Linking point scale process non-linearity, catchment organization and linear system dynamics in a thermodynamic state space

NASA Astrophysics Data System (ADS)

Zehe, Erwin; Loritz, Ralf; Ehret, Uwe; Westhoff, Martijn; Kleidon, Axel; Savenije, Hubert

2017-04-01

It is flabbergasting to note that catchment systems often behave almost linearly, despite of the strong non-linearity of point scale soil water characteristics. In the present study we provide evidence that a thermodynamic treatment of environmental system dynamics is the key to understand how particularly a stronger spatial organization of catchments leads to a more linear rainfall runoff behavior. Our starting point is that water fluxes in a catchment are associated with fluxes of kinetic and potential energy while changes in subsurface water stocks go along with changes in potential energy and chemical energy of subsurface water. Steady state/local equilibrium of the entire system can be defined as a state of minimum free energy, reflecting an equilibrium subsurface water storage, which is determined catchment topography, soil water characteristics and water levels in the stream. Dynamics of the entire system, i.e. deviations from equilibrium storage, are 'pseudo' oscillations in a thermodynamic state space. Either to an excess potential energy in case of wetting while subsequent relaxation back to equilibrium requires drainage/water export. Or to an excess in capillary binding energy in case of driving, while relaxation back to equilibrium requires recharge of the subsurface water stock. While system dynamics is highly non-linear on the 'too dry branch' it is essentially linear on the 'too wet branch' in case of potential energy excess. A steepened topography, which reflects a stronger spatial organization, reduces the equilibrium storage of the catchment system to smaller values, thereby it increases the range of states where the systems behaves linearly due to an excess in potential energy. Contrarily to this a shift to finer textured soils increases the equilibrium storage, which implies that the range of states where the systems behaves linearly is reduced. In this context it is important to note that an increased internal organization of the system due to an elevated density of the preferential flow paths, imply a less non-linear system behavior. This is because they avoid persistence of very dry states system states by facilitating recharge of the soil moisture stock. Based on the proposed approach we compare dynamics of four distinctly different catchments in their respective state space and demonstrate the feasibility of the approach to explain differences and similarities in their rainfall runoff regimes.

Temporal BYY encoding, Markovian state spaces, and space dimension determination.

PubMed

Xu, Lei

2004-09-01

As a complementary to those temporal coding approaches of the current major stream, this paper aims at the Markovian state space temporal models from the perspective of the temporal Bayesian Ying-Yang (BYY) learning with both new insights and new results on not only the discrete state featured Hidden Markov model and extensions but also the continuous state featured linear state spaces and extensions, especially with a new learning mechanism that makes selection of the state number or the dimension of state space either automatically during adaptive learning or subsequently after learning via model selection criteria obtained from this mechanism. Experiments are demonstrated to show how the proposed approach works.

Quasi-Newton methods for parameter estimation in functional differential equations

NASA Technical Reports Server (NTRS)

Brewer, Dennis W.

1988-01-01

A state-space approach to parameter estimation in linear functional differential equations is developed using the theory of linear evolution equations. A locally convergent quasi-Newton type algorithm is applied to distributed systems with particular emphasis on parameters that induce unbounded perturbations of the state. The algorithm is computationally implemented on several functional differential equations, including coefficient and delay estimation in linear delay-differential equations.

A Sequential Ensemble Prediction System at Convection Permitting Scales

NASA Astrophysics Data System (ADS)

Milan, M.; Simmer, C.

2012-04-01

A Sequential Assimilation Method (SAM) following some aspects of particle filtering with resampling, also called SIR (Sequential Importance Resampling), is introduced and applied in the framework of an Ensemble Prediction System (EPS) for weather forecasting on convection permitting scales, with focus to precipitation forecast. At this scale and beyond, the atmosphere increasingly exhibits chaotic behaviour and non linear state space evolution due to convectively driven processes. One way to take full account of non linear state developments are particle filter methods, their basic idea is the representation of the model probability density function by a number of ensemble members weighted by their likelihood with the observations. In particular particle filter with resampling abandons ensemble members (particles) with low weights restoring the original number of particles adding multiple copies of the members with high weights. In our SIR-like implementation we substitute the likelihood way to define weights and introduce a metric which quantifies the "distance" between the observed atmospheric state and the states simulated by the ensemble members. We also introduce a methodology to counteract filter degeneracy, i.e. the collapse of the simulated state space. To this goal we propose a combination of resampling taking account of simulated state space clustering and nudging. By keeping cluster representatives during resampling and filtering, the method maintains the potential for non linear system state development. We assume that a particle cluster with initially low likelihood may evolve in a state space with higher likelihood in a subsequent filter time thus mimicking non linear system state developments (e.g. sudden convection initiation) and remedies timing errors for convection due to model errors and/or imperfect initial condition. We apply a simplified version of the resampling, the particles with highest weights in each cluster are duplicated; for the model evolution for each particle pair one particle evolves using the forward model; the second particle, however, is nudged to the radar and satellite observation during its evolution based on the forward model.

Multivariable control of the Space Shuttle Remote Manipulator System using linearization by state feedback

NASA Technical Reports Server (NTRS)

Gettman, Chang-Ching L.; Adams, Neil; Bedrossian, Nazareth; Valavani, Lena

1993-01-01

This paper demonstrates an approach to nonlinear control system design that uses linearization by state feedback to allow faster maneuvering of payloads by the Shuttle Remote Manipulator System (SRMS). A nonlinear feedback law is defined to cancel the nonlinear plant dynamics so that a linear controller can be designed for the SRMS. First a nonlinear design model was generated via SIMULINK. This design model included nonlinear arm dynamics derived from the Lagrangian approach, linearized servo model, and linearized gearbox model. The current SRMS position hold controller was implemented on this system. Next, a trajectory was defined using a rigid body kinematics SRMS tool, KRMS. The maneuver was simulated. Finally, higher bandwidth controllers were developed. Results of the new controllers were compared with the existing SRMS automatic control modes for the Space Station Freedom Mission Build 4 Payload extended on the SRMS.

On Markov parameters in system identification

NASA Technical Reports Server (NTRS)

Phan, Minh; Juang, Jer-Nan; Longman, Richard W.

1991-01-01

A detailed discussion of Markov parameters in system identification is given. Different forms of input-output representation of linear discrete-time systems are reviewed and discussed. Interpretation of sampled response data as Markov parameters is presented. Relations between the state-space model and particular linear difference models via the Markov parameters are formulated. A generalization of Markov parameters to observer and Kalman filter Markov parameters for system identification is explained. These extended Markov parameters play an important role in providing not only a state-space realization, but also an observer/Kalman filter for the system of interest.

Linear State-Space Representation of the Dynamics of Relative Motion, Based on Restricted Three Body Dynamics

NASA Technical Reports Server (NTRS)

Luquette,Richard J.; Sanner, Robert M.

2004-01-01

Precision Formation Flying is an enabling technology for a variety of proposed space-based observatories, including the Micro-Arcsecond X-ray Imaging Mission (MAXIM) , the associated MAXIM pathfinder mission, Stellar Imager (SI) and the Terrestrial Planet Finder (TPF). An essential element of the technology is the control algorithm, requiring a clear understanding of the dynamics of relative motion. This paper examines the dynamics of relative motion in the context of the Restricted Three Body Problem (RTBP). The natural dynamics of relative motion are presented in their full nonlinear form. Motivated by the desire to apply linear control methods, the dynamics equations are linearized and presented in state-space form. The stability properties are explored for regions in proximity to each of the libration points in the Earth/Moon - Sun rotating frame. The dynamics of relative motion are presented in both the inertial and rotating coordinate frames.

The Biharmonic Oscillator and Asymmetric Linear Potentials: From Classical Trajectories to Momentum-Space Probability Densities in the Extreme Quantum Limit

ERIC Educational Resources Information Center

Ruckle, L. J.; Belloni, M.; Robinett, R. W.

2012-01-01

The biharmonic oscillator and the asymmetric linear well are two confining power-law-type potentials for which complete bound-state solutions are possible in both classical and quantum mechanics. We examine these problems in detail, beginning with studies of their trajectories in position and momentum space, evaluation of the classical probability…

Brownian motion with adaptive drift for remaining useful life prediction: Revisited

NASA Astrophysics Data System (ADS)

Wang, Dong; Tsui, Kwok-Leung

2018-01-01

Linear Brownian motion with constant drift is widely used in remaining useful life predictions because its first hitting time follows the inverse Gaussian distribution. State space modelling of linear Brownian motion was proposed to make the drift coefficient adaptive and incorporate on-line measurements into the first hitting time distribution. Here, the drift coefficient followed the Gaussian distribution, and it was iteratively estimated by using Kalman filtering once a new measurement was available. Then, to model nonlinear degradation, linear Brownian motion with adaptive drift was extended to nonlinear Brownian motion with adaptive drift. However, in previous studies, an underlying assumption used in the state space modelling was that in the update phase of Kalman filtering, the predicted drift coefficient at the current time exactly equalled the posterior drift coefficient estimated at the previous time, which caused a contradiction with the predicted drift coefficient evolution driven by an additive Gaussian process noise. In this paper, to alleviate such an underlying assumption, a new state space model is constructed. As a result, in the update phase of Kalman filtering, the predicted drift coefficient at the current time evolves from the posterior drift coefficient at the previous time. Moreover, the optimal Kalman filtering gain for iteratively estimating the posterior drift coefficient at any time is mathematically derived. A discussion that theoretically explains the main reasons why the constructed state space model can result in high remaining useful life prediction accuracies is provided. Finally, the proposed state space model and its associated Kalman filtering gain are applied to battery prognostics.

State-Dependent Pseudo-Linear Filter for Spacecraft Attitude and Rate Estimation

NASA Technical Reports Server (NTRS)

Bar-Itzhack, Itzhack Y.; Harman, Richard R.

2001-01-01

This paper presents the development and performance of a special algorithm for estimating the attitude and angular rate of a spacecraft. The algorithm is a pseudo-linear Kalman filter, which is an ordinary linear Kalman filter that operates on a linear model whose matrices are current state estimate dependent. The nonlinear rotational dynamics equation of the spacecraft is presented in the state space as a state-dependent linear system. Two types of measurements are considered. One type is a measurement of the quaternion of rotation, which is obtained from a newly introduced star tracker based apparatus. The other type of measurement is that of vectors, which permits the use of a variety of vector measuring sensors like sun sensors and magnetometers. While quaternion measurements are related linearly to the state vector, vector measurements constitute a nonlinear function of the state vector. Therefore, in this paper, a state-dependent linear measurement equation is developed for the vector measurement case. The state-dependent pseudo linear filter is applied to simulated spacecraft rotations and adequate estimates of the spacecraft attitude and rate are obtained for the case of quaternion measurements as well as of vector measurements.

Transfer matrix method for dynamics modeling and independent modal space vibration control design of linear hybrid multibody system

NASA Astrophysics Data System (ADS)

Rong, Bao; Rui, Xiaoting; Lu, Kun; Tao, Ling; Wang, Guoping; Ni, Xiaojun

2018-05-01

In this paper, an efficient method of dynamics modeling and vibration control design of a linear hybrid multibody system (MS) is studied based on the transfer matrix method. The natural vibration characteristics of a linear hybrid MS are solved by using low-order transfer equations. Then, by constructing the brand-new body dynamics equation, augmented operator and augmented eigenvector, the orthogonality of augmented eigenvector of a linear hybrid MS is satisfied, and its state space model expressed in each independent model space is obtained easily. According to this dynamics model, a robust independent modal space-fuzzy controller is designed for vibration control of a general MS, and the genetic optimization of some critical control parameters of fuzzy tuners is also presented. Two illustrative examples are performed, which results show that this method is computationally efficient and with perfect control performance.

Engineering multiphoton states for linear optics computation

NASA Astrophysics Data System (ADS)

Aniello, P.; Lupo, C.; Napolitano, M.; Paris, M. G. A.

2007-03-01

Transformations achievable by linear optical components allow to generate the whole unitary group only when restricted to the one-photon subspace of a multimode Fock space. In this paper, we address the more general problem of encoding quantum information by multiphoton states, and elaborating it via ancillary extensions, linear optical passive devices and photodetection. Our scheme stems in a natural way from the mathematical structures underlying the physics of linear optical passive devices. In particular, we analyze an economical procedure for mapping a fiducial 2-photon 2-mode state into an arbitrary 2-photon 2-mode state using ancillary resources and linear optical passive N-ports assisted by post-selection. We found that adding a single ancilla mode is enough to generate any desired target state. The effect of imperfect photodetection in post-selection is considered and a simple trade-off between success probability and fidelity is derived.

A Fast Solver for Implicit Integration of the Vlasov--Poisson System in the Eulerian Framework

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

Garrett, C. Kristopher; Hauck, Cory D.

In this paper, we present a domain decomposition algorithm to accelerate the solution of Eulerian-type discretizations of the linear, steady-state Vlasov equation. The steady-state solver then forms a key component in the implementation of fully implicit or nearly fully implicit temporal integrators for the nonlinear Vlasov--Poisson system. The solver relies on a particular decomposition of phase space that enables the use of sweeping techniques commonly used in radiation transport applications. The original linear system for the phase space unknowns is then replaced by a smaller linear system involving only unknowns on the boundary between subdomains, which can then be solvedmore » efficiently with Krylov methods such as GMRES. Steady-state solves are combined to form an implicit Runge--Kutta time integrator, and the Vlasov equation is coupled self-consistently to the Poisson equation via a linearized procedure or a nonlinear fixed-point method for the electric field. Finally, numerical results for standard test problems demonstrate the efficiency of the domain decomposition approach when compared to the direct application of an iterative solver to the original linear system.« less

A Fast Solver for Implicit Integration of the Vlasov--Poisson System in the Eulerian Framework

DOE PAGES

Garrett, C. Kristopher; Hauck, Cory D.

2018-04-05

In this paper, we present a domain decomposition algorithm to accelerate the solution of Eulerian-type discretizations of the linear, steady-state Vlasov equation. The steady-state solver then forms a key component in the implementation of fully implicit or nearly fully implicit temporal integrators for the nonlinear Vlasov--Poisson system. The solver relies on a particular decomposition of phase space that enables the use of sweeping techniques commonly used in radiation transport applications. The original linear system for the phase space unknowns is then replaced by a smaller linear system involving only unknowns on the boundary between subdomains, which can then be solvedmore » efficiently with Krylov methods such as GMRES. Steady-state solves are combined to form an implicit Runge--Kutta time integrator, and the Vlasov equation is coupled self-consistently to the Poisson equation via a linearized procedure or a nonlinear fixed-point method for the electric field. Finally, numerical results for standard test problems demonstrate the efficiency of the domain decomposition approach when compared to the direct application of an iterative solver to the original linear system.« less

Evaluating abundance and trends in a Hawaiian avian community using state-space analysis

USGS Publications Warehouse

Camp, Richard J.; Brinck, Kevin W.; Gorresen, P.M.; Paxton, Eben H.

2016-01-01

Estimating population abundances and patterns of change over time are important in both ecology and conservation. Trend assessment typically entails fitting a regression to a time series of abundances to estimate population trajectory. However, changes in abundance estimates from year-to-year across time are due to both true variation in population size (process variation) and variation due to imperfect sampling and model fit. State-space models are a relatively new method that can be used to partition the error components and quantify trends based only on process variation. We compare a state-space modelling approach with a more traditional linear regression approach to assess trends in uncorrected raw counts and detection-corrected abundance estimates of forest birds at Hakalau Forest National Wildlife Refuge, Hawai‘i. Most species demonstrated similar trends using either method. In general, evidence for trends using state-space models was less strong than for linear regression, as measured by estimates of precision. However, while the state-space models may sacrifice precision, the expectation is that these estimates provide a better representation of the real world biological processes of interest because they are partitioning process variation (environmental and demographic variation) and observation variation (sampling and model variation). The state-space approach also provides annual estimates of abundance which can be used by managers to set conservation strategies, and can be linked to factors that vary by year, such as climate, to better understand processes that drive population trends.

Neural network-based nonlinear model predictive control vs. linear quadratic gaussian control

USGS Publications Warehouse

Cho, C.; Vance, R.; Mardi, N.; Qian, Z.; Prisbrey, K.

1997-01-01

One problem with the application of neural networks to the multivariable control of mineral and extractive processes is determining whether and how to use them. The objective of this investigation was to compare neural network control to more conventional strategies and to determine if there are any advantages in using neural network control in terms of set-point tracking, rise time, settling time, disturbance rejection and other criteria. The procedure involved developing neural network controllers using both historical plant data and simulation models. Various control patterns were tried, including both inverse and direct neural network plant models. These were compared to state space controllers that are, by nature, linear. For grinding and leaching circuits, a nonlinear neural network-based model predictive control strategy was superior to a state space-based linear quadratic gaussian controller. The investigation pointed out the importance of incorporating state space into neural networks by making them recurrent, i.e., feeding certain output state variables into input nodes in the neural network. It was concluded that neural network controllers can have better disturbance rejection, set-point tracking, rise time, settling time and lower set-point overshoot, and it was also concluded that neural network controllers can be more reliable and easy to implement in complex, multivariable plants.

Numerical approximation for the infinite-dimensional discrete-time optimal linear-quadratic regulator problem

NASA Technical Reports Server (NTRS)

Gibson, J. S.; Rosen, I. G.

1986-01-01

An abstract approximation framework is developed for the finite and infinite time horizon discrete-time linear-quadratic regulator problem for systems whose state dynamics are described by a linear semigroup of operators on an infinite dimensional Hilbert space. The schemes included the framework yield finite dimensional approximations to the linear state feedback gains which determine the optimal control law. Convergence arguments are given. Examples involving hereditary and parabolic systems and the vibration of a flexible beam are considered. Spline-based finite element schemes for these classes of problems, together with numerical results, are presented and discussed.

Thermodynamic output of single-atom quantum optical amplifiers and their phase-space fingerprint

NASA Astrophysics Data System (ADS)

Perl, Y.; Band, Y. B.; Boukobza, E.

2017-05-01

We analyze a resonant single-atom two-photon quantum optical amplifier both dynamically and thermodynamically. A detailed thermodynamic analysis shows that the nonlinear amplifier is thermodynamically equivalent to the linear amplifier. However, by calculating the Wigner quasiprobability distribution for various initial field states, we show that unique quantum features in optical phase space, absent in the linear amplifier, are retained for extended times, despite the fact that dissipation tends to wash out dynamical features observed at early evolution times. These features are related to the discrete nature of the two-photon matter-field interaction and fingerprint the initial field state at thermodynamic times.

Method of performing computational aeroelastic analyses

NASA Technical Reports Server (NTRS)

Silva, Walter A. (Inventor)

2011-01-01

Computational aeroelastic analyses typically use a mathematical model for the structural modes of a flexible structure and a nonlinear aerodynamic model that can generate a plurality of unsteady aerodynamic responses based on the structural modes for conditions defining an aerodynamic condition of the flexible structure. In the present invention, a linear state-space model is generated using a single execution of the nonlinear aerodynamic model for all of the structural modes where a family of orthogonal functions is used as the inputs. Then, static and dynamic aeroelastic solutions are generated using computational interaction between the mathematical model and the linear state-space model for a plurality of periodic points in time.

A linear quadratic tracker for Control Moment Gyro based attitude control of the Space Station

NASA Technical Reports Server (NTRS)

Kaidy, J. T.

1986-01-01

The paper discusses a design for an attitude control system for the Space Station which produces fast response, with minimal overshoot and cross-coupling with the use of Control Moment Gyros (CMG). The rigid body equations of motion are linearized and discretized and a Linear Quadratic Regulator (LQR) design and analysis study is performed. The resulting design is then modified such that integral and differential terms are added to the state equations to enhance response characteristics. Methods for reduction of computation time through channelization are discussed as well as the reduction of initial torque requirements.

Visualizing the inner product space ℝm×n in a MATLAB-assisted linear algebra classroom

NASA Astrophysics Data System (ADS)

Caglayan, Günhan

2018-05-01

This linear algebra note offers teaching and learning ideas in the treatment of the inner product space ? in a technology-supported learning environment. Classroom activities proposed in this note demonstrate creative ways of integrating MATLAB technology into various properties of Frobenius inner product as visualization tools that complement the algebraic approach. As implemented in linear algebra lessons in a university in the Unites States, the article also incorporates algebraic and visual work of students who experienced these activities with MATLAB software. The connection between the Frobenius norm and the Euclidean norm is also emphasized.

Hybrid Discrete-Continuous Markov Decision Processes

NASA Technical Reports Server (NTRS)

Feng, Zhengzhu; Dearden, Richard; Meuleau, Nicholas; Washington, Rich

2003-01-01

This paper proposes a Markov decision process (MDP) model that features both discrete and continuous state variables. We extend previous work by Boyan and Littman on the mono-dimensional time-dependent MDP to multiple dimensions. We present the principle of lazy discretization, and piecewise constant and linear approximations of the model. Having to deal with several continuous dimensions raises several new problems that require new solutions. In the (piecewise) linear case, we use techniques from partially- observable MDPs (POMDPS) to represent value functions as sets of linear functions attached to different partitions of the state space.

A general U-block model-based design procedure for nonlinear polynomial control systems

NASA Astrophysics Data System (ADS)

Zhu, Q. M.; Zhao, D. Y.; Zhang, Jianhua

2016-10-01

The proposition of U-model concept (in terms of 'providing concise and applicable solutions for complex problems') and a corresponding basic U-control design algorithm was originated in the first author's PhD thesis. The term of U-model appeared (not rigorously defined) for the first time in the first author's other journal paper, which established a framework for using linear polynomial control system design approaches to design nonlinear polynomial control systems (in brief, linear polynomial approaches → nonlinear polynomial plants). This paper represents the next milestone work - using linear state-space approaches to design nonlinear polynomial control systems (in brief, linear state-space approaches → nonlinear polynomial plants). The overall aim of the study is to establish a framework, defined as the U-block model, which provides a generic prototype for using linear state-space-based approaches to design the control systems with smooth nonlinear plants/processes described by polynomial models. For analysing the feasibility and effectiveness, sliding mode control design approach is selected as an exemplary case study. Numerical simulation studies provide a user-friendly step-by-step procedure for the readers/users with interest in their ad hoc applications. In formality, this is the first paper to present the U-model-oriented control system design in a formal way and to study the associated properties and theorems. The previous publications, in the main, have been algorithm-based studies and simulation demonstrations. In some sense, this paper can be treated as a landmark for the U-model-based research from intuitive/heuristic stage to rigour/formal/comprehensive studies.

Multivariable control of the Space Shuttle Remote Manipulator System using linearization by state feedback. M.S. Thesis

NASA Technical Reports Server (NTRS)

Gettman, Chang-Ching LO

1993-01-01

This thesis develops and demonstrates an approach to nonlinear control system design using linearization by state feedback. The design provides improved transient response behavior allowing faster maneuvering of payloads by the SRMS. Modeling uncertainty is accounted for by using a second feedback loop designed around the feedback linearized dynamics. A classical feedback loop is developed to provide the easy implementation required for the relatively small on board computers. Feedback linearization also allows the use of higher bandwidth model based compensation in the outer loop, since it helps maintain stability in the presence of the nonlinearities typically neglected in model based designs.

Highway traffic estimation of improved precision using the derivative-free nonlinear Kalman Filter

NASA Astrophysics Data System (ADS)

Rigatos, Gerasimos; Siano, Pierluigi; Zervos, Nikolaos; Melkikh, Alexey

2015-12-01

The paper proves that the PDE dynamic model of the highway traffic is a differentially flat one and by applying spatial discretization its shows that the model's transformation into an equivalent linear canonical state-space form is possible. For the latter representation of the traffic's dynamics, state estimation is performed with the use of the Derivative-free nonlinear Kalman Filter. The proposed filter consists of the Kalman Filter recursion applied on the transformed state-space model of the highway traffic. Moreover, it makes use of an inverse transformation, based again on differential flatness theory which enables to obtain estimates of the state variables of the initial nonlinear PDE model. By avoiding approximate linearizations and the truncation of nonlinear terms from the PDE model of the traffic's dynamics the proposed filtering methods outperforms, in terms of accuracy, other nonlinear estimators such as the Extended Kalman Filter. The article's theoretical findings are confirmed through simulation experiments.

Performance and reliability enhancement of linear coolers

NASA Astrophysics Data System (ADS)

Mai, M.; Rühlich, I.; Schreiter, A.; Zehner, S.

2010-04-01

Highest efficiency states a crucial requirement for modern tactical IR cryocooling systems. For enhancement of overall efficiency, AIM cryocooler designs where reassessed considering all relevant loss mechanisms and associated components. Performed investigation was based on state-of-the-art simulation software featuring magnet circuitry analysis as well as computational fluid dynamics (CFD) to realistically replicate thermodynamic interactions. As a result, an improved design for AIM linear coolers could be derived. This paper gives an overview on performance enhancement activities and major results. An additional key-requirement for cryocoolers is reliability. In recent time, AIM has introduced linear coolers with full Flexure Bearing suspension on both ends of the driving mechanism incorporating Moving Magnet piston drive. In conjunction with a Pulse-Tube coldfinger these coolers are capable of meeting MTTF's (Mean Time To Failure) in excess of 50,000 hours offering superior reliability for space applications. Ongoing development also focuses on reliability enhancement, deriving space technology into tactical solutions combining both, excelling specific performance with space like reliability. Concerned publication will summarize the progress of this reliability program and give further prospect.

Near-complete teleportation of a superposed coherent state

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

Cheong, Yong Wook; Kim, Hyunjae; Lee, Hai-Woong

2004-09-01

The four Bell-type entangled coherent states, {alpha}>-{alpha}>{+-}-{alpha}>{alpha}> and {alpha}>{alpha}>{+-}-{alpha}>-{alpha}>, can be discriminated with a high probability using only linear optical means, as long as {alpha} is not too small. Based on this observation, we propose a simple scheme to almost completely teleport a superposed coherent state. The nonunitary transformation that is required to complete the teleportation can be achieved by embedding the receiver's field state in a larger Hilbert space consisting of the field and a single atom and performing a unitary transformation on this Hilbert space00.

An algebraic structure of discrete-time biaffine systems

NASA Technical Reports Server (NTRS)

Tarn, T.-J.; Nonoyama, S.

1979-01-01

New results on the realization of finite-dimensional, discrete-time, internally biaffine systems are presented in this paper. The external behavior of such systems is described by multiaffine functions and the state space is constructed via Nerode equivalence relations. We prove that the state space is an affine space. An algorithm which amounts to choosing a frame for the affine space is presented. Our algorithm reduces in the linear and bilinear case to a generalization of algorithms existing in the literature. Explicit existence criteria for span-canonical realizations as well as an affine isomorphism theorem are given.

Phase space information in a non-linear quantum system containing a Kerr-like medium through Su(1, 1)-algebraic treatment

NASA Astrophysics Data System (ADS)

Mohamed, Abdel-Baset A.

2018-05-01

Analytical description for a Su(2)-quantum system interacting with a damped Su(1, 1)-cavity, which is filled with a non-linear Kerr medium, is presented. The dynamics of non-classicality of Su(1, 1)-state is investigated via the negative part of the Wigner function. We show that the negative part depends on the unitary interaction and the Kerr-like medium and it can be disappeared by increasing the dissipation rate and the detuning parameter. The phase space information of the Husimi function and its Wehrl density is very sensitive not only to the coupling to the environment and the unitary interaction but also to the detuning as well as to the Kerr-like medium. The phase space information may be completely erased by increasing the coupling to the environment. The coherence loss of the Su(2)-state is investigated via the Husimi Wehrl entropy. If the effects of the detuning parameter or/and of the Kerr-like medium are combined with the damping effect, the damping effect of the coupling to the environment may be weaken, and the Wehrl entropy is delayed to reach its steady-state value. At the steady-state value, the phase space information and the coherence are quickly lost.

Recent Developments In Theory Of Balanced Linear Systems

NASA Technical Reports Server (NTRS)

Gawronski, Wodek

1994-01-01

Report presents theoretical study of some issues of controllability and observability of system represented by linear, time-invariant mathematical model of the form. x = Ax + Bu, y = Cx + Du, x(0) = xo where x is n-dimensional vector representing state of system; u is p-dimensional vector representing control input to system; y is q-dimensional vector representing output of system; n,p, and q are integers; x(0) is intial (zero-time) state vector; and set of matrices (A,B,C,D) said to constitute state-space representation of system.

Feedback-Equivalence of Nonlinear Systems with Applications to Power System Equations.

NASA Astrophysics Data System (ADS)

Marino, Riccardo

The key concept of the dissertation is feedback equivalence among systems affine in control. Feedback equivalence to linear systems in Brunovsky canonical form and the construction of the corresponding feedback transformation are used to: (i) design a nonlinear regulator for a detailed nonlinear model of a synchronous generator connected to an infinite bus; (ii) establish which power system network structures enjoy the feedback linearizability property and design a stabilizing control law for these networks with a constraint on the control space which comes from the use of d.c. lines. It is also shown that the feedback linearizability property allows the use of state feedback to contruct a linear controllable system with a positive definite linear Hamiltonian structure for the uncontrolled part if the state space is even; a stabilizing control law is derived for such systems. Feedback linearizability property is characterized by the involutivity of certain nested distributions for strongly accessible analytic systems; if the system is defined on a manifold M diffeomorphic to the Euclidean space, it is established that the set where the property holds is a submanifold open and dense in M. If an analytic output map is defined, a set of nested involutive distributions can be always defined and that allows the introduction of an observability property which is the dual concept, in some sense, to feedback linearizability: the goal is to investigate when a nonlinear system affine in control with an analytic output map is feedback equivalent to a linear controllable and observable system. Finally a nested involutive structure of distributions is shown to guarantee the existence of a state feedback that takes a nonlinear system affine in control to a single input one, both feedback equivalent to linear controllable systems, preserving one controlled vector field.

Essential uncontrollability of discrete linear, time-invariant, dynamical systems

NASA Technical Reports Server (NTRS)

Cliff, E. M.

1975-01-01

The concept of a 'best approximating m-dimensional subspace' for a given set of vectors in n-dimensional whole space is introduced. Such a subspace is easily described in terms of the eigenvectors of an associated Gram matrix. This technique is used to approximate an achievable set for a discrete linear time-invariant dynamical system. This approximation characterizes the part of the state space that may be reached using modest levels of control. If the achievable set can be closely approximated by a proper subspace of the whole space then the system is 'essentially uncontrollable'. The notion finds application in studies of failure-tolerant systems, and in decoupling.

Accelerating molecular property calculations with nonorthonormal Krylov space methods

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

Furche, Filipp; Krull, Brandon T.; Nguyen, Brian D.

Here, we formulate Krylov space methods for large eigenvalue problems and linear equation systems that take advantage of decreasing residual norms to reduce the cost of matrix-vector multiplication. The residuals are used as subspace basis without prior orthonormalization, which leads to generalized eigenvalue problems or linear equation systems on the Krylov space. These nonorthonormal Krylov space (nKs) algorithms are favorable for large matrices with irregular sparsity patterns whose elements are computed on the fly, because fewer operations are necessary as the residual norm decreases as compared to the conventional method, while errors in the desired eigenpairs and solution vectors remainmore » small. We consider real symmetric and symplectic eigenvalue problems as well as linear equation systems and Sylvester equations as they appear in configuration interaction and response theory. The nKs method can be implemented in existing electronic structure codes with minor modifications and yields speed-ups of 1.2-1.8 in typical time-dependent Hartree-Fock and density functional applications without accuracy loss. The algorithm can compute entire linear subspaces simultaneously which benefits electronic spectra and force constant calculations requiring many eigenpairs or solution vectors. The nKs approach is related to difference density methods in electronic ground state calculations, and particularly efficient for integral direct computations of exchange-type contractions. By combination with resolution-of-the-identity methods for Coulomb contractions, three- to fivefold speed-ups of hybrid time-dependent density functional excited state and response calculations are achieved.« less

Accelerating molecular property calculations with nonorthonormal Krylov space methods

DOE PAGES

Furche, Filipp; Krull, Brandon T.; Nguyen, Brian D.; ...

2016-05-03

Here, we formulate Krylov space methods for large eigenvalue problems and linear equation systems that take advantage of decreasing residual norms to reduce the cost of matrix-vector multiplication. The residuals are used as subspace basis without prior orthonormalization, which leads to generalized eigenvalue problems or linear equation systems on the Krylov space. These nonorthonormal Krylov space (nKs) algorithms are favorable for large matrices with irregular sparsity patterns whose elements are computed on the fly, because fewer operations are necessary as the residual norm decreases as compared to the conventional method, while errors in the desired eigenpairs and solution vectors remainmore » small. We consider real symmetric and symplectic eigenvalue problems as well as linear equation systems and Sylvester equations as they appear in configuration interaction and response theory. The nKs method can be implemented in existing electronic structure codes with minor modifications and yields speed-ups of 1.2-1.8 in typical time-dependent Hartree-Fock and density functional applications without accuracy loss. The algorithm can compute entire linear subspaces simultaneously which benefits electronic spectra and force constant calculations requiring many eigenpairs or solution vectors. The nKs approach is related to difference density methods in electronic ground state calculations, and particularly efficient for integral direct computations of exchange-type contractions. By combination with resolution-of-the-identity methods for Coulomb contractions, three- to fivefold speed-ups of hybrid time-dependent density functional excited state and response calculations are achieved.« less

Visual Tracking via Sparse and Local Linear Coding.

PubMed

Wang, Guofeng; Qin, Xueying; Zhong, Fan; Liu, Yue; Li, Hongbo; Peng, Qunsheng; Yang, Ming-Hsuan

2015-11-01

The state search is an important component of any object tracking algorithm. Numerous algorithms have been proposed, but stochastic sampling methods (e.g., particle filters) are arguably one of the most effective approaches. However, the discretization of the state space complicates the search for the precise object location. In this paper, we propose a novel tracking algorithm that extends the state space of particle observations from discrete to continuous. The solution is determined accurately via iterative linear coding between two convex hulls. The algorithm is modeled by an optimal function, which can be efficiently solved by either convex sparse coding or locality constrained linear coding. The algorithm is also very flexible and can be combined with many generic object representations. Thus, we first use sparse representation to achieve an efficient searching mechanism of the algorithm and demonstrate its accuracy. Next, two other object representation models, i.e., least soft-threshold squares and adaptive structural local sparse appearance, are implemented with improved accuracy to demonstrate the flexibility of our algorithm. Qualitative and quantitative experimental results demonstrate that the proposed tracking algorithm performs favorably against the state-of-the-art methods in dynamic scenes.

Dynamic Stability Analysis of Linear Time-varying Systems via an Extended Modal Identification Approach

NASA Astrophysics Data System (ADS)

Ma, Zhisai; Liu, Li; Zhou, Sida; Naets, Frank; Heylen, Ward; Desmet, Wim

2017-03-01

The problem of linear time-varying(LTV) system modal analysis is considered based on time-dependent state space representations, as classical modal analysis of linear time-invariant systems and current LTV system modal analysis under the "frozen-time" assumption are not able to determine the dynamic stability of LTV systems. Time-dependent state space representations of LTV systems are first introduced, and the corresponding modal analysis theories are subsequently presented via a stability-preserving state transformation. The time-varying modes of LTV systems are extended in terms of uniqueness, and are further interpreted to determine the system's stability. An extended modal identification is proposed to estimate the time-varying modes, consisting of the estimation of the state transition matrix via a subspace-based method and the extraction of the time-varying modes by the QR decomposition. The proposed approach is numerically validated by three numerical cases, and is experimentally validated by a coupled moving-mass simply supported beam experimental case. The proposed approach is capable of accurately estimating the time-varying modes, and provides a new way to determine the dynamic stability of LTV systems by using the estimated time-varying modes.

Phylogenetic mixtures and linear invariants for equal input models.

PubMed

Casanellas, Marta; Steel, Mike

2017-04-01

The reconstruction of phylogenetic trees from molecular sequence data relies on modelling site substitutions by a Markov process, or a mixture of such processes. In general, allowing mixed processes can result in different tree topologies becoming indistinguishable from the data, even for infinitely long sequences. However, when the underlying Markov process supports linear phylogenetic invariants, then provided these are sufficiently informative, the identifiability of the tree topology can be restored. In this paper, we investigate a class of processes that support linear invariants once the stationary distribution is fixed, the 'equal input model'. This model generalizes the 'Felsenstein 1981' model (and thereby the Jukes-Cantor model) from four states to an arbitrary number of states (finite or infinite), and it can also be described by a 'random cluster' process. We describe the structure and dimension of the vector spaces of phylogenetic mixtures and of linear invariants for any fixed phylogenetic tree (and for all trees-the so called 'model invariants'), on any number n of leaves. We also provide a precise description of the space of mixtures and linear invariants for the special case of [Formula: see text] leaves. By combining techniques from discrete random processes and (multi-) linear algebra, our results build on a classic result that was first established by James Lake (Mol Biol Evol 4:167-191, 1987).

A characterization of positive linear maps and criteria of entanglement for quantum states

NASA Astrophysics Data System (ADS)

Hou, Jinchuan

2010-09-01

Let H and K be (finite- or infinite-dimensional) complex Hilbert spaces. A characterization of positive completely bounded normal linear maps from {\\mathcal B}(H) into {\\mathcal B}(K) is given, which particularly gives a characterization of positive elementary operators including all positive linear maps between matrix algebras. This characterization is then applied to give a representation of quantum channels (operations) between infinite-dimensional systems. A necessary and sufficient criterion of separability is given which shows that a state ρ on HotimesK is separable if and only if (ΦotimesI)ρ >= 0 for all positive finite-rank elementary operators Φ. Examples of NCP and indecomposable positive linear maps are given and are used to recognize some entangled states that cannot be recognized by the PPT criterion and the realignment criterion.

Solving rational matrix equations in the state space with applications to computer-aided control-system design

NASA Technical Reports Server (NTRS)

Packard, A. K.; Sastry, S. S.

1986-01-01

A method of solving a class of linear matrix equations over various rings is proposed, using results from linear geometric control theory. An algorithm, successfully implemented, is presented, along with non-trivial numerical examples. Applications of the method to the algebraic control system design methodology are discussed.

Cluster-type entangled coherent states: Generation and application

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

An, Nguyen Ba; Kim, Jaewan; Korea Institute for Advanced Study, 207-43 Cheongryangni 2-dong, Dongdaemun-gu, Seoul 130-722

2009-10-15

We consider a type of (M+N)-mode entangled coherent states and propose a simple deterministic scheme to generate these states that can fly freely in space. We then exploit such free-flying states to teleport certain kinds of superpositions of multimode coherent states. We also address the issue of manipulating size and type of entangled coherent states by means of linear optics elements only.

Cluster-type entangled coherent states: Generation and application

NASA Astrophysics Data System (ADS)

An, Nguyen Ba; Kim, Jaewan

2009-10-01

We consider a type of (M+N) -mode entangled coherent states and propose a simple deterministic scheme to generate these states that can fly freely in space. We then exploit such free-flying states to teleport certain kinds of superpositions of multimode coherent states. We also address the issue of manipulating size and type of entangled coherent states by means of linear optics elements only.

Robust root clustering for linear uncertain systems using generalized Lyapunov theory

NASA Technical Reports Server (NTRS)

Yedavalli, R. K.

1993-01-01

Consideration is given to the problem of matrix root clustering in subregions of a complex plane for linear state space models with real parameter uncertainty. The nominal matrix root clustering theory of Gutman & Jury (1981) using the generalized Liapunov equation is extended to the perturbed matrix case, and bounds are derived on the perturbation to maintain root clustering inside a given region. The theory makes it possible to obtain an explicit relationship between the parameters of the root clustering region and the uncertainty range of the parameter space.

Regional robust stabilisation and domain-of-attraction estimation for MIMO uncertain nonlinear systems with input saturation

NASA Astrophysics Data System (ADS)

Azizi, S.; Torres, L. A. B.; Palhares, R. M.

2018-01-01

The regional robust stabilisation by means of linear time-invariant state feedback control for a class of uncertain MIMO nonlinear systems with parametric uncertainties and control input saturation is investigated. The nonlinear systems are described in a differential algebraic representation and the regional stability is handled considering the largest ellipsoidal domain-of-attraction (DOA) inside a given polytopic region in the state space. A novel set of sufficient Linear Matrix Inequality (LMI) conditions with new auxiliary decision variables are developed aiming to design less conservative linear state feedback controllers with corresponding larger DOAs, by considering the polytopic description of the saturated inputs. A few examples are presented showing favourable comparisons with recently published similar control design methodologies.

Space Shuttle propulsion parameter estimation using optimal estimation techniques, volume 1

NASA Technical Reports Server (NTRS)

1983-01-01

The mathematical developments and their computer program implementation for the Space Shuttle propulsion parameter estimation project are summarized. The estimation approach chosen is the extended Kalman filtering with a modified Bryson-Frazier smoother. Its use here is motivated by the objective of obtaining better estimates than those available from filtering and to eliminate the lag associated with filtering. The estimation technique uses as the dynamical process the six degree equations-of-motion resulting in twelve state vector elements. In addition to these are mass and solid propellant burn depth as the ""system'' state elements. The ""parameter'' state elements can include aerodynamic coefficient, inertia, center-of-gravity, atmospheric wind, etc. deviations from referenced values. Propulsion parameter state elements have been included not as options just discussed but as the main parameter states to be estimated. The mathematical developments were completed for all these parameters. Since the systems dynamics and measurement processes are non-linear functions of the states, the mathematical developments are taken up almost entirely by the linearization of these equations as required by the estimation algorithms.

Analytical Solution of Steady State Equations for Chemical Reaction Networks with Bilinear Rate Laws

PubMed Central

Halász, Ádám M.; Lai, Hong-Jian; McCabe, Meghan M.; Radhakrishnan, Krishnan; Edwards, Jeremy S.

2014-01-01

True steady states are a rare occurrence in living organisms, yet their knowledge is essential for quasi-steady state approximations, multistability analysis, and other important tools in the investigation of chemical reaction networks (CRN) used to describe molecular processes on the cellular level. Here we present an approach that can provide closed form steady-state solutions to complex systems, resulting from CRN with binary reactions and mass-action rate laws. We map the nonlinear algebraic problem of finding steady states onto a linear problem in a higher dimensional space. We show that the linearized version of the steady state equations obeys the linear conservation laws of the original CRN. We identify two classes of problems for which complete, minimally parameterized solutions may be obtained using only the machinery of linear systems and a judicious choice of the variables used as free parameters. We exemplify our method, providing explicit formulae, on CRN describing signal initiation of two important types of RTK receptor-ligand systems, VEGF and EGF-ErbB1. PMID:24334389

TEAMBLOCKS: HYBRID ABSTRACTIONS FOR PROVABLE MULTI-AGENT AUTONOMY

DTIC Science & Technology

2017-07-28

Raspberry Pi 23 can easily satisfy control loop periods on the order of 10−3s. Thus, we assume that the time to execute a piece of control code, ∆t...Release; Distribution Unlimited. 23 State Space The state space of the aircraft is X = R3 × SO(3) × R3 × R3; states consist of • pI ∈ R3, the...the tbdemo_ghaexecution script uses this operation to make feedback system out of the product of the linear system and PI controller. tbread

Entanglement between total intensity and polarization for pairs of coherent states

NASA Astrophysics Data System (ADS)

Sanchidrián-Vaca, Carlos; Luis, Alfredo

2018-04-01

We examine entanglement between number and polarization, or number and relative phase, in pair coherent states and two-mode squeezed vacuum via linear entropy and covariance criteria. We consider the embedding of the two-mode Hilbert space in a larger space to get a well-defined factorization of the number-phase variables. This can be regarded as a kind of protoentanglement that can be extracted and converted into real particle entanglement via feasible experimental procedures. In particular this reveals interesting entanglement properties of pairs of coherent states.

Rapid Computation of Thermodynamic Properties over Multidimensional Nonbonded Parameter Spaces Using Adaptive Multistate Reweighting.

PubMed

Naden, Levi N; Shirts, Michael R

2016-04-12

We show how thermodynamic properties of molecular models can be computed over a large, multidimensional parameter space by combining multistate reweighting analysis with a linear basis function approach. This approach reduces the computational cost to estimate thermodynamic properties from molecular simulations for over 130,000 tested parameter combinations from over 1000 CPU years to tens of CPU days. This speed increase is achieved primarily by computing the potential energy as a linear combination of basis functions, computed from either modified simulation code or as the difference of energy between two reference states, which can be done without any simulation code modification. The thermodynamic properties are then estimated with the Multistate Bennett Acceptance Ratio (MBAR) as a function of multiple model parameters without the need to define a priori how the states are connected by a pathway. Instead, we adaptively sample a set of points in parameter space to create mutual configuration space overlap. The existence of regions of poor configuration space overlap are detected by analyzing the eigenvalues of the sampled states' overlap matrix. The configuration space overlap to sampled states is monitored alongside the mean and maximum uncertainty to determine convergence, as neither the uncertainty or the configuration space overlap alone is a sufficient metric of convergence. This adaptive sampling scheme is demonstrated by estimating with high precision the solvation free energies of charged particles of Lennard-Jones plus Coulomb functional form with charges between -2 and +2 and generally physical values of σij and ϵij in TIP3P water. We also compute entropy, enthalpy, and radial distribution functions of arbitrary unsampled parameter combinations using only the data from these sampled states and use the estimates of free energies over the entire space to examine the deviation of atomistic simulations from the Born approximation to the solvation free energy.

Alpha-canonical form representation of the open loop dynamics of the Space Shuttle main engine

NASA Technical Reports Server (NTRS)

Duyar, Almet; Eldem, Vasfi; Merrill, Walter C.; Guo, Ten-Huei

1991-01-01

A parameter and structure estimation technique for multivariable systems is used to obtain a state space representation of open loop dynamics of the space shuttle main engine in alpha-canonical form. The parameterization being used is both minimal and unique. The simplified linear model may be used for fault detection studies and control system design and development.

Confining potential in momentum space

NASA Technical Reports Server (NTRS)

Norbury, John W.; Kahana, David E.; Maung, Khin Maung

1992-01-01

A method is presented for the solution in momentum space of the bound state problem with a linear potential in r space. The potential is unbounded at large r leading to a singularity at small q. The singularity is integrable, when regulated by exponentially screening the r-space potential, and is removed by a subtraction technique. The limit of zero screening is taken analytically, and the numerical solution of the subtracted integral equation gives eigenvalues and wave functions in good agreement with position space calculations.

Optical nonlinearities of excitonic states in atomically thin 2D transition metal dichalcogenides

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

Soh, Daniel Beom Soo

We calculated the optical nonlinearities of the atomically thin monolayer transition metal dichalcogenide material (particularly MoS 2), particularly for those linear and nonlinear transition processes that utilize the bound exciton states. We adopted the bound and the unbound exciton states as the basis for the Hilbert space, and derived all the dynamical density matrices that provides the induced current density, from which the nonlinear susceptibilities can be drawn order-by-order via perturbative calculations. We provide the nonlinear susceptibilities for the linear, the second-harmonic, the third-harmonic, and the kerr-type two-photon processes.

A straightforward characterization of non-modal effects from the evolution of linear dynamical systems

NASA Astrophysics Data System (ADS)

Arratia, Cristobal

2014-11-01

A simple construction will be shown, which reveals a general property satisfied by the evolution in time of a state vector composed by a superposition of orthogonal eigenmodes of a linear dynamical system. This property results from the conservation of the inner product between such state vectors evolving forward and backwards in time, and it can be simply evaluated from the state vector and its first and second time derivatives. This provides an efficient way to characterize, instantaneously along any specific phase-space trajectory of the linear system, the relevance of the non-normality of the linearized Navier-Stokes operator on the energy (or any other norm) gain or decay of small perturbations. Examples of this characterization applied to stationary or time dependent base flows will be shown. CONICYT, Concurso de Apoyo al Retorno de Investigadores del Extranjero, folio 821320055.

Some Properties and Stability Results for Sector-Bounded LTI Systems

NASA Technical Reports Server (NTRS)

Gupta, Sandeep; Joshi, Suresh M.

1994-01-01

This paper presents necessary and sufficient conditions for a linear, time-invariant (LTI) system to be inside sector (n, b) in terms of linear matrix inequalities in its state-space realization matrices, which represents a generalization of similar conditions for bounded H(sub infinity)-norm systems. Further, a weaker definition of LTI systems strictly inside closed sector (a, b) is proposed, and state-space characterization of such systems is presented. Sector conditions for stability of the negative feedback interconnection of two LTI systems and for stability of LTI systems with feedback nonlinearities are investigated using the Lyapunov function approach. It is shown that the proposed weaker conditions for an LTI system to be strictly inside a sector are sufficient to establish closed-loop stability of these systems.

Small vibrations of a linearly elastic body surrounded by heavy, incompressible, non-Newtonian fluids with free surfaces

NASA Astrophysics Data System (ADS)

Licht, Christian; Tran Thu Ha

2005-02-01

We consider the small transient motions of a coupled system constituted by a linearly elastic body and two heavy, incompressible, non-Newtonian fluids.Through a formulation in terms of non-linear evolution equations in Hilbert spaces of possible states with finite mechanical energy, we obtain existence and uniqueness results and study the influence of gravity. To cite this article: C. Licht, Tran Thu Ha, C. R. Mecanique 333 (2005).

The Microgravity Isolation Mount: A Linearized State-Space Model a la Newton and Kane

NASA Technical Reports Server (NTRS)

Hampton, R. David; Tryggvason, Bjarni V.; DeCarufel, Jean; Townsend, Miles A.; Wagar, William O.

1999-01-01

Vibration acceleration levels on large space platforms exceed the requirements of many space experiments. The Microgravity Vibration Isolation Mount (MIM) was built by the Canadian Space Agency to attenuate these disturbances to acceptable levels, and has been operational on the Russian Space Station Mir since May 1996. It has demonstrated good isolation performance and has supported several materials science experiments. The MIM uses Lorentz (voice-coil) magnetic actuators to levitate and isolate payloads at the individual experiment/sub-experiment (versus rack) level. Payload acceleration, relative position, and relative orientation (Euler-parameter) measurements are fed to a state-space controller. The controller, in turn, determines the actuator currents needed for effective experiment isolation. This paper presents the development of an algebraic, state-space model of the MIM, in a form suitable for optimal controller design. The equations are first derived using Newton's Second Law directly; then a second derivation (i.e., validation) of the same equations is provided, using Kane's approach.

State-space models’ dirty little secrets: even simple linear Gaussian models can have estimation problems

NASA Astrophysics Data System (ADS)

Auger-Méthé, Marie; Field, Chris; Albertsen, Christoffer M.; Derocher, Andrew E.; Lewis, Mark A.; Jonsen, Ian D.; Mills Flemming, Joanna

2016-05-01

State-space models (SSMs) are increasingly used in ecology to model time-series such as animal movement paths and population dynamics. This type of hierarchical model is often structured to account for two levels of variability: biological stochasticity and measurement error. SSMs are flexible. They can model linear and nonlinear processes using a variety of statistical distributions. Recent ecological SSMs are often complex, with a large number of parameters to estimate. Through a simulation study, we show that even simple linear Gaussian SSMs can suffer from parameter- and state-estimation problems. We demonstrate that these problems occur primarily when measurement error is larger than biological stochasticity, the condition that often drives ecologists to use SSMs. Using an animal movement example, we show how these estimation problems can affect ecological inference. Biased parameter estimates of a SSM describing the movement of polar bears (Ursus maritimus) result in overestimating their energy expenditure. We suggest potential solutions, but show that it often remains difficult to estimate parameters. While SSMs are powerful tools, they can give misleading results and we urge ecologists to assess whether the parameters can be estimated accurately before drawing ecological conclusions from their results.

The design of a linear L-band high power amplifier for mobile communication satellites

NASA Technical Reports Server (NTRS)

Whittaker, N.; Brassard, G.; Li, E.; Goux, P.

1990-01-01

A linear L-band solid state high power amplifier designed for the space segment of the Mobile Satellite (MSAT) mobile communication system is described. The amplifier is capable of producing 35 watts of RF power with multitone signal at an efficiency of 25 percent and with intermodulation products better than 16 dB below carrier.

Control Law Design in a Computational Aeroelasticity Environment

NASA Technical Reports Server (NTRS)

Newsom, Jerry R.; Robertshaw, Harry H.; Kapania, Rakesh K.

2003-01-01

A methodology for designing active control laws in a computational aeroelasticity environment is given. The methodology involves employing a systems identification technique to develop an explicit state-space model for control law design from the output of a computational aeroelasticity code. The particular computational aeroelasticity code employed in this paper solves the transonic small disturbance aerodynamic equation using a time-accurate, finite-difference scheme. Linear structural dynamics equations are integrated simultaneously with the computational fluid dynamics equations to determine the time responses of the structure. These structural responses are employed as the input to a modern systems identification technique that determines the Markov parameters of an "equivalent linear system". The Eigensystem Realization Algorithm is then employed to develop an explicit state-space model of the equivalent linear system. The Linear Quadratic Guassian control law design technique is employed to design a control law. The computational aeroelasticity code is modified to accept control laws and perform closed-loop simulations. Flutter control of a rectangular wing model is chosen to demonstrate the methodology. Various cases are used to illustrate the usefulness of the methodology as the nonlinearity of the aeroelastic system is increased through increased angle-of-attack changes.

Flatness-based control and Kalman filtering for a continuous-time macroeconomic model

NASA Astrophysics Data System (ADS)

Rigatos, G.; Siano, P.; Ghosh, T.; Busawon, K.; Binns, R.

2017-11-01

The article proposes flatness-based control for a nonlinear macro-economic model of the UK economy. The differential flatness properties of the model are proven. This enables to introduce a transformation (diffeomorphism) of the system's state variables and to express the state-space description of the model in the linear canonical (Brunowsky) form in which both the feedback control and the state estimation problem can be solved. For the linearized equivalent model of the macroeconomic system, stabilizing feedback control can be achieved using pole placement methods. Moreover, to implement stabilizing feedback control of the system by measuring only a subset of its state vector elements the Derivative-free nonlinear Kalman Filter is used. This consists of the Kalman Filter recursion applied on the linearized equivalent model of the financial system and of an inverse transformation that is based again on differential flatness theory. The asymptotic stability properties of the control scheme are confirmed.

Linear canonical transformations of coherent and squeezed states in the Wigner phase space. III - Two-mode states

NASA Technical Reports Server (NTRS)

Han, D.; Kim, Y. S.; Noz, Marilyn E.

1990-01-01

It is shown that the basic symmetry of two-mode squeezed states is governed by the group SP(4) in the Wigner phase space which is locally isomorphic to the (3 + 2)-dimensional Lorentz group. This symmetry, in the Schroedinger picture, appears as Dirac's two-oscillator representation of O(3,2). It is shown that the SU(2) and SU(1,1) interferometers exhibit the symmetry of this higher-dimensional Lorentz group. The mathematics of two-mode squeezed states is shown to be applicable to other branches of physics including thermally excited states in statistical mechanics and relativistic extended hadrons in the quark model.

Koopman Invariant Subspaces and Finite Linear Representations of Nonlinear Dynamical Systems for Control.

PubMed

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

2016-01-01

In this wIn this work, we explore finite-dimensional linear representations of nonlinear dynamical systems by restricting the Koopman operator to an invariant subspace spanned by specially chosen observable functions. The Koopman operator is an infinite-dimensional linear operator that evolves functions of the state of a dynamical system. Dominant terms in the Koopman expansion are typically computed using dynamic mode decomposition (DMD). DMD uses linear measurements of the state variables, and it has recently been shown that this may be too restrictive for nonlinear systems. Choosing the right nonlinear observable functions to form an invariant subspace where it is possible to obtain linear reduced-order models, especially those that are useful for control, is an open challenge. Here, we investigate the choice of observable functions for Koopman analysis that enable the use of optimal linear control techniques on nonlinear problems. First, to include a cost on the state of the system, as in linear quadratic regulator (LQR) control, it is helpful to include these states in the observable subspace, as in DMD. However, we find that this is only possible when there is a single isolated fixed point, as systems with multiple fixed points or more complicated attractors are not globally topologically conjugate to a finite-dimensional linear system, and cannot be represented by a finite-dimensional linear Koopman subspace that includes the state. We then present a data-driven strategy to identify relevant observable functions for Koopman analysis by leveraging a new algorithm to determine relevant terms in a dynamical system by ℓ1-regularized regression of the data in a nonlinear function space; we also show how this algorithm is related to DMD. Finally, we demonstrate the usefulness of nonlinear observable subspaces in the design of Koopman operator optimal control laws for fully nonlinear systems using techniques from linear optimal control.ork, we explore finite-dimensional linear representations of nonlinear dynamical systems by restricting the Koopman operator to an invariant subspace spanned by specially chosen observable functions. The Koopman operator is an infinite-dimensional linear operator that evolves functions of the state of a dynamical system. Dominant terms in the Koopman expansion are typically computed using dynamic mode decomposition (DMD). DMD uses linear measurements of the state variables, and it has recently been shown that this may be too restrictive for nonlinear systems. Choosing the right nonlinear observable functions to form an invariant subspace where it is possible to obtain linear reduced-order models, especially those that are useful for control, is an open challenge. Here, we investigate the choice of observable functions for Koopman analysis that enable the use of optimal linear control techniques on nonlinear problems. First, to include a cost on the state of the system, as in linear quadratic regulator (LQR) control, it is helpful to include these states in the observable subspace, as in DMD. However, we find that this is only possible when there is a single isolated fixed point, as systems with multiple fixed points or more complicated attractors are not globally topologically conjugate to a finite-dimensional linear system, and cannot be represented by a finite-dimensional linear Koopman subspace that includes the state. We then present a data-driven strategy to identify relevant observable functions for Koopman analysis by leveraging a new algorithm to determine relevant terms in a dynamical system by ℓ1-regularized regression of the data in a nonlinear function space; we also show how this algorithm is related to DMD. Finally, we demonstrate the usefulness of nonlinear observable subspaces in the design of Koopman operator optimal control laws for fully nonlinear systems using techniques from linear optimal control.

Dynamic Programming for Structured Continuous Markov Decision Problems

NASA Technical Reports Server (NTRS)

Dearden, Richard; Meuleau, Nicholas; Washington, Richard; Feng, Zhengzhu

2004-01-01

We describe an approach for exploiting structure in Markov Decision Processes with continuous state variables. At each step of the dynamic programming, the state space is dynamically partitioned into regions where the value function is the same throughout the region. We first describe the algorithm for piecewise constant representations. We then extend it to piecewise linear representations, using techniques from POMDPs to represent and reason about linear surfaces efficiently. We show that for complex, structured problems, our approach exploits the natural structure so that optimal solutions can be computed efficiently.

Identification of the focal plane wavefront control system using E-M algorithm

NASA Astrophysics Data System (ADS)

Sun, He; Kasdin, N. Jeremy; Vanderbei, Robert

2017-09-01

In a typical focal plane wavefront control (FPWC) system, such as the adaptive optics system of NASA's WFIRST mission, the efficient controllers and estimators in use are usually model-based. As a result, the modeling accuracy of the system influences the ultimate performance of the control and estimation. Currently, a linear state space model is used and calculated based on lab measurements using Fourier optics. Although the physical model is clearly defined, it is usually biased due to incorrect distance measurements, imperfect diagnoses of the optical aberrations, and our lack of knowledge of the deformable mirrors (actuator gains and influence functions). In this paper, we present a new approach for measuring/estimating the linear state space model of a FPWC system using the expectation-maximization (E-M) algorithm. Simulation and lab results in the Princeton's High Contrast Imaging Lab (HCIL) show that the E-M algorithm can well handle both the amplitude and phase errors and accurately recover the system. Using the recovered state space model, the controller creates dark holes with faster speed. The final accuracy of the model depends on the amount of data used for learning.

Probing the Locality of Excited States with Linear Algebra.

PubMed

Etienne, Thibaud

2015-04-14

This article reports a novel theoretical approach related to the analysis of molecular excited states. The strategy introduced here involves gathering two pieces of physical information, coming from Hilbert and direct space operations, into a general, unique quantum mechanical descriptor of electronic transitions' locality. Moreover, the projection of Hilbert and direct space-derived indices in an Argand plane delivers a straightforward way to visually probe the ability of a dye to undergo a long- or short-range charge-transfer. This information can be applied, for instance, to the analysis of the electronic response of families of dyes to light absorption by unveiling the trend of a given push-pull chromophore to increase the electronic cloud polarization magnitude of its main transition with respect to the size extension of its conjugated spacer. We finally demonstrate that all the quantities reported in this article can be reliably approximated by a linear algebraic derivation, based on the contraction of detachment/attachment density matrices from canonical to atomic space. This alternative derivation has the remarkable advantage of a very low computational cost with respect to the previously used numerical integrations, making fast and accurate characterization of large molecular systems' excited states easily affordable.

Projective limits of state spaces II. Quantum formalism

NASA Astrophysics Data System (ADS)

Lanéry, Suzanne; Thiemann, Thomas

2017-06-01

In this series of papers, we investigate the projective framework initiated by Kijowski (1977) and Okołów (2009, 2014, 2013), which describes the states of a quantum theory as projective families of density matrices. A short reading guide to the series can be found in Lanéry (2016). After discussing the formalism at the classical level in a first paper (Lanéry, 2017), the present second paper is devoted to the quantum theory. In particular, we inspect in detail how such quantum projective state spaces relate to inductive limit Hilbert spaces and to infinite tensor product constructions (Lanéry, 2016, subsection 3.1) [1]. Regarding the quantization of classical projective structures into quantum ones, we extend the results by Okołów (2013), that were set up in the context of linear configuration spaces, to configuration spaces given by simply-connected Lie groups, and to holomorphic quantization of complex phase spaces (Lanéry, 2016, subsection 2.2) [1].

Optimal control of coupled parabolic-hyperbolic non-autonomous PDEs: infinite-dimensional state-space approach

NASA Astrophysics Data System (ADS)

Aksikas, I.; Moghadam, A. Alizadeh; Forbes, J. F.

2018-04-01

This paper deals with the design of an optimal state-feedback linear-quadratic (LQ) controller for a system of coupled parabolic-hypebolic non-autonomous partial differential equations (PDEs). The infinite-dimensional state space representation and the corresponding operator Riccati differential equation are used to solve the control problem. Dynamical properties of the coupled system of interest are analysed to guarantee the existence and uniqueness of the solution of the LQ-optimal control problem and also to guarantee the exponential stability of the closed-loop system. Thanks to the eigenvalues and eigenfunctions of the parabolic operator and also the fact that the hyperbolic-associated operator Riccati differential equation can be converted to a scalar Riccati PDE, an algorithm to solve the LQ control problem has been presented. The results are applied to a non-isothermal packed-bed catalytic reactor. The LQ optimal controller designed in the early portion of the paper is implemented for the original non-linear model. Numerical simulations are performed to show the controller performances.

The application of LQR synthesis techniques to the turboshaft engine control problem. [Linear Quadratic Regulator

NASA Technical Reports Server (NTRS)

Pfeil, W. H.; De Los Reyes, G.; Bobula, G. A.

1985-01-01

A power turbine governor was designed for a recent-technology turboshaft engine coupled to a modern, articulated rotor system using Linear Quadratic Regulator (LQR) and Kalman Filter (KF) techniques. A linear, state-space model of the engine and rotor system was derived for six engine power settings from flight idle to maximum continuous. An integrator was appended to the fuel flow input to reduce the steady-state governor error to zero. Feedback gains were calculated for the system states at each power setting using the LQR technique. The main rotor tip speed state is not measurable, so a Kalman Filter of the rotor was used to estimate this state. The crossover of the system was increased to 10 rad/s compared to 2 rad/sec for a current governor. Initial computer simulations with a nonlinear engine model indicate a significant decrease in power turbine speed variation with the LQR governor compared to a conventional governor.

Complex sample survey estimation in static state-space

Treesearch

Raymond L. Czaplewski

2010-01-01

Increased use of remotely sensed data is a key strategy adopted by the Forest Inventory and Analysis Program. However, multiple sensor technologies require complex sampling units and sampling designs. The Recursive Restriction Estimator (RRE) accommodates this complexity. It is a design-consistent Empirical Best Linear Unbiased Prediction for the state-vector, which...

Phase unwrapping algorithm using polynomial phase approximation and linear Kalman filter.

PubMed

Kulkarni, Rishikesh; Rastogi, Pramod

2018-02-01

A noise-robust phase unwrapping algorithm is proposed based on state space analysis and polynomial phase approximation using wrapped phase measurement. The true phase is approximated as a two-dimensional first order polynomial function within a small sized window around each pixel. The estimates of polynomial coefficients provide the measurement of phase and local fringe frequencies. A state space representation of spatial phase evolution and the wrapped phase measurement is considered with the state vector consisting of polynomial coefficients as its elements. Instead of using the traditional nonlinear Kalman filter for the purpose of state estimation, we propose to use the linear Kalman filter operating directly with the wrapped phase measurement. The adaptive window width is selected at each pixel based on the local fringe density to strike a balance between the computation time and the noise robustness. In order to retrieve the unwrapped phase, either a line-scanning approach or a quality guided strategy of pixel selection is used depending on the underlying continuous or discontinuous phase distribution, respectively. Simulation and experimental results are provided to demonstrate the applicability of the proposed method.

Effects of joints in truss structures

NASA Technical Reports Server (NTRS)

Ikegami, R.

1988-01-01

The response of truss-type structures for future space applications, such as Large Deployable Reflector (LDR), will be directly affected by joint performance. Some of the objectives of research at BAC were to characterize structural joints, establish analytical approaches that incorporate joint characteristics, and experimentally establish the validity of the analytical approaches. The test approach to characterize joints for both erectable and deployable-type structures was based upon a Force State Mapping Technique. The approach pictorially shows how the nonlinear joint results can be used for equivalent linear analysis. Testing of the Space Station joints developed at LaRC (a hinged joint at 2 Hz and a clevis joint at 2 Hz) successfully revealed the nonlinear characteristics of the joints. The Space Station joints were effectively linear when loaded to plus or minus 500 pounds with a corresponding displacement of about plus or minus 0.0015 inch. It was indicated that good linear joints exist which are compatible with errected structures, but that difficulty may be encountered if nonlinear-type joints are incorporated in the structure.

Linear canonical transformations of coherent and squeezed states in the Wigner phase space. II - Quantitative analysis

NASA Technical Reports Server (NTRS)

Han, D.; Kim, Y. S.; Noz, Marilyn E.

1989-01-01

It is possible to calculate expectation values and transition probabilities from the Wigner phase-space distribution function. Based on the canonical transformation properties of the Wigner function, an algorithm is developed for calculating these quantities in quantum optics for coherent and squeezed states. It is shown that the expectation value of a dynamical variable can be written in terms of its vacuum expectation value of the canonically transformed variable. Parallel-axis theorems are established for the photon number and its variant. It is also shown that the transition probability between two squeezed states can be reduced to that of the transition from one squeezed state to vacuum.

A feedback linearization approach to spacecraft control using momentum exchange devices. Ph.D. Thesis

NASA Technical Reports Server (NTRS)

Dzielski, John Edward

1988-01-01

Recent developments in the area of nonlinear control theory have shown how coordiante changes in the state and input spaces can be used with nonlinear feedback to transform certain nonlinear ordinary differential equations into equivalent linear equations. These feedback linearization techniques are applied to resolve two problems arising in the control of spacecraft equipped with control moment gyroscopes (CMGs). The first application involves the computation of rate commands for the gimbals that rotate the individual gyroscopes to produce commanded torques on the spacecraft. The second application is to the long-term management of stored momentum in the system of control moment gyroscopes using environmental torques acting on the vehicle. An approach to distributing control effort among a group of redundant actuators is described that uses feedback linearization techniques to parameterize sets of controls which influence a specified subsystem in a desired way. The approach is adapted for use in spacecraft control with double-gimballed gyroscopes to produce an algorithm that avoids problematic gimbal configurations by approximating sets of gimbal rates that drive CMG rotors into desirable configurations. The momentum management problem is stated as a trajectory optimization problem with a nonlinear dynamical constraint. Feedback linearization and collocation are used to transform this problem into an unconstrainted nonlinear program. The approach to trajectory optimization is fast and robust. A number of examples are presented showing applications to the proposed NASA space station.

An Airborne Radar Model For Non-Uniformly Spaced Antenna Arrays

DTIC Science & Technology

2006-03-01

Department of Defense, or the United States Government . AFIT-GE-ENG-06-58 An Airborne Radar Model For Non-Uniformly Spaced Antenna Arrays THESIS Presented...different circular arrays, one containing 24 elements and one containing 15 elements. The circular array per- formance is compared to that of a 6 × 6...model and compared to the radar model of [5, 6, 13]. The two models are mathematically equivalent when the uniformly spaced array is linear. The two

Statistical analysis of excitation energies in actinide and rare-earth nuclei

NASA Astrophysics Data System (ADS)

Levon, A. I.; Magner, A. G.; Radionov, S. V.

2018-04-01

Statistical analysis of distributions of the collective states in actinide and rare-earth nuclei is performed in terms of the nearest-neighbor spacing distribution (NNSD). Several approximations, such as the linear approach to the level repulsion density and that suggested by Brody to the NNSDs were applied for the analysis. We found an intermediate character of the experimental spectra between the order and the chaos for a number of rare-earth and actinide nuclei. The spectra are closer to the Wigner distribution for energies limited by 3 MeV, and to the Poisson distribution for data including higher excitation energies and higher spins. The latter result is in agreement with the theoretical calculations. These features are confirmed by the cumulative distributions, where the Wigner contribution dominates at smaller spacings while the Poisson one is more important at larger spacings, and our linear approach improves the comparison with experimental data at all desired spacings.

Predicted torque equilibrium attitude utilization for Space Station attitude control

NASA Technical Reports Server (NTRS)

Kumar, Renjith R.; Heck, Michael L.; Robertson, Brent P.

1990-01-01

An approximate knowledge of the torque equilibrium attitude (TEA) is shown to improve the performance of a control moment gyroscope (CMG) momentum management/attitude control law for Space Station Freedom. The linearized equations of motion are used in conjunction with a state transformation to obtain a control law which uses full state feedback and the predicted TEA to minimize both attitude excursions and CMG peak and secular momentum. The TEA can be computationally determined either by observing the steady state attitude of a 'controlled' spacecraft using arbitrary initial attitude, or by simulating a fixed attitude spacecraft flying in desired orbit subject to realistic environmental disturbance models.

Particle rejuvenation of Rao-Blackwellized sequential Monte Carlo smoothers for conditionally linear and Gaussian models

NASA Astrophysics Data System (ADS)

Nguyen, Ngoc Minh; Corff, Sylvain Le; Moulines, Éric

2017-12-01

This paper focuses on sequential Monte Carlo approximations of smoothing distributions in conditionally linear and Gaussian state spaces. To reduce Monte Carlo variance of smoothers, it is typical in these models to use Rao-Blackwellization: particle approximation is used to sample sequences of hidden regimes while the Gaussian states are explicitly integrated conditional on the sequence of regimes and observations, using variants of the Kalman filter/smoother. The first successful attempt to use Rao-Blackwellization for smoothing extends the Bryson-Frazier smoother for Gaussian linear state space models using the generalized two-filter formula together with Kalman filters/smoothers. More recently, a forward-backward decomposition of smoothing distributions mimicking the Rauch-Tung-Striebel smoother for the regimes combined with backward Kalman updates has been introduced. This paper investigates the benefit of introducing additional rejuvenation steps in all these algorithms to sample at each time instant new regimes conditional on the forward and backward particles. This defines particle-based approximations of the smoothing distributions whose support is not restricted to the set of particles sampled in the forward or backward filter. These procedures are applied to commodity markets which are described using a two-factor model based on the spot price and a convenience yield for crude oil data.

A Numerical Approximation Framework for the Stochastic Linear Quadratic Regulator on Hilbert Spaces

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

Levajković, Tijana, E-mail: tijana.levajkovic@uibk.ac.at, E-mail: t.levajkovic@sf.bg.ac.rs; Mena, Hermann, E-mail: hermann.mena@uibk.ac.at; Tuffaha, Amjad, E-mail: atufaha@aus.edu

We present an approximation framework for computing the solution of the stochastic linear quadratic control problem on Hilbert spaces. We focus on the finite horizon case and the related differential Riccati equations (DREs). Our approximation framework is concerned with the so-called “singular estimate control systems” (Lasiecka in Optimal control problems and Riccati equations for systems with unbounded controls and partially analytic generators: applications to boundary and point control problems, 2004) which model certain coupled systems of parabolic/hyperbolic mixed partial differential equations with boundary or point control. We prove that the solutions of the approximate finite-dimensional DREs converge to the solutionmore » of the infinite-dimensional DRE. In addition, we prove that the optimal state and control of the approximate finite-dimensional problem converge to the optimal state and control of the corresponding infinite-dimensional problem.« less

Neural-genetic synthesis for state-space controllers based on linear quadratic regulator design for eigenstructure assignment.

PubMed

da Fonseca Neto, João Viana; Abreu, Ivanildo Silva; da Silva, Fábio Nogueira

2010-04-01

Toward the synthesis of state-space controllers, a neural-genetic model based on the linear quadratic regulator design for the eigenstructure assignment of multivariable dynamic systems is presented. The neural-genetic model represents a fusion of a genetic algorithm and a recurrent neural network (RNN) to perform the selection of the weighting matrices and the algebraic Riccati equation solution, respectively. A fourth-order electric circuit model is used to evaluate the convergence of the computational intelligence paradigms and the control design method performance. The genetic search convergence evaluation is performed in terms of the fitness function statistics and the RNN convergence, which is evaluated by landscapes of the energy and norm, as a function of the parameter deviations. The control problem solution is evaluated in the time and frequency domains by the impulse response, singular values, and modal analysis.

Unified quantum no-go theorems and transforming of quantum pure states in a restricted set

NASA Astrophysics Data System (ADS)

Luo, Ming-Xing; Li, Hui-Ran; Lai, Hong; Wang, Xiaojun

2017-12-01

The linear superposition principle in quantum mechanics is essential for several no-go theorems such as the no-cloning theorem, the no-deleting theorem and the no-superposing theorem. In this paper, we investigate general quantum transformations forbidden or permitted by the superposition principle for various goals. First, we prove a no-encoding theorem that forbids linearly superposing of an unknown pure state and a fixed pure state in Hilbert space of a finite dimension. The new theorem is further extended for multiple copies of an unknown state as input states. These generalized results of the no-encoding theorem include the no-cloning theorem, the no-deleting theorem and the no-superposing theorem as special cases. Second, we provide a unified scheme for presenting perfect and imperfect quantum tasks (cloning and deleting) in a one-shot manner. This scheme may lead to fruitful results that are completely characterized with the linear independence of the representative vectors of input pure states. The upper bounds of the efficiency are also proved. Third, we generalize a recent superposing scheme of unknown states with a fixed overlap into new schemes when multiple copies of an unknown state are as input states.

Evaluation of linearly solvable Markov decision process with dynamic model learning in a mobile robot navigation task.

PubMed

Kinjo, Ken; Uchibe, Eiji; Doya, Kenji

2013-01-01

Linearly solvable Markov Decision Process (LMDP) is a class of optimal control problem in which the Bellman's equation can be converted into a linear equation by an exponential transformation of the state value function (Todorov, 2009b). In an LMDP, the optimal value function and the corresponding control policy are obtained by solving an eigenvalue problem in a discrete state space or an eigenfunction problem in a continuous state using the knowledge of the system dynamics and the action, state, and terminal cost functions. In this study, we evaluate the effectiveness of the LMDP framework in real robot control, in which the dynamics of the body and the environment have to be learned from experience. We first perform a simulation study of a pole swing-up task to evaluate the effect of the accuracy of the learned dynamics model on the derived the action policy. The result shows that a crude linear approximation of the non-linear dynamics can still allow solution of the task, despite with a higher total cost. We then perform real robot experiments of a battery-catching task using our Spring Dog mobile robot platform. The state is given by the position and the size of a battery in its camera view and two neck joint angles. The action is the velocities of two wheels, while the neck joints were controlled by a visual servo controller. We test linear and bilinear dynamic models in tasks with quadratic and Guassian state cost functions. In the quadratic cost task, the LMDP controller derived from a learned linear dynamics model performed equivalently with the optimal linear quadratic regulator (LQR). In the non-quadratic task, the LMDP controller with a linear dynamics model showed the best performance. The results demonstrate the usefulness of the LMDP framework in real robot control even when simple linear models are used for dynamics learning.

Bond Length Dependence on Quantum States as Shown by Spectroscopy

ERIC Educational Resources Information Center

Lim, Kieran F.

2005-01-01

A discussion on how a spreadsheet simulation of linear-molecular spectra could be used to explore the dependence of rotational band spacing and contours on average bond lengths in the initial and final quantum states is presented. The simulation of hydrogen chloride IR, iodine UV-vis, and nitrogen UV-vis spectra clearly show whether the average…

The Deleuzian Concept of Structure and Quantum Mechanics

NASA Astrophysics Data System (ADS)

Christiaens, Wim A.

2014-03-01

Gilles Deleuze wanted a philosophy of nature in a pre-kantian almost archaic sense. A central concept in his philosophy is `multiplicity'. Although the concept is philosophical through and through, it has roots in the mathematical notion of manifold, specifically the state spaces for dynamical systems exhibiting non-linear behaviour. Deleuze was attracted to such mathematical structures because he believed they indicated a break with the dogmatic image of thought (the kind of thought that constrains itself into producing representations of reality conceived as particular things with strict borders, behaving and interacting according to invariant covering laws within space). However, even though it is true that a phase space representation of a physical entity is not a typical materialist picture of reality, it derives from a normal Euclidean representation, and can in principle be reduced to it. We want to argue that the real break happens with the quantum state space, and that Deleuze's typical description of a multiplicity fits even better with the quantum state space.

Optimal mode transformations for linear-optical cluster-state generation

DOE PAGES

Uskov, Dmitry B.; Lougovski, Pavel; Alsing, Paul M.; ...

2015-06-15

In this paper, we analyze the generation of linear-optical cluster states (LOCSs) via sequential addition of one and two qubits. Existing approaches employ the stochastic linear-optical two-qubit controlled-Z (CZ) gate with success rate of 1/9 per operation. The question of optimality of the CZ gate with respect to LOCS generation has remained open. We report that there are alternative schemes to the CZ gate that are exponentially more efficient and show that sequential LOCS growth is indeed globally optimal. We find that the optimal cluster growth operation is a state transformation on a subspace of the full Hilbert space. Finally,more » we show that the maximal success rate of postselected entangling n photonic qubits or m Bell pairs into a cluster is (1/2) n-1 and (1/4) m-1, respectively, with no ancilla photons, and we give an explicit optical description of the optimal mode transformations.« less

Recurrence theorems: A unified account

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

Wallace, David, E-mail: david.wallace@balliol.ox.ac.uk

I discuss classical and quantum recurrence theorems in a unified manner, treating both as generalisations of the fact that a system with a finite state space only has so many places to go. Along the way, I prove versions of the recurrence theorem applicable to dynamics on linear and metric spaces and make some comments about applications of the classical recurrence theorem in the foundations of statistical mechanics.

Extended Kalman Filter for Estimation of Parameters in Nonlinear State-Space Models of Biochemical Networks

PubMed Central

Sun, Xiaodian; Jin, Li; Xiong, Momiao

2008-01-01

It is system dynamics that determines the function of cells, tissues and organisms. To develop mathematical models and estimate their parameters are an essential issue for studying dynamic behaviors of biological systems which include metabolic networks, genetic regulatory networks and signal transduction pathways, under perturbation of external stimuli. In general, biological dynamic systems are partially observed. Therefore, a natural way to model dynamic biological systems is to employ nonlinear state-space equations. Although statistical methods for parameter estimation of linear models in biological dynamic systems have been developed intensively in the recent years, the estimation of both states and parameters of nonlinear dynamic systems remains a challenging task. In this report, we apply extended Kalman Filter (EKF) to the estimation of both states and parameters of nonlinear state-space models. To evaluate the performance of the EKF for parameter estimation, we apply the EKF to a simulation dataset and two real datasets: JAK-STAT signal transduction pathway and Ras/Raf/MEK/ERK signaling transduction pathways datasets. The preliminary results show that EKF can accurately estimate the parameters and predict states in nonlinear state-space equations for modeling dynamic biochemical networks. PMID:19018286

Experimental optimal maximum-confidence discrimination and optimal unambiguous discrimination of two mixed single-photon states

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

Steudle, Gesine A.; Knauer, Sebastian; Herzog, Ulrike

2011-05-15

We present an experimental implementation of optimum measurements for quantum state discrimination. Optimum maximum-confidence discrimination and optimum unambiguous discrimination of two mixed single-photon polarization states were performed. For the latter the states of rank 2 in a four-dimensional Hilbert space are prepared using both path and polarization encoding. Linear optics and single photons from a true single-photon source based on a semiconductor quantum dot are utilized.

The Stability Region for Feedback Control of the Wake Behind Twin Oscillating Cylinders

NASA Astrophysics Data System (ADS)

Borggaard, Jeff; Gugercin, Serkan; Zietsman, Lizette

2016-11-01

Linear feedback control has the ability to stabilize vortex shedding behind twin cylinders where cylinder rotation is the actuation mechanism. Complete elimination of the wake is only possible for certain Reynolds numbers and cylinder spacing. This is related to the presence of asymmetric unstable modes in the linearized system. We investigate this region of parameter space using a number of closed-loop simulations that bound this region. We then consider the practical issue of designing feedback controls based on limited state measurements by building a nonlinear compensator using linear robust control theory with and incorporating the nonlinear terms in the compensator (e.g., using the extended Kalman filter). Interpolatory model reduction methods are applied to the large discretized, linearized Navier-Stokes system and used for computing the control laws and compensators. Preliminary closed-loop simulations of a three-dimensional version of this problem will also be presented. Supported in part by the National Science Foundation.

Use of digital control theory state space formalism for feedback at SLC

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

Himel, T.; Hendrickson, L.; Rouse, F.

The algorithms used in the database-driven SLC fast-feedback system are based on the state space formalism of digital control theory. These are implemented as a set of matrix equations which use a Kalman filter to estimate a vector of states from a vector of measurements, and then apply a gain matrix to determine the actuator settings from the state vector. The matrices used in the calculation are derived offline using Linear Quadratic Gaussian minimization. For a given noise spectrum, this procedure minimizes the rms of the states (e.g., the position or energy of the beam). The offline program also allowsmore » simulation of the loop's response to arbitrary inputs, and calculates its frequency response. 3 refs., 3 figs.« less

Universal linear and nonlinear electrodynamics of a Dirac fluid

NASA Astrophysics Data System (ADS)

Sun, Zhiyuan; Basov, Dmitry N.; Fogler, Michael M.

2018-03-01

A general relation is derived between the linear and second-order nonlinear ac conductivities of an electron system in the hydrodynamic regime of frequencies below the interparticle scattering rate. The magnitude and tensorial structure of the hydrodynamic nonlinear conductivity are shown to differ from their counterparts in the more familiar kinetic regime of higher frequencies. Due to universality of the hydrodynamic equations, the obtained formulas are valid for systems with an arbitrary Dirac-like dispersion, ranging from solid-state electron gases to free-space plasmas, either massive or massless, at any temperature, chemical potential, or space dimension. Predictions for photon drag and second-harmonic generation in graphene are presented as one application of this theory.

Fiber-based Coherent Lidar for Target Ranging, Velocimetry, and Atmospheric Wind Sensing

NASA Technical Reports Server (NTRS)

Amzajerdian, Farzin; Pierrottet, Diego

2006-01-01

By employing a combination of optical heterodyne and linear frequency modulation techniques and utilizing state-of-the-art fiber optic technologies, highly efficient, compact and reliable lidar suitable for operation in a space environment is being developed.

Comprehensive Space-Object Characterization using Spectrally Compressive Polarimetric Sensing

DTIC Science & Technology

2015-04-08

90o, 45o, and 135o polarization channels for lin- ear polarization state estimation. This linear polarimetry would satisfy several applications without...persive element. This technique eliminates mechanical movements that hinder conventional polarimetry . The experimental results show clear spatial

Comparison of some optimal control methods for the design of turbine blades

NASA Technical Reports Server (NTRS)

Desilva, B. M. E.; Grant, G. N. C.

1977-01-01

This paper attempts a comparative study of some numerical methods for the optimal control design of turbine blades whose vibration characteristics are approximated by Timoshenko beam idealizations with shear and incorporating simple boundary conditions. The blade was synthesized using the following methods: (1) conjugate gradient minimization of the system Hamiltonian in function space incorporating penalty function transformations, (2) projection operator methods in a function space which includes the frequencies of vibration and the control function, (3) epsilon-technique penalty function transformation resulting in a highly nonlinear programming problem, (4) finite difference discretization of the state equations again resulting in a nonlinear program, (5) second variation methods with complex state differential equations to include damping effects resulting in systems of inhomogeneous matrix Riccatti equations some of which are stiff, (6) quasi-linear methods based on iterative linearization of the state and adjoint equation. The paper includes a discussion of some substantial computational difficulties encountered in the implementation of these techniques together with a resume of work presently in progress using a differential dynamic programming approach.

Decoupled and linear quadratic regulator control of a large, flexible space antenna with an observer in the control loop

NASA Technical Reports Server (NTRS)

Hamer, H. A.; Johnson, K. G.; Young, J. W.

1985-01-01

An analysis is performed to compare decoupled and linear quadratic regulator (LQR) procedures for the control of a large, flexible space antenna. Control objectives involve: (1) commanding changes in the rigid-body modes, (2) nulling initial disturbances in the rigid-body modes, or (3) nulling initial disturbances in the first three flexible modes. Control is achieved with two three-axis control-moment gyros located on the antenna column. Results are presented to illustrate various effects on control requirements for the two procedures. These effects include errors in the initial estimates of state variables, variations in the type, number, and location of sensors, and deletions of state-variable estimates for certain flexible modes after control activation. The advantages of incorporating a time lag in the control feedback are also illustrated. In addition, the effects of inoperative-control situations are analyzed with regard to control requirements and resultant modal responses. Comparisons are included which show the effects of perfect state feedback with no residual modes (ideal case). Time-history responses are presented to illustrate the various effects on the control procedures.

Three dimensional modelling of earthquake rupture cycles on frictional faults

NASA Astrophysics Data System (ADS)

Simpson, Guy; May, Dave

2017-04-01

We are developing an efficient MPI-parallel numerical method to simulate earthquake sequences on preexisting faults embedding within a three dimensional viscoelastic half-space. We solve the velocity form of the elasto(visco)dynamic equations using a continuous Galerkin Finite Element Method on an unstructured pentahedral mesh, which thus permits local spatial refinement in the vicinity of the fault. Friction sliding is coupled to the viscoelastic solid via rate- and state-dependent friction laws using the split-node technique. Our coupled formulation employs a picard-type non-linear solver with a fully implicit, first order accurate time integrator that utilises an adaptive time step that efficiently evolves the system through multiple seismic cycles. The implementation leverages advanced parallel solvers, preconditioners and linear algebra from the Portable Extensible Toolkit for Scientific Computing (PETSc) library. The model can treat heterogeneous frictional properties and stress states on the fault and surrounding solid as well as non-planar fault geometries. Preliminary tests show that the model successfully reproduces dynamic rupture on a vertical strike-slip fault in a half-space governed by rate-state friction with the ageing law.

Time and Memory Efficient Online Piecewise Linear Approximation of Sensor Signals.

PubMed

Grützmacher, Florian; Beichler, Benjamin; Hein, Albert; Kirste, Thomas; Haubelt, Christian

2018-05-23

Piecewise linear approximation of sensor signals is a well-known technique in the fields of Data Mining and Activity Recognition. In this context, several algorithms have been developed, some of them with the purpose to be performed on resource constrained microcontroller architectures of wireless sensor nodes. While microcontrollers are usually constrained in computational power and memory resources, all state-of-the-art piecewise linear approximation techniques either need to buffer sensor data or have an execution time depending on the segment’s length. In the paper at hand, we propose a novel piecewise linear approximation algorithm, with a constant computational complexity as well as a constant memory complexity. Our proposed algorithm’s worst-case execution time is one to three orders of magnitude smaller and its average execution time is three to seventy times smaller compared to the state-of-the-art Piecewise Linear Approximation (PLA) algorithms in our experiments. In our evaluations, we show that our algorithm is time and memory efficient without sacrificing the approximation quality compared to other state-of-the-art piecewise linear approximation techniques, while providing a maximum error guarantee per segment, a small parameter space of only one parameter, and a maximum latency of one sample period plus its worst-case execution time.

Geometrical Phases in Quantum Mechanics

NASA Astrophysics Data System (ADS)

Christian, Joy Julius

In quantum mechanics, the path-dependent geometrical phase associated with a physical system, over and above the familiar dynamical phase, was initially discovered in the context of adiabatically changing environments. Subsequently, Aharonov and Anandan liberated this phase from the original formulation of Berry, which used Hamiltonians, dependent on curves in a classical parameter space, to represent the cyclic variations of the environments. Their purely quantum mechanical treatment, independent of Hamiltonians, instead used the non-trivial topological structure of the projective space of one-dimensional subspaces of an appropriate Hilbert space. The geometrical phase, in their treatment, results from a parallel transport of the time-dependent pure quantum states along a curve in this space, which is endowed with an abelian connection. Unlike Berry, they were able to achieve this without resort to an adiabatic approximation or to a time-independent eigenvalue equation. Prima facie, these two approaches are conceptually quite different. After a review of both approaches, an exposition bridging this apparent conceptual gap is given; by rigorously analyzing a model composite system, it is shown that, in an appropriate correspondence limit, the Berry phase can be recovered as a special case from the Aharonov-Anandan phase. Moreover, the model composite system is used to show that Berry's correction to the traditional Born-Oppenheimer energy spectra indeed brings the spectra closer to the exact results. Then, an experimental arrangement to measure geometrical phases associated with cyclic and non-cyclic variations of quantum states of an entangled composite system is proposed, utilizing the fundamental ideas of the recently opened field of two-particle interferometry. This arrangement not only resolves the controversy regarding the true nature of the phases associated with photon states, but also unequivocally predicts experimentally accessible geometrical phases in a truly quantum regime, and allows, for the first time, the measurements of such phases associated with arbitrary non-cyclic evolutions of entangled linear-momentum photon -states. This non-classical manifestation of the geometrical phases is due to the entangled character of linear-momentum photon-states of two correlated photons produced by parametric down-conversion in non-linear crystals. Finally, the non-local aspect of the geometrical phase is contrasted with the fundamental non-locality of quantum mechanics due to the entangled character of quantum states.

Koopman Invariant Subspaces and Finite Linear Representations of Nonlinear Dynamical Systems for Control

PubMed Central

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

2016-01-01

In this work, we explore finite-dimensional linear representations of nonlinear dynamical systems by restricting the Koopman operator to an invariant subspace spanned by specially chosen observable functions. The Koopman operator is an infinite-dimensional linear operator that evolves functions of the state of a dynamical system. Dominant terms in the Koopman expansion are typically computed using dynamic mode decomposition (DMD). DMD uses linear measurements of the state variables, and it has recently been shown that this may be too restrictive for nonlinear systems. Choosing the right nonlinear observable functions to form an invariant subspace where it is possible to obtain linear reduced-order models, especially those that are useful for control, is an open challenge. Here, we investigate the choice of observable functions for Koopman analysis that enable the use of optimal linear control techniques on nonlinear problems. First, to include a cost on the state of the system, as in linear quadratic regulator (LQR) control, it is helpful to include these states in the observable subspace, as in DMD. However, we find that this is only possible when there is a single isolated fixed point, as systems with multiple fixed points or more complicated attractors are not globally topologically conjugate to a finite-dimensional linear system, and cannot be represented by a finite-dimensional linear Koopman subspace that includes the state. We then present a data-driven strategy to identify relevant observable functions for Koopman analysis by leveraging a new algorithm to determine relevant terms in a dynamical system by ℓ1-regularized regression of the data in a nonlinear function space; we also show how this algorithm is related to DMD. Finally, we demonstrate the usefulness of nonlinear observable subspaces in the design of Koopman operator optimal control laws for fully nonlinear systems using techniques from linear optimal control. PMID:26919740

Linear approximations of nonlinear systems

NASA Technical Reports Server (NTRS)

Hunt, L. R.; Su, R.

1983-01-01

The development of a method for designing an automatic flight controller for short and vertical take off aircraft is discussed. This technique involves transformations of nonlinear systems to controllable linear systems and takes into account the nonlinearities of the aircraft. In general, the transformations cannot always be given in closed form. Using partial differential equations, an approximate linear system called the modified tangent model was introduced. A linear transformation of this tangent model to Brunovsky canonical form can be constructed, and from this the linear part (about a state space point x sub 0) of an exact transformation for the nonlinear system can be found. It is shown that a canonical expansion in Lie brackets about the point x sub 0 yields the same modified tangent model.

Reduced-order dynamic output feedback control of uncertain discrete-time Markov jump linear systems

NASA Astrophysics Data System (ADS)

Morais, Cecília F.; Braga, Márcio F.; Oliveira, Ricardo C. L. F.; Peres, Pedro L. D.

2017-11-01

This paper deals with the problem of designing reduced-order robust dynamic output feedback controllers for discrete-time Markov jump linear systems (MJLS) with polytopic state space matrices and uncertain transition probabilities. Starting from a full order, mode-dependent and polynomially parameter-dependent dynamic output feedback controller, sufficient linear matrix inequality based conditions are provided for the existence of a robust reduced-order dynamic output feedback stabilising controller with complete, partial or none mode dependency assuring an upper bound to the ? or the ? norm of the closed-loop system. The main advantage of the proposed method when compared to the existing approaches is the fact that the dynamic controllers are exclusively expressed in terms of the decision variables of the problem. In other words, the matrices that define the controller realisation do not depend explicitly on the state space matrices associated with the modes of the MJLS. As a consequence, the method is specially suitable to handle order reduction or cluster availability constraints in the context of ? or ? dynamic output feedback control of discrete-time MJLS. Additionally, as illustrated by means of numerical examples, the proposed approach can provide less conservative results than other conditions in the literature.

Microgravity vibration isolation: Optimal preview and feedback control

NASA Technical Reports Server (NTRS)

Hampton, R. D.; Knospe, C. R.; Grodsinsky, C. M.; Allaire, P. E.; Lewis, D. W.

1992-01-01

In order to achieve adequate low-frequency vibration isolation for certain space experiments an active control is needed, due to inherent passive-isolator limitations. Proposed here are five possible state-space models for a one-dimensional vibration isolation system with a quadratic performance index. The five models are subsets of a general set of nonhomogeneous state space equations which includes disturbance terms. An optimal control is determined, using a differential equations approach, for this class of problems. This control is expressed in terms of constant, Linear Quadratic Regulator (LQR) feedback gains and constant feedforward (preview) gains. The gains can be easily determined numerically. They result in a robust controller and offers substantial improvements over a control that uses standard LQR feedback alone.

A "Kanes's Dynamics" Model for the Active Rack Isolation System

NASA Technical Reports Server (NTRS)

Hampton, R. David; Beech, Geoffrey

1999-01-01

Many microgravity space-science experiments require vibratory acceleration levels unachievable without active isolation. The Boeing Corporation's Active Rack Isolation System (ARIS) employs a novel combination of magnetic actuation and mechanical linkages, to address these isolation requirements on the International Space Station (ISS). ARIS provides isolation at the rack (international Standard Payload Rack, or ISPR) level. Effective model-based vibration isolation requires (1) an appropriate isolation device, (2) an adequate dynamic (i.e., mathematical) model of that isolator, and (3) a suitable, corresponding controller. ARIS provides the ISS response to the first requirement. This paper presents one response to the second, in a state-space framework intended to facilitate an optimal-controls approach to the third. The authors use "Kane's Dynamics" to develop an state-space, analytical (algebraic) set of linearized equations of motion for ARIS.

A "Kane's Dynamics" Model for the Active Rack Isolation System

NASA Technical Reports Server (NTRS)

Hampton, R. D.; Beech, G. S.; Rao, N. N. S.; Rupert, J. K.; Kim, Y. K.

2001-01-01

Many microgravity space science experiments require vibratory acceleration levels unachievable without active isolation. The Boeing Corporation's Active Rack Isolation System (ARIS) employs a novel combination of magnetic actuation and mechanical linkages to address these isolation requirements on the International Space Station (ISS). ARIS provides isolation at the rack (International Standard Payload Rack (ISPR)) level. Effective model-based vibration isolation requires: (1) an appropriate isolation device, (2) an adequate dynamic (i.e., mathematical) model of that isolator, and (3) a suitable, corresponding controller. ARIS provides the ISS response to the first requirement. This paper presents one response to the second, in a state space framework intended to facilitate an optimal-controls approach to the third. The authors use "Kane's Dynamics" to develop a state-space, analytical (algebraic) set of linearized equations of motion for ARIS.

Flight control application of new stability robustness bounds for linear uncertain systems

NASA Technical Reports Server (NTRS)

Yedavalli, Rama K.

1993-01-01

This paper addresses the issue of obtaining bounds on the real parameter perturbations of a linear state-space model for robust stability. Based on Kronecker algebra, new, easily computable sufficient bounds are derived that are much less conservative than the existing bounds since the technique is meant for only real parameter perturbations (in contrast to specializing complex variation case to real parameter case). The proposed theory is illustrated with application to several flight control examples.

The application of LQR synthesis techniques to the turboshaft engine control problem

NASA Technical Reports Server (NTRS)

Pfeil, W. H.; De Los Reyes, G.; Bobula, G. A.

1984-01-01

A power turbine governor was designed for a recent-technology turboshaft engine coupled to a modern, articulated rotor system using Linear Quadratic Regulator (LQR) and Kalman Filter (KF) techniques. A linear, state-space model of the engine and rotor system was derived for six engine power settings from flight idle to maximum continuous. An integrator was appended to the fuel flow input to reduce the steady-state governor error to zero. Feedback gains were calculated for the system states at each power setting using the LQR technique. The main rotor tip speed state is not measurable, so a Kalman Filter of the rotor was used to estimate this state. The crossover of the system was increased to 10 rad/s compared to 2 rad/sec for a current governor. Initial computer simulations with a nonlinear engine model indicate a significant decrease in power turbine speed variation with the LQR governor compared to a conventional governor.

Modelling non-linear effects of dark energy

NASA Astrophysics Data System (ADS)

Bose, Benjamin; Baldi, Marco; Pourtsidou, Alkistis

2018-04-01

We investigate the capabilities of perturbation theory in capturing non-linear effects of dark energy. We test constant and evolving w models, as well as models involving momentum exchange between dark energy and dark matter. Specifically, we compare perturbative predictions at 1-loop level against N-body results for four non-standard equations of state as well as varying degrees of momentum exchange between dark energy and dark matter. The interaction is modelled phenomenologically using a time dependent drag term in the Euler equation. We make comparisons at the level of the matter power spectrum and the redshift space monopole and quadrupole. The multipoles are modelled using the Taruya, Nishimichi and Saito (TNS) redshift space spectrum. We find perturbation theory does very well in capturing non-linear effects coming from dark sector interaction. We isolate and quantify the 1-loop contribution coming from the interaction and from the non-standard equation of state. We find the interaction parameter ξ amplifies scale dependent signatures in the range of scales considered. Non-standard equations of state also give scale dependent signatures within this same regime. In redshift space the match with N-body is improved at smaller scales by the addition of the TNS free parameter σv. To quantify the importance of modelling the interaction, we create mock data sets for varying values of ξ using perturbation theory. This data is given errors typical of Stage IV surveys. We then perform a likelihood analysis using the first two multipoles on these sets and a ξ=0 modelling, ignoring the interaction. We find the fiducial growth parameter f is generally recovered even for very large values of ξ both at z=0.5 and z=1. The ξ=0 modelling is most biased in its estimation of f for the phantom w=‑1.1 case.

Estimation for general birth-death processes

PubMed Central

Crawford, Forrest W.; Minin, Vladimir N.; Suchard, Marc A.

2013-01-01

Birth-death processes (BDPs) are continuous-time Markov chains that track the number of “particles” in a system over time. While widely used in population biology, genetics and ecology, statistical inference of the instantaneous particle birth and death rates remains largely limited to restrictive linear BDPs in which per-particle birth and death rates are constant. Researchers often observe the number of particles at discrete times, necessitating data augmentation procedures such as expectation-maximization (EM) to find maximum likelihood estimates. For BDPs on finite state-spaces, there are powerful matrix methods for computing the conditional expectations needed for the E-step of the EM algorithm. For BDPs on infinite state-spaces, closed-form solutions for the E-step are available for some linear models, but most previous work has resorted to time-consuming simulation. Remarkably, we show that the E-step conditional expectations can be expressed as convolutions of computable transition probabilities for any general BDP with arbitrary rates. This important observation, along with a convenient continued fraction representation of the Laplace transforms of the transition probabilities, allows for novel and efficient computation of the conditional expectations for all BDPs, eliminating the need for truncation of the state-space or costly simulation. We use this insight to derive EM algorithms that yield maximum likelihood estimation for general BDPs characterized by various rate models, including generalized linear models. We show that our Laplace convolution technique outperforms competing methods when they are available and demonstrate a technique to accelerate EM algorithm convergence. We validate our approach using synthetic data and then apply our methods to cancer cell growth and estimation of mutation parameters in microsatellite evolution. PMID:25328261

Estimation for general birth-death processes.

PubMed

Crawford, Forrest W; Minin, Vladimir N; Suchard, Marc A

2014-04-01

Birth-death processes (BDPs) are continuous-time Markov chains that track the number of "particles" in a system over time. While widely used in population biology, genetics and ecology, statistical inference of the instantaneous particle birth and death rates remains largely limited to restrictive linear BDPs in which per-particle birth and death rates are constant. Researchers often observe the number of particles at discrete times, necessitating data augmentation procedures such as expectation-maximization (EM) to find maximum likelihood estimates. For BDPs on finite state-spaces, there are powerful matrix methods for computing the conditional expectations needed for the E-step of the EM algorithm. For BDPs on infinite state-spaces, closed-form solutions for the E-step are available for some linear models, but most previous work has resorted to time-consuming simulation. Remarkably, we show that the E-step conditional expectations can be expressed as convolutions of computable transition probabilities for any general BDP with arbitrary rates. This important observation, along with a convenient continued fraction representation of the Laplace transforms of the transition probabilities, allows for novel and efficient computation of the conditional expectations for all BDPs, eliminating the need for truncation of the state-space or costly simulation. We use this insight to derive EM algorithms that yield maximum likelihood estimation for general BDPs characterized by various rate models, including generalized linear models. We show that our Laplace convolution technique outperforms competing methods when they are available and demonstrate a technique to accelerate EM algorithm convergence. We validate our approach using synthetic data and then apply our methods to cancer cell growth and estimation of mutation parameters in microsatellite evolution.

Symmetry properties of the configuration interaction space in relation to one- and two-particle operators: The splitting theorem

NASA Astrophysics Data System (ADS)

Živković, Tomislav P.

1984-09-01

The configuration interaction (CI) space Xn built upon n electrons moving over 2n orthonormalized orbitals χi is considered. It is shown that the space Xn splits into two complementary subspaces X+n and X-n having special properties: each state Ψ+∈X+n and Ψ-∈X-n is ``alternantlike'' in the sense that it has a uniform charge density distribution over all orbitals χi and vanishing bond-orders between all orbitals of the same parity. In addition, matrix elements Γ(ij;kl) of a two-particle density matrix vanish whenever four distinct orbitals are involved and there is an odd number of orbitals of the same parity. Further, Γ(ij;lj)=γ(il)/4 ( j≠i,l), whenever (i) and (l) are of different parity. This last relation shows the connection between a two-particle (Γ) and a one-particle (γ) density matrix. ``Elementary'' alternant and antialternant operators are identified. These operators connect either only the states in the same subspace, or only the states in different subspaces, and each one- and two-particle symmetric operator can be represented by their linear combination. Alternant Hamiltonians, which can be represented as linear combinations of elementary alternant operators, have alternantlike eigenstates. It is also shown that each symmetric Hamiltonian possessing alternantlike eigenstates can be represented as such a linear combination. In particular, the PPP Hamiltonian describing an alternant hydrocarbon system is such a case. Complementary subspaces X+n and X-n can be explicitly constructed using the so-called regular resonance structures (RRS's) which are normalized determinants containing mutually disjunct bond orbitals. Expressions for the derivation of matrix elements of one- and two-particle operators between different RRS's are also derived.

Multiple summing operators on C(K) spaces

NASA Astrophysics Data System (ADS)

Pérez-García, David; Villanueva, Ignacio

2004-04-01

In this paper, we characterize, for 1≤ p<∞, the multiple ( p, 1)-summing multilinear operators on the product of C(K) spaces in terms of their representing polymeasures. As consequences, we obtain a new characterization of ( p, 1)-summing linear operators on C(K) in terms of their representing measures and a new multilinear characterization of L ∞ spaces. We also solve a problem stated by M.S. Ramanujan and E. Schock, improve a result of H. P. Rosenthal and S. J. Szarek, and give new results about polymeasures.

Robust and real-time control of magnetic bearings for space engines

NASA Technical Reports Server (NTRS)

Sinha, Alok; Wang, Kon-Well; Mease, K.; Lewis, S.

1991-01-01

Currently, NASA Lewis Research Center is developing magnetic bearings for Space Shuttle Main Engine (SSME) turbopumps. The control algorithms which have been used are based on either the proportional-intergral-derivative control (PID) approach or the linear quadratic (LQ) state space approach. These approaches lead to an acceptable performance only when the system model is accurately known, which is seldom true in practice. For example, the rotor eccentricity, which is a major source of vibration at high speeds, cannot be predicted accurately. Furthermore, the dynamics of a rotor shaft, which must be treated as a flexible system to model the elastic rotor shaft, is infinite dimensional in theory and the controller can only be developed on the basis of a finite number of modes. Therefore, the development of the control system is further complicated by the possibility of closed loop system instability because of residual or uncontrolled modes, the so called spillover problem. Consequently, novel control algorithms for magnetic bearings are being developed to be robust to inevitable parametric uncertainties, external disturbances, spillover phenomenon and noise. Also, as pointed out earlier, magnetic bearings must exhibit good performance at a speed over 30,000 rpm. This implies that the sampling period available for the design of a digital control system has to be of the order of 0.5 milli-seconds. Therefore, feedback coefficients and other required controller parameters have to be computed off-line so that the on-line computational burden is extremely small. The development of the robust and real-time control algorithms is based on the sliding mode control theory. In this method, a dynamic system is made to move along a manifold of sliding hyperplanes to the origin of the state space. The number of sliding hyperplanes equals that of actuators. The sliding mode controller has two parts; linear state feedback and nonlinear terms. The nonlinear terms guarantee that the systems would reach the intersection of all sliding hyperplanes and remain on it when bounds on the errors in the system parameters and external disturbances are known. The linear part of the control drives the system to the origin of state space. Another important feature is that the controller parameter can be computed off-line. Consequently, on-line computational burden is small.

Entanglement, holography and causal diamonds

NASA Astrophysics Data System (ADS)

de Boer, Jan; Haehl, Felix M.; Heller, Michal P.; Myers, Robert C.

2016-08-01

We argue that the degrees of freedom in a d-dimensional CFT can be reorganized in an insightful way by studying observables on the moduli space of causal diamonds (or equivalently, the space of pairs of timelike separated points). This 2 d-dimensional space naturally captures some of the fundamental nonlocality and causal structure inherent in the entanglement of CFT states. For any primary CFT operator, we construct an observable on this space, which is defined by smearing the associated one-point function over causal diamonds. Known examples of such quantities are the entanglement entropy of vacuum excitations and its higher spin generalizations. We show that in holographic CFTs, these observables are given by suitably defined integrals of dual bulk fields over the corresponding Ryu-Takayanagi minimal surfaces. Furthermore, we explain connections to the operator product expansion and the first law of entanglemententropy from this unifying point of view. We demonstrate that for small perturbations of the vacuum, our observables obey linear two-derivative equations of motion on the space of causal diamonds. In two dimensions, the latter is given by a product of two copies of a two-dimensional de Sitter space. For a class of universal states, we show that the entanglement entropy and its spin-three generalization obey nonlinear equations of motion with local interactions on this moduli space, which can be identified with Liouville and Toda equations, respectively. This suggests the possibility of extending the definition of our new observables beyond the linear level more generally and in such a way that they give rise to new dynamically interacting theories on the moduli space of causal diamonds. Various challenges one has to face in order to implement this idea are discussed.

Modelling, analyses and design of switching converters

NASA Technical Reports Server (NTRS)

Cuk, S. M.; Middlebrook, R. D.

1978-01-01

A state-space averaging method for modelling switching dc-to-dc converters for both continuous and discontinuous conduction mode is developed. In each case the starting point is the unified state-space representation, and the end result is a complete linear circuit model, for each conduction mode, which correctly represents all essential features, namely, the input, output, and transfer properties (static dc as well as dynamic ac small-signal). While the method is generally applicable to any switching converter, it is extensively illustrated for the three common power stages (buck, boost, and buck-boost). The results for these converters are then easily tabulated owing to the fixed equivalent circuit topology of their canonical circuit model. The insights that emerge from the general state-space modelling approach lead to the design of new converter topologies through the study of generic properties of the cascade connection of basic buck and boost converters.

Homoclinic accretion solutions in the Schwarzschild-anti-de Sitter space-time

NASA Astrophysics Data System (ADS)

Mach, Patryk

2015-04-01

The aim of this paper is to clarify the distinction between homoclinic and standard (global) Bondi-type accretion solutions in the Schwarzschild-anti-de Sitter space-time. The homoclinic solutions have recently been discovered numerically for polytropic equations of state. Here I show that they exist also for certain isothermal (linear) equations of state, and an analytic solution of this type is obtained. It is argued that the existence of such solutions is generic, although for sufficiently relativistic matter models (photon gas, ultrahard equation of state) there exist global solutions that can be continued to infinity, similarly to standard Michel's solutions in the Schwarzschild space-time. In contrast to that global solutions should not exist for matter models with a nonvanishing rest-mass component, and this is demonstrated for polytropes. For homoclinic isothermal solutions I derive an upper bound on the mass of the black hole for which stationary transonic accretion is allowed.

A Blocked Linear Method for Optimizing Large Parameter Sets in Variational Monte Carlo

DOE PAGES

Zhao, Luning; Neuscamman, Eric

2017-05-17

We present a modification to variational Monte Carlo’s linear method optimization scheme that addresses a critical memory bottleneck while maintaining compatibility with both the traditional ground state variational principle and our recently-introduced variational principle for excited states. For wave function ansatzes with tens of thousands of variables, our modification reduces the required memory per parallel process from tens of gigabytes to hundreds of megabytes, making the methodology a much better fit for modern supercomputer architectures in which data communication and per-process memory consumption are primary concerns. We verify the efficacy of the new optimization scheme in small molecule tests involvingmore » both the Hilbert space Jastrow antisymmetric geminal power ansatz and real space multi-Slater Jastrow expansions. Satisfied with its performance, we have added the optimizer to the QMCPACK software package, with which we demonstrate on a hydrogen ring a prototype approach for making systematically convergent, non-perturbative predictions of Mott-insulators’ optical band gaps.« less

Nonlinear programming extensions to rational function approximation methods for unsteady aerodynamic forces

NASA Technical Reports Server (NTRS)

Tiffany, Sherwood H.; Adams, William M., Jr.

1988-01-01

The approximation of unsteady generalized aerodynamic forces in the equations of motion of a flexible aircraft are discussed. Two methods of formulating these approximations are extended to include the same flexibility in constraining the approximations and the same methodology in optimizing nonlinear parameters as another currently used extended least-squares method. Optimal selection of nonlinear parameters is made in each of the three methods by use of the same nonlinear, nongradient optimizer. The objective of the nonlinear optimization is to obtain rational approximations to the unsteady aerodynamics whose state-space realization is lower order than that required when no optimization of the nonlinear terms is performed. The free linear parameters are determined using the least-squares matrix techniques of a Lagrange multiplier formulation of an objective function which incorporates selected linear equality constraints. State-space mathematical models resulting from different approaches are described and results are presented that show comparative evaluations from application of each of the extended methods to a numerical example.

Tangent linear super-parameterization: attributable, decomposable moist processes for tropical variability studies

NASA Astrophysics Data System (ADS)

Mapes, B. E.; Kelly, P.; Song, S.; Hu, I. K.; Kuang, Z.

2015-12-01

An economical 10-layer global primitive equation solver is driven by time-independent forcing terms, derived from a training process, to produce a realisting eddying basic state with a tracer q trained to act like water vapor mixing ratio. Within this basic state, linearized anomaly moist physics in the column are applied in the form of a 20x20 matrix. The control matrix was derived from the results of Kuang (2010, 2012) who fitted a linear response function from a cloud resolving model in a state of deep convecting equilibrium. By editing this matrix in physical space and eigenspace, scaling and clipping its action, and optionally adding terms for processes that do not conserve moist statice energy (radiation, surface fluxes), we can decompose and explain the model's diverse moist process coupled variability. Recitified effects of this variability on the general circulation and climate, even in strictly zero-mean centered anomaly physic cases, also are sometimes surprising.

Symplectic evolution of Wigner functions in Markovian open systems.

PubMed

Brodier, O; Almeida, A M Ozorio de

2004-01-01

The Wigner function is known to evolve classically under the exclusive action of a quadratic Hamiltonian. If the system also interacts with the environment through Lindblad operators that are complex linear functions of position and momentum, then the general evolution is the convolution of a non-Hamiltonian classical propagation of the Wigner function with a phase space Gaussian that broadens in time. We analyze the consequences of this in the three generic cases of elliptic, hyperbolic, and parabolic Hamiltonians. The Wigner function always becomes positive in a definite time, which does not depend on the initial pure state. We observe the influence of classical dynamics and dissipation upon this threshold. We also derive an exact formula for the evolving linear entropy as the average of a narrowing Gaussian taken over a probability distribution that depends only on the initial state. This leads to a long time asymptotic formula for the growth of linear entropy. We finally discuss the possibility of recovering the initial state.

System modelling for LISA Pathfinder

NASA Astrophysics Data System (ADS)

Diaz-Aguiló, Marc; Grynagier, Adrien; Rais, Boutheina

LISA Pathfinder is the technology demonstrator for LISA, a space-borne gravitational waves observatory. The goal of the mission is to characterise the dynamics of the LISA Technology Package (LTP) to prove that on-board experimental conditions are compatible with the de-tection of gravitational waves. The LTP is a drag-free dynamics experiment which includes a control loop with sensors (interferometric and capacitive), actuators (capacitive actuators and thrusters), controlled disturbances (magnetic coils, heaters) and which is subject to various endogenous or exogenous noise sources such as infrared pressure or solar wind. The LTP experiment features new hardware which was never flown in space. The mission has a tight operation timeline as it is constrained to about 100 days. It is therefore vital to have efficient and precise means of investigation and diagnostics to be used during the on-orbit operations. These will be conducted using the LTP Data Analysis toolbox (LTPDA) which allows for simulation, parameter identification and various analyses (covariance analysis, state estimation) given an experimental model. The LTPDA toolbox therefore contains a series of models which are state-space representations of each component in the LTP. The State-Space Models (SSM) are objects of a state-space class within the LTPDA toolbox especially designed to address all the requirements of this tool. The user has access to a set of linear models which represent every satellite subsystem; the models are available in different forms representing 1D, 2D and 3D systems, each with settable symbolic and numeric parameters. To limit the possible errors, the models can be automatically linked to produce composite systems and closed-loops of the LTP. Finally, for the sake of completeness, accuracy and maintainability of the tool, the models contain all the physical information they mimic (i.e. variable units, description of parameters, description of inputs/outputs, etc). Models developed for this work include the fixed-point linearized equations of motion for the LTP and the linear models for sensors and actuators with their noise modelling blocks issued from the analysis of the individual actuators. The drag-free controller model includes the dis-crete delays expected in the hardware. In this work we briefly describe the software architecture, in order to concentrate then on the physical description of the models. This is supported by an overview of different user scenarios and some examples of model analysis that highlight the advantages of this high-level programming engineering toolbox for space mission data analysis and calibration.

Piecewise linear approximation for hereditary control problems

NASA Technical Reports Server (NTRS)

Propst, Georg

1987-01-01

Finite dimensional approximations are presented for linear retarded functional differential equations by use of discontinuous piecewise linear functions. The approximation scheme is applied to optimal control problems when a quadratic cost integral has to be minimized subject to the controlled retarded system. It is shown that the approximate optimal feedback operators converge to the true ones both in case the cost integral ranges over a finite time interval as well as in the case it ranges over an infinite time interval. The arguments in the latter case rely on the fact that the piecewise linear approximations to stable systems are stable in a uniform sense. This feature is established using a vector-component stability criterion in the state space R(n) x L(2) and the favorable eigenvalue behavior of the piecewise linear approximations.

Attitude estimation of earth orbiting satellites by decomposed linear recursive filters

NASA Technical Reports Server (NTRS)

Kou, S. R.

1975-01-01

Attitude estimation of earth orbiting satellites (including Large Space Telescope) subjected to environmental disturbances and noises was investigated. Modern control and estimation theory is used as a tool to design an efficient estimator for attitude estimation. Decomposed linear recursive filters for both continuous-time systems and discrete-time systems are derived. By using this accurate estimation of the attitude of spacecrafts, state variable feedback controller may be designed to achieve (or satisfy) high requirements of system performance.

Derivative-Free Estimation of the Score Vector and Observed Information Matrix with Application to State-Space Models

DTIC Science & Technology

2015-07-14

2008). Sequential Monte Carlo smoothing with applica- tion to parameter estimation in non-linear state space models. Bernoulli , 14, 155-179. [22] Parikh...1BcΣ(θ?,δ)(Θ) ] = o ( τk ) for all k ∈ N. (45) The other integral is over the ball BΣ(θ?, δ), i.e. close to θ?; hence we perform a Taylor expansion of...1] R3 (θ, θ?) = ∑ |α|=4 ∂αϕ (θ? + cθ (θ − θ?)) (θ − θ?)α α! . 26 We now use the symmetry of the normal distribution N ( θ?, τ2Σ ) on the ball BΣ(θ

Approximations of thermoelastic and viscoelastic control systems

NASA Technical Reports Server (NTRS)

Burns, J. A.; Liu, Z. Y.; Miller, R. E.

1990-01-01

Well-posed models and computational algorithms are developed and analyzed for control of a class of partial differential equations that describe the motions of thermo-viscoelastic structures. An abstract (state space) framework and a general well-posedness result are presented that can be applied to a large class of thermo-elastic and thermo-viscoelastic models. This state space framework is used in the development of a computational scheme to be used in the solution of a linear quadratic regulator (LQR) control problem. A detailed convergence proof is provided for the viscoelastic model and several numerical results are presented to illustrate the theory and to analyze problems for which the theory is incomplete.

Indirect Identification of Linear Stochastic Systems with Known Feedback Dynamics

NASA Technical Reports Server (NTRS)

Huang, Jen-Kuang; Hsiao, Min-Hung; Cox, David E.

1996-01-01

An algorithm is presented for identifying a state-space model of linear stochastic systems operating under known feedback controller. In this algorithm, only the reference input and output of closed-loop data are required. No feedback signal needs to be recorded. The overall closed-loop system dynamics is first identified. Then a recursive formulation is derived to compute the open-loop plant dynamics from the identified closed-loop system dynamics and known feedback controller dynamics. The controller can be a dynamic or constant-gain full-state feedback controller. Numerical simulations and test data of a highly unstable large-gap magnetic suspension system are presented to demonstrate the feasibility of this indirect identification method.

A methodology for designing robust multivariable nonlinear control systems. Ph.D. Thesis

NASA Technical Reports Server (NTRS)

Grunberg, D. B.

1986-01-01

A new methodology is described for the design of nonlinear dynamic controllers for nonlinear multivariable systems providing guarantees of closed-loop stability, performance, and robustness. The methodology is an extension of the Linear-Quadratic-Gaussian with Loop-Transfer-Recovery (LQG/LTR) methodology for linear systems, thus hinging upon the idea of constructing an approximate inverse operator for the plant. A major feature of the methodology is a unification of both the state-space and input-output formulations. In addition, new results on stability theory, nonlinear state estimation, and optimal nonlinear regulator theory are presented, including the guaranteed global properties of the extended Kalman filter and optimal nonlinear regulators.

Classical phase space and Hadamard states in the BRST formalism for gauge field theories on curved spacetime

NASA Astrophysics Data System (ADS)

Wrochna, Michał; Zahn, Jochen

We investigate linearized gauge theories on globally hyperbolic spacetimes in the BRST formalism. A consistent definition of the classical phase space and of its Cauchy surface analogue is proposed. We prove that it is isomorphic to the phase space in the ‘subsidiary condition’ approach of Hack and Schenkel in the case of Maxwell, Yang-Mills, and Rarita-Schwinger fields. Defining Hadamard states in the BRST formalism in a standard way, their existence in the Maxwell and Yang-Mills case is concluded from known results in the subsidiary condition (or Gupta-Bleuler) formalism. Within our framework, we also formulate criteria for non-degeneracy of the phase space in terms of BRST cohomology and discuss special cases. These include an example in the Yang-Mills case, where degeneracy is not related to a non-trivial topology of the Cauchy surface.

Sparse signals recovered by non-convex penalty in quasi-linear systems.

PubMed

Cui, Angang; Li, Haiyang; Wen, Meng; Peng, Jigen

2018-01-01

The goal of compressed sensing is to reconstruct a sparse signal under a few linear measurements far less than the dimension of the ambient space of the signal. However, many real-life applications in physics and biomedical sciences carry some strongly nonlinear structures, and the linear model is no longer suitable. Compared with the compressed sensing under the linear circumstance, this nonlinear compressed sensing is much more difficult, in fact also NP-hard, combinatorial problem, because of the discrete and discontinuous nature of the [Formula: see text]-norm and the nonlinearity. In order to get a convenience for sparse signal recovery, we set the nonlinear models have a smooth quasi-linear nature in this paper, and study a non-convex fraction function [Formula: see text] in this quasi-linear compressed sensing. We propose an iterative fraction thresholding algorithm to solve the regularization problem [Formula: see text] for all [Formula: see text]. With the change of parameter [Formula: see text], our algorithm could get a promising result, which is one of the advantages for our algorithm compared with some state-of-art algorithms. Numerical experiments show that our method performs much better than some state-of-the-art methods.

Leveraging Structural Characteristics of Interdependent Networks to Model Non-Linear Cascading Risks

DTIC Science & Technology

2013-04-01

and Teresa Wu, Arizona State University Eugene Rex Jalao, Arizona State University and University of the Philippines Christopher Auger, Lars Baldus...Institute of Technology The RITE Approach to Agile Acquisition Timothy Boyce, Iva Sherman, and Nicholas Roussel Space and Naval Warfare Systems Center...Demonstration Office: Ad Hoc Problem Solving as a Mechanism for Adaptive Change Kathryn Aten and John T . Dillard Naval Postgraduate School A

Toward Optimal Manifold Hashing via Discrete Locally Linear Embedding.

PubMed

Rongrong Ji; Hong Liu; Liujuan Cao; Di Liu; Yongjian Wu; Feiyue Huang

2017-11-01

Binary code learning, also known as hashing, has received increasing attention in large-scale visual search. By transforming high-dimensional features to binary codes, the original Euclidean distance is approximated via Hamming distance. More recently, it is advocated that it is the manifold distance, rather than the Euclidean distance, that should be preserved in the Hamming space. However, it retains as an open problem to directly preserve the manifold structure by hashing. In particular, it first needs to build the local linear embedding in the original feature space, and then quantize such embedding to binary codes. Such a two-step coding is problematic and less optimized. Besides, the off-line learning is extremely time and memory consuming, which needs to calculate the similarity matrix of the original data. In this paper, we propose a novel hashing algorithm, termed discrete locality linear embedding hashing (DLLH), which well addresses the above challenges. The DLLH directly reconstructs the manifold structure in the Hamming space, which learns optimal hash codes to maintain the local linear relationship of data points. To learn discrete locally linear embeddingcodes, we further propose a discrete optimization algorithm with an iterative parameters updating scheme. Moreover, an anchor-based acceleration scheme, termed Anchor-DLLH, is further introduced, which approximates the large similarity matrix by the product of two low-rank matrices. Experimental results on three widely used benchmark data sets, i.e., CIFAR10, NUS-WIDE, and YouTube Face, have shown superior performance of the proposed DLLH over the state-of-the-art approaches.

A new state space model for the NASA/JPL 70-meter antenna servo controls

NASA Technical Reports Server (NTRS)

Hill, R. E.

1987-01-01

A control axis referenced model of the NASA/JPL 70-m antenna structure is combined with the dynamic equations of servo components to produce a comprehansive state variable (matrix) model of the coupled system. An interactive Fortran program for generating the linear system model and computing its salient parameters is described. Results are produced in a state variable, block diagram, and in factored transfer function forms to facilitate design and analysis by classical as well as modern control methods.

Many-body instabilities and mass generation in slow Dirac materials

NASA Astrophysics Data System (ADS)

Triola, Christopher; Zhu, Jian-Xin; Migliori, Albert; Balatsky, Alexander V.

2015-07-01

Some Kondo insulators are expected to possess topologically protected surface states with linear Dirac spectrum: the topological Kondo insulators. Because the bulk states of these systems typically have heavy effective electron masses, the surface states may exhibit extraordinarily small Fermi velocities that could force the effective fine structure constant of the surface states into the strong coupling regime. Using a tight-binding model, we study the many-body instabilities of these systems and identify regions of parameter space in which the system exhibits spin density wave and charge density wave order.

Linear control theory for gene network modeling.

PubMed

Shin, Yong-Jun; Bleris, Leonidas

2010-09-16

Systems biology is an interdisciplinary field that aims at understanding complex interactions in cells. Here we demonstrate that linear control theory can provide valuable insight and practical tools for the characterization of complex biological networks. We provide the foundation for such analyses through the study of several case studies including cascade and parallel forms, feedback and feedforward loops. We reproduce experimental results and provide rational analysis of the observed behavior. We demonstrate that methods such as the transfer function (frequency domain) and linear state-space (time domain) can be used to predict reliably the properties and transient behavior of complex network topologies and point to specific design strategies for synthetic networks.

Quantum Entanglement in Random Physical States

NASA Astrophysics Data System (ADS)

Hamma, Alioscia; Santra, Siddhartha; Zanardi, Paolo

2012-07-01

Most states in the Hilbert space are maximally entangled. This fact has proven useful to investigate—among other things—the foundations of statistical mechanics. Unfortunately, most states in the Hilbert space of a quantum many-body system are not physically accessible. We define physical ensembles of states acting on random factorized states by a circuit of length k of random and independent unitaries with local support. We study the typicality of entanglement by means of the purity of the reduced state. We find that for a time k=O(1), the typical purity obeys the area law. Thus, the upper bounds for area law are actually saturated, on average, with a variance that goes to zero for large systems. Similarly, we prove that by means of local evolution a subsystem of linear dimensions L is typically entangled with a volume law when the time scales with the size of the subsystem. Moreover, we show that for large values of k the reduced state becomes very close to the completely mixed state.

On neural networks in identification and control of dynamic systems

NASA Technical Reports Server (NTRS)

Phan, Minh; Juang, Jer-Nan; Hyland, David C.

1993-01-01

This paper presents a discussion of the applicability of neural networks in the identification and control of dynamic systems. Emphasis is placed on the understanding of how the neural networks handle linear systems and how the new approach is related to conventional system identification and control methods. Extensions of the approach to nonlinear systems are then made. The paper explains the fundamental concepts of neural networks in their simplest terms. Among the topics discussed are feed forward and recurrent networks in relation to the standard state-space and observer models, linear and nonlinear auto-regressive models, linear, predictors, one-step ahead control, and model reference adaptive control for linear and nonlinear systems. Numerical examples are presented to illustrate the application of these important concepts.

Analysis of Operating Principles with S-system Models

PubMed Central

Lee, Yun; Chen, Po-Wei; Voit, Eberhard O.

2011-01-01

Operating principles address general questions regarding the response dynamics of biological systems as we observe or hypothesize them, in comparison to a priori equally valid alternatives. In analogy to design principles, the question arises: Why are some operating strategies encountered more frequently than others and in what sense might they be superior? It is at this point impossible to study operation principles in complete generality, but the work here discusses the important situation where a biological system must shift operation from its normal steady state to a new steady state. This situation is quite common and includes many stress responses. We present two distinct methods for determining different solutions to this task of achieving a new target steady state. Both methods utilize the property of S-system models within Biochemical Systems Theory (BST) that steady-states can be explicitly represented as systems of linear algebraic equations. The first method uses matrix inversion, a pseudo-inverse, or regression to characterize the entire admissible solution space. Operations on the basis of the solution space permit modest alterations of the transients toward the target steady state. The second method uses standard or mixed integer linear programming to determine admissible solutions that satisfy criteria of functional effectiveness, which are specified beforehand. As an illustration, we use both methods to characterize alternative response patterns of yeast subjected to heat stress, and compare them with observations from the literature. PMID:21377479

Nonlinear programming extensions to rational function approximations of unsteady aerodynamics

NASA Technical Reports Server (NTRS)

Tiffany, Sherwood H.; Adams, William M., Jr.

1987-01-01

This paper deals with approximating unsteady generalized aerodynamic forces in the equations of motion of a flexible aircraft. Two methods of formulating these approximations are extended to include both the same flexibility in constraining them and the same methodology in optimizing nonlinear parameters as another currently used 'extended least-squares' method. Optimal selection of 'nonlinear' parameters is made in each of the three methods by use of the same nonlinear (nongradient) optimizer. The objective of the nonlinear optimization is to obtain rational approximations to the unsteady aerodynamics whose state-space realization is of lower order than that required when no optimization of the nonlinear terms is performed. The free 'linear' parameters are determined using least-squares matrix techniques on a Lagrange multiplier formulation of an objective function which incorporates selected linear equality constraints. State-space mathematical models resulting from the different approaches are described, and results are presented which show comparative evaluations from application of each of the extended methods to a numerical example. The results obtained for the example problem show a significant (up to 63 percent) reduction in the number of differential equations used to represent the unsteady aerodynamic forces in linear time-invariant equations of motion as compared to a conventional method in which nonlinear terms are not optimized.

A Graphical Approach to the Standard Principal-Agent Model.

ERIC Educational Resources Information Center

Zhou, Xianming

2002-01-01

States the principal-agent theory is difficult to teach because of its technical complexity and intractability. Indicates the equilibrium in the contract space is defined by the incentive parameter and insurance component of pay under a linear contract. Describes a graphical approach that students with basic knowledge of algebra and…

Nonlinear vs. linear biasing in Trp-cage folding simulations

NASA Astrophysics Data System (ADS)

Spiwok, Vojtěch; Oborský, Pavel; Pazúriková, Jana; Křenek, Aleš; Králová, Blanka

2015-03-01

Biased simulations have great potential for the study of slow processes, including protein folding. Atomic motions in molecules are nonlinear, which suggests that simulations with enhanced sampling of collective motions traced by nonlinear dimensionality reduction methods may perform better than linear ones. In this study, we compare an unbiased folding simulation of the Trp-cage miniprotein with metadynamics simulations using both linear (principle component analysis) and nonlinear (Isomap) low dimensional embeddings as collective variables. Folding of the mini-protein was successfully simulated in 200 ns simulation with linear biasing and non-linear motion biasing. The folded state was correctly predicted as the free energy minimum in both simulations. We found that the advantage of linear motion biasing is that it can sample a larger conformational space, whereas the advantage of nonlinear motion biasing lies in slightly better resolution of the resulting free energy surface. In terms of sampling efficiency, both methods are comparable.

Nonlinear vs. linear biasing in Trp-cage folding simulations.

PubMed

Spiwok, Vojtěch; Oborský, Pavel; Pazúriková, Jana; Křenek, Aleš; Králová, Blanka

2015-03-21

Biased simulations have great potential for the study of slow processes, including protein folding. Atomic motions in molecules are nonlinear, which suggests that simulations with enhanced sampling of collective motions traced by nonlinear dimensionality reduction methods may perform better than linear ones. In this study, we compare an unbiased folding simulation of the Trp-cage miniprotein with metadynamics simulations using both linear (principle component analysis) and nonlinear (Isomap) low dimensional embeddings as collective variables. Folding of the mini-protein was successfully simulated in 200 ns simulation with linear biasing and non-linear motion biasing. The folded state was correctly predicted as the free energy minimum in both simulations. We found that the advantage of linear motion biasing is that it can sample a larger conformational space, whereas the advantage of nonlinear motion biasing lies in slightly better resolution of the resulting free energy surface. In terms of sampling efficiency, both methods are comparable.

A Study of Strong Stability of Distributed Systems. Ph.D. Thesis

NASA Technical Reports Server (NTRS)

Cataltepe, Tayfun

1989-01-01

The strong stability of distributed systems is studied and the problem of characterizing strongly stable semigroups of operators associated with distributed systems is addressed. Main emphasis is on contractive systems. Three different approaches to characterization of strongly stable contractive semigroups are developed. The first one is an operator theoretical approach. Using the theory of dilations, it is shown that every strongly stable contractive semigroup is related to the left shift semigroup on an L(exp 2) space. Then, a decomposition for the state space which identifies strongly stable and unstable states is introduced. Based on this decomposition, conditions for a contractive semigroup to be strongly stable are obtained. Finally, extensions of Lyapunov's equation for distributed parameter systems are investigated. Sufficient conditions for weak and strong stabilities of uniformly bounded semigroups are obtained by relaxing the equivalent norm condition on the right hand side of the Lyanupov equation. These characterizations are then applied to the problem of feedback stabilization. First, it is shown via the state space decomposition that under certain conditions a contractive system (A,B) can be strongly stabilized by the feedback -B(*). Then, application of the extensions of the Lyapunov equation results in sufficient conditions for weak, strong, and exponential stabilizations of contractive systems by the feedback -B(*). Finally, it is shown that for a contractive system, the first derivative of x with respect to time = Ax + Bu (where B is any linear bounded operator), there is a related linear quadratic regulator problem and a corresponding steady state Riccati equation which always has a bounded nonnegative solution.

Constructing an Efficient Self-Tuning Aircraft Engine Model for Control and Health Management Applications

NASA Technical Reports Server (NTRS)

Armstrong, Jeffrey B.; Simon, Donald L.

2012-01-01

Self-tuning aircraft engine models can be applied for control and health management applications. The self-tuning feature of these models minimizes the mismatch between any given engine and the underlying engineering model describing an engine family. This paper provides details of the construction of a self-tuning engine model centered on a piecewise linear Kalman filter design. Starting from a nonlinear transient aerothermal model, a piecewise linear representation is first extracted. The linearization procedure creates a database of trim vectors and state-space matrices that are subsequently scheduled for interpolation based on engine operating point. A series of steady-state Kalman gains can next be constructed from a reduced-order form of the piecewise linear model. Reduction of the piecewise linear model to an observable dimension with respect to available sensed engine measurements can be achieved using either a subset or an optimal linear combination of "health" parameters, which describe engine performance. The resulting piecewise linear Kalman filter is then implemented for faster-than-real-time processing of sensed engine measurements, generating outputs appropriate for trending engine performance, estimating both measured and unmeasured parameters for control purposes, and performing on-board gas-path fault diagnostics. Computational efficiency is achieved by designing multidimensional interpolation algorithms that exploit the shared scheduling of multiple trim vectors and system matrices. An example application illustrates the accuracy of a self-tuning piecewise linear Kalman filter model when applied to a nonlinear turbofan engine simulation. Additional discussions focus on the issue of transient response accuracy and the advantages of a piecewise linear Kalman filter in the context of validation and verification. The techniques described provide a framework for constructing efficient self-tuning aircraft engine models from complex nonlinear simulations.Self-tuning aircraft engine models can be applied for control and health management applications. The self-tuning feature of these models minimizes the mismatch between any given engine and the underlying engineering model describing an engine family. This paper provides details of the construction of a self-tuning engine model centered on a piecewise linear Kalman filter design. Starting from a nonlinear transient aerothermal model, a piecewise linear representation is first extracted. The linearization procedure creates a database of trim vectors and state-space matrices that are subsequently scheduled for interpolation based on engine operating point. A series of steady-state Kalman gains can next be constructed from a reduced-order form of the piecewise linear model. Reduction of the piecewise linear model to an observable dimension with respect to available sensed engine measurements can be achieved using either a subset or an optimal linear combination of "health" parameters, which describe engine performance. The resulting piecewise linear Kalman filter is then implemented for faster-than-real-time processing of sensed engine measurements, generating outputs appropriate for trending engine performance, estimating both measured and unmeasured parameters for control purposes, and performing on-board gas-path fault diagnostics. Computational efficiency is achieved by designing multidimensional interpolation algorithms that exploit the shared scheduling of multiple trim vectors and system matrices. An example application illustrates the accuracy of a self-tuning piecewise linear Kalman filter model when applied to a nonlinear turbofan engine simulation. Additional discussions focus on the issue of transient response accuracy and the advantages of a piecewise linear Kalman filter in the context of validation and verification. The techniques described provide a framework for constructing efficient self-tuning aircraft engine models from complex nonlinear simulatns.

Lidar-Based Estimates of Above-Ground Biomass in the Continental US and Mexico Using Ground, Airborne, and Satellite Observations

NASA Technical Reports Server (NTRS)

Nelson, Ross; Margolis, Hank; Montesano, Paul; Sun, Guoqing; Cook, Bruce; Corp, Larry; Andersen, Hans-Erik; DeJong, Ben; Pellat, Fernando Paz; Fickel, Thaddeus;

Modeling of Two-Wheeled Self-Balancing Robot Driven by DC Gearmotors

NASA Astrophysics Data System (ADS)

Frankovský, P.; Dominik, L.; Gmiterko, A.; Virgala, I.; Kurylo, P.; Perminova, O.

2017-08-01

This paper is aimed at modelling a two-wheeled self-balancing robot driven by the geared DC motors. A mathematical model consists of two main parts, the model of robot's mechanical structure and the model of the actuator. Linearized equations of motion are derived and the overall model of the two-wheeled self-balancing robot is represented in state-space realization for the purpose of state feedback controller design.

Multilevel Mixture Kalman Filter

NASA Astrophysics Data System (ADS)

Guo, Dong; Wang, Xiaodong; Chen, Rong

2004-12-01

The mixture Kalman filter is a general sequential Monte Carlo technique for conditional linear dynamic systems. It generates samples of some indicator variables recursively based on sequential importance sampling (SIS) and integrates out the linear and Gaussian state variables conditioned on these indicators. Due to the marginalization process, the complexity of the mixture Kalman filter is quite high if the dimension of the indicator sampling space is high. In this paper, we address this difficulty by developing a new Monte Carlo sampling scheme, namely, the multilevel mixture Kalman filter. The basic idea is to make use of the multilevel or hierarchical structure of the space from which the indicator variables take values. That is, we draw samples in a multilevel fashion, beginning with sampling from the highest-level sampling space and then draw samples from the associate subspace of the newly drawn samples in a lower-level sampling space, until reaching the desired sampling space. Such a multilevel sampling scheme can be used in conjunction with the delayed estimation method, such as the delayed-sample method, resulting in delayed multilevel mixture Kalman filter. Examples in wireless communication, specifically the coherent and noncoherent 16-QAM over flat-fading channels, are provided to demonstrate the performance of the proposed multilevel mixture Kalman filter.

Development of a Linear Stirling Model with Varying Heat Inputs

NASA Technical Reports Server (NTRS)

Regan, Timothy F.; Lewandowski, Edward J.

2007-01-01

The linear model of the Stirling system developed by NASA Glenn Research Center (GRC) has been extended to include a user-specified heat input. Previously developed linear models were limited to the Stirling convertor and electrical load. They represented the thermodynamic cycle with pressure factors that remained constant. The numerical values of the pressure factors were generated by linearizing GRC s non-linear System Dynamic Model (SDM) of the convertor at a chosen operating point. The pressure factors were fixed for that operating point, thus, the model lost accuracy if a transition to a different operating point were simulated. Although the previous linear model was used in developing controllers that manipulated current, voltage, and piston position, it could not be used in the development of control algorithms that regulated hot-end temperature. This basic model was extended to include the thermal dynamics associated with a hot-end temperature that varies over time in response to external changes as well as to changes in the Stirling cycle. The linear model described herein includes not only dynamics of the piston, displacer, gas, and electrical circuit, but also the transient effects of the heater head thermal inertia. The linear version algebraically couples two separate linear dynamic models, one model of the Stirling convertor and one model of the thermal system, through the pressure factors. The thermal system model includes heat flow of heat transfer fluid, insulation loss, and temperature drops from the heat source to the Stirling convertor expansion space. The linear model was compared to a nonlinear model, and performance was very similar. The resulting linear model can be implemented in a variety of computing environments, and is suitable for analysis with classical and state space controls analysis techniques.

Multi-model predictive control based on LMI: from the adaptation of the state-space model to the analytic description of the control law

NASA Astrophysics Data System (ADS)

Falugi, P.; Olaru, S.; Dumur, D.

2010-08-01

This article proposes an explicit robust predictive control solution based on linear matrix inequalities (LMIs). The considered predictive control strategy uses different local descriptions of the system dynamics and uncertainties and thus allows the handling of less conservative input constraints. The computed control law guarantees constraint satisfaction and asymptotic stability. The technique is effective for a class of nonlinear systems embedded into polytopic models. A detailed discussion of the procedures which adapt the partition of the state space is presented. For the practical implementation the construction of suitable (explicit) descriptions of the control law are described upon concrete algorithms.

Modeling and Analysis of Large Amplitude Flight Maneuvers

NASA Technical Reports Server (NTRS)

Anderson, Mark R.

2004-01-01

Analytical methods for stability analysis of large amplitude aircraft motion have been slow to develop because many nonlinear system stability assessment methods are restricted to a state-space dimension of less than three. The proffered approach is to create regional cell-to-cell maps for strategically located two-dimensional subspaces within the higher-dimensional model statespace. These regional solutions capture nonlinear behavior better than linearized point solutions. They also avoid the computational difficulties that emerge when attempting to create a cell map for the entire state-space. Example stability results are presented for a general aviation aircraft and a micro-aerial vehicle configuration. The analytical results are consistent with characteristics that were discovered during previous flight-testing.

An optical flow-based state-space model of the vocal folds.

PubMed

Granados, Alba; Brunskog, Jonas

2017-06-01

High-speed movies of the vocal fold vibration are valuable data to reveal vocal fold features for voice pathology diagnosis. This work presents a suitable Bayesian model and a purely theoretical discussion for further development of a framework for continuum biomechanical features estimation. A linear and Gaussian nonstationary state-space model is proposed and thoroughly discussed. The evolution model is based on a self-sustained three-dimensional finite element model of the vocal folds, and the observation model involves a dense optical flow algorithm. The results show that the method is able to capture different deformation patterns between the computed optical flow and the finite element deformation, controlled by the choice of the model tissue parameters.

Phenomenology of TeV little string theory from holography.

PubMed

Antoniadis, Ignatios; Arvanitaki, Asimina; Dimopoulos, Savas; Giveon, Amit

2012-02-24

We study the graviton phenomenology of TeV little string theory by exploiting its holographic gravity dual five-dimensional theory. This dual corresponds to a linear dilaton background with a large bulk that constrains the standard model fields on the boundary of space. The linear dilaton geometry produces a unique Kaluza-Klein graviton spectrum that exhibits a ~TeV mass gap followed by a near continuum of narrow resonances that are separated from each other by only ~30 GeV. Resonant production of these particles at the LHC is the signature of this framework that distinguishes it from large extra dimensions, where the Kaluza-Klein states are almost a continuum with no mass gap, and warped models, where the states are separated by a TeV.

Application of Multi-Hypothesis Sequential Monte Carlo for Breakup Analysis

NASA Astrophysics Data System (ADS)

Faber, W. R.; Zaidi, W.; Hussein, I. I.; Roscoe, C. W. T.; Wilkins, M. P.; Schumacher, P. W., Jr.

As more objects are launched into space, the potential for breakup events and space object collisions is ever increasing. These events create large clouds of debris that are extremely hazardous to space operations. Providing timely, accurate, and statistically meaningful Space Situational Awareness (SSA) data is crucial in order to protect assets and operations in space. The space object tracking problem, in general, is nonlinear in both state dynamics and observations, making it ill-suited to linear filtering techniques such as the Kalman filter. Additionally, given the multi-object, multi-scenario nature of the problem, space situational awareness requires multi-hypothesis tracking and management that is combinatorially challenging in nature. In practice, it is often seen that assumptions of underlying linearity and/or Gaussianity are used to provide tractable solutions to the multiple space object tracking problem. However, these assumptions are, at times, detrimental to tracking data and provide statistically inconsistent solutions. This paper details a tractable solution to the multiple space object tracking problem applicable to space object breakup events. Within this solution, simplifying assumptions of the underlying probability density function are relaxed and heuristic methods for hypothesis management are avoided. This is done by implementing Sequential Monte Carlo (SMC) methods for both nonlinear filtering as well as hypothesis management. This goal of this paper is to detail the solution and use it as a platform to discuss computational limitations that hinder proper analysis of large breakup events.

Linear-Quadratic-Gaussian Regulator Developed for a Magnetic Bearing

NASA Technical Reports Server (NTRS)

Choi, Benjamin B.

2002-01-01

Linear-Quadratic-Gaussian (LQG) control is a modern state-space technique for designing optimal dynamic regulators. It enables us to trade off regulation performance and control effort, and to take into account process and measurement noise. The Structural Mechanics and Dynamics Branch at the NASA Glenn Research Center has developed an LQG control for a fault-tolerant magnetic bearing suspension rig to optimize system performance and to reduce the sensor and processing noise. The LQG regulator consists of an optimal state-feedback gain and a Kalman state estimator. The first design step is to seek a state-feedback law that minimizes the cost function of regulation performance, which is measured by a quadratic performance criterion with user-specified weighting matrices, and to define the tradeoff between regulation performance and control effort. The next design step is to derive a state estimator using a Kalman filter because the optimal state feedback cannot be implemented without full state measurement. Since the Kalman filter is an optimal estimator when dealing with Gaussian white noise, it minimizes the asymptotic covariance of the estimation error.

Spatio-temporal statistical models for river monitoring networks.

PubMed

Clement, L; Thas, O; Vanrolleghem, P A; Ottoy, J P

2006-01-01

When introducing new wastewater treatment plants (WWTP), investors and policy makers often want to know if there indeed is a beneficial effect of the installation of a WWTP on the river water quality. Such an effect can be established in time as well as in space. Since both temporal and spatial components affect the output of a monitoring network, their dependence structure has to be modelled. River water quality data typically come from a river monitoring network for which the spatial dependence structure is unidirectional. Thus the traditional spatio-temporal models are not appropriate, as they cannot take advantage of this directional information. In this paper, a state-space model is presented in which the spatial dependence of the state variable is represented by a directed acyclic graph, and the temporal dependence by a first-order autoregressive process. The state-space model is extended with a linear model for the mean to estimate the effect of the activation of a WWTP on the dissolved oxygen concentration downstream.

A computational algorithm for spacecraft control and momentum management

NASA Technical Reports Server (NTRS)

Dzielski, John; Bergmann, Edward; Paradiso, Joseph

1990-01-01

Developments in the area of nonlinear control theory have shown how coordinate changes in the state and input spaces of a dynamical system can be used to transform certain nonlinear differential equations into equivalent linear equations. These techniques are applied to the control of a spacecraft equipped with momentum exchange devices. An optimal control problem is formulated that incorporates a nonlinear spacecraft model. An algorithm is developed for solving the optimization problem using feedback linearization to transform to an equivalent problem involving a linear dynamical constraint and a functional approximation technique to solve for the linear dynamics in terms of the control. The original problem is transformed into an unconstrained nonlinear quadratic program that yields an approximate solution to the original problem. Two examples are presented to illustrate the results.

ADER schemes for scalar non-linear hyperbolic conservation laws with source terms in three-space dimensions

NASA Astrophysics Data System (ADS)

Toro, E. F.; Titarev, V. A.

2005-01-01

In this paper we develop non-linear ADER schemes for time-dependent scalar linear and non-linear conservation laws in one-, two- and three-space dimensions. Numerical results of schemes of up to fifth order of accuracy in both time and space illustrate that the designed order of accuracy is achieved in all space dimensions for a fixed Courant number and essentially non-oscillatory results are obtained for solutions with discontinuities. We also present preliminary results for two-dimensional non-linear systems.

First report of xanthomonas vasicola causing bacterial leaf streak on corn in the United States

USDA-ARS?s Scientific Manuscript database

In 2014 and 2015, Zea mays samples (field, seed, and popcorn) were submitted to the Plant and Pest Diagnostic Clinic at the University of Nebraska – Lincoln displaying long, dark, yellow to brown, water-soaked, linear lesions confined to the interveinal spaces of the leaves. Initial symptoms appeare...

Many-body instabilities and mass generation in slow Dirac materials

NASA Astrophysics Data System (ADS)

Triola, Christopher; Zhu, Jianxin; Migliori, Albert; Balatsky, Alexander

2015-03-01

Some Kondo insulators are expected to possess topologically protected surface states with linear Dirac spectrum, the topological Kondo insulators. Because the bulk states of these systems typically have heavy effective electron masses, the surface states may exhibit extraordinarily small Fermi velocities that could force the effective fine structure constant of the surface states into the strong coupling regime. Using a tight-binding model we study the many-body instabilities of these systems and identify regions of parameter space for which antiferromagnetic, ferromagnetic and charge density wave instabilities occur. Work Supported by USDOE BES E304.

Development of a Linear Stirling System Model with Varying Heat Inputs

NASA Technical Reports Server (NTRS)

Regan, Timothy F.; Lewandowski, Edward J.

2007-01-01

The linear model of the Stirling system developed by NASA Glenn Research Center (GRC) has been extended to include a user-specified heat input. Previously developed linear models were limited to the Stirling convertor and electrical load. They represented the thermodynamic cycle with pressure factors that remained constant. The numerical values of the pressure factors were generated by linearizing GRC's nonlinear System Dynamic Model (SDM) of the convertor at a chosen operating point. The pressure factors were fixed for that operating point, thus, the model lost accuracy if a transition to a different operating point were simulated. Although the previous linear model was used in developing controllers that manipulated current, voltage, and piston position, it could not be used in the development of control algorithms that regulated hot-end temperature. This basic model was extended to include the thermal dynamics associated with a hot-end temperature that varies over time in response to external changes as well as to changes in the Stirling cycle. The linear model described herein includes not only dynamics of the piston, displacer, gas, and electrical circuit, but also the transient effects of the heater head thermal inertia. The linear version algebraically couples two separate linear dynamic models, one model of the Stirling convertor and one model of the thermal system, through the pressure factors. The thermal system model includes heat flow of heat transfer fluid, insulation loss, and temperature drops from the heat source to the Stirling convertor expansion space. The linear model was compared to a nonlinear model, and performance was very similar. The resulting linear model can be implemented in a variety of computing environments, and is suitable for analysis with classical and state space controls analysis techniques.

Microprocessor based implementation of attitude and shape control of large space structures

NASA Technical Reports Server (NTRS)

Reddy, A. S. S. R.

1984-01-01

The feasibility of off the shelf eight bit and 16 bit microprocessors to implement linear state variable feedback control laws and assessing the real time response to spacecraft dynamics is studied. The complexity of the dynamic model is described along with the appropriate software. An experimental setup of a beam, microprocessor system for implementing the control laws and the needed generalized software to implement any state variable feedback control system is included.

SparseMaps—A systematic infrastructure for reduced-scaling electronic structure methods. III. Linear-scaling multireference domain-based pair natural orbital N-electron valence perturbation theory

NASA Astrophysics Data System (ADS)

Guo, Yang; Sivalingam, Kantharuban; Valeev, Edward F.; Neese, Frank

2016-03-01

Multi-reference (MR) electronic structure methods, such as MR configuration interaction or MR perturbation theory, can provide reliable energies and properties for many molecular phenomena like bond breaking, excited states, transition states or magnetic properties of transition metal complexes and clusters. However, owing to their inherent complexity, most MR methods are still too computationally expensive for large systems. Therefore the development of more computationally attractive MR approaches is necessary to enable routine application for large-scale chemical systems. Among the state-of-the-art MR methods, second-order N-electron valence state perturbation theory (NEVPT2) is an efficient, size-consistent, and intruder-state-free method. However, there are still two important bottlenecks in practical applications of NEVPT2 to large systems: (a) the high computational cost of NEVPT2 for large molecules, even with moderate active spaces and (b) the prohibitive cost for treating large active spaces. In this work, we address problem (a) by developing a linear scaling "partially contracted" NEVPT2 method. This development uses the idea of domain-based local pair natural orbitals (DLPNOs) to form a highly efficient algorithm. As shown previously in the framework of single-reference methods, the DLPNO concept leads to an enormous reduction in computational effort while at the same time providing high accuracy (approaching 99.9% of the correlation energy), robustness, and black-box character. In the DLPNO approach, the virtual space is spanned by pair natural orbitals that are expanded in terms of projected atomic orbitals in large orbital domains, while the inactive space is spanned by localized orbitals. The active orbitals are left untouched. Our implementation features a highly efficient "electron pair prescreening" that skips the negligible inactive pairs. The surviving pairs are treated using the partially contracted NEVPT2 formalism. A detailed comparison between the partial and strong contraction schemes is made, with conclusions that discourage the strong contraction scheme as a basis for local correlation methods due to its non-invariance with respect to rotations in the inactive and external subspaces. A minimal set of conservatively chosen truncation thresholds controls the accuracy of the method. With the default thresholds, about 99.9% of the canonical partially contracted NEVPT2 correlation energy is recovered while the crossover of the computational cost with the already very efficient canonical method occurs reasonably early; in linear chain type compounds at a chain length of around 80 atoms. Calculations are reported for systems with more than 300 atoms and 5400 basis functions.

Universal quantum computation with temporal-mode bilayer square lattices

NASA Astrophysics Data System (ADS)

Alexander, Rafael N.; Yokoyama, Shota; Furusawa, Akira; Menicucci, Nicolas C.

2018-03-01

We propose an experimental design for universal continuous-variable quantum computation that incorporates recent innovations in linear-optics-based continuous-variable cluster state generation and cubic-phase gate teleportation. The first ingredient is a protocol for generating the bilayer-square-lattice cluster state (a universal resource state) with temporal modes of light. With this state, measurement-based implementation of Gaussian unitary gates requires only homodyne detection. Second, we describe a measurement device that implements an adaptive cubic-phase gate, up to a random phase-space displacement. It requires a two-step sequence of homodyne measurements and consumes a (non-Gaussian) cubic-phase state.

Modeling of aircraft unsteady aerodynamic characteristics. Part 1: Postulated models

NASA Technical Reports Server (NTRS)

Klein, Vladislav; Noderer, Keith D.

1994-01-01

A short theoretical study of aircraft aerodynamic model equations with unsteady effects is presented. The aerodynamic forces and moments are expressed in terms of indicial functions or internal state variables. The first representation leads to aircraft integro-differential equations of motion; the second preserves the state-space form of the model equations. The formulations of unsteady aerodynamics is applied in two examples. The first example deals with a one-degree-of-freedom harmonic motion about one of the aircraft body axes. In the second example, the equations for longitudinal short-period motion are developed. In these examples, only linear aerodynamic terms are considered. The indicial functions are postulated as simple exponentials and the internal state variables are governed by linear, time-invariant, first-order differential equations. It is shown that both approaches to the modeling of unsteady aerodynamics lead to identical models.

Hadamard States for the Linearized Yang-Mills Equation on Curved Spacetime

NASA Astrophysics Data System (ADS)

Gérard, C.; Wrochna, M.

2015-07-01

We construct Hadamard states for the Yang-Mills equation linearized around a smooth, space-compact background solution. We assume the spacetime is globally hyperbolic and its Cauchy surface is compact or equal . We first consider the case when the spacetime is ultra-static, but the background solution depends on time. By methods of pseudodifferential calculus we construct a parametrix for the associated vectorial Klein-Gordon equation. We then obtain Hadamard two-point functions in the gauge theory, acting on Cauchy data. A key role is played by classes of pseudodifferential operators that contain microlocal or spectral type low-energy cutoffs. The general problem is reduced to the ultra-static spacetime case using an extension of the deformation argument of Fulling, Narcowich and Wald. As an aside, we derive a correspondence between Hadamard states and parametrices for the Cauchy problem in ordinary quantum field theory.

A finite state projection algorithm for the stationary solution of the chemical master equation.

PubMed

Gupta, Ankit; Mikelson, Jan; Khammash, Mustafa

2017-10-21

The chemical master equation (CME) is frequently used in systems biology to quantify the effects of stochastic fluctuations that arise due to biomolecular species with low copy numbers. The CME is a system of ordinary differential equations that describes the evolution of probability density for each population vector in the state-space of the stochastic reaction dynamics. For many examples of interest, this state-space is infinite, making it difficult to obtain exact solutions of the CME. To deal with this problem, the Finite State Projection (FSP) algorithm was developed by Munsky and Khammash [J. Chem. Phys. 124(4), 044104 (2006)], to provide approximate solutions to the CME by truncating the state-space. The FSP works well for finite time-periods but it cannot be used for estimating the stationary solutions of CMEs, which are often of interest in systems biology. The aim of this paper is to develop a version of FSP which we refer to as the stationary FSP (sFSP) that allows one to obtain accurate approximations of the stationary solutions of a CME by solving a finite linear-algebraic system that yields the stationary distribution of a continuous-time Markov chain over the truncated state-space. We derive bounds for the approximation error incurred by sFSP and we establish that under certain stability conditions, these errors can be made arbitrarily small by appropriately expanding the truncated state-space. We provide several examples to illustrate our sFSP method and demonstrate its efficiency in estimating the stationary distributions. In particular, we show that using a quantized tensor-train implementation of our sFSP method, problems admitting more than 100 × 10 6 states can be efficiently solved.

A finite state projection algorithm for the stationary solution of the chemical master equation

NASA Astrophysics Data System (ADS)

Gupta, Ankit; Mikelson, Jan; Khammash, Mustafa

2017-10-01

The chemical master equation (CME) is frequently used in systems biology to quantify the effects of stochastic fluctuations that arise due to biomolecular species with low copy numbers. The CME is a system of ordinary differential equations that describes the evolution of probability density for each population vector in the state-space of the stochastic reaction dynamics. For many examples of interest, this state-space is infinite, making it difficult to obtain exact solutions of the CME. To deal with this problem, the Finite State Projection (FSP) algorithm was developed by Munsky and Khammash [J. Chem. Phys. 124(4), 044104 (2006)], to provide approximate solutions to the CME by truncating the state-space. The FSP works well for finite time-periods but it cannot be used for estimating the stationary solutions of CMEs, which are often of interest in systems biology. The aim of this paper is to develop a version of FSP which we refer to as the stationary FSP (sFSP) that allows one to obtain accurate approximations of the stationary solutions of a CME by solving a finite linear-algebraic system that yields the stationary distribution of a continuous-time Markov chain over the truncated state-space. We derive bounds for the approximation error incurred by sFSP and we establish that under certain stability conditions, these errors can be made arbitrarily small by appropriately expanding the truncated state-space. We provide several examples to illustrate our sFSP method and demonstrate its efficiency in estimating the stationary distributions. In particular, we show that using a quantized tensor-train implementation of our sFSP method, problems admitting more than 100 × 106 states can be efficiently solved.

A spatial domain decomposition approach to distributed H ∞ observer design of a linear unstable parabolic distributed parameter system with spatially discrete sensors

NASA Astrophysics Data System (ADS)

Wang, Jun-Wei; Liu, Ya-Qiang; Hu, Yan-Yan; Sun, Chang-Yin

2017-12-01

This paper discusses the design problem of distributed H∞ Luenberger-type partial differential equation (PDE) observer for state estimation of a linear unstable parabolic distributed parameter system (DPS) with external disturbance and measurement disturbance. Both pointwise measurement in space and local piecewise uniform measurement in space are considered; that is, sensors are only active at some specified points or applied at part thereof of the spatial domain. The spatial domain is decomposed into multiple subdomains according to the location of the sensors such that only one sensor is located at each subdomain. By using Lyapunov technique, Wirtinger's inequality at each subdomain, and integration by parts, a Lyapunov-based design of Luenberger-type PDE observer is developed such that the resulting estimation error system is exponentially stable with an H∞ performance constraint, and presented in terms of standard linear matrix inequalities (LMIs). For the case of local piecewise uniform measurement in space, the first mean value theorem for integrals is utilised in the observer design development. Moreover, the problem of optimal H∞ observer design is also addressed in the sense of minimising the attenuation level. Numerical simulation results are presented to show the satisfactory performance of the proposed design method.

Entanglement witness criteria of strong- k-separability for multipartite quantum states

NASA Astrophysics Data System (ADS)

Yan, Siqing; Hou, Jinchuan

2018-07-01

Let H1, H2,\\ldots ,Hn be separable complex Hilbert spaces with \\dim Hi≥ 2 and n≥ 2. Assume that ρ is a state in H=H_1⊗ H_2⊗ \\cdots ⊗ H_n. ρ is called strong- k-separable (2≤ k≤ n) if ρ is separable for any k-partite division of H. In this paper, an entanglement witnesses criterion of strong- k-separability is obtained, which says that ρ is not strong- k-separable if and only if there exist a k-division space H_{m1}⊗ \\cdots ⊗ H_{mk} of H, a finite-rank linear elementary operator positive on product states Λ: B(H_{m2}⊗ \\cdots ⊗ H_{mk})→ B(H_{m1}) and a state ρ 0\\in S(H_{m1}⊗ H_{m1}), such that Tr(Wρ )<0, where W=(Id⊗ Λ ^{\\dagger })ρ 0 is an entanglement witness. In addition, several different methods of constructing entanglement witnesses for multipartite states are also given.

An atomic orbital based real-time time-dependent density functional theory for computing electronic circular dichroism band spectra

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

Goings, Joshua J.; Li, Xiaosong, E-mail: xsli@uw.edu

2016-06-21

One of the challenges of interpreting electronic circular dichroism (ECD) band spectra is that different states may have different rotatory strength signs, determined by their absolute configuration. If the states are closely spaced and opposite in sign, observed transitions may be washed out by nearby states, unlike absorption spectra where transitions are always positive additive. To accurately compute ECD bands, it is necessary to compute a large number of excited states, which may be prohibitively costly if one uses the linear-response time-dependent density functional theory (TDDFT) framework. Here we implement a real-time, atomic-orbital based TDDFT method for computing the entiremore » ECD spectrum simultaneously. The method is advantageous for large systems with a high density of states. In contrast to previous implementations based on real-space grids, the method is variational, independent of nuclear orientation, and does not rely on pseudopotential approximations, making it suitable for computation of chiroptical properties well into the X-ray regime.« less

Chaos control in delayed phase space constructed by the Takens embedding theory

NASA Astrophysics Data System (ADS)

Hajiloo, R.; Salarieh, H.; Alasty, A.

2018-01-01

In this paper, the problem of chaos control in discrete-time chaotic systems with unknown governing equations and limited measurable states is investigated. Using the time-series of only one measurable state, an algorithm is proposed to stabilize unstable fixed points. The approach consists of three steps: first, using Takens embedding theory, a delayed phase space preserving the topological characteristics of the unknown system is reconstructed. Second, a dynamic model is identified by recursive least squares method to estimate the time-series data in the delayed phase space. Finally, based on the reconstructed model, an appropriate linear delayed feedback controller is obtained for stabilizing unstable fixed points of the system. Controller gains are computed using a systematic approach. The effectiveness of the proposed algorithm is examined by applying it to the generalized hyperchaotic Henon system, prey-predator population map, and the discrete-time Lorenz system.

A dynamic measure of controllability and observability for the placement of actuators and sensors on large space structures

NASA Technical Reports Server (NTRS)

Vandervelde, W. E.; Carignan, C. R.

1982-01-01

The degree of controllability of a large space structure is found by a four step procedure: (1) finding the minimum control energy for driving the system from a given initial state to the origin in the prescribed time; (2) finding the region of initial state which can be driven to the origin with constrained control energy and time using optimal control strategy; (3) scaling the axes so that a unit displacement in every direction is equally important to control; and (4) finding the linear measurement of the weighted "volume" of the ellipsoid in the equicontrol space. For observability, the error covariance must be reduced toward zero using measurements optimally, and the criterion must be standardized by the magnitude of tolerable errors. The results obtained using these methods are applied to the vibration modes of a free-free beam.

Dynamic State Estimation of Terrestrial and Solar Plasmas

NASA Astrophysics Data System (ADS)

Kamalabadi, Farzad

A pervasive problem in virtually all branches of space science is the estimation of multi-dimensional state parameters of a dynamical system from a collection of indirect, often incomplete, and imprecise measurements. Subsequent scientific inference is predicated on rigorous analysis, interpretation, and understanding of physical observations and on the reliability of the associated quantitative statistical bounds and performance characteristics of the algorithms used. In this work, we focus on these dynamic state estimation problems and illustrate their importance in the context of two timely activities in space remote sensing. First, we discuss the estimation of multi-dimensional ionospheric state parameters from UV spectral imaging measurements anticipated to be acquired the recently selected NASA Heliophysics mission, Ionospheric Connection Explorer (ICON). Next, we illustrate that similar state-space formulations provide the means for the estimation of 3D, time-dependent densities and temperatures in the solar corona from a series of white-light and EUV measurements. We demonstrate that, while a general framework for the stochastic formulation of the state estimation problem is suited for systematic inference of the parameters of a hidden Markov process, several challenges must be addressed in the assimilation of an increasing volume and diversity of space observations. These challenges are: (1) the computational tractability when faced with voluminous and multimodal data, (2) the inherent limitations of the underlying models which assume, often incorrectly, linear dynamics and Gaussian noise, and (3) the unavailability or inaccuracy of transition probabilities and noise statistics. We argue that pursuing answers to these questions necessitates cross-disciplinary research that enables progress toward systematically reconciling observational and theoretical understanding of the space environment.

Embedding of multidimensional time-dependent observations.

PubMed

Barnard, J P; Aldrich, C; Gerber, M

2001-10-01

A method is proposed to reconstruct dynamic attractors by embedding of multivariate observations of dynamic nonlinear processes. The Takens embedding theory is combined with independent component analysis to transform the embedding into a vector space of linearly independent vectors (phase variables). The method is successfully tested against prediction of the unembedded state vector in two case studies of simulated chaotic processes.

Embedding of multidimensional time-dependent observations

NASA Astrophysics Data System (ADS)

Barnard, Jakobus P.; Aldrich, Chris; Gerber, Marius

2001-10-01

A method is proposed to reconstruct dynamic attractors by embedding of multivariate observations of dynamic nonlinear processes. The Takens embedding theory is combined with independent component analysis to transform the embedding into a vector space of linearly independent vectors (phase variables). The method is successfully tested against prediction of the unembedded state vector in two case studies of simulated chaotic processes.

Nonlinear vs. linear biasing in Trp-cage folding simulations

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

Spiwok, Vojtěch, E-mail: spiwokv@vscht.cz; Oborský, Pavel; Králová, Blanka

2015-03-21

Biased simulations have great potential for the study of slow processes, including protein folding. Atomic motions in molecules are nonlinear, which suggests that simulations with enhanced sampling of collective motions traced by nonlinear dimensionality reduction methods may perform better than linear ones. In this study, we compare an unbiased folding simulation of the Trp-cage miniprotein with metadynamics simulations using both linear (principle component analysis) and nonlinear (Isomap) low dimensional embeddings as collective variables. Folding of the mini-protein was successfully simulated in 200 ns simulation with linear biasing and non-linear motion biasing. The folded state was correctly predicted as the free energymore » minimum in both simulations. We found that the advantage of linear motion biasing is that it can sample a larger conformational space, whereas the advantage of nonlinear motion biasing lies in slightly better resolution of the resulting free energy surface. In terms of sampling efficiency, both methods are comparable.« less

Image science team

NASA Technical Reports Server (NTRS)

Ando, K.

1982-01-01

A substantial technology base of solid state pushbroom sensors exists and is in the process of further evolution at both GSFC and JPL. Technologies being developed relate to short wave infrared (SWIR) detector arrays; HgCdTe hybrid detector arrays; InSb linear and area arrays; passive coolers; spectral beam splitters; the deposition of spectral filters on detector arrays; and the functional design of the shuttle/space platform imaging spectrometer (SIS) system. Spatial and spectral characteristics of field, aircraft and space multispectral sensors are summaried. The status, field of view, and resolution of foreign land observing systems are included.

Reduced conservatism in stability robustness bounds by state transformation

NASA Technical Reports Server (NTRS)

Yedavalli, R. K.; Liang, Z.

1986-01-01

This note addresses the issue of 'conservatism' in the time domain stability robustness bounds obtained by the Liapunov approach. A state transformation is employed to improve the upper bounds on the linear time-varying perturbation of an asymptotically stable linear time-invariant system for robust stability. This improvement is due to the variance of the conservatism of the Liapunov approach with respect to the basis of the vector space in which the Liapunov function is constructed. Improved bounds are obtained, using a transformation, on elemental and vector norms of perturbations (i.e., structured perturbations) as well as on a matrix norm of perturbations (i.e., unstructured perturbations). For the case of a diagonal transformation, an algorithm is proposed to find the 'optimal' transformation. Several examples are presented to illustrate the proposed analysis.

A face and palmprint recognition approach based on discriminant DCT feature extraction.

PubMed

Jing, Xiao-Yuan; Zhang, David

2004-12-01

In the field of image processing and recognition, discrete cosine transform (DCT) and linear discrimination are two widely used techniques. Based on them, we present a new face and palmprint recognition approach in this paper. It first uses a two-dimensional separability judgment to select the DCT frequency bands with favorable linear separability. Then from the selected bands, it extracts the linear discriminative features by an improved Fisherface method and performs the classification by the nearest neighbor classifier. We detailedly analyze theoretical advantages of our approach in feature extraction. The experiments on face databases and palmprint database demonstrate that compared to the state-of-the-art linear discrimination methods, our approach obtains better classification performance. It can significantly improve the recognition rates for face and palmprint data and effectively reduce the dimension of feature space.

Elastic robot control - Nonlinear inversion and linear stabilization

NASA Technical Reports Server (NTRS)

Singh, S. N.; Schy, A. A.

1986-01-01

An approach to the control of elastic robot systems for space applications using inversion, servocompensation, and feedback stabilization is presented. For simplicity, a robot arm (PUMA type) with three rotational joints is considered. The third link is assumed to be elastic. Using an inversion algorithm, a nonlinear decoupling control law u(d) is derived such that in the closed-loop system independent control of joint angles by the three joint torquers is accomplished. For the stabilization of elastic oscillations, a linear feedback torquer control law u(s) is obtained applying linear quadratic optimization to the linearized arm model augmented with a servocompensator about the terminal state. Simulation results show that in spite of uncertainties in the payload and vehicle angular velocity, good joint angle control and damping of elastic oscillations are obtained with the torquer control law u = u(d) + u(s).

The brain as a dynamic physical system.

PubMed

McKenna, T M; McMullen, T A; Shlesinger, M F

1994-06-01

The brain is a dynamic system that is non-linear at multiple levels of analysis. Characterization of its non-linear dynamics is fundamental to our understanding of brain function. Identifying families of attractors in phase space analysis, an approach which has proven valuable in describing non-linear mechanical and electrical systems, can prove valuable in describing a range of behaviors and associated neural activity including sensory and motor repertoires. Additionally, transitions between attractors may serve as useful descriptors for analysing state changes in neurons and neural ensembles. Recent observations of synchronous neural activity, and the emerging capability to record the spatiotemporal dynamics of neural activity by voltage-sensitive dyes and electrode arrays, provide opportunities for observing the population dynamics of neural ensembles within a dynamic systems context. New developments in the experimental physics of complex systems, such as the control of chaotic systems, selection of attractors, attractor switching and transient states, can be a source of powerful new analytical tools and insights into the dynamics of neural systems.

Demonstration of a quantum controlled-NOT gate in the telecommunications band.

PubMed

Chen, Jun; Altepeter, Joseph B; Medic, Milja; Lee, Kim Fook; Gokden, Burc; Hadfield, Robert H; Nam, Sae Woo; Kumar, Prem

2008-04-04

We present the first quantum controlled-not (cnot) gate realized using a fiber-based indistinguishable photon-pair source in the 1.55 microm telecommunications band. Using this free-space cnot gate, all four Bell states are produced and fully characterized by performing quantum-state tomography, demonstrating the gate's unambiguous entangling capability and high fidelity. Telecom-band operation makes this cnot gate particularly suitable for quantum-information-processing tasks that are at the interface of quantum communication and linear optical quantum computing.

Efficient determination of the Markovian time-evolution towards a steady-state of a complex open quantum system

NASA Astrophysics Data System (ADS)

Jonsson, Thorsteinn H.; Manolescu, Andrei; Goan, Hsi-Sheng; Abdullah, Nzar Rauf; Sitek, Anna; Tang, Chi-Shung; Gudmundsson, Vidar

2017-11-01

Master equations are commonly used to describe time evolution of open systems. We introduce a general computationally efficient method for calculating a Markovian solution of the Nakajima-Zwanzig generalized master equation. We do so for a time-dependent transport of interacting electrons through a complex nano scale system in a photon cavity. The central system, described by 120 many-body states in a Fock space, is weakly coupled to the external leads. The efficiency of the approach allows us to place the bias window defined by the external leads high into the many-body spectrum of the cavity photon-dressed states of the central system revealing a cascade of intermediate transitions as the system relaxes to a steady state. The very diverse relaxation times present in the open system, reflecting radiative or non-radiative transitions, require information about the time evolution through many orders of magnitude. In our approach, the generalized master equation is mapped from a many-body Fock space of states to a Liouville space of transitions. We show that this results in a linear equation which is solved exactly through an eigenvalue analysis, which supplies information on the steady state and the time evolution of the system.

Comparison of System Identification Techniques for the Hydraulic Manipulator Test Bed (HMTB)

NASA Technical Reports Server (NTRS)

Morris, A. Terry

1996-01-01

In this thesis linear, dynamic, multivariable state-space models for three joints of the ground-based Hydraulic Manipulator Test Bed (HMTB) are identified. HMTB, housed at the NASA Langley Research Center, is a ground-based version of the Dexterous Orbital Servicing System (DOSS), a representative space station manipulator. The dynamic models of the HMTB manipulator will first be estimated by applying nonparametric identification methods to determine each joint's response characteristics using various input excitations. These excitations include sum of sinusoids, pseudorandom binary sequences (PRBS), bipolar ramping pulses, and chirp input signals. Next, two different parametric system identification techniques will be applied to identify the best dynamical description of the joints. The manipulator is localized about a representative space station orbital replacement unit (ORU) task allowing the use of linear system identification methods. Comparisons, observations, and results of both parametric system identification techniques are discussed. The thesis concludes by proposing a model reference control system to aid in astronaut ground tests. This approach would allow the identified models to mimic on-orbit dynamic characteristics of the actual flight manipulator thus providing astronauts with realistic on-orbit responses to perform space station tasks in a ground-based environment.

Analysis of propulsion system dynamics in the validation of a high-order state space model of the UH-60

NASA Technical Reports Server (NTRS)

Kim, Frederick D.

1992-01-01

Frequency responses generated from a high-order linear model of the UH-60 Black Hawk have shown that the propulsion system influences significantly the vertical and yaw dynamics of the aircraft at frequencies important to high-bandwidth control law designs. The inclusion of the propulsion system comprises the latest step in the development of a high-order linear model of the UH-60 that models additionally the dynamics of the fuselage, rotor, and inflow. A complete validation study of the linear model is presented in the frequency domain for both on-axis and off-axis coupled responses in the hoverflight condition, and on-axis responses for forward speeds of 80 and 120 knots.

A generalized Lyapunov theory for robust root clustering of linear state space models with real parameter uncertainty

NASA Technical Reports Server (NTRS)

Yedavalli, R. K.

1992-01-01

The problem of analyzing and designing controllers for linear systems subject to real parameter uncertainty is considered. An elegant, unified theory for robust eigenvalue placement is presented for a class of D-regions defined by algebraic inequalities by extending the nominal matrix root clustering theory of Gutman and Jury (1981) to linear uncertain time systems. The author presents explicit conditions for matrix root clustering for different D-regions and establishes the relationship between the eigenvalue migration range and the parameter range. The bounds are all obtained by one-shot computation in the matrix domain and do not need any frequency sweeping or parameter gridding. The method uses the generalized Lyapunov theory for getting the bounds.

Estimation of regions of attraction and ultimate boundedness for multiloop LQ regulators. [Linear Quadratic

NASA Technical Reports Server (NTRS)

Joshi, S. M.

1984-01-01

Closed-loop stability is investigated for multivariable linear time-invariant systems controlled by optimal full state feedback linear quadratic (LQ) regulators, with nonlinear gains present in the feedback channels. Estimates are obtained for the region of attraction when the nonlinearities escape the (0.5, infinity) sector in regions away from the origin and for the region of ultimate boundedness when the nonlinearities escape the sector near the origin. The expressions for these regions also provide methods for selecting the performance function parameters in order to obtain LQ designs with better tolerance for nonlinearities. The analytical results are illustrated by applying them to the problem of controlling the rigid-body pitch angle and elastic motion of a large, flexible space antenna.

A neural-network-based exponential H∞ synchronisation for chaotic secure communication via improved genetic algorithm

NASA Astrophysics Data System (ADS)

Hsiao, Feng-Hsiag

2016-10-01

In this study, a novel approach via improved genetic algorithm (IGA)-based fuzzy observer is proposed to realise exponential optimal H∞ synchronisation and secure communication in multiple time-delay chaotic (MTDC) systems. First, an original message is inserted into the MTDC system. Then, a neural-network (NN) model is employed to approximate the MTDC system. Next, a linear differential inclusion (LDI) state-space representation is established for the dynamics of the NN model. Based on this LDI state-space representation, this study proposes a delay-dependent exponential stability criterion derived in terms of Lyapunov's direct method, thus ensuring that the trajectories of the slave system approach those of the master system. Subsequently, the stability condition of this criterion is reformulated into a linear matrix inequality (LMI). Due to GA's random global optimisation search capabilities, the lower and upper bounds of the search space can be set so that the GA will seek better fuzzy observer feedback gains, accelerating feedback gain-based synchronisation via the LMI-based approach. IGA, which exhibits better performance than traditional GA, is used to synthesise a fuzzy observer to not only realise the exponential synchronisation, but also achieve optimal H∞ performance by minimizing the disturbance attenuation level and recovering the transmitted message. Finally, a numerical example with simulations is given in order to demonstrate the effectiveness of our approach.

A simplified dynamic model of the T700 turboshaft engine

NASA Technical Reports Server (NTRS)

Duyar, Ahmet; Gu, Zhen; Litt, Jonathan S.

1992-01-01

A simplified open-loop dynamic model of the T700 turboshaft engine, valid within the normal operating range of the engine, is developed. This model is obtained by linking linear state space models obtained at different engine operating points. Each linear model is developed from a detailed nonlinear engine simulation using a multivariable system identification and realization method. The simplified model may be used with a model-based real time diagnostic scheme for fault detection and diagnostics, as well as for open loop engine dynamics studies and closed loop control analysis utilizing a user generated control law.

Joint sparsity based heterogeneous data-level fusion for target detection and estimation

NASA Astrophysics Data System (ADS)

Niu, Ruixin; Zulch, Peter; Distasio, Marcello; Blasch, Erik; Shen, Dan; Chen, Genshe

2017-05-01

Typical surveillance systems employ decision- or feature-level fusion approaches to integrate heterogeneous sensor data, which are sub-optimal and incur information loss. In this paper, we investigate data-level heterogeneous sensor fusion. Since the sensors monitor the common targets of interest, whose states can be determined by only a few parameters, it is reasonable to assume that the measurement domain has a low intrinsic dimensionality. For heterogeneous sensor data, we develop a joint-sparse data-level fusion (JSDLF) approach based on the emerging joint sparse signal recovery techniques by discretizing the target state space. This approach is applied to fuse signals from multiple distributed radio frequency (RF) signal sensors and a video camera for joint target detection and state estimation. The JSDLF approach is data-driven and requires minimum prior information, since there is no need to know the time-varying RF signal amplitudes, or the image intensity of the targets. It can handle non-linearity in the sensor data due to state space discretization and the use of frequency/pixel selection matrices. Furthermore, for a multi-target case with J targets, the JSDLF approach only requires discretization in a single-target state space, instead of discretization in a J-target state space, as in the case of the generalized likelihood ratio test (GLRT) or the maximum likelihood estimator (MLE). Numerical examples are provided to demonstrate that the proposed JSDLF approach achieves excellent performance with near real-time accurate target position and velocity estimates.

Bulk local states and crosscaps in holographic CFT

DOE PAGES

Nakayama, Yu; Ooguri, Hirosi

2016-10-17

In a weakly coupled gravity theory in the anti-de Sitter space, local states in the bulk are linear superpositions of Ishibashi states for a crosscap in the dual conformal field theory. The superposition structure can be constrained either by the microscopic causality in the bulk gravity or the bootstrap condition in the boundary conformal field theory. We show, contrary to some expectation, that these two conditions are not compatible to each other in the weak gravity regime. As a result, we also present an evidence to show that bulk local states in three dimensions are not organized by the Virasoromore » symmetry.« less

Q-plates as higher order polarization controllers for orbital angular momentum modes of fiber.

PubMed

Gregg, P; Mirhosseini, M; Rubano, A; Marrucci, L; Karimi, E; Boyd, R W; Ramachandran, S

2015-04-15

We demonstrate that a |q|=1/2 plate, in conjunction with appropriate polarization optics, can selectively and switchably excite all linear combinations of the first radial mode order |l|=1 orbital angular momentum (OAM) fiber modes. This enables full mapping of free-space polarization states onto fiber vector modes, including the radially (TM) and azimuthally polarized (TE) modes. The setup requires few optical components and can yield mode purities as high as ∼30  dB. Additionally, just as a conventional fiber polarization controller creates arbitrary elliptical polarization states to counteract fiber birefringence and yield desired polarizations at the output of a single-mode fiber, q-plates disentangle degenerate state mixing effects between fiber OAM states to yield pure states, even after long-length fiber propagation. We thus demonstrate the ability to switch dynamically, potentially at ∼GHz rates, between OAM modes, or create desired linear combinations of them. We envision applications in fiber-based lasers employing vector or OAM mode outputs, as well as communications networking schemes exploiting spatial modes for higher dimensional encoding.

Customized Steady-State Constraints for Parameter Estimation in Non-Linear Ordinary Differential Equation Models

PubMed Central

Rosenblatt, Marcus; Timmer, Jens; Kaschek, Daniel

2016-01-01

Ordinary differential equation models have become a wide-spread approach to analyze dynamical systems and understand underlying mechanisms. Model parameters are often unknown and have to be estimated from experimental data, e.g., by maximum-likelihood estimation. In particular, models of biological systems contain a large number of parameters. To reduce the dimensionality of the parameter space, steady-state information is incorporated in the parameter estimation process. For non-linear models, analytical steady-state calculation typically leads to higher-order polynomial equations for which no closed-form solutions can be obtained. This can be circumvented by solving the steady-state equations for kinetic parameters, which results in a linear equation system with comparatively simple solutions. At the same time multiplicity of steady-state solutions is avoided, which otherwise is problematic for optimization. When solved for kinetic parameters, however, steady-state constraints tend to become negative for particular model specifications, thus, generating new types of optimization problems. Here, we present an algorithm based on graph theory that derives non-negative, analytical steady-state expressions by stepwise removal of cyclic dependencies between dynamical variables. The algorithm avoids multiple steady-state solutions by construction. We show that our method is applicable to most common classes of biochemical reaction networks containing inhibition terms, mass-action and Hill-type kinetic equations. Comparing the performance of parameter estimation for different analytical and numerical methods of incorporating steady-state information, we show that our approach is especially well-tailored to guarantee a high success rate of optimization. PMID:27243005

Customized Steady-State Constraints for Parameter Estimation in Non-Linear Ordinary Differential Equation Models.

PubMed

Rosenblatt, Marcus; Timmer, Jens; Kaschek, Daniel

2016-01-01

Ordinary differential equation models have become a wide-spread approach to analyze dynamical systems and understand underlying mechanisms. Model parameters are often unknown and have to be estimated from experimental data, e.g., by maximum-likelihood estimation. In particular, models of biological systems contain a large number of parameters. To reduce the dimensionality of the parameter space, steady-state information is incorporated in the parameter estimation process. For non-linear models, analytical steady-state calculation typically leads to higher-order polynomial equations for which no closed-form solutions can be obtained. This can be circumvented by solving the steady-state equations for kinetic parameters, which results in a linear equation system with comparatively simple solutions. At the same time multiplicity of steady-state solutions is avoided, which otherwise is problematic for optimization. When solved for kinetic parameters, however, steady-state constraints tend to become negative for particular model specifications, thus, generating new types of optimization problems. Here, we present an algorithm based on graph theory that derives non-negative, analytical steady-state expressions by stepwise removal of cyclic dependencies between dynamical variables. The algorithm avoids multiple steady-state solutions by construction. We show that our method is applicable to most common classes of biochemical reaction networks containing inhibition terms, mass-action and Hill-type kinetic equations. Comparing the performance of parameter estimation for different analytical and numerical methods of incorporating steady-state information, we show that our approach is especially well-tailored to guarantee a high success rate of optimization.

A squeezed light source operated under high vacuum

PubMed Central

Wade, Andrew R.; Mansell, Georgia L.; Chua, Sheon S. Y.; Ward, Robert L.; Slagmolen, Bram J. J.; Shaddock, Daniel A.; McClelland, David E.

2015-01-01

Non-classical squeezed states of light are becoming increasingly important to a range of metrology and other quantum optics applications in cryptography, quantum computation and biophysics. Applications such as improving the sensitivity of advanced gravitational wave detectors and the development of space-based metrology and quantum networks will require robust deployable vacuum-compatible sources. To date non-linear photonics devices operated under high vacuum have been simple single pass systems, testing harmonic generation and the production of classically correlated photon pairs for space-based applications. Here we demonstrate the production under high-vacuum conditions of non-classical squeezed light with an observed 8.6 dB of quantum noise reduction down to 10 Hz. Demonstration of a resonant non-linear optical device, for the generation of squeezed light under vacuum, paves the way to fully exploit the advantages of in-vacuum operations, adapting this technology for deployment into new extreme environments. PMID:26657616

A squeezed light source operated under high vacuum

NASA Astrophysics Data System (ADS)

Wade, Andrew R.; Mansell, Georgia L.; Chua, Sheon S. Y.; Ward, Robert L.; Slagmolen, Bram J. J.; Shaddock, Daniel A.; McClelland, David E.

2015-12-01

Non-classical squeezed states of light are becoming increasingly important to a range of metrology and other quantum optics applications in cryptography, quantum computation and biophysics. Applications such as improving the sensitivity of advanced gravitational wave detectors and the development of space-based metrology and quantum networks will require robust deployable vacuum-compatible sources. To date non-linear photonics devices operated under high vacuum have been simple single pass systems, testing harmonic generation and the production of classically correlated photon pairs for space-based applications. Here we demonstrate the production under high-vacuum conditions of non-classical squeezed light with an observed 8.6 dB of quantum noise reduction down to 10 Hz. Demonstration of a resonant non-linear optical device, for the generation of squeezed light under vacuum, paves the way to fully exploit the advantages of in-vacuum operations, adapting this technology for deployment into new extreme environments.

On the analytical modeling of the nonlinear vibrations of pretensioned space structures

NASA Technical Reports Server (NTRS)

Housner, J. M.; Belvin, W. K.

1983-01-01

Pretensioned structures are receiving considerable attention as candidate large space structures. A typical example is a hoop-column antenna. The large number of preloaded members requires efficient analytical methods for concept validation and design. Validation through analyses is especially important since ground testing may be limited due to gravity effects and structural size. The present investigation has the objective to present an examination of the analytical modeling of pretensioned members undergoing nonlinear vibrations. Two approximate nonlinear analysis are developed to model general structural arrangements which include beam-columns and pretensioned cables attached to a common nucleus, such as may occur at a joint of a pretensioned structure. Attention is given to structures undergoing nonlinear steady-state oscillations due to sinusoidal excitation forces. Three analyses, linear, quasi-linear, and nonlinear are conducted and applied to study the response of a relatively simple cable stiffened structure.

Latest astronomical constraints on some non-linear parametric dark energy models

NASA Astrophysics Data System (ADS)

Yang, Weiqiang; Pan, Supriya; Paliathanasis, Andronikos

2018-04-01

We consider non-linear redshift-dependent equation of state parameters as dark energy models in a spatially flat Friedmann-Lemaître-Robertson-Walker universe. To depict the expansion history of the universe in such cosmological scenarios, we take into account the large-scale behaviour of such parametric models and fit them using a set of latest observational data with distinct origin that includes cosmic microwave background radiation, Supernove Type Ia, baryon acoustic oscillations, redshift space distortion, weak gravitational lensing, Hubble parameter measurements from cosmic chronometers, and finally the local Hubble constant from Hubble space telescope. The fitting technique avails the publicly available code Cosmological Monte Carlo (COSMOMC), to extract the cosmological information out of these parametric dark energy models. From our analysis, it follows that those models could describe the late time accelerating phase of the universe, while they are distinguished from the Λ-cosmology.

A variable structure approach to robust control of VTOL aircraft

NASA Technical Reports Server (NTRS)

Calise, A. J.; Kramer, F.

1982-01-01

This paper examines the application of variable structure control theory to the design of a flight control system for the AV-8A Harrier in a hover mode. The objective in variable structure design is to confine the motion to a subspace of the total state space. The motion in this subspace is insensitive to system parameter variations and external disturbances that lie in the range space of the control. A switching type of control law results from the design procedure. The control system was designed to track a vector velocity command defined in the body frame. For comparison purposes, a proportional controller was designed using optimal linear regulator theory. Both control designs were first evaluated for transient response performance using a linearized model, then a nonlinear simulation study of a hovering approach to landing was conducted. Wind turbulence was modeled using a 1052 destroyer class air wake model.

Dynamics from a mathematical model of a two-state gas laser

NASA Astrophysics Data System (ADS)

Kleanthous, Antigoni; Hua, Tianshu; Manai, Alexandre; Yawar, Kamran; Van Gorder, Robert A.

2018-05-01

Motivated by recent work in the area, we consider the behavior of solutions to a nonlinear PDE model of a two-state gas laser. We first review the derivation of the two-state gas laser model, before deriving a non-dimensional model given in terms of coupled nonlinear partial differential equations. We then classify the steady states of this system, in order to determine the possible long-time asymptotic solutions to this model, as well as corresponding stability results, showing that the only uniform steady state (the zero motion state) is unstable, while a linear profile in space is stable. We then provide numerical simulations for the full unsteady model. We show for a wide variety of initial conditions that the solutions tend toward the stable linear steady state profiles. We also consider traveling wave solutions, and determine the unique wave speed (in terms of the other model parameters) which allows wave-like solutions to exist. Despite some similarities between the model and the inviscid Burger's equation, the solutions we obtain are much more regular than the solutions to the inviscid Burger's equation, with no evidence of shock formation or loss of regularity.

A Solution Space for a System of Null-State Partial Differential Equations: Part 3

NASA Astrophysics Data System (ADS)

Flores, Steven M.; Kleban, Peter

2015-01-01

This article is the third of four that completely and rigorously characterize a solution space for a homogeneous system of 2 N + 3 linear partial differential equations (PDEs) in 2 N variables that arises in conformal field theory (CFT) and multiple Schramm-Löwner evolution (SLE κ ). The system comprises 2 N null-state equations and three conformal Ward identities that govern CFT correlation functions of 2 N one-leg boundary operators. In the first two articles (Flores and Kleban, in Commun Math Phys, arXiv:1212.2301, 2012; Commun Math Phys, arXiv:1404.0035, 2014), we use methods of analysis and linear algebra to prove that dim , with C N the Nth Catalan number. Extending these results, we prove in this article that dim and entirely consists of (real-valued) solutions constructed with the CFT Coulomb gas (contour integral) formalism. In order to prove this claim, we show that a certain set of C N such solutions is linearly independent. Because the formulas for these solutions are complicated, we prove linear independence indirectly. We use the linear injective map of Lemma 15 in Flores and Kleban (Commun Math Phys, arXiv:1212.2301, 2012) to send each solution of the mentioned set to a vector in , whose components we find as inner products of elements in a Temperley-Lieb algebra. We gather these vectors together as columns of a symmetric matrix, with the form of a meander matrix. If the determinant of this matrix does not vanish, then the set of C N Coulomb gas solutions is linearly independent. And if this determinant does vanish, then we construct an alternative set of C N Coulomb gas solutions and follow a similar procedure to show that this set is linearly independent. The latter situation is closely related to CFT minimal models. We emphasize that, although the system of PDEs arises in CFT in away that is typically non-rigorous, our treatment of this system here and in Flores and Kleban (Commun Math Phys, arXiv:1212.2301, 2012; Commun Math Phys, arXiv:1404.0035, 2014; Commun Math Phys, arXiv:1405.2747, 2014) is completely rigorous.

Towards the Solution of the Many-Electron Problem in Real Materials: Equation of State of the Hydrogen Chain with State-of-the-Art Many-Body Methods

DOE PAGES

Motta, Mario; Ceperley, David M.; Chan, Garnet Kin-Lic; ...

2017-09-28

We present numerical results for the equation of state of an infinite chain of hydrogen atoms. A variety of modern many-body methods are employed, with exhaustive cross-checks and validation. Approaches for reaching the continuous space limit and the thermodynamic limit are investigated, proposed, and tested. The detailed comparisons provide a benchmark for assessing the current state of the art in many-body computation, and for the development of new methods. The ground-state energy per atom in the linear chain is accurately determined versus bond length, with a confidence bound given on all uncertainties.

Towards the Solution of the Many-Electron Problem in Real Materials: Equation of State of the Hydrogen Chain with State-of-the-Art Many-Body Methods

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

Motta, Mario; Ceperley, David M.; Chan, Garnet Kin-Lic

We present numerical results for the equation of state of an infinite chain of hydrogen atoms. A variety of modern many-body methods are employed, with exhaustive cross-checks and validation. Approaches for reaching the continuous space limit and the thermodynamic limit are investigated, proposed, and tested. The detailed comparisons provide a benchmark for assessing the current state of the art in many-body computation, and for the development of new methods. The ground-state energy per atom in the linear chain is accurately determined versus bond length, with a confidence bound given on all uncertainties.

Necessary and sufficient conditions for the complete controllability and observability of systems in series using the coprime factorization of a rational matrix

NASA Technical Reports Server (NTRS)

Callier, F. M.; Nahum, C. D.

1975-01-01

The series connection of two linear time-invariant systems that have minimal state space system descriptions is considered. From these descriptions, strict-system-equivalent polynomial matrix system descriptions in the manner of Rosenbrock are derived. They are based on the factorization of the transfer matrix of the subsystems as a ratio of two right or left coprime polynomial matrices. They give rise to a simple polynomial matrix system description of the tandem connection. Theorem 1 states that for the complete controllability and observability of the state space system description of the series connection, it is necessary and sufficient that certain 'denominator' and 'numerator' groups are coprime. Consequences for feedback systems are drawn in Corollary 1. The role of pole-zero cancellations is explained by Lemma 3 and Corollaires 2 and 3.

Dissipative stability analysis and control of two-dimensional Fornasini-Marchesini local state-space model

NASA Astrophysics Data System (ADS)

Wang, Lanning; Chen, Weimin; Li, Lizhen

2017-06-01

This paper is concerned with the problems of dissipative stability analysis and control of the two-dimensional (2-D) Fornasini-Marchesini local state-space (FM LSS) model. Based on the characteristics of the system model, a novel definition of 2-D FM LSS (Q, S, R)-α-dissipativity is given first, and then a sufficient condition in terms of linear matrix inequality (LMI) is proposed to guarantee the asymptotical stability and 2-D (Q, S, R)-α-dissipativity of the systems. As its special cases, 2-D passivity performance and 2-D H∞ performance are also discussed. Furthermore, by use of this dissipative stability condition and projection lemma technique, 2-D (Q, S, R)-α-dissipative state-feedback control problem is solved as well. Finally, a numerical example is given to illustrate the effectiveness of the proposed method.

Analysis of ERTS-1 linear features in New York State

NASA Technical Reports Server (NTRS)

Isachsen, Y. W. (Principal Investigator); Fakundiny, R. H.; Forster, S. W.

1974-01-01

The author has identified the following significant results. All ERTS-1 linears confirmed to date have topographic expression although they may appear as featureless tonal linears on the imagery. A bias is unavoidably introduced against any linears which may parallel raster lines, lithological trends, or the azimuth of solar illumination. Ground study of ERTS-1 topographic lineaments in the Adirondacks indicates: outcrops along linears are even more rare than expected, fault breccias are found along some NNE lineaments, chloritization and slickensiding without brecciation characterize one EW lineament whereas closely-spaced jointing plus a zone of plastic shear define another. Field work in the Catskills suggests that the prominent new NNE lineaments may be surface manifestations of normal faulting in the basement, and that it may become possible to map major joint sets over extensive plateau regions directly on the imagery. Fall and winter images each display some unique linears, and long linears on the fall image commonly appear as aligned segments on the winter scene. A computer-processed color composite image permitted the extraction or additional information on the shaded side of mountains.

Parameter retrieval of chiral metamaterials based on the state-space approach.

PubMed

Zarifi, Davoud; Soleimani, Mohammad; Abdolali, Ali

2013-08-01

This paper deals with the introduction of an approach for the electromagnetic characterization of homogeneous chiral layers. The proposed method is based on the state-space approach and properties of a 4×4 state transition matrix. Based on this, first, the forward problem analysis through the state-space method is reviewed and properties of the state transition matrix of a chiral layer are presented and proved as two theorems. The formulation of a proposed electromagnetic characterization method is then presented. In this method, scattering data for a linearly polarized plane wave incident normally on a homogeneous chiral slab are combined with properties of a state transition matrix and provide a powerful characterization method. The main difference with respect to other well-established retrieval procedures based on the use of the scattering parameters relies on the direct computation of the transfer matrix of the slab as opposed to the conventional calculation of the propagation constant and impedance of the modes supported by the medium. The proposed approach allows avoiding nonlinearity of the problem but requires getting enough equations to fulfill the task which was provided by considering some properties of the state transition matrix. To demonstrate the applicability and validity of the method, the constitutive parameters of two well-known dispersive chiral metamaterial structures at microwave frequencies are retrieved. The results show that the proposed method is robust and reliable.

Drug-Target Interaction Prediction through Label Propagation with Linear Neighborhood Information.

PubMed

Zhang, Wen; Chen, Yanlin; Li, Dingfang

2017-11-25

Interactions between drugs and target proteins provide important information for the drug discovery. Currently, experiments identified only a small number of drug-target interactions. Therefore, the development of computational methods for drug-target interaction prediction is an urgent task of theoretical interest and practical significance. In this paper, we propose a label propagation method with linear neighborhood information (LPLNI) for predicting unobserved drug-target interactions. Firstly, we calculate drug-drug linear neighborhood similarity in the feature spaces, by considering how to reconstruct data points from neighbors. Then, we take similarities as the manifold of drugs, and assume the manifold unchanged in the interaction space. At last, we predict unobserved interactions between known drugs and targets by using drug-drug linear neighborhood similarity and known drug-target interactions. The experiments show that LPLNI can utilize only known drug-target interactions to make high-accuracy predictions on four benchmark datasets. Furthermore, we consider incorporating chemical structures into LPLNI models. Experimental results demonstrate that the model with integrated information (LPLNI-II) can produce improved performances, better than other state-of-the-art methods. The known drug-target interactions are an important information source for computational predictions. The usefulness of the proposed method is demonstrated by cross validation and the case study.

Utilization of the Deep Space Atomic Clock for Europa Gravitational Tide Recovery

NASA Technical Reports Server (NTRS)

Seubert, Jill; Ely, Todd

2015-01-01

Estimation of Europa's gravitational tide can provide strong evidence of the existence of a subsurface liquid ocean. Due to limited close approach tracking data, a Europa flyby mission suffers strong coupling between the gravity solution quality and tracking data quantity and quality. This work explores utilizing Low Gain Antennas with the Deep Space Atomic Clock (DSAC) to provide abundant high accuracy uplink-only radiometric tracking data. DSAC's performance, expected to exhibit an Allan Deviation of less than 3e-15 at one day, provides long-term stability and accuracy on par with the Deep Space Network ground clocks, enabling one-way radiometric tracking data with accuracy equivalent to that of its two-way counterpart. The feasibility of uplink-only Doppler tracking via the coupling of LGAs and DSAC and the expected Doppler data quality are presented. Violations of the Kalman filter's linearization assumptions when state perturbations are included in the flyby analysis results in poor determination of the Europa gravitational tide parameters. B-plane targeting constraints are statistically determined, and a solution to the linearization issues via pre-flyby approach orbit determination is proposed and demonstrated.

Control of the constrained planar simple inverted pendulum

NASA Technical Reports Server (NTRS)

Bavarian, B.; Wyman, B. F.; Hemami, H.

1983-01-01

Control of a constrained planar inverted pendulum by eigenstructure assignment is considered. Linear feedback is used to stabilize and decouple the system in such a way that specified subspaces of the state space are invariant for the closed-loop system. The effectiveness of the feedback law is tested by digital computer simulation. Pre-compensation by an inverse plant is used to improve performance.

Geometric foundations of the theory of feedback equivalence

NASA Technical Reports Server (NTRS)

Hermann, R.

1987-01-01

A description of feedback control is presented within the context of differential equations, differential geometry, and Lie theory. Work related to the integration of differential geometry with the control techniques of feedback linearization is summarized. Particular attention is given to the application of the theory of vector field systems. Feedback invariants for control systems in state space form are also addressed.

Emergent properties of gene evolution: Species as attractors in phenotypic space

NASA Astrophysics Data System (ADS)

Reuveni, Eli; Giuliani, Alessandro

2012-02-01

The question how the observed discrete character of the phenotype emerges from a continuous genetic distance metrics is the core argument of two contrasted evolutionary theories: punctuated equilibrium (stable evolution scattered with saltations in the phenotype) and phyletic gradualism (smooth and linear evolution of the phenotype). Identifying phenotypic saltation on the molecular levels is critical to support the first model of evolution. We have used DNA sequences of ∼1300 genes from 6 isolated populations of the budding yeast Saccharomyces cerevisiae. We demonstrate that while the equivalent measure of the genetic distance show a continuum between lineage distance with no evidence of discrete states, the phenotypic space illustrates only two (discrete) possible states that can be associated with a saltation of the species phenotype. The fact that such saltation spans large fraction of the genome and follows by continuous genetic distance is a proof of the concept that the genotype-phenotype relation is not univocal and may have severe implication when looking for disease related genes and mutations. We used this finding with analogy to attractor-like dynamics and show that punctuated equilibrium could be explained in the framework of non-linear dynamics systems.

Nonlinear predictive control of a boiler-turbine unit: A state-space approach with successive on-line model linearisation and quadratic optimisation.

PubMed

Ławryńczuk, Maciej

2017-03-01

This paper details development of a Model Predictive Control (MPC) algorithm for a boiler-turbine unit, which is a nonlinear multiple-input multiple-output process. The control objective is to follow set-point changes imposed on two state (output) variables and to satisfy constraints imposed on three inputs and one output. In order to obtain a computationally efficient control scheme, the state-space model is successively linearised on-line for the current operating point and used for prediction. In consequence, the future control policy is easily calculated from a quadratic optimisation problem. For state estimation the extended Kalman filter is used. It is demonstrated that the MPC strategy based on constant linear models does not work satisfactorily for the boiler-turbine unit whereas the discussed algorithm with on-line successive model linearisation gives practically the same trajectories as the truly nonlinear MPC controller with nonlinear optimisation repeated at each sampling instant. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Response to Comments on: "Nonlinear phenomena, bifurcations, and routes to chaos in an asymmetrically supported rotor-stator contact system" by Philip Varney, Itzhak Green [J. Sound Vib. 336 (2015) 207-226

NASA Astrophysics Data System (ADS)

Varney, Philip; Green, Itzhak

2017-11-01

The authors would like to thank the discussers for their interest in the paper. The discussers raise several objections to the original work; namely, that the state-space equations of motion were derived incorrectly, thus rendering the original results incorrect by association. In actuality, the error in the original state-space equations (Eq. (16) in the original work) is typographic only. This, in conjunction with a typographic error in Table A1, prevented the discussers from replicating a subset of the original results (though the discussers were able to replicate many of the results presented in the original work, despite the presumed error in the equations). These typographic errors are rectified here. In addition, results are presented here corresponding to the solution that would have been obtained had the state-space equations been incorrect in the manner presumed by the discussers. Finally, the discussers state that the results presented in the original work do not adhere to physical principles because the steady-state solution in one case indicates contact even though the linear response to imbalance is less than the radial clearance. This seeming discrepancy is also addressed here.

Reconstruction of real-space linear matter power spectrum from multipoles of BOSS DR12 results

NASA Astrophysics Data System (ADS)

Lee, Seokcheon

2018-02-01

Recently, the power spectrum (PS) multipoles using the Baryon Oscillation Spectroscopic Survey (BOSS) Data Release 12 (DR12) sample are analyzed [1]. The based model for the analysis is the so-called TNS quasi-linear model and the analysis provides the multipoles up to the hexadecapole [2]. Thus, one might be able to recover the real-space linear matter PS by using the combinations of multipoles to investigate the cosmology [3]. We provide the analytic form of the ratio of quadrupole (hexadecapole) to monopole moments of the quasi-linear PS including the Fingers-of-God (FoG) effect to recover the real-space PS in the linear regime. One expects that observed values of the ratios of multipoles should be consistent with those of the linear theory at large scales. Thus, we compare the ratios of multipoles of the linear theory, including the FoG effect with the measured values. From these, we recover the linear matter power spectra in real-space. These recovered power spectra are consistent with the linear matter power spectra.

Conditions for space invariance in optical data processors used with coherent or noncoherent light.

PubMed

Arsenault, H R

1972-10-01

The conditions for space invariance in coherent and noncoherent optical processors are considered. All linear optical processors are shown to belong to one of two types. The conditions for space invariance are more stringent for noncoherent processors than for coherent processors, so that a system that is linear in coherent light may be nonlinear in noncoherent light. However, any processor that is linear in noncoherent light is also linear in the coherent limit.

Optimal linear-quadratic control of coupled parabolic-hyperbolic PDEs

NASA Astrophysics Data System (ADS)

Aksikas, I.; Moghadam, A. Alizadeh; Forbes, J. F.

2017-10-01

This paper focuses on the optimal control design for a system of coupled parabolic-hypebolic partial differential equations by using the infinite-dimensional state-space description and the corresponding operator Riccati equation. Some dynamical properties of the coupled system of interest are analysed to guarantee the existence and uniqueness of the solution of the linear-quadratic (LQ)-optimal control problem. A state LQ-feedback operator is computed by solving the operator Riccati equation, which is converted into a set of algebraic and differential Riccati equations, thanks to the eigenvalues and the eigenvectors of the parabolic operator. The results are applied to a non-isothermal packed-bed catalytic reactor. The LQ-optimal controller designed in the early portion of the paper is implemented for the original nonlinear model. Numerical simulations are performed to show the controller performances.

Graph theory approach to the eigenvalue problem of large space structures

NASA Technical Reports Server (NTRS)

Reddy, A. S. S. R.; Bainum, P. M.

1981-01-01

Graph theory is used to obtain numerical solutions to eigenvalue problems of large space structures (LSS) characterized by a state vector of large dimensions. The LSS are considered as large, flexible systems requiring both orientation and surface shape control. Graphic interpretation of the determinant of a matrix is employed to reduce a higher dimensional matrix into combinations of smaller dimensional sub-matrices. The reduction is implemented by means of a Boolean equivalent of the original matrices formulated to obtain smaller dimensional equivalents of the original numerical matrix. Computation time becomes less and more accurate solutions are possible. An example is provided in the form of a free-free square plate. Linearized system equations and numerical values of a stiffness matrix are presented, featuring a state vector with 16 components.

A numerical identifiability test for state-space models--application to optimal experimental design.

PubMed

Hidalgo, M E; Ayesa, E

2001-01-01

This paper describes a mathematical tool for identifiability analysis, easily applicable to high order non-linear systems modelled in state-space and implementable in simulators with a time-discrete approach. This procedure also permits a rigorous analysis of the expected estimation errors (average and maximum) in calibration experiments. The methodology is based on the recursive numerical evaluation of the information matrix during the simulation of a calibration experiment and in the setting-up of a group of information parameters based on geometric interpretations of this matrix. As an example of the utility of the proposed test, the paper presents its application to an optimal experimental design of ASM Model No. 1 calibration, in order to estimate the maximum specific growth rate microH and the concentration of heterotrophic biomass XBH.

A momentum-space formulation without partial wave decomposition for scattering of two spin-half particles

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

Fachruddin, Imam, E-mail: imam.fachruddin@sci.ui.ac.id; Salam, Agus

2016-03-11

A new momentum-space formulation for scattering of two spin-half particles, both either identical or unidentical, is formulated. As basis states the free linear-momentum states are not expanded into the angular-momentum states, the system’s spin states are described by the product of the spin states of the two particles, and the system’s isospin states by the total isospin states of the two particles. We evaluate the Lippmann-Schwinger equations for the T-matrix elements in these basis states. The azimuthal behavior of the potential and of the T-matrix elements leads to a set of coupled integral equations for the T-matrix elements in twomore » variables only, which are the magnitude of the relative momentum and the scattering angle. Some symmetry relations for the potential and the T-matrix elements reduce the number of the integral equations to be solved. A set of six spin operators to express any interaction of two spin-half particles is introduced. We show the spin-averaged differential cross section as being calculated in terms of the solution of the set of the integral equations.« less

Model Checking a Byzantine-Fault-Tolerant Self-Stabilizing Protocol for Distributed Clock Synchronization Systems

NASA Technical Reports Server (NTRS)

Malekpour, Mahyar R.

2007-01-01

This report presents the mechanical verification of a simplified model of a rapid Byzantine-fault-tolerant self-stabilizing protocol for distributed clock synchronization systems. This protocol does not rely on any assumptions about the initial state of the system. This protocol tolerates bursts of transient failures, and deterministically converges within a time bound that is a linear function of the self-stabilization period. A simplified model of the protocol is verified using the Symbolic Model Verifier (SMV) [SMV]. The system under study consists of 4 nodes, where at most one of the nodes is assumed to be Byzantine faulty. The model checking effort is focused on verifying correctness of the simplified model of the protocol in the presence of a permanent Byzantine fault as well as confirmation of claims of determinism and linear convergence with respect to the self-stabilization period. Although model checking results of the simplified model of the protocol confirm the theoretical predictions, these results do not necessarily confirm that the protocol solves the general case of this problem. Modeling challenges of the protocol and the system are addressed. A number of abstractions are utilized in order to reduce the state space. Also, additional innovative state space reduction techniques are introduced that can be used in future verification efforts applied to this and other protocols.

Soliton matter in the two-dimensional linear sigma model

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

Dodd, L.R.; Lohe, M.A.; Rossi, M.

1987-10-01

We consider a one-dimensional model of nuclear matter where the quark clusters are described by solutions of the sigma model on a linear lattice in the self-consistent mean field approximation. Exact expressions are given for the baglike solutions confined to a finite interval, corresponding in the infinite interval limit to the free solitons previously found by Campbell and Liao. Periodic, self-consistent solutions which satisfy Bloch's theorem are constructed. Their energies and associated quark sigma field distributions are calculated numerically as functions of the baryon spacing, and compared with those of the uniform quark plasma. The predicted configuration of the groundmore » state depends critically on the assumed manner of filling the lowest band of quark single-particle levels, and on the density. In the absence of additional repulsive forces in the model, we find that the high density massless quark plasma is energetically favored and that there is a smooth transition from the baglike state to a uniform plasma with nonvanishing sigma field at comparatively large lattice constants 2dapprox. =10m/sub q//sup -1/ (m/sub q/ is the quark mass). If dilute filling of the entire band is employed, the clustered state is stable and a first order phase transition can occur for a range of much smaller lattice spacings 2dapprox. =4m/sub q//sup -1/. .AE« less

Valence-bond theory of linear Hubbard and Pariser-Parr-Pople models

NASA Astrophysics Data System (ADS)

Soos, Z. G.; Ramasesha, S.

1984-05-01

The ground and low-lying states of finite quantum-cell models with one state per site are obtained exactly through a real-space basis of valence-bond (VB) diagrams that explicitly conserve the total spin. Regular and alternating Hubbard and Pariser-Parr-Pople (PPP) chains and rings with Ne electrons on N(<=12) sites are extrapolated to infinite arrays. The ground-state energy and optical gap of regular U=4|t| Hubbard chains agree with exact results, suggesting comparable accuracy for alternating Hubbard and PPP models, but differ from mean-field results. Molecular PPP parameters describe well the excitations of finite polyenes, odd polyene ions, linear cyanine dyes, and slightly overestimate the absorption peaks in polyacetylene (CH)x. Molecular correlations contrast sharply with uncorrelated descriptions of topological solitons, which are modeled by regular polyene radicals and their ions for both wide and narrow alternation crossovers. Neutral solitons have no midgap absorption and negative spin densities, while the intensity of the in-gap excitation of charged solitons is not enhanced. The properties of correlated states in quantum-cell models with one valence state per site are discussed in the adiabatic limit for excited-state geometries and instabilities to dimerization.

SparseMaps—A systematic infrastructure for reduced-scaling electronic structure methods. III. Linear-scaling multireference domain-based pair natural orbital N-electron valence perturbation theory

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

Guo, Yang; Sivalingam, Kantharuban; Neese, Frank, E-mail: Frank.Neese@cec.mpg.de

2016-03-07

Multi-reference (MR) electronic structure methods, such as MR configuration interaction or MR perturbation theory, can provide reliable energies and properties for many molecular phenomena like bond breaking, excited states, transition states or magnetic properties of transition metal complexes and clusters. However, owing to their inherent complexity, most MR methods are still too computationally expensive for large systems. Therefore the development of more computationally attractive MR approaches is necessary to enable routine application for large-scale chemical systems. Among the state-of-the-art MR methods, second-order N-electron valence state perturbation theory (NEVPT2) is an efficient, size-consistent, and intruder-state-free method. However, there are still twomore » important bottlenecks in practical applications of NEVPT2 to large systems: (a) the high computational cost of NEVPT2 for large molecules, even with moderate active spaces and (b) the prohibitive cost for treating large active spaces. In this work, we address problem (a) by developing a linear scaling “partially contracted” NEVPT2 method. This development uses the idea of domain-based local pair natural orbitals (DLPNOs) to form a highly efficient algorithm. As shown previously in the framework of single-reference methods, the DLPNO concept leads to an enormous reduction in computational effort while at the same time providing high accuracy (approaching 99.9% of the correlation energy), robustness, and black-box character. In the DLPNO approach, the virtual space is spanned by pair natural orbitals that are expanded in terms of projected atomic orbitals in large orbital domains, while the inactive space is spanned by localized orbitals. The active orbitals are left untouched. Our implementation features a highly efficient “electron pair prescreening” that skips the negligible inactive pairs. The surviving pairs are treated using the partially contracted NEVPT2 formalism. A detailed comparison between the partial and strong contraction schemes is made, with conclusions that discourage the strong contraction scheme as a basis for local correlation methods due to its non-invariance with respect to rotations in the inactive and external subspaces. A minimal set of conservatively chosen truncation thresholds controls the accuracy of the method. With the default thresholds, about 99.9% of the canonical partially contracted NEVPT2 correlation energy is recovered while the crossover of the computational cost with the already very efficient canonical method occurs reasonably early; in linear chain type compounds at a chain length of around 80 atoms. Calculations are reported for systems with more than 300 atoms and 5400 basis functions.« less

Independent-Cluster Parametrizations of Wave Functions in Model Field Theories III. The Coupled-Cluster Phase Spaces and Their Geometrical Structure

NASA Astrophysics Data System (ADS)

Arponen, J. S.; Bishop, R. F.

1993-11-01

In this third paper of a series we study the structure of the phase spaces of the independent-cluster methods. These phase spaces are classical symplectic manifolds which provide faithful descriptions of the quantum mechanical pure states of an arbitrary system. They are "superspaces" in the sense that the full physical many-body or field-theoretic system is described by a point of the space, in contrast to "ordinary" spaces for which the state of the physical system is described rather by the whole space itself. We focus attention on the normal and extended coupled-cluster methods (NCCM and ECCM). Both methods provide parametrizations of the Hilbert space which take into account in increasing degrees of completeness the connectivity properties of the associated perturbative diagram structure. This corresponds to an increasing incorporation of locality into the description of the quantum system. As a result the degree of nonlinearity increases in the dynamical equations that govern the temporal evolution and determine the equilibrium state. Because of the nonlinearity, the structure of the manifold becomes geometrically complicated. We analyse the neighbourhood of the ground state of the one-mode anharmonic bosonic field theory and derive the nonlinear expansion beyond the linear response regime. The expansion is given in terms of normal-mode amplitudes, which provide the best local coordinate system close to the ground state. We generalize the treatment to other nonequilibrium states by considering the similarly defined normal coordinates around the corresponding phase space point. It is pointed out that the coupled-cluster method (CCM) maps display such features as (an)holonomy, or geometric phase. For example, a physical state may be represented by a number of different points on the CCM manifold. For this reason the whole phase spaces in the NCCM or ECCM cannot be covered by a single chart. To account for this non-Euclidean nature we introduce a suitable pseudo-Riemannian metric structure which is compatible with an important subset of all canonical transformations. It is then shown that the phase space of the configuration-interaction method is flat, namely the complex Euclidean space; that the NCCM manifold has zero curvature even though its Reimann tensor does not vanish; and that the ECCM manifold is intrinsically curved. It is pointed out that with the present metrization many of the dimensions of the ECCM phase space are effectively compactified and that the overall topological structure of the space is related to the distribution of the zeros of the Bargmann wave function.

Multi-Maneuver Clohessy-Wiltshire Targeting

NASA Technical Reports Server (NTRS)

Dannemiller, David P.

2011-01-01

Orbital rendezvous involves execution of a sequence of maneuvers by a chaser vehicle to bring the chaser to a desired state relative to a target vehicle while meeting intermediate and final relative constraints. Intermediate and final relative constraints are necessary to meet a multitude of requirements such as to control approach direction, ensure relative position is adequate for operation of space-to-space communication systems and relative sensors, provide fail-safe trajectory features, and provide contingency hold points. The effect of maneuvers on constraints is often coupled, so the maneuvers must be solved for as a set. For example, maneuvers that affect orbital energy change both the chaser's height and downrange position relative to the target vehicle. Rendezvous designers use experience and rules-of-thumb to design a sequence of maneuvers and constraints. A non-iterative method is presented for targeting a rendezvous scenario that includes a sequence of maneuvers and relative constraints. This method is referred to as Multi-Maneuver Clohessy-Wiltshire Targeting (MM_CW_TGT). When a single maneuver is targeted to a single relative position, the classic CW targeting solution is obtained. The MM_CW_TGT method involves manipulation of the CW state transition matrix to form a linear system. As a starting point for forming the algorithm, the effects of a series of impulsive maneuvers on the state are derived. Simple and moderately complex examples are used to demonstrate the pattern of the resulting linear system. The general form of the pattern results in an algorithm for formation of the linear system. The resulting linear system relates the effect of maneuver components and initial conditions on relative constraints specified by the rendezvous designer. Solution of the linear system includes the straight-forward inverse of a square matrix. Inversion of the square matrix is assured if the designer poses a controllable scenario - a scenario where the the constraints can be met by the sequence of maneuvers. Matrices in the linear system are dependent on selection of maneuvers and constraints by the designer, but the matrices are independent of the chaser's initial conditions. For scenarios where the sequence of maneuvers and constraints are fixed, the linear system can be formed and the square matrix inverted prior to real-time operations. Example solutions are presented for several rendezvous scenarios to illustrate the utility of the method. The MM_CW_TGT method has been used during the preliminary design of rendezvous scenarios and is expected to be useful for iterative methods in the generation of an initial guess and corrections.

Physical lumping methods for developing linear reduced models for high speed propulsion systems

NASA Technical Reports Server (NTRS)

Immel, S. M.; Hartley, Tom T.; Deabreu-Garcia, J. Alex

1991-01-01

In gasdynamic systems, information travels in one direction for supersonic flow and in both directions for subsonic flow. A shock occurs at the transition from supersonic to subsonic flow. Thus, to simulate these systems, any simulation method implemented for the quasi-one-dimensional Euler equations must have the ability to capture the shock. In this paper, a technique combining both backward and central differencing is presented. The equations are subsequently linearized about an operating point and formulated into a linear state space model. After proper implementation of the boundary conditions, the model order is reduced from 123 to less than 10 using the Schur method of balancing. Simulations comparing frequency and step response of the reduced order model and the original system models are presented.

Dynamical Cognitive Models of Social Issues in Russia

NASA Astrophysics Data System (ADS)

Mitina, Olga; Abraham, Fred; Petrenko, Victor

We examine and model dynamics in three areas of social cognition: (1) political transformations within Russia, (2) evaluation of political trends in other countries by Russians, and (3) evaluation of Russian stereotypes concerning women. We try to represent consciousness as vectorfields and trajectories in a cognitive state space. We use psychosemantic techniques that allow definition of the state space and the systematic construction of these vectorfields and trajectories and their portrait from research data. Then we construct models to fit them, using multiple regression methods to obtain linear differential equations. These dynamical models of social cognition fit the data quite well. (1) The political transformations were modeled by a spiral repellor in a two-dimensional space of a democratic-totalitarian factor and social depression-optimism factor. (2) The evaluation of alien political trends included a flow away from a saddle toward more stable and moderate political regimes in a 2D space, of democratic-totalitarian and unstable-stable cognitive dimensions. (3) The gender study showed expectations (attractors) for more liberated, emancipated roles for women in the future.

Current understanding of the physics of type III solar radio bursts

NASA Technical Reports Server (NTRS)

Papadopoulos, K.

1980-01-01

One of the most exciting plasma physics investigations of recent years has been connected with the understanding of a new strong turbulent plasma state excited by propagating electron beams. This new state is initiated on the linear level by parametric instabilities (OTS, modulational, etc.) and results in a very dynamic state composed of collective clusters of modes called solitons, cavitons, spikons, etc. Introduction of these concepts into the classic beam-plasma interaction problem has rendered quasi-linear and weak turbulence theories inapplicable over most of the interesting parameter range, and helped explain many paradoxes connected with the propagation of beams in the laboratory and space. Following a brief review of these nonlinear notions, the means by which their application to type III solar radiobursts has revolutionized understanding of their propagation, radioemission and scaling properties and has guided the in situ observations towards a more complete understanding are demonstrated. A particular burst (May 16, 1971) is analyzed in detail and compared with numerical predictions.

Integration of Libration Point Orbit Dynamics into a Universal 3-D Autonomous Formation Flying Algorithm

NASA Technical Reports Server (NTRS)

Folta, David; Bauer, Frank H. (Technical Monitor)

2001-01-01

The autonomous formation flying control algorithm developed by the Goddard Space Flight Center (GSFC) for the New Millennium Program (NMP) Earth Observing-1 (EO-1) mission is investigated for applicability to libration point orbit formations. In the EO-1 formation-flying algorithm, control is accomplished via linearization about a reference transfer orbit with a state transition matrix (STM) computed from state inputs. The effect of libration point orbit dynamics on this algorithm architecture is explored via computation of STMs using the flight proven code, a monodromy matrix developed from a N-body model of a libration orbit, and a standard STM developed from the gravitational and coriolis effects as measured at the libration point. A comparison of formation flying Delta-Vs calculated from these methods is made to a standard linear quadratic regulator (LQR) method. The universal 3-D approach is optimal in the sense that it can be accommodated as an open-loop or closed-loop control using only state information.

Elementary derivation of the quantum propagator for the harmonic oscillator

NASA Astrophysics Data System (ADS)

Shao, Jiushu

2016-10-01

Operator algebra techniques are employed to derive the quantum evolution operator for the harmonic oscillator. The derivation begins with the construction of the annihilation and creation operators and the determination of the wave function for the coherent state as well as its time-dependent evolution, and ends with the transformation of the propagator in a mixed position-coherent-state representation to the desired one in configuration space. Throughout the entire procedure, besides elementary operator manipulations, it is only necessary to solve linear differential equations and to calculate Gaussian integrals.

Quasi-degenerate perturbation theory using matrix product states

NASA Astrophysics Data System (ADS)

Sharma, Sandeep; Jeanmairet, Guillaume; Alavi, Ali

2016-01-01

In this work, we generalize the recently proposed matrix product state perturbation theory (MPSPT) for calculating energies of excited states using quasi-degenerate (QD) perturbation theory. Our formulation uses the Kirtman-Certain-Hirschfelder canonical Van Vleck perturbation theory, which gives Hermitian effective Hamiltonians at each order, and also allows one to make use of Wigner's 2n + 1 rule. Further, our formulation satisfies Granovsky's requirement of model space invariance which is important for obtaining smooth potential energy curves. Thus, when we use MPSPT with the Dyall Hamiltonian, we obtain a model space invariant version of quasi-degenerate n-electron valence state perturbation theory (NEVPT), a property that the usual formulation of QD-NEVPT2 based on a multipartitioning technique lacked. We use our method on the benchmark problems of bond breaking of LiF which shows ionic to covalent curve crossing and the twist around the double bond of ethylene where significant valence-Rydberg mixing occurs in the excited states. In accordance with our previous work, we find that multi-reference linearized coupled cluster theory is more accurate than other multi-reference theories of similar cost.

Smoothing-based compressed state Kalman filter for joint state-parameter estimation: Applications in reservoir characterization and CO2 storage monitoring

NASA Astrophysics Data System (ADS)

Li, Y. J.; Kokkinaki, Amalia; Darve, Eric F.; Kitanidis, Peter K.

2017-08-01

The operation of most engineered hydrogeological systems relies on simulating physical processes using numerical models with uncertain parameters and initial conditions. Predictions by such uncertain models can be greatly improved by Kalman-filter techniques that sequentially assimilate monitoring data. Each assimilation constitutes a nonlinear optimization, which is solved by linearizing an objective function about the model prediction and applying a linear correction to this prediction. However, if model parameters and initial conditions are uncertain, the optimization problem becomes strongly nonlinear and a linear correction may yield unphysical results. In this paper, we investigate the utility of one-step ahead smoothing, a variant of the traditional filtering process, to eliminate nonphysical results and reduce estimation artifacts caused by nonlinearities. We present the smoothing-based compressed state Kalman filter (sCSKF), an algorithm that combines one step ahead smoothing, in which current observations are used to correct the state and parameters one step back in time, with a nonensemble covariance compression scheme, that reduces the computational cost by efficiently exploring the high-dimensional state and parameter space. Numerical experiments show that when model parameters are uncertain and the states exhibit hyperbolic behavior with sharp fronts, as in CO2 storage applications, one-step ahead smoothing reduces overshooting errors and, by design, gives physically consistent state and parameter estimates. We compared sCSKF with commonly used data assimilation methods and showed that for the same computational cost, combining one step ahead smoothing and nonensemble compression is advantageous for real-time characterization and monitoring of large-scale hydrogeological systems with sharp moving fronts.

Three-dimensional polarization states of monochromatic light fields.

PubMed

Azzam, R M A

2011-11-01

The 3×1 generalized Jones vectors (GJVs) [E(x) E(y) E(z)](t) (t indicates the transpose) that describe the linear, circular, and elliptical polarization states of an arbitrary three-dimensional (3-D) monochromatic light field are determined in terms of the geometrical parameters of the 3-D vibration of the time-harmonic electric field. In three dimensions, there are as many distinct linear polarization states as there are points on the surface of a hemisphere, and the number of distinct 3-D circular polarization states equals that of all two-dimensional (2-D) polarization states on the Poincaré sphere, of which only two are circular states. The subset of 3-D polarization states that results from the superposition of three mutually orthogonal x, y, and z field components of equal amplitude is considered as a function of their relative phases. Interesting contours of equal ellipticity and equal inclination of the normal to the polarization ellipse with respect to the x axis are obtained in 2-D phase space. Finally, the 3×3 generalized Jones calculus, in which elastic scattering (e.g., by a nano-object in the near field) is characterized by the 3-D linear transformation E(s)=T E(i), is briefly introduced. In such a matrix transformation, E(i) and E(s) are the 3×1 GJVs of the incident and scattered waves and T is the 3×3 generalized Jones matrix of the scatterer at a given frequency and for given directions of incidence and scattering.

Simultaneous structural and control optimization via linear quadratic regulator eigenstructure assignment

NASA Technical Reports Server (NTRS)

Becus, G. A.; Lui, C. Y.; Venkayya, V. B.; Tischler, V. A.

1987-01-01

A method for simultaneous structural and control design of large flexible space structures (LFSS) to reduce vibration generated by disturbances is presented. Desired natural frequencies and damping ratios for the closed loop system are achieved by using a combination of linear quadratic regulator (LQR) synthesis and numerical optimization techniques. The state and control weighing matrices (Q and R) are expressed in terms of structural parameters such as mass and stiffness. The design parameters are selected by numerical optimization so as to minimize the weight of the structure and to achieve the desired closed-loop eigenvalues. An illustrative example of the design of a two bar truss is presented.

Multispectral Linear Array detector technology

NASA Astrophysics Data System (ADS)

Tower, J. R.; McCarthy, B. M.; Pellon, L. E.; Strong, R. T.; Elabd, H.

1984-01-01

The Multispectral Linear Array (MLA) program sponsored by NASA has the aim to extend space-based remote sensor capabilities. The technology development effort involves the realization of very large, all-solid-state, pushbroom focal planes. The pushbroom, staring focal planes will contain thousands of detectors with the objective to provide two orders of magnitude improvement in detector dwell time compared to present Landsat mechanically scanned systems. Attenton is given to visible and near-infrared sensor development, the shortwave infrared sensor, aspects of filter technology development, the packaging concept, and questions of system performance. First-sample, four-band interference filters have been fabricated successfully, and a hybrid packaging technology is being developed.

Development of a Low Inductance Linear Alternator for Stirling Power Convertors

NASA Technical Reports Server (NTRS)

Geng, Steven M.; Schifer, Nicholas A.

2017-01-01

The free-piston Stirling power convertor is a promising technology for high efficiency heat-to-electricity power conversion in space. Stirling power convertors typically utilize linear alternators for converting mechanical motion into electricity. The linear alternator is one of the heaviest components of modern Stirling power convertors. In addition, state-of-art Stirling linear alternators usually require the use of tuning capacitors or active power factor correction controllers to maximize convertor output power. The linear alternator to be discussed in this paper, eliminates the need for tuning capacitors and delivers electrical power output in which current is inherently in phase with voltage. No power factor correction is needed. In addition, the linear alternator concept requires very little iron, so core loss has been virtually eliminated. This concept is a unique moving coil design where the magnetic flux path is defined by the magnets themselves. This paper presents computational predictions for two different low inductance alternator configurations, and compares the predictions with experimental data for one of the configurations that has been built and is currently being tested.

Development of a Low-Inductance Linear Alternator for Stirling Power Convertors

NASA Technical Reports Server (NTRS)

Geng, Steven M.; Schifer, Nicholas A.

2017-01-01

The free-piston Stirling power convertor is a promising technology for high-efficiency heat-to-electricity power conversion in space. Stirling power convertors typically utilize linear alternators for converting mechanical motion into electricity. The linear alternator is one of the heaviest components of modern Stirling power convertors. In addition, state-of-the-art Stirling linear alternators usually require the use of tuning capacitors or active power factor correction controllers to maximize convertor output power. The linear alternator to be discussed in this paper eliminates the need for tuning capacitors and delivers electrical power output in which current is inherently in phase with voltage. No power factor correction is needed. In addition, the linear alternator concept requires very little iron, so core loss has been virtually eliminated. This concept is a unique moving coil design where the magnetic flux path is defined by the magnets themselves. This paper presents computational predictions for two different low inductance alternator configurations. Additionally, one of the configurations was built and tested at GRC, and the experimental data is compared with the predictions.

Spacecraft nonlinear control

NASA Technical Reports Server (NTRS)

Sheen, Jyh-Jong; Bishop, Robert H.

1992-01-01

The feedback linearization technique is applied to the problem of spacecraft attitude control and momentum management with control moment gyros (CMGs). The feedback linearization consists of a coordinate transformation, which transforms the system to a companion form, and a nonlinear feedback control law to cancel the nonlinear dynamics resulting in a linear equivalent model. Pole placement techniques are then used to place the closed-loop poles. The coordinate transformation proposed here evolves from three output functions of relative degree four, three, and two, respectively. The nonlinear feedback control law is presented. Stability in a neighborhood of a controllable torque equilibrium attitude (TEA) is guaranteed and this fact is demonstrated by the simulation results. An investigation of the nonlinear control law shows that singularities exist in the state space outside the neighborhood of the controllable TEA. The nonlinear control law is simplified by a standard linearization technique and it is shown that the linearized nonlinear controller provides a natural way to select control gains for the multiple-input, multiple-output system. Simulation results using the linearized nonlinear controller show good performance relative to the nonlinear controller in the neighborhood of the TEA.

Spectral functions with the density matrix renormalization group: Krylov-space approach for correction vectors

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

None, None

Frequency-dependent correlations, such as the spectral function and the dynamical structure factor, help illustrate condensed matter experiments. Within the density matrix renormalization group (DMRG) framework, an accurate method for calculating spectral functions directly in frequency is the correction-vector method. The correction vector can be computed by solving a linear equation or by minimizing a functional. Our paper proposes an alternative to calculate the correction vector: to use the Krylov-space approach. This paper also studies the accuracy and performance of the Krylov-space approach, when applied to the Heisenberg, the t-J, and the Hubbard models. The cases we studied indicate that themore » Krylov-space approach can be more accurate and efficient than the conjugate gradient, and that the error of the former integrates best when a Krylov-space decomposition is also used for ground state DMRG.« less

Spectral functions with the density matrix renormalization group: Krylov-space approach for correction vectors

DOE PAGES

None, None

2016-11-21

Frequency-dependent correlations, such as the spectral function and the dynamical structure factor, help illustrate condensed matter experiments. Within the density matrix renormalization group (DMRG) framework, an accurate method for calculating spectral functions directly in frequency is the correction-vector method. The correction vector can be computed by solving a linear equation or by minimizing a functional. Our paper proposes an alternative to calculate the correction vector: to use the Krylov-space approach. This paper also studies the accuracy and performance of the Krylov-space approach, when applied to the Heisenberg, the t-J, and the Hubbard models. The cases we studied indicate that themore » Krylov-space approach can be more accurate and efficient than the conjugate gradient, and that the error of the former integrates best when a Krylov-space decomposition is also used for ground state DMRG.« less

Aeroelastic modeling of the active flexible wing wind-tunnel model

NASA Technical Reports Server (NTRS)

Silva, Walter A.; Heeg, Jennifer; Bennett, Robert M.

1991-01-01

The primary issues involved in the generation of linear, state-space equations of motion of a flexible wind tunnel model, the Active Flexible Wing (AFW), are discussed. The codes that were used and their inherent assumptions and limitations are also briefly discussed. The application of the CAP-TSD code to the AFW for determination of the model's transonic flutter boundary is included as well.

Determinism in synthesized chaotic waveforms.

PubMed

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

2008-03-01

The output of a linear filter driven by a randomly polarized square wave, when viewed backward in time, is shown to exhibit determinism at all times when embedded in a three-dimensional state space. Combined with previous results establishing exponential divergence equivalent to a positive Lyapunov exponent, this result rigorously shows that such reverse-time synthesized waveforms appear equally to have been produced by a deterministic chaotic system.

The Theory of Thermodynamic Systems with Internal Variables of State: Necessary and Sufficient Conditions for Compliance with the Second Law of Thermodynamics

NASA Astrophysics Data System (ADS)

Shnip, A. I.

2018-01-01

Based on the entropy-free thermodynamic approach, a generalized theory of thermodynamic systems with internal variables of state is being developed. For the case of nonlinear thermodynamic systems with internal variables of state and linear relaxation, the necessary and sufficient conditions have been proved for fulfillment of the second law of thermodynamics in entropy-free formulation which, according to the basic theorem of the theory, are also necessary and sufficient for the existence of a thermodynamic potential. Moreover, relations of correspondence between thermodynamic systems with memory and systems with internal variables of state have been established, as well as some useful relations in the spaces of states of both types of systems.

A latent low-dimensional common input drives a pool of motor neurons: a probabilistic latent state-space model.

PubMed

Feeney, Daniel F; Meyer, François G; Noone, Nicholas; Enoka, Roger M

2017-10-01

Motor neurons appear to be activated with a common input signal that modulates the discharge activity of all neurons in the motor nucleus. It has proven difficult for neurophysiologists to quantify the variability in a common input signal, but characterization of such a signal may improve our understanding of how the activation signal varies across motor tasks. Contemporary methods of quantifying the common input to motor neurons rely on compiling discrete action potentials into continuous time series, assuming the motor pool acts as a linear filter, and requiring signals to be of sufficient duration for frequency analysis. We introduce a space-state model in which the discharge activity of motor neurons is modeled as inhomogeneous Poisson processes and propose a method to quantify an abstract latent trajectory that represents the common input received by motor neurons. The approach also approximates the variation in synaptic noise in the common input signal. The model is validated with four data sets: a simulation of 120 motor units, a pair of integrate-and-fire neurons with a Renshaw cell providing inhibitory feedback, the discharge activity of 10 integrate-and-fire neurons, and the discharge times of concurrently active motor units during an isometric voluntary contraction. The simulations revealed that a latent state-space model is able to quantify the trajectory and variability of the common input signal across all four conditions. When compared with the cumulative spike train method of characterizing common input, the state-space approach was more sensitive to the details of the common input current and was less influenced by the duration of the signal. The state-space approach appears to be capable of detecting rather modest changes in common input signals across conditions. NEW & NOTEWORTHY We propose a state-space model that explicitly delineates a common input signal sent to motor neurons and the physiological noise inherent in synaptic signal transmission. This is the first application of a deterministic state-space model to represent the discharge characteristics of motor units during voluntary contractions. Copyright © 2017 the American Physiological Society.

Parameter estimating state reconstruction

NASA Technical Reports Server (NTRS)

George, E. B.

1976-01-01

Parameter estimation is considered for systems whose entire state cannot be measured. Linear observers are designed to recover the unmeasured states to a sufficient accuracy to permit the estimation process. There are three distinct dynamics that must be accommodated in the system design: the dynamics of the plant, the dynamics of the observer, and the system updating of the parameter estimation. The latter two are designed to minimize interaction of the involved systems. These techniques are extended to weakly nonlinear systems. The application to a simulation of a space shuttle POGO system test is of particular interest. A nonlinear simulation of the system is developed, observers designed, and the parameters estimated.

Dynamics modeling and periodic control of horizontal-axis wind turbines

NASA Astrophysics Data System (ADS)

Stol, Karl Alexander

2001-07-01

The development of large multi-megawatt wind turbines has increased the need for active feedback control to meet multiple performance objectives. Power regulation is still of prime concern but there is an increasing interest in mitigating loads for these very large, dynamically soft and highly integrated power systems. This work explores the opportunities for utilizing state space modeling, modal analysis, and multi-objective controllers in advanced horizontal-axis wind turbines. A linear state-space representation of a generic, multiple degree-of-freedom wind turbine is developed to test various control methods and paradigms. The structural model, SymDyn, provides for limited flexibility in the tower, drive train and blades assuming a rigid component architecture with joint springs and dampers. Equations of motion are derived symbolically, verified by numerical simulation, and implemented in the Matlab with Simulink computational environment. AeroDyn, an industry-standard aerodynamics package for wind turbines, provides the aerodynamic load data through interfaced subroutines. Linearization of the structural model produces state equations with periodic coefficients due to the interaction of rotating and non-rotating components. Floquet theory is used to extract the necessary modal properties and several parametric studies identify the damping levels and dominant dynamic coupling influences. Two separate issues of control design are investigated: full-state feedback and state estimation. Periodic gains are developed using time-varying LQR techniques and many different time-invariant control designs are constructed, including a classical PID controller. Disturbance accommodating control (DAC) allows the estimation of wind speed for minimization of the disturbance effects on the system. Controllers are tested in simulation for multiple objectives using measurement of rotor position and rotor speed only and actuation of independent blade pitch. It is found that periodic control is capable of reducing cyclic blade bending moments while regulating speed but that optimal performance requires additional sensor information. Periodic control is also the only design found that could successfully control the yaw alignment although blade loads are increased as a consequence. When speed regulation is the only performance objective then a time-invariant state-space design or PID is appropriate.

An ab initio study of the C3(+) cation using multireference methods

NASA Technical Reports Server (NTRS)

Taylor, Peter R.; Martin, J. M. L.; Francois, J. P.; Gijbels, R.

1991-01-01

The energy difference between the linear 2 sigma(sup +, sub u) and cyclic 2B(sub 2) structures of C3(+) has been investigated using large (5s3p2d1f) basis sets and multireference electron correlation treatments, including complete active space self consistent fields (CASSCF), multireference configuration interaction (MRCI), and averaged coupled-pair functional (ACPF) methods, as well as the single-reference quadratic configuration interaction (QCISD(T)) method. Our best estimate, including a correction for basis set incompleteness, is that the linear form lies above the cyclic from by 5.2(+1.5 to -1.0) kcal/mol. The 2 sigma(sup +, sub u) state is probably not a transition state, but a local minimum. Reliable computation of the cyclic/linear energy difference in C3(+) is extremely demanding of the electron correlation treatment used: of the single-reference methods previously considered, CCSD(T) and QCISD(T) perform best. The MRCI + Q(0.01)/(4s2p1d) energy separation of 1.68 kcal/mol should provide a comparison standard for other electron correlation methods applied to this system.

Structured Kernel Dictionary Learning with Correlation Constraint for Object Recognition.

PubMed

Wang, Zhengjue; Wang, Yinghua; Liu, Hongwei; Zhang, Hao

2017-06-21

In this paper, we propose a new discriminative non-linear dictionary learning approach, called correlation constrained structured kernel KSVD, for object recognition. The objective function for dictionary learning contains a reconstructive term and a discriminative term. In the reconstructive term, signals are implicitly non-linearly mapped into a space, where a structured kernel dictionary, each sub-dictionary of which lies in the span of the mapped signals from the corresponding class, is established. In the discriminative term, by analyzing the classification mechanism, the correlation constraint is proposed in kernel form, constraining the correlations between different discriminative codes, and restricting the coefficient vectors to be transformed into a feature space, where the features are highly correlated inner-class and nearly independent between-classes. The objective function is optimized by the proposed structured kernel KSVD. During the classification stage, the specific form of the discriminative feature is needless to be known, while the inner product of the discriminative feature with kernel matrix embedded is available, and is suitable for a linear SVM classifier. Experimental results demonstrate that the proposed approach outperforms many state-of-the-art dictionary learning approaches for face, scene and synthetic aperture radar (SAR) vehicle target recognition.

On the Validity of the Streaming Model for the Redshift-Space Correlation Function in the Linear Regime

NASA Astrophysics Data System (ADS)

Fisher, Karl B.

1995-08-01

The relation between the galaxy correlation functions in real-space and redshift-space is derived in the linear regime by an appropriate averaging of the joint probability distribution of density and velocity. The derivation recovers the familiar linear theory result on large scales but has the advantage of clearly revealing the dependence of the redshift distortions on the underlying peculiar velocity field; streaming motions give rise to distortions of θ(Ω0.6/b) while variations in the anisotropic velocity dispersion yield terms of order θ(Ω1.2/b2). This probabilistic derivation of the redshift-space correlation function is similar in spirit to the derivation of the commonly used "streaming" model, in which the distortions are given by a convolution of the real-space correlation function with a velocity distribution function. The streaming model is often used to model the redshift-space correlation function on small, highly nonlinear, scales. There have been claims in the literature, however, that the streaming model is not valid in the linear regime. Our analysis confirms this claim, but we show that the streaming model can be made consistent with linear theory provided that the model for the streaming has the functional form predicted by linear theory and that the velocity distribution is chosen to be a Gaussian with the correct linear theory dispersion.

Experimental evidence of space charge driven resonances in high intensity linear accelerators

DOE PAGES

Jeon, Dong -O

2016-01-12

In the construction of high intensity accelerators, it is the utmost goal to minimize the beam loss by avoiding or minimizing contributions of various halo formation mechanisms. As a halo formation mechanism, space charge driven resonances are well known for circular accelerators. However, the recent finding showed that even in linear accelerators the space charge potential can excite the 4σ = 360° fourth order resonance [D. Jeon et al., Phys. Rev. ST Accel. Beams 12, 054204 (2009)]. This study increased the interests in space charge driven resonances of linear accelerators. Experimental studies of the space charge driven resonances of highmore » intensity linear accelerators are rare as opposed to the multitude of simulation studies. This paper presents an experimental evidence of the space charge driven 4σ ¼ 360° resonance and the 2σ x(y) – 2σ z = 0 resonance of a high intensity linear accelerator through beam profile measurements from multiple wire-scanners. Moreover, measured beam profiles agree well with the characteristics of the space charge driven 4σ = 360° resonance and the 2σ x(y) – 2σ z = 0 resonance that are predicted by the simulation.« less

State-space prediction of spring discharge in a karst catchment in southwest China

NASA Astrophysics Data System (ADS)

Li, Zhenwei; Xu, Xianli; Liu, Meixian; Li, Xuezhang; Zhang, Rongfei; Wang, Kelin; Xu, Chaohao

2017-06-01

Southwest China represents one of the largest continuous karst regions in the world. It is estimated that around 1.7 million people are heavily dependent on water derived from karst springs in southwest China. However, there is a limited amount of water supply in this region. Moreover, there is not enough information on temporal patterns of spring discharge in the area. In this context, it is essential to accurately predict spring discharge, as well as understand karst hydrological processes in a thorough manner, so that water shortages in this area could be predicted and managed efficiently. The objectives of this study were to determine the primary factors that govern spring discharge patterns and to develop a state-space model to predict spring discharge. Spring discharge, precipitation (PT), relative humidity (RD), water temperature (WD), and electrical conductivity (EC) were the variables analyzed in the present work, and they were monitored at two different locations (referred to as karst springs A and B, respectively, in this paper) in a karst catchment area in southwest China from May to November 2015. Results showed that a state-space model using any combinations of variables outperformed a classical linear regression, a back-propagation artificial neural network model, and a least square support vector machine in modeling spring discharge time series for karst spring A. The best state-space model was obtained by using PT and RD, which accounted for 99.9% of the total variation in spring discharge. This model was then applied to an independent data set obtained from karst spring B, and it provided accurate spring discharge estimates. Therefore, state-space modeling was a useful tool for predicting spring discharge in karst regions in southwest China, and this modeling procedure may help researchers to obtain accurate results in other karst regions.

A state space approach for piecewise-linear recurrent neural networks for identifying computational dynamics from neural measurements.

PubMed

Durstewitz, Daniel

2017-06-01

The computational and cognitive properties of neural systems are often thought to be implemented in terms of their (stochastic) network dynamics. Hence, recovering the system dynamics from experimentally observed neuronal time series, like multiple single-unit recordings or neuroimaging data, is an important step toward understanding its computations. Ideally, one would not only seek a (lower-dimensional) state space representation of the dynamics, but would wish to have access to its statistical properties and their generative equations for in-depth analysis. Recurrent neural networks (RNNs) are a computationally powerful and dynamically universal formal framework which has been extensively studied from both the computational and the dynamical systems perspective. Here we develop a semi-analytical maximum-likelihood estimation scheme for piecewise-linear RNNs (PLRNNs) within the statistical framework of state space models, which accounts for noise in both the underlying latent dynamics and the observation process. The Expectation-Maximization algorithm is used to infer the latent state distribution, through a global Laplace approximation, and the PLRNN parameters iteratively. After validating the procedure on toy examples, and using inference through particle filters for comparison, the approach is applied to multiple single-unit recordings from the rodent anterior cingulate cortex (ACC) obtained during performance of a classical working memory task, delayed alternation. Models estimated from kernel-smoothed spike time data were able to capture the essential computational dynamics underlying task performance, including stimulus-selective delay activity. The estimated models were rarely multi-stable, however, but rather were tuned to exhibit slow dynamics in the vicinity of a bifurcation point. In summary, the present work advances a semi-analytical (thus reasonably fast) maximum-likelihood estimation framework for PLRNNs that may enable to recover relevant aspects of the nonlinear dynamics underlying observed neuronal time series, and directly link these to computational properties.

Manipulation of a two-photon state in a χ(2)-modulated nonlinear waveguide array

NASA Astrophysics Data System (ADS)

Yang, Y.; Xu, P.; Lu, L. L.; Zhu, S. N.

2014-10-01

We propose to engineer the quantum state in a high-dimensional Hilbert space by taking advantage of a χ(2)-modulated nonlinear waveguide array. By varying the pump condition and the waveguide array length, the momentum correlation between the signal and idler photons can be manipulated, exhibiting bunching, antibunching, and the evolution between these two states, which are characterized by the Schmidt number. We find the Schmidt number is dependent on a structure parameter, namely the ratio of the array length and the number of channels pumped. By designing the linear profile waveguide array, the degree of spatial entanglement shows a periodic relationship with the slope of linear profile, during which a high degree of position-bunching state is suggested. The two-photon self-focusing effect is disclosed when the χ(2) modulation in the waveguide array contains a parabolic profile, which can be designed for efficient coupling between a waveguide array and fibers. These results shed light on a feasible way to achieve desirable quantum state on a single waveguide chip by a compact engineering of χ(2) and also suggest a degree of freedom for quantum walk and other related applications.

Development of flank wear model of cutting tool by using adaptive feedback linear control system on machining AISI D2 steel and AISI 4340 steel

NASA Astrophysics Data System (ADS)

Orra, Kashfull; Choudhury, Sounak K.

2016-12-01

The purpose of this paper is to build an adaptive feedback linear control system to check the variation of cutting force signal to improve the tool life. The paper discusses the use of transfer function approach in improving the mathematical modelling and adaptively controlling the process dynamics of the turning operation. The experimental results shows to be in agreement with the simulation model and error obtained is less than 3%. The state space approach model used in this paper successfully check the adequacy of the control system through controllability and observability test matrix and can be transferred from one state to another by appropriate input control in a finite time. The proposed system can be implemented to other machining process under varying range of cutting conditions to improve the efficiency and observability of the system.

Data driven discrete-time parsimonious identification of a nonlinear state-space model for a weakly nonlinear system with short data record

NASA Astrophysics Data System (ADS)

Relan, Rishi; Tiels, Koen; Marconato, Anna; Dreesen, Philippe; Schoukens, Johan

2018-05-01

Many real world systems exhibit a quasi linear or weakly nonlinear behavior during normal operation, and a hard saturation effect for high peaks of the input signal. In this paper, a methodology to identify a parsimonious discrete-time nonlinear state space model (NLSS) for the nonlinear dynamical system with relatively short data record is proposed. The capability of the NLSS model structure is demonstrated by introducing two different initialisation schemes, one of them using multivariate polynomials. In addition, a method using first-order information of the multivariate polynomials and tensor decomposition is employed to obtain the parsimonious decoupled representation of the set of multivariate real polynomials estimated during the identification of NLSS model. Finally, the experimental verification of the model structure is done on the cascaded water-benchmark identification problem.

Entropy and complexity analysis of hydrogenic Rydberg atoms

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

Lopez-Rosa, S.; Departamento de Fisica Aplicada II, Universidad de Sevilla, 41012-Sevilla; Toranzo, I. V.

The internal disorder of hydrogenic Rydberg atoms as contained in their position and momentum probability densities is examined by means of the following information-theoretic spreading quantities: the radial and logarithmic expectation values, the Shannon entropy, and the Fisher information. As well, the complexity measures of Cramer-Rao, Fisher-Shannon, and Lopez Ruiz-Mancini-Calvet types are investigated in both reciprocal spaces. The leading term of these quantities is rigorously calculated by use of the asymptotic properties of the concomitant entropic functionals of the Laguerre and Gegenbauer orthogonal polynomials which control the wavefunctions of the Rydberg states in both position and momentum spaces. The associatedmore » generalized Heisenberg-like, logarithmic and entropic uncertainty relations are also given. Finally, application to linear (l= 0), circular (l=n- 1), and quasicircular (l=n- 2) states is explicitly done.« less

Existence of Hartree-Fock excited states for atoms and molecules

NASA Astrophysics Data System (ADS)

Lewin, Mathieu

2018-04-01

For neutral and positively charged atoms and molecules, we prove the existence of infinitely many Hartree-Fock critical points below the first energy threshold (that is, the lowest energy of the same system with one electron removed). This is the equivalent, in Hartree-Fock theory, of the famous Zhislin-Sigalov theorem which states the existence of infinitely many eigenvalues below the bottom of the essential spectrum of the N-particle linear Schrödinger operator. Our result improves a theorem of Lions in 1987 who already constructed infinitely many Hartree-Fock critical points, but with much higher energy. Our main contribution is the proof that the Hartree-Fock functional satisfies the Palais-Smale property below the first energy threshold. We then use minimax methods in the N-particle space, instead of working in the one-particle space.

The role of modern control theory in the design of controls for aircraft turbine engines

NASA Technical Reports Server (NTRS)

Zeller, J.; Lehtinen, B.; Merrill, W.

1982-01-01

The development, applications, and current research in modern control theory (MCT) are reviewed, noting the importance for fuel-efficient operation of turbines with variable inlet guide vanes, compressor stators, and exhaust nozzle area. The evolution of multivariable propulsion control design is examined, noting a basis in a matrix formulation of the differential equations defining the process, leading to state space formulations. Reports and papers which appeared from 1970-1982 which dealt with problems in MCT applications to turbine engine control design are outlined, including works on linear quadratic regulator methods, frequency domain methods, identification, estimation, and model reduction, detection, isolation, and accommodation, and state space control, adaptive control, and optimization approaches. Finally, NASA programs in frequency domain design, sensor failure detection, computer-aided control design, and plant modeling are explored

Resonance interaction energy between two entangled atoms in a photonic bandgap environment.

PubMed

Notararigo, Valentina; Passante, Roberto; Rizzuto, Lucia

2018-03-26

We consider the resonance interaction energy between two identical entangled atoms, where one is in the excited state and the other in the ground state. They interact with the quantum electromagnetic field in the vacuum state and are placed in a photonic-bandgap environment with a dispersion relation quadratic near the gap edge and linear for low frequencies, while the atomic transition frequency is assumed to be inside the photonic gap and near its lower edge. This problem is strictly related to the coherent resonant energy transfer between atoms in external environments. The analysis involves both an isotropic three-dimensional model and the one-dimensional case. The resonance interaction asymptotically decays faster with distance compared to the free-space case, specifically as 1/r 2 compared to the 1/r free-space dependence in the three-dimensional case, and as 1/r compared to the oscillatory dependence in free space for the one-dimensional case. Nonetheless, the interaction energy remains significant and much stronger than dispersion interactions between atoms. On the other hand, spontaneous emission is strongly suppressed by the environment and the correlated state is thus preserved by the spontaneous-decay decoherence effects. We conclude that our configuration is suitable for observing the elusive quantum resonance interaction between entangled atoms.

Formulation d'un modele mathematique par des techniques d'estimation de parametres a partir de donnees de vol pour l'helicoptere Bell 427 et l'avion F/A-18 servant a la recherches en aeroservoelasticite

NASA Astrophysics Data System (ADS)

Nadeau-Beaulieu, Michel

In this thesis, three mathematical models are built from flight test data for different aircraft design applications: a ground dynamics model for the Bell 427 helicopter, a prediction model for the rotor and engine parameters for the same helicopter type and a simulation model for the aeroelastic deflections of the F/A-18. In the ground dynamics application, the model structure is derived from physics where the normal force between the helicopter and the ground is modelled as a vertical spring and the frictional force is modelled with static and dynamic friction coefficients. The ground dynamics model coefficients are optimized to ensure that the model matches the landing data within the FAA (Federal Aviation Administration) tolerance bands for a level D flight simulator. In the rotor and engine application, rotors torques (main and tail), the engine torque and main rotor speed are estimated using a state-space model. The model inputs are nonlinear terms derived from the pilot control inputs and the helicopter states. The model parameters are identified using the subspace method and are further optimised with the Levenberg-Marquardt minimisation algorithm. The model built with the subspace method provides an excellent estimate of the outputs within the FAA tolerance bands. The F/A-18 aeroelastic state-space model is built from flight test. The research concerning this model is divided in two parts. Firstly, the deflection of a given structural surface on the aircraft following a differential ailerons control input is represented by a Multiple Inputs Single Outputs linear model whose inputs are the ailerons positions and the structural surfaces deflections. Secondly, a single state-space model is used to represent the deflection of the aircraft wings and trailing edge flaps following any control input. In this case the model is made non-linear by multiplying model inputs into higher order terms and using these terms as the inputs of the state-space equations. In both cases, the identification method is the subspace method. Most fit coefficients between the estimated and the measured signals are above 73% and most correlation coefficient are higher than 90%.

Is the local linearity of space-time inherited from the linearity of probabilities?

NASA Astrophysics Data System (ADS)

Müller, Markus P.; Carrozza, Sylvain; Höhn, Philipp A.

2017-02-01

The appearance of linear spaces, describing physical quantities by vectors and tensors, is ubiquitous in all of physics, from classical mechanics to the modern notion of local Lorentz invariance. However, as natural as this seems to the physicist, most computer scientists would argue that something like a ‘local linear tangent space’ is not very typical and in fact a quite surprising property of any conceivable world or algorithm. In this paper, we take the perspective of the computer scientist seriously, and ask whether there could be any inherently information-theoretic reason to expect this notion of linearity to appear in physics. We give a series of simple arguments, spanning quantum information theory, group representation theory, and renormalization in quantum gravity, that supports a surprising thesis: namely, that the local linearity of space-time might ultimately be a consequence of the linearity of probabilities. While our arguments involve a fair amount of speculation, they have the virtue of being independent of any detailed assumptions on quantum gravity, and they are in harmony with several independent recent ideas on emergent space-time in high-energy physics.

Electron-Phonon Systems on a Universal Quantum Computer

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

Macridin, Alexandru; Spentzouris, Panagiotis; Amundson, James

We present an algorithm that extends existing quantum algorithms forsimulating fermion systems in quantum chemistry and condensed matter physics toinclude phonons. The phonon degrees of freedom are represented with exponentialaccuracy on a truncated Hilbert space with a size that increases linearly withthe cutoff of the maximum phonon number. The additional number of qubitsrequired by the presence of phonons scales linearly with the size of thesystem. The additional circuit depth is constant for systems with finite-rangeelectron-phonon and phonon-phonon interactions and linear for long-rangeelectron-phonon interactions. Our algorithm for a Holstein polaron problem wasimplemented on an Atos Quantum Learning Machine (QLM) quantum simulatoremployingmore » the Quantum Phase Estimation method. The energy and the phonon numberdistribution of the polaron state agree with exact diagonalization results forweak, intermediate and strong electron-phonon coupling regimes.« less

Toward a holographic theory for general spacetimes

NASA Astrophysics Data System (ADS)

Nomura, Yasunori; Salzetta, Nico; Sanches, Fabio; Weinberg, Sean J.

2017-04-01

We study a holographic theory of general spacetimes that does not rely on the existence of asymptotic regions. This theory is to be formulated in a holographic space. When a semiclassical description is applicable, the holographic space is assumed to be a holographic screen: a codimension-1 surface that is capable of encoding states of the gravitational spacetime. Our analysis is guided by conjectured relationships between gravitational spacetime and quantum entanglement in the holographic description. To understand basic features of this picture, we catalog predictions for the holographic entanglement structure of cosmological spacetimes. We find that qualitative features of holographic entanglement entropies for such spacetimes differ from those in AdS/CFT but that the former reduce to the latter in the appropriate limit. The Hilbert space of the theory is analyzed, and two plausible structures are found: a direct-sum and "spacetime-equals-entanglement" structure. The former preserves a naive relationship between linear operators and observable quantities, while the latter respects a more direct connection between holographic entanglement and spacetime. We also discuss the issue of selecting a state in quantum gravity, in particular how the state of the multiverse may be selected in the landscape.

Relationship between neighbourhood socioeconomic position and neighbourhood public green space availability: An environmental inequality analysis in a large German city applying generalized linear models.

PubMed

Schüle, Steffen Andreas; Gabriel, Katharina M A; Bolte, Gabriele

2017-06-01

The environmental justice framework states that besides environmental burdens also resources may be social unequally distributed both on the individual and on the neighbourhood level. This ecological study investigated whether neighbourhood socioeconomic position (SEP) was associated with neighbourhood public green space availability in a large German city with more than 1 million inhabitants. Two different measures were defined for green space availability. Firstly, percentage of green space within neighbourhoods was calculated with the additional consideration of various buffers around the boundaries. Secondly, percentage of green space was calculated based on various radii around the neighbourhood centroid. An index of neighbourhood SEP was calculated with principal component analysis. Log-gamma regression from the group of generalized linear models was applied in order to consider the non-normal distribution of the response variable. All models were adjusted for population density. Low neighbourhood SEP was associated with decreasing neighbourhood green space availability including 200m up to 1000m buffers around the neighbourhood boundaries. Low neighbourhood SEP was also associated with decreasing green space availability based on catchment areas measured from neighbourhood centroids with different radii (1000m up to 3000 m). With an increasing radius the strength of the associations decreased. Social unequally distributed green space may amplify environmental health inequalities in an urban context. Thus, the identification of vulnerable neighbourhoods and population groups plays an important role for epidemiological research and healthy city planning. As a methodical aspect, log-gamma regression offers an adequate parametric modelling strategy for positively distributed environmental variables. Copyright © 2017 Elsevier GmbH. All rights reserved.

The Shock and Vibration Digest. Volume 18, Number 7

DTIC Science & Technology

1986-07-01

long-term dynamic irregularity of a soluble Los Alamos, NM, July 21-23, 1981 quantum mechanical model known as the Jaynes - Cummings model . The analysis...substructure models are obtained % substructure computation can be performed by approximating each state space vector as a independently of the other...Non- and rotational residual flexibilities at the inter- linear joint behavior is modeled by an equivalent face. Data were taken in the form of

Global Well-posedness of the Spatially Homogeneous Kolmogorov-Vicsek Model as a Gradient Flow

NASA Astrophysics Data System (ADS)

Figalli, Alessio; Kang, Moon-Jin; Morales, Javier

2018-03-01

We consider the so-called spatially homogenous Kolmogorov-Vicsek model, a non-linear Fokker-Planck equation of self-driven stochastic particles with orientation interaction under the space-homogeneity. We prove the global existence and uniqueness of weak solutions to the equation. We also show that weak solutions exponentially converge to a steady state, which has the form of the Fisher-von Mises distribution.

Neural net forecasting for geomagnetic activity

NASA Technical Reports Server (NTRS)

Hernandez, J. V.; Tajima, T.; Horton, W.

1993-01-01

We use neural nets to construct nonlinear models to forecast the AL index given solar wind and interplanetary magnetic field (IMF) data. We follow two approaches: (1) the state space reconstruction approach, which is a nonlinear generalization of autoregressive-moving average models (ARMA) and (2) the nonlinear filter approach, which reduces to a moving average model (MA) in the linear limit. The database used here is that of Bargatze et al. (1985).

SeaWiFS: The Western United States and Mexico

NASA Technical Reports Server (NTRS)

2002-01-01

The linear patterns in the clouds over the Pacific suggest contrail origins. Subtle variations in cloud density reveal vortex street downwind (southeast) of Mexico's Guadalupe Island. The Great Salt Lake in Utah is divided into two very different colored bodies of water by a railroad causeway. The southern Gulf of California continues to bloom brightly. Credit: Provided by the SeaWiFS Project, NASA/Goddard Space Flight Center, and ORBIMAGE

Field quantization and squeezed states generation in resonators with time-dependent parameters

NASA Technical Reports Server (NTRS)

Dodonov, V. V.; Klimov, A. B.; Nikonov, D. E.

1992-01-01

The problem of electromagnetic field quantization is usually considered in textbooks under the assumption that the field occupies some empty box. The case when a nonuniform time-dependent dielectric medium is confined in some space region with time-dependent boundaries is studied. The basis of the subsequent consideration is the system of Maxwell's equations in linear passive time-dependent dielectric and magnetic medium without sources.

Effect of random vacancies on the electronic properties of graphene and T graphene: a theoretical approach

NASA Astrophysics Data System (ADS)

Sadhukhan, B.; Nayak, A.; Mookerjee, A.

2017-12-01

In this communication we present together four distinct techniques for the study of electronic structure of solids: the tight-binding linear muffin-tin orbitals, the real space and augmented space recursions and the modified exchange-correlation. Using this we investigate the effect of random vacancies on the electronic properties of the carbon hexagonal allotrope, graphene, and the non-hexagonal allotrope, planar T graphene. We have inserted random vacancies at different concentrations, to simulate disorder in pristine graphene and planar T graphene sheets. The resulting disorder, both on-site (diagonal disorder) as well as in the hopping integrals (off-diagonal disorder), introduces sharp peaks in the vicinity of the Dirac point built up from localized states for both hexagonal and non-hexagonal structures. These peaks become resonances with increasing vacancy concentration. We find that in presence of vacancies, graphene-like linear dispersion appears in planar T graphene and the cross points form a loop in the first Brillouin zone similar to buckled T graphene that originates from π and π* bands without regular hexagonal symmetry. We also calculate the single-particle relaxation time, τ (ěc {q}) of ěc {q} labeled quantum electronic states which originates from scattering due to presence of vacancies, causing quantum level broadening.

Precise, motion-free polarization control in Second Harmonic Generation microscopy using a liquid crystal modulator in the infinity space.

PubMed

Lien, Chi-Hsiang; Tilbury, Karissa; Chen, Shean-Jen; Campagnola, Paul J

2013-01-01

Second Harmonic Generation (SHG) microscopy coupled with polarization analysis has great potential for use in tissue characterization, as molecular and supramolecular structural details can be extracted. Such measurements are difficult to perform quickly and accurately. Here we present a new method that uses a liquid crystal modulator (LCM) located in the infinity space of a SHG laser scanning microscope that allows the generation of any desired linear or circular polarization state. As the device contains no moving parts, polarization can be rotated accurately and faster than by manual or motorized control. The performance in terms of polarization purity was validated using Stokes vector polarimetry, and found to have minimal residual polarization ellipticity. SHG polarization imaging characteristics were validated against well-characterized specimens having cylindrical and/or linear symmetries. The LCM has a small footprint and can be implemented easily in any standard microscope and is cost effective relative to other technologies.

Precise, motion-free polarization control in Second Harmonic Generation microscopy using a liquid crystal modulator in the infinity space

PubMed Central

Lien, Chi-Hsiang; Tilbury, Karissa; Chen, Shean-Jen; Campagnola, Paul J.

2013-01-01

Second Harmonic Generation (SHG) microscopy coupled with polarization analysis has great potential for use in tissue characterization, as molecular and supramolecular structural details can be extracted. Such measurements are difficult to perform quickly and accurately. Here we present a new method that uses a liquid crystal modulator (LCM) located in the infinity space of a SHG laser scanning microscope that allows the generation of any desired linear or circular polarization state. As the device contains no moving parts, polarization can be rotated accurately and faster than by manual or motorized control. The performance in terms of polarization purity was validated using Stokes vector polarimetry, and found to have minimal residual polarization ellipticity. SHG polarization imaging characteristics were validated against well-characterized specimens having cylindrical and/or linear symmetries. The LCM has a small footprint and can be implemented easily in any standard microscope and is cost effective relative to other technologies. PMID:24156059

Multi input single output model predictive control of non-linear bio-polymerization process

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

Arumugasamy, Senthil Kumar; Ahmad, Z.

This paper focuses on Multi Input Single Output (MISO) Model Predictive Control of bio-polymerization process in which mechanistic model is developed and linked with the feedforward neural network model to obtain a hybrid model (Mechanistic-FANN) of lipase-catalyzed ring-opening polymerization of ε-caprolactone (ε-CL) for Poly (ε-caprolactone) production. In this research, state space model was used, in which the input to the model were the reactor temperatures and reactor impeller speeds and the output were the molecular weight of polymer (M{sub n}) and polymer polydispersity index. State space model for MISO created using System identification tool box of Matlab™. This state spacemore » model is used in MISO MPC. Model predictive control (MPC) has been applied to predict the molecular weight of the biopolymer and consequently control the molecular weight of biopolymer. The result shows that MPC is able to track reference trajectory and give optimum movement of manipulated variable.« less

Non-Static error tracking control for near space airship loading platform

NASA Astrophysics Data System (ADS)

Ni, Ming; Tao, Fei; Yang, Jiandong

2018-01-01

A control scheme based on internal model with non-static error is presented against the uncertainty of the near space airship loading platform system. The uncertainty in the tracking table is represented as interval variations in stability and control derivatives. By formulating the tracking problem of the uncertainty system as a robust state feedback stabilization problem of an augmented system, sufficient condition for the existence of robust tracking controller is derived in the form of linear matrix inequality (LMI). Finally, simulation results show that the new method not only has better anti-jamming performance, but also improves the dynamic performance of the high-order systems.

Phase-space analysis of charged and optical beam transport: Wigner rotation angle

NASA Technical Reports Server (NTRS)

Dattoli, G.; Torre, Amalia

1994-01-01

The possibility of using the phase space formalism to establish a correspondence between the dynamical behavior of squeezed states and optical or charged beams, propagating through linear systems, has received a great deal of attention during the last years. In this connection, it has been indicated how optical experiments may be conceived to measure the Wigner rotation angle. In this paper we address the topic within the context of the paraxial propagation of optical or charged beams and suggest a possible experiment for measuring the Wigner angle using an electron beam passing through quadrupoles and drift sections. The analogous optical system is also discussed.

A controls engineering approach for analyzing airplane input-output characteristics

NASA Technical Reports Server (NTRS)

Arbuckle, P. Douglas

1991-01-01

An engineering approach for analyzing airplane control and output characteristics is presented. State-space matrix equations describing the linear perturbation dynamics are transformed from physical coordinates into scaled coordinates. The scaling is accomplished by applying various transformations to the system to employ prior engineering knowledge of the airplane physics. Two different analysis techniques are then explained. Modal analysis techniques calculate the influence of each system input on each fundamental mode of motion and the distribution of each mode among the system outputs. The optimal steady state response technique computes the blending of steady state control inputs that optimize the steady state response of selected system outputs. Analysis of an example airplane model is presented to demonstrate the described engineering approach.

Cooperative scattering and radiation pressure force in dense atomic clouds

NASA Astrophysics Data System (ADS)

Bachelard, R.; Piovella, N.; Courteille, Ph. W.

2011-07-01

Atomic clouds prepared in “timed Dicke” states, i.e. states where the phase of the oscillating atomic dipole moments linearly varies along one direction of space, are efficient sources of superradiant light emission [Scully , Phys. Rev. Lett.PRLTAO0031-900710.1103/PhysRevLett.96.010501 96, 010501 (2006)]. Here, we show that, in contrast to previous assertions, timed Dicke states are not the states automatically generated by incident laser light. In reality, the atoms act back on the driving field because of the finite refraction of the cloud. This leads to nonuniform phase shifts, which, at higher optical densities, dramatically alter the cooperative scattering properties, as we show by explicit calculation of macroscopic observables, such as the radiation pressure force.

From quantum stochastic differential equations to Gisin-Percival state diffusion

NASA Astrophysics Data System (ADS)

Parthasarathy, K. R.; Usha Devi, A. R.

2017-08-01

Starting from the quantum stochastic differential equations of Hudson and Parthasarathy [Commun. Math. Phys. 93, 301 (1984)] and exploiting the Wiener-Itô-Segal isomorphism between the boson Fock reservoir space Γ (L2(R+ ) ⊗(Cn⊕Cn ) ) and the Hilbert space L2(μ ) , where μ is the Wiener probability measure of a complex n-dimensional vector-valued standard Brownian motion {B (t ) ,t ≥0 } , we derive a non-linear stochastic Schrödinger equation describing a classical diffusion of states of a quantum system, driven by the Brownian motion B. Changing this Brownian motion by an appropriate Girsanov transformation, we arrive at the Gisin-Percival state diffusion equation [N. Gisin and J. Percival, J. Phys. A 167, 315 (1992)]. This approach also yields an explicit solution of the Gisin-Percival equation, in terms of the Hudson-Parthasarathy unitary process and a randomized Weyl displacement process. Irreversible dynamics of system density operators described by the well-known Gorini-Kossakowski-Sudarshan-Lindblad master equation is unraveled by coarse-graining over the Gisin-Percival quantum state trajectories.

Some Classes of Imperfect Information Finite State-Space Stochastic Games with Finite-Dimensional Solutions

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

McEneaney, William M.

2004-08-15

Stochastic games under imperfect information are typically computationally intractable even in the discrete-time/discrete-state case considered here. We consider a problem where one player has perfect information.A function of a conditional probability distribution is proposed as an information state.In the problem form here, the payoff is only a function of the terminal state of the system,and the initial information state is either linear ora sum of max-plus delta functions.When the initial information state belongs to these classes, its propagation is finite-dimensional.The state feedback value function is also finite-dimensional,and obtained via dynamic programming,but has a nonstandard form due to the necessity ofmore » an expanded state variable.Under a saddle point assumption,Certainty Equivalence is obtained and the proposed function is indeed an information state.« less

Nonlinear-drifted Brownian motion with multiple hidden states for remaining useful life prediction of rechargeable batteries

NASA Astrophysics Data System (ADS)

Wang, Dong; Zhao, Yang; Yang, Fangfang; Tsui, Kwok-Leung

2017-09-01

Brownian motion with adaptive drift has attracted much attention in prognostics because its first hitting time is highly relevant to remaining useful life prediction and it follows the inverse Gaussian distribution. Besides linear degradation modeling, nonlinear-drifted Brownian motion has been developed to model nonlinear degradation. Moreover, the first hitting time distribution of the nonlinear-drifted Brownian motion has been approximated by time-space transformation. In the previous studies, the drift coefficient is the only hidden state used in state space modeling of the nonlinear-drifted Brownian motion. Besides the drift coefficient, parameters of a nonlinear function used in the nonlinear-drifted Brownian motion should be treated as additional hidden states of state space modeling to make the nonlinear-drifted Brownian motion more flexible. In this paper, a prognostic method based on nonlinear-drifted Brownian motion with multiple hidden states is proposed and then it is applied to predict remaining useful life of rechargeable batteries. 26 sets of rechargeable battery degradation samples are analyzed to validate the effectiveness of the proposed prognostic method. Moreover, some comparisons with a standard particle filter based prognostic method, a spherical cubature particle filter based prognostic method and two classic Bayesian prognostic methods are conducted to highlight the superiority of the proposed prognostic method. Results show that the proposed prognostic method has lower average prediction errors than the particle filter based prognostic methods and the classic Bayesian prognostic methods for battery remaining useful life prediction.

Genetic Algorithm-Based Model Order Reduction of Aeroservoelastic Systems with Consistant States

NASA Technical Reports Server (NTRS)

Zhu, Jin; Wang, Yi; Pant, Kapil; Suh, Peter M.; Brenner, Martin J.

2017-01-01

This paper presents a model order reduction framework to construct linear parameter-varying reduced-order models of flexible aircraft for aeroservoelasticity analysis and control synthesis in broad two-dimensional flight parameter space. Genetic algorithms are used to automatically determine physical states for reduction and to generate reduced-order models at grid points within parameter space while minimizing the trial-and-error process. In addition, balanced truncation for unstable systems is used in conjunction with the congruence transformation technique to achieve locally optimal realization and weak fulfillment of state consistency across the entire parameter space. Therefore, aeroservoelasticity reduced-order models at any flight condition can be obtained simply through model interpolation. The methodology is applied to the pitch-plant model of the X-56A Multi-Use Technology Testbed currently being tested at NASA Armstrong Flight Research Center for flutter suppression and gust load alleviation. The present studies indicate that the reduced-order model with more than 12× reduction in the number of states relative to the original model is able to accurately predict system response among all input-output channels. The genetic-algorithm-guided approach exceeds manual and empirical state selection in terms of efficiency and accuracy. The interpolated aeroservoelasticity reduced order models exhibit smooth pole transition and continuously varying gains along a set of prescribed flight conditions, which verifies consistent state representation obtained by congruence transformation. The present model order reduction framework can be used by control engineers for robust aeroservoelasticity controller synthesis and novel vehicle design.

An automated mapping satellite system ( Mapsat).

USGS Publications Warehouse

Colvocoresses, A.P.

1982-01-01

The favorable environment of space permits a satellite to orbit the Earth with very high stability as long as no local perturbing forces are involved. Solid-state linear-array sensors have no moving parts and create no perturbing force on the satellite. Digital data from highly stabilized stereo linear arrays are amenable to simplified processing to produce both planimetric imagery and elevation data. A satellite imaging system, called Mapsat, including this concept has been proposed to produce data from which automated mapping in near real time can be accomplished. Image maps as large as 1:50 000 scale with contours as close as a 20-m interval may be produced from Mapsat data. -from Author

Analysis technique for controlling system wavefront error with active/adaptive optics

NASA Astrophysics Data System (ADS)

Genberg, Victor L.; Michels, Gregory J.

2017-08-01

The ultimate goal of an active mirror system is to control system level wavefront error (WFE). In the past, the use of this technique was limited by the difficulty of obtaining a linear optics model. In this paper, an automated method for controlling system level WFE using a linear optics model is presented. An error estimate is included in the analysis output for both surface error disturbance fitting and actuator influence function fitting. To control adaptive optics, the technique has been extended to write system WFE in state space matrix form. The technique is demonstrated by example with SigFit, a commercially available tool integrating mechanical analysis with optical analysis.

B-737 Linear Autoland Simulink Model

NASA Technical Reports Server (NTRS)

Belcastro, Celeste (Technical Monitor); Hogge, Edward F.

2004-01-01

The Linear Autoland Simulink model was created to be a modular test environment for testing of control system components in commercial aircraft. The input variables, physical laws, and referenced frames used are summarized. The state space theory underlying the model is surveyed and the location of the control actuators described. The equations used to realize the Dryden gust model to simulate winds and gusts are derived. A description of the pseudo-random number generation method used in the wind gust model is included. The longitudinal autopilot, lateral autopilot, automatic throttle autopilot, engine model and automatic trim devices are considered as subsystems. The experience in converting the Airlabs FORTRAN aircraft control system simulation to a graphical simulation tool (Matlab/Simulink) is described.

Linear, multivariable robust control with a mu perspective

NASA Technical Reports Server (NTRS)

Packard, Andy; Doyle, John; Balas, Gary

1993-01-01

The structured singular value is a linear algebra tool developed to study a particular class of matrix perturbation problems arising in robust feedback control of multivariable systems. These perturbations are called linear fractional, and are a natural way to model many types of uncertainty in linear systems, including state-space parameter uncertainty, multiplicative and additive unmodeled dynamics uncertainty, and coprime factor and gap metric uncertainty. The structured singular value theory provides a natural extension of classical SISO robustness measures and concepts to MIMO systems. The structured singular value analysis, coupled with approximate synthesis methods, make it possible to study the tradeoff between performance and uncertainty that occurs in all feedback systems. In MIMO systems, the complexity of the spatial interactions in the loop gains make it difficult to heuristically quantify the tradeoffs that must occur. This paper examines the role played by the structured singular value (and its computable bounds) in answering these questions, as well as its role in the general robust, multivariable control analysis and design problem.

A 4-cylinder Stirling engine computer program with dynamic energy equations

NASA Technical Reports Server (NTRS)

Daniele, C. J.; Lorenzo, C. F.

1983-01-01

A computer program for simulating the steady state and transient performance of a four cylinder Stirling engine is presented. The thermodynamic model includes both continuity and energy equations and linear momentum terms (flow resistance). Each working space between the pistons is broken into seven control volumes. Drive dynamics and vehicle load effects are included. The model contains 70 state variables. Also included in the model are piston rod seal leakage effects. The computer program includes a model of a hydrogen supply system, from which hydrogen may be added to the system to accelerate the engine. Flow charts are provided.

Tensor network states in time-bin quantum optics

NASA Astrophysics Data System (ADS)

Lubasch, Michael; Valido, Antonio A.; Renema, Jelmer J.; Kolthammer, W. Steven; Jaksch, Dieter; Kim, M. S.; Walmsley, Ian; García-Patrón, Raúl

2018-06-01

The current shift in the quantum optics community towards experiments with many modes and photons necessitates new classical simulation techniques that efficiently encode many-body quantum correlations and go beyond the usual phase-space formulation. To address this pressing demand we formulate linear quantum optics in the language of tensor network states. We extensively analyze the quantum and classical correlations of time-bin interference in a single fiber loop. We then generalize our results to more complex time-bin quantum setups and identify different classes of architectures for high-complexity and low-overhead boson sampling experiments.

Volume of the steady-state space of financial flows in a monetary stock-flow-consistent model

NASA Astrophysics Data System (ADS)

Hazan, Aurélien

2017-05-01

We show that a steady-state stock-flow consistent macro-economic model can be represented as a Constraint Satisfaction Problem (CSP). The set of solutions is a polytope, which volume depends on the constraints applied and reveals the potential fragility of the economic circuit, with no need to study the dynamics. Several methods to compute the volume are compared, inspired by operations research methods and the analysis of metabolic networks, both exact and approximate. We also introduce a random transaction matrix, and study the particular case of linear flows with respect to money stocks.

Non-linear forecasting in high-frequency financial time series

NASA Astrophysics Data System (ADS)

Strozzi, F.; Zaldívar, J. M.

2005-08-01

A new methodology based on state space reconstruction techniques has been developed for trading in financial markets. The methodology has been tested using 18 high-frequency foreign exchange time series. The results are in apparent contradiction with the efficient market hypothesis which states that no profitable information about future movements can be obtained by studying the past prices series. In our (off-line) analysis positive gain may be obtained in all those series. The trading methodology is quite general and may be adapted to other financial time series. Finally, the steps for its on-line application are discussed.

Enlarged perivascular spaces and cognitive impairment after stroke and transient ischemic attack.

PubMed

Arba, Francesco; Quinn, Terence J; Hankey, Graeme J; Lees, Kennedy R; Wardlaw, Joanna M; Ali, Myzoon; Inzitari, Domenico

2018-01-01

Background Previous studies suggested that enlarged perivascular spaces are neuroimaging markers of cerebral small vessel disease. However, it is not clear whether enlarged perivascular spaces are associated with cognitive impairment. We aimed to determine the cross-sectional relationship between enlarged perivascular spaces and small vessel disease, and to investigate the relationship between enlarged perivascular spaces and subsequent cognitive impairment in patients with recent cerebral ischemic event. Methods Anonymized data were accessed from the virtual international stroke trial archive. We rated number of lacunes, white matter hyperintensities, brain atrophy, and enlarged perivascular spaces with validated scales on magnetic resonance brain images after the index stroke. We defined cognitive impairment as a mini mental state examination score of ≤26, recorded at one year post stroke. We examined the associations between enlarged perivascular spaces and clinical and imaging markers of small vessel disease at presentation and clinical evidence of cognitive impairment at one year using linear and logistic regression models. Results We analyzed data on 430 patients with mean (±SD) age 64.7 (±12.7) years, 276 (64%) males. In linear regression analysis, age (β = 0.24; p < 0.001), hypertension (β = 0.09; p = 0.025), and deep white matter hyperintensities (β = 0.31; p < 0.001) were associated with enlarged perivascular spaces. In logistic regression analysis, basal ganglia enlarged perivascular spaces were independently associated with cognitive impairment at one year after adjusting for clinical confounders (OR = 1.72, 95% CI = 1.22-2.42) and for clinical and imaging confounders (OR = 1.54; 95% CI = 1.03-2.31). Conclusions Our data show that in patients with ischemic cerebral events, enlarged perivascular spaces are cross-sectionally associated with age, hypertension, and white matter hyperintensities and suggest that enlarged perivascular spaces in the basal ganglia are associated with cognitive impairment after one year.

In situ synchrotron X-ray diffraction study of hydrides in Zircaloy-4 during thermomechanical cycling

DOE PAGES

Cinbiz, Mahmut N.; Koss, Donald A.; Motta, Arthur T.; ...

2017-02-20

The d-spacing evolution of both in-plane and out-of-plane hydrides has been studied using in situ synchrotron radiation X-ray diffraction during thermo-mechanical cycling of cold-worked stress-relieved Zircaloy-4. The structure of the hydride precipitates is such that the δ{111} d-spacing of the planes aligned with the hydride platelet face is greater than the d-spacing of the 111 planes aligned with the platelet edges. Upon heating from room temperature, the δ{111} planes aligned with hydride plate edges exhibit bi-linear thermally-induced expansion. In contrast, the d-spacing of the (111) plane aligned with the hydride plate face initially contracts upon heating. Furthermore, these experimental resultsmore » can be understood in terms of a reversal of stress state associated with precipitating or dissolving hydride platelets within the α-zirconium matrix.« less

Two elementary proofs of the Wigner theorem on symmetry in quantum mechanics

NASA Astrophysics Data System (ADS)

Simon, R.; Mukunda, N.; Chaturvedi, S.; Srinivasan, V.

2008-11-01

In quantum theory, symmetry has to be defined necessarily in terms of the family of unit rays, the state space. The theorem of Wigner asserts that a symmetry so defined at the level of rays can always be lifted into a linear unitary or an antilinear antiunitary operator acting on the underlying Hilbert space. We present two proofs of this theorem which are both elementary and economical. Central to our proofs is the recognition that a given Wigner symmetry can, by post-multiplication by a unitary symmetry, be taken into either the identity or complex conjugation. Our analysis often focuses on the behaviour of certain two-dimensional subspaces of the Hilbert space under the action of a given Wigner symmetry, but the relevance of this behaviour to the larger picture of the whole Hilbert space is made transparent at every stage.

Very highly excited vibrational states of LiCN using a discrete variable representation

NASA Astrophysics Data System (ADS)

Henderson, James R.; Tennyson, Jonathan

Calculations are presented for the lowest 900 vibrational (J = 0) states of the LiCN floppy system for a two dimensional potential energy surface (rCN frozen). Most of these states lie well above the barrier separating the two linear isomers of the molecule and the point where the classical dynamics of the system becomes chaotic. Analysis of the wavefunctions of individual states in the high energy region shows that while most have an irregular nodal structure, a significant number of states appear regular - corresponding to solutions of standard, 'mode localized' hamiltonians. Motions corresponding in zero-order to Li-CN and Li-NC normal modes as well as free rotor states are identified. The distribution of level spacings is also studied and yields results in good agreement with those obtained by analysing nodal structures.

A bulk localized state and new holographic renormalization group flow in 3D spin-3 gravity

NASA Astrophysics Data System (ADS)

Nakayama, Ryuichi; Suzuki, Tomotaka

2018-04-01

We construct a localized state of a scalar field in 3D spin-3 gravity. 3D spin-3 gravity is thought to be holographically dual to W3-extended CFT on a boundary at infinity. It is known that while W3 algebra is a nonlinear algebra, in the limit of large central charge c a linear finite-dimensional subalgebra generated by Wn (n = 0,±1,±2) and Ln (n = 0,±1) is singled out. The localized state is constructed in terms of these generators. To write down an equation of motion for a scalar field which is satisfied by this localized state, it is necessary to introduce new variables for an internal space α±, β±, γ, in addition to ordinary coordinates x± and y. The higher-dimensional space, which combines the bulk space-time with the “internal space,” which is an analog of superspace in supersymmetric theory, is introduced. The “physical bulk space-time” is a 3D hypersurface with constant α±, β± and γ embedded in this space. We will work in Poincaré coordinates of AdS space and consider W-quasi-primary operators Φh(x+) with a conformal weight h in the boundary and study two and three point functions of W-quasi-primary operators transformed as eix+L‑1heβ+W‑1hΦh(0)e‑β+W‑1he‑ix+L‑1h. Here, Lnh and Wnh are sl(3,R) generators in the hyperbolic basis for Poincaré coordinates. It is shown that in the β+ →∞ limit, the conformal weight changes to a new value h‧ = h/2. This may be regarded as a Renormalization Group (RG) flow. It is argued that this RG flow will be triggered by terms ΔS ∝ β+W ‑1h + β‑W¯ ‑1h added to the action.

Ultrametric properties of the attractor spaces for random iterated linear function systems

NASA Astrophysics Data System (ADS)

Buchovets, A. G.; Moskalev, P. V.

2018-03-01

We investigate attractors of random iterated linear function systems as independent spaces embedded in the ordinary Euclidean space. The introduction on the set of attractor points of a metric that satisfies the strengthened triangle inequality makes this space ultrametric. Then inherent in ultrametric spaces the properties of disconnectedness and hierarchical self-similarity make it possible to define an attractor as a fractal. We note that a rigorous proof of these properties in the case of an ordinary Euclidean space is very difficult.

Exploring Ackermann and LQR stability control of stochastic state-space model of hexacopter equipped with robotic arm

NASA Astrophysics Data System (ADS)

Ibrahim, I. N.; Akkad, M. A. Al; Abramov, I. V.

2018-05-01

This paper discusses the control of Unmanned Aerial Vehicles (UAVs) for active interaction and manipulation of objects. The manipulator motion with an unknown payload was analysed concerning force and moment disturbances, which influence the mass distribution, and the centre of gravity (CG). Therefore, a general dynamics mathematical model of a hexacopter was formulated where a stochastic state-space model was extracted in order to build anti-disturbance controllers. Based on the compound pendulum method, the disturbances model that simulates the robotic arm with a payload was inserted into the stochastic model. This study investigates two types of controllers in order to study the stability of a hexacopter. A controller based on Ackermann’s method and the other - on the linear quadratic regulator (LQR) approach - were presented. The latter constitutes a challenge for UAV control performance especially with the presence of uncertainties and disturbances.

Analysis of helicopter flight dynamics through modeling and simulation of primary flight control actuation system

NASA Astrophysics Data System (ADS)

Nelson, Hunter Barton

A simplified second-order transfer function actuator model used in most flight dynamics applications cannot easily capture the effects of different actuator parameters. The present work integrates a nonlinear actuator model into a nonlinear state space rotorcraft model to determine the effect of actuator parameters on key flight dynamics. The completed actuator model was integrated with a swashplate kinematics where step responses were generated over a range of key hydraulic parameters. The actuator-swashplate system was then introduced into a nonlinear state space rotorcraft simulation where flight dynamics quantities such as bandwidth and phase delay analyzed. Frequency sweeps were simulated for unique actuator configurations using the coupled nonlinear actuator-rotorcraft system. The software package CIFER was used for system identification and compared directly to the linearized models. As the actuator became rate saturated, the effects on bandwidth and phase delay were apparent on the predicted handling qualities specifications.

Flexible missile autopilot design studies with PC-MATLAB/386

NASA Technical Reports Server (NTRS)

Ruth, Michael J.

1989-01-01

Development of a responsive, high-bandwidth missile autopilot for airframes which have structural modes of unusually low frequency presents a challenging design task. Such systems are viable candidates for modern, state-space control design methods. The PC-MATLAB interactive software package provides an environment well-suited to the development of candidate linear control laws for flexible missile autopilots. The strengths of MATLAB include: (1) exceptionally high speed (MATLAB's version for 80386-based PC's offers benchmarks approaching minicomputer and mainframe performance); (2) ability to handle large design models of several hundred degrees of freedom, if necessary; and (3) broad extensibility through user-defined functions. To characterize MATLAB capabilities, a simplified design example is presented. This involves interactive definition of an observer-based state-space compensator for a flexible missile autopilot design task. MATLAB capabilities and limitations, in the context of this design task, are then summarized.

The development rainfall forecasting using kalman filter

NASA Astrophysics Data System (ADS)

Zulfi, Mohammad; Hasan, Moh.; Dwidja Purnomo, Kosala

2018-04-01

Rainfall forecasting is very interesting for agricultural planing. Rainfall information is useful to make decisions about the plan planting certain commodities. In this studies, the rainfall forecasting by ARIMA and Kalman Filter method. Kalman Filter method is used to declare a time series model of which is shown in the form of linear state space to determine the future forecast. This method used a recursive solution to minimize error. The rainfall data in this research clustered by K-means clustering. Implementation of Kalman Filter method is for modelling and forecasting rainfall in each cluster. We used ARIMA (p,d,q) to construct a state space for KalmanFilter model. So, we have four group of the data and one model in each group. In conclusions, Kalman Filter method is better than ARIMA model for rainfall forecasting in each group. It can be showed from error of Kalman Filter method that smaller than error of ARIMA model.

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

Zhao, Luning; Neuscamman, Eric

We present a modification to variational Monte Carlo’s linear method optimization scheme that addresses a critical memory bottleneck while maintaining compatibility with both the traditional ground state variational principle and our recently-introduced variational principle for excited states. For wave function ansatzes with tens of thousands of variables, our modification reduces the required memory per parallel process from tens of gigabytes to hundreds of megabytes, making the methodology a much better fit for modern supercomputer architectures in which data communication and per-process memory consumption are primary concerns. We verify the efficacy of the new optimization scheme in small molecule tests involvingmore » both the Hilbert space Jastrow antisymmetric geminal power ansatz and real space multi-Slater Jastrow expansions. Satisfied with its performance, we have added the optimizer to the QMCPACK software package, with which we demonstrate on a hydrogen ring a prototype approach for making systematically convergent, non-perturbative predictions of Mott-insulators’ optical band gaps.« less

Assessment of current state of the art in modeling techniques and analysis methods for large space structures

NASA Technical Reports Server (NTRS)

Noor, A. K.

1983-01-01

Advances in continuum modeling, progress in reduction methods, and analysis and modeling needs for large space structures are covered with specific attention given to repetitive lattice trusses. As far as continuum modeling is concerned, an effective and verified analysis capability exists for linear thermoelastic stress, birfurcation buckling, and free vibration problems of repetitive lattices. However, application of continuum modeling to nonlinear analysis needs more development. Reduction methods are very effective for bifurcation buckling and static (steady-state) nonlinear analysis. However, more work is needed to realize their full potential for nonlinear dynamic and time-dependent problems. As far as analysis and modeling needs are concerned, three areas are identified: loads determination, modeling and nonclassical behavior characteristics, and computational algorithms. The impact of new advances in computer hardware, software, integrated analysis, CAD/CAM stems, and materials technology is also discussed.

Survivability of Deterministic Dynamical Systems

PubMed Central

Hellmann, Frank; Schultz, Paul; Grabow, Carsten; Heitzig, Jobst; Kurths, Jürgen

2016-01-01

The notion of a part of phase space containing desired (or allowed) states of a dynamical system is important in a wide range of complex systems research. It has been called the safe operating space, the viability kernel or the sunny region. In this paper we define the notion of survivability: Given a random initial condition, what is the likelihood that the transient behaviour of a deterministic system does not leave a region of desirable states. We demonstrate the utility of this novel stability measure by considering models from climate science, neuronal networks and power grids. We also show that a semi-analytic lower bound for the survivability of linear systems allows a numerically very efficient survivability analysis in realistic models of power grids. Our numerical and semi-analytic work underlines that the type of stability measured by survivability is not captured by common asymptotic stability measures. PMID:27405955

Dealing with Uncertainties in Initial Orbit Determination

NASA Technical Reports Server (NTRS)

Armellin, Roberto; Di Lizia, Pierluigi; Zanetti, Renato

2015-01-01

A method to deal with uncertainties in initial orbit determination (IOD) is presented. This is based on the use of Taylor differential algebra (DA) to nonlinearly map the observation uncertainties from the observation space to the state space. When a minimum set of observations is available DA is used to expand the solution of the IOD problem in Taylor series with respect to measurement errors. When more observations are available high order inversion tools are exploited to obtain full state pseudo-observations at a common epoch. The mean and covariance of these pseudo-observations are nonlinearly computed by evaluating the expectation of high order Taylor polynomials. Finally, a linear scheme is employed to update the current knowledge of the orbit. Angles-only observations are considered and simplified Keplerian dynamics adopted to ease the explanation. Three test cases of orbit determination of artificial satellites in different orbital regimes are presented to discuss the feature and performances of the proposed methodology.

Composite fermion basis for two-component Bose gases

NASA Astrophysics Data System (ADS)

Meyer, Marius; Liabotro, Ola

The composite fermion (CF) construction is known to produce wave functions that are not necessarily orthogonal, or even linearly independent, after projection. While usually not a practical issue in the quantum Hall regime, we have previously shown that it presents a technical challenge for rotating Bose gases with low angular momentum. These are systems where the CF approach yield surprisingly good approximations to the exact eigenstates of weak short-range interactions, and so solving the problem of linearly dependent wave functions is of interest. It can also be useful for studying CF excitations for fermions. Here we present several ways of constructing a basis for the space of ``simple CF states'' for two-component rotating Bose gases in the lowest Landau level, and prove that they all give a basis. Using the basis, we study the structure of the lowest-lying state using so-called restricted wave functions. We also examine the scaling of the overlap between the exact and CF wave functions at the maximal possible angular momentum for simple states. This work was financially supported by the Research Council of Norway.

Distributed Time-Varying Formation Robust Tracking for General Linear Multiagent Systems With Parameter Uncertainties and External Disturbances.

PubMed

Hua, Yongzhao; Dong, Xiwang; Li, Qingdong; Ren, Zhang

2017-05-18

This paper investigates the time-varying formation robust tracking problems for high-order linear multiagent systems with a leader of unknown control input in the presence of heterogeneous parameter uncertainties and external disturbances. The followers need to accomplish an expected time-varying formation in the state space and track the state trajectory produced by the leader simultaneously. First, a time-varying formation robust tracking protocol with a totally distributed form is proposed utilizing the neighborhood state information. With the adaptive updating mechanism, neither any global knowledge about the communication topology nor the upper bounds of the parameter uncertainties, external disturbances and leader's unknown input are required in the proposed protocol. Then, in order to determine the control parameters, an algorithm with four steps is presented, where feasible conditions for the followers to accomplish the expected time-varying formation tracking are provided. Furthermore, based on the Lyapunov-like analysis theory, it is proved that the formation tracking error can converge to zero asymptotically. Finally, the effectiveness of the theoretical results is verified by simulation examples.

Constraint-Based Abstract Semantics for Temporal Logic: A Direct Approach to Design and Implementation

NASA Astrophysics Data System (ADS)

Banda, Gourinath; Gallagher, John P.

interpretation provides a practical approach to verifying properties of infinite-state systems. We apply the framework of abstract interpretation to derive an abstract semantic function for the modal μ-calculus, which is the basis for abstract model checking. The abstract semantic function is constructed directly from the standard concrete semantics together with a Galois connection between the concrete state-space and an abstract domain. There is no need for mixed or modal transition systems to abstract arbitrary temporal properties, as in previous work in the area of abstract model checking. Using the modal μ-calculus to implement CTL, the abstract semantics gives an over-approximation of the set of states in which an arbitrary CTL formula holds. Then we show that this leads directly to an effective implementation of an abstract model checking algorithm for CTL using abstract domains based on linear constraints. The implementation of the abstract semantic function makes use of an SMT solver. We describe an implemented system for proving properties of linear hybrid automata and give some experimental results.

Dynamical generation of noiseless quantum subsystems

PubMed

Viola; Knill; Lloyd

2000-10-16

We combine dynamical decoupling and universal control methods for open quantum systems with coding procedures. By exploiting a general algebraic approach, we show how appropriate encodings of quantum states result in obtaining universal control over dynamically generated noise-protected subsystems with limited control resources. In particular, we provide a constructive scheme based on two-body Hamiltonians for performing universal quantum computation over large noiseless spaces which can be engineered in the presence of arbitrary linear quantum noise.

Verification of Faulty Message Passing Systems with Continuous State Space in PVS

NASA Technical Reports Server (NTRS)

Pilotto, Concetta; White, Jerome

2010-01-01

We present a library of Prototype Verification System (PVS) meta-theories that verifies a class of distributed systems in which agent commu nication is through message-passing. The theoretic work, outlined in, consists of iterative schemes for solving systems of linear equations , such as message-passing extensions of the Gauss and Gauss-Seidel me thods. We briefly review that work and discuss the challenges in formally verifying it.

Anomaly General Circulation Models.

NASA Astrophysics Data System (ADS)

Navarra, Antonio

The feasibility of the anomaly model is assessed using barotropic and baroclinic models. In the barotropic case, both a stationary and a time-dependent model has been formulated and constructed, whereas only the stationary, linear case is considered in the baroclinic case. Results from the barotropic model indicate that a relation between the stationary solution and the time-averaged non-linear solution exists. The stationary linear baroclinic solution can therefore be considered with some confidence. The linear baroclinic anomaly model poses a formidable mathematical problem because it is necessary to solve a gigantic linear system to obtain the solution. A new method to find solution of large linear system, based on a projection on the Krylov subspace is shown to be successful when applied to the linearized baroclinic anomaly model. The scheme consists of projecting the original linear system on the Krylov subspace, thereby reducing the dimensionality of the matrix to be inverted to obtain the solution. With an appropriate setting of the damping parameters, the iterative Krylov method reaches a solution even using a Krylov subspace ten times smaller than the original space of the problem. This generality allows the treatment of the important problem of linear waves in the atmosphere. A larger class (nonzonally symmetric) of basic states can now be treated for the baroclinic primitive equations. These problem leads to large unsymmetrical linear systems of order 10000 and more which can now be successfully tackled by the Krylov method. The (R7) linear anomaly model is used to investigate extensively the linear response to equatorial and mid-latitude prescribed heating. The results indicate that the solution is deeply affected by the presence of the stationary waves in the basic state. The instability of the asymmetric flows, first pointed out by Simmons et al. (1983), is active also in the baroclinic case. However, the presence of baroclinic processes modifies the dominant response. The most sensitive areas are identified; they correspond to north Japan, the Pole and Greenland regions. A limited set of higher resolution (R15) experiments indicate that this situation is still present and enhanced at higher resolution. The linear anomaly model is also applied to a realistic case. (Abstract shortened with permission of author.).

A transformed path integral approach for solution of the Fokker-Planck equation

NASA Astrophysics Data System (ADS)

Subramaniam, Gnana M.; Vedula, Prakash

2017-10-01

A novel path integral (PI) based method for solution of the Fokker-Planck equation is presented. The proposed method, termed the transformed path integral (TPI) method, utilizes a new formulation for the underlying short-time propagator to perform the evolution of the probability density function (PDF) in a transformed computational domain where a more accurate representation of the PDF can be ensured. The new formulation, based on a dynamic transformation of the original state space with the statistics of the PDF as parameters, preserves the non-negativity of the PDF and incorporates short-time properties of the underlying stochastic process. New update equations for the state PDF in a transformed space and the parameters of the transformation (including mean and covariance) that better accommodate nonlinearities in drift and non-Gaussian behavior in distributions are proposed (based on properties of the SDE). Owing to the choice of transformation considered, the proposed method maps a fixed grid in transformed space to a dynamically adaptive grid in the original state space. The TPI method, in contrast to conventional methods such as Monte Carlo simulations and fixed grid approaches, is able to better represent the distributions (especially the tail information) and better address challenges in processes with large diffusion, large drift and large concentration of PDF. Additionally, in the proposed TPI method, error bounds on the probability in the computational domain can be obtained using the Chebyshev's inequality. The benefits of the TPI method over conventional methods are illustrated through simulations of linear and nonlinear drift processes in one-dimensional and multidimensional state spaces. The effects of spatial and temporal grid resolutions as well as that of the diffusion coefficient on the error in the PDF are also characterized.

Linear signatures in nonlinear gyrokinetics: interpreting turbulence with pseudospectra

DOE PAGES

Hatch, D. R.; Jenko, F.; Navarro, A. Banon; ...

2016-07-26

A notable feature of plasma turbulence is its propensity to retain features of the underlying linear eigenmodes in a strongly turbulent state—a property that can be exploited to predict various aspects of the turbulence using only linear information. In this context, this work examines gradient-driven gyrokinetic plasma turbulence through three lenses—linear eigenvalue spectra, pseudospectra, and singular value decomposition (SVD). We study a reduced gyrokinetic model whose linear eigenvalue spectra include ion temperature gradient driven modes, stable drift waves, and kinetic modes representing Landau damping. The goal is to characterize in which ways, if any, these familiar ingredients are manifest inmore » the nonlinear turbulent state. This pursuit is aided by the use of pseudospectra, which provide a more nuanced view of the linear operator by characterizing its response to perturbations. We introduce a new technique whereby the nonlinearly evolved phase space structures extracted with SVD are linked to the linear operator using concepts motivated by pseudospectra. Using this technique, we identify nonlinear structures that have connections to not only the most unstable eigenmode but also subdominant modes that are nonlinearly excited. The general picture that emerges is a system in which signatures of the linear physics persist in the turbulence, albeit in ways that cannot be fully explained by the linear eigenvalue approach; a non-modal treatment is necessary to understand key features of the turbulence.« less

Robust H(∞) positional control of 2-DOF robotic arm driven by electro-hydraulic servo system.

PubMed

Guo, Qing; Yu, Tian; Jiang, Dan

2015-11-01

In this paper an H∞ positional feedback controller is developed to improve the robust performance under structural and parametric uncertainty disturbance in electro-hydraulic servo system (EHSS). The robust control model is described as the linear state-space equation by upper linear fractional transformation. According to the solution of H∞ sub-optimal control problem, the robust controller is designed and simplified to lower order linear model which is easily realized in EHSS. The simulation and experimental results can validate the robustness of this proposed method. The comparison result with PI control shows that the robust controller is suitable for this EHSS under the critical condition where the desired system bandwidth is higher and the external load of the hydraulic actuator is closed to its limited capability. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

Integrated Control Modeling for Propulsion Systems Using NPSS

NASA Technical Reports Server (NTRS)

Parker, Khary I.; Felder, James L.; Lavelle, Thomas M.; Withrow, Colleen A.; Yu, Albert Y.; Lehmann, William V. A.

2004-01-01

The Numerical Propulsion System Simulation (NPSS), an advanced engineering simulation environment used to design and analyze aircraft engines, has been enhanced by integrating control development tools into it. One of these tools is a generic controller interface that allows NPSS to communicate with control development software environments such as MATLAB and EASY5. The other tool is a linear model generator (LMG) that gives NPSS the ability to generate linear, time-invariant state-space models. Integrating these tools into NPSS enables it to be used for control system development. This paper will discuss the development and integration of these tools into NPSS. In addition, it will show a comparison of transient model results of a generic, dual-spool, military-type engine model that has been implemented in NPSS and Simulink. It will also show the linear model generator s ability to approximate the dynamics of a nonlinear NPSS engine model.

Topological Weyl superconductor to diffusive thermal Hall metal crossover in the B phase of UPt3

NASA Astrophysics Data System (ADS)

Goswami, Pallab; Nevidomskyy, Andriy H.

2015-12-01

The recent phase-sensitive measurements in the superconducting B phase of UPt3 provide strong evidence for the triplet, chiral kz(kx±i ky) 2 pairing symmetries, which endow the Cooper pairs with orbital angular momentum projections Lz=±2 along the c axis. In the absence of disorder such pairing can support both line and point nodes, and both types of nodal quasiparticles exhibit nontrivial topology in the momentum space. The point nodes, located at the intersections of the closed Fermi surfaces with the c axis, act as the double monopoles and the antimonopoles of the Berry curvature, and generalize the notion of Weyl quasiparticles. Consequently, the B phase should support an anomalous thermal Hall effect, the polar Kerr effect, in addition to the protected Fermi arcs on the (1 ,0 ,0 ) and the (0 ,1 ,0 ) surfaces. The line node at the Fermi surface equator acts as a vortex loop in the momentum space and gives rise to the zero-energy, dispersionless Andreev bound states on the (0 ,0 ,1 ) surface. At the transition from the B phase to the A phase, the time-reversal symmetry is restored, and only the line node survives inside the A phase. As both line and double-Weyl point nodes possess linearly vanishing density of states, we show that weak disorder acts as a marginally relevant perturbation. Consequently, an infinitesimal amount of disorder destroys the ballistic quasiparticle pole, while giving rise to a diffusive phase with a finite density of states at the zero energy. The resulting diffusive phase exhibits T -linear specific heat, and an anomalous thermal Hall effect. We predict that the low-temperature thermodynamic and transport properties display a crossover between a ballistic thermal Hall semimetal and a diffusive thermal Hall metal. By contrast, the diffusive phase obtained from a time-reversal-invariant pairing exhibits only the T -linear specific heat without any anomalous thermal Hall effect.

Noise and Dynamical Pattern Selection in Solidification

NASA Technical Reports Server (NTRS)

Kurtze, Douglas A.

1997-01-01

The overall goal of this project was to understand in more detail how a pattern-forming system can adjust its spacing. "Pattern-forming systems," in this context, are nonequilibrium contina whose state is determined by experimentally adjustable control parameter. Below some critical value of the control system then has available to it a range of linearly stable, spatially periodic steady states, each characterized by a spacing which can lie anywhere within some band of values. These systems like directional solidification, where the solidification front is planar when the ratio of growth velocity to thermal gradient is below its critical value, but takes on a cellular shape above critical. They also include systems without interfaces, such as Benard convection, where it is the fluid velocity field which changes from zero to something spatially periodic as the control parameter is increased through its critical value. The basic question to be addressed was that of how the system chooses one of its myriad possible spacings when the control parameter is above critical, and in particular the role of noise in the selection process. Previous work on explosive crystallization had suggested that one spacing in the range should be preferred, in the sense that weak noise should eventually drive the system to that spacing. That work had also suggested a heuristic argument for identifying the preferred spacing. The project had three main objectives: to understand in more detail how a pattern-forming system can adjust its spacing; to investigate how noise drives a system to its preferred spacing; and to extend the heuristic argument for a preferred spacing in explosive crystallization to other pattern-forming systems.

RB Particle Filter Time Synchronization Algorithm Based on the DPM Model.

PubMed

Guo, Chunsheng; Shen, Jia; Sun, Yao; Ying, Na

2015-09-03

Time synchronization is essential for node localization, target tracking, data fusion, and various other Wireless Sensor Network (WSN) applications. To improve the estimation accuracy of continuous clock offset and skew of mobile nodes in WSNs, we propose a novel time synchronization algorithm, the Rao-Blackwellised (RB) particle filter time synchronization algorithm based on the Dirichlet process mixture (DPM) model. In a state-space equation with a linear substructure, state variables are divided into linear and non-linear variables by the RB particle filter algorithm. These two variables can be estimated using Kalman filter and particle filter, respectively, which improves the computational efficiency more so than if only the particle filter was used. In addition, the DPM model is used to describe the distribution of non-deterministic delays and to automatically adjust the number of Gaussian mixture model components based on the observational data. This improves the estimation accuracy of clock offset and skew, which allows achieving the time synchronization. The time synchronization performance of this algorithm is also validated by computer simulations and experimental measurements. The results show that the proposed algorithm has a higher time synchronization precision than traditional time synchronization algorithms.

Quantum algorithms for Gibbs sampling and hitting-time estimation

DOE PAGES

Chowdhury, Anirban Narayan; Somma, Rolando D.

2017-02-01

In this paper, we present quantum algorithms for solving two problems regarding stochastic processes. The first algorithm prepares the thermal Gibbs state of a quantum system and runs in time almost linear in √Nβ/Ζ and polynomial in log(1/ϵ), where N is the Hilbert space dimension, β is the inverse temperature, Ζ is the partition function, and ϵ is the desired precision of the output state. Our quantum algorithm exponentially improves the dependence on 1/ϵ and quadratically improves the dependence on β of known quantum algorithms for this problem. The second algorithm estimates the hitting time of a Markov chain. Formore » a sparse stochastic matrix Ρ, it runs in time almost linear in 1/(ϵΔ 3/2), where ϵ is the absolute precision in the estimation and Δ is a parameter determined by Ρ, and whose inverse is an upper bound of the hitting time. Our quantum algorithm quadratically improves the dependence on 1/ϵ and 1/Δ of the analog classical algorithm for hitting-time estimation. Finally, both algorithms use tools recently developed in the context of Hamiltonian simulation, spectral gap amplification, and solving linear systems of equations.« less

Numerical modeling of space-time wave extremes using WAVEWATCH III

NASA Astrophysics Data System (ADS)

Barbariol, Francesco; Alves, Jose-Henrique G. M.; Benetazzo, Alvise; Bergamasco, Filippo; Bertotti, Luciana; Carniel, Sandro; Cavaleri, Luigi; Y. Chao, Yung; Chawla, Arun; Ricchi, Antonio; Sclavo, Mauro; Tolman, Hendrik

2017-04-01

A novel implementation of parameters estimating the space-time wave extremes within the spectral wave model WAVEWATCH III (WW3) is presented. The new output parameters, available in WW3 version 5.16, rely on the theoretical model of Fedele (J Phys Oceanogr 42(9):1601-1615, 2012) extended by Benetazzo et al. (J Phys Oceanogr 45(9):2261-2275, 2015) to estimate the maximum second-order nonlinear crest height over a given space-time region. In order to assess the wave height associated to the maximum crest height and the maximum wave height (generally different in a broad-band stormy sea state), the linear quasi-determinism theory of Boccotti (2000) is considered. The new WW3 implementation is tested by simulating sea states and space-time extremes over the Mediterranean Sea (forced by the wind fields produced by the COSMO-ME atmospheric model). Model simulations are compared to space-time wave maxima observed on March 10th, 2014, in the northern Adriatic Sea (Italy), by a stereo camera system installed on-board the "Acqua Alta" oceanographic tower. Results show that modeled space-time extremes are in general agreement with observations. Differences are mostly ascribed to the accuracy of the wind forcing and, to a lesser extent, to the approximations introduced in the space-time extremes parameterizations. Model estimates are expected to be even more accurate over areas larger than the mean wavelength (for instance, the model grid size).

Forecasting Geomagnetic Activity Using Kalman Filters

NASA Astrophysics Data System (ADS)

Veeramani, T.; Sharma, A.

2006-05-01

The coupling of energy from the solar wind to the magnetosphere leads to the geomagnetic activity in the form of storms and substorms and are characterized by indices such as AL, Dst and Kp. The geomagnetic activity has been predicted near-real time using local linear filter models of the system dynamics wherein the time series of the input solar wind and the output magnetospheric response were used to reconstruct the phase space of the system by a time-delay embedding technique. Recently, the radiation belt dynamics have been studied using a adaptive linear state space model [Rigler et al. 2004]. This was achieved by assuming a linear autoregressive equation for the underlying process and an adaptive identification of the model parameters using a Kalman filter approach. We use such a model for predicting the geomagnetic activity. In the case of substorms, the Bargatze et al [1985] data set yields persistence like behaviour when a time resolution of 2.5 minutes was used to test the model for the prediction of the AL index. Unlike the local linear filters, which are driven by the solar wind input without feedback from the observations, the Kalman filter makes use of the observations as and when available to optimally update the model parameters. The update procedure requires the prediction intervals to be long enough so that the forecasts can be used in practice. The time resolution of the data suitable for such forecasting is studied by taking averages over different durations.

Real-time prediction of respiratory motion based on a local dynamic model in an augmented space

NASA Astrophysics Data System (ADS)

Hong, S.-M.; Jung, B.-H.; Ruan, D.

2011-03-01

Motion-adaptive radiotherapy aims to deliver ablative radiation dose to the tumor target with minimal normal tissue exposure, by accounting for real-time target movement. In practice, prediction is usually necessary to compensate for system latency induced by measurement, communication and control. This work focuses on predicting respiratory motion, which is most dominant for thoracic and abdominal tumors. We develop and investigate the use of a local dynamic model in an augmented space, motivated by the observation that respiratory movement exhibits a locally circular pattern in a plane augmented with a delayed axis. By including the angular velocity as part of the system state, the proposed dynamic model effectively captures the natural evolution of respiratory motion. The first-order extended Kalman filter is used to propagate and update the state estimate. The target location is predicted by evaluating the local dynamic model equations at the required prediction length. This method is complementary to existing work in that (1) the local circular motion model characterizes 'turning', overcoming the limitation of linear motion models; (2) it uses a natural state representation including the local angular velocity and updates the state estimate systematically, offering explicit physical interpretations; (3) it relies on a parametric model and is much less data-satiate than the typical adaptive semiparametric or nonparametric method. We tested the performance of the proposed method with ten RPM traces, using the normalized root mean squared difference between the predicted value and the retrospective observation as the error metric. Its performance was compared with predictors based on the linear model, the interacting multiple linear models and the kernel density estimator for various combinations of prediction lengths and observation rates. The local dynamic model based approach provides the best performance for short to medium prediction lengths under relatively low observation rate. Sensitivity analysis indicates its robustness toward the choice of parameters. Its simplicity, robustness and low computation cost makes the proposed local dynamic model an attractive tool for real-time prediction with system latencies below 0.4 s.

Real-time prediction of respiratory motion based on a local dynamic model in an augmented space.

PubMed

Hong, S-M; Jung, B-H; Ruan, D

2011-03-21

Motion-adaptive radiotherapy aims to deliver ablative radiation dose to the tumor target with minimal normal tissue exposure, by accounting for real-time target movement. In practice, prediction is usually necessary to compensate for system latency induced by measurement, communication and control. This work focuses on predicting respiratory motion, which is most dominant for thoracic and abdominal tumors. We develop and investigate the use of a local dynamic model in an augmented space, motivated by the observation that respiratory movement exhibits a locally circular pattern in a plane augmented with a delayed axis. By including the angular velocity as part of the system state, the proposed dynamic model effectively captures the natural evolution of respiratory motion. The first-order extended Kalman filter is used to propagate and update the state estimate. The target location is predicted by evaluating the local dynamic model equations at the required prediction length. This method is complementary to existing work in that (1) the local circular motion model characterizes 'turning', overcoming the limitation of linear motion models; (2) it uses a natural state representation including the local angular velocity and updates the state estimate systematically, offering explicit physical interpretations; (3) it relies on a parametric model and is much less data-satiate than the typical adaptive semiparametric or nonparametric method. We tested the performance of the proposed method with ten RPM traces, using the normalized root mean squared difference between the predicted value and the retrospective observation as the error metric. Its performance was compared with predictors based on the linear model, the interacting multiple linear models and the kernel density estimator for various combinations of prediction lengths and observation rates. The local dynamic model based approach provides the best performance for short to medium prediction lengths under relatively low observation rate. Sensitivity analysis indicates its robustness toward the choice of parameters. Its simplicity, robustness and low computation cost makes the proposed local dynamic model an attractive tool for real-time prediction with system latencies below 0.4 s.

High-Dimensional Quantum Information Processing with Linear Optics

NASA Astrophysics Data System (ADS)

Fitzpatrick, Casey A.

Quantum information processing (QIP) is an interdisciplinary field concerned with the development of computers and information processing systems that utilize quantum mechanical properties of nature to carry out their function. QIP systems have become vastly more practical since the turn of the century. Today, QIP applications span imaging, cryptographic security, computation, and simulation (quantum systems that mimic other quantum systems). Many important strategies improve quantum versions of classical information system hardware, such as single photon detectors and quantum repeaters. Another more abstract strategy engineers high-dimensional quantum state spaces, so that each successful event carries more information than traditional two-level systems allow. Photonic states in particular bring the added advantages of weak environmental coupling and data transmission near the speed of light, allowing for simpler control and lower system design complexity. In this dissertation, numerous novel, scalable designs for practical high-dimensional linear-optical QIP systems are presented. First, a correlated photon imaging scheme using orbital angular momentum (OAM) states to detect rotational symmetries in objects using measurements, as well as building images out of those interactions is reported. Then, a statistical detection method using chains of OAM superpositions distributed according to the Fibonacci sequence is established and expanded upon. It is shown that the approach gives rise to schemes for sorting, detecting, and generating the recursively defined high-dimensional states on which some quantum cryptographic protocols depend. Finally, an ongoing study based on a generalization of the standard optical multiport for applications in quantum computation and simulation is reported upon. The architecture allows photons to reverse momentum inside the device. This in turn enables realistic implementation of controllable linear-optical scattering vertices for carrying out quantum walks on arbitrary graph structures, a powerful tool for any quantum computer. It is shown that the novel architecture provides new, efficient capabilities for the optical quantum simulation of Hamiltonians and topologically protected states. Further, these simulations use exponentially fewer resources than feedforward techniques, scale linearly to higher-dimensional systems, and use only linear optics, thus offering a concrete experimentally achievable implementation of graphical models of discrete-time quantum systems.

DUAL STATE-PARAMETER UPDATING SCHEME ON A CONCEPTUAL HYDROLOGIC MODEL USING SEQUENTIAL MONTE CARLO FILTERS

NASA Astrophysics Data System (ADS)

Noh, Seong Jin; Tachikawa, Yasuto; Shiiba, Michiharu; Kim, Sunmin

Applications of data assimilation techniques have been widely used to improve upon the predictability of hydrologic modeling. Among various data assimilation techniques, sequential Monte Carlo (SMC) filters, known as "particle filters" provide the capability to handle non-linear and non-Gaussian state-space models. This paper proposes a dual state-parameter updating scheme (DUS) based on SMC methods to estimate both state and parameter variables of a hydrologic model. We introduce a kernel smoothing method for the robust estimation of uncertain model parameters in the DUS. The applicability of the dual updating scheme is illustrated using the implementation of the storage function model on a middle-sized Japanese catchment. We also compare performance results of DUS combined with various SMC methods, such as SIR, ASIR and RPF.

Monte Carlo wave-function description of losses in a one-dimensional Bose gas and cooling to the ground state by quantum feedback

NASA Astrophysics Data System (ADS)

Schemmer, M.; Johnson, A.; Photopoulos, R.; Bouchoule, I.

2017-04-01

The effect of atom losses on a homogeneous one-dimensional Bose gas lying within the quasicondensate regime is investigated using a Monte Carlo wave-function approach. The evolution of the system is calculated, conditioned by the loss sequence, namely, the times of individual losses and the position of the removed atoms. We describe the gas within the linearized Bogoliubov approach. For each mode, we find that, for a given quantum trajectory, the state of the system converges towards a coherent state, i.e., the ground state, displaced in phase space. We show that, provided losses are recorded with a temporal and spatially resolved detector, quantum feedback can be implemented and cooling to the ground state of one or several modes can be realized.

Quantum state engineering using one-dimensional discrete-time quantum walks

NASA Astrophysics Data System (ADS)

Innocenti, Luca; Majury, Helena; Giordani, Taira; Spagnolo, Nicolò; Sciarrino, Fabio; Paternostro, Mauro; Ferraro, Alessandro

2017-12-01

Quantum state preparation in high-dimensional systems is an essential requirement for many quantum-technology applications. The engineering of an arbitrary quantum state is, however, typically strongly dependent on the experimental platform chosen for implementation, and a general framework is still missing. Here we show that coined quantum walks on a line, which represent a framework general enough to encompass a variety of different platforms, can be used for quantum state engineering of arbitrary superpositions of the walker's sites. We achieve this goal by identifying a set of conditions that fully characterize the reachable states in the space comprising walker and coin and providing a method to efficiently compute the corresponding set of coin parameters. We assess the feasibility of our proposal by identifying a linear optics experiment based on photonic orbital angular momentum technology.

Minimum complexity echo state network.

PubMed

Rodan, Ali; Tino, Peter

2011-01-01

Reservoir computing (RC) refers to a new class of state-space models with a fixed state transition structure (the reservoir) and an adaptable readout form the state space. The reservoir is supposed to be sufficiently complex so as to capture a large number of features of the input stream that can be exploited by the reservoir-to-output readout mapping. The field of RC has been growing rapidly with many successful applications. However, RC has been criticized for not being principled enough. Reservoir construction is largely driven by a series of randomized model-building stages, with both researchers and practitioners having to rely on a series of trials and errors. To initialize a systematic study of the field, we concentrate on one of the most popular classes of RC methods, namely echo state network, and ask: What is the minimal complexity of reservoir construction for obtaining competitive models and what is the memory capacity (MC) of such simplified reservoirs? On a number of widely used time series benchmarks of different origin and characteristics, as well as by conducting a theoretical analysis we show that a simple deterministically constructed cycle reservoir is comparable to the standard echo state network methodology. The (short-term) MC of linear cyclic reservoirs can be made arbitrarily close to the proved optimal value.

Adaptive attitude control and momentum management for large-angle spacecraft maneuvers

NASA Technical Reports Server (NTRS)

Parlos, Alexander G.; Sunkel, John W.

1992-01-01

The fully coupled equations of motion are systematically linearized around an equilibrium point of a gravity gradient stabilized spacecraft, controlled by momentum exchange devices. These equations are then used for attitude control system design of an early Space Station Freedom flight configuration, demonstrating the errors caused by the improper approximation of the spacecraft dynamics. A full state feedback controller, incorporating gain-scheduled adaptation of the attitude gains, is developed for use during spacecraft on-orbit assembly or operations characterized by significant mass properties variations. The feasibility of the gain adaptation is demonstrated via a Space Station Freedom assembly sequence case study. The attitude controller stability robustness and transient performance during gain adaptation appear satisfactory.

Generalized thermodynamic relations for a system experiencing heat and mass diffusion in the far-from-equilibrium realm based on steepest entropy ascent.

PubMed

Li, Guanchen; von Spakovsky, Michael R

2016-09-01

This paper presents a nonequilibrium thermodynamic model for the relaxation of a local, isolated system in nonequilibrium using the principle of steepest entropy ascent (SEA), which can be expressed as a variational principle in thermodynamic state space. The model is able to arrive at the Onsager relations for such a system. Since no assumption of local equilibrium is made, the conjugate fluxes and forces are intrinsic to the subspaces of the system's state space and are defined using the concepts of hypoequilibrium state and nonequilibrium intensive properties, which describe the nonmutual equilibrium status between subspaces of the thermodynamic state space. The Onsager relations are shown to be a thermodynamic kinematic feature of the system independent of the specific details of the micromechanical dynamics. Two kinds of relaxation processes are studied with different constraints (i.e., conservation laws) corresponding to heat and mass diffusion. Linear behavior in the near-equilibrium region as well as nonlinear behavior in the far-from-equilibrium region are discussed. Thermodynamic relations in the equilibrium and near-equilibrium realm, including the Gibbs relation, the Clausius inequality, and the Onsager relations, are generalized to the far-from-equilibrium realm. The variational principle in the space spanned by the intrinsic conjugate fluxes and forces is expressed via the quadratic dissipation potential. As an application, the model is applied to the heat and mass diffusion of a system represented by a single-particle ensemble, which can also be applied to a simple system of many particles. Phenomenological transport coefficients are also derived in the near-equilibrium realm.

Reduction of respiratory ghosting motion artifacts in conventional two-dimensional multi-slice Cartesian turbo spin-echo: which k-space filling order is the best?

PubMed

Inoue, Yuuji; Yoneyama, Masami; Nakamura, Masanobu; Takemura, Atsushi

2018-06-01

The two-dimensional Cartesian turbo spin-echo (TSE) sequence is widely used in routine clinical studies, but it is sensitive to respiratory motion. We investigated the k-space orders in Cartesian TSE that can effectively reduce motion artifacts. The purpose of this study was to demonstrate the relationship between k-space order and degree of motion artifacts using a moving phantom. We compared the degree of motion artifacts between linear and asymmetric k-space orders. The actual spacing of ghost artifacts in the asymmetric order was doubled compared with that in the linear order in the free-breathing situation. The asymmetric order clearly showed less sensitivity to incomplete breath-hold at the latter half of the imaging period. Because of the actual number of partitions of the k-space and the temporal filling order, the asymmetric k-space order of Cartesian TSE was superior to the linear k-space order for reduction of ghosting motion artifacts.

Adaptive multiregression in reproducing kernel Hilbert spaces: the multiaccess MIMO channel case.

PubMed

Slavakis, Konstantinos; Bouboulis, Pantelis; Theodoridis, Sergios

2012-02-01

This paper introduces a wide framework for online, i.e., time-adaptive, supervised multiregression tasks. The problem is formulated in a general infinite-dimensional reproducing kernel Hilbert space (RKHS). In this context, a fairly large number of nonlinear multiregression models fall as special cases, including the linear case. Any convex, continuous, and not necessarily differentiable function can be used as a loss function in order to quantify the disagreement between the output of the system and the desired response. The only requirement is the subgradient of the adopted loss function to be available in an analytic form. To this end, we demonstrate a way to calculate the subgradients of robust loss functions, suitable for the multiregression task. As it is by now well documented, when dealing with online schemes in RKHS, the memory keeps increasing with each iteration step. To attack this problem, a simple sparsification strategy is utilized, which leads to an algorithmic scheme of linear complexity with respect to the number of unknown parameters. A convergence analysis of the technique, based on arguments of convex analysis, is also provided. To demonstrate the capacity of the proposed method, the multiregressor is applied to the multiaccess multiple-input multiple-output channel equalization task for a setting with poor resources and nonavailable channel information. Numerical results verify the potential of the method, when its performance is compared with those of the state-of-the-art linear techniques, which, in contrast, use space-time coding, more antenna elements, as well as full channel information.

Implications of dune pattern analysis for Titan's surface history

NASA Astrophysics Data System (ADS)

Savage, Christopher J.; Radebaugh, Jani; Christiansen, Eric H.; Lorenz, Ralph D.

2014-02-01

Analysis of large-scale morphological parameters can reveal the reaction of dunes to changes in atmospheric and sedimentary conditions. Over 7000 dune width and 7000 dune spacing measurements were obtained for linear dunes in regions across Saturn's moon Titan from images T21, T23, T28, T44 and T48 collected by the Synthetic Aperture RADAR (SAR) aboard the Cassini spacecraft in order to reconstruct the aeolian surface history of Titan. Dunes in the five study areas are all linear in form, with a mean width of 1.3 km and mean crest spacing of 2.7 km, similar to dunes in the African Saharan and Namib deserts on Earth. At the resolution of Cassini SAR, the dunes have the morphology of large linear dunes, and they lack evidence for features of compound or complex dunes. The large size, spacing and uniform morphology are all indicators that Titan's dunes are mature features, in that they have grown toward a steady state for a long period of time. Dune width decreases to the north, perhaps from increased sediment stabilization caused by a net transport of moisture from south to north, or from increased maturity in dunes to the south. Cumulative probability plots of dune parameters measured at different locations across Titan indicate there is a single population of intermediate-to-large-sized dunes on Titan. This suggests that, unlike analogous dunes in the Namib and Agneitir Sand Seas, dune-forming conditions that generated the current set of dunes were stable and active long enough to erase any evidence of past conditions.

Electrostatic charge on a dust size distribution in a plasma. [in interplanetary space

NASA Technical Reports Server (NTRS)

Houpis, Harry L. F.; Whipple, Elden C., Jr.

1987-01-01

The capacitance of a grain immersed in a steady state plasma containing a size distribution of dust particles is studied. The grain charge is determined by assuming the equilibrium potential has been obtained by a simple balance of electron and ion collection currents. It is shown that the validity of the analytical treatment given here for the linearized Poisson equation is confined to a certain region of space. Within this region and starting at very small plasma Debye length lambda(D), the capacitance at first exhibits a monotonic increase with increasing lambda(D). The capacitance eventually reaches a maximum, followed by a monotonic decrease. The charge density of the dust in the plasma is found to be only a function of the lambda(D); there is no significant dependence on the interparticle spacing.

Velocity-gauge real-time TDDFT within a numerical atomic orbital basis set

NASA Astrophysics Data System (ADS)

Pemmaraju, C. D.; Vila, F. D.; Kas, J. J.; Sato, S. A.; Rehr, J. J.; Yabana, K.; Prendergast, David

2018-05-01

The interaction of laser fields with solid-state systems can be modeled efficiently within the velocity-gauge formalism of real-time time dependent density functional theory (RT-TDDFT). In this article, we discuss the implementation of the velocity-gauge RT-TDDFT equations for electron dynamics within a linear combination of atomic orbitals (LCAO) basis set framework. Numerical results obtained from our LCAO implementation, for the electronic response of periodic systems to both weak and intense laser fields, are compared to those obtained from established real-space grid and Full-Potential Linearized Augmented Planewave approaches. Potential applications of the LCAO based scheme in the context of extreme ultra-violet and soft X-ray spectroscopies involving core-electronic excitations are discussed.

Real-Time Parameter Estimation in the Frequency Domain

NASA Technical Reports Server (NTRS)

Morelli, Eugene A.

2000-01-01

A method for real-time estimation of parameters in a linear dynamic state-space model was developed and studied. The application is aircraft dynamic model parameter estimation from measured data in flight. Equation error in the frequency domain was used with a recursive Fourier transform for the real-time data analysis. Linear and nonlinear simulation examples and flight test data from the F-18 High Alpha Research Vehicle were used to demonstrate that the technique produces accurate model parameter estimates with appropriate error bounds. Parameter estimates converged in less than one cycle of the dominant dynamic mode, using no a priori information, with control surface inputs measured in flight during ordinary piloted maneuvers. The real-time parameter estimation method has low computational requirements and could be implemented

Identification of Geostructures of the Continental Crust Particularly as They Relate to Mineral Resource Evaluation. [Alaska

NASA Technical Reports Server (NTRS)

Lathram, E. H. (Principal Investigator)

1974-01-01

The author has identified the following significant results. A pattern of very old geostructures was recognized, reflecting structures in the crust. This pattern is not peculiar to Alaska, but can be recognized throughout the northern cordillera. A new metallogenic hypothesis for Alaska was developed, based on the relationship of space image linears to known mineral deposits. Using image linear analysis, regional geologic features were also recognized; these features may be used to guide in the location of undiscovered oil and/or gas accumulations in northern Alaska. The effectiveness of ERTS data in enhancing medium and small scale mapping was demonstrated. ERTS data were also used to recognize and monitor the state of large scale vehicular scars on Arctic tundra.

Granger-causality maps of diffusion processes.

PubMed

Wahl, Benjamin; Feudel, Ulrike; Hlinka, Jaroslav; Wächter, Matthias; Peinke, Joachim; Freund, Jan A

2016-02-01

Granger causality is a statistical concept devised to reconstruct and quantify predictive information flow between stochastic processes. Although the general concept can be formulated model-free it is often considered in the framework of linear stochastic processes. Here we show how local linear model descriptions can be employed to extend Granger causality into the realm of nonlinear systems. This novel treatment results in maps that resolve Granger causality in regions of state space. Through examples we provide a proof of concept and illustrate the utility of these maps. Moreover, by integration we convert the local Granger causality into a global measure that yields a consistent picture for a global Ornstein-Uhlenbeck process. Finally, we recover invariance transformations known from the theory of autoregressive processes.

Quasiparticle interference of Fermi arc states in the type-II Weyl semimetal candidate WT e2

NASA Astrophysics Data System (ADS)

Yuan, Yuan; Yang, Xing; Peng, Lang; Wang, Zhi-Jun; Li, Jian; Yi, Chang-Jiang; Xian, Jing-Jing; Shi, You-Guo; Fu, Ying-Shuang

2018-04-01

Weyl semimetals possess linear dispersions through pairs of Weyl nodes in three-dimensional momentum spaces, whose hallmark arclike surface states are connected to Weyl nodes with different chirality. WT e2 was recently predicted to be a new type of Weyl semimetal. Here, we study the quasiparticle interference (QPI) of its Fermi arc surface states by combined spectroscopic-imaging scanning tunneling spectroscopy and density functional theory calculations. We observed the electron scattering on two types of WT e2 surfaces unambiguously. Its scattering signal can be ascribed mainly to trivial surface states. We also address the QPI feature of nontrivial surface states from theoretical calculations. The experimental QPI patterns show some features that are likely related to the nontrivial Fermi arc states, whose existence is, however, not conclusive. Our study provides an indispensable clue for studying the Weyl semimetal phase in WT e2 .

Observables and density matrices embedded in dual Hilbert spaces

NASA Astrophysics Data System (ADS)

Prosen, T.; Martignon, L.; Seligman, T. H.

2015-06-01

The introduction of operator states and of observables in various fields of quantum physics has raised questions about the mathematical structures of the corresponding spaces. In the framework of third quantization it had been conjectured that we deal with Hilbert spaces although the mathematical background was not entirely clear, particularly, when dealing with bosonic operators. This in turn caused some doubts about the correct way to combine bosonic and fermionic operators or, in other words, regular and Grassmann variables. In this paper we present a formal answer to the problems on a simple and very general basis. We illustrate the resulting construction by revisiting the Bargmann transform and finding the known connection between {{L}}2({{R}}) and the Bargmann-Hilbert space. We pursue this line of thinking one step further and discuss the representations of complex extensions of linear canonical transformations as isometries between dual Hilbert spaces. We then use the formalism to give an explicit formulation for Fock spaces involving both fermions and bosons thus solving the problem at the origin of our considerations.

Shift-Variant Multidimensional Systems.

DTIC Science & Technology

1985-05-29

i=0,1,** *N-1 in (3.1), one will get 0() i_0,1,* ,N-1 which is nonnegative due to the Perron - Frobenius Theorem [24]. That is, the A nonnegativity ...and the current input. The state-space model was extended in order to model 2-D discrete LSV systems with support on a causality cone . Subsequently...formulated as a special system of linear equations with nonnegative coefficients whose solution is required to satisfy con- straints like nonnegativity in

State Space Model with hidden variables for reconstruction of gene regulatory networks.

PubMed

Wu, Xi; Li, Peng; Wang, Nan; Gong, Ping; Perkins, Edward J; Deng, Youping; Zhang, Chaoyang

2011-01-01

State Space Model (SSM) is a relatively new approach to inferring gene regulatory networks. It requires less computational time than Dynamic Bayesian Networks (DBN). There are two types of variables in the linear SSM, observed variables and hidden variables. SSM uses an iterative method, namely Expectation-Maximization, to infer regulatory relationships from microarray datasets. The hidden variables cannot be directly observed from experiments. How to determine the number of hidden variables has a significant impact on the accuracy of network inference. In this study, we used SSM to infer Gene regulatory networks (GRNs) from synthetic time series datasets, investigated Bayesian Information Criterion (BIC) and Principle Component Analysis (PCA) approaches to determining the number of hidden variables in SSM, and evaluated the performance of SSM in comparison with DBN. True GRNs and synthetic gene expression datasets were generated using GeneNetWeaver. Both DBN and linear SSM were used to infer GRNs from the synthetic datasets. The inferred networks were compared with the true networks. Our results show that inference precision varied with the number of hidden variables. For some regulatory networks, the inference precision of DBN was higher but SSM performed better in other cases. Although the overall performance of the two approaches is compatible, SSM is much faster and capable of inferring much larger networks than DBN. This study provides useful information in handling the hidden variables and improving the inference precision.

Space-based IR tracking bias removal using background star observations

NASA Astrophysics Data System (ADS)

Clemons, T. M., III; Chang, K. C.

2009-05-01

This paper provides the results of a proposed methodology for removing sensor bias from a space-based infrared (IR) tracking system through the use of stars detected in the background field of the tracking sensor. The tracking system consists of two satellites flying in a lead-follower formation tracking a ballistic target. Each satellite is equipped with a narrow-view IR sensor that provides azimuth and elevation to the target. The tracking problem is made more difficult due to a constant, non-varying or slowly varying bias error present in each sensor's line of sight measurements. As known stars are detected during the target tracking process, the instantaneous sensor pointing error can be calculated as the difference between star detection reading and the known position of the star. The system then utilizes a separate bias filter to estimate the bias value based on these detections and correct the target line of sight measurements to improve the target state vector. The target state vector is estimated through a Linearized Kalman Filter (LKF) for the highly non-linear problem of tracking a ballistic missile. Scenarios are created using Satellite Toolkit(C) for trajectories with associated sensor observations. Mean Square Error results are given for tracking during the period when the target is in view of the satellite IR sensors. The results of this research provide a potential solution to bias correction while simultaneously tracking a target.

Quadratic obstructions to small-time local controllability for scalar-input systems

NASA Astrophysics Data System (ADS)

Beauchard, Karine; Marbach, Frédéric

2018-03-01

We consider nonlinear finite-dimensional scalar-input control systems in the vicinity of an equilibrium. When the linearized system is controllable, the nonlinear system is smoothly small-time locally controllable: whatever m > 0 and T > 0, the state can reach a whole neighborhood of the equilibrium at time T with controls arbitrary small in Cm-norm. When the linearized system is not controllable, we prove that: either the state is constrained to live within a smooth strict manifold, up to a cubic residual, or the quadratic order adds a signed drift with respect to it. This drift holds along a Lie bracket of length (2 k + 1), is quantified in terms of an H-k-norm of the control, holds for controls small in W 2 k , ∞-norm and these spaces are optimal. Our proof requires only C3 regularity of the vector field. This work underlines the importance of the norm used in the smallness assumption on the control, even in finite dimension.

A Kinetic Approach to Propagation and Stability of Detonation Waves

NASA Astrophysics Data System (ADS)

Monaco, R.; Bianchi, M. Pandolfi; Soares, A. J.

2008-12-01

The problem of the steady propagation and linear stability of a detonation wave is formulated in the kinetic frame for a quaternary gas mixture in which a reversible bimolecular reaction takes place. The reactive Euler equations and related Rankine-Hugoniot conditions are deduced from the mesoscopic description of the process. The steady propagation problem is solved for a Zeldovich, von Neuman and Doering (ZND) wave, providing the detonation profiles and the wave thickness for different overdrive degrees. The one-dimensional stability of such detonation wave is then studied in terms of an initial value problem coupled with an acoustic radiation condition at the equilibrium final state. The stability equations and their initial data are deduced from the linearized reactive Euler equations and related Rankine-Hugoniot conditions through a normal mode analysis referred to the complex disturbances of the steady state variables. Some numerical simulations for an elementary reaction of the hydrogen-oxygen chain are proposed in order to describe the time and space evolution of the instabilities induced by the shock front perturbation.

Quasi-linear regime of gravitational instability: Implication to density-velocity relation

NASA Technical Reports Server (NTRS)

Shandarin, Sergei F.

1993-01-01

The well known linear relation between density and peculiar velocity distributions is a powerful tool for studying the large-scale structure in the Universe. Potentially it can test the gravitational instability theory and measure Omega. At present it is used in both ways: the velocity is reconstructed, provided the density is given, and vice versa. Reconstructing the density from the velocity field usually makes use of the Zel'dovich approximation. However, the standard linear approximation in Eulerian space is used when the velocity is reconstructed from the density distribution. I show that the linearized Zel'dovich approximation, in other words the linear approximation in the Lagrangian space, is more accurate for reconstructing velocity. In principle, a simple iteration technique can recover both the density and velocity distributions in Lagrangian space, but its practical application may need an additional study.

Generating log-normal mock catalog of galaxies in redshift space

NASA Astrophysics Data System (ADS)

Agrawal, Aniket; Makiya, Ryu; Chiang, Chi-Ting; Jeong, Donghui; Saito, Shun; Komatsu, Eiichiro

2017-10-01

We present a public code to generate a mock galaxy catalog in redshift space assuming a log-normal probability density function (PDF) of galaxy and matter density fields. We draw galaxies by Poisson-sampling the log-normal field, and calculate the velocity field from the linearised continuity equation of matter fields, assuming zero vorticity. This procedure yields a PDF of the pairwise velocity fields that is qualitatively similar to that of N-body simulations. We check fidelity of the catalog, showing that the measured two-point correlation function and power spectrum in real space agree with the input precisely. We find that a linear bias relation in the power spectrum does not guarantee a linear bias relation in the density contrasts, leading to a cross-correlation coefficient of matter and galaxies deviating from unity on small scales. We also find that linearising the Jacobian of the real-to-redshift space mapping provides a poor model for the two-point statistics in redshift space. That is, non-linear redshift-space distortion is dominated by non-linearity in the Jacobian. The power spectrum in redshift space shows a damping on small scales that is qualitatively similar to that of the well-known Fingers-of-God (FoG) effect due to random velocities, except that the log-normal mock does not include random velocities. This damping is a consequence of non-linearity in the Jacobian, and thus attributing the damping of the power spectrum solely to FoG, as commonly done in the literature, is misleading.

Emergent causality and the N-photon scattering matrix in waveguide QED

NASA Astrophysics Data System (ADS)

Sánchez-Burillo, E.; Cadarso, A.; Martín-Moreno, L.; García-Ripoll, J. J.; Zueco, D.

2018-01-01

In this work we discuss the emergence of approximate causality in a general setup from waveguide QED—i.e. a one-dimensional propagating field interacting with a scatterer. We prove that this emergent causality translates into a structure for the N-photon scattering matrix. Our work builds on the derivation of a Lieb-Robinson-type bound for continuous models and for all coupling strengths, as well as on several intermediate results, of which we highlight: (i) the asymptotic independence of space-like separated wave packets, (ii) the proper definition of input and output scattering states, and (iii) the characterization of the ground state and correlations in the model. We illustrate our formal results by analyzing the two-photon scattering from a quantum impurity in the ultrastrong coupling regime, verifying the cluster decomposition and ground-state nature. Besides, we generalize the cluster decomposition if inelastic or Raman scattering occurs, finding the structure of the S-matrix in momentum space for linear dispersion relations. In this case, we compute the decay of the fluorescence (photon-photon correlations) caused by this S-matrix.

Continuous-variable entanglement distillation of non-Gaussian mixed states

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

Dong Ruifang; Lassen, Mikael; Department of Physics, Technical University of Denmark, Building 309, DK-2800 Lyngby

2010-07-15

Many different quantum-information communication protocols such as teleportation, dense coding, and entanglement-based quantum key distribution are based on the faithful transmission of entanglement between distant location in an optical network. The distribution of entanglement in such a network is, however, hampered by loss and noise that is inherent in all practical quantum channels. Thus, to enable faithful transmission one must resort to the protocol of entanglement distillation. In this paper we present a detailed theoretical analysis and an experimental realization of continuous variable entanglement distillation in a channel that is inflicted by different kinds of non-Gaussian noise. The continuous variablemore » entangled states are generated by exploiting the third order nonlinearity in optical fibers, and the states are sent through a free-space laboratory channel in which the losses are altered to simulate a free-space atmospheric channel with varying losses. We use linear optical components, homodyne measurements, and classical communication to distill the entanglement, and we find that by using this method the entanglement can be probabilistically increased for some specific non-Gaussian noise channels.« less

Cooperative control of two active spacecraft during proximity operations. M.S. Thesis - MIT

NASA Technical Reports Server (NTRS)

Polutchko, Robert J.

1989-01-01

A cooperative autopilot is developed for the control of the relative attitude, relative position and absolute attitude of two maneuvering spacecraft during on orbit proximity operations. The autopilot consists of an open-loop trajectory solver which computes a nine dimensional linearized nominal state trajectory at the beginning of each maneuver and a phase space regulator which maintains the two spacecraft on the nominal trajectory during coast phases of the maneuver. A linear programming algorithm is used to perform jet selection. Simulation tests using a system of two space shuttle vehicles are performed to verify the performance of the cooperative controller and comparisons are made to a traditional passive target/active pursuit vehicle approach to proximity operations. The cooperative autopilot is shown to be able to control the two vehicle system when both the would be pursuit vehicle and the target vehicle are not completely controllable in six degrees of freedom. The cooperative controller is also shown to use as much as 37 percent less fuel and 57 percent fewer jet firings than a single pursuit vehicle during a simple docking approach maneuver.

The Effect of Pulse Shaping QPSK on Bandwidth Efficiency

NASA Technical Reports Server (NTRS)

Purba, Josua Bisuk Mubyarto; Horan, Shelia

1997-01-01

This research investigates the effect of pulse shaping QPSK on bandwidth efficiency over a non-linear channel. This investigation will include software simulations and the hardware implementation. Three kinds of filters: the 5th order Butterworth filter, the 3rd order Bessel filter and the Square Root Raised Cosine filter with a roll off factor (alpha) of 0.25,0.5 and 1, have been investigated as pulse shaping filters. Two different high power amplifiers, one a Traveling Wave Tube Amplifier (TWTA) and the other a Solid State Power Amplifier (SSPA) have been investigated in the hardware implementation. A significant improvement in the bandwidth utilization (rho) for the filtered data compared to unfiltered data through the non-linear channel is shown in the results. This method promises strong performance gains in a bandlimited channel when compared to unfiltered systems. This work was conducted at NMSU in the Center for Space Telemetering, and Telecommunications Systems in the Klipsch School of Electrical and Computer Engineering Department and is supported by a grant from the National Aeronautics and Space Administration (NASA) NAG5-1491.

Effects of different space allowances on growth performance, blood profile and pork quality in a grow-to-finish production system.

PubMed

Jang, J C; Jin, X H; Hong, J S; Kim, Y Y

2017-12-01

This experiment was conducted to evaluate the optimal space allowance on growth performance, blood profile and pork quality of growing-finishing pigs. A total of ninety crossbred pigs [(Yorkshire×Landrace)×Duroc, 30.25±1.13 kg] were allocated into three treatments (0.96: four pigs/pen, 0.96 m2/pig; 0.80: five pigs/pen, 0.80 m2/pig; 0.69: six pigs/pen, 0.69 m2/pig) in a randomized complete block design. Pigs were housed in balanced sex and had free access to feed in all phases for 14 weeks (growing phase I, growing phase II, finishing phase I, and finishing phase II). There was no statistical difference in growing phase, but a linear decrease was observed on average daily gain (ADG, p<0.01), average daily feed intake (ADFI, p<0.01), and body weight (BW, p<0.01) with decreasing space allowance in late finishing phase. On the other hand, a quadratic effect was observed on gain to feed ratio in early finishing phase (p<0.03). Consequently, overall ADG, ADFI, and final BW linearly declined in response to decreased space allowance (p<0.01). The pH of pork had no significant difference in 1 hour after slaughter, whereas there was a linear decrease in 24 h after slaughter with decreasing space allowance. Floor area allowance did not affect pork colors, but shear force linearly increased as floor space decreased (p<0.01). There was a linear increase in serum cortisol concentration on 14 week (p<0.05) with decreased space allocation. Serum IgG was linearly ameliorated as space allowance increased on 10 week (p<0.05) and 14 week (p<0.01). Data from current study indicated that stress derived from reduced space allowance deteriorates the immune system as well as growth performance of pigs, resulting in poor pork quality. Recommended adequate space allowance in a grow-to-finish production system is more than 0.80 m2/pig for maximizing growth performance and production efficiency.

A genetic technique for planning a control sequence to navigate the state space with a quasi-minimum-cost output trajectory for a non-linear multi-dimnensional system

NASA Technical Reports Server (NTRS)

Hein, C.; Meystel, A.

1994-01-01

There are many multi-stage optimization problems that are not easily solved through any known direct method when the stages are coupled. For instance, we have investigated the problem of planning a vehicle's control sequence to negotiate obstacles and reach a goal in minimum time. The vehicle has a known mass, and the controlling forces have finite limits. We have developed a technique that finds admissible control trajectories which tend to minimize the vehicle's transit time through the obstacle field. The immediate applications is that of a space robot which must rapidly traverse around 2-or-3 dimensional structures via application of a rotating thruster or non-rotating on-off for such vehicles is located at the Marshall Space Flight Center in Huntsville Alabama. However, it appears that the development method is applicable to a general set of optimization problems in which the cost function and the multi-dimensional multi-state system can be any nonlinear functions, which are continuous in the operating regions. Other applications included the planning of optimal navigation pathways through a transversability graph; the planning of control input for under-water maneuvering vehicles which have complex control state-space relationships; the planning of control sequences for milling and manufacturing robots; the planning of control and trajectories for automated delivery vehicles; and the optimization and athletic training in slalom sports.

Space Radiation Effects and Hardness Assurance for Linear Integrated Circuits

NASA Technical Reports Server (NTRS)

Johnston, A. H.

2000-01-01

New effects that complicate the application of linear devices in space are discussed, including enhanced damage at low dose rate and proton damage, which cause permanent degradation. Transients produced by protons and heavy ions are also discussed.

Control of nonlinear flexible space structures

NASA Astrophysics Data System (ADS)

Shi, Jianjun

With the advances made in computer technology and efficiency of numerical algorithms over last decade, the MPC strategies have become quite popular among control community. However, application of MPC or GPC to flexible space structure control has not been explored adequately in the literature. The work presented in this thesis primarily focuses on application of GPC to control of nonlinear flexible space structures. This thesis is particularly devoted to the development of various approximate dynamic models, design and assessment of candidate controllers, and extensive numerical simulations for a realistic multibody flexible spacecraft, namely, Jupiter Icy Moons Orbiter (JIMO)---a Prometheus class of spacecraft proposed by NASA for deep space exploratory missions. A stable GPC algorithm is developed for Multi-Input-Multi-Output (MIMO) systems. An end-point weighting (penalty) is used in the GPC cost function to guarantee the nominal stability of the closed-loop system. A method is given to compute the desired end-point state from the desired output trajectory. The methodologies based on Fake Algebraic Riccati Equation (FARE) and constrained nonlinear optimization, are developed for synthesis of state weighting matrix. This makes this formulation more practical. A stable reconfigurable GPC architecture is presented and its effectiveness is demonstrated on both aircraft as well as spacecraft model. A representative in-orbit maneuver is used for assessing the performance of various control strategies using various design models. Different approximate dynamic models used for analysis include linear single body flexible structure, nonlinear single body flexible structure, and nonlinear multibody flexible structure. The control laws evaluated include traditional GPC, feedback linearization-based GPC (FLGPC), reconfigurable GPC, and nonlinear dissipative control. These various control schemes are evaluated for robust stability and robust performance in the presence of parametric uncertainties and input disturbances. Finally, the conclusions are made with regard to the efficacy of these controllers and potential directions for future research.

Reduced nonlinear prognostic model construction from high-dimensional data

NASA Astrophysics Data System (ADS)

Gavrilov, Andrey; Mukhin, Dmitry; Loskutov, Evgeny; Feigin, Alexander

2017-04-01

Construction of a data-driven model of evolution operator using universal approximating functions can only be statistically justified when the dimension of its phase space is small enough, especially in the case of short time series. At the same time in many applications real-measured data is high-dimensional, e.g. it is space-distributed and multivariate in climate science. Therefore it is necessary to use efficient dimensionality reduction methods which are also able to capture key dynamical properties of the system from observed data. To address this problem we present a Bayesian approach to an evolution operator construction which incorporates two key reduction steps. First, the data is decomposed into a set of certain empirical modes, such as standard empirical orthogonal functions or recently suggested nonlinear dynamical modes (NDMs) [1], and the reduced space of corresponding principal components (PCs) is obtained. Then, the model of evolution operator for PCs is constructed which maps a number of states in the past to the current state. The second step is to reduce this time-extended space in the past using appropriate decomposition methods. Such a reduction allows us to capture only the most significant spatio-temporal couplings. The functional form of the evolution operator includes separately linear, nonlinear (based on artificial neural networks) and stochastic terms. Explicit separation of the linear term from the nonlinear one allows us to more easily interpret degree of nonlinearity as well as to deal better with smooth PCs which can naturally occur in the decompositions like NDM, as they provide a time scale separation. Results of application of the proposed method to climate data are demonstrated and discussed. The study is supported by Government of Russian Federation (agreement #14.Z50.31.0033 with the Institute of Applied Physics of RAS). 1. Mukhin, D., Gavrilov, A., Feigin, A., Loskutov, E., & Kurths, J. (2015). Principal nonlinear dynamical modes of climate variability. Scientific Reports, 5, 15510. http://doi.org/10.1038/srep15510

State-space model with deep learning for functional dynamics estimation in resting-state fMRI.

PubMed

Suk, Heung-Il; Wee, Chong-Yaw; Lee, Seong-Whan; Shen, Dinggang

2016-04-01

Studies on resting-state functional Magnetic Resonance Imaging (rs-fMRI) have shown that different brain regions still actively interact with each other while a subject is at rest, and such functional interaction is not stationary but changes over time. In terms of a large-scale brain network, in this paper, we focus on time-varying patterns of functional networks, i.e., functional dynamics, inherent in rs-fMRI, which is one of the emerging issues along with the network modelling. Specifically, we propose a novel methodological architecture that combines deep learning and state-space modelling, and apply it to rs-fMRI based Mild Cognitive Impairment (MCI) diagnosis. We first devise a Deep Auto-Encoder (DAE) to discover hierarchical non-linear functional relations among regions, by which we transform the regional features into an embedding space, whose bases are complex functional networks. Given the embedded functional features, we then use a Hidden Markov Model (HMM) to estimate dynamic characteristics of functional networks inherent in rs-fMRI via internal states, which are unobservable but can be inferred from observations statistically. By building a generative model with an HMM, we estimate the likelihood of the input features of rs-fMRI as belonging to the corresponding status, i.e., MCI or normal healthy control, based on which we identify the clinical label of a testing subject. In order to validate the effectiveness of the proposed method, we performed experiments on two different datasets and compared with state-of-the-art methods in the literature. We also analyzed the functional networks learned by DAE, estimated the functional connectivities by decoding hidden states in HMM, and investigated the estimated functional connectivities by means of a graph-theoretic approach. Copyright © 2016 Elsevier Inc. All rights reserved.

State-space model with deep learning for functional dynamics estimation in resting-state fMRI

PubMed Central

Suk, Heung-Il; Wee, Chong-Yaw; Lee, Seong-Whan; Shen, Dinggang

2017-01-01

Studies on resting-state functional Magnetic Resonance Imaging (rs-fMRI) have shown that different brain regions still actively interact with each other while a subject is at rest, and such functional interaction is not stationary but changes over time. In terms of a large-scale brain network, in this paper, we focus on time-varying patterns of functional networks, i.e., functional dynamics, inherent in rs-fMRI, which is one of the emerging issues along with the network modelling. Specifically, we propose a novel methodological architecture that combines deep learning and state-space modelling, and apply it to rs-fMRI based Mild Cognitive Impairment (MCI) diagnosis. We first devise a Deep Auto-Encoder (DAE) to discover hierarchical non-linear functional relations among regions, by which we transform the regional features into an embedding space, whose bases are complex functional networks. Given the embedded functional features, we then use a Hidden Markov Model (HMM) to estimate dynamic characteristics of functional networks inherent in rs-fMRI via internal states, which are unobservable but can be inferred from observations statistically. By building a generative model with an HMM, we estimate the likelihood of the input features of rs-fMRI as belonging to the corresponding status, i.e., MCI or normal healthy control, based on which we identify the clinical label of a testing subject. In order to validate the effectiveness of the proposed method, we performed experiments on two different datasets and compared with state-of-the-art methods in the literature. We also analyzed the functional networks learned by DAE, estimated the functional connectivities by decoding hidden states in HMM, and investigated the estimated functional connectivities by means of a graph-theoretic approach. PMID:26774612

On a model of three-dimensional bursting and its parallel implementation

NASA Astrophysics Data System (ADS)

Tabik, S.; Romero, L. F.; Garzón, E. M.; Ramos, J. I.

2008-04-01

A mathematical model for the simulation of three-dimensional bursting phenomena and its parallel implementation are presented. The model consists of four nonlinearly coupled partial differential equations that include fast and slow variables, and exhibits bursting in the absence of diffusion. The differential equations have been discretized by means of a second-order accurate in both space and time, linearly-implicit finite difference method in equally-spaced grids. The resulting system of linear algebraic equations at each time level has been solved by means of the Preconditioned Conjugate Gradient (PCG) method. Three different parallel implementations of the proposed mathematical model have been developed; two of these implementations, i.e., the MPI and the PETSc codes, are based on a message passing paradigm, while the third one, i.e., the OpenMP code, is based on a shared space address paradigm. These three implementations are evaluated on two current high performance parallel architectures, i.e., a dual-processor cluster and a Shared Distributed Memory (SDM) system. A novel representation of the results that emphasizes the most relevant factors that affect the performance of the paralled implementations, is proposed. The comparative analysis of the computational results shows that the MPI and the OpenMP implementations are about twice more efficient than the PETSc code on the SDM system. It is also shown that, for the conditions reported here, the nonlinear dynamics of the three-dimensional bursting phenomena exhibits three stages characterized by asynchronous, synchronous and then asynchronous oscillations, before a quiescent state is reached. It is also shown that the fast system reaches steady state in much less time than the slow variables.

Evaluation of pharyngeal space and its correlation with mandible and hyoid bone in patients with different skeletal classes and facial types.

PubMed

Nejaim, Yuri; Aps, Johan K M; Groppo, Francisco Carlos; Haiter Neto, Francisco

2018-06-01

The purpose of this article was to evaluate the pharyngeal space volume, and the size and shape of the mandible and the hyoid bone, as well as their relationships, in patients with different facial types and skeletal classes. Furthermore, we estimated the volume of the pharyngeal space with a formula using only linear measurements. A total of 161 i-CAT Next Generation (Imaging Sciences International, Hatfield, Pa) cone-beam computed tomography images (80 men, 81 women; ages, 21-58 years; mean age, 27 years) were retrospectively studied. Skeletal class and facial type were determined for each patient from multiplanar reconstructions using the NemoCeph software (Nemotec, Madrid, Spain). Linear and angular measurements were performed using 3D imaging software (version 3.4.3; Carestream Health, Rochester, NY), and volumetric analysis of the pharyngeal space was carried out with ITK-SNAP (version 2.4.0; Cognitica, Philadelphia, Pa) segmentation software. For the statistics, analysis of variance and the Tukey test with a significance level of 0.05, Pearson correlation, and linear regression were used. The pharyngeal space volume, when correlated with mandible and hyoid bone linear and angular measurements, showed significant correlations with skeletal class or facial type. The linear regression performed to estimate the volume of the pharyngeal space showed an R of 0.92 and an adjusted R 2 of 0.8362. There were significant correlations between pharyngeal space volume, and the mandible and hyoid bone measurements, suggesting that the stomatognathic system should be evaluated in an integral and nonindividualized way. Furthermore, it was possible to develop a linear regression model, resulting in a useful formula for estimating the volume of the pharyngeal space. Copyright © 2018 American Association of Orthodontists. Published by Elsevier Inc. All rights reserved.

Control method for physical systems and devices

DOEpatents

Guckenheimer, John

1997-01-01

A control method for stabilizing systems or devices that are outside the control domain of a linear controller is provided. When applied to nonlinear systems, the effectiveness of this method depends upon the size of the domain of stability that is produced for the stabilized equilibrium. If this domain is small compared to the accuracy of measurements or the size of disturbances within the system, then the linear controller is likely to fail within a short period. Failure of the system or device can be catastrophic: the system or device can wander far from the desired equilibrium. The method of the invention presents a general procedure to recapture the stability of a linear controller, when the trajectory of a system or device leaves its region of stability. By using a hybrid strategy based upon discrete switching events within the state space of the system or device, the system or device will return from a much larger domain to the region of stability utilized by the linear controller. The control procedure is robust and remains effective under large classes of perturbations of a given underlying system or device.

Modeling, Control and Simulation of Three-Dimensional Robotic Systems with Applications to Biped Locomotion.

NASA Astrophysics Data System (ADS)

Zheng, Yuan-Fang

A three-dimensional, five link biped system is established. Newton-Euler state space formulation is employed to derive the equations of the system. The constraint forces involved in the equations can be eliminated by projection onto a smaller state space system for deriving advanced control laws. A model-referenced adaptive control scheme is developed to control the system. Digital computer simulations of point to point movement are carried out to show that the model-referenced adaptive control increases the dynamic range and speeds up the response of the system in comparison with linear and nonlinear feedback control. Further, the implementation of the controller is simpler. Impact effects of biped contact with the environment are modeled and studied. The instant velocity change at the moment of impact is derived as a function of the biped state and contact speed. The effects of impact on the state, as well as constraints are studied in biped landing on heels and toes simultaneously or on toes first. Rate and nonlinear position feedback are employed for stability of the biped after the impact. The complex structure of the foot is properly modeled. A spring and dashpot pair is suggested to represent the action of plantar fascia during the impact. This action prevents the arch of the foot from collapsing. A mathematical model of the skeletal muscle is discussed. A direct relationship between the stimulus rate and the active state is established. A piecewise linear relation between the length of the contractile element and the isometric force is considered. Hill's characteristic equation is maintained for determining the actual output force during different shortening velocities. A physical threshold model is proposed for recruitment which encompasses the size principle, its manifestations and exceptions to the size principle. Finally the role of spindle feedback in stability of the model is demonstrated by study of a pair of muscles.

Practical Methodology for the Inclusion of Nonlinear Slosh Damping in the Stability Analysis of Liquid-Propelled Space Vehicles

NASA Technical Reports Server (NTRS)

Ottander, John A.; Hall, Robert A.; Powers, J. F.

2018-01-01

A method is presented that allows for the prediction of the magnitude of limit cycles due to adverse control-slosh interaction in liquid propelled space vehicles using non-linear slosh damping. Such a method is an alternative to the industry practice of assuming linear damping and relying on: mechanical slosh baffles to achieve desired stability margins; accepting minimal slosh stability margins; or time domain non-linear analysis to accept time periods of poor stability. Sinusoidal input describing functional analysis is used to develop a relationship between the non-linear slosh damping and an equivalent linear damping at a given slosh amplitude. In addition, a more accurate analytical prediction of the danger zone for slosh mass locations in a vehicle under proportional and derivative attitude control is presented. This method is used in the control-slosh stability analysis of the NASA Space Launch System.

Sampling with poling-based flux balance analysis: optimal versus sub-optimal flux space analysis of Actinobacillus succinogenes.

PubMed

Binns, Michael; de Atauri, Pedro; Vlysidis, Anestis; Cascante, Marta; Theodoropoulos, Constantinos

2015-02-18

Flux balance analysis is traditionally implemented to identify the maximum theoretical flux for some specified reaction and a single distribution of flux values for all the reactions present which achieve this maximum value. However it is well known that the uncertainty in reaction networks due to branches, cycles and experimental errors results in a large number of combinations of internal reaction fluxes which can achieve the same optimal flux value. In this work, we have modified the applied linear objective of flux balance analysis to include a poling penalty function, which pushes each new set of reaction fluxes away from previous solutions generated. Repeated poling-based flux balance analysis generates a sample of different solutions (a characteristic set), which represents all the possible functionality of the reaction network. Compared to existing sampling methods, for the purpose of generating a relatively "small" characteristic set, our new method is shown to obtain a higher coverage than competing methods under most conditions. The influence of the linear objective function on the sampling (the linear bias) constrains optimisation results to a subspace of optimal solutions all producing the same maximal fluxes. Visualisation of reaction fluxes plotted against each other in 2 dimensions with and without the linear bias indicates the existence of correlations between fluxes. This method of sampling is applied to the organism Actinobacillus succinogenes for the production of succinic acid from glycerol. A new method of sampling for the generation of different flux distributions (sets of individual fluxes satisfying constraints on the steady-state mass balances of intermediates) has been developed using a relatively simple modification of flux balance analysis to include a poling penalty function inside the resulting optimisation objective function. This new methodology can achieve a high coverage of the possible flux space and can be used with and without linear bias to show optimal versus sub-optimal solution spaces. Basic analysis of the Actinobacillus succinogenes system using sampling shows that in order to achieve the maximal succinic acid production CO₂ must be taken into the system. Solutions involving release of CO₂ all give sub-optimal succinic acid production.

Linear and nonlinear dynamic analysis by boundary element method. Ph.D. Thesis, 1986 Final Report

NASA Technical Reports Server (NTRS)

Ahmad, Shahid

1991-01-01

An advanced implementation of the direct boundary element method (BEM) applicable to free-vibration, periodic (steady-state) vibration and linear and nonlinear transient dynamic problems involving two and three-dimensional isotropic solids of arbitrary shape is presented. Interior, exterior, and half-space problems can all be solved by the present formulation. For the free-vibration analysis, a new real variable BEM formulation is presented which solves the free-vibration problem in the form of algebraic equations (formed from the static kernels) and needs only surface discretization. In the area of time-domain transient analysis, the BEM is well suited because it gives an implicit formulation. Although the integral formulations are elegant, because of the complexity of the formulation it has never been implemented in exact form. In the present work, linear and nonlinear time domain transient analysis for three-dimensional solids has been implemented in a general and complete manner. The formulation and implementation of the nonlinear, transient, dynamic analysis presented here is the first ever in the field of boundary element analysis. Almost all the existing formulation of BEM in dynamics use the constant variation of the variables in space and time which is very unrealistic for engineering problems and, in some cases, it leads to unacceptably inaccurate results. In the present work, linear and quadratic isoparametric boundary elements are used for discretization of geometry and functional variations in space. In addition, higher order variations in time are used. These methods of analysis are applicable to piecewise-homogeneous materials, such that not only problems of the layered media and the soil-structure interaction can be analyzed but also a large problem can be solved by the usual sub-structuring technique. The analyses have been incorporated in a versatile, general-purpose computer program. Some numerical problems are solved and, through comparisons with available analytical and numerical results, the stability and high accuracy of these dynamic analysis techniques are established.

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Integration of Visual and Joint Information to Enable Linear Reaching Motions

NASA Astrophysics Data System (ADS)

Eberle, Henry; Nasuto, Slawomir J.; Hayashi, Yoshikatsu

2017-01-01

A new dynamics-driven control law was developed for a robot arm, based on the feedback control law which uses the linear transformation directly from work space to joint space. This was validated using a simulation of a two-joint planar robot arm and an optimisation algorithm was used to find the optimum matrix to generate straight trajectories of the end-effector in the work space. We found that this linear matrix can be decomposed into the rotation matrix representing the orientation of the goal direction and the joint relation matrix (MJRM) representing the joint response to errors in the Cartesian work space. The decomposition of the linear matrix indicates the separation of path planning in terms of the direction of the reaching motion and the synergies of joint coordination. Once the MJRM is numerically obtained, the feedfoward planning of reaching direction allows us to provide asymptotically stable, linear trajectories in the entire work space through rotational transformation, completely avoiding the use of inverse kinematics. Our dynamics-driven control law suggests an interesting framework for interpreting human reaching motion control alternative to the dominant inverse method based explanations, avoiding expensive computation of the inverse kinematics and the point-to-point control along the desired trajectories.

Lagrangian or Eulerian; real or Fourier? Not all approaches to large-scale structure are created equal

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

Tassev, Svetlin, E-mail: tassev@astro.princeton.edu

We present a pedagogical systematic investigation of the accuracy of Eulerian and Lagrangian perturbation theories of large-scale structure. We show that significant differences exist between them especially when trying to model the Baryon Acoustic Oscillations (BAO). We find that the best available model of the BAO in real space is the Zel'dovich Approximation (ZA), giving an accuracy of ∼<3% at redshift of z = 0 in modelling the matter 2-pt function around the acoustic peak. All corrections to the ZA around the BAO scale are perfectly perturbative in real space. Any attempt to achieve better precision requires calibrating the theorymore » to simulations because of the need to renormalize those corrections. In contrast, theories which do not fully preserve the ZA as their solution, receive O(1) corrections around the acoustic peak in real space at z = 0, and are thus of suspicious convergence at low redshift around the BAO. As an example, we find that a similar accuracy of 3% for the acoustic peak is achieved by Eulerian Standard Perturbation Theory (SPT) at linear order only at z ≈ 4. Thus even when SPT is perturbative, one needs to include loop corrections for z∼<4 in real space. In Fourier space, all models perform similarly, and are controlled by the overdensity amplitude, thus recovering standard results. However, that comes at a price. Real space cleanly separates the BAO signal from non-linear dynamics. In contrast, Fourier space mixes signal from short mildly non-linear scales with the linear signal from the BAO to the level that non-linear contributions from short scales dominate. Therefore, one has little hope in constructing a systematic theory for the BAO in Fourier space.« less

More green space is related to less antidepressant prescription rates in the Netherlands: A Bayesian geoadditive quantile regression approach.

PubMed

Helbich, Marco; Klein, Nadja; Roberts, Hannah; Hagedoorn, Paulien; Groenewegen, Peter P

2018-06-20

Exposure to green space seems to be beneficial for self-reported mental health. In this study we used an objective health indicator, namely antidepressant prescription rates. Current studies rely exclusively upon mean regression models assuming linear associations. It is, however, plausible that the presence of green space is non-linearly related with different quantiles of the outcome antidepressant prescription rates. These restrictions may contribute to inconsistent findings. Our aim was: a) to assess antidepressant prescription rates in relation to green space, and b) to analyze how the relationship varies non-linearly across different quantiles of antidepressant prescription rates. We used cross-sectional data for the year 2014 at a municipality level in the Netherlands. Ecological Bayesian geoadditive quantile regressions were fitted for the 15%, 50%, and 85% quantiles to estimate green space-prescription rate correlations, controlling for physical activity levels, socio-demographics, urbanicity, etc. RESULTS: The results suggested that green space was overall inversely and non-linearly associated with antidepressant prescription rates. More important, the associations differed across the quantiles, although the variation was modest. Significant non-linearities were apparent: The associations were slightly positive in the lower quantile and strongly negative in the upper one. Our findings imply that an increased availability of green space within a municipality may contribute to a reduction in the number of antidepressant prescriptions dispensed. Green space is thus a central health and community asset, whilst a minimum level of 28% needs to be established for health gains. The highest effectiveness occurred at a municipality surface percentage higher than 79%. This inverse dose-dependent relation has important implications for setting future community-level health and planning policies. Copyright © 2018 Elsevier Inc. All rights reserved.

A compositional framework for Markov processes

NASA Astrophysics Data System (ADS)

Baez, John C.; Fong, Brendan; Pollard, Blake S.

2016-03-01

We define the concept of an "open" Markov process, or more precisely, continuous-time Markov chain, which is one where probability can flow in or out of certain states called "inputs" and "outputs." One can build up a Markov process from smaller open pieces. This process is formalized by making open Markov processes into the morphisms of a dagger compact category. We show that the behavior of a detailed balanced open Markov process is determined by a principle of minimum dissipation, closely related to Prigogine's principle of minimum entropy production. Using this fact, we set up a functor mapping open detailed balanced Markov processes to open circuits made of linear resistors. We also describe how to "black box" an open Markov process, obtaining the linear relation between input and output data that holds in any steady state, including nonequilibrium steady states with a nonzero flow of probability through the system. We prove that black boxing gives a symmetric monoidal dagger functor sending open detailed balanced Markov processes to Lagrangian relations between symplectic vector spaces. This allows us to compute the steady state behavior of an open detailed balanced Markov process from the behaviors of smaller pieces from which it is built. We relate this black box functor to a previously constructed black box functor for circuits.

Mixtures of tense and relaxed state polymerized human hemoglobin regulate oxygen affinity and tissue construct oxygenation

PubMed Central

Belcher, Donald Andrew; Banerjee, Uddyalok; Baehr, Christopher Michael; Richardson, Kristopher Emil; Cabrales, Pedro; Berthiaume, François

2017-01-01

Pure tense (T) and relaxed (R) quaternary state polymerized human hemoglobins (PolyhHbs) were synthesized and their biophysical properties characterized, along with mixtures of T- and R-state PolyhHbs. It was observed that the oxygen affinity of PolyhHb mixtures varied linearly with T-state mole fraction. Computational analysis of PolyhHb facilitated oxygenation of a single fiber in a hepatic hollow fiber (HF) bioreactor was performed to evaluate the oxygenation potential of T- and R-state PolyhHb mixtures. PolyhHb mixtures with T-state mole fractions greater than 50% resulted in hypoxic and hyperoxic zones occupying less than 5% of the total extra capillary space (ECS). Under these conditions, the ratio of the pericentral volume to the perivenous volume in the ECS doubled as the T-state mole fraction increased from 50 to 100%. These results show the effect of varying the T/R-state PolyhHb mole fraction on oxygenation of tissue-engineered constructs and their potential to oxygenate tissues. PMID:29020036

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

Dufour, F., E-mail: dufour@math.u-bordeaux1.fr; Prieto-Rumeau, T., E-mail: tprieto@ccia.uned.es

We consider a discrete-time constrained discounted Markov decision process (MDP) with Borel state and action spaces, compact action sets, and lower semi-continuous cost functions. We introduce a set of hypotheses related to a positive weight function which allow us to consider cost functions that might not be bounded below by a constant, and which imply the solvability of the linear programming formulation of the constrained MDP. In particular, we establish the existence of a constrained optimal stationary policy. Our results are illustrated with an application to a fishery management problem.

Diagnosis of the GLAS climate model's stationary planetary waves using a linearized steady state model

NASA Technical Reports Server (NTRS)

Youngblut, C.

1984-01-01

Orography and geographically fixed heat sources which force a zonally asymmetric motion field are examined. An extensive space-time spectral analysis of the GLAS climate model (D130) response and observations are compared. An updated version of the model (D150) showed a remarkable improvement in the simulation of the standing waves. The main differences in the model code are an improved boundary layer flux computation and a more realistic specification of the global boundary conditions.

The use of Lyapunov differential inequalities for estimating the transients of mechanical systems

NASA Astrophysics Data System (ADS)

Alyshev, A. S.; Dudarenko, N. A.; Melnikov, V. G.; Melnikov, G. I.

2018-05-01

In this paper we consider an autonomous mechanical system in a finite neighborhood of the zero of the phase space of states. The system is given as a matrix differential equation in the Cauchy form with the right-hand side of the polynomial structure. We propose a method for constructing a sequence of linear inhomogeneous differential inequalities for Lyapunov functions. As a result, we obtain estimates of transient processes in the form of functional inequalities.

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

Sivak, David; Crooks, Gavin

A fundamental problem in modern thermodynamics is how a molecular-scale machine performs useful work, while operating away from thermal equilibrium without excessive dissipation. To this end, we derive a friction tensor that induces a Riemannian manifold on the space of thermodynamic states. Within the linear-response regime, this metric structure controls the dissipation of finite-time transformations, and bestows optimal protocols with many useful properties. We discuss the connection to the existing thermodynamic length formalism, and demonstrate the utility of this metric by solving for optimal control parameter protocols in a simple nonequilibrium model.

Transition records of stationary Markov chains.

PubMed

Naudts, Jan; Van der Straeten, Erik

2006-10-01

In any Markov chain with finite state space the distribution of transition records always belongs to the exponential family. This observation is used to prove a fluctuation theorem, and to show that the dynamical entropy of a stationary Markov chain is linear in the number of steps. Three applications are discussed. A known result about entropy production is reproduced. A thermodynamic relation is derived for equilibrium systems with Metropolis dynamics. Finally, a link is made with recent results concerning a one-dimensional polymer model.

Markov and semi-Markov processes as a failure rate

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

Grabski, Franciszek

2016-06-08

In this paper the reliability function is defined by the stochastic failure rate process with a non negative and right continuous trajectories. Equations for the conditional reliability functions of an object, under assumption that the failure rate is a semi-Markov process with an at most countable state space are derived. A proper theorem is presented. The linear systems of equations for the appropriate Laplace transforms allow to find the reliability functions for the alternating, the Poisson and the Furry-Yule failure rate processes.

Active Vibration damping of Smart composite beams based on system identification technique

NASA Astrophysics Data System (ADS)

Bendine, Kouider; Satla, Zouaoui; Boukhoulda, Farouk Benallel; Nouari, Mohammed

2018-03-01

In the present paper, the active vibration control of a composite beam using piezoelectric actuator is investigated. The space state equation is determined using system identification technique based on the structure input output response provided by ANSYS APDL finite element package. The Linear Quadratic (LQG) control law is designed and integrated into ANSYS APDL to perform closed loop simulations. Numerical examples for different types of excitation loads are presented to test the efficiency and the accuracy of the proposed model.

Satellite Vegetation Index Data as a Tool to Forecast Population Dynamics of Medically Important Mosquitoes at Military Installations in the Continental United States

DTIC Science & Technology

2008-07-01

for the two installations. We obtained monthly North American normalized differ- ence vegetation index ( NDVI ) satellite climate data sets for 1981-2005...from the Goddard Space Flight Center."*-" The NDVI measures the greenness of the earth, capturing in one index the combined effects of temperature...humidity, insola- tion, elevation, soils, land use. and precipitation on vegeta- tion. There is an almost-linear relationship between NDVI values and

Probabilistic modeling of anatomical variability using a low dimensional parameterization of diffeomorphisms.

PubMed

Zhang, Miaomiao; Wells, William M; Golland, Polina

2017-10-01

We present an efficient probabilistic model of anatomical variability in a linear space of initial velocities of diffeomorphic transformations and demonstrate its benefits in clinical studies of brain anatomy. To overcome the computational challenges of the high dimensional deformation-based descriptors, we develop a latent variable model for principal geodesic analysis (PGA) based on a low dimensional shape descriptor that effectively captures the intrinsic variability in a population. We define a novel shape prior that explicitly represents principal modes as a multivariate complex Gaussian distribution on the initial velocities in a bandlimited space. We demonstrate the performance of our model on a set of 3D brain MRI scans from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database. Our model yields a more compact representation of group variation at substantially lower computational cost than the state-of-the-art method such as tangent space PCA (TPCA) and probabilistic principal geodesic analysis (PPGA) that operate in the high dimensional image space. Copyright © 2017 Elsevier B.V. All rights reserved.

Conformation-driven quantum interference effects mediated by through-space conjugation in self-assembled monolayers

NASA Astrophysics Data System (ADS)

Carlotti, Marco; Kovalchuk, Andrii; Wächter, Tobias; Qiu, Xinkai; Zharnikov, Michael; Chiechi, Ryan C.

2016-12-01

Tunnelling currents through tunnelling junctions comprising molecules with cross-conjugation are markedly lower than for their linearly conjugated analogues. This effect has been shown experimentally and theoretically to arise from destructive quantum interference, which is understood to be an intrinsic, electronic property of molecules. Here we show experimental evidence of conformation-driven interference effects by examining through-space conjugation in which π-conjugated fragments are arranged face-on or edge-on in sufficiently close proximity to interact through space. Observing these effects in the latter requires trapping molecules in a non-equilibrium conformation closely resembling the X-ray crystal structure, which we accomplish using self-assembled monolayers to construct bottom-up, large-area tunnelling junctions. In contrast, interference effects are completely absent in zero-bias simulations on the equilibrium, gas-phase conformation, establishing through-space conjugation as both of fundamental interest and as a potential tool for tuning tunnelling charge-transport in large-area, solid-state molecular-electronic devices.

Nonlinear spherical perturbations in quintessence models of dark energy

NASA Astrophysics Data System (ADS)

Pratap Rajvanshi, Manvendra; Bagla, J. S.

2018-06-01

Observations have confirmed the accelerated expansion of the universe. The accelerated expansion can be modelled by invoking a cosmological constant or a dynamical model of dark energy. A key difference between these models is that the equation of state parameter w for dark energy differs from ‑1 in dynamical dark energy (DDE) models. Further, the equation of state parameter is not constant for a general DDE model. Such differences can be probed using the variation of scale factor with time by measuring distances. Another significant difference between the cosmological constant and DDE models is that the latter must cluster. Linear perturbation analysis indicates that perturbations in quintessence models of dark energy do not grow to have a significant amplitude at small length scales. In this paper we study the response of quintessence dark energy to non-linear perturbations in dark matter. We use a fully relativistic model for spherically symmetric perturbations. In this study we focus on thawing models. We find that in response to non-linear perturbations in dark matter, dark energy perturbations grow at a faster rate than expected in linear perturbation theory. We find that dark energy perturbation remains localised and does not diffuse out to larger scales. The dominant drivers of the evolution of dark energy perturbations are the local Hubble flow and a supression of gradients of the scalar field. We also find that the equation of state parameter w changes in response to perturbations in dark matter such that it also becomes a function of position. The variation of w in space is correlated with density contrast for matter. Variation of w and perturbations in dark energy are more pronounced in response to large scale perturbations in matter while the dependence on the amplitude of matter perturbations is much weaker.

Generating log-normal mock catalog of galaxies in redshift space

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

Agrawal, Aniket; Makiya, Ryu; Saito, Shun

We present a public code to generate a mock galaxy catalog in redshift space assuming a log-normal probability density function (PDF) of galaxy and matter density fields. We draw galaxies by Poisson-sampling the log-normal field, and calculate the velocity field from the linearised continuity equation of matter fields, assuming zero vorticity. This procedure yields a PDF of the pairwise velocity fields that is qualitatively similar to that of N-body simulations. We check fidelity of the catalog, showing that the measured two-point correlation function and power spectrum in real space agree with the input precisely. We find that a linear biasmore » relation in the power spectrum does not guarantee a linear bias relation in the density contrasts, leading to a cross-correlation coefficient of matter and galaxies deviating from unity on small scales. We also find that linearising the Jacobian of the real-to-redshift space mapping provides a poor model for the two-point statistics in redshift space. That is, non-linear redshift-space distortion is dominated by non-linearity in the Jacobian. The power spectrum in redshift space shows a damping on small scales that is qualitatively similar to that of the well-known Fingers-of-God (FoG) effect due to random velocities, except that the log-normal mock does not include random velocities. This damping is a consequence of non-linearity in the Jacobian, and thus attributing the damping of the power spectrum solely to FoG, as commonly done in the literature, is misleading.« less

Localization of Stable and Chaotic Nonpropagating Structures in Nonlinear Mesoscopic Lattices.

NASA Astrophysics Data System (ADS)

Greenfield, Alan Barry

Recent developments in the study of non-linear localized states, especially non-propagating ones, are outlined. Theoretical models of linear and nonlinear states in a lattice of coupled pendulums and related systems are reviewed. Particular attention is paid to those states which can be described by the Nonlinear Schrodinger equation as well as states where two modes can coexist and states exhibiting chaos. Measurement of localized stable and chaotic states in a 35 site physical pendulum lattice is reported. Various measurement techniques that were used are explained. States that were measured include the tanh profile or kink soliton, and the corresponding uniform state in the wavelength 2 mode, a similar soliton and uniform state in the wavelength 4 mode, a domain wall between the wavelength 2 and 4 modes and a domain wall between a chaotic state and the wavelength 2 mode. Amplitude profiles were measured for the stable kink and domain wall states and smooth curves were obtained by dividing the kink states by the corresponding uniform states. Return maps were measured for two sites in the chaotic domain wall. Simulation of a chaotic domain wall in a 50 site numerical lattice is reported. This system has the advantage that its parameters can be modified much more easily than those of the physical lattice. An attempt is made at quantifying the level of chaos as a function of lattice site with fractal dimension calculations on return maps embedded in a three dimensional space. The drive plane of the chaotic domain wall is mapped out in the drive amplitude - drive frequency plane. Transitions to various stable and quasiperiodic domain walls are noted.

Design of cladding rods-assisted depressed-core few-mode fibers with improved modal spacing

NASA Astrophysics Data System (ADS)

Han, Jiawei; Zhang, Jie

2018-03-01

This paper investigates the design details of cladding rods-assisted (CRA) depressed-core (DC) few-mode fibers (FMFs) that feature more equally spaced linearly polarized (LP) modal effective indices, suitable for high-spatial-density weakly-coupled mode-division multiplexing systems. The influences of the index profile of cladding rods on LP mode-resolved effective index, bending sensitivity, and effective area Aeff, are numerically described. Based on the design considerations of LP modal Aeff-dependent spatial efficiency and LP modal bending loss-dependent robustness, the small LP21-LP02 and LP22-LP03 modal spacing limitations, encountered in state-of-the-art weakly-coupled step-index FMFs, have been substantially improved by at least 25%. In addition, the proposed CRA DC FMFs also show sufficiently large effective areas (in excess of 110 μm2) for all guided LP modes, which are expected to exhibit good nonlinear performance.

Quantum walks and wavepacket dynamics on a lattice with twisted photons.

PubMed

Cardano, Filippo; Massa, Francesco; Qassim, Hammam; Karimi, Ebrahim; Slussarenko, Sergei; Paparo, Domenico; de Lisio, Corrado; Sciarrino, Fabio; Santamato, Enrico; Boyd, Robert W; Marrucci, Lorenzo

2015-03-01

The "quantum walk" has emerged recently as a paradigmatic process for the dynamic simulation of complex quantum systems, entanglement production and quantum computation. Hitherto, photonic implementations of quantum walks have mainly been based on multipath interferometric schemes in real space. We report the experimental realization of a discrete quantum walk taking place in the orbital angular momentum space of light, both for a single photon and for two simultaneous photons. In contrast to previous implementations, the whole process develops in a single light beam, with no need of interferometers; it requires optical resources scaling linearly with the number of steps; and it allows flexible control of input and output superposition states. Exploiting the latter property, we explored the system band structure in momentum space and the associated spin-orbit topological features by simulating the quantum dynamics of Gaussian wavepackets. Our demonstration introduces a novel versatile photonic platform for quantum simulations.

Quantum walks and wavepacket dynamics on a lattice with twisted photons

PubMed Central

Cardano, Filippo; Massa, Francesco; Qassim, Hammam; Karimi, Ebrahim; Slussarenko, Sergei; Paparo, Domenico; de Lisio, Corrado; Sciarrino, Fabio; Santamato, Enrico; Boyd, Robert W.; Marrucci, Lorenzo

2015-01-01

The “quantum walk” has emerged recently as a paradigmatic process for the dynamic simulation of complex quantum systems, entanglement production and quantum computation. Hitherto, photonic implementations of quantum walks have mainly been based on multipath interferometric schemes in real space. We report the experimental realization of a discrete quantum walk taking place in the orbital angular momentum space of light, both for a single photon and for two simultaneous photons. In contrast to previous implementations, the whole process develops in a single light beam, with no need of interferometers; it requires optical resources scaling linearly with the number of steps; and it allows flexible control of input and output superposition states. Exploiting the latter property, we explored the system band structure in momentum space and the associated spin-orbit topological features by simulating the quantum dynamics of Gaussian wavepackets. Our demonstration introduces a novel versatile photonic platform for quantum simulations. PMID:26601157

Method for hue plane preserving color correction.

PubMed

Mackiewicz, Michal; Andersen, Casper F; Finlayson, Graham

2016-11-01

Hue plane preserving color correction (HPPCC), introduced by Andersen and Hardeberg [Proceedings of the 13th Color and Imaging Conference (CIC) (2005), pp. 141-146], maps device-dependent color values (RGB) to colorimetric color values (XYZ) using a set of linear transforms, realized by white point preserving 3×3 matrices, where each transform is learned and applied in a subregion of color space, defined by two adjacent hue planes. The hue plane delimited subregions of camera RGB values are mapped to corresponding hue plane delimited subregions of estimated colorimetric XYZ values. Hue planes are geometrical half-planes, where each is defined by the neutral axis and a chromatic color in a linear color space. The key advantage of the HPPCC method is that, while offering an estimation accuracy of higher order methods, it maintains the linear colorimetric relations of colors in hue planes. As a significant result, it therefore also renders the colorimetric estimates invariant to exposure and shading of object reflection. In this paper, we present a new flexible and robust version of HPPCC using constrained least squares in the optimization, where the subregions can be chosen freely in number and position in order to optimize the results while constraining transform continuity at the subregion boundaries. The method is compared to a selection of other state-of-the-art characterization methods, and the results show that it outperforms the original HPPCC method.

Dynamical transitions in large systems of mean field-coupled Landau-Stuart oscillators: Extensive chaos and cluster states.

PubMed

Ku, Wai Lim; Girvan, Michelle; Ott, Edward

2015-12-01

In this paper, we study dynamical systems in which a large number N of identical Landau-Stuart oscillators are globally coupled via a mean-field. Previously, it has been observed that this type of system can exhibit a variety of different dynamical behaviors. These behaviors include time periodic cluster states in which each oscillator is in one of a small number of groups for which all oscillators in each group have the same state which is different from group to group, as well as a behavior in which all oscillators have different states and the macroscopic dynamics of the mean field is chaotic. We argue that this second type of behavior is "extensive" in the sense that the chaotic attractor in the full phase space of the system has a fractal dimension that scales linearly with N and that the number of positive Lyapunov exponents of the attractor also scales linearly with N. An important focus of this paper is the transition between cluster states and extensive chaos as the system is subjected to slow adiabatic parameter change. We observe discontinuous transitions between the cluster states (which correspond to low dimensional dynamics) and the extensively chaotic states. Furthermore, examining the cluster state, as the system approaches the discontinuous transition to extensive chaos, we find that the oscillator population distribution between the clusters continually evolves so that the cluster state is always marginally stable. This behavior is used to reveal the mechanism of the discontinuous transition. We also apply the Kaplan-Yorke formula to study the fractal structure of the extensively chaotic attractors.

Dynamical transitions in large systems of mean field-coupled Landau-Stuart oscillators: Extensive chaos and cluster states

NASA Astrophysics Data System (ADS)

Ku, Wai Lim; Girvan, Michelle; Ott, Edward

2015-12-01

In this paper, we study dynamical systems in which a large number N of identical Landau-Stuart oscillators are globally coupled via a mean-field. Previously, it has been observed that this type of system can exhibit a variety of different dynamical behaviors. These behaviors include time periodic cluster states in which each oscillator is in one of a small number of groups for which all oscillators in each group have the same state which is different from group to group, as well as a behavior in which all oscillators have different states and the macroscopic dynamics of the mean field is chaotic. We argue that this second type of behavior is "extensive" in the sense that the chaotic attractor in the full phase space of the system has a fractal dimension that scales linearly with N and that the number of positive Lyapunov exponents of the attractor also scales linearly with N. An important focus of this paper is the transition between cluster states and extensive chaos as the system is subjected to slow adiabatic parameter change. We observe discontinuous transitions between the cluster states (which correspond to low dimensional dynamics) and the extensively chaotic states. Furthermore, examining the cluster state, as the system approaches the discontinuous transition to extensive chaos, we find that the oscillator population distribution between the clusters continually evolves so that the cluster state is always marginally stable. This behavior is used to reveal the mechanism of the discontinuous transition. We also apply the Kaplan-Yorke formula to study the fractal structure of the extensively chaotic attractors.

Quality-by-Design (QbD): An integrated process analytical technology (PAT) approach for a dynamic pharmaceutical co-precipitation process characterization and process design space development.

PubMed

Wu, Huiquan; White, Maury; Khan, Mansoor A

2011-02-28

The aim of this work was to develop an integrated process analytical technology (PAT) approach for a dynamic pharmaceutical co-precipitation process characterization and design space development. A dynamic co-precipitation process by gradually introducing water to the ternary system of naproxen-Eudragit L100-alcohol was monitored at real-time in situ via Lasentec FBRM and PVM. 3D map of count-time-chord length revealed three distinguishable process stages: incubation, transition, and steady-state. The effects of high risk process variables (slurry temperature, stirring rate, and water addition rate) on both derived co-precipitation process rates and final chord-length-distribution were evaluated systematically using a 3(3) full factorial design. Critical process variables were identified via ANOVA for both transition and steady state. General linear models (GLM) were then used for parameter estimation for each critical variable. Clear trends about effects of each critical variable during transition and steady state were found by GLM and were interpreted using fundamental process principles and Nyvlt's transfer model. Neural network models were able to link process variables with response variables at transition and steady state with R(2) of 0.88-0.98. PVM images evidenced nucleation and crystal growth. Contour plots illustrated design space via critical process variables' ranges. It demonstrated the utility of integrated PAT approach for QbD development. Published by Elsevier B.V.

Genetic Algorithm-Guided, Adaptive Model Order Reduction of Flexible Aircrafts

NASA Technical Reports Server (NTRS)

Zhu, Jin; Wang, Yi; Pant, Kapil; Suh, Peter; Brenner, Martin J.

2017-01-01

This paper presents a methodology for automated model order reduction (MOR) of flexible aircrafts to construct linear parameter-varying (LPV) reduced order models (ROM) for aeroservoelasticity (ASE) analysis and control synthesis in broad flight parameter space. The novelty includes utilization of genetic algorithms (GAs) to automatically determine the states for reduction while minimizing the trial-and-error process and heuristics requirement to perform MOR; balanced truncation for unstable systems to achieve locally optimal realization of the full model; congruence transformation for "weak" fulfillment of state consistency across the entire flight parameter space; and ROM interpolation based on adaptive grid refinement to generate a globally functional LPV ASE ROM. The methodology is applied to the X-56A MUTT model currently being tested at NASA/AFRC for flutter suppression and gust load alleviation. Our studies indicate that X-56A ROM with less than one-seventh the number of states relative to the original model is able to accurately predict system response among all input-output channels for pitch, roll, and ASE control at various flight conditions. The GA-guided approach exceeds manual and empirical state selection in terms of efficiency and accuracy. The adaptive refinement allows selective addition of the grid points in the parameter space where flight dynamics varies dramatically to enhance interpolation accuracy without over-burdening controller synthesis and onboard memory efforts downstream. The present MOR framework can be used by control engineers for robust ASE controller synthesis and novel vehicle design.

Time domain simulation of harmonic ultrasound images and beam patterns in 3D using the k-space pseudospectral method.

PubMed

Treeby, Bradley E; Tumen, Mustafa; Cox, B T

2011-01-01

A k-space pseudospectral model is developed for the fast full-wave simulation of nonlinear ultrasound propagation through heterogeneous media. The model uses a novel equation of state to account for nonlinearity in addition to power law absorption. The spectral calculation of the spatial gradients enables a significant reduction in the number of required grid nodes compared to finite difference methods. The model is parallelized using a graphical processing unit (GPU) which allows the simulation of individual ultrasound scan lines using a 256 x 256 x 128 voxel grid in less than five minutes. Several numerical examples are given, including the simulation of harmonic ultrasound images and beam patterns using a linear phased array transducer.

Frequency domain system identification methods - Matrix fraction description approach

NASA Technical Reports Server (NTRS)

Horta, Luca G.; Juang, Jer-Nan

1993-01-01

This paper presents the use of matrix fraction descriptions for least-squares curve fitting of the frequency spectra to compute two matrix polynomials. The matrix polynomials are intermediate step to obtain a linearized representation of the experimental transfer function. Two approaches are presented: first, the matrix polynomials are identified using an estimated transfer function; second, the matrix polynomials are identified directly from the cross/auto spectra of the input and output signals. A set of Markov parameters are computed from the polynomials and subsequently realization theory is used to recover a minimum order state space model. Unevenly spaced frequency response functions may be used. Results from a simple numerical example and an experiment are discussed to highlight some of the important aspect of the algorithm.

An Approach to Assess Observation Impact Based on Observation-Minus-Forecast Residuals

NASA Technical Reports Server (NTRS)

Todling, Ricardo

2009-01-01

Langland and Baker (2004) introduced an approach to assess the impact of observations on the forecasts. In that, a state-space aspect of the forecast is defined and a procedure is derived that relates changes in the aspect with changes in the initial conditions associated with the assimilation of observations) ultimately providing information about the impact of individual observations on the forecast. Some features of the approach are to be noted. The typical choice of forecast aspect employed in related works is rather arbitrary and leads to an incomplete assessment of the observing system. Furthermore, the state-space forecast aspect requires availability of a verification state that should ideally be uncorrelated with the forecast but in practice is not. Lastly, the approach involves the adjoint operator of the entire data assimilation system and as such it is constrained by the validity of this operator. In this presentation, an observation-space metric is used that, for a relatively time-homogeneous observing system, allows inferring observation impact on the forecast without some of the limitations above. Specifically, using observation-minus-forecast residuals leads to an approach with the following features: (i) it suggests a rather natural choice of forecast aspect, directly linked to the analysis system and providing full assessment of the observations; (ii) it naturally avoids introducing undesirable correlations in the forecast aspect by verifying against the observations; and (iii) it does not involve linearization and use of adjoints; therefore being applicable to any length of forecast. The state and observation-space approaches might be complementary to some degree, and involve different limitations and complexities. Illustrations are given using the NASA GEOS-5 data.

MIST - MINIMUM-STATE METHOD FOR RATIONAL APPROXIMATION OF UNSTEADY AERODYNAMIC FORCE COEFFICIENT MATRICES

NASA Technical Reports Server (NTRS)

Karpel, M.

1994-01-01

Various control analysis, design, and simulation techniques of aeroservoelastic systems require the equations of motion to be cast in a linear, time-invariant state-space form. In order to account for unsteady aerodynamics, rational function approximations must be obtained to represent them in the first order equations of the state-space formulation. A computer program, MIST, has been developed which determines minimum-state approximations of the coefficient matrices of the unsteady aerodynamic forces. The Minimum-State Method facilitates the design of lower-order control systems, analysis of control system performance, and near real-time simulation of aeroservoelastic phenomena such as the outboard-wing acceleration response to gust velocity. Engineers using this program will be able to calculate minimum-state rational approximations of the generalized unsteady aerodynamic forces. Using the Minimum-State formulation of the state-space equations, they will be able to obtain state-space models with good open-loop characteristics while reducing the number of aerodynamic equations by an order of magnitude more than traditional approaches. These low-order state-space mathematical models are good for design and simulation of aeroservoelastic systems. The computer program, MIST, accepts tabular values of the generalized aerodynamic forces over a set of reduced frequencies. It then determines approximations to these tabular data in the LaPlace domain using rational functions. MIST provides the capability to select the denominator coefficients in the rational approximations, to selectably constrain the approximations without increasing the problem size, and to determine and emphasize critical frequency ranges in determining the approximations. MIST has been written to allow two types data weighting options. The first weighting is a traditional normalization of the aerodynamic data to the maximum unit value of each aerodynamic coefficient. The second allows weighting the importance of different tabular values in determining the approximations based upon physical characteristics of the system. Specifically, the physical weighting capability is such that each tabulated aerodynamic coefficient, at each reduced frequency value, is weighted according to the effect of an incremental error of this coefficient on aeroelastic characteristics of the system. In both cases, the resulting approximations yield a relatively low number of aerodynamic lag states in the subsequent state-space model. MIST is written in ANSI FORTRAN 77 for DEC VAX series computers running VMS. It requires approximately 1Mb of RAM for execution. The standard distribution medium for this package is a 9-track 1600 BPI magnetic tape in DEC VAX FILES-11 format. It is also available on a TK50 tape cartridge in DEC VAX BACKUP format. MIST was developed in 1991. DEC VAX and VMS are trademarks of Digital Equipment Corporation. FORTRAN 77 is a registered trademark of Lahey Computer Systems, Inc.

Linear Clouds

NASA Technical Reports Server (NTRS)

2006-01-01

[figure removed for brevity, see original site] Context image for PIA03667 Linear Clouds

These clouds are located near the edge of the south polar region. The cloud tops are the puffy white features in the bottom half of the image.

Image information: VIS instrument. Latitude -80.1N, Longitude 52.1E. 17 meter/pixel resolution.

Note: this THEMIS visual image has not been radiometrically nor geometrically calibrated for this preliminary release. An empirical correction has been performed to remove instrumental effects. A linear shift has been applied in the cross-track and down-track direction to approximate spacecraft and planetary motion. Fully calibrated and geometrically projected images will be released through the Planetary Data System in accordance with Project policies at a later time.

NASA's Jet Propulsion Laboratory manages the 2001 Mars Odyssey mission for NASA's Office of Space Science, Washington, D.C. The Thermal Emission Imaging System (THEMIS) was developed by Arizona State University, Tempe, in collaboration with Raytheon Santa Barbara Remote Sensing. The THEMIS investigation is led by Dr. Philip Christensen at Arizona State University. Lockheed Martin Astronautics, Denver, is the prime contractor for the Odyssey project, and developed and built the orbiter. Mission operations are conducted jointly from Lockheed Martin and from JPL, a division of the California Institute of Technology in Pasadena.

Thermodynamic description of Hofmeister effects on the LCST of thermosensitive polymers.

PubMed

Heyda, Jan; Dzubiella, Joachim

2014-09-18

Cosolvent effects on protein or polymer collapse transitions are typically discussed in terms of a two-state free energy change that is strictly linear in cosolute concentration. Here we investigate in detail the nonlinear thermodynamic changes of the collapse transition occurring at the lower critical solution temperature (LCST) of the role-model polymer poly(N-isopropylacrylamide) [PNIPAM] induced by Hofmeister salts. First, we establish an equation, based on the second-order expansion of the two-state free energy in concentration and temperature space, which excellently fits the experimental LCST curves and enables us to directly extract the corresponding thermodynamic parameters. Linear free energy changes, grounded on generic excluded-volume mechanisms, are indeed found for strongly hydrated kosmotropes. In contrast, for weakly hydrated chaotropes, we find significant nonlinear changes related to higher order thermodynamic derivatives of the preferential interaction parameter between salts and polymer. The observed non-monotonic behavior of the LCST can then be understood from a not yet recognized sign change of the preferential interaction parameter with salt concentration. Finally, we find that solute partitioning models can possibly predict the linear free energy changes for the kosmotropes, but fail for chaotropes. Our findings cast strong doubt on their general applicability to protein unfolding transitions induced by chaotropes.

Direct k-space imaging of Mahan cones at clean and Bi-covered Cu(111) surfaces

NASA Astrophysics Data System (ADS)

Winkelmann, Aimo; Akin Ünal, A.; Tusche, Christian; Ellguth, Martin; Chiang, Cheng-Tien; Kirschner, Jürgen

2012-08-01

Using a specifically tailored experimental approach, we revisit the exemplary effect of photoemission from quasi-free electronic states in crystals. Applying a momentum microscope, we measure photoelectron momentum patterns emitted into the complete half-space above the sample after excitation from a linearly polarized laser light source. By the application of a fully three-dimensional (3D) geometrical model of direct optical transitions, we explain the characteristic intensity distributions that are formed by the photoelectrons in k-space under the combination of energy conservation and crystal momentum conservation in the 3D bulk as well as at the two-dimensional (2D) surface. For bismuth surface alloys on Cu(111), the energy-resolved photoelectron momentum patterns allow us to identify specific emission processes in which bulk excited electrons are subsequently diffracted by an atomic 2D surface grating. The polarization dependence of the observed intensity features in momentum space is explained based on the different relative orientations of characteristic reciprocal space directions with respect to the electric field vector of the incident light.

Velocity-gauge real-time TDDFT within a numerical atomic orbital basis set

DOE PAGES

Pemmaraju, C. D.; Vila, F. D.; Kas, J. J.; ...

2018-02-07

The interaction of laser fields with solid-state systems can be modeled efficiently within the velocity-gauge formalism of real-time time dependent density functional theory (RT-TDDFT). In this article, we discuss the implementation of the velocity-gauge RT-TDDFT equations for electron dynamics within a linear combination of atomic orbitals (LCAO) basis set framework. Numerical results obtained from our LCAO implementation, for the electronic response of periodic systems to both weak and intense laser fields, are compared to those obtained from established real-space grid and Full-Potential Linearized Augmented Planewave approaches. As a result, potential applications of the LCAO based scheme in the context ofmore » extreme ultra-violet and soft X-ray spectroscopies involving core-electronic excitations are discussed.« less

Testing the scalar sector of the twin Higgs model at colliders

NASA Astrophysics Data System (ADS)

Chacko, Zackaria; Kilic, Can; Najjari, Saereh; Verhaaren, Christopher B.

2018-03-01

We consider mirror twin Higgs models in which the breaking of the global symmetry is realized linearly. In this scenario, the radial mode in the Higgs potential is present in the spectrum and constitutes a second portal between the twin and SM sectors. We show that a study of the properties of this particle at colliders, when combined with precision measurements of the light Higgs, can be used to overdetermine the form of the scalar potential, thereby confirming that it possesses an enhanced global symmetry as dictated by the twin Higgs mechanism. We find that, although the reach of the LHC for this state is limited, future linear colliders will be able to explore a significant part of the preferred parameter space, allowing the possibility of directly testing the twin Higgs framework.

Velocity-gauge real-time TDDFT within a numerical atomic orbital basis set

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

Pemmaraju, C. D.; Vila, F. D.; Kas, J. J.

The interaction of laser fields with solid-state systems can be modeled efficiently within the velocity-gauge formalism of real-time time dependent density functional theory (RT-TDDFT). In this article, we discuss the implementation of the velocity-gauge RT-TDDFT equations for electron dynamics within a linear combination of atomic orbitals (LCAO) basis set framework. Numerical results obtained from our LCAO implementation, for the electronic response of periodic systems to both weak and intense laser fields, are compared to those obtained from established real-space grid and Full-Potential Linearized Augmented Planewave approaches. As a result, potential applications of the LCAO based scheme in the context ofmore » extreme ultra-violet and soft X-ray spectroscopies involving core-electronic excitations are discussed.« less

An exact solution of the van der Waals interaction between two ground-state hydrogen atoms

NASA Astrophysics Data System (ADS)

Koga, Toshikatsu; Matsumoto, Shinya

1985-06-01

A momentum space treatment shows that perturbation equations for the H(1s)-H(1s) van der Waals interaction can be exactly solved in their Schrödinger forms without invoking any variational methods. Using the Fock transformation, which projects the momentum vector of an electron from the three-dimensional hyperplane onto the four-dimensional hypersphere, we solve the third order integral-type perturbation equation with respect to the reciprocal of the internuclear distance R. An exact third order wave function is found as a linear combination of infinite number of four-dimensional spherical harmonics. The result allows us to evaluate the exact dispersion energy E6R-6, which is completely determined by the first three coefficients of the above linear combination.

Dynamic analysis of Free-Piston Stirling Engine/Linear Alternator-load system-experimentally validated

NASA Technical Reports Server (NTRS)

Kankam, M. David; Rauch, Jeffrey S.; Santiago, Walter

1992-01-01

This paper discusses the effects of variations in system parameters on the dynamic behavior of the Free-Piston Stirling Engine/Linear Alternator (FPSE/LA)-load system. The mathematical formulations incorporate both the mechanical and thermodynamic properties of the FPSE, as well as the electrical equations of the connected load. A state-space technique in the frequency domain is applied to the resulting system of equations to facilitate the evaluation of parametric impacts on the system dynamic stability. Also included is a discussion on the system transient stability as affected by sudden changes in some key operating conditions. Some representative results are correlated with experimental data to verify the model and analytic formulation accuracies. Guidelines are given for ranges of the system parameters which will ensure an overall stable operation.

Dynamic analysis of free-piston Stirling engine/linear alternator-load system - Experimentally validated

NASA Technical Reports Server (NTRS)

Kankam, M. D.; Rauch, Jeffrey S.; Santiago, Walter

1992-01-01

This paper discusses the effects of a variations in system parameters on the dynamic behavior of a Free-Piston Stirling Engine/Linear Alternator (FPSE/LA)-load system. The mathematical formulations incorporates both the mechanical and thermodynamic properties of the FPSE, as well as the electrical equations of the connected load. State-space technique in the frequency domain is applied to the resulting system of equations to facilitate the evaluation of parametric impacts on the system dynamic stability. Also included is a discussion on the system transient stability as affected by sudden changes in some key operating conditions. Some representative results are correlated with experimental data to verify the model and analytic formulation accuracies. Guidelines are given for ranges of the system parameters which will ensure an overall stable operation.

The Linear Parameters and the Decoupling Matrix for Linearly Coupled Motion in 6 Dimensional Phase Space

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

Parzen, George

It will be shown that starting from a coordinate system where the 6 phase space coordinates are linearly coupled, one can go to a new coordinate system, where the motion is uncoupled, by means of a linear transformation. The original coupled coordinates and the new uncoupled coordinates are related by a 6 x 6 matrix, R. R will be called the decoupling matrix. It will be shown that of the 36 elements of the 6 x 6 decoupling matrix R, only 12 elements are independent. This may be contrasted with the results for motion in 4- dimensional phase space, wheremore » R has 4 independent elements. A set of equations is given from which the 12 elements of R can be computed from the one period transfer matrix. This set of equations also allows the linear parameters, the β i,α i, i = 1, 3, for the uncoupled coordinates, to be computed from the one period transfer matrix. An alternative procedure for computing the linear parameters,β i,α i, i = 1, 3, and the 12 independent elements of the decoupling matrix R is also given which depends on computing the eigenvectors of the one period transfer matrix. These results can be used in a tracking program, where the one period transfer matrix can be computed by multiplying the transfer matrices of all the elements in a period, to compute the linear parameters α i and β i, i = 1, 3, and the elements of the decoupling matrix R. The procedure presented here for studying coupled motion in 6-dimensional phase space can also be applied to coupled motion in 4-dimensional phase space, where it may be a useful alternative procedure to the procedure presented by Edwards and Teng. In particular, it gives a simpler programing procedure for computing the beta functions and the emittances for coupled motion in 4-dimensional phase space.« less

The linear parameters and the decoupling matrix for linearly coupled motion in 6 dimensional phase space. Informal report

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

Parzen, G.

It will be shown that starting from a coordinate system where the 6 phase space coordinates are linearly coupled, one can go to a new coordinate system, where the motion is uncoupled, by means of a linear transformation. The original coupled coordinates and the new uncoupled coordinates are related by a 6 {times} 6 matrix, R. R will be called the decoupling matrix. It will be shown that of the 36 elements of the 6 {times} 6 decoupling matrix R, only 12 elements are independent. This may be contrasted with the results for motion in 4-dimensional phase space, where Rmore » has 4 independent elements. A set of equations is given from which the 12 elements of R can be computed from the one period transfer matrix. This set of equations also allows the linear parameters, {beta}{sub i}, {alpha}{sub i} = 1, 3, for the uncoupled coordinates, to be computed from the one period transfer matrix. An alternative procedure for computing the linear parameters, the {beta}{sub i}, {alpha}{sub i} i = 1, 3, and the 12 independent elements of the decoupling matrix R is also given which depends on computing the eigenvectors of the one period transfer matrix. These results can be used in a tracking program, where the one period transfer matrix can be computed by multiplying the transfer matrices of all the elements in a period, to compute the linear parameters {alpha}{sub i} and {beta}{sub i}, i = 1, 3, and the elements of the decoupling matrix R. The procedure presented here for studying coupled motion in 6-dimensional phase space can also be applied to coupled motion in 4-dimensional phase space, where it may be a useful alternative procedure to the procedure presented by Edwards and Teng. In particular, it gives a simpler programming procedure for computing the beta functions and the emittances for coupled motion in 4-dimensional phase space.« less

Segmented strings in AdS 3

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

Callebaut, Nele; Gubser, Steven S.; Samberg, Andreas

We study segmented strings in flat space and in AdS 3. In flat space, these well known classical motions describe strings which at any instant of time are piecewise linear. In AdS 3, the worldsheet is composed of faces each of which is a region bounded by null geodesics in an AdS 2 subspace of AdS 3. The time evolution can be described by specifying the null geodesic motion of kinks in the string at which two segments are joined. The outcome of collisions of kinks on the worldsheet can be worked out essentially using considerations of causality. We studymore » several examples of closed segmented strings in AdS 3 and find an unexpected quasi-periodic behavior. Here, we also work out a WKB analysis of quantum states of yo-yo strings in AdS 5 and find a logarithmic term reminiscent of the logarithmic twist of string states on the leading Regge trajectory.« less

Segmented strings in AdS 3

DOE PAGES

Callebaut, Nele; Gubser, Steven S.; Samberg, Andreas; ...

2015-11-17

We study segmented strings in flat space and in AdS 3. In flat space, these well known classical motions describe strings which at any instant of time are piecewise linear. In AdS 3, the worldsheet is composed of faces each of which is a region bounded by null geodesics in an AdS 2 subspace of AdS 3. The time evolution can be described by specifying the null geodesic motion of kinks in the string at which two segments are joined. The outcome of collisions of kinks on the worldsheet can be worked out essentially using considerations of causality. We studymore » several examples of closed segmented strings in AdS 3 and find an unexpected quasi-periodic behavior. Here, we also work out a WKB analysis of quantum states of yo-yo strings in AdS 5 and find a logarithmic term reminiscent of the logarithmic twist of string states on the leading Regge trajectory.« less

Efficient Transition Probability Computation for Continuous-Time Branching Processes via Compressed Sensing.

PubMed

Xu, Jason; Minin, Vladimir N

2015-07-01

Branching processes are a class of continuous-time Markov chains (CTMCs) with ubiquitous applications. A general difficulty in statistical inference under partially observed CTMC models arises in computing transition probabilities when the discrete state space is large or uncountable. Classical methods such as matrix exponentiation are infeasible for large or countably infinite state spaces, and sampling-based alternatives are computationally intensive, requiring integration over all possible hidden events. Recent work has successfully applied generating function techniques to computing transition probabilities for linear multi-type branching processes. While these techniques often require significantly fewer computations than matrix exponentiation, they also become prohibitive in applications with large populations. We propose a compressed sensing framework that significantly accelerates the generating function method, decreasing computational cost up to a logarithmic factor by only assuming the probability mass of transitions is sparse. We demonstrate accurate and efficient transition probability computations in branching process models for blood cell formation and evolution of self-replicating transposable elements in bacterial genomes.

Application of fault factor method to fault detection and diagnosis for space shuttle main engine

NASA Astrophysics Data System (ADS)

Cha, Jihyoung; Ha, Chulsu; Ko, Sangho; Koo, Jaye

2016-09-01

This paper deals with an application of the multiple linear regression algorithm to fault detection and diagnosis for the space shuttle main engine (SSME) during a steady state. In order to develop the algorithm, the energy balance equations, which balances the relation among pressure, mass flow rate and power at various locations within the SSME, are obtained. Then using the measurement data of some important parameters of the engine, fault factors which reflects the deviation of each equation from the normal state are estimated. The probable location of each fault and the levels of severity can be obtained from the estimated fault factors. This process is numerically demonstrated for the SSME at 104% Rated Propulsion Level (RPL) by using the simulated measurement data from the mathematical models of the engine. The result of the current study is particularly important considering that the recently developed reusable Liquid Rocket Engines (LREs) have staged-combustion cycles similarly to the SSME.

Efficient Transition Probability Computation for Continuous-Time Branching Processes via Compressed Sensing

PubMed Central

Xu, Jason; Minin, Vladimir N.

2016-01-01

Branching processes are a class of continuous-time Markov chains (CTMCs) with ubiquitous applications. A general difficulty in statistical inference under partially observed CTMC models arises in computing transition probabilities when the discrete state space is large or uncountable. Classical methods such as matrix exponentiation are infeasible for large or countably infinite state spaces, and sampling-based alternatives are computationally intensive, requiring integration over all possible hidden events. Recent work has successfully applied generating function techniques to computing transition probabilities for linear multi-type branching processes. While these techniques often require significantly fewer computations than matrix exponentiation, they also become prohibitive in applications with large populations. We propose a compressed sensing framework that significantly accelerates the generating function method, decreasing computational cost up to a logarithmic factor by only assuming the probability mass of transitions is sparse. We demonstrate accurate and efficient transition probability computations in branching process models for blood cell formation and evolution of self-replicating transposable elements in bacterial genomes. PMID:26949377

A low-order model of the equatorial ocean-atmosphere system

NASA Astrophysics Data System (ADS)

Legnani, Roberto

A low order model of the equatorial ocean-atmosphere coupled system is presented. The model atmosphere includes a hydrological cycle with cloud-radiation interaction. The model ocean is based on mixed layer dynamics with a parameterization of entrainment processes. The coupling takes place via transfer to momentum, sensible heat, latent heat and short wave and long wave radiation through the ocean surface. The dynamical formulation is that of the primitive equations of an equatorial beta-plane, with zonally periodic and meridionally infinite geometry. The system is expanded into the set of normal modes pertinent to the linear problem and severly truncated to a few modes; 54 degrees of freedom are retained. Some nonlinear terms of the equations are evaluated in physical space and then projected onto the functional space; other terms are evaluated directly in the functional space. Sensitivity tests to variations of the parameters are performed, and some results from 10-year initial value simulations are presented. The model is capable of supporting oscillations of different time scales, ranging from a few days to a few years; it prefers a particular zonally asymmetric state, but temporarily switches to a different (opposite) zonally asymmetric state in an event-like fashion.

a Low-Order Model of the Equatorial Ocean-Atmosphere System.

NASA Astrophysics Data System (ADS)

Legnani, Roberto

A low order model of the equatorial ocean-atmosphere coupled system is presented. The model atmosphere includes a hydrological cycle with cloud-radiation interaction. The model ocean is based on mixed layer dynamics with a parameterization of entrainment processes. The coupling takes place via transfer to momentum, sensible heat, latent heat and short -wave and long-wave radiation through the ocean surface. The dynamical formulation is that of the primitive equations of an equatorial beta-plane, with zonally periodic and meridionally infinite geometry. The system is expanded into the set of normal modes pertinent to the linear problem and severely truncated to a few modes; 54 degrees of freedom are retained. Some nonlinear terms of the equations are evaluated in physical space and then projected onto the functional space; other terms are evaluated directly in the functional space. Sensitivity tests to variations of the parameters are performed, and some results from 10-year initial value simulations are presented. The model is capable of supporting oscillations of different time scales, ranging from a few days to a few years; it prefers a particular zonally asymmetric state, but temporarily switches to a different (opposite) zonally asymmetric state in an event-like fashion.

The Effects of Space Radiation on Linear Integrated Circuit

NASA Technical Reports Server (NTRS)

Johnston, A.

2000-01-01

Permanent and transient effects are discussed that are induced in linear integrated circuits by space radiation. Recent developments include enhanced damage at low dose rate, increased damage from protons due to displacement effects, and transients in digital comparators that can cause circuit malfunctions.

Adaptive matching of the iota ring linear optics for space charge compensation

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

Romanov, A.; Bruhwiler, D. L.; Cook, N.

Many present and future accelerators must operate with high intensity beams when distortions induced by space charge forces are among major limiting factors. Betatron tune depression of above approximately 0.1 per cell leads to significant distortions of linear optics. Many aspects of machine operation depend on proper relations between lattice functions and phase advances, and can be i proved with proper treatment of space charge effects. We implement an adaptive algorithm for linear lattice re matching with full account of space charge in the linear approximation for the case of Fermilab’s IOTA ring. The method is based on a searchmore » for initial second moments that give closed solution and, at the same predefined set of goals for emittances, beta functions, dispersions and phase advances at and between points of interest. Iterative singular value decomposition based technique is used to search for optimum by varying wide array of model parameters« less

A Few New 2+1-Dimensional Nonlinear Dynamics and the Representation of Riemann Curvature Tensors

NASA Astrophysics Data System (ADS)

Wang, Yan; Zhang, Yufeng; Zhang, Xiangzhi

2016-09-01

We first introduced a linear stationary equation with a quadratic operator in ∂x and ∂y, then a linear evolution equation is given by N-order polynomials of eigenfunctions. As applications, by taking N=2, we derived a (2+1)-dimensional generalized linear heat equation with two constant parameters associative with a symmetric space. When taking N=3, a pair of generalized Kadomtsev-Petviashvili equations with the same eigenvalues with the case of N=2 are generated. Similarly, a second-order flow associative with a homogeneous space is derived from the integrability condition of the two linear equations, which is a (2+1)-dimensional hyperbolic equation. When N=3, the third second flow associative with the homogeneous space is generated, which is a pair of new generalized Kadomtsev-Petviashvili equations. Finally, as an application of a Hermitian symmetric space, we established a pair of spectral problems to obtain a new (2+1)-dimensional generalized Schrödinger equation, which is expressed by the Riemann curvature tensors.

Magnetic susceptibility of Inconel alloys 718, 625, and 600 at cryogenic temperatures

NASA Technical Reports Server (NTRS)

Goldberg, Ira B.; Mitchell, Michael R.; Murphy, Allan R.; Goldfarb, Ronald B.; Loughran, Robert J.

1990-01-01

After a hydrogen fuel bleed valve problem on the Discovery Space Shuttle was traced to the strong magnetization of Inconel 718 in the armature of the linear variable differential transformer near liquid hydrogen temperatures, the ac magnetic susceptibility of three samples of Inconel 718 of slightly different compositions, one sample of Inconel 625, and on sample of Inconel 600 were measured as a function of temperature. Inconel 718 alloys are found to exhibit a spin glass state below 16 K. Inconel 600 exhibits three different magnetic phases, the lowest-temperature state (below 6 K) being somewhat similar to that of Inconel 718. The magnetic states of the Inconel alloys and their magnetic susceptibilities appear to be strongly dependent on the exact composition of the alloy.

Turbulent Motion of Liquids in Hydraulic Resistances with a Linear Cylindrical Slide-Valve

PubMed Central

Velescu, C.; Popa, N. C.

2015-01-01

We analyze the motion of viscous and incompressible liquids in the annular space of controllable hydraulic resistances with a cylindrical linear slide-valve. This theoretical study focuses on the turbulent and steady-state motion regimes. The hydraulic resistances mentioned above are the most frequent type of hydraulic resistances used in hydraulic actuators and automation systems. To study the liquids' motion in the controllable hydraulic resistances with a linear cylindrical slide-valve, the report proposes an original analytic method. This study can similarly be applied to any other type of hydraulic resistance. Another purpose of this study is to determine certain mathematical relationships useful to approach the theoretical functionality of hydraulic resistances with magnetic controllable fluids as incompressible fluids in the presence of a controllable magnetic field. In this report, we established general analytic equations to calculate (i) velocity and pressure distributions, (ii) average velocity, (iii) volume flow rate of the liquid, (iv) pressures difference, and (v) radial clearance. PMID:26167532

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.

Turbulent Motion of Liquids in Hydraulic Resistances with a Linear Cylindrical Slide-Valve.

PubMed

Velescu, C; Popa, N C

2015-01-01

We analyze the motion of viscous and incompressible liquids in the annular space of controllable hydraulic resistances with a cylindrical linear slide-valve. This theoretical study focuses on the turbulent and steady-state motion regimes. The hydraulic resistances mentioned above are the most frequent type of hydraulic resistances used in hydraulic actuators and automation systems. To study the liquids' motion in the controllable hydraulic resistances with a linear cylindrical slide-valve, the report proposes an original analytic method. This study can similarly be applied to any other type of hydraulic resistance. Another purpose of this study is to determine certain mathematical relationships useful to approach the theoretical functionality of hydraulic resistances with magnetic controllable fluids as incompressible fluids in the presence of a controllable magnetic field. In this report, we established general analytic equations to calculate (i) velocity and pressure distributions, (ii) average velocity, (iii) volume flow rate of the liquid, (iv) pressures difference, and (v) radial clearance.

Large deformation image classification using generalized locality-constrained linear coding.

PubMed

Zhang, Pei; Wee, Chong-Yaw; Niethammer, Marc; Shen, Dinggang; Yap, Pew-Thian

2013-01-01

Magnetic resonance (MR) imaging has been demonstrated to be very useful for clinical diagnosis of Alzheimer's disease (AD). A common approach to using MR images for AD detection is to spatially normalize the images by non-rigid image registration, and then perform statistical analysis on the resulting deformation fields. Due to the high nonlinearity of the deformation field, recent studies suggest to use initial momentum instead as it lies in a linear space and fully encodes the deformation field. In this paper we explore the use of initial momentum for image classification by focusing on the problem of AD detection. Experiments on the public ADNI dataset show that the initial momentum, together with a simple sparse coding technique-locality-constrained linear coding (LLC)--can achieve a classification accuracy that is comparable to or even better than the state of the art. We also show that the performance of LLC can be greatly improved by introducing proper weights to the codebook.

Bayesian inference of radiation belt loss timescales.

NASA Astrophysics Data System (ADS)

Camporeale, E.; Chandorkar, M.

2017-12-01

Electron fluxes in the Earth's radiation belts are routinely studied using the classical quasi-linear radial diffusion model. Although this simplified linear equation has proven to be an indispensable tool in understanding the dynamics of the radiation belt, it requires specification of quantities such as the diffusion coefficient and electron loss timescales that are never directly measured. Researchers have so far assumed a-priori parameterisations for radiation belt quantities and derived the best fit using satellite data. The state of the art in this domain lacks a coherent formulation of this problem in a probabilistic framework. We present some recent progress that we have made in performing Bayesian inference of radial diffusion parameters. We achieve this by making extensive use of the theory connecting Gaussian Processes and linear partial differential equations, and performing Markov Chain Monte Carlo sampling of radial diffusion parameters. These results are important for understanding the role and the propagation of uncertainties in radiation belt simulations and, eventually, for providing a probabilistic forecast of energetic electron fluxes in a Space Weather context.

Nonlinear Riccati equations as a unifying link between linear quantum mechanics and other fields of physics

NASA Astrophysics Data System (ADS)

Schuch, Dieter

2014-04-01

Theoretical physics seems to be in a kind of schizophrenic state. Many phenomena in the observable macroscopic world obey nonlinear evolution equations, whereas the microscopic world is governed by quantum mechanics, a fundamental theory that is supposedly linear. In order to combine these two worlds in a common formalism, at least one of them must sacrifice one of its dogmas. I claim that linearity in quantum mechanics is not as essential as it apparently seems since quantum mechanics can be reformulated in terms of nonlinear Riccati equations. In a first step, it will be shown where complex Riccati equations appear in time-dependent quantum mechanics and how they can be treated and compared with similar space-dependent Riccati equations in supersymmetric quantum mechanics. Furthermore, the time-independent Schrödinger equation can also be rewritten as a complex Riccati equation. Finally, it will be shown that (real and complex) Riccati equations also appear in many other fields of physics, like statistical thermodynamics and cosmology.

Probabilistic quantum cloning of a subset of linearly dependent states

NASA Astrophysics Data System (ADS)

Rui, Pinshu; Zhang, Wen; Liao, Yanlin; Zhang, Ziyun

2018-02-01

It is well known that a quantum state, secretly chosen from a certain set, can be probabilistically cloned with positive cloning efficiencies if and only if all the states in the set are linearly independent. In this paper, we focus on probabilistic quantum cloning of a subset of linearly dependent states. We show that a linearly-independent subset of linearly-dependent quantum states {| Ψ 1⟩,| Ψ 2⟩,…,| Ψ n ⟩} can be probabilistically cloned if and only if any state in the subset cannot be expressed as a linear superposition of the other states in the set {| Ψ 1⟩,| Ψ 2⟩,…,| Ψ n ⟩}. The optimal cloning efficiencies are also investigated.

Structural robustness with suboptimal responses for linear state space model

NASA Technical Reports Server (NTRS)

Keel, L. H.; Lim, Kyong B.; Juang, Jer-Nan

1989-01-01

A relationship between the closed-loop eigenvalues and the amount of perturbations in the open-loop matrix is addressed in the context of performance robustness. If the allowable perturbation ranges of elements of the open-loop matrix A and the desired tolerance of the closed-loop eigenvalues are given such that max(j) of the absolute value of Delta-lambda(j) (A+BF) should be less than some prescribed value, what is a state feedback controller F which satisfies the closed-loop eigenvalue perturbation-tolerance requirement for a class of given perturbation in A? The paper gives an algorithm to design such a controller. Numerical examples are included for illustration.

Asymptotic analysis of noisy fitness maximization, applied to metabolism & growth

NASA Astrophysics Data System (ADS)

De Martino, Daniele; Masoero, Davide

2016-12-01

We consider a population dynamics model coupling cell growth to a diffusion in the space of metabolic phenotypes as it can be obtained from realistic constraints-based modeling. In the asymptotic regime of slow diffusion, that coincides with the relevant experimental range, the resulting non-linear Fokker-Planck equation is solved for the steady state in the WKB approximation that maps it into the ground state of a quantum particle in an Airy potential plus a centrifugal term. We retrieve scaling laws for growth rate fluctuations and time response with respect to the distance from the maximum growth rate suggesting that suboptimal populations can have a faster response to perturbations.

Reconfiguration of a smart surface using heteroclinic connections

PubMed Central

McInnes, Colin R.; Xu, Ming

2017-01-01

A reconfigurable smart surface with multiple equilibria is presented, modelled using discrete point masses and linear springs with geometric nonlinearity. An energy-efficient reconfiguration scheme is then investigated to connect equal-energy unstable (but actively controlled) equilibria. In principle, zero net energy input is required to transition the surface between these unstable states, compared to transitions between stable equilibria across a potential barrier. These transitions between equal-energy unstable states, therefore, form heteroclinic connections in the phase space of the problem. Moreover, the smart surface model developed can be considered as a unit module for a range of applications, including modules which can aggregate together to form larger distributed smart surface systems. PMID:28265191

Generation of squeezing in a driven many-body system

NASA Astrophysics Data System (ADS)

Hebbe Madhusudhana, Bharath; Boguslawski, Matthew; Anquez, Martin; Robbins, Bryce; Barrios, Maryrose; Hoang, Thai; Chapman, Michael

2016-05-01

In a spin-1 Bose-Einstein condensate, the non-linear spin-dependent collisional interactions can create entanglement and squeezing. Typically, the condensate is initialized at an unstable fixed point of the phase space, and subsequent free evolution under a time-independent Hamiltonian creates the squeezed state. Alternatively, it is possible to generate squeezing by driving the system localized at a stable fixed point. Here, we demonstrate that periodic modulation of the Hamiltonian can generate highly squeezed states. Our measurements show -5 dB of squeezing, limited by the detection, but calculations indicate that a theoretical potential of -20 dB of squeezing. We discuss the advantages of this method compared with the typical techniques.

Non-linear effects in bunch compressor of TARLA

NASA Astrophysics Data System (ADS)

Yildiz, Hüseyin; Aksoy, Avni; Arikan, Pervin

2016-03-01

Transport of a beam through an accelerator beamline is affected by high order and non-linear effects such as space charge, coherent synchrotron radiation, wakefield, etc. These effects damage form of the beam, and they lead particle loss, emittance growth, bunch length variation, beam halo formation, etc. One of the known non-linear effects on low energy machine is space charge effect. In this study we focus on space charge effect for Turkish Accelerator and Radiation Laboratory in Ankara (TARLA) machine which is designed to drive InfraRed Free Electron Laser covering the range of 3-250 µm. Moreover, we discuss second order effects on bunch compressor of TARLA.

Robust global identifiability theory using potentials--Application to compartmental models.

PubMed

Wongvanich, N; Hann, C E; Sirisena, H R

2015-04-01

This paper presents a global practical identifiability theory for analyzing and identifying linear and nonlinear compartmental models. The compartmental system is prolonged onto the potential jet space to formulate a set of input-output equations that are integrals in terms of the measured data, which allows for robust identification of parameters without requiring any simulation of the model differential equations. Two classes of linear and non-linear compartmental models are considered. The theory is first applied to analyze the linear nitrous oxide (N2O) uptake model. The fitting accuracy of the identified models from differential jet space and potential jet space identifiability theories is compared with a realistic noise level of 3% which is derived from sensor noise data in the literature. The potential jet space approach gave a match that was well within the coefficient of variation. The differential jet space formulation was unstable and not suitable for parameter identification. The proposed theory is then applied to a nonlinear immunological model for mastitis in cows. In addition, the model formulation is extended to include an iterative method which allows initial conditions to be accurately identified. With up to 10% noise, the potential jet space theory predicts the normalized population concentration infected with pathogens, to within 9% of the true curve. Copyright © 2015 Elsevier Inc. All rights reserved.

Linear Mapping of Numbers onto Space Requires Attention

ERIC Educational Resources Information Center

Anobile, Giovanni; Cicchini, Guido Marco; Burr, David C.

2012-01-01

Mapping of number onto space is fundamental to mathematics and measurement. Previous research suggests that while typical adults with mathematical schooling map numbers veridically onto a linear scale, pre-school children and adults without formal mathematics training, as well as individuals with dyscalculia, show strong compressive,…

Excited-state potential-energy surfaces of metal-adsorbed organic molecules from linear expansion Δ-self-consistent field density-functional theory (ΔSCF-DFT).

PubMed

Maurer, Reinhard J; Reuter, Karsten

2013-07-07

Accurate and efficient simulation of excited state properties is an important and much aspired cornerstone in the study of adsorbate dynamics on metal surfaces. To this end, the recently proposed linear expansion Δ-self-consistent field method by Gavnholt et al. [Phys. Rev. B 78, 075441 (2008)] presents an efficient alternative to time consuming quasi-particle calculations. In this method, the standard Kohn-Sham equations of density-functional theory are solved with the constraint of a non-equilibrium occupation in a region of Hilbert-space resembling gas-phase orbitals of the adsorbate. In this work, we discuss the applicability of this method for the excited-state dynamics of metal-surface mounted organic adsorbates, specifically in the context of molecular switching. We present necessary advancements to allow for a consistent quality description of excited-state potential-energy surfaces (PESs), and illustrate the concept with the application to Azobenzene adsorbed on Ag(111) and Au(111) surfaces. We find that the explicit inclusion of substrate electronic states modifies the topologies of intra-molecular excited-state PESs of the molecule due to image charge and hybridization effects. While the molecule in gas phase shows a clear energetic separation of resonances that induce isomerization and backreaction, the surface-adsorbed molecule does not. The concomitant possibly simultaneous induction of both processes would lead to a significantly reduced switching efficiency of such a mechanism.

Experimental analysis of bidirectional reflectance distribution function cross section conversion term in direction cosine space.

PubMed

Butler, Samuel D; Nauyoks, Stephen E; Marciniak, Michael A

2015-06-01

Of the many classes of bidirectional reflectance distribution function (BRDF) models, two popular classes of models are the microfacet model and the linear systems diffraction model. The microfacet model has the benefit of speed and simplicity, as it uses geometric optics approximations, while linear systems theory uses a diffraction approach to compute the BRDF, at the expense of greater computational complexity. In this Letter, nongrazing BRDF measurements of rough and polished surface-reflecting materials at multiple incident angles are scaled by the microfacet cross section conversion term, but in the linear systems direction cosine space, resulting in great alignment of BRDF data at various incident angles in this space. This results in a predictive BRDF model for surface-reflecting materials at nongrazing angles, while avoiding some of the computational complexities in the linear systems diffraction model.

On the Existence of Star Products on Quotient Spaces of Linear Hamiltonian Torus Actions

NASA Astrophysics Data System (ADS)

Herbig, Hans-Christian; Iyengar, Srikanth B.; Pflaum, Markus J.

2009-08-01

We discuss BFV deformation quantization (Bordemann et al. in A homological approach to singular reduction in deformation quantization, singularity theory, pp. 443-461. World Scientific, Hackensack, 2007) in the special case of a linear Hamiltonian torus action. In particular, we show that the Koszul complex on the moment map of an effective linear Hamiltonian torus action is acyclic. We rephrase the nonpositivity condition of Arms and Gotay (Adv Math 79(1):43-103, 1990) for linear Hamiltonian torus actions. It follows that reduced spaces of such actions admit continuous star products.

Space and frequency-multiplexed optical linear algebra processor - Fabrication and initial tests

NASA Technical Reports Server (NTRS)

Casasent, D.; Jackson, J.

1986-01-01

A new optical linear algebra processor architecture is described. Space and frequency-multiplexing are used to accommodate bipolar and complex-valued data. A fabricated laboratory version of this processor is described, the electronic support system used is discussed, and initial test data obtained on it are presented.

Dirac Theory on a Space with Linear Lie Type Fuzziness

NASA Astrophysics Data System (ADS)

Shariati, Ahmad; Khorrami, Mohammad; Fatollahi, Amir H.

2012-08-01

A spinor theory on a space with linear Lie type noncommutativity among spatial coordinates is presented. The model is based on the Fourier space corresponding to spatial coordinates, as this Fourier space is commutative. When the group is compact, the real space exhibits lattice characteristics (as the eigenvalues of space operators are discrete), and the similarity of such a lattice with ordinary lattices is manifested, among other things, in a phenomenon resembling the famous fermion doubling problem. A projection is introduced to make the dynamical number of spinors equal to that corresponding to the ordinary space. The actions for free and interacting spinors (with Fermi-like interactions) are presented. The Feynman rules are extracted and 1-loop corrections are investigated.

Stochastic search, optimization and regression with energy applications

NASA Astrophysics Data System (ADS)

Hannah, Lauren A.

Designing clean energy systems will be an important task over the next few decades. One of the major roadblocks is a lack of mathematical tools to economically evaluate those energy systems. However, solutions to these mathematical problems are also of interest to the operations research and statistical communities in general. This thesis studies three problems that are of interest to the energy community itself or provide support for solution methods: R&D portfolio optimization, nonparametric regression and stochastic search with an observable state variable. First, we consider the one stage R&D portfolio optimization problem to avoid the sequential decision process associated with the multi-stage. The one stage problem is still difficult because of a non-convex, combinatorial decision space and a non-convex objective function. We propose a heuristic solution method that uses marginal project values---which depend on the selected portfolio---to create a linear objective function. In conjunction with the 0-1 decision space, this new problem can be solved as a knapsack linear program. This method scales well to large decision spaces. We also propose an alternate, provably convergent algorithm that does not exploit problem structure. These methods are compared on a solid oxide fuel cell R&D portfolio problem. Next, we propose Dirichlet Process mixtures of Generalized Linear Models (DPGLM), a new method of nonparametric regression that accommodates continuous and categorical inputs, and responses that can be modeled by a generalized linear model. We prove conditions for the asymptotic unbiasedness of the DP-GLM regression mean function estimate. We also give examples for when those conditions hold, including models for compactly supported continuous distributions and a model with continuous covariates and categorical response. We empirically analyze the properties of the DP-GLM and why it provides better results than existing Dirichlet process mixture regression models. We evaluate DP-GLM on several data sets, comparing it to modern methods of nonparametric regression like CART, Bayesian trees and Gaussian processes. Compared to existing techniques, the DP-GLM provides a single model (and corresponding inference algorithms) that performs well in many regression settings. Finally, we study convex stochastic search problems where a noisy objective function value is observed after a decision is made. There are many stochastic search problems whose behavior depends on an exogenous state variable which affects the shape of the objective function. Currently, there is no general purpose algorithm to solve this class of problems. We use nonparametric density estimation to take observations from the joint state-outcome distribution and use them to infer the optimal decision for a given query state. We propose two solution methods that depend on the problem characteristics: function-based and gradient-based optimization. We examine two weighting schemes, kernel-based weights and Dirichlet process-based weights, for use with the solution methods. The weights and solution methods are tested on a synthetic multi-product newsvendor problem and the hour-ahead wind commitment problem. Our results show that in some cases Dirichlet process weights offer substantial benefits over kernel based weights and more generally that nonparametric estimation methods provide good solutions to otherwise intractable problems.

Comparing Two Approaches for Assessing Observation Impact

NASA Technical Reports Server (NTRS)

Todling, Ricardo

2013-01-01

Langland and Baker introduced an approach to assess the impact of observations on the forecasts. In that approach, a state-space aspect of the forecast is defined and a procedure is derived ultimately relating changes in the aspect with changes in the observing system. Some features of the state-space approach are to be noted: the typical choice of forecast aspect is rather subjective and leads to incomplete assessment of the observing system, it requires availability of a verification state that is in practice correlated with the forecast, and it involves the adjoint operator of the entire data assimilation system and is thus constrained by the validity of this operator. This article revisits the topic of observation impacts from the perspective of estimation theory. An observation-space metric is used to allow inferring observation impact on the forecasts without the limitations just mentioned. Using differences of observation-minus-forecast residuals obtained from consecutive forecasts leads to the following advantages: (i) it suggests a rather natural choice of forecast aspect that directly links to the data assimilation procedure, (ii) it avoids introducing undesirable correlations in the forecast aspect since verification is done against the observations, and (iii) it does not involve linearization and use of adjoints. The observation-space approach has the additional advantage of being nearly cost free and very simple to implement. In its simplest form it reduces to evaluating the statistics of observationminus- background and observation-minus-analysis residuals with traditional methods. Illustrations comparing the approaches are given using the NASA Goddard Earth Observing System.

Shape in Picture: Mathematical Description of Shape in Grey-Level Images

DTIC Science & Technology

1992-09-11

representation is scale-space, derived frrr- the linear isotropic diffusion equation; recently other types of equations have been considered. Multiscale...recognition of dimensions in the general case of an arbitrary denominator is similar to that just explained. 3 Linear Inequalities in the Two-Dimensional...solid region containing all pixels of the space, whose coordinates satisfy a linear inequality. A Um C scspt fr Digital Geometry 41 s a a v--’ -0 7 O

RatCar system for estimating locomotion states using neural signals with parameter monitoring: Vehicle-formed brain-machine interfaces for rat.

PubMed

Fukayama, Osamu; Taniguchi, Noriyuki; Suzuki, Takafumi; Mabuchi, Kunihiko

2008-01-01

An online brain-machine interface (BMI) in the form of a small vehicle, the 'RatCar,' has been developed. A rat had neural electrodes implanted in its primary motor cortex and basal ganglia regions to continuously record neural signals. Then, a linear state space model represents a correlation between the recorded neural signals and locomotion states (i.e., moving velocity and azimuthal variances) of the rat. The model parameters were set so as to minimize estimation errors, and the locomotion states were estimated from neural firing rates using a Kalman filter algorithm. The results showed a small oscillation to achieve smooth control of the vehicle in spite of fluctuating firing rates with noises applied to the model. Major variation of the model variables converged in a first 30 seconds of the experiments and lasted for the entire one hour session.

Coin state properties in quantum walks

PubMed Central

Andrade, R. F. S.

2013-01-01

Recent experimental advances have measured individual coin components in discrete time quantum walks, which have not received the due attention in most theoretical studies on the theme. Here is presented a detailed investigation of the properties of M, the difference between square modulus of coin states of discrete quantum walks on a linear chain. Local expectation values are obtained in terms of real and imaginary parts of the Fourier transformed wave function. A simple expression is found for the average difference between coin states in terms of an angle θ gauging the coin operator and its initial state. These results are corroborated by numerical integration of dynamical equations in real space. The local dependence is characterized both by large and short period modulations. The richness of revealed patterns suggests that the amount of information stored and retrieved from quantum walks is significantly enhanced if M is taken into account. PMID:23756358

Aeroservoelastic modeling and applications using minimum-state approximations of the unsteady aerodynamics

NASA Technical Reports Server (NTRS)

Tiffany, Sherwood H.; Karpel, Mordechay

1989-01-01

Various control analysis, design, and simulation techniques for aeroelastic applications require the equations of motion to be cast in a linear time-invariant state-space form. Unsteady aerodynamics forces have to be approximated as rational functions of the Laplace variable in order to put them in this framework. For the minimum-state method, the number of denominator roots in the rational approximation. Results are shown of applying various approximation enhancements (including optimization, frequency dependent weighting of the tabular data, and constraint selection) with the minimum-state formulation to the active flexible wing wind-tunnel model. The results demonstrate that good models can be developed which have an order of magnitude fewer augmenting aerodynamic equations more than traditional approaches. This reduction facilitates the design of lower order control systems, analysis of control system performance, and near real-time simulation of aeroservoelastic phenomena.

2-Point microstructure archetypes for improved elastic properties

NASA Astrophysics Data System (ADS)

Adams, Brent L.; Gao, Xiang

2004-01-01

Rectangular models of material microstructure are described by their 1- and 2-point (spatial) correlation statistics of placement of local state. In the procedure described here the local state space is described in discrete form; and the focus is on placement of local state within a finite number of cells comprising rectangular models. It is illustrated that effective elastic properties (generalized Hashin Shtrikman bounds) can be obtained that are linear in components of the correlation statistics. Within this framework the concept of an eigen-microstructure within the microstructure hull is useful. Given the practical innumerability of the microstructure hull, however, we introduce a method for generating a sequence of archetypes of eigen-microstructure, from the 2-point correlation statistics of local state, assuming that the 1-point statistics are stationary. The method is illustrated by obtaining an archetype for an imaginary two-phase material where the objective is to maximize the combination C_{xxxx}^{*} + C_{xyxy}^{*}

A Hybrid of Deep Network and Hidden Markov Model for MCI Identification with Resting-State fMRI.

PubMed

Suk, Heung-Il; Lee, Seong-Whan; Shen, Dinggang

2015-10-01

In this paper, we propose a novel method for modelling functional dynamics in resting-state fMRI (rs-fMRI) for Mild Cognitive Impairment (MCI) identification. Specifically, we devise a hybrid architecture by combining Deep Auto-Encoder (DAE) and Hidden Markov Model (HMM). The roles of DAE and HMM are, respectively, to discover hierarchical non-linear relations among features, by which we transform the original features into a lower dimension space, and to model dynamic characteristics inherent in rs-fMRI, i.e. , internal state changes. By building a generative model with HMMs for each class individually, we estimate the data likelihood of a test subject as MCI or normal healthy control, based on which we identify the clinical label. In our experiments, we achieved the maximal accuracy of 81.08% with the proposed method, outperforming state-of-the-art methods in the literature.

A Hybrid of Deep Network and Hidden Markov Model for MCI Identification with Resting-State fMRI

PubMed Central

Suk, Heung-Il; Lee, Seong-Whan; Shen, Dinggang

2015-01-01

In this paper, we propose a novel method for modelling functional dynamics in resting-state fMRI (rs-fMRI) for Mild Cognitive Impairment (MCI) identification. Specifically, we devise a hybrid architecture by combining Deep Auto-Encoder (DAE) and Hidden Markov Model (HMM). The roles of DAE and HMM are, respectively, to discover hierarchical non-linear relations among features, by which we transform the original features into a lower dimension space, and to model dynamic characteristics inherent in rs-fMRI, i.e., internal state changes. By building a generative model with HMMs for each class individually, we estimate the data likelihood of a test subject as MCI or normal healthy control, based on which we identify the clinical label. In our experiments, we achieved the maximal accuracy of 81.08% with the proposed method, outperforming state-of-the-art methods in the literature. PMID:27054199

Characterization of a measurement-based noiseless linear amplifier and its applications

NASA Astrophysics Data System (ADS)

Zhao, Jie; Haw, Jing Yan; Symul, Thomas; Lam, Ping Koy; Assad, Syed M.

2017-07-01

A noiseless linear amplifier (NLA) adds no noise to the signals it processes, which works only in a probabilistic way. It can be realized approximately with either a physical implementation that truncates the working space of the NLA on a photon-number basis or a measurement-based implementation that realizes the truncation virtually by a bounded postselection filter. To examine the relationship between these two approximate NLAs, we characterize in detail the measurement-based NLA and compare it with its physical counterpart in terms of their abilities to preserve the state Gaussianity and their probability of success. The link between these amplifiers is further clarified by integrating them into a measure-and-prepare setup. We stress the equivalence between the physical and the measurement-based approaches holds only when the effective parameters, the amplification gain, the cutoff, and the amplitude of the input state, are taken into account. Finally, we construct a 1-to-infinity cloner using the two amplifiers and show that a fidelity surpassing the no-cloning limit is achievable with the measurement-based NLA.

A finite difference solution for the propagation of sound in near sonic flows

NASA Technical Reports Server (NTRS)

Hariharan, S. I.; Lester, H. C.

1983-01-01

An explicit time/space finite difference procedure is used to model the propagation of sound in a quasi one-dimensional duct containing high Mach number subsonic flow. Nonlinear acoustic equations are derived by perturbing the time-dependent Euler equations about a steady, compressible mean flow. The governing difference relations are based on a fourth-order, two-step (predictor-corrector) MacCormack scheme. The solution algorithm functions by switching on a time harmonic source and allowing the difference equations to iterate to a steady state. The principal effect of the non-linearities was to shift acoustical energy to higher harmonics. With increased source strengths, wave steepening was observed. This phenomenon suggests that the acoustical response may approach a shock behavior at at higher sound pressure level as the throat Mach number aproaches unity. On a peak level basis, good agreement between the nonlinear finite difference and linear finite element solutions was observed, even through a peak sound pressure level of about 150 dB occurred in the throat region. Nonlinear steady state waveform solutions are shown to be in excellent agreement with a nonlinear asymptotic theory.

Orbital State Uncertainty Realism

NASA Astrophysics Data System (ADS)

Horwood, J.; Poore, A. B.

2012-09-01

Fundamental to the success of the space situational awareness (SSA) mission is the rigorous inclusion of uncertainty in the space surveillance network. The *proper characterization of uncertainty* in the orbital state of a space object is a common requirement to many SSA functions including tracking and data association, resolution of uncorrelated tracks (UCTs), conjunction analysis and probability of collision, sensor resource management, and anomaly detection. While tracking environments, such as air and missile defense, make extensive use of Gaussian and local linearity assumptions within algorithms for uncertainty management, space surveillance is inherently different due to long time gaps between updates, high misdetection rates, nonlinear and non-conservative dynamics, and non-Gaussian phenomena. The latter implies that "covariance realism" is not always sufficient. SSA also requires "uncertainty realism"; the proper characterization of both the state and covariance and all non-zero higher-order cumulants. In other words, a proper characterization of a space object's full state *probability density function (PDF)* is required. In order to provide a more statistically rigorous treatment of uncertainty in the space surveillance tracking environment and to better support the aforementioned SSA functions, a new class of multivariate PDFs are formulated which more accurately characterize the uncertainty of a space object's state or orbit. The new distribution contains a parameter set controlling the higher-order cumulants which gives the level sets a distinctive "banana" or "boomerang" shape and degenerates to a Gaussian in a suitable limit. Using the new class of PDFs within the general Bayesian nonlinear filter, the resulting filter prediction step (i.e., uncertainty propagation) is shown to have the *same computational cost as the traditional unscented Kalman filter* with the former able to maintain a proper characterization of the uncertainty for up to *ten times as long* as the latter. The filter correction step also furnishes a statistically rigorous *prediction error* which appears in the likelihood ratios for scoring the association of one report or observation to another. Thus, the new filter can be used to support multi-target tracking within a general multiple hypothesis tracking framework. Additionally, the new distribution admits a distance metric which extends the classical Mahalanobis distance (chi^2 statistic). This metric provides a test for statistical significance and facilitates single-frame data association methods with the potential to easily extend the covariance-based track association algorithm of Hill, Sabol, and Alfriend. The filtering, data fusion, and association methods using the new class of orbital state PDFs are shown to be mathematically tractable and operationally viable.

Small-world networks exhibit pronounced intermittent synchronization

NASA Astrophysics Data System (ADS)

Choudhary, Anshul; Mitra, Chiranjit; Kohar, Vivek; Sinha, Sudeshna; Kurths, Jürgen

2017-11-01

We report the phenomenon of temporally intermittently synchronized and desynchronized dynamics in Watts-Strogatz networks of chaotic Rössler oscillators. We consider topologies for which the master stability function (MSF) predicts stable synchronized behaviour, as the rewiring probability (p) is tuned from 0 to 1. MSF essentially utilizes the largest non-zero Lyapunov exponent transversal to the synchronization manifold in making stability considerations, thereby ignoring the other Lyapunov exponents. However, for an N-node networked dynamical system, we observe that the difference in its Lyapunov spectra (corresponding to the N - 1 directions transversal to the synchronization manifold) is crucial and serves as an indicator of the presence of intermittently synchronized behaviour. In addition to the linear stability-based (MSF) analysis, we further provide global stability estimate in terms of the fraction of state-space volume shared by the intermittently synchronized state, as p is varied from 0 to 1. This fraction becomes appreciably large in the small-world regime, which is surprising, since this limit has been otherwise considered optimal for synchronized dynamics. Finally, we characterize the nature of the observed intermittency and its dominance in state-space as network rewiring probability (p) is varied.

Non-linear effects in bunch compressor of TARLA

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

Yildiz, Hüseyin, E-mail: huseyinyildiz006@gmail.com, E-mail: huseyinyildiz@gazi.edu.tr; Aksoy, Avni; Arikan, Pervin

2016-03-25

Transport of a beam through an accelerator beamline is affected by high order and non-linear effects such as space charge, coherent synchrotron radiation, wakefield, etc. These effects damage form of the beam, and they lead particle loss, emittance growth, bunch length variation, beam halo formation, etc. One of the known non-linear effects on low energy machine is space charge effect. In this study we focus on space charge effect for Turkish Accelerator and Radiation Laboratory in Ankara (TARLA) machine which is designed to drive InfraRed Free Electron Laser covering the range of 3-250 µm. Moreover, we discuss second order effects onmore » bunch compressor of TARLA.« less

A linear programming manual

NASA Technical Reports Server (NTRS)

Tuey, R. C.

1972-01-01

Computer solutions of linear programming problems are outlined. Information covers vector spaces, convex sets, and matrix algebra elements for solving simultaneous linear equations. Dual problems, reduced cost analysis, ranges, and error analysis are illustrated.

Fast Magnetosonic Waves Observed by Van Allen Probes: Testing Local Wave Excitation Mechanism

NASA Astrophysics Data System (ADS)

Min, Kyungguk; Liu, Kaijun; Wang, Xueyi; Chen, Lunjin; Denton, Richard E.

2018-01-01

Linear Vlasov theory and particle-in-cell (PIC) simulations for electromagnetic fluctuations in a homogeneous, magnetized, and collisionless plasma are used to investigate a fast magnetosonic wave event observed by the Van Allen Probes. The fluctuating magnetic field observed exhibits a series of spectral peaks at harmonics of the proton cyclotron frequency Ωp and has a dominant compressional component, which can be classified as fast magnetosonic waves. Furthermore, the simultaneously observed proton phase space density exhibits positive slopes in the perpendicular velocity space, ∂fp/∂v⊥>0, which can be a source for these waves. Linear theory analyses and PIC simulations use plasma and field parameters measured in situ except that the modeled proton distribution is modified to have larger ∂fp/∂v⊥ under the assumption that the observed distribution corresponds to a marginally stable state when the distribution has already been scattered by the excited waves. The results show that the positive slope is the source of the proton cyclotron harmonic waves at propagation quasi-perpendicular to the background magnetic field, and as a result of interactions with the excited waves the evolving proton distribution progresses approximately toward the observed distribution.

Design, characterization, and control of the NASA three degree of freedom reaction compensation platform

NASA Technical Reports Server (NTRS)

Birkhimer, Craig; Newman, Wyatt; Choi, Benjamin; Lawrence, Charles

1994-01-01

Increasing research is being done into industrial uses for the microgravity environment aboard orbiting space vehicles. However, there is some concern over the effects of reaction forces produced by moving objects, especially motors, robotic actuators, and astronauts. Reaction forces produced by the movement of these objects may manifest themselves as undesirable accelerations in the space vehicle making the vehicle unusable for microgravity applications. It is desirable to provide compensation for such forces using active means. This paper presents the design and experimental evaluation of the NASA three degree of freedom reaction compensation platform, a system designed to be a testbed for the feasibility of active attenuation of reaction forces caused by moving objects in a microgravity environment. Unique 'linear motors,' which convert electrical current directly into rectilinear force, are used in the platform design. The linear motors induce accelerations of the displacer inertias. These accelerations create reaction forces that may be controlled to counteract disturbance forces introduced to the platform. The stated project goal is to reduce reaction forces by 90 percent, or -20 dB. Description of the system hardware, characterization of the actuators and the composite system, and design of the software safety system and control software are included.

A robust momentum management and attitude control system for the space station

NASA Technical Reports Server (NTRS)

Speyer, J. L.; Rhee, Ihnseok

1991-01-01

A game theoretic controller is synthesized for momentum management and attitude control of the Space Station in the presence of uncertainties in the moments of inertia. Full state information is assumed since attitude rates are assumed to be very assurately measured. By an input-output decomposition of the uncertainty in the system matrices, the parameter uncertainties in the dynamic system are represented as an unknown gain associated with an internal feedback loop (IFL). The input and output matrices associated with the IFL form directions through which the uncertain parameters affect system response. If the quadratic form of the IFL output augments the cost criterion, then enhanced parameter robustness is anticipated. By considering the input and the input disturbance from the IFL as two noncooperative players, a linear-quadratic differential game is constructed. The solution in the form of a linear controller is used for synthesis. Inclusion of the external disturbance torques results in a dynamic feedback controller which consists of conventional PID (proportional integral derivative) control and cyclic disturbance rejection filters. It is shown that the game theoretic design allows large variations in the inertias in directions of importance.

Kernel-based Joint Feature Selection and Max-Margin Classification for Early Diagnosis of Parkinson’s Disease

NASA Astrophysics Data System (ADS)

Adeli, Ehsan; Wu, Guorong; Saghafi, Behrouz; An, Le; Shi, Feng; Shen, Dinggang

2017-01-01

Feature selection methods usually select the most compact and relevant set of features based on their contribution to a linear regression model. Thus, these features might not be the best for a non-linear classifier. This is especially crucial for the tasks, in which the performance is heavily dependent on the feature selection techniques, like the diagnosis of neurodegenerative diseases. Parkinson’s disease (PD) is one of the most common neurodegenerative disorders, which progresses slowly while affects the quality of life dramatically. In this paper, we use the data acquired from multi-modal neuroimaging data to diagnose PD by investigating the brain regions, known to be affected at the early stages. We propose a joint kernel-based feature selection and classification framework. Unlike conventional feature selection techniques that select features based on their performance in the original input feature space, we select features that best benefit the classification scheme in the kernel space. We further propose kernel functions, specifically designed for our non-negative feature types. We use MRI and SPECT data of 538 subjects from the PPMI database, and obtain a diagnosis accuracy of 97.5%, which outperforms all baseline and state-of-the-art methods.

Linear and nonlinear response of a rotating tokamak plasma to a resonant error-field

NASA Astrophysics Data System (ADS)

Fitzpatrick, Richard

2014-09-01

An in-depth investigation of the effect of a resonant error-field on a rotating, quasi-cylindrical, tokamak plasma is preformed within the context of constant-ψ, resistive-magnetohydrodynamical theory. General expressions for the response of the plasma at the rational surface to the error-field are derived in both the linear and nonlinear regimes, and the extents of these regimes mapped out in parameter space. Torque-balance equations are also obtained in both regimes. These equations are used to determine the steady-state plasma rotation at the rational surface in the presence of the error-field. It is found that, provided the intrinsic plasma rotation is sufficiently large, the torque-balance equations possess dynamically stable low-rotation and high-rotation solution branches, separated by a forbidden band of dynamically unstable solutions. Moreover, bifurcations between the two stable solution branches are triggered as the amplitude of the error-field is varied. A low- to high-rotation bifurcation is invariably associated with a significant reduction in the width of the magnetic island chain driven at the rational surface, and vice versa. General expressions for the bifurcation thresholds are derived and their domains of validity mapped out in parameter space.

Kernel-based Joint Feature Selection and Max-Margin Classification for Early Diagnosis of Parkinson’s Disease

PubMed Central

Adeli, Ehsan; Wu, Guorong; Saghafi, Behrouz; An, Le; Shi, Feng; Shen, Dinggang

2017-01-01

Feature selection methods usually select the most compact and relevant set of features based on their contribution to a linear regression model. Thus, these features might not be the best for a non-linear classifier. This is especially crucial for the tasks, in which the performance is heavily dependent on the feature selection techniques, like the diagnosis of neurodegenerative diseases. Parkinson’s disease (PD) is one of the most common neurodegenerative disorders, which progresses slowly while affects the quality of life dramatically. In this paper, we use the data acquired from multi-modal neuroimaging data to diagnose PD by investigating the brain regions, known to be affected at the early stages. We propose a joint kernel-based feature selection and classification framework. Unlike conventional feature selection techniques that select features based on their performance in the original input feature space, we select features that best benefit the classification scheme in the kernel space. We further propose kernel functions, specifically designed for our non-negative feature types. We use MRI and SPECT data of 538 subjects from the PPMI database, and obtain a diagnosis accuracy of 97.5%, which outperforms all baseline and state-of-the-art methods. PMID:28120883

Robust momentum management and attitude control system for the Space Station

NASA Technical Reports Server (NTRS)

Rhee, Ihnseok; Speyer, Jason L.

1992-01-01

A game theoretic controller is synthesized for momentum management and attitude control of the Space Station in the presence of uncertainties in the moments of inertia. Full state information is assumed since attitude rates are assumed to be very accurately measured. By an input-output decomposition of the uncertainty in the system matrices, the parameter uncertainties in the dynamic system are represented as an unknown gain associated with an internal feedback loop (IFL). The input and output matrices associated with the IFL form directions through which the uncertain parameters affect system response. If the quadratic form of the IFL output augments the cost criterion, then enhanced parameter robustness is anticipated. By considering the input and the input disturbance from the IFL as two noncooperative players, a linear-quadratic differential game is constructed. The solution in the form of a linear controller is used for synthesis. Inclusion of the external disturbance torques results in a dynamic feedback controller which consists of conventional PID (proportional integral derivative) control and cyclic disturbance rejection filters. It is shown that the game theoretic design allows large variations in the inertias in directions of importance.

Application of Semi-Definite Programming for Many-Fermion Systems

NASA Astrophysics Data System (ADS)

Zhao, Zhengji; Braams, Bastiaan; Fukuda, Mituhiro; Overton, Michael

2003-03-01

The ground state energy and other important observables of a many-fermion system with one- and two-body interactions only can all be obtained from the first order and second order Reduced Density Matrices (RDM's) of the system. Using these density matrices and a family of associated representability conditions one may obtain an approximation method for electronic structure theory that is in the mathematical form of Semi-Definite Programming (SDP): minimize a linear matrix functional over a space of positive semidefinite matrices subject to linear constraints. The representability conditions are some known necessary conditions, starting with the well-known P, Q, and G conditions [Claude Garrod and Jerome K. Percus, Reducation of the N-Particle Variational Problem, J. Math. Phys. 5 (1964) 1756-1776]. The RDM method with SDP has great potential advantages over the wave function method when the particle number N is large. The dimension of the full configuration space increases exponentially with N, but in RDM method with SDP the dimension of the objective matrix (which includes RDM's) increases only polynomially with N. We will report on the effect of adding the generalized three-index conditions proposed in [R. M. Erdahl, Representability, Int. J. Quantum Chem. 13 (1978) 697-718].

Comparison of lossless compression techniques for prepress color images

NASA Astrophysics Data System (ADS)

Van Assche, Steven; Denecker, Koen N.; Philips, Wilfried R.; Lemahieu, Ignace L.

1998-12-01

In the pre-press industry color images have both a high spatial and a high color resolution. Such images require a considerable amount of storage space and impose long transmission times. Data compression is desired to reduce these storage and transmission problems. Because of the high quality requirements in the pre-press industry only lossless compression is acceptable. Most existing lossless compression schemes operate on gray-scale images. In this case the color components of color images must be compressed independently. However, higher compression ratios can be achieved by exploiting inter-color redundancies. In this paper we present a comparison of three state-of-the-art lossless compression techniques which exploit such color redundancies: IEP (Inter- color Error Prediction) and a KLT-based technique, which are both linear color decorrelation techniques, and Interframe CALIC, which uses a non-linear approach to color decorrelation. It is shown that these techniques are able to exploit color redundancies and that color decorrelation can be done effectively and efficiently. The linear color decorrelators provide a considerable coding gain (about 2 bpp) on some typical prepress images. The non-linear interframe CALIC predictor does not yield better results, but the full interframe CALIC technique does.

Chirped or time modulated excitation compared to short pulses for photoacoustic imaging in acoustic attenuating media

NASA Astrophysics Data System (ADS)

Burgholzer, P.; Motz, C.; Lang, O.; Berer, T.; Huemer, M.

2018-02-01

In photoacoustic imaging, optically generated acoustic waves transport the information about embedded structures to the sample surface. Usually, short laser pulses are used for the acoustic excitation. Acoustic attenuation increases for higher frequencies, which reduces the bandwidth and limits the spatial resolution. One could think of more efficient waveforms than single short pulses, such as pseudo noise codes, chirped, or harmonic excitation, which could enable a higher information-transfer from the samples interior to its surface by acoustic waves. We used a linear state space model to discretize the wave equation, such as the Stoke's equation, but this method could be used for any other linear wave equation. Linear estimators and a non-linear function inversion were applied to the measured surface data, for onedimensional image reconstruction. The proposed estimation method allows optimizing the temporal modulation of the excitation laser such that the accuracy and spatial resolution of the reconstructed image is maximized. We have restricted ourselves to one-dimensional models, as for higher dimensions the one-dimensional reconstruction, which corresponds to the acoustic wave without attenuation, can be used as input for any ultrasound imaging method, such as back-projection or time-reversal method.

Characterizations of linear sufficient statistics

NASA Technical Reports Server (NTRS)

Peters, B. C., Jr.; Reoner, R.; Decell, H. P., Jr.

1977-01-01

A surjective bounded linear operator T from a Banach space X to a Banach space Y must be a sufficient statistic for a dominated family of probability measures defined on the Borel sets of X. These results were applied, so that they characterize linear sufficient statistics for families of the exponential type, including as special cases the Wishart and multivariate normal distributions. The latter result was used to establish precisely which procedures for sampling from a normal population had the property that the sample mean was a sufficient statistic.

Robust estimation of carotid artery wall motion using the elasticity-based state-space approach.

PubMed

Gao, Zhifan; Xiong, Huahua; Liu, Xin; Zhang, Heye; Ghista, Dhanjoo; Wu, Wanqing; Li, Shuo

2017-04-01

The dynamics of the carotid artery wall has been recognized as a valuable indicator to evaluate the status of atherosclerotic disease in the preclinical stage. However, it is still a challenge to accurately measure this dynamics from ultrasound images. This paper aims at developing an elasticity-based state-space approach for accurately measuring the two-dimensional motion of the carotid artery wall from the ultrasound imaging sequences. In our approach, we have employed a linear elasticity model of the carotid artery wall, and converted it into the state space equation. Then, the two-dimensional motion of carotid artery wall is computed by solving this state-space approach using the H ∞ filter and the block matching method. In addition, a parameter training strategy is proposed in this study for dealing with the parameter initialization problem. In our experiment, we have also developed an evaluation function to measure the tracking accuracy of the motion of the carotid artery wall by considering the influence of the sizes of the two blocks (acquired by our approach and the manual tracing) containing the same carotid wall tissue and their overlapping degree. Then, we have compared the performance of our approach with the manual traced results drawn by three medical physicians on 37 healthy subjects and 103 unhealthy subjects. The results have showed that our approach was highly correlated (Pearson's correlation coefficient equals 0.9897 for the radial motion and 0.9536 for the longitudinal motion), and agreed well (width the 95% confidence interval is 89.62 µm for the radial motion and 387.26 µm for the longitudinal motion) with the manual tracing method. We also compared our approach to the three kinds of previous methods, including conventional block matching methods, Kalman-based block matching methods and the optical flow. Altogether, we have been able to successfully demonstrate the efficacy of our elasticity-model based state-space approach (EBS) for more accurate tracking of the 2-dimensional motion of the carotid artery wall, towards more effective assessment of the status of atherosclerotic disease in the preclinical stage. Copyright © 2017 Elsevier B.V. All rights reserved.

Periodic-disturbance accommodating control of the space station for asymptotic momentum management

NASA Technical Reports Server (NTRS)

Warren, Wayne; Wie, Bong; Geller, David

1989-01-01

Periodic-disturbance accommodating control is investigated for asymptotic momentum management of control moment gyros used as primary actuating devices for the Space Station. The proposed controller utilizes the concepts of quaternion feedback control and periodic-disturbance accommodation to achieve oscillations about the constant torque equilibrium attitude, while minimizing the control effort required. Three-axis coupled equations of motion, written in terms of quaternions, are derived for roll/yaw controller design and stability analysis. The quaternion feedback controller designed using the linear-quadratic regulator synthesis technique is shown to be robust for a wide range of pitch angles. It is also shown that the proposed controller tunes the open-loop unstable vehicle to a stable oscillatory motion which minimizes the control effort needed for steady-state operations.

Studies of Pilot Control During Launching and Reentry of Space Vehicles, Utilizing the Human Centrifuge

NASA Technical Reports Server (NTRS)

Clark, Carl C.; Woodling, C. H.

1959-01-01

With the ever increasing complexity of airplanes and the nearness to reality of manned space vehicles the use of pilot-controlled flight simulators has become imperative. The state of the art in flight simulation has progressed well with the demand. Pilot-controlled flight simulators are finding increasing uses in aeromedical research, airplane and airplane systems design, and preflight training. At the present many flight simulators are in existence with various degrees of sophistication and sundry purposes. These vary from fixed base simulators where the pilot applies control inputs according to visual cues presented to him on an instrument display to moving base simulators where various combinations of angular and linear motions are added in an attempt to improve the flight simulation.

The Behavior of TCP and Its Extensions in Space

NASA Technical Reports Server (NTRS)

Wang, Ruhai; Horan, Stephen

2001-01-01

The performance of Transmission Control Protocol (TCP) in space has been examined from the observations of simulation and experimental tests for several years at National Aeronautics and Space Administration (NASA), Department of Defense (DoD) and universities. At New Mexico State University (NMSU), we have been concentrating on studying the performance of two protocol suites: the file transfer protocol (ftp) running over Transmission Control Protocol/Internet Protocol (TCP/IP) stack and the file protocol (fp) running over the Space Communications Protocol Standards (SCPS)-Transport Protocol (TP) developed under the Consultative Committee for Space Data Systems (CCSDS) standards process. SCPS-TP is considered to be TCP's extensions for space communications. This dissertation experimentally studies the behavior of TCP and SCPS-TP by running the protocol suites over both the Space-to-Ground Link Simulator (SGLS) test-bed and realistic satellite link. The study concentrates on comparing protocol behavior by plotting the averaged file transfer times for different experimental configurations and analyzing them using Statistical Analysis System (SAS) based procedures. The effects of different link delays and various Bit-Error-Rates (BERS) on each protocol performance are also studied and linear regression models are built for experiments over SGLS test-bed to reflect the relationships between the file transfer time and various transmission conditions.

Dynamical transitions in large systems of mean field-coupled Landau-Stuart oscillators: Extensive chaos and cluster states

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

Ku, Wai Lim; Girvan, Michelle; Ott, Edward

In this paper, we study dynamical systems in which a large number N of identical Landau-Stuart oscillators are globally coupled via a mean-field. Previously, it has been observed that this type of system can exhibit a variety of different dynamical behaviors. These behaviors include time periodic cluster states in which each oscillator is in one of a small number of groups for which all oscillators in each group have the same state which is different from group to group, as well as a behavior in which all oscillators have different states and the macroscopic dynamics of the mean field ismore » chaotic. We argue that this second type of behavior is “extensive” in the sense that the chaotic attractor in the full phase space of the system has a fractal dimension that scales linearly with N and that the number of positive Lyapunov exponents of the attractor also scales linearly with N. An important focus of this paper is the transition between cluster states and extensive chaos as the system is subjected to slow adiabatic parameter change. We observe discontinuous transitions between the cluster states (which correspond to low dimensional dynamics) and the extensively chaotic states. Furthermore, examining the cluster state, as the system approaches the discontinuous transition to extensive chaos, we find that the oscillator population distribution between the clusters continually evolves so that the cluster state is always marginally stable. This behavior is used to reveal the mechanism of the discontinuous transition. We also apply the Kaplan-Yorke formula to study the fractal structure of the extensively chaotic attractors.« less

Optimal linear and nonlinear feature extraction based on the minimization of the increased risk of misclassification. [Bayes theorem - statistical analysis/data processing

NASA Technical Reports Server (NTRS)

Defigueiredo, R. J. P.

1974-01-01

General classes of nonlinear and linear transformations were investigated for the reduction of the dimensionality of the classification (feature) space so that, for a prescribed dimension m of this space, the increase of the misclassification risk is minimized.

A Factorization Approach to the Linear Regulator Quadratic Cost Problem

NASA Technical Reports Server (NTRS)

Milman, M. H.

1985-01-01

A factorization approach to the linear regulator quadratic cost problem is developed. This approach makes some new connections between optimal control, factorization, Riccati equations and certain Wiener-Hopf operator equations. Applications of the theory to systems describable by evolution equations in Hilbert space and differential delay equations in Euclidean space are presented.

Testing the scalar sector of the twin Higgs model at colliders

DOE PAGES

Chacko, Zackaria; Kilic, Can; Najjari, Saereh; ...

2018-03-22

We consider Mirror Twin Higgs models in which the breaking of the global symmetry is realized linearly. In this scenario, the radial mode in the Higgs potential is present in the spectrum, and constitutes a second portal between the twin and SM sectors. We show that a study of the properties of this particle at colliders, when combined with precision measurements of the light Higgs, can be used to overdetermine the form of the scalar potential, thereby confirming that it possesses an enhanced global symmetry as dictated by the Twin Higgs mechanism. We find that, although the reach of themore » LHC for this state is limited, future linear colliders will be able to explore a significant part of the preferred parameter space, allowing the possibility of directly testing the Twin Higgs framework.« less

Solution of the finite Milne problem in stochastic media with RVT Technique

NASA Astrophysics Data System (ADS)

Slama, Howida; El-Bedwhey, Nabila A.; El-Depsy, Alia; Selim, Mustafa M.

2017-12-01

This paper presents the solution to the Milne problem in the steady state with isotropic scattering phase function. The properties of the medium are considered as stochastic ones with Gaussian or exponential distributions and hence the problem treated as a stochastic integro-differential equation. To get an explicit form for the radiant energy density, the linear extrapolation distance, reflectivity and transmissivity in the deterministic case the problem is solved using the Pomraning-Eddington method. The obtained solution is found to be dependent on the optical space variable and thickness of the medium which are considered as random variables. The random variable transformation (RVT) technique is used to find the first probability density function (1-PDF) of the solution process. Then the stochastic linear extrapolation distance, reflectivity and transmissivity are calculated. For illustration, numerical results with conclusions are provided.

Dirac State in Giant Magnetoresistive Materials

NASA Astrophysics Data System (ADS)

Wu, Y.; Jo, N. H.; Ochi, M.; Huang, L.; Mou, D.; Kong, T.; Mun, E.; Wang, L.; Lee, Y.; Bud'Ko, S. L.; Canfield, P. C.; Trivedi, N.; Arito, R.; Kaminski, A.

We use ultrahigh resolution, tunable, vacuum ultraviolet laser-based angle-resolved photoemission spectroscopy (ARPES) to study the electronic properties of materials that recently were discovered to display titanic magnetoresistance. We find that that several of these materials have Dirac-like features in their band structure. In some materials those features are ``ordinary'' Dirac cones, while in others the linear Dirac dispersion of two crossing bands forms a linear object in 3D momentum space. Our observation poses an important question about the role of Dirac dispersion in the unusually high, non-saturating magnetoresistance of these materials. Research was supported by the US DOE, Office of Basic Energy Sciences under Contract No. DE-AC02-07CH11358; Gordon and Betty Moore Foundation EPiQS Initiative (Grant No. GBMF4411); CEM, a NSF MRSEC, under Grant No. DMR-1420451.

Nonlinear Semi-Supervised Metric Learning Via Multiple Kernels and Local Topology.

PubMed

Li, Xin; Bai, Yanqin; Peng, Yaxin; Du, Shaoyi; Ying, Shihui

2018-03-01

Changing the metric on the data may change the data distribution, hence a good distance metric can promote the performance of learning algorithm. In this paper, we address the semi-supervised distance metric learning (ML) problem to obtain the best nonlinear metric for the data. First, we describe the nonlinear metric by the multiple kernel representation. By this approach, we project the data into a high dimensional space, where the data can be well represented by linear ML. Then, we reformulate the linear ML by a minimization problem on the positive definite matrix group. Finally, we develop a two-step algorithm for solving this model and design an intrinsic steepest descent algorithm to learn the positive definite metric matrix. Experimental results validate that our proposed method is effective and outperforms several state-of-the-art ML methods.

Testing the scalar sector of the twin Higgs model at colliders

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

Chacko, Zackaria; Kilic, Can; Najjari, Saereh

We consider Mirror Twin Higgs models in which the breaking of the global symmetry is realized linearly. In this scenario, the radial mode in the Higgs potential is present in the spectrum, and constitutes a second portal between the twin and SM sectors. We show that a study of the properties of this particle at colliders, when combined with precision measurements of the light Higgs, can be used to overdetermine the form of the scalar potential, thereby confirming that it possesses an enhanced global symmetry as dictated by the Twin Higgs mechanism. We find that, although the reach of themore » LHC for this state is limited, future linear colliders will be able to explore a significant part of the preferred parameter space, allowing the possibility of directly testing the Twin Higgs framework.« less

A State-Space Approach to Optimal Level-Crossing Prediction for Linear Gaussian Processes

NASA Technical Reports Server (NTRS)

Martin, Rodney Alexander

2009-01-01

In many complex engineered systems, the ability to give an alarm prior to impending critical events is of great importance. These critical events may have varying degrees of severity, and in fact they may occur during normal system operation. In this article, we investigate approximations to theoretically optimal methods of designing alarm systems for the prediction of level-crossings by a zero-mean stationary linear dynamic system driven by Gaussian noise. An optimal alarm system is designed to elicit the fewest false alarms for a fixed detection probability. This work introduces the use of Kalman filtering in tandem with the optimal level-crossing problem. It is shown that there is a negligible loss in overall accuracy when using approximations to the theoretically optimal predictor, at the advantage of greatly reduced computational complexity. I

Hamiltonian modelling of relative motion.

PubMed

Kasdin, N Jeremy; Gurfil, Pini

2004-05-01

This paper presents a Hamiltonian approach to modelling relative spacecraft motion based on derivation of canonical coordinates for the relative state-space dynamics. The Hamiltonian formulation facilitates the modelling of high-order terms and orbital perturbations while allowing us to obtain closed-form solutions to the relative motion problem. First, the Hamiltonian is partitioned into a linear term and a high-order term. The Hamilton-Jacobi equations are solved for the linear part by separation, and new constants for the relative motions are obtained, they are called epicyclic elements. The influence of higher order terms and perturbations, such as the oblateness of the Earth, are incorporated into the analysis by a variation of parameters procedure. Closed-form solutions for J(2-) and J(4-)invariant orbits and for periodic high-order unperturbed relative motion, in terms of the relative motion elements only, are obtained.

Multiplicity fluctuation analysis of target residues in nucleus-emulsion collisions at a few hundred MeV/nucleon

NASA Astrophysics Data System (ADS)

Zhang, Dong-Hai; Chen, Yan-Ling; Wang, Guo-Rong; Li, Wang-Dong; Wang, Qing; Yao, Ji-Jie; Zhou, Jian-Guo; Zheng, Su-Hua; Xu, Li-Ling; Miao, Hui-Feng; Wang, Peng

2014-07-01

Multiplicity fluctuation of the target evaporated fragments emitted in 290 MeV/u 12C-AgBr, 400 MeV/u 12C-AgBr, 400 MeV/u 20Ne-AgBr and 500 MeV/u 56Fe-AgBr interactions is investigated using the scaled factorial moment method in two-dimensional normal phase space and cumulative variable space, respectively. It is found that in normal phase space the scaled factorial moment (ln) increases linearly with the increase of the divided number of phase space (lnM)for lower q-value and increases linearly with the increase of lnM, and then becomes saturated or decreased for a higher q-value. In cumulative variable space ln decreases linearly with increase of lnM. This indicates that no evidence of non-statistical multiplicity fluctuation is observed in our data sets. So, any fluctuation indicated in the results of normal variable space analysis is totally caused by the non-uniformity of the single-particle density distribution.

Linear and Nonlinear Time-Frequency Analysis for Parameter Estimation of Resident Space Objects

DTIC Science & Technology

2017-02-22

AFRL-AFOSR-UK-TR-2017-0023 Linear and Nonlinear Time -Frequency Analysis for Parameter Estimation of Resident Space Objects Marco Martorella...estimated to average 1 hour per response, including the time for reviewing instructions, searching existing   data sources, gathering and maintaining the...Nonlinear Time -Frequency Analysis for Parameter Estimation of Resident Space Objects 5a.  CONTRACT NUMBER 5b.  GRANT NUMBER FA9550-14-1-0183 5c.  PROGRAM

Bennett's acceptance ratio and histogram analysis methods enhanced by umbrella sampling along a reaction coordinate in configurational space.

PubMed

Kim, Ilsoo; Allen, Toby W

2012-04-28

Free energy perturbation, a method for computing the free energy difference between two states, is often combined with non-Boltzmann biased sampling techniques in order to accelerate the convergence of free energy calculations. Here we present a new extension of the Bennett acceptance ratio (BAR) method by combining it with umbrella sampling (US) along a reaction coordinate in configurational space. In this approach, which we call Bennett acceptance ratio with umbrella sampling (BAR-US), the conditional histogram of energy difference (a mapping of the 3N-dimensional configurational space via a reaction coordinate onto 1D energy difference space) is weighted for marginalization with the associated population density along a reaction coordinate computed by US. This procedure produces marginal histograms of energy difference, from forward and backward simulations, with higher overlap in energy difference space, rendering free energy difference estimations using BAR statistically more reliable. In addition to BAR-US, two histogram analysis methods, termed Bennett overlapping histograms with US (BOH-US) and Bennett-Hummer (linear) least square with US (BHLS-US), are employed as consistency and convergence checks for free energy difference estimation by BAR-US. The proposed methods (BAR-US, BOH-US, and BHLS-US) are applied to a 1-dimensional asymmetric model potential, as has been used previously to test free energy calculations from non-equilibrium processes. We then consider the more stringent test of a 1-dimensional strongly (but linearly) shifted harmonic oscillator, which exhibits no overlap between two states when sampled using unbiased Brownian dynamics. We find that the efficiency of the proposed methods is enhanced over the original Bennett's methods (BAR, BOH, and BHLS) through fast uniform sampling of energy difference space via US in configurational space. We apply the proposed methods to the calculation of the electrostatic contribution to the absolute solvation free energy (excess chemical potential) of water. We then address the controversial issue of ion selectivity in the K(+) ion channel, KcsA. We have calculated the relative binding affinity of K(+) over Na(+) within a binding site of the KcsA channel for which different, though adjacent, K(+) and Na(+) configurations exist, ideally suited to these US-enhanced methods. Our studies demonstrate that the significant improvements in free energy calculations obtained using the proposed methods can have serious consequences for elucidating biological mechanisms and for the interpretation of experimental data.

The MICE grand challenge lightcone simulation - I. Dark matter clustering

NASA Astrophysics Data System (ADS)

Fosalba, P.; Crocce, M.; Gaztañaga, E.; Castander, F. J.

2015-04-01

We present a new N-body simulation from the Marenostrum Institut de Ciències de l'Espai (MICE) collaboration, the MICE Grand Challenge (MICE-GC), containing about 70 billion dark matter particles in a (3 Gpc h-1)3 comoving volume. Given its large volume and fine spatial resolution, spanning over five orders of magnitude in dynamic range, it allows an accurate modelling of the growth of structure in the universe from the linear through the highly non-linear regime of gravitational clustering. We validate the dark matter simulation outputs using 3D and 2D clustering statistics, and discuss mass-resolution effects in the non-linear regime by comparing to previous simulations and the latest numerical fits. We show that the MICE-GC run allows for a measurement of the BAO feature with per cent level accuracy and compare it to state-of-the-art theoretical models. We also use sub-arcmin resolution pixelized 2D maps of the dark matter counts in the lightcone to make tomographic analyses in real and redshift space. Our analysis shows the simulation reproduces the Kaiser effect on large scales, whereas we find a significant suppression of power on non-linear scales relative to the real space clustering. We complete our validation by presenting an analysis of the three-point correlation function in this and previous MICE simulations, finding further evidence for mass-resolution effects. This is the first of a series of three papers in which we present the MICE-GC simulation, along with a wide and deep mock galaxy catalogue built from it. This mock is made publicly available through a dedicated web portal, http://cosmohub.pic.es.

Linear FMCW Laser Radar for Precision Range and Vector Velocity Measurements

NASA Technical Reports Server (NTRS)

Pierrottet, Diego; Amzajerdian, Farzin; Petway, Larry; Barnes, Bruce; Lockhard, George; Rubio, Manuel

2008-01-01

An all fiber linear frequency modulated continuous wave (FMCW) coherent laser radar system is under development with a goal to aide NASA s new Space Exploration initiative for manned and robotic missions to the Moon and Mars. By employing a combination of optical heterodyne and linear frequency modulation techniques and utilizing state-of-the-art fiber optic technologies, highly efficient, compact and reliable laser radar suitable for operation in a space environment is being developed. Linear FMCW lidar has the capability of high-resolution range measurements, and when configured into a multi-channel receiver system it has the capability of obtaining high precision horizontal and vertical velocity measurements. Precision range and vector velocity data are beneficial to navigating planetary landing pods to the preselected site and achieving autonomous, safe soft-landing. The all-fiber coherent laser radar has several important advantages over more conventional pulsed laser altimeters or range finders. One of the advantages of the coherent laser radar is its ability to measure directly the platform velocity by extracting the Doppler shift generated from the motion, as opposed to time of flight range finders where terrain features such as hills, cliffs, or slopes add error to the velocity measurement. Doppler measurements are about two orders of magnitude more accurate than the velocity estimates obtained by pulsed laser altimeters. In addition, most of the components of the device are efficient and reliable commercial off-the-shelf fiber optic telecommunication components. This paper discusses the design and performance of a second-generation brassboard system under development at NASA Langley Research Center as part of the Autonomous Landing and Hazard Avoidance (ALHAT) project.

A Regularized Linear Dynamical System Framework for Multivariate Time Series Analysis.

PubMed

Liu, Zitao; Hauskrecht, Milos

2015-01-01

Linear Dynamical System (LDS) is an elegant mathematical framework for modeling and learning Multivariate Time Series (MTS). However, in general, it is difficult to set the dimension of an LDS's hidden state space. A small number of hidden states may not be able to model the complexities of a MTS, while a large number of hidden states can lead to overfitting. In this paper, we study learning methods that impose various regularization penalties on the transition matrix of the LDS model and propose a regularized LDS learning framework (rLDS) which aims to (1) automatically shut down LDSs' spurious and unnecessary dimensions, and consequently, address the problem of choosing the optimal number of hidden states; (2) prevent the overfitting problem given a small amount of MTS data; and (3) support accurate MTS forecasting. To learn the regularized LDS from data we incorporate a second order cone program and a generalized gradient descent method into the Maximum a Posteriori framework and use Expectation Maximization to obtain a low-rank transition matrix of the LDS model. We propose two priors for modeling the matrix which lead to two instances of our rLDS. We show that our rLDS is able to recover well the intrinsic dimensionality of the time series dynamics and it improves the predictive performance when compared to baselines on both synthetic and real-world MTS datasets.

Paraxial diffractive elements for space-variant linear transforms

NASA Astrophysics Data System (ADS)

Teiwes, Stephan; Schwarzer, Heiko; Gu, Ben-Yuan

1998-06-01

Optical linear transform architectures bear good potential for future developments of very powerful hybrid vision systems and neural network classifiers. The optical modules of such systems could be used as pre-processors to solve complex linear operations at very high speed in order to simplify an electronic data post-processing. However, the applicability of linear optical architectures is strongly connected with the fundamental question of how to implement a specific linear transform by optical means and physical imitations. The large majority of publications on this topic focusses on the optical implementation of space-invariant transforms by the well-known 4f-setup. Only few papers deal with approaches to implement selected space-variant transforms. In this paper, we propose a simple algebraic method to design diffractive elements for an optical architecture in order to realize arbitrary space-variant transforms. The design procedure is based on a digital model of scalar, paraxial wave theory and leads to optimal element transmission functions within the model. Its computational and physical limitations are discussed in terms of complexity measures. Finally, the design procedure is demonstrated by some examples. Firstly, diffractive elements for the realization of different rotation operations are computed and, secondly, a Hough transform element is presented. The correct optical functions of the elements are proved in computer simulation experiments.

Passive millimeter wave differential interference contrast polarimetry

DOEpatents

Bernacki, Bruce E; Kelly, James F; Sheen, David M; Tedeschi, Jonathan R; Hall, Thomas E; Hatchell, Brian K; Valdez, Patrick; McMakin, Douglas L

2014-04-29

Differential polarization imaging systems include an axicon configured to provide a displacement of ray bundles associated with different image patches. The displaced ray bundles are directed to antenna horns and orthomode transducers so as to provide outputs correspond to orthogonal linear states of polarization (SOPs). The outputs are directed to a differential radiometer so that Stokes parameter differences between image patches can be obtained. The ray bundle displacements can be selected to correspond to a mechanical spacing of antenna horns. In some examples, ray bundle displacement corresponds to a displacement less than the diffraction limit.