To react or not to react? Intrinsic stochasticity of human control in virtual stick balancing

PubMed Central

Zgonnikov, Arkady; Lubashevsky, Ihor; Kanemoto, Shigeru; Miyazawa, Toru; Suzuki, Takashi

2014-01-01

Understanding how humans control unstable systems is central to many research problems, with applications ranging from quiet standing to aircraft landing. Increasingly, much evidence appears in favour of event-driven control hypothesis: human operators only start actively controlling the system when the discrepancy between the current and desired system states becomes large enough. The event-driven models based on the concept of threshold can explain many features of the experimentally observed dynamics. However, much still remains unclear about the dynamics of human-controlled systems, which likely indicates that humans use more intricate control mechanisms. This paper argues that control activation in humans may be not threshold-driven, but instead intrinsically stochastic, noise-driven. Specifically, we suggest that control activation stems from stochastic interplay between the operator's need to keep the controlled system near the goal state, on the one hand, and the tendency to postpone interrupting the system dynamics, on the other hand. We propose a model capturing this interplay and show that it matches the experimental data on human balancing of virtual overdamped stick. Our results illuminate that the noise-driven activation mechanism plays a crucial role at least in the considered task, and, hypothetically, in a broad range of human-controlled processes. PMID:25056217

Shock dynamics of two-lane driven lattice gases

NASA Astrophysics Data System (ADS)

Schiffmann, Christoph; Appert-Rolland, Cécile; Santen, Ludger

2010-06-01

Driven lattice gases such as those of the ASEP model are useful tools for the modelling of various stochastic transport processes carried out by self-driven particles, such as molecular motors or vehicles in road traffic. Often these processes take place in one-dimensional systems offering several tracks to the particles, and in many cases the particles are able to change track with a given rate. In this work we consider the case of strong coupling where the rate of hopping along the tracks and the exchange rates are of the same order, and show how a phenomenological approach based on a domain wall theory can be used to describe the dynamics of the system. In particular, the domain walls on the different tracks form pairs, whose dynamics dominate the behaviour of the system.

Periodic and quasiperiodic revivals in periodically driven interacting quantum systems

NASA Astrophysics Data System (ADS)

Luitz, David J.; Lazarides, Achilleas; Bar Lev, Yevgeny

2018-01-01

Recently it has been shown that interparticle interactions generically destroy dynamical localization in periodically driven systems, resulting in diffusive transport and heating. In this Rapid Communication we rigorously construct a family of interacting driven systems which are dynamically localized and effectively decoupled from the external driving potential. We show that these systems exhibit tunable periodic or quasiperiodic revivals of the many-body wave function and thus of all physical observables. By numerically examining spinless fermions on a one-dimensional lattice we show that the analytically obtained revivals of such systems remain stable for finite systems with open boundary conditions while having a finite lifetime in the presence of static spatial disorder. We find this lifetime to be inversely proportional to the disorder strength.

Dynamic Long-Term Anticipation of Chaotic States

DOE Office of Scientific and Technical Information (OSTI.GOV)

Voss, Henning U.

2001-07-02

Introducing a short time delay into the coupling of two synchronizing chaotic systems, it was shown recently that the driven system may anticipate the driving system in real time. Augmenting the phase space of the driven system, we accomplish anticipation times that are multiples of the coupling delay time and exceed characteristic time scales of the chaotic dynamics. The stability properties of the associated anticipatory synchronization manifold in certain cases turn out to be the same as for identically synchronizing oscillators.

Asynchronous Data-Driven Classification of Weapon Systems

DTIC Science & Technology

2009-10-01

Classification of Weapon SystemsF Xin Jin† Kushal Mukherjee† Shalabh Gupta† Asok Ray † Shashi Phoha† Thyagaraju Damarla‡ xuj103@psu.edu kum162@psu.edu szg107...Orlando, FL. [8] A. Ray , “Symbolic dynamic analysis of complex systems for anomaly detection,” Signal Processing, vol. 84, no. 7, pp. 1115–1130, July...2004. [9] S. Gupta and A. Ray , “Symbolic dynamic filtering for data-driven pat- tern recognition,” PATTERN RECOGNITION: Theory and Application

How Complex, Probable, and Predictable is Genetically Driven Red Queen Chaos?

PubMed

Duarte, Jorge; Rodrigues, Carla; Januário, Cristina; Martins, Nuno; Sardanyés, Josep

2015-12-01

Coevolution between two antagonistic species has been widely studied theoretically for both ecologically- and genetically-driven Red Queen dynamics. A typical outcome of these systems is an oscillatory behavior causing an endless series of one species adaptation and others counter-adaptation. More recently, a mathematical model combining a three-species food chain system with an adaptive dynamics approach revealed genetically driven chaotic Red Queen coevolution. In the present article, we analyze this mathematical model mainly focusing on the impact of species rates of evolution (mutation rates) in the dynamics. Firstly, we analytically proof the boundedness of the trajectories of the chaotic attractor. The complexity of the coupling between the dynamical variables is quantified using observability indices. By using symbolic dynamics theory, we quantify the complexity of genetically driven Red Queen chaos computing the topological entropy of existing one-dimensional iterated maps using Markov partitions. Co-dimensional two bifurcation diagrams are also built from the period ordering of the orbits of the maps. Then, we study the predictability of the Red Queen chaos, found in narrow regions of mutation rates. To extend the previous analyses, we also computed the likeliness of finding chaos in a given region of the parameter space varying other model parameters simultaneously. Such analyses allowed us to compute a mean predictability measure for the system in the explored region of the parameter space. We found that genetically driven Red Queen chaos, although being restricted to small regions of the analyzed parameter space, might be highly unpredictable.

Intermittent dynamics in complex systems driven to depletion.

PubMed

Escobar, Juan V; Pérez Castillo, Isaac

2018-03-19

When complex systems are driven to depletion by some external factor, their non-stationary dynamics can present an intermittent behaviour between relative tranquility and burst of activity whose consequences are often catastrophic. To understand and ultimately be able to predict such dynamics, we propose an underlying mechanism based on sharp thresholds of a local generalized energy density that naturally leads to negative feedback. We find a transition from a continuous regime to an intermittent one, in which avalanches can be predicted despite the stochastic nature of the process. This model may have applications in many natural and social complex systems where a rapid depletion of resources or generalized energy drives the dynamics. In particular, we show how this model accurately describes the time evolution and avalanches present in a real social system.

Event-driven management algorithm of an Engineering documents circulation system

NASA Astrophysics Data System (ADS)

Kuzenkov, V.; Zebzeev, A.; Gromakov, E.

2015-04-01

Development methodology of an engineering documents circulation system in the design company is reviewed. Discrete event-driven automatic models using description algorithms of project management is offered. Petri net use for dynamic design of projects is offered.

Multiscale System for Environmentally-Driven Infectious Disease with Threshold Control Strategy

NASA Astrophysics Data System (ADS)

Sun, Xiaodan; Xiao, Yanni

A multiscale system for environmentally-driven infectious disease is proposed, in which control measures at three different scales are implemented when the number of infected hosts exceeds a certain threshold. Our coupled model successfully describes the feedback mechanisms of between-host dynamics on within-host dynamics by employing one-scale variable guided enhancement of interventions on other scales. The modeling approach provides a novel idea of how to link the large-scale dynamics to small-scale dynamics. The dynamic behaviors of the multiscale system on two time-scales, i.e. fast system and slow system, are investigated. The slow system is further simplified to a two-dimensional Filippov system. For the Filippov system, we study the dynamics of its two subsystems (i.e. free-system and control-system), the sliding mode dynamics, the boundary equilibrium bifurcations, as well as the global behaviors. We prove that both subsystems may undergo backward bifurcations and the sliding domain exists. Meanwhile, it is possible that the pseudo-equilibrium exists and is globally stable, or the pseudo-equilibrium, the disease-free equilibrium and the real equilibrium are tri-stable, or the pseudo-equilibrium and the real equilibrium are bi-stable, or the pseudo-equilibrium and disease-free equilibrium are bi-stable, which depends on the threshold value and other parameter values. The global stability of the pseudo-equilibrium reveals that we may maintain the number of infected hosts at a previously given value. Moreover, the bi-stability and tri-stability indicate that whether the number of infected individuals tends to zero or a previously given value or other positive values depends on the parameter values and the initial states of the system. These results highlight the challenges in the control of environmentally-driven infectious disease.

Chaos and Hyperchaos in Coupled Antiphase Driven Toda Oscillators

NASA Astrophysics Data System (ADS)

Stankevich, Nataliya V.; Dvorak, Anton; Astakhov, Vladimir; Jaros, Patrycja; Kapitaniak, Marcin; Perlikowski, Przemysław; Kapitaniak, Tomasz

2018-01-01

The dynamics of two coupled antiphase driven Toda oscillators is studied. We demonstrate three different routes of transition to chaotic dynamics associated with different bifurcations of periodic and quasi-periodic regimes. As a result of these, two types of chaotic dynamics with one and two positive Lyapunov exponents are observed. We argue that the results obtained are robust as they can exist in a wide range of the system parameters.

Dynamical states, possibilities and propagation of stress signal

PubMed Central

Malik, Md. Zubbair; Ali, Shahnawaz; Singh, Soibam Shyamchand; Ishrat, Romana; Singh, R. K. Brojen

2017-01-01

The stress driven dynamics of Notch-Wnt-p53 cross-talk is subjected to a few possible dynamical states governed by simple fractal rules, and allowed to decide its own fate by choosing one of these states which are contributed from long range correlation with varied fluctuations due to active molecular interaction. The topological properties of the networks corresponding to these dynamical states have hierarchical features with assortive structure. The stress signal driven by nutlin and modulated by mediator GSK3 acts as anti-apoptotic signal in this system, whereas, the stress signal driven by Axin and modulated by GSK3 behaves as anti-apoptotic for a certain range of Axin and GSK3 interaction, and beyond which the signal acts as favor-apoptotic signal. However, this stress system prefers to stay in an active dynamical state whose counterpart complex network is closest to hierarchical topology with exhibited roles of few interacting hubs. During the propagation of stress signal, the system allows the propagator pathway to inherit all possible properties of the state to the receiver pathway/pathways with slight modifications, indicating efficient information processing and democratic sharing of responsibilities in the system via cross-talk. The increase in the number of cross-talk pathways in the system favors to establish self-organization. PMID:28106087

Dynamical states, possibilities and propagation of stress signal.

PubMed

Malik, Md Zubbair; Ali, Shahnawaz; Singh, Soibam Shyamchand; Ishrat, Romana; Singh, R K Brojen

2017-01-20

The stress driven dynamics of Notch-Wnt-p53 cross-talk is subjected to a few possible dynamical states governed by simple fractal rules, and allowed to decide its own fate by choosing one of these states which are contributed from long range correlation with varied fluctuations due to active molecular interaction. The topological properties of the networks corresponding to these dynamical states have hierarchical features with assortive structure. The stress signal driven by nutlin and modulated by mediator GSK3 acts as anti-apoptotic signal in this system, whereas, the stress signal driven by Axin and modulated by GSK3 behaves as anti-apoptotic for a certain range of Axin and GSK3 interaction, and beyond which the signal acts as favor-apoptotic signal. However, this stress system prefers to stay in an active dynamical state whose counterpart complex network is closest to hierarchical topology with exhibited roles of few interacting hubs. During the propagation of stress signal, the system allows the propagator pathway to inherit all possible properties of the state to the receiver pathway/pathways with slight modifications, indicating efficient information processing and democratic sharing of responsibilities in the system via cross-talk. The increase in the number of cross-talk pathways in the system favors to establish self-organization.

Fluctuation-driven price dynamics and investment strategies

PubMed Central

Li, Yan; Zheng, Bo; Chen, Ting-Ting; Jiang, Xiong-Fei

2017-01-01

Investigation of the driven mechanism of the price dynamics in complex financial systems is important and challenging. In this paper, we propose an investment strategy to study how dynamic fluctuations drive the price movements. The strategy is successfully applied to different stock markets in the world, and the result indicates that the driving effect of the dynamic fluctuations is rather robust. We investigate how the strategy performance is influenced by the market states and optimize the strategy performance by introducing two parameters. The strategy is also compared with several typical technical trading rules. Our findings not only provide an investment strategy which extends investors’ profits, but also offer a useful method to look into the dynamic properties of complex financial systems. PMID:29240783

Fluctuation-driven price dynamics and investment strategies.

PubMed

Li, Yan; Zheng, Bo; Chen, Ting-Ting; Jiang, Xiong-Fei

2017-01-01

Investigation of the driven mechanism of the price dynamics in complex financial systems is important and challenging. In this paper, we propose an investment strategy to study how dynamic fluctuations drive the price movements. The strategy is successfully applied to different stock markets in the world, and the result indicates that the driving effect of the dynamic fluctuations is rather robust. We investigate how the strategy performance is influenced by the market states and optimize the strategy performance by introducing two parameters. The strategy is also compared with several typical technical trading rules. Our findings not only provide an investment strategy which extends investors' profits, but also offer a useful method to look into the dynamic properties of complex financial systems.

Application of largest Lyapunov exponent analysis on the studies of dynamics under external forces

NASA Astrophysics Data System (ADS)

Odavić, Jovan; Mali, Petar; Tekić, Jasmina; Pantić, Milan; Pavkov-Hrvojević, Milica

2017-06-01

Dynamics of driven dissipative Frenkel-Kontorova model is examined by using largest Lyapunov exponent computational technique. Obtained results show that besides the usual way where behavior of the system in the presence of external forces is studied by analyzing its dynamical response function, the largest Lyapunov exponent analysis can represent a very convenient tool to examine system dynamics. In the dc driven systems, the critical depinning force for particular structure could be estimated by computing the largest Lyapunov exponent. In the dc+ac driven systems, if the substrate potential is the standard sinusoidal one, calculation of the largest Lyapunov exponent offers a more sensitive way to detect the presence of Shapiro steps. When the amplitude of the ac force is varied the behavior of the largest Lyapunov exponent in the pinned regime completely reflects the behavior of Shapiro steps and the critical depinning force, in particular, it represents the mirror image of the amplitude dependence of critical depinning force. This points out an advantage of this technique since by calculating the largest Lyapunov exponent in the pinned regime we can get an insight into the dynamics of the system when driving forces are applied. Additionally, the system is shown to be not chaotic even in the case of incommensurate structures and large amplitudes of external force, which is a consequence of overdampness of the model and the Middleton's no passing rule.

Dynamical Models for Sloshing Dynamics of Helium 2 Under Low-G Conditions

NASA Technical Reports Server (NTRS)

Hung, R. J.; Long, Y. T.

1997-01-01

Coupling of sloshing dynamics within a partially filled rotating dewar of superfluid helium 2 with spacecraft dynamics are investigated in response to the realistic environmental disturbance forces and torques acting on the spacecraft during normal operation. This study investigates: (1) the rotating bubble of superfluid helium 2 reacting to combined environmental disturbances, including gravity gradient, aerodynamic, and magnetic forces and torques; (2) characteristics of slosh reaction forces and torques coupling with spacecraft dynamics; (3) the contribution of slosh dynamics to over-all spacecraft dynamics; and (4) activating of attitude and translation control system. The numerical computation of sloshing dynamics is based on the rotational frame, while the spacecraft dynamics is associated with non-rotational frame. Results show that the contributions of spacecraft dynamics are driven by the environmental disturbances coupling with slosh dynamics. Without considering the effects of environmental disturbances-driven slosh dynamics acting on spacecraft coupling with the spacecraft dynamics may lead to the wrong results for the development of spacecraft system guidance and attitude control techniques.

Probabilistic density function method for nonlinear dynamical systems driven by colored noise.

PubMed

Barajas-Solano, David A; Tartakovsky, Alexandre M

2016-05-01

We present a probability density function (PDF) method for a system of nonlinear stochastic ordinary differential equations driven by colored noise. The method provides an integrodifferential equation for the temporal evolution of the joint PDF of the system's state, which we close by means of a modified large-eddy-diffusivity (LED) closure. In contrast to the classical LED closure, the proposed closure accounts for advective transport of the PDF in the approximate temporal deconvolution of the integrodifferential equation. In addition, we introduce the generalized local linearization approximation for deriving a computable PDF equation in the form of a second-order partial differential equation. We demonstrate that the proposed closure and localization accurately describe the dynamics of the PDF in phase space for systems driven by noise with arbitrary autocorrelation time. We apply the proposed PDF method to analyze a set of Kramers equations driven by exponentially autocorrelated Gaussian colored noise to study nonlinear oscillators and the dynamics and stability of a power grid. Numerical experiments show the PDF method is accurate when the noise autocorrelation time is either much shorter or longer than the system's relaxation time, while the accuracy decreases as the ratio of the two timescales approaches unity. Similarly, the PDF method accuracy decreases with increasing standard deviation of the noise.

Excitation Method of Linear-Motor-Type Rail Brake without Using Power Sources by Dynamic Braking with Zero Electrical Output

NASA Astrophysics Data System (ADS)

Sakamoto, Yasuaki; Kashiwagi, Takayuki; Hasegawa, Hitoshi; Sasakawa, Takashi; Fujii, Nobuo

The eddy current rail brake is a type of braking system used in railway vehicles. Because of problems such as rail heating and problems associated with ensuring that power is supplied when the feeder malfunctions, this braking system has not been used for practical applications in Japan. Therefore, we proposed the use of linear induction motor (LIM) technology in eddy current rail brake systems. The LIM rail brake driven by dynamic braking can reduce rail heating and generate the energy required for self-excitation. In this paper, we present an excitation system and control method for the LIM rail brake driven by “dynamic braking with zero electrical output”. The proposed system is based on the concept that the LIM rail brake can be energized without using excitation power sources such as a feeder circuit and that high reliability can be realized by providing an independent excitation system. We have studied this system and conducted verification tests using a prototype LIM rail brake on a roller rig. The results show that the system performance is adequate for commercializing the proposed system, in which the LIM rail brake is driven without using any excitation power source.

Floquet spin states in graphene under ac-driven spin-orbit interaction

NASA Astrophysics Data System (ADS)

López, A.; Sun, Z. Z.; Schliemann, J.

2012-05-01

We study the role of periodically driven time-dependent Rashba spin-orbit coupling (RSOC) on a monolayer graphene sample. After recasting the originally 4×4 system of dynamical equations as two time-reversal related two-level problems, the quasienergy spectrum and the related dynamics are investigated via various techniques and approximations. In the static case, the system is gapped at the Dirac point. The rotating wave approximation (RWA) applied to the driven system unphysically preserves this feature, while the Magnus-Floquet approach as well as a numerically exact evaluation of the Floquet equation show that this gap is dynamically closed. In addition, a sizable oscillating pattern of the out-of-plane spin polarization is found in the driven case for states that are completely unpolarized in the static limit. Evaluation of the autocorrelation function shows that the original uniform interference pattern corresponding to time-independent RSOC gets distorted. The resulting structure can be qualitatively explained as a consequence of the transitions induced by the ac driving among the static eigenstates, i.e., these transitions modulate the relative phases that add up to give the quantum revivals of the autocorrelation function. Contrary to the static case, in the driven scenario, quantum revivals (suppressions) are correlated to spin-up (down) phases.

Koopman operator theory: Past, present, and future

NASA Astrophysics Data System (ADS)

Brunton, Steven; Kaiser, Eurika; Kutz, Nathan

2017-11-01

Koopman operator theory has emerged as a dominant method to represent nonlinear dynamics in terms of an infinite-dimensional linear operator. The Koopman operator acts on the space of all possible measurement functions of the system state, advancing these measurements with the flow of the dynamics. A linear representation of nonlinear dynamics has tremendous potential to enable the prediction, estimation, and control of nonlinear systems with standard textbook methods developed for linear systems. Dynamic mode decomposition has become the leading data-driven method to approximate the Koopman operator, although there are still open questions and challenges around how to obtain accurate approximations for strongly nonlinear systems. This talk will provide an introductory overview of modern Koopman operator theory, reviewing the basics and describing recent theoretical and algorithmic developments. Particular emphasis will be placed on the use of data-driven Koopman theory to characterize and control high-dimensional fluid dynamic systems. This talk will also address key advances in the rapidly growing fields of machine learning and data science that are likely to drive future developments.

Emergent phases and critical behavior in a non-Markovian open quantum system

NASA Astrophysics Data System (ADS)

Cheung, H. F. H.; Patil, Y. S.; Vengalattore, M.

2018-05-01

Open quantum systems exhibit a range of novel out-of-equilibrium behavior due to the interplay between coherent quantum dynamics and dissipation. Of particular interest in these systems are driven, dissipative transitions, the emergence of dynamical phases with novel broken symmetries, and critical behavior that lies beyond the conventional paradigm of Landau-Ginzburg phenomenology. Here, we consider a parametrically driven two-mode system in the presence of non-Markovian system-reservoir interactions. We show that the non-Markovian dynamics modifies the phase diagram of this system, resulting in the emergence of a broken symmetry phase in a universality class that has no counterpart in the corresponding Markovian system. This emergent phase is accompanied by enhanced two-mode entanglement that remains robust at finite temperatures. Such reservoir-engineered dynamical phases can potentially shed light on universal aspects of dynamical phase transitions in a wide range of nonequilibrium systems, and aid in the development of techniques for the robust generation of entanglement and quantum correlations at finite temperatures with potential applications to quantum control, state preparation, and metrology.

Vlasov dynamics of periodically driven systems

NASA Astrophysics Data System (ADS)

Banerjee, Soumyadip; Shah, Kushal

2018-04-01

Analytical solutions of the Vlasov equation for periodically driven systems are of importance in several areas of plasma physics and dynamical systems and are usually approximated using ponderomotive theory. In this paper, we derive the plasma distribution function predicted by ponderomotive theory using Hamiltonian averaging theory and compare it with solutions obtained by the method of characteristics. Our results show that though ponderomotive theory is relatively much easier to use, its predictions are very restrictive and are likely to be very different from the actual distribution function of the system. We also analyse all possible initial conditions which lead to periodic solutions of the Vlasov equation for periodically driven systems and conjecture that the irreducible polynomial corresponding to the initial condition must only have squares of the spatial and momentum coordinate. The resulting distribution function for other initial conditions is aperiodic and can lead to complex relaxation processes within the plasma.

Phase Transitions and Scaling in Systems Far from Equilibrium

NASA Astrophysics Data System (ADS)

Täuber, Uwe C.

2017-03-01

Scaling ideas and renormalization group approaches proved crucial for a deep understanding and classification of critical phenomena in thermal equilibrium. Over the past decades, these powerful conceptual and mathematical tools were extended to continuous phase transitions separating distinct nonequilibrium stationary states in driven classical and quantum systems. In concordance with detailed numerical simulations and laboratory experiments, several prominent dynamical universality classes have emerged that govern large-scale, long-time scaling properties both near and far from thermal equilibrium. These pertain to genuine specific critical points as well as entire parameter space regions for steady states that display generic scale invariance. The exploration of nonstationary relaxation properties and associated physical aging scaling constitutes a complementary potent means to characterize cooperative dynamics in complex out-of-equilibrium systems. This review describes dynamic scaling features through paradigmatic examples that include near-equilibrium critical dynamics, driven lattice gases and growing interfaces, correlation-dominated reaction-diffusion systems, and basic epidemic models.

Control dynamics of interaction quenched ultracold bosons in periodically driven lattices

NASA Astrophysics Data System (ADS)

Mistakidis, Simeon; Schmelcher, Peter; Group of Fundamental Processes in Quantum Physics Team

2016-05-01

The out-of-equilibrium dynamics of ultracold bosons following an interaction quench upon a periodically driven optical lattice is investigated. It is shown that an interaction quench triggers the inter-well tunneling dynamics, while for the intra-well dynamics breathing and cradle-like processes can be generated. In particular, the occurrence of a resonance between the cradle and tunneling modes is revealed. On the other hand, the employed periodic driving enforces the bosons in the mirror wells to oscillate out-of-phase and to exhibit a dipole mode, while in the central well the cloud experiences a breathing mode. The dynamical behaviour of the system is investigated with respect to the driving frequency revealing a resonant behaviour of the intra-well dynamics. To drive the system in a highly non-equilibrium state an interaction quench upon the driving is performed giving rise to admixtures of excitations in the outer wells, an enhanced breathing in the center and an amplification of the tunneling dynamics. As a result of the quench the system experiences multiple resonances between the inter- and intra-well dynamics at different quench amplitudes. Deutsche Forschungsgemeinschaft, SFB 925 ``Light induced dynamics and control of correlated quantum systems''.

Thermodynamics of a periodically driven qubit

NASA Astrophysics Data System (ADS)

Donvil, Brecht

2018-04-01

We present a new approach to the open system dynamics of a periodically driven qubit in contact with a temperature bath. We are specifically interested in the thermodynamics of the qubit. It is well known that by combining the Markovian approximation with Floquet theory it is possible to derive a stochastic Schrödinger equation in for the state of the qubit. We follow here a different approach. We use Floquet theory to embed the time-non autonomous qubit dynamics into time-autonomous yet infinite dimensional dynamics. We refer to the resulting infinite dimensional system as the dressed-qubit. Using the Markovian approximation we derive the stochastic Schrödinger equation for the dressed-qubit. The advantage of our approach is that the jump operators are ladder operators of the Hamiltonian. This simplifies the formulation of the thermodynamics. We use the thermodynamics of the infinite dimensional system to recover the thermodynamical description for the driven qubit. We compare our results with the existing literature and recover the known results.

A geospatial framework for dynamic route planning using congestion prediction in transportation systems.

DOT National Transportation Integrated Search

2011-01-01

The goal this research is to develop an end-to-end data-driven system, dubbed TransDec : (short for Transportation Decision-Making), to enable decision-making queries in : transportation systems with dynamic, real-time and historical data. With Trans...

Reynolds-number-dependent dynamical transitions on hydrodynamic synchronization modes of externally driven colloids

NASA Astrophysics Data System (ADS)

Oyama, Norihiro; Teshigawara, Kosuke; Molina, John Jairo; Yamamoto, Ryoichi; Taniguchi, Takashi

2018-03-01

The collective dynamics of externally driven Np-colloidal systems (1 ≤Np≤4 ) in a confined viscous fluid have been investigated using three-dimensional direct numerical simulations with fully resolved hydrodynamics. The dynamical modes of collective particle motion are studied by changing the particle Reynolds number as determined by the strength of the external driving force and the confining wall distance. For a system with Np=3 , we found that at a critical Reynolds number a dynamical mode transition occurs from the doublet-singlet mode to the triplet mode, which has not been reported experimentally. The dynamical mode transition was analyzed in detail from the following two viewpoints: (1) spectrum analysis of the time evolution of a tagged particle velocity and (2) the relative acceleration of the doublet cluster with respect to the singlet particle. For a system with Np=4 , we found similar dynamical mode transitions from the doublet-singlet-singlet mode to the triplet-singlet mode and further to the quartet mode.

Reynolds-number-dependent dynamical transitions on hydrodynamic synchronization modes of externally driven colloids.

PubMed

Oyama, Norihiro; Teshigawara, Kosuke; Molina, John Jairo; Yamamoto, Ryoichi; Taniguchi, Takashi

2018-03-01

The collective dynamics of externally driven N_{p}-colloidal systems (1≤N_{p}≤4) in a confined viscous fluid have been investigated using three-dimensional direct numerical simulations with fully resolved hydrodynamics. The dynamical modes of collective particle motion are studied by changing the particle Reynolds number as determined by the strength of the external driving force and the confining wall distance. For a system with N_{p}=3, we found that at a critical Reynolds number a dynamical mode transition occurs from the doublet-singlet mode to the triplet mode, which has not been reported experimentally. The dynamical mode transition was analyzed in detail from the following two viewpoints: (1) spectrum analysis of the time evolution of a tagged particle velocity and (2) the relative acceleration of the doublet cluster with respect to the singlet particle. For a system with N_{p}=4, we found similar dynamical mode transitions from the doublet-singlet-singlet mode to the triplet-singlet mode and further to the quartet mode.

Designing an optimal software intensive system acquisition: A game theoretic approach

NASA Astrophysics Data System (ADS)

Buettner, Douglas John

The development of schedule-constrained software-intensive space systems is challenging. Case study data from national security space programs developed at the U.S. Air Force Space and Missile Systems Center (USAF SMC) provide evidence of the strong desire by contractors to skip or severely reduce software development design and early defect detection methods in these schedule-constrained environments. The research findings suggest recommendations to fully address these issues at numerous levels. However, the observations lead us to investigate modeling and theoretical methods to fundamentally understand what motivated this behavior in the first place. As a result, Madachy's inspection-based system dynamics model is modified to include unit testing and an integration test feedback loop. This Modified Madachy Model (MMM) is used as a tool to investigate the consequences of this behavior on the observed defect dynamics for two remarkably different case study software projects. Latin Hypercube sampling of the MMM with sample distributions for quality, schedule and cost-driven strategies demonstrate that the higher cost and effort quality-driven strategies provide consistently better schedule performance than the schedule-driven up-front effort-reduction strategies. Game theory reasoning for schedule-driven engineers cutting corners on inspections and unit testing is based on the case study evidence and Austin's agency model to describe the observed phenomena. Game theory concepts are then used to argue that the source of the problem and hence the solution to developers cutting corners on quality for schedule-driven system acquisitions ultimately lies with the government. The game theory arguments also lead to the suggestion that the use of a multi-player dynamic Nash bargaining game provides a solution for our observed lack of quality game between the government (the acquirer) and "large-corporation" software developers. A note is provided that argues this multi-player dynamic Nash bargaining game also provides the solution to Freeman Dyson's problem, for a way to place a label of good or bad on systems.

Study of an External Neutron Source for an Accelerator-Driven System using the PHITS Code

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sugawara, Takanori; Iwasaki, Tomohiko; Chiba, Takashi

A code system for the Accelerator Driven System (ADS) has been under development for analyzing dynamic behaviors of a subcritical core coupled with an accelerator. This code system named DSE (Dynamics calculation code system for a Subcritical system with an External neutron source) consists of an accelerator part and a reactor part. The accelerator part employs a database, which is calculated by using PHITS, for investigating the effect related to the accelerator such as the changes of beam energy, beam diameter, void generation, and target level. This analysis method using the database may introduce some errors into dynamics calculations sincemore » the neutron source data derived from the database has some errors in fitting or interpolating procedures. In this study, the effects of various events are investigated to confirm that the method based on the database is appropriate.« less

Book Review: Dynamic Systems for Everyone

EPA Science Inventory

Asish Ghosh starts the epilogue of the second edition of Dynamic Systems for Everyone with this quote: “We are now witnessing major technological advancements in areas, like artificial intelligence, robotics and self driven cars. …The pace of change is accelerating, ...

A data driven nonlinear stochastic model for blood glucose dynamics.

PubMed

Zhang, Yan; Holt, Tim A; Khovanova, Natalia

2016-03-01

The development of adequate mathematical models for blood glucose dynamics may improve early diagnosis and control of diabetes mellitus (DM). We have developed a stochastic nonlinear second order differential equation to describe the response of blood glucose concentration to food intake using continuous glucose monitoring (CGM) data. A variational Bayesian learning scheme was applied to define the number and values of the system's parameters by iterative optimisation of free energy. The model has the minimal order and number of parameters to successfully describe blood glucose dynamics in people with and without DM. The model accounts for the nonlinearity and stochasticity of the underlying glucose-insulin dynamic process. Being data-driven, it takes full advantage of available CGM data and, at the same time, reflects the intrinsic characteristics of the glucose-insulin system without detailed knowledge of the physiological mechanisms. We have shown that the dynamics of some postprandial blood glucose excursions can be described by a reduced (linear) model, previously seen in the literature. A comprehensive analysis demonstrates that deterministic system parameters belong to different ranges for diabetes and controls. Implications for clinical practice are discussed. This is the first study introducing a continuous data-driven nonlinear stochastic model capable of describing both DM and non-DM profiles. Copyright © 2015 The Authors. Published by Elsevier Ireland Ltd.. All rights reserved.

LCP method for a planar passive dynamic walker based on an event-driven scheme

NASA Astrophysics Data System (ADS)

Zheng, Xu-Dong; Wang, Qi

2018-06-01

The main purpose of this paper is to present a linear complementarity problem (LCP) method for a planar passive dynamic walker with round feet based on an event-driven scheme. The passive dynamic walker is treated as a planar multi-rigid-body system. The dynamic equations of the passive dynamic walker are obtained by using Lagrange's equations of the second kind. The normal forces and frictional forces acting on the feet of the passive walker are described based on a modified Hertz contact model and Coulomb's law of dry friction. The state transition problem of stick-slip between feet and floor is formulated as an LCP, which is solved with an event-driven scheme. Finally, to validate the methodology, four gaits of the walker are simulated: the stance leg neither slips nor bounces; the stance leg slips without bouncing; the stance leg bounces without slipping; the walker stands after walking several steps.

LCP method for a planar passive dynamic walker based on an event-driven scheme

NASA Astrophysics Data System (ADS)

Zheng, Xu-Dong; Wang, Qi

2018-02-01

The main purpose of this paper is to present a linear complementarity problem (LCP) method for a planar passive dynamic walker with round feet based on an event-driven scheme. The passive dynamic walker is treated as a planar multi-rigid-body system. The dynamic equations of the passive dynamic walker are obtained by using Lagrange's equations of the second kind. The normal forces and frictional forces acting on the feet of the passive walker are described based on a modified Hertz contact model and Coulomb's law of dry friction. The state transition problem of stick-slip between feet and floor is formulated as an LCP, which is solved with an event-driven scheme. Finally, to validate the methodology, four gaits of the walker are simulated: the stance leg neither slips nor bounces; the stance leg slips without bouncing; the stance leg bounces without slipping; the walker stands after walking several steps.

Data Driven Model Development for the Supersonic Semispan Transport (S(sup 4)T)

NASA Technical Reports Server (NTRS)

Kukreja, Sunil L.

2011-01-01

We investigate two common approaches to model development for robust control synthesis in the aerospace community; namely, reduced order aeroservoelastic modelling based on structural finite-element and computational fluid dynamics based aerodynamic models and a data-driven system identification procedure. It is shown via analysis of experimental Super- Sonic SemiSpan Transport (S4T) wind-tunnel data using a system identification approach it is possible to estimate a model at a fixed Mach, which is parsimonious and robust across varying dynamic pressures.

Dynamics of a coherently driven micromaser by the Monte Carlo wavefunction approach

NASA Astrophysics Data System (ADS)

Bonacina, L.; Casagrande, F.; Lulli, A.

2000-08-01

Using a Monte Carlo wavefunction approach we investigate the dynamics of a micromaser driven by a resonant coherent field. At steady state, for increasing interaction times, the system exhibits driven Rabi oscillations, followed by collapse as the range of micromaser trapping states is approached. The system operates in regimes ranging from a strong to a weak amplifier. In the strong-amplifier regime the cavity mode shows a preferred phase and can exhibit quadrature squeezing and sub-Poissonian photon statistics. In the weak-amplifier regime the cavity mode has no preferred phase, is super-Poissonian and is influenced by trapping effects; no revival of Rabi oscillations occurs. The main predictions can be compared with experimental measurements on the populations of atoms leaving the cavity.

A Dynamic Human Health Risk Assessment System

PubMed Central

Prasad, Umesh; Singh, Gurmit; Pant, A. B.

2012-01-01

An online human health risk assessment system (OHHRAS) has been designed and developed in the form of a prototype database-driven system and made available for the population of India through a website – www.healthriskindia.in. OHHRAS provide the three utilities, that is, health survey, health status, and bio-calculators. The first utility health survey is functional on the basis of database being developed dynamically and gives the desired output to the user on the basis of input criteria entered into the system; the second utility health status is providing the output on the basis of dynamic questionnaire and ticked (selected) answers and generates the health status reports based on multiple matches set as per advise of medical experts and the third utility bio-calculators are very useful for the scientists/researchers as online statistical analysis tool that gives more accuracy and save the time of user. The whole system and database-driven website has been designed and developed by using the software (mainly are PHP, My-SQL, Deamweaver, C++ etc.) and made available publically through a database-driven website (www.healthriskindia.in), which are very useful for researchers, academia, students, and general masses of all sectors. PMID:22778520

Dynamics of High Pressure Reacting Shear Flows

DTIC Science & Technology

2015-10-02

liquid rockets, future gas turbines • When the combustion systems are for propulsion, limited tankage dictates that on-board propellants be stored in...system dynamics • Combustion dynamics always includes acoustic waves, which in enclosed systems can sometimes reach detrimental amplitudes – eg...a high pressure, chemically reacting, multiphase, acoustically driven, shear flow in the form of a coaxial jet flame • Explore how the presence of

Mapping repulsive to attractive interaction in driven-dissipative quantum systems

NASA Astrophysics Data System (ADS)

Li, Andy C. Y.; Koch, Jens

2017-11-01

Repulsive and attractive interactions usually lead to very different physics. Striking exceptions exist in the dynamics of driven-dissipative quantum systems. For the example of a photonic Bose-Hubbard dimer, we establish a one-to-one mapping relating cases of onsite repulsion and attraction. We prove that the mapping is valid for an entire class of Markovian open quantum systems with a time-reversal-invariant Hamiltonian and physically meaningful inverse-sign Hamiltonian. To underline the broad applicability of the mapping, we illustrate the one-to-one correspondence between the nonequilibrium dynamics in a geometrically frustrated spin lattice and those in a non-frustrated partner lattice.

Asymptotic Dynamics of Self-driven Vehicles in a Closed Boundary

NASA Astrophysics Data System (ADS)

Lee, Chi-Lun; Huang, Chia-Ling

2011-08-01

We study the asymptotic dynamics of self-driven vehicles in a loop using a car-following model with the consideration of volume exclusions. In particular, we derive the dynamical steady states for the single-cluster case and obtain the corresponding fundamental diagrams, exhibiting two branches representative of entering and leaving the jam, respectively. By simulations we find that the speed average over all vehicles eventually reaches the same value, regardless of final clustering states. The autocorrelation functions for overall speed average and single-vehicle speed are studied, each revealing a unique time scale. We also discuss the role of noises in vehicular accelerations. Based on our observations we give trial definitions about the degree of chaoticity for general self-driven many-body systems.

Driven Langevin systems: fluctuation theorems and faithful dynamics

NASA Astrophysics Data System (ADS)

Sivak, David; Chodera, John; Crooks, Gavin

2014-03-01

Stochastic differential equations of motion (e.g., Langevin dynamics) provide a popular framework for simulating molecular systems. Any computational algorithm must discretize these equations, yet the resulting finite time step integration schemes suffer from several practical shortcomings. We show how any finite time step Langevin integrator can be thought of as a driven, nonequilibrium physical process. Amended by an appropriate work-like quantity (the shadow work), nonequilibrium fluctuation theorems can characterize or correct for the errors introduced by the use of finite time steps. We also quantify, for the first time, the magnitude of deviations between the sampled stationary distribution and the desired equilibrium distribution for equilibrium Langevin simulations of solvated systems of varying size. We further 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 that has essentially universally appropriate properties for the simulation of Langevin dynamics for molecular systems in equilibrium, nonequilibrium, and path sampling contexts.

Nonlinear effects in the bounded dust-vortex flow in plasma

NASA Astrophysics Data System (ADS)

Laishram, Modhuchandra; Sharma, Devendra; Chattopdhyay, Prabal K.; Kaw, Predhiman K.

2017-03-01

The vortex structures in a cloud of electrically suspended dust in a streaming plasma constitutes a driven system with a rich nonlinear flow regime. Experimentally recovered toroidal formations of this system have motivated study of its volumetrically driven-dissipative vortex flow dynamics using two-dimensional hydrodynamics in the incompressible Navier-Stokes regime. Nonlinear equilibrium solutions are obtained for this system where a nonuniformly driven two-dimensional dust flow exhibits distinct regions of localized accelerations and strong friction caused by stationary fluids at the confining boundaries resisting the dust flow. In agreement with observations in experiments, it is demonstrated that the nonlinear effects appear in the limit of small viscosity, where the primary vortices form scaling with the most dominant spatial scales of the domain topology and develop separated virtual boundaries along their periphery. This separation is triggered beyond a critical dust viscosity that signifies a structural bifurcation. Emergence of uniform vorticity core and secondary vortices with a newer level of identical dynamics highlights the applicability of the studied dynamics to gigantic vortex flows, such as the Jovian great red spot, to microscopic biophysical intracellular activity.

Signal Processing in Periodically Forced Gradient Frequency Neural Networks

PubMed Central

Kim, Ji Chul; Large, Edward W.

2015-01-01

Oscillatory instability at the Hopf bifurcation is a dynamical phenomenon that has been suggested to characterize active non-linear processes observed in the auditory system. Networks of oscillators poised near Hopf bifurcation points and tuned to tonotopically distributed frequencies have been used as models of auditory processing at various levels, but systematic investigation of the dynamical properties of such oscillatory networks is still lacking. Here we provide a dynamical systems analysis of a canonical model for gradient frequency neural networks driven by a periodic signal. We use linear stability analysis to identify various driven behaviors of canonical oscillators for all possible ranges of model and forcing parameters. The analysis shows that canonical oscillators exhibit qualitatively different sets of driven states and transitions for different regimes of model parameters. We classify the parameter regimes into four main categories based on their distinct signal processing capabilities. This analysis will lead to deeper understanding of the diverse behaviors of neural systems under periodic forcing and can inform the design of oscillatory network models of auditory signal processing. PMID:26733858

Stochastic driven systems far from equilibrium

NASA Astrophysics Data System (ADS)

Kim, Kyung Hyuk

We study the dynamics and steady states of two systems far from equilibrium: a 1-D driven lattice gas and a driven Brownian particle with inertia. (1) We investigate the dynamical scaling behavior of a 1-D driven lattice gas model with two species of particles hopping in opposite directions. We confirm numerically that the dynamic exponent is equal to z = 1.5. We show analytically that a quasi-particle representation relates all phase points to a special phase line directly related to the single-species asymmetric simple exclusion process. Quasi-particle two-point correlations decay exponentially, and in such a manner that quasi-particles of opposite charge dynamically screen each other with a special balance. The balance encompasses all over the phase space. These results indicate that the model belongs to the Kardar-Parisi-Zhang (KPZ) universality class. (2) We investigate the non-equilibrium thermodynamics of a Brownian particle with inertia under feedback control of its inertia. We find such open systems can act as a molecular refrigerator due to an entropy pumping mechanism. We extend the fluctuation theorems to the refrigerator. The entropy pumping modifies both the Jarzynski equality and the fluctuation theorems. We discover that the entropy pumping has a dual role of work and heat. We also investigate the thermodynamics of the particle under a hydrodynamic interaction described by a Langevin equation with a multiplicative noise. The Stratonovich stochastic integration prescription involved in the definition of heat is shown to be the unique physical choice.

Experiments on vibration-driven stick-slip locomotion: A sliding bifurcation perspective

NASA Astrophysics Data System (ADS)

Du, Zhouwei; Fang, Hongbin; Zhan, Xiong; Xu, Jian

2018-05-01

Dry friction appears at the contact interface between two surfaces and is the source of stick-slip vibrations. Instead of being a negative factor, dry friction is essential for vibration-driven locomotion system to take effect. However, the dry-friction-induced stick-slip locomotion has not been fully understood in previous research, especially in terms of experiments. In this paper, we experimentally study the stick-slip dynamics of a vibration-driven locomotion system from a sliding bifurcation perspective. To this end, we first design and build a vibration-driven locomotion prototype based on an internal piezoelectric cantilever. By utilizing the mechanical resonance, the small piezoelectric deformation is significantly amplified to drive the prototype to achieve effective locomotion. Through identifying the stick-slip characteristics in velocity histories, we could categorize the system's locomotion into four types and obtain a stick-slip categorization diagram. In each zone of the diagram the locomotion exhibits qualitatively different stick-slip dynamics. Such categorization diagram is actually a sliding bifurcation diagram; crossing from one stick-slip zone to another corresponds to the triggering of a sliding bifurcation. In addition, a simplified single degree-of-freedom model is established, with the rationality of simplification been explained theoretically and numerically. Based on the equivalent model, a numerical stick-slip categorization is also obtained, which shows good agreement with the experiments both qualitatively and quantitatively. To the best of our knowledge, this is the first work that experimentally generates a sliding bifurcation diagram. The obtained stick-slip categorizations deepen our understanding of stick-slip dynamics in vibration-driven systems and could serve as a base for system design and optimization.

Traffic and related self-driven many-particle systems

NASA Astrophysics Data System (ADS)

Helbing, Dirk

2001-10-01

Since the subject of traffic dynamics has captured the interest of physicists, many surprising effects have been revealed and explained. Some of the questions now understood are the following: Why are vehicles sometimes stopped by ``phantom traffic jams'' even though drivers all like to drive fast? What are the mechanisms behind stop-and-go traffic? Why are there several different kinds of congestion, and how are they related? Why do most traffic jams occur considerably before the road capacity is reached? Can a temporary reduction in the volume of traffic cause a lasting traffic jam? Under which conditions can speed limits speed up traffic? Why do pedestrians moving in opposite directions normally organize into lanes, while similar systems ``freeze by heating''? All of these questions have been answered by applying and extending methods from statistical physics and nonlinear dynamics to self-driven many-particle systems. This article considers the empirical data and then reviews the main approaches to modeling pedestrian and vehicle traffic. These include microscopic (particle-based), mesoscopic (gas-kinetic), and macroscopic (fluid-dynamic) models. Attention is also paid to the formulation of a micro-macro link, to aspects of universality, and to other unifying concepts, such as a general modeling framework for self-driven many-particle systems, including spin systems. While the primary focus is upon vehicle and pedestrian traffic, applications to biological or socio-economic systems such as bacterial colonies, flocks of birds, panics, and stock market dynamics are touched upon as well.

Data Driven Model Development for the SuperSonic SemiSpan Transport (S(sup 4)T)

NASA Technical Reports Server (NTRS)

Kukreja, Sunil L.

2011-01-01

In this report, we will investigate two common approaches to model development for robust control synthesis in the aerospace community; namely, reduced order aeroservoelastic modelling based on structural finite-element and computational fluid dynamics based aerodynamic models, and a data-driven system identification procedure. It is shown via analysis of experimental SuperSonic SemiSpan Transport (S4T) wind-tunnel data that by using a system identification approach it is possible to estimate a model at a fixed Mach, which is parsimonious and robust across varying dynamic pressures.

Dynamical singularities of glassy systems in a quantum quench.

PubMed

Obuchi, Tomoyuki; Takahashi, Kazutaka

2012-11-01

We present a prototype of behavior of glassy systems driven by quantum dynamics in a quenching protocol by analyzing the random energy model in a transverse field. We calculate several types of dynamical quantum amplitude and find a freezing transition at some critical time. The behavior is understood by the partition-function zeros in the complex temperature plane. We discuss the properties of the freezing phase as a dynamical chaotic phase, which are contrasted to those of the spin-glass phase in the static system.

A fuzzy Petri-net-based mode identification algorithm for fault diagnosis of complex systems

NASA Astrophysics Data System (ADS)

Propes, Nicholas C.; Vachtsevanos, George

2003-08-01

Complex dynamical systems such as aircraft, manufacturing systems, chillers, motor vehicles, submarines, etc. exhibit continuous and event-driven dynamics. These systems undergo several discrete operating modes from startup to shutdown. For example, a certain shipboard system may be operating at half load or full load or may be at start-up or shutdown. Of particular interest are extreme or "shock" operating conditions, which tend to severely impact fault diagnosis or the progression of a fault leading to a failure. Fault conditions are strongly dependent on the operating mode. Therefore, it is essential that in any diagnostic/prognostic architecture, the operating mode be identified as accurately as possible so that such functions as feature extraction, diagnostics, prognostics, etc. can be correlated with the predominant operating conditions. This paper introduces a mode identification methodology that incorporates both time- and event-driven information about the process. A fuzzy Petri net is used to represent the possible successive mode transitions and to detect events from processed sensor signals signifying a mode change. The operating mode is initialized and verified by analysis of the time-driven dynamics through a fuzzy logic classifier. An evidence combiner module is used to combine the results from both the fuzzy Petri net and the fuzzy logic classifier to determine the mode. Unlike most event-driven mode identifiers, this architecture will provide automatic mode initialization through the fuzzy logic classifier and robustness through the combining of evidence of the two algorithms. The mode identification methodology is applied to an AC Plant typically found as a component of a shipboard system.

Quantum ratchets, the orbital Josephson effect, and chaos in Bose-Einstein condensates

NASA Astrophysics Data System (ADS)

Carr, Lincoln D.; Heimsoth, Martin; Creffield, Charles E.; Sols, Fernando

2014-03-01

In a system of ac-driven condensed bosons we study a new type of Josephson effect occurring between states sharing the same region of space and the same internal atom structure. We first develop a technique to calculate the long-time dynamics of a driven interacting many-body system. For resonant frequencies, this dynamics can be shown to derive from an effective time-independent Hamiltonian which is expressed in terms of standard creation and annihilation operators. Within the subspace of resonant states, and if the undriven states are plane waves, a locally repulsive interaction between bosons translates into an effective attraction. We apply the method to study the effect of interactions on the coherent ratchet current of an asymmetrically driven boson system. We find a wealth of dynamical regimes which includes Rabi oscillations, self-trapping and chaotic behavior. In the latter case, a full quantum many-body calculation deviates from the mean-field results by predicting large quantum fluctuations of the relative particle number. Moreover, we find that chaos and entanglement, as defined by a variety of widely used and accepted measures, are overlapping but distinct notions. Funded by Spanish MINECO, the Ramon y Cajal program (CEC), the Comunidad de Madrid through Grant Microseres, the Heidelberg Center for Quantum Dynamics, and the NSF.

Flight dynamics system software development environment (FDS/SDE) tutorial

NASA Technical Reports Server (NTRS)

Buell, John; Myers, Philip

1986-01-01

A sample development scenario using the Flight Dynamics System Software Development Environment (FDS/SDE) is presented. The SDE uses a menu-driven, fill-in-the-blanks format that provides online help at all steps, thus eliminating lengthy training and allowing immediate use of this new software development tool.

Chevrons, filaments, spinning clusters and phase coexistence: emergent dynamics of 2- and 3-d particle suspensions driven by multiaxial magnetic fields

DOE PAGES

Solis, Kyle J.; Martin, James E.

2017-07-06

In recent years a rich variety of emergent phenomena have been observed when suspensions of magnetic particles are subjected to alternating magnetic fields. These particle assemblies often exhibit vigorous dynamics due to the injection of energy from the field. These include surface and interface phenomena, such as highly organized, segmented “snakes” that can be induced to swim by structural symmetry breaking, and “asters” and “anti-asters,” particle assemblies that can be manipulated to capture and transport cargo. In bulk suspensions of magnetic platelets subjected to multiaxial alternating fields, advection lattices and even vortex lattices have been created, and a variety ofmore » biomimetic dynamics – serpents, bees and amoebas – have been discovered in magnetic fluids suspended in an immiscible liquid. In this paper several new driven phases are presented, including flying chevrons, dense spinning clusters, filaments, and examples of phase coexistence in driven phases. These observations broaden the growing field of driven magnetic suspensions and present new challenges to those interested in simulating the dynamics of these complex systems.« less

Data-Driven Zero-Sum Neuro-Optimal Control for a Class of Continuous-Time Unknown Nonlinear Systems With Disturbance Using ADP.

PubMed

Wei, Qinglai; Song, Ruizhuo; Yan, Pengfei

2016-02-01

This paper is concerned with a new data-driven zero-sum neuro-optimal control problem for continuous-time unknown nonlinear systems with disturbance. According to the input-output data of the nonlinear system, an effective recurrent neural network is introduced to reconstruct the dynamics of the nonlinear system. Considering the system disturbance as a control input, a two-player zero-sum optimal control problem is established. Adaptive dynamic programming (ADP) is developed to obtain the optimal control under the worst case of the disturbance. Three single-layer neural networks, including one critic and two action networks, are employed to approximate the performance index function, the optimal control law, and the disturbance, respectively, for facilitating the implementation of the ADP method. Convergence properties of the ADP method are developed to show that the system state will converge to a finite neighborhood of the equilibrium. The weight matrices of the critic and the two action networks are also convergent to finite neighborhoods of their optimal ones. Finally, the simulation results will show the effectiveness of the developed data-driven ADP methods.

Depinning and nonequilibrium dynamic phases of particle assemblies driven over random and ordered substrates: A review

DOE PAGES

Reichhardt, Charles; Olson Reichhardt, Cynthia Jane

2016-12-20

Here, we review the depinning and nonequilibrium phases of collectively interacting particle systems driven over random or periodic substrates. This type of system is relevant to vortices in type-II superconductors, sliding charge density waves, electron crystals, colloids, stripe and pattern forming systems, and skyrmions, and could also have connections to jamming, glassy behaviors, and active matter. These systems are also ideal for exploring the broader issues of characterizing transient and steady state nonequilibrium flow phases as well as nonequilibrium phase transitions between distinct dynamical phases, analogous to phase transitions between different equilibrium states. We discuss the differences between elastic andmore » plastic depinning on random substrates and the different types of nonequilibrium phases which are associated with specific features in the velocity-force curves, fluctuation spectra, scaling relations, and local or global particle ordering. We describe how these quantities can change depending on the dimension, anisotropy, disorder strength, and the presence of hysteresis. Within the moving phase we discuss how there can be a transition from a liquid-like state to dynamically ordered moving crystal, smectic, or nematic states. Systems with periodic or quasiperiodic substrates can have multiple nonequilibrium second or first order transitions in the moving state between chaotic and coherent phases, and can exhibit hysteresis. We also discuss systems with competing repulsive and attractive interactions, which undergo dynamical transitions into stripes and other complex morphologies when driven over random substrates. Throughout this work we highlight open issues and future directions such as absorbing phase transitions, nonequilibrium work relations, inertia, the role of non-dissipative dynamics such as Magnus effects, and how these results could be extended to the broader issues of plasticity in crystals, amorphous solids, and jamming phenomena.« less

Depinning and nonequilibrium dynamic phases of particle assemblies driven over random and ordered substrates: a review

NASA Astrophysics Data System (ADS)

Reichhardt, C.; Olson Reichhardt, C. J.

2017-02-01

We review the depinning and nonequilibrium phases of collectively interacting particle systems driven over random or periodic substrates. This type of system is relevant to vortices in type-II superconductors, sliding charge density waves, electron crystals, colloids, stripe and pattern forming systems, and skyrmions, and could also have connections to jamming, glassy behaviors, and active matter. These systems are also ideal for exploring the broader issues of characterizing transient and steady state nonequilibrium flow phases as well as nonequilibrium phase transitions between distinct dynamical phases, analogous to phase transitions between different equilibrium states. We discuss the differences between elastic and plastic depinning on random substrates and the different types of nonequilibrium phases which are associated with specific features in the velocity-force curves, fluctuation spectra, scaling relations, and local or global particle ordering. We describe how these quantities can change depending on the dimension, anisotropy, disorder strength, and the presence of hysteresis. Within the moving phase we discuss how there can be a transition from a liquid-like state to dynamically ordered moving crystal, smectic, or nematic states. Systems with periodic or quasiperiodic substrates can have multiple nonequilibrium second or first order transitions in the moving state between chaotic and coherent phases, and can exhibit hysteresis. We also discuss systems with competing repulsive and attractive interactions, which undergo dynamical transitions into stripes and other complex morphologies when driven over random substrates. Throughout this work we highlight open issues and future directions such as absorbing phase transitions, nonequilibrium work relations, inertia, the role of non-dissipative dynamics such as Magnus effects, and how these results could be extended to the broader issues of plasticity in crystals, amorphous solids, and jamming phenomena.

Negative differential mobility in interacting particle systems

NASA Astrophysics Data System (ADS)

Chatterjee, Amit Kumar; Basu, Urna; Mohanty, P. K.

2018-05-01

Driven particles in the presence of crowded environment, obstacles, or kinetic constraints often exhibit negative differential mobility (NDM) due to their decreased dynamical activity. Based on the empirical studies of conserved lattice gas model, two species exclusion model and other interacting particle systems we propose a new mechanism for complex many-particle systems where slowing down of certain non-driven degrees of freedom by the external field can give rise to NDM. To prove that the slowing down of the non-driven degrees is indeed the underlying cause, we consider several driven diffusive systems including two species exclusion models, misanthrope process, and show from the exact steady state results that NDM indeed appears when some non-driven modes are slowed down deliberately. For clarity, we also provide a simple pedagogical example of two interacting random walkers on a ring which conforms to the proposed scenario.

Fisher information due to a phase noisy laser under non-Markovian environment

DOE Office of Scientific and Technical Information (OSTI.GOV)

Abdel-Khalek, S., E-mail: sayedquantum@yahoo.co.uk

2014-12-15

More recently, K. Berrada [Annals of Physics 340 (2014) 60-69] [1] studied the geometric phase of a two-level atom system driven by a phase noise laser under non-Markovian dynamics in terms of different parameters involved in the whole system, and collapse and revival phenomena were found for large class of states. In this paper, using this noise effect, we study the quantum fisher information (QFI) for a two-level atom system driven by a phase noise laser under non-Markovian dynamics. A new quantity, called QFI flow is used to characterize the damping effect and unveil a fundamental connection between non-Markovian behaviormore » and dynamics of system–environment correlations under phase noise laser. It is shown that QFI flow has disappeared suddenly followed by a sudden birth depending on the kind of the environment damping. QFI flow provides an indicator to characterize the dissipative quantum system’s decoherence by analyzing the behavior of the dynamical non-Markovian coefficients.« less

Sensitivity analysis of reactive ecological dynamics.

PubMed

Verdy, Ariane; Caswell, Hal

2008-08-01

Ecological systems with asymptotically stable equilibria may exhibit significant transient dynamics following perturbations. In some cases, these transient dynamics include the possibility of excursions away from the equilibrium before the eventual return; systems that exhibit such amplification of perturbations are called reactive. Reactivity is a common property of ecological systems, and the amplification can be large and long-lasting. The transient response of a reactive ecosystem depends on the parameters of the underlying model. To investigate this dependence, we develop sensitivity analyses for indices of transient dynamics (reactivity, the amplification envelope, and the optimal perturbation) in both continuous- and discrete-time models written in matrix form. The sensitivity calculations require expressions, some of them new, for the derivatives of equilibria, eigenvalues, singular values, and singular vectors, obtained using matrix calculus. Sensitivity analysis provides a quantitative framework for investigating the mechanisms leading to transient growth. We apply the methodology to a predator-prey model and a size-structured food web model. The results suggest predator-driven and prey-driven mechanisms for transient amplification resulting from multispecies interactions.

Spectral functions of a time-periodically driven Falicov-Kimball model: Real-space Floquet dynamical mean-field theory study

NASA Astrophysics Data System (ADS)

Qin, Tao; Hofstetter, Walter

2017-08-01

We present a systematic study of the spectral functions of a time-periodically driven Falicov-Kimball Hamiltonian. In the high-frequency limit, this system can be effectively described as a Harper-Hofstadter-Falicov-Kimball model. Using real-space Floquet dynamical mean-field theory (DMFT), we take into account the interaction effects and contributions from higher Floquet bands in a nonperturbative way. Our calculations show a high degree of similarity between the interacting driven system and its effective static counterpart with respect to spectral properties. However, as also illustrated by our results, one should bear in mind that Floquet DMFT describes a nonequilibrium steady state, while an effective static Hamiltonian describes an equilibrium state. We further demonstrate the possibility of using real-space Floquet DMFT to study edge states on a cylinder geometry.

Interaction quenched ultracold few-boson ensembles in periodically driven lattices

NASA Astrophysics Data System (ADS)

Mistakidis, Simeon; Schmelcher, Peter; Theory Group of Fundamental Processes in Quantum Physics Team

2017-04-01

The out-of-equilibrium dynamics of interaction quenched finite ultracold bosonic ensembles in periodically driven one-dimensional optical lattices is investigated. It is shown that periodic driving enforces the bosons in the outer wells of the finite lattice to exhibit out-of-phase dipole-like modes, while in the central well the atomic cloud experiences a local breathing mode. The dynamical behavior is investigated with varying driving frequency, revealing a resonant-like behavior of the intra-well dynamics. An interaction quench in the periodically driven lattice gives rise to admixtures of different excitations in the outer wells, an enhanced breathing in the center and an amplification of the tunneling dynamics. We observe then multiple resonances between the inter- and intra-well dynamics at different quench amplitudes, with the position of the resonances being tunable via the driving frequency. Our results pave the way for future investigations on the use of combined driving protocols in order to excite different inter- and intra-well modes and to subsequently control them. Deutsche Forschungsgemeinschaft (DFG) in the framework of the SFB 925 ``Light induced dynamics and control of correlated quantum systems''.

Modeling and control of a cable-suspended robot for inspection of vertical structures

NASA Astrophysics Data System (ADS)

Barry, Nicole; Fisher, Erin; Vaughan, Joshua

2016-09-01

In this paper, a cable-driven system is examined for the application of inspection of large, vertical-walled structures such as chemical storage tanks, large ship hulls, and high-rise buildings. Such cable-driven systems are not commonly used for these tasks due to vibration, which decreases inspection accuracy and degrades safety. The flexible nature of the cables make them difficult to control. In this paper, input shaping is implemented on a cable-driven system to reduce vibration. To design the input shapers, a model of the cable-driven system was developed. Analysis of the dominant dynamics and changes in them over the large workspace are also presented. The performance improvements provided by the input shaping controller are quantified through a series of simulations.

Depinning and heterogeneous dynamics of colloidal crystal layers under shear flow

NASA Astrophysics Data System (ADS)

Gerloff, Sascha; Klapp, Sabine H. L.

2016-12-01

Using Brownian dynamics (BD) simulations and an analytical approach we investigate the shear-induced, nonequilibrium dynamics of dense colloidal suspensions confined to a narrow slit-pore. Focusing on situations where the colloids arrange in well-defined layers with solidlike in-plane structure, the confined films display complex, nonlinear behavior such as collective depinning and local transport via density excitations. These phenomena are reminiscent of colloidal monolayers driven over a periodic substrate potential. In order to deepen this connection, we present an effective model that maps the dynamics of the shear-driven colloidal layers to the motion of a single particle driven over an effective substrate potential. This model allows us to estimate the critical shear rate of the depinning transition based on the equilibrium configuration, revealing the impact of important parameters, such as the slit-pore width and the interaction strength. We then turn to heterogeneous systems where a layer of small colloids is sheared with respect to bottom layers of large particles. For these incommensurate systems we find that the particle transport is dominated by density excitations resembling the so-called "kink" solutions of the Frenkel-Kontorova (FK) model. In contrast to the FK model, however, the corresponding "antikinks" do not move.

Radical chiral Floquet phases in a periodically driven Kitaev model and beyond

NASA Astrophysics Data System (ADS)

Po, Hoi Chun; Fidkowski, Lukasz; Vishwanath, Ashvin; Potter, Andrew C.

2017-12-01

We theoretically discover a family of nonequilibrium fractional topological phases in which time-periodic driving of a 2D system produces excitations with fractional statistics, and produces chiral quantum channels that propagate a quantized fractional number of qubits along the sample edge during each driving period. These phases share some common features with fractional quantum Hall states, but are sharply distinct dynamical phenomena. Unlike the integer-valued invariant characterizing the equilibrium quantum Hall conductance, these phases are characterized by a dynamical topological invariant that is a square root of a rational number, inspiring the label: radical chiral Floquet phases. We construct solvable models of driven and interacting spin systems with these properties, and identify an unusual bulk-boundary correspondence between the chiral edge dynamics and bulk "anyon time-crystal" order characterized by dynamical transmutation of electric-charge into magnetic-flux excitations in the bulk.

Bifurcation Theory of the Transition to Collisionless Ion-temperature-gradient-driven Plasma Turbulence

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kolesnikov, R.A.; Krommes, J.A.

The collisionless limit of the transition to ion-temperature-gradient-driven plasma turbulence is considered with a dynamical-systems approach. The importance of systematic analysis for understanding the differences in the bifurcations and dynamics of linearly damped and undamped systems is emphasized. A model with ten degrees of freedom is studied as a concrete example. A four-dimensional center manifold (CM) is analyzed, and fixed points of its dynamics are identified and used to predict a ''Dimits shift'' of the threshold for turbulence due to the excitation of zonal flows. The exact value of that shift in terms of physical parameters is established for themore » model; the effects of higher-order truncations on the dynamics are noted. Multiple-scale analysis of the CM equations is used to discuss possible effects of modulational instability on scenarios for the transition to turbulence in both collisional and collisionless cases.« less

Digital Suicide Prevention: Can Technology Become a Game-changer?

PubMed

Vahabzadeh, Arshya; Sahin, Ned; Kalali, Amir

2016-01-01

Suicide continues to be a leading cause of death and has been recognized as a significant public health issue. Rapid advances in data science can provide us with useful tools for suicide prevention, and help to dynamically assess suicide risk in quantitative data-driven ways. In this article, the authors highlight the most current international research in digital suicide prevention, including the use of machine learning, smartphone applications, and wearable sensor driven systems. The authors also discuss future opportunities for digital suicide prevention, and propose a novel Sensor-driven Mental State Assessment System.

Chaos as an intermittently forced linear system.

PubMed

Brunton, Steven L; Brunton, Bingni W; Proctor, Joshua L; Kaiser, Eurika; Kutz, J Nathan

2017-05-30

Understanding the interplay of order and disorder in chaos is a central challenge in modern quantitative science. Approximate linear representations of nonlinear dynamics have long been sought, driving considerable interest in Koopman theory. We present a universal, data-driven decomposition of chaos as an intermittently forced linear system. This work combines delay embedding and Koopman theory to decompose chaotic dynamics into a linear model in the leading delay coordinates with forcing by low-energy delay coordinates; this is called the Hankel alternative view of Koopman (HAVOK) analysis. This analysis is applied to the Lorenz system and real-world examples including Earth's magnetic field reversal and measles outbreaks. In each case, forcing statistics are non-Gaussian, with long tails corresponding to rare intermittent forcing that precedes switching and bursting phenomena. The forcing activity demarcates coherent phase space regions where the dynamics are approximately linear from those that are strongly nonlinear.The huge amount of data generated in fields like neuroscience or finance calls for effective strategies that mine data to reveal underlying dynamics. Here Brunton et al.develop a data-driven technique to analyze chaotic systems and predict their dynamics in terms of a forced linear model.

System Dynamics to Climate-Driven Water Budget Analysis in the Eastern Snake Plains Aquifer

NASA Astrophysics Data System (ADS)

Ryu, J.; Contor, B.; Wylie, A.; Johnson, G.; Allen, R. G.

2010-12-01

Climate variability, weather extremes and climate change continue to threaten the sustainability of water resources in the western United States. Given current climate change projections, increasing temperature is likely to modify the timing, form, and intensity of precipitation events, which consequently affect regional and local hydrologic cycles. As a result, drought, water shortage, and subsequent water conflicts may become an increasing threat in monotone hydrologic systems in arid lands, such as the Eastern Snake Plain Aquifer (ESPA). The ESPA, in particular, is a critical asset in the state of Idaho. It is known as the economic lifeblood for more than half of Idaho’s population so that water resources availability and aquifer management due to climate change is of great interest, especially over the next few decades. In this study, we apply system dynamics as a methodology with which to address dynamically complex problems in ESPA’s water resources management. Aquifer recharge and discharge dynamics are coded in STELLA modeling system as input and output, respectively to identify long-term behavior of aquifer responses to climate-driven hydrological changes.

The Dynamical Balance of the Brain at Rest

PubMed Central

Deco, Gustavo; Corbetta, Maurizio

2014-01-01

We review evidence that spontaneous, i.e. not stimulus- or task-driven, activity in the brain is not noise, but orderly organized at the level of large scale systems in a series of functional networks that maintain at all times a high level of coherence. These networks of spontaneous activity correlation or resting state networks (RSN) are closely related to the underlying anatomical connectivity, but their topography is also gated by the history of prior task activation. Network coherence does not depend on covert cognitive activity, but its strength and integrity relates to behavioral performance. Some RSN are functionally organized as dynamically competing systems both at rest and during tasks. Computational studies show that one of such dynamics, the anti-correlation between networks, depends on noise driven transitions between different multi-stable cluster synchronization states. These multi-stable states emerge because of transmission delays between regions that are modeled as coupled oscillators systems. Large-scale systems dynamics are useful for keeping different functional sub-networks in a state of heightened competition, which can be stabilized and fired by even small modulations of either sensory or internal signals. PMID:21196530

Critical slowing down in driven-dissipative Bose-Hubbard lattices

NASA Astrophysics Data System (ADS)

Vicentini, Filippo; Minganti, Fabrizio; Rota, Riccardo; Orso, Giuliano; Ciuti, Cristiano

2018-01-01

We explore theoretically the dynamical properties of a first-order dissipative phase transition in coherently driven Bose-Hubbard systems, describing, e.g., lattices of coupled nonlinear optical cavities. Via stochastic trajectory calculations based on the truncated Wigner approximation, we investigate the dynamical behavior as a function of system size for one-dimensional (1D) and 2D square lattices in the regime where mean-field theory predicts nonlinear bistability. We show that a critical slowing down emerges for increasing number of sites in 2D square lattices, while it is absent in 1D arrays. We characterize the peculiar properties of the collective phases in the critical region.

Two-rate periodic protocol with dynamics driven through many cycles

NASA Astrophysics Data System (ADS)

Kar, Satyaki

2017-02-01

We study the long time dynamics in closed quantum systems periodically driven via time dependent parameters with two frequencies ω1 and ω2=r ω1 . Tuning of the ratio r there can unleash plenty of dynamical phenomena to occur. Our study includes integrable models like Ising and X Y models in d =1 and the Kitaev model in d =1 and 2 and can also be extended to Dirac fermions in graphene. We witness the wave-function overlap or dynamic freezing that occurs within some small/ intermediate frequency regimes in the (ω1,r ) plane (with r ≠0 ) when the ground state is evolved through a single cycle of driving. However, evolved states soon become steady with long driving, and the freezing scenario gets rarer. We extend the formalism of adiabatic-impulse approximation for many cycle driving within our two-rate protocol and show the near-exact comparisons at small frequencies. An extension of the rotating wave approximation is also developed to gather an analytical framework of the dynamics at high frequencies. Finally we compute the entanglement entropy in the stroboscopically evolved states within the gapped phases of the system and observe how it gets tuned with the ratio r in our protocol. The minimally entangled states are found to fall within the regime of dynamical freezing. In general, the results indicate that the entanglement entropy in our driven short-ranged integrable systems follow a genuine nonarea law of scaling and show a convergence (with a r dependent pace) towards volume scaling behavior as the driving is continued for a long time.

Imaging the Dynamics of the Ferroelectric Stripe Phase Near a Field-Driven Phase Transition in Bismuth Ferrite

NASA Astrophysics Data System (ADS)

Laanait, Nouamane; Li, Qian; Zhang, Zhan; Kalinin, Sergei

Electric field-driven phase transitions in multiferroic systems such as Bismuth Ferrite could potentially host interesting domain dynamics due to the coexistence of multiple order parameters. Structural imaging of these dynamics under a host of elastic and electric boundary conditions is therefore of interest. Here, we present X-ray diffraction microscopy (XDM) studies of the domain wall dynamics in a bismuth ferrite thin-film near the field-driven transition from rhombohedral to monoclinic (R to M). XDM is a novel full-field imaging technique that uses Bragg diffraction contrast to image structural configurations with sub-100nm lateral resolutions and fast acquisition times (milliseconds to seconds per image). We find that under electric fields 100 kV/cm, a bismuth ferrite thin-film (100 nm BiFeO3/DyScO3 (110)) undergoes a structural phase transition but that this new phase (M) is pinned by the preexisting ferroelectric/ferroelastic stripe phase (R). At higher fields ( 300 kV/cm), we observe unusually slow domain wall dynamics in the stripe phase, consisting of periodicity doubling, domain wall roughening and crowding. These observed ferroelastic domain wall spatial dynamics are weakly constrained by the crystal symmetry of the orthorhombic substrate but exhibit nonlinear dynamics more commonly associated with disordered nematic systems. This work was supported by the Eugene P. Wigner Fellowship program at Oak Ridge National Laboratory, a U.S. Department of Energy facility.

Broken detailed balance and non-equilibrium dynamics in living systems: a review

NASA Astrophysics Data System (ADS)

Gnesotto, F. S.; Mura, F.; Gladrow, J.; Broedersz, C. P.

2018-06-01

Living systems operate far from thermodynamic equilibrium. Enzymatic activity can induce broken detailed balance at the molecular scale. This molecular scale breaking of detailed balance is crucial to achieve biological functions such as high-fidelity transcription and translation, sensing, adaptation, biochemical patterning, and force generation. While biological systems such as motor enzymes violate detailed balance at the molecular scale, it remains unclear how non-equilibrium dynamics manifests at the mesoscale in systems that are driven through the collective activity of many motors. Indeed, in several cellular systems the presence of non-equilibrium dynamics is not always evident at large scales. For example, in the cytoskeleton or in chromosomes one can observe stationary stochastic processes that appear at first glance thermally driven. This raises the question how non-equilibrium fluctuations can be discerned from thermal noise. We discuss approaches that have recently been developed to address this question, including methods based on measuring the extent to which the system violates the fluctuation-dissipation theorem. We also review applications of this approach to reconstituted cytoskeletal networks, the cytoplasm of living cells, and cell membranes. Furthermore, we discuss a more recent approach to detect actively driven dynamics, which is based on inferring broken detailed balance. This constitutes a non-invasive method that uses time-lapse microscopy data, and can be applied to a broad range of systems in cells and tissue. We discuss the ideas underlying this method and its application to several examples including flagella, primary cilia, and cytoskeletal networks. Finally, we briefly discuss recent developments in stochastic thermodynamics and non-equilibrium statistical mechanics, which offer new perspectives to understand the physics of living systems.

Broken detailed balance and non-equilibrium dynamics in living systems: a review.

PubMed

Gnesotto, F S; Mura, F; Gladrow, J; Broedersz, C P

2018-06-01

Living systems operate far from thermodynamic equilibrium. Enzymatic activity can induce broken detailed balance at the molecular scale. This molecular scale breaking of detailed balance is crucial to achieve biological functions such as high-fidelity transcription and translation, sensing, adaptation, biochemical patterning, and force generation. While biological systems such as motor enzymes violate detailed balance at the molecular scale, it remains unclear how non-equilibrium dynamics manifests at the mesoscale in systems that are driven through the collective activity of many motors. Indeed, in several cellular systems the presence of non-equilibrium dynamics is not always evident at large scales. For example, in the cytoskeleton or in chromosomes one can observe stationary stochastic processes that appear at first glance thermally driven. This raises the question how non-equilibrium fluctuations can be discerned from thermal noise. We discuss approaches that have recently been developed to address this question, including methods based on measuring the extent to which the system violates the fluctuation-dissipation theorem. We also review applications of this approach to reconstituted cytoskeletal networks, the cytoplasm of living cells, and cell membranes. Furthermore, we discuss a more recent approach to detect actively driven dynamics, which is based on inferring broken detailed balance. This constitutes a non-invasive method that uses time-lapse microscopy data, and can be applied to a broad range of systems in cells and tissue. We discuss the ideas underlying this method and its application to several examples including flagella, primary cilia, and cytoskeletal networks. Finally, we briefly discuss recent developments in stochastic thermodynamics and non-equilibrium statistical mechanics, which offer new perspectives to understand the physics of living systems.

Event- and Time-Driven Techniques Using Parallel CPU-GPU Co-processing for Spiking Neural Networks

PubMed Central

Naveros, Francisco; Garrido, Jesus A.; Carrillo, Richard R.; Ros, Eduardo; Luque, Niceto R.

2017-01-01

Modeling and simulating the neural structures which make up our central neural system is instrumental for deciphering the computational neural cues beneath. Higher levels of biological plausibility usually impose higher levels of complexity in mathematical modeling, from neural to behavioral levels. This paper focuses on overcoming the simulation problems (accuracy and performance) derived from using higher levels of mathematical complexity at a neural level. This study proposes different techniques for simulating neural models that hold incremental levels of mathematical complexity: leaky integrate-and-fire (LIF), adaptive exponential integrate-and-fire (AdEx), and Hodgkin-Huxley (HH) neural models (ranged from low to high neural complexity). The studied techniques are classified into two main families depending on how the neural-model dynamic evaluation is computed: the event-driven or the time-driven families. Whilst event-driven techniques pre-compile and store the neural dynamics within look-up tables, time-driven techniques compute the neural dynamics iteratively during the simulation time. We propose two modifications for the event-driven family: a look-up table recombination to better cope with the incremental neural complexity together with a better handling of the synchronous input activity. Regarding the time-driven family, we propose a modification in computing the neural dynamics: the bi-fixed-step integration method. This method automatically adjusts the simulation step size to better cope with the stiffness of the neural model dynamics running in CPU platforms. One version of this method is also implemented for hybrid CPU-GPU platforms. Finally, we analyze how the performance and accuracy of these modifications evolve with increasing levels of neural complexity. We also demonstrate how the proposed modifications which constitute the main contribution of this study systematically outperform the traditional event- and time-driven techniques under increasing levels of neural complexity. PMID:28223930

The dynamics of information-driven coordination phenomena: A transfer entropy analysis

PubMed Central

Borge-Holthoefer, Javier; Perra, Nicola; Gonçalves, Bruno; González-Bailón, Sandra; Arenas, Alex; Moreno, Yamir; Vespignani, Alessandro

2016-01-01

Data from social media provide unprecedented opportunities to investigate the processes that govern the dynamics of collective social phenomena. We consider an information theoretical approach to define and measure the temporal and structural signatures typical of collective social events as they arise and gain prominence. We use the symbolic transfer entropy analysis of microblogging time series to extract directed networks of influence among geolocalized subunits in social systems. This methodology captures the emergence of system-level dynamics close to the onset of socially relevant collective phenomena. The framework is validated against a detailed empirical analysis of five case studies. In particular, we identify a change in the characteristic time scale of the information transfer that flags the onset of information-driven collective phenomena. Furthermore, our approach identifies an order-disorder transition in the directed network of influence between social subunits. In the absence of clear exogenous driving, social collective phenomena can be represented as endogenously driven structural transitions of the information transfer network. This study provides results that can help define models and predictive algorithms for the analysis of societal events based on open source data. PMID:27051875

The dynamics of information-driven coordination phenomena: A transfer entropy analysis.

PubMed

Borge-Holthoefer, Javier; Perra, Nicola; Gonçalves, Bruno; González-Bailón, Sandra; Arenas, Alex; Moreno, Yamir; Vespignani, Alessandro

2016-04-01

Data from social media provide unprecedented opportunities to investigate the processes that govern the dynamics of collective social phenomena. We consider an information theoretical approach to define and measure the temporal and structural signatures typical of collective social events as they arise and gain prominence. We use the symbolic transfer entropy analysis of microblogging time series to extract directed networks of influence among geolocalized subunits in social systems. This methodology captures the emergence of system-level dynamics close to the onset of socially relevant collective phenomena. The framework is validated against a detailed empirical analysis of five case studies. In particular, we identify a change in the characteristic time scale of the information transfer that flags the onset of information-driven collective phenomena. Furthermore, our approach identifies an order-disorder transition in the directed network of influence between social subunits. In the absence of clear exogenous driving, social collective phenomena can be represented as endogenously driven structural transitions of the information transfer network. This study provides results that can help define models and predictive algorithms for the analysis of societal events based on open source data.

Simulating large-scale pedestrian movement using CA and event driven model: Methodology and case study

NASA Astrophysics Data System (ADS)

Li, Jun; Fu, Siyao; He, Haibo; Jia, Hongfei; Li, Yanzhong; Guo, Yi

2015-11-01

Large-scale regional evacuation is an important part of national security emergency response plan. Large commercial shopping area, as the typical service system, its emergency evacuation is one of the hot research topics. A systematic methodology based on Cellular Automata with the Dynamic Floor Field and event driven model has been proposed, and the methodology has been examined within context of a case study involving the evacuation within a commercial shopping mall. Pedestrians walking is based on Cellular Automata and event driven model. In this paper, the event driven model is adopted to simulate the pedestrian movement patterns, the simulation process is divided into normal situation and emergency evacuation. The model is composed of four layers: environment layer, customer layer, clerk layer and trajectory layer. For the simulation of movement route of pedestrians, the model takes into account purchase intention of customers and density of pedestrians. Based on evacuation model of Cellular Automata with Dynamic Floor Field and event driven model, we can reflect behavior characteristics of customers and clerks at the situations of normal and emergency evacuation. The distribution of individual evacuation time as a function of initial positions and the dynamics of the evacuation process is studied. Our results indicate that the evacuation model using the combination of Cellular Automata with Dynamic Floor Field and event driven scheduling can be used to simulate the evacuation of pedestrian flows in indoor areas with complicated surroundings and to investigate the layout of shopping mall.

On the rates of type Ia supernovae originating from white dwarf collisions in quadruple star systems

NASA Astrophysics Data System (ADS)

Hamers, Adrian S.

2018-04-01

We consider the evolution of stellar hierarchical quadruple systems in the 2+2 (two binaries orbiting each other's barycentre) and 3+1 (triple orbited by a fourth star) configurations. In our simulations, we take into account the effects of secular dynamical evolution, stellar evolution, tidal evolution and encounters with passing stars. We focus on type Ia supernovae (SNe Ia) driven by collisions of carbon-oxygen (CO) white dwarfs (WDs). Such collisions can arise from several channels: (1) collisions due to extremely high eccentricities induced by secular evolution, (2) collisions following a dynamical instability of the system, and (3) collisions driven by semisecular evolution. The systems considered here have initially wide inner orbits, with initial semilatus recti larger than 12 {au}, implying no interaction if the orbits were isolated. However, taking into account dynamical evolution, we find that ≈0.4 (≈0.6) of 2+2 (3+1) systems interact. In particular, Roche Lobe overflow can be triggered possibly in highly eccentric orbits, dynamical instability can ensue due to mass-loss-driven orbital expansion or secular evolution, or a semisecular regime can be entered. We compute the delay-time distributions (DTDs) of collision-induced SNe Ia, and find that they are flatter compared to the observed DTD. Moreover, our combined SNe Ia rates are (3.7± 0.7) × 10^{-6} M_⊙^{-1} and (1.3± 0.2) × 10^{-6} M_⊙^{-1} for 2+2 and 3+1 systems, respectively, three orders of magnitude lower compared to the observed rate, of order 10^{-3} M_⊙^{-1}. The low rates can be ascribed to interactions before the stars evolve to CO WDs. However, our results are lower limits given that we considered a subset of quadruple systems.

On the rates of Type Ia supernovae originating from white dwarf collisions in quadruple star systems

NASA Astrophysics Data System (ADS)

Hamers, Adrian S.

2018-07-01

We consider the evolution of stellar hierarchical quadruple systems in the 2+2 (two binaries orbiting each other's barycentre) and 3+1 (triple orbited by a fourth star) configurations. In our simulations, we take into account the effects of secular dynamical evolution, stellar evolution, tidal evolution, and encounters with passing stars. We focus on Type Ia supernovae (SNe Ia) driven by collisions of carbon-oxygen (CO) white dwarfs (WDs). Such collisions can arise from several channels: (1) collisions due to extremely high eccentricities induced by secular evolution, (2) collisions following a dynamical instability of the system, and (3) collisions driven by semisecular evolution. The systems considered here have initially wide inner orbits, with initial semilatus recti larger than 12 au, implying no interaction if the orbits were isolated. However, taking into account dynamical evolution, we find that ≈0.4 (≈0.6) of 2+2 (3+1) systems interact. In particular, Roche lobe overflow can be triggered possibly in highly eccentric orbits, dynamical instability can ensue due to mass-loss-driven orbital expansion or secular evolution, or a semisecular regime can be entered. We compute the delay-time distributions (DTDs) of collision-induced SNe Ia, and find that they are flatter compared to the observed DTD. Moreover, our combined SNe Ia rates are (3.7± 0.7) × 10^{-6} M_{⊙}^{-1} and (1.3± 0.2) × 10^{-6} M_{⊙}^{-1} for 2+2 and 3+1 systems, respectively, three orders of magnitude lower compared to the observed rate, of the order of 10^{-3} M_{⊙}^{-1}. The low rates can be ascribed to interactions before the stars evolve to CO WDs. However, our results are lower limits given that we considered a subset of quadruple systems.

Initial Results from an Energy-Aware Airborne Dynamic, Data-Driven Application System Performing Sampling in Coherent Boundary-Layer Structures

NASA Astrophysics Data System (ADS)

Frew, E.; Argrow, B. M.; Houston, A. L.; Weiss, C.

2014-12-01

The energy-aware airborne dynamic, data-driven application system (EA-DDDAS) performs persistent sampling in complex atmospheric conditions by exploiting wind energy using the dynamic data-driven application system paradigm. The main challenge for future airborne sampling missions is operation with tight integration of physical and computational resources over wireless communication networks, in complex atmospheric conditions. The physical resources considered here include sensor platforms, particularly mobile Doppler radar and unmanned aircraft, the complex conditions in which they operate, and the region of interest. Autonomous operation requires distributed computational effort connected by layered wireless communication. Onboard decision-making and coordination algorithms can be enhanced by atmospheric models that assimilate input from physics-based models and wind fields derived from multiple sources. These models are generally too complex to be run onboard the aircraft, so they need to be executed in ground vehicles in the field, and connected over broadband or other wireless links back to the field. Finally, the wind field environment drives strong interaction between the computational and physical systems, both as a challenge to autonomous path planning algorithms and as a novel energy source that can be exploited to improve system range and endurance. Implementation details of a complete EA-DDDAS will be provided, along with preliminary flight test results targeting coherent boundary-layer structures.

Machine Learning-based discovery of closures for reduced models of dynamical systems

NASA Astrophysics Data System (ADS)

Pan, Shaowu; Duraisamy, Karthik

2017-11-01

Despite the successful application of machine learning (ML) in fields such as image processing and speech recognition, only a few attempts has been made toward employing ML to represent the dynamics of complex physical systems. Previous attempts mostly focus on parameter calibration or data-driven augmentation of existing models. In this work we present a ML framework to discover closure terms in reduced models of dynamical systems and provide insights into potential problems associated with data-driven modeling. Based on exact closure models for linear system, we propose a general linear closure framework from viewpoint of optimization. The framework is based on trapezoidal approximation of convolution term. Hyperparameters that need to be determined include temporal length of memory effect, number of sampling points, and dimensions of hidden states. To circumvent the explicit specification of memory effect, a general framework inspired from neural networks is also proposed. We conduct both a priori and posteriori evaluations of the resulting model on a number of non-linear dynamical systems. This work was supported in part by AFOSR under the project ``LES Modeling of Non-local effects using Statistical Coarse-graining'' with Dr. Jean-Luc Cambier as the technical monitor.

Resonances in a periodically driven bosonic system.

PubMed

Quelle, Anton; Smith, Cristiane Morais

2017-11-01

Periodically driven systems are a common topic in modern physics. In optical lattices specifically, driving is at the origin of many interesting phenomena. However, energy is not conserved in driven systems, and under periodic driving, heating of a system is a real concern. In an effort to better understand this phenomenon, the heating of single-band systems has been studied, with a focus on disorder- and interaction-induced effects, such as many-body localization. Nevertheless, driven systems occur in a much wider context than this, leaving room for further research. Here, we fill this gap by studying a noninteracting model, characterized by discrete, periodically spaced energy levels that are unbounded from above. We couple these energy levels resonantly through a periodic drive, and discuss the heating dynamics of this system as a function of the driving protocol. In this way, we show that a combination of stimulated emission and absorption causes the presence of resonant stable states. This will serve to elucidate the conditions under which resonant driving causes heating in quantum systems.

Resonances in a periodically driven bosonic system

NASA Astrophysics Data System (ADS)

Quelle, Anton; Smith, Cristiane Morais

2017-11-01

Periodically driven systems are a common topic in modern physics. In optical lattices specifically, driving is at the origin of many interesting phenomena. However, energy is not conserved in driven systems, and under periodic driving, heating of a system is a real concern. In an effort to better understand this phenomenon, the heating of single-band systems has been studied, with a focus on disorder- and interaction-induced effects, such as many-body localization. Nevertheless, driven systems occur in a much wider context than this, leaving room for further research. Here, we fill this gap by studying a noninteracting model, characterized by discrete, periodically spaced energy levels that are unbounded from above. We couple these energy levels resonantly through a periodic drive, and discuss the heating dynamics of this system as a function of the driving protocol. In this way, we show that a combination of stimulated emission and absorption causes the presence of resonant stable states. This will serve to elucidate the conditions under which resonant driving causes heating in quantum systems.

Digital Suicide Prevention: Can Technology Become a Game-changer?

PubMed Central

Sahin, Ned; Kalali, Amir

2016-01-01

Suicide continues to be a leading cause of death and has been recognized as a significant public health issue. Rapid advances in data science can provide us with useful tools for suicide prevention, and help to dynamically assess suicide risk in quantitative data-driven ways. In this article, the authors highlight the most current international research in digital suicide prevention, including the use of machine learning, smartphone applications, and wearable sensor driven systems. The authors also discuss future opportunities for digital suicide prevention, and propose a novel Sensor-driven Mental State Assessment System. PMID:27800282

Multi-source micro-friction identification for a class of cable-driven robots with passive backbone

NASA Astrophysics Data System (ADS)

Tjahjowidodo, Tegoeh; Zhu, Ke; Dailey, Wayne; Burdet, Etienne; Campolo, Domenico

2016-12-01

This paper analyses the dynamics of cable-driven robots with a passive backbone and develops techniques for their dynamic identification, which are tested on the H-Man, a planar cabled differential transmission robot for haptic interaction. The mechanism is optimized for human-robot interaction by accounting for the cost-benefit-ratio of the system, specifically by eliminating the necessity of an external force sensor to reduce the overall cost. As a consequence, this requires an effective dynamic model for accurate force feedback applications which include friction behavior in the system. We first consider the significance of friction in both the actuator and backbone spaces. Subsequently, we study the required complexity of the stiction model for the application. Different models representing different levels of complexity are investigated, ranging from the conventional approach of Coulomb to an advanced model which includes hysteresis. The results demonstrate each model's ability to capture the dynamic behavior of the system. In general, it is concluded that there is a trade-off between model accuracy and the model cost.

Emergent dynamic structures and statistical law in spherical lattice gas automata.

PubMed

Yao, Zhenwei

2017-12-01

Various lattice gas automata have been proposed in the past decades to simulate physics and address a host of problems on collective dynamics arising in diverse fields. In this work, we employ the lattice gas model defined on the sphere to investigate the curvature-driven dynamic structures and analyze the statistical behaviors in equilibrium. Under the simple propagation and collision rules, we show that the uniform collective movement of the particles on the sphere is geometrically frustrated, leading to several nonequilibrium dynamic structures not found in the planar lattice, such as the emergent bubble and vortex structures. With the accumulation of the collision effect, the system ultimately reaches equilibrium in the sense that the distribution of the coarse-grained speed approaches the two-dimensional Maxwell-Boltzmann distribution despite the population fluctuations in the coarse-grained cells. The emergent regularity in the statistical behavior of the system is rationalized by mapping our system to a generalized random walk model. This work demonstrates the capability of the spherical lattice gas automaton in revealing the lattice-guided dynamic structures and simulating the equilibrium physics. It suggests the promising possibility of using lattice gas automata defined on various curved surfaces to explore geometrically driven nonequilibrium physics.

Emergent dynamic structures and statistical law in spherical lattice gas automata

NASA Astrophysics Data System (ADS)

Yao, Zhenwei

2017-12-01

Various lattice gas automata have been proposed in the past decades to simulate physics and address a host of problems on collective dynamics arising in diverse fields. In this work, we employ the lattice gas model defined on the sphere to investigate the curvature-driven dynamic structures and analyze the statistical behaviors in equilibrium. Under the simple propagation and collision rules, we show that the uniform collective movement of the particles on the sphere is geometrically frustrated, leading to several nonequilibrium dynamic structures not found in the planar lattice, such as the emergent bubble and vortex structures. With the accumulation of the collision effect, the system ultimately reaches equilibrium in the sense that the distribution of the coarse-grained speed approaches the two-dimensional Maxwell-Boltzmann distribution despite the population fluctuations in the coarse-grained cells. The emergent regularity in the statistical behavior of the system is rationalized by mapping our system to a generalized random walk model. This work demonstrates the capability of the spherical lattice gas automaton in revealing the lattice-guided dynamic structures and simulating the equilibrium physics. It suggests the promising possibility of using lattice gas automata defined on various curved surfaces to explore geometrically driven nonequilibrium physics.

A defect-driven diagnostic method for machine tool spindles

PubMed Central

Vogl, Gregory W.; Donmez, M. Alkan

2016-01-01

Simple vibration-based metrics are, in many cases, insufficient to diagnose machine tool spindle condition. These metrics couple defect-based motion with spindle dynamics; diagnostics should be defect-driven. A new method and spindle condition estimation device (SCED) were developed to acquire data and to separate system dynamics from defect geometry. Based on this method, a spindle condition metric relying only on defect geometry is proposed. Application of the SCED on various milling and turning spindles shows that the new approach is robust for diagnosing the machine tool spindle condition. PMID:28065985

On Mixed Data and Event Driven Design for Adaptive-Critic-Based Nonlinear $H_{\\infty}$ Control.

PubMed

Wang, Ding; Mu, Chaoxu; Liu, Derong; Ma, Hongwen

2018-04-01

In this paper, based on the adaptive critic learning technique, the control for a class of unknown nonlinear dynamic systems is investigated by adopting a mixed data and event driven design approach. The nonlinear control problem is formulated as a two-player zero-sum differential game and the adaptive critic method is employed to cope with the data-based optimization. The novelty lies in that the data driven learning identifier is combined with the event driven design formulation, in order to develop the adaptive critic controller, thereby accomplishing the nonlinear control. The event driven optimal control law and the time driven worst case disturbance law are approximated by constructing and tuning a critic neural network. Applying the event driven feedback control, the closed-loop system is built with stability analysis. Simulation studies are conducted to verify the theoretical results and illustrate the control performance. It is significant to observe that the present research provides a new avenue of integrating data-based control and event-triggering mechanism into establishing advanced adaptive critic systems.

Information-theoretic model selection for optimal prediction of stochastic dynamical systems from data

NASA Astrophysics Data System (ADS)

Darmon, David

2018-03-01

In the absence of mechanistic or phenomenological models of real-world systems, data-driven models become necessary. The discovery of various embedding theorems in the 1980s and 1990s motivated a powerful set of tools for analyzing deterministic dynamical systems via delay-coordinate embeddings of observations of their component states. However, in many branches of science, the condition of operational determinism is not satisfied, and stochastic models must be brought to bear. For such stochastic models, the tool set developed for delay-coordinate embedding is no longer appropriate, and a new toolkit must be developed. We present an information-theoretic criterion, the negative log-predictive likelihood, for selecting the embedding dimension for a predictively optimal data-driven model of a stochastic dynamical system. We develop a nonparametric estimator for the negative log-predictive likelihood and compare its performance to a recently proposed criterion based on active information storage. Finally, we show how the output of the model selection procedure can be used to compare candidate predictors for a stochastic system to an information-theoretic lower bound.

Light-driven dynamic Archimedes spirals and periodic oscillatory patterns of topological solitons in anisotropic soft matter

DOE PAGES

Martinez, Angel; Smalyukh, Ivan I.

2015-02-12

Oscillatory and excitable systems very commonly exhibit formation of dynamic non-equilibrium patterns. For example, rotating spiral patterns are observed in biological, chemical, and physical systems ranging from organization of slime mold cells to Belousov-Zhabotinsky reactions, and to crystal growth from nuclei with screw dislocations. Here we describe spontaneous formation of spiral waves and a large variety of other dynamic patterns in anisotropic soft matter driven by low-intensity light. The unstructured ambient or microscope light illumination of thin liquid crystal films in contact with a self-assembled azobenzene monolayer causes spontaneous formation, rich spatial organization, and dynamics of twisted domains and topologicalmore » solitons accompanied by the dynamic patterning of azobenzene group orientations within the monolayer. Linearly polarized incident light interacts with the twisted liquid crystalline domains, mimicking their dynamics and yielding patterns in the polarization state of transmitted light, which can be transformed to similar dynamic patterns in its intensity and interference color. This shows that the delicate light-soft-matter interaction can yield complex self-patterning of both. Finally, we uncover underpinning physical mechanisms and discuss potential uses.« less

Entanglement replication in driven dissipative many-body systems.

PubMed

Zippilli, S; Paternostro, M; Adesso, G; Illuminati, F

2013-01-25

We study the dissipative dynamics of two independent arrays of many-body systems, locally driven by a common entangled field. We show that in the steady state the entanglement of the driving field is reproduced in an arbitrarily large series of inter-array entangled pairs over all distances. Local nonclassical driving thus realizes a scale-free entanglement replication and long-distance entanglement distribution mechanism that has immediate bearing on the implementation of quantum communication networks.

ISM simulations: an overview of models

NASA Astrophysics Data System (ADS)

de Avillez, M. A.; Breitschwerdt, D.; Asgekar, A.; Spitoni, E.

2015-03-01

Until recently the dynamical evolution of the interstellar medium (ISM) was simulated using collisional ionization equilibrium (CIE) conditions. However, the ISM is a dynamical system, in which the plasma is naturally driven out of equilibrium due to atomic and dynamic processes operating on different timescales. A step forward in the field comprises a multi-fluid approach taking into account the joint thermal and dynamical evolutions of the ISM gas.

Double-well dynamics of noise-driven control activation in human intermittent control: the case of stick balancing.

PubMed

Zgonnikov, Arkady; Lubashevsky, Ihor

2015-11-01

When facing a task of balancing a dynamic system near an unstable equilibrium, humans often adopt intermittent control strategy: Instead of continuously controlling the system, they repeatedly switch the control on and off. Paradigmatic example of such a task is stick balancing. Despite the simplicity of the task itself, the complexity of human intermittent control dynamics in stick balancing still puzzles researchers in motor control. Here we attempt to model one of the key mechanisms of human intermittent control, control activation, using as an example the task of overdamped stick balancing. In doing so, we focus on the concept of noise-driven activation, a more general alternative to the conventional threshold-driven activation. We describe control activation as a random walk in an energy potential, which changes in response to the state of the controlled system. By way of numerical simulations, we show that the developed model captures the core properties of human control activation observed previously in the experiments on overdamped stick balancing. Our results demonstrate that the double-well potential model provides tractable mathematical description of human control activation at least in the considered task and suggest that the adopted approach can potentially aid in understanding human intermittent control in more complex processes.

A Model Driven Question-Answering System for a CAI Environment. Final Report (July 1970 to May 1972).

ERIC Educational Resources Information Center

Brown, John S.; And Others

A question answering system which permits a computer-assisted instruction (CAI) student greater initiative in the variety of questions he can ask is described. A method is presented to represent the dynamic processes of a subject matter area by augmented finite state automata, which permits efficient inferencing about dynamic processes and…

Semiconductor lasers driven by self-sustained chaotic electronic oscillators and applications to optical chaos cryptography.

PubMed

Kingni, Sifeu Takougang; Mbé, Jimmi Hervé Talla; Woafo, Paul

2012-09-01

In this work, we numerically study the dynamics of vertical cavity surface emitting laser (VCSEL) firstly when it is driven by Chua's oscillator, secondly in case where it is driven by a broad frequency spectral bandwidth chaotic oscillator developed by Nana et al. [Commun. Nonlinear Sci. Numer. Simul. 14, 2266 (2009)]. We demonstrated that the VCSEL generated robust chaotic dynamics compared to the ones found in VCSEL subject to a sinusoidally modulated current and therefore it is more suitable for chaos encryption techniques. The synchronization characteristics and the communication performances of unidirectional coupled VCSEL driven by the broad frequency spectral bandwidth chaotic oscillators are investigated numerically. The results show that high-quality synchronization and transmission of messages can be realized for suitable system parameters. Chaos shift keying method is successfully applied to encrypt a message at a high bitrate.

Grain size distribution in sheared polycrystals

NASA Astrophysics Data System (ADS)

Sarkar, Tanmoy; Biswas, Santidan; Chaudhuri, Pinaki; Sain, Anirban

2017-12-01

Plastic deformation in solids induced by external stresses is of both fundamental and practical interest. Using both phase field crystal modeling and molecular dynamics simulations, we study the shear response of monocomponent polycrystalline solids. We subject mesocale polycrystalline samples to constant strain rates in a planar Couette flow geometry for studying its plastic flow, in particular its grain deformation dynamics. As opposed to equilibrium solids where grain dynamics is mainly driven by thermal diffusion, external stress/strain induce a much higher level of grain deformation activity in the form of grain rotation, coalescence, and breakage, mediated by dislocations. Despite this, the grain size distribution of this driven system shows only a weak power-law correction to its equilibrium log-normal behavior. We interpret the grain reorganization dynamics using a stochastic model.

A Null Space Control of Two Wheels Driven Mobile Manipulator Using Passivity Theory

NASA Astrophysics Data System (ADS)

Shibata, Tsuyoshi; Murakami, Toshiyuki

This paper describes a control strategy of null space motion of a two wheels driven mobile manipulator. Recently, robot is utilized in various industrial fields and it is preferable for the robot manipulator to have multiple degrees of freedom motion. Several studies of kinematics for null space motion have been proposed. However stability analysis of null space motion is not enough. Furthermore, these approaches apply to stable systems, but they do not apply unstable systems. Then, in this research, base of manipulator equips with two wheels driven mobile robot. This robot is called two wheels driven mobile manipulator, which becomes unstable system. In the proposed approach, a control design of null space uses passivity based stabilizing. A proposed controller is decided so that closed-loop system of robot dynamics satisfies passivity. This is passivity based control. Then, control strategy is that stabilizing of the robot system applies to work space observer based approach and null space control while keeping end-effector position. The validity of the proposed approach is verified by simulations and experiments of two wheels driven mobile manipulator.

A smartphone-based prototype system for incident/work zone management driven by crowd-sourced data.

DOT National Transportation Integrated Search

2015-02-01

This project develops a smartphone-based prototype system that supplements the 511 system to improve its dynamic traffic : routing service to state highway users under non-recurrent congestion. This system will save considerable time to provide cruci...

Linear dynamical modes as new variables for data-driven ENSO forecast

NASA Astrophysics Data System (ADS)

Gavrilov, Andrey; Seleznev, Aleksei; Mukhin, Dmitry; Loskutov, Evgeny; Feigin, Alexander; Kurths, Juergen

2018-05-01

A new data-driven model for analysis and prediction of spatially distributed time series is proposed. The model is based on a linear dynamical mode (LDM) decomposition of the observed data which is derived from a recently developed nonlinear dimensionality reduction approach. The key point of this approach is its ability to take into account simple dynamical properties of the observed system by means of revealing the system's dominant time scales. The LDMs are used as new variables for empirical construction of a nonlinear stochastic evolution operator. The method is applied to the sea surface temperature anomaly field in the tropical belt where the El Nino Southern Oscillation (ENSO) is the main mode of variability. The advantage of LDMs versus traditionally used empirical orthogonal function decomposition is demonstrated for this data. Specifically, it is shown that the new model has a competitive ENSO forecast skill in comparison with the other existing ENSO models.

Data-based adjoint and H2 optimal control of the Ginzburg-Landau equation

NASA Astrophysics Data System (ADS)

Banks, Michael; Bodony, Daniel

2017-11-01

Equation-free, reduced-order methods of control are desirable when the governing system of interest is of very high dimension or the control is to be applied to a physical experiment. Two-phase flow optimal control problems, our target application, fit these criteria. Dynamic Mode Decomposition (DMD) is a data-driven method for model reduction that can be used to resolve the dynamics of very high dimensional systems and project the dynamics onto a smaller, more manageable basis. We evaluate the effectiveness of DMD-based forward and adjoint operator estimation when applied to H2 optimal control approaches applied to the linear and nonlinear Ginzburg-Landau equation. Perspectives on applying the data-driven adjoint to two phase flow control will be given. Office of Naval Research (ONR) as part of the Multidisciplinary University Research Initiatives (MURI) Program, under Grant Number N00014-16-1-2617.

Cellular automaton model for molecular traffic jams

NASA Astrophysics Data System (ADS)

Belitsky, V.; Schütz, G. M.

2011-07-01

We consider the time evolution of an exactly solvable cellular automaton with random initial conditions both in the large-scale hydrodynamic limit and on the microscopic level. This model is a version of the totally asymmetric simple exclusion process with sublattice parallel update and thus may serve as a model for studying traffic jams in systems of self-driven particles. We study the emergence of shocks from the microscopic dynamics of the model. In particular, we introduce shock measures whose time evolution we can compute explicitly, both in the thermodynamic limit and for open boundaries where a boundary-induced phase transition driven by the motion of a shock occurs. The motion of the shock, which results from the collective dynamics of the exclusion particles, is a random walk with an internal degree of freedom that determines the jump direction. This type of hopping dynamics is reminiscent of some transport phenomena in biological systems.

Cooperative inter- and intra-layer lattice dynamics of photoexcited multi-walled carbon nanotubes studied by ultrafast electron diffraction.

PubMed

Sun, Shuaishuai; Li, Zhongwen; Li, Zi-An; Xiao, Ruijuan; Zhang, Ming; Tian, Huanfang; Yang, Huaixin; Li, Jianqi

2018-04-26

Optical tuning and probing ultrafast structural response of nanomaterials driven by electronic excitation constitute a challenging but promising approach for understanding microscopic mechanisms and applications in microelectromechanical systems and optoelectrical devices. Here we use pulsed electron diffraction in a transmission electron microscope to investigate laser-induced tubular lattice dynamics of multi-walled carbon nanotubes (MWCNTs) with varying laser fluence and initial specimen temperature. Our photoexcitation experiments demonstrate cooperative and inverse collective atomic motions in intralayer and interlayer directions, whose strengths and rates depend on pump fluence. The electron-driven and thermally driven structural responses with opposite amplitudes cause a crossover between intralayer and interlayer directions. Our ab initio calculations support these findings and reveal that electrons excited from π to π* orbitals in a carbon tube weaken the intralayer bonds while strengthening the interlayer bonds along the radial direction. Moreover, by probing the structural dynamics of MWCNTs at initial temperatures of 300 and 100 K, we uncover the concomitance of thermal and nonthermal dynamical processes and their mutual influence in MWCNTs. Our results illustrate the nature of electron-driven nonthermal process and electron-phonon thermalization in the MWCNTs, and bear implications for the intricate energy conversion and transfer in materials at the nanoscale.

Average dynamics of a finite set of coupled phase oscillators

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dima, Germán C., E-mail: gdima@df.uba.ar; Mindlin, Gabriel B.

2014-06-15

We study the solutions of a dynamical system describing the average activity of an infinitely large set of driven coupled excitable units. We compared their topological organization with that reconstructed from the numerical integration of finite sets. In this way, we present a strategy to establish the pertinence of approximating the dynamics of finite sets of coupled nonlinear units by the dynamics of its infinitely large surrogate.

Average dynamics of a finite set of coupled phase oscillators

PubMed Central

Dima, Germán C.; Mindlin, Gabriel B.

2014-01-01

We study the solutions of a dynamical system describing the average activity of an infinitely large set of driven coupled excitable units. We compared their topological organization with that reconstructed from the numerical integration of finite sets. In this way, we present a strategy to establish the pertinence of approximating the dynamics of finite sets of coupled nonlinear units by the dynamics of its infinitely large surrogate. PMID:24985426

Average dynamics of a finite set of coupled phase oscillators.

PubMed

Dima, Germán C; Mindlin, Gabriel B

2014-06-01

We study the solutions of a dynamical system describing the average activity of an infinitely large set of driven coupled excitable units. We compared their topological organization with that reconstructed from the numerical integration of finite sets. In this way, we present a strategy to establish the pertinence of approximating the dynamics of finite sets of coupled nonlinear units by the dynamics of its infinitely large surrogate.

Theory-Driven Models for Correcting Fight or Flight Imbalance in Gulf War Illness

DTIC Science & Technology

2011-09-01

testing on software • Performed static and dynamic analysis on safety code Research Interests To understand how the nervous system operates, how...dynamics of these systems to reset control of the HPA-immune axis to normal. We have completed the negotiation of sub-awards to the CFIDS Association...We propose that severe physical or psychological insult to the endocrine and immune systems can displace these from a normal regulatory equilibrium

Intermittency and dynamical Lee-Yang zeros of open quantum systems.

PubMed

Hickey, James M; Flindt, Christian; Garrahan, Juan P

2014-12-01

We use high-order cumulants to investigate the Lee-Yang zeros of generating functions of dynamical observables in open quantum systems. At long times the generating functions take on a large-deviation form with singularities of the associated cumulant generating functions-or dynamical free energies-signifying phase transitions in the ensemble of dynamical trajectories. We consider a driven three-level system as well as the dissipative Ising model. Both systems exhibit dynamical intermittency in the statistics of quantum jumps. From the short-time behavior of the dynamical Lee-Yang zeros, we identify critical values of the counting field which we attribute to the observed intermittency and dynamical phase coexistence. Furthermore, for the dissipative Ising model we construct a trajectory phase diagram and estimate the value of the transverse field where the stationary state changes from being ferromagnetic (inactive) to paramagnetic (active).

Real-time monitoring of Lévy flights in a single quantum system

NASA Astrophysics Data System (ADS)

Issler, M.; Höller, J.; Imamoǧlu, A.

2016-02-01

Lévy flights are random walks where the dynamics is dominated by rare events. Even though they have been studied in vastly different physical systems, their observation in a single quantum system has remained elusive. Here we analyze a periodically driven open central spin system and demonstrate theoretically that the dynamics of the spin environment exhibits Lévy flights. For the particular realization in a single-electron charged quantum dot driven by periodic resonant laser pulses, we use Monte Carlo simulations to confirm that the long waiting times between successive nuclear spin-flip events are governed by a power-law distribution; the corresponding exponent η =-3 /2 can be directly measured in real time by observing the waiting time distribution of successive photon emission events. Remarkably, the dominant intrinsic limitation of the scheme arising from nuclear quadrupole coupling can be minimized by adjusting the magnetic field or by implementing spin echo.

Recurrence plots revisited

NASA Astrophysics Data System (ADS)

Casdagli, M. C.

1997-09-01

We show that recurrence plots (RPs) give detailed characterizations of time series generated by dynamical systems driven by slowly varying external forces. For deterministic systems we show that RPs of the time series can be used to reconstruct the RP of the driving force if it varies sufficiently slowly. If the driving force is one-dimensional, its functional form can then be inferred up to an invertible coordinate transformation. The same results hold for stochastic systems if the RP of the time series is suitably averaged and transformed. These results are used to investigate the nonlinear prediction of time series generated by dynamical systems driven by slowly varying external forces. We also consider the problem of detecting a small change in the driving force, and propose a surrogate data technique for assessing statistical significance. Numerically simulated time series and a time series of respiration rates recorded from a subject with sleep apnea are used as illustrative examples.

Reliable fuzzy H∞ control for active suspension of in-wheel motor driven electric vehicles with dynamic damping

NASA Astrophysics Data System (ADS)

Shao, Xinxin; Naghdy, Fazel; Du, Haiping

2017-03-01

A fault-tolerant fuzzy H∞ control design approach for active suspension of in-wheel motor driven electric vehicles in the presence of sprung mass variation, actuator faults and control input constraints is proposed. The controller is designed based on the quarter-car active suspension model with a dynamic-damping-in-wheel-motor-driven-system, in which the suspended motor is operated as a dynamic absorber. The Takagi-Sugeno (T-S) fuzzy model is used to model this suspension with possible sprung mass variation. The parallel-distributed compensation (PDC) scheme is deployed to derive a fault-tolerant fuzzy controller for the T-S fuzzy suspension model. In order to reduce the motor wear caused by the dynamic force transmitted to the in-wheel motor, the dynamic force is taken as an additional controlled output besides the traditional optimization objectives such as sprung mass acceleration, suspension deflection and actuator saturation. The H∞ performance of the proposed controller is derived as linear matrix inequalities (LMIs) comprising three equality constraints which are solved efficiently by means of MATLAB LMI Toolbox. The proposed controller is applied to an electric vehicle suspension and its effectiveness is demonstrated through computer simulation.

Driven evolution of a constitutional dynamic library of molecular helices toward the selective generation of [2 x 2] gridlike arrays under the pressure of metal ion coordination.

PubMed

Giuseppone, Nicolas; Schmitt, Jean-Louis; Lehn, Jean-Marie

2006-12-27

Constitutional dynamics, self-assembly, and helical-folding control are brought together in the efficient Sc(OTf)3/microwave-catalyzed transimination of helical oligohydrazone strands, yielding highly diverse dynamic libraries of interconverting constituents through assembly, dissociation, and exchange of components. The transimination-type mechanism of the ScIII-promoted exchange, as well as its regioselectivity, occurring only at the extremities of the helical strands, allow one to perform directional terminal polymerization/depolymerization processes when starting with dissymmetric strands. A particular library is subsequently brought to express quantitatively [2 x 2] gridlike metallosupramolecular arrays in the presence of ZnII ions by component recombination generating the correct ligand from the dynamic set of interconverting strands. This behavior represents a process of driven evolution of a constitutional dynamic chemical system under the pressure (coordination interaction) of an external effector (metal ions).

Data-Driven Modeling of Complex Systems by means of a Dynamical ANN

NASA Astrophysics Data System (ADS)

Seleznev, A.; Mukhin, D.; Gavrilov, A.; Loskutov, E.; Feigin, A.

2017-12-01

The data-driven methods for modeling and prognosis of complex dynamical systems become more and more popular in various fields due to growth of high-resolution data. We distinguish the two basic steps in such an approach: (i) determining the phase subspace of the system, or embedding, from available time series and (ii) constructing an evolution operator acting in this reduced subspace. In this work we suggest a novel approach combining these two steps by means of construction of an artificial neural network (ANN) with special topology. The proposed ANN-based model, on the one hand, projects the data onto a low-dimensional manifold, and, on the other hand, models a dynamical system on this manifold. Actually, this is a recurrent multilayer ANN which has internal dynamics and capable of generating time series. Very important point of the proposed methodology is the optimization of the model allowing us to avoid overfitting: we use Bayesian criterion to optimize the ANN structure and estimate both the degree of evolution operator nonlinearity and the complexity of nonlinear manifold which the data are projected on. The proposed modeling technique will be applied to the analysis of high-dimensional dynamical systems: Lorenz'96 model of atmospheric turbulence, producing high-dimensional space-time chaos, and quasi-geostrophic three-layer model of the Earth's atmosphere with the natural orography, describing the dynamics of synoptical vortexes as well as mesoscale blocking systems. The possibility of application of the proposed methodology to analyze real measured data is also discussed. The study was supported by the Russian Science Foundation (grant #16-12-10198).

Functionally dissociable influences on learning rate in a dynamic environment

PubMed Central

McGuire, Joseph T.; Nassar, Matthew R.; Gold, Joshua I.; Kable, Joseph W.

2015-01-01

Summary Maintaining accurate beliefs in a changing environment requires dynamically adapting the rate at which one learns from new experiences. Beliefs should be stable in the face of noisy data, but malleable in periods of change or uncertainty. Here we used computational modeling, psychophysics and fMRI to show that adaptive learning is not a unitary phenomenon in the brain. Rather, it can be decomposed into three computationally and neuroanatomically distinct factors that were evident in human subjects performing a spatial-prediction task: (1) surprise-driven belief updating, related to BOLD activity in visual cortex; (2) uncertainty-driven belief updating, related to anterior prefrontal and parietal activity; and (3) reward-driven belief updating, a context-inappropriate behavioral tendency related to activity in ventral striatum. These distinct factors converged in a core system governing adaptive learning. This system, which included dorsomedial frontal cortex, responded to all three factors and predicted belief updating both across trials and across individuals. PMID:25459409

Transition Manifolds of Complex Metastable Systems: Theory and Data-Driven Computation of Effective Dynamics.

PubMed

Bittracher, Andreas; Koltai, Péter; Klus, Stefan; Banisch, Ralf; Dellnitz, Michael; Schütte, Christof

2018-01-01

We consider complex dynamical systems showing metastable behavior, but no local separation of fast and slow time scales. The article raises the question of whether such systems exhibit a low-dimensional manifold supporting its effective dynamics. For answering this question, we aim at finding nonlinear coordinates, called reaction coordinates, such that the projection of the dynamics onto these coordinates preserves the dominant time scales of the dynamics. We show that, based on a specific reducibility property, the existence of good low-dimensional reaction coordinates preserving the dominant time scales is guaranteed. Based on this theoretical framework, we develop and test a novel numerical approach for computing good reaction coordinates. The proposed algorithmic approach is fully local and thus not prone to the curse of dimension with respect to the state space of the dynamics. Hence, it is a promising method for data-based model reduction of complex dynamical systems such as molecular dynamics.

Coupled dynamic systems and Le Chatelier's principle in noise control

NASA Astrophysics Data System (ADS)

Maidanik, G.; Becker, K. J.

2004-05-01

Investigation of coupling an externally driven dynamic system-a master dynamic system-to a passive one-an adjunct dynamic system-reveals that the response of the adjunct dynamic system affects the precoupled response of the master dynamic system. The responses, in the two dynamic systems when coupled, are estimated by the stored energies (Es) and (E0), respectively. Since the adjunct dynamic system, prior to coupling, was with zero (0) stored energy, E0s=0, the precoupled stored energy (E00) in the master dynamic system is expected to be reduced to (E0) when coupling is instituted; i.e., one expects E0

Ecological and evolutionary dynamics of interconnectedness and modularity

PubMed Central

Nordbotten, Jan M.; Levin, Simon A.; Szathmáry, Eörs; Stenseth, Nils C.

2018-01-01

In this contribution, we develop a theoretical framework for linking microprocesses (i.e., population dynamics and evolution through natural selection) with macrophenomena (such as interconnectedness and modularity within an ecological system). This is achieved by developing a measure of interconnectedness for population distributions defined on a trait space (generalizing the notion of modularity on graphs), in combination with an evolution equation for the population distribution. With this contribution, we provide a platform for understanding under what environmental, ecological, and evolutionary conditions ecosystems evolve toward being more or less modular. A major contribution of this work is that we are able to decompose the overall driver of changes at the macro level (such as interconnectedness) into three components: (i) ecologically driven change, (ii) evolutionarily driven change, and (iii) environmentally driven change. PMID:29311333

A bifurcation giving birth to order in an impulsively driven complex system

NASA Astrophysics Data System (ADS)

Seshadri, Akshay; Sujith, R. I.

2016-08-01

Nonlinear oscillations lie at the heart of numerous complex systems. Impulsive forcing arises naturally in many scenarios, and we endeavour to study nonlinear oscillators subject to such forcing. We model these kicked oscillatory systems as a piecewise smooth dynamical system, whereby their dynamics can be investigated. We investigate the problem of pattern formation in a turbulent combustion system and apply this formalism with the aim of explaining the observed dynamics. We identify that the transition of this system from low amplitude chaotic oscillations to large amplitude periodic oscillations is the result of a discontinuity induced bifurcation. Further, we provide an explanation for the occurrence of intermittent oscillations in the system.

A bifurcation giving birth to order in an impulsively driven complex system

DOE Office of Scientific and Technical Information (OSTI.GOV)

Seshadri, Akshay, E-mail: akshayseshadri@gmail.com; Sujith, R. I., E-mail: sujith@iitm.ac.in

Nonlinear oscillations lie at the heart of numerous complex systems. Impulsive forcing arises naturally in many scenarios, and we endeavour to study nonlinear oscillators subject to such forcing. We model these kicked oscillatory systems as a piecewise smooth dynamical system, whereby their dynamics can be investigated. We investigate the problem of pattern formation in a turbulent combustion system and apply this formalism with the aim of explaining the observed dynamics. We identify that the transition of this system from low amplitude chaotic oscillations to large amplitude periodic oscillations is the result of a discontinuity induced bifurcation. Further, we provide anmore » explanation for the occurrence of intermittent oscillations in the system.« less

Review on the Modeling of Electrostatic MEMS

PubMed Central

Chuang, Wan-Chun; Lee, Hsin-Li; Chang, Pei-Zen; Hu, Yuh-Chung

2010-01-01

Electrostatic-driven microelectromechanical systems devices, in most cases, consist of couplings of such energy domains as electromechanics, optical electricity, thermoelectricity, and electromagnetism. Their nonlinear working state makes their analysis complex and complicated. This article introduces the physical model of pull-in voltage, dynamic characteristic analysis, air damping effect, reliability, numerical modeling method, and application of electrostatic-driven MEMS devices. PMID:22219707

On the Stable Limit Cycle of a Weight-Driven Pendulum Clock

ERIC Educational Resources Information Center

Llibre, J; Teixeira, M. A.

2010-01-01

In a recent paper (Denny 2002 Eur. J. Phys. 23 449-58), entitled "The pendulum clock: a venerable dynamical system", Denny showed that in a first approximation the steady-state motion of a weight-driven pendulum clock is shown to be a stable limit cycle. He placed the problem in a historical context and obtained an approximate solution using the…

Application of Bounded Linear Stability Analysis Method for Metrics-Driven Adaptive Control

NASA Technical Reports Server (NTRS)

Bakhtiari-Nejad, Maryam; Nguyen, Nhan T.; Krishnakumar, Kalmanje

2009-01-01

This paper presents the application of Bounded Linear Stability Analysis (BLSA) method for metrics-driven adaptive control. The bounded linear stability analysis method is used for analyzing stability of adaptive control models, without linearizing the adaptive laws. Metrics-driven adaptive control introduces a notion that adaptation should be driven by some stability metrics to achieve robustness. By the application of bounded linear stability analysis method the adaptive gain is adjusted during the adaptation in order to meet certain phase margin requirements. Analysis of metrics-driven adaptive control is evaluated for a second order system that represents a pitch attitude control of a generic transport aircraft. The analysis shows that the system with the metrics-conforming variable adaptive gain becomes more robust to unmodeled dynamics or time delay. The effect of analysis time-window for BLSA is also evaluated in order to meet the stability margin criteria.

Piecewise adiabatic following in non-Hermitian cycling

NASA Astrophysics Data System (ADS)

Gong, Jiangbin; Wang, Qing-hai

2018-05-01

The time evolution of periodically driven non-Hermitian systems is in general nonunitary but can be stable. It is hence of considerable interest to examine the adiabatic following dynamics in periodically driven non-Hermitian systems. We show in this work the possibility of piecewise adiabatic following interrupted by hopping between instantaneous system eigenstates. This phenomenon is first observed in a computational model and then theoretically explained, using an exactly solvable model, in terms of the Stokes phenomenon. In the latter case, the piecewise adiabatic following is shown to be a genuine critical behavior and the precise phase boundary in the parameter space is located. Interestingly, the critical boundary for piecewise adiabatic following is found to be unrelated to the domain for exceptional points. To characterize the adiabatic following dynamics, we also advocate a simple definition of the Aharonov-Anandan (AA) phase for nonunitary cyclic dynamics, which always yields real AA phases. In the slow driving limit, the AA phase reduces to the Berry phase if adiabatic following persists throughout the driving without hopping, but oscillates violently and does not approach any limit in cases of piecewise adiabatic following. This work exposes the rich features of nonunitary dynamics in cases of slow cycling and should stimulate future applications of nonunitary dynamics.

Hierarchical structure and dynamics of oligocarbonate-functionalized PEG block copolymer gels

NASA Astrophysics Data System (ADS)

Prabhu, Vivek; Wei, Guangmin; Ali, Samim; Venkataraman, Shrinivas; Yang, Yi Yan; Hedrick, James

Hierarchical, self-assembled block copolymers in aqueous solutions provide advanced materials for biomaterial applications. Recent advancements in the synthesis of aliphatic polycarbonates have shown nontraditional micellar and hierarchical structures driven by the supramolecular assembly of the carbonate block functionality that includes cholesterol, vitamin D, and fluorene. This presentation shall describe the supramolecular assembly structure and dynamics observed by static and dynamic light scattering, small-angle neutron scattering and transmission electron microscopy in a model pi-pi stacking driven fluorene system. The combination of real-space and reciprocal space methods to develop appropriate models that quantify the structure from the micelle to transient gel network will be discussed. 1) Biomedical Research Council, Agency for Science, Technology and Research, Singapore, 2) NIST Materials Genome Initiative.

Spatio-temporal organization of dynamics in a two-dimensional periodically driven vortex flow: A Lagrangian flow network perspective.

PubMed

Lindner, Michael; Donner, Reik V

2017-03-01

We study the Lagrangian dynamics of passive tracers in a simple model of a driven two-dimensional vortex resembling real-world geophysical flow patterns. Using a discrete approximation of the system's transfer operator, we construct a directed network that describes the exchange of mass between distinct regions of the flow domain. By studying different measures characterizing flow network connectivity at different time-scales, we are able to identify the location of dynamically invariant structures and regions of maximum dispersion. Specifically, our approach allows us to delimit co-existing flow regimes with different dynamics. To validate our findings, we compare several network characteristics to the well-established finite-time Lyapunov exponents and apply a receiver operating characteristic analysis to identify network measures that are particularly useful for unveiling the skeleton of Lagrangian chaos.

Deterministic representation of chaos with application to turbulence

NASA Technical Reports Server (NTRS)

Zak, M.

1987-01-01

Chaotic motions of nonlinear dynamical systems are decomposed into mean components and fluctuations. The approach is based upon the concept that the fluctuations driven by the instability of the original (unperturbed) motion grow until a new stable state is approached. The Reynolds-type equations written for continuous as well as for finite-degrees-of-freedom dynamical systems are closed by using this stabilization principle. The theory is applied to conservative systems, to strange attractors and to turbulent motions.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Solis, Kyle J.; Martin, James E.

In recent years a rich variety of emergent phenomena have been observed when suspensions of magnetic particles are subjected to alternating magnetic fields. These particle assemblies often exhibit vigorous dynamics due to the injection of energy from the field. These include surface and interface phenomena, such as highly organized, segmented “snakes” that can be induced to swim by structural symmetry breaking, and “asters” and “anti-asters,” particle assemblies that can be manipulated to capture and transport cargo. In bulk suspensions of magnetic platelets subjected to multiaxial alternating fields, advection lattices and even vortex lattices have been created, and a variety ofmore » biomimetic dynamics – serpents, bees and amoebas – have been discovered in magnetic fluids suspended in an immiscible liquid. In this paper several new driven phases are presented, including flying chevrons, dense spinning clusters, filaments, and examples of phase coexistence in driven phases. These observations broaden the growing field of driven magnetic suspensions and present new challenges to those interested in simulating the dynamics of these complex systems.« less

Discovering governing equations from data by sparse identification of nonlinear dynamics

NASA Astrophysics Data System (ADS)

Brunton, Steven

The ability to discover physical laws and governing equations from data is one of humankind's greatest intellectual achievements. A quantitative understanding of dynamic constraints and balances in nature has facilitated rapid development of knowledge and enabled advanced technology, including aircraft, combustion engines, satellites, and electrical power. There are many more critical data-driven problems, such as understanding cognition from neural recordings, inferring patterns in climate, determining stability of financial markets, predicting and suppressing the spread of disease, and controlling turbulence for greener transportation and energy. With abundant data and elusive laws, data-driven discovery of dynamics will continue to play an increasingly important role in these efforts. This work develops a general framework to discover the governing equations underlying a dynamical system simply from data measurements, leveraging advances in sparsity-promoting techniques and machine learning. The resulting models are parsimonious, balancing model complexity with descriptive ability while avoiding overfitting. The only assumption about the structure of the model is that there are only a few important terms that govern the dynamics, so that the equations are sparse in the space of possible functions. This perspective, combining dynamical systems with machine learning and sparse sensing, is explored with the overarching goal of real-time closed-loop feedback control of complex systems. This is joint work with Joshua L. Proctor and J. Nathan Kutz. Video Abstract: https://www.youtube.com/watch?v=gSCa78TIldg

Dynamic trapping near a quantum critical point

NASA Astrophysics Data System (ADS)

Kolodrubetz, Michael; Katz, Emanuel; Polkovnikov, Anatoli

2015-02-01

The study of dynamics in closed quantum systems has been revitalized by the emergence of experimental systems that are well-isolated from their environment. In this paper, we consider the closed-system dynamics of an archetypal model: spins driven across a second-order quantum critical point, which are traditionally described by the Kibble-Zurek mechanism. Imbuing the driving field with Newtonian dynamics, we find that the full closed system exhibits a robust new phenomenon—dynamic critical trapping—in which the system is self-trapped near the critical point due to efficient absorption of field kinetic energy by heating the quantum spins. We quantify limits in which this phenomenon can be observed and generalize these results by developing a Kibble-Zurek scaling theory that incorporates the dynamic field. Our findings can potentially be interesting in the context of early universe physics, where the role of the driving field is played by the inflaton or a modulus field.

Nonequilibrium steady states and resonant tunneling in time-periodically driven systems with interactions

NASA Astrophysics Data System (ADS)

Qin, Tao; Hofstetter, Walter

2018-03-01

Time-periodically driven systems are a versatile toolbox for realizing interesting effective Hamiltonians. Heating, caused by excitations to high-energy states, is a challenge for experiments. While most setups so far address the relatively weakly interacting regime, it is of general interest to study heating in strongly correlated systems. Using Floquet dynamical mean-field theory, we study nonequilibrium steady states (NESS) in the Falicov-Kimball model, with time-periodically driven kinetic energy or interaction. We systematically investigate the nonequilibrium properties of the NESS. For a driven kinetic energy, we show that resonant tunneling, where the interaction is an integer multiple of the driving frequency, plays an important role in the heating. In the strongly correlated regime, we show that this can be well understood using Fermi's golden rule and the Schrieffer-Wolff transformation for a time-periodically driven system. We furthermore demonstrate that resonant tunneling can be used to control the population of Floquet states to achieve "photodoping." For driven interactions introduced by an oscillating magnetic field near a widely adopted Feshbach resonance, we find that the double occupancy is strongly modulated. Our calculations apply to shaken ultracold-atom systems and to solid-state systems in a spatially uniform but time-dependent electric field. They are also closely related to lattice modulation spectroscopy. Our calculations are helpful to understand the latest experiments on strongly correlated Floquet systems.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Klein, Steven Karl; Determan, John C.

Dynamic System Simulation (DSS) models of fissile solution systems have been developed and verified against a variety of historical configurations. DSS techniques have been applied specifically to subcritical accelerator-driven systems using fissile solution fuels of uranium. Initial DSS models were developed in DESIRE, a specialized simulation scripting language. In order to tailor the DSS models to specifically meet needs of system designers they were converted to a Visual Studio implementation, and one of these subsequently to National Instrument’s LabVIEW for human factors engineering and operator training. Specific operational characteristics of subcritical accelerator-driven systems have been examined using a DSS modelmore » tailored to this particular class using fissile fuel.« less

Period doubling in period-one steady states

NASA Astrophysics Data System (ADS)

Wang, Reuben R. W.; Xing, Bo; Carlo, Gabriel G.; Poletti, Dario

2018-02-01

Nonlinear classical dissipative systems present a rich phenomenology in their "route to chaos," including period doubling, i.e., the system evolves with a period which is twice that of the driving. However, typically the attractor of a periodically driven quantum open system evolves with a period which exactly matches that of the driving. Here, we analyze a periodically driven many-body open quantum system whose classical correspondent presents period doubling. We show that by studying the dynamical correlations, it is possible to show the occurrence of period doubling in the quantum (period-one) steady state. We also discuss that such systems are natural candidates for clean and intrinsically robust Floquet time crystals.

Chaos and noise.

PubMed

He, Temple; Habib, Salman

2013-09-01

Simple dynamical systems--with a small number of degrees of freedom--can behave in a complex manner due to the presence of chaos. Such systems are most often (idealized) limiting cases of more realistic situations. Isolating a small number of dynamical degrees of freedom in a realistically coupled system generically yields reduced equations with terms that can have a stochastic interpretation. In situations where both noise and chaos can potentially exist, it is not immediately obvious how Lyapunov exponents, key to characterizing chaos, should be properly defined. In this paper, we show how to do this in a class of well-defined noise-driven dynamical systems, derived from an underlying Hamiltonian model.

Model based manipulator control

NASA Technical Reports Server (NTRS)

Petrosky, Lyman J.; Oppenheim, Irving J.

1989-01-01

The feasibility of using model based control (MBC) for robotic manipulators was investigated. A double inverted pendulum system was constructed as the experimental system for a general study of dynamically stable manipulation. The original interest in dynamically stable systems was driven by the objective of high vertical reach (balancing), and the planning of inertially favorable trajectories for force and payload demands. The model-based control approach is described and the results of experimental tests are summarized. Results directly demonstrate that MBC can provide stable control at all speeds of operation and support operations requiring dynamic stability such as balancing. The application of MBC to systems with flexible links is also discussed.

Prototype Development: Context-Driven Dynamic XML Ophthalmologic Data Capture Application

PubMed Central

Schwei, Kelsey M; Kadolph, Christopher; Finamore, Joseph; Cancel, Efrain; McCarty, Catherine A; Okorie, Asha; Thomas, Kate L; Allen Pacheco, Jennifer; Pathak, Jyotishman; Ellis, Stephen B; Denny, Joshua C; Rasmussen, Luke V; Tromp, Gerard; Williams, Marc S; Vrabec, Tamara R; Brilliant, Murray H

2017-01-01

Background The capture and integration of structured ophthalmologic data into electronic health records (EHRs) has historically been a challenge. However, the importance of this activity for patient care and research is critical. Objective The purpose of this study was to develop a prototype of a context-driven dynamic extensible markup language (XML) ophthalmologic data capture application for research and clinical care that could be easily integrated into an EHR system. Methods Stakeholders in the medical, research, and informatics fields were interviewed and surveyed to determine data and system requirements for ophthalmologic data capture. On the basis of these requirements, an ophthalmology data capture application was developed to collect and store discrete data elements with important graphical information. Results The context-driven data entry application supports several features, including ink-over drawing capability for documenting eye abnormalities, context-based Web controls that guide data entry based on preestablished dependencies, and an adaptable database or XML schema that stores Web form specifications and allows for immediate changes in form layout or content. The application utilizes Web services to enable data integration with a variety of EHRs for retrieval and storage of patient data. Conclusions This paper describes the development process used to create a context-driven dynamic XML data capture application for optometry and ophthalmology. The list of ophthalmologic data elements identified as important for care and research can be used as a baseline list for future ophthalmologic data collection activities. PMID:28903894

Microscopic origin and macroscopic implications of lane formation in mixtures of oppositely driven particles

NASA Astrophysics Data System (ADS)

Klymko, Katherine; Geissler, Phillip L.; Whitelam, Stephen

2016-08-01

Colloidal particles of two types, driven in opposite directions, can segregate into lanes [Vissers et al., Soft Matter 7, 2352 (2011), 10.1039/c0sm01343a]. This phenomenon can be reproduced by two-dimensional Brownian dynamics simulations of model particles [Dzubiella et al., Phys. Rev. E 65, 021402 (2002), 10.1103/PhysRevE.65.021402]. Here we use computer simulation to assess the generality of lane formation with respect to variation of particle type and dynamical protocol. We find that laning results from rectification of diffusion on the scale of a particle diameter: oppositely driven particles must, in the time taken to encounter each other in the direction of the drive, diffuse in the perpendicular direction by about one particle diameter. This geometric constraint implies that the diffusion constant of a particle, in the presence of those of the opposite type, grows approximately linearly with the Péclet number, a prediction confirmed by our numerics over a range of model parameters. Such environment-dependent diffusion is statistically similar to an effective interparticle attraction; consistent with this observation, we find that oppositely driven nonattractive colloids display features characteristic of the simplest model system possessing both interparticle attractions and persistent motion, the driven Ising lattice gas [Katz, Leibowitz, and Spohn, J. Stat. Phys. 34, 497 (1984), 10.1007/BF01018556]. These features include long-ranged correlations in the disordered regime, a critical regime characterized by a change in slope of the particle current with the Péclet number, and fluctuations that grow with system size. By analogy, we suggest that lane formation in the driven colloid system is a phase transition in the macroscopic limit, but that macroscopic phase separation would not occur in finite time upon starting from disordered initial conditions.

Sparse dynamical Boltzmann machine for reconstructing complex networks with binary dynamics

NASA Astrophysics Data System (ADS)

Chen, Yu-Zhong; Lai, Ying-Cheng

2018-03-01

Revealing the structure and dynamics of complex networked systems from observed data is a problem of current interest. Is it possible to develop a completely data-driven framework to decipher the network structure and different types of dynamical processes on complex networks? We develop a model named sparse dynamical Boltzmann machine (SDBM) as a structural estimator for complex networks that host binary dynamical processes. The SDBM attains its topology according to that of the original system and is capable of simulating the original binary dynamical process. We develop a fully automated method based on compressive sensing and a clustering algorithm to construct the SDBM. We demonstrate, for a variety of representative dynamical processes on model and real world complex networks, that the equivalent SDBM can recover the network structure of the original system and simulates its dynamical behavior with high precision.

Sparse dynamical Boltzmann machine for reconstructing complex networks with binary dynamics.

PubMed

Chen, Yu-Zhong; Lai, Ying-Cheng

2018-03-01

Revealing the structure and dynamics of complex networked systems from observed data is a problem of current interest. Is it possible to develop a completely data-driven framework to decipher the network structure and different types of dynamical processes on complex networks? We develop a model named sparse dynamical Boltzmann machine (SDBM) as a structural estimator for complex networks that host binary dynamical processes. The SDBM attains its topology according to that of the original system and is capable of simulating the original binary dynamical process. We develop a fully automated method based on compressive sensing and a clustering algorithm to construct the SDBM. We demonstrate, for a variety of representative dynamical processes on model and real world complex networks, that the equivalent SDBM can recover the network structure of the original system and simulates its dynamical behavior with high precision.

A data-driven prediction method for fast-slow systems

NASA Astrophysics Data System (ADS)

Groth, Andreas; Chekroun, Mickael; Kondrashov, Dmitri; Ghil, Michael

2016-04-01

In this work, we present a prediction method for processes that exhibit a mixture of variability on low and fast scales. The method relies on combining empirical model reduction (EMR) with singular spectrum analysis (SSA). EMR is a data-driven methodology for constructing stochastic low-dimensional models that account for nonlinearity and serial correlation in the estimated noise, while SSA provides a decomposition of the complex dynamics into low-order components that capture spatio-temporal behavior on different time scales. Our study focuses on the data-driven modeling of partial observations from dynamical systems that exhibit power spectra with broad peaks. The main result in this talk is that the combination of SSA pre-filtering with EMR modeling improves, under certain circumstances, the modeling and prediction skill of such a system, as compared to a standard EMR prediction based on raw data. Specifically, it is the separation into "fast" and "slow" temporal scales by the SSA pre-filtering that achieves the improvement. We show, in particular that the resulting EMR-SSA emulators help predict intermittent behavior such as rapid transitions between specific regions of the system's phase space. This capability of the EMR-SSA prediction will be demonstrated on two low-dimensional models: the Rössler system and a Lotka-Volterra model for interspecies competition. In either case, the chaotic dynamics is produced through a Shilnikov-type mechanism and we argue that the latter seems to be an important ingredient for the good prediction skills of EMR-SSA emulators. Shilnikov-type behavior has been shown to arise in various complex geophysical fluid models, such as baroclinic quasi-geostrophic flows in the mid-latitude atmosphere and wind-driven double-gyre ocean circulation models. This pervasiveness of the Shilnikow mechanism of fast-slow transition opens interesting perspectives for the extension of the proposed EMR-SSA approach to more realistic situations.

Evaluation of near surface ozone and particulate matter in air quality simulations driven by dynamically downscaled historical meteorological fields

EPA Science Inventory

In this study, techniques typically used for future air quality projections are applied to a historical 11-year period to assess the performance of the modeling system when the driving meteorological conditions are obtained using dynamical downscaling of coarse-scale fields witho...

Predation and bark beetle dynamics

Treesearch

John D. Reeve

1997-01-01

Bark beetle populations may undergo dramatic fluctuations and are often important pests in coniferous forests.Their dynamics are thought to be primarily driven by factors affecting the resistance of the host tree to attack, i.e., bottom-up forces, while natural enemies are usually assigned a minor role in these systems.I present behavioral experiments that suggest that...

Dynamical stability of a many-body Kapitza pendulum

DOE Office of Scientific and Technical Information (OSTI.GOV)

Citro, Roberta, E-mail: citro@sa.infn.it; Dalla Torre, Emanuele G., E-mail: emanuele.dalla-torre@biu.ac.il; Department of Physics, Harvard University, Cambridge, MA 02138

We consider a many-body generalization of the Kapitza pendulum: the periodically-driven sine–Gordon model. We show that this interacting system is dynamically stable to periodic drives with finite frequency and amplitude. This finding is in contrast to the common belief that periodically-driven unbounded interacting systems should always tend to an absorbing infinite-temperature state. The transition to an unstable absorbing state is described by a change in the sign of the kinetic term in the Floquet Hamiltonian and controlled by the short-wavelength degrees of freedom. We investigate the stability phase diagram through an analytic high-frequency expansion, a self-consistent variational approach, and amore » numeric semiclassical calculation. Classical and quantum experiments are proposed to verify the validity of our results.« less

Investigation of a driven fermionic system and detecting chiral edge modes in an optical lattice

NASA Astrophysics Data System (ADS)

Görg, Frederik; Messer, Michael; Jotzu, Gregor; Sandholzer, Kilian; Desbuquois, Rémi; Goldman, Nathan; Esslinger, Tilman

2017-04-01

Periodically driven systems of ultracold fermions in optical lattices allow to implement a large variety of effective Hamiltonians through Floquet engineering. An important question is whether this method can be extended to interacting systems. We investigate driven two-body systems in an array of double wells and measure the double occupancy and the spin-spin correlator in the large frequency limit and when driving resonantly to an energy scale of the underlying static Hamiltonian. We analyze whether the emerging states of the driven system can be adiabatically connected to states in the unshaken lattice. In addition, we measure the amplitude of the micromotion which describes the short time dynamics of the system and compare it directly to theory. In another context we propose a method to create topological interfaces and detect chiral edge modes in a two dimensional optical lattice. We illustrate this through an optical lattice realization of the Haldane model for cold atoms, where an additional spatially-varying lattice potential induces distinct topological phases in separated regions of space.

Cyclic Game Dynamics Driven by Iterated Reasoning

PubMed Central

Frey, Seth; Goldstone, Robert L.

2013-01-01

Recent theories from complexity science argue that complex dynamics are ubiquitous in social and economic systems. These claims emerge from the analysis of individually simple agents whose collective behavior is surprisingly complicated. However, economists have argued that iterated reasoning–what you think I think you think–will suppress complex dynamics by stabilizing or accelerating convergence to Nash equilibrium. We report stable and efficient periodic behavior in human groups playing the Mod Game, a multi-player game similar to Rock-Paper-Scissors. The game rewards subjects for thinking exactly one step ahead of others in their group. Groups that play this game exhibit cycles that are inconsistent with any fixed-point solution concept. These cycles are driven by a “hopping” behavior that is consistent with other accounts of iterated reasoning: agents are constrained to about two steps of iterated reasoning and learn an additional one-half step with each session. If higher-order reasoning can be complicit in complex emergent dynamics, then cyclic and chaotic patterns may be endogenous features of real-world social and economic systems. PMID:23441191

Real time unsupervised learning of visual stimuli in neuromorphic VLSI systems

NASA Astrophysics Data System (ADS)

Giulioni, Massimiliano; Corradi, Federico; Dante, Vittorio; Del Giudice, Paolo

2015-10-01

Neuromorphic chips embody computational principles operating in the nervous system, into microelectronic devices. In this domain it is important to identify computational primitives that theory and experiments suggest as generic and reusable cognitive elements. One such element is provided by attractor dynamics in recurrent networks. Point attractors are equilibrium states of the dynamics (up to fluctuations), determined by the synaptic structure of the network; a ‘basin’ of attraction comprises all initial states leading to a given attractor upon relaxation, hence making attractor dynamics suitable to implement robust associative memory. The initial network state is dictated by the stimulus, and relaxation to the attractor state implements the retrieval of the corresponding memorized prototypical pattern. In a previous work we demonstrated that a neuromorphic recurrent network of spiking neurons and suitably chosen, fixed synapses supports attractor dynamics. Here we focus on learning: activating on-chip synaptic plasticity and using a theory-driven strategy for choosing network parameters, we show that autonomous learning, following repeated presentation of simple visual stimuli, shapes a synaptic connectivity supporting stimulus-selective attractors. Associative memory develops on chip as the result of the coupled stimulus-driven neural activity and ensuing synaptic dynamics, with no artificial separation between learning and retrieval phases.

Real time unsupervised learning of visual stimuli in neuromorphic VLSI systems.

PubMed

Giulioni, Massimiliano; Corradi, Federico; Dante, Vittorio; del Giudice, Paolo

2015-10-14

Neuromorphic chips embody computational principles operating in the nervous system, into microelectronic devices. In this domain it is important to identify computational primitives that theory and experiments suggest as generic and reusable cognitive elements. One such element is provided by attractor dynamics in recurrent networks. Point attractors are equilibrium states of the dynamics (up to fluctuations), determined by the synaptic structure of the network; a 'basin' of attraction comprises all initial states leading to a given attractor upon relaxation, hence making attractor dynamics suitable to implement robust associative memory. The initial network state is dictated by the stimulus, and relaxation to the attractor state implements the retrieval of the corresponding memorized prototypical pattern. In a previous work we demonstrated that a neuromorphic recurrent network of spiking neurons and suitably chosen, fixed synapses supports attractor dynamics. Here we focus on learning: activating on-chip synaptic plasticity and using a theory-driven strategy for choosing network parameters, we show that autonomous learning, following repeated presentation of simple visual stimuli, shapes a synaptic connectivity supporting stimulus-selective attractors. Associative memory develops on chip as the result of the coupled stimulus-driven neural activity and ensuing synaptic dynamics, with no artificial separation between learning and retrieval phases.

Asymptotic theory of time-varying social networks with heterogeneous activity and tie allocation.

PubMed

Ubaldi, Enrico; Perra, Nicola; Karsai, Márton; Vezzani, Alessandro; Burioni, Raffaella; Vespignani, Alessandro

2016-10-24

The dynamic of social networks is driven by the interplay between diverse mechanisms that still challenge our theoretical and modelling efforts. Amongst them, two are known to play a central role in shaping the networks evolution, namely the heterogeneous propensity of individuals to i) be socially active and ii) establish a new social relationships with their alters. Here, we empirically characterise these two mechanisms in seven real networks describing temporal human interactions in three different settings: scientific collaborations, Twitter mentions, and mobile phone calls. We find that the individuals' social activity and their strategy in choosing ties where to allocate their social interactions can be quantitatively described and encoded in a simple stochastic network modelling framework. The Master Equation of the model can be solved in the asymptotic limit. The analytical solutions provide an explicit description of both the system dynamic and the dynamical scaling laws characterising crucial aspects about the evolution of the networks. The analytical predictions match with accuracy the empirical observations, thus validating the theoretical approach. Our results provide a rigorous dynamical system framework that can be extended to include other processes shaping social dynamics and to generate data driven predictions for the asymptotic behaviour of social networks.

Asymptotic theory of time-varying social networks with heterogeneous activity and tie allocation

NASA Astrophysics Data System (ADS)

Ubaldi, Enrico; Perra, Nicola; Karsai, Márton; Vezzani, Alessandro; Burioni, Raffaella; Vespignani, Alessandro

2016-10-01

The dynamic of social networks is driven by the interplay between diverse mechanisms that still challenge our theoretical and modelling efforts. Amongst them, two are known to play a central role in shaping the networks evolution, namely the heterogeneous propensity of individuals to i) be socially active and ii) establish a new social relationships with their alters. Here, we empirically characterise these two mechanisms in seven real networks describing temporal human interactions in three different settings: scientific collaborations, Twitter mentions, and mobile phone calls. We find that the individuals’ social activity and their strategy in choosing ties where to allocate their social interactions can be quantitatively described and encoded in a simple stochastic network modelling framework. The Master Equation of the model can be solved in the asymptotic limit. The analytical solutions provide an explicit description of both the system dynamic and the dynamical scaling laws characterising crucial aspects about the evolution of the networks. The analytical predictions match with accuracy the empirical observations, thus validating the theoretical approach. Our results provide a rigorous dynamical system framework that can be extended to include other processes shaping social dynamics and to generate data driven predictions for the asymptotic behaviour of social networks.

Learning-Based Adaptive Optimal Tracking Control of Strict-Feedback Nonlinear Systems.

PubMed

Gao, Weinan; Jiang, Zhong-Ping; Weinan Gao; Zhong-Ping Jiang; Gao, Weinan; Jiang, Zhong-Ping

2018-06-01

This paper proposes a novel data-driven control approach to address the problem of adaptive optimal tracking for a class of nonlinear systems taking the strict-feedback form. Adaptive dynamic programming (ADP) and nonlinear output regulation theories are integrated for the first time to compute an adaptive near-optimal tracker without any a priori knowledge of the system dynamics. Fundamentally different from adaptive optimal stabilization problems, the solution to a Hamilton-Jacobi-Bellman (HJB) equation, not necessarily a positive definite function, cannot be approximated through the existing iterative methods. This paper proposes a novel policy iteration technique for solving positive semidefinite HJB equations with rigorous convergence analysis. A two-phase data-driven learning method is developed and implemented online by ADP. The efficacy of the proposed adaptive optimal tracking control methodology is demonstrated via a Van der Pol oscillator with time-varying exogenous signals.

Quick-look guide to the crustal dynamics project's data information system

NASA Technical Reports Server (NTRS)

Noll, Carey E.; Behnke, Jeanne M.; Linder, Henry G.

1987-01-01

Described are the contents of the Crustal Dynamics Project Data Information System (DIS) and instructions on the use of this facility. The main purpose of the DIS is to store all geodetic data products acquired by the Project in a central data bank and to maintain information about the archive of all Project-related data. Access and use of the DIS menu-driven system is described as well as procedures for contacting DIS staff and submitting data requests.

Access Control for Cooperation Systems Based on Group Situation

NASA Astrophysics Data System (ADS)

Kim, Minsoo; Joshi, James B. D.; Kim, Minkoo

Cooperation systems characterize many emerging environments such as ubiquitous and pervasive systems. Agent based cooperation systems have been proposed in the literature to address challenges of such emerging application environments. A key aspect of such agent based cooperation system is the group situation that changes dynamically and governs the requirements of the cooperation. While individual agent context is important, the overall cooperation behavior is more driven by the group context because of relationships and interactions between agents. Dynamic access control based on group situation is a crucial challenge in such cooperation systems. In this paper we propose a dynamic role based access control model for cooperation systems based on group situation. The model emphasizes capability based agent to role mapping and group situation based permission assignment to allow capturing dynamic access policies that evolve continuously.

Light-field-driven currents in graphene

NASA Astrophysics Data System (ADS)

Higuchi, Takuya; Heide, Christian; Ullmann, Konrad; Weber, Heiko B.; Hommelhoff, Peter

2017-10-01

The ability to steer electrons using the strong electromagnetic field of light has opened up the possibility of controlling electron dynamics on the sub-femtosecond (less than 10-15 seconds) timescale. In dielectrics and semiconductors, various light-field-driven effects have been explored, including high-harmonic generation, sub-optical-cycle interband population transfer and the non-perturbative change of the transient polarizability. In contrast, much less is known about light-field-driven electron dynamics in narrow-bandgap systems or in conductors, in which screening due to free carriers or light absorption hinders the application of strong optical fields. Graphene is a promising platform with which to achieve light-field-driven control of electrons in a conducting material, because of its broadband and ultrafast optical response, weak screening and high damage threshold. Here we show that a current induced in monolayer graphene by two-cycle laser pulses is sensitive to the electric-field waveform, that is, to the exact shape of the optical carrier field of the pulse, which is controlled by the carrier-envelope phase, with a precision on the attosecond (10-18 seconds) timescale. Such a current, dependent on the carrier-envelope phase, shows a striking reversal of the direction of the current as a function of the driving field amplitude at about two volts per nanometre. This reversal indicates a transition of light-matter interaction from the weak-field (photon-driven) regime to the strong-field (light-field-driven) regime, where the intraband dynamics influence interband transitions. We show that in this strong-field regime the electron dynamics are governed by sub-optical-cycle Landau-Zener-Stückelberg interference, composed of coherent repeated Landau-Zener transitions on the femtosecond timescale. Furthermore, the influence of this sub-optical-cycle interference can be controlled with the laser polarization state. These coherent electron dynamics in graphene take place on a hitherto unexplored timescale, faster than electron-electron scattering (tens of femtoseconds) and electron-phonon scattering (hundreds of femtoseconds). We expect these results to have direct ramifications for band-structure tomography and light-field-driven petahertz electronics.

Light-field-driven currents in graphene.

PubMed

Higuchi, Takuya; Heide, Christian; Ullmann, Konrad; Weber, Heiko B; Hommelhoff, Peter

2017-10-12

The ability to steer electrons using the strong electromagnetic field of light has opened up the possibility of controlling electron dynamics on the sub-femtosecond (less than 10 -15 seconds) timescale. In dielectrics and semiconductors, various light-field-driven effects have been explored, including high-harmonic generation, sub-optical-cycle interband population transfer and the non-perturbative change of the transient polarizability. In contrast, much less is known about light-field-driven electron dynamics in narrow-bandgap systems or in conductors, in which screening due to free carriers or light absorption hinders the application of strong optical fields. Graphene is a promising platform with which to achieve light-field-driven control of electrons in a conducting material, because of its broadband and ultrafast optical response, weak screening and high damage threshold. Here we show that a current induced in monolayer graphene by two-cycle laser pulses is sensitive to the electric-field waveform, that is, to the exact shape of the optical carrier field of the pulse, which is controlled by the carrier-envelope phase, with a precision on the attosecond (10 -18 seconds) timescale. Such a current, dependent on the carrier-envelope phase, shows a striking reversal of the direction of the current as a function of the driving field amplitude at about two volts per nanometre. This reversal indicates a transition of light-matter interaction from the weak-field (photon-driven) regime to the strong-field (light-field-driven) regime, where the intraband dynamics influence interband transitions. We show that in this strong-field regime the electron dynamics are governed by sub-optical-cycle Landau-Zener-Stückelberg interference, composed of coherent repeated Landau-Zener transitions on the femtosecond timescale. Furthermore, the influence of this sub-optical-cycle interference can be controlled with the laser polarization state. These coherent electron dynamics in graphene take place on a hitherto unexplored timescale, faster than electron-electron scattering (tens of femtoseconds) and electron-phonon scattering (hundreds of femtoseconds). We expect these results to have direct ramifications for band-structure tomography and light-field-driven petahertz electronics.

Ecological and evolutionary dynamics of interconnectedness and modularity.

PubMed

Nordbotten, Jan M; Levin, Simon A; Szathmáry, Eörs; Stenseth, Nils C

2018-01-23

In this contribution, we develop a theoretical framework for linking microprocesses (i.e., population dynamics and evolution through natural selection) with macrophenomena (such as interconnectedness and modularity within an ecological system). This is achieved by developing a measure of interconnectedness for population distributions defined on a trait space (generalizing the notion of modularity on graphs), in combination with an evolution equation for the population distribution. With this contribution, we provide a platform for understanding under what environmental, ecological, and evolutionary conditions ecosystems evolve toward being more or less modular. A major contribution of this work is that we are able to decompose the overall driver of changes at the macro level (such as interconnectedness) into three components: ( i ) ecologically driven change, ( ii ) evolutionarily driven change, and ( iii ) environmentally driven change. Copyright © 2018 the Author(s). Published by PNAS.

A necessary condition for dispersal driven growth of populations with discrete patch dynamics.

PubMed

Guiver, Chris; Packman, David; Townley, Stuart

2017-07-07

We revisit the question of when can dispersal-induced coupling between discrete sink populations cause overall population growth? Such a phenomenon is called dispersal driven growth and provides a simple explanation of how dispersal can allow populations to persist across discrete, spatially heterogeneous, environments even when individual patches are adverse or unfavourable. For two classes of mathematical models, one linear and one non-linear, we provide necessary conditions for dispersal driven growth in terms of the non-existence of a common linear Lyapunov function, which we describe. Our approach draws heavily upon the underlying positive dynamical systems structure. Our results apply to both discrete- and continuous-time models. The theory is illustrated with examples and both biological and mathematical conclusions are drawn. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

Application of Petri Nets in Bone Remodeling

PubMed Central

Li, Lingxi; Yokota, Hiroki

2009-01-01

Understanding a mechanism of bone remodeling is a challenging task for both life scientists and model builders, since this highly interactive and nonlinear process can seldom be grasped by simple intuition. A set of ordinary differential equations (ODEs) have been built for simulating bone formation as well as bone resorption. Although solving ODEs numerically can provide useful predictions for dynamical behaviors in a continuous time frame, an actual bone remodeling process in living tissues is driven by discrete events of molecular and cellular interactions. Thus, an event-driven tool such as Petri nets (PNs), which may dynamically and graphically mimic individual molecular collisions or cellular interactions, seems to augment the existing ODE-based systems analysis. Here, we applied PNs to expand the ODE-based approach and examined discrete, dynamical behaviors of key regulatory molecules and bone cells. PNs have been used in many engineering areas, but their application to biological systems needs to be explored. Our PN model was based on 8 ODEs that described an osteoprotegerin linked molecular pathway consisting of 4 types of bone cells. The models allowed us to conduct both qualitative and quantitative evaluations and evaluate homeostatic equilibrium states. The results support that application of PN models assists understanding of an event-driven bone remodeling mechanism using PN-specific procedures such as places, transitions, and firings. PMID:19838338

Self-organization of complex networks as a dynamical system

NASA Astrophysics Data System (ADS)

Aoki, Takaaki; Yawata, Koichiro; Aoyagi, Toshio

2015-01-01

To understand the dynamics of real-world networks, we investigate a mathematical model of the interplay between the dynamics of random walkers on a weighted network and the link weights driven by a resource carried by the walkers. Our numerical studies reveal that, under suitable conditions, the co-evolving dynamics lead to the emergence of stationary power-law distributions of the resource and link weights, while the resource quantity at each node ceaselessly changes with time. We analyze the network organization as a deterministic dynamical system and find that the system exhibits multistability, with numerous fixed points, limit cycles, and chaotic states. The chaotic behavior of the system leads to the continual changes in the microscopic network dynamics in the absence of any external random noises. We conclude that the intrinsic interplay between the states of the nodes and network reformation constitutes a major factor in the vicissitudes of real-world networks.

Self-organization of complex networks as a dynamical system.

PubMed

Aoki, Takaaki; Yawata, Koichiro; Aoyagi, Toshio

2015-01-01

To understand the dynamics of real-world networks, we investigate a mathematical model of the interplay between the dynamics of random walkers on a weighted network and the link weights driven by a resource carried by the walkers. Our numerical studies reveal that, under suitable conditions, the co-evolving dynamics lead to the emergence of stationary power-law distributions of the resource and link weights, while the resource quantity at each node ceaselessly changes with time. We analyze the network organization as a deterministic dynamical system and find that the system exhibits multistability, with numerous fixed points, limit cycles, and chaotic states. The chaotic behavior of the system leads to the continual changes in the microscopic network dynamics in the absence of any external random noises. We conclude that the intrinsic interplay between the states of the nodes and network reformation constitutes a major factor in the vicissitudes of real-world networks.

Hard Sphere Simulation by Event-Driven Molecular Dynamics: Breakthrough, Numerical Difficulty, and Overcoming the issues

NASA Astrophysics Data System (ADS)

Isobe, Masaharu

Hard sphere/disk systems are among the simplest models and have been used to address numerous fundamental problems in the field of statistical physics. The pioneering numerical works on the solid-fluid phase transition based on Monte Carlo (MC) and molecular dynamics (MD) methods published in 1957 represent historical milestones, which have had a significant influence on the development of computer algorithms and novel tools to obtain physical insights. This chapter addresses the works of Alder's breakthrough regarding hard sphere/disk simulation: (i) event-driven molecular dynamics, (ii) long-time tail, (iii) molasses tail, and (iv) two-dimensional melting/crystallization. From a numerical viewpoint, there are serious issues that must be overcome for further breakthrough. Here, we present a brief review of recent progress in this area.

Model and system learners, optimal process constructors and kinetic theory-based goal-oriented design: A new paradigm in materials and processes informatics

NASA Astrophysics Data System (ADS)

Abisset-Chavanne, Emmanuelle; Duval, Jean Louis; Cueto, Elias; Chinesta, Francisco

2018-05-01

Traditionally, Simulation-Based Engineering Sciences (SBES) has relied on the use of static data inputs (model parameters, initial or boundary conditions, … obtained from adequate experiments) to perform simulations. A new paradigm in the field of Applied Sciences and Engineering has emerged in the last decade. Dynamic Data-Driven Application Systems [9, 10, 11, 12, 22] allow the linkage of simulation tools with measurement devices for real-time control of simulations and applications, entailing the ability to dynamically incorporate additional data into an executing application, and in reverse, the ability of an application to dynamically steer the measurement process. It is in that context that traditional "digital-twins" are giving raise to a new generation of goal-oriented data-driven application systems, also known as "hybrid-twins", embracing models based on physics and models exclusively based on data adequately collected and assimilated for filling the gap between usual model predictions and measurements. Within this framework new methodologies based on model learners, machine learning and kinetic goal-oriented design are defining a new paradigm in materials, processes and systems engineering.

Two dynamic regimes in the human gut microbiome

PubMed Central

Smillie, Chris S.; Alm, Eric J.

2017-01-01

The gut microbiome is a dynamic system that changes with host development, health, behavior, diet, and microbe-microbe interactions. Prior work on gut microbial time series has largely focused on autoregressive models (e.g. Lotka-Volterra). However, we show that most of the variance in microbial time series is non-autoregressive. In addition, we show how community state-clustering is flawed when it comes to characterizing within-host dynamics and that more continuous methods are required. Most organisms exhibited stable, mean-reverting behavior suggestive of fixed carrying capacities and abundant taxa were largely shared across individuals. This mean-reverting behavior allowed us to apply sparse vector autoregression (sVAR)—a multivariate method developed for econometrics—to model the autoregressive component of gut community dynamics. We find a strong phylogenetic signal in the non-autoregressive co-variance from our sVAR model residuals, which suggests niche filtering. We show how changes in diet are also non-autoregressive and that Operational Taxonomic Units strongly correlated with dietary variables have much less of an autoregressive component to their variance, which suggests that diet is a major driver of microbial dynamics. Autoregressive variance appears to be driven by multi-day recovery from frequent facultative anaerobe blooms, which may be driven by fluctuations in luminal redox. Overall, we identify two dynamic regimes within the human gut microbiota: one likely driven by external environmental fluctuations, and the other by internal processes. PMID:28222117

Two dynamic regimes in the human gut microbiome.

PubMed

Gibbons, Sean M; Kearney, Sean M; Smillie, Chris S; Alm, Eric J

2017-02-01

The gut microbiome is a dynamic system that changes with host development, health, behavior, diet, and microbe-microbe interactions. Prior work on gut microbial time series has largely focused on autoregressive models (e.g. Lotka-Volterra). However, we show that most of the variance in microbial time series is non-autoregressive. In addition, we show how community state-clustering is flawed when it comes to characterizing within-host dynamics and that more continuous methods are required. Most organisms exhibited stable, mean-reverting behavior suggestive of fixed carrying capacities and abundant taxa were largely shared across individuals. This mean-reverting behavior allowed us to apply sparse vector autoregression (sVAR)-a multivariate method developed for econometrics-to model the autoregressive component of gut community dynamics. We find a strong phylogenetic signal in the non-autoregressive co-variance from our sVAR model residuals, which suggests niche filtering. We show how changes in diet are also non-autoregressive and that Operational Taxonomic Units strongly correlated with dietary variables have much less of an autoregressive component to their variance, which suggests that diet is a major driver of microbial dynamics. Autoregressive variance appears to be driven by multi-day recovery from frequent facultative anaerobe blooms, which may be driven by fluctuations in luminal redox. Overall, we identify two dynamic regimes within the human gut microbiota: one likely driven by external environmental fluctuations, and the other by internal processes.

Charge and spin dynamics driven by ultrashort extreme broadband pulses: A theory perspective

NASA Astrophysics Data System (ADS)

Moskalenko, Andrey S.; Zhu, Zhen-Gang; Berakdar, Jamal

2017-02-01

This article gives an overview on recent theoretical progress in controlling the charge and spin dynamics in low-dimensional electronic systems by means of ultrashort and ultrabroadband electromagnetic pulses. A particular focus is put on sub-cycle and single-cycle pulses and their utilization for coherent control. The discussion is mostly limited to cases where the pulse duration is shorter than the characteristic time scales associated with the involved spectral features of the excitations. The relevant current theoretical knowledge is presented in a coherent, pedagogic manner. We work out that the pulse action amounts in essence to a quantum map between the quantum states of the system at an appropriately chosen time moment during the pulse. The influence of a particular pulse shape on the post-pulse dynamics is reduced to several integral parameters entering the expression for the quantum map. The validity range of this reduction scheme for different strengths of the driving fields is established and discussed for particular nanostructures. Acting with a periodic pulse sequence, it is shown how the system can be steered to and largely maintained in predefined states. The conditions for this nonequilibrium sustainability are worked out by means of geometric phases, which are identified as the appropriate quantities to indicate quasistationarity of periodically driven quantum systems. Demonstrations are presented for the control of the charge, spin, and valley degrees of freedom in nanostructures on picosecond and subpicosecond time scales. The theory is illustrated with several applications to one-dimensional semiconductor quantum wires and superlattices, double quantum dots, semiconductor and graphene quantum rings. In the case of a periodic pulsed driving the influence of the relaxation and decoherence processes is included by utilizing the density matrix approach. The integrated and time-dependent spectra of the light emitted from the driven system deliver information on its spin-dependent dynamics. We review examples of such spectra of photons emitted from pulse-driven nanostructures as well as a possibility to characterize and control the light polarization on an ultrafast time scale. Furthermore, we consider the response of strongly correlated systems to short broadband pulses and show that this case bears a great potential to unveil high order correlations while they build up upon excitations.

Molecular dynamics simulations of large macromolecular complexes.

PubMed

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

2015-04-01

Connecting dynamics to structural data from diverse experimental sources, molecular dynamics simulations permit the exploration of biological phenomena in unparalleled detail. Advances in simulations are moving the atomic resolution descriptions of biological systems into the million-to-billion atom regime, in which numerous cell functions reside. In this opinion, we review the progress, driven by large-scale molecular dynamics simulations, in the study of viruses, ribosomes, bioenergetic systems, and other diverse applications. These examples highlight the utility of molecular dynamics simulations in the critical task of relating atomic detail to the function of supramolecular complexes, a task that cannot be achieved by smaller-scale simulations or existing experimental approaches alone. Copyright © 2015 Elsevier Ltd. All rights reserved.

The Kibble-Zurek mechanism in phase transitions of non-equilibrium systems

NASA Astrophysics Data System (ADS)

Cheung, Hil F. H.; Patil, Yogesh S.; Date, Aditya G.; Vengalattore, Mukund

2017-04-01

We experimentally realize a driven-dissipative phase transition using a mechanical parametric amplifier to demonstrate key signatures of a second order phase transition, including a point where the susceptibilities and relaxation time scales diverge, and where the system exhibits a spontaneous breaking of symmetry. Though reminiscent of conventional equilibrium phase transitions, it is unclear if such driven-dissipative phase transitions are amenable to the conventional Landau-Ginsburg-Wilson paradigm, which relies on concepts of scale invariance and universality, and recent work has shown that such phase transitions can indeed lie beyond such conventional universality classes. By quenching the system past the critical point, we investigate the dynamics of the emergent ordered phase and find that our measurements are in excellent agreement with the Kibble-Zurek mechanism. In addition to verifying the Kibble-Zurek hypothesis in driven-dissipative phase transitions for the first time, we also demonstrate that the measured critical exponents accurately reflect the interplay between intrinsic coherent dynamics and environmental correlations, showing a clear departure from mean field exponents in the case of non-Markovian system-bath interactions. We further discuss how reservoir engineering and the imposition of artificial environmental correlations can result in the stabilization of novel many-body quantum phases and aid in the creation of exotic non-equilibrium states of matter.

Dynamic Data-Driven Reduced-Order Models of Macroscale Quantities for the Prediction of Equilibrium System State for Multiphase Porous Medium Systems

NASA Astrophysics Data System (ADS)

Talbot, C.; McClure, J. E.; Armstrong, R. T.; Mostaghimi, P.; Hu, Y.; Miller, C. T.

2017-12-01

Microscale simulation of multiphase flow in realistic, highly-resolved porous medium systems of a sufficient size to support macroscale evaluation is computationally demanding. Such approaches can, however, reveal the dynamic, steady, and equilibrium states of a system. We evaluate methods to utilize dynamic data to reduce the cost associated with modeling a steady or equilibrium state. We construct data-driven models using extensions to dynamic mode decomposition (DMD) and its connections to Koopman Operator Theory. DMD and its variants comprise a class of equation-free methods for dimensionality reduction of time-dependent nonlinear dynamical systems. DMD furnishes an explicit reduced representation of system states in terms of spatiotemporally varying modes with time-dependent oscillation frequencies and amplitudes. We use DMD to predict the steady and equilibrium macroscale state of a realistic two-fluid porous medium system imaged using micro-computed tomography (µCT) and simulated using the lattice Boltzmann method (LBM). We apply Koopman DMD to direct numerical simulation data resulting from simulations of multiphase fluid flow through a 1440x1440x4320 section of a full 1600x1600x5280 realization of imaged sandstone. We determine a representative set of system observables via dimensionality reduction techniques including linear and kernel principal component analysis. We demonstrate how this subset of macroscale quantities furnishes a representation of the time-evolution of the system in terms of dynamic modes, and discuss the selection of a subset of DMD modes yielding the optimal reduced model, as well as the time-dependence of the error in the predicted equilibrium value of each macroscale quantity. Finally, we describe how the above procedure, modified to incorporate methods from compressed sensing and random projection techniques, may be used in an online fashion to facilitate adaptive time-stepping and parsimonious storage of system states over time.

Hybridized Kibble-Zurek scaling in the driven critical dynamics across an overlapping critical region

NASA Astrophysics Data System (ADS)

Zhai, Liang-Jun; Wang, Huai-Yu; Yin, Shuai

2018-04-01

The conventional Kibble-Zurek scaling describes the scaling behavior in the driven dynamics across a single critical region. In this paper, we study the driven dynamics across an overlapping critical region, in which a critical region (Region A) is overlaid by another critical region (Region B). We develop a hybridized Kibble-Zurek scaling (HKZS) to characterize the scaling behavior in the driven process. According to the HKZS, the driven dynamics in the overlapping region can be described by the critical theories for both Region A and Region B simultaneously. This results in a constraint on the scaling function in the overlapping critical region. We take the quantum Ising chain in an imaginary longitudinal field as an example. In this model, the critical region of the Yang-Lee edge singularity and the critical region of the ferromagnetic-paramagnetic phase transition overlap with each other. We numerically confirm the HKZS by simulating the driven dynamics in this overlapping critical region. The HKZSs in other models are also discussed.

Dynamic modeling and motion simulation for a winged hybrid-driven underwater glider

NASA Astrophysics Data System (ADS)

Wang, Shu-Xin; Sun, Xiu-Jun; Wang, Yan-Hui; Wu, Jian-Guo; Wang, Xiao-Ming

2011-03-01

PETREL, a winged hybrid-driven underwater glider is a novel and practical marine survey platform which combines the features of legacy underwater glider and conventional AUV (autonomous underwater vehicle). It can be treated as a multi-rigid-body system with a floating base and a particular hydrodynamic profile. In this paper, theorems on linear and angular momentum are used to establish the dynamic equations of motion of each rigid body and the effect of translational and rotational motion of internal masses on the attitude control are taken into consideration. In addition, due to the unique external shape with fixed wings and deflectable rudders and the dual-drive operation in thrust and glide modes, the approaches of building dynamic model of conventional AUV and hydrodynamic model of submarine are introduced, and the tailored dynamic equations of the hybrid glider are formulated. Moreover, the behaviors of motion in glide and thrust operation are analyzed based on the simulation and the feasibility of the dynamic model is validated by data from lake field trials.

Using Movies to Analyse Gene Circuit Dynamics in Single Cells

PubMed Central

Locke, James CW; Elowitz, Michael B

2010-01-01

Preface Many bacterial systems rely on dynamic genetic circuits to control critical processes. A major goal of systems biology is to understand these behaviours in terms of individual genes and their interactions. However, traditional techniques based on population averages wash out critical dynamics that are either unsynchronized between cells or driven by fluctuations, or ‘noise,’ in cellular components. Recently, the combination of time-lapse microscopy, quantitative image analysis, and fluorescent protein reporters has enabled direct observation of multiple cellular components over time in individual cells. In conjunction with mathematical modelling, these techniques are now providing powerful insights into genetic circuit behaviour in diverse microbial systems. PMID:19369953

Structure-driven turbulence in ``No man's Land''

NASA Astrophysics Data System (ADS)

Kosuga, Yusuke; Diamond, Patrick

2012-10-01

Structures are often observed in many physical systems. In tokamaks, for example, such structures are observed as density blobs and holes. Such density blobs and holes are generated at the tokamak edge, where strong gradient perturbations generate an outgoing blob and an incoming hole. Since density holes can propagate from the edge to the core, such structures may play an important role in understanding the phenomenology of the edge-core coupling region, so-called ``No Man's Land.'' In this work, we discuss the dynamics of such structures in real space. In particular, we consider the dynamics of density blobs and holes in the Hasegawa-Wakatani system. Specific questions addressed here include: i) how these structures extract free energy and enhance transport? how different is the relaxation driven by such structures from that driven by linear drift waves? ii) how these structures interact with shear flows? In particular, how these structures interact with a shear layer, which can absorb structures resonantly? iii) how can we calculate the coupled evolution of structures and shear flows? Implications for edge-core coupling problem are discussed as well.

Data-driven Inference and Investigation of Thermosphere Dynamics and Variations

NASA Astrophysics Data System (ADS)

Mehta, P. M.; Linares, R.

2017-12-01

This paper presents a methodology for data-driven inference and investigation of thermosphere dynamics and variations. The approach uses data-driven modal analysis to extract the most energetic modes of variations for neutral thermospheric species using proper orthogonal decomposition, where the time-independent modes or basis represent the dynamics and the time-depedent coefficients or amplitudes represent the model parameters. The data-driven modal analysis approach combined with sparse, discrete observations is used to infer amplitues for the dynamic modes and to calibrate the energy content of the system. In this work, two different data-types, namely the number density measurements from TIMED/GUVI and the mass density measurements from CHAMP/GRACE are simultaneously ingested for an accurate and self-consistent specification of the thermosphere. The assimilation process is achieved with a non-linear least squares solver and allows estimation/tuning of the model parameters or amplitudes rather than the driver. In this work, we use the Naval Research Lab's MSIS model to derive the most energetic modes for six different species, He, O, N2, O2, H, and N. We examine the dominant drivers of variations for helium in MSIS and observe that seasonal latitudinal variation accounts for about 80% of the dynamic energy with a strong preference of helium for the winter hemisphere. We also observe enhanced helium presence near the poles at GRACE altitudes during periods of low solar activity (Feb 2007) as previously deduced. We will also examine the storm-time response of helium derived from observations. The results are expected to be useful in tuning/calibration of the physics-based models.

Consistency properties of chaotic systems driven by time-delayed feedback

NASA Astrophysics Data System (ADS)

Jüngling, T.; Soriano, M. C.; Oliver, N.; Porte, X.; Fischer, I.

2018-04-01

Consistency refers to the property of an externally driven dynamical system to respond in similar ways to similar inputs. In a delay system, the delayed feedback can be considered as an external drive to the undelayed subsystem. We analyze the degree of consistency in a generic chaotic system with delayed feedback by means of the auxiliary system approach. In this scheme an identical copy of the nonlinear node is driven by exactly the same signal as the original, allowing us to verify complete consistency via complete synchronization. In the past, the phenomenon of synchronization in delay-coupled chaotic systems has been widely studied using correlation functions. Here, we analytically derive relationships between characteristic signatures of the correlation functions in such systems and unequivocally relate them to the degree of consistency. The analytical framework is illustrated and supported by numerical calculations of the logistic map with delayed feedback for different replica configurations. We further apply the formalism to time series from an experiment based on a semiconductor laser with a double fiber-optical feedback loop. The experiment constitutes a high-quality replica scheme for studying consistency of the delay-driven laser and confirms the general theoretical results.

Diffusion-assisted selective dynamical recoupling: A new approach to measure background gradients in magnetic resonance

NASA Astrophysics Data System (ADS)

Álvarez, Gonzalo A.; Shemesh, Noam; Frydman, Lucio

2014-02-01

Dynamical decoupling, a generalization of the original NMR spin-echo sequence, is becoming increasingly relevant as a tool for reducing decoherence in quantum systems. Such sequences apply non-equidistant refocusing pulses for optimizing the coupling between systems, and environmental fluctuations characterized by a given noise spectrum. One such sequence, dubbed Selective Dynamical Recoupling (SDR) [P. E. S. Smith, G. Bensky, G. A. Álvarez, G. Kurizki, and L. Frydman, Proc. Natl. Acad. Sci. 109, 5958 (2012)], allows one to coherently reintroduce diffusion decoherence effects driven by fluctuations arising from restricted molecular diffusion [G. A. Álvarez, N. Shemesh, and L. Frydman, Phys. Rev. Lett. 111, 080404 (2013)]. The fully-refocused, constant-time, and constant-number-of-pulses nature of SDR also allows one to filter out "intrinsic" T1 and T2 weightings, as well as pulse errors acting as additional sources of decoherence. This article explores such features when the fluctuations are now driven by unrestricted molecular diffusion. In particular, we show that diffusion-driven SDR can be exploited to investigate the decoherence arising from the frequency fluctuations imposed by internal gradients. As a result, SDR presents a unique way of probing and characterizing these internal magnetic fields, given an a priori known free diffusion coefficient. This has important implications in studies of structured systems, including porous media and live tissues, where the internal gradients may serve as fingerprints for the system's composition or structure. The principles of this method, along with full analytical solutions for the unrestricted diffusion-driven modulation of the SDR signal, are presented. The potential of this approach is demonstrated with the generation of a novel source of MRI contrast, based on the background gradients active in an ex vivo mouse brain. Additional features and limitations of this new method are discussed.

Data-driven forecasting of high-dimensional chaotic systems with long short-term memory networks.

PubMed

Vlachas, Pantelis R; Byeon, Wonmin; Wan, Zhong Y; Sapsis, Themistoklis P; Koumoutsakos, Petros

2018-05-01

We introduce a data-driven forecasting method for high-dimensional chaotic systems using long short-term memory (LSTM) recurrent neural networks. The proposed LSTM neural networks perform inference of high-dimensional dynamical systems in their reduced order space and are shown to be an effective set of nonlinear approximators of their attractor. We demonstrate the forecasting performance of the LSTM and compare it with Gaussian processes (GPs) in time series obtained from the Lorenz 96 system, the Kuramoto-Sivashinsky equation and a prototype climate model. The LSTM networks outperform the GPs in short-term forecasting accuracy in all applications considered. A hybrid architecture, extending the LSTM with a mean stochastic model (MSM-LSTM), is proposed to ensure convergence to the invariant measure. This novel hybrid method is fully data-driven and extends the forecasting capabilities of LSTM networks.

Flight Validation of a Metrics Driven L(sub 1) Adaptive Control

NASA Technical Reports Server (NTRS)

Dobrokhodov, Vladimir; Kitsios, Ioannis; Kaminer, Isaac; Jones, Kevin D.; Xargay, Enric; Hovakimyan, Naira; Cao, Chengyu; Lizarraga, Mariano I.; Gregory, Irene M.

2008-01-01

The paper addresses initial steps involved in the development and flight implementation of new metrics driven L1 adaptive flight control system. The work concentrates on (i) definition of appropriate control driven metrics that account for the control surface failures; (ii) tailoring recently developed L1 adaptive controller to the design of adaptive flight control systems that explicitly address these metrics in the presence of control surface failures and dynamic changes under adverse flight conditions; (iii) development of a flight control system for implementation of the resulting algorithms onboard of small UAV; and (iv) conducting a comprehensive flight test program that demonstrates performance of the developed adaptive control algorithms in the presence of failures. As the initial milestone the paper concentrates on the adaptive flight system setup and initial efforts addressing the ability of a commercial off-the-shelf AP with and without adaptive augmentation to recover from control surface failures.

Towards classification of the bifurcation structure of a spherical cavitation bubble.

PubMed

Behnia, Sohrab; Sojahrood, Amin Jafari; Soltanpoor, Wiria; Sarkhosh, Leila

2009-12-01

We focus on a single cavitation bubble driven by ultrasound, a system which is a specimen of forced nonlinear oscillators and is characterized by its extreme sensitivity to the initial conditions. The driven radial oscillations of the bubble are considered to be implicated by the principles of chaos physics and owing to specific ranges of control parameters, can be periodic or chaotic. Despite the growing number of investigations on its dynamics, there is not yet an inclusive yardstick to sort the dynamical behavior of the bubble into classes; also, the response oscillations are so complex that long term prediction on the behavior becomes difficult to accomplish. In this study, the nonlinear dynamics of a bubble oscillator was treated numerically and the simulations were proceeded with bifurcation diagrams. The calculated bifurcation diagrams were compared in an attempt to classify the bubble dynamic characteristics when varying the control parameters. The comparison reveals distinctive bifurcation patterns as a consequence of driving the systems with unequal ratios of R(0)lambda (where R(0) is the bubble initial radius and lambda is the wavelength of the driving ultrasonic wave). Results indicated that systems having the equal ratio of R(0)lambda, share remarkable similarities in their bifurcating behavior and can be classified under a unit category.

Parameter identifiability of linear dynamical systems

NASA Technical Reports Server (NTRS)

Glover, K.; Willems, J. C.

1974-01-01

It is assumed that the system matrices of a stationary linear dynamical system were parametrized by a set of unknown parameters. The question considered here is, when can such a set of unknown parameters be identified from the observed data? Conditions for the local identifiability of a parametrization are derived in three situations: (1) when input/output observations are made, (2) when there exists an unknown feedback matrix in the system and (3) when the system is assumed to be driven by white noise and only output observations are made. Also a sufficient condition for global identifiability is derived.

High-harmonic spectroscopy of ultrafast many-body dynamics in strongly correlated systems

NASA Astrophysics Data System (ADS)

Silva, R. E. F.; Blinov, Igor V.; Rubtsov, Alexey N.; Smirnova, O.; Ivanov, M.

2018-05-01

We bring together two topics that, until now, have been the focus of intense but non-overlapping research efforts. The first concerns high-harmonic generation in solids, which occurs when an intense light field excites a highly non-equilibrium electronic response in a semiconductor or a dielectric. The second concerns many-body dynamics in strongly correlated systems such as the Mott insulator. We show that high-harmonic generation can be used to time-resolve ultrafast many-body dynamics associated with an optically driven phase transition, with accuracy far exceeding one cycle of the driving light field. Our work paves the way for time-resolving highly non-equilibrium many-body dynamics in strongly correlated systems, with few femtosecond accuracy.

Interplay of interfacial noise and curvature-driven dynamics in two dimensions

NASA Astrophysics Data System (ADS)

Roy, Parna; Sen, Parongama

2017-02-01

We explore the effect of interplay of interfacial noise and curvature-driven dynamics in a binary spin system. An appropriate model is the generalized two-dimensional voter model proposed earlier [M. J. de Oliveira, J. F. F. Mendes, and M. A. Santos, J. Phys. A: Math. Gen. 26, 2317 (1993), 10.1088/0305-4470/26/10/006], where the flipping probability of a spin depends on the state of its neighbors and is given in terms of two parameters, x and y . x =0.5 andy =1 correspond to the conventional voter model which is purely interfacial noise driven, while x =1 and y =1 correspond to the Ising model, where coarsening is fully curvature driven. The coarsening phenomena for 0.5 0.5 ; the effect of x appears in altering the value of the parameter occurring in the scaling function only.

Fault Detection for Nonlinear Process With Deterministic Disturbances: A Just-In-Time Learning Based Data Driven Method.

PubMed

Yin, Shen; Gao, Huijun; Qiu, Jianbin; Kaynak, Okyay

2017-11-01

Data-driven fault detection plays an important role in industrial systems due to its applicability in case of unknown physical models. In fault detection, disturbances must be taken into account as an inherent characteristic of processes. Nevertheless, fault detection for nonlinear processes with deterministic disturbances still receive little attention, especially in data-driven field. To solve this problem, a just-in-time learning-based data-driven (JITL-DD) fault detection method for nonlinear processes with deterministic disturbances is proposed in this paper. JITL-DD employs JITL scheme for process description with local model structures to cope with processes dynamics and nonlinearity. The proposed method provides a data-driven fault detection solution for nonlinear processes with deterministic disturbances, and owns inherent online adaptation and high accuracy of fault detection. Two nonlinear systems, i.e., a numerical example and a sewage treatment process benchmark, are employed to show the effectiveness of the proposed method.

Lagrangian chaos in three- dimensional steady buoyancy-driven flows

NASA Astrophysics Data System (ADS)

Contreras, Sebastian; Speetjens, Michel; Clercx, Herman

2016-11-01

Natural convection plays a key role in fluid dynamics owing to its ubiquitous presence in nature and industry. Buoyancy-driven flows are prototypical systems in the study of thermal instabilities and pattern formation. The differentially heated cavity problem has been widely studied for the investigation of buoyancy-induced oscillatory flow. However, far less attention has been devoted to the three-dimensional Lagrangian transport properties in such flows. This study seeks to address this by investigating Lagrangian transport in the steady flow inside a cubic cavity differentially-heated from the side. The theoretical and numerical analysis expands on previously reported similarities between the current flow and lid-driven flows. The Lagrangian dynamics are controlled by the Péclet number (Pe) and the Prandtl number (Pr). Pe controls the behaviour qualitatively in that growing Pe progressively perturbs the integable state (Pe =0), thus paving the way to chaotic dynamics. Pr plays an entirely quantitative role in that Pr<1 and Pr>1 amplifies and diminishes, respectively, the perturbative effect of non-zero Pe. S.C. acknowledges financial support from Consejo Nacional de Ciencia y Tecnología (CONACYT).

Automatic procedures generator for orbital rendezvous maneuver

NASA Technical Reports Server (NTRS)

Kohn, W.; Van Valkenburg, J. A.; Dunn, C. K.

1985-01-01

This paper describes the development of an expert system for defining and dynamically updating procedures for an orbital rendezvous maneuver. The product of the expert system is a procedure represented by a Moore automaton. The construction is recursive and driven by a simulation of the rendezvousing bodies.

Introduction to State Estimation of High-Rate System Dynamics.

PubMed

Hong, Jonathan; Laflamme, Simon; Dodson, Jacob; Joyce, Bryan

2018-01-13

Engineering systems experiencing high-rate dynamic events, including airbags, debris detection, and active blast protection systems, could benefit from real-time observability for enhanced performance. However, the task of high-rate state estimation is challenging, in particular for real-time applications where the rate of the observer's convergence needs to be in the microsecond range. This paper identifies the challenges of state estimation of high-rate systems and discusses the fundamental characteristics of high-rate systems. A survey of applications and methods for estimators that have the potential to produce accurate estimations for a complex system experiencing highly dynamic events is presented. It is argued that adaptive observers are important to this research. In particular, adaptive data-driven observers are advantageous due to their adaptability and lack of dependence on the system model.

A locomotive-track coupled vertical dynamics model with gear transmissions

NASA Astrophysics Data System (ADS)

Chen, Zaigang; Zhai, Wanming; Wang, Kaiyun

2017-02-01

A gear transmission system is a key element in a locomotive for the transmission of traction or braking forces between the motor and the wheel-rail interface. Its dynamic performance has a direct effect on the operational reliability of the locomotive and its components. This paper proposes a comprehensive locomotive-track coupled vertical dynamics model, in which the locomotive is driven by axle-hung motors. In this coupled dynamics model, the dynamic interactions between the gear transmission system and the other components, e.g. motor and wheelset, are considered based on the detailed analysis of its structural properties and working mechanism. Thus, the mechanical transmission system for power delivery from the motor to the wheelset via gear transmission is coupled with a traditional locomotive-track dynamics system via the wheel-rail contact interface and the gear mesh interface. This developed dynamics model enables investigations of the dynamic performance of the entire dynamics system under the excitations from the wheel-rail contact interface and/or the gear mesh interface. Dynamic interactions are demonstrated by numerical simulations using this dynamics model. The results indicate that both of the excitations from the wheel-rail contact interface and the gear mesh interface have a significant effect on the dynamic responses of the components in this coupled dynamics system.

Adjustment of Adaptive Gain with Bounded Linear Stability Analysis to Improve Time-Delay Margin for Metrics-Driven Adaptive Control

NASA Technical Reports Server (NTRS)

Bakhtiari-Nejad, Maryam; Nguyen, Nhan T.; Krishnakumar, Kalmanje Srinvas

2009-01-01

This paper presents the application of Bounded Linear Stability Analysis (BLSA) method for metrics driven adaptive control. The bounded linear stability analysis method is used for analyzing stability of adaptive control models, without linearizing the adaptive laws. Metrics-driven adaptive control introduces a notion that adaptation should be driven by some stability metrics to achieve robustness. By the application of bounded linear stability analysis method the adaptive gain is adjusted during the adaptation in order to meet certain phase margin requirements. Analysis of metrics-driven adaptive control is evaluated for a linear damaged twin-engine generic transport model of aircraft. The analysis shows that the system with the adjusted adaptive gain becomes more robust to unmodeled dynamics or time delay.

Integrating complex business processes for knowledge-driven clinical decision support systems.

PubMed

Kamaleswaran, Rishikesan; McGregor, Carolyn

2012-01-01

This paper presents in detail the component of the Complex Business Process for Stream Processing framework that is responsible for integrating complex business processes to enable knowledge-driven Clinical Decision Support System (CDSS) recommendations. CDSSs aid the clinician in supporting the care of patients by providing accurate data analysis and evidence-based recommendations. However, the incorporation of a dynamic knowledge-management system that supports the definition and enactment of complex business processes and real-time data streams has not been researched. In this paper we discuss the process web service as an innovative method of providing contextual information to a real-time data stream processing CDSS.

Advanced optical manufacturing digital integrated system

NASA Astrophysics Data System (ADS)

Tao, Yizheng; Li, Xinglan; Li, Wei; Tang, Dingyong

2012-10-01

It is necessarily to adapt development of advanced optical manufacturing technology with modern science technology development. To solved these problems which low of ration, ratio of finished product, repetition, consistent in big size and high precision in advanced optical component manufacturing. Applied business driven and method of Rational Unified Process, this paper has researched advanced optical manufacturing process flow, requirement of Advanced Optical Manufacturing integrated System, and put forward architecture and key technology of it. Designed Optical component core and Manufacturing process driven of Advanced Optical Manufacturing Digital Integrated System. the result displayed effective well, realized dynamic planning Manufacturing process, information integration improved ratio of production manufactory.

Real time unsupervised learning of visual stimuli in neuromorphic VLSI systems

PubMed Central

Giulioni, Massimiliano; Corradi, Federico; Dante, Vittorio; del Giudice, Paolo

2015-01-01

Neuromorphic chips embody computational principles operating in the nervous system, into microelectronic devices. In this domain it is important to identify computational primitives that theory and experiments suggest as generic and reusable cognitive elements. One such element is provided by attractor dynamics in recurrent networks. Point attractors are equilibrium states of the dynamics (up to fluctuations), determined by the synaptic structure of the network; a ‘basin’ of attraction comprises all initial states leading to a given attractor upon relaxation, hence making attractor dynamics suitable to implement robust associative memory. The initial network state is dictated by the stimulus, and relaxation to the attractor state implements the retrieval of the corresponding memorized prototypical pattern. In a previous work we demonstrated that a neuromorphic recurrent network of spiking neurons and suitably chosen, fixed synapses supports attractor dynamics. Here we focus on learning: activating on-chip synaptic plasticity and using a theory-driven strategy for choosing network parameters, we show that autonomous learning, following repeated presentation of simple visual stimuli, shapes a synaptic connectivity supporting stimulus-selective attractors. Associative memory develops on chip as the result of the coupled stimulus-driven neural activity and ensuing synaptic dynamics, with no artificial separation between learning and retrieval phases. PMID:26463272

Resonance of magnetization excited by voltage in magnetoelectric heterostructures

NASA Astrophysics Data System (ADS)

Yu, Guoliang; Zhang, Huaiwu; Li, Yuanxun; Li, Jie; Zhang, Dainan; Sun, Nian

2018-04-01

Manipulation of magnetization dynamics is critical for spin-based devices. Voltage driven magnetization resonance is promising for realizing low-power information processing systems. Here, we show through Finite Element Method (FEM) simulations that magnetization resonance in nanoscale magnetic elements can be generated by a radio frequency (rf) voltage via the converse magnetoelectric (ME) effect. The magnetization dynamics induced by voltage in a ME heterostructures is simulated by taking into account the magnetoelastic and piezoelectric coupling mechanisms among magnetization, strain and voltage. The frequency of the excited magnetization resonance is equal to the driving rf voltage frequency. The proposed voltage driven magnetization resonance excitation mechanism opens a way toward energy-efficient spin based device applications.

How Dynamics of Learning Are Linked to Innovation Support Services: Insights from a Smallholder Commercialization Project in Kenya

ERIC Educational Resources Information Center

Kilelu, Catherine W.; Klerkx, Laurens; Leeuwis, Cees

2014-01-01

Purpose: The important role of learning is noted in the literature on demand-driven approaches to supporting agricultural innovation. Most of this literature has focused on macrolevel structural perspectives on the organization of pluralistic innovation support systems. This has provided little insight at the micro-level on the dynamics of demand…

MODELING MERCURY DYNAMICS IN STREAM SYSTEMS WITH WASP7: CHARACTERIZING PROCESSES CONTROLLING SHORT AND LONG TERM RESPONSE

EPA Science Inventory

Mercury transport through stream ecosystems is driven by a complicated set of transport and transformation reactions operating on a variety of scales in the atmosphere, landscape, surface water, and biota. Riverine systems typically have short residence times and can experience l...

Identification of Stochastically Perturbed Autonomous Systems from Temporal Sequences of Probability Density Functions

NASA Astrophysics Data System (ADS)

Nie, Xiaokai; Luo, Jingjing; Coca, Daniel; Birkin, Mark; Chen, Jing

2018-03-01

The paper introduces a method for reconstructing one-dimensional iterated maps that are driven by an external control input and subjected to an additive stochastic perturbation, from sequences of probability density functions that are generated by the stochastic dynamical systems and observed experimentally.

Symmetry breaking, phase separation and anomalous fluctuations in driven granular gas

NASA Astrophysics Data System (ADS)

Meerson, Baruch; Pöschel, Thorsten; Sasorov, Pavel V.; Schwager, Thomas

2003-03-01

What is the role of noise, caused by the discrete nature of particles, in granular dynamics? We address this question by considering a simple driven granular system: an ensemble of nearly elastically colliding hard spheres in a rectangular box, driven by a rapidly vibrating side wall at zero gravity. The elementary state of this system is a strip of enhanced particle density away from the driving wall. Granular hydrodynamics (GHD) predicts a symmetry breaking instability of this state, when the aspect ratio of the confining box exceeds a threshold value, while the average density of the gas is within a ``spinodal interval". At large aspect ratios this instability leads to phase separation similar to that in van der Waals gas. In the present work (see cond-mat/0208286) we focus on the system behavior around the threshold of the symmetry-breaking instability. We put GHD into a quantitative test by performing extensive event-driven molecular dynamic simulations in 2D. Please watch the movies of the simulations at http://summa.physik.hu-berlin.de/ kies/HD/. We found that the supercritical bifurcation curve, predicted by GHD, agrees with the simulations well below and well above the instability threshold. In a wide region of aspect ratios around the threshold the system is dominated by fluctuations. We checked that the fluctuation strength goes down when the number of particles increases. However, fluctuations remain strong (and the critical region wide) even for as many as 4 ot 10^4 particles. We conclude by suggesting that fluctuations may put a severe limitation on the validity of continuum theories of granular flow in systems with a moderately large number of particles.

Power-law Growth and Punctuated Equilibrium Dynamics in Water Resources Systems

NASA Astrophysics Data System (ADS)

Parolari, A.; Katul, G. G.; Porporato, A. M.

2015-12-01

The global rise in population-driven water scarcity and recent appreciation of strong dynamic coupling between human and natural systems has called for new approaches to predict the future sustainability of regional and global water resources systems. The dynamics of coupled human-water systems are driven by a complex set of social, environmental, and technological factors. Present projections of water resources systems range from a finite carrying capacity regulated by accessible freshwater, or `peak renewable water,' to punctuated evolution with new supplied and improved efficiency gained from technological and social innovation. However, these projections have yet to be quantified from observations or in a comprehensive theoretical framework. Using data on global water withdrawals and storage capacity of regional water supply systems, non-trivial dynamics are identified in water resources systems development over time, including power-law growth and punctuated equilibria. Two models are introduced to explain this behavior: (1) a delay differential equation and (2) a power-law with log-periodic oscillations, both of which rely on past conditions (or system memory) to describe the present rate of growth in the system. In addition, extension of the first model demonstrates how system delays and punctuated equilibria can emerge from coupling between human population growth and associated resource demands. Lastly, anecdotal evidence is used to demonstrate the likelihood of power-law growth in global water use from the agricultural revolution 3000 BC to the present. In a practical sense, the presence of these patterns in models with delayed oscillations suggests that current decision-making related to water resources development results from the historical accumulation of resource use decisions, technological and social changes, and their consequences.

Dynamics of particulate organic matter composition in coastal systems: Forcing of spatio-temporal variability at multi-systems scale

NASA Astrophysics Data System (ADS)

Liénart, Camilla; Savoye, Nicolas; David, Valérie; Ramond, Pierre; Rodriguez Tress, Paco; Hanquiez, Vincent; Marieu, Vincent; Aubert, Fabien; Aubin, Sébastien; Bichon, Sabrina; Boinet, Christophe; Bourasseau, Line; Bozec, Yann; Bréret, Martine; Breton, Elsa; Caparros, Jocelyne; Cariou, Thierry; Claquin, Pascal; Conan, Pascal; Corre, Anne-Marie; Costes, Laurence; Crouvoisier, Muriel; Del Amo, Yolanda; Derriennic, Hervé; Dindinaud, François; Duran, Robert; Durozier, Maïa; Devesa, Jérémy; Ferreira, Sophie; Feunteun, Eric; Garcia, Nicole; Geslin, Sandrine; Grossteffan, Emilie; Gueux, Aurore; Guillaudeau, Julien; Guillou, Gaël; Jolly, Orianne; Lachaussée, Nicolas; Lafont, Michel; Lagadec, Véronique; Lamoureux, Jézabel; Lauga, Béatrice; Lebreton, Benoît; Lecuyer, Eric; Lehodey, Jean-Paul; Leroux, Cédric; L'Helguen, Stéphane; Macé, Eric; Maria, Eric; Mousseau, Laure; Nowaczyk, Antoine; Pineau, Philippe; Petit, Franck; Pujo-Pay, Mireille; Raimbault, Patrick; Rimmelin-Maury, Peggy; Rouaud, Vanessa; Sauriau, Pierre-Guy; Sultan, Emmanuelle; Susperregui, Nicolas

2018-03-01

In costal systems, particulate organic matter (POM) results from a multiplicity of sources having their respective dynamics in terms of production, decomposition, transport and burial. The POM pool experiences thus considerable spatial and temporal variability. In order to better understand this variability, the present study employs statistical multivariate analyses to investigate links between POM composition and environmental forcings for a panel of twelve coastal systems distributed along the three maritime regions of France and monitored weekly to monthly for 1 to 8 years. At multi-system scale, two main gradients of POC composition have been identified: a 'Continent-Ocean' gradient associated with hydrodynamics, sedimentary dynamics and depth of the water column, and a gradient of trophic status related to nutrient availability. At local scale, seasonality of POC composition appears to be station-specific but still related to part of the above-mentioned forcings. A typology of systems was established by coupling spatial and temporal variability of POC composition. Four groups were highlighted: (1) the estuarine stations where POC composition is dominated by terrestrial POM and driven by hydrodynamics and sedimentary processes, (2) the oligotrophic systems, characterized by the contribution of diazotrophs due to low nutrient availability, and the marine meso/eutroph systems whose POC composition is (3) either deeply dominated by phytoplankton or (4) dominated by phytoplankton but where the contribution of continental and benthic POC is not negligible and is driven by hydrodynamics, sedimentary processes and the height of the water column. Finally, the present study provides several insights into the different forcings to POM composition and dynamics in temperate coastal systems at local and multi-system scales. This work also presents a methodological approach that establishes statistical links between forcings and POM composition, helping to gain more objectively insight of forcings.

Minimum fuel control of a vehicle with a continuously variable transmission. [control system simulation

NASA Technical Reports Server (NTRS)

Burghart, J. H.; Donoghue, J. F.

1980-01-01

The design and evaluation of a control system for a sedan with a heat engine and a continuously variable transmission, is considered in a effort to minimize fuel consumption and achieve satisfactory dynamic response of vehicle variables as the vehicle is driven over a standard driving cycle. Even though the vehicle system was highly nonlinear, attention was restricted to linear control algorithms which could be easily understood and implemented demonstrated by simulation. Simulation results also revealed that the vehicle could exhibit unexpected dynamic behavior which must be taken into account in any control system design.

Dynamic Data-Driven UAV Network for Plume Characterization

DTIC Science & Technology

2016-05-23

data collection where simulations and measurements become a symbiotic feedback control system where simulations inform measurement locations and the...and measurements become a symbiotic feedback control system where simulations inform measurement locations and the measured data augments simulations...data analysis techniques with mobile sensor data collection where simulations and measurements become a symbiotic feedback control system where

Dynamic Transition and Resonance in Coupled Oscillators Under Symmetry-Breaking Fields

NASA Astrophysics Data System (ADS)

Choi, J.; Choi, M. Y.; Chung, M. S.; Yoon, B.-G.

2013-06-01

We investigate numerically the dynamic properties of a system of globally coupled oscillators driven by periodic symmetry-breaking fields in the presence of noise. The phase distribution of the oscillators is computed and a dynamic transition is disclosed. It is further found that the stochastic resonance is closely related to the behavior of the dynamic order parameter, which is in turn explained by the formation of a bi-cluster in the system. Here noise tends to symmetrize the motion of the oscillators, facilitating the bi-cluster formation. The observed resonance appears to be of the same class as the resonance present in the two-dimensional Ising model under oscillating fields.

Driven fragmentation of granular gases.

PubMed

Cruz Hidalgo, Raúl; Pagonabarraga, Ignacio

2008-06-01

The dynamics of homogeneously heated granular gases which fragment due to particle collisions is analyzed. We introduce a kinetic model which accounts for correlations induced at the grain collisions and analyze both the kinetics and relevant distribution functions these systems develop. The work combines analytical and numerical studies based on direct simulation Monte Carlo calculations. A broad family of fragmentation probabilities is considered, and its implications for the system kinetics are discussed. We show that generically these driven materials evolve asymptotically into a dynamical scaling regime. If the fragmentation probability tends to a constant, the grain number diverges at a finite time, leading to a shattering singularity. If the fragmentation probability vanishes, then the number of grains grows monotonously as a power law. We consider different homogeneous thermostats and show that the kinetics of these systems depends weakly on both the grain inelasticity and driving. We observe that fragmentation plays a relevant role in the shape of the velocity distribution of the particles. When the fragmentation is driven by local stochastic events, the long velocity tail is essentially exponential independently of the heating frequency and the breaking rule. However, for a Lowe-Andersen thermostat, numerical evidence strongly supports the conjecture that the scaled velocity distribution follows a generalized exponential behavior f(c) approximately exp(-cn) , with n approximately 1.2 , regarding less the fragmentation mechanisms.

Improving dynamic performances of PWM-driven servo-pneumatic systems via a novel pneumatic circuit.

PubMed

Taghizadeh, Mostafa; Ghaffari, Ali; Najafi, Farid

2009-10-01

In this paper, the effect of pneumatic circuit design on the input-output behavior of PWM-driven servo-pneumatic systems is investigated and their control performances are improved using linear controllers instead of complex and costly nonlinear ones. Generally, servo-pneumatic systems are well known for their nonlinear behavior. However, PWM-driven servo-pneumatic systems have the advantage of flexibility in the design of pneumatic circuits which affects the input-output linearity of the whole system. A simple pneumatic circuit with only one fast switching valve is designed which leads to a quasi-linear input-output relation. The quasi-linear behavior of the proposed circuit is verified both experimentally and by simulations. Closed loop position control experiments are then carried out using linear P- and PD-controllers. Since the output position is noisy and cannot be directly differentiated, a Kalman filter is designed to estimate the velocity of the cylinder. Highly improved tracking performances are obtained using these linear controllers, compared to previous works with nonlinear controllers.

Floquet prethermalization and regimes of heating in a periodically driven, interacting quantum system

NASA Astrophysics Data System (ADS)

Weidinger, Simon A.; Knap, Michael

2017-04-01

We study the regimes of heating in the periodically driven O(N)-model, which is a well established model for interacting quantum many-body systems. By computing the absorbed energy with a non-equilibrium Keldysh Green’s function approach, we establish three dynamical regimes: at short times a single-particle dominated regime, at intermediate times a stable Floquet prethermal regime in which the system ceases to absorb, and at parametrically late times a thermalizing regime. Our simulations suggest that in the thermalizing regime the absorbed energy grows algebraically in time with an exponent that approaches the universal value of 1/2, and is thus significantly slower than linear Joule heating. Our results demonstrate the parametric stability of prethermal states in a many-body system driven at frequencies that are comparable to its microscopic scales. This paves the way for realizing exotic quantum phases, such as time crystals or interacting topological phases, in the prethermal regime of interacting Floquet systems.

The Nurse Leader Role in Crisis Management.

PubMed

Edmonson, Cole; Sumagaysay, Dio; Cueman, Marie; Chappell, Stacey

2016-09-01

Leaders from the American Organization of Nurse Executives describe the dynamic state of today's healthcare system related to crisis management. Adaptive leadership, driven by strong values and morality, can guide leaders and organizations through the most difficult times.

Reversible Vector Ratchet Effect in Skyrmion Systems

NASA Astrophysics Data System (ADS)

Ma, Xiaoyu; Reichhardt, Charles; Reichhardt, Cynthia

Magnetic skyrmions are topological non-trivial spin textures found in several magnetic materials. Since their motion can be controlled using ultralow current densities, skyrmions are appealing for potential applications in spintronics as information carriers and processing devices. In this work, we studied the collective transport properties of driven skyrmions based on a particle-like model with molecular dynamics (MD) simulation. Our results show that ac driven skyrmions interacting with an asymmetric substrate provide a realization of a new class of ratchet system, which we call a vector ratchet, that arises due to the effect of the Magnus term on the skyrmion dynamics. In a vector ratchet, the dc motion induced by the ac drive can be described as a vector that can be rotated up to 360 degrees relative to the substrate asymmetry direction. This could represent a new method for controlling skyrmion motion for spintronic applications.

Dimension reduction for stochastic dynamical systems forced onto a manifold by large drift: a constructive approach with examples from theoretical biology

NASA Astrophysics Data System (ADS)

Parsons, Todd L.; Rogers, Tim

2017-10-01

Systems composed of large numbers of interacting agents often admit an effective coarse-grained description in terms of a multidimensional stochastic dynamical system, driven by small-amplitude intrinsic noise. In applications to biological, ecological, chemical and social dynamics it is common for these models to posses quantities that are approximately conserved on short timescales, in which case system trajectories are observed to remain close to some lower-dimensional subspace. Here, we derive explicit and general formulae for a reduced-dimension description of such processes that is exact in the limit of small noise and well-separated slow and fast dynamics. The Michaelis-Menten law of enzyme-catalysed reactions, and the link between the Lotka-Volterra and Wright-Fisher processes are explored as a simple worked examples. Extensions of the method are presented for infinite dimensional systems and processes coupled to non-Gaussian noise sources.

Dynamic self-organization of side-propelling colloidal rods: experiments and simulations.

PubMed

Vutukuri, Hanumantha Rao; Preisler, Zdeněk; Besseling, Thijs H; van Blaaderen, Alfons; Dijkstra, Marjolein; Huck, Wilhelm T S

2016-12-06

In recent years, there is a growing interest in designing artificial analogues of living systems, fueled not only by potential applications as 'smart micro-machines', but also by the demand for simple models that can be used to study the behavior of their more complex natural counterparts. Here, we present a facile, internally driven, experimental system comprised of fluorescently labeled colloidal silica rods of which the self-propulsion is powered by the decomposition of H 2 O 2 catalyzed by a length-wise half Pt coating of the particles in order to study how shape anisotropy and swimming direction affect the collective behavior. We investigated the emerging structures and their time evolution for various particle concentrations in (quasi-)two dimensional systems for three aspect ratios of the rods on a single particle level using a combination of experiments and simulations. We found that the dynamic self-organization relied on a competition between self-propulsion and phoretic attractions induced by phoresis of the rods. We observed that the particle clustering behavior depends on the concentration as well as the aspect ratio of the rods. Our findings provide a more detailed understanding of dynamic self-organization of anisotropic particles and the role the propulsion direction plays in internally driven systems.

Ultra-fast relaxation, decoherence, and localization of photoexcited states in π-conjugated polymers

NASA Astrophysics Data System (ADS)

Mannouch, Jonathan R.; Barford, William; Al-Assam, Sarah

2018-01-01

The exciton relaxation dynamics of photoexcited electronic states in poly(p-phenylenevinylene) are theoretically investigated within a coarse-grained model, in which both the exciton and nuclear degrees of freedom are treated quantum mechanically. The Frenkel-Holstein Hamiltonian is used to describe the strong exciton-phonon coupling present in the system, while external damping of the internal nuclear degrees of freedom is accounted for by a Lindblad master equation. Numerically, the dynamics are computed using the time evolving block decimation and quantum jump trajectory techniques. The values of the model parameters physically relevant to polymer systems naturally lead to a separation of time scales, with the ultra-fast dynamics corresponding to energy transfer from the exciton to the internal phonon modes (i.e., the C-C bond oscillations), while the longer time dynamics correspond to damping of these phonon modes by the external dissipation. Associated with these time scales, we investigate the following processes that are indicative of the system relaxing onto the emissive chromophores of the polymer: (1) Exciton-polaron formation occurs on an ultra-fast time scale, with the associated exciton-phonon correlations present within half a vibrational time period of the C-C bond oscillations. (2) Exciton decoherence is driven by the decay in the vibrational overlaps associated with exciton-polaron formation, occurring on the same time scale. (3) Exciton density localization is driven by the external dissipation, arising from "wavefunction collapse" occurring as a result of the system-environment interactions. Finally, we show how fluorescence anisotropy measurements can be used to investigate the exciton decoherence process during the relaxation dynamics.

Investigating rare events with nonequilibrium work measurements. I. Nonequilibrium transition path probabilities

NASA Astrophysics Data System (ADS)

Moradi, Mahmoud; Sagui, Celeste; Roland, Christopher

2014-01-01

We have developed a formalism for investigating transition pathways and transition probabilities for rare events in biomolecular systems. In this paper, we set the theoretical framework for employing nonequilibrium work relations to estimate the relative reaction rates associated with different classes of transition pathways. Particularly, we derive an extension of Crook's transient fluctuation theorem, which relates the relative transition rates of driven systems in the forward and reverse directions, and allows for the calculation of these relative rates using work measurements (e.g., in Steered Molecular Dynamics). The formalism presented here can be combined with Transition Path Theory to relate the equilibrium and driven transition rates. The usefulness of this framework is illustrated by means of a Gaussian model and a driven proline dimer.

General relativistic dynamics of an extreme mass-ratio binary interacting with an external body

NASA Astrophysics Data System (ADS)

Yang, Huan; Casals, Marc

2017-10-01

We study the dynamics of a hierarchical three-body system in the general relativistic regime: an extreme mass-ratio inner binary under the tidal influence of an external body. The inner binary consists of a central Schwarzschild black hole and a test body moving around it. We discuss three types of tidal effects on the orbit of the test body. First, the angular momentum of the inner binary precesses around the angular momentum of the outer binary. Second, the tidal field drives a "transient resonance" when the radial and azimuthal frequencies are commensurable. In contrast with resonances driven by the gravitational self-force, this tidal-driven resonance may boost the orbital angular momentum and eccentricity (a relativistic version of the Kozai-Lidov effect). Finally, for an orbit-dynamical effect during the nonresonant phase, we calculate the correction to the innermost stable circular (mean) orbit due to the tidal interaction. Hierarchical three-body systems are potential sources for future space-based gravitational wave missions, and the tidal effects that we find could contribute significantly to their waveform.

Course 3: Modelling Motor Protein Systems

NASA Astrophysics Data System (ADS)

Duke, T.

Contents 1 Making a move: Principles of energy transduction 1.1 Motor proteins and Carnot engines 1.2 Simple Brownian ratchet 1.3 Polymerization ratchet 1.4 Isothermal ratchets 1.5 Motor proteins as isothermal ratchets 1.6 Design principles for effective motors 2 Pulling together: Mechano-chemical model of actomyosin 2.1 Swinging lever-arm model 2.2 Mechano-chemical coupling 2.3 Equivalent isothermal ratchet 2.4 Many motors working together 2.5 Designed to work 2.6 Force-velocity relation 2.7 Dynamical instability and biochemical synchronization 2.8 Transient response ofmuscle 3 Motors at work: Collective properties of motor proteins 3.1 Dynamical instabilities 3.2 Bidirectional movement 3.3 Critical behaviour 3.4 Oscillations 3.5 Dynamic buckling instability 3.6 Undulation of flagella 4 Sense and sensitivity: Mechano-sensation in hearing 4.1 System performance 4.2 Mechano-sensors: Hair bundles 4.3 Active amplification 4.4 Self-tuned criticality 4.5 Motor-driven oscillations 4.6 Channel compliance and relaxation oscillations 4.7 Channel-driven oscillations 4.8 Hearing at the noise limit

A data-driven emulation framework for representing water-food nexus in a changing cold region

NASA Astrophysics Data System (ADS)

Nazemi, A.; Zandmoghaddam, S.; Hatami, S.

2017-12-01

Water resource systems are under increasing pressure globally. Growing population along with competition between water demands and emerging effects of climate change have caused enormous vulnerabilities in water resource management across many regions. Diagnosing such vulnerabilities and provision of effective adaptation strategies requires the availability of simulation tools that can adequately represent the interactions between competing water demands for limiting water resources and inform decision makers about the critical vulnerability thresholds under a range of potential natural and anthropogenic conditions. Despite a significant progress in integrated modeling of water resource systems, regional models are often unable to fully represent the contemplating dynamics within the key elements of water resource systems locally. Here we propose a data-driven approach to emulate a complex regional water resource system model developed for Oldman River Basin in southern Alberta, Canada. The aim of the emulation is to provide a detailed understanding of the trade-offs and interaction at the Oldman Reservoir, which is the key to flood control and irrigated agriculture in this over-allocated semi-arid cold region. Different surrogate models are developed to represent the dynamic of irrigation demand and withdrawal as well as reservoir evaporation and release individually. The nan-falsified offline models are then integrated through the water balance equation at the reservoir location to provide a coupled model for representing the dynamic of reservoir operation and water allocation at the local scale. The performance of individual and integrated models are rigorously examined and sources of uncertainty are highlighted. To demonstrate the practical utility of such surrogate modeling approach, we use the integrated data-driven model for examining the trade-off in irrigation water supply, reservoir storage and release under a range of changing climate, upstream streamflow and local irrigation conditions.

Introduction to State Estimation of High-Rate System Dynamics

PubMed Central

Dodson, Jacob; Joyce, Bryan

2018-01-01

Engineering systems experiencing high-rate dynamic events, including airbags, debris detection, and active blast protection systems, could benefit from real-time observability for enhanced performance. However, the task of high-rate state estimation is challenging, in particular for real-time applications where the rate of the observer’s convergence needs to be in the microsecond range. This paper identifies the challenges of state estimation of high-rate systems and discusses the fundamental characteristics of high-rate systems. A survey of applications and methods for estimators that have the potential to produce accurate estimations for a complex system experiencing highly dynamic events is presented. It is argued that adaptive observers are important to this research. In particular, adaptive data-driven observers are advantageous due to their adaptability and lack of dependence on the system model. PMID:29342855

All-electrical detection of spin dynamics in magnetic antidot lattices by the inverse spin Hall effect

DOE PAGES

Jungfleisch, Matthias B.; Zhang, Wei; Ding, Junjia; ...

2016-02-03

The understanding of spin dynamics in laterally confined structures on sub-micron length scales has become a significant aspect of the development of novel magnetic storage technologies. Numerous ferromagnetic resonance measurements, optical characterization by Kerr microscopy and Brillouin light scattering spectroscopy and x-ray studies were carried out to detect the dynamics in patterned magnetic antidot lattices. Here, we investigate Oersted-field driven spin dynamics in rectangular Ni80Fe20/Pt antidot lattices with different lattice parameters by electrical means. When the system is driven to resonance, a dc voltage across the length of the sample is detected that changes its sign upon field reversal, whichmore » is in agreement with a rectification mechanism based on the inverse spin Hall effect. Furthermore, we show that the voltage output scales linearly with the applied microwave drive in the investigated range of powers. Lastly, our findings have direct implications on the development of engineered magnonics applications and devices.« less

Universal Pinning Energy Barrier for Driven Domain Walls in Thin Ferromagnetic Films

NASA Astrophysics Data System (ADS)

Jeudy, V.; Mougin, A.; Bustingorry, S.; Savero Torres, W.; Gorchon, J.; Kolton, A. B.; Lemaître, A.; Jamet, J.-P.

2016-07-01

We report a comparative study of magnetic field driven domain wall motion in thin films made of different magnetic materials for a wide range of field and temperature. The full thermally activated creep motion, observed below the depinning threshold, is shown to be described by a unique universal energy barrier function. Our findings should be relevant for other systems whose dynamics can be modeled by elastic interfaces moving on disordered energy landscapes.

Flow-driven waves and sink-driven oscillations during aggregation of Dictyostelium discoideum

NASA Astrophysics Data System (ADS)

Gholami, Azam; Zykov, Vladimir; Steinbock, Oliver; Bodenschatz, Eberhard

The slime mold Dictyostelium discoideum (D.d) is a well-known model system for the study of biological pattern formation. Under starvation, D.d. cells aggregate chemotactically towards cAMP signals emitted periodically from an aggregation center. In the natural environment, D.d cells may experience fluid flows that can profoundly change the underlying wave generation process. We investigate spatial-temporal dynamics of a uniformly distributed population of D.d. cells in a flow-through narrow microfluidic channel with a cell-free inlet area. We show that flow can significantly influence the dynamics of the system and lead to a flow- driven instability that initiate downstream traveling cAMP waves. We also show that cell-free boundary regions have a significant effect on the observed patterns and can lead to a new kind of instability. Since there are no cells in the inlet to produce cAMP, the points in the vicinity of the inlet lose cAMP due to advection or diffusion and gain only a little from the upstream of the channel (inlet). In other words, there is a large negative flux of cAMP in the neighborhood close to the inlet, which can be considered as a sink. This negative flux close to the inlet drives a new kind of instability called sink-driven oscillations. Financial support of the MaxSynBio Consortium is acknowledged.

Designing a dynamic data driven application system for estimating real-time load of dissolved organic carbon in a river

Treesearch

Ying Ouyang

2012-01-01

Understanding the dynamics of naturally occurring dissolved organic carbon (DOC) in a river is central to estimating surface water quality, aquatic carbon cycling, and global climate change. Currently, determination of the DOC in surface water is primarily accomplished by manually collecting samples for laboratory analysis, which requires at least 24 h. In other words...

Prototype Development: Context-Driven Dynamic XML Ophthalmologic Data Capture Application.

PubMed

Peissig, Peggy; Schwei, Kelsey M; Kadolph, Christopher; Finamore, Joseph; Cancel, Efrain; McCarty, Catherine A; Okorie, Asha; Thomas, Kate L; Allen Pacheco, Jennifer; Pathak, Jyotishman; Ellis, Stephen B; Denny, Joshua C; Rasmussen, Luke V; Tromp, Gerard; Williams, Marc S; Vrabec, Tamara R; Brilliant, Murray H

2017-09-13

The capture and integration of structured ophthalmologic data into electronic health records (EHRs) has historically been a challenge. However, the importance of this activity for patient care and research is critical. The purpose of this study was to develop a prototype of a context-driven dynamic extensible markup language (XML) ophthalmologic data capture application for research and clinical care that could be easily integrated into an EHR system. Stakeholders in the medical, research, and informatics fields were interviewed and surveyed to determine data and system requirements for ophthalmologic data capture. On the basis of these requirements, an ophthalmology data capture application was developed to collect and store discrete data elements with important graphical information. The context-driven data entry application supports several features, including ink-over drawing capability for documenting eye abnormalities, context-based Web controls that guide data entry based on preestablished dependencies, and an adaptable database or XML schema that stores Web form specifications and allows for immediate changes in form layout or content. The application utilizes Web services to enable data integration with a variety of EHRs for retrieval and storage of patient data. This paper describes the development process used to create a context-driven dynamic XML data capture application for optometry and ophthalmology. The list of ophthalmologic data elements identified as important for care and research can be used as a baseline list for future ophthalmologic data collection activities. ©Peggy Peissig, Kelsey M Schwei, Christopher Kadolph, Joseph Finamore, Efrain Cancel, Catherine A McCarty, Asha Okorie, Kate L Thomas, Jennifer Allen Pacheco, Jyotishman Pathak, Stephen B Ellis, Joshua C Denny, Luke V Rasmussen, Gerard Tromp, Marc S Williams, Tamara R Vrabec, Murray H Brilliant. Originally published in JMIR Medical Informatics (http://medinform.jmir.org), 13.09.2017.

Processes on the emergent landscapes of biochemical reaction networks and heterogeneous cell population dynamics: differentiation in living matters

PubMed Central

Li, Fangting

2017-01-01

The notion of an attractor has been widely employed in thinking about the nonlinear dynamics of organisms and biological phenomena as systems and as processes. The notion of a landscape with valleys and mountains encoding multiple attractors, however, has a rigorous foundation only for closed, thermodynamically non-driven, chemical systems, such as a protein. Recent advances in the theory of nonlinear stochastic dynamical systems and its applications to mesoscopic reaction networks, one reaction at a time, have provided a new basis for a landscape of open, driven biochemical reaction systems under sustained chemostat. The theory is equally applicable not only to intracellular dynamics of biochemical regulatory networks within an individual cell but also to tissue dynamics of heterogeneous interacting cell populations. The landscape for an individual cell, applicable to a population of isogenic non-interacting cells under the same environmental conditions, is defined on the counting space of intracellular chemical compositions x = (x1,x2, … ,xN) in a cell, where xℓ is the concentration of the ℓth biochemical species. Equivalently, for heterogeneous cell population dynamics xℓ is the number density of cells of the ℓth cell type. One of the insights derived from the landscape perspective is that the life history of an individual organism, which occurs on the hillsides of a landscape, is nearly deterministic and ‘programmed’, while population-wise an asynchronous non-equilibrium steady state resides mostly in the lowlands of the landscape. We argue that a dynamic ‘blue-sky’ bifurcation, as a representation of Waddington's landscape, is a more robust mechanism for a cell fate decision and subsequent differentiation than the widely pictured pitch-fork bifurcation. We revisit, in terms of the chemostatic driving forces upon active, living matter, the notions of near-equilibrium thermodynamic branches versus far-from-equilibrium states. The emergent landscape perspective permits a quantitative discussion of a wide range of biological phenomena as nonlinear, stochastic dynamics. PMID:28490602

Dynamic Performance of Subway Vehicle with Linear Induction Motor System

NASA Astrophysics Data System (ADS)

Wu, Pingbo; Luo, Ren; Hu, Yan; Zeng, Jing

The light rail vehicle with Linear Induction Motor (LIM) bogie, which is a new type of urban rail traffic tool, has the advantages of low costs, wide applicability, low noise, simple maintenance and better dynamic behavior. This kind of vehicle, supported and guided by the wheel and rail, is not driven by the wheel/rail adhesion force, but driven by the electromagnetic force between LIM and reaction plate. In this paper, three different types of suspensions and their characteristic are discussed with considering the interactions both between wheel and rail and between LIM and reaction plate. A nonlinear mathematical model of the vehicle with LIM bogie is set up by using the software SIMPACK, and the electromechanical model is also set up on Simulink roof. Then the running behavior of the LIM vehicle is simulated, and the influence of suspension on the vehicle dynamic performance is investigated.

Hyperswitch Network For Hypercube Computer

NASA Technical Reports Server (NTRS)

Chow, Edward; Madan, Herbert; Peterson, John

1989-01-01

Data-driven dynamic switching enables high speed data transfer. Proposed hyperswitch network based on mixed static and dynamic topologies. Routing header modified in response to congestion or faults encountered as path established. Static topology meets requirement if nodes have switching elements that perform necessary routing header revisions dynamically. Hypercube topology now being implemented with switching element in each computer node aimed at designing very-richly-interconnected multicomputer system. Interconnection network connects great number of small computer nodes, using fixed hypercube topology, characterized by point-to-point links between nodes.

Reconstructing latent dynamical noise for better forecasting observables

NASA Astrophysics Data System (ADS)

Hirata, Yoshito

2018-03-01

I propose a method for reconstructing multi-dimensional dynamical noise inspired by the embedding theorem of Muldoon et al. [Dyn. Stab. Syst. 13, 175 (1998)] by regarding multiple predictions as different observables. Then, applying the embedding theorem by Stark et al. [J. Nonlinear Sci. 13, 519 (2003)] for a forced system, I produce time series forecast by supplying the reconstructed past dynamical noise as auxiliary information. I demonstrate the proposed method on toy models driven by auto-regressive models or independent Gaussian noise.

Comparison of driven and simulated "free" stall flutter in a wind tunnel

NASA Astrophysics Data System (ADS)

Culler, Ethan; Farnsworth, John; Fagley, Casey; Seidel, Jurgen

2016-11-01

Stall flutter and dynamic stall have received a significant amount of attention over the years. To experimentally study this problem, the body undergoing stall flutter is typically driven at a characteristic, single frequency sinusoid with a prescribed pitching amplitude and mean angle of attack offset. This approach allows for testing with repeatable kinematics, however it effectively decouples the structural motion from the aerodynamic forcing. Recent results suggest that this driven approach could misrepresent the forcing observed in a "free" stall flutter scenario. Specifically, a dynamically pitched rigid NACA 0018 wing section was tested in the wind tunnel under two modes of operation: (1) Cyber-Physical where "free" stall flutter was physically simulated through a custom motor-control system modeling a torsional spring and (2) Direct Motor-Driven Dynamic Pitch at a single frequency sinusoid representative of the cyber-physical motion. The time-resolved pitch angle and moment were directly measured and compared for each case. It was found that small deviations in the pitch angle trajectory between these two operational cases generate significantly different aerodynamic pitching moments on the wing section, with the pitching moments nearly 180o out of phase in some cases. This work is supported by the Air Force Office of Scientific Research through the Flow Interactions and Control Program and by the National Defense Science and Engineering Graduate Fellowship Program.

Dynamic Data Driven Applications Systems (DDDAS)

DTIC Science & Technology

2012-05-03

response) – Earthquakes, hurricanes, tornados, wildfires, floods, landslides, tsunamis, … • Critical Infrastructure systems – Electric-powergrid...Multiphase Flow Weather and Climate Structural Mechanics Seismic Processing Aerodynamics Geophysical Fluids Quantum Chemistry Actinide Chemistry...Alloys • Approach and Objectives:  Consider porous SMAs:  similar macroscopic behavior but mass /weight is less, and thus attractive for

Coherent control in simple quantum systems

NASA Technical Reports Server (NTRS)

Prants, Sergey V.

1995-01-01

Coherent dynamics of two, three, and four-level quantum systems, simultaneously driven by concurrent laser pulses of arbitrary and different forms, is treated by using a nonperturbative, group-theoretical approach. The respective evolution matrices are calculated in an explicit form. General aspects of controllability of few-level atoms by using laser fields are treated analytically.

Tensegrity and motor-driven effective interactions in a model cytoskeleton

NASA Astrophysics Data System (ADS)

Wang, Shenshen; Wolynes, Peter G.

2012-04-01

Actomyosin networks are major structural components of the cell. They provide mechanical integrity and allow dynamic remodeling of eukaryotic cells, self-organizing into the diverse patterns essential for development. We provide a theoretical framework to investigate the intricate interplay between local force generation, network connectivity, and collective action of molecular motors. This framework is capable of accommodating both regular and heterogeneous pattern formation, arrested coarsening and macroscopic contraction in a unified manner. We model the actomyosin system as a motorized cat's cradle consisting of a crosslinked network of nonlinear elastic filaments subjected to spatially anti-correlated motor kicks acting on motorized (fibril) crosslinks. The phase diagram suggests there can be arrested phase separation which provides a natural explanation for the aggregation and coalescence of actomyosin condensates. Simulation studies confirm the theoretical picture that a nonequilibrium many-body system driven by correlated motor kicks can behave as if it were at an effective equilibrium, but with modified interactions that account for the correlation of the motor driven motions of the actively bonded nodes. Regular aster patterns are observed both in Brownian dynamics simulations at effective equilibrium and in the complete stochastic simulations. The results show that large-scale contraction requires correlated kicking.

How pattern formation in ring networks of excitatory and inhibitory spiking neurons depends on the input current regime.

PubMed

Kriener, Birgit; Helias, Moritz; Rotter, Stefan; Diesmann, Markus; Einevoll, Gaute T

2013-01-01

Pattern formation, i.e., the generation of an inhomogeneous spatial activity distribution in a dynamical system with translation invariant structure, is a well-studied phenomenon in neuronal network dynamics, specifically in neural field models. These are population models to describe the spatio-temporal dynamics of large groups of neurons in terms of macroscopic variables such as population firing rates. Though neural field models are often deduced from and equipped with biophysically meaningful properties, a direct mapping to simulations of individual spiking neuron populations is rarely considered. Neurons have a distinct identity defined by their action on their postsynaptic targets. In its simplest form they act either excitatorily or inhibitorily. When the distribution of neuron identities is assumed to be periodic, pattern formation can be observed, given the coupling strength is supracritical, i.e., larger than a critical weight. We find that this critical weight is strongly dependent on the characteristics of the neuronal input, i.e., depends on whether neurons are mean- or fluctuation driven, and different limits in linearizing the full non-linear system apply in order to assess stability. In particular, if neurons are mean-driven, the linearization has a very simple form and becomes independent of both the fixed point firing rate and the variance of the input current, while in the very strongly fluctuation-driven regime the fixed point rate, as well as the input mean and variance are important parameters in the determination of the critical weight. We demonstrate that interestingly even in "intermediate" regimes, when the system is technically fluctuation-driven, the simple linearization neglecting the variance of the input can yield the better prediction of the critical coupling strength. We moreover analyze the effects of structural randomness by rewiring individual synapses or redistributing weights, as well as coarse-graining on the formation of inhomogeneous activity patterns.

How pattern formation in ring networks of excitatory and inhibitory spiking neurons depends on the input current regime

PubMed Central

Kriener, Birgit; Helias, Moritz; Rotter, Stefan; Diesmann, Markus; Einevoll, Gaute T.

2014-01-01

Pattern formation, i.e., the generation of an inhomogeneous spatial activity distribution in a dynamical system with translation invariant structure, is a well-studied phenomenon in neuronal network dynamics, specifically in neural field models. These are population models to describe the spatio-temporal dynamics of large groups of neurons in terms of macroscopic variables such as population firing rates. Though neural field models are often deduced from and equipped with biophysically meaningful properties, a direct mapping to simulations of individual spiking neuron populations is rarely considered. Neurons have a distinct identity defined by their action on their postsynaptic targets. In its simplest form they act either excitatorily or inhibitorily. When the distribution of neuron identities is assumed to be periodic, pattern formation can be observed, given the coupling strength is supracritical, i.e., larger than a critical weight. We find that this critical weight is strongly dependent on the characteristics of the neuronal input, i.e., depends on whether neurons are mean- or fluctuation driven, and different limits in linearizing the full non-linear system apply in order to assess stability. In particular, if neurons are mean-driven, the linearization has a very simple form and becomes independent of both the fixed point firing rate and the variance of the input current, while in the very strongly fluctuation-driven regime the fixed point rate, as well as the input mean and variance are important parameters in the determination of the critical weight. We demonstrate that interestingly even in “intermediate” regimes, when the system is technically fluctuation-driven, the simple linearization neglecting the variance of the input can yield the better prediction of the critical coupling strength. We moreover analyze the effects of structural randomness by rewiring individual synapses or redistributing weights, as well as coarse-graining on the formation of inhomogeneous activity patterns. PMID:24501591

Cooperation guided by the coexistence of imitation dynamics and aspiration dynamics in structured populations

NASA Astrophysics Data System (ADS)

Xu, Kuangyi; Li, Kun; Cong, Rui; Wang, Long

2017-02-01

In the framework of the evolutionary game theory, two fundamentally different mechanisms, the imitation process and the aspiration-driven dynamics, can be adopted by players to update their strategies. In the former case, individuals imitate the strategy of a more successful peer, while in the latter case individuals change their strategies based on a comparison of payoffs they collect in the game to their own aspiration levels. Here we explore how cooperation evolves for the coexistence of these two dynamics. Intriguingly, cooperation reaches its lowest level when a certain moderate fraction of individuals pick aspiration-level-driven rule while the others choose pairwise comparison rule. Furthermore, when individuals can adjust their update rules besides their strategies, either imitation dynamics or aspiration-driven dynamics will finally take over the entire population, and the stationary cooperation level is determined by the outcome of competition between these two dynamics. We find that appropriate synergetic effects and moderate aspiration level boost the fixation probability of aspiration-driven dynamics most effectively. Our work may be helpful in understanding the cooperative behavior induced by the coexistence of imitation dynamics and aspiration dynamics in the society.

Bursting dynamics in Rayleigh-Bénard convection

NASA Astrophysics Data System (ADS)

Dan, Surajit; Ghosh, Manojit; Nandukumar, Yada; Dana, Syamal K.; Pal, Pinaki

2017-06-01

We report bursting dynamics in a parametrically driven Rayleigh-Bénard convection (RBC) model of low Prandtl-number fluids with free-slip boundary conditions. A four dimensional RBC model [P. Pal, K. Kumar, P. Maity, S.K. Dana, Phys. Rev. E 87, 023001 (2013)] is used for this study. The dynamical system shows pitchfork, Hopf and gluing bifurcations near the onset of RBC of low Prandtl-number fluids. Around the bifurcation points, when the Rayleigh number of the system is slowly modulated periodically, two unknown kinds of bursting appears, namely, Hopf/Hopf via pitchfork bifurcation and Hopf/Hopf via gluing bifurcation besides the conventional Hopf/Hopf (elliptical) and pitchfork/pitchfork bursting.

A dynamic system with digital lock-in-photon-counting for pharmacokinetic diffuse fluorescence tomography

NASA Astrophysics Data System (ADS)

Yin, Guoyan; Zhang, Limin; Zhang, Yanqi; Liu, Han; Du, Wenwen; Ma, Wenjuan; Zhao, Huijuan; Gao, Feng

2018-02-01

Pharmacokinetic diffuse fluorescence tomography (DFT) can describe the metabolic processes of fluorescent agents in biomedical tissue and provide helpful information for tumor differentiation. In this paper, a dynamic DFT system was developed by employing digital lock-in-photon-counting with square wave modulation, which predominates in ultra-high sensitivity and measurement parallelism. In this system, 16 frequency-encoded laser diodes (LDs) driven by self-designed light source system were distributed evenly in the imaging plane and irradiated simultaneously. Meanwhile, 16 detection fibers collected emission light in parallel by the digital lock-in-photon-counting module. The fundamental performances of the proposed system were assessed with phantom experiments in terms of stability, linearity, anti-crosstalk as well as images reconstruction. The results validated the availability of the proposed dynamic DFT system.

Contributions of Dynamic Systems Theory to Cognitive Development

PubMed Central

Spencer, John P.; Austin, Andrew; Schutte, Anne R.

2015-01-01

This paper examines the contributions of dynamic systems theory to the field of cognitive development, focusing on modeling using dynamic neural fields. A brief overview highlights the contributions of dynamic systems theory and the central concepts of dynamic field theory (DFT). We then probe empirical predictions and findings generated by DFT around two examples—the DFT of infant perseverative reaching that explains the Piagetian A-not-B error, and the DFT of spatial memory that explain changes in spatial cognition in early development. A systematic review of the literature around these examples reveals that computational modeling is having an impact on empirical research in cognitive development; however, this impact does not extend to neural and clinical research. Moreover, there is a tendency for researchers to interpret models narrowly, anchoring them to specific tasks. We conclude on an optimistic note, encouraging both theoreticians and experimentalists to work toward a more theory-driven future. PMID:26052181

Understanding force-generating microtubule systems through in vitro reconstitution

PubMed Central

Kok, Maurits; Dogterom, Marileen

2016-01-01

ABSTRACT Microtubules switch between growing and shrinking states, a feature known as dynamic instability. The biochemical parameters underlying dynamic instability are modulated by a wide variety of microtubule-associated proteins that enable the strict control of microtubule dynamics in cells. The forces generated by controlled growth and shrinkage of microtubules drive a large range of processes, including organelle positioning, mitotic spindle assembly, and chromosome segregation. In the past decade, our understanding of microtubule dynamics and microtubule force generation has progressed significantly. Here, we review the microtubule-intrinsic process of dynamic instability, the effect of external factors on this process, and how the resulting forces act on various biological systems. Recently, reconstitution-based approaches have strongly benefited from extensive biochemical and biophysical characterization of individual components that are involved in regulating or transmitting microtubule-driven forces. We will focus on the current state of reconstituting increasingly complex biological systems and provide new directions for future developments. PMID:27715396

Automated adaptive inference of phenomenological dynamical models.

PubMed

Daniels, Bryan C; Nemenman, Ilya

2015-08-21

Dynamics of complex systems is often driven by large and intricate networks of microscopic interactions, whose sheer size obfuscates understanding. With limited experimental data, many parameters of such dynamics are unknown, and thus detailed, mechanistic models risk overfitting and making faulty predictions. At the other extreme, simple ad hoc models often miss defining features of the underlying systems. Here we develop an approach that instead constructs phenomenological, coarse-grained models of network dynamics that automatically adapt their complexity to the available data. Such adaptive models produce accurate predictions even when microscopic details are unknown. The approach is computationally tractable, even for a relatively large number of dynamical variables. Using simulated data, it correctly infers the phase space structure for planetary motion, avoids overfitting in a biological signalling system and produces accurate predictions for yeast glycolysis with tens of data points and over half of the interacting species unobserved.

Automated adaptive inference of phenomenological dynamical models

PubMed Central

Daniels, Bryan C.; Nemenman, Ilya

2015-01-01

Dynamics of complex systems is often driven by large and intricate networks of microscopic interactions, whose sheer size obfuscates understanding. With limited experimental data, many parameters of such dynamics are unknown, and thus detailed, mechanistic models risk overfitting and making faulty predictions. At the other extreme, simple ad hoc models often miss defining features of the underlying systems. Here we develop an approach that instead constructs phenomenological, coarse-grained models of network dynamics that automatically adapt their complexity to the available data. Such adaptive models produce accurate predictions even when microscopic details are unknown. The approach is computationally tractable, even for a relatively large number of dynamical variables. Using simulated data, it correctly infers the phase space structure for planetary motion, avoids overfitting in a biological signalling system and produces accurate predictions for yeast glycolysis with tens of data points and over half of the interacting species unobserved. PMID:26293508

Machine Learning

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chikkagoudar, Satish; Chatterjee, Samrat; Thomas, Dennis G.

The absence of a robust and unified theory of cyber dynamics presents challenges and opportunities for using machine learning based data-driven approaches to further the understanding of the behavior of such complex systems. Analysts can also use machine learning approaches to gain operational insights. In order to be operationally beneficial, cybersecurity machine learning based models need to have the ability to: (1) represent a real-world system, (2) infer system properties, and (3) learn and adapt based on expert knowledge and observations. Probabilistic models and Probabilistic graphical models provide these necessary properties and are further explored in this chapter. Bayesian Networksmore » and Hidden Markov Models are introduced as an example of a widely used data driven classification/modeling strategy.« less

Time-dependent nonlinear Jaynes-Cummings dynamics of a trapped ion

NASA Astrophysics Data System (ADS)

Krumm, F.; Vogel, W.

2018-04-01

In quantum interaction problems with explicitly time-dependent interaction Hamiltonians, the time ordering plays a crucial role for describing the quantum evolution of the system under consideration. In such complex scenarios, exact solutions of the dynamics are rarely available. Here we study the nonlinear vibronic dynamics of a trapped ion, driven in the resolved sideband regime with some small frequency mismatch. By describing the pump field in a quantized manner, we are able to derive exact solutions for the dynamics of the system. This eventually allows us to provide analytical solutions for various types of time-dependent quantities. In particular, we study in some detail the electronic and the motional quantum dynamics of the ion, as well as the time evolution of the nonclassicality of the motional quantum state.

Dynamic model of time-dependent complex networks.

PubMed

Hill, Scott A; Braha, Dan

2010-10-01

The characterization of the "most connected" nodes in static or slowly evolving complex networks has helped in understanding and predicting the behavior of social, biological, and technological networked systems, including their robustness against failures, vulnerability to deliberate attacks, and diffusion properties. However, recent empirical research of large dynamic networks (characterized by irregular connections that evolve rapidly) has demonstrated that there is little continuity in degree centrality of nodes over time, even when their degree distributions follow a power law. This unexpected dynamic centrality suggests that the connections in these systems are not driven by preferential attachment or other known mechanisms. We present an approach to explain real-world dynamic networks and qualitatively reproduce these dynamic centrality phenomena. This approach is based on a dynamic preferential attachment mechanism, which exhibits a sharp transition from a base pure random walk scheme.

System-level power optimization for real-time distributed embedded systems

NASA Astrophysics Data System (ADS)

Luo, Jiong

Power optimization is one of the crucial design considerations for modern electronic systems. In this thesis, we present several system-level power optimization techniques for real-time distributed embedded systems, based on dynamic voltage scaling, dynamic power management, and management of peak power and variance of the power profile. Dynamic voltage scaling has been widely acknowledged as an important and powerful technique to trade off dynamic power consumption and delay. Efficient dynamic voltage scaling requires effective variable-voltage scheduling mechanisms that can adjust voltages and clock frequencies adaptively based on workloads and timing constraints. For this purpose, we propose static variable-voltage scheduling algorithms utilizing criticalpath driven timing analysis for the case when tasks are assumed to have uniform switching activities, as well as energy-gradient driven slack allocation for a more general scenario. The proposed techniques can achieve closeto-optimal power savings with very low computational complexity, without violating any real-time constraints. We also present algorithms for power-efficient joint scheduling of multi-rate periodic task graphs along with soft aperiodic tasks. The power issue is addressed through both dynamic voltage scaling and power management. Periodic task graphs are scheduled statically. Flexibility is introduced into the static schedule to allow the on-line scheduler to make local changes to PE schedules through resource reclaiming and slack stealing, without interfering with the validity of the global schedule. We provide a unified framework in which the response times of aperiodic tasks and power consumption are dynamically optimized simultaneously. Interconnection network fabrics point to a new generation of power-efficient and scalable interconnection architectures for distributed embedded systems. As the system bandwidth continues to increase, interconnection networks become power/energy limited as well. Variable-frequency links have been designed by circuit designers for both parallel and serial links, which can adaptively regulate the supply voltage of transceivers to a desired link frequency, to exploit the variations in bandwidth requirement for power savings. We propose solutions for simultaneous dynamic voltage scaling of processors and links. The proposed solution considers real-time scheduling, flow control, and packet routing jointly. It can trade off the power consumption on processors and communication links via efficient slack allocation, and lead to more power savings than dynamic voltage scaling on processors alone. For battery-operated systems, the battery lifespan is an important concern. Due to the effects of discharge rate and battery recovery, the discharge pattern of batteries has an impact on the battery lifespan. Battery models indicate that even under the same average power consumption, reducing peak power current and variance in the power profile can increase the battery efficiency and thereby prolong battery lifetime. To take advantage of these effects, we propose battery-driven scheduling techniques for embedded applications, to reduce the peak power and the variance in the power profile of the overall system under real-time constraints. The proposed scheduling algorithms are also beneficial in addressing reliability and signal integrity concerns by effectively controlling peak power and variance of the power profile.

On Connection Between Topology and Memory Loss in Sheared Granular Materials

NASA Astrophysics Data System (ADS)

Kovalcinova, Lenka; Kramar, Miro; Mischaikow, Konstantin; Kondic, Lou

We present combined results of discrete element simulations and topological data analysis that allows us to characterize the geometrical properties of force networks. Our numerical setup consists of the system of cylindrical particles placed inside rectangular box with periodic boundary conditions along the horizontal direction. System dynamics is driven by constant shearing speed of the top and bottom walls (in the opposite directions) and pressure applied on the top wall in a dense flow regime. Our study reveals the origin of memory loss in granular systems through local rapid changes in force networks. To understand these rapid events we analyze the evolution of the largest Lyapunov exponent in a simpler case of granular system without inter-particle friction and explore a correlation with topological measures. Surprisingly, our results suggest that the memory loss is driven mainly by pressure even in the case of fixed inertial number. We conclude that the interplay between physical properties of the granular system and force network geometry is a key to understand the dynamics of the sheared systems. This research was supported by NSF Grant No. DMS-1521717 and DARPA No. HR0011-16-2-0033.

Feedforward Categorization on AER Motion Events Using Cortex-Like Features in a Spiking Neural Network.

PubMed

Zhao, Bo; Ding, Ruoxi; Chen, Shoushun; Linares-Barranco, Bernabe; Tang, Huajin

2015-09-01

This paper introduces an event-driven feedforward categorization system, which takes data from a temporal contrast address event representation (AER) sensor. The proposed system extracts bio-inspired cortex-like features and discriminates different patterns using an AER based tempotron classifier (a network of leaky integrate-and-fire spiking neurons). One of the system's most appealing characteristics is its event-driven processing, with both input and features taking the form of address events (spikes). The system was evaluated on an AER posture dataset and compared with two recently developed bio-inspired models. Experimental results have shown that it consumes much less simulation time while still maintaining comparable performance. In addition, experiments on the Mixed National Institute of Standards and Technology (MNIST) image dataset have demonstrated that the proposed system can work not only on raw AER data but also on images (with a preprocessing step to convert images into AER events) and that it can maintain competitive accuracy even when noise is added. The system was further evaluated on the MNIST dynamic vision sensor dataset (in which data is recorded using an AER dynamic vision sensor), with testing accuracy of 88.14%.

Using the Time-Driven Activity-Based Costing Model in the Eye Clinic at The Hospital for Sick Children: A Case Study and Lessons Learned.

PubMed

Gulati, Sanchita; During, David; Mainland, Jeff; Wong, Agnes M F

2018-01-01

One of the key challenges to healthcare organizations is the development of relevant and accurate cost information. In this paper, we used time-driven activity-based costing (TDABC) method to calculate the costs of treating individual patients with specific medical conditions over their full cycle of care. We discussed how TDABC provides a critical, systematic and data-driven approach to estimate costs accurately and dynamically, as well as its potential to enable structural and rational cost reduction to bring about a sustainable healthcare system. © 2018 Longwoods Publishing.

Anomalous metastability in a temperature-driven transition

NASA Astrophysics Data System (ADS)

Ibáñez Berganza, M.; Coletti, P.; Petri, A.

2014-06-01

The Langer theory of metastability provides a description of the lifetime and properties of the metastable phase of the Ising model field-driven transition, describing the magnetic-field-driven transition in ferromagnets and the chemical-potential-driven transition of fluids. An immediate further step is to apply it to the study of a transition driven by the temperature, as the one exhibited by the two-dimensional Potts model. For this model, a study based on the analytical continuation of the free energy (Meunier J. L. and Morel A., Eur. Phys. J. B, 13 (2000) 341) predicts the anomalous vanishing of the metastable temperature range in the large-system-size limit, an issue that has been controversial since the eighties. By a GPU algorithm we compare the Monte Carlo dynamics with the theory. For temperatures close to the transition we obtain agreement and characterize the dependence on the system size, which is essentially different with respect to the Ising case. For smaller temperatures, we observe the onset of stationary states with non-Boltzmann statistics, not predicted by the theory.

Collective Transport Properties of Driven Skyrmions with Random Disorder

NASA Astrophysics Data System (ADS)

Reichhardt, C.; Ray, D.; Reichhardt, C. J. Olson

2015-05-01

We use particle-based simulations to examine the static and driven collective phases of Skyrmions interacting with random quenched disorder. We show that nondissipative effects due to the Magnus term reduce the depinning threshold and strongly affect the Skyrmion motion and the nature of the dynamic phases. The quenched disorder causes the Hall angle to become drive dependent in the moving Skyrmion phase, while different flow regimes produce distinct signatures in the transport curves. For weak disorder, the Skyrmions form a pinned crystal and depin elastically, while for strong disorder the system forms a pinned amorphous state that depins plastically. At high drives the Skyrmions can dynamically reorder into a moving crystal, with the onset of reordering determined by the strength of the Magnus term.

Resonant Thermalization of Periodically Driven Strongly Correlated Electrons

NASA Astrophysics Data System (ADS)

Peronaci, Francesco; Schiró, Marco; Parcollet, Olivier

2018-05-01

We study the dynamics of the Fermi-Hubbard model driven by a time-periodic modulation of the interaction within nonequilibrium dynamical mean-field theory. For moderate interaction, we find clear evidence of thermalization to a genuine infinite-temperature state with no residual oscillations. Quite differently, in the strongly correlated regime, we find a quasistationary extremely long-lived state with oscillations synchronized with the drive (Floquet prethermalization). Remarkably, the nature of this state dramatically changes upon tuning the drive frequency. In particular, we show the existence of a critical frequency at which the system rapidly thermalizes despite the large interaction. We characterize this resonant thermalization and provide an analytical understanding in terms of a breakdown of the periodic Schrieffer-Wolff transformation.

Sloshing of Cryogenic Helium Driven by Lateral Impulse/Gravity Gradient-Dominated/or g-Jitter-Dominated Accelerations and Orbital Dynamics

NASA Technical Reports Server (NTRS)

Hung, R. J.; Long, Y. T.; Zu, G. J.

1996-01-01

The coupling of slosh dynamics within a partially filled rotating dewar of superfluid helium 11 with spacecraft orbital dynamics is investigated in response to the environmental disturbances of (a) lateral impulses, (b) gravity gradients and (c) g-jitter forces. The purpose of this study is to investigate how the coupling of helium 11 fluid slosh dynamics driven by three cases of environmental force with spacecraft dynamics can affect the bubble deformations and their associated fluid and spacecraft mass centre fluctuations. The numerical computation of slosh dynamics is based on a rotational frame, while the spacecraft dynamics is associated with a non-rotational frame. Results show that the major contribution of orbital dynamics is driven by coupling with slosh dynamics. Neglecting the effect of slosh dynamics acting on the spacecraft may lead to the wrong results for the development of orbital and attitude control techniques.

Entanglement control in a superconducting qubit system by an electromagnetic field

NASA Astrophysics Data System (ADS)

Zhang, Y. Q.; Xu, J. B.

2011-08-01

By making use of the dynamical algebraic method we investigate a quantum system consisting of superconducting qubits interacting with data buses, where the qubits are driven by time-dependent electromagnetic field and obtain an explicit expression of time evolution operator. Furthermore, we explore the entanglement dynamics and the influence of the time-dependent electromagnetic field and the initial state on the entanglement sudden death and birth for the system. It is shown that the entanglement between the qubit and bus as well as the entanglement sudden death and birth can be controlled by the time-dependent electromagnetic field.

InfoSymbiotics/DDDAS - The power of Dynamic Data Driven Applications Systems for New Capabilities in Environmental -, Geo-, and Space- Sciences

NASA Astrophysics Data System (ADS)

Darema, F.

2016-12-01

InfoSymbiotics/DDDAS embodies the power of Dynamic Data Driven Applications Systems (DDDAS), a concept whereby an executing application model is dynamically integrated, in a feed-back loop, with the real-time data-acquisition and control components, as well as other data sources of the application system. Advanced capabilities can be created through such new computational approaches in modeling and simulations, and in instrumentation methods, and include: enhancing the accuracy of the application model; speeding-up the computation to allow faster and more comprehensive models of a system, and create decision support systems with the accuracy of full-scale simulations; in addition, the notion of controlling instrumentation processes by the executing application results in more efficient management of application-data and addresses challenges of how to architect and dynamically manage large sets of heterogeneous sensors and controllers, an advance over the static and ad-hoc ways of today - with DDDAS these sets of resources can be managed adaptively and in optimized ways. Large-Scale-Dynamic-Data encompasses the next wave of Big Data, and namely dynamic data arising from ubiquitous sensing and control in engineered, natural, and societal systems, through multitudes of heterogeneous sensors and controllers instrumenting these systems, and where opportunities and challenges at these "large-scales" relate not only to data size but the heterogeneity in data, data collection modalities, fidelities, and timescales, ranging from real-time data to archival data. In tandem with this important dimension of dynamic data, there is an extended view of Big Computing, which includes the collective computing by networked assemblies of multitudes of sensors and controllers, this range from the high-end to the real-time seamlessly integrated and unified, and comprising the Large-Scale-Big-Computing. InfoSymbiotics/DDDAS engenders transformative impact in many application domains, ranging from the nano-scale to the terra-scale and to the extra-terra-scale. The talk will address opportunities for new capabilities together with corresponding research challenges, with illustrative examples from several application areas including environmental sciences, geosciences, and space sciences.

Analytical Studies on the Synchronization of a Network of Linearly-Coupled Simple Chaotic Systems

NASA Astrophysics Data System (ADS)

Sivaganesh, G.; Arulgnanam, A.; Seethalakshmi, A. N.; Selvaraj, S.

2018-05-01

We present explicit generalized analytical solutions for a network of linearly-coupled simple chaotic systems. Analytical solutions are obtained for the normalized state equations of a network of linearly-coupled systems driven by a common chaotic drive system. Two parameter bifurcation diagrams revealing the various hidden synchronization regions, such as complete, phase and phase-lag synchronization are identified using the analytical results. The synchronization dynamics and their stability are studied using phase portraits and the master stability function, respectively. Further, experimental results for linearly-coupled simple chaotic systems are presented to confirm the analytical results. The synchronization dynamics of a network of chaotic systems studied analytically is reported for the first time.

Time-resolved photoelectron spectroscopy of IR-driven electron dynamics in a charge transfer model system.

PubMed

Falge, Mirjam; Fröbel, Friedrich Georg; Engel, Volker; Gräfe, Stefanie

2017-08-02

If the adiabatic approximation is valid, electrons smoothly adapt to molecular geometry changes. In contrast, as a characteristic of diabatic dynamics, the electron density does not follow the nuclear motion. Recently, we have shown that the asymmetry in time-resolved photoelectron spectra serves as a tool to distinguish between these dynamics [Falge et al., J. Phys. Chem. Lett., 2012, 3, 2617]. Here, we investigate the influence of an additional, moderately intense infrared (IR) laser field, as often applied in attosecond time-resolved experiments, on such asymmetries. This is done using a simple model for coupled electronic-nuclear motion. We calculate time-resolved photoelectron spectra and their asymmetries and demonstrate that the spectra directly map the bound electron-nuclear dynamics. From the asymmetries, we can trace the IR field-induced population transfer and both the field-driven and intrinsic (non-)adiabatic dynamics. This holds true when considering superposition states accompanied by electronic coherences. The latter are observable in the asymmetries for sufficiently short XUV pulses to coherently probe the coupled states. It is thus documented that the asymmetry is a measure for phases in bound electron wave packets and non-adiabatic dynamics.

Differentiation Driven Changes in the Dynamic Organization of Basal Transcription Initiation

PubMed Central

Giglia-Mari, Giuseppina; Mourgues, Sophie; Nonnekens, Julie; Andrieux, Lise O.; de Wit, Jan; Miquel, Catherine; Wijgers, Nils; Maas, Alex; Fousteri, Maria; Hoeijmakers, Jan H. J.; Vermeulen, Wim

2009-01-01

Studies based on cell-free systems and on in vitro–cultured living cells support the concept that many cellular processes, such as transcription initiation, are highly dynamic: individual proteins stochastically bind to their substrates and disassemble after reaction completion. This dynamic nature allows quick adaptation of transcription to changing conditions. However, it is unknown to what extent this dynamic transcription organization holds for postmitotic cells embedded in mammalian tissue. To allow analysis of transcription initiation dynamics directly into living mammalian tissues, we created a knock-in mouse model expressing fluorescently tagged TFIIH. Surprisingly and in contrast to what has been observed in cultured and proliferating cells, postmitotic murine cells embedded in their tissue exhibit a strong and long-lasting transcription-dependent immobilization of TFIIH. This immobilization is both differentiation driven and development dependent. Furthermore, although very statically bound, TFIIH can be remobilized to respond to new transcriptional needs. This divergent spatiotemporal transcriptional organization in different cells of the soma revisits the generally accepted highly dynamic concept of the kinetic framework of transcription and shows how basic processes, such as transcription, can be organized in a fundamentally different fashion in intact organisms as previously deduced from in vitro studies. PMID:19841728

DDDAS for space applications

NASA Astrophysics Data System (ADS)

Blasch, Erik; Pham, Khanh D.; Shen, Dan; Chen, Genshe

2018-05-01

The dynamic data-driven applications systems (DDDAS) paradigm is meant to inject measurements into the execution model for enhanced systems performance. One area off interest in DDDAS is for space situation awareness (SSA). For SSA, data is collected about the space environment to determine object motions, environments, and model updates. Dynamically coupling between the data and models enhances the capabilities of each system by complementing models with data for system control, execution, and sensor management. The paper overviews some of the recent developments in SSA made possible from DDDAS techniques which are for object detection, resident space object tracking, atmospheric models for enhanced sensing, cyber protection, and information management.

Dynamic regime of coherent population trapping and optimization of frequency modulation parameters in atomic clocks.

PubMed

Yudin, V I; Taichenachev, A V; Basalaev, M Yu; Kovalenko, D V

2017-02-06

We theoretically investigate the dynamic regime of coherent population trapping (CPT) in the presence of frequency modulation (FM). We have formulated the criteria for quasi-stationary (adiabatic) and dynamic (non-adiabatic) responses of atomic system driven by this FM. Using the density matrix formalism for Λ system, the error signal is exactly calculated and optimized. It is shown that the optimal FM parameters correspond to the dynamic regime of atomic-field interaction, which significantly differs from conventional description of CPT resonances in the frame of quasi-stationary approach (under small modulation frequency). Obtained theoretical results are in good qualitative agreement with different experiments. Also we have found CPT-analogue of Pound-Driver-Hall regime of frequency stabilization.

Gauge theory for finite-dimensional dynamical systems.

PubMed

Gurfil, Pini

2007-06-01

Gauge theory is a well-established concept in quantum physics, electrodynamics, and cosmology. This concept has recently proliferated into new areas, such as mechanics and astrodynamics. In this paper, we discuss a few applications of gauge theory in finite-dimensional dynamical systems. We focus on the concept of rescriptive gauge symmetry, which is, in essence, rescaling of an independent variable. We show that a simple gauge transformation of multiple harmonic oscillators driven by chaotic processes can render an apparently "disordered" flow into a regular dynamical process, and that there exists a strong connection between gauge transformations and reduction theory of ordinary differential equations. Throughout the discussion, we demonstrate the main ideas by considering examples from diverse fields, including quantum mechanics, chemistry, rigid-body dynamics, and information theory.

Epidemic Dynamics in Open Quantum Spin Systems

NASA Astrophysics Data System (ADS)

Pérez-Espigares, Carlos; Marcuzzi, Matteo; Gutiérrez, Ricardo; Lesanovsky, Igor

2017-10-01

We explore the nonequilibrium evolution and stationary states of an open many-body system that displays epidemic spreading dynamics in a classical and a quantum regime. Our study is motivated by recent experiments conducted in strongly interacting gases of highly excited Rydberg atoms where the facilitated excitation of Rydberg states competes with radiative decay. These systems approximately implement open quantum versions of models for population dynamics or disease spreading where species can be in a healthy, infected or immune state. We show that in a two-dimensional lattice, depending on the dominance of either classical or quantum effects, the system may display a different kind of nonequilibrium phase transition. We moreover discuss the observability of our findings in laser driven Rydberg gases with particular focus on the role of long-range interactions.

Discrete Time-Crystalline Order in Cavity and Circuit QED Systems

NASA Astrophysics Data System (ADS)

Gong, Zongping; Hamazaki, Ryusuke; Ueda, Masahito

2018-01-01

Discrete time crystals are a recently proposed and experimentally observed out-of-equilibrium dynamical phase of Floquet systems, where the stroboscopic dynamics of a local observable repeats itself at an integer multiple of the driving period. We address this issue in a driven-dissipative setup, focusing on the modulated open Dicke model, which can be implemented by cavity or circuit QED systems. In the thermodynamic limit, we employ semiclassical approaches and find rich dynamical phases on top of the discrete time-crystalline order. In a deep quantum regime with few qubits, we find clear signatures of a transient discrete time-crystalline behavior, which is absent in the isolated counterpart. We establish a phenomenology of dissipative discrete time crystals by generalizing the Landau theory of phase transitions to Floquet open systems.

Sensor Web Dynamic Measurement Techniques and Adaptive Observing Strategies

NASA Technical Reports Server (NTRS)

Talabac, Stephen J.

2004-01-01

Sensor Web observing systems may have the potential to significantly improve our ability to monitor, understand, and predict the evolution of rapidly evolving, transient, or variable environmental features and events. This improvement will come about by integrating novel data collection techniques, new or improved instruments, emerging communications technologies and protocols, sensor mark-up languages, and interoperable planning and scheduling systems. In contrast to today's observing systems, "event-driven" sensor webs will synthesize real- or near-real time measurements and information from other platforms and then react by reconfiguring the platforms and instruments to invoke new measurement modes and adaptive observation strategies. Similarly, "model-driven" sensor webs will utilize environmental prediction models to initiate targeted sensor measurements or to use a new observing strategy. The sensor web concept contrasts with today's data collection techniques and observing system operations concepts where independent measurements are made by remote sensing and in situ platforms that do not share, and therefore cannot act upon, potentially useful complementary sensor measurement data and platform state information. This presentation describes NASA's view of event-driven and model-driven Sensor Webs and highlights several research and development activities at the Goddard Space Flight Center.

Dynamics of bow-tie shaped bursting: Forced pendulum with dynamic feedback.

PubMed

Hongray, Thotreithem; Balakrishnan, Janaki

2016-12-01

A detailed study is performed on the parameter space of the mechanical system of a driven pendulum with damping and constant torque under feedback control. We report an interesting bow-tie shaped bursting oscillatory behaviour, which is exhibited for small driving frequencies, in a certain parameter regime, which has not been reported earlier in this forced system with dynamic feedback. We show that the bursting oscillations are caused because of a transition of the quiescent state to the spiking state by a saddle-focus bifurcation, and because of another saddle-focus bifurcation, which leads to cessation of spiking, bringing the system back to the quiescent state. The resting period between two successive bursts (T rest ) is estimated analytically.

Joint Loads and Cartilage Stress in Intact Joints of Military Transtibial Amputees: Enhancing Quality of Life

DTIC Science & Technology

2017-04-01

crosstalk); analysis of tested subjects underway. 4) Developed analytical methods to obtain knee joint loads using EMG-driven inverse dynamics; analysis of...13/2018. Completion %: 40. Task 1.3: EMG-driven inverse dynamic (ID) analyses with OpenSim for amputee and control group subjects. Target date: 1...predicted by EMG-driven inverse dynamics. Two-three conference papers are being prepared for submission in February 2017. Other achievements. None

Non-smooth saddle-node bifurcations III: Strange attractors in continuous time

NASA Astrophysics Data System (ADS)

Fuhrmann, G.

2016-08-01

Non-smooth saddle-node bifurcations give rise to minimal sets of interesting geometry built of so-called strange non-chaotic attractors. We show that certain families of quasiperiodically driven logistic differential equations undergo a non-smooth bifurcation. By a previous result on the occurrence of non-smooth bifurcations in forced discrete time dynamical systems, this yields that within the class of families of quasiperiodically driven differential equations, non-smooth saddle-node bifurcations occur in a set with non-empty C2-interior.

Aspects of jamming in two-dimensional athermal frictionless systems.

PubMed

Reichhardt, C; Reichhardt, C J Olson

2014-05-07

In this work we provide an overview of jamming transitions in two dimensional systems focusing on the limit of frictionless particle interactions in the absence of thermal fluctuations. We first discuss jamming in systems with short range repulsive interactions, where the onset of jamming occurs at a critical packing density and where certain quantities show a divergence indicative of critical behavior. We describe how aspects of the dynamics change as the jamming density is approached and how these dynamics can be explored using externally driven probes. Different particle shapes can produce jamming densities much lower than those observed for disk-shaped particles, and we show how jamming exhibits fragility for some shapes while for other shapes this is absent. Next we describe the effects of long range interactions and jamming behavior in systems such as charged colloids, vortices in type-II superconductors, and dislocations. We consider the effect of adding obstacles to frictionless jamming systems and discuss connections between this type of jamming and systems that exhibit depinning transitions. Finally, we discuss open questions such as whether the jamming transition in all these different systems can be described by the same or a small subset of universal behaviors, as well as future directions for studies of jamming transitions in two dimensional systems, such as jamming in self-driven or active matter systems.

The nature of the laning transition in two dimensions

NASA Astrophysics Data System (ADS)

Glanz, T.; Löwen, H.

2012-11-01

If a binary colloidal mixture is oppositely driven by an external field, a transition towards a laned state occurs at sufficiently large drives, where particles driven alike form elongated structures (‘lanes’) characterized by a large correlation length ξ along the drive. Here we perform extensive Brownian dynamics computer simulations on a two-dimensional equimolar binary Yukawa system driven by a constant force that acts oppositely on the two species. We systematically address finite-size effects on lane formation by exploring large systems up to 262 144 particles under various boundary conditions. It is found that the correlation length ξ along the field depends exponentially on the driving force (or Peclet number). Conversely, in a finite system, ξ reaches a fraction of the system size at a driving force which is logarithmic in the system size, implying massive finite-size corrections. For a fixed finite drive, ξ does not diverge in the thermodynamic limit. Therefore, though laning has a signature as a sharp transition in a finite system, it is a smooth crossover in the thermodynamic limit.

A frictionally and hydraulically constrained model of the convectively driven mean flow in partially enclosed seas

NASA Astrophysics Data System (ADS)

Maxworthy, T.

1997-08-01

A simple three-layer model of the dynamics of partially enclosed seas, driven by a surface buoyancy flux, is presented. It contains two major elements, a hydraulic constraint at the exit contraction and friction in the interior of the main body of the sea; both together determine the vertical structure and magnitudes of the interior flow variables, i.e. velocity and density. Application of the model to the large-scale dynamics of the Red Sea gives results that are not in disagreement with observation once the model is applied, also, to predict the dense outflow from the Gulf of Suez. The latter appears to be the agent responsible for the formation of dense bottom water in this system. Also, the model is reasonably successful in predicting the density of the outflow from the Persian Gulf, and can be applied to any number of other examples of convectively driven flow in long, narrow channels, with or without sills and constrictions at their exits.

Near Mbar-Level Dynamic Loading of Materials by Direct Laser-Irradiation

NASA Astrophysics Data System (ADS)

Tierney, T. E.; Swift, D. C.; Gammel, J. T.; Luo, S.; Johnson, R. P.

2003-12-01

We are developing techniques to perform direct-laser-illumination-driven, dynamic materials experiments at up to Mbar pressures with use of the Trident Laser Laboratory at Los Alamos. By temporally controlling the laser-irradiance, we are able to shape our loading for studies of fast-rise shocks, precursors, or isentropic compression. Laser-driven shock experiments are advantageous when considering the efficiency (fast turnaround), relative ease of sample recovery, taylorable dynamic loading, and in-situ structure diagnostics. Frequently, these experiments last 1-5 nanoseconds, and thus, permit investigation of rate-dependent processes and high strain rate environments. Laser-driven dynamic experiments are an important complement to traditional dynamic (e.g., light-gas gun) and static (e.g., diamond-anvil cell) experiments with certain advantages in studying equation of state, phase transitions and mechanical-chemical properties of Earth and planetary materials. Understanding high-pressure behavior in this regime is critical to phase boundaries for planetary interiors and dynamic properties of impact processes. Although we have studied silicates, oxides, metals, alloys and organic materials, this paper will focus on shocked and isentropically-compressed results obtained for iron in the range of 10-70 GPa (0.1-0.7 Mbar). Free surface velocities are measured using a Velocity Interferometer System for Any Reflector (VISAR). Nanosecond-scale laser experiments were interpreted with careful attention to exaggerated elastic-plastic effects and using accurate new equations of state for the phases of iron. This poster will present our technique, experimental results, and interpretation. *Work performed under the auspices of the US DOE under contract No. W-7405-ENG-36.

Calibration of visually guided reaching is driven by error-corrective learning and internal dynamics.

PubMed

Cheng, Sen; Sabes, Philip N

2007-04-01

The sensorimotor calibration of visually guided reaching changes on a trial-to-trial basis in response to random shifts in the visual feedback of the hand. We show that a simple linear dynamical system is sufficient to model the dynamics of this adaptive process. In this model, an internal variable represents the current state of sensorimotor calibration. Changes in this state are driven by error feedback signals, which consist of the visually perceived reach error, the artificial shift in visual feedback, or both. Subjects correct for > or =20% of the error observed on each movement, despite being unaware of the visual shift. The state of adaptation is also driven by internal dynamics, consisting of a decay back to a baseline state and a "state noise" process. State noise includes any source of variability that directly affects the state of adaptation, such as variability in sensory feedback processing, the computations that drive learning, or the maintenance of the state. This noise is accumulated in the state across trials, creating temporal correlations in the sequence of reach errors. These correlations allow us to distinguish state noise from sensorimotor performance noise, which arises independently on each trial from random fluctuations in the sensorimotor pathway. We show that these two noise sources contribute comparably to the overall magnitude of movement variability. Finally, the dynamics of adaptation measured with random feedback shifts generalizes to the case of constant feedback shifts, allowing for a direct comparison of our results with more traditional blocked-exposure experiments.

Detecting changes in forced climate attractors with Wasserstein distance

NASA Astrophysics Data System (ADS)

Robin, Yoann; Yiou, Pascal; Naveau, Philippe

2017-07-01

The climate system can been described by a dynamical system and its associated attractor. The dynamics of this attractor depends on the external forcings that influence the climate. Such forcings can affect the mean values or variances, but regions of the attractor that are seldom visited can also be affected. It is an important challenge to measure how the climate attractor responds to different forcings. Currently, the Euclidean distance or similar measures like the Mahalanobis distance have been favored to measure discrepancies between two climatic situations. Those distances do not have a natural building mechanism to take into account the attractor dynamics. In this paper, we argue that a Wasserstein distance, stemming from optimal transport theory, offers an efficient and practical way to discriminate between dynamical systems. After treating a toy example, we explore how the Wasserstein distance can be applied and interpreted to detect non-autonomous dynamics from a Lorenz system driven by seasonal cycles and a warming trend.

Dynamics of poroelastocapillary rise

NASA Astrophysics Data System (ADS)

Nasouri, Babak; Elfring, Gwynn

2017-11-01

The surface-tension-driven rise of a liquid between two elastic sheets can result in their deformation or coalescence depending on their flexibility. When the sheets are poroelastic, the flexibility of the immersed parts of the sheets can change considerably thereby altering the dynamical behavior of the system. To better understand this phenomenon, we study the poroelastocapillary rise of a wetting liquid between poroelastic sheets. Using the lubrication theory and linear elasticity, we quantify the effects of the change in material properties of the wet sheets on the capillary rise and the equilibrium state of the system.

Quantum transitions driven by one-bond defects in quantum Ising rings.

PubMed

Campostrini, Massimo; Pelissetto, Andrea; Vicari, Ettore

2015-04-01

We investigate quantum scaling phenomena driven by lower-dimensional defects in quantum Ising-like models. We consider quantum Ising rings in the presence of a bond defect. In the ordered phase, the system undergoes a quantum transition driven by the bond defect between a magnet phase, in which the gap decreases exponentially with increasing size, and a kink phase, in which the gap decreases instead with a power of the size. Close to the transition, the system shows a universal scaling behavior, which we characterize by computing, either analytically or numerically, scaling functions for the low-level energy differences and the two-point correlation function. We discuss the implications of these results for the nonequilibrium dynamics in the presence of a slowly varying parallel magnetic field h, when going across the first-order quantum transition at h=0.

Data-assisted reduced-order modeling of extreme events in complex dynamical systems

PubMed Central

Koumoutsakos, Petros

2018-01-01

The prediction of extreme events, from avalanches and droughts to tsunamis and epidemics, depends on the formulation and analysis of relevant, complex dynamical systems. Such dynamical systems are characterized by high intrinsic dimensionality with extreme events having the form of rare transitions that are several standard deviations away from the mean. Such systems are not amenable to classical order-reduction methods through projection of the governing equations due to the large intrinsic dimensionality of the underlying attractor as well as the complexity of the transient events. Alternatively, data-driven techniques aim to quantify the dynamics of specific, critical modes by utilizing data-streams and by expanding the dimensionality of the reduced-order model using delayed coordinates. In turn, these methods have major limitations in regions of the phase space with sparse data, which is the case for extreme events. In this work, we develop a novel hybrid framework that complements an imperfect reduced order model, with data-streams that are integrated though a recurrent neural network (RNN) architecture. The reduced order model has the form of projected equations into a low-dimensional subspace that still contains important dynamical information about the system and it is expanded by a long short-term memory (LSTM) regularization. The LSTM-RNN is trained by analyzing the mismatch between the imperfect model and the data-streams, projected to the reduced-order space. The data-driven model assists the imperfect model in regions where data is available, while for locations where data is sparse the imperfect model still provides a baseline for the prediction of the system state. We assess the developed framework on two challenging prototype systems exhibiting extreme events. We show that the blended approach has improved performance compared with methods that use either data streams or the imperfect model alone. Notably the improvement is more significant in regions associated with extreme events, where data is sparse. PMID:29795631

Data-assisted reduced-order modeling of extreme events in complex dynamical systems.

PubMed

Wan, Zhong Yi; Vlachas, Pantelis; Koumoutsakos, Petros; Sapsis, Themistoklis

2018-01-01

The prediction of extreme events, from avalanches and droughts to tsunamis and epidemics, depends on the formulation and analysis of relevant, complex dynamical systems. Such dynamical systems are characterized by high intrinsic dimensionality with extreme events having the form of rare transitions that are several standard deviations away from the mean. Such systems are not amenable to classical order-reduction methods through projection of the governing equations due to the large intrinsic dimensionality of the underlying attractor as well as the complexity of the transient events. Alternatively, data-driven techniques aim to quantify the dynamics of specific, critical modes by utilizing data-streams and by expanding the dimensionality of the reduced-order model using delayed coordinates. In turn, these methods have major limitations in regions of the phase space with sparse data, which is the case for extreme events. In this work, we develop a novel hybrid framework that complements an imperfect reduced order model, with data-streams that are integrated though a recurrent neural network (RNN) architecture. The reduced order model has the form of projected equations into a low-dimensional subspace that still contains important dynamical information about the system and it is expanded by a long short-term memory (LSTM) regularization. The LSTM-RNN is trained by analyzing the mismatch between the imperfect model and the data-streams, projected to the reduced-order space. The data-driven model assists the imperfect model in regions where data is available, while for locations where data is sparse the imperfect model still provides a baseline for the prediction of the system state. We assess the developed framework on two challenging prototype systems exhibiting extreme events. We show that the blended approach has improved performance compared with methods that use either data streams or the imperfect model alone. Notably the improvement is more significant in regions associated with extreme events, where data is sparse.

Experiments in cooperative manipulation: A system perspective

NASA Technical Reports Server (NTRS)

Schneider, Stanley A.; Cannon, Robert H., Jr.

1989-01-01

In addition to cooperative dynamic control, the system incorporates real time vision feedback, a novel programming technique, and a graphical high level user interface. By focusing on the vertical integration problem, not only these subsystems are examined, but also their interfaces and interactions. The control system implements a multi-level hierarchical structure; the techniques developed for operator input, strategic command, and cooperative dynamic control are presented. At the highest level, a mouse-based graphical user interface allows an operator to direct the activities of the system. Strategic command is provided by a table-driven finite state machine; this methodology provides a powerful yet flexible technique for managing the concurrent system interactions. The dynamic controller implements object impedance control; an extension of Nevill Hogan's impedance control concept to cooperative arm manipulation of a single object. Experimental results are presented, showing the system locating and identifying a moving object catching it, and performing a simple cooperative assembly. Results from dynamic control experiments are also presented, showing the controller's excellent dynamic trajectory tracking performance, while also permitting control of environmental contact force.

Single neuron computation: from dynamical system to feature detector.

PubMed

Hong, Sungho; Agüera y Arcas, Blaise; Fairhall, Adrienne L

2007-12-01

White noise methods are a powerful tool for characterizing the computation performed by neural systems. These methods allow one to identify the feature or features that a neural system extracts from a complex input and to determine how these features are combined to drive the system's spiking response. These methods have also been applied to characterize the input-output relations of single neurons driven by synaptic inputs, simulated by direct current injection. To interpret the results of white noise analysis of single neurons, we would like to understand how the obtained feature space of a single neuron maps onto the biophysical properties of the membrane, in particular, the dynamics of ion channels. Here, through analysis of a simple dynamical model neuron, we draw explicit connections between the output of a white noise analysis and the underlying dynamical system. We find that under certain assumptions, the form of the relevant features is well defined by the parameters of the dynamical system. Further, we show that under some conditions, the feature space is spanned by the spike-triggered average and its successive order time derivatives.

Orbital and spin dynamics of intraband electrons in quantum rings driven by twisted light.

PubMed

Quinteiro, G F; Tamborenea, P I; Berakdar, J

2011-12-19

We theoretically investigate the effect that twisted light has on the orbital and spin dynamics of electrons in quantum rings possessing sizable Rashba spin-orbit interaction. The system Hamiltonian for such a strongly inhomogeneous light field exhibits terms which induce both spin-conserving and spin-flip processes. We analyze the dynamics in terms of the perturbation introduced by a weak light field on the Rasha electronic states, and describe the effects that the orbital angular momentum as well as the inhomogeneous character of the beam have on the orbital and the spin dynamics.

Gelation in a model 1-component system with adhesive hard-sphere interactions

NASA Astrophysics Data System (ADS)

Kim, Jung Min; Eberle, Aaron; Fang, Jun; Wagner, Norman

2012-02-01

Colloidal dispersions can undergo a dynamical arrest of the disperse phase leading to a system with solid-like properties when either the volume fraction or the interparticle potential is varied. Systems that contain low to moderate particulate concentrations form gels whereas higher concentrations lead to glassy states in which caging by nearest neighbors can be a significant contributor to the arrested long-time dynamics. Colloid polymer mixtures have been the prevalent model system for studying the effect of attraction, where attractions are entropically driven by depletion effects, in which gelation has been shown to be a result of phase separation [1]. Using the model 1-component octadecyl coated silica nanoparticle system, Eberle et al. [2] found the gel-line to intersect the spinodal to the left of the critical point, and at higher concentrations extended toward the mode coupling theory attractive driven glass line. . We continue this study by varying the particle diameter and find quantitative differences which we explain by gravity. 1. Lu, P.J., et al., Nature, 2008. 453(7194): p. 499-504.2. Eberle, A.P.R., N.J. Wagner, and R. Castaneda-Priego, Physical Review Letters, 2011. 106(10).

AST: Activity-Security-Trust driven modeling of time varying networks.

PubMed

Wang, Jian; Xu, Jiake; Liu, Yanheng; Deng, Weiwen

2016-02-18

Network modeling is a flexible mathematical structure that enables to identify statistical regularities and structural principles hidden in complex systems. The majority of recent driving forces in modeling complex networks are originated from activity, in which an activity potential of a time invariant function is introduced to identify agents' interactions and to construct an activity-driven model. However, the new-emerging network evolutions are already deeply coupled with not only the explicit factors (e.g. activity) but also the implicit considerations (e.g. security and trust), so more intrinsic driving forces behind should be integrated into the modeling of time varying networks. The agents undoubtedly seek to build a time-dependent trade-off among activity, security, and trust in generating a new connection to another. Thus, we reasonably propose the Activity-Security-Trust (AST) driven model through synthetically considering the explicit and implicit driving forces (e.g. activity, security, and trust) underlying the decision process. AST-driven model facilitates to more accurately capture highly dynamical network behaviors and figure out the complex evolution process, allowing a profound understanding of the effects of security and trust in driving network evolution, and improving the biases induced by only involving activity representations in analyzing the dynamical processes.

Rayleigh-type parametric chemical oscillation.

PubMed

Ghosh, Shyamolina; Ray, Deb Shankar

2015-09-28

We consider a nonlinear chemical dynamical system of two phase space variables in a stable steady state. When the system is driven by a time-dependent sinusoidal forcing of a suitable scaling parameter at a frequency twice the output frequency and the strength of perturbation exceeds a threshold, the system undergoes sustained Rayleigh-type periodic oscillation, wellknown for parametric oscillation in pipe organs and distinct from the usual forced quasiperiodic oscillation of a damped nonlinear system where the system is oscillatory even in absence of any external forcing. Our theoretical analysis of the parametric chemical oscillation is corroborated by full numerical simulation of two well known models of chemical dynamics, chlorite-iodine-malonic acid and iodine-clock reactions.

Fluctuation-Driven Neural Dynamics Reproduce Drosophila Locomotor Patterns

PubMed Central

Cruchet, Steeve; Gustafson, Kyle; Benton, Richard; Floreano, Dario

2015-01-01

The neural mechanisms determining the timing of even simple actions, such as when to walk or rest, are largely mysterious. One intriguing, but untested, hypothesis posits a role for ongoing activity fluctuations in neurons of central action selection circuits that drive animal behavior from moment to moment. To examine how fluctuating activity can contribute to action timing, we paired high-resolution measurements of freely walking Drosophila melanogaster with data-driven neural network modeling and dynamical systems analysis. We generated fluctuation-driven network models whose outputs—locomotor bouts—matched those measured from sensory-deprived Drosophila. From these models, we identified those that could also reproduce a second, unrelated dataset: the complex time-course of odor-evoked walking for genetically diverse Drosophila strains. Dynamical models that best reproduced both Drosophila basal and odor-evoked locomotor patterns exhibited specific characteristics. First, ongoing fluctuations were required. In a stochastic resonance-like manner, these fluctuations allowed neural activity to escape stable equilibria and to exceed a threshold for locomotion. Second, odor-induced shifts of equilibria in these models caused a depression in locomotor frequency following olfactory stimulation. Our models predict that activity fluctuations in action selection circuits cause behavioral output to more closely match sensory drive and may therefore enhance navigation in complex sensory environments. Together these data reveal how simple neural dynamics, when coupled with activity fluctuations, can give rise to complex patterns of animal behavior. PMID:26600381

Data-Driven Based Asynchronous Motor Control for Printing Servo Systems

NASA Astrophysics Data System (ADS)

Bian, Min; Guo, Qingyun

Modern digital printing equipment aims to the environmental-friendly industry with high dynamic performances and control precision and low vibration and abrasion. High performance motion control system of printing servo systems was required. Control system of asynchronous motor based on data acquisition was proposed. Iterative learning control (ILC) algorithm was studied. PID control was widely used in the motion control. However, it was sensitive to the disturbances and model parameters variation. The ILC applied the history error data and present control signals to approximate the control signal directly in order to fully track the expect trajectory without the system models and structures. The motor control algorithm based on the ILC and PID was constructed and simulation results were given. The results show that data-driven control method is effective dealing with bounded disturbances for the motion control of printing servo systems.

Space station dynamics, attitude control and momentum management

NASA Technical Reports Server (NTRS)

Sunkel, John W.; Singh, Ramen P.; Vengopal, Ravi

1989-01-01

The Space Station Attitude Control System software test-bed provides a rigorous environment for the design, development and functional verification of GN and C algorithms and software. The approach taken for the simulation of the vehicle dynamics and environmental models using a computationally efficient algorithm is discussed. The simulation includes capabilities for docking/berthing dynamics, prescribed motion dynamics associated with the Mobile Remote Manipulator System (MRMS) and microgravity disturbances. The vehicle dynamics module interfaces with the test-bed through the central Communicator facility which is in turn driven by the Station Control Simulator (SCS) Executive. The Communicator addresses issues such as the interface between the discrete flight software and the continuous vehicle dynamics, and multi-programming aspects such as the complex flow of control in real-time programs. Combined with the flight software and redundancy management modules, the facility provides a flexible, user-oriented simulation platform.

Near-infrared light-responsive dynamic wrinkle patterns.

PubMed

Li, Fudong; Hou, Honghao; Yin, Jie; Jiang, Xuesong

2018-04-01

Dynamic micro/nanopatterns provide an effective approach for on-demand tuning of surface properties to realize a smart surface. We report a simple yet versatile strategy for the fabrication of near-infrared (NIR) light-responsive dynamic wrinkles by using a carbon nanotube (CNT)-containing poly(dimethylsiloxane) (PDMS) elastomer as the substrate for the bilayer systems, with various functional polymers serving as the top stiff layers. The high photon-to-thermal energy conversion of CNT leads to the NIR-controlled thermal expansion of the elastic CNT-PDMS substrate, resulting in dynamic regulation of the applied strain (ε) of the bilayer system by the NIR on/off cycle to obtain a reversible wrinkle pattern. The switchable surface topological structures can transfer between the wrinkled state and the wrinkle-free state within tens of seconds via NIR irradiation. As a proof-of-concept application, this type of NIR-driven dynamic wrinkle pattern was used in smart displays, dynamic gratings, and light control electronics.

Analysis of current-driven oscillatory dynamics of single-layer homoepitaxial islands on crystalline conducting substrates

NASA Astrophysics Data System (ADS)

Dasgupta, Dwaipayan; Kumar, Ashish; Maroudas, Dimitrios

2018-03-01

We report results of a systematic study on the complex oscillatory current-driven dynamics of single-layer homoepitaxial islands on crystalline substrate surfaces and the dependence of this driven dynamical behavior on important physical parameters, including island size, substrate surface orientation, and direction of externally applied electric field. The analysis is based on a nonlinear model of driven island edge morphological evolution that accounts for curvature-driven edge diffusion, edge electromigration, and edge diffusional anisotropy. Using a linear theory of island edge morphological stability, we calculate a critical island size at which the island's equilibrium edge shape becomes unstable, which sets a lower bound for the onset of time-periodic oscillatory dynamical response. Using direct dynamical simulations, we study the edge morphological dynamics of current-driven single-layer islands at larger-than-critical size, and determine the actual island size at which the migrating islands undergo a transition from steady to time-periodic asymptotic states through a subcritical Hopf bifurcation. At the highest symmetry of diffusional anisotropy examined, on {111} surfaces of face-centered cubic crystalline substrates, we find that more complex stable oscillatory states can be reached through period-doubling bifurcation at island sizes larger than those at the Hopf points. We characterize in detail the island morphology and dynamical response at the stable time-periodic asymptotic states, determine the range of stability of these oscillatory states terminated by island breakup, and explain the morphological features of the stable oscillating islands on the basis of linear stability theory.

A comprehensive study of the delay vector variance method for quantification of nonlinearity in dynamical systems

PubMed Central

Mandic, D. P.; Ryan, K.; Basu, B.; Pakrashi, V.

2016-01-01

Although vibration monitoring is a popular method to monitor and assess dynamic structures, quantification of linearity or nonlinearity of the dynamic responses remains a challenging problem. We investigate the delay vector variance (DVV) method in this regard in a comprehensive manner to establish the degree to which a change in signal nonlinearity can be related to system nonlinearity and how a change in system parameters affects the nonlinearity in the dynamic response of the system. A wide range of theoretical situations are considered in this regard using a single degree of freedom (SDOF) system to obtain numerical benchmarks. A number of experiments are then carried out using a physical SDOF model in the laboratory. Finally, a composite wind turbine blade is tested for different excitations and the dynamic responses are measured at a number of points to extend the investigation to continuum structures. The dynamic responses were measured using accelerometers, strain gauges and a Laser Doppler vibrometer. This comprehensive study creates a numerical and experimental benchmark for structurally dynamical systems where output-only information is typically available, especially in the context of DVV. The study also allows for comparative analysis between different systems driven by the similar input. PMID:26909175

Reservoir Computing Beyond Memory-Nonlinearity Trade-off.

PubMed

Inubushi, Masanobu; Yoshimura, Kazuyuki

2017-08-31

Reservoir computing is a brain-inspired machine learning framework that employs a signal-driven dynamical system, in particular harnessing common-signal-induced synchronization which is a widely observed nonlinear phenomenon. Basic understanding of a working principle in reservoir computing can be expected to shed light on how information is stored and processed in nonlinear dynamical systems, potentially leading to progress in a broad range of nonlinear sciences. As a first step toward this goal, from the viewpoint of nonlinear physics and information theory, we study the memory-nonlinearity trade-off uncovered by Dambre et al. (2012). Focusing on a variational equation, we clarify a dynamical mechanism behind the trade-off, which illustrates why nonlinear dynamics degrades memory stored in dynamical system in general. Moreover, based on the trade-off, we propose a mixture reservoir endowed with both linear and nonlinear dynamics and show that it improves the performance of information processing. Interestingly, for some tasks, significant improvements are observed by adding a few linear dynamics to the nonlinear dynamical system. By employing the echo state network model, the effect of the mixture reservoir is numerically verified for a simple function approximation task and for more complex tasks.

Neurodynamics in the Sensorimotor Loop: Representing Behavior Relevant External Situations

PubMed Central

Pasemann, Frank

2017-01-01

In the context of the dynamical system approach to cognition and supposing that brains or brain-like systems controlling the behavior of autonomous systems are permanently driven by their sensor signals, the paper approaches the question of neurodynamics in the sensorimotor loop in a purely formal way. This is carefully done by addressing the problem in three steps, using the time-discrete dynamics of standard neural networks and a fiber space representation for better clearness. Furthermore, concepts like meta-transients, parametric stability and dynamical forms are introduced, where meta-transients describe the effect of realistic sensor inputs, parametric stability refers to a class of sensor inputs all generating the “same type” of dynamic behavior, and a dynamical form comprises the corresponding class of parametrized dynamical systems. It is argued that dynamical forms are the essential internal representatives of behavior relevant external situations. Consequently, it is suggested that dynamical forms are the basis for a memory of these situations. Finally, based on the observation that not all brain process have a direct effect on the motor activity, a natural splitting of neurodynamics into vertical (internal) and horizontal (effective) parts is introduced. PMID:28217092

Hawking radiation and nonequilibrium quantum critical current noise.

PubMed

Sonner, Julian; Green, A G

2012-08-31

The dynamical scaling of quantum critical systems in thermal equilibrium may be inherited in the driven steady state, leading to universal out-of-equilibrium behavior. This attractive notion has been demonstrated in just a few cases. We demonstrate how holography-a mapping between the quantum critical system and a gravity dual-provides an illuminating perspective and new results. Nontrivial out-of-equilibrium universality is particularly apparent in current noise, which is dual to Hawking radiation in the gravitational system. We calculate this in a two-dimensional system driven by a strong in-plane electric field and deduce a universal scaling function interpolating between previously established equilibrium and far-from-equilibrium current noise. Since this applies at all fields, out-of-equilibrium experiments no longer require very high fields for comparison with theory.

Dynamic metastability in the two-dimensional Potts ferromagnet

NASA Astrophysics Data System (ADS)

Ibáñez Berganza, Miguel; Petri, Alberto; Coletti, Pietro

2014-05-01

We investigate the nonequilibrium dynamics of the two-dimensional (2D) Potts model on the square lattice after a quench below the discontinuous transition point. By means of numerical simulations of systems with q =12, 24, and 48, we observe the onset of a stationary regime below the temperature-driven transition, in a temperature interval decreasing with the system size and increasing with q. These results obtained dynamically agree with those obtained from the analytical continuation of the free energy [J. L. Meunier and A. Morel, Eur. Phys. J. B 13, 341 (2000), 10.1007/s100510050040], from which metastability in the 2D Potts model results to be a finite-size effect.

31P NMR study of discrete time-crystalline signatures in an ordered crystal of ammonium dihydrogen phosphate

NASA Astrophysics Data System (ADS)

Rovny, Jared; Blum, Robert L.; Barrett, Sean E.

2018-05-01

The rich dynamics and phase structure of driven systems include the recently described phenomenon of the "discrete time crystal" (DTC), a robust phase which spontaneously breaks the discrete time translation symmetry of its driving Hamiltonian. Experiments in trapped ions and diamond nitrogen vacancy centers have recently shown evidence for this DTC order. Here, we show nuclear magnetic resonance (NMR) data of DTC behavior in a third, strikingly different, system: a highly ordered spatial crystal in three dimensions. We devise a DTC echo experiment to probe the coherence of the driven system. We examine potential decay mechanisms for the DTC oscillations, and demonstrate the important effect of the internal Hamiltonian during nonzero duration pulses.

Exact results for Schrödinger cats in driven-dissipative systems and their feedback control

NASA Astrophysics Data System (ADS)

Minganti, Fabrizio; Bartolo, Nicola; Lolli, Jared; Casteels, Wim; Ciuti, Cristiano

2016-05-01

In quantum optics, photonic Schrödinger cats are superpositions of two coherent states with opposite phases and with a significant number of photons. Recently, these states have been observed in the transient dynamics of driven-dissipative resonators subject to engineered two-photon processes. Here we present an exact analytical solution of the steady-state density matrix for this class of systems, including one-photon losses, which are considered detrimental for the achievement of cat states. We demonstrate that the unique steady state is a statistical mixture of two cat-like states with opposite parity, in spite of significant one-photon losses. The transient dynamics to the steady state depends dramatically on the initial state and can pass through a metastable regime lasting orders of magnitudes longer than the photon lifetime. By considering individual quantum trajectories in photon-counting configuration, we find that the system intermittently jumps between two cats. Finally, we propose and study a feedback protocol based on this behaviour to generate a pure cat-like steady state.

Evaluating the utility of dynamical downscaling in agricultural impacts projections

PubMed Central

Glotter, Michael; Elliott, Joshua; McInerney, David; Best, Neil; Foster, Ian; Moyer, Elisabeth J.

2014-01-01

Interest in estimating the potential socioeconomic costs of climate change has led to the increasing use of dynamical downscaling—nested modeling in which regional climate models (RCMs) are driven with general circulation model (GCM) output—to produce fine-spatial-scale climate projections for impacts assessments. We evaluate here whether this computationally intensive approach significantly alters projections of agricultural yield, one of the greatest concerns under climate change. Our results suggest that it does not. We simulate US maize yields under current and future CO2 concentrations with the widely used Decision Support System for Agrotechnology Transfer crop model, driven by a variety of climate inputs including two GCMs, each in turn downscaled by two RCMs. We find that no climate model output can reproduce yields driven by observed climate unless a bias correction is first applied. Once a bias correction is applied, GCM- and RCM-driven US maize yields are essentially indistinguishable in all scenarios (<10% discrepancy, equivalent to error from observations). Although RCMs correct some GCM biases related to fine-scale geographic features, errors in yield are dominated by broad-scale (100s of kilometers) GCM systematic errors that RCMs cannot compensate for. These results support previous suggestions that the benefits for impacts assessments of dynamically downscaling raw GCM output may not be sufficient to justify its computational demands. Progress on fidelity of yield projections may benefit more from continuing efforts to understand and minimize systematic error in underlying climate projections. PMID:24872455

From localization to anomalous diffusion in the dynamics of coupled kicked rotors

NASA Astrophysics Data System (ADS)

Notarnicola, Simone; Iemini, Fernando; Rossini, Davide; Fazio, Rosario; Silva, Alessandro; Russomanno, Angelo

2018-02-01

We study the effect of many-body quantum interference on the dynamics of coupled periodically kicked systems whose classical dynamics is chaotic and shows an unbounded energy increase. We specifically focus on an N -coupled kicked rotors model: We find that the interplay of quantumness and interactions dramatically modifies the system dynamics, inducing a transition between energy saturation and unbounded energy increase. We discuss this phenomenon both numerically and analytically through a mapping onto an N -dimensional Anderson model. The thermodynamic limit N →∞ , in particular, always shows unbounded energy growth. This dynamical delocalization is genuinely quantum and very different from the classical one: Using a mean-field approximation, we see that the system self-organizes so that the energy per site increases in time as a power law with exponent smaller than 1. This wealth of phenomena is a genuine effect of quantum interference: The classical system for N ≥2 always behaves ergodically with an energy per site linearly increasing in time. Our results show that quantum mechanics can deeply alter the regularity or ergodicity properties of a many-body-driven system.

A computational model of amoeboid cell swimming in unbounded medium and through obstacles

NASA Astrophysics Data System (ADS)

Campbell, Eric; Bagchi, Prosenjit

2017-11-01

Pseudopod-driven motility is commonly observed in eukaryotic cells. Pseudopodia are actin-rich protrusions of the cellular membrane which extend, bifurcate, and retract in cycles resulting in amoeboid locomotion. While actin-myosin interactions are responsible for pseudopod generation, cell deformability is crucial concerning pseudopod dynamics. Because pseudopodia are highly dynamic, cells are capable of deforming into complex shapes over time. Pseudopod-driven motility represents a multiscale and complex process, coupling cell deformation, protein biochemistry, and cytoplasmic and extracellular fluid motion. In this work, we present a 3D computational model of amoeboid cell swimming in an extracellular medium (ECM). The ECM is represented as a fluid medium with or without obstacles. The model integrates full cell deformation, a coarse-grain reaction-diffusion system for protein dynamics, and fluid interaction. Our model generates pseudopodia which bifurcate and retract, showing remarkable similarity to experimental observations. Influence of cell deformation, protein diffusivity and cytoplasmic viscosity on the swimming speed is analyzed in terms of altered pseudopod dynamics. Insights into the role of matrix porosity and obstacle size on cell motility are also provided. Funded by NSF CBET 1438255.

Solar wind dynamic pressure and electric field as the main factors controlling Saturn's aurorae.

PubMed

Crary, F J; Clarke, J T; Dougherty, M K; Hanlon, P G; Hansen, K C; Steinberg, J T; Barraclough, B L; Coates, A J; Gérard, J-C; Grodent, D; Kurth, W S; Mitchell, D G; Rymer, A M; Young, D T

2005-02-17

The interaction of the solar wind with Earth's magnetosphere gives rise to the bright polar aurorae and to geomagnetic storms, but the relation between the solar wind and the dynamics of the outer planets' magnetospheres is poorly understood. Jupiter's magnetospheric dynamics and aurorae are dominated by processes internal to the jovian system, whereas Saturn's magnetosphere has generally been considered to have both internal and solar-wind-driven processes. This hypothesis, however, is tentative because of limited simultaneous solar wind and magnetospheric measurements. Here we report solar wind measurements, immediately upstream of Saturn, over a one-month period. When combined with simultaneous ultraviolet imaging we find that, unlike Jupiter, Saturn's aurorae respond strongly to solar wind conditions. But in contrast to Earth, the main controlling factor appears to be solar wind dynamic pressure and electric field, with the orientation of the interplanetary magnetic field playing a much more limited role. Saturn's magnetosphere is, therefore, strongly driven by the solar wind, but the solar wind conditions that drive it differ from those that drive the Earth's magnetosphere.

Ultrafast electronic dynamics driven by nuclear motion

NASA Astrophysics Data System (ADS)

Vendrell, Oriol

2016-05-01

The transfer of electrical charge on a microscopic scale plays a fundamental role in chemistry, in biology, and in technological applications. In this contribution, we will discuss situations in which nuclear motion plays a central role in driving the electronic dynamics of photo-excited or photo-ionized molecular systems. In particular, we will explore theoretically the ultrafast transfer of a double electron hole between the functional groups of glycine after K-shell ionization and subsequent Auger decay. Although a large energy gap of about 15 eV initially exists between the two electronic states involved and coherent electronic dynamics play no role in the hole transfer, we will illustrate how the double hole can be transferred within 3 to 4 fs between both functional ends of the glycine molecule driven solely by specific nuclear displacements and non-Born-Oppenheimer effects. This finding challenges the common wisdom that nuclear dynamics of the molecular skeleton are unimportant for charge transfer processes at the few-femtosecond time scale and shows that they can even play a prominent role. We thank the Hamburg Centre for Ultrafast Imaging and the Volkswagen Foundation for financial support.

Observation of dynamical vortices after quenches in a system with topology

NASA Astrophysics Data System (ADS)

Fläschner, N.; Vogel, D.; Tarnowski, M.; Rem, B. S.; Lühmann, D.-S.; Heyl, M.; Budich, J. C.; Mathey, L.; Sengstock, K.; Weitenberg, C.

2018-03-01

Topological phases constitute an exotic form of matter characterized by non-local properties rather than local order parameters1. The paradigmatic Haldane model on a hexagonal lattice features such topological phases distinguished by an integer topological invariant known as the first Chern number2. Recently, the identification of non-equilibrium signatures of topology in the dynamics of such systems has attracted particular attention3-6. Here, we experimentally study the dynamical evolution of the wavefunction using time- and momentum-resolved full state tomography for spin-polarized fermionic atoms in driven optical lattices7. We observe the appearance, movement and annihilation of dynamical vortices in momentum space after sudden quenches close to the topological phase transition. These dynamical vortices can be interpreted as dynamical Fisher zeros of the Loschmidt amplitude8, which signal a so-called dynamical phase transition9,10. Our results pave the way to a deeper understanding of the connection between topological phases and non-equilibrium dynamics.

Forward Thinking: Progress Report

ERIC Educational Resources Information Center

Colorado Department of Education, 2008

2008-01-01

In September 2007 the Colorado Department of Education and the Colorado State Board of Education jointly announced the launch of "Forward Thinking", an ambitious plan "to create a purpose-driven and dynamic system of educational leadership, service and support that relentlessly focuses on the learning of all students." The…

Gauge theory for finite-dimensional dynamical systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gurfil, Pini

2007-06-15

Gauge theory is a well-established concept in quantum physics, electrodynamics, and cosmology. This concept has recently proliferated into new areas, such as mechanics and astrodynamics. In this paper, we discuss a few applications of gauge theory in finite-dimensional dynamical systems. We focus on the concept of rescriptive gauge symmetry, which is, in essence, rescaling of an independent variable. We show that a simple gauge transformation of multiple harmonic oscillators driven by chaotic processes can render an apparently ''disordered'' flow into a regular dynamical process, and that there exists a strong connection between gauge transformations and reduction theory of ordinary differentialmore » equations. Throughout the discussion, we demonstrate the main ideas by considering examples from diverse fields, including quantum mechanics, chemistry, rigid-body dynamics, and information theory.« less

Master stability functions reveal diffusion-driven pattern formation in networks

NASA Astrophysics Data System (ADS)

Brechtel, Andreas; Gramlich, Philipp; Ritterskamp, Daniel; Drossel, Barbara; Gross, Thilo

2018-03-01

We study diffusion-driven pattern formation in networks of networks, a class of multilayer systems, where different layers have the same topology, but different internal dynamics. Agents are assumed to disperse within a layer by undergoing random walks, while they can be created or destroyed by reactions between or within a layer. We show that the stability of homogeneous steady states can be analyzed with a master stability function approach that reveals a deep analogy between pattern formation in networks and pattern formation in continuous space. For illustration, we consider a generalized model of ecological meta-food webs. This fairly complex model describes the dispersal of many different species across a region consisting of a network of individual habitats while subject to realistic, nonlinear predator-prey interactions. In this example, the method reveals the intricate dependence of the dynamics on the spatial structure. The ability of the proposed approach to deal with this fairly complex system highlights it as a promising tool for ecology and other applications.

Efficient excitation of nonlinear phonons via chirped pulses: Induced structural phase transitions

NASA Astrophysics Data System (ADS)

Itin, A. P.; Katsnelson, M. I.

2018-05-01

Nonlinear phononics play important role in strong laser-solid interactions. We discuss a dynamical protocol for efficient phonon excitation, considering recent inspiring proposals: inducing ferroelectricity in paraelectric perovskites, and inducing structural deformations in cuprates [Subedi et al., Phys. Rev. B 89, 220301(R) (2014), 10.1103/PhysRevB.89.220301; Phys. Rev. B 95, 134113 (2017), 10.1103/PhysRevB.95.134113]. High-frequency phonon modes are driven by midinfrared pulses, and coupled to lower-frequency modes those indirect excitations cause structural deformations. We study in more detail the case of KTaO3 without strain, where it was not possible to excite the needed low-frequency phonon mode by resonant driving of the higher frequency one. Behavior of the system is explained using a reduced model of coupled driven nonlinear oscillators. We find a dynamical mechanism which prevents effective excitation at resonance driving. To induce ferroelectricity, we employ driving with sweeping frequency, realizing so-called capture into resonance. The method can be applied to many other related systems.

BMI cyberworkstation: enabling dynamic data-driven brain-machine interface research through cyberinfrastructure.

PubMed

Zhao, Ming; Rattanatamrong, Prapaporn; DiGiovanna, Jack; Mahmoudi, Babak; Figueiredo, Renato J; Sanchez, Justin C; Príncipe, José C; Fortes, José A B

2008-01-01

Dynamic data-driven brain-machine interfaces (DDDBMI) have great potential to advance the understanding of neural systems and improve the design of brain-inspired rehabilitative systems. This paper presents a novel cyberinfrastructure that couples in vivo neurophysiology experimentation with massive computational resources to provide seamless and efficient support of DDDBMI research. Closed-loop experiments can be conducted with in vivo data acquisition, reliable network transfer, parallel model computation, and real-time robot control. Behavioral experiments with live animals are supported with real-time guarantees. Offline studies can be performed with various configurations for extensive analysis and training. A Web-based portal is also provided to allow users to conveniently interact with the cyberinfrastructure, conducting both experimentation and analysis. New motor control models are developed based on this approach, which include recursive least square based (RLS) and reinforcement learning based (RLBMI) algorithms. The results from an online RLBMI experiment shows that the cyberinfrastructure can successfully support DDDBMI experiments and meet the desired real-time requirements.

Dynamic data driven bidirectional reflectance distribution function measurement system

NASA Astrophysics Data System (ADS)

Nauyoks, Stephen E.; Freda, Sam; Marciniak, Michael A.

2014-09-01

The bidirectional reflectance distribution function (BRDF) is a fitted distribution function that defines the scatter of light off of a surface. The BRDF is dependent on the directions of both the incident and scattered light. Because of the vastness of the measurement space of all possible incident and reflected directions, the calculation of BRDF is usually performed using a minimal amount of measured data. This may lead to poor fits and uncertainty in certain regions of incidence or reflection. A dynamic data driven application system (DDDAS) is a concept that uses an algorithm on collected data to influence the collection space of future data acquisition. The authors propose a DDD-BRDF algorithm that fits BRDF data as it is being acquired and uses on-the-fly fittings of various BRDF models to adjust the potential measurement space. In doing so, it is hoped to find the best model to fit a surface and the best global fit of the BRDF with a minimum amount of collection space.

Non-equilibrium phase transitions in a driven-dissipative system of interacting bosons

NASA Astrophysics Data System (ADS)

Young, Jeremy T.; Foss-Feig, Michael; Gorshkov, Alexey V.; Maghrebi, Mohammad F.

2017-04-01

Atomic, molecular, and optical systems provide unique opportunities to study simple models of driven-dissipative many-body quantum systems. Typically, one is interested in the resultant steady state, but the non-equilibrium nature of the physics involved presents several problems in understanding its behavior theoretically. Recently, it has been shown that in many of these models, it is possible to map the steady-state phase transitions onto classical equilibrium phase transitions. In the language of Keldysh field theory, this relation typically only becomes apparent after integrating out massive fields near the critical point, leaving behind a single massless field undergoing near-equilibrium dynamics. In this talk, we study a driven-dissipative XXZ bosonic model and discover critical points at which two fields become gapless. Each critical point separates three different possible phases: a uniform phase, an anti-ferromagnetic phase, and a limit cycle phase. Furthermore, a description in terms of an equilibrium phase transition does not seem possible, so the associated phase transitions appear to be inherently non-equilibrium.

Dynamic I/O Power Management for Hard Real-Time Systems

DTIC Science & Technology

2005-01-01

recently emerged as an attractive alternative to inflexible hardware solutions. DPM for hard real - time systems has received relatively little attention...In particular, energy-driven I/O device scheduling for real - time systems has not been considered before. We present the first online DPM algorithm...which we call Low Energy Device Scheduler (LEDES), for hard real - time systems . LEDES takes as inputs a predetermined task schedule and a device-usage

Integrated multidisciplinary analysis tool IMAT users' guide

NASA Technical Reports Server (NTRS)

Meissner, Frances T. (Editor)

1988-01-01

The Integrated Multidisciplinary Analysis Tool (IMAT) is a computer software system developed at Langley Research Center. IMAT provides researchers and analysts with an efficient capability to analyze satellite controls systems influenced by structural dynamics. Using a menu-driven executive system, IMAT leads the user through the program options. IMAT links a relational database manager to commercial and in-house structural and controls analysis codes. This paper describes the IMAT software system and how to use it.

Self-sorting of dynamic metallosupramolecular libraries (DMLs) via metal-driven selection.

PubMed

Kocsis, Istvan; Dumitrescu, Dan; Legrand, Yves-Marie; van der Lee, Arie; Grosu, Ion; Barboiu, Mihail

2014-03-11

"Metal-driven" selection between finite mononuclear and polymeric metallosupramolecular species can be quantitatively achieved in solution and in a crystalline state via coupled coordination/stacking interactional algorithms within dynamic metallosupramolecular libraries - DMLs.

Self-Organization of Metal Nanoparticles in Light: Electrodynamics-Molecular Dynamics Simulations and Optical Binding Experiments.

PubMed

McCormack, Patrick; Han, Fei; Yan, Zijie

2018-02-01

Light-driven self-organization of metal nanoparticles (NPs) can lead to unique optical matter systems, yet simulation of such self-organization (i.e., optical binding) is a complex computational problem that increases nonlinearly with system size. Here we show that a combined electrodynamics-molecular dynamics simulation technique can simulate the trajectories and predict stable configurations of silver NPs in optical fields. The simulated dynamic equilibrium of a two-NP system matches the probability density of oscillations for two optically bound NPs obtained experimentally. The predicted stable configurations for up to eight NPs are further compared to experimental observations of silver NP clusters formed by optical binding in a Bessel beam. All configurations are confirmed to form in real systems, including pentagonal clusters with five-fold symmetry. Our combined simulations and experiments have revealed a diverse optical matter system formed by anisotropic optical binding interactions, providing a new strategy to discover artificial materials.

How to Shift Power to Learners: Encouraging FE Dynamism, Replacing Centralised Procurement

ERIC Educational Resources Information Center

Wolf, Alison

2010-01-01

This monograph discusses how to make England's further education (FE) system genuinely responsive to learner demand, as well as stable, affordable, and of high quality. It looks at how a demand-driven system can be organised and funded, at what is required of governments, and what can be left to learners themselves and to the education and…

Automation for deep space vehicle monitoring

NASA Technical Reports Server (NTRS)

Schwuttke, Ursula M.

1991-01-01

Information on automation for deep space vehicle monitoring is given in viewgraph form. Information is given on automation goals and strategy; the Monitor Analyzer of Real-time Voyager Engineering Link (MARVEL); intelligent input data management; decision theory for making tradeoffs; dynamic tradeoff evaluation; evaluation of anomaly detection results; evaluation of data management methods; system level analysis with cooperating expert systems; the distributed architecture of multiple expert systems; and event driven response.

Compressed-air flow control system.

PubMed

Bong, Ki Wan; Chapin, Stephen C; Pregibon, Daniel C; Baah, David; Floyd-Smith, Tamara M; Doyle, Patrick S

2011-02-21

We present the construction and operation of a compressed-air driven flow system that can be used for a variety of microfluidic applications that require rapid dynamic response and precise control of multiple inlet streams. With the use of inexpensive and readily available parts, we describe how to assemble this versatile control system and further explore its utility in continuous- and pulsed-flow microfluidic procedures for the synthesis and analysis of microparticles.

Transition wave in the collapse of the San Saba bridge

NASA Astrophysics Data System (ADS)

Brun, Michele; Giaccu, Gian Felice; Movchan, Alexander; Slepyan, Leonid

2014-09-01

A domino wave is a well-known illustration of a transition wave, which appears to reach a stable regime of propagation. Nature also provides spectacular cases of gravity driven transition waves at large scale, observed in snow avalanches and landslides. On a different scale, the micro-structure level interaction between different constituents of the macro-system may influence critical regimes leading to instabilities in avalanche-like flow systems. Most transition waves observed in systems such as bulletproof vests, racing helmets under impact, shock-wave driven fracture in solids, are transient. For some structured waveguides a transition wave may stabilize to achieve a steady regime. Here we show that the failure of a long bridge is also driven by a transition wave that may allow for steady-state regimes. The recent observation of a failure of the San Saba Bridge in Texas provides experimental evidence supporting an elegant theory based on the notion of transition failure wave. No one would think of an analogy between a snow avalanche and a collapsing bridge. Despite an apparent controversy of such a comparison, these two phenomena can both be described in the framework of a model of the dynamic gravity driven transition fault.

Model implementation for dynamic computation of system cost

NASA Astrophysics Data System (ADS)

Levri, J.; Vaccari, D.

The Advanced Life Support (ALS) Program metric is the ratio of the equivalent system mass (ESM) of a mission based on International Space Station (ISS) technology to the ESM of that same mission based on ALS technology. ESM is a mission cost analog that converts the volume, power, cooling and crewtime requirements of a mission into mass units to compute an estimate of the life support system emplacement cost. Traditionally, ESM has been computed statically, using nominal values for system sizing. However, computation of ESM with static, nominal sizing estimates cannot capture the peak sizing requirements driven by system dynamics. In this paper, a dynamic model for a near-term Mars mission is described. The model is implemented in Matlab/Simulink' for the purpose of dynamically computing ESM. This paper provides a general overview of the crew, food, biomass, waste, water and air blocks in the Simulink' model. Dynamic simulations of the life support system track mass flow, volume and crewtime needs, as well as power and cooling requirement profiles. The mission's ESM is computed, based upon simulation responses. Ultimately, computed ESM values for various system architectures will feed into an optimization search (non-derivative) algorithm to predict parameter combinations that result in reduced objective function values.

Out-of-equilibrium dynamical mean-field equations for the perceptron model

NASA Astrophysics Data System (ADS)

Agoritsas, Elisabeth; Biroli, Giulio; Urbani, Pierfrancesco; Zamponi, Francesco

2018-02-01

Perceptrons are the building blocks of many theoretical approaches to a wide range of complex systems, ranging from neural networks and deep learning machines, to constraint satisfaction problems, glasses and ecosystems. Despite their applicability and importance, a detailed study of their Langevin dynamics has never been performed yet. Here we derive the mean-field dynamical equations that describe the continuous random perceptron in the thermodynamic limit, in a very general setting with arbitrary noise and friction kernels, not necessarily related by equilibrium relations. We derive the equations in two ways: via a dynamical cavity method, and via a path-integral approach in its supersymmetric formulation. The end point of both approaches is the reduction of the dynamics of the system to an effective stochastic process for a representative dynamical variable. Because the perceptron is formally very close to a system of interacting particles in a high dimensional space, the methods we develop here can be transferred to the study of liquid and glasses in high dimensions. Potentially interesting applications are thus the study of the glass transition in active matter, the study of the dynamics around the jamming transition, and the calculation of rheological properties in driven systems.

Current-Driven Dynamics of Skyrmions Stabilized in MnSi Nanowires Revealed by Topological Hall Effect

NASA Astrophysics Data System (ADS)

Liang, Dong; Degrave, John; Stolt, Matthew; Tokura, Yoshinori; Jin, Song

2015-03-01

Skyrmions, novel topologically stable spin vortices, hold promise for next-generation high-density magnetic storage technologies due to their nanoscale domains and ultralow energy consumption. One-dimensional (1D) nanowires are ideal hosts for skyrmions since they not only serve as a natural platform for magnetic racetrack memory devices but also can potentially stabilize skyrmions. We use the topological Hall effect (THE) to study the phase stability and current-driven dynamics of the skyrmions in MnSi nanowires. The THE was observed in an extended magnetic field-temperature window (15 to 30 K), suggesting stabilization of skyrmion phase in nanowires compared with the bulk (27 to 29.5 K). Furthermore, we study skyrmion dynamics in this extended skyrmion phase region and found that under the high current-density of 108-109Am-2 enabled by nanowire geometry, the THE decreases with increasing current densities, which demonstrates the current-driven motion of skyrmions generating the emergent electric field. These results open up the exploration of nanowires as an attractive platform for investigating skyrmion physics in 1D systems and exploiting skyrmions in magnetic storage concepts. This work is supported by US National Science Foundation (ECCS-1231916) and JSPS Grant-in-Aid for Scientific Research No. 24224009.

Two-Speed Gearbox Dynamic Simulation Predictions and Test Validation

NASA Technical Reports Server (NTRS)

Lewicki, David G.; DeSmidt, Hans; Smith, Edward C.; Bauman, Steven W.

2010-01-01

Dynamic simulations and experimental validation tests were performed on a two-stage, two-speed gearbox as part of the drive system research activities of the NASA Fundamental Aeronautics Subsonics Rotary Wing Project. The gearbox was driven by two electromagnetic motors and had two electromagnetic, multi-disk clutches to control output speed. A dynamic model of the system was created which included a direct current electric motor with proportional-integral-derivative (PID) speed control, a two-speed gearbox with dual electromagnetically actuated clutches, and an eddy current dynamometer. A six degree-of-freedom model of the gearbox accounted for the system torsional dynamics and included gear, clutch, shaft, and load inertias as well as shaft flexibilities and a dry clutch stick-slip friction model. Experimental validation tests were performed on the gearbox in the NASA Glenn gear noise test facility. Gearbox output speed and torque as well as drive motor speed and current were compared to those from the analytical predictions. The experiments correlate very well with the predictions, thus validating the dynamic simulation methodologies.

Coupled Leidenfrost states as a monodisperse granular clock

NASA Astrophysics Data System (ADS)

Liu, Rui; Yang, Mingcheng; Chen, Ke; Hou, Meiying; To, Kiwing

2016-08-01

Using an event-driven molecular dynamics simulation, we show that simple monodisperse granular beads confined in coupled columns may oscillate as a different type of granular clock. To trigger this oscillation, the system needs to be driven against gravity into a density-inverted state, with a high-density clustering phase supported from below by a gaslike low-density phase (Leidenfrost effect) in each column. Our analysis reveals that the density-inverted structure and the relaxation dynamics between the phases can amplify any small asymmetry between the columns, and lead to a giant oscillation. The oscillation occurs only for an intermediate range of the coupling strength, and the corresponding phase diagram can be universally described with a characteristic height of the density-inverted structure. A minimal two-phase model is proposed and a linear stability analysis shows that the triggering mechanism of the oscillation can be explained as a switchable two-parameter Andronov-Hopf bifurcation. Numerical solutions of the model also reproduce similar oscillatory dynamics to the simulation results.

Role of activity in human dynamics

NASA Astrophysics Data System (ADS)

Zhou, T.; Kiet, H. A. T.; Kim, B. J.; Wang, B.-H.; Holme, P.

2008-04-01

The human society is a very complex system; still, there are several non-trivial, general features. One type of them is the presence of power-law-distributed quantities in temporal statistics. In this letter, we focus on the origin of power laws in rating of movies. We present a systematic empirical exploration of the time between two consecutive ratings of movies (the interevent time). At an aggregate level, we find a monotonous relation between the activity of individuals and the power law exponent of the interevent time distribution. At an individual level, we observe a heavy-tailed distribution for each user, as well as a negative correlation between the activity and the width of the distribution. We support these findings by a similar data set from mobile phone text-message communication. Our results demonstrate a significant role of the activity of individuals on the society-level patterns of human behavior. We believe this is a common character in the interest-driven human dynamics, corresponding to (but different from) the universality classes of task-driven dynamics.

Stratification Modelling of Key Bacterial Taxa Driven by Metabolic Dynamics in Meromictic Lakes.

PubMed

Zhu, Kaicheng; Lauro, Federico M; Su, Haibin

2018-06-22

In meromictic lakes, the water column is stratified into distinguishable steady layers with different physico-chemical properties. The bottom portion, known as monimolimnion, has been studied for the functional stratification of microbial populations. Recent experiments have reported the profiles of bacterial and nutrient spatial distributions, but quantitative understanding is invoked to unravel the underlying mechanism of maintaining the discrete spatial organization. Here a reaction-diffusion model is developed to highlight the spatial pattern coupled with the light-driven metabolism of bacteria, which is resilient to a wide range of dynamical correlation between bacterial and nutrient species at the molecular level. Particularly, exact analytical solutions of the system are presented together with numerical results, in a good agreement with measurements in Ace lake and Rogoznica lake. Furthermore, one quantitative prediction is reported here on the dynamics of the seasonal stratification patterns in Ace lake. The active role played by the bacterial metabolism at microscale clearly shapes the biogeochemistry landscape of lake-wide ecology at macroscale.

Multiscale modeling and simulation of microtubule-motor-protein assemblies

NASA Astrophysics Data System (ADS)

Gao, Tong; Blackwell, Robert; Glaser, Matthew A.; Betterton, M. D.; Shelley, Michael J.

2015-12-01

Microtubules and motor proteins self-organize into biologically important assemblies including the mitotic spindle and the centrosomal microtubule array. Outside of cells, microtubule-motor mixtures can form novel active liquid-crystalline materials driven out of equilibrium by adenosine triphosphate-consuming motor proteins. Microscopic motor activity causes polarity-dependent interactions between motor proteins and microtubules, but how these interactions yield larger-scale dynamical behavior such as complex flows and defect dynamics is not well understood. We develop a multiscale theory for microtubule-motor systems in which Brownian dynamics simulations of polar microtubules driven by motors are used to study microscopic organization and stresses created by motor-mediated microtubule interactions. We identify polarity-sorting and crosslink tether relaxation as two polar-specific sources of active destabilizing stress. We then develop a continuum Doi-Onsager model that captures polarity sorting and the hydrodynamic flows generated by these polar-specific active stresses. In simulations of active nematic flows on immersed surfaces, the active stresses drive turbulent flow dynamics and continuous generation and annihilation of disclination defects. The dynamics follow from two instabilities, and accounting for the immersed nature of the experiment yields unambiguous characteristic length and time scales. When turning off the hydrodynamics in the Doi-Onsager model, we capture formation of polar lanes as observed in the Brownian dynamics simulation.

Multiscale modeling and simulation of microtubule-motor-protein assemblies.

PubMed

Gao, Tong; Blackwell, Robert; Glaser, Matthew A; Betterton, M D; Shelley, Michael J

2015-01-01

Microtubules and motor proteins self-organize into biologically important assemblies including the mitotic spindle and the centrosomal microtubule array. Outside of cells, microtubule-motor mixtures can form novel active liquid-crystalline materials driven out of equilibrium by adenosine triphosphate-consuming motor proteins. Microscopic motor activity causes polarity-dependent interactions between motor proteins and microtubules, but how these interactions yield larger-scale dynamical behavior such as complex flows and defect dynamics is not well understood. We develop a multiscale theory for microtubule-motor systems in which Brownian dynamics simulations of polar microtubules driven by motors are used to study microscopic organization and stresses created by motor-mediated microtubule interactions. We identify polarity-sorting and crosslink tether relaxation as two polar-specific sources of active destabilizing stress. We then develop a continuum Doi-Onsager model that captures polarity sorting and the hydrodynamic flows generated by these polar-specific active stresses. In simulations of active nematic flows on immersed surfaces, the active stresses drive turbulent flow dynamics and continuous generation and annihilation of disclination defects. The dynamics follow from two instabilities, and accounting for the immersed nature of the experiment yields unambiguous characteristic length and time scales. When turning off the hydrodynamics in the Doi-Onsager model, we capture formation of polar lanes as observed in the Brownian dynamics simulation.

Multiscale modeling and simulation of microtubule–motor-protein assemblies

PubMed Central

Gao, Tong; Blackwell, Robert; Glaser, Matthew A.; Betterton, M. D.; Shelley, Michael J.

2016-01-01

Microtubules and motor proteins self-organize into biologically important assemblies including the mitotic spindle and the centrosomal microtubule array. Outside of cells, microtubule-motor mixtures can form novel active liquid-crystalline materials driven out of equilibrium by adenosine triphosphate–consuming motor proteins. Microscopic motor activity causes polarity-dependent interactions between motor proteins and microtubules, but how these interactions yield larger-scale dynamical behavior such as complex flows and defect dynamics is not well understood. We develop a multiscale theory for microtubule-motor systems in which Brownian dynamics simulations of polar microtubules driven by motors are used to study microscopic organization and stresses created by motor-mediated microtubule interactions. We identify polarity-sorting and crosslink tether relaxation as two polar-specific sources of active destabilizing stress. We then develop a continuum Doi-Onsager model that captures polarity sorting and the hydrodynamic flows generated by these polar-specific active stresses. In simulations of active nematic flows on immersed surfaces, the active stresses drive turbulent flow dynamics and continuous generation and annihilation of disclination defects. The dynamics follow from two instabilities, and accounting for the immersed nature of the experiment yields unambiguous characteristic length and time scales. When turning off the hydrodynamics in the Doi-Onsager model, we capture formation of polar lanes as observed in the Brownian dynamics simulation. PMID:26764729

Single Cell Detection with Driven Magnetic Beads

NASA Astrophysics Data System (ADS)

McNaughton, B. H.; Agayan, R. R.; Stoica, V. A.; Clarke, R.; Kopelman, R.

Shifts in the nonlinear rotational frequency of magnetic beads (microspheres) offer a new and dynamic approach for the detection of single cells. We present the first demonstration of this capability by measuring the changes in the nonlinear rotational frequency of magnetic beads driven by an external magnetic field. The presence of an Escherichia coli bacterium on the surface of a 2.0 μm magnetic bead affects the drag of the system, thus changing the nonlinear rotation rate. Measurement of this rotational frequency is straight-forward utilizing standard microscopy techniques.

Quantum recurrence and fractional dynamic localization in ac-driven perfect state transfer Hamiltonians

DOE Office of Scientific and Technical Information (OSTI.GOV)

Longhi, Stefano, E-mail: stefano.longhi@fisi.polimi.it

Quantum recurrence and dynamic localization are investigated in a class of ac-driven tight-binding Hamiltonians, the Krawtchouk quantum chain, which in the undriven case provides a paradigmatic Hamiltonian model that realizes perfect quantum state transfer and mirror inversion. The equivalence between the ac-driven single-particle Krawtchouk Hamiltonian H{sup -hat} (t) and the non-interacting ac-driven bosonic junction Hamiltonian enables to determine in a closed form the quasi energy spectrum of H{sup -hat} (t) and the conditions for exact wave packet reconstruction (dynamic localization). In particular, we show that quantum recurrence, which is predicted by the general quantum recurrence theorem, is exact for themore » Krawtchouk quantum chain in a dense range of the driving amplitude. Exact quantum recurrence provides perfect wave packet reconstruction at a frequency which is fractional than the driving frequency, a phenomenon that can be referred to as fractional dynamic localization.« less

A Demand-Driven Approach for a Multi-Agent System in Supply Chain Management

NASA Astrophysics Data System (ADS)

Kovalchuk, Yevgeniya; Fasli, Maria

This paper presents the architecture of a multi-agent decision support system for Supply Chain Management (SCM) which has been designed to compete in the TAC SCM game. The behaviour of the system is demand-driven and the agents plan, predict, and react dynamically to changes in the market. The main strength of the system lies in the ability of the Demand agent to predict customer winning bid prices - the highest prices the agent can offer customers and still obtain their orders. This paper investigates the effect of the ability to predict customer order prices on the overall performance of the system. Four strategies are proposed and compared for predicting such prices. The experimental results reveal which strategies are better and show that there is a correlation between the accuracy of the models' predictions and the overall system performance: the more accurate the prediction of customer order prices, the higher the profit.

Knowledge Management Systems: Linking Contribution, Refinement and Use

ERIC Educational Resources Information Center

Chung, Ting-ting

2009-01-01

Electronic knowledge repositories represent one of the fundamental tools for knowledge management (KM) initiatives. Existing research, however, has largely focused on supply-side driven research questions, such as employee motivation to contribute knowledge to a repository. This research turns attention to the dynamic relationship between the…

A dynamic nitrogen budget model of a Pacific Northwest salt marsh

EPA Science Inventory

The role of salt marshes as either nitrogen sinks or sources in relation to their adjacent estuaries has been a focus of ecosystem service research for many decades. The complex hydrology of these systems is driven by tides, upland surface runoff, precipitation, evapotranspirati...

Connecting Seasonal Riparian Buffer Metrics and Nitrogen Concentrations in a Pulse-Driven Agricultural System

EPA Science Inventory

Riparian buffers have been well studied as best management practices for nutrient reduction at field scales yet their effectiveness for bettering water quality at watershed scales has been difficult to determine. Seasonal dynamics of the stream network are often overlooked when ...

Dynamics of entanglement entropy of interacting fermions in a 1D driven harmonic trap

NASA Astrophysics Data System (ADS)

McKenney, Joshua R.; Porter, William J.; Drut, Joaquín E.

2018-03-01

Following up on a recent analysis of two cold atoms in a time-dependent harmonic trap in one dimension, we explore the entanglement entropy of two and three fermions in the same situation when driven through a parametric resonance. We find that the presence of such a resonance in the two-particle system leaves a clear imprint on the entanglement entropy. We show how the signal is modified by attractive and repulsive contact interactions, and how it remains present for the three-particle system. Additionaly, we extend the work of recent experiments to demonstrate how restricting observation to a limited subsystem gives rise to locally thermal behavior.

Dispersive Readout of Adiabatic Phases

NASA Astrophysics Data System (ADS)

Kohler, Sigmund

2017-11-01

We propose a protocol for the measurement of adiabatic phases of periodically driven quantum systems coupled to an open cavity that enables dispersive readout. It turns out that the cavity transmission exhibits peaks at frequencies determined by a resonance condition that involves the dynamical and the geometric phase. Since these phases scale differently with the driving frequency, one can determine them by fitting the peak positions to the theoretically expected behavior. For the derivation of the resonance condition and for a numerical study, we develop a Floquet theory for the dispersive readout of ac driven quantum systems. The feasibility is demonstrated for two test cases that generalize Landau-Zener-Stückelberg-Majorana interference to two-parameter driving.

New technique for simulation of optical fiber amplifiers control schemes in dynamic WDM systems

NASA Astrophysics Data System (ADS)

Freitas, Marcio; Klein, Jackson; Givigi, Sidney, Jr.; Calmon, Luiz C.

2005-04-01

One topic that has attracted attention is related to the behavior of the optical amplifiers under dynamic conditions, specifically because amplifiers working in a saturated condition produce power transients in all-optical reconfigurable WDM networks, e.g. adding/dropping channels. The goal of this work is to introduce the multiwavelength time-driven simulations technique, capable of simulation and analysis of transient effects in all-optical WDM networks with optical amplifiers, and allow the use of control schemes to avoid or minimize the impacts of transient effects in the system performance.

Dynamics of embedded curves by doubly-nonlocal reaction-diffusion systems

NASA Astrophysics Data System (ADS)

von Brecht, James H.; Blair, Ryan

2017-11-01

We study a class of nonlocal, energy-driven dynamical models that govern the motion of closed, embedded curves from both an energetic and dynamical perspective. Our energetic results provide a variety of ways to understand physically motivated energetic models in terms of more classical, combinatorial measures of complexity for embedded curves. This line of investigation culminates in a family of complexity bounds that relate a rather broad class of models to a generalized, or weighted, variant of the crossing number. Our dynamic results include global well-posedness of the associated partial differential equations, regularity of equilibria for these flows as well as a more detailed investigation of dynamics near such equilibria. Finally, we explore a few global dynamical properties of these models numerically.

Chaos without nonlinear dynamics.

PubMed

Corron, Ned J; Hayes, Scott T; Pethel, Shawn D; Blakely, Jonathan N

2006-07-14

A linear, second-order filter driven by randomly polarized pulses is shown to generate a waveform that is chaotic under time reversal. That is, the filter output exhibits determinism and a positive Lyapunov exponent when viewed backward in time. The filter is demonstrated experimentally using a passive electronic circuit, and the resulting waveform exhibits a Lorenz-like butterfly structure. This phenomenon suggests that chaos may be connected to physical theories whose underlying framework is not that of a traditional deterministic nonlinear dynamical system.

Modeling stick-slip-separation dynamics in a bimodal standing wave ultrasonic motor

NASA Astrophysics Data System (ADS)

Li, Xiang; Yao, Zhiyuan; Lv, Qibao; Liu, Zhen

2016-11-01

Ultrasonic motor (USM) is an electromechanical coupling system with ultrasonic vibration, which is driven by the frictional contact force between the stator (vibrating body) and the rotor/slider (driven body). Stick-slip motion can occur at the contact interface when USM is operating, which may affect the performance of the motor. This paper develops a physically-based model to investigate the complex stick-slip-separation dynamics in a bimodal standing wave ultrasonic motor. The model includes both friction nonlinearity and intermittent separation nonlinearity of the system. Utilizing Hamilton's principle and assumed mode method, the dynamic equations of the stator are deduced. Based on the dynamics of the stator and the slider, sticking force during the stick phase is derived, which is used to examine the stick-to-slip transition. Furthermore, the stick-slip-separation kinematics is analyzed by establishing analytical criteria that predict the transition between stick, slip and separation of the interface. Stick-slip-separation motion is observed in the resulting model, and numerical simulations are performed to study the influence of parameters on the range of possible motions. Results show that stick-slip motion can occur with greater preload and smaller voltage amplitude. Furthermore, a dimensionless parameter is proposed to predict the occurrence of stick-slip versus slip-separation motions, and its role in designing ultrasonic motors is discussed. It is shown that slip-separation motion is favorable for the slider velocity.

Dynamics of driven flow with exclusion in graphenelike structures

NASA Astrophysics Data System (ADS)

Stinchcombe, R. B.; de Queiroz, S. L. A.

2015-05-01

We present a mean-field theory for the dynamics of driven flow with exclusion in graphenelike structures, and numerically check its predictions. We treat first a specific combination of bond transmissivity rates, where mean field predicts, and numerics to a large extent confirms, that the sublattice structure characteristic of honeycomb networks becomes irrelevant. Dynamics, in the various regions of the phase diagram set by open boundary injection and ejection rates, is then in general identical to that of one-dimensional systems, although some discrepancies remain between mean-field theory and numerical results, in similar ways for both geometries. However, at the critical point for which the characteristic exponent is z =3 /2 in one dimension, the mean-field value z =2 is approached for very large systems with constant (finite) aspect ratio. We also treat a second combination of bond (and boundary) rates where, more typically, sublattice distinction persists. For the two rate combinations, in continuum or late-time limits, respectively, the coupled sets of mean-field dynamical equations become tractable with various techniques and give a two-band spectrum, gapless in the critical phase. While for the second rate combination quantitative discrepancies between mean-field theory and simulations increase for most properties and boundary rates investigated, theory still is qualitatively correct in general, and gives a fairly good quantitative account of features such as the late-time evolution of density profile differences from their steady-state values.

Stationary States of Boundary Driven Exclusion Processes with Nonreversible Boundary Dynamics

NASA Astrophysics Data System (ADS)

Erignoux, C.; Landim, C.; Xu, T.

2018-05-01

We prove a law of large numbers for the empirical density of one-dimensional, boundary driven, symmetric exclusion processes with different types of non-reversible dynamics at the boundary. The proofs rely on duality techniques.

Science-Based, Community-Driven Approach to Reducing Glacier Lake Outburst Flood Risks in the Nepal Himalaya

NASA Astrophysics Data System (ADS)

Rounce, D.; McKinney, D. C.; Byers, A. C.; Shrestha, M. K.; Cuellar, A. D.; Sherpa, S. F.

2016-12-01

Over the past several decades, hundreds of lower altitude Himalayan glaciers have been melting, leaving behind new glacier lakes, holding millions of cubic meters of water. Usually contained by dams of loose boulders and soil, these lakes present a risk of glacial lake outburst floods (GLOFs). These glacial-dominated areas pose unique challenges to downstream communities in adapting to global climate change, particularly in terms of increasing threats of GLOFs. This interdisciplinary research captures unique knowledge of the Himalayan region and contributes to the development of a new generation of scientists in the area of coupled natural and human systems of glacier-dominated mountain systems. The goals of the research are to: (1) Understand natural system dynamics through an analysis of the impacts of climate change on glacial lakes, (2) Understand the human system dynamics through the strengthening of community resiliency to glacial lake hazards by developing community-driven glacial lake risk reduction systems, (3) Understand how the natural system affects the human system through the assessment of local ecological knowledge and understanding of hydrological resources and the vulnerability of the social-ecological system to GLOF hazard, and (4) Understand how the human system affects the natural system through the design and modeling of community-driven solutions to analyze the reduction of flood risk and the evolution of glacial lakes. The project integrates in situ physical and societal observations with geospatial analyses, intensive glacial hydrology and outburst flood modeling, key respondents' interviews, and community level mappings and focus groups. The Imja glacial lake in the Khumbu region of Nepal is the field research site. The project is assessing outburst flood-related processes that include glacier hydrology, river flow, hydraulics, and sediment/debris transport models. These natural system impacts are being integrated with the human science aspects to evaluate socio-economic impacts of potential outburst flood events on communities, households, and ecotourism.

Nonlinear Dynamics of Biofilm Growth on Sediment Surfaces

NASA Astrophysics Data System (ADS)

Molz, F. J.; Murdoch, L. C.; Faybishenko, B.

2013-12-01

Bioclogging often begins with the establishment of small colonies (microcolonies), which then form biofilms on the surfaces of a porous medium. These biofilm-porous media surfaces are not simple coatings of single microbes, but complex assemblages of cooperative and competing microbes, interacting with their chemical environment. This leads one to ask: what are the underlying dynamics involved with biofilm growth? To begin answering this question, we have extended the work of Kot et al. (1992, Bull. Mathematical Bio.) from a fully mixed chemostat to an idealized, one-dimensional, biofilm environment, taking into account a simple predator-prey microbial competition, with the prey feeding on a specified food source. With a variable (periodic) food source, Kot et al. (1992) were able to demonstrate chaotic dynamics in the coupled substrate-prey-predator system. Initially, deterministic chaos was thought by many to be mainly a mathematical phenomenon. However, several recent publications (e.g., Becks et al, 2005, Nature Letters; Graham et al. 2007, Int. Soc Microb. Eco. J.; Beninca et al., 2008, Nature Letters; Saleh, 2011, IJBAS) have brought together, using experimental studies and relevant mathematics, a breakthrough discovery that deterministic chaos is present in relatively simple biochemical systems. Two of us (Faybishenko and Molz, 2013, Procedia Environ. Sci)) have numerically analyzed a mathematical model of rhizosphere dynamics (Kravchenko et al., 2004, Microbiology) and detected patterns of nonlinear dynamical interactions supporting evidence of synchronized synergetic oscillations of microbial populations, carbon and oxygen concentrations driven by root exudation into a fully mixed system. In this study, we have extended the application of the Kot et al. model to investigate a spatially-dependent biofilm system. We will present the results of numerical simulations obtained using COMSOL Multi-Physics software, which we used to determine the nature of the complex dynamics. We found that complex dynamics occur even with a constant food supply maintained at the upstream boundary of the biofilm. Results will be presented along with a description of the model, including 3 coupled partial differential equations and examples of the localized and propagating nonlinear dynamics inherent in the system. Contrary to a common opinion that chaos in many mechanical systems is a type of instability, appearing when energy is added, we hypothesize, based on the results of our modeling, that chaos in biofilm dynamics and other microbial ecosystems is driven by a competitive decrease in the food supply (i.e., chemical energy). We also hypothesize that, somewhat paradoxically, this, in turn, may support a long-term system stability that could cause bioclogging in porous media.

Recent Results on "Approximations to Optimal Alarm Systems for Anomaly Detection"

NASA Technical Reports Server (NTRS)

Martin, Rodney Alexander

2009-01-01

An optimal alarm system and its approximations may use Kalman filtering for univariate linear dynamic systems driven by Gaussian noise to provide a layer of predictive capability. Predicted Kalman filter future process values and a fixed critical threshold can be used to construct a candidate level-crossing event over a predetermined prediction window. An optimal alarm system can be designed to elicit the fewest false alarms for a fixed detection probability in this particular scenario.

Fuzzy inductive reasoning: a consolidated approach to data-driven construction of complex dynamical systems

NASA Astrophysics Data System (ADS)

Nebot, Àngela; Mugica, Francisco

2012-10-01

Fuzzy inductive reasoning (FIR) is a modelling and simulation methodology derived from the General Systems Problem Solver. It compares favourably with other soft computing methodologies, such as neural networks, genetic or neuro-fuzzy systems, and with hard computing methodologies, such as AR, ARIMA, or NARMAX, when it is used to predict future behaviour of different kinds of systems. This paper contains an overview of the FIR methodology, its historical background, and its evolution.

AST: Activity-Security-Trust driven modeling of time varying networks

PubMed Central

Wang, Jian; Xu, Jiake; Liu, Yanheng; Deng, Weiwen

2016-01-01

Network modeling is a flexible mathematical structure that enables to identify statistical regularities and structural principles hidden in complex systems. The majority of recent driving forces in modeling complex networks are originated from activity, in which an activity potential of a time invariant function is introduced to identify agents’ interactions and to construct an activity-driven model. However, the new-emerging network evolutions are already deeply coupled with not only the explicit factors (e.g. activity) but also the implicit considerations (e.g. security and trust), so more intrinsic driving forces behind should be integrated into the modeling of time varying networks. The agents undoubtedly seek to build a time-dependent trade-off among activity, security, and trust in generating a new connection to another. Thus, we reasonably propose the Activity-Security-Trust (AST) driven model through synthetically considering the explicit and implicit driving forces (e.g. activity, security, and trust) underlying the decision process. AST-driven model facilitates to more accurately capture highly dynamical network behaviors and figure out the complex evolution process, allowing a profound understanding of the effects of security and trust in driving network evolution, and improving the biases induced by only involving activity representations in analyzing the dynamical processes. PMID:26888717

Controlling Contagion Processes in Activity Driven Networks

NASA Astrophysics Data System (ADS)

Liu, Suyu; Perra, Nicola; Karsai, Márton; Vespignani, Alessandro

2014-03-01

The vast majority of strategies aimed at controlling contagion processes on networks consider the connectivity pattern of the system either quenched or annealed. However, in the real world, many networks are highly dynamical and evolve, in time, concurrently with the contagion process. Here, we derive an analytical framework for the study of control strategies specifically devised for a class of time-varying networks, namely activity-driven networks. We develop a block variable mean-field approach that allows the derivation of the equations describing the coevolution of the contagion process and the network dynamic. We derive the critical immunization threshold and assess the effectiveness of three different control strategies. Finally, we validate the theoretical picture by simulating numerically the spreading process and control strategies in both synthetic networks and a large-scale, real-world, mobile telephone call data set.

Systems analysis of the vestibulo-ocular system. [mathematical model of vestibularly driven head and eye movements

NASA Technical Reports Server (NTRS)

Schmid, R. M.

1973-01-01

The vestibulo-ocular system is examined from the standpoint of system theory. The evolution of a mathematical model of the vestibulo-ocular system in an attempt to match more and more experimental data is followed step by step. The final model explains many characteristics of the eye movement in vestibularly induced nystagmus. The analysis of the dynamic behavior of the model at the different stages of its development is illustrated in time domain, mainly in a qualitative way.

On Cognition, Structured Sequence Processing, and Adaptive Dynamical Systems

NASA Astrophysics Data System (ADS)

Petersson, Karl Magnus

2008-11-01

Cognitive neuroscience approaches the brain as a cognitive system: a system that functionally is conceptualized in terms of information processing. We outline some aspects of this concept and consider a physical system to be an information processing device when a subclass of its physical states can be viewed as representational/cognitive and transitions between these can be conceptualized as a process operating on these states by implementing operations on the corresponding representational structures. We identify a generic and fundamental problem in cognition: sequentially organized structured processing. Structured sequence processing provides the brain, in an essential sense, with its processing logic. In an approach addressing this problem, we illustrate how to integrate levels of analysis within a framework of adaptive dynamical systems. We note that the dynamical system framework lends itself to a description of asynchronous event-driven devices, which is likely to be important in cognition because the brain appears to be an asynchronous processing system. We use the human language faculty and natural language processing as a concrete example through out.

Dynamically generated patterns in dense suspensions of active filaments

NASA Astrophysics Data System (ADS)

Prathyusha, K. R.; Henkes, Silke; Sknepnek, Rastko

2018-02-01

We use Langevin dynamics simulations to study dynamical behavior of a dense planar layer of active semiflexible filaments. Using the strength of active force and the thermal persistence length as parameters, we map a detailed phase diagram and identify several nonequilibrium phases in this system. In addition to a slowly flowing melt phase, we observe that, for sufficiently high activity, collective flow accompanied by signatures of local polar and nematic order appears in the system. This state is also characterized by strong density fluctuations. Furthermore, we identify an activity-driven crossover from this state of coherently flowing bundles of filaments to a phase with no global flow, formed by individual filaments coiled into rotating spirals. This suggests a mechanism where the system responds to activity by changing the shape of active agents, an effect with no analog in systems of active particles without internal degrees of freedom.

Advanced Education and Technology Business Plan, 2010-13. Highlights

ERIC Educational Resources Information Center

Alberta Advanced Education and Technology, 2010

2010-01-01

The Ministry of Advanced Education and Technology envisions Alberta's prosperity through innovation and lifelong learning. Advanced Education and Technology's mission is to lead the development of a knowledge-driven future through a dynamic and integrated advanced learning and innovation system. This paper presents the highlights of the business…

Advanced Education and Technology Business Plan, 2011-14

ERIC Educational Resources Information Center

Alberta Advanced Education and Technology, 2011

2011-01-01

Advanced Education and Technology's mission is to lead the development of a knowledge-driven future through a dynamic and integrated advanced learning and innovation system. Its core businesses are to: (1) provide strategic leadership for Campus Alberta and Alberta Innovates; and (2) engage learners, industry and the community in learning…

Novel linear piezoelectric motor for precision position stage

NASA Astrophysics Data System (ADS)

Chen, Chao; Shi, Yunlai; Zhang, Jun; Wang, Junshan

2016-03-01

Conventional servomotor and stepping motor face challenges in nanometer positioning stages due to the complex structure, motion transformation mechanism, and slow dynamic response, especially directly driven by linear motor. A new butterfly-shaped linear piezoelectric motor for linear motion is presented. A two-degree precision position stage driven by the proposed linear ultrasonic motor possesses a simple and compact configuration, which makes the system obtain shorter driving chain. Firstly, the working principle of the linear ultrasonic motor is analyzed. The oscillation orbits of two driving feet on the stator are produced successively by using the anti-symmetric and symmetric vibration modes of the piezoelectric composite structure, and the slider pressed on the driving feet can be propelled twice in only one vibration cycle. Then with the derivation of the dynamic equation of the piezoelectric actuator and transient response model, start-upstart-up and settling state characteristics of the proposed linear actuator is investigated theoretically and experimentally, and is applicable to evaluate step resolution of the precision platform driven by the actuator. Moreover the structure of the two-degree position stage system is described and a special precision displacement measurement system is built. Finally, the characteristics of the two-degree position stage are studied. In the closed-loop condition the positioning accuracy of plus or minus <0.5 μm is experimentally obtained for the stage propelled by the piezoelectric motor. A precision position stage based the proposed butterfly-shaped linear piezoelectric is theoretically and experimentally investigated.

Data-driven modeling reveals cell behaviors controlling self-organization during Myxococcus xanthus development

PubMed Central

Cotter, Christopher R.; Schüttler, Heinz-Bernd; Igoshin, Oleg A.; Shimkets, Lawrence J.

2017-01-01

Collective cell movement is critical to the emergent properties of many multicellular systems, including microbial self-organization in biofilms, embryogenesis, wound healing, and cancer metastasis. However, even the best-studied systems lack a complete picture of how diverse physical and chemical cues act upon individual cells to ensure coordinated multicellular behavior. Known for its social developmental cycle, the bacterium Myxococcus xanthus uses coordinated movement to generate three-dimensional aggregates called fruiting bodies. Despite extensive progress in identifying genes controlling fruiting body development, cell behaviors and cell–cell communication mechanisms that mediate aggregation are largely unknown. We developed an approach to examine emergent behaviors that couples fluorescent cell tracking with data-driven models. A unique feature of this approach is the ability to identify cell behaviors affecting the observed aggregation dynamics without full knowledge of the underlying biological mechanisms. The fluorescent cell tracking revealed large deviations in the behavior of individual cells. Our modeling method indicated that decreased cell motility inside the aggregates, a biased walk toward aggregate centroids, and alignment among neighboring cells in a radial direction to the nearest aggregate are behaviors that enhance aggregation dynamics. Our modeling method also revealed that aggregation is generally robust to perturbations in these behaviors and identified possible compensatory mechanisms. The resulting approach of directly combining behavior quantification with data-driven simulations can be applied to more complex systems of collective cell movement without prior knowledge of the cellular machinery and behavioral cues. PMID:28533367

Dynamically enriched topological orders in driven two-dimensional systems

NASA Astrophysics Data System (ADS)

Potter, Andrew C.; Morimoto, Takahiro

2017-04-01

Time-periodic driving of a quantum system can enable new dynamical topological phases of matter that could not exist in thermal equilibrium. We investigate two related classes of dynamical topological phenomena in 2D systems: Floquet symmetry-protected topological phases (FSPTs) and Floquet enriched topological orders (FETs). By constructing solvable lattice models for a complete set of 2D bosonic FSPT phases, we show that bosonic FSPTs can be understood as topological pumps which deposit loops of 1D SPT chains onto the boundary during each driving cycle, which protects a nontrivial edge state by dynamically tuning the edge to a self-dual point poised between the 1D SPT and trivial phases of the edge. By coupling these FSPT models to dynamical gauge fields, we construct solvable models of FET orders in which anyon excitations are dynamically transmuted into topologically distinct anyon types during each driving period. These bosonic FSPT and gauged FSPT models are classified by group cohomology methods. In addition, we also construct examples of "beyond cohomology" FET orders, which can be viewed as topological pumps of 1D topological chains formed of emergent anyonic quasiparticles.

Thermally and electrically controllable multiple high harmonics generation by harmonically driven quasi-two-dimensional electron gas

NASA Astrophysics Data System (ADS)

Maglevanny, I. I.; Smolar, V. A.; Karyakina, T. I.

2018-06-01

In this paper, we consider the activation processes in nonlinear meta-stable system based on a lateral (quasi-two-dimensional) superlattice and study the dynamics of such a system externally driven by a harmonic force. The internal control parameters are the longitudinal applied electric field and the sample temperature. The spontaneous transverse electric field is considered as an order parameter. The forced violations of order parameter are considered as a response of a system to periodic driving. We investigate the cooperative effects of self-organization and high harmonic forcing from the viewpoint of catastrophe theory and show the possibility of generation of third and higher odd harmonics in output signal that lead to distortion of its wave front. A higher harmonics detection strategy is further proposed and explained in detail by exploring the influences of system parameters on the response output of the system that are discussed through numerical simulations.

Faraday waves under time-reversed excitation.

PubMed

Pietschmann, Dirk; Stannarius, Ralf; Wagner, Christian; John, Thomas

2013-03-01

Do parametrically driven systems distinguish periodic excitations that are time mirrors of each other? Faraday waves in a Newtonian fluid are studied under excitation with superimposed harmonic wave forms. We demonstrate that the threshold parameters for the stability of the ground state are insensitive to a time inversion of the driving function. This is a peculiarity of some dynamic systems. The Faraday system shares this property with standard electroconvection in nematic liquid crystals [J. Heuer et al., Phys. Rev. E 78, 036218 (2008)]. In general, time inversion of the excitation affects the asymptotic stability of a parametrically driven system, even when it is described by linear ordinary differential equations. Obviously, the observed symmetry has to be attributed to the particular structure of the underlying differential equation system. The pattern selection of the Faraday waves above threshold, on the other hand, discriminates between time-mirrored excitation functions.

An intelligent factory-wide optimal operation system for continuous production process

NASA Astrophysics Data System (ADS)

Ding, Jinliang; Chai, Tianyou; Wang, Hongfeng; Wang, Junwei; Zheng, Xiuping

2016-03-01

In this study, a novel intelligent factory-wide operation system for a continuous production process is designed to optimise the entire production process, which consists of multiple units; furthermore, this system is developed using process operational data to avoid the complexity of mathematical modelling of the continuous production process. The data-driven approach aims to specify the structure of the optimal operation system; in particular, the operational data of the process are used to formulate each part of the system. In this context, the domain knowledge of process engineers is utilised, and a closed-loop dynamic optimisation strategy, which combines feedback, performance prediction, feed-forward, and dynamic tuning schemes into a framework, is employed. The effectiveness of the proposed system has been verified using industrial experimental results.

A model of the human in a cognitive prediction task.

NASA Technical Reports Server (NTRS)

Rouse, W. B.

1973-01-01

The human decision maker's behavior when predicting future states of discrete linear dynamic systems driven by zero-mean Gaussian processes is modeled. The task is on a slow enough time scale that physiological constraints are insignificant compared with cognitive limitations. The model is basically a linear regression system identifier with a limited memory and noisy observations. Experimental data are presented and compared to the model.

Interorganizational health care systems implementations: an exploratory study of early electronic commerce initiatives.

PubMed

Payton, F C; Ginzberg, M J

2001-01-01

Changing business practices, customers needs, and market dynamics have driven many organizations to implement interorganizational systems (IOSs). IOSs have been successfully implemented in the banking, cotton, airline, and consumer-goods industries, and recently attention has turned to the health care industry. This article describes an exploratory study of health care IOS implementations based on the voluntary community health information network (CHIN) model.

Design Tools for Dynamic, Data-Driven, Stream Mining Systems

DTIC Science & Technology

2015-01-01

Headquarters Services , Directorate for Information Operations and Reports, 1215 Jefferson Davis Highway, Suite 1204, Arlington VA 22202-4302. Respondents should...be aware that notwithstanding any other provision of law , no person shall be subject to a penalty for failing to comply with a collection of...systems that are targeted to resource- and energy-constrained embedded environments, such as unmanned areal vehicles (UAVs), mobile communication

DOE Office of Scientific and Technical Information (OSTI.GOV)

Costa, Liborio I., E-mail: liborio78@gmail.com

A new Markov Chain Monte Carlo method for simulating the dynamics of particle systems characterized by hard-core interactions is introduced. In contrast to traditional Kinetic Monte Carlo approaches, where the state of the system is associated with minima in the energy landscape, in the proposed method, the state of the system is associated with the set of paths traveled by the atoms and the transition probabilities for an atom to be displaced are proportional to the corresponding velocities. In this way, the number of possible state-to-state transitions is reduced to a discrete set, and a direct link between the Montemore » Carlo time step and true physical time is naturally established. The resulting rejection-free algorithm is validated against event-driven molecular dynamics: the equilibrium and non-equilibrium dynamics of hard disks converge to the exact results with decreasing displacement size.« less

Experimental Chaos - Proceedings of the 3rd Conference

NASA Astrophysics Data System (ADS)

Harrison, Robert G.; Lu, Weiping; Ditto, William; Pecora, Lou; Spano, Mark; Vohra, Sandeep

1996-10-01

The Table of Contents for the full book PDF is as follows: * Preface * Spatiotemporal Chaos and Patterns * Scale Segregation via Formation of Domains in a Nonlinear Optical System * Laser Dynamics as Hydrodynamics * Spatiotemporal Dynamics of Human Epileptic Seizures * Experimental Transition to Chaos in a Quasi 1D Chain of Oscillators * Measuring Coupling in Spatiotemporal Dynamical Systems * Chaos in Vortex Breakdown * Dynamical Analysis * Radial Basis Function Modelling and Prediction of Time Series * Nonlinear Phenomena in Polyrhythmic Hand Movements * Using Models to Diagnose, Test and Control Chaotic Systems * New Real-Time Analysis of Time Series Data with Physical Wavelets * Control and Synchronization * Measuring and Controlling Chaotic Dynamics in a Slugging Fluidized Bed * Control of Chaos in a Laser with Feedback * Synchronization and Chaotic Diode Resonators * Control of Chaos by Continuous-time Feedback with Delay * A Framework for Communication using Chaos Sychronization * Control of Chaos in Switching Circuits * Astrophysics, Meteorology and Oceanography * Solar-Wind-Magnetospheric Dynamics via Satellite Data * Nonlinear Dynamics of the Solar Atmosphere * Fractal Dimension of Scalar and Vector Variables from Turbulence Measurements in the Atmospheric Surface Layer * Mechanics * Escape and Overturning: Subtle Transient Behavior in Nonlinear Mechanical Models * Organising Centres in the Dynamics of Parametrically Excited Double Pendulums * Intermittent Behaviour in a Heating System Driven by Phase Transitions * Hydrodynamics * Size Segregation in Couette Flow of Granular Material * Routes to Chaos in Rotational Taylor-Couette Flow * Experimental Study of the Laminar-Turbulent Transition in an Open Flow System * Chemistry * Order and Chaos in Excitable Media under External Forcing * A Chemical Wave Propagation with Accelerating Speed Accompanied by Hydrodynamic Flow * Optics * Instabilities in Semiconductor Lasers with Optical Injection * Spatio-Temporal Dynamics of a Bimode CO2 Laser with Saturable Absorber * Chaotic Homoclinic Phenomena in Opto-Thermal Devices * Observation and Characterisation of Low-Frequency Chaos in Semiconductor Lasers with External Feedback * Condensed Matter * The Application of Nonlinear Dynamics in the Study of Ferroelectric Materials * Cellular Convection in a Small Aspect Ratio Liquid Crystal Device * Driven Spin-Wave Dynamics in YIG Films * Quantum Chaology in Quartz * Small Signal Amplification Caused by Nonlinear Properties of Ferroelectrics * Composite Materials Evolved from Chaos * Electronics and Circuits * Controlling a Chaotic Array of Pulse-Coupled Fitzhugh-Nagumo Circuits * Experimental Observation of On-Off Intermittency * Phase Lock-In of Chaotic Relaxation Oscillators * Biology and Medicine * Singular Value Decomposition and Circuit Structure in Invertebrate Ganglia * Nonlinear Forecasting of Spike Trains from Neurons of a Mollusc * Ultradian Rhythm in the Sensitive Plants: Chaos or Coloured Noise? * Chaos and the Crayfish Sixth Ganglion * Hardware Coupled Nonlinear Oscillators as a Model of Retina

Study on initiative vibration absorbing technology of optics in strong disturbed environment

NASA Astrophysics Data System (ADS)

Jia, Si-nan; Xiong, Mu-di; Zou, Xiao-jie

2007-12-01

Strong disturbed environment is apt to cause irregular vibration, which seriously affects optical collimation. To improve the performance of laser beam, three-point dynamic vibration absorbing method is proposed, and laser beam initiative vibration absorbing system is designed. The maladjustment signal is detected by position sensitive device (PSD), three groups of PZT are driven to adjust optical element in real-time, so the performance of output-beam is improved. The coupling model of the system is presented. Multivariable adaptive closed-loop decoupling arithmetic is used to design three-input-three-output decoupling controller, so that high precision dynamic adjusting is realized. Experiments indicate that the system has good shock absorbing efficiency.

Many-body dynamics of driven-dissipative Rydberg cavity polaritons

NASA Astrophysics Data System (ADS)

Pistorius, Tim; Fan, Jingtao; Weimer, Hendrik

2017-04-01

The usage of photons as long-range information carriers has greatly increased the interest in systems with nonlinear optical properties in recent years. The nonlinearity is easily achievable in Rydberg mediums through the strong van der Waals interaction which makes them one of the best candidates for such a system. Here, we propose a way to analyze the steady state solutions of a Rydberg medium in a cavity through the combination of the variational principle for open quantum systems and the P-distribution of the density matrix. To get a better understanding of the many-body-dynamics a transformation into the polariton picture is performed and investigated. Volkswagen Foundation, Deutsche Forschungsgemeinschaft.

Localization of intense electromagnetic waves in a relativistically hot plasma.

PubMed

Shukla, P K; Eliasson, B

2005-02-18

We consider nonlinear interactions between intense short electromagnetic waves (EMWs) and a relativistically hot electron plasma that supports relativistic electron holes (REHs). It is shown that such EMW-REH interactions are governed by a coupled nonlinear system of equations composed of a nonlinear Schro dinger equation describing the dynamics of the EMWs and the Poisson-relativistic Vlasov system describing the dynamics of driven REHs. The present nonlinear system of equations admits both a linearly trapped discrete number of eigenmodes of the EMWs in a quasistationary REH and a modification of the REH by large-amplitude trapped EMWs. Computer simulations of the relativistic Vlasov and Maxwell-Poisson system of equations show complex interactions between REHs loaded with localized EMWs.

Floquet prethermalization and regimes of heating in a periodically driven, interacting quantum system

NASA Astrophysics Data System (ADS)

Weidinger, Simon; Knap, Michael

We study the regimes of heating in the periodically driven O (N) -model, which represents a generic model for interacting quantum many-body systems. By computing the absorbed energy with a non-equilibrium Keldysh Green's function approach, we establish three dynamical regimes: at short times a single-particle dominated regime, at intermediate times a stable Floquet prethermal regime in which the system ceases to absorb, and at parametrically late times a thermalizing regime. Our simulations suggest that in the thermalizing regime the absorbed energy grows algebraically in time with an the exponent that approaches the universal value of 1 / 2 , and is thus significantly slower than linear Joule heating. Our results demonstrate the parametric stability of prethermal states in a generic many-body system driven at frequencies that are comparable to its microscopic scales. This paves the way for realizing exotic quantum phases, such as time crystals or interacting topological phases, in the prethermal regime of interacting Floquet systems. We acknowledge support from the Technical University of Munich - Institute for Advanced Study, funded by the German Excellence Initiative and the European Union FP7 under Grant agreement 291763, and from the DFG Grant No. KN 1254/1-1.

Near-infrared light–responsive dynamic wrinkle patterns

PubMed Central

Hou, Honghao; Yin, Jie

2018-01-01

Dynamic micro/nanopatterns provide an effective approach for on-demand tuning of surface properties to realize a smart surface. We report a simple yet versatile strategy for the fabrication of near-infrared (NIR) light–responsive dynamic wrinkles by using a carbon nanotube (CNT)–containing poly(dimethylsiloxane) (PDMS) elastomer as the substrate for the bilayer systems, with various functional polymers serving as the top stiff layers. The high photon-to-thermal energy conversion of CNT leads to the NIR-controlled thermal expansion of the elastic CNT-PDMS substrate, resulting in dynamic regulation of the applied strain (ε) of the bilayer system by the NIR on/off cycle to obtain a reversible wrinkle pattern. The switchable surface topological structures can transfer between the wrinkled state and the wrinkle-free state within tens of seconds via NIR irradiation. As a proof-of-concept application, this type of NIR-driven dynamic wrinkle pattern was used in smart displays, dynamic gratings, and light control electronics. PMID:29740615

Investigating multiphoton phenomena using nonlinear dynamics

NASA Astrophysics Data System (ADS)

Huang, Shu

Many seemingly simple systems can display extraordinarily complex dynamics which has been studied and uncovered through nonlinear dynamical theory. The leitmotif of this thesis is changing phase-space structures and their (linear or non-linear) stabilities by adding control functions (which act on the system as external perturbations) to the relevant Hamiltonians. These phase-space structures may be periodic orbits, invariant tori or their stable and unstable manifolds. One-electron systems and diatomic molecules are fundamental and important staging ground for new discoveries in nonlinear dynamics. In past years, increasing emphasis and effort has been put on the control or manipulation of these systems. Recent developments of nonlinear dynamical tools can provide efficient ways of doing so. In the first subtopic of the thesis, we are adding a control function to restore tori at prescribed locations in phase space. In the remainder of the thesis, a control function with parameters is used to change the linear stability of the periodic orbits which govern the processes in question. In this thesis, we report our theoretical analyses on multiphoton ionization of Rydberg atoms exposed to strong microwave fields and the dissociation of diatomic molecules exposed to bichromatic lasers using nonlinear dynamical tools. This thesis is composed of three subtopics. In the first subtopic, we employ local control theory to reduce the stochastic ionization of hydrogen atom in a strong microwave field by adding a relatively small control term to the original Hamiltonian. In the second subtopic, we perform periodic orbit analysis to investigate multiphoton ionization driven by a bichromatic microwave field. Our results show quantitative and qualitative agreement with previous studies, and hence identify the mechanism through which short periodic orbits organize the dynamics in multiphoton ionization. In addition, we achieve substantial time savings with this approach. In the third subtopic we extend our periodic orbit analysis to the dissociation of diatomic molecules driven by a bichromatic laser. In this problem, our results based on periodic orbit analysis again show good agreement with previous work, and hence promise more potential applications of this approach in molecular physics.

Simulation of quantum dynamics based on the quantum stochastic differential equation.

PubMed

Li, Ming

2013-01-01

The quantum stochastic differential equation derived from the Lindblad form quantum master equation is investigated. The general formulation in terms of environment operators representing the quantum state diffusion is given. The numerical simulation algorithm of stochastic process of direct photodetection of a driven two-level system for the predictions of the dynamical behavior is proposed. The effectiveness and superiority of the algorithm are verified by the performance analysis of the accuracy and the computational cost in comparison with the classical Runge-Kutta algorithm.

Entropy-driven homochiral self-sorting of a dynamic library.

PubMed

Atcher, Joan; Bujons, Jordi; Alfonso, Ignacio

2017-04-11

A dynamic mixture of stereoisomeric macrocycles derived from glutamic acid displayed a homochiral self-selection when increasing the acetonitrile content of the aqueous mixed medium. The homochiral self-sorting required the anionic form of the side chains and increased at higher temperature, implying an entropic origin. Conformational analysis (NMR and MD simulations) allowed us to explain the observed behaviour. The results show that entropy can play a role in the homochiral self-sorting in adaptive bio-inspired chemical systems.

Dynamical stability of slip-stacking particles

DOE Office of Scientific and Technical Information (OSTI.GOV)

Eldred, Jeffrey; Zwaska, Robert

2014-09-01

We study the stability of particles in slip-stacking configuration, used to nearly double proton beam intensity at Fermilab. We introduce universal area factors to calculate the available phase space area for any set of beam parameters without individual simulation. We find perturbative solutions for stable particle trajectories. We establish Booster beam quality requirements to achieve 97% slip-stacking efficiency. We show that slip-stacking dynamics directly correspond to the driven pendulum and to the system of two standing-wave traps moving with respect to each other.

Condensation of helium in aerogel and athermal dynamics of the random-field Ising model.

PubMed

Aubry, Geoffroy J; Bonnet, Fabien; Melich, Mathieu; Guyon, Laurent; Spathis, Panayotis; Despetis, Florence; Wolf, Pierre-Etienne

2014-08-22

High resolution measurements reveal that condensation isotherms of (4)He in high porosity silica aerogel become discontinuous below a critical temperature. We show that this behavior does not correspond to an equilibrium phase transition modified by the disorder induced by the aerogel structure, but to the disorder-driven critical point predicted for the athermal out-of-equilibrium dynamics of the random-field Ising model. Our results evidence the key role of nonequilibrium effects in the phase transitions of disordered systems.

Managing lifelike behavior in a dynamic self-assembled system

NASA Astrophysics Data System (ADS)

Ropp, Chad; Bachelard, Nicolas; Wang, Yuan; Zhang, Xiang

Self-organization can arise outside of thermodynamic equilibrium in a process of dynamic self-assembly. This is observed in nature, for example in flocking birds, but can also be created artificially with non-living entities. Such dynamic systems often display lifelike properties, including the ability to self-heal and adapt to environmental changes, which arise due to the collective and often complex interactions between the many individual elements. Such interactions are inherently difficult to predict and control, and limit the development of artificial systems. Here, we report a fundamentally new method to manage dynamic self-assembly through the direct external control of collective phenomena. Our system consists of a waveguide filled with mobile scattering particles. These particles spontaneously self-organize when driven by a coherent field, self-heal when mechanically perturbed, and adapt to changes in the drive wavelength. This behavior is governed by particle interactions that are completely mediated by coherent wave scattering. Compared to hydrodynamic interactions which lead to compact ordered structures, our system displays sinusoidal degeneracy and many different steady-state geometries that can be adjusted using the external field.

"Structure and dynamics in complex chemical systems: Gaining new insights through recent advances in time-resolved spectroscopies.” ACS Division of Physical Chemistry Symposium presented at the Fall National ACS Meeting in Boston, MA, August 2015

DOE Office of Scientific and Technical Information (OSTI.GOV)

Crawford, Daniel

8-Session Symposium on STRUCTURE AND DYNAMICS IN COMPLEX CHEMICAL SYSTEMS: GAINING NEW INSIGHTS THROUGH RECENT ADVANCES IN TIME-RESOLVED SPECTROSCOPIES. The intricacy of most chemical, biochemical, and material processes and their applications are underscored by the complex nature of the environments in which they occur. Substantial challenges for building a global understanding of a heterogeneous system include (1) identifying unique signatures associated with specific structural motifs within the heterogeneous distribution, and (2) resolving the significance of each of multiple time scales involved in both small- and large-scale nuclear reorganization. This symposium focuses on the progress in our understanding of dynamics inmore » complex systems driven by recent innovations in time-resolved spectroscopies and theoretical developments. Such advancement is critical for driving discovery at the molecular level facilitating new applications. Broad areas of interest include: Structural relaxation and the impact of structure on dynamics in liquids, interfaces, biochemical systems, materials, and other heterogeneous environments.« less

Eco-evolutionary Red Queen dynamics regulate biodiversity in a metabolite-driven microbial system.

PubMed

Bonachela, Juan A; Wortel, Meike T; Stenseth, Nils Chr

2017-12-15

The Red Queen Hypothesis proposes that perpetual co-evolution among organisms can result from purely biotic drivers. After more than four decades, there is no satisfactory understanding as to which mechanisms trigger Red Queen dynamics or their implications for ecosystem features such as biodiversity. One reason for such a knowledge gap is that typical models are complicated theories where limit cycles represent an idealized Red Queen, and therefore cannot be used to devise experimental setups. Here, we bridge this gap by introducing a simple model for microbial systems able to show Red Queen dynamics. We explore diverse biotic sources that can drive the emergence of the Red Queen and that have the potential to be found in nature or to be replicated in the laboratory. Our model enables an analytical understanding of how Red Queen dynamics emerge in our setup, and the translation of model terms and phenomenology into general underlying mechanisms. We observe, for example, that in our system the Red Queen offers opportunities for the increase of biodiversity by facilitating challenging conditions for intraspecific dominance, whereas stasis tends to homogenize the system. Our results can be used to design and engineer experimental microbial systems showing Red Queen dynamics.

Exploring a QoS Driven Scheduling Approach for Peer-to-Peer Live Streaming Systems with Network Coding

PubMed Central

Cui, Laizhong; Lu, Nan; Chen, Fu

2014-01-01

Most large-scale peer-to-peer (P2P) live streaming systems use mesh to organize peers and leverage pull scheduling to transmit packets for providing robustness in dynamic environment. The pull scheduling brings large packet delay. Network coding makes the push scheduling feasible in mesh P2P live streaming and improves the efficiency. However, it may also introduce some extra delays and coding computational overhead. To improve the packet delay, streaming quality, and coding overhead, in this paper are as follows. we propose a QoS driven push scheduling approach. The main contributions of this paper are: (i) We introduce a new network coding method to increase the content diversity and reduce the complexity of scheduling; (ii) we formulate the push scheduling as an optimization problem and transform it to a min-cost flow problem for solving it in polynomial time; (iii) we propose a push scheduling algorithm to reduce the coding overhead and do extensive experiments to validate the effectiveness of our approach. Compared with previous approaches, the simulation results demonstrate that packet delay, continuity index, and coding ratio of our system can be significantly improved, especially in dynamic environments. PMID:25114968

Effects of cross correlation on the relaxation time of a bistable system driven by cross-correlated noise

NASA Astrophysics Data System (ADS)

Mei, Dongcheng; Xie, Chongwei; Zhang, Li

2003-11-01

We study the effects of correlations between additive and multiplicative noise on relaxation time in a bistable system driven by cross-correlated noise. Using the projection-operator method, we derived an analytic expression for the relaxation time Tc of the system, which is the function of additive (α) and multiplicative (D) noise intensities, correlation intensity λ of noise, and correlation time τ of noise. After introducing a noise intensity ratio and a dimensionless parameter R=D/α, and then performing numerical computations, we find the following: (i) For the case of R<1, the relaxation time Tc increases as R increases. (ii) For the cases of R⩾1, there is a one-peak structure on the Tc-R plot and the effects of cross-correlated noise on the relaxation time are very notable. (iii) For the case of R<1, Tc almost does not change with both λ and τ, and for the cases of R⩾1, Tc decreases as λ increases, however Tc increases as τ increases. λ and τ play opposite roles in Tc, i.e., λ enhances the fluctuation decay of dynamical variable and τ slows down the fluctuation decay of dynamical variable.

Reducing usage of the computational resources by event driven approach to model predictive control

NASA Astrophysics Data System (ADS)

Misik, Stefan; Bradac, Zdenek; Cela, Arben

2017-08-01

This paper deals with a real-time and optimal control of dynamic systems while also considers the constraints which these systems might be subject to. Main objective of this work is to propose a simple modification of the existing Model Predictive Control approach to better suit needs of computational resource-constrained real-time systems. An example using model of a mechanical system is presented and the performance of the proposed method is evaluated in a simulated environment.

IMAT (Integrated Multidisciplinary Analysis Tool) user's guide for the VAX/VMS computer

NASA Technical Reports Server (NTRS)

Meissner, Frances T. (Editor)

1988-01-01

The Integrated Multidisciplinary Analysis Tool (IMAT) is a computer software system for the VAX/VMS computer developed at the Langley Research Center. IMAT provides researchers and analysts with an efficient capability to analyze satellite control systems influenced by structural dynamics. Using a menu-driven executive system, IMAT leads the user through the program options. IMAT links a relational database manager to commercial and in-house structural and controls analysis codes. This paper describes the IMAT software system and how to use it.

Evidence for a Quantum-to-Classical Transition in a Pair of Coupled Quantum Rotors

NASA Astrophysics Data System (ADS)

Gadway, Bryce; Reeves, Jeremy; Krinner, Ludwig; Schneble, Dominik

2013-05-01

The understanding of how classical dynamics can emerge in closed quantum systems is a problem of fundamental importance. Remarkably, while classical behavior usually arises from coupling to thermal fluctuations or random spectral noise, it may also be an innate property of certain isolated, periodically driven quantum systems. Here, we experimentally realize the simplest such system, consisting of two coupled, kicked quantum rotors, by subjecting a coherent atomic matter wave to two periodically pulsed, incommensurate optical lattices. Momentum transport in this system is found to be radically different from that in a single kicked rotor, with a breakdown of dynamical localization and the emergence of classical diffusion. Our observation, which confirms a long-standing prediction for many-dimensional quantum-chaotic systems, sheds new light on the quantum-classical correspondence.

Stochastic modeling indicates that aging and somatic evolution in the hematopoetic system are driven by non-cell-autonomous processes.

PubMed

Rozhok, Andrii I; Salstrom, Jennifer L; DeGregori, James

2014-12-01

Age-dependent tissue decline and increased cancer incidence are widely accepted to be rate-limited by the accumulation of somatic mutations over time. Current models of carcinogenesis are dominated by the assumption that oncogenic mutations have defined advantageous fitness effects on recipient stem and progenitor cells, promoting and rate-limiting somatic evolution. However, this assumption is markedly discrepant with evolutionary theory, whereby fitness is a dynamic property of a phenotype imposed upon and widely modulated by environment. We computationally modeled dynamic microenvironment-dependent fitness alterations in hematopoietic stem cells (HSC) within the Sprengel-Liebig system known to govern evolution at the population level. Our model for the first time integrates real data on age-dependent dynamics of HSC division rates, pool size, and accumulation of genetic changes and demonstrates that somatic evolution is not rate-limited by the occurrence of mutations, but instead results from aged microenvironment-driven alterations in the selective/fitness value of previously accumulated genetic changes. Our results are also consistent with evolutionary models of aging and thus oppose both somatic mutation-centric paradigms of carcinogenesis and tissue functional decline. In total, we demonstrate that aging directly promotes HSC fitness decline and somatic evolution via non-cell-autonomous mechanisms.

A quantum relaxation-time approximation for finite fermion systems

NASA Astrophysics Data System (ADS)

Reinhard, P.-G.; Suraud, E.

2015-03-01

We propose a relaxation time approximation for the description of the dynamics of strongly excited fermion systems. Our approach is based on time-dependent density functional theory at the level of the local density approximation. This mean-field picture is augmented by collisional correlations handled in relaxation time approximation which is inspired from the corresponding semi-classical picture. The method involves the estimate of microscopic relaxation rates/times which is presently taken from the well established semi-classical experience. The relaxation time approximation implies evaluation of the instantaneous equilibrium state towards which the dynamical state is progressively driven at the pace of the microscopic relaxation time. As test case, we consider Na clusters of various sizes excited either by a swift ion projectile or by a short and intense laser pulse, driven in various dynamical regimes ranging from linear to strongly non-linear reactions. We observe a strong effect of dissipation on sensitive observables such as net ionization and angular distributions of emitted electrons. The effect is especially large for moderate excitations where typical relaxation/dissipation time scales efficiently compete with ionization for dissipating the available excitation energy. Technical details on the actual procedure to implement a working recipe of such a quantum relaxation approximation are given in appendices for completeness.

The dynamic model on the impact of biodiesel blend mandate (B5) on Malaysian palm oil domestic demand: A preliminary finding

NASA Astrophysics Data System (ADS)

Abidin, Norhaslinda Zainal; Applanaidu, Shri-Dewi; Sapiri, Hasimah

2014-12-01

Over the last ten years, world biofuels production has increased dramatically. The biodiesel demand is driven by the increases in fossil fuel prices, government policy mandates, income from gross domestic product and population growth. In the European Union, biofuel consumption is mostly driven by blending mandates in both France and Germany. In the case of Malaysia, biodiesel has started to be exported since 2006. The B5 of 5% blend of palm oil based biodiesel into diesel in all government vehicles was implemented in February 2009 and it is expected to be implemented nationwide in the nearest time. How will the blend mandate will project growth in the domestic demand of palm oil in Malaysia? To analyze this issue, a system dynamics model was constructed to evaluate the impact of blend mandate implementation on the palm oil domestic demand influence. The base run of simulation analysis indicates that the trend of domestic demand will increase until 2030 in parallel with the implementation of 5 percent of biodiesel mandate. Finally, this study depicts that system dynamics is a useful tool to gain insight and to experiment with the impact of changes in blend mandate implementation on the future growth of Malaysian palm oil domestic demand sector.

Development of 1D Liner Compression Code for IDL

NASA Astrophysics Data System (ADS)

Shimazu, Akihisa; Slough, John; Pancotti, Anthony

2015-11-01

A 1D liner compression code is developed to model liner implosion dynamics in the Inductively Driven Liner Experiment (IDL) where FRC plasmoid is compressed via inductively-driven metal liners. The driver circuit, magnetic field, joule heating, and liner dynamics calculations are performed at each time step in sequence to couple these effects in the code. To obtain more realistic magnetic field results for a given drive coil geometry, 2D and 3D effects are incorporated into the 1D field calculation through use of correction factor table lookup approach. Commercial low-frequency electromagnetic fields solver, ANSYS Maxwell 3D, is used to solve the magnetic field profile for static liner condition at various liner radius in order to derive correction factors for the 1D field calculation in the code. The liner dynamics results from the code is verified to be in good agreement with the results from commercial explicit dynamics solver, ANSYS Explicit Dynamics, and previous liner experiment. The developed code is used to optimize the capacitor bank and driver coil design for better energy transfer and coupling. FRC gain calculations are also performed using the liner compression data from the code for the conceptual design of the reactor sized system for fusion energy gains.

Prethermal time crystals in a one-dimensional periodically driven Floquet system

NASA Astrophysics Data System (ADS)

Zeng, Tian-Sheng; Sheng, D. N.

2017-09-01

Motivated by experimental observations of time-symmetry breaking behavior in a periodically driven (Floquet) system, we study a one-dimensional spin model to explore the stability of such Floquet discrete time crystals (DTCs) under the interplay between interaction and the microwave driving. For intermediate interactions and high drivings, from the time evolution of both stroboscopic spin polarization and mutual information between two ends, we show that Floquet DTCs can exist in a prethermal time regime without the tuning of strong disorder. For much weak interactions the system is a symmetry-unbroken phase, while for strong interactions it gives its way to a thermal phase. Through analyzing the entanglement dynamics, we show that large driving fields protect the prethermal DTCs from many-body localization and thermalization. Our results suggest that by increasing the spin interaction, one can drive the experimental system into optimal regime for observing a robust prethermal DTC phase.

Instabilities and finger formation in replacement fronts driven by an oversaturated solution

NASA Astrophysics Data System (ADS)

Kondratiuk, Paweł; Tredak, Hanna; Upadhyay, Virat; Ladd, Anthony J. C.; Szymczak, Piotr

2017-08-01

We consider a simple model of infiltration-driven mineral replacement, in which the chemical coupling between precipitation and dissolution leads to the appearance of a reaction front advancing into the system. Such fronts are usually accompanied by a local increase of porosity. We analyze the linear stability of the replacement front to establish whether such a localized porosity increase can lead to global instability and pattern formation in these systems. We find that for a wide range of control parameters such fronts are unstable. However, both short- and long-wavelength perturbations are stabilized, whereas in a purely dissolutional instability only short wavelengths are stable. We analyze the morphologies of the dissolution patterns emerging in the later stages of the evolution of the system, when the dynamics are beyond the linear regime. Implications of these results for the natural systems are discussed, particularly in the context of karst formation in terra rossa-covered carbonate bedrock.

Ergodicity in natural earthquake fault networks

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tiampo, K. F.; Rundle, J. B.; Holliday, J.

2007-06-15

Numerical simulations have shown that certain driven nonlinear systems can be characterized by mean-field statistical properties often associated with ergodic dynamics [C. D. Ferguson, W. Klein, and J. B. Rundle, Phys. Rev. E 60, 1359 (1999); D. Egolf, Science 287, 101 (2000)]. These driven mean-field threshold systems feature long-range interactions and can be treated as equilibriumlike systems with statistically stationary dynamics over long time intervals. Recently the equilibrium property of ergodicity was identified in an earthquake fault system, a natural driven threshold system, by means of the Thirumalai-Mountain (TM) fluctuation metric developed in the study of diffusive systems [K. F.more » Tiampo, J. B. Rundle, W. Klein, J. S. Sa Martins, and C. D. Ferguson, Phys. Rev. Lett. 91, 238501 (2003)]. We analyze the seismicity of three naturally occurring earthquake fault networks from a variety of tectonic settings in an attempt to investigate the range of applicability of effective ergodicity, using the TM metric and other related statistics. Results suggest that, once variations in the catalog data resulting from technical and network issues are accounted for, all of these natural earthquake systems display stationary periods of metastable equilibrium and effective ergodicity that are disrupted by large events. We conclude that a constant rate of events is an important prerequisite for these periods of punctuated ergodicity and that, while the level of temporal variability in the spatial statistics is the controlling factor in the ergodic behavior of seismic networks, no single statistic is sufficient to ensure quantification of ergodicity. Ergodicity in this application not only requires that the system be stationary for these networks at the applicable spatial and temporal scales, but also implies that they are in a state of metastable equilibrium, one in which the ensemble averages can be substituted for temporal averages in studying their spatiotemporal evolution.« less

Combining Theory-Driven Evaluation and Causal Loop Diagramming for Opening the 'Black Box' of an Intervention in the Health Sector: A Case of Performance-Based Financing in Western Uganda.

PubMed

Renmans, Dimitri; Holvoet, Nathalie; Criel, Bart

2017-09-03

Increased attention on "complexity" in health systems evaluation has resulted in many different methodological responses. Theory-driven evaluations and systems thinking are two such responses that aim for better understanding of the mechanisms underlying given outcomes. Here, we studied the implementation of a performance-based financing intervention by the Belgian Technical Cooperation in Western Uganda to illustrate a methodological strategy of combining these two approaches. We utilized a systems dynamics tool called causal loop diagramming (CLD) to generate hypotheses feeding into a theory-driven evaluation. Semi-structured interviews were conducted with 30 health workers from two districts (Kasese and Kyenjojo) and with 16 key informants. After CLD, we identified three relevant hypotheses: "success to the successful", "growth and underinvestment", and "supervision conundrum". The first hypothesis leads to increasing improvements in performance, as better performance leads to more incentives, which in turn leads to better performance. The latter two hypotheses point to potential bottlenecks. Thus, the proposed methodological strategy was a useful tool for identifying hypotheses that can inform a theory-driven evaluation. The hypotheses are represented in a comprehensible way while highlighting the underlying assumptions, and are more easily falsifiable than hypotheses identified without using CLD.

Real-time observation of fluctuations at the driven-dissipative Dicke phase transition

PubMed Central

Brennecke, Ferdinand; Mottl, Rafael; Baumann, Kristian; Landig, Renate; Donner, Tobias; Esslinger, Tilman

2013-01-01

We experimentally study the influence of dissipation on the driven Dicke quantum phase transition, realized by coupling external degrees of freedom of a Bose–Einstein condensate to the light field of a high-finesse optical cavity. The cavity provides a natural dissipation channel, which gives rise to vacuum-induced fluctuations and allows us to observe density fluctuations of the gas in real-time. We monitor the divergence of these fluctuations over two orders of magnitude while approaching the phase transition, and observe a behavior that deviates significantly from that expected for a closed system. A correlation analysis of the fluctuations reveals the diverging time scale of the atomic dynamics and allows us to extract a damping rate for the external degree of freedom of the atoms. We find good agreement with our theoretical model including dissipation via both the cavity field and the atomic field. Using a dissipation channel to nondestructively gain information about a quantum many-body system provides a unique path to study the physics of driven-dissipative systems. PMID:23818599

Nonlinear Dynamics of a Magnetically Driven Duffing-Type Spring-Magnet Oscillator in the Static Magnetic Field of a Coil

ERIC Educational Resources Information Center

Donoso, Guillermo; Ladera, Celso L.

2012-01-01

We study the nonlinear oscillations of a forced and weakly dissipative spring-magnet system moving in the magnetic fields of two fixed coaxial, hollow induction coils. As the first coil is excited with a dc current, both a linear and a cubic magnet-position dependent force appear on the magnet-spring system. The second coil, located below the…

Computation in Dynamically Bounded Asymmetric Systems

PubMed Central

Rutishauser, Ueli; Slotine, Jean-Jacques; Douglas, Rodney

2015-01-01

Previous explanations of computations performed by recurrent networks have focused on symmetrically connected saturating neurons and their convergence toward attractors. Here we analyze the behavior of asymmetrical connected networks of linear threshold neurons, whose positive response is unbounded. We show that, for a wide range of parameters, this asymmetry brings interesting and computationally useful dynamical properties. When driven by input, the network explores potential solutions through highly unstable ‘expansion’ dynamics. This expansion is steered and constrained by negative divergence of the dynamics, which ensures that the dimensionality of the solution space continues to reduce until an acceptable solution manifold is reached. Then the system contracts stably on this manifold towards its final solution trajectory. The unstable positive feedback and cross inhibition that underlie expansion and divergence are common motifs in molecular and neuronal networks. Therefore we propose that very simple organizational constraints that combine these motifs can lead to spontaneous computation and so to the spontaneous modification of entropy that is characteristic of living systems. PMID:25617645

Modeling light-induced charge transfer dynamics across a metal-molecule-metal junction: Bridging classical electrodynamics and quantum dynamics

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hu, Zixuan; Ratner, Mark A.; Seideman, Tamar, E-mail: t-seideman@northwestern.edu

2014-12-14

We develop a numerical approach for simulating light-induced charge transport dynamics across a metal-molecule-metal conductance junction. The finite-difference time-domain method is used to simulate the plasmonic response of the metal structures. The Huygens subgridding technique, as adapted to Lorentz media, is used to bridge the vastly disparate length scales of the plasmonic metal electrodes and the molecular system, maintaining accuracy. The charge and current densities calculated with classical electrodynamics are transformed to an electronic wavefunction, which is then propagated through the molecular linker via the Heisenberg equations of motion. We focus mainly on development of the theory and exemplify ourmore » approach by a numerical illustration of a simple system consisting of two silver cylinders bridged by a three-site molecular linker. The electronic subsystem exhibits fascinating light driven dynamics, wherein the charge density oscillates at the driving optical frequency, exhibiting also the natural system timescales, and a resonance phenomenon leads to strong conductance enhancement.« less

100J Pulsed Laser Shock Driver for Dynamic Compression Research

NASA Astrophysics Data System (ADS)

Wang, X.; Sethian, J.; Bromage, J.; Fochs, S.; Broege, D.; Zuegel, J.; Roides, R.; Cuffney, R.; Brent, G.; Zweiback, J.; Currier, Z.; D'Amico, K.; Hawreliak, J.; Zhang, J.; Rigg, P. A.; Gupta, Y. M.

2017-06-01

Logos Technologies and the Laboratory for Laser Energetics (LLE, University of Rochester) - in partnership with Washington State University - have designed, built and deployed a one of a kind 100J pulsed UV (351 nm) laser system to perform real-time, x-ray diffraction and imaging experiments in laser-driven compression experiments at the Dynamic Compression Sector (DCS) at the Advanced Photon Source, Argonne National Laboratory. The laser complements the other dynamic compression drivers at DCS. The laser system features beam smoothing for 2-d spatially uniform loading of samples and four, highly reproducible, temporal profiles (total pulse duration: 5-15 ns) to accommodate a wide variety of scientific needs. Other pulse shapes can be achieved as the experimental needs evolve. Timing of the laser pulse is highly precise (<200 ps) to allow accurate synchronization of the x-rays with the dynamic compression event. Details of the laser system, its operating parameters, and representative results will be presented. Work supported by DOE/NNSA.

Algebraic aspects of the driven dynamics in the density operator and correlation functions calculation for multi-level open quantum systems

NASA Astrophysics Data System (ADS)

Bogolubov, Nikolai N.; Soldatov, Andrey V.

2017-12-01

Exact and approximate master equations were derived by the projection operator method for the reduced statistical operator of a multi-level quantum system with finite number N of quantum eigenstates interacting with arbitrary external classical fields and dissipative environment simultaneously. It was shown that the structure of these equations can be simplified significantly if the free Hamiltonian driven dynamics of an arbitrary quantum multi-level system under the influence of the external driving fields as well as its Markovian and non-Markovian evolution, stipulated by the interaction with the environment, are described in terms of the SU(N) algebra representation. As a consequence, efficient numerical methods can be developed and employed to analyze these master equations for real problems in various fields of theoretical and applied physics. It was also shown that literally the same master equations hold not only for the reduced density operator but also for arbitrary nonequilibrium multi-time correlation functions as well under the only assumption that the system and the environment are uncorrelated at some initial moment of time. A calculational scheme was proposed to account for these lost correlations in a regular perturbative way, thus providing additional computable terms to the correspondent master equations for the correlation functions.

Inflation with a massive vector field nonminimally coupled to gravity

NASA Astrophysics Data System (ADS)

Páramos, J.

2018-01-01

The possibility that inflation is driven by a massive vector field with SO(3) global symmetry nonminimally coupled to gravity is presented. Through an appropriate Ansatz for the vector field, the behaviour of the equations of motion is studied through the ensuing dynamical system, focusing on the characterisation of the ensuing fixed points.

New Evidence on the Development of the Word "Big."

ERIC Educational Resources Information Center

Sena, Rhonda; Smith, Linda B.

1990-01-01

Results indicate that curvilinear trend in children's understanding of word "big" is not obtained in all stimulus contexts. This suggests that meaning and use of "big" is complex, and may not refer simply to larger objects in a set. Proposes that meaning of "big" constitutes a dynamic system driven by many perceptual,…

A Process Dynamics and Control Experiment for the Undergraduate Laboratory

ERIC Educational Resources Information Center

Spencer, Jordan L.

2009-01-01

This paper describes a process control experiment. The apparatus includes a three-vessel glass flow system with a variable flow configuration, means for feeding dye solution controlled by a stepper-motor driven valve, and a flow spectrophotometer. Students use impulse response data and nonlinear regression to estimate three parameters of a model…

The "Uptake" of a Sport-for-Development Programme in South Africa

ERIC Educational Resources Information Center

Burnett, Cora

2015-01-01

This article reports on the "uptake" dynamics and resultant manifestations of a school-based, incentive-driven, sport-for-development programme in the South African context of poverty. The ecological systems theory of Brofenbrenner, the theory of complexity and a neo-liberal framework underpin the social constructions of local meanings…

Alfvén Turbulence Driven by High-Dimensional Interior Crisis in the Solar Wind

NASA Astrophysics Data System (ADS)

Chian, A. C.-L.; Rempel, E. L.; Macau, E. E. N.; Rosa, R. R.; Christiansen, F.

2003-09-01

Alfvén intermittent turbulence has been observed in the solar wind. It has been previously shown that the interplanetary Alfvén intermittent turbulence can appear due to a low-dimensional temporal chaos [1]. In this paper, we study the nonlinear spatiotemporal dynamics of Alfvén waves governed by the Kuramoto-Sivashinsky equation which describes the phase evolution of a large-amplitude Alfvén wave. We investigate the Alfvén turbulence driven by a high-dimensional interior crisis, which is a global bifurcation caused by the collision of a chaotic attractor with an unstable periodic orbit. This nonlinear phenomenon is analyzed using the numerical solutions of the model equation. The identification of the unstable periodic orbits and their invariant manifolds is fundamental for understanding the instability, chaos and turbulence in complex systems such as the solar wind plasma. The high-dimensional dynamical system approach to space environment turbulence developed in this paper can improve our interpretation of the origin and the nature of Alfvén turbulence observed in the solar wind.

Le Chatelier Principle for Out-of-Equilibrium and Boundary-Driven Systems: Application to Dynamical Phase Transitions.

PubMed

Shpielberg, O; Akkermans, E

2016-06-17

A stability analysis is presented for boundary-driven and out-of-equilibrium systems in the framework of the hydrodynamic macroscopic fluctuation theory. A Hamiltonian description is proposed which allows us to thermodynamically interpret the additivity principle. A necessary and sufficient condition for the validity of the additivity principle is obtained as an extension of the Le Chatelier principle. These stability conditions result from a diagonal quadratic form obtained using the cumulant generating function. This approach allows us to provide a proof for the stability of the weakly asymmetric exclusion process and to reduce the search for stability to the solution of two coupled linear ordinary differential equations instead of nonlinear partial differential equations. Additional potential applications of these results are discussed in the realm of classical and quantum systems.

Le Chatelier Principle for Out-of-Equilibrium and Boundary-Driven Systems: Application to Dynamical Phase Transitions

NASA Astrophysics Data System (ADS)

Shpielberg, O.; Akkermans, E.

2016-06-01

A stability analysis is presented for boundary-driven and out-of-equilibrium systems in the framework of the hydrodynamic macroscopic fluctuation theory. A Hamiltonian description is proposed which allows us to thermodynamically interpret the additivity principle. A necessary and sufficient condition for the validity of the additivity principle is obtained as an extension of the Le Chatelier principle. These stability conditions result from a diagonal quadratic form obtained using the cumulant generating function. This approach allows us to provide a proof for the stability of the weakly asymmetric exclusion process and to reduce the search for stability to the solution of two coupled linear ordinary differential equations instead of nonlinear partial differential equations. Additional potential applications of these results are discussed in the realm of classical and quantum systems.

Domain wall dynamics driven by spin transfer torque and the spin-orbit field.

PubMed

Hayashi, Masamitsu; Nakatani, Yoshinobu; Fukami, Shunsuke; Yamanouchi, Michihiko; Mitani, Seiji; Ohno, Hideo

2012-01-18

We have studied current-driven dynamics of domain walls when an in-plane magnetic field is present in perpendicularly magnetized nanowires using an analytical model and micromagnetic simulations. We model an experimentally studied system, ultrathin magnetic nanowires with perpendicular anisotropy, where an effective in-plane magnetic field is developed when current is passed along the nanowire due to the Rashba-like spin-orbit coupling. Using a one-dimensional model of a domain wall together with micromagnetic simulations, we show that the existence of such in-plane magnetic fields can either lower or raise the threshold current needed to cause domain wall motion. In the presence of the in-plane field, the threshold current differs for positive and negative currents for a given wall chirality, and the wall motion becomes sensitive to out-of-plane magnetic fields. We show that large non-adiabatic spin torque can counteract the effect of the in-plane field.

Data-driven sensor placement from coherent fluid structures

NASA Astrophysics Data System (ADS)

Manohar, Krithika; Kaiser, Eurika; Brunton, Bingni W.; Kutz, J. Nathan; Brunton, Steven L.

2017-11-01

Optimal sensor placement is a central challenge in the prediction, estimation and control of fluid flows. We reinterpret sensor placement as optimizing discrete samples of coherent fluid structures for full state reconstruction. This permits a drastic reduction in the number of sensors required for faithful reconstruction, since complex fluid interactions can often be described by a small number of coherent structures. Our work optimizes point sensors using the pivoted matrix QR factorization to sample coherent structures directly computed from flow data. We apply this sampling technique in conjunction with various data-driven modal identification methods, including the proper orthogonal decomposition (POD) and dynamic mode decomposition (DMD). In contrast to POD-based sensors, DMD demonstrably enables the optimization of sensors for prediction in systems exhibiting multiple scales of dynamics. Finally, reconstruction accuracy from pivot sensors is shown to be competitive with sensors obtained using traditional computationally prohibitive optimization methods.

Air-Breathing Hypersonic Vehicle Tracking Control Based on Adaptive Dynamic Programming.

PubMed

Mu, Chaoxu; Ni, Zhen; Sun, Changyin; He, Haibo

2017-03-01

In this paper, we propose a data-driven supplementary control approach with adaptive learning capability for air-breathing hypersonic vehicle tracking control based on action-dependent heuristic dynamic programming (ADHDP). The control action is generated by the combination of sliding mode control (SMC) and the ADHDP controller to track the desired velocity and the desired altitude. In particular, the ADHDP controller observes the differences between the actual velocity/altitude and the desired velocity/altitude, and then provides a supplementary control action accordingly. The ADHDP controller does not rely on the accurate mathematical model function and is data driven. Meanwhile, it is capable to adjust its parameters online over time under various working conditions, which is very suitable for hypersonic vehicle system with parameter uncertainties and disturbances. We verify the adaptive supplementary control approach versus the traditional SMC in the cruising flight, and provide three simulation studies to illustrate the improved performance with the proposed approach.

A plasma deflagration accelerator as a platform for laboratory astrophysics

NASA Astrophysics Data System (ADS)

Underwood, Thomas C.; Loebner, Keith T. K.; Cappelli, Mark A.

2017-06-01

The replication of astrophysical flows in the laboratory is critical for isolating particular phenomena and dynamics that appear in complex, highly-coupled natural systems. In particular, plasma jets are observed in astrophysical contexts at a variety of scales, typically at high magnetic Reynolds number and driven by internal currents. In this paper, we present detailed measurements of the plasma parameters within deflagration-produced plasma jets, the scaling of these parameters against both machine operating conditions and the corresponding astrophysical phenomena. Using optical and spectroscopic diagnostics, including Schlieren cinematography, we demonstrate the production of current-driven plasma jets of ∼100 km/s and magnetic Reynolds numbers of ∼100, and discuss the dynamics of their acceleration into vacuum. The results of this study will contribute to the reproduction of various types of astrophysical jets in the laboratory and indicate the ability to further probe active research areas such as jet collimation, stability, and interaction.

Effect of Forcing Function on Nonlinear Acoustic Standing Waves

NASA Technical Reports Server (NTRS)

Finkheiner, Joshua R.; Li, Xiao-Fan; Raman, Ganesh; Daniels, Chris; Steinetz, Bruce

2003-01-01

Nonlinear acoustic standing waves of high amplitude have been demonstrated by utilizing the effects of resonator shape to prevent the pressure waves from entering saturation. Experimentally, nonlinear acoustic standing waves have been generated by shaking an entire resonating cavity. While this promotes more efficient energy transfer than a piston-driven resonator, it also introduces complicated structural dynamics into the system. Experiments have shown that these dynamics result in resonator forcing functions comprised of a sum of several Fourier modes. However, previous numerical studies of the acoustics generated within the resonator assumed simple sinusoidal waves as the driving force. Using a previously developed numerical code, this paper demonstrates the effects of using a forcing function constructed with a series of harmonic sinusoidal waves on resonating cavities. From these results, a method will be demonstrated which allows the direct numerical analysis of experimentally generated nonlinear acoustic waves in resonators driven by harmonic forcing functions.

Quantum gases. Observation of many-body dynamics in long-range tunneling after a quantum quench.

PubMed

Meinert, Florian; Mark, Manfred J; Kirilov, Emil; Lauber, Katharina; Weinmann, Philipp; Gröbner, Michael; Daley, Andrew J; Nägerl, Hanns-Christoph

2014-06-13

Quantum tunneling is at the heart of many low-temperature phenomena. In strongly correlated lattice systems, tunneling is responsible for inducing effective interactions, and long-range tunneling substantially alters many-body properties in and out of equilibrium. We observe resonantly enhanced long-range quantum tunneling in one-dimensional Mott-insulating Hubbard chains that are suddenly quenched into a tilted configuration. Higher-order tunneling processes over up to five lattice sites are observed as resonances in the number of doubly occupied sites when the tilt per site is tuned to integer fractions of the Mott gap. This forms a basis for a controlled study of many-body dynamics driven by higher-order tunneling and demonstrates that when some degrees of freedom are frozen out, phenomena that are driven by small-amplitude tunneling terms can still be observed. Copyright © 2014, American Association for the Advancement of Science.

Data-driven monitoring for stochastic systems and its application on batch process

NASA Astrophysics Data System (ADS)

Yin, Shen; Ding, Steven X.; Haghani Abandan Sari, Adel; Hao, Haiyang

2013-07-01

Batch processes are characterised by a prescribed processing of raw materials into final products for a finite duration and play an important role in many industrial sectors due to the low-volume and high-value products. Process dynamics and stochastic disturbances are inherent characteristics of batch processes, which cause monitoring of batch processes a challenging problem in practice. To solve this problem, a subspace-aided data-driven approach is presented in this article for batch process monitoring. The advantages of the proposed approach lie in its simple form and its abilities to deal with stochastic disturbances and process dynamics existing in the process. The kernel density estimation, which serves as a non-parametric way of estimating the probability density function, is utilised for threshold calculation. An industrial benchmark of fed-batch penicillin production is finally utilised to verify the effectiveness of the proposed approach.

Characterising Wildlife Trade Market Supply-Demand Dynamics

PubMed Central

Rowcliffe, M.; Cowlishaw, G.; Alexander, J. S.; Ntiamoa-Baidu, Y.; Brenya, A.; Milner-Gulland, E. J.

2016-01-01

The trade in wildlife products can represent an important source of income for poor people, but also threaten wildlife locally, regionally and internationally. Bushmeat provides livelihoods for hunters, traders and sellers, protein to rural and urban consumers, and has depleted the populations of many tropical forest species. Management interventions can be targeted towards the consumers or suppliers of wildlife products. There has been a general assumption in the bushmeat literature that the urban trade is driven by consumer demand with hunters simply fulfilling this demand. Using the urban bushmeat trade in the city of Kumasi, Ghana, as a case study, we use a range of datasets to explore the processes driving the urban bushmeat trade. We characterise the nature of supply and demand by explicitly considering three market attributes: resource condition, hunter behaviour, and consumer behaviour. Our results suggest that bushmeat resources around Kumasi are becoming increasingly depleted and are unable to meet demand, that hunters move in and out of the trade independently of price signals generated by the market, and that, for the Kumasi bushmeat system, consumption levels are driven not by consumer choice but by shortfalls in supply and consequent price responses. Together, these results indicate that supply-side processes dominate the urban bushmeat trade in Kumasi. This suggests that future management interventions should focus on changing hunter behaviour, although complementary interventions targeting consumer demand are also likely to be necessary in the long term. Our approach represents a structured and repeatable method to assessing market dynamics in information-poor systems. The findings serve as a caution against assuming that wildlife markets are demand driven, and highlight the value of characterising market dynamics to inform appropriate management. PMID:27632169

Characterising Wildlife Trade Market Supply-Demand Dynamics.

PubMed

McNamara, J; Rowcliffe, M; Cowlishaw, G; Alexander, J S; Ntiamoa-Baidu, Y; Brenya, A; Milner-Gulland, E J

2016-01-01

The trade in wildlife products can represent an important source of income for poor people, but also threaten wildlife locally, regionally and internationally. Bushmeat provides livelihoods for hunters, traders and sellers, protein to rural and urban consumers, and has depleted the populations of many tropical forest species. Management interventions can be targeted towards the consumers or suppliers of wildlife products. There has been a general assumption in the bushmeat literature that the urban trade is driven by consumer demand with hunters simply fulfilling this demand. Using the urban bushmeat trade in the city of Kumasi, Ghana, as a case study, we use a range of datasets to explore the processes driving the urban bushmeat trade. We characterise the nature of supply and demand by explicitly considering three market attributes: resource condition, hunter behaviour, and consumer behaviour. Our results suggest that bushmeat resources around Kumasi are becoming increasingly depleted and are unable to meet demand, that hunters move in and out of the trade independently of price signals generated by the market, and that, for the Kumasi bushmeat system, consumption levels are driven not by consumer choice but by shortfalls in supply and consequent price responses. Together, these results indicate that supply-side processes dominate the urban bushmeat trade in Kumasi. This suggests that future management interventions should focus on changing hunter behaviour, although complementary interventions targeting consumer demand are also likely to be necessary in the long term. Our approach represents a structured and repeatable method to assessing market dynamics in information-poor systems. The findings serve as a caution against assuming that wildlife markets are demand driven, and highlight the value of characterising market dynamics to inform appropriate management.

Dynamic behavior of microscale particles controlled by standing bulk acoustic waves

DOE Office of Scientific and Technical Information (OSTI.GOV)

Greenhall, J.; Raeymaekers, B., E-mail: bart.raeymaekers@utah.edu; Guevara Vasquez, F.

2014-10-06

We analyze the dynamic behavior of a spherical microparticle submerged in a fluid medium, driven to the node of a standing bulk acoustic wave created by two opposing transducers. We derive the dynamics of the fluid-particle system taking into account the acoustic radiation force and the time-dependent and time-independent drag force acting on the particle. Using this dynamic model, we characterize the transient and steady-state behavior of the fluid-particle system as a function of the particle and fluid properties and the transducer operating parameters. The results show that the settling time and percent overshoot of the particle trajectory are dependentmore » on the ratio of the acoustic radiation force and time-independent damping force. In addition, we show that the particle oscillates around the node of the standing wave with an amplitude that depends on the ratio of the time-dependent drag forces and the particle inertia.« less

Visualization in mechanics: the dynamics of an unbalanced roller

NASA Astrophysics Data System (ADS)

Cumber, Peter S.

2017-04-01

It is well known that mechanical engineering students often find mechanics a difficult area to grasp. This article describes a system of equations describing the motion of a balanced and an unbalanced roller constrained by a pivot arm. A wide range of dynamics can be simulated with the model. The equations of motion are embedded in a graphical user interface for its numerical solution in MATLAB. This allows a student's focus to be on the influence of different parameters on the system dynamics. The simulation tool can be used as a dynamics demonstrator in a lecture or as an educational tool driven by the imagination of the student. By way of demonstration the simulation tool has been applied to a range of roller-pivot arm configurations. In addition, approximations to the equations of motion are explored and a second-order model is shown to be accurate for a limited range of parameters.

Kibble-Zurek scaling and string-net coarsening in topologically ordered systems.

PubMed

Chandran, Anushya; Burnell, F J; Khemani, Vedika; Sondhi, S L

2013-10-09

We consider the non-equilibrium dynamics of topologically ordered systems driven across a continuous phase transition into proximate phases with no, or reduced, topological order. This dynamics exhibits scaling in the spirit of Kibble and Zurek but now without the presence of symmetry breaking and a local order parameter. The late stages of the process are seen to exhibit a slow, coarsening dynamics for the string-net that underlies the physics of the topological phase, a potentially interesting signature of topological order. We illustrate these phenomena in the context of particular phase transitions out of the Abelian Z2 topologically ordered phase of the toric code/Z2 gauge theory, and the non-Abelian SU(2)k ordered phases of the relevant Levin-Wen models.

Bursts of activity in collective cell migration

PubMed Central

Chepizhko, Oleksandr; Giampietro, Costanza; Mastrapasqua, Eleonora; Nourazar, Mehdi; Ascagni, Miriam; Sugni, Michela; Fascio, Umberto; Leggio, Livio; Malinverno, Chiara; Scita, Giorgio; Santucci, Stéphane; Alava, Mikko J.; Zapperi, Stefano; La Porta, Caterina A. M.

2016-01-01

Dense monolayers of living cells display intriguing relaxation dynamics, reminiscent of soft and glassy materials close to the jamming transition, and migrate collectively when space is available, as in wound healing or in cancer invasion. Here we show that collective cell migration occurs in bursts that are similar to those recorded in the propagation of cracks, fluid fronts in porous media, and ferromagnetic domain walls. In analogy with these systems, the distribution of activity bursts displays scaling laws that are universal in different cell types and for cells moving on different substrates. The main features of the invasion dynamics are quantitatively captured by a model of interacting active particles moving in a disordered landscape. Our results illustrate that collective motion of living cells is analogous to the corresponding dynamics in driven, but inanimate, systems. PMID:27681632

Flow-Driven Waves and Phase-Locked Self-Organization in Quasi-One-Dimensional Colonies of Dictyostelium discoideum

NASA Astrophysics Data System (ADS)

Gholami, A.; Steinbock, O.; Zykov, V.; Bodenschatz, E.

2015-01-01

We report experiments on flow-driven waves in a microfluidic channel containing the signaling slime mold Dictyostelium discoideum. The observed cyclic adenosine monophosphate (cAMP) wave trains developed spontaneously in the presence of flow and propagated with the velocity proportional to the imposed flow velocity. The period of the wave trains was independent of the flow velocity. Perturbations of flow-driven waves via external periodic pulses of the signaling agent cAMP induced 1 ∶1 , 2 ∶1 , 3 ∶1 , and 1 ∶2 frequency responses, reminiscent of Arnold tongues in forced oscillatory systems. We expect our observations to be generic to active media governed by reaction-diffusion-advection dynamics, where spatially bound autocatalytic processes occur under flow conditions.

AC Current Driven Dynamic Vortex State in YBa2Cu3O7-x (Postprint)

DTIC Science & Technology

2012-02-01

coexisting steady states of driven vortex motion with different characteristics: a quasi-static disordered glassy state in the sample interior and a...coexisting, vortex, plastic, dynamic, calculations, disordered , hysteretic, model, films, edges 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF...characteris- tics: a quasi-static disordered glassy state in the sample interior and a dynamic state of plastic motion near the edges. Finite- element

Impulse processing: A dynamical systems model of incremental eye movements in the visual world paradigm

PubMed Central

Kukona, Anuenue; Tabor, Whitney

2011-01-01

The visual world paradigm presents listeners with a challenging problem: they must integrate two disparate signals, the spoken language and the visual context, in support of action (e.g., complex movements of the eyes across a scene). We present Impulse Processing, a dynamical systems approach to incremental eye movements in the visual world that suggests a framework for integrating language, vision, and action generally. Our approach assumes that impulses driven by the language and the visual context impinge minutely on a dynamical landscape of attractors corresponding to the potential eye-movement behaviors of the system. We test three unique predictions of our approach in an empirical study in the visual world paradigm, and describe an implementation in an artificial neural network. We discuss the Impulse Processing framework in relation to other models of the visual world paradigm. PMID:21609355

DNA-Binding Kinetics Determines the Mechanism of Noise-Induced Switching in Gene Networks

PubMed Central

Tse, Margaret J.; Chu, Brian K.; Roy, Mahua; Read, Elizabeth L.

2015-01-01

Gene regulatory networks are multistable dynamical systems in which attractor states represent cell phenotypes. Spontaneous, noise-induced transitions between these states are thought to underlie critical cellular processes, including cell developmental fate decisions, phenotypic plasticity in fluctuating environments, and carcinogenesis. As such, there is increasing interest in the development of theoretical and computational approaches that can shed light on the dynamics of these stochastic state transitions in multistable gene networks. We applied a numerical rare-event sampling algorithm to study transition paths of spontaneous noise-induced switching for a ubiquitous gene regulatory network motif, the bistable toggle switch, in which two mutually repressive genes compete for dominant expression. We find that the method can efficiently uncover detailed switching mechanisms that involve fluctuations both in occupancies of DNA regulatory sites and copy numbers of protein products. In addition, we show that the rate parameters governing binding and unbinding of regulatory proteins to DNA strongly influence the switching mechanism. In a regime of slow DNA-binding/unbinding kinetics, spontaneous switching occurs relatively frequently and is driven primarily by fluctuations in DNA-site occupancies. In contrast, in a regime of fast DNA-binding/unbinding kinetics, switching occurs rarely and is driven by fluctuations in levels of expressed protein. Our results demonstrate how spontaneous cell phenotype transitions involve collective behavior of both regulatory proteins and DNA. Computational approaches capable of simulating dynamics over many system variables are thus well suited to exploring dynamic mechanisms in gene networks. PMID:26488666

Taple-top imaging of the non-adiabatically driven isomerization in the acetylene cation

NASA Astrophysics Data System (ADS)

Beaulieu, Samuel; Ibrahim, Heide; Wales, Benji; Schmidt, Bruno E.; Thiré, Nicolas; Bisson, Éric; Hebeisen, Christoph T.; Wanie, Vincent; Giguere, Mathieu; Kieffer, Jean-Claude; Sanderson, Joe; Schuurman, Michael S.; Légaré, François

2014-05-01

One of the primary goals of modern ultrafast science is to follow nuclear and electronic evolution of molecules as they undergo a photo-chemical reaction. Most of the interesting dynamics phenomena in molecules occur when an electronically excited state is populated. When the energy difference between electronic ground and excited states is large, Free Electron Laser (FEL) and HHG-based VUV sources were, up to date, the only light sources able to efficiently initiate those non-adiabatic dynamics. We have developed a simple table-top approach to initiate those rich dynamics via multiphoton absorption. As a proof of principle, we studied the ultrafast isomerization of the acetylene cation. We have chosen this model system for isomerization since the internal conversion mechanism which leads to proton migration is still under debate since decades. Using 266 nm multiphoton absorption as a pump and 800 nm induced Coulomb Explosion as a probe, we have shoot the first high-resolution molecular movie of the non-adiabatically driven proton migration in the acetylene cation. The experimental results are in excellent agreement with high level ab initio trajectory simulations.

Configuring and Characterizing X-Rays for Laser-Driven Compression Experiments at the Dynamic Compression Sector

NASA Astrophysics Data System (ADS)

Li, Y.; Capatina, D.; D'Amico, K.; Eng, P.; Hawreliak, J.; Graber, T.; Rickerson, D.; Klug, J.; Rigg, P. A.; Gupta, Y. M.

2017-06-01

Coupling laser-driven compression experiments to the x-ray beam at the Dynamic Compression Sector (DCS) at the Advanced Photon Source (APS) of Argonne National Laboratory requires state-of-the-art x-ray focusing, pulse isolation, and diagnostics capabilities. The 100J UV pulsed laser system can be fired once every 20 minutes so precise alignment and focusing of the x-rays on each new sample must be fast and reproducible. Multiple Kirkpatrick-Baez (KB) mirrors are used to achieve a focal spot size as small as 50 μm at the target, while the strategic placement of scintillating screens, cameras, and detectors allows for fast diagnosis of the beam shape, intensity, and alignment of the sample to the x-ray beam. In addition, a series of x-ray choppers and shutters are used to ensure that the sample is exposed to only a single x-ray pulse ( 80ps) during the dynamic compression event and require highly precise synchronization. Details of the technical requirements, layout, and performance of these instruments will be presented. Work supported by DOE/NNSA.

Efficient GIS-based model-driven method for flood risk management and its application in central China

NASA Astrophysics Data System (ADS)

Liu, Y.; Zhou, J.; Song, L.; Zou, Q.; Guo, J.; Wang, Y.

2014-02-01

In recent years, an important development in flood management has been the focal shift from flood protection towards flood risk management. This change greatly promoted the progress of flood control research in a multidisciplinary way. Moreover, given the growing complexity and uncertainty in many decision situations of flood risk management, traditional methods, e.g., tight-coupling integration of one or more quantitative models, are not enough to provide decision support for managers. Within this context, this paper presents a beneficial methodological framework to enhance the effectiveness of decision support systems, through the dynamic adaptation of support regarding the needs of the decision-maker. In addition, we illustrate a loose-coupling technical prototype for integrating heterogeneous elements, such as multi-source data, multidisciplinary models, GIS tools and existing systems. The main innovation is the application of model-driven concepts, which put the system in a state of continuous iterative optimization. We define the new system as a model-driven decision support system (MDSS ). Two characteristics that differentiate the MDSS are as follows: (1) it is made accessible to non-technical specialists; and (2) it has a higher level of adaptability and compatibility. Furthermore, the MDSS was employed to manage the flood risk in the Jingjiang flood diversion area, located in central China near the Yangtze River. Compared with traditional solutions, we believe that this model-driven method is efficient, adaptable and flexible, and thus has bright prospects of application for comprehensive flood risk management.

Experimental Investigations on the Surface-Driven Capillary Flow of Aqueous Microparticle Suspensions in the Microfluidic Laboratory-On Systems

NASA Astrophysics Data System (ADS)

Mukhopadhyay, Subhadeep

In this work, total 1592 individual leakage-free polymethylmethacrylate (PMMA) microfluidic devices as laboratory-on-a-chip systems are fabricated by maskless lithography, hot embossing lithography, and direct bonding technique. Total 1094 individual Audio Video Interleave Files as experimental outputs related to the surface-driven capillary flow have been recorded and analyzed. The influence of effective viscosity, effect of surface wettability, effect of channel aspect ratio, and effect of centrifugal force on the surface-driven microfluidic flow of aqueous microparticle suspensions have been successfully and individually investigated in these laboratory-on-a-chip systems. Also, 5 micron polystyrene particles have been separated from the aqueous microparticle suspensions in the microfluidic lab-on-a-chip systems of modified design with 98% separation efficiency, and 10 micron polystyrene particles have been separated with 100% separation efficiency. About the novelty of this work, the experimental investigations have been performed on the surface-driven microfluidic flow of aqueous microparticle suspensions with the investigations on the separation time in particle-size based separation mechanism to control these suspensions in the microfluidic lab-on-a-chip systems. This research work contains a total of 10,112 individual experimental outputs obtained using total 30 individual instruments by author’s own hands-on completely during more than three years continuously. Author has performed the experimental investigations on both the fluid statics and fluid dynamics to develop an automated fluid machine.

Reduced Perceptual Exclusivity during Object and Grating Rivalry in Autism

PubMed Central

Freyberg, J.; Robertson, C.E.; Baron-Cohen, S.

2015-01-01

Background The dynamics of binocular rivalry may be a behavioural footprint of excitatory and inhibitory neural transmission in visual cortex. Given the presence of atypical visual features in Autism Spectrum Conditions (ASC), and evidence in support of the idea of an imbalance in excitatory/inhibitory neural transmission in ASC, we hypothesized that binocular rivalry might prove a simple behavioural marker of such a transmission imbalance in the autistic brain. In support of this hypothesis, we previously reported a slower rate of rivalry in ASC, driven by reduced perceptual exclusivity. Methods We tested whether atypical dynamics of binocular rivalry in ASC are specific to certain stimulus features. 53 participants (26 with ASC, matched for age, sex and IQ) participated in binocular rivalry experiments in which the dynamics of rivalry were measured at two levels of stimulus complexity, low (grayscale gratings) and high (coloured objects). Results Individuals with ASC experienced a slower rate of rivalry, driven by longer transitional states between dominant percepts. These exaggerated transitional states were present at both low and high levels of stimulus complexity, suggesting that atypical rivalry dynamics in autism are robust with respect to stimulus choice. Interactions between stimulus properties and rivalry dynamics in autism indicate that achromatic grating stimuli produce stronger group differences. Conclusion These results confirm the finding of atypical dynamics of binocular rivalry in ASC. These dynamics were present for stimuli of both low and high levels of visual complexity, suggesting an imbalance in competitive interactions throughout the visual system of individuals with ASC. PMID:26382002

Operationalising a social-ecological system perspective on the Arctic Ocean.

PubMed

Crépin, Anne-Sophie; Gren, Åsa; Engström, Gustav; Ospina, Daniel

2017-12-01

We propose a framework to support management that builds on a social-ecological system perspective on the Arctic Ocean. We illustrate the framework's application for two policy-relevant scenarios of climate-driven change, picturing a shift in zooplankton composition and alternatively a crab invasion. We analyse archetypical system dynamics between the socio-economic, the natural, and the governance systems in these scenarios. Our holistic approach can help managers identify looming problems arising from complex system interactions and prioritise among problems and solutions, even when available data are limited.

Dynamical inversion of the energy landscape promotes non-equilibrium self-assembly of binary mixtures

DOE PAGES

Pestana, Luis Ruiz; Minnetian, Natalie; Lammers, Laura Nielsen; ...

2018-01-02

When driven out of equilibrium, many diverse systems can form complex spatial and dynamical patterns, even in the absence of attractive interactions. Using kinetic Monte Carlo simulations, we investigate the phase behavior of a binary system of particles of dissimilar size confined between semiflexible planar surfaces, in which the nanoconfinement introduces a non-local coupling between particles, which we model as an activation energy barrier to diffusion that decreases with the local fraction of the larger particle. The system autonomously reaches a cyclical non-equilibrium state characterized by the formation and dissolution of metastable micelle-like clusters with the small particles in themore » core and the large ones in the surrounding corona. The power spectrum of the fluctuations in the aggregation number exhibits 1/f noise reminiscent of self-organized critical systems. Finally, we suggest that the dynamical metastability of the micellar structures arises from an inversion of the energy landscape, in which the relaxation dynamics of one of the species induces a metastable phase for the other species.« less

Dynamical inversion of the energy landscape promotes non-equilibrium self-assembly of binary mixtures

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pestana, Luis Ruiz; Minnetian, Natalie; Lammers, Laura Nielsen

When driven out of equilibrium, many diverse systems can form complex spatial and dynamical patterns, even in the absence of attractive interactions. Using kinetic Monte Carlo simulations, we investigate the phase behavior of a binary system of particles of dissimilar size confined between semiflexible planar surfaces, in which the nanoconfinement introduces a non-local coupling between particles, which we model as an activation energy barrier to diffusion that decreases with the local fraction of the larger particle. The system autonomously reaches a cyclical non-equilibrium state characterized by the formation and dissolution of metastable micelle-like clusters with the small particles in themore » core and the large ones in the surrounding corona. The power spectrum of the fluctuations in the aggregation number exhibits 1/f noise reminiscent of self-organized critical systems. Finally, we suggest that the dynamical metastability of the micellar structures arises from an inversion of the energy landscape, in which the relaxation dynamics of one of the species induces a metastable phase for the other species.« less

Generalized Synchronization in AN Array of Nonlinear Dynamic Systems with Applications to Chaotic Cnn

NASA Astrophysics Data System (ADS)

Min, Lequan; Chen, Guanrong

This paper establishes some generalized synchronization (GS) theorems for a coupled discrete array of difference systems (CDADS) and a coupled continuous array of differential systems (CCADS). These constructive theorems provide general representations of GS in CDADS and CCADS. Based on these theorems, one can design GS-driven CDADS and CCADS via appropriate (invertible) transformations. As applications, the results are applied to autonomous and nonautonomous coupled Chen cellular neural network (CNN) CDADS and CCADS, discrete bidirectional Lorenz CNN CDADS, nonautonomous bidirectional Chua CNN CCADS, and nonautonomously bidirectional Chen CNN CDADS and CCADS, respectively. Extensive numerical simulations show their complex dynamic behaviors. These theorems provide new means for understanding the GS phenomena of complex discrete and continuously differentiable networks.

Intrinsic subpicosecond magnetization reversal driven by femtosecond laser pulses in GdFeCo amorphous films

DOE Office of Scientific and Technical Information (OSTI.GOV)

Li, Shufa; Gao, Ruixin; Cheng, Chuyuan

2013-12-09

Ultrafast magnetization dynamics in GdFeCo films triggered by femtosecond laser pulses with and without an external field applied is studied experimentally for different excitation fluence. It is found that subpicosecond magnetization reversal occurs simultaneously in the ultrafast dynamics of both saturation and remnant magnetization states and almost identical within 13 ps, whereas relatively slow magnetization reversal across compensation point appears only in the dynamics of saturation magnetization state. It shows the subpicosecond magnetization reversal is external field independent, and originates from intrinsic magnetic evolution in ferrimagnetic system. The intrinsic subpicosecond reversal is qualitatively explained by linear reversal.

Path-space variational inference for non-equilibrium coarse-grained systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Harmandaris, Vagelis, E-mail: harman@uoc.gr; Institute of Applied and Computational Mathematics; Kalligiannaki, Evangelia, E-mail: ekalligian@tem.uoc.gr

In this paper we discuss information-theoretic tools for obtaining optimized coarse-grained molecular models for both equilibrium and non-equilibrium molecular simulations. The latter are ubiquitous in physicochemical and biological applications, where they are typically associated with coupling mechanisms, multi-physics and/or boundary conditions. In general the non-equilibrium steady states are not known explicitly as they do not necessarily have a Gibbs structure. The presented approach can compare microscopic behavior of molecular systems to parametric and non-parametric coarse-grained models using the relative entropy between distributions on the path space and setting up a corresponding path-space variational inference problem. The methods can become entirelymore » data-driven when the microscopic dynamics are replaced with corresponding correlated data in the form of time series. Furthermore, we present connections and generalizations of force matching methods in coarse-graining with path-space information methods. We demonstrate the enhanced transferability of information-based parameterizations to different observables, at a specific thermodynamic point, due to information inequalities. We discuss methodological connections between information-based coarse-graining of molecular systems and variational inference methods primarily developed in the machine learning community. However, we note that the work presented here addresses variational inference for correlated time series due to the focus on dynamics. The applicability of the proposed methods is demonstrated on high-dimensional stochastic processes given by overdamped and driven Langevin dynamics of interacting particles.« less

Dynamics of non-Markovian exclusion processes

NASA Astrophysics Data System (ADS)

Khoromskaia, Diana; Harris, Rosemary J.; Grosskinsky, Stefan

2014-12-01

Driven diffusive systems are often used as simple discrete models of collective transport phenomena in physics, biology or social sciences. Restricting attention to one-dimensional geometries, the asymmetric simple exclusion process (ASEP) plays a paradigmatic role to describe noise-activated driven motion of entities subject to an excluded volume interaction and many variants have been studied in recent years. While in the standard ASEP the noise is Poissonian and the process is therefore Markovian, in many applications the statistics of the activating noise has a non-standard distribution with possible memory effects resulting from internal degrees of freedom or external sources. This leads to temporal correlations and can significantly affect the shape of the current-density relation as has been studied recently for a number of scenarios. In this paper we report a general framework to derive the fundamental diagram of ASEPs driven by non-Poissonian noise by using effectively only two simple quantities, viz., the mean residual lifetime of the jump distribution and a suitably defined temporal correlation length. We corroborate our results by detailed numerical studies for various noise statistics under periodic boundary conditions and discuss how our approach can be applied to more general driven diffusive systems.

Parity-time symmetry breaking in magnetic systems

DOE PAGES

Galda, Alexey; Vinokur, Valerii M.

2016-07-14

The understanding of out-of-equilibrium physics, especially dynamic instabilities and dynamic phase transitions, is one of the major challenges of contemporary science, spanning the broadest wealth of research areas that range from quantum optics to living organisms. By focusing on nonequilibrium dynamics of an open dissipative spin system, we introduce a non-Hermitian Hamiltonian approach, in which non-Hermiticity reflects dissipation and deviation from equilibrium. The imaginary part of the proposed spin Hamiltonian describes the effects of Gilbert damping and applied Slonczewski spin-transfer torque. In the classical limit, our approach reproduces Landau-Lifshitz-Gilbert-Slonczewski dynamics of a large macrospin. Here, we reveal the spin-transfer torque-drivenmore » parity-time symmetry-breaking phase transition corresponding to a transition from precessional to exponentially damped spin dynamics. Micromagnetic simulations for nanoscale ferromagnetic disks demonstrate the predicted effect. These findings can pave the way to a general quantitative description of out-of-equilibrium phase transitions driven by spontaneous parity-time symmetry breaking.« less

A perspective on bridging scales and design of models using low-dimensional manifolds and data-driven model inference

PubMed Central

Zenil, Hector; Kiani, Narsis A.; Ball, Gordon; Gomez-Cabrero, David

2016-01-01

Systems in nature capable of collective behaviour are nonlinear, operating across several scales. Yet our ability to account for their collective dynamics differs in physics, chemistry and biology. Here, we briefly review the similarities and differences between mathematical modelling of adaptive living systems versus physico-chemical systems. We find that physics-based chemistry modelling and computational neuroscience have a shared interest in developing techniques for model reductions aiming at the identification of a reduced subsystem or slow manifold, capturing the effective dynamics. By contrast, as relations and kinetics between biological molecules are less characterized, current quantitative analysis under the umbrella of bioinformatics focuses on signal extraction, correlation, regression and machine-learning analysis. We argue that model reduction analysis and the ensuing identification of manifolds bridges physics and biology. Furthermore, modelling living systems presents deep challenges as how to reconcile rich molecular data with inherent modelling uncertainties (formalism, variables selection and model parameters). We anticipate a new generative data-driven modelling paradigm constrained by identified governing principles extracted from low-dimensional manifold analysis. The rise of a new generation of models will ultimately connect biology to quantitative mechanistic descriptions, thereby setting the stage for investigating the character of the model language and principles driving living systems. This article is part of the themed issue ‘Multiscale modelling at the physics–chemistry–biology interface’. PMID:27698038

Cross-Diffusion Driven Instability for a Lotka-Volterra Competitive Reaction-Diffusion System

NASA Astrophysics Data System (ADS)

Gambino, G.; Lombardo, M. C.; Sammartino, M.

2008-04-01

In this work we investigate the possibility of the pattern formation for a reaction-diffusion system with nonlinear diffusion terms. Through a linear stability analysis we find the conditions which allow a homogeneous steady state (stable for the kinetics) to become unstable through a Turing mechanism. In particular, we show how cross-diffusion effects are responsible for the initiation of spatial patterns. Finally, we find a Fisher amplitude equation which describes the weakly nonlinear dynamics of the system near the marginal stability.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Vaezi, P.; Holland, C.; Thakur, S. C.

The Controlled Shear Decorrelation Experiment (CSDX) linear plasma device provides a unique platform for investigating the underlying physics of self-regulating drift-wave turbulence/zonal flow dynamics. A minimal model of 3D drift-reduced nonlocal cold ion fluid equations which evolves density, vorticity, and electron temperature fluctuations, with proper sheath boundary conditions, is used to simulate dynamics of the turbulence in CSDX and its response to changes in parallel boundary conditions. These simulations are then carried out using the BOUndary Turbulence (BOUT++) framework and use equilibrium electron density and temperature profiles taken from experimental measurements. The results show that density gradient-driven drift-waves are themore » dominant instability in CSDX. However, the choice of insulating or conducting endplate boundary conditions affects the linear growth rates and energy balance of the system due to the absence or addition of Kelvin-Helmholtz modes generated by the sheath-driven equilibrium E × B shear and sheath-driven temperature gradient instability. Moreover, nonlinear simulation results show that the boundary conditions impact the turbulence structure and zonal flow formation, resulting in less broadband (more quasi-coherent) turbulence and weaker zonal flow in conducting boundary condition case. These results are qualitatively consistent with earlier experimental observations.« less

Magnetization dynamics driven by spin-polarized current in nanomagnets

NASA Astrophysics Data System (ADS)

Carpentieri, M.; Torres, L.; Azzerboni, B.; Finocchio, G.; Consolo, G.; Lopez-Diaz, L.

2007-09-01

In this report, micromagnetic simulations of magnetization dynamics driven by spin-polarized currents (SPCs) on magnetic nanopillars of permalloy/Cu/permalloy with different rectangular cross-sections are presented. Complete dynamical stability diagrams from initial parallel and antiparallel states have been computed for 100 ns. The effects of a space-dependent polarization function together with the presence of magnetostatic coupling from the fixed layer and classical Ampere field have been taken into account.

Gigahertz dynamics of a strongly driven single quantum spin.

PubMed

Fuchs, G D; Dobrovitski, V V; Toyli, D M; Heremans, F J; Awschalom, D D

2009-12-11

Two-level systems are at the core of numerous real-world technologies such as magnetic resonance imaging and atomic clocks. Coherent control of the state is achieved with an oscillating field that drives dynamics at a rate determined by its amplitude. As the strength of the field is increased, a different regime emerges where linear scaling of the manipulation rate breaks down and complex dynamics are expected. By calibrating the spin rotation with an adiabatic passage, we have measured the room-temperature "strong-driving" dynamics of a single nitrogen vacancy center in diamond. With an adiabatic passage to calibrate the spin rotation, we observed dynamics on sub-nanosecond time scales. Contrary to conventional thinking, this breakdown of the rotating wave approximation provides opportunities for time-optimal quantum control of a single spin.

Proceedings of the 2nd Experimental Chaos Conference

NASA Astrophysics Data System (ADS)

Ditto, William; Pecora, Lou; Shlesinger, Michael; Spano, Mark; Vohra, Sandeep

1995-02-01

The Table of Contents for the full book PDF is as follows: * Introduction * Spatiotemporal Phenomena * Experimental Studies of Chaotic Mixing * Using Random Maps in the Analysis of Experimental Fluid Flows * Transition to Spatiotemporal Chaos in a Reaction-Diffusion System * Ion-Dynamical Chaos in Plasmas * Optics * Chaos in a Synchronously Driven Optical Resonator * Chaos, Patterns and Defects in Stimulated Scattering Phenomena * Test of the Normal Form for a Subcritical Bifurcation * Observation of Bifurcations and Chaos in a Driven Fiber Optic Coil * Applications -- Communications * Robustness and Signal Recovery in a Synchronized Chaotic System * Synchronizing Nonautonomous Chaotic Circuits * Synchronization of Pulse-Coupled Chaotic Oscillators * Ocean Transmission Effects on Chaotic Signals * Controlling Symbolic Dynamics for Communication * Applications -- Control * Analysis of Nonlinear Actuators Using Chaotic Waveforms * Controlling Chaos in a Quasiperiodic Electronic System * Control of Chaos in a CO2 Laser * General Research * Video-Based Analysis of Bifurcation Phenomena in Radio-Frequency-Excited Inert Gas Plasmas * Transition from Soliton to Chaotic Motion During the Impact of a Nonlinear Structure * Sonoluminescence in a Single Bubble: Periodic, Quasiperiodic and Chaotic Light Source * Quantum Chaos Experiments Using Microwave Cavities * Experiments on Quantum Chaos With and Without Time Reversibility * When Small Noise Imposed on Deterministic Dynamics Becomes Important * Biology * Chaos Control for Cardiac Arrhythmias * Irregularities in Spike Trains of Cat Retinal Ganglion Cells * Broad-Band Synchronization in Monkey Neocortex * Applicability of Correlation Dimension Calculations to Blood Pressure Signal in Rats * Tests for Deterministic Chaos in Noisy Time Series * The Crayfish Mechanoreceptor Cell: A Biological Example of Stochastic Resonance * Chemistry * Chaos During Heterogeneous Chemical Reactions * Stabilizing and Tracking Unstable Periodic Orbits and Stationary States in Chemical Systems * Recursive Proportional-Feedback and Its Use to Control Chaos in an Electrochemical System * Temperature Patterns on Catalytic Surfaces * Meteorology/Oceanography * Nonlinear Evolution of Water Waves: Hilbert's View * Fractal Properties of Isoconcentration Surfaces in a Smoke Plume * Fractal Dimensions of Remotely Sensed Atmospheric Signals * Are Ocean Surface Waves Chaotic? * Dynamical Attractor Reconstruction for a Marine Stratocumulus Cloud

Planetary Systems Dynamics Eccentric patterns in debris disks & Planetary migration in binary systems

NASA Astrophysics Data System (ADS)

Faramaz, V.; Beust, H.; Augereau, J.-C.; Bonsor, A.; Thébault, P.; Wu, Y.; Marshall, J. P.; del Burgo, C.; Ertel, S.; Eiroa, C.; Montesinos, B.; Mora, A.

2014-01-01

We present some highlights of two ongoing investigations that deal with the dynamics of planetary systems. Firstly, until recently, observed eccentric patterns in debris disks were found in young systems. However recent observations of Gyr-old eccentric debris disks leads to question the survival timescale of this type of asymmetry. One such disk was recently observed in the far-IR by the Herschel Space Observatory around ζ2 Reticuli. Secondly, as a binary companion orbits a circumprimary disk, it creates regions where planet formation is strongly handicapped. However, some planets were detected in this zone in tight binary systems (γ Cep, HD 196885). We aim to determine whether a binary companion can affect migration such that planets are brought in these regions and focus in particular on the planetesimal-driven migration mechanism.

Deconstructing the core dynamics from a complex time-lagged regulatory biological circuit.

PubMed

Eriksson, O; Brinne, B; Zhou, Y; Björkegren, J; Tegnér, J

2009-03-01

Complex regulatory dynamics is ubiquitous in molecular networks composed of genes and proteins. Recent progress in computational biology and its application to molecular data generate a growing number of complex networks. Yet, it has been difficult to understand the governing principles of these networks beyond graphical analysis or extensive numerical simulations. Here the authors exploit several simplifying biological circumstances which thereby enable to directly detect the underlying dynamical regularities driving periodic oscillations in a dynamical nonlinear computational model of a protein-protein network. System analysis is performed using the cell cycle, a mathematically well-described complex regulatory circuit driven by external signals. By introducing an explicit time delay and using a 'tearing-and-zooming' approach the authors reduce the system to a piecewise linear system with two variables that capture the dynamics of this complex network. A key step in the analysis is the identification of functional subsystems by identifying the relations between state-variables within the model. These functional subsystems are referred to as dynamical modules operating as sensitive switches in the original complex model. By using reduced mathematical representations of the subsystems the authors derive explicit conditions on how the cell cycle dynamics depends on system parameters, and can, for the first time, analyse and prove global conditions for system stability. The approach which includes utilising biological simplifying conditions, identification of dynamical modules and mathematical reduction of the model complexity may be applicable to other well-characterised biological regulatory circuits. [Includes supplementary material].

Dynamic Data Driven Applications Systems (DDDAS)

DTIC Science & Technology

2013-03-06

INS •  Chip-scale atomic clocks •  Ad hoc networks •  Polymorphic networks •  Agile networks •  Laser communications •  Frequency-agile RF...atomi clocks •  Ad hoc networks •  Polymorphic networks •  Agile networks •  Laser co munications •  Frequency-agile RF systems...Real-Time Doppler Wind Wind field Sensor observations Energy Estimation Atmospheric Models for On-line Planning Planning and Control

Time step rescaling recovers continuous-time dynamical properties for discrete-time Langevin integration of nonequilibrium systems.

PubMed

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.

Implementing a Dynamic Database-Driven Course Using LAMP

ERIC Educational Resources Information Center

Laverty, Joseph Packy; Wood, David; Turchek, John

2011-01-01

This paper documents the formulation of a database driven open source architecture web development course. The design of a web-based curriculum faces many challenges: a) relative emphasis of client and server-side technologies, b) choice of a server-side language, and c) the cost and efficient delivery of a dynamic web development, database-driven…

Rayleigh-Taylor mixing with time-dependent acceleration

NASA Astrophysics Data System (ADS)

Abarzhi, Snezhana

2016-10-01

We extend the momentum model to describe Rayleigh-Taylor (RT) mixing driven by a time-dependent acceleration. The acceleration is a power-law function of time, similarly to astrophysical and plasma fusion applications. In RT flow the dynamics of a fluid parcel is driven by a balance per unit mass of the rates of momentum gain and loss. We find analytical solutions in the cases of balanced and imbalanced gains and losses, and identify their dependence on the acceleration exponent. The existence is shown of two typical regimes of self-similar RT mixing-acceleration-driven Rayleigh-Taylor-type and dissipation-driven Richtymer-Meshkov-type with the latter being in general non-universal. Possible scenarios are proposed for transitions from the balanced dynamics to the imbalanced self-similar dynamics. Scaling and correlations properties of RT mixing are studied on the basis of dimensional analysis. Departures are outlined of RT dynamics with time-dependent acceleration from canonical cases of homogeneous turbulence as well as blast waves with first and second kind self-similarity. The work is supported by the US National Science Foundation.

Rayleigh-Taylor mixing with space-dependent acceleration

NASA Astrophysics Data System (ADS)

Abarzhi, Snezhana

2016-11-01

We extend the momentum model to describe Rayleigh-Taylor (RT) mixing driven by a space-dependent acceleration. The acceleration is a power-law function of space coordinate, similarly to astrophysical and plasma fusion applications. In RT flow the dynamics of a fluid parcel is driven by a balance per unit mass of the rates of momentum gain and loss. We find analytical solutions in the cases of balanced and imbalanced gains and losses, and identify their dependence on the acceleration exponent. The existence is shown of two typical sub-regimes of self-similar RT mixing - the acceleration-driven Rayleigh-Taylor-type mixing and dissipation-driven Richtymer-Meshkov-type mixing with the latter being in general non-universal. Possible scenarios are proposed for transitions from the balanced dynamics to the imbalanced self-similar dynamics. Scaling and correlations properties of RT mixing are studied on the basis of dimensional analysis. Departures are outlined of RT dynamics with space-dependent acceleration from canonical cases of homogeneous turbulence as well as blast waves with first and second kind self-similarity. The work is supported by the US National Science Foundation.

75 FR 35329 - Notification and Reporting of Aircraft Accidents or Incidents and Overdue Aircraft, and...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-06-22

...-driven fixed-wing aircraft heavier than air, that is supported in flight by the dynamic reaction of the... reporting of runway incursions: ``Any event in which an aircraft operated by an air carrier: (i) Lands or... during normal operations, such as those involving seaplanes, hot-air balloons, unmanned aircraft systems...

A System Dynamics Model for Long-Term Planning of the Undergraduate Education in Brazil

ERIC Educational Resources Information Center

Strauss, Luísa Mariele; Borenstein, Denis

2015-01-01

Higher education in Brazil has experienced a rapid expansion since the 1990s as a consequence of the government's pliability in launching new programs and educational institutions. This expansion was mainly driven by the private sector. Despite this expansion, Brazil has not yet achieved the enrollment goal expected in the National Education Plan…

Tremor Frequency Profile as a Function of Level of Mental Retardation

ERIC Educational Resources Information Center

Sprague, Robert L.; Deutsch, Katherine M.; Newell, Karl M.

2007-01-01

The characteristic slowness of movement initiation and execution in adult individuals with mental retardation may be driven by the slower frequency profile of the dynamics of the system. To investigate this hypothesis, we examined the resting and postural finger tremor frequency profile (single and dual limb) of adults as a function of level of…

Monitoring land surface albedo and vegetation dynamics using high spatial and temporal resolution synthetic data from Landsat and MODIS BRDF/albedo product

USDA-ARS?s Scientific Manuscript database

Climate warming over the past half century has led to observable changes in vegetation phenology and growing season length; which can be measured globally using remote sensing derived vegetation indices. Previous studies in mid- and high northern latitude systems show temperature driven earlier spri...

Theoretical studies on a new pattern of laser-driven systems: towards elucidation of direct photo-injection in dye-sensitized solar cells

NASA Astrophysics Data System (ADS)

Mishima, Kenji; Yamashita, Koichi

2011-03-01

We theoretically and numerically investigated a new type of analytically solvable laser-driven systems inspired by electron-injection dynamics in dye-sensitized solar cells. The simple analytical expressions were found to be useful for understanding the difference between dye excitation and direct photo-injection occurring between dye molecule and semiconductor nanoparticles. More importantly, we propose a method for discriminating experimentally dye excitation and direct photo-injection by using time-dependent fluorescence. We found that dye excitation shows no significant quantum beat whereas the direct photo-injection shows a significant quantum beat. This work was supported by Funding Program for World-Leading Innovative R&D on Science and Technology (FIRST) ``Development of Organic Photovoltaics toward a Low-Carbon Society,'' Cabinet Office, Japan.

Prony Ringdown GUI (CERTS Prony Ringdown, part of the DSI Tool Box)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tuffner, Francis; Marinovici, PNNL Laurentiu; Hauer, PNNL John

2014-02-21

The PNNL Prony Ringdown graphical user interface is one analysis tool included in the Dynamic System Identification toolbox (DSI Toolbox). The Dynamic System Identification toolbox is a MATLAB-based collection of tools for parsing and analyzing phasor measurement unit data, especially in regards to small signal stability. It includes tools to read the data, preprocess it, and perform small signal analysis. 5. Method of Solution: The Dynamic System Identification Toolbox (DSI Toolbox) is designed to provide a research environment for examining phasor measurement unit data and performing small signal stability analysis. The software uses a series of text-driven menus to helpmore » guide users and organize the toolbox features. Methods for reading in populate phasor measurement unit data are provided, with appropriate preprocessing options for small-signal-stability analysis. The toolbox includes the Prony Ringdown GUI and basic algorithms to estimate information on oscillatory modes of the system, such as modal frequency and damping ratio.« less

Dynamic analysis of the tether transportation system using absolute nodal coordinate formulation

NASA Astrophysics Data System (ADS)

Sun, Xin; Xu, Ming; Zhong, Rui

2017-10-01

Long space tethers are becoming a rising concern as an alternate way for transportation in space. It benefits from fuel economizing. This paper focuses on the dynamics of the tether transportation system, which consists of two end satellites connected by a flexible tether, and a movable vehicle driven by the actuator carried by itself. The Absolute Nodal Coordinate Formulation is applied to the establishment of the equation of motion, so that the influence caused by the distributed mass and elasticity of the tether is introduced. Moreover, an approximated method for accelerating the calculation of the generalized gravitational forces on the tether is proposed by substituting the volume integral every step into summation of finite terms. Afterwards, dynamic evolutions of such a system in different configurations are illustrated using numerical simulations. The deflection of the tether and the trajectory of the crawler during the transportation is investigated. Finally, the effect on the orbit of the system due to the crawler is revealed.

ROBUS-2: A Fault-Tolerant Broadcast Communication System

NASA Technical Reports Server (NTRS)

Torres-Pomales, Wilfredo; Malekpour, Mahyar R.; Miner, Paul S.

2005-01-01

The Reliable Optical Bus (ROBUS) is the core communication system of the Scalable Processor-Independent Design for Enhanced Reliability (SPIDER), a general-purpose fault-tolerant integrated modular architecture currently under development at NASA Langley Research Center. The ROBUS is a time-division multiple access (TDMA) broadcast communication system with medium access control by means of time-indexed communication schedule. ROBUS-2 is a developmental version of the ROBUS providing guaranteed fault-tolerant services to the attached processing elements (PEs), in the presence of a bounded number of faults. These services include message broadcast (Byzantine Agreement), dynamic communication schedule update, clock synchronization, and distributed diagnosis (group membership). The ROBUS also features fault-tolerant startup and restart capabilities. ROBUS-2 is tolerant to internal as well as PE faults, and incorporates a dynamic self-reconfiguration capability driven by the internal diagnostic system. This version of the ROBUS is intended for laboratory experimentation and demonstrations of the capability to reintegrate failed nodes, dynamically update the communication schedule, and tolerate and recover from correlated transient faults.

Noise induced chaos in optically driven colloidal rings.

NASA Astrophysics Data System (ADS)

Roichman, Yael; Zaslavsky, George; Grier, David G.

2007-03-01

Given a constant flux of energy, many driven dissipative systems rapidly organize themselves into configurations that support steady state motion. Examples include swarming of bacterial colonies, convection in shaken sandpiles, and synchronization in flowing traffic. How simple objects interacting in simple ways self-organize generally is not understood, mainly because so few of the available experimental systems afford the necessary access to their microscopic degrees of freedom. This talk introduces a new class of model driven dissipative systems typified by three colloidal spheres circulating around a ring-like optical trap known as an optical vortex. By controlling the interplay between hydrodynamic interactions and fixed disorder we are able to drive a transition from a previously predicted periodic steady state to fully developed chaos. In addition, by tracking both microscopic trajectories and macroscopic collective fluctuations the relation between the onset of microscopic weak chaos and the evolution of space-time self-similarity in macroscopic transport properties is revealed. In a broader scope, several optical vortices can be coupled to create a large dissipative system where each building block has internal degrees of freedom. In such systems the little understood dynamics of processes like frustration and jamming, fluctuation-dissipation relations and the propagation of collective motion can be tracked microscopically.

Quantum dynamics of light-driven chiral molecular motors.

PubMed

Yamaki, Masahiro; Nakayama, Shin-ichiro; Hoki, Kunihito; Kono, Hirohiko; Fujimura, Yuichi

2009-03-21

The results of theoretical studies on quantum dynamics of light-driven molecular motors with internal rotation are presented. Characteristic features of chiral motors driven by a non-helical, linearly polarized electric field of light are explained on the basis of symmetry argument. The rotational potential of the chiral motor is characterized by a ratchet form. The asymmetric potential determines the directional motion: the rotational direction is toward the gentle slope of the asymmetric potential. This direction is called the intuitive direction. To confirm the unidirectional rotational motion, results of quantum dynamical calculations of randomly-oriented molecular motors are presented. A theoretical design of the smallest light-driven molecular machine is presented. The smallest chiral molecular machine has an optically driven engine and a running propeller on its body. The mechanisms of transmission of driving forces from the engine to the propeller are elucidated by using a quantum dynamical treatment. The results provide a principle for control of optically-driven molecular bevel gears. Temperature effects are discussed using the density operator formalism. An effective method for ultrafast control of rotational motions in any desired direction is presented with the help of a quantum control theory. In this method, visible or UV light pulses are applied to drive the motor via an electronic excited state. A method for driving a large molecular motor consisting of an aromatic hydrocarbon is presented. The molecular motor is operated by interactions between the induced dipole of the molecular motor and the electric field of light pulses.

Dynamical transitions of a driven Ising interface

NASA Astrophysics Data System (ADS)

Sahai, Manish K.; Sengupta, Surajit

2008-03-01

We study the structure of an interface in a three-dimensional Ising system created by an external nonuniform field H(r,t) . H changes sign over a two-dimensional plane of arbitrary orientation. When the field is pulled with velocity ve , [i.e., H(r,t)=H(r-vet) ], the interface undergoes several dynamical transitions. For low velocities it is pinned by the field profile and moves along with it, the distribution of local slopes undergoing a series of commensurate-incommensurate transitions. For large ve the interface depins and grows with Kardar-Parisi-Zhang exponents.

Jdpd: an open java simulation kernel for molecular fragment dissipative particle dynamics.

PubMed

van den Broek, Karina; Kuhn, Hubert; Zielesny, Achim

2018-05-21

Jdpd is an open Java simulation kernel for Molecular Fragment Dissipative Particle Dynamics with parallelizable force calculation, efficient caching options and fast property calculations. It is characterized by an interface and factory-pattern driven design for simple code changes and may help to avoid problems of polyglot programming. Detailed input/output communication, parallelization and process control as well as internal logging capabilities for debugging purposes are supported. The new kernel may be utilized in different simulation environments ranging from flexible scripting solutions up to fully integrated "all-in-one" simulation systems.

Adaptive Sampling using Support Vector Machines

DOE Office of Scientific and Technical Information (OSTI.GOV)

D. Mandelli; C. Smith

2012-11-01

Reliability/safety analysis of stochastic dynamic systems (e.g., nuclear power plants, airplanes, chemical plants) is currently performed through a combination of Event-Tress and Fault-Trees. However, these conventional methods suffer from certain drawbacks: • Timing of events is not explicitly modeled • Ordering of events is preset by the analyst • The modeling of complex accident scenarios is driven by expert-judgment For these reasons, there is currently an increasing interest into the development of dynamic PRA methodologies since they can be used to address the deficiencies of conventional methods listed above.

Defect chaos of oscillating hexagons in rotating convection

PubMed

Echebarria; Riecke

2000-05-22

Using coupled Ginzburg-Landau equations, the dynamics of hexagonal patterns with broken chiral symmetry are investigated, as they appear in rotating non-Boussinesq or surface-tension-driven convection. We find that close to the secondary Hopf bifurcation to oscillating hexagons the dynamics are well described by a single complex Ginzburg-Landau equation (CGLE) coupled to the phases of the hexagonal pattern. At the band center these equations reduce to the usual CGLE and the system exhibits defect chaos. Away from the band center a transition to a frozen vortex state is found.

Impacts of climate change on the formation and stability of late Quaternary sand sheets and falling dunes, Black Mesa region, southern Colorado Plateau, USA

USGS Publications Warehouse

Ellwein, Amy L.; Mahan, Shannon; McFadden, Leslie D.

2015-01-01

Widely used predictive models of eolian system dynamics are typically based entirely on climatic variables and do not account for landscape complexity and geomorphic history. Climate-only assumptions fail to give accurate predictions of the dynamics of this and many other dune fields. A growing body of work suggests that eolian deposits in wind-driven semiarid climates may be more strongly related to increases in sediment supply than to increases in aridity.

Reconstruction of dynamical systems from resampled point processes produced by neuron models

NASA Astrophysics Data System (ADS)

Pavlova, Olga N.; Pavlov, Alexey N.

2018-04-01

Characterization of dynamical features of chaotic oscillations from point processes is based on embedding theorems for non-uniformly sampled signals such as the sequences of interspike intervals (ISIs). This theoretical background confirms the ability of attractor reconstruction from ISIs generated by chaotically driven neuron models. The quality of such reconstruction depends on the available length of the analyzed dataset. We discuss how data resampling improves the reconstruction for short amount of data and show that this effect is observed for different types of mechanisms for spike generation.

General Relativistic Effects on Neutrino-driven Winds from Young, Hot Neutron Stars and r-Process Nucleosynthesis

NASA Astrophysics Data System (ADS)

Otsuki, Kaori; Tagoshi, Hideyuki; Kajino, Toshitaka; Wanajo, Shin-ya

2000-04-01

Neutrino-driven winds from young hot neutron stars, which are formed by supernova explosions, are the most promising candidate site for r-process nucleosynthesis. We study general relativistic effects on this wind in Schwarzschild geometry in order to look for suitable conditions for successful r-process nucleosynthesis. It is quantitatively demonstrated that general relativistic effects play a significant role in increasing the entropy and decreasing the dynamic timescale of the neutrino-driven wind. Exploring the wide parameter region that determines the expansion dynamics of the wind, we find interesting physical conditions that lead to successful r-process nucleosynthesis. The conditions that we found are realized in a neutrino-driven wind with a very short dynamic timescale, τdyn~6 ms, and a relatively low entropy, S~140. We carry out α-process and r-process nucleosynthesis calculations on these conditions with our single network code, which includes over 3000 isotopes, and confirm quantitatively that the second and third r-process abundance peaks are produced in neutrino-driven winds.

Adaptation to conflict via context-driven anticipatory signals in the dorsomedial prefrontal cortex.

PubMed

Horga, Guillermo; Maia, Tiago V; Wang, Pengwei; Wang, Zhishun; Marsh, Rachel; Peterson, Bradley S

2011-11-09

Behavioral interference elicited by competing response tendencies adapts to contextual changes. Recent nonhuman primate research suggests a key mnemonic role of distinct prefrontal cells in supporting such context-driven behavioral adjustments by maintaining conflict information across trials, but corresponding prefrontal functions have yet to be probed in humans. Using event-related functional magnetic resonance imaging, we investigated the human neural substrates of contextual adaptations to conflict. We found that a neural system comprising the rostral dorsomedial prefrontal cortex and portions of the dorsolateral prefrontal cortex specifically encodes the history of previously experienced conflict and influences subsequent adaptation to conflict on a trial-by-trial basis. This neural system became active in anticipation of stimulus onsets during preparatory periods and interacted with a second neural system engaged during the processing of conflict. Our findings suggest that a dynamic interaction between a system that represents conflict history and a system that resolves conflict underlies the contextual adaptation to conflict.

Adaptation to Conflict via Context-Driven Anticipatory Signals in the Dorsomedial Prefrontal Cortex

PubMed Central

Horga, Guillermo; Maia, Tiago V.; Wang, Pengwei; Wang, Zhishun; Marsh, Rachel; Peterson, Bradley S.

2011-01-01

Behavioral interference elicited by competing response tendencies adapts to contextual changes. Recent nonhuman primate research suggests a key mnemonic role of distinct prefrontal cells in supporting such context-driven behavioral adjustments by maintaining conflict information across trials, but corresponding prefrontal functions have yet to be probed in humans. Using event-related functional magnetic resonance imaging (fMRI), we investigated the human neural substrates of contextual adaptations to conflict. We found that a neural system comprising the rostral dorsomedial prefrontal cortex and portions of the dorsolateral prefrontal cortex specifically encodes the history of previously experienced conflict and influences subsequent adaptation to conflict on a trial-by-trial basis. This neural system became active in anticipation of stimulus onsets during preparatory periods and interacted with a second neural system engaged during the processing of conflict. Our findings suggest that a dynamic interaction between a system that represents conflict history and a system that resolves conflict underlies the contextual adaptation to conflict. PMID:22072672

Statistical inference for noisy nonlinear ecological dynamic systems.

PubMed

Wood, Simon N

2010-08-26

Chaotic ecological dynamic systems defy conventional statistical analysis. Systems with near-chaotic dynamics are little better. Such systems are almost invariably driven by endogenous dynamic processes plus demographic and environmental process noise, and are only observable with error. Their sensitivity to history means that minute changes in the driving noise realization, or the system parameters, will cause drastic changes in the system trajectory. This sensitivity is inherited and amplified by the joint probability density of the observable data and the process noise, rendering it useless as the basis for obtaining measures of statistical fit. Because the joint density is the basis for the fit measures used by all conventional statistical methods, this is a major theoretical shortcoming. The inability to make well-founded statistical inferences about biological dynamic models in the chaotic and near-chaotic regimes, other than on an ad hoc basis, leaves dynamic theory without the methods of quantitative validation that are essential tools in the rest of biological science. Here I show that this impasse can be resolved in a simple and general manner, using a method that requires only the ability to simulate the observed data on a system from the dynamic model about which inferences are required. The raw data series are reduced to phase-insensitive summary statistics, quantifying local dynamic structure and the distribution of observations. Simulation is used to obtain the mean and the covariance matrix of the statistics, given model parameters, allowing the construction of a 'synthetic likelihood' that assesses model fit. This likelihood can be explored using a straightforward Markov chain Monte Carlo sampler, but one further post-processing step returns pure likelihood-based inference. I apply the method to establish the dynamic nature of the fluctuations in Nicholson's classic blowfly experiments.

Nonequilibrium-thermodynamics approach to open quantum systems

NASA Astrophysics Data System (ADS)

Semin, Vitalii; Petruccione, Francesco

2014-11-01

Open quantum systems are studied from the thermodynamical point of view unifying the principle of maximum informational entropy and the hypothesis of relaxation times hierarchy. The result of the unification is a non-Markovian and local-in-time master equation that provides a direct connection for dynamical and thermodynamical properties of open quantum systems. The power of the approach is illustrated by the application to the damped harmonic oscillator and the damped driven two-level system, resulting in analytical expressions for the non-Markovian and nonequilibrium entropy and inverse temperature.

Precision vector control of a superconducting RF cavity driven by an injection locked magnetron

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chase, Brian; Pasquinelli, Ralph; Cullerton, Ed

The technique presented in this paper enables the regulation of both radio frequency amplitude and phase in narrow band devices such as a Superconducting RF (SRF) cavity driven by constant power output devices i.e. magnetrons [1]. The ability to use low cost high efficiency magnetrons for accelerator RF power systems, with tight vector regulation, presents a substantial cost savings in both construction and operating costs - compared to current RF power system technology. An operating CW system at 2.45 GHz has been experimentally developed. Vector control of an injection locked magnetron has been extensively tested and characterized with a SRFmore » cavity as the load. Amplitude dynamic range of 30 dB, amplitude stability of 0.3% r.m.s, and phase stability of 0.26 degrees r.m.s. has been demonstrated.« less

Quantifying Ubiquitin Signaling

PubMed Central

Ordureau, Alban; Münch, Christian; Harper, J. Wade

2015-01-01

Ubiquitin (UB)-driven signaling systems permeate biology, and are often integrated with other types of post-translational modifications (PTMs), most notably phosphorylation. Flux through such pathways is typically dictated by the fractional stoichiometry of distinct regulatory modifications and protein assemblies as well as the spatial organization of pathway components. Yet, we rarely understand the dynamics and stoichiometry of rate-limiting intermediates along a reaction trajectory. Here, we review how quantitative proteomic tools and enrichment strategies are being used to quantify UB-dependent signaling systems, and to integrate UB signaling with regulatory phosphorylation events. A key regulatory feature of ubiquitylation is that the identity of UB chain linkage types can control downstream processes. We also describe how proteomic and enzymological tools can be used to identify and quantify UB chain synthesis and linkage preferences. The emergence of sophisticated quantitative proteomic approaches will set a new standard for elucidating biochemical mechanisms of UB-driven signaling systems. PMID:26000850

Two-fluid model of a Bose-Einstein condensate in the cavity optomechanical regime

NASA Astrophysics Data System (ADS)

Goldbaum, Dan; Zhang, Keye; Meystre, Pierre

2010-03-01

We analyze an atomic Bose-Einstein condensate trapped in a high-Q optical cavity driven by a feeble optical field. The dynamics of the resulting collective density excitation of the condensate are formally analogous to the central model system of cavity optomechanics: a radiation pressure driven mechanical oscillator [Brennecke et al., Science 322, 235 (2008)]. However, although BEC-based optomechanical systems have several desirable properties, one must also take into account the effect of atom-atom interactions. We treat these interactions via a two-fluid model that retains the intuitive appeal of the non-interacting two-mode description. We find that the Bogoliubov excitation spectrum of this system comprises a gapped upper branch and a lower branch that can include an unstable excitation mode. [4pt] D. S. Goldbaum, K. Zhang and P. Meystre, Two-fluid model of a Bose-Einstein condensate in the cavity optomechanical regime, arXiv:0911.3234.

High-speed multi-frame dynamic transmission electron microscope image acquisition system with arbitrary timing

DOEpatents

Reed, Bryan W.; DeHope, William J.; Huete, Glenn; LaGrange, Thomas B.; Shuttlesworth, Richard M.

2016-02-23

An electron microscope is disclosed which has a laser-driven photocathode and an arbitrary waveform generator (AWG) laser system ("laser"). The laser produces a train of temporally-shaped laser pulses each being of a programmable pulse duration, and directs the laser pulses to the laser-driven photocathode to produce a train of electron pulses. An image sensor is used along with a deflector subsystem. The deflector subsystem is arranged downstream of the target but upstream of the image sensor, and has a plurality of plates. A control system having a digital sequencer controls the laser and a plurality of switching components, synchronized with the laser, to independently control excitation of each one of the deflector plates. This allows each electron pulse to be directed to a different portion of the image sensor, as well as to enable programmable pulse durations and programmable inter-pulse spacings.

Precision vector control of a superconducting RF cavity driven by an injection locked magnetron

DOE PAGES

Chase, Brian; Pasquinelli, Ralph; Cullerton, Ed; ...

2015-03-01

The technique presented in this paper enables the regulation of both radio frequency amplitude and phase in narrow band devices such as a Superconducting RF (SRF) cavity driven by constant power output devices i.e. magnetrons [1]. The ability to use low cost high efficiency magnetrons for accelerator RF power systems, with tight vector regulation, presents a substantial cost savings in both construction and operating costs - compared to current RF power system technology. An operating CW system at 2.45 GHz has been experimentally developed. Vector control of an injection locked magnetron has been extensively tested and characterized with a SRFmore » cavity as the load. Amplitude dynamic range of 30 dB, amplitude stability of 0.3% r.m.s, and phase stability of 0.26 degrees r.m.s. has been demonstrated.« less

Parametrically driven hybrid qubit-photon systems: Dissipation-induced quantum entanglement and photon production from vacuum

NASA Astrophysics Data System (ADS)

Remizov, S. V.; Zhukov, A. A.; Shapiro, D. S.; Pogosov, W. V.; Lozovik, Yu. E.

2017-10-01

We consider a dissipative evolution of a parametrically driven qubit-cavity system under the periodic modulation of coupling energy between two subsystems, which leads to the amplification of counter-rotating processes. We reveal a very rich dynamical behavior of this hybrid system. In particular, we find that the energy dissipation in one of the subsystems can enhance quantum effects in another subsystem. For instance, optimal cavity decay assists the stabilization of entanglement and quantum correlations between qubits even in the steady state and the compensation of finite qubit relaxation. On the contrary, energy dissipation in qubit subsystems results in enhanced photon production from vacuum for strong modulation but destroys both quantum concurrence and quantum mutual information between qubits. Our results provide deeper insights to nonstationary cavity quantum electrodynamics in the context of quantum information processing and might be of importance for dissipative quantum state engineering.

Versatile microwave-driven trapped ion spin system for quantum information processing

PubMed Central

Piltz, Christian; Sriarunothai, Theeraphot; Ivanov, Svetoslav S.; Wölk, Sabine; Wunderlich, Christof

2016-01-01

Using trapped atomic ions, we demonstrate a tailored and versatile effective spin system suitable for quantum simulations and universal quantum computation. By simply applying microwave pulses, selected spins can be decoupled from the remaining system and, thus, can serve as a quantum memory, while simultaneously, other coupled spins perform conditional quantum dynamics. Also, microwave pulses can change the sign of spin-spin couplings, as well as their effective strength, even during the course of a quantum algorithm. Taking advantage of the simultaneous long-range coupling between three spins, a coherent quantum Fourier transform—an essential building block for many quantum algorithms—is efficiently realized. This approach, which is based on microwave-driven trapped ions and is complementary to laser-based methods, opens a new route to overcoming technical and physical challenges in the quest for a quantum simulator and a quantum computer. PMID:27419233

High-speed multiframe dynamic transmission electron microscope image acquisition system with arbitrary timing

DOEpatents

Reed, Bryan W.; DeHope, William J.; Huete, Glenn; LaGrange, Thomas B.; Shuttlesworth, Richard M.

2015-10-20

An electron microscope is disclosed which has a laser-driven photocathode and an arbitrary waveform generator (AWG) laser system ("laser"). The laser produces a train of temporally-shaped laser pulses of a predefined pulse duration and waveform, and directs the laser pulses to the laser-driven photocathode to produce a train of electron pulses. An image sensor is used along with a deflector subsystem. The deflector subsystem is arranged downstream of the target but upstream of the image sensor, and has two pairs of plates arranged perpendicular to one another. A control system controls the laser and a plurality of switching components synchronized with the laser, to independently control excitation of each one of the deflector plates. This allows each electron pulse to be directed to a different portion of the image sensor, as well as to be provided with an independently set duration and independently set inter-pulse spacings.

High-speed multiframe dynamic transmission electron microscope image acquisition system with arbitrary timing

DOEpatents

Reed, Bryan W.; Dehope, William J; Huete, Glenn; LaGrange, Thomas B.; Shuttlesworth, Richard M

2016-06-21

An electron microscope is disclosed which has a laser-driven photocathode and an arbitrary waveform generator (AWG) laser system ("laser"). The laser produces a train of temporally-shaped laser pulses of a predefined pulse duration and waveform, and directs the laser pulses to the laser-driven photocathode to produce a train of electron pulses. An image sensor is used along with a deflector subsystem. The deflector subsystem is arranged downstream of the target but upstream of the image sensor, and has two pairs of plates arranged perpendicular to one another. A control system controls the laser and a plurality of switching components synchronized with the laser, to independently control excitation of each one of the deflector plates. This allows each electron pulse to be directed to a different portion of the image sensor, as well as to be provided with an independently set duration and independently set inter-pulse spacings.

Vergence accommodation and monocular closed loop blur accommodation have similar dynamic characteristics.

PubMed

Suryakumar, Rajaraman; Meyers, Jason P; Irving, Elizabeth L; Bobier, William R

2007-02-01

Retinal blur and disparity are two different sensory signals known to cause a change in accommodative response. These inputs have differing neurological correlates that feed into a final common pathway. The purpose of this study was to investigate the dynamic properties of monocular blur driven accommodation and binocular disparity driven vergence-accommodation (VA) in human subjects. The results show that when response amplitudes are matched, blur accommodation and VA share similar dynamic properties.

Dynamics of flexible bodies in tree topology - A computer oriented approach

NASA Technical Reports Server (NTRS)

Singh, R. P.; Vandervoort, R. J.; Likins, P. W.

1984-01-01

An approach suited for automatic generation of the equations of motion for large mechanical systems (i.e., large space structures, mechanisms, robots, etc.) is presented. The system topology is restricted to a tree configuration. The tree is defined as an arbitrary set of rigid and flexible bodies connected by hinges characterizing relative translations and rotations of two adjoining bodies. The equations of motion are derived via Kane's method. The resulting equation set is of minimum dimension. Dynamical equations are imbedded in a computer program called TREETOPS. Extensive control simulation capability is built in the TREETOPS program. The simulation is driven by an interactive set-up program resulting in an easy to use analysis tool.

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.

A real-time spiking cerebellum model for learning robot control.

PubMed

Carrillo, Richard R; Ros, Eduardo; Boucheny, Christian; Coenen, Olivier J-M D

2008-01-01

We describe a neural network model of the cerebellum based on integrate-and-fire spiking neurons with conductance-based synapses. The neuron characteristics are derived from our earlier detailed models of the different cerebellar neurons. We tested the cerebellum model in a real-time control application with a robotic platform. Delays were introduced in the different sensorimotor pathways according to the biological system. The main plasticity in the cerebellar model is a spike-timing dependent plasticity (STDP) at the parallel fiber to Purkinje cell connections. This STDP is driven by the inferior olive (IO) activity, which encodes an error signal using a novel probabilistic low frequency model. We demonstrate the cerebellar model in a robot control system using a target-reaching task. We test whether the system learns to reach different target positions in a non-destructive way, therefore abstracting a general dynamics model. To test the system's ability to self-adapt to different dynamical situations, we present results obtained after changing the dynamics of the robotic platform significantly (its friction and load). The experimental results show that the cerebellar-based system is able to adapt dynamically to different contexts.

Correlation between Gini index and mobility in a stochastic kinetic model of economic exchange

NASA Astrophysics Data System (ADS)

Bertotti, Maria Letizia; Chattopadhyay, Amit K.; Modanese, Giovanni

Starting from a class of stochastically driven kinetic models of economic exchange, here we present results highlighting the correlation of the Gini inequality index with the social mobility rate, close to dynamical equilibrium. Except for the "canonical-additive case", our numerical results consistently indicate negative values of the correlation coefficient, in agreement with empirical evidence. This confirms that growing inequality is not conducive to social mobility which then requires an "external source" to sustain its dynamics. On the other hand, the sign of the correlation between inequality and total income in the canonical ensemble depends on the way wealth enters or leaves the system. At a technical level, the approach involves a generalization of a stochastic dynamical system formulation, that further paves the way for a probabilistic formulation of perturbed economic exchange models.

Parity-time symmetry-breaking mechanism of dynamic Mott transitions in dissipative systems

DOE PAGES

Tripathi, Vikram; Galda, Alexey; Barman, Himadri; ...

2016-07-05

Here, we describe the critical behavior of the electric field-driven (dynamic) Mott insulator-to-metal transitions in dissipative Fermi and Bose systems in terms of non-Hermitian Hamiltonians invariant under simultaneous parity (P) and time-reversal (T) operations. The dynamic Mott transition is identified as a PT symmetry-breaking phase transition, with the Mott insulating state corresponding to the regime of unbroken PT symmetry with a real energy spectrum. We also established that the imaginary part of the Hamiltonian arises from the combined effects of the driving field and inherent dissipation. We derive the renormalization and collapse of the Mott gap at the dielectric breakdownmore » and describe the resulting critical behavior of transport characteristics. The critical exponent we obtained is in an excellent agreement with experimental findings.« less

Photochemically and Thermally Driven Full-Color Reflection in a Self-Organized Helical Superstructure Enabled by a Halogen-Bonded Chiral Molecular Switch.

PubMed

Wang, Hao; Bisoyi, Hari Krishna; Wang, Ling; Urbas, Augustine M; Bunning, Timothy J; Li, Quan

2018-02-05

Supramolecular approaches toward the fabrication of functional materials and systems have been an enabling endeavor. Recently, halogen bonding has been harnessed as a promising supramolecular tool. Herein we report the synthesis and characterization of a novel halogen-bonded light-driven axially chiral molecular switch. The photoactive halogen-bonded chiral switch is able to induce a self-organized, tunable helical superstructure, that is, cholesteric liquid crystal (CLC), when doped into an achiral liquid crystal (LC) host. The halogen-bonded switch as a chiral dopant has a high helical twisting power (HTP) and shows a large change of its HTP upon photoisomerization. This light-driven dynamic modulation enables reversible selective reflection color tuning across the entire visible spectrum. The chiral switch also displays a temperature-dependent HTP change that enables thermally driven red, green, and blue (RGB) reflection colors in the self-organized helical superstructure. © 2018 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

A data driven control method for structure vibration suppression

NASA Astrophysics Data System (ADS)

Xie, Yangmin; Wang, Chao; Shi, Hang; Shi, Junwei

2018-02-01

High radio-frequency space applications have motivated continuous research on vibration suppression of large space structures both in academia and industry. This paper introduces a novel data driven control method to suppress vibrations of flexible structures and experimentally validates the suppression performance. Unlike model-based control approaches, the data driven control method designs a controller directly from the input-output test data of the structure, without requiring parametric dynamics and hence free of system modeling. It utilizes the discrete frequency response via spectral analysis technique and formulates a non-convex optimization problem to obtain optimized controller parameters with a predefined controller structure. Such approach is then experimentally applied on an end-driving flexible beam-mass structure. The experiment results show that the presented method can achieve competitive disturbance rejections compared to a model-based mixed sensitivity controller under the same design criterion but with much less orders and design efforts, demonstrating the proposed data driven control is an effective approach for vibration suppression of flexible structures.

Electron-rich driven electrochemical solid-state amorphization in Li-Si alloys.

PubMed

Wang, Zhiguo; Gu, Meng; Zhou, Yungang; Zu, Xiaotao; Connell, Justin G; Xiao, Jie; Perea, Daniel; Lauhon, Lincoln J; Bang, Junhyeok; Zhang, Shengbai; Wang, Chongmin; Gao, Fei

2013-09-11

The physical and chemical behaviors of materials used in energy storage devices, such as lithium-ion batteries (LIBs), are mainly controlled by an electrochemical process, which normally involves insertion/extraction of ions into/from a host lattice with a concurrent flow of electrons to compensate charge balance. The fundamental physics and chemistry governing the behavior of materials in response to the ions insertion/extraction is not known. Herein, a combination of in situ lithiation experiments and large-scale ab initio molecular dynamics simulations are performed to explore the mechanisms of the electrochemically driven solid-state amorphization in Li-Si systems. We find that local electron-rich condition governs the electrochemically driven solid-state amorphization of Li-Si alloys. This discovery provides the fundamental explanation of why lithium insertion in semiconductor and insulators leads to amorphization, whereas in metals, it leads to a crystalline alloy. The present work correlates electrochemically driven reactions with ion insertion, electron transfer, lattice stability, and phase equilibrium.

Electron-Rich Driven Electrochemical Solid-State Amorphization in Li-Si Alloys

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wang, Zhiguo; Gu, Meng; Zhou, Yungang

2013-08-14

The physical and chemical behaviors of materials used in energy storage devices, such as lithium-ion batteries (LIBs), are mainly controlled by an electrochemical process, which normally involves insertion/extraction of ions into/from a host lattice with a concurrent flow of electrons to compensate charge balance. The fundamental physics and chemistry governing the behavior of materials in response to the ions insertion/extraction is not known. Herein, a combination of in situ lithiation experiments and large-scale ab initio molecular dynamics simulations are performed to explore the mechanisms of the electrochemically driven solid-state amorphization in Li-Si systems. We find that local electron-rich condition governsmore » the electrochemically driven solid-state amorphization of Li-Si alloys. This discovery provides the fundamental explanation of why lithium insertion in semiconductor and insulators leads to amorphization, whereas in metals, it leads to a crystalline alloy. The present work correlates electrochemically driven reactions with ion insertion, electron transfer, lattice stability and phase equilibrium.« less

Master-slave control with trajectory planning and Bouc-Wen model for tracking control of piezo-driven stage

NASA Astrophysics Data System (ADS)

Lu, Xiaojun; Liu, Changli; Chen, Lei

2018-04-01

In this paper, a redundant Piezo-driven stage having 3RRR compliant mechanism is introduced, we propose the master-slave control with trajectory planning (MSCTP) strategy and Bouc-Wen model to improve its micro-motion tracking performance. The advantage of the proposed controller lies in that its implementation only requires a simple control strategy without the complexity of modeling to avoid the master PEA's tracking error. The dynamic model of slave PEA system with Bouc-Wen hysteresis is established and identified via particle swarm optimization (PSO) approach. The Piezo-driven stage with operating period T=1s and 2s is implemented to track a prescribed circle. The simulation results show that MSCTP with Bouc-Wen model reduces the trajectory tracking errors to the range of the accuracy of our available measurement.

Seasonal and flow-driven dynamics of particulate and dissolved mercury and methylmercury in a stream impacted by an industrial mercury source

DOE PAGES

Riscassi, Ami; Miller, Carrie; Brooks, Scott

2015-11-17

Sediments and floodplain soils in the East Fork Poplar Creek watershed (Oak Ridge, TN, USA) are contaminated with high levels of mercury (Hg) from an industrial source at the headwaters. Although baseflow conditions have been monitored, concentrations of Hg and methylmercury (MeHg) during high-flow storm events, when the stream is more hydrologically connected to the floodplain, have yet to be assessed. This paper evaluated baseflow and event-driven Hg and MeHg dynamics in East Fork Poplar Creek, 5 km upstream of the confluence with Poplar Creek, to determine the importance of hydrology to in-stream concentrations and downstream loads and to ascertainmore » whether the dynamics are comparable to those of systems without an industrial Hg source. Particulate Hg and MeHg were positively correlated with discharge (r 2 = 0.64 and 0.58, respectively) and total suspended sediment (r 2 = 0.97 and 0.89, respectively), and dissolved Hg also increased with increasing flow (r 2 = 0.18) and was associated with increases in dissolved organic carbon (r 2 = 0.65), similar to the dynamics observed in uncontaminated systems. Dissolved MeHg decreased with increases in discharge (r 2 = 0.23) and was not related to dissolved organic carbon concentrations (p = 0.56), dynamics comparable to relatively uncontaminated watersheds with a small percentage of wetlands (<10%). Finally, although stormflows exert a dominant control on particulate Hg, particulate MeHg, and dissolved Hg concentrations and loads, baseflows were associated with the highest dissolved MeHg concentration (0.38 ng/L) and represented the majority of the annual dissolved MeHg load.« less

Data-driven reverse engineering of signaling pathways using ensembles of dynamic models.

PubMed

Henriques, David; Villaverde, Alejandro F; Rocha, Miguel; Saez-Rodriguez, Julio; Banga, Julio R

2017-02-01

Despite significant efforts and remarkable progress, the inference of signaling networks from experimental data remains very challenging. The problem is particularly difficult when the objective is to obtain a dynamic model capable of predicting the effect of novel perturbations not considered during model training. The problem is ill-posed due to the nonlinear nature of these systems, the fact that only a fraction of the involved proteins and their post-translational modifications can be measured, and limitations on the technologies used for growing cells in vitro, perturbing them, and measuring their variations. As a consequence, there is a pervasive lack of identifiability. To overcome these issues, we present a methodology called SELDOM (enSEmbLe of Dynamic lOgic-based Models), which builds an ensemble of logic-based dynamic models, trains them to experimental data, and combines their individual simulations into an ensemble prediction. It also includes a model reduction step to prune spurious interactions and mitigate overfitting. SELDOM is a data-driven method, in the sense that it does not require any prior knowledge of the system: the interaction networks that act as scaffolds for the dynamic models are inferred from data using mutual information. We have tested SELDOM on a number of experimental and in silico signal transduction case-studies, including the recent HPN-DREAM breast cancer challenge. We found that its performance is highly competitive compared to state-of-the-art methods for the purpose of recovering network topology. More importantly, the utility of SELDOM goes beyond basic network inference (i.e. uncovering static interaction networks): it builds dynamic (based on ordinary differential equation) models, which can be used for mechanistic interpretations and reliable dynamic predictions in new experimental conditions (i.e. not used in the training). For this task, SELDOM's ensemble prediction is not only consistently better than predictions from individual models, but also often outperforms the state of the art represented by the methods used in the HPN-DREAM challenge.

Data-driven reverse engineering of signaling pathways using ensembles of dynamic models

PubMed Central

Henriques, David; Villaverde, Alejandro F.; Banga, Julio R.

2017-01-01

Despite significant efforts and remarkable progress, the inference of signaling networks from experimental data remains very challenging. The problem is particularly difficult when the objective is to obtain a dynamic model capable of predicting the effect of novel perturbations not considered during model training. The problem is ill-posed due to the nonlinear nature of these systems, the fact that only a fraction of the involved proteins and their post-translational modifications can be measured, and limitations on the technologies used for growing cells in vitro, perturbing them, and measuring their variations. As a consequence, there is a pervasive lack of identifiability. To overcome these issues, we present a methodology called SELDOM (enSEmbLe of Dynamic lOgic-based Models), which builds an ensemble of logic-based dynamic models, trains them to experimental data, and combines their individual simulations into an ensemble prediction. It also includes a model reduction step to prune spurious interactions and mitigate overfitting. SELDOM is a data-driven method, in the sense that it does not require any prior knowledge of the system: the interaction networks that act as scaffolds for the dynamic models are inferred from data using mutual information. We have tested SELDOM on a number of experimental and in silico signal transduction case-studies, including the recent HPN-DREAM breast cancer challenge. We found that its performance is highly competitive compared to state-of-the-art methods for the purpose of recovering network topology. More importantly, the utility of SELDOM goes beyond basic network inference (i.e. uncovering static interaction networks): it builds dynamic (based on ordinary differential equation) models, which can be used for mechanistic interpretations and reliable dynamic predictions in new experimental conditions (i.e. not used in the training). For this task, SELDOM’s ensemble prediction is not only consistently better than predictions from individual models, but also often outperforms the state of the art represented by the methods used in the HPN-DREAM challenge. PMID:28166222

A numerical investigation on the influence of engine shape and mixing processes on wave engine performance

NASA Astrophysics Data System (ADS)

Erickson, Robert R.

Wave engines are a class of unsteady, air-breathing propulsion devices that use an intermittent combustion process to generate thrust. The inherently simple mechanical design of the wave engine allows for a relatively low cost per unit propulsion system, yet unsatisfactory overall performance has severely limited the development of commercially successful wave engines. The primary objective of this investigation was to develop a more detailed physical understanding of the influence of gas dynamic nonlinearities, unsteady combustion processes, and engine shape on overall wave engine performance. Within this study, several numerical models were developed and applied to wave engines and related applications. The first portion of this investigation examined the influence of duct shape on driven oscillations in acoustic compression devices, which represent a simplified physical system closely related in several ways to the wave engine. A numerical model based on an application of the Galerkin method was developed to simulate large amplitude, one-dimensional acoustic waves driven in closed ducts. Results from this portion of the investigation showed that gas-dynamic nonlinearities significantly influence the properties of driven oscillations by transferring acoustic energy from the fundamental driven mode into higher harmonic modes. The second portion of this investigation presented and analyzed results from a numerical model of wave engine dynamics based on the quasi one-dimensional conservation equations in addition to separate sub-models for mixing and heat release. This model was then used to perform parametric studies of the characteristics of mixing and engine shape. The objectives of these studies were to determine the influence of mixing characteristics and engine shape on overall wave engine performance and to develop insight into the physical processes controlling overall performance trends. Results from this model showed that wave engine performance was strongly dependent on the coupling between the unsteady heat release that drives oscillations in the engine and the characteristics that determine the acoustic properties of the engine such as engine shape and mean property gradients. Simulation results showed that average thrust generation decreased dramatically when the natural acoustic mode frequencies of the engine and the frequency content of the unsteady heat release were not aligned.