for complex Langevin equations
NASA Astrophysics Data System (ADS)
Borlenghi, Simone; Iubini, Stefano; Lepri, Stefano; Fransson, Jonas
2017-07-01
We study irreversible processes for nonlinear oscillators networks described by complex-valued Langevin equations that account for coupling to different thermochemical baths. Dissipation is introduced via non-Hermitian terms in the Hamiltonian of the model. We apply the stochastic thermodynamics formalism to compute explicit expressions for the entropy production rates. We discuss in particular the nonequilibrium steady states of the network characterized by a constant production rate of entropy and flows of energy and particle currents. For two specific examples, a one-dimensional chain and a dimer, numerical calculations are presented. The role of asymmetric coupling among the oscillators on the entropy production is illustrated.
Data driven Langevin modeling of biomolecular dynamics
NASA Astrophysics Data System (ADS)
Schaudinnus, Norbert; Rzepiela, Andrzej J.; Hegger, Rainer; Stock, Gerhard
2013-05-01
Based on a given time series, the data-driven Langevin equation proposed by Hegger and Stock [J. Chem. Phys. 130, 034106 (2009), 10.1063/1.3058436] aims to construct a low-dimensional dynamical model of the system. Adopting various simple model problems of biomolecular dynamics, this work presents a systematic study of the theoretical virtues and limitations as well as of the practical applicability and performance of the method. As the method requires only local information, the input data need not to be Boltzmann weighted in order to warrant that the Langevin model yields correct Boltzmann-distributed results. Moreover, a delay embedding of the state vector allows for the treatment of memory effects. The robustness of the modeling with respect to wrongly chosen model parameters or low sampling is discussed, as well as the treatment of inertial effects. Given sufficiently sampled input data, the Langevin modeling is shown to successfully recover the correct statistics (such as the probability distribution) and the dynamics (such as the position autocorrelation function) of all considered problems.
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.
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.
Estimating the speed-up of adaptively restrained Langevin dynamics
NASA Astrophysics Data System (ADS)
Trstanova, Zofia; Redon, Stephane
2017-05-01
We consider Adaptively Restrained Langevin dynamics, in which the kinetic energy function vanishes for small velocities. Properly parameterized, this dynamics makes it possible to reduce the computational complexity of updating inter-particle forces, and to accelerate the computation of ergodic averages of molecular simulations. In this paper, we analyze the influence of the method parameters on the total achievable speed-up. In particular, we estimate both the algorithmic speed-up, resulting from incremental force updates, and the influence of the change of the dynamics on the asymptotic variance. This allows us to propose a practical strategy for the parameterization of the method. We validate these theoretical results by representative numerical experiments.
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.
Combining the complex Langevin method and the generalized Lefschetz-thimble method
NASA Astrophysics Data System (ADS)
Nishimura, Jun; Shimasaki, Shinji
2017-06-01
The complex Langevin method and the generalized Lefschetz-thimble method are two closely related approaches to the sign problem, which are both based on complexification of the original dynamical variables. The former can be viewed as a generalization of the stochastic quantization using the Langevin equation, whereas the latter is a deformation of the integration contour using the so-called holomorphic gradient flow. In order to clarify their relationship, we propose a formulation which combines the two methods by applying the former method to the real variables that parametrize the deformed integration contour in the latter method. Three versions, which differ in the treatment of the residual sign problem in the latter method, are considered. By applying them to a single-variable model, we find, in particular, that one of the versions interpolates the complex Langevin method and the original Lefschetz-thimble 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.
Bifurcation dynamics of the tempered fractional Langevin equation
Zeng, Caibin Yang, Qigui; Chen, YangQuan
2016-08-15
Tempered fractional processes offer a useful extension for turbulence to include low frequencies. In this paper, we investigate the stochastic phenomenological bifurcation, or stochastic P-bifurcation, of the Langevin equation perturbed by tempered fractional Brownian motion. However, most standard tools from the well-studied framework of random dynamical systems cannot be applied to systems driven by non-Markovian noise, so it is desirable to construct possible approaches in a non-Markovian framework. We first derive the spectral density function of the considered system based on the generalized Parseval's formula and the Wiener-Khinchin theorem. Then we show that it enjoys interesting and diverse bifurcation phenomena exchanging between or among explosive-like, unimodal, and bimodal kurtosis. Therefore, our procedures in this paper are not merely comparable in scope to the existing theory of Markovian systems but also provide a possible approach to discern P-bifurcation dynamics in the non-Markovian settings.
Ab initio sampling of transition paths by conditioned Langevin dynamics
NASA Astrophysics Data System (ADS)
Delarue, Marc; Koehl, Patrice; Orland, Henri
2017-10-01
We propose a novel stochastic method to generate Brownian paths conditioned to start at an initial point and end at a given final point during a fixed time tf under a given potential U(x). These paths are sampled with a probability given by the overdamped Langevin dynamics. We show that these paths can be exactly generated by a local stochastic partial differential equation. This equation cannot be solved in general but we present several approximations that are valid either in the low temperature regime or in the presence of barrier crossing. We show that this method warrants the generation of statistically independent transition paths. It is computationally very efficient. We illustrate the method first on two simple potentials, the two-dimensional Mueller potential and the Mexican hat potential, and then on the multi-dimensional problem of conformational transitions in proteins using the "Mixed Elastic Network Model" as a benchmark.
NASA Astrophysics Data System (ADS)
Huang, Yandong; Rüdiger, Sten; Shuai, Jianwei
2013-12-01
The random opening and closing of ion channels establishes channel noise, which can be approximated and included into stochastic differential equations (Langevin approach). The Langevin approach is often incorporated to model stochastic ion channel dynamics for systems with a large number of channels. Here, we introduce a discretization procedure of a channel-based Langevin approach to simulate the stochastic channel dynamics with small and intermediate numbers of channels. We show that our Langevin approach with discrete channel open fractions can give a good approximation of the original Markov dynamics even for only 10 K channels. We suggest that the better approximation by the discretized Langevin approach originates from the improved representation of events that trigger action potentials.
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
Full simulation of chiral random matrix theory at nonzero chemical potential by complex Langevin
NASA Astrophysics Data System (ADS)
Mollgaard, A.; Splittorff, K.
2015-02-01
It is demonstrated that the complex Langevin method can simulate chiral random matrix theory at nonzero chemical potential. The successful match with the analytic prediction for the chiral condensate is established through a shift of matrix integration variables and choosing a polar representation for the new matrix elements before complexification. Furthermore, we test the proposal to work with a Langevin-time-dependent quark mass and find that it allows us to control the fluctuations of the phase of the fermion determinant throughout the Langevin trajectory.
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.
Langevin approach with rescaled noise for stochastic channel dynamics in Hodgkin-Huxley neurons
NASA Astrophysics Data System (ADS)
Huang, Yan-Dong; Xiang, Li; Shuai, Jian-Wei
2015-12-01
The Langevin approach has been applied to model the random open and closing dynamics of ion channels. It has long been known that the gate-based Langevin approach is not sufficiently accurate to reproduce the statistics of stochastic channel dynamics in Hodgkin-Huxley neurons. Here, we introduce a modified gate-based Langevin approach with rescaled noise strength to simulate stochastic channel dynamics. The rescaled independent gate and identical gate Langevin approaches improve the statistical results for the mean membrane voltage, inter-spike interval, and spike amplitude. Project supported by the National Natural Science Foundation for Distinguished Young Scholars of China (Grant No. 11125419), the National Natural Science Foundation of China (Grant No. 10925525), and the Funds for the Leading Talents of Fujian Province, China.
NASA Astrophysics Data System (ADS)
Wan, Shun Zhou; Wang, Cun Xin; Shi, Yun Yu
An efficient procedure is introduced for a generalized Langevin dynamics simulation when the exponential model is taken for the friction kernel. The leap frog algorithm is used for numerical integration of the generalized Langevin equation. Simulation with this model has been performed on a cyclic undecapeptide, cyclosporin A (CPA). By comparison with the results obtained from previous simulations, the method proves to be reliable and efficient in the simulation of CPA.
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.
Hydrodynamic analysis of the Schrödinger-Langevin equation for wave packet dynamics
NASA Astrophysics Data System (ADS)
Chou, Chia-Chun
2017-10-01
Frictional effects on the wave packet dynamics of quantum systems are investigated in the framework of the Schrödinger-Langevin equation. The Schrödinger-Langevin equation is directly solved using the split-operator method. Frictional effects impede the propagation and suppress the spreading of the wave packet. Computational results are presented for an Eckart barrier scattering problem, the decay of a metastable state, and the long-time behavior of a decaying quantum system. Significant features of dissipative Bohmian trajectory dynamics are analyzed for these quantum processes.
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.
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.
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.
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.
Reference trajectory approach to Langevin equations in gas phase collision dynamics
Schatz, G.C.; Moser, M.D.
1980-09-15
A new approach to the development of Langevin-like equations for studying gas phase collisional energy tranfer and other dynamical problems is introduced. The exact equations of motion are first expressed in terms of the deviations of the coordinates and momenta from some reference trajectory values and then linearized about those values. A partitioning between fast and slow variables is then assumed, and those members of the above mentioned linearized equations which refer to the fast variables are re-expressed as integral equations. A ''local Brownian-like'' approximation is then made in the memory kernel appearing in the integral equations to reduce them to algebraic equations; substitution of these into the slow variable equations of motion, we obtain Langevin-like equations for the slow variables.Applications of this Langevin-like approach to several models of gas phase VT collisional energy transfer show that it is capable of quantitative predictions (errors typically<20%) of the first and second (classical) moments of the final translational under fairly lenient conditions. In a collinear Kr+CO/sub 2/(000) model, the average energy transfer is accurate to 5% for initial translational energies as high as 10 eV, while for a collinear He+H/sub 2/ model, energy transfers accurate to 30% or better are obtained with five quanta of initial vibrational excitation in the H/sub 2/. Accurate results are obtained even when the average energy transfer is of different sign than that of the reference. WE also demonstrate that the Langevin equation works well when the average energy transfer becomes comparable to a quantum of vibrational energy (i.e., in the nonperturbative regime) provided that the necessary time scale separations for invoking the Langevin treatment exist.
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.
Nonequilibrium Langevin dynamics: A demonstration study of shear flow fluctuations in a simple fluid
NASA Astrophysics Data System (ADS)
Belousov, Roman; Cohen, E. G. D.; Rondoni, Lamberto
2017-08-01
The present paper is based on a recent success of the second-order stochastic fluctuation theory in describing time autocorrelations of equilibrium and nonequilibrium physical systems. In particular, it was shown to yield values of the related deterministic parameters of the Langevin equation for a Couette flow in a microscopic molecular dynamics model of a simple fluid. In this paper we find all the remaining constants of the stochastic dynamics, which then is simulated numerically and compared directly with the original physical system. By using these data, we study in detail the accuracy and precision of a second-order Langevin model for nonequilibrium physical systems theoretically and computationally. We find an intriguing relation between an applied external force and cumulants of the resulting flow fluctuations. This is characterized by a linear dependence of an athermal cumulant ratio, an apposite quantity introduced here. In addition, we discuss how the order of a given Langevin dynamics can be raised systematically by introducing colored noise.
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.
Langevin dynamics for the transport of flexible biological macromolecules in confined geometries.
Peters, Michael H
2011-01-14
The transport of flexible biological macromolecules in confined geometries is found in a variety of important biophysical systems including biomolecular movements through pores in cell walls, vesicle walls, and synthetic nanopores for sequencing methods. In this study, we extend our previous analysis of the Fokker-Planck and Langevin dynamics for describing the coupled translational and rotational motions of single structured macromolecules near structured external surfaces or walls [M. H. Peters, J. Chem. Phys. 110, 528 (1999); 112, 5488 (2000)] to the problem of many interacting macromolecules in the presence of structured external surfaces representing the confining geometry. Overall macromolecular flexibility is modeled through specified interaction potentials between the structured Brownian subunits (B-particles), as already demonstrated for protein and DNA molecules briefly reviewed here. We derive the Fokker-Planck equation using a formal multiple time scale perturbation expansion of the Liouville equation for the entire system, i.e., solvent, macromolecules, and external surface. A configurational-orientational Langevin displacement equation is also obtained for use in Brownian dynamics applications. We demonstrate important effects of the external surface on implicit solvent forces through formal descriptions of the grand friction tensor and equilibrium average force of the solvent on the B-particles. The formal analysis provides both transparency of all terms of the Langevin displacement equation as well as a prescription for their determination. As an example, application of the methods developed, the real-time movement of an α-helix protein through a carbon nanotube is simulated.
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.
NASA Astrophysics Data System (ADS)
Bustingorry, Sebastian; Cugliandolo, Leticia F.; Domínguez, Daniel
2007-01-01
We study the relaxation dynamics of flux lines in dirty high-temperature superconductors using numerical simulations of a London-Langevin model of the interacting vortex lines. By analyzing the equilibrium dynamics in the vortex liquid phase we find a dynamic crossover to a glassy nonequilibrium regime. We then focus on the out-of-equilibrium dynamics of the vortex glass phase using tools that are common in the study of other glassy systems. By monitoring the two-times roughness and dynamic wandering we identify and characterize finite-size effects that are similar, though more complex, than the ones found in the stationary roughness of clean interface dynamics. The two-times density-density correlation and mean-squared-displacement correlation age and their temporal scaling follows a multiplicative law similar to the one found at criticality. The linear responses also age and the comparison with their associated correlations shows that the equilibrium fluctuation-dissipation relation is modified in a simple manner that allows for the identification of an effective temperature characterizing the dynamics of the slow modes. The effective temperature is closely related to the vortex liquid-vortex glass crossover temperature. Interestingly enough, our study demonstrates that the glassy dynamics in the vortex glass is basically identical to the one of a single elastic line in a disordered environment (with the same type of scaling though with different parameters). Possible extensions and the experimental relevance of these results are also discussed.
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.
NASA Astrophysics Data System (ADS)
Majka, M.; Góra, P. F.
2016-10-01
While the origins of temporal correlations in Langevin dynamics have been thoroughly researched, the understanding of spatially correlated noise (SCN) is rather incomplete. In particular, very little is known about the relation between friction and SCN. In this article, starting from the microscopic, deterministic model, we derive the analytical formula for the spatial correlation function in the particle-bath interactions. This expression shows that SCN is the inherent component of binary mixtures, originating from the effective (entropic) interactions. Further, employing this spatial correlation function, we postulate the thermodynamically consistent Langevin equation driven by the Gaussian SCN and calculate the adequate fluctuation-dissipation relation. The thermodynamical consistency is achieved by introducing the spatially variant friction coefficient, which can be also derived analytically. This coefficient exhibits a number of intriguing properties, e.g., the singular behavior for certain types of interactions. Eventually, we apply this new theory to the system of two charged particles in the presence of counter-ions. Such particles interact via the screened-charge Yukawa potential and the inclusion of SCN leads to the emergence of the anomalous frictionless regime. In this regime the particles can experience active propulsion leading to the transient attraction effect. This effect suggests a nonequilibrium mechanism facilitating the molecular binding of the like-charged particles.
Majka, M; Góra, P F
2016-10-01
While the origins of temporal correlations in Langevin dynamics have been thoroughly researched, the understanding of spatially correlated noise (SCN) is rather incomplete. In particular, very little is known about the relation between friction and SCN. In this article, starting from the microscopic, deterministic model, we derive the analytical formula for the spatial correlation function in the particle-bath interactions. This expression shows that SCN is the inherent component of binary mixtures, originating from the effective (entropic) interactions. Further, employing this spatial correlation function, we postulate the thermodynamically consistent Langevin equation driven by the Gaussian SCN and calculate the adequate fluctuation-dissipation relation. The thermodynamical consistency is achieved by introducing the spatially variant friction coefficient, which can be also derived analytically. This coefficient exhibits a number of intriguing properties, e.g., the singular behavior for certain types of interactions. Eventually, we apply this new theory to the system of two charged particles in the presence of counter-ions. Such particles interact via the screened-charge Yukawa potential and the inclusion of SCN leads to the emergence of the anomalous frictionless regime. In this regime the particles can experience active propulsion leading to the transient attraction effect. This effect suggests a nonequilibrium mechanism facilitating the molecular binding of the like-charged particles.
Langevin dynamics of the choline head group in a membrane environment.
Konstant, P H; Pearce, L L; Harvey, S C
1994-01-01
Computer simulations of dipalmitoylphosphatidylcholine (DPPC) have been performed using Langevin dynamics and a Marcelja-type mean field. This work has focused on the dynamics of the choline head group to parameterize the empirical constraints against phosphorus-carbon dipolar couplings (Dp-c) as measured by nuclear magnetic resonance (13C-NMR). The results show good agreement with experimental values at constraints equivalent to the choline tilt observed in joint refinement of x-ray diffraction and neutron diffraction scatterings. Quadrupolar splittings for the alpha and beta positions are also calculated and compared with 2H-NMR experiments. The model predicts torsional transition rates around the alpha-beta bonds and for the two C-O-P-O torsions. It also predicts T1 relaxation times for the alpha and beta carbons. PMID:7948684
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.
Sivak, David A; Chodera, John D; Crooks, Gavin E
2014-06-19
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.
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.; ...
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
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
NASA Astrophysics Data System (ADS)
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.
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.
Langevin dynamics simulation of a one-dimensional linear spin chain with long-range interactions
NASA Astrophysics Data System (ADS)
Ati, Moncef; Enachescu, Cristian; Bouamrane, Rachid
2017-07-01
In this paper we study the critical behavior of a simple one-dimensional rotor spin in the form of a linear chain with long-range interactions, using the mean field Langevin dynamics approach and in the presence of fluctuations added by a heat bath. We have computed the specific heat, the magnetic susceptibility, the Binder fourth-order cumulant, and the magnetization, and then we have calculated the critical exponents using finite-size scaling. In addition, we provide a relation between the thermal bath temperature and the temperature of the system. Our results confirm the existence of a second-order critical temperature in the one-dimensional chain of spins with long-range interaction.
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.
NASA Astrophysics Data System (ADS)
Lázaro-Lázaro, Edilio; Mendoza-Méndez, Patricia; Elizondo-Aguilera, Luis Fernando; Perera-Burgos, Jorge Adrián; Ramírez-González, Pedro Ezequiel; Pérez-Ángel, Gabriel; Castañeda-Priego, Ramón; Medina-Noyola, Magdaleno
2017-05-01
A fundamental challenge of the theory of liquids is to understand the similarities and differences in the macroscopic dynamics of both colloidal and atomic liquids, which originate in the (Newtonian or Brownian) nature of the microscopic motion of their constituents. Starting from the recently discovered long-time dynamic equivalence between a colloidal and an atomic liquid that share the same interparticle pair potential, in this work we develop a self-consistent generalized Langevin equation theory for the dynamics of equilibrium multicomponent atomic liquids, applicable as an approximate but quantitative theory describing the long-time diffusive dynamical properties of simple equilibrium atomic liquids. When complemented with a Gaussian-like approximation, this theory is also able to provide a reasonable representation of the passage from a ballistic to diffusive behavior. We illustrate the applicability of the resulting theory with three particular examples, namely, a monodisperse and a polydisperse monocomponent hard-sphere liquid and a highly size-asymmetric binary hard-sphere mixture. To assess the quantitative accuracy of our results, we perform event-driven molecular dynamics simulations, which corroborate the general features of the theoretical predictions.
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
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.
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.
Langevin dynamics simulation of polymer-assisted virus-like assembly
Mahalik, J. P.; Muthukumar, M.
2012-01-01
Starting from a coarse grained representation of the building units of the minute virus of mice and a flexible polyelectrolyte molecule, we have explored the mechanism of assembly into icosahedral structures with the help of Langevin dynamics simulations and the parallel tempering technique. Regular icosahedra with appropriate symmetry form only in a narrow range of temperature and polymer length. Within this region of parameters where successful assembly would proceed, we have systematically investigated the growth kinetics. The assembly of icosahedra is found to follow the classical nucleation and growth mechanism in the absence of the polymer, with the three regimes of nucleation, linear growth, and slowing down in the later stage. The calculated average nucleation time obeys the laws expected from the classical nucleation theory. The linear growth rate is found to obey the laws of secondary nucleation as in the case of lamellar growth in polymer crystallization. The same mechanism is seen in the simulations of the assembly of icosahedra in the presence of the polymer as well. The polymer reduces the nucleation barrier significantly by enhancing the local concentration of subunits via adsorbing them on their backbone. The details of growth in the presence of the polymer are also found to be consistent with the classical nucleation theory, despite the smallness of the assembled structures. PMID:22482588
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.
Mouhat, Félix; Sorella, Sandro; Vuilleumier, Rodolphe; Saitta, Antonino Marco; Casula, Michele
2017-06-13
We introduce a novel approach for a fully quantum description of coupled electron-ion systems from first principles. It combines the variational quantum Monte Carlo solution of the electronic part with the path integral formalism for the quantum nuclear dynamics. On the one hand, the path integral molecular dynamics includes nuclear quantum effects by adding a set of fictitious classical particles (beads) aimed at reproducing nuclear quantum fluctuations via a harmonic kinetic term. On the other hand, variational quantum Monte Carlo can provide Born-Oppenheimer potential energy surfaces with a precision comparable to the most-advanced post-Hartree-Fock approaches, and with a favorable scaling with the system size. In order to cope with the intrinsic noise due to the stochastic nature of quantum Monte Carlo methods, we generalize the path integral molecular dynamics using a Langevin thermostat correlated according to the covariance matrix of quantum Monte Carlo nuclear forces. The variational parameters of the quantum Monte Carlo wave function are evolved during the nuclear dynamics, such that the Born-Oppenheimer potential energy surface is unbiased. Statistical errors on the wave function parameters are reduced by resorting to bead grouping average, which we show to be accurate and well-controlled. Our general algorithm relies on a Trotter breakup between the dynamics driven by ionic forces and the one set by the harmonic interbead couplings. The latter is exactly integrated, even in the presence of the Langevin thermostat, thanks to the mapping onto an Ornstein-Uhlenbeck process. This framework turns out to be also very efficient in the case of noiseless (deterministic) ionic forces. The new implementation is validated on the Zundel ion (H5O2(+)) by direct comparison with standard path integral Langevin dynamics calculations made with a coupled cluster potential energy surface. Nuclear quantum effects are confirmed to be dominant over thermal effects well beyond
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.
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.
NASA Astrophysics Data System (ADS)
Angulo, Gonzalo; Jedrak, Jakub; Ochab-Marcinek, Anna; Pasitsuparoad, Pakorn; Radzewicz, Czesław; Wnuk, Paweł; Rosspeintner, Arnulf
2017-06-01
The dynamics of unimolecular photo-triggered reactions can be strongly affected by the surrounding medium for which a large number of theoretical descriptions have been used in the past. An accurate description of these reactions requires knowing the potential energy surface and the friction felt by the reactants. Most of these theories start from the Langevin equation to derive the dynamics, but there are few examples comparing it with experiments. Here we explore the applicability of a Generalized Langevin Equation (GLE) with an arbitrary potential and a non-Markovian friction. To this end, we have performed broadband fluorescence measurements with sub-picosecond time resolution of a covalently linked organic electron donor-acceptor system in solvents of changing viscosity and dielectric permittivity. In order to establish the free energy surface (FES) of the reaction, we resort to stationary electronic spectroscopy. On the other hand, the dynamics of a non-reacting substance, Coumarin 153, provide the calibrating tool for the non-Markovian friction over the FES, which is assumed to be solute independent. A simpler and computationally faster approach uses the Generalized Smoluchowski Equation (GSE), which can be derived from the GLE for pure harmonic potentials. Both approaches reproduce the measurements in most of the solvents reasonably well. At long times, some differences arise from the errors inherited from the analysis of the stationary solvatochromism and at short times from the excess excitation energy. However, whenever the dynamics become slow, the GSE shows larger deviations than the GLE, the results of which always agree qualitatively with the measured dynamics, regardless of the solvent viscosity or dielectric properties. The method applied here can be used to predict the dynamics of any other reacting system, given the FES parameters and solvent dynamics are provided. Thus no fitting parameters enter the GLE simulations, within the applicability
Angulo, Gonzalo; Jedrak, Jakub; Ochab-Marcinek, Anna; Pasitsuparoad, Pakorn; Radzewicz, Czesław; Wnuk, Paweł; Rosspeintner, Arnulf
2017-06-28
The dynamics of unimolecular photo-triggered reactions can be strongly affected by the surrounding medium for which a large number of theoretical descriptions have been used in the past. An accurate description of these reactions requires knowing the potential energy surface and the friction felt by the reactants. Most of these theories start from the Langevin equation to derive the dynamics, but there are few examples comparing it with experiments. Here we explore the applicability of a Generalized Langevin Equation (GLE) with an arbitrary potential and a non-Markovian friction. To this end, we have performed broadband fluorescence measurements with sub-picosecond time resolution of a covalently linked organic electron donor-acceptor system in solvents of changing viscosity and dielectric permittivity. In order to establish the free energy surface (FES) of the reaction, we resort to stationary electronic spectroscopy. On the other hand, the dynamics of a non-reacting substance, Coumarin 153, provide the calibrating tool for the non-Markovian friction over the FES, which is assumed to be solute independent. A simpler and computationally faster approach uses the Generalized Smoluchowski Equation (GSE), which can be derived from the GLE for pure harmonic potentials. Both approaches reproduce the measurements in most of the solvents reasonably well. At long times, some differences arise from the errors inherited from the analysis of the stationary solvatochromism and at short times from the excess excitation energy. However, whenever the dynamics become slow, the GSE shows larger deviations than the GLE, the results of which always agree qualitatively with the measured dynamics, regardless of the solvent viscosity or dielectric properties. The method applied here can be used to predict the dynamics of any other reacting system, given the FES parameters and solvent dynamics are provided. Thus no fitting parameters enter the GLE simulations, within the applicability
NASA Astrophysics Data System (ADS)
Loheac, Andrew C.; Drut, Joaquín E.
2017-05-01
We analyze the pressure and density equations of state of unpolarized nonrelativistic fermions at finite temperature in one spatial dimension with contact interactions. For attractively interacting regimes, we perform a third-order lattice perturbation theory calculation, assess its convergence properties by comparing with hybrid Monte Carlo results (there is no sign problem in this regime), and demonstrate agreement with real Langevin calculations. For repulsive interactions, we present lattice perturbation theory results as well as complex Langevin calculations, with a modified action to prevent uncontrolled excursions in the complex plane. Although perturbation theory is a common tool, our implementation of it is unconventional; we use a Hubbard-Stratonovich transformation to decouple the system and automate the application of Wick's theorem, thus generating the diagrammatic expansion, including symmetry factors, at any desired order. We also present an efficient technique to tackle nested Matsubara frequency sums without relying on contour integration, which is independent of dimension and applies to both relativistic and nonrelativistic systems, as well as all energy-independent interactions. We find exceptional agreement between perturbative and nonperturbative results at weak couplings, and furnish predictions based on complex Langevin at strong couplings. We additionally present perturbative calculations of up to the fifth-order virial coefficient for repulsive and attractive couplings. Both the lattice perturbation theory and complex Langevin formalisms can easily be extended to a variety of situations including polarized systems, bosons, and higher dimension.
NASA Astrophysics Data System (ADS)
Reeves, Daniel B.; Weaver, John B.
2015-11-01
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.
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.
Langevin spin dynamics based on ab initio calculations: numerical schemes and applications.
Rózsa, L; Udvardi, L; Szunyogh, L
2014-05-28
A method is proposed to study the finite-temperature behaviour of small magnetic clusters based on solving the stochastic Landau-Lifshitz-Gilbert equations, where the effective magnetic field is calculated directly during the solution of the dynamical equations from first principles instead of relying on an effective spin Hamiltonian. Different numerical solvers are discussed in the case of a one-dimensional Heisenberg chain with nearest-neighbour interactions. We performed detailed investigations for a monatomic chain of ten Co atoms on top of a Au(0 0 1) surface. We found a spiral-like ground state of the spins due to Dzyaloshinsky-Moriya interactions, while the finite-temperature magnetic behaviour of the system was well described by a nearest-neighbour Heisenberg model including easy-axis anisotropy.
NASA Astrophysics Data System (ADS)
Cameron, M. K.
2013-08-01
The large time behavior of a stochastic system with infinitesimally small noise can be described in terms of Freidlin's cycles. We show that if the system is gradient and the potential satisfies certain non-restrictive conditions, the hierarchy of cycles has a structure of a full binary tree, and each cycle is exited via the lowest saddle adjacent to it. Exploiting this property, we propose an algorithm for computing the asymptotic zero-temperature path and building a hierarchy of Freidlin's cycles associated with the transition process between two given local equilibria. This algorithm is suitable for systems with a complex potential energy landscape with numerous minima. We apply it to find the asymptotic zero-temperature path and Freidlin's cycles involved into the transition process between the two lowest minima of the Lennard-Jones cluster of 38 atoms. D. Wales's stochastic network of minima and transition states of this cluster is used as an input.
NASA Astrophysics Data System (ADS)
Nagata, Keitaro; Nishimura, Jun; Shimasaki, Shinji
2016-07-01
Recently, the complex Langevin method has been applied successfully to finite density QCD either in the deconfinement phase or in the heavy dense limit with the aid of a new technique called the gauge cooling. In the confinement phase with light quarks, however, convergence to wrong limits occurs due to the singularity in the drift term caused by small eigenvalues of the Dirac operator including the mass term. We propose that this singular-drift problem should also be overcome by the gauge cooling with different criteria for choosing the complexified gauge transformation. The idea is tested in chiral Random Matrix Theory for finite density QCD, where exact results are reproduced at zero temperature with light quarks. It is shown that the gauge cooling indeed changes drastically the eigenvalue distribution of the Dirac operator measured during the Langevin process. Despite its non-holomorphic nature, this eigenvalue distribution has a universal diverging behavior at the origin in the chiral limit due to a generalized Banks-Casher relation as we confirm explicitly.
Complexity in Dynamical Systems
NASA Astrophysics Data System (ADS)
Moore, Cristopher David
The study of chaos has shown us that deterministic systems can have a kind of unpredictability, based on a limited knowledge of their initial conditions; after a finite time, the motion appears essentially random. This observation has inspired a general interest in the subject of unpredictability, and more generally, complexity; how can we characterize how "complex" a dynamical system is?. In this thesis, we attempt to answer this question with a paradigm of complexity that comes from computer science, we extract sets of symbol sequences, or languages, from a dynamical system using standard methods of symbolic dynamics; we then ask what kinds of grammars or automata are needed a generate these languages. This places them in the Chomsky heirarchy, which in turn tells us something about how subtle and complex the dynamical system's behavior is. This gives us insight into the question of unpredictability, since these automata can also be thought of as computers attempting to predict the system. In the culmination of the thesis, we find a class of smooth, two-dimensional maps which are equivalent to the highest class in the Chomsky heirarchy, the turning machine; they are capable of universal computation. Therefore, these systems possess a kind of unpredictability qualitatively different from the usual "chaos": even if the initial conditions are known exactly, questions about the system's long-term dynamics are undecidable. No algorithm exists to answer them. Although this kind of unpredictability has been discussed in the context of distributed, many-degree-of -freedom systems (for instance, cellular automata) we believe this is the first example of such phenomena in a smooth, finite-degree-of-freedom system.
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.
Nattino, Francesco; Galparsoro, Oihana; Costanzo, Francesca; Díez Muiño, Ricardo; Alducin, Maite; Kroes, Geert-Jan
2016-06-28
Accurately modeling surface temperature and surface motion effects is necessary to study molecule-surface reactions in which the energy dissipation to surface phonons can largely affect the observables of interest. We present here a critical comparison of two methods that allow to model such effects, namely, the ab initio molecular dynamics (AIMD) method and the generalized Langevin oscillator (GLO) model, using the dissociation of N2 on W(110) as a benchmark. AIMD is highly accurate as the surface atoms are explicitly part of the dynamics, but this advantage comes with a large computational cost. The GLO model is much more computationally convenient, but accounts for lattice motion effects in a very approximate way. Results show that, despite its simplicity, the GLO model is able to capture the physics of the system to a large extent, returning dissociation probabilities which are in better agreement with AIMD than static-surface results. Furthermore, the GLO model and the AIMD method predict very similar energy transfer to the lattice degrees of freedom in the non-reactive events, and similar dissociation dynamics.
NASA Astrophysics Data System (ADS)
Nattino, Francesco; Galparsoro, Oihana; Costanzo, Francesca; Díez Muiño, Ricardo; Alducin, Maite; Kroes, Geert-Jan
2016-06-01
Accurately modeling surface temperature and surface motion effects is necessary to study molecule-surface reactions in which the energy dissipation to surface phonons can largely affect the observables of interest. We present here a critical comparison of two methods that allow to model such effects, namely, the ab initio molecular dynamics (AIMD) method and the generalized Langevin oscillator (GLO) model, using the dissociation of N2 on W(110) as a benchmark. AIMD is highly accurate as the surface atoms are explicitly part of the dynamics, but this advantage comes with a large computational cost. The GLO model is much more computationally convenient, but accounts for lattice motion effects in a very approximate way. Results show that, despite its simplicity, the GLO model is able to capture the physics of the system to a large extent, returning dissociation probabilities which are in better agreement with AIMD than static-surface results. Furthermore, the GLO model and the AIMD method predict very similar energy transfer to the lattice degrees of freedom in the non-reactive events, and similar dissociation dynamics.
From shape to randomness: A classification of Langevin stochasticity
NASA Astrophysics Data System (ADS)
Eliazar, Iddo; Cohen, Morrel H.
2013-01-01
The Langevin equation-perhaps the most elemental stochastic differential equation in the physical sciences-describes the dynamics of a random motion driven simultaneously by a deterministic potential field and by a stochastic white noise. The Langevin equation is, in effect, a mechanism that maps the stochastic white-noise input to a stochastic output: a stationary steady state distribution in the case of potential wells, and a transient extremum distribution in the case of potential gradients. In this paper we explore the degree of randomness of the Langevin equation’s stochastic output, and classify it à la Mandelbrot into five states of randomness ranging from “infra-mild” to “ultra-wild”. We establish closed-form and highly implementable analytic results that determine the randomness of the Langevin equation’s stochastic output-based on the shape of the Langevin equation’s potential field.
Probability Density Function Method for Langevin Equations with Colored Noise
Wang, Peng; Tartakovsky, Alexandre M.; Tartakovsky, Daniel M.
2013-04-05
We present a novel method to derive closed-form, computable PDF equations for Langevin systems with colored noise. The derived equations govern the dynamics of joint or marginal probability density functions (PDFs) of state variables, and rely on a so-called Large-Eddy-Diffusivity (LED) closure. We demonstrate the accuracy of the proposed PDF method for linear and nonlinear Langevin equations, describing the classical Brownian displacement and dispersion in porous media.
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.
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 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.
Variance Reduction Using Nonreversible Langevin Samplers.
Duncan, A B; Lelièvre, T; Pavliotis, G A
A standard approach to computing expectations with respect to a given target measure is to introduce an overdamped Langevin equation which is reversible with respect to the target distribution, and to approximate the expectation by a time-averaging estimator. As has been noted in recent papers [30, 37, 61, 72], introducing an appropriately chosen nonreversible component to the dynamics is beneficial, both in terms of reducing the asymptotic variance and of speeding up convergence to the target distribution. In this paper we present a detailed study of the dependence of the asymptotic variance on the deviation from reversibility. Our theoretical findings are supported by numerical simulations.
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.
Modeling wildfire incident complexity dynamics.
Thompson, Matthew P
2013-01-01
Wildfire management in the United States and elsewhere is challenged by substantial uncertainty regarding the location and timing of fire events, the socioeconomic and ecological consequences of these events, and the costs of suppression. Escalating U.S. Forest Service suppression expenditures is of particular concern at a time of fiscal austerity as swelling fire management budgets lead to decreases for non-fire programs, and as the likelihood of disruptive within-season borrowing potentially increases. Thus there is a strong interest in better understanding factors influencing suppression decisions and in turn their influence on suppression costs. As a step in that direction, this paper presents a probabilistic analysis of geographic and temporal variation in incident management team response to wildfires. The specific focus is incident complexity dynamics through time for fires managed by the U.S. Forest Service. The modeling framework is based on the recognition that large wildfire management entails recurrent decisions across time in response to changing conditions, which can be represented as a stochastic dynamic system. Daily incident complexity dynamics are modeled according to a first-order Markov chain, with containment represented as an absorbing state. A statistically significant difference in complexity dynamics between Forest Service Regions is demonstrated. Incident complexity probability transition matrices and expected times until containment are presented at national and regional levels. Results of this analysis can help improve understanding of geographic variation in incident management and associated cost structures, and can be incorporated into future analyses examining the economic efficiency of wildfire management.
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.
Fractional dynamics of complex networks
NASA Astrophysics Data System (ADS)
Turalska, Malgorzata; West, Bruce J.
2014-03-01
The relation between the behavior of a single element and the global dynamics of its host network is an open problem in the science of complex networks. Typically one attempts to infer the global dynamics by combining the behavior of single elements within the system, following a bottom-up approach. Here we address an inverse problem. We show that for a generic model within the Ising universality class it is possible to construct a description of the dynamics of an individual element, given the information about the network's global behavior. We demonstrate that the individual trajectory response to the collective motion of the network is described by a linear fractional differential equation, whose analytic solution is the Mittag-Leffler function. This solution is obtained through a subordination procedure without the necessity of linearizing the underlying dynamics, that is, the solution retains the influence of the nonlinear network dynamics on the individual. Moreover the solutions to the fractional equation of motion suggest a new direction for designing control mechanisms for complex networks. The implications of this new perspective are explored by introducing a control signal into a small number of network elements and analyzing the subsequent change in the network dynamics.
Langevin equation for a free particle driven by power law type of noises
NASA Astrophysics Data System (ADS)
Sandev, Trifce; Tomovski, Živorad
2014-01-01
We study a generalized Langevin equation for a free particle driven by N internal noises. The mean square displacement and velocity autocorrelation function are derived in case of a mixture of Dirac delta, power law and Mittag-Leffler noises. Additionally, a frictional memory kernel of distributed order is considered. The long time limit and short time limit are analyzed, and the dominant contributions of noises on particle dynamics is discussed. Various different diffusive behaviors (subdiffusion, superdiffusion, normal diffusion, ultraslow diffusion) are obtained. The considered problem may be used in the theory of anomalous diffusion in complex environment.
Modeling Wildfire Incident Complexity Dynamics
Thompson, Matthew P.
2013-01-01
Wildfire management in the United States and elsewhere is challenged by substantial uncertainty regarding the location and timing of fire events, the socioeconomic and ecological consequences of these events, and the costs of suppression. Escalating U.S. Forest Service suppression expenditures is of particular concern at a time of fiscal austerity as swelling fire management budgets lead to decreases for non-fire programs, and as the likelihood of disruptive within-season borrowing potentially increases. Thus there is a strong interest in better understanding factors influencing suppression decisions and in turn their influence on suppression costs. As a step in that direction, this paper presents a probabilistic analysis of geographic and temporal variation in incident management team response to wildfires. The specific focus is incident complexity dynamics through time for fires managed by the U.S. Forest Service. The modeling framework is based on the recognition that large wildfire management entails recurrent decisions across time in response to changing conditions, which can be represented as a stochastic dynamic system. Daily incident complexity dynamics are modeled according to a first-order Markov chain, with containment represented as an absorbing state. A statistically significant difference in complexity dynamics between Forest Service Regions is demonstrated. Incident complexity probability transition matrices and expected times until containment are presented at national and regional levels. Results of this analysis can help improve understanding of geographic variation in incident management and associated cost structures, and can be incorporated into future analyses examining the economic efficiency of wildfire management. PMID:23691014
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.
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.
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.
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.
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.
Langevin model of low-energy fission
Sierk, Arnold John
2017-09-05
Since the earliest days of fission, stochastic models have been used to describe and model the process. For a quarter century, numerical solutions of Langevin equations have been used to model fission of highly excited nuclei, where microscopic potential-energy effects have been neglected. In this paper I present a Langevin model for the fission of nuclei with low to medium excitation energies, for which microscopic effects in the potential energy cannot be ignored. I solve Langevin equations in a five-dimensional space of nuclear deformations. The macroscopic-microscopic potential energy from a global nuclear structure model well benchmarked to nuclear masses ismore » tabulated on a mesh of approximately 107 points in this deformation space. The potential is defined continuously inside the mesh boundaries by use of a moving five-dimensional cubic spline approximation. Because of reflection symmetry, the effective mesh is nearly twice this size. For the inertia, I use a (possibly scaled) approximation to the inertia tensor defined by irrotational flow. A phenomenological dissipation tensor related to one-body dissipation is used. A normal-mode analysis of the dynamical system at the saddle point and the assumption of quasiequilibrium provide distributions of initial conditions appropriate to low excitation energies, and are extended to model spontaneous fission. A dynamical model of postscission fragment motion including dynamical deformations and separation allows the calculation of final mass and kinetic-energy distributions, along with other interesting quantities. The model makes quantitative predictions for fragment mass and kinetic-energy yields, some of which are very close to measured ones. Varying the energy of the incident neutron for induced fission allows the prediction of energy dependencies of fragment yields and average kinetic energies. With a simple approximation for spontaneous fission starting conditions, quantitative predictions are made for
Langevin model of low-energy fission
NASA Astrophysics Data System (ADS)
Sierk, Arnold J.
2017-09-01
Background: Since the earliest days of fission, stochastic models have been used to describe and model the process. For a quarter century, numerical solutions of Langevin equations have been used to model fission of highly excited nuclei, where microscopic potential-energy effects have been neglected. Purpose: In this paper I present a Langevin model for the fission of nuclei with low to medium excitation energies, for which microscopic effects in the potential energy cannot be ignored. Method: I solve Langevin equations in a five-dimensional space of nuclear deformations. The macroscopic-microscopic potential energy from a global nuclear structure model well benchmarked to nuclear masses is tabulated on a mesh of approximately 107 points in this deformation space. The potential is defined continuously inside the mesh boundaries by use of a moving five-dimensional cubic spline approximation. Because of reflection symmetry, the effective mesh is nearly twice this size. For the inertia, I use a (possibly scaled) approximation to the inertia tensor defined by irrotational flow. A phenomenological dissipation tensor related to one-body dissipation is used. A normal-mode analysis of the dynamical system at the saddle point and the assumption of quasiequilibrium provide distributions of initial conditions appropriate to low excitation energies, and are extended to model spontaneous fission. A dynamical model of postscission fragment motion including dynamical deformations and separation allows the calculation of final mass and kinetic-energy distributions, along with other interesting quantities. Results: The model makes quantitative predictions for fragment mass and kinetic-energy yields, some of which are very close to measured ones. Varying the energy of the incident neutron for induced fission allows the prediction of energy dependencies of fragment yields and average kinetic energies. With a simple approximation for spontaneous fission starting conditions
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.
NASA Astrophysics Data System (ADS)
Goldschmidt, Yadin Y.; Liu, Jin-Tao
2007-11-01
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 Bi2Sr2CaCu2O8+δ 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 dynamical measurements in the presence of a current that clearly identifies 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° with respect to the 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.
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.
Wealth dynamics on complex networks
NASA Astrophysics Data System (ADS)
Garlaschelli, Diego; Loffredo, Maria I.
2004-07-01
We study a model of wealth dynamics (Physica A 282 (2000) 536) which mimics transactions among economic agents. The outcomes of the model are shown to depend strongly on the topological properties of the underlying transaction network. The extreme cases of a fully connected and a fully disconnected network yield power-law and log-normal forms of the wealth distribution, respectively. We perform numerical simulations in order to test the model on more complex network topologies. We show that the mixed form of most empirical distributions (displaying a non-smooth transition from a log-normal to a power-law form) can be traced back to a heterogeneous topology with varying link density, which on the other hand is a recently observed property of real networks.
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
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.
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
Complex Dynamics of Equatorial Scintillation
NASA Astrophysics Data System (ADS)
Piersanti, Mirko; Materassi, Massimo; Forte, Biagio; Cicone, Antonio
2017-04-01
Radio power scintillation, namely highly irregular fluctuations of the power of trans-ionospheric GNSS signals, is the effect of ionospheric plasma turbulence. The scintillation patterns on radio signals crossing the medium inherit the ionospheric turbulence characteristics of inter-scale coupling, local randomness and large time variability. On this basis, the remote sensing of local features of the turbulent plasma is feasible by studying radio scintillation induced by the ionosphere. The distinctive character of intermittent turbulent media depends on the fluctuations on the space- and time-scale statistical properties of the medium. Hence, assessing how the signal fluctuation properties vary under different Helio-Geophysical conditions will help to understand the corresponding dynamics of the turbulent medium crossed by the signal. Data analysis tools, provided by complex system science, appear to be best fitting to study the response of a turbulent medium, as the Earth's equatorial ionosphere, to the non-linear forcing exerted by the Solar Wind (SW). In particular we used the Adaptive Local Iterative Filtering, the Wavelet analysis and the Information theory data analysis tool. We have analysed the radio scintillation and ionospheric fluctuation data at low latitude focusing on the time and space multi-scale variability and on the causal relationship between forcing factors from the SW environment and the ionospheric response.
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.
Langevin simulation of the chirally decomposed sine-Gordon model
Moriconi, L.; Moriconi, M.
2005-07-01
A large class of quantum and statistical field theoretical models, encompassing relevant condensed matter and non-Abelian gauge systems, are defined in terms of complex actions. As the ordinary Monte Carlo methods are useless in dealing with these models, alternative computational strategies have been proposed along the years. The Langevin technique, in particular, is known to be frequently plagued with difficulties such as strong numerical instabilities or subtle ergodic behavior. Regarding the chirally decomposed version of the sine-Gordon model as a prototypical case for the failure of the Langevin approach, we devise a truncation prescription in the stochastic differential equations which yields numerical stability and is assumed not to spoil the Berezinskii-Kosterlitz-Thouless transition. This conjecture is supported by a finite size scaling analysis, whereby a massive phase ending at a line of critical points is clearly observed for the truncated stochastic model.
Modelling platelet–blood flow interaction using the subcellular element Langevin method
Sweet, Christopher R.; Chatterjee, Santanu; Xu, Zhiliang; Bisordi, Katharine; Rosen, Elliot D.; Alber, Mark
2011-01-01
In this paper, a new three-dimensional modelling approach is described for studying fluid–viscoelastic cell interaction, the subcellular element Langevin (SCEL) method, with cells modelled by subcellular elements (SCEs) and SCE cells coupled with fluid flow and substrate models by using the Langevin equation. It is demonstrated that: (i) the new method is computationally efficient, scaling as 𝒪(N) for N SCEs; (ii) cell geometry, stiffness and adhesivity can be modelled by directly relating parameters to experimentally measured values; (iii) modelling the fluid–platelet interface as a surface leads to a very good correlation with experimentally observed platelet flow interactions. Using this method, the three-dimensional motion of a viscoelastic platelet in a shear blood flow was simulated and compared with experiments on tracking platelets in a blood chamber. It is shown that the complex platelet-flipping dynamics under linear shear flows can be accurately recovered with the SCEL model when compared with the experiments. All experimental details and electronic supplementary material are archived at http://biomath.math.nd.edu/scelsupplementaryinformation/. PMID:21593027
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.
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.
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.
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.
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.
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
Complexity and nonseparability of classical Liouvillian dynamics.
Prosen, Tomaž
2011-03-01
We propose a simple complexity indicator of classical Liouvillian dynamics, namely the separability entropy, which determines the logarithm of an effective number of terms in a Schmidt decomposition of phase space density with respect to an arbitrary fixed product basis. We show that linear growth of separability entropy provides a stricter criterion of complexity than Kolmogorov-Sinai entropy, namely it requires that the dynamics be exponentially unstable, nonlinear, and non-Markovian.
Complex dynamic in ecological time series
Peter Turchin; Andrew D. Taylor
1992-01-01
Although the possibility of complex dynamical behaviors-limit cycles, quasiperiodic oscillations, and aperiodic chaos-has been recognized theoretically, most ecologists are skeptical of their importance in nature. In this paper we develop a methodology for reconstructing endogenous (or deterministic) dynamics from ecological time series. Our method consists of fitting...
The Self as a Complex Dynamic System
ERIC Educational Resources Information Center
Mercer, Sarah
2011-01-01
This article explores the potential offered by complexity theories for understanding language learners' sense of self and attempts to show how the self might usefully be conceived of as a complex dynamic system. Rather than presenting empirical findings, the article discusses existent research on the self and aims at outlining a conceptual…
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
Functional Complexity and Regulation through RNA Dynamics
Dethoff, Elizabeth A.; Chugh, Jeetender; Mustoe, Anthony M.; Al-Hashimi, Hashim M.
2012-01-01
Preface Conformational changes involving coding and non-coding RNAs form the basis for genetic regulatory elements and provide an important source of complexity for driving many fundamental processes of life. While RNA is highly flexible, the underlying dynamics are robust and limited to transitions between the few conformations that preserve favorable base-pairing and stacking interactions. The mechanisms by which cellular processes harness RNA’s intrinsic dynamic behavior and steer it towards functionally productive pathways are complex. Versatile functions and ease of integration into a wide variety of genetic circuits and biochemical pathways suggests a general and fundamental role for RNA dynamics in cellular processes. PMID:22337051
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.
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.
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.
Controllability of Complex Dynamic Objects
NASA Astrophysics Data System (ADS)
Kalach, G. G.; Kazachek, N. A.; Morozov, A. A.
2017-01-01
Quality requirements for mobile robots intended for both specialized and everyday use are increasing in step with the complexity of the technological tasks assigned to the robots. Whether a mobile robot is for ground, aerial, or underwater use, the relevant quality characteristics can be summarized under the common concept of agility. This term denotes the object’s (the robot)’s ability to react quickly to control actions (change speed and direction), turn in a limited area, etc. When using this approach in integrated assessment of the quality characteristics of an object with the control system, it seems more constructive to use the term “degree of control”. This paper assesses the degree of control by an example of a mobile robot with the variable-geometry drive wheel axle. We show changes in the degree of control depending on the robot’s configuration, and results illustrated by calculation data, computer and practical experiments. We describe the prospects of using intelligent technology for efficient control of objects with a high degree of controllability.
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.
Ontology of Earth's nonlinear dynamic complex systems
NASA Astrophysics Data System (ADS)
Babaie, Hassan; Davarpanah, Armita
2017-04-01
As a complex system, Earth and its major integrated and dynamically interacting subsystems (e.g., hydrosphere, atmosphere) display nonlinear behavior in response to internal and external influences. The Earth Nonlinear Dynamic Complex Systems (ENDCS) ontology formally represents the semantics of the knowledge about the nonlinear system element (agent) behavior, function, and structure, inter-agent and agent-environment feedback loops, and the emergent collective properties of the whole complex system as the result of interaction of the agents with other agents and their environment. It also models nonlinear concepts such as aperiodic, random chaotic behavior, sensitivity to initial conditions, bifurcation of dynamic processes, levels of organization, self-organization, aggregated and isolated functionality, and emergence of collective complex behavior at the system level. By incorporating several existing ontologies, the ENDCS ontology represents the dynamic system variables and the rules of transformation of their state, emergent state, and other features of complex systems such as the trajectories in state (phase) space (attractor and strange attractor), basins of attractions, basin divide (separatrix), fractal dimension, and system's interface to its environment. The ontology also defines different object properties that change the system behavior, function, and structure and trigger instability. ENDCS will help to integrate the data and knowledge related to the five complex subsystems of Earth by annotating common data types, unifying the semantics of shared terminology, and facilitating interoperability among different fields of Earth science.
Synchronization of fractional order complex dynamical networks
NASA Astrophysics Data System (ADS)
Wang, Yu; Li, Tianzeng
2015-06-01
In this letter the synchronization of complex dynamical networks with fractional order chaotic nodes is studied. A fractional order controller for synchronization of complex network is presented. Some new sufficient synchronization criteria are proposed based on the Lyapunov stability theory and the LaSalle invariance principle. These synchronization criteria can apply to an arbitrary fractional order complex network in which the coupling-configuration matrix and the inner-coupling matrix are not assumed to be symmetric or irreducible. It means that this method is more general and effective. Numerical simulations of two fractional order complex networks demonstrate the universality and the effectiveness of the proposed method.
Constructing minimal models for complex system dynamics
NASA Astrophysics Data System (ADS)
Barzel, Baruch; Liu, Yang-Yu; Barabási, Albert-László
2015-05-01
One of the strengths of statistical physics is the ability to reduce macroscopic observations into microscopic models, offering a mechanistic description of a system's dynamics. This paradigm, rooted in Boltzmann's gas theory, has found applications from magnetic phenomena to subcellular processes and epidemic spreading. Yet, each of these advances were the result of decades of meticulous model building and validation, which are impossible to replicate in most complex biological, social or technological systems that lack accurate microscopic models. Here we develop a method to infer the microscopic dynamics of a complex system from observations of its response to external perturbations, allowing us to construct the most general class of nonlinear pairwise dynamics that are guaranteed to recover the observed behaviour. The result, which we test against both numerical and empirical data, is an effective dynamic model that can predict the system's behaviour and provide crucial insights into its inner workings.
Collective dynamics of active filament complexes
NASA Astrophysics Data System (ADS)
Nogucci, Hironobu; Ishihara, Shuji
2016-05-01
Networks of biofilaments are essential for the formation of cellular structures that support various biological functions. For the most part, previous studies have investigated the collective dynamics of rodlike biofilaments; however, the shapes of the actual subcellular components are often more elaborate. In this study, we considered an active object composed of two active filaments, which represents the progression from rodlike biofilaments to complex-shaped biofilaments. Specifically, we numerically assessed the collective behaviors of these active objects in two dimensions and observed several types of dynamics, depending on the density and the angle of the two filaments as shape parameters of the object. Among the observed collective dynamics, a moving density band that we named a "moving smectic" is introduced here for the first time. By analyzing the trajectories of individual objects and the interactions among them, this study demonstrated how interactions among active biofilaments with complex shapes could produce collective dynamics in a nontrivial manner.
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.
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.
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.
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.
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.
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…
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.
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.
Fokker-Planck description for a linear delayed Langevin equation with additive Gaussian noise
NASA Astrophysics Data System (ADS)
Giuggioli, Luca; McKetterick, Thomas John; Kenkre, V. M.; Chase, Matthew
2016-09-01
We construct an equivalent probability description of linear multi-delay Langevin equations subject to additive Gaussian white noise. By exploiting the time-convolutionless transform and a time variable transformation we are able to write a Fokker-Planck equation (FPE) for the 1-time and for the 2-time probability distributions valid irrespective of the regime of stability of the Langevin equations. We solve exactly the derived FPEs and analyze the aging dynamics by studying analytically the conditional probability distribution. We discuss explicitly why the initially conditioned distribution is not sufficient to describe fully out a non-Markov process as both preparation and observation times have bearing on its dynamics. As our analytic procedure can also be applied to linear Langevin equations with memory kernels, we compare the non-Markov dynamics of a one-delay system with that of a generalized Langevin equation with an exponential as well as a power law memory. Application to a generalization of the Green-Kubo formula is also presented.
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.
Exactly solvable nonequilibrium Langevin relaxation of a trapped nanoparticle
NASA Astrophysics Data System (ADS)
Salazar, Domingos S. P.; Lira, Sérgio A.
2016-11-01
In this work, we study the nonequilibrium statistical properties of the relaxation dynamics of a nanoparticle trapped in a harmonic potential. We report an exact time-dependent analytical solution to the Langevin dynamics that arises from the stochastic differential equation of our system’s energy in the underdamped regime. By utilizing this stochastic thermodynamics approach, we are able to completely describe the heat exchange process between the nanoparticle and the surrounding environment. As an important consequence of our results, we observe the validity of the heat exchange fluctuation theorem in our setup, which holds for systems arbitrarily far from equilibrium conditions. By extending our results for the case of N noninterating nanoparticles, we perform analytical asymptotic limits and direct numerical simulations that corroborate our analytical predictions.
Fractional Langevin equation: Overdamped, underdamped, and critical behaviors
NASA Astrophysics Data System (ADS)
Burov, S.; Barkai, E.
2008-09-01
The dynamical phase diagram of the fractional Langevin equation is investigated for a harmonically bound particle. It is shown that critical exponents mark dynamical transitions in the behavior of the system. Four different critical exponents are found. (i) αc=0.402±0.002 marks a transition to a nonmonotonic underdamped phase, (ii) αR=0.441… marks a transition to a resonance phase when an external oscillating field drives the system, and (iii) αχ1=0.527… and (iv) αχ2=0.707… mark transitions to a double-peak phase of the “loss” when such an oscillating field present. As a physical explanation we present a cage effect, where the medium induces an elastic type of friction. Phase diagrams describing over and underdamped regimes, with or without resonances, show behaviors different from normal.
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.
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.
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.
Langevin Equations for Reaction-Diffusion Processes.
Benitez, Federico; Duclut, Charlie; Chaté, Hugues; Delamotte, Bertrand; Dornic, Ivan; Muñoz, Miguel A
2016-09-02
For reaction-diffusion processes with at most bimolecular reactants, we derive well-behaved, numerically tractable, exact Langevin equations that govern a stochastic variable related to the response field in field theory. Using duality relations, we show how the particle number and other quantities of interest can be computed. Our work clarifies long-standing conceptual issues encountered in field-theoretical approaches and paves the way for systematic numerical and theoretical analyses of reaction-diffusion problems.
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
Channel-based Langevin approach for the stochastic Hodgkin-Huxley neuron
NASA Astrophysics Data System (ADS)
Huang, Yandong; Rüdiger, Sten; Shuai, Jianwei
2013-01-01
Stochasticity in ion channel gating is the major source of intrinsic neuronal noise, which can induce many important effects in neuronal dynamics. Several numerical implementations of the Langevin approach have been proposed to approximate the Markovian dynamics of the Hodgkin-Huxley neuronal model. In this work an improved channel-based Langevin approach is proposed by introducing a truncation procedure to limit the state fractions in the range of [0, 1]. The truncated fractions are put back into the state fractions in the next time step for channel noise calculation. Our simulations show that the bounded Langevin approaches combined with the restored process give better approximations to the statistics of action potentials with the Markovian method. As a result, in our approach the channel state fractions are disturbed by two terms of noise: an uncorrelated Gaussian noise and a time-correlated noise obtained from the truncated fractions. We suggest that the restoration of truncated fractions is a critical process for a bounded Langevin method.
Channel-based Langevin approach for the stochastic Hodgkin-Huxley neuron.
Huang, Yandong; Rüdiger, Sten; Shuai, Jianwei
2013-01-01
Stochasticity in ion channel gating is the major source of intrinsic neuronal noise, which can induce many important effects in neuronal dynamics. Several numerical implementations of the Langevin approach have been proposed to approximate the Markovian dynamics of the Hodgkin-Huxley neuronal model. In this work an improved channel-based Langevin approach is proposed by introducing a truncation procedure to limit the state fractions in the range of [0, 1]. The truncated fractions are put back into the state fractions in the next time step for channel noise calculation. Our simulations show that the bounded Langevin approaches combined with the restored process give better approximations to the statistics of action potentials with the Markovian method. As a result, in our approach the channel state fractions are disturbed by two terms of noise: an uncorrelated Gaussian noise and a time-correlated noise obtained from the truncated fractions. We suggest that the restoration of truncated fractions is a critical process for a bounded Langevin method.
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
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=√
Dynamics of Pre-replicative Complex Assembly*
Tsakraklides, Vasiliki; Bell, Stephen P.
2010-01-01
The pre-replicative complex (pre-RC) is formed at all potential origins of replication through the action of the origin recognition complex (ORC), Cdc6, Cdt1, and the Mcm2-7 complex. The end result of pre-RC formation is the loading of the Mcm2-7 replicative helicase onto origin DNA. We examined pre-RC formation in vitro and found that it proceeds through separable binding events. Origin-bound ORC recruits Cdc6, and this ternary complex then promotes helicase loading in the presence of a pre-formed Mcm2-7-Cdt1 complex. Using a stepwise pre-RC assembly assay, we investigated the fate of pre-RC components during later stages of the reaction. We determined that helicase loading is accompanied by dissociation of ORC, Cdc6, and Cdt1 from origin DNA. This dissociation requires ATP hydrolysis at a late stage of pre-RC assembly. Our results indicate that pre-RC formation is a dynamic process. PMID:20097898
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
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.
System crash as dynamics of complex networks.
Yu, Yi; Xiao, Gaoxi; Zhou, Jie; Wang, Yubo; Wang, Zhen; Kurths, Jürgen; Schellnhuber, Hans Joachim
2016-10-18
Complex systems, from animal herds to human nations, sometimes crash drastically. Although the growth and evolution of systems have been extensively studied, our understanding of how systems crash is still limited. It remains rather puzzling why some systems, appearing to be doomed to fail, manage to survive for a long time whereas some other systems, which seem to be too big or too strong to fail, crash rapidly. In this contribution, we propose a network-based system dynamics model, where individual actions based on the local information accessible in their respective system structures may lead to the "peculiar" dynamics of system crash mentioned above. Extensive simulations are carried out on synthetic and real-life networks, which further reveal the interesting system evolution leading to the final crash. Applications and possible extensions of the proposed model are discussed.
Correlations in a generalized elastic model: Fractional Langevin equation approach
NASA Astrophysics Data System (ADS)
Taloni, Alessandro; Chechkin, Aleksei; Klafter, Joseph
2010-12-01
The generalized elastic model (GEM) provides the evolution equation which governs the stochastic motion of several many-body systems in nature, such as polymers, membranes, and growing interfaces. On the other hand a probe (tracer) particle in these systems performs a fractional Brownian motion due to the spatial interactions with the other system’s components. The tracer’s anomalous dynamics can be described by a fractional Langevin equation (FLE) with a space-time correlated noise. We demonstrate that the description given in terms of GEM coincides with that furnished by the relative FLE, by showing that the correlation functions of the stochastic field obtained within the FLE framework agree with the corresponding quantities calculated from the GEM. Furthermore we show that the Fox H -function formalism appears to be very convenient to describe the correlation properties within the FLE approach.
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.
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.
Simulating the dynamics of complex plasmas.
Schwabe, M; Graves, D B
2013-08-01
Complex plasmas are low-temperature plasmas that contain micrometer-size particles in addition to the neutral gas particles and the ions and electrons that make up the plasma. The microparticles interact strongly and display a wealth of collective effects. Here we report on linked numerical simulations that reproduce many of the experimental results of complex plasmas. We model a capacitively coupled plasma with a fluid code written for the commercial package comsol. The output of this model is used to calculate forces on microparticles. The microparticles are modeled using the molecular dynamics package lammps, which we extended to include the forces from the plasma. Using this method, we are able to reproduce void formation, the separation of particles of different sizes into layers, lane formation, vortex formation, and other effects.
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.
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
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.
Complex networks repair strategies: Dynamic models
NASA Astrophysics Data System (ADS)
Fu, Chaoqi; Wang, Ying; Gao, Yangjun; Wang, Xiaoyang
2017-09-01
Network repair strategies are tactical methods that restore the efficiency of damaged networks; however, unreasonable repair strategies not only waste resources, they are also ineffective for network recovery. Most extant research on network repair focuses on static networks, but results and findings on static networks cannot be applied to evolutionary dynamic networks because, in dynamic models, complex network repair has completely different characteristics. For instance, repaired nodes face more severe challenges, and require strategic repair methods in order to have a significant effect. In this study, we propose the Shell Repair Strategy (SRS) to minimize the risk of secondary node failures due to the cascading effect. Our proposed method includes the identification of a set of vital nodes that have a significant impact on network repair and defense. Our identification of these vital nodes reduces the number of switching nodes that face the risk of secondary failures during the dynamic repair process. This is positively correlated with the size of the average degree < k > and enhances network invulnerability.
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.
Boltzmann-Langevin transport model for heavy-ion collisions
Ayik, S. |
1994-06-01
Heavy-ion collisions at intermediate energies exhibit catastrophic phenomena which requires descriptions based on stochastic transport models. First, the Boltzmann-Langevin model, which provides an example of such stochastic approaches, is briefly described. Then, a projection method for obtaining numerical solutions of the Boltzmann-Langevin equation is discussed. Finally, some applications of the model to heavy-ion collisions are presented.
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.
Complex mode dynamics of coupled wave oscillators
NASA Astrophysics Data System (ADS)
Alexander, T. J.; Yan, D.; Kevrekidis, P. G.
2013-12-01
We explore how nonlinear coherent waves localized in a few wells of a periodic potential can act analogously to a chain of coupled oscillators. We identify the small-amplitude oscillation modes of these “coupled wave oscillators” and find that they can be extended into the large amplitude regime, where some “ring” for long times. We also reveal the appearance of complex behavior such as the breakdown of Josephson-like oscillations, the destabilization of fundamental oscillation modes, and the emergence of chaotic oscillations for large amplitude excitations. We show that the dynamics may be accurately described by a discrete model with nearest-neighbor coupling, in which the lattice oscillators bear an effective mass.
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
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.
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.
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.
Baczewski, Andrew D.; Bond, Stephen D.
2013-01-01
Generalized Langevin dynamics (GLD) arise in the modeling of a number of systems, ranging from structured fluids that exhibit a viscoelastic mechanical response, to biological systems, and other media that exhibit anomalous diffusive phenomena. Molecular dynamics (MD) simulations that include GLD in conjunction with external and/or pairwise forces require the development of numerical integrators that are efficient, stable, and have known convergence properties. In this article, we derive a family of extended variable integrators for the Generalized Langevin equation with a positive Prony series memory kernel. Using stability and error analysis, we identify a superlative choice of parameters and implement the corresponding numerical algorithm in the LAMMPS MD software package. Salient features of the algorithm include exact conservation of the first and second moments of the equilibrium velocity distribution in some important cases, stable behavior in the limit of conventional Langevin dynamics, and the use of a convolution-free formalism that obviates the need for explicit storage of the time history of particle velocities. Capability is demonstrated with respect to accuracy in numerous canonical examples, stability in certain limits, and an exemplary application in which the effect of a harmonic confining potential is mapped onto a memory kernel.
NASA Astrophysics Data System (ADS)
Pahlavani, M. R.; Mirfathi, S. M.
2017-07-01
Neutron multiplicity prior to scission and evaluation of mass distribution of fission fragments with the fission time scale for neutron induced fission of plutonium isotopes are investigated using a dynamical Langevin approach. Also, mass yield of fragments and prompt neutron multiplicity in different time scales of the fission process are compared with experimental data. Reasonable agreement is achieved between calculated and available experimental data.
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.
Guiding locomotion in complex, dynamic environments
Fajen, Brett R.
2013-01-01
Locomotion in complex, dynamic environments is an integral part of many daily activities, including walking in crowded spaces, driving on busy roadways, and playing sports. Many of the tasks that humans perform in such environments involve interactions with moving objects—that is, they require people to coordinate their own movement with the movements of other objects. A widely adopted framework for research on the detection, avoidance, and interception of moving objects is the bearing angle model, according to which observers move so as to keep the bearing angle of the object constant for interception and varying for obstacle avoidance. The bearing angle model offers a simple, parsimonious account of visual control but has several significant limitations and does not easily scale up to more complex tasks. In this paper, I introduce an alternative account of how humans choose actions and guide locomotion in the presence of moving objects. I show how the new approach addresses the limitations of the bearing angle model and accounts for a variety of behaviors involving moving objects, including (1) choosing whether to pass in front of or behind a moving obstacle, (2) perceiving whether a gap between a pair of moving obstacles is passable, (3) avoiding a collision while passing through single or multiple lanes of traffic, (4) coordinating speed and direction of locomotion during interception, (5) simultaneously intercepting a moving target while avoiding a stationary or moving obstacle, and (6) knowing whether to abandon the chase of a moving target. I also summarize data from recent studies that support the new approach. PMID:23885238
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.
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
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.
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.
A path-integral Langevin equation treatment of low-temperature doped helium clusters.
Ing, Christopher; Hinsen, Konrad; Yang, Jing; Zeng, Toby; Li, Hui; Roy, Pierre-Nicholas
2012-06-14
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)] 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 He(N)-CO(2) 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)], an open-source molecular simulation package.
Dynamic growth of selected Paleozoic reef complexes
Bowsher, A.L.
1986-03-01
The sequential positioning of the compound biothermal facies of paleozoic reefs reflects the history of water movement (rise or fall) over the shelf on which the reef complex accumulated. Siliciclastic deposits are directly related to reef complexes. Reef complexes built on a constructional platform generally show progradation in response to increase water depth over the platform. At least one reef complex in the Sacramento Mountains is retrograde, having formed over a platform that is partly a destructional surface. Reefs are best characterized as progradational or retrogradational in preference to transgressional or regressional. The reef complex often shows several different growth stages separated by hiatuses, although the depositional breaks may appear to be minor. The complex may record tilting of the subreef platform. The reef complex is only a facet of the total sedimentary pattern of the depositional basin. A method is illustrated for determining the relative rate of construction (growth) of reef complexes.
Double symbolic joint entropy in nonlinear dynamic complexity analysis
NASA Astrophysics Data System (ADS)
Yao, Wenpo; Wang, Jun
2017-07-01
Symbolizations, the base of symbolic dynamic analysis, are classified as global static and local dynamic approaches which are combined by joint entropy in our works for nonlinear dynamic complexity analysis. Two global static methods, symbolic transformations of Wessel N. symbolic entropy and base-scale entropy, and two local ones, namely symbolizations of permutation and differential entropy, constitute four double symbolic joint entropies that have accurate complexity detections in chaotic models, logistic and Henon map series. In nonlinear dynamical analysis of different kinds of heart rate variability, heartbeats of healthy young have higher complexity than those of the healthy elderly, and congestive heart failure (CHF) patients are lowest in heartbeats' joint entropy values. Each individual symbolic entropy is improved by double symbolic joint entropy among which the combination of base-scale and differential symbolizations have best complexity analysis. Test results prove that double symbolic joint entropy is feasible in nonlinear dynamic complexity analysis.
Fractional Langevin equation and Riemann-Liouville fractional derivative.
Sau Fa, Kwok
2007-10-01
In this present work we consider a fractional Langevin equation with Riemann-Liouville fractional time derivative which modifies the classical Newtonian force, nonlocal dissipative force, and long-time correlation. We investigate the first two moments, variances and position and velocity correlation functions of this system. We also compare them with the results obtained from the same fractional Langevin equation which uses the Caputo fractional derivative.
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.
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.
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
Investigation of thermal denaturation of DNA molecules based on langevin equation approach
NASA Astrophysics Data System (ADS)
Hui-jie, Yang; Yi-zhong, Zhuo; Xi-zhen, Wu
1994-07-01
In this paper, by using non-equilibrium transport theory, the thermal denaturation of DNA molecules is investigated as a preliminary step to clarify the dynamical process of DNA transcription. The distribution functions of the displacement of base pairs at different temperatures are calculated. A modified model is also proposed which can reproduce the essential features of the denaturation process. Calculations show that Langevin equation is an effective tool for describing the dynamical process of DNA molecules and it seems to be more advantageous over the Nosé method.
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.
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
Langevin Equation Methods for Laser Cooling Calculations
NASA Astrophysics Data System (ADS)
Dunjko, Vanja; Hatamian, T. S.; Bergeman, T.
1996-05-01
The Langevin equation (LE) offers an alternative means for computing velocity distributions of laser-cooled atoms from given force and diffusion functions (F and D). Computations with the LE are often lengthier than with the Fokker-Planck equation (FPE), but one may consider spatial dependence of F and D, effects of non-zero correlation time, and problems in 2 and 3 dimensions, as shown by Javanainen.(J. Javanainen, Phys. Rev. A 46), 5819 (1992) With a colored noise algorithm(R.F. Fox et al.), Phys. Rev. A 38, 5938 (1988). to simulate a finite correlation time, we find in cases studied so far that the velocity distribution narrows, thereby increasing the discrepancy with quantum results. When spatial dependence in F and D is included in the LE using another algorithm,(Greiner al.), J. Stat. Phys. 51, 95 (1988). we find that the velocity distribution for 2-level atom cooling exhibits a dip at v=0 because atoms in the light shift potential wells are cooled more slowly.(M. Doery et al.), Phys. Rev. A 51, 4881 (1995). This dip is absent in results with the FPE, and is sharper with the LE than with the quantum density matrix approach because there is no averaging over the deBroglie wavelength.
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.
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.
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-
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
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.
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%.
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.
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.
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.
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.
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.
Complexity and dynamics of topological and community structure in complex networks
NASA Astrophysics Data System (ADS)
Berec, Vesna
2017-07-01
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.
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
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…
Complex dynamics and empirical evidence (Invited Paper)
NASA Astrophysics Data System (ADS)
Delli Gatti, Domenico; Gaffeo, Edoardo; Giulioni, Gianfranco; Gallegati, Mauro; Kirman, Alan; Palestrini, Antonio; Russo, Alberto
2005-05-01
Standard macroeconomics, based on a reductionist approach centered on the representative agent, is badly equipped to explain the empirical evidence where heterogeneity and industrial dynamics are the rule. In this paper we show that a simple agent-based model of heterogeneous financially fragile agents is able to replicate a large number of scaling type stylized facts with a remarkable degree of statistical precision.
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.
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.
Topology identification of complex dynamical networks
NASA Astrophysics Data System (ADS)
Zhao, Junchan; Li, Qin; Lu, Jun-An; Jiang, Zhong-Ping
2010-06-01
Recently, some researchers investigated the topology identification for complex networks via LaSalle's invariance principle. The principle cannot be directly applied to time-varying systems since the positive limit sets are generally not invariant. In this paper, we study the topology identification problem for a class of weighted complex networks with time-varying node systems. Adaptive identification laws are proposed to estimate the coupling parameters of the networks with and without communication delays. We prove that the asymptotic identification is ensured by a persistently exciting condition. Numerical simulations are given to demonstrate the effectiveness of the proposed approach.
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.
Neural networks and dynamic complex systems
Fox, G.; Furmanski, Wojtek; Ho, Alex; Koller, J.; Simic, P.; Wong, Isaac
1989-01-01
We describe the use of neural networks for optimization and inference associated with a variety of complex systems. We show how a string formalism can be used for parallel computer decomposition, message routing and sequential optimizing compilers. We extend these ideas to a general treatment of spatial assessment and distributed artificial intelligence. 34 refs., 12 figs.
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.
Mapping complex traits as a dynamic system.
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. Copyright © 2015 Elsevier B.V. All rights reserved.
Mapping complex traits as a dynamic system
Sun, Lidan; Wu, Rongling
2017-01-01
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. PMID:25772476
Metapopulation dynamics in a complex ecological landscape.
Colombo, E H; Anteneodo, C
2015-08-01
We propose a general model to study the interplay between spatial dispersal and environment spatiotemporal fluctuations in metapopulation dynamics. An ecological landscape of favorable patches is generated like a Lévy dust, which allows to build a range of patterns, from dispersed to clustered ones. Locally, the dynamics is driven by a canonical model for the time evolution of the population density, consisting of a logistic expression plus multiplicative noises. Spatial coupling is introduced by means of two spreading mechanisms: diffusion and selective dispersal driven by patch suitability. We focus on the long-time population size as a function of habitat configurations, environment fluctuations, and coupling schemes. We obtain the conditions, that the spatial distribution of favorable patches and the coupling mechanisms must fulfill, to grant population survival. The fundamental phenomenon that we observe is the positive feedback between environment fluctuations and spatial spread preventing extinction.
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.
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
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.
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.
Conedy: a scientific tool to investigate complex network dynamics.
Rothkegel, Alexander; Lehnertz, Klaus
2012-03-01
We present Conedy, a performant scientific tool to numerically investigate dynamics on complex networks. Conedy allows to create networks and provides automatic code generation and compilation to ensure performant treatment of arbitrary node dynamics. Conedy can be interfaced via an internal script interpreter or via a Python module.
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.
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…
Universal properties of dynamically complex systems - The organization of chaos
NASA Astrophysics Data System (ADS)
Procaccia, Itamar
1988-06-01
The complex dynamic behavior of natural systems far from equilibrium is discussed. Progress that has been made in understanding universal aspects of the paths to such behavior, of the trajectories at the borderline of chaos, and of the nature of the complexity in the chaotic regime, is reviewed. The emerging grammar of chaos is examined.
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…
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…
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.
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.
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.
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.
Spatial price dynamics: From complex network perspective
NASA Astrophysics Data System (ADS)
Li, Y. L.; Bi, J. T.; Sun, H. J.
2008-10-01
The spatial price problem means that if the supply price plus the transportation cost is less than the demand price, there exists a trade. Thus, after an amount of exchange, the demand price will decrease. This process is continuous until an equilibrium state is obtained. However, how the trade network structure affects this process has received little attention. In this paper, we give a evolving model to describe the levels of spatial price on different complex network structures. The simulation results show that the network with shorter path length is sensitive to the variation of prices.
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
ERIC Educational Resources Information Center
Henry, Alastair
2016-01-01
Currently, the inner dynamics of teacher identity transformations remain a "black box." Conceptualizing preservice teacher identity as a complex dynamic system, and the notion of "being someone who teaches" in dialogical terms as involving shifts between different teacher voices, the study investigates the dynamical processes…
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.
Diffusion described with quantum Langevin equation in tilted periodic potential
NASA Astrophysics Data System (ADS)
Duan, Hong-Guang; Liang, Xian-Ting
2012-11-01
In this paper, diffusion behavior of Brownian particles moving in a 1D periodic potential landscape has been theoretically investigated by using the general quantum Langevin equation. At first, in the condition of weak disorder, some anomalous diffusive behaviors have been revealed in the process. Then, two types of mean square displacement, ensemble averaged and time averaged mean square displacement, have been investigated in a long time, and the weak ergodicity breaking phenomenon has been revealed. It is shown that the general quantum Langevin equation can exhibit some novel details of the experimental diffusion process.
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
Numerical simulation of the Langevin equation for skewed turbulence
Ermak, D. L.; Nasstrom, J. S.
1994-12-01
In this paper the authors present a numerical method for the generalized Langevin equation of motion with skewed random forcing for the case of homogeneous, skewed turbulence. The authors begin by showing how the analytic solution to the Langevin equation for this case can be used to determine the relationship between the particle velocity moments and the properties of the skewed random force. They then present a numerical method that uses simple probability distribution functions to simulate the effect of the random force. The numerical solution is shown to be exact in the limit of infinitesimal time steps, and to be within acceptable error limits when practical time steps are used.
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.
Lisin, E. A.; Lisina, I. I.; Vaulina, O. S.; Petrov, O. F.
2015-03-15
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)
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.
Implicit numerical schemes for the stochastic Liouville equation in Langevin form.
Håkansson, Pär; Nair, Prasanth B
2011-05-28
We present and numerically test implicit as well as explicit numerical schemes for solving the Stochastic Liouville Equation in Langevin form. It is found that implicit schemes provide significant gain in robustness, for example, when nonsecular Hamiltonian terms cannot be ignored in electron and nuclear spin resonance. Implicit schemes open up several spectroscopic relaxation problems for direct interpretation using the Stochastic Liouville Equation. To illustrate the proposed numerical schemes, studies are presented for an electron paramagnetic resonance problem involving a coordinated copper complex and a fluorescence problem. This journal is © the Owner Societies 2011
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.
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.
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.
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.
Dynamics of Ranking Processes in Complex Systems
NASA Astrophysics Data System (ADS)
Blumm, Nicholas; Ghoshal, Gourab; Forró, Zalán; Schich, Maximilian; Bianconi, Ginestra; Bouchaud, Jean-Philippe; Barabási, Albert-László
2012-09-01
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.
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.
Visualization of chemical reaction dynamics: Toward understanding complex polyatomic reactions
SUZUKI, Toshinori
2013-01-01
Polyatomic molecules have several electronic states that have similar energies. Consequently, their chemical dynamics often involve nonadiabatic transitions between multiple potential energy surfaces. Elucidating the complex reactions of polyatomic molecules is one of the most important tasks of theoretical and experimental studies of chemical dynamics. This paper describes our recent experimental studies of the multidimensional multisurface dynamics of polyatomic molecules based on two-dimensional ion/electron imaging. It also discusses ultrafast photoelectron spectroscopy of liquids for elucidating nonadiabatic electronic dynamics in aqueous solutions. PMID:23318678
Visualization of chemical reaction dynamics: toward understanding complex polyatomic reactions.
Suzuki, Toshinori
2013-01-01
Polyatomic molecules have several electronic states that have similar energies. Consequently, their chemical dynamics often involve nonadiabatic transitions between multiple potential energy surfaces. Elucidating the complex reactions of polyatomic molecules is one of the most important tasks of theoretical and experimental studies of chemical dynamics. This paper describes our recent experimental studies of the multidimensional multisurface dynamics of polyatomic molecules based on two-dimensional ion/electron imaging. It also discusses ultrafast photoelectron spectroscopy of liquids for elucidating nonadiabatic electronic dynamics in aqueous solutions. (Communicated by Hiroo INOKUCHI, M.J.A.)
The topology and dynamics of complex networks
NASA Astrophysics Data System (ADS)
Dezso, Zoltan
We start with a brief introduction about the topological properties of real networks. Most real networks are scale-free, being characterized by a power-law degree distribution. The scale-free nature of real networks leads to unexpected properties such as the vanishing epidemic threshold. Traditional methods aiming to reduce the spreading rate of viruses cannot succeed on eradicating the epidemic on a scale-free network. We demonstrate that policies that discriminate between the nodes, curing mostly the highly connected nodes, can restore a finite epidemic threshold and potentially eradicate the virus. We find that the more biased a policy is towards the hubs, the more chance it has to bring the epidemic threshold above the virus' spreading rate. We continue by studying a large Web portal as a model system for a rapidly evolving network. We find that the visitation pattern of a news document decays as a power law, in contrast with the exponential prediction provided by simple models of site visitation. This is rooted in the inhomogeneous nature of the browsing pattern characterizing individual users: the time interval between consecutive visits by the same user to the site follows a power law distribution, in contrast with the exponential expected for Poisson processes. We show that the exponent characterizing the individual user's browsing patterns determines the power-law decay in a document's visitation. Finally, we turn our attention to biological networks and demonstrate quantitatively that protein complexes in the yeast, Saccharomyces cerevisiae, are comprised of a core in which subunits are highly coexpressed, display the same deletion phenotype (essential or non-essential) and share identical functional classification and cellular localization. The results allow us to define the deletion phenotype and cellular task of most known complexes, and to identify with high confidence the biochemical role of hundreds of proteins with yet unassigned functionality.
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
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.
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.
Complex dynamics in the Oregonator model with linear delayed feedback
NASA Astrophysics Data System (ADS)
Sriram, K.; Bernard, S.
2008-06-01
The Belousov-Zhabotinsky (BZ) reaction can display a rich dynamics when a delayed feedback is applied. We used the Oregonator model of the oscillating BZ reaction to explore the dynamics brought about by a linear delayed feedback. The time-delayed feedback can generate a succession of complex dynamics: period-doubling bifurcation route to chaos; amplitude death; fat, wrinkled, fractal, and broken tori; and mixed-mode oscillations. We observed that this dynamics arises due to a delay-driven transition, or toggling of the system between large and small amplitude oscillations, through a canard bifurcation. We used a combination of numerical bifurcation continuation techniques and other numerical methods to explore the dynamics in the strength of feedback-delay space. We observed that the period-doubling and quasiperiodic route to chaos span a low-dimensional subspace, perhaps due to the trapping of the trajectories in the small amplitude regime near the canard; and the trapped chaotic trajectories get ejected from the small amplitude regime due to a crowding effect to generate chaotic-excitable spikes. We also qualitatively explained the observed dynamics by projecting a three-dimensional phase portrait of the delayed dynamics on the two-dimensional nullclines. This is the first instance in which it is shown that the interaction of delay and canard can bring about complex dynamics.
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…
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…
Ergodic properties of fractional Langevin motion with spatial correlated noise
NASA Astrophysics Data System (ADS)
Duan, H.-G.; Liang, X.-T.
2012-06-01
In this paper, using fractional Langevin equation, we investigate the diffusion behavior of particles in the potential with spatial correlated noise (random disorder). Weak ergodicity breaking is revealed by plotting time averaged mean square displacement and ergodicity breaking parameter. The results are consistent with continuous time random walk (CTRW) and also in agreement with the properties of ones obtained with experiments.
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.
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.
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.
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.
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.
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.
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
Characterizing the Dynamics of Proteasome Complexes by Proteomics Approaches
Kaake, Robyn M.; Kao, Athit; Yu, Clinton
2014-01-01
Abstract Significance: The proteasome is the degradation machine of the ubiquitin-proteasome system, which is critical in controlling many essential biological processes. Aberrant regulation of proteasome-dependent protein degradation can lead to various human diseases, and general proteasome inhibitors have shown efficacy for cancer treatments. Though clinically effective, current proteasome inhibitors have detrimental side effects and, thus, better therapeutic strategies targeting proteasomes are needed. Therefore, a comprehensive characterization of proteasome complexes will provide the molecular details that are essential for developing new and improved drugs. Recent Advances: New mass spectrometry (MS)-based proteomics approaches have been developed to study protein interaction networks and structural topologies of proteasome complexes. The results have helped define the dynamic proteomes of proteasome complexes, thus providing new insights into the mechanisms underlying proteasome function and regulation. Critical Issues: The proteasome exists as heterogeneous populations in tissues/cells, and its proteome is highly dynamic and complex. In addition, proteasome complexes are regulated by various mechanisms under different physiological conditions. Consequently, complete proteomic profiling of proteasome complexes remains a major challenge for the field. Future Directions: We expect that proteomic methodologies enabling full characterization of proteasome complexes will continue to evolve. Further advances in MS instrumentation and protein separation techniques will be needed to facilitate the detailed proteomic analysis of low-abundance components and subpopulations of proteasome complexes. The results will help us understand proteasome biology as well as provide new therapeutic targets for disease diagnostics and treatment. Antioxid. Redox Signal. 21, 2444–2456. PMID:24423446
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.
Tozan, Yesim; Ompad, Danielle C
2015-06-01
In a variety of urban health frameworks, cities are conceptualized as complex and dynamic yet commonly used epidemiological methods have failed to address this complexity and dynamism head on due to their narrow problem definitions and linear analytical representations. Scholars from a variety of disciplines have also long conceptualized cities as systems, but few have modeled urban health issues as problems within a system. Systems thinking in general and system dynamics in particular are relatively new approaches in public health, but ones that hold immense promise as methodologies to model and analyze the complexity underlying urban processes to effectively inform policy actions in dynamic environments. This conceptual essay reviews the utility of applying the concepts, principles, and methods of systems thinking to the study of complex urban health phenomena as a complementary approach to standard epidemiological methods using specific examples and provides recommendations on how to better incorporate systems thinking methods in urban health research and practice.
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
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.
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.
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.
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.
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
Modeling near-barrier collisions of heavy ions based on a Langevin-type approach
NASA Astrophysics Data System (ADS)
Karpov, A. V.; Saiko, V. V.
2017-08-01
Background: Multinucleon transfer in low-energy nucleus-nucleus collisions is proposed as a method of production of yet-unknown neutron-rich nuclei hardly reachable by other methods. Purpose: Modeling of dynamics of nuclear reactions induced by heavy ions in their full complexity of competing reaction channels remains to be a challenging task. The work is aimed at development of such a model and its application to the analysis of multinucleon transfer in deep inelastic collisions of heavy ions leading, in particular, to formation of neutron-rich isotopes in the vicinity of the N =126 shell closure. Method: Multidimensional dynamical model of nucleus-nucleus collisions based on the Langevin equations has been proposed. It is combined with a statistical model for simulation of de-excitation of primary reaction fragments. The model provides a continuous description of the system evolution starting from the well-separated target and projectile in the entrance channel of the reaction up to the formation of final reaction products. Results: A rather complete set of experimental data available for reactions 136Xe+198Pt,208Pb,209Bi was analyzed within the developed model. The model parameters have been determined. The calculated energy, mass, charge, and angular distributions of reaction products, their various correlations as well as cross sections for production of specific isotopes agree well with the data. On this basis, optimal experimental conditions for synthesizing the neutron-rich nuclei in the vicinity of the N =126 shell were formulated and the corresponding cross sections were predicted. Conclusions: The production yields of neutron-rich nuclei with N =126 weakly depend on the incident energy. At the same time, the corresponding angular distributions are strongly energy dependent. They are peaked at grazing angles for larger energies and extend up to the forward angles at low near-barrier collision energies. The corresponding cross sections exceed 100 nb for
The complex dynamics of products and its asymptotic properties
Cristelli, Matthieu; Zaccaria, Andrea; Pietronero, Luciano
2017-01-01
We analyse global export data within the Economic Complexity framework. We couple the new economic dimension Complexity, which captures how sophisticated products are, with an index called logPRODY, a measure of the income of the respective exporters. Products’ aggregate motion is treated as a 2-dimensional dynamical system in the Complexity-logPRODY plane. We find that this motion can be explained by a quantitative model involving the competition on the markets, that can be mapped as a scalar field on the Complexity-logPRODY plane and acts in a way akin to a potential. This explains the movement of products towards areas of the plane in which the competition is higher. We analyse market composition in more detail, finding that for most products it tends, over time, to a characteristic configuration, which depends on the Complexity of the products. This market configuration, which we called asymptotic, is characterized by higher levels of competition. PMID:28520794
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.
Complex systems dynamics in aging: new evidence, continuing questions.
Cohen, Alan A
2016-02-01
There have long been suggestions that aging is tightly linked to the complex dynamics of the physiological systems that maintain homeostasis, and in particular to dysregulation of regulatory networks of molecules. This review synthesizes recent work that is starting to provide evidence for the importance of such complex systems dynamics in aging. There is now clear evidence that physiological dysregulation--the gradual breakdown in the capacity of complex regulatory networks to maintain homeostasis--is an emergent property of these regulatory networks, and that it plays an important role in aging. It can be measured simply using small numbers of biomarkers. Additionally, there are indications of the importance during aging of emergent physiological processes, functional processes that cannot be easily understood through clear metabolic pathways, but can nonetheless be precisely quantified and studied. The overall role of such complex systems dynamics in aging remains an important open question, and to understand it future studies will need to distinguish and integrate related aspects of aging research, including multi-factorial theories of aging, systems biology, bioinformatics, network approaches, robustness, and loss of complexity.
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.
Dynamical complexity of short and noisy time series. Compression-Complexity vs. Shannon entropy
NASA Astrophysics Data System (ADS)
Nagaraj, Nithin; Balasubramanian, Karthi
2017-07-01
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.
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.
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.
Complex Dynamics of Compound Vesicles in Linear Flow
NASA Astrophysics Data System (ADS)
Levant, Michael; Steinberg, Victor
2014-04-01
We report first experimental observations of dynamics of compound vesicles in linear flow realized in a microfluidic four-roll mill. We show that while a compound vesicle undergoes the same main tank-treading, trembling (TR), and tumbling regimes, its dynamics are far richer and more complex than that of unilamellar vesicles. A new swinging motion of the inner vesicle is found in TR in accord with simulations. The inner and outer vesicles can exist simultaneously in different dynamical regimes and can undergo either synchronized or unsynchronized motions depending on the filling factor. A compound vesicle can be used as a physical model to study white blood cell dynamics in flow similar to a unilamellar vesicle used successfully to model anucleate cells.
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.
Critical fluctuations and anomalous transport in soft Yukawa-Langevin systems.
Ratynskaia, S; Regnoli, G; Rypdal, K; Klumov, B; Morfill, G
2009-10-01
Simulation of a Langevin-dynamics model demonstrates emergence of critical fluctuations and anomalous grain transport which have been observed in experiments on "soft" quasi-two-dimensional dusty plasma clusters. Our model does not contain external drive or plasma interactions that serve to drive the system away from thermodynamic equilibrium. The grains are confined by an external potential, interact via static Yukawa forces, and are subject to stochastic heating and dissipation from neutrals. One remarkable feature is emergence of leptokurtic probability distributions of grain displacements xi(tau) on time scales tau < tau(Delta), where tau(Delta) is the time at which the standard deviation sigma(tau) identical with (xi(2)(tau))(1/2) approaches the mean intergrain distance Delta. Others are development of humps in the distributions on multiples of Delta , anomalous Hurst exponents, and transitions from leptokurtic toward Gaussian displacement distributions on time scales tau > tau(Delta). The latter is a signature of intermittency, here interpreted as a transition from bursty transport associated with hopping on intermediate time scales to vortical flows on longer time scales. These intermittency features are quantitatively modeled by a single-particle Itô-Langevin stochastic equation with a nonlinear drift term.
NASA Astrophysics Data System (ADS)
Usang, Mark; Ivanyuk, Fedir; Ishizuka, Chikako; Chiba, Satoshi
2017-09-01
The Langevin dynamical description of fission observables is inspired by the random evolution of shape parameters across the potential surface. In these work, we shall use mass and friction tensors inspired from Linear Response Theory (microscopic transport coefficients) and obtain the fission observables associated with these calculations. We compare these microscopic results with calculations using hydrodynamical mass tensor and wall-window friction tensor (macroscopic transport coefficients). We are able to calculate the fission product yield, Coulomb kinetic energy and prescission kinetic energy from the Langevin calculation. This allows us to observe the systematic of average light and heavy mass fission product yield calculated using both microscopic and macroscopic calculations. We also compare the results of microscopic and macroscopic calculation total kinetic energy (TKE) with Viola's TKE systematics. In the case of 236,239U compound nucleus, we do the microscopic calculation for several excitation energy up to 30 MeV and afterwards compare it to the TKE of experimental data and corresponding macroscopic TKE. Reasonable agreement of microscopic TKE to experiment is obtained which shows decreasing TKE with increasing excitation energy. Macroscopic TKE however, is independent of excitation energy and thus contrary to experimental data.
Force-linearization closure for non-Markovian Langevin systems with time delay
NASA Astrophysics Data System (ADS)
Loos, Sarah A. M.; Klapp, Sabine H. L.
2017-07-01
This paper is concerned with the Fokker-Planck (FP) description of classical stochastic systems with discrete time delay. The non-Markovian character of the corresponding Langevin dynamics naturally leads to a coupled infinite hierarchy of FP equations for the various n -time joint distribution functions. Here, we present an approach to close the hierarchy at the one-time level based on a linearization of the deterministic forces in all members of the hierarchy starting from the second one. This leads to a closed equation for the one-time probability density in the steady state. Considering two generic nonlinear systems, a colloidal particle in a sinusoidal or bistable potential supplemented by a linear delay force, we demonstrate that our approach yields a very accurate representation of the density as compared to quasiexact numerical results from direct solution of the Langevin equation. Moreover, the results are significantly improved against those from a small-delay approximation and a perturbation-theoretical approach. We also discuss the possibility of accessing transport-related quantities, such as escape times, based on an additional Kramers approximation. Our approach applies to a wide class of models with nonlinear deterministic forces.
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.
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.
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.
Fokker-Planck and Langevin equations for arbitrary slip velocities
NASA Astrophysics Data System (ADS)
Fernández-Feria, R.; Riesco-Chueca, P.
1987-11-01
An expression for the Fokker-Planck equation governing the velocity distribution function of particles or heavy molecules immersed in a host light gas valid for arbitrary mean velocities of the heavy component is given. This expression generalizes previous results which were limited to small differences between the mean velocities of the heavy and light components compared with the thermal velocity of the light gas. The derivation assumes a Maxwellian velocity distribution function for the light gas, elastic heavy-light collisions, and makes use of integrals computed by Riesco-Chueca, Fernández-Feria, and Fernández de la Mora in Ref. 1. The stochastic Langevin equation associated with this Fokker-Planck collision operator is also obtained. More in general, we derive the Langevin equation corresponding to the general form of the Fokker-Planck collision operator, and particularize it to the present case.
Dynamical process of complex systems and fractional differential equations
NASA Astrophysics Data System (ADS)
Hara, Hiroaki; Tamura, Yoshiyasu
2013-10-01
Behavior of dynamical process of complex systems is investigated. Specifically we analyse two types of ideal complex systems. For analysing the ideal complex systems, we define the response functions describing the internal states to an external force. The internal states are obtained as a relaxation process showing a "power law" distribution, such as scale free behaviors observed in actual measurements. By introducing a hybrid system, the logarithmic time, and double logarithmic time, we show how the "slow relaxation" (SR) process and "super slow relaxation" (SSR) process occur. Regarding the irregular variations of the internal states as an activation process, we calculate the response function to the external force. The behaviors are classified into "power", "exponential", and "stretched exponential" type. Finally we construct a fractional differential equation (FDE) describing the time evolution of these complex systems. In our theory, the exponent of the FDE or that of the power law distribution is expressed in terms of the parameters characterizing the structure of the system.
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.
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.
Model for complex heart rate dynamics in health and diseases
NASA Astrophysics Data System (ADS)
Kotani, Kiyoshi; Struzik, Zbigniew R.; Takamasu, Kiyoshi; Stanley, H. Eugene; Yamamoto, Yoshiharu
2005-10-01
A physiologically motivated, dynamical model of cardiovascular autonomic regulation is shown to be capable of generating long-range correlated and multifractal heart rate. Virtual disease simulations are carried out systematically to account for the disease-induced relative dysfunction of the parasympathetic and the sympathetic branches of the autonomic control. Statistical agreement of the simulation results with those of real life data is reached, suggesting the possible use of the model as a state-of-the-art basis for further understanding of the physiological correlates of complex heart rate dynamics.
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.
The Langevin method and Hubbard-like models
NASA Astrophysics Data System (ADS)
Gross, Mark; Hamber, Herbert
1989-12-01
We reexamine the difficulties associated with application of the Langevin method to numerical simulation of models with non-positive definite statistical weights, including the Hubbard model. We show how to avoid the violent crossing of the zeroes of the weights and how to move those nodes away from the real axis. However, it still appears necessary to keep track of the sign (or phase) of the weight.
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.
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
Bursting Transition Dynamics Within the Pre-Bötzinger Complex
NASA Astrophysics Data System (ADS)
Duan, Lixia; Chen, Xi; Tang, Xuhui; Su, Jianzhong
The pre-Bötzinger complex of the mammalian brain stem plays a crucial role in the respiratory rhythms generation. Neurons within the pre-Bötzinger complex have been found experimentally to yield different firing activities. In this paper, we study the spiking and bursting activities related to the respiratory rhythms in the pre-Bötzinger complex based on a mathematical model proposed by Butera. Using the one-dimensional first recurrence map induced by dynamics, we investigate the different bursting patterns and their transition of the pre-Bötzinger complex neurons based on the Butera model, after we derived a one-dimensional map from the dynamical characters of the differential equations, and we obtained conditions for the transition of different bursting patterns. These analytical results were verified through numerical simulations. We conclude that the one-dimensional map contains similar rhythmic patterns as the Butera model and can be used as a simpler modeling tool to study fast-slow models like pre-Bötzinger complex neural circuit.
Transient aging in fractional Brownian and Langevin-equation motion
NASA Astrophysics Data System (ADS)
Kursawe, Jochen; Schulz, Johannes; Metzler, Ralf
2013-12-01
Stochastic processes driven by stationary fractional Gaussian noise, that is, fractional Brownian motion and fractional Langevin-equation motion, are usually considered to be ergodic in the sense that, after an algebraic relaxation, time and ensemble averages of physical observables coincide. Recently it was demonstrated that fractional Brownian motion and fractional Langevin-equation motion under external confinement are transiently nonergodic—time and ensemble averages behave differently—from the moment when the particle starts to sense the confinement. Here we show that these processes also exhibit transient aging, that is, physical observables such as the time-averaged mean-squared displacement depend on the time lag between the initiation of the system at time t=0 and the start of the measurement at the aging time ta. In particular, it turns out that for fractional Langevin-equation motion the aging dependence on ta is different between the cases of free and confined motion. We obtain explicit analytical expressions for the aged moments of the particle position as well as the time-averaged mean-squared displacement and present a numerical analysis of this transient aging phenomenon.
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.
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
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.
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.
Modeling Dynamic Perceptual Attention in Complex Virtual Environments
2005-01-01
Modeling Dynamic Perceptual Attention in Complex Virtual Environments Youngjun Kim, Martin van Velsen and Randall W. Hill, Jr. Institute for...Youngjun Kim, Martin van Velsen and Randall W. Hill, Jr. the human realm. Spatial cognition and especially spatial attention has allowed humans to make...At any point in time, the virtual human must recognize which object is the most salient among those 4 Youngjun Kim, Martin van Velsen and
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
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.
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.
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.
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
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.
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.
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
γ-Tubulin ring complexes regulate microtubule plus end dynamics
Bouissou, Anaïs; Vérollet, Christel; Sousa, Aureliana; Sampaio, Paula; Wright, Michel; Sunkel, Claudio E.; Merdes, Andreas
2009-01-01
γ-Tubulin is critical for the initiation and regulation of microtubule (MT) assembly. In Drosophila melanogaster, it acts within two main complexes: the γ-tubulin small complex (γ-TuSC) and the γ-tubulin ring complex (γ-TuRC). Proteins specific of the γ-TuRC, although nonessential for viability, are required for efficient mitotic progression. Until now, their role during interphase remained poorly understood. Using RNA interference in Drosophila S2 cells, we show that the γ-TuRC is not critical for overall MT organization. However, depletion of any component of this complex results in an increase of MT dynamics. Combined immunofluorescence and live imaging analysis allows us to reveal that the γ-TuRC localizes along interphase MTs and that distal γ-tubulin spots match with sites of pause or rescue events. We propose that, in addition to its role in nucleation, the γ-TuRC associated to MTs may regulate their dynamics by limiting catastrophes. PMID:19948476
Complex elaboration: making sense of meiotic cohesin dynamics
Rankin, Susannah
2015-01-01
In mitotically dividing cells, the cohesin complex tethers sister chromatids, the products of DNA replication, together from the time they are generated during S phase until anaphase. Cohesion between sister chromatids ensures accurate chromosome segregation, and promotes normal gene regulation and certain kinds of DNA repair. In somatic cells, the core cohesin complex is composed of four subunits: Smc1, Smc3, Rad21 and an SA subunit. During meiotic cell divisions meiosis-specific isoforms of several of the cohesin subunits are also expressed and incorporated into distinct meiotic cohesin complexes. The relative contributions of these meiosis-specific forms of cohesin to chromosome dynamics during meiotic progression have not been fully worked out. However, the localization of these proteins during chromosome pairing and synapsis, and their unique loss-of-function phenotypes, suggest non-overlapping roles in controlling meiotic chromosome behavior. Many of the proteins that regulate cohesin function during mitosis also appear to regulate cohesin during meiosis. Here we review how cohesin contributes to meiotic chromosome dynamics, and explore similarities and differences between cohesin regulation during the mitotic cell cycle and meiotic progression. A deeper understanding of the regulation and function of cohesin in meiosis will provide important new insights into how the cohesin complex is able to promote distinct kinds of chromosome interactions under diverse conditions. PMID:25895170
Is the Langevin phase equation an efficient model for oscillating neurons?
NASA Astrophysics Data System (ADS)
Ota, Keisuke; Tsunoda, Takamasa; Omori, Toshiaki; Watanabe, Shigeo; Miyakawa, Hiroyoshi; Okada, Masato; Aonishi, Toru
2009-12-01
The Langevin phase model is an important canonical model for capturing coherent oscillations of neural populations. However, little attention has been given to verifying its applicability. In this paper, we demonstrate that the Langevin phase equation is an efficient model for neural oscillators by using the machine learning method in two steps: (a) Learning of the Langevin phase model. We estimated the parameters of the Langevin phase equation, i.e., a phase response curve and the intensity of white noise from physiological data measured in the hippocampal CA1 pyramidal neurons. (b) Test of the estimated model. We verified whether a Fokker-Planck equation derived from the Langevin phase equation with the estimated parameters could capture the stochastic oscillatory behavior of the same neurons disturbed by periodic perturbations. The estimated model could predict the neural behavior, so we can say that the Langevin phase equation is an efficient model for oscillating neurons.
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.
Dynamically reconfigurable complex emulsions via tunable interfacial tensions
NASA Astrophysics Data System (ADS)
Zarzar, Lauren D.; Sresht, Vishnu; Sletten, Ellen M.; Kalow, Julia A.; Blankschtein, Daniel; Swager, Timothy M.
2015-02-01
Emulsification is a powerful, well-known technique for mixing and dispersing immiscible components within a continuous liquid phase. Consequently, emulsions are central components of medicine, food and performance materials. Complex emulsions, including Janus droplets (that is, droplets with faces of differing chemistries) and multiple emulsions, are of increasing importance in pharmaceuticals and medical diagnostics, in the fabrication of microparticles and capsules for food, in chemical separations, in cosmetics, and in dynamic optics. Because complex emulsion properties and functions are related to the droplet geometry and composition, the development of rapid, simple fabrication approaches allowing precise control over the droplets' physical and chemical characteristics is critical. Significant advances in the fabrication of complex emulsions have been made using a number of procedures, ranging from large-scale, less precise techniques that give compositional heterogeneity using high-shear mixers and membranes, to small-volume but more precise microfluidic methods. However, such approaches have yet to create droplet morphologies that can be controllably altered after emulsification. Reconfigurable complex liquids potentially have great utility as dynamically tunable materials. Here we describe an approach to the one-step fabrication of three- and four-phase complex emulsions with highly controllable and reconfigurable morphologies. The fabrication makes use of the temperature-sensitive miscibility of hydrocarbon, silicone and fluorocarbon liquids, and is applied to both the microfluidic and the scalable batch production of complex droplets. We demonstrate that droplet geometries can be alternated between encapsulated and Janus configurations by varying the interfacial tensions using hydrocarbon and fluorinated surfactants including stimuli-responsive and cleavable surfactants. This yields a generalizable strategy for the fabrication of multiphase emulsions with
Dynamically reconfigurable complex emulsions via tunable interfacial tensions
Zarzar, Lauren D.; Sresht, Vishnu; Sletten, Ellen M.; Kalow, Julia A.; Blankschtein, Daniel; Swager, Timothy M.
2015-01-01
Emulsification is a powerful, well-known technique for mixing and dispersing immiscible components within a continuous liquid phase. Consequently, emulsions are central components of medicine, food and performance materials. Complex emulsions, including multiple emulsions and Janus droplets which contain hemispheres of differing material, are of increasing importance1 in pharmaceuticals and medical diagnostics2, in the fabrication of microparticles and capsules3–5 for food6, in chemical separations7, in cosmetics8, and in dynamic optics9. Because complex emulsion properties and functions are related to the droplet geometry and composition, the development of rapid, simple fabrication approaches allowing precise control over the droplets’ physical and chemical characteristics is critical. Significant advances in the fabrication of complex emulsions have been made using a number of procedures, ranging from large-scale, less precise techniques that give compositional heterogeneity using high-shear mixers and membranes10, to small-volume but more precise microfluidic methods11,12. However, such approaches have yet to create droplet morphologies that can be controllably altered after emulsification. Reconfigurable complex liquids potentially have greatly increased utility as dynamically tunable materials. Here we describe an approach to the one-step fabrication of three- and four-phase complex emulsions with highly controllable and reconfigurable morphologies. The fabrication makes use of the temperature-sensitive miscibility of hydrocarbon, silicone and fluorocarbon liquids, and is applied to both the microfluidic and the scalable batch production of complex droplets. We demonstrate that droplet geometries can be alternated between encapsulated and Janus configurations by varying the interfacial tensions using hydrocarbon and fluorinated surfactants including stimuli-responsive and cleavable surfactants. This yields a generalizable strategy for the fabrication of
The Complexity of Dynamics in Small Neural Circuits.
Fasoli, Diego; Cattani, Anna; Panzeri, Stefano
2016-08-01
Mean-field approximations are a powerful tool for studying large neural networks. However, they do not describe well the behavior of networks composed of a small number of neurons. In this case, major differences between the mean-field approximation and the real behavior of the network can arise. Yet, many interesting problems in neuroscience involve the study of mesoscopic networks composed of a few tens of neurons. Nonetheless, mathematical methods that correctly describe networks of small size are still rare, and this prevents us to make progress in understanding neural dynamics at these intermediate scales. Here we develop a novel systematic analysis of the dynamics of arbitrarily small networks composed of homogeneous populations of excitatory and inhibitory firing-rate neurons. We study the local bifurcations of their neural activity with an approach that is largely analytically tractable, and we numerically determine the global bifurcations. We find that for strong inhibition these networks give rise to very complex dynamics, caused by the formation of multiple branching solutions of the neural dynamics equations that emerge through spontaneous symmetry-breaking. This qualitative change of the neural dynamics is a finite-size effect of the network, that reveals qualitative and previously unexplored differences between mesoscopic cortical circuits and their mean-field approximation. The most important consequence of spontaneous symmetry-breaking is the ability of mesoscopic networks to regulate their degree of functional heterogeneity, which is thought to help reducing the detrimental effect of noise correlations on cortical information processing.
Modeling the Complex Dynamics and Changing Correlations of Epileptic Events
Wulsin, Drausin F.; Fox, Emily B.; Litt, Brian
2014-01-01
Patients with epilepsy can manifest short, sub-clinical epileptic “bursts” in addition to full-blown clinical seizures. We believe the relationship between these two classes of events—something not previously studied quantitatively—could yield important insights into the nature and intrinsic dynamics of seizures. A goal of our work is to parse these complex epileptic events into distinct dynamic regimes. A challenge posed by the intracranial EEG (iEEG) data we study is the fact that the number and placement of electrodes can vary between patients. We develop a Bayesian nonparametric Markov switching process that allows for (i) shared dynamic regimes between a variable number of channels, (ii) asynchronous regime-switching, and (iii) an unknown dictionary of dynamic regimes. We encode a sparse and changing set of dependencies between the channels using a Markov-switching Gaussian graphical model for the innovations process driving the channel dynamics and demonstrate the importance of this model in parsing and out-of-sample predictions of iEEG data. We show that our model produces intuitive state assignments that can help automate clinical analysis of seizures and enable the comparison of sub-clinical bursts and full clinical seizures. PMID:25284825
Nonequilibrium dynamics of language games on complex networks
NASA Astrophysics Data System (ADS)
Dall'Asta, Luca; Baronchelli, Andrea; Barrat, Alain; Loreto, Vittorio
2006-09-01
The naming game is a model of nonequilibrium dynamics for the self-organized emergence of a linguistic convention or a communication system in a population of agents with pairwise local interactions. We present an extensive study of its dynamics on complex networks, that can be considered as the most natural topological embedding for agents involved in language games and opinion dynamics. Except for some community structured networks on which metastable phases can be observed, agents playing the naming game always manage to reach a global consensus. This convergence is obtained after a time generically scaling with the population’s size N as tconv˜N1.4±0.1 , i.e., much faster than for agents embedded on regular lattices. Moreover, the memory capacity required by the system scales only linearly with its size. Particular attention is given to heterogenous networks, in which the dynamical activity pattern of a node depends on its degree. High-degree nodes have a fundamental role, but require larger memory capacity. They govern the dynamics acting as spreaders of (linguistic) conventions. The effects of other properties, such as the average degree and the clustering, are also discussed.
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.
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
Reconstruction of the modified discrete Langevin equation from persistent time series
Czechowski, Zbigniew
2016-05-15
The discrete Langevin-type equation, which can describe persistent processes, was introduced. The procedure of reconstruction of the equation from time series was proposed and tested on synthetic data, with short and long-tail distributions, generated by different Langevin equations. Corrections due to the finite sampling rates were derived. For an exemplary meteorological time series, an appropriate Langevin equation, which constitutes a stochastic macroscopic model of the phenomenon, was reconstructed.
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.
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
Boltzmann-Langevin approach to pre-equilibrium correlations in nuclear collisions
NASA Astrophysics Data System (ADS)
Gavin, Sean; Moschelli, George; Zin, Christopher
2017-06-01
Correlations born before the onset of hydrodynamic flow can leave observable traces on the final-state particles. Measurement of these correlations yield important information on the isotropization and thermalization processes. Starting from a Boltzmann-like kinetic theory in the presence of dynamic Langevin noise, we derive a new partial differential equation for the two-particle correlation function that respects the microscopic conservation laws. To illustrate how these equations can be used, we study the effect of thermalization on long-range correlations. We show quite generally that two-particle correlations at early times depend on S , the average probability that a parton suffers no interactions. We extract S from transverse momentum fluctuations measured in nucleus-nucleus collisions and predict the degree of partial thermalization in proton-nucleus experiments.
NASA Astrophysics Data System (ADS)
Grebenkov, Denis S.; Vahabi, Mahsa
2014-01-01
We consider a generalized Langevin equation that can be used to describe thermal motion of a tracer in a viscoelastic medium by accounting for inertial and hydrodynamic effects at short times, subdiffusive scaling at intermediate times, and eventual optical trapping at long times. We derive a Laplace-type integral representation for the linear response function that governs the diffusive dynamics. This representation is particularly well suited for rapid numerical computation and theoretical analysis. In particular, we deduce explicit formulas for the mean and variance of the time averaged (TA) mean square displacement (MSD) and velocity autocorrelation function (VACF). The asymptotic behavior of the TA MSD and TA VACF is investigated at different time scales. Some biophysical and microrheological applications are discussed, with an emphasis on the statistical analysis of optical tweezers' single-particle tracking experiments in polymer networks and living cells.
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.
Inelastic X-ray scattering on liquid benzene analyzed using a generalized Langevin equation
NASA Astrophysics Data System (ADS)
Yoshida, Koji; Fukuyama, Nami; Yamaguchi, Toshio; Hosokawa, Shinya; Uchiyama, Hiroshi; Tsutsui, Satoshi; Baron, Alfred Q. R.
2017-07-01
The dynamic structure factor, S(Q,ω), of liquid benzene was measured by meV-resolved inelastic X-ray scattering (IXS) and analyzed using a generalized Langevin model with a memory function including fast, μ-relaxation and slow, structural, α-relaxation. The model well reproduced the experimental S(Q,ω) of liquid benzene. The dispersion relation of the collective excitation energy yields the high-frequency sound velocity for liquid benzene as related to the α-relaxation. The ratio of the high-frequency to the adiabatic sound velocity is approximately 1.5, larger to that of carbon tetrachloride and smaller than those of methanol and water, reflecting the nature of intermolecular interactions.
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.
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.
Precise Regulation of Gene Expression Dynamics Favors Complex Promoter Architectures
Müller, Dirk; Stelling, Jörg
2009-01-01
Promoters process signals through recruitment of transcription factors and RNA polymerase, and dynamic changes in promoter activity constitute a major noise source in gene expression. However, it is barely understood how complex promoter architectures determine key features of promoter dynamics. Here, we employ prototypical promoters of yeast ribosomal protein genes as well as simplified versions thereof to analyze the relations among promoter design, complexity, and function. These promoters combine the action of a general regulatory factor with that of specific transcription factors, a common motif of many eukaryotic promoters. By comprehensively analyzing stationary and dynamic promoter properties, this model-based approach enables us to pinpoint the structural characteristics underlying the observed behavior. Functional tradeoffs impose constraints on the promoter architecture of ribosomal protein genes. We find that a stable scaffold in the natural design results in low transcriptional noise and strong co-regulation of target genes in the presence of gene silencing. This configuration also exhibits superior shut-off properties, and it can serve as a tunable switch in living cells. Model validation with independent experimental data suggests that the models are sufficiently realistic. When combined, our results offer a mechanistic explanation for why specific factors are associated with low protein noise in vivo. Many of these findings hold for a broad range of model parameters and likely apply to other eukaryotic promoters of similar structure. PMID:19180182
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.
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.
Large scale molecular dynamics study of polymer-surfactant complex
NASA Astrophysics Data System (ADS)
Goswami, Monojoy; Sumpter, Bobby
2012-02-01
In this work, we study the self-assembly of cationic polyelectrolytes mediated by anionic surfactants in dilute or semi-dilute and gel states. The understanding of the dilute system is a requirement for the understanding of gel states. The importance of polyelectrolyte with oppositely charged colloidal particles can be found in biological systems, such as immobilization of enzymes in polyelectrolyte complexes or nonspecific association of DNA with protein. With the same understanding, interaction of surfactants with polyelectrolytes shows intriguing phenomena that are important for both in academic research as well as industrial applications. Many useful properties of PE surfactant complexes come from the highly ordered structures of surfactant self-assembly inside the PE aggregate. We do large scale molecular dynamics simulation using LAMMPS to understand the structure and dynamics of PE-surfactant systems. Our investigation shows highly ordered ring-string structures that have been observed experimentally in biological systems. We will investigate many different properties of PE-surfactant complexation which will be helpful for pharmaceutical, engineering and biological applications.
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.
The Dynamics of Coalition Formation on Complex Networks
Auer, S.; Heitzig, J.; Kornek, U.; Schöll, E.; Kurths, J.
2015-01-01
Complex networks describe the structure of many socio-economic systems. However, in studies of decision-making processes the evolution of the underlying social relations are disregarded. In this report, we aim to understand the formation of self-organizing domains of cooperation (“coalitions”) on an acquaintance network. We include both the network’s influence on the formation of coalitions and vice versa how the network adapts to the current coalition structure, thus forming a social feedback loop. We increase complexity from simple opinion adaptation processes studied in earlier research to more complex decision-making determined by costs and benefits, and from bilateral to multilateral cooperation. We show how phase transitions emerge from such coevolutionary dynamics, which can be interpreted as processes of great transformations. If the network adaptation rate is high, the social dynamics prevent the formation of a grand coalition and therefore full cooperation. We find some empirical support for our main results: Our model develops a bimodal coalition size distribution over time similar to those found in social structures. Our detection and distinguishing of phase transitions may be exemplary for other models of socio-economic systems with low agent numbers and therefore strong finite-size effects. PMID:26303622
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.
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
2007-06-30
equivalently , the 3nite-state machine Fig. 2 can be started from any arbitrary state corresponding to no speci3c initial condition.) While the time...University Research Initiative (MURI) Project Characterization and Mitigation of Failures in Complex Dynamical Systems Principal Investigator: Professor...Failure (CSF) Multidisciplinary University Research Initiative (MURI) project has been to formulate and disseminate a knowledge base of science and
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.
Structure and dynamics of solvent shells around photoexcited metal complexes.
Szymczak, Jaroslaw J; Hofmann, Franziska D; Meuwly, Markus
2013-05-07
Understanding the geometry, energetics and dynamics of solvated transition metal (TM) compounds is decisive in characterizing and optimizing their function. Here, we demonstrate that it is possible to quantify the structural dynamics of solvated [Ru(II)(bpy)3], an important TM-complex for solar-energy harvesting research, by using state-of-the art force fields together with molecular simulations. Electronic excitation to [Ru(III)(bpy)3] leads to a nonequilibrium system in which excess energy is redistributed to the surrounding solvent following a cascade of dynamical effects that can be characterized by the simulations. The study reveals that the structure of the surrounding solvent relaxes towards the equilibrium on a sub-picosecond to a few-picosecond time scale. Analysis of solvent residence and rotational reorientation times during relaxation demonstrates increased dynamics in the inner solvation sphere on the picosecond time scale. Energy transfer to the solvent occurs on different time scales for the different degrees of freedom which range from a few hundred fs to several picoseconds.
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.
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
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.
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.
Dynamics of self-organization in complex adaptive networks
NASA Astrophysics Data System (ADS)
D'Humières, D.; Huberman, B. A.
1984-02-01
We study the dynamical behavior of complex adaptive automata during unsupervised learning of periodic training sets. A new technique for their analysis is presented and applied to an adaptive network with distributed memory. We show that with general imput pattern sequences, the system can display behavior that ranges from convergence into simple fixed points and oscillations to chaotic wanderings. We also test the ability of the self-organized automaton to recognize spatial patterns, discriminate between them, and to elicit meaningful information out of noisy inputs. In this configuration we determine that the higher the ratio of excitation to inhibition, the broader the equivalence class into which patterns are put together.
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.
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.
Causal influence in linear Langevin networks without feedback
NASA Astrophysics Data System (ADS)
Auconi, Andrea; Giansanti, Andrea; Klipp, Edda
2017-04-01
The intuition of causation is so fundamental that almost every research study in life sciences refers to this concept. However, a widely accepted formal definition of causal influence between observables is still missing. In the framework of linear Langevin networks without feedback (linear response models) we propose a measure of causal influence based on a new decomposition of information flows over time. We discuss its main properties and we compare it with other information measures like the transfer entropy. We are currently unable to extend the definition of causal influence to systems with a general feedback structure and nonlinearities.
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.
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.
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.
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.
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).
Computational complexity of ecological and evolutionary spatial dynamics
Ibsen-Jensen, Rasmus; Chatterjee, Krishnendu; Nowak, Martin A.
2015-01-01
There are deep, yet largely unexplored, connections between computer science and biology. Both disciplines examine how information proliferates in time and space. Central results in computer science describe the complexity of algorithms that solve certain classes of problems. An algorithm is deemed efficient if it can solve a problem in polynomial time, which means the running time of the algorithm is a polynomial function of the length of the input. There are classes of harder problems for which the fastest possible algorithm requires exponential time. Another criterion is the space requirement of the algorithm. There is a crucial distinction between algorithms that can find a solution, verify a solution, or list several distinct solutions in given time and space. The complexity hierarchy that is generated in this way is the foundation of theoretical computer science. Precise complexity results can be notoriously difficult. The famous question whether polynomial time equals nondeterministic polynomial time (i.e., P = NP) is one of the hardest open problems in computer science and all of mathematics. Here, we consider simple processes of ecological and evolutionary spatial dynamics. The basic question is: What is the probability that a new invader (or a new mutant) will take over a resident population? We derive precise complexity results for a variety of scenarios. We therefore show that some fundamental questions in this area cannot be answered by simple equations (assuming that P is not equal to NP). PMID:26644569
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.
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
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 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 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..
Dynamic of astrophysical jets in the complex octonion space
NASA Astrophysics Data System (ADS)
Weng, Zi-Hua
2015-06-01
The paper aims to consider the strength gradient force as the dynamic of astrophysical jets, explaining the movement phenomena of astrophysical jets. J. C. Maxwell applied the quaternion analysis to describe the electromagnetic theory. This encourages others to adopt the complex quaternion and octonion to depict the electromagnetic and gravitational theories. In the complex octonion space, it is capable of deducing the field potential, field strength, field source, angular momentum, torque, force and so forth. As one component of the force, the strength gradient force relates to the gradient of the norm of field strength only, and is independent of not only the direction of field strength but also the mass and electric charge for the test particle. When the strength gradient force is considered as the thrust of the astrophysical jets, one can deduce some movement features of astrophysical jets, including the bipolarity, matter ingredient, precession, symmetric distribution, emitting, collimation, stability, continuing acceleration and so forth. The above results reveal that the strength gradient force is able to be applied to explain the main mechanical features of astrophysical jets, and is the competitive candidate of the dynamic of astrophysical jets.
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.
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
Identifying Changes of Complex Flood Dynamics with Recurrence Analysis
NASA Astrophysics Data System (ADS)
Wendi, D.; Merz, B.; Marwan, N.
2016-12-01
Temporal changes in flood hazard system are known to be difficult to detect and attribute due to multiple drivers that include complex processes that are non-stationary and highly variable. These drivers, such as human-induced climate change, natural climate variability, implementation of flood defense, river training, or land use change, could impact variably on space-time scales and influence or mask each other. Flood time series may show complex behavior that vary at a range of time scales and may cluster in time. Moreover hydrological time series (i.e. discharge) are often subject to measurement errors, such as rating curve error especially in the case of extremes where observation are actually derived through extrapolation. This study focuses on the application of recurrence based data analysis techniques (recurrence plot) for understanding and quantifying spatio-temporal changes in flood hazard in Germany. The recurrence plot is known as an effective tool to visualize the dynamics of phase space trajectories i.e. constructed from a time series by using an embedding dimension and a time delay, and it is known to be effective in analyzing non-stationary and non-linear time series. Sensitivity of the common measurement errors and noise on recurrence analysis will also be analyzed and evaluated against conventional methods. The emphasis will be on the identification of characteristic recurrence properties that could associate typical dynamic to certain flood events.
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.
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.
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.
Dynamical complexity of the Brans-Dicke cosmology
Hrycyna, Orest; Szydłowski, Marek E-mail: marek.szydlowski@uj.edu.pl
2013-12-01
The dynamics of the Brans-Dicke theory with a quadratic scalar field potential function and barotropic matter is investigated. The dynamical system methods are used to reveal complexity of dynamical evolution in homogeneous and isotropic cosmological models. The structure of phase space crucially depends on the parameter of the theory ω{sub BD} as well as barotropic matter index w{sub m}. In our analysis these parameters are treated as bifurcation parameters. We found sets of values of these parameters which lead to generic evolutional scenarios. We show that in isotropic and homogeneous models in the Brans-Dicke theory with a quadratic potential function the de Sitter state appears naturally. Stability conditions of this state are fully investigated. It is shown that these models can explain accelerated expansion of the Universe without the assumption of the substantial form of dark matter and dark energy. The Poincare construction of compactified phase space with a circle at infinity is used to show that phase space trajectories in a physical region can be equipped with a structure of a vector field on nontrivial topological closed space. For ω{sub BD} < −3/2 we show new types of early and late time evolution leading from the anti-de Sitter to the de Sitter state through an asymmetric bounce. In the theory without a ghost we find bouncing solutions and the coexistence of the bounces and the singularity. Following the Peixoto theorem some conclusions about structural stability are drawn.
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.
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
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.
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.
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.
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.
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
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.
Uneyama, Takashi; Miyaguchi, Tomoshige; Akimoto, Takuma
2015-09-01
The mean-square displacement (MSD) is widely utilized to study the dynamical properties of stochastic processes. The time-averaged MSD (TAMSD) provides some information on the dynamics which cannot be extracted from the ensemble-averaged MSD. In particular, the relative standard deviation (RSD) of the TAMSD can be utilized to study the long-time relaxation behavior. In this work, we consider a class of Langevin equations which are multiplicatively coupled to time-dependent and fluctuating diffusivities. Various interesting dynamics models such as entangled polymers and supercooled liquids can be interpreted as the Langevin equations with time-dependent and fluctuating diffusivities. We derive a general formula for the RSD of the TAMSD for the Langevin equation with the time-dependent and fluctuating diffusivity. We show that the RSD can be expressed in terms of the correlation function of the diffusivity. The RSD exhibits the crossover at the long time region. The crossover time is related to a weighted average relaxation time for the diffusivity. Thus the crossover time gives some information on the relaxation time of fluctuating diffusivity which cannot be extracted from the ensemble-averaged MSD. We discuss the universality and possible applications of the formula via some simple examples.
NASA Astrophysics Data System (ADS)
Uneyama, Takashi; Miyaguchi, Tomoshige; Akimoto, Takuma
2015-09-01
The mean-square displacement (MSD) is widely utilized to study the dynamical properties of stochastic processes. The time-averaged MSD (TAMSD) provides some information on the dynamics which cannot be extracted from the ensemble-averaged MSD. In particular, the relative standard deviation (RSD) of the TAMSD can be utilized to study the long-time relaxation behavior. In this work, we consider a class of Langevin equations which are multiplicatively coupled to time-dependent and fluctuating diffusivities. Various interesting dynamics models such as entangled polymers and supercooled liquids can be interpreted as the Langevin equations with time-dependent and fluctuating diffusivities. We derive a general formula for the RSD of the TAMSD for the Langevin equation with the time-dependent and fluctuating diffusivity. We show that the RSD can be expressed in terms of the correlation function of the diffusivity. The RSD exhibits the crossover at the long time region. The crossover time is related to a weighted average relaxation time for the diffusivity. Thus the crossover time gives some information on the relaxation time of fluctuating diffusivity which cannot be extracted from the ensemble-averaged MSD. We discuss the universality and possible applications of the formula via some simple examples.
Computational complexity of symbolic dynamics at the onset of chaos
NASA Astrophysics Data System (ADS)
Lakdawala, Porus
1996-05-01
In a variety of studies of dynamical systems, the edge of order and chaos has been singled out as a region of complexity. It was suggested by Wolfram, on the basis of qualitative behavior of cellular automata, that the computational basis for modeling this region is the universal Turing machine. In this paper, following a suggestion of Crutchfield, we try to show that the Turing machine model may often be too powerful as a computational model to describe the boundary of order and chaos. In particular we study the region of the first accumulation of period doubling in unimodal and bimodal maps of the interval, from the point of view of language theory. We show that in relation to the ``extended'' Chomsky hierarchy, the relevant computational model in the unimodal case is the nested stack automaton or the related indexed languages, while the bimodal case is modeled by the linear bounded automaton or the related context-sensitive languages.
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 Ion Dynamics in Carbonate Lithium-Ion Battery Electrolytes
Ong, Mitchell T.; Bhatia, Harsh; Gyulassy, Attila G.; ...
2017-03-06
Li-ion battery performance is strongly influenced by ionic conductivity, which depends on the mobility of the Li ions in solution, and is related to their solvation structure. In this work, we have performed first-principles molecular dynamics (FPMD) simulations of a LiPF6 salt solvated in different Li-ion battery organic electrolytes. We employ an analytical method using relative angles from successive time intervals to characterize complex ionic motion in multiple dimensions from our FPMD simulations. We find different characteristics of ionic motion on different time scales. We find that the Li ion exhibits a strong caging effect due to its strong solvationmore » structure, while the counterion, PF6– undergoes more Brownian-like motion. Lastly, our results show that ionic motion can be far from purely diffusive and provide a quantitative characterization of the microscopic motion of ions over different time scales.« less
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.
Assessment of EEG frequency dynamics using complex demodulation.
Draganova, R; Popivanov, D
1999-01-01
The complex demodulation (CD) approach was applied to human EEG recorded during a cognitive task performance, including voluntary goal-directed movements. The standard CD algorithm was extended by a simple procedure using frequency histograms and power spectra to select the characteristic frequencies of EEG segments around the task performance. In the majority of records, amplitude modulation was found, which decreased or disappeared in the period prior to and at the very beginning of the task performance. It was found that the decrease of modulation in fast beta and gamma components begins approximately one second before that of the alpha components. Frequency modulation appeared in some records at the end of the task in beta and gamma components. The results showed that a cognitive task performance is accompanied by non-linear processes in the frequency components of EEG. These dynamic changes could extend the findings of event-related desynchronization obtained by linear methods.
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.
Secure complex event processing in a heterogeneous and dynamic network
NASA Astrophysics Data System (ADS)
Buddhika, Thilina; Ray, Indrakshi; Linderman, Mark; Jayasumana, Anura
2014-06-01
Battlefield monitoring involves collecting streaming data from different sources, transmitting the data over a heterogeneous network, and processing queries in real-time in order to respond to events in a timely manner. Nodes in these networks differ with respect to their trustworthiness, processing, storage, and communication capabilities. Links in the network differ with respect to their communication bandwidth. The topology of the network itself is subject to change, as the nodes and links may become unavailable. Continuous queries executed in such environments must also meet some quality of service (QoS) requirements, such as, response time and throughput. Data streams generated from the various nodes in the network belong to different security levels; consequently, these must be processed in a secure manner without causing unauthorized leakage or modification. Towards this end, we demonstrate how an existing complex event processing system can be extended to execute queries and events in a secure manner in such a dynamic and heterogeneous environment.
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.
Photobleaching Methods to Study Golgi Complex Dynamics in Living Cells
Snapp, Erik Lee
2014-01-01
The Golgi complex (GC) is a highly dynamic organelle that constantly receives and exports proteins and lipids from both the endoplasmic reticulum and the plasma membrane. While protein trafficking can be monitored with traditional biochemical methods, these approaches average the behaviors of millions of cells, provide modest temporal information and no spatial information. Photobleaching methods enable investigators to monitor protein trafficking in single cells or even single GC stacks with subsecond precision. Furthermore, photobleaching can be exploited to monitor the behaviors of resident GC proteins to provide insight into mechanisms of retention and trafficking. In this chapter, general photobleaching approaches with laser scanning confocal microscopes are described. Importantly, the problems associated with many fluorescent proteins (FPs) and their uses in the secretory pathway are discussed and appropriate choices are suggested. For example, Enhanced Green Fluorescent Protein (EGFP) and most red FPs are extremely problematic. Finally, options for data analyses are described. PMID:24295308
Complex dynamical behaviors of daily data series in stock exchange
NASA Astrophysics Data System (ADS)
Wang, Hongchun; Chen, Guanrong; Lü, Jinhu
2004-12-01
It is well known that many economic data series show chaotic behaviors. In this Letter, we further investigate the complex dynamical behaviors of the daily data series, including opening quotation, closing quotation, maximum price, minimum price, and total exchange quantum, in Shenzhen stock exchange and Shanghai stock exchange, which are two representative stock exchanges in mainland China. The maximum Lyapunov exponents, correlation dimensions, and frequency spectra are calculated for these time series. Our results indicate that some daily data series of stock exchanges display low-dimensional chaotic behaviors, and some other daily data series do not show any chaotic behavior. Moreover, we introduce a weighted one-rank local-region approach for predicting short-term daily data series of stock exchange.
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.
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
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.
A Qualitative Model of Human Interaction with Complex Dynamic Systems
NASA Technical Reports Server (NTRS)
Hess, Ronald A.
1987-01-01
A qualitative model describing human interaction with complex dynamic systems is developed. The model is hierarchical in nature and consists of three parts: a behavior generator, an internal model, and a sensory information processor. The behavior generator is responsible for action decomposition, turning higher level goals or missions into physical action at the human-machine interface. The internal model is an internal representation of the environment which the human is assumed to possess and is divided into four submodel categories. The sensory information processor is responsible for sensory composition. All three parts of the model act in consort to allow anticipatory behavior on the part of the human in goal-directed interaction with dynamic systems. Human workload and error are interpreted in this framework, and the familiar example of an automobile commute is used to illustrate the nature of the activity in the three model elements. Finally, with the qualitative model as a guide, verbal protocols from a manned simulation study of a helicopter instrument landing task are analyzed with particular emphasis on the effect of automation on human-machine performance.
A qualitative model of human interaction with complex dynamic systems
NASA Technical Reports Server (NTRS)
Hess, Ronald A.
1987-01-01
A qualitative model describing human interaction with complex dynamic systems is developed. The model is hierarchical in nature and consists of three parts: a behavior generator, an internal model, and a sensory information processor. The behavior generator is responsible for action decomposition, turning higher level goals or missions into physical action at the human-machine interface. The internal model is an internal representation of the environment which the human is assumed to possess and is divided into four submodel categories. The sensory information processor is responsible for sensory composition. All three parts of the model act in consort to allow anticipatory behavior on the part of the human in goal-directed interaction with dynamic systems. Human workload and error are interpreted in this framework, and the familiar example of an automobile commute is used to illustrate the nature of the activity in the three model elements. Finally, with the qualitative model as a guide, verbal protocols from a manned simulation study of a helicopter instrument landing task are analyzed with particular emphasis on the effect of automation on human-machine performance.
The geometry of chaotic dynamics — a complex network perspective
NASA Astrophysics Data System (ADS)
Donner, R. V.; Heitzig, J.; Donges, J. F.; Zou, Y.; Marwan, N.; Kurths, J.
2011-12-01
Recently, several complex network approaches to time series analysis have been developed and applied to study a wide range of model systems as well as real-world data, e.g., geophysical or financial time series. Among these techniques, recurrence-based concepts and prominently ɛ-recurrence networks, most faithfully represent the geometrical fine structure of the attractors underlying chaotic (and less interestingly non-chaotic) time series. In this paper we demonstrate that the well known graph theoretical properties local clustering coefficient and global (network) transitivity can meaningfully be exploited to define two new local and two new global measures of dimension in phase space: local upper and lower clustering dimension as well as global upper and lower transitivity dimension. Rigorous analytical as well as numerical results for self-similar sets and simple chaotic model systems suggest that these measures are well-behaved in most non-pathological situations and that they can be estimated reasonably well using ɛ-recurrence networks constructed from relatively short time series. Moreover, we study the relationship between clustering and transitivity dimensions on the one hand, and traditional measures like pointwise dimension or local Lyapunov dimension on the other hand. We also provide further evidence that the local clustering coefficients, or equivalently the local clustering dimensions, are useful for identifying unstable periodic orbits and other dynamically invariant objects from time series. Our results demonstrate that ɛ-recurrence networks exhibit an important link between dynamical systems and graph theory.
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.
Copper dynamics in doped metal-bis(histidine) complexes.
Colaneri, Michael J; Vitali, Jacqueline
2014-07-03
Electron paramagnetic resonance (EPR) temperature-dependent measurements were undertaken on three Cu(II)-doped metal-histidine complexes to assess copper site dynamic behavior. Previous single-crystal EPR analysis on two of these, zinc d,l-histidine pentahydrate (ZnDLH) and bis(l-histidinato)cadmium dihydrate (CdLH), found that doped Cu(2+) can be modeled as hopping between two neighboring conformational states, with a temperature-dependent rate becoming large enough at room temperature to produce an "averaged" spectrum. By comparing spectra from their powdered form, we show that Cu(2+) doped into a third system, Cd(2+)-d,l-histidine (CdDLH), also exhibits temperature-dependent EPR with features indicating a similar motional-averaging process. In addition, the change of g and copper hyperfine parameters from low to high temperature for CdDLH resembles that in ZnDLH, whereas the change in these parameters for CdLH is like that found in a fourth copper-doped system, zinc l-histidine dihydrate (ZnLH). Taken together, these results suggest that averaging motion between neighboring copper sites is common in metal-bis(histidine) compounds. More detailed studies on biological models are thus warranted, especially because they reveal unique relationships between structure, dynamic processes, and stability and can lead to a better understanding of the role played by site flexibility in copper proteins.
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.
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
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.
A family of optimal excitations for inducing complex dynamics in planar dynamical systems
NASA Astrophysics Data System (ADS)
Booker, S. M.
2000-01-01
A class of planar dynamical systems is considered which models a wide variety of physical problems; this class is of a form to which Melnikov's method may be applied. It is shown that a family of excitations exists which is optimal for inducing a homoclinic tangle, and hence horseshoe dynamics, in such dynamical systems (in the sense that the optimal excitations are functions of smallest Lp (0,T ) norm, 1icons/Journals/Common/le" ALT="le" ALIGN="TOP"/> picons/Journals/Common/le" ALT="le" ALIGN="TOP"/> icons/Journals/Common/infty" ALT="infty" ALIGN="TOP"/> , which will produce a simple zero in the Melnikov function). These optimal functions are particularly effective at inducing complex dynamics in the nonlinear system of interest; they are of both theoretical and practical interest. An illustration is given of this approach for two well known problems in nonlinear dynamics: the pendulum, and Duffing's equation. Numerical results are presented which confirm the accuracy and practical significance of this approach.
Híjar, Humberto
2015-02-01
We study the Brownian motion of a particle bound by a harmonic potential and immersed in a fluid with a uniform shear flow. We describe this problem first in terms of a linear Fokker-Planck equation which is solved to obtain the probability distribution function for finding the particle in a volume element of its associated phase space. We find the explicit form of this distribution in the stationary limit and use this result to show that both the equipartition law and the equation of state of the trapped particle are modified from their equilibrium form by terms increasing as the square of the imposed shear rate. Subsequently, we propose an alternative description of this problem in terms of a generalized Langevin equation that takes into account the effects of hydrodynamic correlations and sound propagation on the dynamics of the trapped particle. We show that these effects produce significant changes, manifested as long-time tails and resonant peaks, in the equilibrium and nonequilibrium correlation functions for the velocity of the Brownian particle. We implement numerical simulations based on molecular dynamics and multiparticle collision dynamics, and observe a very good quantitative agreement between the predictions of the model and the numerical results, thus suggesting that this kind of numerical simulations could be used as complement of current experimental techniques.
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
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.
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.
Dynamics of vortices in complex wakes: Modeling, analysis, and experiments
NASA Astrophysics Data System (ADS)
Basu, Saikat
The thesis develops singly-periodic mathematical models for complex laminar wakes which are formed behind vortex-shedding bluff bodies. These wake structures exhibit a variety of patterns as the bodies oscillate or are in close proximity of one another. The most well-known formation comprises two counter-rotating vortices in each shedding cycle and is popularly known as the von Karman vortex street. Of the more complex configurations, as a specific example, this thesis investigates one of the most commonly occurring wake arrangements, which consists of two pairs of vortices in each shedding period. The paired vortices are, in general, counter-rotating and belong to a more general definition of the 2P mode, which involves periodic release of four vortices into the flow. The 2P arrangement can, primarily, be sub-classed into two types: one with a symmetric orientation of the two vortex pairs about the streamwise direction in a periodic domain and the other in which the two vortex pairs per period are placed in a staggered geometry about the wake centerline. The thesis explores the governing dynamics of such wakes and characterizes the corresponding relative vortex motion. In general, for both the symmetric as well as the staggered four vortex periodic arrangements, the thesis develops two-dimensional potential flow models (consisting of an integrable Hamiltonian system of point vortices) that consider spatially periodic arrays of four vortices with their strengths being +/-Gamma1 and +/-Gamma2. Vortex formations observed in the experiments inspire the assumed spatial symmetry. The models demonstrate a number of dynamic modes that are classified using a bifurcation analysis of the phase space topology, consisting of level curves of the Hamiltonian. Despite the vortex strengths in each pair being unequal in magnitude, some initial conditions lead to relative equilibrium when the vortex configuration moves with invariant size and shape. The scaled comparisons of the
Complex systems approach to fire dynamics and climate change impacts
NASA Astrophysics Data System (ADS)
Pueyo, S.
2012-04-01
I present some recent advances in complex systems theory as a contribution to understanding fire regimes and forecasting their response to a changing climate, qualitatively and quantitatively. In many regions of the world, fire sizes have been found to follow, approximately, a power-law frequency distribution. As noted by several authors, this distribution also arises in the "forest fire" model used by physicists to study mechanisms that give rise to scale invariance (the power law is a scale-invariant distribution). However, this model does not give and does not pretend to give a realistic description of fire dynamics. For example, it gives no role to weather and climate. Pueyo (2007) developed a variant of the "forest fire" model that is also simple but attempts to be more realistic. It also results into a power law, but the parameters of this distribution change through time as a function of weather and climate. Pueyo (2007) observed similar patterns of response to weather in data from boreal forest fires, and used the fitted response functions to forecast fire size distributions in a possible climate change scenario, including the upper extreme of the distribution. For some parameter values, the model in Pueyo (2007) displays a qualitatively different behavior, consisting of simple percolation. In this case, fire is virtually absent, but megafires sweep through the ecosystem a soon as environmental forcings exceed a critical threshold. Evidence gathered by Pueyo et al. (2010) suggests that this is realistic for tropical rainforests (specifically, well-conserved upland rainforests). Some climate models suggest that major tropical rainforest regions are going to become hotter and drier if climate change goes ahead unchecked, which could cause such abrupt shifts. Not all fire regimes are well described by this model. Using data from a tropical savanna region, Pueyo et al. (2010) found that the dynamics in this area do not match its assumptions, even though fire
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.
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.
Symbolic dynamics techniques for complex systems: Application to share price dynamics
NASA Astrophysics Data System (ADS)
Xu, Dan; Beck, Christian
2017-05-01
The symbolic dynamics technique is well known for low-dimensional dynamical systems and chaotic maps, and lies at the roots of the thermodynamic formalism of dynamical systems. Here we show that this technique can also be successfully applied to time series generated by complex systems of much higher dimensionality. Our main example is the investigation of share price returns in a coarse-grained way. A nontrivial spectrum of Rényi entropies is found. We study how the spectrum depends on the time scale of returns, the sector of stocks considered, as well as the number of symbols used for the symbolic description. Overall our analysis confirms that in the symbol space transition probabilities of observed share price returns depend on the entire history of previous symbols, thus emphasizing the need for a modelling based on non-Markovian stochastic processes. Our method allows for quantitative comparisons of entirely different complex systems, for example the statistics of symbol sequences generated by share price returns using 4 symbols can be compared with that of genomic sequences.
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
Kwac, Kijeong; Lee, Chewook; Jung, Yousung; Han, Jaebeom; Kwak, Kyungwon; Zheng, Junrong; Fayer, M D; Cho, Minhaeng
2006-12-28
Molecular dynamics (MD) simulations and quantum mechanical electronic structure calculations are used to investigate the nature and dynamics of the phenol-benzene complex in the mixed solvent, benzene/CCl4. Under thermal equilibrium conditions, the complexes are continuously dissociating and forming. The MD simulations are used to calculate the experimental observables related to the phenol hydroxyl stretching mode, i.e., the two dimensional infrared vibrational echo spectrum as a function of time, which directly displays the formation and dissociation of the complex through the growth of off-diagonal peaks, and the linear absorption spectrum, which displays two hydroxyl stretch peaks, one for the complex and one for the free phenol. The results of the simulations are compared to previously reported experimental data and are found to be in quite reasonable agreement. The electronic structure calculations show that the complex is T shaped. The classical potential used for the phenol-benzene interaction in the MD simulations is in good accord with the highest level of the electronic structure calculations. A variety of other features is extracted from the simulations including the relationship between the structure and the projection of the electric field on the hydroxyl group. The fluctuating electric field is used to determine the hydroxyl stretch frequency-frequency correlation function (FFCF). The simulations are also used to examine the number distribution of benzene and CCl4 molecules in the first solvent shell around the phenol. It is found that the distribution is not that of the solvent mole fraction of benzene. There are substantial probabilities of finding a phenol in either a pure benzene environment or a pure CCl4 environment. A conjecture is made that relates the FFCF to the local number of benzene molecules in phenol's first solvent shell.
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
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.
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
Complex demodulation of cardiorespiratory dynamics preceding vasovagal syncope.
Lipsitz, L A; Hayano, J; Sakata, S; Okada, A; Morin, R J
1998-09-08
The dynamic autonomic processes leading to vasovagal syncope are poorly understood. We used complex demodulation to continuously assess changes in respiration, R-R interval, and arterial pressure (blood pressure) variability during 60 degree head-up tilt in 25 healthy subjects with tilt-induced vasovagal syncope and 25 age-matched nonsyncopal control subjects. Coherence and transfer function analyses were used to examine the relation between respiration and R-R interval variability before syncope. Baseline blood pressure, R-R, and ventilation were similar between syncope subjects and control subjects. Syncope subjects experienced an increase in tidal volume and decrease in BP beginning 3 minutes before impending syncope (systolic blood pressure <80 mm Hg) necessitated termination of tilt. Approximately 90 seconds before syncope there was a sudden prolongation of R-R interval and increase in amplitude of high and low frequency R-R interval variability, indicating an abrupt enhancement of vagal tone. The increase in respiratory amplitude between 180 and 90 seconds before syncope was not accompanied by changes in R-R interval or R-R variability, suggesting a dissociation between respiration and the respiratory sinus arrhythmia. The coherence analysis showed fewer syncope subjects with coherence between respiratory and R-R interval variabilities and lower transfer magnitudes in syncope subjects compared with control subjects. Nonsyncopal subjects had no change in respiratory, R-R interval, or blood pressure dynamics during matched time periods before the time of syncope. Vasovagal syncope is preceded by a period of hyperpnea and cardiorespiratory decoupling followed by an abrupt increase in cardiovagal tone. Respiratory pumping without inspiratory cardiac slowing may partially counteract preload reduction until sudden bradycardia precipitates syncope.
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.