On the sighting of unicorns: A variational approach to computing invariant sets in dynamical systems

NASA Astrophysics Data System (ADS)

Junge, Oliver; Kevrekidis, Ioannis G.

2017-06-01

We propose to compute approximations to invariant sets in dynamical systems by minimizing an appropriate distance between a suitably selected finite set of points and its image under the dynamics. We demonstrate, through computational experiments, that this approach can successfully converge to approximations of (maximal) invariant sets of arbitrary topology, dimension, and stability, such as, e.g., saddle type invariant sets with complicated dynamics. We further propose to extend this approach by adding a Lennard-Jones type potential term to the objective function, which yields more evenly distributed approximating finite point sets, and illustrate the procedure through corresponding numerical experiments.

On the sighting of unicorns: A variational approach to computing invariant sets in dynamical systems.

PubMed

Junge, Oliver; Kevrekidis, Ioannis G

2017-06-01

We propose to compute approximations to invariant sets in dynamical systems by minimizing an appropriate distance between a suitably selected finite set of points and its image under the dynamics. We demonstrate, through computational experiments, that this approach can successfully converge to approximations of (maximal) invariant sets of arbitrary topology, dimension, and stability, such as, e.g., saddle type invariant sets with complicated dynamics. We further propose to extend this approach by adding a Lennard-Jones type potential term to the objective function, which yields more evenly distributed approximating finite point sets, and illustrate the procedure through corresponding numerical experiments.

Computation of Quasi-Periodic Normally Hyperbolic Invariant Tori: Algorithms, Numerical Explorations and Mechanisms of Breakdown

NASA Astrophysics Data System (ADS)

Canadell, Marta; Haro, Àlex

2017-12-01

We present several algorithms for computing normally hyperbolic invariant tori carrying quasi-periodic motion of a fixed frequency in families of dynamical systems. The algorithms are based on a KAM scheme presented in Canadell and Haro (J Nonlinear Sci, 2016. doi: 10.1007/s00332-017-9389-y), to find the parameterization of the torus with prescribed dynamics by detuning parameters of the model. The algorithms use different hyperbolicity and reducibility properties and, in particular, compute also the invariant bundles and Floquet transformations. We implement these methods in several 2-parameter families of dynamical systems, to compute quasi-periodic arcs, that is, the parameters for which 1D normally hyperbolic invariant tori with a given fixed frequency do exist. The implementation lets us to perform the continuations up to the tip of the quasi-periodic arcs, for which the invariant curves break down. Three different mechanisms of breakdown are analyzed, using several observables, leading to several conjectures.

Algorithms for computations of Loday algebras' invariants

NASA Astrophysics Data System (ADS)

Hussain, Sharifah Kartini Said; Rakhimov, I. S.; Basri, W.

2017-04-01

The paper is devoted to applications of some computer programs to study structural determination of Loday algebras. We present how these computer programs can be applied in computations of various invariants of Loday algebras and provide several computer programs in Maple to verify Loday algebras' identities, the isomorphisms between the algebras, as a special case, to describe the automorphism groups, centroids and derivations.

Slow quenches in two-dimensional time-reversal symmetric Z2 topological insulators

NASA Astrophysics Data System (ADS)

Ulčakar, Lara; Mravlje, Jernej; Ramšak, Anton; Rejec, Tomaž

2018-05-01

We study the topological properties and transport in the Bernevig-Hughes-Zhang model undergoing a slow quench between different topological regimes. Due to the closing of the band gap during the quench, the system ends up in an excited state. We prove that for quenches that preserve the time-reversal symmetry, the Z2 invariant remains equal to the one evaluated in the initial state. On the other hand, the bulk spin Hall conductivity does change, and its time average approaches that of the ground state of the final Hamiltonian. The deviations from the ground-state spin Hall conductivity as a function of the quench time follow the Kibble-Zurek scaling. We also consider the breaking of the time-reversal symmetry, which restores the correspondence between the bulk invariant and the transport properties after the quench.

Rotation-invariant image and video description with local binary pattern features.

PubMed

Zhao, Guoying; Ahonen, Timo; Matas, Jiří; Pietikäinen, Matti

2012-04-01

In this paper, we propose a novel approach to compute rotation-invariant features from histograms of local noninvariant patterns. We apply this approach to both static and dynamic local binary pattern (LBP) descriptors. For static-texture description, we present LBP histogram Fourier (LBP-HF) features, and for dynamic-texture recognition, we present two rotation-invariant descriptors computed from the LBPs from three orthogonal planes (LBP-TOP) features in the spatiotemporal domain. LBP-HF is a novel rotation-invariant image descriptor computed from discrete Fourier transforms of LBP histograms. The approach can be also generalized to embed any uniform features into this framework, and combining the supplementary information, e.g., sign and magnitude components of the LBP, together can improve the description ability. Moreover, two variants of rotation-invariant descriptors are proposed to the LBP-TOP, which is an effective descriptor for dynamic-texture recognition, as shown by its recent success in different application problems, but it is not rotation invariant. In the experiments, it is shown that the LBP-HF and its extensions outperform noninvariant and earlier versions of the rotation-invariant LBP in the rotation-invariant texture classification. In experiments on two dynamic-texture databases with rotations or view variations, the proposed video features can effectively deal with rotation variations of dynamic textures (DTs). They also are robust with respect to changes in viewpoint, outperforming recent methods proposed for view-invariant recognition of DTs.

Computer calculation of Witten's 3-manifold invariant

NASA Astrophysics Data System (ADS)

Freed, Daniel S.; Gompf, Robert E.

1991-10-01

Witten's 2+1 dimensional Chern-Simons theory is exactly solvable. We compute the partition function, a topological invariant of 3-manifolds, on generalized Seifert spaces. Thus we test the path integral using the theory of 3-manifolds. In particular, we compare the exact solution with the asymptotic formula predicted by perturbation theory. We conclude that this path integral works as advertised and gives an effective topological invariant.

Feedback-Driven Dynamic Invariant Discovery

NASA Technical Reports Server (NTRS)

Zhang, Lingming; Yang, Guowei; Rungta, Neha S.; Person, Suzette; Khurshid, Sarfraz

2014-01-01

Program invariants can help software developers identify program properties that must be preserved as the software evolves, however, formulating correct invariants can be challenging. In this work, we introduce iDiscovery, a technique which leverages symbolic execution to improve the quality of dynamically discovered invariants computed by Daikon. Candidate invariants generated by Daikon are synthesized into assertions and instrumented onto the program. The instrumented code is executed symbolically to generate new test cases that are fed back to Daikon to help further re ne the set of candidate invariants. This feedback loop is executed until a x-point is reached. To mitigate the cost of symbolic execution, we present optimizations to prune the symbolic state space and to reduce the complexity of the generated path conditions. We also leverage recent advances in constraint solution reuse techniques to avoid computing results for the same constraints across iterations. Experimental results show that iDiscovery converges to a set of higher quality invariants compared to the initial set of candidate invariants in a small number of iterations.

Accuracy & Computational Considerations for Wide--Angle One--way Seismic Propagators and Multiple Scattering by Invariant Embedding

NASA Astrophysics Data System (ADS)

Thomson, C. J.

2004-12-01

Pseudodifferential operators (PSDOs) yield in principle exact one--way seismic wave equations, which are attractive both conceptually and for their promise of computational efficiency. The one--way operators can be extended to include multiple--scattering effects, again in principle exactly. In practice approximations must be made and, as an example, the variable--wavespeed Helmholtz equation for scalar waves in two space dimensions is here factorized to give the one--way wave equation. This simple case permits clear identification of a sequence of physically reasonable approximations to be used when the mathematically exact PSDO one--way equation is implemented on a computer. As intuition suggests, these approximations hinge on the medium gradients in the direction transverse to the main propagation direction. A key point is that narrow--angle approximations are to be avoided in the interests of accuracy. Another key consideration stems from the fact that the so--called ``standard--ordering'' PSDO indicates how lateral interpolation of the velocity structure can significantly reduce computational costs associated with the Fourier or plane--wave synthesis lying at the heart of the calculations. The decision on whether a slow or a fast Fourier transform code should be used rests upon how many lateral model parameters are truly distinct. A third important point is that the PSDO theory shows what approximations are necessary in order to generate an exponential one--way propagator for the laterally varying case, representing the intuitive extension of classical integral--transform solutions for a laterally homogeneous medium. This exponential propagator suggests the use of larger discrete step sizes, and it can also be used to approach phase--screen like approximations (though the latter are not the main interest here). Numerical comparisons with finite--difference solutions will be presented in order to assess the approximations being made and to gain an understanding of computation time differences. The ideas described extend to the three--dimensional, generally anisotropic case and to multiple scattering by invariant embedding.

Model-Invariant Hybrid Computations of Separated Flows for RCA Standard Test Cases

NASA Technical Reports Server (NTRS)

Woodruff, Stephen

2016-01-01

NASA's Revolutionary Computational Aerosciences (RCA) subproject has identified several smooth-body separated flows as standard test cases to emphasize the challenge these flows present for computational methods and their importance to the aerospace community. Results of computations of two of these test cases, the NASA hump and the FAITH experiment, are presented. The computations were performed with the model-invariant hybrid LES-RANS formulation, implemented in the NASA code VULCAN-CFD. The model- invariant formulation employs gradual LES-RANS transitions and compensation for model variation to provide more accurate and efficient hybrid computations. Comparisons revealed that the LES-RANS transitions employed in these computations were sufficiently gradual that the compensating terms were unnecessary. Agreement with experiment was achieved only after reducing the turbulent viscosity to mitigate the effect of numerical dissipation. The stream-wise evolution of peak Reynolds shear stress was employed as a measure of turbulence dynamics in separated flows useful for evaluating computations.

Complete set of invariants of a 4th order tensor: the 12 tasks of HARDI from ternary quartics.

PubMed

Papadopoulo, Théo; Ghosh, Aurobrata; Deriche, Rachid

2014-01-01

Invariants play a crucial role in Diffusion MRI. In DTI (2nd order tensors), invariant scalars (FA, MD) have been successfully used in clinical applications. But DTI has limitations and HARDI models (e.g. 4th order tensors) have been proposed instead. These, however, lack invariant features and computing them systematically is challenging. We present a simple and systematic method to compute a functionally complete set of invariants of a non-negative 3D 4th order tensor with respect to SO3. Intuitively, this transforms the tensor's non-unique ternary quartic (TQ) decomposition (from Hilbert's theorem) to a unique canonical representation independent of orientation - the invariants. The method consists of two steps. In the first, we reduce the 18 degrees-of-freedom (DOF) of a TQ representation by 3-DOFs via an orthogonal transformation. This transformation is designed to enhance a rotation-invariant property of choice of the 3D 4th order tensor. In the second, we further reduce 3-DOFs via a 3D rotation transformation of coordinates to arrive at a canonical set of invariants to SO3 of the tensor. The resulting invariants are, by construction, (i) functionally complete, (ii) functionally irreducible (if desired), (iii) computationally efficient and (iv) reversible (mappable to the TQ coefficients or shape); which is the novelty of our contribution in comparison to prior work. Results from synthetic and real data experiments validate the method and indicate its importance.

Robust photometric invariant features from the color tensor.

PubMed

van de Weijer, Joost; Gevers, Theo; Smeulders, Arnold W M

2006-01-01

Luminance-based features are widely used as low-level input for computer vision applications, even when color data is available. The extension of feature detection to the color domain prevents information loss due to isoluminance and allows us to exploit the photometric information. To fully exploit the extra information in the color data, the vector nature of color data has to be taken into account and a sound framework is needed to combine feature and photometric invariance theory. In this paper, we focus on the structure tensor, or color tensor, which adequately handles the vector nature of color images. Further, we combine the features based on the color tensor with photometric invariant derivatives to arrive at photometric invariant features. We circumvent the drawback of unstable photometric invariants by deriving an uncertainty measure to accompany the photometric invariant derivatives. The uncertainty is incorporated in the color tensor, hereby allowing the computation of robust photometric invariant features. The combination of the photometric invariance theory and tensor-based features allows for detection of a variety of features such as photometric invariant edges, corners, optical flow, and curvature. The proposed features are tested for noise characteristics and robustness to photometric changes. Experiments show that the proposed features are robust to scene incidental events and that the proposed uncertainty measure improves the applicability of full invariants.

Machine learning strategies for systems with invariance properties

NASA Astrophysics Data System (ADS)

Ling, Julia; Jones, Reese; Templeton, Jeremy

2016-08-01

In many scientific fields, empirical models are employed to facilitate computational simulations of engineering systems. For example, in fluid mechanics, empirical Reynolds stress closures enable computationally-efficient Reynolds Averaged Navier Stokes simulations. Likewise, in solid mechanics, constitutive relations between the stress and strain in a material are required in deformation analysis. Traditional methods for developing and tuning empirical models usually combine physical intuition with simple regression techniques on limited data sets. The rise of high performance computing has led to a growing availability of high fidelity simulation data. These data open up the possibility of using machine learning algorithms, such as random forests or neural networks, to develop more accurate and general empirical models. A key question when using data-driven algorithms to develop these empirical models is how domain knowledge should be incorporated into the machine learning process. This paper will specifically address physical systems that possess symmetry or invariance properties. Two different methods for teaching a machine learning model an invariance property are compared. In the first method, a basis of invariant inputs is constructed, and the machine learning model is trained upon this basis, thereby embedding the invariance into the model. In the second method, the algorithm is trained on multiple transformations of the raw input data until the model learns invariance to that transformation. Results are discussed for two case studies: one in turbulence modeling and one in crystal elasticity. It is shown that in both cases embedding the invariance property into the input features yields higher performance at significantly reduced computational training costs.

Machine learning strategies for systems with invariance properties

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

Ling, Julia; Jones, Reese E.; Templeton, Jeremy Alan

Here, in many scientific fields, empirical models are employed to facilitate computational simulations of engineering systems. For example, in fluid mechanics, empirical Reynolds stress closures enable computationally-efficient Reynolds-Averaged Navier-Stokes simulations. Likewise, in solid mechanics, constitutive relations between the stress and strain in a material are required in deformation analysis. Traditional methods for developing and tuning empirical models usually combine physical intuition with simple regression techniques on limited data sets. The rise of high-performance computing has led to a growing availability of high-fidelity simulation data, which open up the possibility of using machine learning algorithms, such as random forests or neuralmore » networks, to develop more accurate and general empirical models. A key question when using data-driven algorithms to develop these models is how domain knowledge should be incorporated into the machine learning process. This paper will specifically address physical systems that possess symmetry or invariance properties. Two different methods for teaching a machine learning model an invariance property are compared. In the first , a basis of invariant inputs is constructed, and the machine learning model is trained upon this basis, thereby embedding the invariance into the model. In the second method, the algorithm is trained on multiple transformations of the raw input data until the model learns invariance to that transformation. Results are discussed for two case studies: one in turbulence modeling and one in crystal elasticity. It is shown that in both cases embedding the invariance property into the input features yields higher performance with significantly reduced computational training costs.« less

Machine learning strategies for systems with invariance properties

DOE PAGES

Ling, Julia; Jones, Reese E.; Templeton, Jeremy Alan

2016-05-06

Here, in many scientific fields, empirical models are employed to facilitate computational simulations of engineering systems. For example, in fluid mechanics, empirical Reynolds stress closures enable computationally-efficient Reynolds-Averaged Navier-Stokes simulations. Likewise, in solid mechanics, constitutive relations between the stress and strain in a material are required in deformation analysis. Traditional methods for developing and tuning empirical models usually combine physical intuition with simple regression techniques on limited data sets. The rise of high-performance computing has led to a growing availability of high-fidelity simulation data, which open up the possibility of using machine learning algorithms, such as random forests or neuralmore » networks, to develop more accurate and general empirical models. A key question when using data-driven algorithms to develop these models is how domain knowledge should be incorporated into the machine learning process. This paper will specifically address physical systems that possess symmetry or invariance properties. Two different methods for teaching a machine learning model an invariance property are compared. In the first , a basis of invariant inputs is constructed, and the machine learning model is trained upon this basis, thereby embedding the invariance into the model. In the second method, the algorithm is trained on multiple transformations of the raw input data until the model learns invariance to that transformation. Results are discussed for two case studies: one in turbulence modeling and one in crystal elasticity. It is shown that in both cases embedding the invariance property into the input features yields higher performance with significantly reduced computational training costs.« less

Numerosity as a topological invariant.

PubMed

Kluth, Tobias; Zetzsche, Christoph

2016-01-01

The ability to quickly recognize the number of objects in our environment is a fundamental cognitive function. However, it is far from clear which computations and which actual neural processing mechanisms are used to provide us with such a skill. Here we try to provide a detailed and comprehensive analysis of this issue, which comprises both the basic mathematical foundations and the peculiarities imposed by the structure of the visual system and by the neural computations provided by the visual cortex. We suggest that numerosity should be considered as a mathematical invariant. Making use of concepts from mathematical topology--like connectedness, Betti numbers, and the Gauss-Bonnet theorem--we derive the basic computations suited for the computation of this invariant. We show that the computation of numerosity is possible in a neurophysiologically plausible fashion using only computational elements which are known to exist in the visual cortex. We further show that a fundamental feature of numerosity perception, its Weber property, arises naturally, assuming noise in the basic neural operations. The model is tested on an extended data set (made publicly available). It is hoped that our results can provide a general framework for future research on the invariance properties of the numerosity system.

The development of newborn object recognition in fast and slow visual worlds

PubMed Central

Wood, Justin N.; Wood, Samantha M. W.

2016-01-01

Object recognition is central to perception and cognition. Yet relatively little is known about the environmental factors that cause invariant object recognition to emerge in the newborn brain. Is this ability a hardwired property of vision? Or does the development of invariant object recognition require experience with a particular kind of visual environment? Here, we used a high-throughput controlled-rearing method to examine whether newborn chicks (Gallus gallus) require visual experience with slowly changing objects to develop invariant object recognition abilities. When newborn chicks were raised with a slowly rotating virtual object, the chicks built invariant object representations that generalized across novel viewpoints and rotation speeds. In contrast, when newborn chicks were raised with a virtual object that rotated more quickly, the chicks built viewpoint-specific object representations that failed to generalize to novel viewpoints and rotation speeds. Moreover, there was a direct relationship between the speed of the object and the amount of invariance in the chick's object representation. Thus, visual experience with slowly changing objects plays a critical role in the development of invariant object recognition. These results indicate that invariant object recognition is not a hardwired property of vision, but is learned rapidly when newborns encounter a slowly changing visual world. PMID:27097925

Modular invariant inflation

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

Kobayashi, Tatsuo; Nitta, Daisuke; Urakawa, Yuko

2016-08-08

Modular invariance is a striking symmetry in string theory, which may keep stringy corrections under control. In this paper, we investigate a phenomenological consequence of the modular invariance, assuming that this symmetry is preserved as well as in a four dimensional (4D) low energy effective field theory. As a concrete setup, we consider a modulus field T whose contribution in the 4D effective field theory remains invariant under the modular transformation and study inflation drived by T. The modular invariance restricts a possible form of the scalar potenntial. As a result, large field models of inflation are hardly realized. Meanwhile,more » a small field model of inflation can be still accomodated in this restricted setup. The scalar potential traced during the slow-roll inflation mimics the hilltop potential V{sub ht}, but it also has a non-negligible deviation from V{sub ht}. Detecting the primordial gravitational waves predicted in this model is rather challenging. Yet, we argue that it may be still possible to falsify this model by combining the information in the reheating process which can be determined self-completely in this setup.« less

Computation of pattern invariance in brain-like structures.

PubMed

Ullman, S; Soloviev, S

1999-10-01

A fundamental capacity of the perceptual systems and the brain in general is to deal with the novel and the unexpected. In vision, we can effortlessly recognize a familiar object under novel viewing conditions, or recognize a new object as a member of a familiar class, such as a house, a face, or a car. This ability to generalize and deal efficiently with novel stimuli has long been considered a challenging example of brain-like computation that proved extremely difficult to replicate in artificial systems. In this paper we present an approach to generalization and invariant recognition. We focus our discussion on the problem of invariance to position in the visual field, but also sketch how similar principles could apply to other domains.The approach is based on the use of a large repertoire of partial generalizations that are built upon past experience. In the case of shift invariance, visual patterns are described as the conjunction of multiple overlapping image fragments. The invariance to the more primitive fragments is built into the system by past experience. Shift invariance of complex shapes is obtained from the invariance of their constituent fragments. We study by simulations aspects of this shift invariance method and then consider its extensions to invariant perception and classification by brain-like structures.

On Integral Invariants for Effective 3-D Motion Trajectory Matching and Recognition.

PubMed

Shao, Zhanpeng; Li, Youfu

2016-02-01

Motion trajectories tracked from the motions of human, robots, and moving objects can provide an important clue for motion analysis, classification, and recognition. This paper defines some new integral invariants for a 3-D motion trajectory. Based on two typical kernel functions, we design two integral invariants, the distance and area integral invariants. The area integral invariants are estimated based on the blurred segment of noisy discrete curve to avoid the computation of high-order derivatives. Such integral invariants for a motion trajectory enjoy some desirable properties, such as computational locality, uniqueness of representation, and noise insensitivity. Moreover, our formulation allows the analysis of motion trajectories at a range of scales by varying the scale of kernel function. The features of motion trajectories can thus be perceived at multiscale levels in a coarse-to-fine manner. Finally, we define a distance function to measure the trajectory similarity to find similar trajectories. Through the experiments, we examine the robustness and effectiveness of the proposed integral invariants and find that they can capture the motion cues in trajectory matching and sign recognition satisfactorily.

SHARP ENTRYWISE PERTURBATION BOUNDS FOR MARKOV CHAINS.

PubMed

Thiede, Erik; VAN Koten, Brian; Weare, Jonathan

For many Markov chains of practical interest, the invariant distribution is extremely sensitive to perturbations of some entries of the transition matrix, but insensitive to others; we give an example of such a chain, motivated by a problem in computational statistical physics. We have derived perturbation bounds on the relative error of the invariant distribution that reveal these variations in sensitivity. Our bounds are sharp, we do not impose any structural assumptions on the transition matrix or on the perturbation, and computing the bounds has the same complexity as computing the invariant distribution or computing other bounds in the literature. Moreover, our bounds have a simple interpretation in terms of hitting times, which can be used to draw intuitive but rigorous conclusions about the sensitivity of a chain to various types of perturbations.

The time-delay signature of quark-gluon plasma formation in relativistic nuclear collisions

NASA Astrophysics Data System (ADS)

Rischke, Dirk H.; Gyulassy, Miklos

1996-02-01

The hydrodynamic expansion of quark-gluon plasmas with spherical and longitudinally boost-invariant geometries is studied as a function of the initial energy density. The sensitivity of the collective flow pattern to uncertainties in the nuclear matter equation of state is explored. We concentrate on the effect of a possible finite width, ΔT ˜ 0.1 Tc, of the transition region between quark-gluon plasma and hadronic phase. Although slow deflagration solutions that act to stall the expansion do not exist for ΔT > 0.08 Tc, we find, nevertheless, that the equation of state remains sufficiently soft in the transition region to delay the propagation of ordinary rarefaction waves for a considerable time. We compute the dependence of the pion-interferometry correlation function on ΔT, since this is the most promising observable for time-delayed expansion. The signature of time delay, proposed by Pratt and Bertsch, is an enhancement of the ratio of the inverse width of the pion correlation function in out-direction to that in side-direction. One of our main results is that this generic signature of quark-gluon plasma formation is rather robust to the uncertainties in the width of the transition region. Furthermore, for longitudinal boost-invariant geometries, the signal is likely to be maximized around RHIC energies

Evaluating measurement invariance across assessment modes of phone interview and computer self-administered survey for the PROMIS measures in a population-based cohort of localized prostate cancer survivors.

PubMed

Wang, Mian; Chen, Ronald C; Usinger, Deborah S; Reeve, Bryce B

2017-11-01

To evaluate measurement invariance (phone interview vs computer self-administered survey) of 15 PROMIS measures responded by a population-based cohort of localized prostate cancer survivors. Participants were part of the North Carolina Prostate Cancer Comparative Effectiveness and Survivorship Study. Out of the 952 men who took the phone interview at 24 months post-treatment, 401 of them also completed the same survey online using a home computer. Unidimensionality of the PROMIS measures was examined using single-factor confirmatory factor analysis (CFA) models. Measurement invariance testing was conducted using longitudinal CFA via a model comparison approach. For strongly or partially strongly invariant measures, changes in the latent factors and factor autocorrelations were also estimated and tested. Six measures (sleep disturbance, sleep-related impairment, diarrhea, illness impact-negative, illness impact-positive, and global satisfaction with sex life) had locally dependent items, and therefore model modifications had to be made on these domains prior to measurement invariance testing. Overall, seven measures achieved strong invariance (all items had equal loadings and thresholds), and four measures achieved partial strong invariance (each measure had one item with unequal loadings and thresholds). Three measures (pain interference, interest in sexual activity, and global satisfaction with sex life) failed to establish configural invariance due to between-mode differences in factor patterns. This study supports the use of phone-based live interviewers in lieu of PC-based assessment (when needed) for many of the PROMIS measures.

Neural-Network Object-Recognition Program

NASA Technical Reports Server (NTRS)

Spirkovska, L.; Reid, M. B.

1993-01-01

HONTIOR computer program implements third-order neural network exhibiting invariance under translation, change of scale, and in-plane rotation. Invariance incorporated directly into architecture of network. Only one view of each object needed to train network for two-dimensional-translation-invariant recognition of object. Also used for three-dimensional-transformation-invariant recognition by training network on only set of out-of-plane rotated views. Written in C language.

Using the Kernel Method of Test Equating for Estimating the Standard Errors of Population Invariance Measures. Research Report. ETS RR-06-20

ERIC Educational Resources Information Center

Moses, Tim

2006-01-01

Population invariance is an important requirement of test equating. An equating function is said to be population invariant when the choice of (sub)population used to compute the equating function does not matter. In recent studies, the extent to which equating functions are population invariant is typically addressed in terms of practical…

Invariance of an Extended Technology Acceptance Model Across Gender and Age Group

ERIC Educational Resources Information Center

Ahmad, Tunku Badariah Tunku; Madarsha, Kamal Basha; Zainuddin, Ahmad Marzuki; Ismail, Nik Ahmad Hisham; Khairani, Ahmad Zamri; Nordin, Mohamad Sahari

2011-01-01

In this study, we examined the likelihood of a TAME (extended technology acceptance model), in which the interrelationships among computer self-efficacy, perceived usefulness, intention to use and self-reported use of computer-mediated technology were tested. In addition, the gender- and age-invariant of its causal structure were evaluated. The…

Scope and applications of translation invariant wavelets to image registration

NASA Technical Reports Server (NTRS)

Chettri, Samir; LeMoigne, Jacqueline; Campbell, William

1997-01-01

The first part of this article introduces the notion of translation invariance in wavelets and discusses several wavelets that have this property. The second part discusses the possible applications of such wavelets to image registration. In the case of registration of affinely transformed images, we would conclude that the notion of translation invariance is not really necessary. What is needed is affine invariance and one way to do this is via the method of moment invariants. Wavelets or, in general, pyramid processing can then be combined with the method of moment invariants to reduce the computational load.

Cartan invariants and event horizon detection

NASA Astrophysics Data System (ADS)

Brooks, D.; Chavy-Waddy, P. C.; Coley, A. A.; Forget, A.; Gregoris, D.; MacCallum, M. A. H.; McNutt, D. D.

2018-04-01

We show that it is possible to locate the event horizon of a black hole (in arbitrary dimensions) by the zeros of certain Cartan invariants. This approach accounts for the recent results on the detection of stationary horizons using scalar polynomial curvature invariants, and improves upon them since the proposed method is computationally less expensive. As an application, we produce Cartan invariants that locate the event horizons for various exact four-dimensional and five-dimensional stationary, asymptotically flat (or (anti) de Sitter), black hole solutions and compare the Cartan invariants with the corresponding scalar curvature invariants that detect the event horizon.

Computation of Quasiperiodic Normally Hyperbolic Invariant Tori: Rigorous Results

NASA Astrophysics Data System (ADS)

Canadell, Marta; Haro, Àlex

2017-12-01

The development of efficient methods for detecting quasiperiodic oscillations and computing the corresponding invariant tori is a subject of great importance in dynamical systems and their applications in science and engineering. In this paper, we prove the convergence of a new Newton-like method for computing quasiperiodic normally hyperbolic invariant tori carrying quasiperiodic motion in smooth families of real-analytic dynamical systems. The main result is stated as an a posteriori KAM-like theorem that allows controlling the inner dynamics on the torus with appropriate detuning parameters, in order to obtain a prescribed quasiperiodic motion. The Newton-like method leads to several fast and efficient computational algorithms, which are discussed and tested in a companion paper (Canadell and Haro in J Nonlinear Sci, 2017. doi: 10.1007/s00332-017-9388-z), in which new mechanisms of breakdown are presented.

Combinatorial invariants and covariants as tools for conical intersections.

PubMed

Ryb, Itai; Baer, Roi

2004-12-01

The combinatorial invariant and covariant are introduced as practical tools for analysis of conical intersections in molecules. The combinatorial invariant is a quantity depending on adiabatic electronic states taken at discrete nuclear configuration points. It is invariant to the phase choice (gauge) of these states. In the limit that the points trace a loop in nuclear configuration space, the value of the invariant approaches the corresponding Berry phase factor. The Berry phase indicates the presence of an odd or even number of conical intersections on surfaces bounded by these loops. Based on the combinatorial invariant, we develop a computationally simple and efficient method for locating conical intersections. The method is robust due to its use of gauge invariant nature. It does not rely on the landscape of intersecting potential energy surfaces nor does it require the computation of nonadiabatic couplings. We generalize the concept to open paths and combinatorial covariants for higher dimensions obtaining a technique for the construction of the gauge-covariant adiabatic-diabatic transformation matrix. This too does not make use of nonadiabatic couplings. The importance of using gauge-covariant expressions is underlined throughout. These techniques can be readily implemented by standard quantum chemistry codes. (c) 2004 American Institute of Physics.

Singular Perturbations and Time-Scale Methods in Control Theory: Survey 1976-1982.

DTIC Science & Technology

1982-12-01

established in the 1960s, when they first became a means for simplified computation of optimal trajectories. It was soon recognized that singular...null-space of P(ao). The asymptotic values of the invariant zeros and associated invariant-zero directions as € O are the values computed from the...49 ’ 49 7. WEAK COUPLING AND TIME SCALES The need for model simplification with a reduction (or distribution) of computational effort is

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

Meeks, Kelsey; Pantoya, Michelle L.; Green, Micah

For dispersions containing a single type of particle, it has been observed that the onset of percolation coincides with a critical value of volume fraction. When the volume fraction is calculated based on excluded volume, this critical percolation threshold is nearly invariant to particle shape. The critical threshold has been calculated to high precision for simple geometries using Monte Carlo simulations, but this method is slow at best, and infeasible for complex geometries. This article explores an analytical approach to the prediction of percolation threshold in polydisperse mixtures. Specifically, this paper suggests an extension of the concept of excluded volume,more » and applies that extension to the 2D binary disk system. The simple analytical expression obtained is compared to Monte Carlo results from the literature. In conclusion, the result may be computed extremely rapidly and matches key parameters closely enough to be useful for composite material design.« less

Time-scale invariance as an emergent property in a perceptron with realistic, noisy neurons

PubMed Central

Buhusi, Catalin V.; Oprisan, Sorinel A.

2013-01-01

In most species, interval timing is time-scale invariant: errors in time estimation scale up linearly with the estimated duration. In mammals, time-scale invariance is ubiquitous over behavioral, lesion, and pharmacological manipulations. For example, dopaminergic drugs induce an immediate, whereas cholinergic drugs induce a gradual, scalar change in timing. Behavioral theories posit that time-scale invariance derives from particular computations, rules, or coding schemes. In contrast, we discuss a simple neural circuit, the perceptron, whose output neurons fire in a clockwise fashion (interval timing) based on the pattern of coincidental activation of its input neurons. We show numerically that time-scale invariance emerges spontaneously in a perceptron with realistic neurons, in the presence of noise. Under the assumption that dopaminergic drugs modulate the firing of input neurons, and that cholinergic drugs modulate the memory representation of the criterion time, we show that a perceptron with realistic neurons reproduces the pharmacological clock and memory patterns, and their time-scale invariance, in the presence of noise. These results suggest that rather than being a signature of higher-order cognitive processes or specific computations related to timing, time-scale invariance may spontaneously emerge in a massively-connected brain from the intrinsic noise of neurons and circuits, thus providing the simplest explanation for the ubiquity of scale invariance of interval timing. PMID:23518297

Using the Kernel Method of Test Equating for Estimating the Standard Errors of Population Invariance Measures

ERIC Educational Resources Information Center

Moses, Tim

2008-01-01

Equating functions are supposed to be population invariant, meaning that the choice of subpopulation used to compute the equating function should not matter. The extent to which equating functions are population invariant is typically assessed in terms of practical difference criteria that do not account for equating functions' sampling…

Scale invariant texture descriptors for classifying celiac disease

PubMed Central

Hegenbart, Sebastian; Uhl, Andreas; Vécsei, Andreas; Wimmer, Georg

2013-01-01

Scale invariant texture recognition methods are applied for the computer assisted diagnosis of celiac disease. In particular, emphasis is given to techniques enhancing the scale invariance of multi-scale and multi-orientation wavelet transforms and methods based on fractal analysis. After fine-tuning to specific properties of our celiac disease imagery database, which consists of endoscopic images of the duodenum, some scale invariant (and often even viewpoint invariant) methods provide classification results improving the current state of the art. However, not each of the investigated scale invariant methods is applicable successfully to our dataset. Therefore, the scale invariance of the employed approaches is explicitly assessed and it is found that many of the analyzed methods are not as scale invariant as they theoretically should be. Results imply that scale invariance is not a key-feature required for successful classification of our celiac disease dataset. PMID:23481171

Hidden scale invariance of metals

NASA Astrophysics Data System (ADS)

Hummel, Felix; Kresse, Georg; Dyre, Jeppe C.; Pedersen, Ulf R.

2015-11-01

Density functional theory (DFT) calculations of 58 liquid elements at their triple point show that most metals exhibit near proportionality between the thermal fluctuations of the virial and the potential energy in the isochoric ensemble. This demonstrates a general "hidden" scale invariance of metals making the condensed part of the thermodynamic phase diagram effectively one dimensional with respect to structure and dynamics. DFT computed density scaling exponents, related to the Grüneisen parameter, are in good agreement with experimental values for the 16 elements where reliable data were available. Hidden scale invariance is demonstrated in detail for magnesium by showing invariance of structure and dynamics. Computed melting curves of period three metals follow curves with invariance (isomorphs). The experimental structure factor of magnesium is predicted by assuming scale invariant inverse power-law (IPL) pair interactions. However, crystal packings of several transition metals (V, Cr, Mn, Fe, Nb, Mo, Ta, W, and Hg), most post-transition metals (Ga, In, Sn, and Tl), and the metalloids Si and Ge cannot be explained by the IPL assumption. The virial-energy correlation coefficients of iron and phosphorous are shown to increase at elevated pressures. Finally, we discuss how scale invariance explains the Grüneisen equation of state and a number of well-known empirical melting and freezing rules.

Mixing properties of the one-atom maser

NASA Astrophysics Data System (ADS)

Bruneau, Laurent

2014-06-01

We study the relaxation properties of the quantized electromagnetic field in a cavity under repeated interactions with single two-level atoms, so-called one-atom maser. We improve the ergodic results obtained in Bruneau and Pillet (J Stat Phys 134(5-6):1071-1095, 2009) and prove that, whenever the atoms are initially distributed according to the canonical ensemble at temperature , all the invariant states are mixing. Under some non-resonance condition this invariant state is known to be thermal equilibirum at some renormalized temperature and we prove that the mixing is then arbitrarily slow, in other words that there is no lower bound on the relaxation speed.

A Balanced Comparison of Object Invariances in Monkey IT Neurons.

PubMed

Ratan Murty, N Apurva; Arun, Sripati P

2017-01-01

Our ability to recognize objects across variations in size, position, or rotation is based on invariant object representations in higher visual cortex. However, we know little about how these invariances are related. Are some invariances harder than others? Do some invariances arise faster than others? These comparisons can be made only upon equating image changes across transformations. Here, we targeted invariant neural representations in the monkey inferotemporal (IT) cortex using object images with balanced changes in size, position, and rotation. Across the recorded population, IT neurons generalized across size and position both stronger and faster than to rotations in the image plane as well as in depth. We obtained a similar ordering of invariances in deep neural networks but not in low-level visual representations. Thus, invariant neural representations dynamically evolve in a temporal order reflective of their underlying computational complexity.

Propagators for gauge-invariant observables in cosmology

NASA Astrophysics Data System (ADS)

Fröb, Markus B.; Lima, William C. C.

2018-05-01

We make a proposal for gauge-invariant observables in perturbative quantum gravity in cosmological spacetimes, building on the recent work of Brunetti et al (2016 J. High Energy Phys. JHEP08(2016)032). These observables are relational, and are obtained by evaluating the field operator in a field-dependent coordinate system. We show that it is possible to define this coordinate system such that the non-localities inherent in any higher-order observable in quantum gravity are causal, i.e. the value of the gauge-invariant observable at a point x only depends on the metric and inflation perturbations in the past light cone of x. We then construct propagators for the metric and inflaton perturbations in a gauge adapted to that coordinate system, which simplifies the calculation of loop corrections, and give explicit expressions for relevant cases: matter- and radiation-dominated eras and slow-roll inflation.

FAST TRACK COMMUNICATION: On the Liouvillian solution of second-order linear differential equations and algebraic invariant curves

NASA Astrophysics Data System (ADS)

Man, Yiu-Kwong

2010-10-01

In this communication, we present a method for computing the Liouvillian solution of second-order linear differential equations via algebraic invariant curves. The main idea is to integrate Kovacic's results on second-order linear differential equations with the Prelle-Singer method for computing first integrals of differential equations. Some examples on using this approach are provided.

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

Hill, Christopher T.

We review and expand upon recent work demonstrating that Weyl invariant theories can be broken "inertially," which does not depend upon a potential. This can be understood in a general way by the "current algebra" of these theories, independently of specific Lagrangians. Maintaining the exact Weyl invariance in a renormalized quantum theory can be accomplished by renormalization conditions that refer back to the VEV's of fields in the action. We illustrate the computation of a Weyl invariant Coleman-Weinberg potential that breaks a U(1) symmetry together,with scale invariance.

The Invar tensor package: Differential invariants of Riemann

NASA Astrophysics Data System (ADS)

Martín-García, J. M.; Yllanes, D.; Portugal, R.

2008-10-01

The long standing problem of the relations among the scalar invariants of the Riemann tensor is computationally solved for all 6ṡ10 objects with up to 12 derivatives of the metric. This covers cases ranging from products of up to 6 undifferentiated Riemann tensors to cases with up to 10 covariant derivatives of a single Riemann. We extend our computer algebra system Invar to produce within seconds a canonical form for any of those objects in terms of a basis. The process is as follows: (1) an invariant is converted in real time into a canonical form with respect to the permutation symmetries of the Riemann tensor; (2) Invar reads a database of more than 6ṡ10 relations and applies those coming from the cyclic symmetry of the Riemann tensor; (3) then applies the relations coming from the Bianchi identity, (4) the relations coming from commutations of covariant derivatives, (5) the dimensionally-dependent identities for dimension 4, and finally (6) simplifies invariants that can be expressed as product of dual invariants. Invar runs on top of the tensor computer algebra systems xTensor (for Mathematica) and Canon (for Maple). Program summaryProgram title:Invar Tensor Package v2.0 Catalogue identifier:ADZK_v2_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/ADZK_v2_0.html Program obtainable from:CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions:Standard CPC licence, http://cpc.cs.qub.ac.uk/licence/licence.html No. of lines in distributed program, including test data, etc.:3 243 249 No. of bytes in distributed program, including test data, etc.:939 Distribution format:tar.gz Programming language:Mathematica and Maple Computer:Any computer running Mathematica versions 5.0 to 6.0 or Maple versions 9 and 11 Operating system:Linux, Unix, Windows XP, MacOS RAM:100 Mb Word size:64 or 32 bits Supplementary material:The new database of relations is much larger than that for the previous version and therefore has not been included in the distribution. To obtain the Mathematica and Maple database files click on this link. Classification:1.5, 5 Does the new version supersede the previous version?:Yes. The previous version (1.0) only handled algebraic invariants. The current version (2.0) has been extended to cover differential invariants as well. Nature of problem:Manipulation and simplification of scalar polynomial expressions formed from the Riemann tensor and its covariant derivatives. Solution method:Algorithms of computational group theory to simplify expressions with tensors that obey permutation symmetries. Tables of syzygies of the scalar invariants of the Riemann tensor. Reasons for new version:With this new version, the user can manipulate differential invariants of the Riemann tensor. Differential invariants are required in many physical problems in classical and quantum gravity. Summary of revisions:The database of syzygies has been expanded by a factor of 30. New commands were added in order to deal with the enlarged database and to manipulate the covariant derivative. Restrictions:The present version only handles scalars, and not expressions with free indices. Additional comments:The distribution file for this program is over 53 Mbytes and therefore is not delivered directly when download or Email is requested. Instead a html file giving details of how the program can be obtained is sent. Running time:One second to fully reduce any monomial of the Riemann tensor up to degree 7 or order 10 in terms of independent invariants. The Mathematica notebook included in the distribution takes approximately 5 minutes to run.

n-D shape/texture optimal synthetic description and modeling by GEOGINE

NASA Astrophysics Data System (ADS)

Fiorini, Rodolfo A.; Dacquino, Gianfranco F.

2004-12-01

GEOGINE(GEOmetrical enGINE), a state-of-the-art OMG (Ontological Model Generator) based on n-D Tensor Invariants for multidimensional shape/texture optimal synthetic description and learning, is presented. Usually elementary geometric shape robust characterization, subjected to geometric transformation, on a rigorous mathematical level is a key problem in many computer applications in different interest areas. The past four decades have seen solutions almost based on the use of n-Dimensional Moment and Fourier descriptor invariants. The present paper introduces a new approach for automatic model generation based on n -Dimensional Tensor Invariants as formal dictionary. An ontological model is the kernel used for specifying ontologies so that how close an ontology can be from the real world depends on the possibilities offered by the ontological model. By this approach even chromatic information content can be easily and reliably decoupled from target geometric information and computed into robus colour shape parameter attributes. Main GEOGINEoperational advantages over previous approaches are: 1) Automated Model Generation, 2) Invariant Minimal Complete Set for computational efficiency, 3) Arbitrary Model Precision for robust object description.

Transport in Dynamical Astronomy and Multibody Problems

NASA Astrophysics Data System (ADS)

Dellnitz, Michael; Junge, Oliver; Koon, Wang Sang; Lekien, Francois; Lo, Martin W.; Marsden, Jerrold E.; Padberg, Kathrin; Preis, Robert; Ross, Shane D.; Thiere, Bianca

We combine the techniques of almost invariant sets (using tree structured box elimination and graph partitioning algorithms) with invariant manifold and lobe dynamics techniques. The result is a new computational technique for computing key dynamical features, including almost invariant sets, resonance regions as well as transport rates and bottlenecks between regions in dynamical systems. This methodology can be applied to a variety of multibody problems, including those in molecular modeling, chemical reaction rates and dynamical astronomy. In this paper we focus on problems in dynamical astronomy to illustrate the power of the combination of these different numerical tools and their applicability. In particular, we compute transport rates between two resonance regions for the three-body system consisting of the Sun, Jupiter and a third body (such as an asteroid). These resonance regions are appropriate for certain comets and asteroids.

A Balanced Comparison of Object Invariances in Monkey IT Neurons

PubMed Central

2017-01-01

Abstract Our ability to recognize objects across variations in size, position, or rotation is based on invariant object representations in higher visual cortex. However, we know little about how these invariances are related. Are some invariances harder than others? Do some invariances arise faster than others? These comparisons can be made only upon equating image changes across transformations. Here, we targeted invariant neural representations in the monkey inferotemporal (IT) cortex using object images with balanced changes in size, position, and rotation. Across the recorded population, IT neurons generalized across size and position both stronger and faster than to rotations in the image plane as well as in depth. We obtained a similar ordering of invariances in deep neural networks but not in low-level visual representations. Thus, invariant neural representations dynamically evolve in a temporal order reflective of their underlying computational complexity. PMID:28413827

Fully Numerical Methods for Continuing Families of Quasi-Periodic Invariant Tori in Astrodynamics

NASA Astrophysics Data System (ADS)

Baresi, Nicola; Olikara, Zubin P.; Scheeres, Daniel J.

2018-06-01

Quasi-periodic invariant tori are of great interest in astrodynamics because of their capability to further expand the design space of satellite missions. However, there is no general consent on what is the best methodology for computing these dynamical structures. This paper compares the performance of four different approaches available in the literature. The first two methods compute invariant tori of flows by solving a system of partial differential equations via either central differences or Fourier techniques. In contrast, the other two strategies calculate invariant curves of maps via shooting algorithms: one using surfaces of section, and one using a stroboscopic map. All of the numerical procedures are tested in the co-rotating frame of the Earth as well as in the planar circular restricted three-body problem. The results of our numerical simulations show which of the reviewed procedures should be preferred for future studies of astrodynamics systems.

Fully Numerical Methods for Continuing Families of Quasi-Periodic Invariant Tori in Astrodynamics

NASA Astrophysics Data System (ADS)

Baresi, Nicola; Olikara, Zubin P.; Scheeres, Daniel J.

2018-01-01

Quasi-periodic invariant tori are of great interest in astrodynamics because of their capability to further expand the design space of satellite missions. However, there is no general consent on what is the best methodology for computing these dynamical structures. This paper compares the performance of four different approaches available in the literature. The first two methods compute invariant tori of flows by solving a system of partial differential equations via either central differences or Fourier techniques. In contrast, the other two strategies calculate invariant curves of maps via shooting algorithms: one using surfaces of section, and one using a stroboscopic map. All of the numerical procedures are tested in the co-rotating frame of the Earth as well as in the planar circular restricted three-body problem. The results of our numerical simulations show which of the reviewed procedures should be preferred for future studies of astrodynamics systems.

Projection rule for complex-valued associative memory with large constant terms

NASA Astrophysics Data System (ADS)

Kitahara, Michimasa; Kobayashi, Masaki

Complex-valued Associative Memory (CAM) has an inherent property of rotation invariance. Rotation invariance produces many undesirable stable states and reduces the noise robustness of CAM. Constant terms may remove rotation invariance, but if the constant terms are too small, rotation invariance does not vanish. In this paper, we eliminate rotation invariance by introducing large constant terms to complex-valued neurons. We have to make constant terms sufficiently large to improve the noise robustness. We introduce a parameter to control the amplitudes of constant terms into projection rule. The large constant terms are proved to be effective by our computer simulations.

Affine invariants of convex polygons.

PubMed

Flusser, Jan

2002-01-01

In this correspondence, we prove that the affine invariants, for image registration and object recognition, proposed recently by Yang and Cohen (see ibid., vol.8, no.7, p.934-46, July 1999) are algebraically dependent. We show how to select an independent and complete set of the invariants. The use of this new set leads to a significant reduction of the computing complexity without decreasing the discrimination power.

A Geometric Method for Model Reduction of Biochemical Networks with Polynomial Rate Functions.

PubMed

Samal, Satya Swarup; Grigoriev, Dima; Fröhlich, Holger; Weber, Andreas; Radulescu, Ovidiu

2015-12-01

Model reduction of biochemical networks relies on the knowledge of slow and fast variables. We provide a geometric method, based on the Newton polytope, to identify slow variables of a biochemical network with polynomial rate functions. The gist of the method is the notion of tropical equilibration that provides approximate descriptions of slow invariant manifolds. Compared to extant numerical algorithms such as the intrinsic low-dimensional manifold method, our approach is symbolic and utilizes orders of magnitude instead of precise values of the model parameters. Application of this method to a large collection of biochemical network models supports the idea that the number of dynamical variables in minimal models of cell physiology can be small, in spite of the large number of molecular regulatory actors.

Quantum implications of a scale invariant regularization

NASA Astrophysics Data System (ADS)

Ghilencea, D. M.

2018-04-01

We study scale invariance at the quantum level in a perturbative approach. For a scale-invariant classical theory, the scalar potential is computed at a three-loop level while keeping manifest this symmetry. Spontaneous scale symmetry breaking is transmitted at a quantum level to the visible sector (of ϕ ) by the associated Goldstone mode (dilaton σ ), which enables a scale-invariant regularization and whose vacuum expectation value ⟨σ ⟩ generates the subtraction scale (μ ). While the hidden (σ ) and visible sector (ϕ ) are classically decoupled in d =4 due to an enhanced Poincaré symmetry, they interact through (a series of) evanescent couplings ∝ɛ , dictated by the scale invariance of the action in d =4 -2 ɛ . At the quantum level, these couplings generate new corrections to the potential, as scale-invariant nonpolynomial effective operators ϕ2 n +4/σ2 n. These are comparable in size to "standard" loop corrections and are important for values of ϕ close to ⟨σ ⟩. For n =1 , 2, the beta functions of their coefficient are computed at three loops. In the IR limit, dilaton fluctuations decouple, the effective operators are suppressed by large ⟨σ ⟩, and the effective potential becomes that of a renormalizable theory with explicit scale symmetry breaking by the DR scheme (of μ =constant).

Noise-invariant Neurons in the Avian Auditory Cortex: Hearing the Song in Noise

PubMed Central

Moore, R. Channing; Lee, Tyler; Theunissen, Frédéric E.

2013-01-01

Given the extraordinary ability of humans and animals to recognize communication signals over a background of noise, describing noise invariant neural responses is critical not only to pinpoint the brain regions that are mediating our robust perceptions but also to understand the neural computations that are performing these tasks and the underlying circuitry. Although invariant neural responses, such as rotation-invariant face cells, are well described in the visual system, high-level auditory neurons that can represent the same behaviorally relevant signal in a range of listening conditions have yet to be discovered. Here we found neurons in a secondary area of the avian auditory cortex that exhibit noise-invariant responses in the sense that they responded with similar spike patterns to song stimuli presented in silence and over a background of naturalistic noise. By characterizing the neurons' tuning in terms of their responses to modulations in the temporal and spectral envelope of the sound, we then show that noise invariance is partly achieved by selectively responding to long sounds with sharp spectral structure. Finally, to demonstrate that such computations could explain noise invariance, we designed a biologically inspired noise-filtering algorithm that can be used to separate song or speech from noise. This novel noise-filtering method performs as well as other state-of-the-art de-noising algorithms and could be used in clinical or consumer oriented applications. Our biologically inspired model also shows how high-level noise-invariant responses could be created from neural responses typically found in primary auditory cortex. PMID:23505354

Noise-invariant neurons in the avian auditory cortex: hearing the song in noise.

PubMed

Moore, R Channing; Lee, Tyler; Theunissen, Frédéric E

2013-01-01

Given the extraordinary ability of humans and animals to recognize communication signals over a background of noise, describing noise invariant neural responses is critical not only to pinpoint the brain regions that are mediating our robust perceptions but also to understand the neural computations that are performing these tasks and the underlying circuitry. Although invariant neural responses, such as rotation-invariant face cells, are well described in the visual system, high-level auditory neurons that can represent the same behaviorally relevant signal in a range of listening conditions have yet to be discovered. Here we found neurons in a secondary area of the avian auditory cortex that exhibit noise-invariant responses in the sense that they responded with similar spike patterns to song stimuli presented in silence and over a background of naturalistic noise. By characterizing the neurons' tuning in terms of their responses to modulations in the temporal and spectral envelope of the sound, we then show that noise invariance is partly achieved by selectively responding to long sounds with sharp spectral structure. Finally, to demonstrate that such computations could explain noise invariance, we designed a biologically inspired noise-filtering algorithm that can be used to separate song or speech from noise. This novel noise-filtering method performs as well as other state-of-the-art de-noising algorithms and could be used in clinical or consumer oriented applications. Our biologically inspired model also shows how high-level noise-invariant responses could be created from neural responses typically found in primary auditory cortex.

Inertial Spontaneous Symmetry Breaking and Quantum Scale Invariance

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

Ferreira, Pedro G.; Hill, Christopher T.; Ross, Graham G.

Weyl invariant theories of scalars and gravity can generate all mass scales spontaneously, initiated by a dynamical process of "inertial spontaneous symmetry breaking" that does not involve a potential. This is dictated by the structure of the Weyl current,more » $$K_\\mu$$, and a cosmological phase during which the universe expands and the Einstein-Hilbert effective action is formed. Maintaining exact Weyl invariance in the renormalised quantum theory is straightforward when renormalisation conditions are referred back to the VEV's of fields in the action of the theory, which implies a conserved Weyl current. We do not require scale invariant regulators. We illustrate the computation of a Weyl invariant Coleman-Weinberg potential.« less

A scale-invariant change detection method for land use/cover change research

NASA Astrophysics Data System (ADS)

Xing, Jin; Sieber, Renee; Caelli, Terrence

2018-07-01

Land Use/Cover Change (LUCC) detection relies increasingly on comparing remote sensing images with different spatial and spectral scales. Based on scale-invariant image analysis algorithms in computer vision, we propose a scale-invariant LUCC detection method to identify changes from scale heterogeneous images. This method is composed of an entropy-based spatial decomposition, two scale-invariant feature extraction methods, Maximally Stable Extremal Region (MSER) and Scale-Invariant Feature Transformation (SIFT) algorithms, a spatial regression voting method to integrate MSER and SIFT results, a Markov Random Field-based smoothing method, and a support vector machine classification method to assign LUCC labels. We test the scale invariance of our new method with a LUCC case study in Montreal, Canada, 2005-2012. We found that the scale-invariant LUCC detection method provides similar accuracy compared with the resampling-based approach but this method avoids the LUCC distortion incurred by resampling.

iGRaND: an invariant frame for RGBD sensor feature detection and descriptor extraction with applications

NASA Astrophysics Data System (ADS)

Willis, Andrew R.; Brink, Kevin M.

2016-06-01

This article describes a new 3D RGBD image feature, referred to as iGRaND, for use in real-time systems that use these sensors for tracking, motion capture, or robotic vision applications. iGRaND features use a novel local reference frame derived from the image gradient and depth normal (hence iGRaND) that is invariant to scale and viewpoint for Lambertian surfaces. Using this reference frame, Euclidean invariant feature components are computed at keypoints which fuse local geometric shape information with surface appearance information. The performance of the feature for real-time odometry is analyzed and its computational complexity and accuracy is compared with leading alternative 3D features.

Slow Feature Analysis on Retinal Waves Leads to V1 Complex Cells

PubMed Central

Dähne, Sven; Wilbert, Niko; Wiskott, Laurenz

2014-01-01

The developing visual system of many mammalian species is partially structured and organized even before the onset of vision. Spontaneous neural activity, which spreads in waves across the retina, has been suggested to play a major role in these prenatal structuring processes. Recently, it has been shown that when employing an efficient coding strategy, such as sparse coding, these retinal activity patterns lead to basis functions that resemble optimal stimuli of simple cells in primary visual cortex (V1). Here we present the results of applying a coding strategy that optimizes for temporal slowness, namely Slow Feature Analysis (SFA), to a biologically plausible model of retinal waves. Previously, SFA has been successfully applied to model parts of the visual system, most notably in reproducing a rich set of complex-cell features by training SFA with quasi-natural image sequences. In the present work, we obtain SFA units that share a number of properties with cortical complex-cells by training on simulated retinal waves. The emergence of two distinct properties of the SFA units (phase invariance and orientation tuning) is thoroughly investigated via control experiments and mathematical analysis of the input-output functions found by SFA. The results support the idea that retinal waves share relevant temporal and spatial properties with natural visual input. Hence, retinal waves seem suitable training stimuli to learn invariances and thereby shape the developing early visual system such that it is best prepared for coding input from the natural world. PMID:24810948

Fast or slow? Compressions (or not) in number-to-line mappings.

PubMed

Candia, Victor; Deprez, Paola; Wernery, Jannis; Núñez, Rafael

2015-01-01

We investigated, in a university student population, spontaneous (non-speeded) fast and slow number-to-line mapping responses using non-symbolic (dots) and symbolic (words) stimuli. Seeking for less conventionalized responses, we used anchors 0-130, rather than the standard 0-100. Slow responses to both types of stimuli only produced linear mappings with no evidence of non-linear compression. In contrast, fast responses revealed distinct patterns of non-linear compression for dots and words. A predicted logarithmic compression was observed in fast responses to dots in the 0-130 range, but not in the reduced 0-100 range, indicating compression in proximity of the upper anchor 130, not the standard 100. Moreover, fast responses to words revealed an unexpected significant negative compression in the reduced 0-100 range, but not in the 0-130 range, indicating compression in proximity to the lower anchor 0. Results show that fast responses help revealing the fundamentally distinct nature of symbolic and non-symbolic quantity representation. Whole number words, being intrinsically mediated by cultural phenomena such as language and education, emphasize the invariance of magnitude between them—essential for linear mappings, and therefore, unlike non-symbolic (psychophysical) stimuli, yield spatial mappings that don't seem to be influenced by the Weber-Fechner law of psychophysics. However, high levels of education (when combined with an absence of standard upper anchors) may lead fast responses to overestimate magnitude invariance on the lower end of word numerals.

Dynamics of a linear system coupled to a chain of light nonlinear oscillators analyzed through a continuous approximation

NASA Astrophysics Data System (ADS)

Charlemagne, S.; Ture Savadkoohi, A.; Lamarque, C.-H.

2018-07-01

The continuous approximation is used in this work to describe the dynamics of a nonlinear chain of light oscillators coupled to a linear main system. A general methodology is applied to an example where the chain has local nonlinear restoring forces. The slow invariant manifold is detected at fast time scale. At slow time scale, equilibrium and singular points are sought around this manifold in order to predict periodic regimes and strongly modulated responses of the system. Analytical predictions are in good accordance with numerical results and represent a potent tool for designing nonlinear chains for passive control purposes.

The complexity of translationally invariant low-dimensional spin lattices in 3D

NASA Astrophysics Data System (ADS)

Bausch, Johannes; Piddock, Stephen

2017-11-01

In this theoretical paper, we consider spin systems in three spatial dimensions and consider the computational complexity of estimating the ground state energy, known as the local Hamiltonian problem, for translationally invariant Hamiltonians. We prove that the local Hamiltonian problem for 3D lattices with face-centered cubic unit cells and 4-local translationally invariant interactions between spin-3/2 particles and open boundary conditions is QMAEXP-complete, where QMAEXP is the class of problems which can be verified in exponential time on a quantum computer. We go beyond a mere embedding of past hard 1D history state constructions, for which the local spin dimension is enormous: even state-of-the-art constructions have local dimension 42. We avoid such a large local dimension by combining some different techniques in a novel way. For the verifier circuit which we embed into the ground space of the local Hamiltonian, we utilize a recently developed computational model, called a quantum ring machine, which is especially well suited for translationally invariant history state constructions. This is encoded with a new and particularly simple universal gate set, which consists of a single 2-qubit gate applied only to nearest-neighbour qubits. The Hamiltonian construction involves a classical Wang tiling problem as a binary counter which translates one cube side length into a binary description for the encoded verifier input and a carefully engineered history state construction that implements the ring machine on the cubic lattice faces. These novel techniques allow us to significantly lower the local spin dimension, surpassing the best translationally invariant result to date by two orders of magnitude (in the number of degrees of freedom per coupling). This brings our models on par with the best non-translationally invariant construction.

Orthogonal bases of invariants in tensor models

NASA Astrophysics Data System (ADS)

Diaz, Pablo; Rey, Soo-Jong

2018-02-01

Representation theory provides an efficient framework to count and classify invariants in tensor models of (gauge) symmetry G d = U( N 1) ⊗ · · · ⊗ U( N d ) . We show that there are two natural ways of counting invariants, one for arbitrary G d and another valid for large rank of G d . We construct basis of invariant operators based on the counting, and compute correlators of their elements. The basis associated with finite rank of G d diagonalizes two-point function. It is analogous to the restricted Schur basis used in matrix models. We comment on future directions for investigation.

Weyl current, scale-invariant inflation, and Planck scale generation

DOE PAGES

Ferreira, Pedro G.; Hill, Christopher T.; Ross, Graham G.

2017-02-08

Scalar fields,more » $$\\phi$$ i, can be coupled nonminimally to curvature and satisfy the general criteria: (i) the theory has no mass input parameters, including M P=0; (ii) the $$\\phi$$ i have arbitrary values and gradients, but undergo a general expansion and relaxation to constant values that satisfy a nontrivial constraint, K($$\\phi$$ i)=constant; (iii) this constraint breaks scale symmetry spontaneously, and the Planck mass is dynamically generated; (iv) there can be adequate inflation associated with slow roll in a scale-invariant potential subject to the constraint; (v) the final vacuum can have a small to vanishing cosmological constant; (vi) large hierarchies in vacuum expectation values can naturally form; (vii) there is a harmless dilaton which naturally eludes the usual constraints on massless scalars. Finally, these models are governed by a global Weyl scale symmetry and its conserved current, K μ. At the quantum level the Weyl scale symmetry can be maintained by an invariant specification of renormalized quantities.« less

Using Global Invariant Manifolds to Understand Metastability in the Burgers Equation With Small Viscosity

NASA Astrophysics Data System (ADS)

Beck, Margaret; Wayne, C. Eugene

2009-01-01

The large-time behavior of solutions to the Burgers equation with small viscosity is described using invariant manifolds. In particular, a geometric explanation is provided for a phenomenon known as metastability, which in the present context means that solutions spend a very long time near the family of solutions known as diffusive N-waves before finally converging to a stable self-similar diffusion wave. More precisely, it is shown that in terms of similarity, or scaling, variables in an algebraically weighted L^2 space, the self-similar diffusion waves correspond to a one-dimensional global center manifold of stationary solutions. Through each of these fixed points there exists a one-dimensional, global, attractive, invariant manifold corresponding to the diffusive N-waves. Thus, metastability corresponds to a fast transient in which solutions approach this metastable manifold of diffusive N-waves, followed by a slow decay along this manifold, and, finally, convergence to the self-similar diffusion wave.

Automated LASCO CME Catalog for Solar Cycle 23: Are CMEs Scale Invariant?

NASA Astrophysics Data System (ADS)

Robbrecht, E.; Berghmans, D.; Van der Linden, R. A. M.

2009-02-01

In this paper, we present the first automatically constructed LASCO coronal mass ejection (CME) catalog, a result of the application of the Computer Aided CME Tracking software (CACTus) on the LASCO archive during the interval 1997 September-2007 January. We have studied the CME characteristics and have compared them with similar results obtained by manual detection (CDAW CME catalog). On average, CACTus detects less than two events per day during solar minimum, up to eight events during maximum, nearly half of them being narrow (<20°). Assuming a correction factor, we find that the CACTus CME rate is surprisingly consistent with CME rates found during the past 30 years. The CACTus statistics show that small-scale outflow is ubiquitously observed in the outer corona. The majority of CACTus-only events are narrow transients related to previous CME activity or to intensity variations in the slow solar wind, reflecting its turbulent nature. A significant fraction (about 15%) of CACTus-only events were identified as independent events, thus not related to other CME activity. The CACTus CME width distribution is essentially scale invariant in angular span over a range of scales from 20° to 120° while previous catalogs present a broad maximum around 30°. The possibility that the size of coronal mass outflows follow a power-law distribution could indicate that no typical CME size exists, i.e., that the narrow transients are not different from the larger well defined CMEs.

Extending the excluded volume for percolation threshold estimates in polydisperse systems: The binary disk system

DOE PAGES

Meeks, Kelsey; Pantoya, Michelle L.; Green, Micah; ...

2017-06-01

For dispersions containing a single type of particle, it has been observed that the onset of percolation coincides with a critical value of volume fraction. When the volume fraction is calculated based on excluded volume, this critical percolation threshold is nearly invariant to particle shape. The critical threshold has been calculated to high precision for simple geometries using Monte Carlo simulations, but this method is slow at best, and infeasible for complex geometries. This article explores an analytical approach to the prediction of percolation threshold in polydisperse mixtures. Specifically, this paper suggests an extension of the concept of excluded volume,more » and applies that extension to the 2D binary disk system. The simple analytical expression obtained is compared to Monte Carlo results from the literature. In conclusion, the result may be computed extremely rapidly and matches key parameters closely enough to be useful for composite material design.« less

Vanishing of local non-Gaussianity in canonical single field inflation

NASA Astrophysics Data System (ADS)

Bravo, Rafael; Mooij, Sander; Palma, Gonzalo A.; Pradenas, Bastián

2018-05-01

We study the production of observable primordial local non-Gaussianity in two opposite regimes of canonical single field inflation: attractor (standard single field slow-roll inflation) and non attractor (ultra slow-roll inflation). In the attractor regime, the standard derivation of the bispectrum's squeezed limit using co-moving coordinates gives the well known Maldacena's consistency relation fNL = 5 (1‑ns) / 12. On the other hand, in the non-attractor regime, the squeezed limit offers a substantial violation of this relation given by fNL = 5/2. In this work we argue that, independently of whether inflation is attractor or non-attractor, the size of the observable primordial local non-Gaussianity is predicted to be fNLobs = 0 (a result that was already understood to hold in the case of attractor models). To show this, we follow the use of the so-called Conformal Fermi Coordinates (CFC), recently introduced in the literature. These coordinates parametrize the local environment of inertial observers in a perturbed FRW spacetime, allowing one to identify and compute gauge invariant quantities, such as n-point correlation functions. Concretely, we find that during inflation, after all the modes have exited the horizon, the squeezed limit of the 3-point correlation function of curvature perturbations vanishes in the CFC frame, regardless of the inflationary regime. We argue that such a cancellation should persist after inflation ends.

Journeys through antigravity?

NASA Astrophysics Data System (ADS)

Carrasco, John Joseph M.; Chemissany, Wissam; Kallosh, Renata

2014-01-01

A possibility of journeys through antigravity has recently been proposed, with the suggestion that Weyl-invariant extension of scalars coupled to Einstein gravity allows for an unambiguous classical evolution through cosmological singularities in anisotropic spacetimes. We compute the Weyl invariant curvature squared and find that it blows up for the proposed anisotropic solution both at the Big Crunch as well as at the Big Bang. Therefore the cosmological singularities are not resolved by uplifting Einstein theory to a Weyl invariant model.

On the deep structure of the blowing-up of curve singularities

NASA Astrophysics Data System (ADS)

Elias, Juan

2001-09-01

Let C be a germ of curve singularity embedded in (kn, 0). It is well known that the blowing-up of C centred on its closed ring, Bl(C), is a finite union of curve singularities. If C is reduced we can iterate this process and, after a finite number of steps, we find only non-singular curves. This is the desingularization process. The main idea of this paper is to linearize the blowing-up of curve singularities Bl(C) [rightward arrow] C. We perform this by studying the structure of [script O]Bl(C)/[script O]C as W-module, where W is a discrete valuation ring contained in [script O]C. Since [script O]Bl(C)/[script O]C is a torsion W-module, its structure is determined by the invariant factors of [script O]C in [script O]Bl(C). The set of invariant factors is called in this paper as the set of micro-invariants of C (see Definition 1·2).In the first section we relate the micro-invariants of C to the Hilbert function of C (Proposition 1·3), and we show how to compute them from the Hilbert function of some quotient of [script O]C (see Proposition 1·4).The main result of this paper is Theorem 3·3 where we give upper bounds of the micro-invariants in terms of the regularity, multiplicity and embedding dimension. As a corollary we improve and we recover some results of [6]. These bounds can be established as a consequence of the study of the Hilbert function of a filtration of ideals g = {g[r,i+1]}i [gt-or-equal, slanted] 0 of the tangent cone of [script O]C (see Section 2). The main property of g is that the ideals g[r,i+1] have initial degree bigger than the Castelnuovo-Mumford regularity of the tangent cone of [script O]C.Section 4 is devoted to computation the micro-invariants of branches; we show how to compute them from the semigroup of values of C and Bl(C) (Proposition 4·3). The case of monomial curve singularities is especially studied; we end Section 4 with some explicit computations.In the last section we study some geometric properties of C that can be deduced from special values of the micro-invariants, and we specially study the relationship of the micro-invariants with the Hilbert function of [script O]Bl(C). We end the paper studying the natural equisingularity criteria that can be defined from the micro-invariants and its relationship with some of the known equisingularity criteria.

New Actions Upon Old Objects: A New Ontological Perspective on Functions.

ERIC Educational Resources Information Center

Schwarz, Baruch; Dreyfus, Tommy

1995-01-01

A computer microworld called Triple Representation Model uses graphical, tabular, and algebraic representations to influence conceptions of function. A majority of students were able to cope with partial data, recognize invariants while coordinating actions among representations, and recognize invariants while creating and comparing different…

Dynamics of Equilibrium Points in a Uniformly Rotating Second-Order and Degree Gravitational Field

NASA Astrophysics Data System (ADS)

Feng, Jinglang; Hou, Xiyun

2017-07-01

Using tools such as periodic orbits and invariant manifolds, the global dynamics around equilibrium points (EPs) in a rotating second-order and degree gravitational field are studied. For EPs on the long axis, planar and vertical periodic families are computed, and their stability properties are investigated. Invariant manifolds are also computed, and their relation to the first-order resonances is briefly discussed. For EPs on the short axis, planar and vertical periodic families are studied, with special emphasis on the genealogy of the planar periodic families. Our studies show that the global dynamics around EPs are highly similar to those around libration points in the circular restricted three-body problem, such as spatial halo orbits, invariant manifolds, and the genealogy of planar periodic families.

The Invariance Hypothesis Implies Domain-Specific Regions in Visual Cortex

PubMed Central

Leibo, Joel Z.; Liao, Qianli; Anselmi, Fabio; Poggio, Tomaso

2015-01-01

Is visual cortex made up of general-purpose information processing machinery, or does it consist of a collection of specialized modules? If prior knowledge, acquired from learning a set of objects is only transferable to new objects that share properties with the old, then the recognition system’s optimal organization must be one containing specialized modules for different object classes. Our analysis starts from a premise we call the invariance hypothesis: that the computational goal of the ventral stream is to compute an invariant-to-transformations and discriminative signature for recognition. The key condition enabling approximate transfer of invariance without sacrificing discriminability turns out to be that the learned and novel objects transform similarly. This implies that the optimal recognition system must contain subsystems trained only with data from similarly-transforming objects and suggests a novel interpretation of domain-specific regions like the fusiform face area (FFA). Furthermore, we can define an index of transformation-compatibility, computable from videos, that can be combined with information about the statistics of natural vision to yield predictions for which object categories ought to have domain-specific regions in agreement with the available data. The result is a unifying account linking the large literature on view-based recognition with the wealth of experimental evidence concerning domain-specific regions. PMID:26496457

Integer sequence discovery from small graphs

PubMed Central

Hoppe, Travis; Petrone, Anna

2015-01-01

We have exhaustively enumerated all simple, connected graphs of a finite order and have computed a selection of invariants over this set. Integer sequences were constructed from these invariants and checked against the Online Encyclopedia of Integer Sequences (OEIS). 141 new sequences were added and six sequences were extended. From the graph database, we were able to programmatically suggest relationships among the invariants. It will be shown that we can readily visualize any sequence of graphs with a given criteria. The code has been released as an open-source framework for further analysis and the database was constructed to be extensible to invariants not considered in this work. PMID:27034526

Measurement invariance, the lack thereof, and modeling change.

PubMed

Edwards, Michael C; Houts, Carrie R; Wirth, R J

2017-08-17

Measurement invariance issues should be considered during test construction. In this paper, we provide a conceptual overview of measurement invariance and describe how the concept is implemented in several different statistical approaches. Typical applications look for invariance over things such as mode of administration (paper and pencil vs. computer based), language/translation, age, time, and gender, to cite just a few examples. To the extent that the relationships between items and constructs are stable/invariant, we can be more confident in score interpretations. A series of simulated examples are reported which highlight different kinds of non-invariance, the impact it can have, and the effect of appropriately modeling a lack of invariance. One example focuses on the longitudinal context, where measurement invariance is critical to understanding trends over time. Software syntax is provided to help researchers apply these models with their own data. The simulation studies demonstrate the negative impact an erroneous assumption of invariance may have on scores and substantive conclusions drawn from naively analyzing those scores. Measurement invariance implies that the links between the items and the construct of interest are invariant over some domain, grouping, or classification. Examining a new or existing test for measurement invariance should be part of any test construction/implementation plan. In addition to reviewing implications of the simulation study results, we also provide a discussion of the limitations of current approaches and areas in need of additional research.

Complexified boost invariance and holographic heavy ion collisions

DOE PAGES

Gubser, Steven S.; van der Schee, Wilke

2015-01-08

At strong coupling holographic studies have shown that heavy ion collisions do not obey normal boost invariance. Here we study a modified boost invariance through a complex shift in time, and show that this leads to surprisingly good agreement with numerical holographic computations. When including perturbations the agreement becomes even better, both in the hydrodynamic and the far-from-equilibrium regime. Finally, one of the main advantages is an analytic formulation of the stress-energy tensor of the longitudinal dynamics of holographic heavy ion collisions.

Combining color and shape information for illumination-viewpoint invariant object recognition.

PubMed

Diplaros, Aristeidis; Gevers, Theo; Patras, Ioannis

2006-01-01

In this paper, we propose a new scheme that merges color- and shape-invariant information for object recognition. To obtain robustness against photometric changes, color-invariant derivatives are computed first. Color invariance is an important aspect of any object recognition scheme, as color changes considerably with the variation in illumination, object pose, and camera viewpoint. These color invariant derivatives are then used to obtain similarity invariant shape descriptors. Shape invariance is equally important as, under a change in camera viewpoint and object pose, the shape of a rigid object undergoes a perspective projection on the image plane. Then, the color and shape invariants are combined in a multidimensional color-shape context which is subsequently used as an index. As the indexing scheme makes use of a color-shape invariant context, it provides a high-discriminative information cue robust against varying imaging conditions. The matching function of the color-shape context allows for fast recognition, even in the presence of object occlusion and cluttering. From the experimental results, it is shown that the method recognizes rigid objects with high accuracy in 3-D complex scenes and is robust against changing illumination, camera viewpoint, object pose, and noise.

The distinct character of anisotropy and intermittency in inertial and kinetic range solar wind plasma turbulence

NASA Astrophysics Data System (ADS)

Kiyani, Khurom; Chapman, Sandra; Osman, Kareem; Sahraoui, Fouad; Hnat, Bogdan

2014-05-01

The anisotropic nature of the scaling properties of solar wind magnetic turbulence fluctuations is investigated scale by scale using high cadence in situ magnetic field measurements from the Cluster, ACE and STEREO spacecraft missions in both fast and slow quiet solar wind conditions. The data span five decades in scales from the inertial range to the electron Larmor radius. We find a clear transition in scaling behaviour between the inertial and kinetic range of scales, which provides a direct, quantitative constraint on the physical processes that mediate the cascade of energy through these scales. In the inertial (magnetohydrodynamic) range the statistical nature of turbulent fluctuations are known to be anisotropic, both in the vector components of the magnetic field fluctuations (variance anisotropy) and in the spatial scales of these fluctuations (wavevector or k-anisotropy). We show for the first time that, when measuring parallel to the local magnetic field direction, the full statistical signature of the magnetic and Elsasser field fluctuations is that of a non-Gaussian globally scale-invariant process. This is distinct from the classic multi-exponent statistics observed when the local magnetic field is perpendicular to the flow direction. These observations suggest the weakness, or absence, of a parallel magnetofluid turbulence energy cascade. In contrast to the inertial range, there is a successive increase toward isotropy between parallel and transverse power at scales below the ion Larmor radius, with isotropy being achieved at the electron Larmor radius. Computing higher-order statistics, we show that the full statistical signature of both parallel, and perpendicular fluctuations at scales below the ion Larmor radius are that of an isotropic globally scale-invariant non-Gaussian process. Lastly, we perform a survey of multiple intervals of quiet solar wind sampled under different plasma conditions (fast, slow wind; plasma beta etc.) and find that the above results on the scaling transition between inertial and kinetic range scales are qualitatively robust, and that quantitatively, there is a spread in the values of the scaling exponents.

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

Bolis, Nadia; Albrecht, Andreas; Holman, R.

We consider the effects of entanglement in the initial quantum state of scalar and tensor fluctuations during inflation. We allow the gauge-invariant scalar and tensor fluctuations to be entangled in the initial state and compute modifications to the various cosmological power spectra. We compute the angular power spectra (C{sub l}’s) for some specific cases of our entangled state and discuss what signals one might expect to find in CMB data. This entanglement also can break rotational invariance, allowing for the possibility that some of the large scale anomalies in the CMB power spectrum might be explained by this mechanism.

Computational Imaging in Demanding Conditions

DTIC Science & Technology

2015-11-18

spatiotemporal domain where such blur is not present.  Detailed Accomplishments:  ● Removing  Atmospheric   Turbulence  via Space-Invariant  Deconvolution:  ○ To...given image sequence distorted by  atmospheric   turbulence . This approach  reduces the space and time-varying deblurring problem to a shift invariant...SUBJECT TERMS Image processing, Computational imaging, turbulence , blur, enhancement 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF ABSTRACT 18

Selective processing of auditory evoked responses with iterative-randomized stimulation and averaging: A strategy for evaluating the time-invariant assumption.

PubMed

Valderrama, Joaquin T; de la Torre, Angel; Medina, Carlos; Segura, Jose C; Thornton, A Roger D

2016-03-01

The recording of auditory evoked potentials (AEPs) at fast rates allows the study of neural adaptation, improves accuracy in estimating hearing threshold and may help diagnosing certain pathologies. Stimulation sequences used to record AEPs at fast rates require to be designed with a certain jitter, i.e., not periodical. Some authors believe that stimuli from wide-jittered sequences may evoke auditory responses of different morphology, and therefore, the time-invariant assumption would not be accomplished. This paper describes a methodology that can be used to analyze the time-invariant assumption in jittered stimulation sequences. The proposed method [Split-IRSA] is based on an extended version of the iterative randomized stimulation and averaging (IRSA) technique, including selective processing of sweeps according to a predefined criterion. The fundamentals, the mathematical basis and relevant implementation guidelines of this technique are presented in this paper. The results of this study show that Split-IRSA presents an adequate performance and that both fast and slow mechanisms of adaptation influence the evoked-response morphology, thus both mechanisms should be considered when time-invariance is assumed. The significance of these findings is discussed. Crown Copyright © 2016. Published by Elsevier B.V. All rights reserved.

Early universe cosmology, effective supergravity, and invariants of algebraic forms

NASA Astrophysics Data System (ADS)

Sinha, Kuver

2015-09-01

The presence of light scalars can have profound effects on early universe cosmology, influencing its thermal history as well as paradigms like inflation and baryogenesis. Effective supergravity provides a framework to make quantifiable, model-independent studies of these effects. The Riemannian curvature of the Kähler manifold spanned by scalars belonging to chiral superfields, evaluated along supersymmetry breaking directions, provides an order parameter (in the sense that it must necessarily take certain values) for phenomena as diverse as slow roll modular inflation, nonthermal cosmological histories, and the viability of Affleck-Dine baryogenesis. Within certain classes of UV completions, the order parameter for theories with n scalar moduli is conjectured to be related to invariants of n -ary cubic forms (for example, for models with three moduli, the order parameter is given by a function on the ring of invariants spanned by the Aronhold invariants). Within these completions, and under the caveats spelled out, this may provide an avenue to obtain necessary conditions for the above phenomena that are in principle calculable given nothing but the intersection numbers of a Calabi-Yau compactification geometry. As an additional result, abstract relations between holomorphic sectional and bisectional curvatures are utilized to constrain Affleck-Dine baryogenesis on a wide class of Kähler geometries.

Dynamics of Equilibrium Points in a Uniformly Rotating Second-Order and Degree Gravitational Field

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

Feng, Jinglang; Hou, Xiyun, E-mail: jinglang@nju.edu.cn, E-mail: silence@nju.edu.cn

2017-07-01

Using tools such as periodic orbits and invariant manifolds, the global dynamics around equilibrium points (EPs) in a rotating second-order and degree gravitational field are studied. For EPs on the long axis, planar and vertical periodic families are computed, and their stability properties are investigated. Invariant manifolds are also computed, and their relation to the first-order resonances is briefly discussed. For EPs on the short axis, planar and vertical periodic families are studied, with special emphasis on the genealogy of the planar periodic families. Our studies show that the global dynamics around EPs are highly similar to those around libration points in the circularmore » restricted three-body problem, such as spatial halo orbits, invariant manifolds, and the genealogy of planar periodic families.« less

The Development of Invariant Object Recognition Requires Visual Experience with Temporally Smooth Objects

ERIC Educational Resources Information Center

Wood, Justin N.; Wood, Samantha M. W.

2018-01-01

How do newborns learn to recognize objects? According to temporal learning models in computational neuroscience, the brain constructs object representations by extracting smoothly changing features from the environment. To date, however, it is unknown whether newborns depend on smoothly changing features to build invariant object representations.…

2D Affine and Projective Shape Analysis.

PubMed

Bryner, Darshan; Klassen, Eric; Huiling Le; Srivastava, Anuj

2014-05-01

Current techniques for shape analysis tend to seek invariance to similarity transformations (rotation, translation, and scale), but certain imaging situations require invariance to larger groups, such as affine or projective groups. Here we present a general Riemannian framework for shape analysis of planar objects where metrics and related quantities are invariant to affine and projective groups. Highlighting two possibilities for representing object boundaries-ordered points (or landmarks) and parameterized curves-we study different combinations of these representations (points and curves) and transformations (affine and projective). Specifically, we provide solutions to three out of four situations and develop algorithms for computing geodesics and intrinsic sample statistics, leading up to Gaussian-type statistical models, and classifying test shapes using such models learned from training data. In the case of parameterized curves, we also achieve the desired goal of invariance to re-parameterizations. The geodesics are constructed by particularizing the path-straightening algorithm to geometries of current manifolds and are used, in turn, to compute shape statistics and Gaussian-type shape models. We demonstrate these ideas using a number of examples from shape and activity recognition.

Infrared Ship Classification Using A New Moment Pattern Recognition Concept

NASA Astrophysics Data System (ADS)

Casasent, David; Pauly, John; Fetterly, Donald

1982-03-01

An analysis of the statistics of the moments and the conventional invariant moments shows that the variance of the latter become quite large as the order of the moments and the degree of invariance increases. Moreso, the need to whiten the error volume increases with the order and degree, but so does the computational load associated with computing the whitening operator. We thus advance a new estimation approach to the use of moments in pattern recog-nition that overcomes these problems. This work is supported by experimental verification and demonstration on an infrared ship pattern recognition problem. The computational load associated with our new algorithm is also shown to be very low.

Rapid convergence of optimal control in NMR using numerically-constructed toggling frames

NASA Astrophysics Data System (ADS)

Coote, Paul; Anklin, Clemens; Massefski, Walter; Wagner, Gerhard; Arthanari, Haribabu

2017-08-01

We present a numerical method for rapidly solving the Bloch equation for an arbitrary time-varying spin-1/2 Hamiltonian. The method relies on fast, vectorized computations such as summation and quaternion multiplication, rather than slow computations such as matrix exponentiation. A toggling frame is constructed in which the Hamiltonian is time-invariant, and therefore has a simple analytical solution. The key insight is that constructing this frame is faster than solving the system dynamics in the original frame. Rapidly solving the Bloch equations for an arbitrary Hamiltonian is particularly useful in the context of NMR optimal control. Optimal control theory can be used to design pulse shapes for a range of tasks in NMR spectroscopy. However, it requires multiple simulations of the Bloch equations at each stage of the algorithm, and for each relevant set of parameters (e.g. chemical shift frequencies). This is typically time consuming. We demonstrate that by working in an appropriate toggling frame, optimal control pulses can be generated much faster. We present a new alternative to the well-known GRAPE algorithm to continuously update the toggling-frame as the optimal pulse is generated, and demonstrate that this approach is extremely fast. The use and benefit of rapid optimal pulse generation is demonstrated for 19F fragment screening experiments.

Differential invariants in nonclassical models of hydrodynamics

NASA Astrophysics Data System (ADS)

Bublik, Vasily V.

2017-10-01

In this paper, differential invariants are used to construct solutions for equations of the dynamics of a viscous heat-conducting gas and the dynamics of a viscous incompressible fluid modified by nanopowder inoculators. To describe the dynamics of a viscous heat-conducting gas, we use the complete system of Navier—Stokes equations with allowance for heat fluxes. Mathematical description of the dynamics of liquid metals under high-energy external influences (laser radiation or plasma flow) includes, in addition to the Navier—Stokes system of an incompressible viscous fluid, also heat fluxes and processes of nonequilibrium crystallization of a deformable fluid. Differentially invariant solutions are a generalization of partially invariant solutions, and their active study for various models of continuous medium mechanics is just beginning. Differentially invariant solutions can also be considered as solutions with differential constraints; therefore, when developing them, the approaches and methods developed by the science schools of academicians N. N. Yanenko and A. F. Sidorov will be actively used. In the construction of partially invariant and differentially invariant solutions, there are overdetermined systems of differential equations that require a compatibility analysis. The algorithms for reducing such systems to involution in a finite number of steps are described by Cartan, Finikov, Kuranishi, and other authors. However, the difficultly foreseeable volume of intermediate calculations complicates their practical application. Therefore, the methods of computer algebra are actively used here, which largely helps in solving this difficult problem. It is proposed to use the constructed exact solutions as tests for formulas, algorithms and their software implementations when developing and creating numerical methods and computational program complexes. This combination of effective numerical methods, capable of solving a wide class of problems, with analytical methods makes it possible to make the results of mathematical modeling more accurate and reliable.

Reducing Sun Exposure for Prevention of Skin Cancers: Factorial Invariance and Reliability of the Self-Efficacy Scale for Sun Protection

PubMed Central

Babbin, Steven F.; Yin, Hui-Qing; Rossi, Joseph S.; Redding, Colleen A.; Paiva, Andrea L.; Velicer, Wayne F.

2015-01-01

The Self-Efficacy Scale for Sun Protection consists of two correlated factors with three items each for Sunscreen Use and Avoidance. This study evaluated two crucial psychometric assumptions, factorial invariance and scale reliability, with a sample of adults (N = 1356) participating in a computer-tailored, population-based intervention study. A measure has factorial invariance when the model is the same across subgroups. Three levels of invariance were tested, from least to most restrictive: (1) Configural Invariance (nonzero factor loadings unconstrained); (2) Pattern Identity Invariance (equal factor loadings); and (3) Strong Factorial Invariance (equal factor loadings and measurement errors). Strong Factorial Invariance was a good fit for the model across seven grouping variables: age, education, ethnicity, gender, race, skin tone, and Stage of Change for Sun Protection. Internal consistency coefficient Alpha and factor rho scale reliability, respectively, were .84 and .86 for Sunscreen Use, .68 and .70 for Avoidance, and .78 and .78 for the global (total) scale. The psychometric evidence demonstrates strong empirical support that the scale is consistent, has internal validity, and can be used to assess population-based adult samples. PMID:26457203

Born approximation in linear-time invariant system

NASA Astrophysics Data System (ADS)

Gumjudpai, Burin

2017-09-01

An alternative way of finding the LTI’s solution with the Born approximation, is investigated. We use Born approximation in the LTI and in the transformed LTI in form of Helmholtz equation. General solution are considered as infinite series or Feynman graph. Slow-roll approximation are explored. Transforming the LTI system into Helmholtz equation, approximated general solution can be found for any given forms of force with its initial value.

Connecting the dots across time: reconstruction of single-cell signalling trajectories using time-stamped data

NASA Astrophysics Data System (ADS)

Mukherjee, Sayak; Stewart, David; Stewart, William; Lanier, Lewis L.; Das, Jayajit

2017-08-01

Single-cell responses are shaped by the geometry of signalling kinetic trajectories carved in a multidimensional space spanned by signalling protein abundances. It is, however, challenging to assay a large number (more than 3) of signalling species in live-cell imaging, which makes it difficult to probe single-cell signalling kinetic trajectories in large dimensions. Flow and mass cytometry techniques can measure a large number (4 to more than 40) of signalling species but are unable to track single cells. Thus, cytometry experiments provide detailed time-stamped snapshots of single-cell signalling kinetics. Is it possible to use the time-stamped cytometry data to reconstruct single-cell signalling trajectories? Borrowing concepts of conserved and slow variables from non-equilibrium statistical physics we develop an approach to reconstruct signalling trajectories using snapshot data by creating new variables that remain invariant or vary slowly during the signalling kinetics. We apply this approach to reconstruct trajectories using snapshot data obtained from in silico simulations, live-cell imaging measurements, and, synthetic flow cytometry datasets. The application of invariants and slow variables to reconstruct trajectories provides a radically different way to track objects using snapshot data. The approach is likely to have implications for solving matching problems in a wide range of disciplines.

On the Computation of Finite Invariant Sets of Mappings.

DTIC Science & Technology

1988-02-01

for the calculation of such invariant cycles. We refer here only to Doedel [1], looss et al [3], Kevrekidis et al [4], Van Veldhuizen ,[6], where further... van Veldhuizen , On Polygonal Approximations of an Invariant Curve, Dept.of Mathem. and Comp. Science, Vrije Universiteit Amsterdam, Techni- cal Report 1987, Math. Comp. to appear DATE Fl .LMED ...of van der Pol’s equation " x2) x - A(l - x ) X’ + x - 0 (16) As shown, for example in [2], the solution satisfies x - 2 cos(wt)+ A (0.75 sin(wt

Near-affine-invariant texture learning for lung tissue analysis using isotropic wavelet frames.

PubMed

Depeursinge, Adrien; Van de Ville, Dimitri; Platon, Alexandra; Geissbuhler, Antoine; Poletti, Pierre-Alexandre; Müller, Henning

2012-07-01

We propose near-affine-invariant texture descriptors derived from isotropic wavelet frames for the characterization of lung tissue patterns in high-resolution computed tomography (HRCT) imaging. Affine invariance is desirable to enable learning of nondeterministic textures without a priori localizations, orientations, or sizes. When combined with complementary gray-level histograms, the proposed method allows a global classification accuracy of 76.9% with balanced precision among five classes of lung tissue using a leave-one-patient-out cross validation, in accordance with clinical practice.

Improving Strategies via SMT Solving

NASA Astrophysics Data System (ADS)

Gawlitza, Thomas Martin; Monniaux, David

We consider the problem of computing numerical invariants of programs by abstract interpretation. Our method eschews two traditional sources of imprecision: (i) the use of widening operators for enforcing convergence within a finite number of iterations (ii) the use of merge operations (often, convex hulls) at the merge points of the control flow graph. It instead computes the least inductive invariant expressible in the domain at a restricted set of program points, and analyzes the rest of the code en bloc. We emphasize that we compute this inductive invariant precisely. For that we extend the strategy improvement algorithm of Gawlitza and Seidl [17]. If we applied their method directly, we would have to solve an exponentially sized system of abstract semantic equations, resulting in memory exhaustion. Instead, we keep the system implicit and discover strategy improvements using SAT modulo real linear arithmetic (SMT). For evaluating strategies we use linear programming. Our algorithm has low polynomial space complexity and performs for contrived examples in the worst case exponentially many strategy improvement steps; this is unsurprising, since we show that the associated abstract reachability problem is Π2 P -complete.

Empirical test of the spectral invariants theory using imaging spectroscopy data from a coniferous forest

NASA Astrophysics Data System (ADS)

Lukeš, Petr; Rautiainen, Miina; Stenberg, Pauline; Malenovský, Zbyněk

2011-08-01

The spectral invariants theory presents an alternative approach for modeling canopy scattering in remote sensing applications. The theory is particularly appealing in the case of coniferous forests, which typically display grouped structures and require computationally intensive calculation to account for the geometric arrangement of their canopies. However, the validity of the spectral invariants theory should be tested with empirical data sets from different vegetation types. In this paper, we evaluate a method to retrieve two canopy spectral invariants, the recollision probability and the escape factor, for a coniferous forest using imaging spectroscopy data from multiangular CHRIS PROBA and NADIR-view AISA Eagle sensors. Our results indicated that in coniferous canopies the spectral invariants theory performs well in the near infrared spectral range. In the visible range, on the other hand, the spectral invariants theory may not be useful. Secondly, our study suggested that retrieval of the escape factor could be used as a new method to describe the BRDF of a canopy.

Feedforward object-vision models only tolerate small image variations compared to human

PubMed Central

Ghodrati, Masoud; Farzmahdi, Amirhossein; Rajaei, Karim; Ebrahimpour, Reza; Khaligh-Razavi, Seyed-Mahdi

2014-01-01

Invariant object recognition is a remarkable ability of primates' visual system that its underlying mechanism has constantly been under intense investigations. Computational modeling is a valuable tool toward understanding the processes involved in invariant object recognition. Although recent computational models have shown outstanding performances on challenging image databases, they fail to perform well in image categorization under more complex image variations. Studies have shown that making sparse representation of objects by extracting more informative visual features through a feedforward sweep can lead to higher recognition performances. Here, however, we show that when the complexity of image variations is high, even this approach results in poor performance compared to humans. To assess the performance of models and humans in invariant object recognition tasks, we built a parametrically controlled image database consisting of several object categories varied in different dimensions and levels, rendered from 3D planes. Comparing the performance of several object recognition models with human observers shows that only in low-level image variations the models perform similar to humans in categorization tasks. Furthermore, the results of our behavioral experiments demonstrate that, even under difficult experimental conditions (i.e., briefly presented masked stimuli with complex image variations), human observers performed outstandingly well, suggesting that the models are still far from resembling humans in invariant object recognition. Taken together, we suggest that learning sparse informative visual features, although desirable, is not a complete solution for future progresses in object-vision modeling. We show that this approach is not of significant help in solving the computational crux of object recognition (i.e., invariant object recognition) when the identity-preserving image variations become more complex. PMID:25100986

Fast space-varying convolution using matrix source coding with applications to camera stray light reduction.

PubMed

Wei, Jianing; Bouman, Charles A; Allebach, Jan P

2014-05-01

Many imaging applications require the implementation of space-varying convolution for accurate restoration and reconstruction of images. Here, we use the term space-varying convolution to refer to linear operators whose impulse response has slow spatial variation. In addition, these space-varying convolution operators are often dense, so direct implementation of the convolution operator is typically computationally impractical. One such example is the problem of stray light reduction in digital cameras, which requires the implementation of a dense space-varying deconvolution operator. However, other inverse problems, such as iterative tomographic reconstruction, can also depend on the implementation of dense space-varying convolution. While space-invariant convolution can be efficiently implemented with the fast Fourier transform, this approach does not work for space-varying operators. So direct convolution is often the only option for implementing space-varying convolution. In this paper, we develop a general approach to the efficient implementation of space-varying convolution, and demonstrate its use in the application of stray light reduction. Our approach, which we call matrix source coding, is based on lossy source coding of the dense space-varying convolution matrix. Importantly, by coding the transformation matrix, we not only reduce the memory required to store it; we also dramatically reduce the computation required to implement matrix-vector products. Our algorithm is able to reduce computation by approximately factoring the dense space-varying convolution operator into a product of sparse transforms. Experimental results show that our method can dramatically reduce the computation required for stray light reduction while maintaining high accuracy.

Halo orbit transfer trajectory design using invariant manifold in the Sun-Earth system accounting radiation pressure and oblateness

NASA Astrophysics Data System (ADS)

Srivastava, Vineet K.; Kumar, Jai; Kushvah, Badam Singh

2018-01-01

In this paper, we study the invariant manifold and its application in transfer trajectory problem from a low Earth parking orbit to the Sun-Earth L1 and L2-halo orbits with the inclusion of radiation pressure and oblateness. Invariant manifold of the halo orbit provides a natural entrance to travel the spacecraft in the solar system along some specific paths due to its strong hyperbolic character. In this regard, the halo orbits near both collinear Lagrangian points are computed first. The manifold's approximation near the nominal halo orbit is computed using the eigenvectors of the monodromy matrix. The obtained local approximation provides globalization of the manifold by applying backward time propagation to the governing equations of motion. The desired transfer trajectory well suited for the transfer is explored by looking at a possible intersection between the Earth's parking orbit of the spacecraft and the manifold.

Topologically invariant macroscopic statistics in balanced networks of conductance-based integrate-and-fire neurons.

PubMed

Yger, Pierre; El Boustani, Sami; Destexhe, Alain; Frégnac, Yves

2011-10-01

The relationship between the dynamics of neural networks and their patterns of connectivity is far from clear, despite its importance for understanding functional properties. Here, we have studied sparsely-connected networks of conductance-based integrate-and-fire (IF) neurons with balanced excitatory and inhibitory connections and with finite axonal propagation speed. We focused on the genesis of states with highly irregular spiking activity and synchronous firing patterns at low rates, called slow Synchronous Irregular (SI) states. In such balanced networks, we examined the "macroscopic" properties of the spiking activity, such as ensemble correlations and mean firing rates, for different intracortical connectivity profiles ranging from randomly connected networks to networks with Gaussian-distributed local connectivity. We systematically computed the distance-dependent correlations at the extracellular (spiking) and intracellular (membrane potential) levels between randomly assigned pairs of neurons. The main finding is that such properties, when they are averaged at a macroscopic scale, are invariant with respect to the different connectivity patterns, provided the excitatory-inhibitory balance is the same. In particular, the same correlation structure holds for different connectivity profiles. In addition, we examined the response of such networks to external input, and found that the correlation landscape can be modulated by the mean level of synchrony imposed by the external drive. This modulation was found again to be independent of the external connectivity profile. We conclude that first and second-order "mean-field" statistics of such networks do not depend on the details of the connectivity at a microscopic scale. This study is an encouraging step toward a mean-field description of topological neuronal networks.

Saliency image of feature building for image quality assessment

NASA Astrophysics Data System (ADS)

Ju, Xinuo; Sun, Jiyin; Wang, Peng

2011-11-01

The purpose and method of image quality assessment are quite different for automatic target recognition (ATR) and traditional application. Local invariant feature detectors, mainly including corner detectors, blob detectors and region detectors etc., are widely applied for ATR. A saliency model of feature was proposed to evaluate feasibility of ATR in this paper. The first step consisted of computing the first-order derivatives on horizontal orientation and vertical orientation, and computing DoG maps in different scales respectively. Next, saliency images of feature were built based auto-correlation matrix in different scale. Then, saliency images of feature of different scales amalgamated. Experiment were performed on a large test set, including infrared images and optical images, and the result showed that the salient regions computed by this model were consistent with real feature regions computed by mostly local invariant feature extraction algorithms.

Solid harmonic wavelet scattering for predictions of molecule properties

NASA Astrophysics Data System (ADS)

Eickenberg, Michael; Exarchakis, Georgios; Hirn, Matthew; Mallat, Stéphane; Thiry, Louis

2018-06-01

We present a machine learning algorithm for the prediction of molecule properties inspired by ideas from density functional theory (DFT). Using Gaussian-type orbital functions, we create surrogate electronic densities of the molecule from which we compute invariant "solid harmonic scattering coefficients" that account for different types of interactions at different scales. Multilinear regressions of various physical properties of molecules are computed from these invariant coefficients. Numerical experiments show that these regressions have near state-of-the-art performance, even with relatively few training examples. Predictions over small sets of scattering coefficients can reach a DFT precision while being interpretable.

Enhanced and effective conformational sampling of protein molecular systems for their free energy landscapes.

PubMed

Higo, Junichi; Ikebe, Jinzen; Kamiya, Narutoshi; Nakamura, Haruki

2012-03-01

Protein folding and protein-ligand docking have long persisted as important subjects in biophysics. Using multicanonical molecular dynamics (McMD) simulations with realistic expressions, i.e., all-atom protein models and an explicit solvent, free-energy landscapes have been computed for several systems, such as the folding of peptides/proteins composed of a few amino acids up to nearly 60 amino-acid residues, protein-ligand interactions, and coupled folding and binding of intrinsically disordered proteins. Recent progress in conformational sampling and its applications to biophysical systems are reviewed in this report, including descriptions of several outstanding studies. In addition, an algorithm and detailed procedures used for multicanonical sampling are presented along with the methodology of adaptive umbrella sampling. Both methods control the simulation so that low-probability regions along a reaction coordinate are sampled frequently. The reaction coordinate is the potential energy for multicanonical sampling and is a structural identifier for adaptive umbrella sampling. One might imagine that this probability control invariably enhances conformational transitions among distinct stable states, but this study examines the enhanced conformational sampling of a simple system and shows that reasonably well-controlled sampling slows the transitions. This slowing is induced by a rapid change of entropy along the reaction coordinate. We then provide a recipe to speed up the sampling by loosening the rapid change of entropy. Finally, we report all-atom McMD simulation results of various biophysical systems in an explicit solvent.

Invariant Visual Object and Face Recognition: Neural and Computational Bases, and a Model, VisNet

PubMed Central

Rolls, Edmund T.

2012-01-01

Neurophysiological evidence for invariant representations of objects and faces in the primate inferior temporal visual cortex is described. Then a computational approach to how invariant representations are formed in the brain is described that builds on the neurophysiology. A feature hierarchy model in which invariant representations can be built by self-organizing learning based on the temporal and spatial statistics of the visual input produced by objects as they transform in the world is described. VisNet can use temporal continuity in an associative synaptic learning rule with a short-term memory trace, and/or it can use spatial continuity in continuous spatial transformation learning which does not require a temporal trace. The model of visual processing in the ventral cortical stream can build representations of objects that are invariant with respect to translation, view, size, and also lighting. The model has been extended to provide an account of invariant representations in the dorsal visual system of the global motion produced by objects such as looming, rotation, and object-based movement. The model has been extended to incorporate top-down feedback connections to model the control of attention by biased competition in, for example, spatial and object search tasks. The approach has also been extended to account for how the visual system can select single objects in complex visual scenes, and how multiple objects can be represented in a scene. The approach has also been extended to provide, with an additional layer, for the development of representations of spatial scenes of the type found in the hippocampus. PMID:22723777

Invariant Visual Object and Face Recognition: Neural and Computational Bases, and a Model, VisNet.

PubMed

Rolls, Edmund T

2012-01-01

Neurophysiological evidence for invariant representations of objects and faces in the primate inferior temporal visual cortex is described. Then a computational approach to how invariant representations are formed in the brain is described that builds on the neurophysiology. A feature hierarchy model in which invariant representations can be built by self-organizing learning based on the temporal and spatial statistics of the visual input produced by objects as they transform in the world is described. VisNet can use temporal continuity in an associative synaptic learning rule with a short-term memory trace, and/or it can use spatial continuity in continuous spatial transformation learning which does not require a temporal trace. The model of visual processing in the ventral cortical stream can build representations of objects that are invariant with respect to translation, view, size, and also lighting. The model has been extended to provide an account of invariant representations in the dorsal visual system of the global motion produced by objects such as looming, rotation, and object-based movement. The model has been extended to incorporate top-down feedback connections to model the control of attention by biased competition in, for example, spatial and object search tasks. The approach has also been extended to account for how the visual system can select single objects in complex visual scenes, and how multiple objects can be represented in a scene. The approach has also been extended to provide, with an additional layer, for the development of representations of spatial scenes of the type found in the hippocampus.

Dimensional analysis using toric ideals: primitive invariants.

PubMed

Atherton, Mark A; Bates, Ronald A; Wynn, Henry P

2014-01-01

Classical dimensional analysis in its original form starts by expressing the units for derived quantities, such as force, in terms of power products of basic units [Formula: see text] etc. This suggests the use of toric ideal theory from algebraic geometry. Within this the Graver basis provides a unique primitive basis in a well-defined sense, which typically has more terms than the standard Buckingham approach. Some textbook examples are revisited and the full set of primitive invariants found. First, a worked example based on convection is introduced to recall the Buckingham method, but using computer algebra to obtain an integer [Formula: see text] matrix from the initial integer [Formula: see text] matrix holding the exponents for the derived quantities. The [Formula: see text] matrix defines the dimensionless variables. But, rather than this integer linear algebra approach it is shown how, by staying with the power product representation, the full set of invariants (dimensionless groups) is obtained directly from the toric ideal defined by [Formula: see text]. One candidate for the set of invariants is a simple basis of the toric ideal. This, although larger than the rank of [Formula: see text], is typically not unique. However, the alternative Graver basis is unique and defines a maximal set of invariants, which are primitive in a simple sense. In addition to the running example four examples are taken from: a windmill, convection, electrodynamics and the hydrogen atom. The method reveals some named invariants. A selection of computer algebra packages is used to show the considerable ease with which both a simple basis and a Graver basis can be found.

Gromov-Witten invariants and localization

NASA Astrophysics Data System (ADS)

Morrison, David R.

2017-11-01

We give a pedagogical review of the computation of Gromov-Witten invariants via localization in 2D gauged linear sigma models. We explain the relationship between the two-sphere partition function of the theory and the Kähler potential on the conformal manifold. We show how the Kähler potential can be assembled from classical, perturbative, and non-perturbative contributions, and explain how the non-perturbative contributions are related to the Gromov-Witten invariants of the corresponding Calabi-Yau manifold. We then explain how localization enables efficient calculation of the two-sphere partition function and, ultimately, the Gromov-Witten invariants themselves. This is a contribution to the review issue ‘Localization techniques in quantum field theories’ (ed V Pestun and M Zabzine) which contains 17 chapters, available at [1].

Biomorphic networks: approach to invariant feature extraction and segmentation for ATR

NASA Astrophysics Data System (ADS)

Baek, Andrew; Farhat, Nabil H.

1998-10-01

Invariant features in two dimensional binary images are extracted in a single layer network of locally coupled spiking (pulsating) model neurons with prescribed synapto-dendritic response. The feature vector for an image is represented as invariant structure in the aggregate histogram of interspike intervals obtained by computing time intervals between successive spikes produced from each neuron over a given period of time and combining such intervals from all neurons in the network into a histogram. Simulation results show that the feature vectors are more pattern-specific and invariant under translation, rotation, and change in scale or intensity than achieved in earlier work. We also describe an application of such networks to segmentation of line (edge-enhanced or silhouette) images. The biomorphic spiking network's capabilities in segmentation and invariant feature extraction may prove to be, when they are combined, valuable in Automated Target Recognition (ATR) and other automated object recognition systems.

On the Convergence of an Implicitly Restarted Arnoldi Method

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

Lehoucq, Richard B.

We show that Sorensen's [35] implicitly restarted Arnoldi method (including its block extension) is simultaneous iteration with an implicit projection step to accelerate convergence to the invariant subspace of interest. By using the geometric convergence theory for simultaneous iteration due to Watkins and Elsner [43], we prove that an implicitly restarted Arnoldi method can achieve a super-linear rate of convergence to the dominant invariant subspace of a matrix. Moreover, we show how an IRAM computes a nested sequence of approximations for the partial Schur decomposition associated with the dominant invariant subspace of a matrix.

Rapid multi-modality preregistration based on SIFT descriptor.

PubMed

Chen, Jian; Tian, Jie

2006-01-01

This paper describes the scale invariant feature transform (SIFT) method for rapid preregistration of medical image. This technique originates from Lowe's method wherein preregistration is achieved by matching the corresponding keypoints between two images. The computational complexity has been reduced when we applied SIFT preregistration method before refined registration due to its O(n) exponential calculations. The features of SIFT are highly distinctive and invariant to image scaling and rotation, and partially invariant to change in illumination and contrast, it is robust and repeatable for cursorily matching two images. We also altered the descriptor so our method can deal with multimodality preregistration.

Multiscale Rotation-Invariant Convolutional Neural Networks for Lung Texture Classification.

PubMed

Wang, Qiangchang; Zheng, Yuanjie; Yang, Gongping; Jin, Weidong; Chen, Xinjian; Yin, Yilong

2018-01-01

We propose a new multiscale rotation-invariant convolutional neural network (MRCNN) model for classifying various lung tissue types on high-resolution computed tomography. MRCNN employs Gabor-local binary pattern that introduces a good property in image analysis-invariance to image scales and rotations. In addition, we offer an approach to deal with the problems caused by imbalanced number of samples between different classes in most of the existing works, accomplished by changing the overlapping size between the adjacent patches. Experimental results on a public interstitial lung disease database show a superior performance of the proposed method to state of the art.

Computation of partially invariant solutions for the Einstein Walker manifolds' identifying equations

NASA Astrophysics Data System (ADS)

Nadjafikhah, Mehdi; Jafari, Mehdi

2013-12-01

In this paper, partially invariant solutions (PISs) method is applied in order to obtain new four-dimensional Einstein Walker manifolds. This method is based on subgroup classification for the symmetry group of partial differential equations (PDEs) and can be regarded as the generalization of the similarity reduction method. For this purpose, those cases of PISs which have the defect structure δ=1 and are resulted from two-dimensional subalgebras are considered in the present paper. Also it is shown that the obtained PISs are distinct from the invariant solutions that obtained by similarity reduction method.

A model for size- and rotation-invariant pattern processing in the visual system.

PubMed

Reitboeck, H J; Altmann, J

1984-01-01

The mapping of retinal space onto the striate cortex of some mammals can be approximated by a log-polar function. It has been proposed that this mapping is of functional importance for scale- and rotation-invariant pattern recognition in the visual system. An exact log-polar transform converts centered scaling and rotation into translations. A subsequent translation-invariant transform, such as the absolute value of the Fourier transform, thus generates overall size- and rotation-invariance. In our model, the translation-invariance is realized via the R-transform. This transform can be executed by simple neural networks, and it does not require the complex computations of the Fourier transform, used in Mellin-transform size-invariance models. The logarithmic space distortion and differentiation in the first processing stage of the model is realized via "Mexican hat" filters whose diameter increases linearly with eccentricity, similar to the characteristics of the receptive fields of retinal ganglion cells. Except for some special cases, the model can explain object recognition independent of size, orientation and position. Some general problems of Mellin-type size-invariance models-that also apply to our model-are discussed.

Towards the computation of time-periodic inertial range dynamics

NASA Astrophysics Data System (ADS)

van Veen, L.; Vela-Martín, A.; Kawahara, G.

2018-04-01

We explore the possibility of computing simple invariant solutions, like travelling waves or periodic orbits, in Large Eddy Simulation (LES) on a periodic domain with constant external forcing. The absence of material boundaries and the simple forcing mechanism make this system a comparatively simple target for the study of turbulent dynamics through invariant solutions. We show, that in spite of the application of eddy viscosity the computations are still rather challenging and must be performed on GPU cards rather than conventional coupled CPUs. We investigate the onset of turbulence in this system by means of bifurcation analysis, and present a long-period, large-amplitude unstable periodic orbit that is filtered from a turbulent time series. Although this orbit is computed on a coarse grid, with only a small separation between the integral scale and the LES filter length, the periodic dynamics seem to capture a regeneration process of the large-scale vortices.

A New Formulation for Hybrid LES-RANS Computations

NASA Technical Reports Server (NTRS)

Woodruff, Stephen L.

2013-01-01

Ideally, a hybrid LES-RANS computation would employ LES only where necessary to make up for the failure of the RANS model to provide sufficient accuracy or to provide time-dependent information. Current approaches are fairly restrictive in the placement of LES and RANS regions; an LES-RANS transition in a boundary layer, for example, yields an unphysical log-layer shift. A hybrid computation is formulated here to allow greater control over the placement of LES and RANS regions and the transitions between them. The concept of model invariance is introduced, which provides a basis for interpreting hybrid results within an LES-RANS transition zone. Consequences of imposing model invariance include the addition of terms to the governing equations that compensate for unphysical gradients created as the model changes between RANS and LES. Computational results illustrate the increased accuracy of the approach and its insensitivity to the location of the transition and to the blending function employed.

Computer Proficiency for Online Learning: Factorial Invariance of Scores among Teachers

ERIC Educational Resources Information Center

Martin, Amy L.; Reeves, Todd D.; Smith, Thomas J.; Walker, David A.

2016-01-01

Online learning is variously employed in K-12 education, including for teacher professional development. However, the use of computer-based technologies for learning purposes assumes learner computer proficiency, making this construct an important domain of procedural knowledge in formal and informal online learning contexts. Addressing this…

Investigating Measurement Invariance in Computer-Based Personality Testing: The Impact of Using Anchor Items on Effect Size Indices

ERIC Educational Resources Information Center

Egberink, Iris J. L.; Meijer, Rob R.; Tendeiro, Jorge N.

2015-01-01

A popular method to assess measurement invariance of a particular item is based on likelihood ratio tests with all other items as anchor items. The results of this method are often only reported in terms of statistical significance, and researchers proposed different methods to empirically select anchor items. It is unclear, however, how many…

Invariant recognition drives neural representations of action sequences

PubMed Central

Poggio, Tomaso

2017-01-01

Recognizing the actions of others from visual stimuli is a crucial aspect of human perception that allows individuals to respond to social cues. Humans are able to discriminate between similar actions despite transformations, like changes in viewpoint or actor, that substantially alter the visual appearance of a scene. This ability to generalize across complex transformations is a hallmark of human visual intelligence. Advances in understanding action recognition at the neural level have not always translated into precise accounts of the computational principles underlying what representations of action sequences are constructed by human visual cortex. Here we test the hypothesis that invariant action discrimination might fill this gap. Recently, the study of artificial systems for static object perception has produced models, Convolutional Neural Networks (CNNs), that achieve human level performance in complex discriminative tasks. Within this class, architectures that better support invariant object recognition also produce image representations that better match those implied by human and primate neural data. However, whether these models produce representations of action sequences that support recognition across complex transformations and closely follow neural representations of actions remains unknown. Here we show that spatiotemporal CNNs accurately categorize video stimuli into action classes, and that deliberate model modifications that improve performance on an invariant action recognition task lead to data representations that better match human neural recordings. Our results support our hypothesis that performance on invariant discrimination dictates the neural representations of actions computed in the brain. These results broaden the scope of the invariant recognition framework for understanding visual intelligence from perception of inanimate objects and faces in static images to the study of human perception of action sequences. PMID:29253864

Self-organization via active exploration in robotic applications

NASA Technical Reports Server (NTRS)

Ogmen, H.; Prakash, R. V.

1992-01-01

We describe a neural network based robotic system. Unlike traditional robotic systems, our approach focussed on non-stationary problems. We indicate that self-organization capability is necessary for any system to operate successfully in a non-stationary environment. We suggest that self-organization should be based on an active exploration process. We investigated neural architectures having novelty sensitivity, selective attention, reinforcement learning, habit formation, flexible criteria categorization properties and analyzed the resulting behavior (consisting of an intelligent initiation of exploration) by computer simulations. While various computer vision researchers acknowledged recently the importance of active processes (Swain and Stricker, 1991), the proposed approaches within the new framework still suffer from a lack of self-organization (Aloimonos and Bandyopadhyay, 1987; Bajcsy, 1988). A self-organizing, neural network based robot (MAVIN) has been recently proposed (Baloch and Waxman, 1991). This robot has the capability of position, size rotation invariant pattern categorization, recognition and pavlovian conditioning. Our robot does not have initially invariant processing properties. The reason for this is the emphasis we put on active exploration. We maintain the point of view that such invariant properties emerge from an internalization of exploratory sensory-motor activity. Rather than coding the equilibria of such mental capabilities, we are seeking to capture its dynamics to understand on the one hand how the emergence of such invariances is possible and on the other hand the dynamics that lead to these invariances. The second point is crucial for an adaptive robot to acquire new invariances in non-stationary environments, as demonstrated by the inverting glass experiments of Helmholtz. We will introduce Pavlovian conditioning circuits in our future work for the precise objective of achieving the generation, coordination, and internalization of sequence of actions.

Securing SIFT: Privacy-preserving Outsourcing Computation of Feature Extractions Over Encrypted Image Data.

PubMed

Hu, Shengshan; Wang, Qian; Wang, Jingjun; Qin, Zhan; Ren, Kui

2016-05-13

Advances in cloud computing have greatly motivated data owners to outsource their huge amount of personal multimedia data and/or computationally expensive tasks onto the cloud by leveraging its abundant resources for cost saving and flexibility. Despite the tremendous benefits, the outsourced multimedia data and its originated applications may reveal the data owner's private information, such as the personal identity, locations or even financial profiles. This observation has recently aroused new research interest on privacy-preserving computations over outsourced multimedia data. In this paper, we propose an effective and practical privacy-preserving computation outsourcing protocol for the prevailing scale-invariant feature transform (SIFT) over massive encrypted image data. We first show that previous solutions to this problem have either efficiency/security or practicality issues, and none can well preserve the important characteristics of the original SIFT in terms of distinctiveness and robustness. We then present a new scheme design that achieves efficiency and security requirements simultaneously with the preservation of its key characteristics, by randomly splitting the original image data, designing two novel efficient protocols for secure multiplication and comparison, and carefully distributing the feature extraction computations onto two independent cloud servers. We both carefully analyze and extensively evaluate the security and effectiveness of our design. The results show that our solution is practically secure, outperforms the state-of-theart, and performs comparably to the original SIFT in terms of various characteristics, including rotation invariance, image scale invariance, robust matching across affine distortion, addition of noise and change in 3D viewpoint and illumination.

SecSIFT: Privacy-preserving Outsourcing Computation of Feature Extractions Over Encrypted Image Data.

PubMed

Hu, Shengshan; Wang, Qian; Wang, Jingjun; Qin, Zhan; Ren, Kui

2016-05-13

Advances in cloud computing have greatly motivated data owners to outsource their huge amount of personal multimedia data and/or computationally expensive tasks onto the cloud by leveraging its abundant resources for cost saving and flexibility. Despite the tremendous benefits, the outsourced multimedia data and its originated applications may reveal the data owner's private information, such as the personal identity, locations or even financial profiles. This observation has recently aroused new research interest on privacy-preserving computations over outsourced multimedia data. In this paper, we propose an effective and practical privacy-preserving computation outsourcing protocol for the prevailing scale-invariant feature transform (SIFT) over massive encrypted image data. We first show that previous solutions to this problem have either efficiency/security or practicality issues, and none can well preserve the important characteristics of the original SIFT in terms of distinctiveness and robustness. We then present a new scheme design that achieves efficiency and security requirements simultaneously with the preservation of its key characteristics, by randomly splitting the original image data, designing two novel efficient protocols for secure multiplication and comparison, and carefully distributing the feature extraction computations onto two independent cloud servers. We both carefully analyze and extensively evaluate the security and effectiveness of our design. The results show that our solution is practically secure, outperforms the state-of-theart, and performs comparably to the original SIFT in terms of various characteristics, including rotation invariance, image scale invariance, robust matching across affine distortion, addition of noise and change in 3D viewpoint and illumination.

Assigning Main Orientation to an EOH Descriptor on Multispectral Images.

PubMed

Li, Yong; Shi, Xiang; Wei, Lijun; Zou, Junwei; Chen, Fang

2015-07-01

This paper proposes an approach to compute an EOH (edge-oriented histogram) descriptor with main orientation. EOH has a better matching ability than SIFT (scale-invariant feature transform) on multispectral images, but does not assign a main orientation to keypoints. Alternatively, it tends to assign the same main orientation to every keypoint, e.g., zero degrees. This limits EOH to matching keypoints between images of translation misalignment only. Observing this limitation, we propose assigning to keypoints the main orientation that is computed with PIIFD (partial intensity invariant feature descriptor). In the proposed method, SIFT keypoints are detected from images as the extrema of difference of Gaussians, and every keypoint is assigned to the main orientation computed with PIIFD. Then, EOH is computed for every keypoint with respect to its main orientation. In addition, an implementation variant is proposed for fast computation of the EOH descriptor. Experimental results show that the proposed approach performs more robustly than the original EOH on image pairs that have a rotation misalignment.

Surface Current Density Mapping for Identification of Gastric Slow Wave Propagation

PubMed Central

Bradshaw, L. A.; Cheng, L. K.; Richards, W. O.; Pullan, A. J.

2009-01-01

The magnetogastrogram records clinically relevant parameters of the electrical slow wave of the stomach noninvasively. Besides slow wave frequency, gastric slow wave propagation velocity is a potentially useful clinical indicator of the state of health of gastric tissue, but it is a difficult parameter to determine from noninvasive bioelectric or biomagnetic measurements. We present a method for computing the surface current density (SCD) from multichannel magnetogastrogram recordings that allows computation of the propagation velocity of the gastric slow wave. A moving dipole source model with hypothetical as well as realistic biomagnetometer parameters demonstrates that while a relatively sparse array of magnetometer sensors is sufficient to compute a single average propagation velocity, more detailed information about spatial variations in propagation velocity requires higher density magnetometer arrays. Finally, the method is validated with simultaneous MGG and serosal EMG measurements in a porcine subject. PMID:19403355

Generation of skeletal mechanism by means of projected entropy participation indices

NASA Astrophysics Data System (ADS)

Paolucci, Samuel; Valorani, Mauro; Ciottoli, Pietro Paolo; Galassi, Riccardo Malpica

2017-11-01

When the dynamics of reactive systems develop very-slow and very-fast time scales separated by a range of active time scales, with gaps in the fast/active and slow/active time scales, then it is possible to achieve multi-scale adaptive model reduction along-with the integration of the ODEs using the G-Scheme. The scheme assumes that the dynamics is decomposed into active, slow, fast, and invariant subspaces. We derive expressions that establish a direct link between time scales and entropy production by using estimates provided by the G-Scheme. To calculate the contribution to entropy production, we resort to a standard model of a constant pressure, adiabatic, batch reactor, where the mixture temperature of the reactants is initially set above the auto-ignition temperature. Numerical experiments show that the contribution to entropy production of the fast subspace is of the same magnitude as the error threshold chosen for the identification of the decomposition of the tangent space, and the contribution of the slow subspace is generally much smaller than that of the active subspace. The information on entropy production associated with reactions within each subspace is used to define an entropy participation index that is subsequently utilized for model reduction.

Instantons, quivers and noncommutative Donaldson-Thomas theory

NASA Astrophysics Data System (ADS)

Cirafici, Michele; Sinkovics, Annamaria; Szabo, Richard J.

2011-12-01

We construct noncommutative Donaldson-Thomas invariants associated with abelian orbifold singularities by analyzing the instanton contributions to a six-dimensional topological gauge theory. The noncommutative deformation of this gauge theory localizes on noncommutative instantons which can be classified in terms of three-dimensional Young diagrams with a colouring of boxes according to the orbifold group. We construct a moduli space for these gauge field configurations which allows us to compute its virtual numbers via the counting of representations of a quiver with relations. The quiver encodes the instanton dynamics of the noncommutative gauge theory, and is associated to the geometry of the singularity via the generalized McKay correspondence. The index of BPS states which compute the noncommutative Donaldson-Thomas invariants is realized via topological quantum mechanics based on the quiver data. We illustrate these constructions with several explicit examples, involving also higher rank Coulomb branch invariants and geometries with compact divisors, and connect our approach with other ones in the literature.

Invariant operators, orthogonal bases and correlators in general tensor models

NASA Astrophysics Data System (ADS)

Diaz, Pablo; Rey, Soo-Jong

2018-07-01

We study invariant operators in general tensor models. We show that representation theory provides an efficient framework to count and classify invariants in tensor models of (gauge) symmetry Gd = U (N1) ⊗ ⋯ ⊗ U (Nd). As a continuation and completion of our earlier work, we present two natural ways of counting invariants, one for arbitrary Gd and another valid for large rank of Gd. We construct bases of invariant operators based on the counting, and compute correlators of their elements. The basis associated with finite rank of Gd diagonalizes the two-point function of the free theory. It is analogous to the restricted Schur basis used in matrix models. We show that the constructions get almost identical as we swap the Littlewood-Richardson numbers in multi-matrix models with Kronecker coefficients in general tensor models. We explore the parallelism between matrix model and tensor model in depth from the perspective of representation theory and comment on several ideas for future investigation.

What makes viewpoint-invariant properties perceptually salient?

PubMed

Jacobs, David W

2003-07-01

It has been noted that many of the perceptually salient image properties identified by the Gestalt psychologists, such as collinearity, parallelism, and good continuation, age invariant to changes in viewpoint. However, I show that viewpoint invariance is not sufficient to distinguish these Gestalt properties; one can define an infinite number of viewpoint-invariant properties that are not perceptually salient. I then show that generally, the perceptually salient viewpoint-invariant properties are minimal, in the sense that they can be derived by using less image information than for nonsalient properties. This finding provides support for the hypothesis that the biological relevance of an image property is determined both by the extent to which it provides information about the world and by the ease with which this property can be computed. [An abbreviated version of this work, including technical details that are avoided in this paper, is contained in K. Boyer and S. Sarker, eds., Perceptual Organization for Artificial Vision Systems (Kluwer Academic, Dordrecht, The Netherlands, 2000), pp. 121-138.

All Chern-Simons invariants of 4D, N = 1 gauged superform hierarchies

NASA Astrophysics Data System (ADS)

Becker, Katrin; Becker, Melanie; Linch, William D.; Randall, Stephen; Robbins, Daniel

2017-04-01

We give a geometric description of supersymmetric gravity/(non-)abelian p-form hierarchies in superspaces with 4D, N = 1 super-Poincaré invariance. These hierarchies give rise to Chern-Simons-like invariants, such as those of the 5D, N = 1 graviphoton and the eleven-dimensional 3-form but also generalizations such as Green-Schwarz-like/ BF -type couplings. Previous constructions based on prepotential superfields are reinterpreted in terms of p-forms in superspace thereby elucidating the underlying geometry. This vastly simplifies the calculations of superspace field-strengths, Bianchi identities, and Chern-Simons invariants. Using this, we prove the validity of a recursive formula for the conditions defining these actions for any such tensor hierarchy. Solving it at quadratic and cubic orders, we recover the known results for the BF -type and cubic Chern-Simons actions. As an application, we compute the quartic invariant ˜ AdAdAdA + . . . relevant, for example, to seven-dimensional supergravity compactifications.

Validation and Measurement Invariance of the Computer Attitude Measure for Young Students (CAMYS)

ERIC Educational Resources Information Center

Asil, Mustafa; Teo, Timothy; Noyes, Jan

2014-01-01

Students' attitudes toward technology, especially computers, play a key role in the effective integration of Information and Communication Technologies (ICT). Although numerous attitude scales have been developed to measure attitude toward computers, we found only a few instruments designed for young students aged 11-13 years. Among these attitude…

Comparison of Low-Energy Lunar Transfer Trajectories to Invariant Manifolds

NASA Technical Reports Server (NTRS)

Anderson, Rodney L.; Parker, Jeffrey S.

2011-01-01

In this study, transfer trajectories from the Earth to the Moon that encounter the Moon at various flight path angles are examined, and lunar approach trajectories are compared to the invariant manifolds of selected unstable orbits in the circular restricted three-body problem. Previous work focused on lunar impact and landing trajectories encountering the Moon normal to the surface, and this research extends the problem with different flight path angles in three dimensions. The lunar landing geometry for a range of Jacobi constants are computed, and approaches to the Moon via invariant manifolds from unstable orbits are analyzed for different energy levels.

A Consistent AVHRR Visible Calibration Record Based on Multiple Methods Applicable for the NOAA Degrading Orbits. Part 2 ; Validation

NASA Technical Reports Server (NTRS)

Doelling, David R.; Bhatt, Rajendra; Scarino, Benjamin R.; Gopalan, Arun; Haney, Conor O.; Minnis, Patrick; Bedka, Kristopher M.

2016-01-01

Consistent cross-sensor Advanced Very High Resolution Radiometer (AVHRR) calibration coefficients are determined using desert, polar ice, and deep convective cloud (DCC) invariant Earth targets. The greatest AVHRR calibration challenge is the slow orbit degradation of the host satellite, which precesses toward a terminator orbit. This issue is solved by characterizing the invariant targets with NOAA-16 AVHRR observed radiances that have been referenced to the Aqua Moderate Resolution Imaging Spectrometer (MODIS) calibration using simultaneous nadir overpass (SNO) observations. Another benefit of the NOAA-16 invariant target-modeled reflectance method is that, because of the similarities among the AVHRR spectral response functions, a smaller spectral band adjustment factor is required than when establishing calibrations relative to a non-AVHRR reference instrument. The sensor- and band-specific calibration uncertainties, with respect to the calibration reference, are, on average, 2 percent and 3 percent for channels 1 and 2, respectively. The uncertainties are smaller for sensors that are in afternoon orbits, have longer records, and spend less time in terminator conditions. The multiple invariant targets referenced to Aqua MODIS (MITRAM) AVHRR calibration coefficients are evaluated for individual target consistency, compared against Aqua MODIS/AVHRR SNOs, and selected published calibration gains. The MITRAM and SNO relative calibration biases mostly agree to within 1 percent for channels 1 and 2, respectively. The individual invariant target and MITRAM sensor relative calibration biases are mostly consistent to within 1 percent and 2 percent for channels 1 and 2, respectively. The differences between the MITRAM and other published calibrations are mostly attributed to the reference instrument calibration differences.

European Scientific Notes. Volume 35, Number 12,

DTIC Science & Technology

1981-12-31

been redesigned to work A. Osorio, which was organized some 3 with the Intel 8085 microprocessor, it years ago and contains about half of the has the...operational set. attempt to derive a set of invariants MOISE is based on the Intel 8085A upon which virtually speaker-invariant microprocessor, and...FACILITY software interface; a Research Signal Processor (RSP) using reduced computational It has been IBM International’s complexity algorithms for

Transient Invariant and Quasi-Invariant Structures in an Example of an Aperiodically Time Dependent Fluid Flow

NASA Astrophysics Data System (ADS)

Fortunati, Alessandro; Wiggins, Stephen

Starting from the concept of invariant KAM tori for nearly-integrable Hamiltonian systems with periodic or quasi-periodic nonautonomous perturbation, the paper analyzes the “analogue” of this class of invariant objects when the dependence on time is aperiodic. The investigation is carried out in a model motivated by the problem of a traveling wave in a channel over a smooth, quasi- and asymptotically flat (from which the “transient” feature) bathymetry, representing a case in which the described structures play the role of barriers to fluid transport in phase space. The paper provides computational evidence for the existence of transient structures also for “large” values of the perturbation size, as a complement to the rigorous results already proven by the first author for real-analytic bathymetry functions.

Attractor reconstruction for non-linear systems: a methodological note

USGS Publications Warehouse

Nichols, J.M.; Nichols, J.D.

2001-01-01

Attractor reconstruction is an important step in the process of making predictions for non-linear time-series and in the computation of certain invariant quantities used to characterize the dynamics of such series. The utility of computed predictions and invariant quantities is dependent on the accuracy of attractor reconstruction, which in turn is determined by the methods used in the reconstruction process. This paper suggests methods by which the delay and embedding dimension may be selected for a typical delay coordinate reconstruction. A comparison is drawn between the use of the autocorrelation function and mutual information in quantifying the delay. In addition, a false nearest neighbor (FNN) approach is used in minimizing the number of delay vectors needed. Results highlight the need for an accurate reconstruction in the computation of the Lyapunov spectrum and in prediction algorithms.

Fluctuating ideal-gas lattice Boltzmann method with fluctuation dissipation theorem for nonvanishing velocities.

PubMed

Kaehler, G; Wagner, A J

2013-06-01

Current implementations of fluctuating ideal-gas descriptions with the lattice Boltzmann methods are based on a fluctuation dissipation theorem, which, while greatly simplifying the implementation, strictly holds only for zero mean velocity and small fluctuations. We show how to derive the fluctuation dissipation theorem for all k, which was done only for k=0 in previous derivations. The consistent derivation requires, in principle, locally velocity-dependent multirelaxation time transforms. Such an implementation is computationally prohibitively expensive but, with a small computational trick, it is feasible to reproduce the correct FDT without overhead in computation time. It is then shown that the previous standard implementations perform poorly for non vanishing mean velocity as indicated by violations of Galilean invariance of measured structure factors. Results obtained with the method introduced here show a significant reduction of the Galilean invariance violations.

ON SUN-TO-EARTH PROPAGATION OF CORONAL MASS EJECTIONS: II. SLOW EVENTS AND COMPARISON WITH OTHERS

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

Liu, Ying D.; Hu, Huidong; Wang, Chi

As a follow-up study on Sun-to-Earth propagation of fast coronal mass ejections (CMEs), we examine the Sun-to-Earth characteristics of slow CMEs combining heliospheric imaging and in situ observations. Three events of particular interest, the 2010 June 16, 2011 March 25, and 2012 September 25 CMEs, are selected for this study. We compare slow CMEs with fast and intermediate-speed events, and obtain key results complementing the attempt of Liu et al. to create a general picture of CME Sun-to-Earth propagation: (1) the Sun-to-Earth propagation of a typical slow CME can be approximately described by two phases, a gradual acceleration out tomore » about 20–30 solar radii, followed by a nearly invariant speed around the average solar wind level; (2) comparison between different types of CMEs indicates that faster CMEs tend to accelerate and decelerate more rapidly and have shorter cessation distances for the acceleration and deceleration; (3) both intermediate-speed and slow CMEs would have speeds comparable to the average solar wind level before reaching 1 au; (4) slow CMEs have a high potential to interact with other solar wind structures in the Sun–Earth space due to their slow motion, providing critical ingredients to enhance space weather; and (5) the slow CMEs studied here lack strong magnetic fields at the Earth but tend to preserve a flux-rope structure with an axis generally perpendicular to the radial direction from the Sun. We also suggest a “best” strategy for the application of a triangulation concept in determining CME Sun-to-Earth kinematics, which helps to clarify confusions about CME geometry assumptions in the triangulation and to improve CME analysis and observations.« less

Theoretical, Experimental, and Computational Evaluation of Several Vane-Type Slow-Wave Structures

NASA Technical Reports Server (NTRS)

Wallett, Thomas M.; Qureshi, A. Haq

1994-01-01

Several types of periodic vane slow-wave structures were fabricated. The dispersion characteristics were found by theoretical analysis, experimental testing, and computer simulation using the MAFIA code. Computer-generated characteristics agreed to approximately within 2 percent of the experimental characteristics for all structures. The theoretical characteristics, however, deviated increasingly as the width to height ratio became smaller. Interaction impedances were also computed based on the experimental and computer-generated resonance frequency shifts due to the introduction of a perturbing dielectric rod.

Probing Higgs self-coupling of a classically scale invariant model in e+e- → Zhh: Evaluation at physical point

NASA Astrophysics Data System (ADS)

Fujitani, Y.; Sumino, Y.

2018-04-01

A classically scale invariant extension of the standard model predicts large anomalous Higgs self-interactions. We compute missing contributions in previous studies for probing the Higgs triple coupling of a minimal model using the process e+e- → Zhh. Employing a proper order counting, we compute the total and differential cross sections at the leading order, which incorporate the one-loop corrections between zero external momenta and their physical values. Discovery/exclusion potential of a future e+e- collider for this model is estimated. We also find a unique feature in the momentum dependence of the Higgs triple vertex for this class of models.

HONTIOR - HIGHER-ORDER NEURAL NETWORK FOR TRANSFORMATION INVARIANT OBJECT RECOGNITION

NASA Technical Reports Server (NTRS)

Spirkovska, L.

1994-01-01

Neural networks have been applied in numerous fields, including transformation invariant object recognition, wherein an object is recognized despite changes in the object's position in the input field, size, or rotation. One of the more successful neural network methods used in invariant object recognition is the higher-order neural network (HONN) method. With a HONN, known relationships are exploited and the desired invariances are built directly into the architecture of the network, eliminating the need for the network to learn invariance to transformations. This results in a significant reduction in the training time required, since the network needs to be trained on only one view of each object, not on numerous transformed views. Moreover, one hundred percent accuracy is guaranteed for images characterized by the built-in distortions, providing noise is not introduced through pixelation. The program HONTIOR implements a third-order neural network having invariance to translation, scale, and in-plane rotation built directly into the architecture, Thus, for 2-D transformation invariance, the network needs only to be trained on just one view of each object. HONTIOR can also be used for 3-D transformation invariant object recognition by training the network only on a set of out-of-plane rotated views. Historically, the major drawback of HONNs has been that the size of the input field was limited to the memory required for the large number of interconnections in a fully connected network. HONTIOR solves this problem by coarse coding the input images (coding an image as a set of overlapping but offset coarser images). Using this scheme, large input fields (4096 x 4096 pixels) can easily be represented using very little virtual memory (30Mb). The HONTIOR distribution consists of three main programs. The first program contains the training and testing routines for a third-order neural network. The second program contains the same training and testing procedures as the first, but it also contains a number of functions to display and edit training and test images. Finally, the third program is an auxiliary program which calculates the included angles for a given input field size. HONTIOR is written in C language, and was originally developed for Sun3 and Sun4 series computers. Both graphic and command line versions of the program are provided. The command line version has been successfully compiled and executed both on computers running the UNIX operating system and on DEC VAX series computer running VMS. The graphic version requires the SunTools windowing environment, and therefore runs only on Sun series computers. The executable for the graphics version of HONTIOR requires 1Mb of RAM. The standard distribution medium for HONTIOR is a .25 inch streaming magnetic tape cartridge in UNIX tar format. It is also available on a 3.5 inch diskette in UNIX tar format. The package includes sample input and output data. HONTIOR was developed in 1991. Sun, Sun3 and Sun4 are trademarks of Sun Microsystems, Inc. UNIX is a registered trademark of AT&T Bell Laboratories. DEC, VAX, and VMS are trademarks of Digital Equipment Corporation.

Exhaustive analysis of the modular structure of the spliceosomal assembly network: a petri net approach.

PubMed

Bortfeldt, Ralf H; Schuster, Stefan; Koch, Ina

2011-01-01

Spliceosomes are macro-complexes involving hundreds of proteins with many functional interactions. Spliceosome assembly belongs to the key processes that enable splicing of mRNA and modulate alternative splicing. A detailed list of factors involved in spliceosomal reactions has been assorted over the past decade, but, their functional interplay is often unknown and most of the present biological models cover only parts of the complete assembly process. It is a challenging task to build a computational model that integrates dispersed knowledge and combines a multitude of reaction schemes proposed earlier. Because for most reactions involved in spliceosome assembly kinetic parameters are not available, we propose a discrete modeling using Petri nets, through which we are enabled to get insights into the system's behavior via computation of structural and dynamic properties. In this paper, we compile and examine reactions from experimental reports that contribute to a functional spliceosome. All these reactions form a network, which describes the inventory and conditions necessary to perform the splicing process. The analysis is mainly based on system invariants. Transition invariants (T-invariants) can be interpreted as signaling routes through the network. Due to the huge number of T-invariants that arise with increasing network size and complexity, maximal common transition sets (MCTS) and T-clusters were used for further analysis. Additionally, we introduce a false color map representation, which allows a quick survey of network modules and the visual detection of single reactions or reaction sequences, which participate in more than one signaling route. We designed a structured model of spliceosome assembly, which combines the demands on a platform that i) can display involved factors and concurrent processes, ii) offers the possibility to run computational methods for knowledge extraction, and iii) is successively extendable as new insights into spliceosome function are reported by experimental reports. The network consists of 161 transitions (reactions) and 140 places (reactants). All reactions are part of at least one of the 71 T-invariants. These T-invariants define pathways, which are in good agreement with the current knowledge and known hypotheses on reaction sequences during spliceosome assembly, hence contributing to a functional spliceosome. We demonstrate that present knowledge, in particular of the initial part of the assembly process, describes parallelism and interaction of signaling routes, which indicate functional redundancy and reflect the dependency of spliceosome assembly initiation on different cellular conditions. The complexity of the network is further increased by two switches, which introduce alternative routes during A-complex formation in early spliceosome assembly and upon transition from the B-complex to the C-complex. By compiling known reactions into a complete network, the combinatorial nature of invariant computation leads to pathways that have previously not been described as connected routes, although their constituents were known. T-clusters divide the network into modules, which we interpret as building blocks in spliceosome maturation. We conclude that Petri net representations of large biological networks and system invariants, are well-suited as a means for validating the integration of experimental knowledge into a consistent model. Based on this network model, the design of further experiments is facilitated.

Exhaustive analysis of the modular structure of the spliceosomal assembly network: a Petri net approach.

PubMed

Bortfeldt, Ralf H; Schuster, Stefan; Koch, Ina

2010-01-01

Spliceosomes are macro-complexes involving hundreds of proteins with many functional interactions. Spliceosome assembly belongs to the key processes that enable splicing of mRNA and modulate alternative splicing. A detailed list of factors involved in spliceosomal reactions has been assorted over the past decade, but, their functional interplay is often unknown and most of the present biological models cover only parts of the complete assembly process. It is a challenging task to build a computational model that integrates dispersed knowledge and combines a multitude of reaction schemes proposed earlier.Because for most reactions involved in spliceosome assembly kinetic parameters are not available, we propose a discrete modeling using Petri nets, through which we are enabled to get insights into the system's behavior via computation of structural and dynamic properties. In this paper, we compile and examine reactions from experimental reports that contribute to a functional spliceosome. All these reactions form a network, which describes the inventory and conditions necessary to perform the splicing process. The analysis is mainly based on system invariants. Transition invariants (T-invariants) can be interpreted as signaling routes through the network. Due to the huge number of T-invariants that arise with increasing network size and complexity, maximal common transition sets (MCTS) and T-clusters were used for further analysis. Additionally, we introduce a false color map representation, which allows a quick survey of network modules and the visual detection of single reactions or reaction sequences, which participate in more than one signaling route. We designed a structured model of spliceosome assembly, which combines the demands on a platform that i) can display involved factors and concurrent processes, ii) offers the possibility to run computational methods for knowledge extraction, and iii) is successively extendable as new insights into spliceosome function are reported by experimental reports. The network consists of 161 transitions (reactions) and 140 places (reactants). All reactions are part of at least one of the 71 T-invariants. These T-invariants define pathways, which are in good agreement with the current knowledge and known hypotheses on reaction sequences during spliceosome assembly, hence contributing to a functional spliceosome. We demonstrate that present knowledge, in particular of the initial part of the assembly process, describes parallelism and interaction of signaling routes, which indicate functional redundancy and reflect the dependency of spliceosome assembly initiation on different cellular conditions. The complexity of the network is further increased by two switches, which introduce alternative routes during A-complex formation in early spliceosome assembly and upon transition from the B-complex to the C-complex. By compiling known reactions into a complete network, the combinatorial nature of invariant computation leads to pathways that have previously not been described as connected routes, although their constituents were known. T-clusters divide the network into modules, which we interpret as building blocks in spliceosome maturation. We conclude that Petri net representations of large biological networks and system invariants, are well-suited as a means for validating the integration of experimental knowledge into a consistent model. Based on this network model, the design of further experiments is facilitated.

Gauge-invariant effective potential: Equilibrium and nonequilibrium aspects

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

Boyanovsky, D.; Brahm, D.; Holman, R.

1996-07-01

We propose a gauge-invariant formulation of the effective potential in terms of a gauge-invariant order parameter, for the Abelian Higgs model. The one-loop contribution at zero and finite temperature is computed explicitly, and the leading terms in the high temperature expansion are obtained. The result is contrasted with the effective potential obtained in several covariant gauge-fixing schemes, and the gauge-invariant quantities that can be reliably extracted from these are identified. It is pointed out that the gauge-invariant effective potential in the one-loop approximation is complex for {ital all} {ital values} of the order parameter between the maximum and the minimummore » of the tree level potential, both at zero and nonzero temperatures. The imaginary part is related to long-wavelength instabilities towards phase separation. We study the real-time dynamics of initial states in the spinodal region, and relate the imaginary part of the effective potential to the growth rate of equal-time gauge-invariant correlation functions in these states. We conjecture that the spinodal instabilities may play a role in nonequilibrium processes {ital inside} the nucleating bubbles if the transition is first order. {copyright} {ital 1996 The American Physical Society.}« less

Invariant visual object recognition: a model, with lighting invariance.

PubMed

Rolls, Edmund T; Stringer, Simon M

2006-01-01

How are invariant representations of objects formed in the visual cortex? We describe a neurophysiological and computational approach which focusses on a feature hierarchy model in which invariant representations can be built by self-organizing learning based on the statistics of the visual input. The model can use temporal continuity in an associative synaptic learning rule with a short term memory trace, and/or it can use spatial continuity in Continuous Transformation learning. The model of visual processing in the ventral cortical stream can build representations of objects that are invariant with respect to translation, view, size, and in this paper we show also lighting. The model has been extended to provide an account of invariant representations in the dorsal visual system of the global motion produced by objects such as looming, rotation, and object-based movement. The model has been extended to incorporate top-down feedback connections to model the control of attention by biased competition in for example spatial and object search tasks. The model has also been extended to account for how the visual system can select single objects in complex visual scenes, and how multiple objects can be represented in a scene.

Computational foundations of the visual number sense.

PubMed

Stoianov, Ivilin Peev; Zorzi, Marco

2017-01-01

We provide an emergentist perspective on the computational mechanism underlying numerosity perception, its development, and the role of inhibition, based on our deep neural network model. We argue that the influence of continuous visual properties does not challenge the notion of number sense, but reveals limit conditions for the computation that yields invariance in numerosity perception. Alternative accounts should be formalized in a computational model.

Out with the old, in with the new: Assessing change in screen time when measurement changes over time.

PubMed

Gunnell, Katie E; Brunet, Jennifer; Bélanger, Mathieu

2018-03-01

We examined if screen time can be assessed over time when the measurement protocol has changed to reflect advances in technology. Beginning in 2011, 929 youth (9-12 years at time one) living in in New Brunswick (Canada) self-reported the amount of time spent watching television (cycles 1-13), using computers (cycles 1-13), and playing video games (cycles 3-13). Using longitudinal invariance to test a shifting indicators model of screen time, we found that the relationships between the latent variable reflecting overall screen time and the indicators used to assess screen time were invariant across cycles (weak invariance). We also found that 31 out of 37 indicator intercepts were invariant, meaning that most indicators were answered similarly (i.e., on the same metric) across cycles (partial strong invariance), and that 28 out of 37 indicator residuals were invariant indicating that similar sources of error were present over time (partial strict invariance). Overall, across all survey cycles, 76% of indicators were fully invariant. Whereas issues were noted when new examples of screen-based technology (e.g., iPads) were added, having established partial invariance, we suggest it is still possible to assess change in screen time despite having changing indicators over time. Although it is not possible to draw definitive conclusions concerning other self-report measures of screen time, our findings may assist other researchers considering modifying self-report measures in longitudinal studies to reflect technological advancements and increase the precision of their results.

Applications of invariants in general relativity

NASA Astrophysics Data System (ADS)

Pelavas, Nicos

This thesis explores various kinds of invariants and their use in general relativity. To start, the simplest invariants, those polynomial in the Riemann tensor, are examined and the currently accepted Carminati-Zakhary set is compared to the Carminati-McLenaghan set. A number of algebraic relations linking the two sets are given. The concept of gravitational entropy, as proposed by Penrose, has some physically appealing properties which have motivated attempts to quantify this notion using various invariants. We study this in the context of self-similar spacetimes. A general result is obtained which gives the Lie derivative of any invariant or ratio of invariants along a homothetic trajectory. A direct application of this result shows that the currently used gravitational epoch function fails to satisfy certain criteria. Based on this work, candidates for a gravitational epoch function are proposed that behave accordingly in these models. The instantaneous ergo surface in the Kerr solution is studied and shown to possess conical points at the poles when embedded in three dimensional Euclidean space. These intrinsic singularities had remained undiscovered for a generation. We generalize the Gauss-Bonnet theorem to accommodate these points and use it to compute a topological invariant, the Euler characteristic, for this surface. Interest in solutions admitting a cosmological constant has prompted us to study ergo surfaces in stationary non-asymptotically flat spacetimes. In these cases we show that there is in fact a family of ergo surfaces. By using a kinematic invariant constructed from timelike Killing vectors we try to find a preferred ergo surface. We illustrate to what extent this invariant fails to provide such a measure.

Computer simulation of the mathematical modeling involved in constitutive equation development: Via symbolic computations

NASA Technical Reports Server (NTRS)

Arnold, S. M.; Tan, H. Q.; Dong, X.

1989-01-01

Development of new material models for describing the high temperature constitutive behavior of real materials represents an important area of research in engineering disciplines. Derivation of mathematical expressions (constitutive equations) which describe this high temperature material behavior can be quite time consuming, involved and error prone; thus intelligent application of symbolic systems to facilitate this tedious process can be of significant benefit. A computerized procedure (SDICE) capable of efficiently deriving potential based constitutive models, in analytical form is presented. This package, running under MACSYMA, has the following features: partial differentiation, tensor computations, automatic grouping and labeling of common factors, expression substitution and simplification, back substitution of invariant and tensorial relations and a relational data base. Also limited aspects of invariant theory were incorporated into SDICE due to the utilization of potentials as a starting point and the desire for these potentials to be frame invariant (objective). Finally not only calculation of flow and/or evolutionary laws were accomplished but also the determination of history independent nonphysical coefficients in terms of physically measurable parameters, e.g., Young's modulus, was achieved. The uniqueness of SDICE resides in its ability to manipulate expressions in a general yet predefined order and simplify expressions so as to limit expression growth. Results are displayed when applicable utilizing index notation.

Massively parallel algorithms for real-time wavefront control of a dense adaptive optics system

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

Fijany, A.; Milman, M.; Redding, D.

1994-12-31

In this paper massively parallel algorithms and architectures for real-time wavefront control of a dense adaptive optic system (SELENE) are presented. The authors have already shown that the computation of a near optimal control algorithm for SELENE can be reduced to the solution of a discrete Poisson equation on a regular domain. Although, this represents an optimal computation, due the large size of the system and the high sampling rate requirement, the implementation of this control algorithm poses a computationally challenging problem since it demands a sustained computational throughput of the order of 10 GFlops. They develop a novel algorithm,more » designated as Fast Invariant Imbedding algorithm, which offers a massive degree of parallelism with simple communication and synchronization requirements. Due to these features, this algorithm is significantly more efficient than other Fast Poisson Solvers for implementation on massively parallel architectures. The authors also discuss two massively parallel, algorithmically specialized, architectures for low-cost and optimal implementation of the Fast Invariant Imbedding algorithm.« less

Recovery of speed of information processing in closed-head-injury patients.

PubMed

Zwaagstra, R; Schmidt, I; Vanier, M

1996-06-01

After severe traumatic brain injury, patients almost invariably demonstrate a slowing of reaction time, reflecting a slowing of central information processing. Methodological problems associated with the traditional method for the analysis of longitudinal data (MANOVA) severely complicate studies on cognitive recovery. It is argued that multilevel models are often better suited for the analysis of improvement over time in clinical settings. Multilevel models take into account individual differences in both overall performance level and recovery. These models enable individual predictions for the recovery of speed of information processing. Recovery is modelled in a group of closed-head-injury patients (N = 24). Recovery was predicted by age and severity of injury, as indicated by coma duration. Over a period up to 44 months post trauma, reaction times were found to decrease faster for patients with longer coma duration.

Neural correlations enable invariant coding and perception of natural stimuli in weakly electric fish

PubMed Central

Metzen, Michael G; Hofmann, Volker; Chacron, Maurice J

2016-01-01

Neural representations of behaviorally relevant stimulus features displaying invariance with respect to different contexts are essential for perception. However, the mechanisms mediating their emergence and subsequent refinement remain poorly understood in general. Here, we demonstrate that correlated neural activity allows for the emergence of an invariant representation of natural communication stimuli that is further refined across successive stages of processing in the weakly electric fish Apteronotus leptorhynchus. Importantly, different patterns of input resulting from the same natural communication stimulus occurring in different contexts all gave rise to similar behavioral responses. Our results thus reveal how a generic neural circuit performs an elegant computation that mediates the emergence and refinement of an invariant neural representation of natural stimuli that most likely constitutes a neural correlate of perception. DOI: http://dx.doi.org/10.7554/eLife.12993.001 PMID:27128376

Performance limitations of translationally symmetric nonimaging devices

NASA Astrophysics Data System (ADS)

Bortz, John C.; Shatz, Narkis E.; Winston, Roland

2001-11-01

The component of the optical direction vector along the symmetry axis is conserved for all rays propagated through a translationally symmetric optical device. This quality, referred to herein as the translational skew invariant, is analogous to the conventional skew invariant, which is conserved in rotationally symmetric optical systems. The invariance of both of these quantities is a consequence of Noether's theorem. We show how performance limits for translationally symmetric nonimaging optical devices can be derived from the distributions of the translational skew invariant for the optical source and for the target to which flux is to be transferred. Examples of computed performance limits are provided. In addition, we show that a numerically optimized non-tracking solar concentrator utilizing symmetry-breaking surface microstructure can overcome the performance limits associated with translational symmetry. The optimized design provides a 47.4% increase in efficiency and concentration relative to an ideal translationally symmetric concentrator.

Global stability and tumor clearance conditions for a cancer chemotherapy system

NASA Astrophysics Data System (ADS)

Valle, Paul A.; Starkov, Konstantin E.; Coria, Luis N.

2016-11-01

In this paper we study the global dynamics of a cancer chemotherapy system presented by de Pillis et al. (2007). This mathematical model describes the interaction between tumor cells, effector-immune cells, circulating lymphocytes and chemotherapy treatment. By applying the localization method of compact invariant sets, we find lower and upper bounds for these three cells populations. Further, we define a bounded domain in R+,04 where all compact invariant sets of the system are located and provide conditions under which this domain is positively invariant. We apply LaSalle's invariance principle and one result concerning two-dimensional competitive systems in order to derive sufficient conditions for tumor clearance and global asymptotic stability of the tumor-free equilibrium point. These conditions are computed by using bounds of the localization domain and they are given in terms of the chemotherapy treatment. Finally, we perform numerical simulations in order to illustrate our results.

Learning invariance from natural images inspired by observations in the primary visual cortex.

PubMed

Teichmann, Michael; Wiltschut, Jan; Hamker, Fred

2012-05-01

The human visual system has the remarkable ability to largely recognize objects invariant of their position, rotation, and scale. A good interpretation of neurobiological findings involves a computational model that simulates signal processing of the visual cortex. In part, this is likely achieved step by step from early to late areas of visual perception. While several algorithms have been proposed for learning feature detectors, only few studies at hand cover the issue of biologically plausible learning of such invariance. In this study, a set of Hebbian learning rules based on calcium dynamics and homeostatic regulations of single neurons is proposed. Their performance is verified within a simple model of the primary visual cortex to learn so-called complex cells, based on a sequence of static images. As a result, the learned complex-cell responses are largely invariant to phase and position.

Invariant and partially-invariant solutions of the equations describing a non-stationary and isentropic flow for an ideal and compressible fluid in (3 + 1) dimensions

NASA Astrophysics Data System (ADS)

Grundland, A. M.; Lalague, L.

1996-04-01

This paper presents a new method of constructing, certain classes of solutions of a system of partial differential equations (PDEs) describing the non-stationary and isentropic flow for an ideal compressible fluid. A generalization of the symmetry reduction method to the case of partially-invariant solutions (PISs) has been formulated. We present a new algorithm for constructing PISs and discuss in detail the necessary conditions for the existence of non-reducible PISs. All these solutions have the defect structure 0305-4470/29/8/019/img1 and are computed from four-dimensional symmetric subalgebras. These theoretical considerations are illustrated by several examples. Finally, some new classes of invariant solutions obtained by the symmetry reduction method are included. These solutions represent central, conical, rational, spherical, cylindrical and non-scattering double waves.

Probability density functions for CP-violating rephasing invariants

NASA Astrophysics Data System (ADS)

Fortin, Jean-François; Giasson, Nicolas; Marleau, Luc

2018-05-01

The implications of the anarchy principle on CP violation in the lepton sector are investigated. A systematic method is introduced to compute the probability density functions for the CP-violating rephasing invariants of the PMNS matrix from the Haar measure relevant to the anarchy principle. Contrary to the CKM matrix which is hierarchical, it is shown that the Haar measure, and hence the anarchy principle, are very likely to lead to the observed PMNS matrix. Predictions on the CP-violating Dirac rephasing invariant |jD | and Majorana rephasing invariant |j1 | are also obtained. They correspond to 〈 |jD | 〉 Haar = π / 105 ≈ 0.030 and 〈 |j1 | 〉 Haar = 1 / (6 π) ≈ 0.053 respectively, in agreement with the experimental hint from T2K of | jDexp | ≈ 0.032 ± 0.005 (or ≈ 0.033 ± 0.003) for the normal (or inverted) hierarchy.

Energy functions for regularization algorithms

NASA Technical Reports Server (NTRS)

Delingette, H.; Hebert, M.; Ikeuchi, K.

1991-01-01

Regularization techniques are widely used for inverse problem solving in computer vision such as surface reconstruction, edge detection, or optical flow estimation. Energy functions used for regularization algorithms measure how smooth a curve or surface is, and to render acceptable solutions these energies must verify certain properties such as invariance with Euclidean transformations or invariance with parameterization. The notion of smoothness energy is extended here to the notion of a differential stabilizer, and it is shown that to void the systematic underestimation of undercurvature for planar curve fitting, it is necessary that circles be the curves of maximum smoothness. A set of stabilizers is proposed that meet this condition as well as invariance with rotation and parameterization.

Automated nystagmus analysis. [on-line computer technique for eye data processing

NASA Technical Reports Server (NTRS)

Oman, C. M.; Allum, J. H. J.; Tole, J. R.; Young, L. R.

1973-01-01

Several methods have recently been used for on-line analysis of nystagmus: A digital computer program has been developed to accept sampled records of eye position, detect fast phase components, and output cumulative slow phase position, continuous slow phase velocity, instantaneous fast phase frequency, and other parameters. The slow phase velocity is obtained by differentiation of the calculated cumulative position rather than the original eye movement record. Also, a prototype analog device has been devised which calculates the velocity of the slow phase component during caloric testing. Examples of clinical and research eye movement records analyzed with these devices are shown.

Comparison of sampling techniques for Bayesian parameter estimation

NASA Astrophysics Data System (ADS)

Allison, Rupert; Dunkley, Joanna

2014-02-01

The posterior probability distribution for a set of model parameters encodes all that the data have to tell us in the context of a given model; it is the fundamental quantity for Bayesian parameter estimation. In order to infer the posterior probability distribution we have to decide how to explore parameter space. Here we compare three prescriptions for how parameter space is navigated, discussing their relative merits. We consider Metropolis-Hasting sampling, nested sampling and affine-invariant ensemble Markov chain Monte Carlo (MCMC) sampling. We focus on their performance on toy-model Gaussian likelihoods and on a real-world cosmological data set. We outline the sampling algorithms themselves and elaborate on performance diagnostics such as convergence time, scope for parallelization, dimensional scaling, requisite tunings and suitability for non-Gaussian distributions. We find that nested sampling delivers high-fidelity estimates for posterior statistics at low computational cost, and should be adopted in favour of Metropolis-Hastings in many cases. Affine-invariant MCMC is competitive when computing clusters can be utilized for massive parallelization. Affine-invariant MCMC and existing extensions to nested sampling naturally probe multimodal and curving distributions.

Spectral resolution of SU(3)-invariant solutions of the Yang-Baxter equation

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

Alishauskas, S.I.; Kulish, P.P.

1986-11-20

The spectral resolution of invariant R-matrices is computed on the basis of solution of the defining equation. Multiple representations in the Clebsch-Gordon series are considered by means of the classifying operator A: a linear combination of known operators of third and fourth degrees in the group generators. The matrix elements of A in a nonorthonormal basis are found. Explicit expressions are presented for the spectral resolutions for a number of representations.

Spectral resolution of SU(3)-invariant solutions of the Yang-Baxter equation

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

Alishavskas, S.I.; Kulish, P.P.

1986-11-01

The spectral resolution of invariant R-matrices is computed on the basis of solution of the defining equation. Multiple representations in the Clebsch-Gordon series are considered by means of the classifying operator A: a linear combination of known operators of third and fourth degrees in the group generators. The matrix elements of A in a nonorthonormal basis are found. Explicit expressions are presented for the spectral resolutions for a number of representations.

Extended observability of linear time-invariant systems under recurrent loss of output data

NASA Technical Reports Server (NTRS)

Luck, Rogelio; Ray, Asok; Halevi, Yoram

1989-01-01

Recurrent loss of sensor data in integrated control systems of an advanced aircraft may occur under different operating conditions that include detected frame errors and queue saturation in computer networks, and bad data suppression in signal processing. This paper presents an extension of the concept of observability based on a set of randomly selected nonconsecutive outputs in finite-dimensional, linear, time-invariant systems. Conditions for testing extended observability have been established.

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

Gubser, Steven S.; van der Schee, Wilke

At strong coupling holographic studies have shown that heavy ion collisions do not obey normal boost invariance. Here we study a modified boost invariance through a complex shift in time, and show that this leads to surprisingly good agreement with numerical holographic computations. When including perturbations the agreement becomes even better, both in the hydrodynamic and the far-from-equilibrium regime. Finally, one of the main advantages is an analytic formulation of the stress-energy tensor of the longitudinal dynamics of holographic heavy ion collisions.

Invariant Theory for Dispersed Transverse Isotropy: An Efficient Means for Modeling Fiber Splay

NASA Technical Reports Server (NTRS)

Freed, alan D.; Einstein, Daniel R.; Vesely, Ivan

2004-01-01

Most soft tissues possess an oriented architecture of collagen fiber bundles, conferring both anisotropy and nonlinearity to their elastic behavior. Transverse isotropy has often been assumed for a subset of these tissues that have a single macroscopically-identifiable preferred fiber direction. Micro-structural studies, however, suggest that, in some tissues, collagen fibers are approximately normally distributed about a mean preferred fiber direction. Structural constitutive equations that account for this dispersion of fibers have been shown to capture the mechanical complexity of these tissues quite well. Such descriptions, however, are computationally cumbersome for two-dimensional (2D) fiber distributions, let alone for fully three-dimensional (3D) fiber populations. In this paper, we develop a new constitutive law for such tissues, based on a novel invariant theory for dispersed transverse isotropy. The invariant theory is based on a novel closed-form splay invariant that can easily handle 3D fiber populations, and that only requires a single parameter in the 2D case. The model is polyconvex and fits biaxial data for aortic valve tissue as accurately as the standard structural model. Modification of the fiber stress-strain law requires no re-formulation of the constitutive tangent matrix, making the model flexible for different types of soft tissues. Most importantly, the model is computationally expedient in a finite-element analysis.

A Quantum Simulation on the Emergence of Lorentz Invariance

NASA Astrophysics Data System (ADS)

Zueco, David; Quijandría, Fernando; Blas, Diego; Pujòlas, Oriol

2014-03-01

Lorentz invariance (LI) is one of the best tested symmetries of Nature. It is natural to think that LI is a fundamental property. However, this does not need to be so. In fact, it could be an emergent symmetry in the low energy world. One motivation on Lorentz-violating theories may come from consistent non-relativistic models of gravity, where LI appears at low energies. The basic approach is by taking two interacting quantum fields. The bare (uncoupled fields) have different light velocities, say v1 and v2. The coupling tends to ``synchronize'' those velocities providing a common light velocity: the LI emergence. So far, only perturbative calculations are available. In this perturbative regime the emergence of LI is too slow. Therefore it is mandatory going beyond perturbative calculations. In this talk I will discuss that such models for emergent Lorentz Invariance can be simulated in an analog quantum simulator. In 1+1 dimensions two transmission lines coupled trough Josephson Junctions do the job. We show that the emergence can be checked by measuring photon correlations. Everything within the state of the art in circuit QED. We show that our proposal can provide a definite answer about the LI emergence hypothesis in the strong coupling regime.

MPL-A program for computations with iterated integrals on moduli spaces of curves of genus zero

NASA Astrophysics Data System (ADS)

Bogner, Christian

2016-06-01

We introduce the Maple program MPL for computations with multiple polylogarithms. The program is based on homotopy invariant iterated integrals on moduli spaces M0,n of curves of genus 0 with n ordered marked points. It includes the symbol map and procedures for the analytic computation of period integrals on M0,n. It supports the automated computation of a certain class of Feynman integrals.

n-SIFT: n-dimensional scale invariant feature transform.

PubMed

Cheung, Warren; Hamarneh, Ghassan

2009-09-01

We propose the n-dimensional scale invariant feature transform (n-SIFT) method for extracting and matching salient features from scalar images of arbitrary dimensionality, and compare this method's performance to other related features. The proposed features extend the concepts used for 2-D scalar images in the computer vision SIFT technique for extracting and matching distinctive scale invariant features. We apply the features to images of arbitrary dimensionality through the use of hyperspherical coordinates for gradients and multidimensional histograms to create the feature vectors. We analyze the performance of a fully automated multimodal medical image matching technique based on these features, and successfully apply the technique to determine accurate feature point correspondence between pairs of 3-D MRI images and dynamic 3D + time CT data.

Primary decomposition of zero-dimensional ideals over finite fields

NASA Astrophysics Data System (ADS)

Gao, Shuhong; Wan, Daqing; Wang, Mingsheng

2009-03-01

A new algorithm is presented for computing primary decomposition of zero-dimensional ideals over finite fields. Like Berlekamp's algorithm for univariate polynomials, the new method is based on the invariant subspace of the Frobenius map acting on the quotient algebra. The dimension of the invariant subspace equals the number of primary components, and a basis of the invariant subspace yields a complete decomposition. Unlike previous approaches for decomposing multivariate polynomial systems, the new method does not need primality testing nor any generic projection, instead it reduces the general decomposition problem directly to root finding of univariate polynomials over the ground field. Also, it is shown how Groebner basis structure can be used to get partial primary decomposition without any root finding.

A fast invariant imbedding method for multiple scattering calculations and an application to equivalent widths of CO2 lines on Venus

NASA Technical Reports Server (NTRS)

Sato, M.; Kawabata, K.; Hansen, J. E.

1977-01-01

The invariant imbedding method considered is based on an equation which describes the change in the reflected radiation when an optically thin layer is added to the top of the atmosphere. The equation is used to treat the problem of reflection from a planetary atmosphere as an initial value problem. A fast method is discussed for the solution of the invariant imbedding equation. The speed and accuracy of the new method are illustrated by comparing it with the doubling program published by Hansen and Travis (1974). Computations are performed of the equivalent widths of carbon dioxide absorption lines in solar radiation reflected by Venus for several models of the planetary atmosphere.

Large-Scale Corrections to the CMB Anisotropy from Asymptotic de Sitter Mode

NASA Astrophysics Data System (ADS)

Sojasi, A.

2018-01-01

In this study, large-scale effects from asymptotic de Sitter mode on the CMB anisotropy are investigated. Besides the slow variation of the Hubble parameter onset of the last stage of inflation, the recent observational constraints from Planck and WMAP on spectral index confirm that the geometry of the universe can not be pure de Sitter in this era. Motivated by these evidences, we use this mode to calculate the power spectrum of the CMB anisotropy on the large scale. It is found that the CMB spectrum is dependent on the index of Hankel function ν which in the de Sitter limit ν → 3/2, the power spectrum reduces to the scale invariant result. Also, the result shows that the spectrum of anisotropy is dependent on angular scale and slow-roll parameter and these additional corrections are swept away by a cutoff scale parameter H ≪ M ∗ < M P .

Berry phase of primordial scalar and tensor perturbations in single-field inflationary models

NASA Astrophysics Data System (ADS)

Balajany, Hamideh; Mehrafarin, Mohammad

2018-06-01

In the framework of the single-field slow-roll inflation, we derive the Hamiltonian of the linear primordial scalar and tensor perturbations in the form of time-dependent harmonic oscillator Hamiltonians. We find the invariant operators of the resulting Hamiltonians and use their eigenstates to calculate the adiabatic Berry phase for sub-horizon modes in terms of the Lewis-Riesenfeld phase. We conclude by discussing the discrepancy in the results of Pal et al. (2013) [21] for these Berry phases, which is resolved to yield agreement with our results.

Limited Memory Block Krylov Subspace Optimization for Computing Dominant Singular Value Decompositions

DTIC Science & Technology

2012-03-22

with performance profiles, Math. Program., 91 (2002), pp. 201–213. [6] P. DRINEAS, R. KANNAN, AND M. W. MAHONEY , Fast Monte Carlo algorithms for matrices...computing invariant subspaces of non-Hermitian matri- ces, Numer. Math., 25 ( 1975 /76), pp. 123–136. [25] , Matrix algorithms Vol. II: Eigensystems

Computing with scale-invariant neural representations

NASA Astrophysics Data System (ADS)

Howard, Marc; Shankar, Karthik

The Weber-Fechner law is perhaps the oldest quantitative relationship in psychology. Consider the problem of the brain representing a function f (x) . Different neurons have receptive fields that support different parts of the range, such that the ith neuron has a receptive field at xi. Weber-Fechner scaling refers to the finding that the width of the receptive field scales with xi as does the difference between the centers of adjacent receptive fields. Weber-Fechner scaling is exponentially resource-conserving. Neurophysiological evidence suggests that neural representations obey Weber-Fechner scaling in the visual system and perhaps other systems as well. We describe an optimality constraint that is solved by Weber-Fechner scaling, providing an information-theoretic rationale for this principle of neural coding. Weber-Fechner scaling can be generated within a mathematical framework using the Laplace transform. Within this framework, simple computations such as translation, correlation and cross-correlation can be accomplished. This framework can in principle be extended to provide a general computational language for brain-inspired cognitive computation on scale-invariant representations. Supported by NSF PHY 1444389 and the BU Initiative for the Physics and Mathematics of Neural Systems,.

A projected preconditioned conjugate gradient algorithm for computing many extreme eigenpairs of a Hermitian matrix [A projected preconditioned conjugate gradient algorithm for computing a large eigenspace of a Hermitian matrix

DOE PAGES

Vecharynski, Eugene; Yang, Chao; Pask, John E.

2015-02-25

Here, we present an iterative algorithm for computing an invariant subspace associated with the algebraically smallest eigenvalues of a large sparse or structured Hermitian matrix A. We are interested in the case in which the dimension of the invariant subspace is large (e.g., over several hundreds or thousands) even though it may still be small relative to the dimension of A. These problems arise from, for example, density functional theory (DFT) based electronic structure calculations for complex materials. The key feature of our algorithm is that it performs fewer Rayleigh–Ritz calculations compared to existing algorithms such as the locally optimalmore » block preconditioned conjugate gradient or the Davidson algorithm. It is a block algorithm, and hence can take advantage of efficient BLAS3 operations and be implemented with multiple levels of concurrency. We discuss a number of practical issues that must be addressed in order to implement the algorithm efficiently on a high performance computer.« less

Stochastic Stability of Sampled Data Systems with a Jump Linear Controller

NASA Technical Reports Server (NTRS)

Gonzalez, Oscar R.; Herencia-Zapana, Heber; Gray, W. Steven

2004-01-01

In this paper an equivalence between the stochastic stability of a sampled-data system and its associated discrete-time representation is established. The sampled-data system consists of a deterministic, linear, time-invariant, continuous-time plant and a stochastic, linear, time-invariant, discrete-time, jump linear controller. The jump linear controller models computer systems and communication networks that are subject to stochastic upsets or disruptions. This sampled-data model has been used in the analysis and design of fault-tolerant systems and computer-control systems with random communication delays without taking into account the inter-sample response. This paper shows that the known equivalence between the stability of a deterministic sampled-data system and the associated discrete-time representation holds even in a stochastic framework.

4Pi microscopy deconvolution with a variable point-spread function.

PubMed

Baddeley, David; Carl, Christian; Cremer, Christoph

2006-09-20

To remove the axial sidelobes from 4Pi images, deconvolution forms an integral part of 4Pi microscopy. As a result of its high axial resolution, the 4Pi point spread function (PSF) is particularly susceptible to imperfect optical conditions within the sample. This is typically observed as a shift in the position of the maxima under the PSF envelope. A significantly varying phase shift renders deconvolution procedures based on a spatially invariant PSF essentially useless. We present a technique for computing the forward transformation in the case of a varying phase at a computational expense of the same order of magnitude as that of the shift invariant case, a method for the estimation of PSF phase from an acquired image, and a deconvolution procedure built on these techniques.

Real-space mapping of topological invariants using artificial neural networks

NASA Astrophysics Data System (ADS)

Carvalho, D.; García-Martínez, N. A.; Lado, J. L.; Fernández-Rossier, J.

2018-03-01

Topological invariants allow one to characterize Hamiltonians, predicting the existence of topologically protected in-gap modes. Those invariants can be computed by tracing the evolution of the occupied wave functions under twisted boundary conditions. However, those procedures do not allow one to calculate a topological invariant by evaluating the system locally, and thus require information about the wave functions in the whole system. Here we show that artificial neural networks can be trained to identify the topological order by evaluating a local projection of the density matrix. We demonstrate this for two different models, a one-dimensional topological superconductor and a two-dimensional quantum anomalous Hall state, both with spatially modulated parameters. Our neural network correctly identifies the different topological domains in real space, predicting the location of in-gap states. By combining a neural network with a calculation of the electronic states that uses the kernel polynomial method, we show that the local evaluation of the invariant can be carried out by evaluating a local quantity, in particular for systems without translational symmetry consisting of tens of thousands of atoms. Our results show that supervised learning is an efficient methodology to characterize the local topology of a system.

Stochastic local operations and classical communication (SLOCC) and local unitary operations (LU) classifications of n qubits via ranks and singular values of the spin-flipping matrices

NASA Astrophysics Data System (ADS)

Li, Dafa

2018-06-01

We construct ℓ -spin-flipping matrices from the coefficient matrices of pure states of n qubits and show that the ℓ -spin-flipping matrices are congruent and unitary congruent whenever two pure states of n qubits are SLOCC and LU equivalent, respectively. The congruence implies the invariance of ranks of the ℓ -spin-flipping matrices under SLOCC and then permits a reduction of SLOCC classification of n qubits to calculation of ranks of the ℓ -spin-flipping matrices. The unitary congruence implies the invariance of singular values of the ℓ -spin-flipping matrices under LU and then permits a reduction of LU classification of n qubits to calculation of singular values of the ℓ -spin-flipping matrices. Furthermore, we show that the invariance of singular values of the ℓ -spin-flipping matrices Ω 1^{(n)} implies the invariance of the concurrence for even n qubits and the invariance of the n-tangle for odd n qubits. Thus, the concurrence and the n-tangle can be used for LU classification and computing the concurrence and the n-tangle only performs additions and multiplications of coefficients of states.

A theory of frequency domain invariants: spherical harmonic identities for BRDF/lighting transfer and image consistency.

PubMed

Mahajan, Dhruv; Ramamoorthi, Ravi; Curless, Brian

2008-02-01

This paper develops a theory of frequency domain invariants in computer vision. We derive novel identities using spherical harmonics, which are the angular frequency domain analog to common spatial domain invariants such as reflectance ratios. These invariants are derived from the spherical harmonic convolution framework for reflection from a curved surface. Our identities apply in a number of canonical cases, including single and multiple images of objects under the same and different lighting conditions. One important case we consider is two different glossy objects in two different lighting environments. For this case, we derive a novel identity, independent of the specific lighting configurations or BRDFs, that allows us to directly estimate the fourth image if the other three are available. The identity can also be used as an invariant to detecttampering in the images. While this paper is primarily theoretical, it has the potential to lay the mathematical foundations for two important practical applications. First, we can develop more general algorithms for inverse rendering problems, which can directly relight and change material properties by transferring the BRDF or lighting from another object or illumination. Second, we can check the consistency of an image, to detect tampering or image splicing.

On Functional Module Detection in Metabolic Networks

PubMed Central

Koch, Ina; Ackermann, Jörg

2013-01-01

Functional modules of metabolic networks are essential for understanding the metabolism of an organism as a whole. With the vast amount of experimental data and the construction of complex and large-scale, often genome-wide, models, the computer-aided identification of functional modules becomes more and more important. Since steady states play a key role in biology, many methods have been developed in that context, for example, elementary flux modes, extreme pathways, transition invariants and place invariants. Metabolic networks can be studied also from the point of view of graph theory, and algorithms for graph decomposition have been applied for the identification of functional modules. A prominent and currently intensively discussed field of methods in graph theory addresses the Q-modularity. In this paper, we recall known concepts of module detection based on the steady-state assumption, focusing on transition-invariants (elementary modes) and their computation as minimal solutions of systems of Diophantine equations. We present the Fourier-Motzkin algorithm in detail. Afterwards, we introduce the Q-modularity as an example for a useful non-steady-state method and its application to metabolic networks. To illustrate and discuss the concepts of invariants and Q-modularity, we apply a part of the central carbon metabolism in potato tubers (Solanum tuberosum) as running example. The intention of the paper is to give a compact presentation of known steady-state concepts from a graph-theoretical viewpoint in the context of network decomposition and reduction and to introduce the application of Q-modularity to metabolic Petri net models. PMID:24958145

Gravity dual for a model of perception

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

Nakayama, Yu, E-mail: nakayama@berkeley.edu

2011-01-15

One of the salient features of human perception is its invariance under dilatation in addition to the Euclidean group, but its non-invariance under special conformal transformation. We investigate a holographic approach to the information processing in image discrimination with this feature. We claim that a strongly coupled analogue of the statistical model proposed by Bialek and Zee can be holographically realized in scale invariant but non-conformal Euclidean geometries. We identify the Bayesian probability distribution of our generalized Bialek-Zee model with the GKPW partition function of the dual gravitational system. We provide a concrete example of the geometric configuration based onmore » a vector condensation model coupled with the Euclidean Einstein-Hilbert action. From the proposed geometry, we study sample correlation functions to compute the Bayesian probability distribution.« less

Adiabatic invariance with first integrals of motion

NASA Astrophysics Data System (ADS)

Adib, Artur B.

2002-10-01

The construction of a microthermodynamic formalism for isolated systems based on the concept of adiabatic invariance is an old but seldom appreciated effort in the literature, dating back at least to P. Hertz [Ann. Phys. (Leipzig) 33, 225 (1910)]. An apparently independent extension of such formalism for systems bearing additional first integrals of motion was recently proposed by Hans H. Rugh [Phys. Rev. E 64, 055101 (2001)], establishing the concept of adiabatic invariance even in such singular cases. After some remarks in connection with the formalism pioneered by Hertz, it will be suggested that such an extension can incidentally explain the success of a dynamical method for computing the entropy of classical interacting fluids, at least in some potential applications where the presence of additional first integrals cannot be ignored.

A three-layer model of natural image statistics.

PubMed

Gutmann, Michael U; Hyvärinen, Aapo

2013-11-01

An important property of visual systems is to be simultaneously both selective to specific patterns found in the sensory input and invariant to possible variations. Selectivity and invariance (tolerance) are opposing requirements. It has been suggested that they could be joined by iterating a sequence of elementary selectivity and tolerance computations. It is, however, unknown what should be selected or tolerated at each level of the hierarchy. We approach this issue by learning the computations from natural images. We propose and estimate a probabilistic model of natural images that consists of three processing layers. Two natural image data sets are considered: image patches, and complete visual scenes downsampled to the size of small patches. For both data sets, we find that in the first two layers, simple and complex cell-like computations are performed. In the third layer, we mainly find selectivity to longer contours; for patch data, we further find some selectivity to texture, while for the downsampled complete scenes, some selectivity to curvature is observed. Copyright © 2013 Elsevier Ltd. All rights reserved.

Comparative analysis of feature extraction methods in satellite imagery

NASA Astrophysics Data System (ADS)

Karim, Shahid; Zhang, Ye; Asif, Muhammad Rizwan; Ali, Saad

2017-10-01

Feature extraction techniques are extensively being used in satellite imagery and getting impressive attention for remote sensing applications. The state-of-the-art feature extraction methods are appropriate according to the categories and structures of the objects to be detected. Based on distinctive computations of each feature extraction method, different types of images are selected to evaluate the performance of the methods, such as binary robust invariant scalable keypoints (BRISK), scale-invariant feature transform, speeded-up robust features (SURF), features from accelerated segment test (FAST), histogram of oriented gradients, and local binary patterns. Total computational time is calculated to evaluate the speed of each feature extraction method. The extracted features are counted under shadow regions and preprocessed shadow regions to compare the functioning of each method. We have studied the combination of SURF with FAST and BRISK individually and found very promising results with an increased number of features and less computational time. Finally, feature matching is conferred for all methods.

Time reversal invariance for a nonlinear scatterer exhibiting contact acoustic nonlinearity

NASA Astrophysics Data System (ADS)

Blanloeuil, Philippe; Rose, L. R. Francis; Veidt, Martin; Wang, Chun H.

2018-03-01

The time reversal invariance of an ultrasonic plane wave interacting with a contact interface characterized by a unilateral contact law is investigated analytically and numerically. It is shown analytically that despite the contact nonlinearity, the re-emission of a time reversed version of the reflected and transmitted waves can perfectly recover the original pulse shape, thereby demonstrating time reversal invariance for this type of contact acoustic nonlinearity. With the aid of finite element modelling, the time-reversal analysis is extended to finite-size nonlinear scatterers such as closed cracks. The results show that time reversal invariance holds provided that all the additional frequencies generated during the forward propagation, such as higher harmonics, sub-harmonics and zero-frequency component, are fully included in the retro-propagation. If the scattered waves are frequency filtered during receiving or transmitting, such as through the use of narrowband transducers, the recombination of the time-reversed waves will not exactly recover the original incident wave. This discrepancy due to incomplete time invariance can be exploited as a new method for characterizing damage by defining damage indices that quantify the departure from time reversal invariance. The sensitivity of these damage indices for various crack lengths and contact stress levels is investigated computationally, indicating some advantages of this narrowband approach relative to the more conventional measurement of higher harmonic amplitude, which requires broadband transducers.

The Kolmogorov-Obukhov Statistical Theory of Turbulence

NASA Astrophysics Data System (ADS)

Birnir, Björn

2013-08-01

In 1941 Kolmogorov and Obukhov postulated the existence of a statistical theory of turbulence, which allows the computation of statistical quantities that can be simulated and measured in a turbulent system. These are quantities such as the moments, the structure functions and the probability density functions (PDFs) of the turbulent velocity field. In this paper we will outline how to construct this statistical theory from the stochastic Navier-Stokes equation. The additive noise in the stochastic Navier-Stokes equation is generic noise given by the central limit theorem and the large deviation principle. The multiplicative noise consists of jumps multiplying the velocity, modeling jumps in the velocity gradient. We first estimate the structure functions of turbulence and establish the Kolmogorov-Obukhov 1962 scaling hypothesis with the She-Leveque intermittency corrections. Then we compute the invariant measure of turbulence, writing the stochastic Navier-Stokes equation as an infinite-dimensional Ito process, and solving the linear Kolmogorov-Hopf functional differential equation for the invariant measure. Finally we project the invariant measure onto the PDF. The PDFs turn out to be the normalized inverse Gaussian (NIG) distributions of Barndorff-Nilsen, and compare well with PDFs from simulations and experiments.

Investigating Gender and Racial/Ethnic Invariance in Use of a Course Management System in Higher Education

ERIC Educational Resources Information Center

Li, Yi; Wang, Qiu; Campbell, John

2015-01-01

This study focused on learning equity in colleges and universities where teaching and learning depends heavily on computer technologies. The study used the Structural Equation Modeling (SEM) to investigate gender and racial/ethnic heterogeneity in the use of a computer based course management system (CMS). Two latent variables (CMS usage and…

An algorithm for control system design via parameter optimization. M.S. Thesis

NASA Technical Reports Server (NTRS)

Sinha, P. K.

1972-01-01

An algorithm for design via parameter optimization has been developed for linear-time-invariant control systems based on the model reference adaptive control concept. A cost functional is defined to evaluate the system response relative to nominal, which involves in general the error between the system and nominal response, its derivatives and the control signals. A program for the practical implementation of this algorithm has been developed, with the computational scheme for the evaluation of the performance index based on Lyapunov's theorem for stability of linear invariant systems.

Killings, duality and characteristic polynomials

NASA Astrophysics Data System (ADS)

Álvarez, Enrique; Borlaf, Javier; León, José H.

1998-03-01

In this paper the complete geometrical setting of (lowest order) abelian T-duality is explored with the help of some new geometrical tools (the reduced formalism). In particular, all invariant polynomials (the integrands of the characteristic classes) can be explicitly computed for the dual model in terms of quantities pertaining to the original one and with the help of the canonical connection whose intrinsic characterization is given. Using our formalism the physically, and T-duality invariant, relevant result that top forms are zero when there is an isometry without fixed points is easily proved. © 1998

Moment-based approaches in imaging part 2: invariance

PubMed Central

Shu, Huazhong; Luo, Limin; Coatrieux, Jean-Louis

2005-01-01

The several moment families have been reviewed in a first paper [1]. A classification was proposed in order to get a better understanding of their relations. More attention was given to orthogonal moments (in particular Legendre, Zernike, Tchebichef, Krawtchouk, Racah, dual Hahn). Important properties for computer vision applications were just sketched, among which invariance and robustness to noise. These properties may drive the choice of moments when addressing a specific problem. A short, thus non-exhaustive, review of the literature on these issues is proposed in this second paper. PMID:18270055

Lorentz symmetry violation in the fermion number anomaly with the chiral overlap operator

NASA Astrophysics Data System (ADS)

Makino, Hiroki; Morikawa, Okuto

2016-12-01

Recently, Grabowska and Kaplan proposed a four-dimensional lattice formulation of chiral gauge theories on the basis of a chiral overlap operator. We compute the classical continuum limit of the fermion number anomaly in this formulation. Unexpectedly, we find that the continuum limit contains a term which is not Lorentz invariant. The term is, however, proportional to the gauge anomaly coefficient, and thus the fermion number anomaly in this lattice formulation automatically restores the Lorentz-invariant form when and only when the anomaly cancellation condition is met.

Transformer Industry Productivity Slows.

ERIC Educational Resources Information Center

Otto, Phyllis Flohr

1981-01-01

Annual productivity increases averaged 2.4 percent during 1963-79, slowing since 1972 to 1.5 percent; computer-assisted design and product standardization aided growth in output per employee-hour. (Author)

3D Data Acquisition Platform for Human Activity Understanding

DTIC Science & Technology

2016-03-02

address fundamental research problems of representation and invariant description of3D data, human motion modeling and applications of human activity analysis, and computational optimization of large-scale 3D data.

3D Data Acquisition Platform for Human Activity Understanding

DTIC Science & Technology

2016-03-02

address fundamental research problems of representation and invariant description of 3D data, human motion modeling and applications of human activity analysis, and computational optimization of large-scale 3D data.

Rapid Global Fitting of Large Fluorescence Lifetime Imaging Microscopy Datasets

PubMed Central

Warren, Sean C.; Margineanu, Anca; Alibhai, Dominic; Kelly, Douglas J.; Talbot, Clifford; Alexandrov, Yuriy; Munro, Ian; Katan, Matilda

2013-01-01

Fluorescence lifetime imaging (FLIM) is widely applied to obtain quantitative information from fluorescence signals, particularly using Förster Resonant Energy Transfer (FRET) measurements to map, for example, protein-protein interactions. Extracting FRET efficiencies or population fractions typically entails fitting data to complex fluorescence decay models but such experiments are frequently photon constrained, particularly for live cell or in vivo imaging, and this leads to unacceptable errors when analysing data on a pixel-wise basis. Lifetimes and population fractions may, however, be more robustly extracted using global analysis to simultaneously fit the fluorescence decay data of all pixels in an image or dataset to a multi-exponential model under the assumption that the lifetime components are invariant across the image (dataset). This approach is often considered to be prohibitively slow and/or computationally expensive but we present here a computationally efficient global analysis algorithm for the analysis of time-correlated single photon counting (TCSPC) or time-gated FLIM data based on variable projection. It makes efficient use of both computer processor and memory resources, requiring less than a minute to analyse time series and multiwell plate datasets with hundreds of FLIM images on standard personal computers. This lifetime analysis takes account of repetitive excitation, including fluorescence photons excited by earlier pulses contributing to the fit, and is able to accommodate time-varying backgrounds and instrument response functions. We demonstrate that this global approach allows us to readily fit time-resolved fluorescence data to complex models including a four-exponential model of a FRET system, for which the FRET efficiencies of the two species of a bi-exponential donor are linked, and polarisation-resolved lifetime data, where a fluorescence intensity and bi-exponential anisotropy decay model is applied to the analysis of live cell homo-FRET data. A software package implementing this algorithm, FLIMfit, is available under an open source licence through the Open Microscopy Environment. PMID:23940626

The Impact of Cortical Deafferentation on the Neocortical Slow Oscillation

PubMed Central

Lemieux, Maxime; Chen, Jen-Yung; Lonjers, Peter; Bazhenov, Maxim

2014-01-01

Slow oscillation is the main brain rhythm observed during deep sleep in mammals. Although several studies have demonstrated its neocortical origin, the extent of the thalamic contribution is still a matter of discussion. Using electrophysiological recordings in vivo on cats and computational modeling, we found that the local thalamic inactivation or the complete isolation of the neocortical slabs maintained within the brain dramatically reduced the expression of slow and fast oscillations in affected cortical areas. The slow oscillation began to recover 12 h after thalamic inactivation. The slow oscillation, but not faster activities, nearly recovered after 30 h and persisted for weeks in the isolated slabs. We also observed an increase of the membrane potential fluctuations recorded in vivo several hours after thalamic inactivation. Mimicking this enhancement in a network computational model with an increased postsynaptic activity of long-range intracortical afferents or scaling K+ leak current, but not several other Na+ and K+ intrinsic currents was sufficient for recovering the slow oscillation. We conclude that, in the intact brain, the thalamus contributes to the generation of cortical active states of the slow oscillation and mediates its large-scale synchronization. Our study also suggests that the deafferentation-induced alterations of the sleep slow oscillation can be counteracted by compensatory intracortical mechanisms and that the sleep slow oscillation is a fundamental and intrinsic state of the neocortex. PMID:24741059

Comparing the Psychometric Properties of Two Physical Activity Self-Efficacy Instruments in Urban, Adolescent Girls: Validity, Measurement Invariance, and Reliability

PubMed Central

Voskuil, Vicki R.; Pierce, Steven J.; Robbins, Lorraine B.

2017-01-01

Aims: This study compared the psychometric properties of two self-efficacy instruments related to physical activity. Factorial validity, cross-group and longitudinal invariance, and composite reliability were examined. Methods: Secondary analysis was conducted on data from a group randomized controlled trial investigating the effect of a 17-week intervention on increasing moderate to vigorous physical activity among 5th–8th grade girls (N = 1,012). Participants completed a 6-item Physical Activity Self-Efficacy Scale (PASE) and a 7-item Self-Efficacy for Exercise Behaviors Scale (SEEB) at baseline and post-intervention. Confirmatory factor analyses for intervention and control groups were conducted with Mplus Version 7.4 using robust weighted least squares estimation. Model fit was evaluated with the chi-square index, comparative fit index, and root mean square error of approximation. Composite reliability for latent factors with ordinal indicators was computed from Mplus output using SAS 9.3. Results: Mean age of the girls was 12.2 years (SD = 0.96). One-third of the girls were obese. Girls represented a diverse sample with over 50% indicating black race and an additional 19% identifying as mixed or other race. Both instruments demonstrated configural invariance for simultaneous analysis of cross-group and longitudinal invariance based on alternative fit indices. However, simultaneous metric invariance was not met for the PASE or the SEEB instruments. Partial metric invariance for the simultaneous analysis was achieved for the PASE with one factor loading identified as non-invariant. Partial metric invariance was not met for the SEEB. Longitudinal scalar invariance was achieved for both instruments in the control group but not the intervention group. Composite reliability for the PASE ranged from 0.772 to 0.842. Reliability for the SEEB ranged from 0.719 to 0.800 indicating higher reliability for the PASE. Reliability was more stable over time in the control group for both instruments. Conclusions: Results suggest that the intervention influenced how girls responded to indicator items. Neither of the instruments achieved simultaneous metric invariance making it difficult to assess mean differences in PA self-efficacy between groups. PMID:28824487

The ASACUSA Micromegas Tracker: A cylindrical, bulk Micromegas detector for antimatter research.

PubMed

Radics, B; Nagata, Y; Yamazaki, Y; Ishikawa, S; Kuroda, N; Matsuda, Y; Anfreville, M; Aune, S; Boyer, M; Chateau, F; Combet, M; Granelli, R; Legou, P; Mandjavidze, I; Procureur, S; Riallot, M; Vallage, B; Vandenbroucke, M

2015-08-01

The ASACUSA Micromegas Tracker (AMT; ASACUSA: Atomic Spectroscopy and Collisions Using Slow Antiprotons) was designed to be able to reconstruct antiproton-nucleon annihilation vertices in three dimensions. The goal of this device is to study antihydrogen formation processes in the ASACUSA cusp trap, which was designed to synthesise a spin-polarised antihydrogen beam for precise tests of Charge, Parity, and Time (CPT) symmetry invariance. This paper discusses the structure and technical details of an AMT detector built into such an environment, its data acquisition system and the first performance with cosmic rays.

The ASACUSA Micromegas Tracker: A cylindrical, bulk Micromegas detector for antimatter research

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

Radics, B., E-mail: balint.radics@riken.jp; Nagata, Y.; Yamazaki, Y.

2015-08-15

The ASACUSA Micromegas Tracker (AMT; ASACUSA: Atomic Spectroscopy and Collisions Using Slow Antiprotons) was designed to be able to reconstruct antiproton-nucleon annihilation vertices in three dimensions. The goal of this device is to study antihydrogen formation processes in the ASACUSA cusp trap, which was designed to synthesise a spin-polarised antihydrogen beam for precise tests of Charge, Parity, and Time (CPT) symmetry invariance. This paper discusses the structure and technical details of an AMT detector built into such an environment, its data acquisition system and the first performance with cosmic rays.

Limit Theorems for Dispersing Billiards with Cusps

NASA Astrophysics Data System (ADS)

Bálint, P.; Chernov, N.; Dolgopyat, D.

2011-12-01

Dispersing billiards with cusps are deterministic dynamical systems with a mild degree of chaos, exhibiting "intermittent" behavior that alternates between regular and chaotic patterns. Their statistical properties are therefore weak and delicate. They are characterized by a slow (power-law) decay of correlations, and as a result the classical central limit theorem fails. We prove that a non-classical central limit theorem holds, with a scaling factor of {sqrt{nlog n}} replacing the standard {sqrt{n}} . We also derive the respective Weak Invariance Principle, and we identify the class of observables for which the classical CLT still holds.

The shift-invariant discrete wavelet transform and application to speech waveform analysis.

PubMed

Enders, Jörg; Geng, Weihua; Li, Peijun; Frazier, Michael W; Scholl, David J

2005-04-01

The discrete wavelet transform may be used as a signal-processing tool for visualization and analysis of nonstationary, time-sampled waveforms. The highly desirable property of shift invariance can be obtained at the cost of a moderate increase in computational complexity, and accepting a least-squares inverse (pseudoinverse) in place of a true inverse. A new algorithm for the pseudoinverse of the shift-invariant transform that is easier to implement in array-oriented scripting languages than existing algorithms is presented together with self-contained proofs. Representing only one of the many and varied potential applications, a recorded speech waveform illustrates the benefits of shift invariance with pseudoinvertibility. Visualization shows the glottal modulation of vowel formants and frication noise, revealing secondary glottal pulses and other waveform irregularities. Additionally, performing sound waveform editing operations (i.e., cutting and pasting sections) on the shift-invariant wavelet representation automatically produces quiet, click-free section boundaries in the resulting sound. The capabilities of this wavelet-domain editing technique are demonstrated by changing the rate of a recorded spoken word. Individual pitch periods are repeated to obtain a half-speed result, and alternate individual pitch periods are removed to obtain a double-speed result. The original pitch and formant frequencies are preserved. In informal listening tests, the results are clear and understandable.

The shift-invariant discrete wavelet transform and application to speech waveform analysis

NASA Astrophysics Data System (ADS)

Enders, Jörg; Geng, Weihua; Li, Peijun; Frazier, Michael W.; Scholl, David J.

2005-04-01

The discrete wavelet transform may be used as a signal-processing tool for visualization and analysis of nonstationary, time-sampled waveforms. The highly desirable property of shift invariance can be obtained at the cost of a moderate increase in computational complexity, and accepting a least-squares inverse (pseudoinverse) in place of a true inverse. A new algorithm for the pseudoinverse of the shift-invariant transform that is easier to implement in array-oriented scripting languages than existing algorithms is presented together with self-contained proofs. Representing only one of the many and varied potential applications, a recorded speech waveform illustrates the benefits of shift invariance with pseudoinvertibility. Visualization shows the glottal modulation of vowel formants and frication noise, revealing secondary glottal pulses and other waveform irregularities. Additionally, performing sound waveform editing operations (i.e., cutting and pasting sections) on the shift-invariant wavelet representation automatically produces quiet, click-free section boundaries in the resulting sound. The capabilities of this wavelet-domain editing technique are demonstrated by changing the rate of a recorded spoken word. Individual pitch periods are repeated to obtain a half-speed result, and alternate individual pitch periods are removed to obtain a double-speed result. The original pitch and formant frequencies are preserved. In informal listening tests, the results are clear and understandable. .

On Facilitating the use of HARDI in population studies by creating Rotation-Invariant Markers

PubMed Central

Caruyer, Emmanuel; Verma, Ragini

2014-01-01

We design and evaluate a novel method to compute rotationally invariant features using High Angular Resolution Diffusion Imaging (HARDI) data. These measures quantify the complexity of the angular diffusion profile modeled using a higher order model, thereby giving more information than classical diffusion tensor-derived parameters. The method is based on the spherical harmonic (SH) representation of the angular diffusion information, and is generalizable to a range of HARDI reconstruction models. These scalars are obtained as homogeneous polynomials of the SH representation of a HARDI reconstruction model. We show that finding such polynomials is equivalent to solving a large linear system of equations, and present a numerical method based on sparse matrices to efficiently solve this system. Among the solutions, we only keep a subset of algebraically independent polynomials, using an algorithm based on a numerical implementation of the Jacobian criterion. We compute a set of 12 or 25 rotationally invariant measures representative of the underlying white matter for the rank-4 or rank-6 spherical harmonics (SH) representation of the apparent diffusion coefficient (ADC) profile, respectively. Synthetic data was used to investigate and quantify the difference in contrast. Real data acquired with multiple repetitions showed that within subject variation in the invariants was less than the difference across subjects - facilitating their use to study population differences. These results demonstrate that our measures are able to characterize white matter, especially complex white matter found in regions of fiber crossings and hence can be used to derive new biomarkers for HARDI and can be used for HARDI-based population analysis. PMID:25465846

The invariant cleavage pattern displayed by ascidian embryos depends on spindle positioning along the cell's longest axis in the apical plane and relies on asynchronous cell divisions

PubMed Central

Dumollard, Rémi; Minc, Nicolas; Salez, Gregory; Aicha, Sameh Ben; Bekkouche, Faisal; Hebras, Céline; Besnardeau, Lydia; McDougall, Alex

2017-01-01

The ascidian embryo is an ideal system to investigate how cell position is determined during embryogenesis. Using 3D timelapse imaging and computational methods we analyzed the planar cell divisions in ascidian early embryos and found that spindles in every cell tend to align at metaphase in the long length of the apical surface except in cells undergoing unequal cleavage. Furthermore, the invariant and conserved cleavage pattern of ascidian embryos was found to consist in alternate planar cell divisions between ectoderm and endomesoderm. In order to test the importance of alternate cell divisions we manipulated zygotic transcription induced by β-catenin or downregulated wee1 activity, both of which abolish this cell cycle asynchrony. Crucially, abolishing cell cycle asynchrony consistently disrupted the spindle orienting mechanism underpinning the invariant cleavage pattern. Our results demonstrate how an evolutionary conserved cell cycle asynchrony maintains the invariant cleavage pattern driving morphogenesis of the ascidian blastula. DOI: http://dx.doi.org/10.7554/eLife.19290.001 PMID:28121291

Accurate Cold-Test Model of Helical TWT Slow-Wave Circuits

NASA Technical Reports Server (NTRS)

Kory, Carol L.; Dayton, James A., Jr.

1997-01-01

Recently, a method has been established to accurately calculate cold-test data for helical slow-wave structures using the three-dimensional electromagnetic computer code, MAFIA. Cold-test parameters have been calculated for several helical traveling-wave tube (TWT) slow-wave circuits possessing various support rod configurations, and results are presented here showing excellent agreement with experiment. The helical models include tape thickness, dielectric support shapes and material properties consistent with the actual circuits. The cold-test data from this helical model can be used as input into large-signal helical TWT interaction codes making it possible, for the first time, to design a complete TWT via computer simulation.

Breaking cover: neural responses to slow and fast camouflage-breaking motion.

PubMed

Yin, Jiapeng; Gong, Hongliang; An, Xu; Chen, Zheyuan; Lu, Yiliang; Andolina, Ian M; McLoughlin, Niall; Wang, Wei

2015-08-22

Primates need to detect and recognize camouflaged animals in natural environments. Camouflage-breaking movements are often the only visual cue available to accomplish this. Specifically, sudden movements are often detected before full recognition of the camouflaged animal is made, suggesting that initial processing of motion precedes the recognition of motion-defined contours or shapes. What are the neuronal mechanisms underlying this initial processing of camouflaged motion in the primate visual brain? We investigated this question using intrinsic-signal optical imaging of macaque V1, V2 and V4, along with computer simulations of the neural population responses. We found that camouflaged motion at low speed was processed as a direction signal by both direction- and orientation-selective neurons, whereas at high-speed camouflaged motion was encoded as a motion-streak signal primarily by orientation-selective neurons. No population responses were found to be invariant to the camouflage contours. These results suggest that the initial processing of camouflaged motion at low and high speeds is encoded as direction and motion-streak signals in primate early visual cortices. These processes are consistent with a spatio-temporal filter mechanism that provides for fast processing of motion signals, prior to full recognition of camouflage-breaking animals. © 2015 The Authors.

Breaking cover: neural responses to slow and fast camouflage-breaking motion

PubMed Central

Yin, Jiapeng; Gong, Hongliang; An, Xu; Chen, Zheyuan; Lu, Yiliang; Andolina, Ian M.; McLoughlin, Niall; Wang, Wei

2015-01-01

Primates need to detect and recognize camouflaged animals in natural environments. Camouflage-breaking movements are often the only visual cue available to accomplish this. Specifically, sudden movements are often detected before full recognition of the camouflaged animal is made, suggesting that initial processing of motion precedes the recognition of motion-defined contours or shapes. What are the neuronal mechanisms underlying this initial processing of camouflaged motion in the primate visual brain? We investigated this question using intrinsic-signal optical imaging of macaque V1, V2 and V4, along with computer simulations of the neural population responses. We found that camouflaged motion at low speed was processed as a direction signal by both direction- and orientation-selective neurons, whereas at high-speed camouflaged motion was encoded as a motion-streak signal primarily by orientation-selective neurons. No population responses were found to be invariant to the camouflage contours. These results suggest that the initial processing of camouflaged motion at low and high speeds is encoded as direction and motion-streak signals in primate early visual cortices. These processes are consistent with a spatio-temporal filter mechanism that provides for fast processing of motion signals, prior to full recognition of camouflage-breaking animals. PMID:26269500

Computer Simulation of Microwave Devices

NASA Technical Reports Server (NTRS)

Kory, Carol L.

1997-01-01

The accurate simulation of cold-test results including dispersion, on-axis beam interaction impedance, and attenuation of a helix traveling-wave tube (TWT) slow-wave circuit using the three-dimensional code MAFIA (Maxwell's Equations Solved by the Finite Integration Algorithm) was demonstrated for the first time. Obtaining these results is a critical step in the design of TWT's. A well-established procedure to acquire these parameters is to actually build and test a model or a scale model of the circuit. However, this procedure is time-consuming and expensive, and it limits freedom to examine new variations to the basic circuit. These limitations make the need for computational methods crucial since they can lower costs, reduce tube development time, and lessen limitations on novel designs. Computer simulation has been used to accurately obtain cold-test parameters for several slow-wave circuits. Although the helix slow-wave circuit remains the mainstay of the TWT industry because of its exceptionally wide bandwidth, until recently it has been impossible to accurately analyze a helical TWT using its exact dimensions because of the complexity of its geometrical structure. A new computer modeling technique developed at the NASA Lewis Research Center overcomes these difficulties. The MAFIA three-dimensional mesh for a C-band helix slow-wave circuit is shown.

Synaptotagmin 7 confers frequency invariance onto specialized depressing synapses

NASA Astrophysics Data System (ADS)

Turecek, Josef; Jackman, Skyler L.; Regehr, Wade G.

2017-11-01

At most synapses in the brain, short-term plasticity dynamically modulates synaptic strength. Rapid frequency-dependent changes in synaptic strength have key roles in sensory adaptation, gain control and many other neural computations. However, some auditory, vestibular and cerebellar synapses maintain constant strength over a wide range of firing frequencies, and as a result efficiently encode firing rates. Despite its apparent simplicity, frequency-invariant transmission is difficult to achieve because of inherent synaptic nonlinearities. Here we study frequency-invariant transmission at synapses from Purkinje cells to deep cerebellar nuclei and at vestibular synapses in mice. Prolonged activation of these synapses leads to initial depression, which is followed by steady-state responses that are frequency invariant for their physiological activity range. We find that synaptotagmin 7 (Syt7), a calcium sensor for short-term facilitation, is present at both synapses. It was unclear why a sensor for facilitation would be present at these and other depressing synapses. We find that at Purkinje cell and vestibular synapses, Syt7 supports facilitation that is normally masked by depression, which can be revealed in wild-type mice but is absent in Syt7 knockout mice. In wild-type mice, facilitation increases with firing frequency and counteracts depression to produce frequency-invariant transmission. In Syt7-knockout mice, Purkinje cell and vestibular synapses exhibit conventional use-dependent depression, weakening to a greater extent as the firing frequency is increased. Presynaptic rescue of Syt7 expression restores both facilitation and frequency-invariant transmission. Our results identify a function for Syt7 at synapses that exhibit overall depression, and demonstrate that facilitation has an unexpected and important function in producing frequency-invariant transmission.

Qubit-qubit interaction in quantum computers: errors and scaling laws

NASA Astrophysics Data System (ADS)

Gea-Banacloche, Julio R.

1998-07-01

This paper explores the limitations that interaction between the physical qubits making up a quantum computer may impose on the computer's performance. For computers using atoms as qubits, magnetic dipole-dipole interactions are likely to be dominant; various types of errors which they might introduce are considered here. The strength of the interaction may be reduce by increasing the distance between qubits, which in general will make the computer slower. For ion-chain based quantum computers the slowing down due to this effect is found to be generally more sever than that due to other causes. In particular, this effect alone would be enough to make these systems unacceptably slow for large-scale computation, whether they use the center of mass motion as the 'bus' or whether they do this via an optical cavity mode.

Extending matchgates into universal quantum computation

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

Brod, Daniel J.; Galvao, Ernesto F.

2011-08-15

Matchgates are a family of two-qubit gates associated with noninteracting fermions. They are classically simulatable if acting only on nearest neighbors but become universal for quantum computation if we relax this restriction or use swap gates [Jozsa and Miyake, Proc. R. Soc. A 464, 3089 (2008)]. We generalize this result by proving that any nonmatchgate parity-preserving unitary is capable of extending the computational power of matchgates into universal quantum computation. We identify the single local invariant of parity-preserving unitaries responsible for this, and discuss related results in the context of fermionic systems.

Noniterative computation of infimum in H(infinity) optimisation for plants with invariant zeros on the j(omega)-axis

NASA Technical Reports Server (NTRS)

Chen, B. M.; Saber, A.

1993-01-01

A simple and noniterative procedure for the computation of the exact value of the infimum in the singular H(infinity)-optimization problem is presented, as a continuation of our earlier work. Our problem formulation is general and we do not place any restrictions in the finite and infinite zero structures of the system, and the direct feedthrough terms between the control input and the controlled output variables and between the disturbance input and the measurement output variables. Our method is applicable to a class of singular H(infinity)-optimization problems for which the transfer functions from the control input to the controlled output and from the disturbance input to the measurement output satisfy certain geometric conditions. In particular, the paper extends the result of earlier work by allowing these two transfer functions to have invariant zeros on the j(omega) axis.

Diagonal Born-Oppenheimer correction for coupled-cluster wave-functions

NASA Astrophysics Data System (ADS)

Shamasundar, K. R.

2018-06-01

We examine how geometry-dependent normalisation freedom of electronic wave-functions affects extraction of a meaningful diagonal Born-Oppenheimer correction (DBOC) to the ground-state Born-Oppenheimer potential energy surface (PES). By viewing this freedom as a kind of gauge-freedom, it is shown that DBOC and the resulting associated mass-dependent adiabatic PES are gauge-invariant quantities. A sum-over-states (SOS) formula for DBOC which explicitly exhibits this invariance is derived. A biorthogonal formulation suitable for DBOC computations using standard unnormalised coupled-cluster (CC) wave-functions is presented. This is shown to lead to a biorthogonal version of SOS formula with similar properties. On this basis, different computational schemes for evaluating DBOC using approximate CC wave-functions are derived. One of this agrees with the formula used in the current literature. The connection to adiabatic-to-diabatic transformations in non-adiabatic dynamics is explored and complications arising from biorthogonal nature of CC theory are identified.

Texture feature extraction based on a uniformity estimation method for local brightness and structure in chest CT images.

PubMed

Peng, Shao-Hu; Kim, Deok-Hwan; Lee, Seok-Lyong; Lim, Myung-Kwan

2010-01-01

Texture feature is one of most important feature analysis methods in the computer-aided diagnosis (CAD) systems for disease diagnosis. In this paper, we propose a Uniformity Estimation Method (UEM) for local brightness and structure to detect the pathological change in the chest CT images. Based on the characteristics of the chest CT images, we extract texture features by proposing an extension of rotation invariant LBP (ELBP(riu4)) and the gradient orientation difference so as to represent a uniform pattern of the brightness and structure in the image. The utilization of the ELBP(riu4) and the gradient orientation difference allows us to extract rotation invariant texture features in multiple directions. Beyond this, we propose to employ the integral image technique to speed up the texture feature computation of the spatial gray level dependent method (SGLDM). Copyright © 2010 Elsevier Ltd. All rights reserved.

Tachyon constant-roll inflation

NASA Astrophysics Data System (ADS)

Mohammadi, A.; Saaidi, Kh.; Golanbari, T.

2018-04-01

The constant-roll inflation is studied where the inflaton is taken as a tachyon field. Based on this approach, the second slow-roll parameter is taken as a constant which leads to a differential equation for the Hubble parameter. Finding an exact solution for the Hubble parameter is difficult and leads us to a numerical solution for the Hubble parameter. On the other hand, since in this formalism the slow-roll parameter η is constant and could not be assumed to be necessarily small, the perturbation parameters should be reconsidered again which, in turn, results in new terms appearing in the amplitude of scalar perturbations and the scalar spectral index. Utilizing the numerical solution for the Hubble parameter, we estimate the perturbation parameter at the horizon exit time and compare it with observational data. The results show that, for specific values of the constant parameter η , we could have an almost scale-invariant amplitude of scalar perturbations. Finally, the attractor behavior for the solution of the model is presented, and we determine that the feature could be properly satisfied.

Phenomenological constraints on A N in p ↑ p → π X from Lorentz invariance relations

DOE PAGES

Gamberg, Leonard; Kang, Zhong-Bo; Pitonyak, Daniel; ...

2017-04-27

Here, we present a new analysis of A N in p ↑ p → πX within the collinear twist-3 factorization formalism. We incorporate recently derived Lorentz invariance relations into our calculation and focus on input from the kinematical twist-3 functions, which are weighted integrals of transverse momentum dependent (TMD) functions. Particularly, we use the latest extractions of the Sivers and Collins functions with TMD evolution to compute certain terms in AN . Consequently, we are able to constrain the remaining contributions from the lesser known dynamical twist-3 correlators.

Stereo Correspondence Using Moment Invariants

NASA Astrophysics Data System (ADS)

Premaratne, Prashan; Safaei, Farzad

Autonomous navigation is seen as a vital tool in harnessing the enormous potential of Unmanned Aerial Vehicles (UAV) and small robotic vehicles for both military and civilian use. Even though, laser based scanning solutions for Simultaneous Location And Mapping (SLAM) is considered as the most reliable for depth estimation, they are not feasible for use in UAV and land-based small vehicles due to their physical size and weight. Stereovision is considered as the best approach for any autonomous navigation solution as stereo rigs are considered to be lightweight and inexpensive. However, stereoscopy which estimates the depth information through pairs of stereo images can still be computationally expensive and unreliable. This is mainly due to some of the algorithms used in successful stereovision solutions require high computational requirements that cannot be met by small robotic vehicles. In our research, we implement a feature-based stereovision solution using moment invariants as a metric to find corresponding regions in image pairs that will reduce the computational complexity and improve the accuracy of the disparity measures that will be significant for the use in UAVs and in small robotic vehicles.

Nonlinear dynamics as an engine of computation.

PubMed

Kia, Behnam; Lindner, John F; Ditto, William L

2017-03-06

Control of chaos teaches that control theory can tame the complex, random-like behaviour of chaotic systems. This alliance between control methods and physics-cybernetical physics-opens the door to many applications, including dynamics-based computing. In this article, we introduce nonlinear dynamics and its rich, sometimes chaotic behaviour as an engine of computation. We review our work that has demonstrated how to compute using nonlinear dynamics. Furthermore, we investigate the interrelationship between invariant measures of a dynamical system and its computing power to strengthen the bridge between physics and computation.This article is part of the themed issue 'Horizons of cybernetical physics'. © 2017 The Author(s).

Nonlinear dynamics as an engine of computation

PubMed Central

Lindner, John F.; Ditto, William L.

2017-01-01

Control of chaos teaches that control theory can tame the complex, random-like behaviour of chaotic systems. This alliance between control methods and physics—cybernetical physics—opens the door to many applications, including dynamics-based computing. In this article, we introduce nonlinear dynamics and its rich, sometimes chaotic behaviour as an engine of computation. We review our work that has demonstrated how to compute using nonlinear dynamics. Furthermore, we investigate the interrelationship between invariant measures of a dynamical system and its computing power to strengthen the bridge between physics and computation. This article is part of the themed issue ‘Horizons of cybernetical physics’. PMID:28115619

Detweiler's redshift invariant for spinning particles along circular orbits on a Schwarzschild background

NASA Astrophysics Data System (ADS)

Bini, Donato; Damour, Thibault; Geralico, Andrea; Kavanagh, Chris

2018-05-01

We study the metric perturbations induced by a classical spinning particle moving along a circular orbit on a Schwarzschild background, limiting the analysis to effects which are first order in spin. The particle is assumed to move on the equatorial plane and has its spin aligned with the z axis. The metric perturbations are obtained by using two different approaches, i.e., by working in two different gauges: the Regge-Wheeler gauge (using the Regge-Wheeler-Zerilli formalism) and a radiation gauge (using the Teukolsky formalism). We then compute the linear-in-spin contribution to the first-order self-force contribution to Detweiler's redshift invariant up to the 8.5 post-Newtonian order. We check that our result is the same in both gauges, as appropriate for a gauge-invariant quantity, and agrees with the currently known 3.5 post-Newtonian results.

Path-integral invariants in abelian Chern-Simons theory

NASA Astrophysics Data System (ADS)

Guadagnini, E.; Thuillier, F.

2014-05-01

We consider the U(1) Chern-Simons gauge theory defined in a general closed oriented 3-manifold M; the functional integration is used to compute the normalized partition function and the expectation values of the link holonomies. The non-perturbative path-integral is defined in the space of the gauge orbits of the connections which belong to the various inequivalent U(1) principal bundles over M; the different sectors of configuration space are labelled by the elements of the first homology group of M and are characterized by appropriate background connections. The gauge orbits of flat connections, whose classification is also based on the homology group, control the non-perturbative contributions to the mean values. The functional integration is carried out in any 3-manifold M, and the corresponding path-integral invariants turn out to be strictly related with the abelian Reshetikhin-Turaev surgery invariants.

Gauge-invariant variables and entanglement entropy

NASA Astrophysics Data System (ADS)

Agarwal, Abhishek; Karabali, Dimitra; Nair, V. P.

2017-12-01

The entanglement entropy (EE) of gauge theories in three spacetime dimensions is analyzed using manifestly gauge-invariant variables defined directly in the continuum. Specifically, we focus on the Maxwell, Maxwell-Chern-Simons (MCS), and non-Abelian Yang-Mills theories. Special attention is paid to the analysis of edge modes and their contribution to EE. The contact term is derived without invoking the replica method and its physical origin is traced to the phase space volume measure for the edge modes. The topological contribution to the EE for the MCS case is calculated. For all the Abelian cases, the EE presented in this paper agrees with known results in the literature. The EE for the non-Abelian theory is computed in a gauge-invariant Gaussian approximation, which incorporates the dynamically generated mass gap. A formulation of the contact term for the non-Abelian case is also presented.

Invariance of Topological Indices Under Hilbert Space Truncation

DOE PAGES

Huang, Zhoushen; Zhu, Wei; Arovas, Daniel P.; ...

2018-01-05

Here, we show that the topological index of a wave function, computed in the space of twisted boundary phases, is preserved under Hilbert space truncation, provided the truncated state remains normalizable. If truncation affects the boundary condition of the resulting state, the invariant index may acquire a different physical interpretation. If the index is symmetry protected, the truncation should preserve the protecting symmetry. We discuss implications of this invariance using paradigmatic integer and fractional Chern insulators, Z 2 topological insulators, and spin-1 Affleck-Kennedy-Lieb-Tasaki and Heisenberg chains, as well as its relation with the notion of bulk entanglement. As a possiblemore » application, we propose a partial quantum tomography scheme from which the topological index of a generic multicomponent wave function can be extracted by measuring only a small subset of wave function components, equivalent to the measurement of a bulk entanglement topological index.« less

Hierarchical Feature Extraction With Local Neural Response for Image Recognition.

PubMed

Li, Hong; Wei, Yantao; Li, Luoqing; Chen, C L P

2013-04-01

In this paper, a hierarchical feature extraction method is proposed for image recognition. The key idea of the proposed method is to extract an effective feature, called local neural response (LNR), of the input image with nontrivial discrimination and invariance properties by alternating between local coding and maximum pooling operation. The local coding, which is carried out on the locally linear manifold, can extract the salient feature of image patches and leads to a sparse measure matrix on which maximum pooling is carried out. The maximum pooling operation builds the translation invariance into the model. We also show that other invariant properties, such as rotation and scaling, can be induced by the proposed model. In addition, a template selection algorithm is presented to reduce computational complexity and to improve the discrimination ability of the LNR. Experimental results show that our method is robust to local distortion and clutter compared with state-of-the-art algorithms.

Anomalies in the 1D Anderson model: Beyond the band-centre and band-edge cases

NASA Astrophysics Data System (ADS)

Tessieri, L.; Izrailev, F. M.

2018-03-01

We consider the one-dimensional Anderson model with weak disorder. Using the Hamiltonian map approach, we analyse the validity of the random-phase approximation for resonant values of the energy, E = 2 cos(πr) , with r a rational number. We expand the invariant measure of the phase variable in powers of the disorder strength and we show that, contrary to what happens at the centre and at the edges of the band, for all other resonant energies the leading term of the invariant measure is uniform. When higher-order terms are taken into account, a modulation of the invariant measure appears for all resonant values of the energy. This implies that, when the localisation length is computed within the second-order approximation in the disorder strength, the Thouless formula is valid everywhere except at the band centre and at the band edges.

A computational exploration of complementary learning mechanisms in the primate ventral visual pathway.

PubMed

Spoerer, Courtney J; Eguchi, Akihiro; Stringer, Simon M

2016-02-01

In order to develop transformation invariant representations of objects, the visual system must make use of constraints placed upon object transformation by the environment. For example, objects transform continuously from one point to another in both space and time. These two constraints have been exploited separately in order to develop translation and view invariance in a hierarchical multilayer model of the primate ventral visual pathway in the form of continuous transformation learning and temporal trace learning. We show for the first time that these two learning rules can work cooperatively in the model. Using these two learning rules together can support the development of invariance in cells and help maintain object selectivity when stimuli are presented over a large number of locations or when trained separately over a large number of viewing angles. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

Reflection symmetry detection using locally affine invariant edge correspondence.

PubMed

Wang, Zhaozhong; Tang, Zesheng; Zhang, Xiao

2015-04-01

Reflection symmetry detection receives increasing attentions in recent years. The state-of-the-art algorithms mainly use the matching of intensity-based features (such as the SIFT) within a single image to find symmetry axes. This paper proposes a novel approach by establishing the correspondence of locally affine invariant edge-based features, which are superior to the intensity based in the aspects that it is insensitive to illumination variations, and applicable to textureless objects. The locally affine invariance is achieved by simple linear algebra for efficient and robust computations, making the algorithm suitable for detections under object distortions like perspective projection. Commonly used edge detectors and a voting process are, respectively, used before and after the edge description and matching steps to form a complete reflection detection pipeline. Experiments are performed using synthetic and real-world images with both multiple and single reflection symmetry axis. The test results are compared with existing algorithms to validate the proposed method.

Invariance of Topological Indices Under Hilbert Space Truncation

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

Huang, Zhoushen; Zhu, Wei; Arovas, Daniel P.

Here, we show that the topological index of a wave function, computed in the space of twisted boundary phases, is preserved under Hilbert space truncation, provided the truncated state remains normalizable. If truncation affects the boundary condition of the resulting state, the invariant index may acquire a different physical interpretation. If the index is symmetry protected, the truncation should preserve the protecting symmetry. We discuss implications of this invariance using paradigmatic integer and fractional Chern insulators, Z 2 topological insulators, and spin-1 Affleck-Kennedy-Lieb-Tasaki and Heisenberg chains, as well as its relation with the notion of bulk entanglement. As a possiblemore » application, we propose a partial quantum tomography scheme from which the topological index of a generic multicomponent wave function can be extracted by measuring only a small subset of wave function components, equivalent to the measurement of a bulk entanglement topological index.« less

High-order computer-assisted estimates of topological entropy

NASA Astrophysics Data System (ADS)

Grote, Johannes

The concept of Taylor Models is introduced, which offers highly accurate C0-estimates for the enclosures of functional dependencies, combining high-order Taylor polynomial approximation of functions and rigorous estimates of the truncation error, performed using verified interval arithmetic. The focus of this work is on the application of Taylor Models in algorithms for strongly nonlinear dynamical systems. A method to obtain sharp rigorous enclosures of Poincare maps for certain types of flows and surfaces is developed and numerical examples are presented. Differential algebraic techniques allow the efficient and accurate computation of polynomial approximations for invariant curves of certain planar maps around hyperbolic fixed points. Subsequently we introduce a procedure to extend these polynomial curves to verified Taylor Model enclosures of local invariant manifolds with C0-errors of size 10-10--10 -14, and proceed to generate the global invariant manifold tangle up to comparable accuracy through iteration in Taylor Model arithmetic. Knowledge of the global manifold structure up to finite iterations of the local manifold pieces enables us to find all homoclinic and heteroclinic intersections in the generated manifold tangle. Combined with the mapping properties of the homoclinic points and their ordering we are able to construct a subshift of finite type as a topological factor of the original planar system to obtain rigorous lower bounds for its topological entropy. This construction is fully automatic and yields homoclinic tangles with several hundred homoclinic points. As an example rigorous lower bounds for the topological entropy of the Henon map are computed, which to the best knowledge of the authors yield the largest such estimates published so far.

Self-force correction to geodetic spin precession in Kerr spacetime

NASA Astrophysics Data System (ADS)

Akcay, Sarp

2017-08-01

We present an expression for the gravitational self-force correction to the geodetic spin precession of a spinning compact object with small, but non-negligible mass in a bound, equatorial orbit around a Kerr black hole. We consider only conservative backreaction effects due to the mass of the compact object (m1), thus neglecting the effects of its spin s1 on its motion; i.e., we impose s1≪G m12/c and m1≪m2, where m2 is the mass parameter of the background Kerr spacetime. We encapsulate the correction to the spin precession in ψ , the ratio of the accumulated spin-precession angle to the total azimuthal angle over one radial orbit in the equatorial plane. Our formulation considers the gauge-invariant O (m1) part of the correction to ψ , denoted by Δ ψ , and is a generalization of the results of Akcay et al. [Classical Quantum Gravity 34, 084001 (2017), 10.1088/1361-6382/aa61d6] to Kerr spacetime. Additionally, we compute the zero-eccentricity limit of Δ ψ and show that this quantity differs from the circular orbit Δ ψcirc by a gauge-invariant quantity containing the gravitational self-force correction to general relativistic periapsis advance in Kerr spacetime. Our result for Δ ψ is expressed in a manner that readily accommodates numerical/analytical self-force computations, e.g., in the radiation gauge, and paves the way for the computation of a new eccentric-orbit Kerr gauge invariant beyond the generalized redshift.

Making classical and quantum canonical general relativity computable through a power series expansion in the inverse cosmological constant.

PubMed

Gambini, R; Pullin, J

2000-12-18

We consider general relativity with a cosmological constant as a perturbative expansion around a completely solvable diffeomorphism invariant field theory. This theory is the lambda --> infinity limit of general relativity. This allows an explicit perturbative computational setup in which the quantum states of the theory and the classical observables can be explicitly computed. An unexpected relationship arises at a quantum level between the discrete spectrum of the volume operator and the allowed values of the cosmological constant.

Curvature perturbations in the early universe: Theoretical models and observational tests

NASA Astrophysics Data System (ADS)

Vallinotto, Alberto

A very general prediction of inflation is that the power spectrum of density perturbations is characterized by a spectral index ns which is scale independent and approximately equal to unity. Drawing from the potential reconstruction method and adopting the slow-roll parameter expansion technique, we derive all possible single field inflationary potentials that would lead to a scale invariant density spectral index, consistent with current observations. In the process, a new method to determine the functional form of the inflationary potential in the slow roll approximation is devised, based on the reparametrization of the field dynamics with respect to the slow roll parameter epsilon which also allowed to show that under the assumptions made the investigation proved to be exhaustive and that no other solutions are available. Next, we focus on the fact that there exist a large class of inflationary models currently ruled out because the predicted production of curvature perturbations during the slow-roll stage results exponentially suppressed. We investigate whether an alternative mechanism for the generation of curvature perturbations can be devised for such a class of models. In the process, it is shown that it is sufficient for the inflationary potential to exhibit a broken symmetry to successfully convert isocurvature perturbations, which are excited during the slow-roll stage, into curvature perturbations thanks to an inhomogeneous decay stage. This conclusion is general, requiring as a sufficient condition only the fact that the inflation potential is characterized by a broken symmetry. Finally, we show that the perturbations thus produced are generally characterized by a non-negligible degree of non-gaussianity, which then provides a clear experimental signature for experimental detection or rejection.

No variation and low synonymous substitution rates in coral mtDNA despite high nuclear variation

PubMed Central

Hellberg, Michael E

2006-01-01

Background The mitochondrial DNA (mtDNA) of most animals evolves more rapidly than nuclear DNA, and often shows higher levels of intraspecific polymorphism and population subdivision. The mtDNA of anthozoans (corals, sea fans, and their kin), by contrast, appears to evolve slowly. Slow mtDNA evolution has been reported for several anthozoans, however this slow pace has been difficult to put in phylogenetic context without parallel surveys of nuclear variation or calibrated rates of synonymous substitution that could permit quantitative rate comparisons across taxa. Here, I survey variation in the coding region of a mitochondrial gene from a coral species (Balanophyllia elegans) known to possess high levels of nuclear gene variation, and estimate synonymous rates of mtDNA substitution by comparison to another coral (Tubastrea coccinea). Results The mtDNA surveyed (630 bp of cytochrome oxidase subunit I) was invariant among individuals sampled from 18 populations spanning 3000 km of the range of B. elegans, despite high levels of variation and population subdivision for allozymes over these same populations. The synonymous substitution rate between B. elegans and T. coccinea (0.05%/site/106 years) is similar to that in most plants, but 50–100 times lower than rates typical for most animals. In addition, while substitutions to mtDNA in most animals exhibit a strong bias toward transitions, mtDNA from these corals does not. Conclusion Slow rates of mitochondrial nucleotide substitution result in low levels of intraspecific mtDNA variation in corals, even when nuclear loci vary. Slow mtDNA evolution appears to be the basal condition among eukaryotes. mtDNA substitution rates switch from slow to fast abruptly and unidirectionally. This switch may stem from the loss of just one or a few mitochondrion-specific DNA repair or replication genes. PMID:16542456

Cyclical Behavior of Productivity in the Machine Tool Industry.

ERIC Educational Resources Information Center

Duke, John; Brand, Horst

1981-01-01

Productivity growth was slow during 1958-80, partly because of the industry's tendency to retain skilled workers during cyclical downturns; computers and other electronic equipment aided production, but diffusion of such innovations has been slow. (Author)

The dynamics of neuronal redundancy in decision making

NASA Astrophysics Data System (ADS)

Daniels, Bryan; Flack, Jessica; Krakauer, David

We propose two temporal phases of collective computation in a visual motion direction discrimination task by analyzing recordings from 169 neural channels in the prefrontal cortex of macaque monkeys. Phase I is a distributed phase in which uncertainty is substantially reduced by pooling information from many cells. Phase II is a redundant phase in which numerous single cells contain all the information present at the population level in Phase I. A dynamic distributed model connects low redundancy to a slow timescale of information aggregation, and provides a common explanation for both behaviors that differs only in the degree of recurrent excitation. We attribute the slow timescale of information accumulation to critical slowing down near the transition to a memory-carrying collective state. We suggest that this dynamic of slow distributed accumulation followed by fast collective propagation is a generic feature of robust collective computing systems related to consensus formation.

Numeric invariants from multidimensional persistence

DOE PAGES

Skryzalin, Jacek; Carlsson, Gunnar

2017-05-19

Topological data analysis is the study of data using techniques from algebraic topology. Often, one begins with a finite set of points representing data and a “filter” function which assigns a real number to each datum. Using both the data and the filter function, one can construct a filtered complex for further analysis. For example, applying the homology functor to the filtered complex produces an algebraic object known as a “one-dimensional persistence module”, which can often be interpreted as a finite set of intervals representing various geometric features in the data. If one runs the above process incorporating multiple filtermore » functions simultaneously, one instead obtains a multidimensional persistence module. Unfortunately, these are much more difficult to interpret. In this article, we analyze the space of multidimensional persistence modules from the perspective of algebraic geometry. First we build a moduli space of a certain subclass of easily analyzed multidimensional persistence modules, which we construct specifically to capture much of the information which can be gained by using multidimensional persistence instead of one-dimensional persistence. Fruthermore, we argue that the global sections of this space provide interesting numeric invariants when evaluated against our subclass of multidimensional persistence modules. Finally, we extend these global sections to the space of all multidimensional persistence modules and discuss how the resulting numeric invariants might be used to study data. This paper extends the results of Adcock et al. (Homol Homotopy Appl 18(1), 381–402, 2016) by constructing numeric invariants from the computation of a multidimensional persistence module as given by Carlsson et al. (J Comput Geom 1(1), 72–100, 2010).« less

Equivariant K3 invariants

DOE PAGES

Cheng, Miranda C. N.; Duncan, John F. R.; Harrison, Sarah M.; ...

2017-01-01

In this note, we describe a connection between the enumerative geometry of curves in K3 surfaces and the chiral ring of an auxiliary superconformal field theory. We consider the invariants calculated by Yau–Zaslow (capturing the Euler characters of the moduli spaces of D2-branes on curves of given genus), together with their refinements to carry additional quantum numbers by Katz–Klemm–Vafa (KKV), and Katz–Klemm–Pandharipande (KKP). We show that these invariants can be reproduced by studying the Ramond ground states of an auxiliary chiral superconformal field theory which has recently been observed to give rise to mock modular moonshine for a variety ofmore » sporadic simple groups that are subgroups of Conway’s group. We also study equivariant versions of these invariants. A K3 sigma model is specified by a choice of 4-plane in the K3 D-brane charge lattice. Symmetries of K3 sigma models are naturally identified with 4-plane preserving subgroups of the Conway group, according to the work of Gaberdiel–Hohenegger–Volpato, and one may consider corresponding equivariant refined K3 Gopakumar–Vafa invariants. The same symmetries naturally arise in the auxiliary CFT state space, affording a suggestive alternative view of the same computation. We comment on a lift of this story to the generating function of elliptic genera of symmetric products of K3 surfaces.« less

Fast associative memory + slow neural circuitry = the computational model of the brain.

NASA Astrophysics Data System (ADS)

Berkovich, Simon; Berkovich, Efraim; Lapir, Gennady

1997-08-01

We propose a computational model of the brain based on a fast associative memory and relatively slow neural processors. In this model, processing time is expensive but memory access is not, and therefore most algorithmic tasks would be accomplished by using large look-up tables as opposed to calculating. The essential feature of an associative memory in this context (characteristic for a holographic type memory) is that it works without an explicit mechanism for resolution of multiple responses. As a result, the slow neuronal processing elements, overwhelmed by the flow of information, operate as a set of templates for ranking of the retrieved information. This structure addresses the primary controversy in the brain architecture: distributed organization of memory vs. localization of processing centers. This computational model offers an intriguing explanation of many of the paradoxical features in the brain architecture, such as integration of sensors (through DMA mechanism), subliminal perception, universality of software, interrupts, fault-tolerance, certain bizarre possibilities for rapid arithmetics etc. In conventional computer science the presented type of a computational model did not attract attention as it goes against the technological grain by using a working memory faster than processing elements.

Slow adaptation of ventricular repolarization as a cause of arrhythmia?

PubMed

Bueno-Orovio, A; Hanson, B M; Gill, J S; Taggart, P; Rodriguez, B

2014-01-01

This article is part of the Focus Theme of Methods of Information in Medicine on "Biosignal Interpretation: Advanced Methods for Studying Cardiovascular and Respiratory Systems". Adaptation of the QT-interval to changes in heart rate reflects on the body-surface electrocardiogram the adaptation of action potential duration (APD) at the cellular level. The initial fast phase of APD adaptation has been shown to modulate the arrhythmia substrate. Whether the slow phase is potentially proarrhythmic remains unclear. To analyze in-vivo human data and use computer simulations to examine effects of the slow APD adaptation phase on dispersion of repolarization and reentry in the human ventricle. Electrograms were acquired from 10 left and 10 right ventricle (LV/RV) endocardial sites in 15 patients with normal ventricles during RV pacing. Activation-recovery intervals, as a surrogate for APD, were measured during a sustained increase in heart rate. Observed dynamics were studied using computer simulations of human tissue electrophysiology. Spatial heterogeneity of rate adaptation was observed in all patients. Inhomogeneity in slow APD adaptation time constants (Δτ(s)) was greater in LV than RV (Δτ(s)(LV) = 31.8 ± 13.2, Δτ(s)(RV) = 19.0 ± 12.8 s , P< 0.01). Simulations showed that altering local slow time constants of adaptation was sufficient to convert partial wavefront block to block with successful reentry. Using electrophysiological data acquired in-vivo in human and computer simulations, we identify heterogeneity in the slow phase of APD adaptation as an important component of arrhythmogenesis.

Slow-roll corrections in multi-field inflation: a separate universes approach

NASA Astrophysics Data System (ADS)

Karčiauskas, Mindaugas; Kohri, Kazunori; Mori, Taro; White, Jonathan

2018-05-01

In view of cosmological parameters being measured to ever higher precision, theoretical predictions must also be computed to an equally high level of precision. In this work we investigate the impact on such predictions of relaxing some of the simplifying assumptions often used in these computations. In particular, we investigate the importance of slow-roll corrections in the computation of multi-field inflation observables, such as the amplitude of the scalar spectrum Pζ, its spectral tilt ns, the tensor-to-scalar ratio r and the non-Gaussianity parameter fNL. To this end we use the separate universes approach and δ N formalism, which allows us to consider slow-roll corrections to the non-Gaussianity of the primordial curvature perturbation as well as corrections to its two-point statistics. In the context of the δ N expansion, we divide slow-roll corrections into two categories: those associated with calculating the correlation functions of the field perturbations on the initial flat hypersurface and those associated with determining the derivatives of the e-folding number with respect to the field values on the initial flat hypersurface. Using the results of Nakamura & Stewart '96, corrections of the first kind can be written in a compact form. Corrections of the second kind arise from using different levels of slow-roll approximation in solving for the super-horizon evolution, which in turn corresponds to using different levels of slow-roll approximation in the background equations of motion. We consider four different levels of approximation and apply the results to a few example models. The various approximations are also compared to exact numerical solutions.

Third Congress on Information System Science and Technology

DTIC Science & Technology

1968-04-01

versions of the same compiler. The " fast compile-slow execute" and the "slow compile- fast execute" gimmick is the greatest hoax ever per- petrated on the... fast such natural language analysis and translation can be accomplished. If the fairly superficial syntactic anal- ysis of a sentence which is...two kinds of computer: a fast computer with large immediate access and bulk memory for rear echelon and large installation em- ployment, and a

Quantitative quasiperiodicity

NASA Astrophysics Data System (ADS)

Das, Suddhasattwa; Saiki, Yoshitaka; Sander, Evelyn; Yorke, James A.

2017-11-01

The Birkhoff ergodic theorem concludes that time averages, i.e. Birkhoff averages, B_N( f):=Σn=0N-1 f(x_n)/N of a function f along a length N ergodic trajectory (x_n) of a function T converge to the space average \\int f dμ , where μ is the unique invariant probability measure. Convergence of the time average to the space average is slow. We use a modified average of f(x_n) by giving very small weights to the ‘end’ terms when n is near 0 or N-1 . When (x_n) is a trajectory on a quasiperiodic torus and f and T are C^∞ , our weighted Birkhoff average (denoted \

Simplified microprocessor design for VLSI control applications

NASA Technical Reports Server (NTRS)

Cameron, K.

1991-01-01

A design technique for microprocessors combining the simplicity of reduced instruction set computers (RISC's) with the richer instruction sets of complex instruction set computers (CISC's) is presented. They utilize the pipelined instruction decode and datapaths common to RISC's. Instruction invariant data processing sequences which transparently support complex addressing modes permit the formulation of simple control circuitry. Compact implementations are possible since neither complicated controllers nor large register sets are required.

Robust Real-Time and Rotation-Invariant American Sign Language Alphabet Recognition Using Range Camera

NASA Astrophysics Data System (ADS)

Lahamy, H.; Lichti, D.

2012-07-01

The automatic interpretation of human gestures can be used for a natural interaction with computers without the use of mechanical devices such as keyboards and mice. The recognition of hand postures have been studied for many years. However, most of the literature in this area has considered 2D images which cannot provide a full description of the hand gestures. In addition, a rotation-invariant identification remains an unsolved problem even with the use of 2D images. The objective of the current study is to design a rotation-invariant recognition process while using a 3D signature for classifying hand postures. An heuristic and voxelbased signature has been designed and implemented. The tracking of the hand motion is achieved with the Kalman filter. A unique training image per posture is used in the supervised classification. The designed recognition process and the tracking procedure have been successfully evaluated. This study has demonstrated the efficiency of the proposed rotation invariant 3D hand posture signature which leads to 98.24% recognition rate after testing 12723 samples of 12 gestures taken from the alphabet of the American Sign Language.

Rotationally Invariant Image Representation for Viewing Direction Classification in Cryo-EM

PubMed Central

Zhao, Zhizhen; Singer, Amit

2014-01-01

We introduce a new rotationally invariant viewing angle classification method for identifying, among a large number of cryo-EM projection images, similar views without prior knowledge of the molecule. Our rotationally invariant features are based on the bispectrum. Each image is denoised and compressed using steerable principal component analysis (PCA) such that rotating an image is equivalent to phase shifting the expansion coefficients. Thus we are able to extend the theory of bispectrum of 1D periodic signals to 2D images. The randomized PCA algorithm is then used to efficiently reduce the dimensionality of the bispectrum coefficients, enabling fast computation of the similarity between any pair of images. The nearest neighbors provide an initial classification of similar viewing angles. In this way, rotational alignment is only performed for images with their nearest neighbors. The initial nearest neighbor classification and alignment are further improved by a new classification method called vector diffusion maps. Our pipeline for viewing angle classification and alignment is experimentally shown to be faster and more accurate than reference-free alignment with rotationally invariant K-means clustering, MSA/MRA 2D classification, and their modern approximations. PMID:24631969

Random SU(2) invariant tensors

NASA Astrophysics Data System (ADS)

Li, Youning; Han, Muxin; Ruan, Dong; Zeng, Bei

2018-04-01

SU(2) invariant tensors are states in the (local) SU(2) tensor product representation but invariant under the global group action. They are of importance in the study of loop quantum gravity. A random tensor is an ensemble of tensor states. An average over the ensemble is carried out when computing any physical quantities. The random tensor exhibits a phenomenon known as ‘concentration of measure’, which states that for any bipartition the average value of entanglement entropy of its reduced density matrix is asymptotically the maximal possible as the local dimensions go to infinity. We show that this phenomenon is also true when the average is over the SU(2) invariant subspace instead of the entire space for rank-n tensors in general. It is shown in our earlier work Li et al (2017 New J. Phys. 19 063029) that the subleading correction of the entanglement entropy has a mild logarithmic divergence when n  =  4. In this paper, we show that for n  >  4 the subleading correction is not divergent but a finite number. In some special situation, the number could be even smaller than 1/2, which is the subleading correction of random state over the entire Hilbert space of tensors.

Wave computation on the Poincaré dodecahedral space

NASA Astrophysics Data System (ADS)

Bachelot-Motet, Agnès

2013-12-01

We compute the waves propagating on a compact 3-manifold of constant positive curvature with a non-trivial topology: the Poincaré dodecahedral space that is a plausible model of multi-connected universe. We transform the Cauchy problem to a mixed problem posed on a fundamental domain determined by the quaternionic calculus. We adopt a variational approach using a space of finite elements that is invariant under the action of the binary icosahedral group. The computation of the transient waves is validated with their spectral analysis by computing a lot of eigenvalues of the Laplace-Beltrami operator.

Extending matchgates into universal quantum computation

NASA Astrophysics Data System (ADS)

Brod, Daniel J.; Galvão, Ernesto F.

2011-08-01

Matchgates are a family of two-qubit gates associated with noninteracting fermions. They are classically simulatable if acting only on nearest neighbors but become universal for quantum computation if we relax this restriction or use swap gates [Jozsa and Miyake, Proc. R. Soc. ANATUAS1364-502110.1098/rspa.2008.0189 464, 3089 (2008)]. We generalize this result by proving that any nonmatchgate parity-preserving unitary is capable of extending the computational power of matchgates into universal quantum computation. We identify the single local invariant of parity-preserving unitaries responsible for this, and discuss related results in the context of fermionic systems.

GYC: A program to compute the turbulent boundary layer on a rotating cone

NASA Technical Reports Server (NTRS)

Sullivan, R. D.

1976-01-01

A computer program, GYC, which is capable of computing the properties of a compressible turbulent boundary layer on a rotating axisymmetric cone-cylinder body, according to the principles of invariant modeling was studied. The program is extended to include the calculation of the turbulence scale by a differential equation. GYC is in operation on the CDC-7600 computer and has undergone several corrections and improvements as a result of the experience gained. The theoretical basis for the program and the method of implementation, as well as information on its operation are given.

Concurrent image-based visual servoing with adaptive zooming for non-cooperative rendezvous maneuvers

NASA Astrophysics Data System (ADS)

Pomares, Jorge; Felicetti, Leonard; Pérez, Javier; Emami, M. Reza

2018-02-01

An image-based servo controller for the guidance of a spacecraft during non-cooperative rendezvous is presented in this paper. The controller directly utilizes the visual features from image frames of a target spacecraft for computing both attitude and orbital maneuvers concurrently. The utilization of adaptive optics, such as zooming cameras, is also addressed through developing an invariant-image servo controller. The controller allows for performing rendezvous maneuvers independently from the adjustments of the camera focal length, improving the performance and versatility of maneuvers. The stability of the proposed control scheme is proven analytically in the invariant space, and its viability is explored through numerical simulations.

Discrete Thermodynamics

DOE PAGES

Margolin, L. G.; Hunter, A.

2017-10-18

Here, we consider the dependence of velocity probability distribution functions on the finite size of a thermodynamic system. We are motivated by applications to computational fluid dynamics, hence discrete thermodynamics. We then begin by describing a coarsening process that represents geometric renormalization. Then, based only on the requirements of conservation, we demonstrate that the pervasive assumption of local thermodynamic equilibrium is not form invariant. We develop a perturbative correction that restores form invariance to second-order in a small parameter associated with macroscopic gradients. Finally, we interpret the corrections in terms of unresolved kinetic energy and discuss the implications of ourmore » results both in theory and as applied to numerical simulation.« less

Discrete Thermodynamics

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

Margolin, L. G.; Hunter, A.

Here, we consider the dependence of velocity probability distribution functions on the finite size of a thermodynamic system. We are motivated by applications to computational fluid dynamics, hence discrete thermodynamics. We then begin by describing a coarsening process that represents geometric renormalization. Then, based only on the requirements of conservation, we demonstrate that the pervasive assumption of local thermodynamic equilibrium is not form invariant. We develop a perturbative correction that restores form invariance to second-order in a small parameter associated with macroscopic gradients. Finally, we interpret the corrections in terms of unresolved kinetic energy and discuss the implications of ourmore » results both in theory and as applied to numerical simulation.« less

Renormalization of the Lattice Heavy Quark Classical Velocity

NASA Astrophysics Data System (ADS)

Mandula, Jeffrey E.; Ogilvie, Michael C.

1996-03-01

In the lattice formulation of the Heavy Quark Effective Theory (LHQET), the "classical velocity" v becomes renormalized. The origin of this renormalization is the reduction of Lorentz (or O(4)) invariance to (hyper)cubic invariance. The renormalization is finite and depends on the form of the decretization of the reduced heavy quark Dirac equation. For the Forward Time — Centered Space discretization, the renormalization is computed both perturbatively, to one loop, and non-perturbatively using two ensembles of lattices, one at β = 5.7 and the other at β = 6.1 The estimates agree, and indicate that for small classical velocities, ν→ is reduced by about 25-30%.

Reformulations of Yang–Mills theories with space–time tensor fields

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

Guo, Zhi-Qiang, E-mail: gzhqedu@gmail.com

2016-01-15

We provide the reformulations of Yang–Mills theories in terms of gauge invariant metric-like variables in three and four dimensions. The reformulations are used to analyze the dimension two gluon condensate and give gauge invariant descriptions of gluon polarization. In three dimensions, we obtain a non-zero dimension two gluon condensate by one loop computation, whose value is similar to the square of photon mass in the Schwinger model. In four dimensions, we obtain a Lagrangian with the dual property, which shares the similar but different property with the dual superconductor scenario. We also make discussions on the effectiveness of one loopmore » approximation.« less

Functional equations for orbifold wreath products

NASA Astrophysics Data System (ADS)

Farsi, Carla; Seaton, Christopher

2017-10-01

We present generating functions for extensions of multiplicative invariants of wreath symmetric products of orbifolds presented as the quotient by the locally free action of a compact, connected Lie group in terms of orbifold sector decompositions. Particularly interesting instances of these product formulas occur for the Euler and Euler-Satake characteristics, which we compute for a class of weighted projective spaces. This generalizes results known for global quotients by finite groups to all closed, effective orbifolds. We also describe a combinatorial approach to extensions of multiplicative invariants using decomposable functors that recovers the formula for the Euler-Satake characteristic of a wreath product of a global quotient orbifold.

Improving the Selection, Classification, and Utilization of Army Enlisted Personnel: Technical Appendix to the Annual Report

DTIC Science & Technology

1983-10-01

03.1 I20 -06 -20 -26 79.0 SfC sic SCaflayepm VS -09 -27 33 -13 -23 -16 .14 3 .ŝ of 2 2? 09 40-40 .09 -17 -28 .00 .10 -it .’ -20 72 073 040.Uu.s jsos...difference between the chi-squares for these *two models (pattern invariance vs . loading invariance) was computed to be 63.83 with 30 degrees of freedom...paragraphs in order to master or pass the objective or to receive a "GO." Typical criterion-referenced scores are number of objectives A" passed, GO vs . NO

Three-Dimensional Simulation of Traveling-Wave Tube Cold-Test Characteristics Using MAFIA

NASA Technical Reports Server (NTRS)

Kory, Carol L.; Wilson, Jeffrey D.

1995-01-01

The three-dimensional simulation code MAFIA was used to compute the cold-test parameters - frequency-phase dispersion, beam on-axis interaction impedance, and attenuation - for two types of traveling-wave tube (TWT) slow-wave circuits. The potential for this electromagnetic computer modeling code to reduce the time and cost of TWT development is demonstrated by the high degree of accuracy achieved in calculating these parameters. Generalized input files were developed for ferruled coupled-cavity and TunneLadder slow-wave circuits. These files make it easy to model circuits of arbitrary dimensions. The utility of these files was tested by applying each to a specific TWT slow-wave circuit and comparing the results with experimental data. Excellent agreement was obtained.

FREQ: A computational package for multivariable system loop-shaping procedures

NASA Technical Reports Server (NTRS)

Giesy, Daniel P.; Armstrong, Ernest S.

1989-01-01

Many approaches in the field of linear, multivariable time-invariant systems analysis and controller synthesis employ loop-sharing procedures wherein design parameters are chosen to shape frequency-response singular value plots of selected transfer matrices. A software package, FREQ, is documented for computing within on unified framework many of the most used multivariable transfer matrices for both continuous and discrete systems. The matrices are evaluated at user-selected frequency-response values, and singular values against frequency. Example computations are presented to demonstrate the use of the FREQ code.

Lorenz, Gödel and Penrose: new perspectives on determinism and causality in fundamental physics

NASA Astrophysics Data System (ADS)

Palmer, T. N.

2014-07-01

Despite being known for his pioneering work on chaotic unpredictability, the key discovery at the core of meteorologist Ed Lorenz's work is the link between space-time calculus and state-space fractal geometry. Indeed, properties of Lorenz's fractal invariant set relate space-time calculus to deep areas of mathematics such as Gödel's Incompleteness Theorem. Could such properties also provide new perspectives on deep unsolved issues in fundamental physics? Recent developments in cosmology motivate what is referred to as the 'cosmological invariant set postulate': that the universe ? can be considered a deterministic dynamical system evolving on a causal measure-zero fractal invariant set ? in its state space. Symbolic representations of ? are constructed explicitly based on permutation representations of quaternions. The resulting 'invariant set theory' provides some new perspectives on determinism and causality in fundamental physics. For example, while the cosmological invariant set appears to have a rich enough structure to allow a description of (quantum) probability, its measure-zero character ensures it is sparse enough to prevent invariant set theory being constrained by the Bell inequality (consistent with a partial violation of the so-called measurement independence postulate). The primacy of geometry as embodied in the proposed theory extends the principles underpinning general relativity. As a result, the physical basis for contemporary programmes which apply standard field quantisation to some putative gravitational lagrangian is questioned. Consistent with Penrose's suggestion of a deterministic but non-computable theory of fundamental physics, an alternative 'gravitational theory of the quantum' is proposed based on the geometry of ?, with new perspectives on the problem of black-hole information loss and potential observational consequences for the dark universe.

Characterizing Responses of Translation Invariant Neurons to Natural Stimuli: Maximally Informative Invariant Dimensions

PubMed Central

Eickenberg, Michael; Rowekamp, Ryan J.; Kouh, Minjoon; Sharpee, Tatyana O.

2012-01-01

Our visual system is capable of recognizing complex objects even when their appearances change drastically under various viewing conditions. Especially in the higher cortical areas, the sensory neurons reflect such functional capacity in their selectivity for complex visual features and invariance to certain object transformations, such as image translation. Due to the strong nonlinearities necessary to achieve both the selectivity and invariance, characterizing and predicting the response patterns of these neurons represents a formidable computational challenge. A related problem is that such neurons are poorly driven by randomized inputs, such as white noise, and respond strongly only to stimuli with complex high-order correlations, such as natural stimuli. Here we describe a novel two-step optimization technique that can characterize both the shape selectivity and the range and coarseness of position invariance from neural responses to natural stimuli. One step in the optimization involves finding the template as the maximally informative dimension given the estimated spatial location where the response could have been triggered within each image. The estimates of the locations that triggered the response are subsequently updated in the next step. Under the assumption of a monotonic relationship between the firing rate and stimulus projections on the template at a given position, the most likely location is the one that has the largest projection on the estimate of the template. The algorithm shows quick convergence during optimization, and the estimation results are reliable even in the regime of small signal-to-noise ratios. When we apply the algorithm to responses of complex cells in the primary visual cortex (V1) to natural movies, we find that responses of the majority of cells were significantly better described by translation invariant models based on one template compared with position-specific models with several relevant features. PMID:22734487

Time-dependent Gutzwiller theory of magnetic excitations in the Hubbard model

NASA Astrophysics Data System (ADS)

Seibold, G.; Becca, F.; Rubin, P.; Lorenzana, J.

2004-04-01

We use a spin-rotational invariant Gutzwiller energy functional to compute random-phase-approximation-like (RPA) fluctuations on top of the Gutzwiller approximation (GA). The method can be viewed as an extension of the previously developed GA+RPA approach for the charge sector [G. Seibold and J. Lorenzana, Phys. Rev. Lett. 86, 2605 (2001)] with respect to the inclusion of the magnetic excitations. Unlike the charge case, no assumptions about the time evolution of the double occupancy are needed in this case. Interestingly, in a spin-rotational invariant system, we find the correct degeneracy between triplet excitations, showing the consistency of both computations. Since no restrictions are imposed on the symmetry of the underlying saddle-point solution, our approach is suitable for the evaluation of the magnetic susceptibility and dynamical structure factor in strongly correlated inhomogeneous systems. We present a detailed study of the quality of our approach by comparing with exact diagonalization results and show its much higher accuracy compared to the conventional Hartree-Fock+RPA theory. In infinite dimensions, where the GA becomes exact for the Gutzwiller variational energy, we evaluate ferromagnetic and antiferromagnetic instabilities from the transverse magnetic susceptibility. The resulting phase diagram is in complete agreement with previous variational computations.

Effect of Helical Slow-Wave Circuit Variations on TWT Cold-Test Characteristics

NASA Technical Reports Server (NTRS)

Kory, Carol L.; Dayton, J. A., Jr.

1998-01-01

Recent advances in the state of the art of computer modeling offer the possibility for the first time to evaluate the effect that slow-wave structure parameter variations, such as manufacturing tolerances, have on the cold-test characteristics of helical traveling-wave tubes (TWT's). This will enable manufacturers to determine the cost effectiveness of controlling the dimensions of the component parts of the TWT, which is almost impossible to do experimentally without building a large number of tubes and controlling several parameters simultaneously. The computer code MAFIA is used in this analysis to determine the effect on dispersion and on-axis interaction impedance of several helical slow-wave circuit parameter variations, including thickness and relative dielectric constant of the support rods, tape width, and height of the metallized films deposited on the dielectric rods. Previous computer analyzes required so many approximations that accurate determinations of the effect of many relevant dimensions on tube performance were practically impossible.

Effect of Helical Slow-Wave Circuit Variations on TWT Cold-Test Characteristics

NASA Technical Reports Server (NTRS)

Kory, Carol L.; Dayton, James A., Jr.

1997-01-01

Recent advances in the state of the art of computer modeling offer the possibility for the first time to evaluate the effect that slow-wave structure parameter variations, such as manufacturing tolerances, have on the cold-test characteristics of helical traveling-wave tubes (TWT's). This will enable manufacturers to determine the cost effectiveness of controlling the dimensions of the component parts of the TWT, which is almost impossible to do experimentally without building a large number of tubes and controlling several parameters simultaneously. The computer code MAFIA is used in this analysis to determine the effect on dispersion and on-axis interaction impedance of several helical slow-wave circuit parameter variations, including thickness and relative dielectric constant of the support rods, tape width, and height of the metallized films deposited on the dielectric rods. Previous computer analyses required so many approximations that accurate determinations of the effect of many relevant dimensions on tube performance were practically impossible.

Effect of Helical Slow-Wave Circuit Variations on TWT Cold-Test Characteristics

NASA Technical Reports Server (NTRS)

Kory, Carol L.; Dayton, James A., Jr.

1998-01-01

Recent advances in the state of the art of computer modeling offer the possibility for the first time to evaluate the effect that slow-wave structure parameter variations, such'as manufacturing tolerances, have on the cold-test characteristics of helical traveling-wave tubes (TWT's). This will enable manufacturers to determine the cost effectiveness of controlling the dimensions of the component parts of the TWT, which is almost impossible to do experimentally without building a large number of tubes and controlling several parameters simultaneously. The computer code MAxwell's equations by the Finite Integration Algorithm (MAFIA) is used in this analysis to determine the effect on dispersion and on-axis interaction impedance of several helical slow-wave circuit parameter variations, including thickness and relative dielectric constant of the support rods, tape width, and height of the metallized films deposited on the dielectric rods. Previous computer analyzes required so many approximations that accurate determinations of the effect of many relevant dimensions on tube performance were practically impossible.

Control Theory and Statistical Generalizations.

ERIC Educational Resources Information Center

Powers, William T.

1990-01-01

Contrasts modeling methods in control theory to the methods of statistical generalizations in empirical studies of human or animal behavior. Presents a computer simulation that predicts behavior based on variables (effort and rewards) determined by the invariable (desired reward). Argues that control theory methods better reflect relationships to…

Translation and Rotation Invariant Multiscale Image Registration

DTIC Science & Technology

2002-03-01

be computed without human interaction. This allows for the automation of image registration [16]. According to Tashakkori et al [35], the correlation...Intelligence, 21 (10):1074– 1081 (October 1999). 34. Strang, G. and T. Nguyen. Wavelets and Filter Banks . Wellesley, Cambridge, 1996. 35. Tashakkori

Modularization of biochemical networks based on classification of Petri net t-invariants.

PubMed

Grafahrend-Belau, Eva; Schreiber, Falk; Heiner, Monika; Sackmann, Andrea; Junker, Björn H; Grunwald, Stefanie; Speer, Astrid; Winder, Katja; Koch, Ina

2008-02-08

Structural analysis of biochemical networks is a growing field in bioinformatics and systems biology. The availability of an increasing amount of biological data from molecular biological networks promises a deeper understanding but confronts researchers with the problem of combinatorial explosion. The amount of qualitative network data is growing much faster than the amount of quantitative data, such as enzyme kinetics. In many cases it is even impossible to measure quantitative data because of limitations of experimental methods, or for ethical reasons. Thus, a huge amount of qualitative data, such as interaction data, is available, but it was not sufficiently used for modeling purposes, until now. New approaches have been developed, but the complexity of data often limits the application of many of the methods. Biochemical Petri nets make it possible to explore static and dynamic qualitative system properties. One Petri net approach is model validation based on the computation of the system's invariant properties, focusing on t-invariants. T-invariants correspond to subnetworks, which describe the basic system behavior.With increasing system complexity, the basic behavior can only be expressed by a huge number of t-invariants. According to our validation criteria for biochemical Petri nets, the necessary verification of the biological meaning, by interpreting each subnetwork (t-invariant) manually, is not possible anymore. Thus, an automated, biologically meaningful classification would be helpful in analyzing t-invariants, and supporting the understanding of the basic behavior of the considered biological system. Here, we introduce a new approach to automatically classify t-invariants to cope with network complexity. We apply clustering techniques such as UPGMA, Complete Linkage, Single Linkage, and Neighbor Joining in combination with different distance measures to get biologically meaningful clusters (t-clusters), which can be interpreted as modules. To find the optimal number of t-clusters to consider for interpretation, the cluster validity measure, Silhouette Width, is applied. We considered two different case studies as examples: a small signal transduction pathway (pheromone response pathway in Saccharomyces cerevisiae) and a medium-sized gene regulatory network (gene regulation of Duchenne muscular dystrophy). We automatically classified the t-invariants into functionally distinct t-clusters, which could be interpreted biologically as functional modules in the network. We found differences in the suitability of the various distance measures as well as the clustering methods. In terms of a biologically meaningful classification of t-invariants, the best results are obtained using the Tanimoto distance measure. Considering clustering methods, the obtained results suggest that UPGMA and Complete Linkage are suitable for clustering t-invariants with respect to the biological interpretability. We propose a new approach for the biological classification of Petri net t-invariants based on cluster analysis. Due to the biologically meaningful data reduction and structuring of network processes, large sets of t-invariants can be evaluated, allowing for model validation of qualitative biochemical Petri nets. This approach can also be applied to elementary mode analysis.

Modularization of biochemical networks based on classification of Petri net t-invariants

PubMed Central

Grafahrend-Belau, Eva; Schreiber, Falk; Heiner, Monika; Sackmann, Andrea; Junker, Björn H; Grunwald, Stefanie; Speer, Astrid; Winder, Katja; Koch, Ina

2008-01-01

Background Structural analysis of biochemical networks is a growing field in bioinformatics and systems biology. The availability of an increasing amount of biological data from molecular biological networks promises a deeper understanding but confronts researchers with the problem of combinatorial explosion. The amount of qualitative network data is growing much faster than the amount of quantitative data, such as enzyme kinetics. In many cases it is even impossible to measure quantitative data because of limitations of experimental methods, or for ethical reasons. Thus, a huge amount of qualitative data, such as interaction data, is available, but it was not sufficiently used for modeling purposes, until now. New approaches have been developed, but the complexity of data often limits the application of many of the methods. Biochemical Petri nets make it possible to explore static and dynamic qualitative system properties. One Petri net approach is model validation based on the computation of the system's invariant properties, focusing on t-invariants. T-invariants correspond to subnetworks, which describe the basic system behavior. With increasing system complexity, the basic behavior can only be expressed by a huge number of t-invariants. According to our validation criteria for biochemical Petri nets, the necessary verification of the biological meaning, by interpreting each subnetwork (t-invariant) manually, is not possible anymore. Thus, an automated, biologically meaningful classification would be helpful in analyzing t-invariants, and supporting the understanding of the basic behavior of the considered biological system. Methods Here, we introduce a new approach to automatically classify t-invariants to cope with network complexity. We apply clustering techniques such as UPGMA, Complete Linkage, Single Linkage, and Neighbor Joining in combination with different distance measures to get biologically meaningful clusters (t-clusters), which can be interpreted as modules. To find the optimal number of t-clusters to consider for interpretation, the cluster validity measure, Silhouette Width, is applied. Results We considered two different case studies as examples: a small signal transduction pathway (pheromone response pathway in Saccharomyces cerevisiae) and a medium-sized gene regulatory network (gene regulation of Duchenne muscular dystrophy). We automatically classified the t-invariants into functionally distinct t-clusters, which could be interpreted biologically as functional modules in the network. We found differences in the suitability of the various distance measures as well as the clustering methods. In terms of a biologically meaningful classification of t-invariants, the best results are obtained using the Tanimoto distance measure. Considering clustering methods, the obtained results suggest that UPGMA and Complete Linkage are suitable for clustering t-invariants with respect to the biological interpretability. Conclusion We propose a new approach for the biological classification of Petri net t-invariants based on cluster analysis. Due to the biologically meaningful data reduction and structuring of network processes, large sets of t-invariants can be evaluated, allowing for model validation of qualitative biochemical Petri nets. This approach can also be applied to elementary mode analysis. PMID:18257938

DREAM3D simulations of inner-belt dynamics

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

Cunningham, Gregory Scott

2015-05-26

A 1973 paper by Lyons and Thorne explains the two-belt structure for electrons in the inner magnetosphere as a balance between inward radial diffusion and loss to the atmosphere, where the loss to the atmosphere is enabled by pitch-angle scattering from Coulomb and wave-particle interactions. In the 1973 paper, equilibrium solutions to a decoupled set of 1D radial diffusion equations, one for each value of the first invariant of motion, μ, were computed to produce the equilibrium two-belt structure. Each 1D radial diffusion equation incorporated an L-and μ-dependent `lifetime' due to the Coulomb and wave-particle interactions. This decoupling of themore » problem is appropriate under the assumption that radial diffusion is slow in comparison to pitch-angle scattering. However, for some values of μ and L the lifetime associated with pitch-angle scattering is comparable to the timescale associated with radial diffusion, suggesting that the true equilibrium solutions might reflect `coupled modes' involving pitch-angle scattering and radial diffusion and thus requiring a 3D diffusion model. In the work we show here, we have computed the equilibrium solutions using our 3D diffusion model, DREAM3D, that allows for such coupling. We find that the 3D equilibrium solutions are quite similar to the solutions shown in the 1973 paper when we use the same physical models for radial diffusion and pitch-angle scattering from hiss. However, we show that the equilibrium solutions are quite sensitive to various aspects of the physics model employed in the 1973 paper that can be improved, suggesting that additional work needs to be done to understand the two-belt structure.« less

Impact of the "Symmetric Instability of the Computational Kind" at mesoscale- and submesoscale-permitting resolutions

NASA Astrophysics Data System (ADS)

Ducousso, Nicolas; Le Sommer, J.; Molines, J.-M.; Bell, M.

2017-12-01

The energy- and enstrophy-conserving momentum advection scheme (EEN) used over the last 10 years in NEMO is subject to a spurious numerical instability. This instability, referred to as the Symmetric Instability of the Computational Kind (SICK), arises from a discrete imbalance between the two components of the vector-invariant form of momentum advection. The properties and the method for removing this instability have been documented by Hollingsworth et al. (1983), but the extent to which the SICK may interfere with processes of interest at mesoscale- and submesoscale-permitting resolutions is still unkown. In this paper, the impact of the SICK in realistic ocean model simulations is assessed by comparing model integrations with different versions of the EEN momentum advection scheme. Investigations are undertaken with a global mesoscale-permitting resolution (1/4 °) configuration and with a regional North Atlantic Ocean submesoscale-permitting resolution (1/60 °) configuration. At both resolutions, the instability is found to alter primarily the most energetic current systems, such as equatorial jets, western boundary currents and coherent vortices. The impact of the SICK is found to increase with model resolution with a noticeable impact at mesoscale-permitting resolution and a dramatic impact at submesoscale-permitting resolution. The SICK is shown to distort the normal functioning of current systems, by redirecting the slow energy transfer between balanced motions to a spurious energy transfer to internal inertia-gravity waves and to dissipation. Our results indicate that the SICK is likely to have significantly corrupted NEMO solutions (when run with the EEN scheme) at mesocale-permitting and finer resolutions over the last 10 years.

Artificial Neural Network L* from different magnetospheric field models

NASA Astrophysics Data System (ADS)

Yu, Y.; Koller, J.; Zaharia, S. G.; Jordanova, V. K.

2011-12-01

The third adiabatic invariant L* plays an important role in modeling and understanding the radiation belt dynamics. The popular way to numerically obtain the L* value follows the recipe described by Roederer [1970], which is, however, slow and computational expensive. This work focuses on a new technique, which can compute the L* value in microseconds without losing much accuracy: artificial neural networks. Since L* is related to the magnetic flux enclosed by a particle drift shell, global magnetic field information needed to trace the drift shell is required. A series of currently popular empirical magnetic field models are applied to create the L* data pool using 1 million data samples which are randomly selected within a solar cycle and within the global magnetosphere. The networks, trained from the above L* data pool, can thereby be used for fairly efficient L* calculation given input parameters valid within the trained temporal and spatial range. Besides the empirical magnetospheric models, a physics-based self-consistent inner magnetosphere model (RAM-SCB) developed at LANL is also utilized to calculate L* values and then to train the L* neural network. This model better predicts the magnetospheric configuration and therefore can significantly improve the L*. The above neural network L* technique will enable, for the first time, comprehensive solar-cycle long studies of radiation belt processes. However, neural networks trained from different magnetic field models can result in different L* values, which could cause mis-interpretation of radiation belt dynamics, such as where the source of the radiation belt charged particle is and which mechanism is dominant in accelerating the particles. Such a fact calls for attention to cautiously choose a magnetospheric field model for the L* calculation.

Dynamic Encoding of Face Information in the Human Fusiform Gyrus

PubMed Central

Ghuman, Avniel Singh; Brunet, Nicolas M.; Li, Yuanning; Konecky, Roma O.; Pyles, John A.; Walls, Shawn A.; Destefino, Vincent; Wang, Wei; Richardson, R. Mark

2014-01-01

Humans’ ability to rapidly and accurately detect, identify, and classify faces under variable conditions derives from a network of brain regions highly tuned to face information. The fusiform face area (FFA) is thought to be a computational hub for face processing, however temporal dynamics of face information processing in FFA remains unclear. Here we use multivariate pattern classification to decode the temporal dynamics of expression-invariant face information processing using electrodes placed directly upon FFA in humans. Early FFA activity (50-75 ms) contained information regarding whether participants were viewing a face. Activity between 200-500 ms contained expression-invariant information about which of 70 faces participants were viewing along with the individual differences in facial features and their configurations. Long-lasting (500+ ms) broadband gamma frequency activity predicted task performance. These results elucidate the dynamic computational role FFA plays in multiple face processing stages and indicate what information is used in performing these visual analyses. PMID:25482825

Role of visual and non-visual cues in constructing a rotation-invariant representation of heading in parietal cortex

PubMed Central

Sunkara, Adhira

2015-01-01

As we navigate through the world, eye and head movements add rotational velocity patterns to the retinal image. When such rotations accompany observer translation, the rotational velocity patterns must be discounted to accurately perceive heading. The conventional view holds that this computation requires efference copies of self-generated eye/head movements. Here we demonstrate that the brain implements an alternative solution in which retinal velocity patterns are themselves used to dissociate translations from rotations. These results reveal a novel role for visual cues in achieving a rotation-invariant representation of heading in the macaque ventral intraparietal area. Specifically, we show that the visual system utilizes both local motion parallax cues and global perspective distortions to estimate heading in the presence of rotations. These findings further suggest that the brain is capable of performing complex computations to infer eye movements and discount their sensory consequences based solely on visual cues. DOI: http://dx.doi.org/10.7554/eLife.04693.001 PMID:25693417

Applications of the similarity relations in radiative transfer to remote sensing implementation and flux simulation

NASA Astrophysics Data System (ADS)

Yang, P.; Ding, J.; Tang, G.; King, M. D.; Platnick, S. E.; Meyer, K.; Mlawer, E. J.

2017-12-01

Van de Hulst (1974) showed several quasi-invariant quantities in radiative transfer concerning multiple scattering. Recently, we illustrated that the aforesaid quasi-invariant quantities are useful in remote sensing of ice cloud properties from spaceborne radiometric observations (Ding et al. 2017). Specifically, the overall performance of an ice cloud optical property model can be estimated without carrying out detailed retrieval implementation. In this presentation, we will review the radiative transfer similarity relations and some recent results including the study by Ding et al. (2017). Furthermore, we will illustrate an application of the similarity relations to improvement of broadband radiative flux computation. For example, the Rapid Radiative Transfer Model (RRTM, Mlawer et al, 1999) does not consider multiple scattering in the longwave spectral regime (RRTMG-LW) ("G" indicates a version suitable for GCM applications). We show that the similarity relations can be used to effectively improve the accuracy of RRTMG-LW without increasing computational effort.

Dynamic encoding of face information in the human fusiform gyrus.

PubMed

Ghuman, Avniel Singh; Brunet, Nicolas M; Li, Yuanning; Konecky, Roma O; Pyles, John A; Walls, Shawn A; Destefino, Vincent; Wang, Wei; Richardson, R Mark

2014-12-08

Humans' ability to rapidly and accurately detect, identify and classify faces under variable conditions derives from a network of brain regions highly tuned to face information. The fusiform face area (FFA) is thought to be a computational hub for face processing; however, temporal dynamics of face information processing in FFA remains unclear. Here we use multivariate pattern classification to decode the temporal dynamics of expression-invariant face information processing using electrodes placed directly on FFA in humans. Early FFA activity (50-75 ms) contained information regarding whether participants were viewing a face. Activity between 200 and 500 ms contained expression-invariant information about which of 70 faces participants were viewing along with the individual differences in facial features and their configurations. Long-lasting (500+ms) broadband gamma frequency activity predicted task performance. These results elucidate the dynamic computational role FFA plays in multiple face processing stages and indicate what information is used in performing these visual analyses.

KAM tori and whiskered invariant tori for non-autonomous systems

NASA Astrophysics Data System (ADS)

Canadell, Marta; de la Llave, Rafael

2015-08-01

We consider non-autonomous dynamical systems which converge to autonomous (or periodic) systems exponentially fast in time. Such systems appear naturally as models of many physical processes affected by external pulses. We introduce definitions of non-autonomous invariant tori and non-autonomous whiskered tori and their invariant manifolds and we prove their persistence under small perturbations, smooth dependence on parameters and several geometric properties (if the systems are Hamiltonian, the tori are Lagrangian manifolds). We note that such definitions are problematic for general time-dependent systems, but we show that they are unambiguous for systems converging exponentially fast to autonomous. The proof of persistence relies only on a standard Implicit Function Theorem in Banach spaces and it does not require that the rotations in the tori are Diophantine nor that the systems we consider preserve any geometric structure. We only require that the autonomous system preserves these objects. In particular, when the autonomous system is integrable, we obtain the persistence of tori with rational rotational. We also discuss fast and efficient algorithms for their computation. The method also applies to infinite dimensional systems which define a good evolution, e.g. PDE's. When the systems considered are Hamiltonian, we show that the time dependent invariant tori are isotropic. Hence, the invariant tori of maximal dimension are Lagrangian manifolds. We also obtain that the (un)stable manifolds of whiskered tori are Lagrangian manifolds. We also include a comparison with the more global theory developed in Blazevski and de la Llave (2011).

Predictions of the spontaneous symmetry-breaking theory for visual code completeness and spatial scaling in single-cell learning rules.

PubMed

Webber, C J

2001-05-01

This article shows analytically that single-cell learning rules that give rise to oriented and localized receptive fields, when their synaptic weights are randomly and independently initialized according to a plausible assumption of zero prior information, will generate visual codes that are invariant under two-dimensional translations, rotations, and scale magnifications, provided that the statistics of their training images are sufficiently invariant under these transformations. Such codes span different image locations, orientations, and size scales with equal economy. Thus, single-cell rules could account for the spatial scaling property of the cortical simple-cell code. This prediction is tested computationally by training with natural scenes; it is demonstrated that a single-cell learning rule can give rise to simple-cell receptive fields spanning the full range of orientations, image locations, and spatial frequencies (except at the extreme high and low frequencies at which the scale invariance of the statistics of digitally sampled images must ultimately break down, because of the image boundary and the finite pixel resolution). Thus, no constraint on completeness, or any other coupling between cells, is necessary to induce the visual code to span wide ranges of locations, orientations, and size scales. This prediction is made using the theory of spontaneous symmetry breaking, which we have previously shown can also explain the data-driven self-organization of a wide variety of transformation invariances in neurons' responses, such as the translation invariance of complex cell response.

Measurement of the underlying event in the Drell–Yan process in proton–proton collisions at $$\\sqrt{s} = 7~\\mbox{TeV}$$

DOE PAGES

Chatrchyan, S.; Khachatryan, V.; Sirunyan, A. M.; ...

2012-09-20

A measurement of the underlying event (UE) activity in proton-proton collisions at a center-of-mass energy of 7 TeV is performed using Drell--Yan events in a data sample corresponding to an integrated luminosity of 2.2 inverse femtobarns, collected by the CMS experiment at the LHC. The activity measured in the muonic final state (q q-bar to opposite-sign muons) is corrected to the particle level and compared with the predictions of various Monte Carlo generators and hadronization models. The dependence of the UE activity on the dimuon invariant mass is well described by PYTHIA and HERWIG++ tunes derived from the leading jet/trackmore » approach, illustrating the universality of the UE activity. The UE activity is observed to be independent of the dimuon invariant mass in the region above 40 GeV, while a slow increase is observed with increasing transverse momentum of the dimuon system. The dependence of the UE activity on the transverse momentum of the dimuon system is accurately described by MADGRAPH, which simulates multiple hard emissions.« less

Measurement of the underlying event in the Drell–Yan process in proton–proton collisions at $$\\sqrt{s} = 7~\\mbox{TeV}$$

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

Chatrchyan, S.; Khachatryan, V.; Sirunyan, A. M.

A measurement of the underlying event (UE) activity in proton-proton collisions at a center-of-mass energy of 7 TeV is performed using Drell--Yan events in a data sample corresponding to an integrated luminosity of 2.2 inverse femtobarns, collected by the CMS experiment at the LHC. The activity measured in the muonic final state (q q-bar to opposite-sign muons) is corrected to the particle level and compared with the predictions of various Monte Carlo generators and hadronization models. The dependence of the UE activity on the dimuon invariant mass is well described by PYTHIA and HERWIG++ tunes derived from the leading jet/trackmore » approach, illustrating the universality of the UE activity. The UE activity is observed to be independent of the dimuon invariant mass in the region above 40 GeV, while a slow increase is observed with increasing transverse momentum of the dimuon system. The dependence of the UE activity on the transverse momentum of the dimuon system is accurately described by MADGRAPH, which simulates multiple hard emissions.« less

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

Domènech, Guillem; Hiramatsu, Takashi; Lin, Chunshan

We consider a cosmological model in which the tensor mode becomes massive during inflation, and study the Cosmic Microwave Background (CMB) temperature and polarization bispectra arising from the mixing between the scalar mode and the massive tensor mode during inflation. The model assumes the existence of a preferred spatial frame during inflation. The local Lorentz invariance is already broken in cosmology due to the existence of a preferred rest frame. The existence of a preferred spatial frame further breaks the remaining local SO(3) invariance and in particular gives rise to a mass in the tensor mode. At linear perturbation level,more » we minimize our model so that the vector mode remains non-dynamical, while the scalar mode is the same as the one in single-field slow-roll inflation. At non-linear perturbation level, this inflationary massive graviton phase leads to a sizeable scalar-scalar-tensor coupling, much greater than the scalar-scalar-scalar one, as opposed to the conventional case. This scalar-scalar-tensor interaction imprints a scale dependent feature in the CMB temperature and polarization bispectra. Very intriguingly, we find a surprizing similarity between the predicted scale dependence and the scale-dependent non-Gaussianities at low multipoles hinted in the WMAP and Planck results.« less

TISK 1.0: An easy-to-use Python implementation of the time-invariant string kernel model of spoken word recognition.

PubMed

You, Heejo; Magnuson, James S

2018-06-01

This article describes a new Python distribution of TISK, the time-invariant string kernel model of spoken word recognition (Hannagan et al. in Frontiers in Psychology, 4, 563, 2013). TISK is an interactive-activation model similar to the TRACE model (McClelland & Elman in Cognitive Psychology, 18, 1-86, 1986), but TISK replaces most of TRACE's reduplicated, time-specific nodes with theoretically motivated time-invariant, open-diphone nodes. We discuss the utility of computational models as theory development tools, the relative merits of TISK as compared to other models, and the ways in which researchers might use this implementation to guide their own research and theory development. We describe a TISK model that includes features that facilitate in-line graphing of simulation results, integration with standard Python data formats, and graph and data export. The distribution can be downloaded from https://github.com/maglab-uconn/TISK1.0 .

Neural networks for data compression and invariant image recognition

NASA Technical Reports Server (NTRS)

Gardner, Sheldon

1989-01-01

An approach to invariant image recognition (I2R), based upon a model of biological vision in the mammalian visual system (MVS), is described. The complete I2R model incorporates several biologically inspired features: exponential mapping of retinal images, Gabor spatial filtering, and a neural network associative memory. In the I2R model, exponentially mapped retinal images are filtered by a hierarchical set of Gabor spatial filters (GSF) which provide compression of the information contained within a pixel-based image. A neural network associative memory (AM) is used to process the GSF coded images. We describe a 1-D shape function method for coding of scale and rotationally invariant shape information. This method reduces image shape information to a periodic waveform suitable for coding as an input vector to a neural network AM. The shape function method is suitable for near term applications on conventional computing architectures equipped with VLSI FFT chips to provide a rapid image search capability.

Equicontrollability and the model following problem

NASA Technical Reports Server (NTRS)

Curran, R. T.

1971-01-01

Equicontrollability and its application to the linear time-invariant model-following problem are discussed. The problem is presented in the form of two systems, the plant and the model. The requirement is to find a controller to apply to the plant so that the resultant compensated plant behaves, in an input-output sense, the same as the model. All systems are assumed to be linear and time-invariant. The basic approach is to find suitable equicontrollable realizations of the plant and model and to utilize feedback so as to produce a controller of minimal state dimension. The concept of equicontrollability is a generalization of control canonical (phase variable) form applied to multivariable systems. It allows one to visualize clearly the effects of feedback and to pinpoint the parameters of a multivariable system which are invariant under feedback. The basic contributions are the development of equicontrollable form; solution of the model-following problem in an entirely algorithmic way, suitable for computer programming; and resolution of questions on system decoupling.

Effect of strong disorder on three-dimensional chiral topological insulators: Phase diagrams, maps of the bulk invariant, and existence of topological extended bulk states

NASA Astrophysics Data System (ADS)

Song, Juntao; Fine, Carolyn; Prodan, Emil

2014-11-01

The effect of strong disorder on chiral-symmetric three-dimensional lattice models is investigated via analytical and numerical methods. The phase diagrams of the models are computed using the noncommutative winding number, as functions of disorder strength and model's parameters. The localized/delocalized characteristic of the quantum states is probed with level statistics analysis. Our study reconfirms the accurate quantization of the noncommutative winding number in the presence of strong disorder, and its effectiveness as a numerical tool. Extended bulk states are detected above and below the Fermi level, which are observed to undergo the so-called "levitation and pair annihilation" process when the system is driven through a topological transition. This suggests that the bulk invariant is carried by these extended states, in stark contrast with the one-dimensional case where the extended states are completely absent and the bulk invariant is carried by the localized states.

A novel rotational invariants target recognition method for rotating motion blurred images

NASA Astrophysics Data System (ADS)

Lan, Jinhui; Gong, Meiling; Dong, Mingwei; Zeng, Yiliang; Zhang, Yuzhen

2017-11-01

The imaging of the image sensor is blurred due to the rotational motion of the carrier and reducing the target recognition rate greatly. Although the traditional mode that restores the image first and then identifies the target can improve the recognition rate, it takes a long time to recognize. In order to solve this problem, a rotating fuzzy invariants extracted model was constructed that recognizes target directly. The model includes three metric layers. The object description capability of metric algorithms that contain gray value statistical algorithm, improved round projection transformation algorithm and rotation-convolution moment invariants in the three metric layers ranges from low to high, and the metric layer with the lowest description ability among them is as the input which can eliminate non pixel points of target region from degenerate image gradually. Experimental results show that the proposed model can improve the correct target recognition rate of blurred image and optimum allocation between the computational complexity and function of region.

Latent Computational Complexity of Symmetry-Protected Topological Order with Fractional Symmetry.

PubMed

Miller, Jacob; Miyake, Akimasa

2018-04-27

An emerging insight is that ground states of symmetry-protected topological orders (SPTOs) possess latent computational complexity in terms of their many-body entanglement. By introducing a fractional symmetry of SPTO, which requires the invariance under 3-colorable symmetries of a lattice, we prove that every renormalization fixed-point state of 2D (Z_{2})^{m} SPTO with fractional symmetry can be utilized for universal quantum computation using only Pauli measurements, as long as it belongs to a nontrivial 2D SPTO phase. Our infinite family of fixed-point states may serve as a base model to demonstrate the idea of a "quantum computational phase" of matter, whose states share universal computational complexity ubiquitously.

Deep Wavelet Scattering for Quantum Energy Regression

NASA Astrophysics Data System (ADS)

Hirn, Matthew

Physical functionals are usually computed as solutions of variational problems or from solutions of partial differential equations, which may require huge computations for complex systems. Quantum chemistry calculations of ground state molecular energies is such an example. Indeed, if x is a quantum molecular state, then the ground state energy E0 (x) is the minimum eigenvalue solution of the time independent Schrödinger Equation, which is computationally intensive for large systems. Machine learning algorithms do not simulate the physical system but estimate solutions by interpolating values provided by a training set of known examples {(xi ,E0 (xi) } i <= n . However, precise interpolations may require a number of examples that is exponential in the system dimension, and are thus intractable. This curse of dimensionality may be circumvented by computing interpolations in smaller approximation spaces, which take advantage of physical invariants. Linear regressions of E0 over a dictionary Φ ={ϕk } k compute an approximation E 0 as: E 0 (x) =∑kwkϕk (x) , where the weights {wk } k are selected to minimize the error between E0 and E 0 on the training set. The key to such a regression approach then lies in the design of the dictionary Φ. It must be intricate enough to capture the essential variability of E0 (x) over the molecular states x of interest, while simple enough so that evaluation of Φ (x) is significantly less intensive than a direct quantum mechanical computation (or approximation) of E0 (x) . In this talk we present a novel dictionary Φ for the regression of quantum mechanical energies based on the scattering transform of an intermediate, approximate electron density representation ρx of the state x. The scattering transform has the architecture of a deep convolutional network, composed of an alternating sequence of linear filters and nonlinear maps. Whereas in many deep learning tasks the linear filters are learned from the training data, here the physical properties of E0 (invariance to isometric transformations of the state x, stable to deformations of x) are leveraged to design a collection of linear filters ρx *ψλ for an appropriate wavelet ψ. These linear filters are composed with the nonlinear modulus operator, and the process is iterated upon so that at each layer stable, invariant features are extracted: ϕk (x) = ∥ | | ρx *ψλ1 | * ψλ2 | * ... *ψλm ∥ , k = (λ1 , ... ,λm) , m = 1 , 2 , ... The scattering transform thus encodes not only interactions at multiple scales (in the first layer, m = 1), but also features that encode complex phenomena resulting from a cascade of interactions across scales (in subsequent layers, m >= 2). Numerical experiments give state of the art accuracy over data bases of organic molecules, while theoretical results guarantee performance for the component of the ground state energy resulting from Coulombic interactions. Supported by the ERC InvariantClass 320959 Grant.

Phase-Locked Loop for Precisely Timed Acoustic Stimulation during Sleep

PubMed Central

Santostasi, Giovanni; Malkani, Roneil; Riedner, Brady; Bellesi, Michele; Tononi, Giulio; Paller, Ken A.; Zee, Phyllis C.

2016-01-01

Background A Brain-Computer Interface could potentially enhance the various benefits of sleep. New Method We describe a strategy for enhancing slow-wave sleep (SWS) by stimulating the sleeping brain with periodic acoustic stimuli that produce resonance in the form of enhanced slow-wave activity in the electroencephalogram (EEG). The system delivers each acoustic stimulus at a particular phase of an electrophysiological rhythm using a Phase-Locked Loop (PLL). Results The PLL is computationally economical and well suited to follow and predict the temporal behavior of the EEG during slow-wave sleep. Comparison with Existing Methods Acoustic stimulation methods may be able to enhance SWS without the risks inherent in electrical stimulation or pharmacological methods. The PLL method differs from other acoustic stimulation methods that are based on detecting a single slow wave rather than modeling slow-wave activity over an extended period of time. Conclusions By providing real-time estimates of the phase of ongoing EEG oscillations, the PLL can rapidly adjust to physiological changes, thus opening up new possibilities to study brain dynamics during sleep. Future application of these methods hold promise for enhancing sleep quality and associated daytime behavior and improving physiologic function. PMID:26617321

Multifractals embedded in short time series: An unbiased estimation of probability moment

NASA Astrophysics Data System (ADS)

Qiu, Lu; Yang, Tianguang; Yin, Yanhua; Gu, Changgui; Yang, Huijie

2016-12-01

An exact estimation of probability moments is the base for several essential concepts, such as the multifractals, the Tsallis entropy, and the transfer entropy. By means of approximation theory we propose a new method called factorial-moment-based estimation of probability moments. Theoretical prediction and computational results show that it can provide us an unbiased estimation of the probability moments of continuous order. Calculations on probability redistribution model verify that it can extract exactly multifractal behaviors from several hundred recordings. Its powerfulness in monitoring evolution of scaling behaviors is exemplified by two empirical cases, i.e., the gait time series for fast, normal, and slow trials of a healthy volunteer, and the closing price series for Shanghai stock market. By using short time series with several hundred lengths, a comparison with the well-established tools displays significant advantages of its performance over the other methods. The factorial-moment-based estimation can evaluate correctly the scaling behaviors in a scale range about three generations wider than the multifractal detrended fluctuation analysis and the basic estimation. The estimation of partition function given by the wavelet transform modulus maxima has unacceptable fluctuations. Besides the scaling invariance focused in the present paper, the proposed factorial moment of continuous order can find its various uses, such as finding nonextensive behaviors of a complex system and reconstructing the causality relationship network between elements of a complex system.

The role of pore geometry in single nanoparticle detection

DOE PAGES

Davenport, Matthew; Healy, Ken; Pevarnik, Matthew; ...

2012-08-22

In this study, we observe single nanoparticle translocation events via resistive pulse sensing using silicon nitride pores described by a range of lengths and diameters. Pores are prepared by focused ion beam milling in 50 nm-, 100 nm-, and 500 nm-thick silicon nitride membranes with diameters fabricated to accommodate spherical silica nanoparticles with sizes chosen to mimic that of virus particles. In this manner, we are able to characterize the role of pore geometry in three key components of the detection scheme, namely, event magnitude, event duration, and event frequency. We find that the electric field created by the appliedmore » voltage and the pore’s geometry is a critical factor. We develop approximations to describe this field, which are verified with computer simulations, and interactions between particles and this field. In so doing, we formulate what we believe to be the first approximation for the magnitude of ionic current blockage that explicitly addresses the invariance of access resistance of solid-state pores during particle translocation. These approximations also provide a suitable foundation for estimating the zeta potential of the particles and/or pore surface when studied in conjunction with event durations. We also verify that translocation achieved by electro-osmostic transport is an effective means of slowing translocation velocities of highly charged particles without compromising particle capture rate as compared to more traditional approaches based on electrophoretic transport.« less

A falsely fat curvaton with an observable running of the spectral tilt

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

Peloso, Marco; Sorbo, Lorenzo; Tasinato, Gianmassimo, E-mail: peloso@physics.umn.edu, E-mail: sorbo@physics.umass.edu, E-mail: gianmassimo.tasinato@port.ac.uk

2014-06-01

In slow roll inflation, the running of the spectral tilt is generically proportional to the square of the deviation from scale invariance, α{sub s}∝(n{sub s}−1){sup 2}, and is therefore currently undetectable. We present a mechanism able to generate a much larger running within slow roll. The mechanism is based on a curvaton field with a large mass term, and a time evolving normalization. This may happen for instance to the angular direction of a complex field in presence of an evolving radial direction. At the price of a single tuning between the mass term and the rate of change ofmore » the normalization, the curvaton can be made effectively light at the CMB scales, giving a spectral tilt in agreement with observations. The lightness is not preserved at later times, resulting in a detectable running of the spectral tilt. This mechanism shows that fields with a large mass term do not necessarily decouple from the inflationary physics, and provides a new tool for model building in inflation.« less

Some analyses of the chemistry and diffusion of SST exhaust materials during phase 3 of the wake period. [in lower stratosphere

NASA Technical Reports Server (NTRS)

Hilst, G. R.; Donaldson, C. D.; Contiliano, R. M.

1973-01-01

In the generally stably stratified lower stratosphere, SST exhaust plumes could spend a significant length of time in a relatively undispersed state. This effort has utilized invariant modeling techniques to simulate the separate and combined effects of atmospheric turbulence, turbulent diffusion, and chemical reactions of SST exhaust materials in the lower stratosphere. The primary results to date are: (1) The combination of relatively slow diffusive mixing and rapid chemical reactions during the Phase III wake period minimizes the effect of SST exhausts on O3 depletion by the so-called NOx catalytic cycle. While the SST-produced NO is substantially above background concentrations, it appears diffusive mixing of NO and O3 is simply too slow to produce the O3 depletions originally proposed. (2) The time required to dilute the SST exhaust plume may be a significant fraction of the total time these materials are resident in the lower stratosphere. If this is the case, then prior estimates of the environmental impact of these materials must be revised significantly downward.

Computer graphics application in the engineering design integration system

NASA Technical Reports Server (NTRS)

Glatt, C. R.; Abel, R. W.; Hirsch, G. N.; Alford, G. E.; Colquitt, W. N.; Stewart, W. A.

1975-01-01

The computer graphics aspect of the Engineering Design Integration (EDIN) system and its application to design problems were discussed. Three basic types of computer graphics may be used with the EDIN system for the evaluation of aerospace vehicles preliminary designs: offline graphics systems using vellum-inking or photographic processes, online graphics systems characterized by direct coupled low cost storage tube terminals with limited interactive capabilities, and a minicomputer based refresh terminal offering highly interactive capabilities. The offline line systems are characterized by high quality (resolution better than 0.254 mm) and slow turnaround (one to four days). The online systems are characterized by low cost, instant visualization of the computer results, slow line speed (300 BAUD), poor hard copy, and the early limitations on vector graphic input capabilities. The recent acquisition of the Adage 330 Graphic Display system has greatly enhanced the potential for interactive computer aided design.

Safe Computing: An Overview of Viruses.

ERIC Educational Resources Information Center

Wodarz, Nan

2001-01-01

A computer virus is a program that replicates itself, in conjunction with an additional program that can harm a computer system. Common viruses include boot-sector, macro, companion, overwriting, and multipartite. Viruses can be fast, slow, stealthy, and polymorphic. Anti-virus products are described. (MLH)

Technical notes and correspondence: Stochastic robustness of linear time-invariant control systems

NASA Technical Reports Server (NTRS)

Stengel, Robert F.; Ray, Laura R.

1991-01-01

A simple numerical procedure for estimating the stochastic robustness of a linear time-invariant system is described. Monte Carlo evaluations of the system's eigenvalues allows the probability of instability and the related stochastic root locus to be estimated. This analysis approach treats not only Gaussian parameter uncertainties but non-Gaussian cases, including uncertain-but-bounded variation. Confidence intervals for the scalar probability of instability address computational issues inherent in Monte Carlo simulation. Trivial extensions of the procedure admit consideration of alternate discriminants; thus, the probabilities that stipulated degrees of instability will be exceeded or that closed-loop roots will leave desirable regions can also be estimated. Results are particularly amenable to graphical presentation.

Cosmic Strings Stabilized by Quantum Fluctuations

NASA Astrophysics Data System (ADS)

Weigel, H.

2017-03-01

Fermion quantum corrections to the energy of cosmic strings are computed. A number of rather technical tools are needed to formulate this correction, and isospin and gauge invariance are employed to verify consistency of these tools. These corrections must also be included when computing the energy of strings that are charged by populating fermion bound states in its background. It is found that charged strings are dynamically stabilized in theories similar to the standard model of particle physics.

Time-Warp–Invariant Neuronal Processing

PubMed Central

Gütig, Robert; Sompolinsky, Haim

2009-01-01

Fluctuations in the temporal durations of sensory signals constitute a major source of variability within natural stimulus ensembles. The neuronal mechanisms through which sensory systems can stabilize perception against such fluctuations are largely unknown. An intriguing instantiation of such robustness occurs in human speech perception, which relies critically on temporal acoustic cues that are embedded in signals with highly variable duration. Across different instances of natural speech, auditory cues can undergo temporal warping that ranges from 2-fold compression to 2-fold dilation without significant perceptual impairment. Here, we report that time-warp–invariant neuronal processing can be subserved by the shunting action of synaptic conductances that automatically rescales the effective integration time of postsynaptic neurons. We propose a novel spike-based learning rule for synaptic conductances that adjusts the degree of synaptic shunting to the temporal processing requirements of a given task. Applying this general biophysical mechanism to the example of speech processing, we propose a neuronal network model for time-warp–invariant word discrimination and demonstrate its excellent performance on a standard benchmark speech-recognition task. Our results demonstrate the important functional role of synaptic conductances in spike-based neuronal information processing and learning. The biophysics of temporal integration at neuronal membranes can endow sensory pathways with powerful time-warp–invariant computational capabilities. PMID:19582146

Plasma clearance of neostigmine and pyridostigmine in the dog.

PubMed Central

Baker, P R; Calvey, T N; Chan, K; Macnee, C M; Taylor, K

1978-01-01

1 The pharmacokinetics of neostigmine and pyridostigmine was studied in conscious dogs by the use of a cross-over design. 2 Both neostigmine and pyridostigmine were cleared from plasma in a biexponential manner. 3 The apparent volume of distribution of pyridostigmine was invariably greater than that of neostigmine, and its fast disposition half-life was approximately three times longer. 4 The whole body clearance and the urinary elimination of pyridostigmine was approximately twice that of neostigmine. 5 The slow disposition half-life of pyridostigmine was approximately three times longer than that of neostigmine, suggesting that the longer duration of action of pyridostigmine is related to the differential clearance of the two quarternary amines from plasma. PMID:667495

Effect of grain size on the high temperature properties of B2 aluminides

NASA Technical Reports Server (NTRS)

Whittenberger, J. Daniel

1987-01-01

Measurements of the slow plastic flow behavior of cobalt, iron and nickel B2 crystal structure aluminides were conducted on materials fabricated by metallurical techniques. Due to this processing, the aluminides invariably had small equiaxed grains, ranging in size from about 3 to 60 microns in diameter. Grain size was dependent on the extrusion temperature used for powder consolidation, and it proved to be remarkably stable at elevated temperatures. Mechanical properties of all three aluminides were determined via constant velocity compression testing in air between 1000 and 1400 K at strain rates ranging from approx. 10 to the minus 3 power to 10 to the minus 7 power s (-1).

Computer Science and the Liberal Arts

ERIC Educational Resources Information Center

Shannon, Christine

2010-01-01

Computer science and the liberal arts have much to offer each other. Yet liberal arts colleges, in particular, have been slow to recognize the opportunity that the study of computer science provides for achieving the goals of a liberal education. After the precipitous drop in computer science enrollments during the first decade of this century,…

Enhanced Image-Aided Navigation Algorithm with Automatic Calibration and Affine Distortion Prediction

DTIC Science & Technology

2012-03-01

Lowe, David G. “Distinctive Image Features from Scale-Invariant Keypoints”. International Journal of Computer Vision, 2004. 13. Maybeck, Peter S...Fairfax Drive - 3rd Floor Arlington,VA 22203 Dr. Stefanie Tompkins ; (703)248–1540; Stefanie.Tompkins@darpa.mil DARPA Distribution A. Approved for Public

Teaching Quality Object-Oriented Programming

ERIC Educational Resources Information Center

Feldman, Yishai A.

2005-01-01

Computer science students need to learn how to write high-quality software. An important methodology for achieving quality is design-by-contract, in which code is developed together with its specification, which is given as class invariants and method pre- and postconditions. This paper describes practical experience in teaching design-by-contract…

Models and Methodologies for Multimedia Courseware Production.

ERIC Educational Resources Information Center

Barker, Philip; Giller, Susan

Many new technologies are now available for delivering and/or providing access to computer-based learning (CBL) materials. These technologies vary in sophistication in many important ways, depending upon the bandwidth that they provide, the interactivity that they offer and the types of end-user connectivity that they support.Invariably,…

A Tensor-Train accelerated solver for integral equations in complex geometries

NASA Astrophysics Data System (ADS)

Corona, Eduardo; Rahimian, Abtin; Zorin, Denis

2017-04-01

We present a framework using the Quantized Tensor Train (QTT) decomposition to accurately and efficiently solve volume and boundary integral equations in three dimensions. We describe how the QTT decomposition can be used as a hierarchical compression and inversion scheme for matrices arising from the discretization of integral equations. For a broad range of problems, computational and storage costs of the inversion scheme are extremely modest O (log ⁡ N) and once the inverse is computed, it can be applied in O (Nlog ⁡ N) . We analyze the QTT ranks for hierarchically low rank matrices and discuss its relationship to commonly used hierarchical compression techniques such as FMM and HSS. We prove that the QTT ranks are bounded for translation-invariant systems and argue that this behavior extends to non-translation invariant volume and boundary integrals. For volume integrals, the QTT decomposition provides an efficient direct solver requiring significantly less memory compared to other fast direct solvers. We present results demonstrating the remarkable performance of the QTT-based solver when applied to both translation and non-translation invariant volume integrals in 3D. For boundary integral equations, we demonstrate that using a QTT decomposition to construct preconditioners for a Krylov subspace method leads to an efficient and robust solver with a small memory footprint. We test the QTT preconditioners in the iterative solution of an exterior elliptic boundary value problem (Laplace) formulated as a boundary integral equation in complex, multiply connected geometries.

Application of symbolic computations to the constitutive modeling of structural materials

NASA Technical Reports Server (NTRS)

Arnold, Steven M.; Tan, H. Q.; Dong, X.

1990-01-01

In applications involving elevated temperatures, the derivation of mathematical expressions (constitutive equations) describing the material behavior can be quite time consuming, involved and error-prone. Therefore intelligent application of symbolic systems to faciliate this tedious process can be of significant benefit. Presented here is a problem oriented, self contained symbolic expert system, named SDICE, which is capable of efficiently deriving potential based constitutive models in analytical form. This package, running under DOE MACSYMA, has the following features: (1) potential differentiation (chain rule), (2) tensor computations (utilizing index notation) including both algebraic and calculus; (3) efficient solution of sparse systems of equations; (4) automatic expression substitution and simplification; (5) back substitution of invariant and tensorial relations; (6) the ability to form the Jacobian and Hessian matrix; and (7) a relational data base. Limited aspects of invariant theory were also incorporated into SDICE due to the utilization of potentials as a starting point and the desire for these potentials to be frame invariant (objective). The uniqueness of SDICE resides in its ability to manipulate expressions in a general yet pre-defined order and simplify expressions so as to limit expression growth. Results are displayed, when applicable, utilizing index notation. SDICE was designed to aid and complement the human constitutive model developer. A number of examples are utilized to illustrate the various features contained within SDICE. It is expected that this symbolic package can and will provide a significant incentive to the development of new constitutive theories.

Chandrasekhar-type algorithms for fast recursive estimation in linear systems with constant parameters

NASA Technical Reports Server (NTRS)

Choudhury, A. K.; Djalali, M.

1975-01-01

In this recursive method proposed, the gain matrix for the Kalman filter and the convariance of the state vector are computed not via the Riccati equation, but from certain other equations. These differential equations are of Chandrasekhar-type. The 'invariant imbedding' idea resulted in the reduction of the basic boundary value problem of transport theory to an equivalent initial value system, a significant computational advance. Initial value experience showed that there is some computational savings in the method and the loss of positive definiteness of the covariance matrix is less vulnerable.

Quantum Computing Architectural Design

NASA Astrophysics Data System (ADS)

West, Jacob; Simms, Geoffrey; Gyure, Mark

2006-03-01

Large scale quantum computers will invariably require scalable architectures in addition to high fidelity gate operations. Quantum computing architectural design (QCAD) addresses the problems of actually implementing fault-tolerant algorithms given physical and architectural constraints beyond those of basic gate-level fidelity. Here we introduce a unified framework for QCAD that enables the scientist to study the impact of varying error correction schemes, architectural parameters including layout and scheduling, and physical operations native to a given architecture. Our software package, aptly named QCAD, provides compilation, manipulation/transformation, multi-paradigm simulation, and visualization tools. We demonstrate various features of the QCAD software package through several examples.

Short Tree, Long Tree, Right Tree, Wrong Tree: New Acquisition Bias Corrections for Inferring SNP Phylogenies

PubMed Central

Leaché, Adam D.; Banbury, Barbara L.; Felsenstein, Joseph; de Oca, Adrián nieto-Montes; Stamatakis, Alexandros

2015-01-01

Single nucleotide polymorphisms (SNPs) are useful markers for phylogenetic studies owing in part to their ubiquity throughout the genome and ease of collection. Restriction site associated DNA sequencing (RADseq) methods are becoming increasingly popular for SNP data collection, but an assessment of the best practises for using these data in phylogenetics is lacking. We use computer simulations, and new double digest RADseq (ddRADseq) data for the lizard family Phrynosomatidae, to investigate the accuracy of RAD loci for phylogenetic inference. We compare the two primary ways RAD loci are used during phylogenetic analysis, including the analysis of full sequences (i.e., SNPs together with invariant sites), or the analysis of SNPs on their own after excluding invariant sites. We find that using full sequences rather than just SNPs is preferable from the perspectives of branch length and topological accuracy, but not of computational time. We introduce two new acquisition bias corrections for dealing with alignments composed exclusively of SNPs, a conditional likelihood method and a reconstituted DNA approach. The conditional likelihood method conditions on the presence of variable characters only (the number of invariant sites that are unsampled but known to exist is not considered), while the reconstituted DNA approach requires the user to specify the exact number of unsampled invariant sites prior to the analysis. Under simulation, branch length biases increase with the amount of missing data for both acquisition bias correction methods, but branch length accuracy is much improved in the reconstituted DNA approach compared to the conditional likelihood approach. Phylogenetic analyses of the empirical data using concatenation or a coalescent-based species tree approach provide strong support for many of the accepted relationships among phrynosomatid lizards, suggesting that RAD loci contain useful phylogenetic signal across a range of divergence times despite the presence of missing data. Phylogenetic analysis of RAD loci requires careful attention to model assumptions, especially if downstream analyses depend on branch lengths. PMID:26227865

Low-energy transfers to cislunar periodic orbits visiting triangular libration points

NASA Astrophysics Data System (ADS)

Lei, Hanlun; Xu, Bo

2018-01-01

This paper investigates the cislunar periodic orbits that pass through triangular libration points of the Earth-Moon system and studies the techniques on design low-energy transfer trajectories. In order to compute periodic orbits, families of impulsive transfers between triangular libration points are taken to generate the initial guesses of periodic orbits, and multiple shooting techniques are applied to solving the problem. Then, varieties of periodic orbits in cislunar space are obtained, and stability analysis shows that the majority of them are unstable. Among these periodic orbits, an unstable periodic orbit in near 3:2 resonance with the Moon is taken as the nominal orbit of an assumed mission. As the stable manifolds of the target orbit could approach the Moon, low-energy transfer trajectories can be designed by combining lunar gravity assist with the invariant manifold structure of the target orbit. In practice, both the natural and perturbed invariant manifolds are considered to obtain the low-energy transfers, which are further refined to the Sun-perturbed Earth-Moon system. Results indicate that (a) compared to the case of natural invariant manifolds, the optimal transfers using perturbed invariant manifolds could reduce flight time at least 50 days, (b) compared to the cheapest direct transfer, the optimal low-energy transfer obtained by combining lunar gravity assist and invariant manifolds could save on-board fuel consumption more than 200 m/s, and (c) by taking advantage of the gravitational perturbation of the Sun, the low-energy transfers could save more fuel consumption than the corresponding ones obtained in the Earth-Moon system.

Frequency domain system identification of helicopter rotor dynamics incorporating models with time periodic coefficients

NASA Astrophysics Data System (ADS)

Hwang, Sunghwan

1997-08-01

One of the most prominent features of helicopter rotor dynamics in forward flight is the periodic coefficients in the equations of motion introduced by the rotor rotation. The frequency response characteristics of such a linear time periodic system exhibits sideband behavior, which is not the case for linear time invariant systems. Therefore, a frequency domain identification methodology for linear systems with time periodic coefficients was developed, because the linear time invariant theory cannot account for sideband behavior. The modulated complex Fourier series was introduced to eliminate the smearing effect of Fourier series expansions of exponentially modulated periodic signals. A system identification theory was then developed using modulated complex Fourier series expansion. Correlation and spectral density functions were derived using the modulated complex Fourier series expansion for linear time periodic systems. Expressions of the identified harmonic transfer function were then formulated using the spectral density functions both with and without additive noise processes at input and/or output. A procedure was developed to identify parameters of a model to match the frequency response characteristics between measured and estimated harmonic transfer functions by minimizing an objective function defined in terms of the trace of the squared frequency response error matrix. Feasibility was demonstrated by the identification of the harmonic transfer function and parameters for helicopter rigid blade flapping dynamics in forward flight. This technique is envisioned to satisfy the needs of system identification in the rotating frame, especially in the context of individual blade control. The technique was applied to the coupled flap-lag-inflow dynamics of a rigid blade excited by an active pitch link. The linear time periodic technique results were compared with the linear time invariant technique results. Also, the effect of noise processes and initial parameter guess on the identification procedure were investigated. To study the effect of elastic modes, a rigid blade with a trailing edge flap excited by a smart actuator was selected and system parameters were successfully identified, but with some expense of computational storage and time. Conclusively, the linear time periodic technique substantially improved the identified parameter accuracy compared to the linear time invariant technique. Also, the linear time periodic technique was robust to noises and initial guess of parameters. However, an elastic mode of higher frequency relative to the system pumping frequency tends to increase the computer storage requirement and computing time.

Making Cloud Computing Available For Researchers and Innovators (Invited)

NASA Astrophysics Data System (ADS)

Winsor, R.

2010-12-01

High Performance Computing (HPC) facilities exist in most academic institutions but are almost invariably over-subscribed. Access is allocated based on academic merit, the only practical method of assigning valuable finite compute resources. Cloud computing on the other hand, and particularly commercial clouds, draw flexibly on an almost limitless resource as long as the user has sufficient funds to pay the bill. How can the commercial cloud model be applied to scientific computing? Is there a case to be made for a publicly available research cloud and how would it be structured? This talk will explore these themes and describe how Cybera, a not-for-profit non-governmental organization in Alberta Canada, aims to leverage its high speed research and education network to provide cloud computing facilities for a much wider user base.

Symmetry breaking, mixing, instability, and low-frequency variability in a minimal Lorenz-like system.

PubMed

Lucarini, Valerio; Fraedrich, Klaus

2009-08-01

Starting from the classical Saltzman two-dimensional convection equations, we derive via a severe spectral truncation a minimal 10 ODE system which includes the thermal effect of viscous dissipation. Neglecting this process leads to a dynamical system which includes a decoupled generalized Lorenz system. The consideration of this process breaks an important symmetry and couples the dynamics of fast and slow variables, with the ensuing modifications to the structural properties of the attractor and of the spectral features. When the relevant nondimensional number (Eckert number Ec) is different from zero, an additional time scale of O(Ec(-1)) is introduced in the system, as shown with standard multiscale analysis and made clear by several numerical evidences. Moreover, the system is ergodic and hyperbolic, the slow variables feature long-term memory with 1/f(3/2) power spectra, and the fast variables feature amplitude modulation. Increasing the strength of the thermal-viscous feedback has a stabilizing effect, as both the metric entropy and the Kaplan-Yorke attractor dimension decrease monotonically with Ec. The analyzed system features very rich dynamics: it overcomes some of the limitations of the Lorenz system and might have prototypical value in relevant processes in complex systems dynamics, such as the interaction between slow and fast variables, the presence of long-term memory, and the associated extreme value statistics. This analysis shows how neglecting the coupling of slow and fast variables only on the basis of scale analysis can be catastrophic. In fact, this leads to spurious invariances that affect essential dynamical properties (ergodicity, hyperbolicity) and that cause the model losing ability in describing intrinsically multiscale processes.

Modeling place field activity with hierarchical slow feature analysis

PubMed Central

Schönfeld, Fabian; Wiskott, Laurenz

2015-01-01

What are the computational laws of hippocampal activity? In this paper we argue for the slowness principle as a fundamental processing paradigm behind hippocampal place cell firing. We present six different studies from the experimental literature, performed with real-life rats, that we replicated in computer simulations. Each of the chosen studies allows rodents to develop stable place fields and then examines a distinct property of the established spatial encoding: adaptation to cue relocation and removal; directional dependent firing in the linear track and open field; and morphing and scaling the environment itself. Simulations are based on a hierarchical Slow Feature Analysis (SFA) network topped by a principal component analysis (ICA) output layer. The slowness principle is shown to account for the main findings of the presented experimental studies. The SFA network generates its responses using raw visual input only, which adds to its biological plausibility but requires experiments performed in light conditions. Future iterations of the model will thus have to incorporate additional information, such as path integration and grid cell activity, in order to be able to also replicate studies that take place during darkness. PMID:26052279

Performance evaluation of digital phase-locked loops for advanced deep space transponders

NASA Technical Reports Server (NTRS)

Nguyen, T. M.; Hinedi, S. M.; Yeh, H.-G.; Kyriacou, C.

1994-01-01

The performances of the digital phase-locked loops (DPLL's) for the advanced deep-space transponders (ADT's) are investigated. DPLL's considered in this article are derived from the analog phase-locked loop, which is currently employed by the NASA standard deep space transponder, using S-domain to Z-domain mapping techniques. Three mappings are used to develop digital approximations of the standard deep space analog phase-locked loop, namely the bilinear transformation (BT), impulse invariant transformation (IIT), and step invariant transformation (SIT) techniques. The performance in terms of the closed loop phase and magnitude responses, carrier tracking jitter, and response of the loop to the phase offset (the difference between in incoming phase and reference phase) is evaluated for each digital approximation. Theoretical results of the carrier tracking jitter for command-on and command-off cases are then validated by computer simulation. Both theoretical and computer simulation results show that at high sampling frequency, the DPLL's approximated by all three transformations have the same tracking jitter. However, at low sampling frequency, the digital approximation using BT outperforms the others. The minimum sampling frequency for adequate tracking performance is determined for each digital approximation of the analog loop. In addition, computer simulation shows that the DPLL developed by BT provides faster response to the phase offset than IIT and SIT.

Adaptive surrogate model based multi-objective transfer trajectory optimization between different libration points

NASA Astrophysics Data System (ADS)

Peng, Haijun; Wang, Wei

2016-10-01

An adaptive surrogate model-based multi-objective optimization strategy that combines the benefits of invariant manifolds and low-thrust control toward developing a low-computational-cost transfer trajectory between libration orbits around the L1 and L2 libration points in the Sun-Earth system has been proposed in this paper. A new structure for a multi-objective transfer trajectory optimization model that divides the transfer trajectory into several segments and gives the dominations for invariant manifolds and low-thrust control in different segments has been established. To reduce the computational cost of multi-objective transfer trajectory optimization, a mixed sampling strategy-based adaptive surrogate model has been proposed. Numerical simulations show that the results obtained from the adaptive surrogate-based multi-objective optimization are in agreement with the results obtained using direct multi-objective optimization methods, and the computational workload of the adaptive surrogate-based multi-objective optimization is only approximately 10% of that of direct multi-objective optimization. Furthermore, the generating efficiency of the Pareto points of the adaptive surrogate-based multi-objective optimization is approximately 8 times that of the direct multi-objective optimization. Therefore, the proposed adaptive surrogate-based multi-objective optimization provides obvious advantages over direct multi-objective optimization methods.

Pose Invariant Face Recognition Based on Hybrid Dominant Frequency Features

NASA Astrophysics Data System (ADS)

Wijaya, I. Gede Pasek Suta; Uchimura, Keiichi; Hu, Zhencheng

Face recognition is one of the most active research areas in pattern recognition, not only because the face is a human biometric characteristics of human being but also because there are many potential applications of the face recognition which range from human-computer interactions to authentication, security, and surveillance. This paper presents an approach to pose invariant human face image recognition. The proposed scheme is based on the analysis of discrete cosine transforms (DCT) and discrete wavelet transforms (DWT) of face images. From both the DCT and DWT domain coefficients, which describe the facial information, we build compact and meaningful features vector, using simple statistical measures and quantization. This feature vector is called as the hybrid dominant frequency features. Then, we apply a combination of the L2 and Lq metric to classify the hybrid dominant frequency features to a person's class. The aim of the proposed system is to overcome the high memory space requirement, the high computational load, and the retraining problems of previous methods. The proposed system is tested using several face databases and the experimental results are compared to a well-known Eigenface method. The proposed method shows good performance, robustness, stability, and accuracy without requiring geometrical normalization. Furthermore, the purposed method has low computational cost, requires little memory space, and can overcome retraining problem.

Phase-Space Detection of Cyber Events

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

Hernandez Jimenez, Jarilyn M; Ferber, Aaron E; Prowell, Stacy J

Energy Delivery Systems (EDS) are a network of processes that produce, transfer and distribute energy. EDS are increasingly dependent on networked computing assets, as are many Industrial Control Systems. Consequently, cyber-attacks pose a real and pertinent threat, as evidenced by Stuxnet, Shamoon and Dragonfly. Hence, there is a critical need for novel methods to detect, prevent, and mitigate effects of such attacks. To detect cyber-attacks in EDS, we developed a framework for gathering and analyzing timing data that involves establishing a baseline execution profile and then capturing the effect of perturbations in the state from injecting various malware. The datamore » analysis was based on nonlinear dynamics and graph theory to improve detection of anomalous events in cyber applications. The goal was the extraction of changing dynamics or anomalous activity in the underlying computer system. Takens' theorem in nonlinear dynamics allows reconstruction of topologically invariant, time-delay-embedding states from the computer data in a sufficiently high-dimensional space. The resultant dynamical states were nodes, and the state-to-state transitions were links in a mathematical graph. Alternatively, sequential tabulation of executing instructions provides the nodes with corresponding instruction-to-instruction links. Graph theorems guarantee graph-invariant measures to quantify the dynamical changes in the running applications. Results showed a successful detection of cyber events.« less

Statistical Systems with Z

NASA Astrophysics Data System (ADS)

William, Peter

In this dissertation several two dimensional statistical systems exhibiting discrete Z(n) symmetries are studied. For this purpose a newly developed algorithm to compute the partition function of these models exactly is utilized. The zeros of the partition function are examined in order to obtain information about the observable quantities at the critical point. This occurs in the form of critical exponents of the order parameters which characterize phenomena at the critical point. The correlation length exponent is found to agree very well with those computed from strong coupling expansions for the mass gap and with Monte Carlo results. In Feynman's path integral formalism the partition function of a statistical system can be related to the vacuum expectation value of the time ordered product of the observable quantities of the corresponding field theoretic model. Hence a generalization of ordinary scale invariance in the form of conformal invariance is focussed upon. This principle is very suitably applicable, in the case of two dimensional statistical models undergoing second order phase transitions at criticality. The conformal anomaly specifies the universality class to which these models belong. From an evaluation of the partition function, the free energy at criticality is computed, to determine the conformal anomaly of these models. The conformal anomaly for all the models considered here are in good agreement with the predicted values.

Computer-Based Education (CBE): Tomorrow's Traditional System.

ERIC Educational Resources Information Center

Rizza, Peter J., Jr.

1981-01-01

Examines the role of computer technology in education; discusses reasons for the slow evolution of Computer-Based Education (CBE); explores educational areas in which CBE can be used; presents barriers to widespread use of CBE; and describes the responsibilities of education, government, and business in supporting technology-oriented education.…

Theory and computation of non-RRKM lifetime distributions and rates in chemical systems with three or more degrees of freedom

NASA Astrophysics Data System (ADS)

Gabern, Frederic; Koon, Wang S.; Marsden, Jerrold E.; Ross, Shane D.

2005-11-01

The computation, starting from basic principles, of chemical reaction rates in realistic systems (with three or more degrees of freedom) has been a longstanding goal of the chemistry community. Our current work, which merges tube dynamics with Monte Carlo methods provides some key theoretical and computational tools for achieving this goal. We use basic tools of dynamical systems theory, merging the ideas of Koon et al. [W.S. Koon, M.W. Lo, J.E. Marsden, S.D. Ross, Heteroclinic connections between periodic orbits and resonance transitions in celestial mechanics, Chaos 10 (2000) 427-469.] and De Leon et al. [N. De Leon, M.A. Mehta, R.Q. Topper, Cylindrical manifolds in phase space as mediators of chemical reaction dynamics and kinetics. I. Theory, J. Chem. Phys. 94 (1991) 8310-8328.], particularly the use of invariant manifold tubes that mediate the reaction, into a tool for the computation of lifetime distributions and rates of chemical reactions and scattering phenomena, even in systems that exhibit non-statistical behavior. Previously, the main problem with the application of tube dynamics has been with the computation of volumes in phase spaces of high dimension. The present work provides a starting point for overcoming this hurdle with some new ideas and implements them numerically. Specifically, an algorithm that uses tube dynamics to provide the initial bounding box for a Monte Carlo volume determination is used. The combination of a fine scale method for determining the phase space structure (invariant manifold theory) with statistical methods for volume computations (Monte Carlo) is the main contribution of this paper. The methodology is applied here to a three degree of freedom model problem and may be useful for higher degree of freedom systems as well.

Weighted fusion of depth and inertial data to improve view invariance for real-time human action recognition

NASA Astrophysics Data System (ADS)

Chen, Chen; Hao, Huiyan; Jafari, Roozbeh; Kehtarnavaz, Nasser

2017-05-01

This paper presents an extension to our previously developed fusion framework [10] involving a depth camera and an inertial sensor in order to improve its view invariance aspect for real-time human action recognition applications. A computationally efficient view estimation based on skeleton joints is considered in order to select the most relevant depth training data when recognizing test samples. Two collaborative representation classifiers, one for depth features and one for inertial features, are appropriately weighted to generate a decision making probability. The experimental results applied to a multi-view human action dataset show that this weighted extension improves the recognition performance by about 5% over equally weighted fusion deployed in our previous fusion framework.

Finsler-type modification of the Coulomb law

NASA Astrophysics Data System (ADS)

Itin, Yakov; Lämmerzahl, Claus; Perlick, Volker

2014-12-01

Finsler geometry is a natural generalization of pseudo-Riemannian geometry. It can be motivated e.g. by a modified version of the Ehlers-Pirani-Schild axiomatic approach to space-time theory. Also, some scenarios of quantum gravity suggest a modified dispersion relation which could be phrased in terms of Finsler geometry. On a Finslerian space-time, the universality of free fall is still satisfied but local Lorentz invariance is violated in a way not covered by standard Lorentz invariance violation schemes. In this paper we consider a Finslerian modification of Maxwell's equations. The corrections to the Coulomb potential and to the hydrogen energy levels are computed. We find that the Finsler metric corrections yield a splitting of the energy levels. Experimental data provide bounds for the Finsler parameters.

Optical ranked-order filtering using threshold decomposition

DOEpatents

Allebach, Jan P.; Ochoa, Ellen; Sweeney, Donald W.

1990-01-01

A hybrid optical/electronic system performs median filtering and related ranked-order operations using threshold decomposition to encode the image. Threshold decomposition transforms the nonlinear neighborhood ranking operation into a linear space-invariant filtering step followed by a point-to-point threshold comparison step. Spatial multiplexing allows parallel processing of all the threshold components as well as recombination by a second linear, space-invariant filtering step. An incoherent optical correlation system performs the linear filtering, using a magneto-optic spatial light modulator as the input device and a computer-generated hologram in the filter plane. Thresholding is done electronically. By adjusting the value of the threshold, the same architecture is used to perform median, minimum, and maximum filtering of images. A totally optical system is also disclosed.

On the Benefits of Multimodal Annotations for Vocabulary Uptake from Reading

ERIC Educational Resources Information Center

Boers, Frank; Warren, Paul; Grimshaw, Gina; Siyanova-Chanturia, Anna

2017-01-01

Several research articles published in the realm of Computer Assisted Language Learning (CALL) have reported evidence of the benefits of multimodal annotations, i.e. the provision of pictorial as well as verbal clarifications, for vocabulary uptake from reading. Almost invariably, these publications account for the observed benefits with reference…

Invariant Geometric Evolutions of Surfaces and Volumetric Smoothing

DTIC Science & Technology

1994-04-15

1991. [40] D. G. Lowe, "Organization of smooth image curves at multiple scales," International Journal of Computer Vision 3, pp. 119-130, 1989. [41] E ... Lutwak , "On some affine isoperimetric inequalities," J. Differential Geometry 23, pp. 1-13, 1986. [42] F. Mokhatarian and A. Mackworth, "A theory of

Exotic Gauge Bosons in the 331 Model

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

Romero, D.; Ravinez, O.; Diaz, H.

We analize the bosonic sector of the 331 model which contains exotic leptons, quarks and bosons (E,J,U,V) in order to satisfy the weak gauge SU(3){sub L} invariance. We develop the Feynman rules of the entire kinetic bosonic sector which will let us to compute some of the Z(0)' decays modes.

Enhancing Self-Motivation in Learning Programming Using Game-Based Simulation and Metrics

ERIC Educational Resources Information Center

Jiau, H. C.; Chen, J. C.; Ssu, Kuo-Feng

2009-01-01

Game-based assignments typically form an integral component of computer programming courses. The effectiveness of the assignments in motivating students to carry out repetitive programming tasks is somewhat limited since their outcomes are invariably limited to a simple win or loss scenario. Accordingly, this paper develops a simulation…

Efficient and robust model-to-image alignment using 3D scale-invariant features.

PubMed

Toews, Matthew; Wells, William M

2013-04-01

This paper presents feature-based alignment (FBA), a general method for efficient and robust model-to-image alignment. Volumetric images, e.g. CT scans of the human body, are modeled probabilistically as a collage of 3D scale-invariant image features within a normalized reference space. Features are incorporated as a latent random variable and marginalized out in computing a maximum a posteriori alignment solution. The model is learned from features extracted in pre-aligned training images, then fit to features extracted from a new image to identify a globally optimal locally linear alignment solution. Novel techniques are presented for determining local feature orientation and efficiently encoding feature intensity in 3D. Experiments involving difficult magnetic resonance (MR) images of the human brain demonstrate FBA achieves alignment accuracy similar to widely-used registration methods, while requiring a fraction of the memory and computation resources and offering a more robust, globally optimal solution. Experiments on CT human body scans demonstrate FBA as an effective system for automatic human body alignment where other alignment methods break down. Copyright © 2012 Elsevier B.V. All rights reserved.

Template match using local feature with view invariance

NASA Astrophysics Data System (ADS)

Lu, Cen; Zhou, Gang

2013-10-01

Matching the template image in the target image is the fundamental task in the field of computer vision. Aiming at the deficiency in the traditional image matching methods and inaccurate matching in scene image with rotation, illumination and view changing, a novel matching algorithm using local features are proposed in this paper. The local histograms of the edge pixels (LHoE) are extracted as the invariable feature to resist view and brightness changing. The merits of the LHoE is that the edge points have been little affected with view changing, and the LHoE can resist not only illumination variance but also the polution of noise. For the process of matching are excuded only on the edge points, the computation burden are highly reduced. Additionally, our approach is conceptually simple, easy to implement and do not need the training phase. The view changing can be considered as the combination of rotation, illumination and shear transformation. Experimental results on simulated and real data demonstrated that the proposed approach is superior to NCC(Normalized cross-correlation) and Histogram-based methods with view changing.

Efficient and Robust Model-to-Image Alignment using 3D Scale-Invariant Features

PubMed Central

Toews, Matthew; Wells, William M.

2013-01-01

This paper presents feature-based alignment (FBA), a general method for efficient and robust model-to-image alignment. Volumetric images, e.g. CT scans of the human body, are modeled probabilistically as a collage of 3D scale-invariant image features within a normalized reference space. Features are incorporated as a latent random variable and marginalized out in computing a maximum a-posteriori alignment solution. The model is learned from features extracted in pre-aligned training images, then fit to features extracted from a new image to identify a globally optimal locally linear alignment solution. Novel techniques are presented for determining local feature orientation and efficiently encoding feature intensity in 3D. Experiments involving difficult magnetic resonance (MR) images of the human brain demonstrate FBA achieves alignment accuracy similar to widely-used registration methods, while requiring a fraction of the memory and computation resources and offering a more robust, globally optimal solution. Experiments on CT human body scans demonstrate FBA as an effective system for automatic human body alignment where other alignment methods break down. PMID:23265799

Limit cycles and conformal invariance

NASA Astrophysics Data System (ADS)

Fortin, Jean-François; Grinstein, Benjamín; Stergiou, Andreas

2013-01-01

There is a widely held belief that conformal field theories (CFTs) require zero beta functions. Nevertheless, the work of Jack and Osborn implies that the beta functions are not actually the quantites that decide conformality, but until recently no such behavior had been exhibited. Our recent work has led to the discovery of CFTs with nonzero beta functions, more precisely CFTs that live on recurrent trajectories, e.g., limit cycles, of the beta-function vector field. To demonstrate this we study the S function of Jack and Osborn. We use Weyl consistency conditions to show that it vanishes at fixed points and agrees with the generator Q of limit cycles on them. Moreover, we compute S to third order in perturbation theory, and explicitly verify that it agrees with our previous determinations of Q. A byproduct of our analysis is that, in perturbation theory, unitarity and scale invariance imply conformal invariance in four-dimensional quantum field theories. Finally, we study some properties of these new, "cyclic" CFTs, and point out that the a-theorem still governs the asymptotic behavior of renormalization-group flows.

A 2-categorical state sum model

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

Baratin, Aristide, E-mail: abaratin@uwaterloo.ca; Freidel, Laurent, E-mail: lfreidel@perimeterinstitute.ca

It has long been argued that higher categories provide the proper algebraic structure underlying state sum invariants of 4-manifolds. This idea has been refined recently, by proposing to use 2-groups and their representations as specific examples of 2-categories. The challenge has been to make these proposals fully explicit. Here, we give a concrete realization of this program. Building upon our earlier work with Baez and Wise on the representation theory of 2-groups, we construct a four-dimensional state sum model based on a categorified version of the Euclidean group. We define and explicitly compute the simplex weights, which may be viewedmore » a categorified analogue of Racah-Wigner 6j-symbols. These weights solve a hexagon equation that encodes the formal invariance of the state sum under the Pachner moves of the triangulation. This result unravels the combinatorial formulation of the Feynman amplitudes of quantum field theory on flat spacetime proposed in A. Baratin and L. Freidel [Classical Quantum Gravity 24, 2027–2060 (2007)] which was shown to lead after gauge-fixing to Korepanov’s invariant of 4-manifolds.« less

Shift-, rotation-, and scale-invariant shape recognition system using an optical Hough transform

NASA Astrophysics Data System (ADS)

Schmid, Volker R.; Bader, Gerhard; Lueder, Ernst H.

1998-02-01

We present a hybrid shape recognition system with an optical Hough transform processor. The features of the Hough space offer a separate cancellation of distortions caused by translations and rotations. Scale invariance is also provided by suitable normalization. The proposed system extends the capabilities of Hough transform based detection from only straight lines to areas bounded by edges. A very compact optical design is achieved by a microlens array processor accepting incoherent light as direct optical input and realizing the computationally expensive connections massively parallel. Our newly developed algorithm extracts rotation and translation invariant normalized patterns of bright spots on a 2D grid. A neural network classifier maps the 2D features via a nonlinear hidden layer onto the classification output vector. We propose initialization of the connection weights according to regions of activity specifically assigned to each neuron in the hidden layer using a competitive network. The presented system is designed for industry inspection applications. Presently we have demonstrated detection of six different machined parts in real-time. Our method yields very promising detection results of more than 96% correctly classified parts.

Left-invariant Einstein metrics on S3 ×S3

NASA Astrophysics Data System (ADS)

Belgun, Florin; Cortés, Vicente; Haupt, Alexander S.; Lindemann, David

2018-06-01

The classification of homogeneous compact Einstein manifolds in dimension six is an open problem. We consider the remaining open case, namely left-invariant Einstein metrics g on G = SU(2) × SU(2) =S3 ×S3. Einstein metrics are critical points of the total scalar curvature functional for fixed volume. The scalar curvature S of a left-invariant metric g is constant and can be expressed as a rational function in the parameters determining the metric. The critical points of S, subject to the volume constraint, are given by the zero locus of a system of polynomials in the parameters. In general, however, the determination of the zero locus is apparently out of reach. Instead, we consider the case where the isotropy group K of g in the group of motions is non-trivial. When K ≇Z2 we prove that the Einstein metrics on G are given by (up to homothety) either the standard metric or the nearly Kähler metric, based on representation-theoretic arguments and computer algebra. For the remaining case K ≅Z2 we present partial results.

Secondary structure in solution of two anti-HIV-1 hammerhead ribozymes as investigated by two-dimensional 1H 500 MHz NMR spectroscopy in water

NASA Technical Reports Server (NTRS)

Sarma, R. H.; Sarma, M. H.; Rein, R.; Shibata, M.; Setlik, R. S.; Ornstein, R. L.; Kazim, A. L.; Cairo, A.; Tomasi, T. B.

1995-01-01

Two hammerhead chimeric RNA/DNA ribozymes (HRz) were synthesized in pure form. Both were 30 nucleotides long, and the sequences were such that they could be targeted to cleave the HIV-1 gag RNA. Named HRz-W and HRz-M, the former had its invariable core region conserved, the latter had a uridine in the invariable region replaced by a guanine. Their secodary structures were determined by 2D NOESY 1H 500 MHz NMR spectroscopy in 90% water and 10% D2(0), following the imino protons. The data show that both HRz-M and HRz-W form identical secondary structures with stem regions consisting of continuous stacks of AT and GT pairs. An energy minimized computer model of this stem region is provided. The results suggest that the loss of catalytic activity that is known to result when an invariant core residue is replaced is not related to the secondary structure of the ribozymes in the absence of substrate.

Second-order statistics of colour codes modulate transformations that effectuate varying degrees of scene invariance and illumination invariance.

PubMed

Mausfeld, Rainer; Andres, Johannes

2002-01-01

We argue, from an ethology-inspired perspective, that the internal concepts 'surface colours' and 'illumination colours' are part of the data format of two different representational primitives. Thus, the internal concept of 'colour' is not a unitary one but rather refers to two different types of 'data structure', each with its own proprietary types of parameters and relations. The relation of these representational structures is modulated by a class of parameterised transformations whose effects are mirrored in the idealised computational achievements of illumination invariance of colour codes, on the one hand, and scene invariance, on the other hand. Because the same characteristics of a light array reaching the eye can be physically produced in many different ways, the visual system, then, has to make an 'inference' whether a chromatic deviation of the space-averaged colour codes from the neutral point is due to a 'non-normal', ie chromatic, illumination or due to an imbalanced spectral reflectance composition. We provide evidence that the visual system uses second-order statistics of chromatic codes of a single view of a scene in order to modulate corresponding transformations. In our experiments we used centre surround configurations with inhomogeneous surrounds given by a random structure of overlapping circles, referred to as Seurat configurations. Each family of surrounds has a fixed space-average of colour codes, but differs with respect to the covariance matrix of colour codes of pixels that defines the chromatic variance along some chromatic axis and the covariance between luminance and chromatic channels. We found that dominant wavelengths of red-green equilibrium settings of the infield exhibited a stable and strong dependence on the chromatic variance of the surround. High variances resulted in a tendency towards 'scene invariance', low variances in a tendency towards 'illumination invariance' of the infield.

Graph cuts with invariant object-interaction priors: application to intervertebral disc segmentation.

PubMed

Ben Ayed, Ismail; Punithakumar, Kumaradevan; Garvin, Gregory; Romano, Walter; Li, Shuo

2011-01-01

This study investigates novel object-interaction priors for graph cut image segmentation with application to intervertebral disc delineation in magnetic resonance (MR) lumbar spine images. The algorithm optimizes an original cost function which constrains the solution with learned prior knowledge about the geometric interactions between different objects in the image. Based on a global measure of similarity between distributions, the proposed priors are intrinsically invariant with respect to translation and rotation. We further introduce a scale variable from which we derive an original fixed-point equation (FPE), thereby achieving scale-invariance with only few fast computations. The proposed priors relax the need of costly pose estimation (or registration) procedures and large training sets (we used a single subject for training), and can tolerate shape deformations, unlike template-based priors. Our formulation leads to an NP-hard problem which does not afford a form directly amenable to graph cut optimization. We proceeded to a relaxation of the problem via an auxiliary function, thereby obtaining a nearly real-time solution with few graph cuts. Quantitative evaluations over 60 intervertebral discs acquired from 10 subjects demonstrated that the proposed algorithm yields a high correlation with independent manual segmentations by an expert. We further demonstrate experimentally the invariance of the proposed geometric attributes. This supports the fact that a single subject is sufficient for training our algorithm, and confirms the relevance of the proposed priors to disc segmentation.

Hearing in noisy environments: noise invariance and contrast gain control

PubMed Central

Willmore, Ben D B; Cooke, James E; King, Andrew J

2014-01-01

Contrast gain control has recently been identified as a fundamental property of the auditory system. Electrophysiological recordings in ferrets have shown that neurons continuously adjust their gain (their sensitivity to change in sound level) in response to the contrast of sounds that are heard. At the level of the auditory cortex, these gain changes partly compensate for changes in sound contrast. This means that sounds which are structurally similar, but have different contrasts, have similar neuronal representations in the auditory cortex. As a result, the cortical representation is relatively invariant to stimulus contrast and robust to the presence of noise in the stimulus. In the inferior colliculus (an important subcortical auditory structure), gain changes are less reliably compensatory, suggesting that contrast- and noise-invariant representations are constructed gradually as one ascends the auditory pathway. In addition to noise invariance, contrast gain control provides a variety of computational advantages over static neuronal representations; it makes efficient use of neuronal dynamic range, may contribute to redundancy-reducing, sparse codes for sound and allows for simpler decoding of population responses. The circuits underlying auditory contrast gain control are still under investigation. As in the visual system, these circuits may be modulated by factors other than stimulus contrast, forming a potential neural substrate for mediating the effects of attention as well as interactions between the senses. PMID:24907308

Potential energy surface fitting by a statistically localized, permutationally invariant, local interpolating moving least squares method for the many-body potential: Method and application to N{sub 4}

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

Bender, Jason D.; Doraiswamy, Sriram; Candler, Graham V., E-mail: truhlar@umn.edu, E-mail: candler@aem.umn.edu

2014-02-07

Fitting potential energy surfaces to analytic forms is an important first step for efficient molecular dynamics simulations. Here, we present an improved version of the local interpolating moving least squares method (L-IMLS) for such fitting. Our method has three key improvements. First, pairwise interactions are modeled separately from many-body interactions. Second, permutational invariance is incorporated in the basis functions, using permutationally invariant polynomials in Morse variables, and in the weight functions. Third, computational cost is reduced by statistical localization, in which we statistically correlate the cutoff radius with data point density. We motivate our discussion in this paper with amore » review of global and local least-squares-based fitting methods in one dimension. Then, we develop our method in six dimensions, and we note that it allows the analytic evaluation of gradients, a feature that is important for molecular dynamics. The approach, which we call statistically localized, permutationally invariant, local interpolating moving least squares fitting of the many-body potential (SL-PI-L-IMLS-MP, or, more simply, L-IMLS-G2), is used to fit a potential energy surface to an electronic structure dataset for N{sub 4}. We discuss its performance on the dataset and give directions for further research, including applications to trajectory calculations.« less

Effects of Relativity Lead to"Warp Speed" Computations

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

Vay, J.-L.

A scientist at Lawrence Berkeley National Laboratory has discovered that a previously unnoticed consequence of Einstein's special theory of relativity can lead to speedup of computer calculations by orders of magnitude when applied to the computer modeling of a certain class of physical systems. This new finding offers the possibility of tackling some problems in a much shorter time and with far more precision than was possible before, as well as studying some configurations in every detail for the first time. The basis of Einstein's theory is the principle of relativity, which states that the laws of physics are themore » same for all observers, whether the 'observer' is a turtle 'racing' with a rabbit, or a beam of particles moving at near light speed. From the invariance of the laws of physics, one may be tempted to infer that the complexity of a system is independent of the motion of the observer, and consequently, a computer simulation will require the same number of mathematical operations, independently of the reference frame that is used for the calculation. Length contraction and time dilation are well known consequences of the special theory of relativity which lead to very counterintuitive effects. An alien observing human activity through a telescope in a spaceship traveling in the Vicinity of the earth near the speed of light would see everything flattened in the direction of propagation of its spaceship (for him, the earth would have the shape of a pancake), while all motions on earth would appear extremely slow, slowed almost to a standstill. Conversely, a space scientist observing the alien through a telescope based on earth would see a flattened alien almost to a standstill in a flattened spaceship. Meanwhile, an astronaut sitting in a spaceship moving at some lower velocity than the alien spaceship with regard to earth might see both the alien spaceship and the earth flattened in the same proportion and the motion unfolding in each of them at the same speed. Let us now assume that each protagonist (the alien, the space scientist and the astronaut) is to run a computer simulation describing the motion of all of them in a single calculation. In order to model a physical system on a computer, scientists often divide space and time into small chunks. Since the computer must calculated some things for each chunk, having a large system containing numerous small chunks translates to long calculations requiring many computational steps on supercomputers. Let us assume that each protagonist of our intergalactic story uses the space and time slicing as described and chooses to perform the calculation in its own frame of reference. For the alien and the space scientist, the slicing of space and time results in an exceedingly large number of chunks, due to the wide disparity of spatial and time scales needed to describe both their own environment and motion together with the other extremely flattened environment and slowed motion. Since the disparity of scales is reduced for the astronaut, who is traveling at an intermediate velocity, the number of computer operations needed to complete the calculation in his frame of reference will be significantly lower, possibly by many orders of magnitude. Analogously, the new discovery at Lawrence Berkeley National Laboratory shows that there exists a frame of reference minimizing the number of computational operations needed for studying the interaction of beams of particles or light (lasers) interacting at, or near, light speed with other particles or with surrounding structures. Speedups ranging from ten to a million times or more are predicted for the modeling of beams interacting with electron clouds, such as those in the upcoming Large Hadron Collider 'atom smasher' accelerator at CERN (Switzerland), and in free electron lasers and tabletop laser wakefield accelerators. The discovery has surprised many physicists and was received initially with much skepticism. It sounded too much like a 'free lunch'. Yet, the demonstration of a speedup of a stunning one thousand times in a test simulation of a particle beam interacting with a background of electrons (see image), has proven that the effect is real and can be applied successfully, at least to some problems. Work is being actively pursued at Berkeley Lab and elsewhere to validate the feasibility of the method for a wider range of applications, as well as to apply the already successful method to more problems, where it might help getting better understanding of some processes and eventually lead to new findings.« less

Grouping Inhibits Motion Fading by Giving Rise to Virtual Trackable Features

ERIC Educational Resources Information Center

Hsieh, P. -J.; Tse, P. U.

2007-01-01

After prolonged viewing of a slowly drifting or rotating pattern under strict fixation, the pattern appears to slow down and then momentarily stop. The authors show that grouping can slow down the process of "motion fading," suggesting that cortical configural form analysis interacts with the computation of motion signals during motion fading. The…

Fast-slow asymptotics for a Markov chain model of fast sodium current

NASA Astrophysics Data System (ADS)

Starý, Tomáš; Biktashev, Vadim N.

2017-09-01

We explore the feasibility of using fast-slow asymptotics to eliminate the computational stiffness of discrete-state, continuous-time deterministic Markov chain models of ionic channels underlying cardiac excitability. We focus on a Markov chain model of fast sodium current, and investigate its asymptotic behaviour with respect to small parameters identified in different ways.

Computer Ethics: A Slow Fade from Black and White to Shades of Gray

ERIC Educational Resources Information Center

Kraft, Theresa A.; Carlisle, Judith

2011-01-01

The expanded use of teaching case based analysis based on current events and news stories relating to computer ethics improves student engagement, encourages creativity and fosters an active learning environment. Professional ethics standards, accreditation standards for computer curriculum, ethics theories, resources for ethics on the internet,…

Spatiotemporal canards in neural field equations

NASA Astrophysics Data System (ADS)

Avitabile, D.; Desroches, M.; Knobloch, E.

2017-04-01

Canards are special solutions to ordinary differential equations that follow invariant repelling slow manifolds for long time intervals. In realistic biophysical single-cell models, canards are responsible for several complex neural rhythms observed experimentally, but their existence and role in spatially extended systems is largely unexplored. We identify and describe a type of coherent structure in which a spatial pattern displays temporal canard behavior. Using interfacial dynamics and geometric singular perturbation theory, we classify spatiotemporal canards and give conditions for the existence of folded-saddle and folded-node canards. We find that spatiotemporal canards are robust to changes in the synaptic connectivity and firing rate. The theory correctly predicts the existence of spatiotemporal canards with octahedral symmetry in a neural field model posed on the unit sphere.

Adiabatic particle motion in a nearly drift-free magnetic field - Application to the geomagnetic tail

NASA Technical Reports Server (NTRS)

Stern, D. P.

1978-01-01

An investigation is made of the adiabatic particle motion occurring in an almost drift-free magnetic field. The dependence of the mean drift velocity on the equatorial pitch angle and the variation of the local drift velocity along the trajectories is studied. The fields considered are two-dimensional and resemble the geomagnetic tail. Derivations are presented for instantaneous and average drift velocities, bounce times, longitudinal invariants, and approximations to the adiabatic Hamiltonian. As expected, the mean drift velocity is significantly smaller than the instantaneous drift velocities found at typical points on the trajectory. The slow drift indicates that particles advance in the dawn-dusk direction rather slowly in the plasma sheet of the magnetospheric tail.

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

Tsvelik, A. M.; Yevtushenko, O. M.

We study the low energy physics of a Kondo chain where electrons from a one-dimensional band interact with magnetic moments via an anisotropic exchange interaction. It is demonstrated that the anisotropy gives rise to two different phases which are separated by a quantum phase transition. In the phase with easy plane anisotropy, Z2 symmetry between sectors with different helicity of the electrons is broken. As a result, localization effects are suppressed and the dc transport acquires (partial) symmetry protection. This effect is similar to the protection of the edge transport in time-reversal invariant topological insulators. The phase with easy axismore » anisotropy corresponds to the Tomonaga-Luttinger liquid with a pronounced spin-charge separation. The slow charge density wave modes have no protection against localizatioin.« less

Numerical tests of local scale invariance in ageing q-state Potts models

NASA Astrophysics Data System (ADS)

Lorenz, E.; Janke, W.

2007-01-01

Much effort has been spent over the last years to achieve a coherent theoretical description of ageing as a non-linear dynamics process. Long supposed to be a consequence of the slow dynamics of glassy systems only, ageing phenomena could also be identified in the phase-ordering kinetics of simple ferromagnets. As a phenomenological approach Henkel et al. developed a group of local scale transformations under which two-time autocorrelation and response functions should transform covariantly. This work is to extend previous numerical tests of the predicted scaling functions for the Ising model by Monte Carlo simulations of two-dimensional q-state Potts models with q=3 and 8, which, in equilibrium, undergo temperature-driven phase transitions of second and first order, respectively.

Aspects géométriques et intégrables des modèles de matrices aléatoires

NASA Astrophysics Data System (ADS)

Marchal, Olivier

2010-12-01

This thesis deals with the geometric and integrable aspects associated with random matrix models. Its purpose is to provide various applications of random matrix theory, from algebraic geometry to partial differential equations of integrable systems. The variety of these applications shows why matrix models are important from a mathematical point of view. First, the thesis will focus on the study of the merging of two intervals of the eigenvalues density near a singular point. Specifically, we will show why this special limit gives universal equations from the Painlevé II hierarchy of integrable systems theory. Then, following the approach of (bi) orthogonal polynomials introduced by Mehta to compute partition functions, we will find Riemann-Hilbert and isomonodromic problems connected to matrix models, making the link with the theory of Jimbo, Miwa and Ueno. In particular, we will describe how the hermitian two-matrix models provide a degenerate case of Jimbo-Miwa-Ueno's theory that we will generalize in this context. Furthermore, the loop equations method, with its central notions of spectral curve and topological expansion, will lead to the symplectic invariants of algebraic geometry recently proposed by Eynard and Orantin. This last point will be generalized to the case of non-hermitian matrix models (arbitrary beta) paving the way to "quantum algebraic geometry" and to the generalization of symplectic invariants to "quantum curves". Finally, this set up will be applied to combinatorics in the context of topological string theory, with the explicit computation of an hermitian random matrix model enumerating the Gromov-Witten invariants of a toric Calabi-Yau threefold.

Scale invariance and longitudinal stability of the Physical Functioning Western Ontario and MacMaster Universities Osteoarthritis Index using the Rasch model.

PubMed

Ayala, Alba; Bilbao, Amaia; Garcia-Perez, Sonia; Escobar, Antonio; Forjaz, Maria João

2018-03-01

The Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) measures the quality of life of patients with osteoarthritis (OA), and there is a specific scale for the physical functioning dimension, the short version with seven items WOMAC-pf. This study describes the application of the Rasch model to explore scale invariance and response stability of the WOMAC-pf short version across affected joint and over time. A sample of 884 patients with OA, from 15 hospitals in Spain, completed the WOMAC-pf before surgery (baseline) and at 3, 6 and 12 months post-surgery of hip or knee. The invariance by joint was explored through the differential item functioning (DIF) analysis of the Rasch model using baseline data, and time stability (DIF by time) were evaluated in stack data (each participant is represented four times, one by time point). Mean age of the patients was of 69.13 years (SD 10.01), 59.3% of them were women (n = 524), 59.2% had knee OA (n = 523) and 40.8% hip OA (n = 361). Item "putting on socks" showed DIF by joint and time. Fit to the Rasch model using stack data improved when this item was removed. Good reliability for individual use, local independency and unidimensionality of the models were confirmed. WOMAC-pf 7-item short version was invariant over time and joint when item "putting on socks" was removed. Researchers should carefully evaluate this item as it presents problems in scale invariance and stability, which could affect results when comparing data by joint or when computing change scores.

Left–right coordination from simple to extreme conditions during split‐belt locomotion in the chronic spinal adult cat

PubMed Central

Desrochers, Étienne; Thibaudier, Yann; Hurteau, Marie‐France; Dambreville, Charline

2016-01-01

Key points Coordination between the left and right sides is essential for dynamic stability during locomotion.The immature or neonatal mammalian spinal cord can adjust to differences in speed between the left and right sides during split‐belt locomotion by taking more steps on the fast side.We show that the adult mammalian spinal cord can also adjust its output so that the fast side can take more steps.During split‐belt locomotion, only certain parts of the cycle are modified to adjust left–right coordination, primarily those associated with swing onset.When the fast limb takes more steps than the slow limb, strong left–right interactions persist.Therefore, the adult mammalian spinal cord has a remarkable adaptive capacity for left–right coordination, from simple to extreme conditions. Abstract Although left–right coordination is essential for locomotion, its control is poorly understood, particularly in adult mammals. To investigate the spinal control of left–right coordination, a spinal transection was performed in six adult cats that were then trained to recover hindlimb locomotion. Spinal cats performed tied‐belt locomotion from 0.1 to 1.0 m s−1 and split‐belt locomotion with low to high (1:1.25–10) slow/fast speed ratios. With the left hindlimb stepping at 0.1 m s−1 and the right hindlimb stepping from 0.2 to 1.0 m s−1, 1:1, 1:2, 1:3, 1:4 and 1:5 left–right step relationships could appear. The appearance of 1:2+ relationships was not linearly dependent on the difference in speed between the slow and fast belts. The last step taken by the fast hindlimb displayed longer cycle, stance and swing durations and increased extensor activity, as the slow limb transitioned to swing. During split‐belt locomotion with 1:1, 1:2 and 1:3 relationships, the timing of stance onset of the fast limb relative to the slow limb and placement of both limbs at contact were invariant with increasing slow/fast speed ratios. In contrast, the timing of stance onset of the slow limb relative to the fast limb and the placement of both limbs at swing onset were modulated with slow/fast speed ratios. Thus, left–right coordination is adjusted by modifying specific parts of the cycle. Results highlight the remarkable adaptive capacity of the adult mammalian spinal cord, providing insight into spinal mechanisms and sensory signals regulating left–right coordination. PMID:27426732

Quantum many-body adiabaticity, topological Thouless pump and driven impurity in a one-dimensional quantum fluid

NASA Astrophysics Data System (ADS)

Lychkovskiy, Oleg; Gamayun, Oleksandr; Cheianov, Vadim

2018-02-01

The quantum adiabatic theorem states that a driven system can be kept arbitrarily close to the instantaneous eigenstate of its Hamiltonian if the latter varies in time slowly enough. When it comes to applying the adiabatic theorem in practice, the key question to be answered is how slow slowly enough is. This question can be an intricate one, especially for many-body systems, where the limits of slow driving and large system size may not commute. Recently we have shown how the quantum adiabaticity in many-body systems is related to the generalized orthogonality catastrophe [arXiv 1611.00663, to appear in Phys. Rev. Lett.]. We have proven a rigorous inequality relating these two phenomena and applied it to establish conditions for the quantized transport in the topological Thouless pump. In the present contribution we (i) review these developments and (ii) apply the inequality to establish the conditions for adiabaticity in a one-dimensional system consisting of a quantum fluid and an impurity particle pulled through the fluid by an external force. The latter analysis is vital for the correct quantitative description of the phenomenon of quasi-Bloch oscillations in a one-dimensional translation invariant impurity-fluid system.

ORACLS- OPTIMAL REGULATOR ALGORITHMS FOR THE CONTROL OF LINEAR SYSTEMS (CDC VERSION)

NASA Technical Reports Server (NTRS)

Armstrong, E. S.

1994-01-01

This control theory design package, called Optimal Regulator Algorithms for the Control of Linear Systems (ORACLS), was developed to aid in the design of controllers and optimal filters for systems which can be modeled by linear, time-invariant differential and difference equations. Optimal linear quadratic regulator theory, currently referred to as the Linear-Quadratic-Gaussian (LQG) problem, has become the most widely accepted method of determining optimal control policy. Within this theory, the infinite duration time-invariant problems, which lead to constant gain feedback control laws and constant Kalman-Bucy filter gains for reconstruction of the system state, exhibit high tractability and potential ease of implementation. A variety of new and efficient methods in the field of numerical linear algebra have been combined into the ORACLS program, which provides for the solution to time-invariant continuous or discrete LQG problems. The ORACLS package is particularly attractive to the control system designer because it provides a rigorous tool for dealing with multi-input and multi-output dynamic systems in both continuous and discrete form. The ORACLS programming system is a collection of subroutines which can be used to formulate, manipulate, and solve various LQG design problems. The ORACLS program is constructed in a manner which permits the user to maintain considerable flexibility at each operational state. This flexibility is accomplished by providing primary operations, analysis of linear time-invariant systems, and control synthesis based on LQG methodology. The input-output routines handle the reading and writing of numerical matrices, printing heading information, and accumulating output information. The basic vector-matrix operations include addition, subtraction, multiplication, equation, norm construction, tracing, transposition, scaling, juxtaposition, and construction of null and identity matrices. The analysis routines provide for the following computations: the eigenvalues and eigenvectors of real matrices; the relative stability of a given matrix; matrix factorization; the solution of linear constant coefficient vector-matrix algebraic equations; the controllability properties of a linear time-invariant system; the steady-state covariance matrix of an open-loop stable system forced by white noise; and the transient response of continuous linear time-invariant systems. The control law design routines of ORACLS implement some of the more common techniques of time-invariant LQG methodology. For the finite-duration optimal linear regulator problem with noise-free measurements, continuous dynamics, and integral performance index, a routine is provided which implements the negative exponential method for finding both the transient and steady-state solutions to the matrix Riccati equation. For the discrete version of this problem, the method of backwards differencing is applied to find the solutions to the discrete Riccati equation. A routine is also included to solve the steady-state Riccati equation by the Newton algorithms described by Klein, for continuous problems, and by Hewer, for discrete problems. Another routine calculates the prefilter gain to eliminate control state cross-product terms in the quadratic performance index and the weighting matrices for the sampled data optimal linear regulator problem. For cases with measurement noise, duality theory and optimal regulator algorithms are used to calculate solutions to the continuous and discrete Kalman-Bucy filter problems. Finally, routines are included to implement the continuous and discrete forms of the explicit (model-in-the-system) and implicit (model-in-the-performance-index) model following theory. These routines generate linear control laws which cause the output of a dynamic time-invariant system to track the output of a prescribed model. In order to apply ORACLS, the user must write an executive (driver) program which inputs the problem coefficients, formulates and selects the routines to be used to solve the problem, and specifies the desired output. There are three versions of ORACLS source code available for implementation: CDC, IBM, and DEC. The CDC version has been implemented on a CDC 6000 series computer with a central memory of approximately 13K (octal) of 60 bit words. The CDC version is written in FORTRAN IV, was developed in 1978, and last updated in 1989. The IBM version has been implemented on an IBM 370 series computer with a central memory requirement of approximately 300K of 8 bit bytes. The IBM version is written in FORTRAN IV and was generated in 1981. The DEC version has been implemented on a VAX series computer operating under VMS. The VAX version is written in FORTRAN 77 and was generated in 1986.

ORACLS- OPTIMAL REGULATOR ALGORITHMS FOR THE CONTROL OF LINEAR SYSTEMS (DEC VAX VERSION)

NASA Technical Reports Server (NTRS)

Frisch, H.

1994-01-01

This control theory design package, called Optimal Regulator Algorithms for the Control of Linear Systems (ORACLS), was developed to aid in the design of controllers and optimal filters for systems which can be modeled by linear, time-invariant differential and difference equations. Optimal linear quadratic regulator theory, currently referred to as the Linear-Quadratic-Gaussian (LQG) problem, has become the most widely accepted method of determining optimal control policy. Within this theory, the infinite duration time-invariant problems, which lead to constant gain feedback control laws and constant Kalman-Bucy filter gains for reconstruction of the system state, exhibit high tractability and potential ease of implementation. A variety of new and efficient methods in the field of numerical linear algebra have been combined into the ORACLS program, which provides for the solution to time-invariant continuous or discrete LQG problems. The ORACLS package is particularly attractive to the control system designer because it provides a rigorous tool for dealing with multi-input and multi-output dynamic systems in both continuous and discrete form. The ORACLS programming system is a collection of subroutines which can be used to formulate, manipulate, and solve various LQG design problems. The ORACLS program is constructed in a manner which permits the user to maintain considerable flexibility at each operational state. This flexibility is accomplished by providing primary operations, analysis of linear time-invariant systems, and control synthesis based on LQG methodology. The input-output routines handle the reading and writing of numerical matrices, printing heading information, and accumulating output information. The basic vector-matrix operations include addition, subtraction, multiplication, equation, norm construction, tracing, transposition, scaling, juxtaposition, and construction of null and identity matrices. The analysis routines provide for the following computations: the eigenvalues and eigenvectors of real matrices; the relative stability of a given matrix; matrix factorization; the solution of linear constant coefficient vector-matrix algebraic equations; the controllability properties of a linear time-invariant system; the steady-state covariance matrix of an open-loop stable system forced by white noise; and the transient response of continuous linear time-invariant systems. The control law design routines of ORACLS implement some of the more common techniques of time-invariant LQG methodology. For the finite-duration optimal linear regulator problem with noise-free measurements, continuous dynamics, and integral performance index, a routine is provided which implements the negative exponential method for finding both the transient and steady-state solutions to the matrix Riccati equation. For the discrete version of this problem, the method of backwards differencing is applied to find the solutions to the discrete Riccati equation. A routine is also included to solve the steady-state Riccati equation by the Newton algorithms described by Klein, for continuous problems, and by Hewer, for discrete problems. Another routine calculates the prefilter gain to eliminate control state cross-product terms in the quadratic performance index and the weighting matrices for the sampled data optimal linear regulator problem. For cases with measurement noise, duality theory and optimal regulator algorithms are used to calculate solutions to the continuous and discrete Kalman-Bucy filter problems. Finally, routines are included to implement the continuous and discrete forms of the explicit (model-in-the-system) and implicit (model-in-the-performance-index) model following theory. These routines generate linear control laws which cause the output of a dynamic time-invariant system to track the output of a prescribed model. In order to apply ORACLS, the user must write an executive (driver) program which inputs the problem coefficients, formulates and selects the routines to be used to solve the problem, and specifies the desired output. There are three versions of ORACLS source code available for implementation: CDC, IBM, and DEC. The CDC version has been implemented on a CDC 6000 series computer with a central memory of approximately 13K (octal) of 60 bit words. The CDC version is written in FORTRAN IV, was developed in 1978, and last updated in 1986. The IBM version has been implemented on an IBM 370 series computer with a central memory requirement of approximately 300K of 8 bit bytes. The IBM version is written in FORTRAN IV and was generated in 1981. The DEC version has been implemented on a VAX series computer operating under VMS. The VAX version is written in FORTRAN 77 and was generated in 1986.

Teaching Older Adults to Use Computers: Recommendations Based on Cognitive Aging Research.

ERIC Educational Resources Information Center

Jones, Brett D.; Bayen, Ute J.

1998-01-01

Reviews cognitive aging research that identifies the following effects on older adults: cognitive slowing, limited processing resources, lack of inhibition of irrelevant stimuli, and sensory deficits. Makes recommendations for teaching older adults to use computers. (SK)

Accurate hybrid stochastic simulation of a system of coupled chemical or biochemical reactions.

PubMed

Salis, Howard; Kaznessis, Yiannis

2005-02-01

The dynamical solution of a well-mixed, nonlinear stochastic chemical kinetic system, described by the Master equation, may be exactly computed using the stochastic simulation algorithm. However, because the computational cost scales with the number of reaction occurrences, systems with one or more "fast" reactions become costly to simulate. This paper describes a hybrid stochastic method that partitions the system into subsets of fast and slow reactions, approximates the fast reactions as a continuous Markov process, using a chemical Langevin equation, and accurately describes the slow dynamics using the integral form of the "Next Reaction" variant of the stochastic simulation algorithm. The key innovation of this method is its mechanism of efficiently monitoring the occurrences of slow, discrete events while simultaneously simulating the dynamics of a continuous, stochastic or deterministic process. In addition, by introducing an approximation in which multiple slow reactions may occur within a time step of the numerical integration of the chemical Langevin equation, the hybrid stochastic method performs much faster with only a marginal decrease in accuracy. Multiple examples, including a biological pulse generator and a large-scale system benchmark, are simulated using the exact and proposed hybrid methods as well as, for comparison, a previous hybrid stochastic method. Probability distributions of the solutions are compared and the weak errors of the first two moments are computed. In general, these hybrid methods may be applied to the simulation of the dynamics of a system described by stochastic differential, ordinary differential, and Master equations.

Electronic Data Interchange in Procurement

DTIC Science & Technology

1990-04-01

contract management and order processing systems. This conversion of automated information to paper and back to automated form is not only slow and...automated purchasing computer and the contractor’s order processing computer through telephone lines, as illustrated in Figure 1-1. Computer-to-computer...into the contractor’s order processing or contract management system. This approach - converting automated information to paper and back to automated

Strategy for reflector pattern calculation - Let the computer do the work

NASA Technical Reports Server (NTRS)

Lam, P. T.; Lee, S.-W.; Hung, C. C.; Acosta, R.

1986-01-01

Using high frequency approximations, the secondary pattern of a reflector antenna can be calculated by numerically evaluating a radiation integral I(u,v). In recent years, tremendous effort has been expended to reducing I(u,v) to Fourier integrals. These reduction schemes are invariably reflector geometry dependent. Hence, different analyses/computer software development must be carried out for different reflector shapes/boundaries. It is pointed out, that, as the computer power improves, these reduction schemes are no longer necessary. Comparable accuracy and computation time can be achieved by evaluating I(u,v) by a brute force FFT described in this note. Furthermore, there is virtually no restriction on the reflector geometry by using the brute force FFT.

Strategy for reflector pattern calculation: Let the computer do the work

NASA Technical Reports Server (NTRS)

Lam, P. T.; Lee, S. W.; Hung, C. C.; Acousta, R.

1985-01-01

Using high frequency approximations, the secondary pattern of a reflector antenna can be calculated by numerically evaluating a radiation integral I(u,v). In recent years, tremendous effort has been expended to reducing I(u,v) to Fourier integrals. These reduction schemes are invariably reflector geometry dependent. Hence, different analyses/computer software development must be carried out for different reflector shapes/boundaries. it is pointed out, that, as the computer power improves, these reduction schemes are no longer necessary. Comparable accuracy and computation time can be achieved by evaluating I(u,v) by a brute force FFT described in this note. Furthermore, there is virtually no restriction on the reflector geometry by using the brute force FFT.

QUEST - A Bayesian adaptive psychometric method

NASA Technical Reports Server (NTRS)

Watson, A. B.; Pelli, D. G.

1983-01-01

An adaptive psychometric procedure that places each trial at the current most probable Bayesian estimate of threshold is described. The procedure takes advantage of the common finding that the human psychometric function is invariant in form when expressed as a function of log intensity. The procedure is simple, fast, and efficient, and may be easily implemented on any computer.

Evaluation of Available Software for Reconstruction of a Structure from its Imagery

DTIC Science & Technology

2017-04-01

Math . 2, 164–168. Lowe, D. G. (1999) Object recognition from local scale-invariant features, in Proc. Int. Conf. Computer Vision, Vol. 2, pp. 1150–1157...Marquardt, D. (1963) An algorithm for least-squares estimation of nonlinear parameters, SIAM J. Appl. Math . 11(2), 431–441. UNCLASSIFIED 11 DST-Group–TR

The Impact of Item Position Change on Item Parameters and Common Equating Results under the 3PL Model

ERIC Educational Resources Information Center

Meyers, Jason L.; Murphy, Stephen; Goodman, Joshua; Turhan, Ahmet

2012-01-01

Operational testing programs employing item response theory (IRT) applications benefit from of the property of item parameter invariance whereby item parameter estimates obtained from one sample can be applied to other samples (when the underlying assumptions are satisfied). In theory, this feature allows for applications such as computer-adaptive…

Boltzmann's "H"-Theorem and the Assumption of Molecular Chaos

ERIC Educational Resources Information Center

Boozer, A. D.

2011-01-01

We describe a simple dynamical model of a one-dimensional ideal gas and use computer simulations of the model to illustrate two fundamental results of kinetic theory: the Boltzmann transport equation and the Boltzmann "H"-theorem. Although the model is time-reversal invariant, both results predict that the behaviour of the gas is time-asymmetric.…

Application of augmented-Lagrangian methods in meteorology: Comparison of different conjugate-gradient codes for large-scale minimization

NASA Technical Reports Server (NTRS)

Navon, I. M.

1984-01-01

A Lagrange multiplier method using techniques developed by Bertsekas (1982) was applied to solving the problem of enforcing simultaneous conservation of the nonlinear integral invariants of the shallow water equations on a limited area domain. This application of nonlinear constrained optimization is of the large dimensional type and the conjugate gradient method was found to be the only computationally viable method for the unconstrained minimization. Several conjugate-gradient codes were tested and compared for increasing accuracy requirements. Robustness and computational efficiency were the principal criteria.

Non-polynomial closed string field theory: loops and conformal maps

NASA Astrophysics Data System (ADS)

Hua, Long; Kaku, Michio

1990-11-01

Recently, we proposed the complete classical action for the non-polynomial closed string field theory, which succesfully reproduced all closed string tree amplitudes. (The action was simultaneously proposed by the Kyoto group). In this paper, we analyze the structure of the theory. We (a) compute the explicit conformal map for all g-loop, p-puncture diagrams, (b) compute all one-loop, two-puncture maps in terms of hyper-elliptic functions, and (c) analyze their modular structure. We analyze, but do not resolve, the question of modular invariance.

Dual-scale topology optoelectronic processor.

PubMed

Marsden, G C; Krishnamoorthy, A V; Esener, S C; Lee, S H

1991-12-15

The dual-scale topology optoelectronic processor (D-STOP) is a parallel optoelectronic architecture for matrix algebraic processing. The architecture can be used for matrix-vector multiplication and two types of vector outer product. The computations are performed electronically, which allows multiplication and summation concepts in linear algebra to be generalized to various nonlinear or symbolic operations. This generalization permits the application of D-STOP to many computational problems. The architecture uses a minimum number of optical transmitters, which thereby reduces fabrication requirements while maintaining area-efficient electronics. The necessary optical interconnections are space invariant, minimizing space-bandwidth requirements.

A two-dimensional spectrum analysis for sedimentation velocity experiments of mixtures with heterogeneity in molecular weight and shape.

PubMed

Brookes, Emre; Cao, Weiming; Demeler, Borries

2010-02-01

We report a model-independent analysis approach for fitting sedimentation velocity data which permits simultaneous determination of shape and molecular weight distributions for mono- and polydisperse solutions of macromolecules. Our approach allows for heterogeneity in the frictional domain, providing a more faithful description of the experimental data for cases where frictional ratios are not identical for all components. Because of increased accuracy in the frictional properties of each component, our method also provides more reliable molecular weight distributions in the general case. The method is based on a fine grained two-dimensional grid search over s and f/f (0), where the grid is a linear combination of whole boundary models represented by finite element solutions of the Lamm equation with sedimentation and diffusion parameters corresponding to the grid points. A Monte Carlo approach is used to characterize confidence limits for the determined solutes. Computational algorithms addressing the very large memory needs for a fine grained search are discussed. The method is suitable for globally fitting multi-speed experiments, and constraints based on prior knowledge about the experimental system can be imposed. Time- and radially invariant noise can be eliminated. Serial and parallel implementations of the method are presented. We demonstrate with simulated and experimental data of known composition that our method provides superior accuracy and lower variance fits to experimental data compared to other methods in use today, and show that it can be used to identify modes of aggregation and slow polymerization.

Restoration of dimensional reduction in the random-field Ising model at five dimensions

NASA Astrophysics Data System (ADS)

Fytas, Nikolaos G.; Martín-Mayor, Víctor; Picco, Marco; Sourlas, Nicolas

2017-04-01

The random-field Ising model is one of the few disordered systems where the perturbative renormalization group can be carried out to all orders of perturbation theory. This analysis predicts dimensional reduction, i.e., that the critical properties of the random-field Ising model in D dimensions are identical to those of the pure Ising ferromagnet in D -2 dimensions. It is well known that dimensional reduction is not true in three dimensions, thus invalidating the perturbative renormalization group prediction. Here, we report high-precision numerical simulations of the 5D random-field Ising model at zero temperature. We illustrate universality by comparing different probability distributions for the random fields. We compute all the relevant critical exponents (including the critical slowing down exponent for the ground-state finding algorithm), as well as several other renormalization-group invariants. The estimated values of the critical exponents of the 5D random-field Ising model are statistically compatible to those of the pure 3D Ising ferromagnet. These results support the restoration of dimensional reduction at D =5 . We thus conclude that the failure of the perturbative renormalization group is a low-dimensional phenomenon. We close our contribution by comparing universal quantities for the random-field problem at dimensions 3 ≤D <6 to their values in the pure Ising model at D -2 dimensions, and we provide a clear verification of the Rushbrooke equality at all studied dimensions.

Restoration of dimensional reduction in the random-field Ising model at five dimensions.

PubMed

Fytas, Nikolaos G; Martín-Mayor, Víctor; Picco, Marco; Sourlas, Nicolas

2017-04-01

The random-field Ising model is one of the few disordered systems where the perturbative renormalization group can be carried out to all orders of perturbation theory. This analysis predicts dimensional reduction, i.e., that the critical properties of the random-field Ising model in D dimensions are identical to those of the pure Ising ferromagnet in D-2 dimensions. It is well known that dimensional reduction is not true in three dimensions, thus invalidating the perturbative renormalization group prediction. Here, we report high-precision numerical simulations of the 5D random-field Ising model at zero temperature. We illustrate universality by comparing different probability distributions for the random fields. We compute all the relevant critical exponents (including the critical slowing down exponent for the ground-state finding algorithm), as well as several other renormalization-group invariants. The estimated values of the critical exponents of the 5D random-field Ising model are statistically compatible to those of the pure 3D Ising ferromagnet. These results support the restoration of dimensional reduction at D=5. We thus conclude that the failure of the perturbative renormalization group is a low-dimensional phenomenon. We close our contribution by comparing universal quantities for the random-field problem at dimensions 3≤D<6 to their values in the pure Ising model at D-2 dimensions, and we provide a clear verification of the Rushbrooke equality at all studied dimensions.

Stochastic multifractal forecasts: from theory to applications in radar meteorology

NASA Astrophysics Data System (ADS)

da Silva Rocha Paz, Igor; Tchiguirinskaia, Ioulia; Schertzer, Daniel

2017-04-01

Radar meteorology has been very inspiring for the development of multifractals. It has enabled to work on a 3D+1 field with many challenging applications, including predictability and stochastic forecasts, especially nowcasts that are particularly demanding in computation speed. Multifractals are indeed parsimonious stochastic models that require only a few physically meaningful parameters, e.g. Universal Multifractal (UM) parameters, because they are based on non-trivial symmetries of nonlinear equations. We first recall the physical principles of multifractal predictability and predictions, which are so closely related that the latter correspond to the most optimal predictions in the multifractal framework. Indeed, these predictions are based on the fundamental duality of a relatively slow decay of large scale structures and an injection of new born small scale structures. Overall, this triggers a mulfitractal inverse cascade of unpredictability. With the help of high resolution rainfall radar data (≈ 100 m), we detail and illustrate the corresponding stochastic algorithm in the framework of (causal) UM Fractionally Integrated Flux models (UM-FIF), where the rainfall field is obtained with the help of a fractional integration of a conservative multifractal flux, whose average is strictly scale invariant (like the energy flux in a dynamic cascade). Whereas, the introduction of small structures is rather straightforward, the deconvolution of the past of the field is more subtle, but nevertheless achievable, to obtain the past of the flux. Then, one needs to only fractionally integrate a multiplicative combination of past and future fluxes to obtain a nowcast realisation.

Global transport in a nonautonomous periodic standard map

DOE PAGES

Calleja, Renato C.; del-Castillo-Negrete, D.; Martinez-del-Rio, D.; ...

2017-04-14

A non-autonomous version of the standard map with a periodic variation of the perturbation parameter is introduced and studied via an autonomous map obtained from the iteration of the nonautonomous map over a period. Symmetry properties in the variables and parameters of the map are found and used to find relations between rotation numbers of invariant sets. The role of the nonautonomous dynamics on period-one orbits, stability and bifurcation is studied. The critical boundaries for the global transport and for the destruction of invariant circles with fixed rotation number are studied in detail using direct computation and a continuation method.more » In the case of global transport, the critical boundary has a particular symmetrical horn shape. Here, the results are contrasted with similar calculations found in the literature.« less

Global transport in a nonautonomous periodic standard map

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

Calleja, Renato C.; del-Castillo-Negrete, D.; Martinez-del-Rio, D.

A non-autonomous version of the standard map with a periodic variation of the perturbation parameter is introduced and studied via an autonomous map obtained from the iteration of the nonautonomous map over a period. Symmetry properties in the variables and parameters of the map are found and used to find relations between rotation numbers of invariant sets. The role of the nonautonomous dynamics on period-one orbits, stability and bifurcation is studied. The critical boundaries for the global transport and for the destruction of invariant circles with fixed rotation number are studied in detail using direct computation and a continuation method.more » In the case of global transport, the critical boundary has a particular symmetrical horn shape. Here, the results are contrasted with similar calculations found in the literature.« less

Long-distance effects in B→ K^*ℓ ℓ from analyticity

NASA Astrophysics Data System (ADS)

Bobeth, Christoph; Chrzaszcz, Marcin; van Dyk, Danny; Virto, Javier

2018-06-01

We discuss a novel approach to systematically determine the dominant long-distance contribution to B→ K^*ℓ ℓ decays in the kinematic region where the dilepton invariant mass is below the open charm threshold. This approach provides the most consistent and reliable determination to date and can be used to compute Standard Model predictions for all observables of interest, including the kinematic region where the dilepton invariant mass lies between the J/ψ and the ψ (2S) resonances. We illustrate the power of our results by performing a New Physics fit to the Wilson coefficient C_9. This approach is systematically improvable from theoretical and experimental sides, and applies to other decay modes of the type B→ Vℓ ℓ , B→ Pℓ ℓ and B→ Vγ.

Real-time object tracking based on scale-invariant features employing bio-inspired hardware.

PubMed

Yasukawa, Shinsuke; Okuno, Hirotsugu; Ishii, Kazuo; Yagi, Tetsuya

2016-09-01

We developed a vision sensor system that performs a scale-invariant feature transform (SIFT) in real time. To apply the SIFT algorithm efficiently, we focus on a two-fold process performed by the visual system: whole-image parallel filtering and frequency-band parallel processing. The vision sensor system comprises an active pixel sensor, a metal-oxide semiconductor (MOS)-based resistive network, a field-programmable gate array (FPGA), and a digital computer. We employed the MOS-based resistive network for instantaneous spatial filtering and a configurable filter size. The FPGA is used to pipeline process the frequency-band signals. The proposed system was evaluated by tracking the feature points detected on an object in a video. Copyright © 2016 Elsevier Ltd. All rights reserved.

Dark matter and neutrino masses from a scale-invariant multi-Higgs portal

NASA Astrophysics Data System (ADS)

Karam, Alexandros; Tamvakis, Kyriakos

2015-10-01

We consider a classically scale invariant version of the Standard Model, extended by an extra dark S U (2 )X gauge group. Apart from the dark gauge bosons and a dark scalar doublet which is coupled to the Standard Model Higgs through a portal coupling, we incorporate right-handed neutrinos and an additional real singlet scalar field. After symmetry breaking à la Coleman-Weinberg, we examine the multi-Higgs sector and impose theoretical and experimental constraints. In addition, by computing the dark matter relic abundance and the spin-independent scattering cross section off a nucleon we determine the viable dark matter mass range in accordance with present limits. The model can be tested in the near future by collider experiments and direct detection searches such as XENON 1T.

H(2)- and H(infinity)-design tools for linear time-invariant systems

NASA Technical Reports Server (NTRS)

Ly, Uy-Loi

1989-01-01

Recent advances in optimal control have brought design techniques based on optimization of H(2) and H(infinity) norm criteria, closer to be attractive alternatives to single-loop design methods for linear time-variant systems. Significant steps forward in this technology are the deeper understanding of performance and robustness issues of these design procedures and means to perform design trade-offs. However acceptance of the technology is hindered by the lack of convenient design tools to exercise these powerful multivariable techniques, while still allowing single-loop design formulation. Presented is a unique computer tool for designing arbitrary low-order linear time-invarient controllers than encompasses both performance and robustness issues via the familiar H(2) and H(infinity) norm optimization. Application to disturbance rejection design for a commercial transport is demonstrated.

Optical ranked-order filtering using threshold decomposition

DOEpatents

Allebach, J.P.; Ochoa, E.; Sweeney, D.W.

1987-10-09

A hybrid optical/electronic system performs median filtering and related ranked-order operations using threshold decomposition to encode the image. Threshold decomposition transforms the nonlinear neighborhood ranking operation into a linear space-invariant filtering step followed by a point-to-point threshold comparison step. Spatial multiplexing allows parallel processing of all the threshold components as well as recombination by a second linear, space-invariant filtering step. An incoherent optical correlation system performs the linear filtering, using a magneto-optic spatial light modulator as the input device and a computer-generated hologram in the filter plane. Thresholding is done electronically. By adjusting the value of the threshold, the same architecture is used to perform median, minimum, and maximum filtering of images. A totally optical system is also disclosed. 3 figs.

The Perspective Structure of Visual Space

PubMed Central

2015-01-01

Luneburg’s model has been the reference for experimental studies of visual space for almost seventy years. His claim for a curved visual space has been a source of inspiration for visual scientists as well as philosophers. The conclusion of many experimental studies has been that Luneburg’s model does not describe visual space in various tasks and conditions. Remarkably, no alternative model has been suggested. The current study explores perspective transformations of Euclidean space as a model for visual space. Computations show that the geometry of perspective spaces is considerably different from that of Euclidean space. Collinearity but not parallelism is preserved in perspective space and angles are not invariant under translation and rotation. Similar relationships have shown to be properties of visual space. Alley experiments performed early in the nineteenth century have been instrumental in hypothesizing curved visual spaces. Alleys were computed in perspective space and compared with reconstructed alleys of Blumenfeld. Parallel alleys were accurately described by perspective geometry. Accurate distance alleys were derived from parallel alleys by adjusting the interstimulus distances according to the size-distance invariance hypothesis. Agreement between computed and experimental alleys and accommodation of experimental results that rejected Luneburg’s model show that perspective space is an appropriate model for how we perceive orientations and angles. The model is also appropriate for perceived distance ratios between stimuli but fails to predict perceived distances. PMID:27648222

LANL* V1.0: a radiation belt drift shell model suitable for real-time and reanalysis applications

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

Koller, Josep; Reeves, Geoffrey D; Friedel, Reiner H W

2008-01-01

Space weather modeling, forecasts, and predictions, especially for the radiation belts in the inner magnetosphere, require detailed information about the Earth's magnetic field. Results depend on the magnetic field model and the L* (pron. L-star) values which are used to describe particle drift shells. Space wather models require integrating particle motions along trajectories that encircle the Earth. Numerical integration typically takes on the order of 10{sup 5} calls to a magnetic field model which makes the L* calculations very slow, in particular when using a dynamic and more accurate magnetic field model. Researchers currently tend to pick simplistic models overmore » more accurate ones but also risking large inaccuracies and even wrong conclusions. For example, magnetic field models affect the calculation of electron phase space density by applying adiabatic invariants including the drift shell value L*. We present here a new method using a surrogate model based on a neural network technique to replace the time consuming L* calculations made with modern magnetic field models. The advantage of surrogate models (or meta-models) is that they can compute the same output in a fraction of the time while adding only a marginal error. Our drift shell model LANL* (Los Alamos National Lab L-star) is based on L* calculation using the TSK03 model. The surrogate model has currently been tested and validated only for geosynchronous regions but the method is generally applicable to any satellite orbit. Computations with the new model are several million times faster compared to the standard integration method while adding less than 1% error. Currently, real-time applications for forecasting and even nowcasting inner magnetospheric space weather is limited partly due to the long computing time of accurate L* values. Without them, real-time applications are limited in accuracy. Reanalysis application of past conditions in the inner magnetosphere are used to understand physical processes and their effect. Without sufficiently accurate L* values, the interpretation of reanalysis results becomes difficult and uncertain. However, with a method that can calculate accurate L* values orders of magnitude faster, analyzing whole solar cycles worth of data suddenly becomes feasible.« less

A Game Theoretic Fault Detection Filter

NASA Technical Reports Server (NTRS)

Chung, Walter H.; Speyer, Jason L.

1995-01-01

The fault detection process is modelled as a disturbance attenuation problem. The solution to this problem is found via differential game theory, leading to an H(sub infinity) filter which bounds the transmission of all exogenous signals save the fault to be detected. For a general class of linear systems which includes some time-varying systems, it is shown that this transmission bound can be taken to zero by simultaneously bringing the sensor noise weighting to zero. Thus, in the limit, a complete transmission block can he achieved, making the game filter into a fault detection filter. When we specialize this result to time-invariant system, it is found that the detection filter attained in the limit is identical to the well known Beard-Jones Fault Detection Filter. That is, all fault inputs other than the one to be detected (the "nuisance faults") are restricted to an invariant subspace which is unobservable to a projection on the output. For time-invariant systems, it is also shown that in the limit, the order of the state-space and the game filter can be reduced by factoring out the invariant subspace. The result is a lower dimensional filter which can observe only the fault to be detected. A reduced-order filter can also he generated for time-varying systems, though the computational overhead may be intensive. An example given at the end of the paper demonstrates the effectiveness of the filter as a tool for fault detection and identification.

Non-Markovianity Measure Based on Brukner-Zeilinger Invariant Information for Unital Quantum Dynamical Maps

NASA Astrophysics Data System (ADS)

He, Zhi; Zhu, Lie-Qiang; Li, Li

2017-03-01

A non-Markovianity measure based on Brukner-Zeilinger invariant information to characterize non-Markovian effect of open systems undergoing unital dynamical maps is proposed. The method takes advantage of non-increasing property of the Brukner-Zeilinger invariant information under completely positive and trace-preserving unital maps. The simplicity of computing the Brukner-Zeilinger invariant information is the advantage of the proposed measure because of mainly depending on the purity of quantum state. The measure effectively captures the characteristics of non-Markovianity of unital dynamical maps. As some concrete application, we consider two typical non-Markovian noise channels, i.e., the phase damping channel and the random unitary channel to show the sensitivity of the proposed measure. By investigation, we find that the conditions of detecting the non-Markovianity for the phase damping channel are consistent with the results of existing measures for non-Markovianity, i.e., information flow, divisibility and quantum mutual information. However, for the random unitary channel non-Markovian conditions are same to that of the information flow, but is different from that of the divisibility and quantum mutual information. Supported by the National Natural Science Foundation of China under Grant No. 61505053, the Natural Science Foundation of Hunan Province under Grant No. 2015JJ3092, the Research Foundation of Education Bureau of Hunan Province, China under Grant No. 16B177, the School Foundation from the Hunan University of Arts and Science under Grant No. 14ZD01

On-line confidence monitoring during decision making.

PubMed

Dotan, Dror; Meyniel, Florent; Dehaene, Stanislas

2018-02-01

Humans can readily assess their degree of confidence in their decisions. Two models of confidence computation have been proposed: post hoc computation using post-decision variables and heuristics, versus online computation using continuous assessment of evidence throughout the decision-making process. Here, we arbitrate between these theories by continuously monitoring finger movements during a manual sequential decision-making task. Analysis of finger kinematics indicated that subjects kept separate online records of evidence and confidence: finger deviation continuously reflected the ongoing accumulation of evidence, whereas finger speed continuously reflected the momentary degree of confidence. Furthermore, end-of-trial finger speed predicted the post-decisional subjective confidence rating. These data indicate that confidence is computed on-line, throughout the decision process. Speed-confidence correlations were previously interpreted as a post-decision heuristics, whereby slow decisions decrease subjective confidence, but our results suggest an adaptive mechanism that involves the opposite causality: by slowing down when unconfident, participants gain time to improve their decisions. Copyright © 2017 Elsevier B.V. All rights reserved.

Evaluating Nurses Acceptance of Hospital Information Systems: A Case Study of a Tertiary Care Hospital.

PubMed

Khalifa, Mohamed

2016-01-01

This study aims at evaluating hospital information systems (HIS) acceptance factors among nurses, in order to provide suggestions for successful HIS implementation. The study used mainly quantitative survey methods to collect data directly from nurses through a questionnaire. The availability of computers in the hospital was one of the most influential factors, with a special emphasis on the unavailability of laptop computers and computers on wheels to facilitate immediate data entry and retrieval when nurses are at the point of care. Nurses believed that HIS might frequently slow down the process of care delivery and increase the time spent by patients inside the hospital especially during slow performance and responsiveness phases. Recommendations were classified into three main areas; improving system performance and availability of computers in the hospital, increasing organizational support in the form of providing training and protected time for nurses' to learn and enhancing users' feedback by listening to their complaints and considering their suggestions.

Slow-light transmission with high group index and large normalized delay bandwidth product through successive defect rods on intrinsic photonic crystal waveguide

NASA Astrophysics Data System (ADS)

Elshahat, Sayed; Khan, Karim; Yadav, Ashish; Bibbò, Luigi; Ouyang, Zhengbiao

2018-07-01

We proposed a strategy with successive cavities as energy reservoirs of electromagnetic energy and light-speed reducers introduced in the first and second rows of rods on the walls of an intrinsic photonic crystal waveguide (PCW) for slow-light transmission in the PCW concerning applications for optical communication, optical computation and optical signal processing. Subsequently, plane-wave expansion method (PWE) is used for studying slow-light properties and finite-difference time-domain (FDTD) method to demonstrate the slow-light propagating property of our proposed structure. We obtained group index as exceedingly large as 6123 with normalized delay bandwidth product (NDBP) as high as 0.48. We designed a facile but more generalized structure that may provide a vital theoretical basis for further enhancing the storage capacity properties of slow light with wideband and high NDBP.

WTO — a deterministic approach to 4-fermion physics

NASA Astrophysics Data System (ADS)

Passarino, Giampiero

1996-09-01

The program WTO, which is designed for computing cross sections and other relevant observables in the e+e- annihilation into four fermions, is described. The various quantities are computed over both a completely inclusive experimental set-up and a realistic one, i.e. with cuts on the final state energies, final state angles, scattering angles and final state invariant masses. Initial state QED corrections are included by means of the structure function approach while final state QCD corrections are applicable in their naive formulation. A gauge restoring mechanism is included according to the Fermion-Loop scheme. The program structure is highly modular and particular care has been devoted to computing efficiency and speed.

Efficient Implementation of the Invariant Imbedding T-Matrix Method and the Separation of Variables Method Applied to Large Nonspherical Inhomogeneous Particles

NASA Technical Reports Server (NTRS)

Bi, Lei; Yang, Ping; Kattawar, George W.; Mishchenko, Michael I.

2012-01-01

Three terms, ''Waterman's T-matrix method'', ''extended boundary condition method (EBCM)'', and ''null field method'', have been interchangeable in the literature to indicate a method based on surface integral equations to calculate the T-matrix. Unlike the previous method, the invariant imbedding method (IIM) calculates the T-matrix by the use of a volume integral equation. In addition, the standard separation of variables method (SOV) can be applied to compute the T-matrix of a sphere centered at the origin of the coordinate system and having a maximal radius such that the sphere remains inscribed within a nonspherical particle. This study explores the feasibility of a numerical combination of the IIM and the SOV, hereafter referred to as the IIMþSOV method, for computing the single-scattering properties of nonspherical dielectric particles, which are, in general, inhomogeneous. The IIMþSOV method is shown to be capable of solving light-scattering problems for large nonspherical particles where the standard EBCM fails to converge. The IIMþSOV method is flexible and applicable to inhomogeneous particles and aggregated nonspherical particles (overlapped circumscribed spheres) representing a challenge to the standard superposition T-matrix method. The IIMþSOV computational program, developed in this study, is validated against EBCM simulated spheroid and cylinder cases with excellent numerical agreement (up to four decimal places). In addition, solutions for cylinders with large aspect ratios, inhomogeneous particles, and two-particle systems are compared with results from discrete dipole approximation (DDA) computations, and comparisons with the improved geometric-optics method (IGOM) are found to be quite encouraging.

Comparing the Robustness of High-Frequency Traveling-Wave Tube Slow-Wave Circuits

NASA Technical Reports Server (NTRS)

Chevalier, Christine T.; Wilson, Jeffrey D.; Kory, Carol L.

2007-01-01

A three-dimensional electromagnetic field simulation software package was used to compute the cold-test parameters, phase velocity, on-axis interaction impedance, and attenuation, for several high-frequency traveling-wave tube slow-wave circuit geometries. This research effort determined the effects of variations in circuit dimensions on cold-test performance. The parameter variations were based on the tolerances of conventional micromachining techniques.

Advanced Computational Techniques for Power Tube Design.

DTIC Science & Technology

1986-07-01

fixturing applications, in addition to the existing computer-aided engineering capabilities. o Helix TWT Manufacturing has Implemented a tooling and fixturing...illustrates the ajor features of this computer network. ) The backbone of our system is a Sytek Broadband Network (LAN) which Interconnects terminals and...automatic network analyzer (FANA) which electrically characterizes the slow-wave helices of traveling-wave tubes ( TWTs ) -- both for engineering design

A MAP fixed-point, packing-unpacking routine for the IBM 7094 computer

Treesearch

Robert S. Helfman

1966-01-01

Two MAP (Macro Assembly Program) computer routines for packing and unpacking fixed point data are described. Use of these routines with Fortran IV Programs provides speedy access to quantities of data which far exceed the normal storage capacity of IBM 7000-series computers. Many problems that could not be attempted because of the slow access-speed of tape...

Narayanaswamy's 1971 aging theory and material time

NASA Astrophysics Data System (ADS)

Dyre, Jeppe C.

2015-09-01

The Bochkov-Kuzovlev nonlinear fluctuation-dissipation theorem is used to derive Narayanaswamy's phenomenological theory of physical aging, in which this highly nonlinear phenomenon is described by a linear material-time convolution integral. A characteristic property of the Narayanaswamy aging description is material-time translational invariance, which is here taken as the basic assumption of the derivation. It is shown that only one possible definition of the material time obeys this invariance, namely, the square of the distance travelled from a configuration of the system far back in time. The paper concludes with suggestions for computer simulations that test for consequences of material-time translational invariance. One of these is the "unique-triangles property" according to which any three points on the system's path form a triangle such that two side lengths determine the third; this is equivalent to the well-known triangular relation for time-autocorrelation functions of aging spin glasses [L. F. Cugliandolo and J. Kurchan, J. Phys. A: Math. Gen. 27, 5749 (1994)]. The unique-triangles property implies a simple geometric interpretation of out-of-equilibrium time-autocorrelation functions, which extends to aging a previously proposed framework for such functions in equilibrium [J. C. Dyre, e-print arXiv:cond-mat/9712222 (1997)].

Perception of biological motion from size-invariant body representations.

PubMed

Lappe, Markus; Wittinghofer, Karin; de Lussanet, Marc H E

2015-01-01

The visual recognition of action is one of the socially most important and computationally demanding capacities of the human visual system. It combines visual shape recognition with complex non-rigid motion perception. Action presented as a point-light animation is a striking visual experience for anyone who sees it for the first time. Information about the shape and posture of the human body is sparse in point-light animations, but it is essential for action recognition. In the posturo-temporal filter model of biological motion perception posture information is picked up by visual neurons tuned to the form of the human body before body motion is calculated. We tested whether point-light stimuli are processed through posture recognition of the human body form by using a typical feature of form recognition, namely size invariance. We constructed a point-light stimulus that can only be perceived through a size-invariant mechanism. This stimulus changes rapidly in size from one image to the next. It thus disrupts continuity of early visuo-spatial properties but maintains continuity of the body posture representation. Despite this massive manipulation at the visuo-spatial level, size-changing point-light figures are spontaneously recognized by naive observers, and support discrimination of human body motion.

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

Costigliola, Lorenzo; Schrøder, Thomas B.; Dyre, Jeppe C.

The recent theoretical prediction by Maimbourg and Kurchan [e-print http://arxiv.org/abs/1603.05023 (2016)] that for regular pair-potential systems the virial potential-energy correlation coefficient increases towards unity as the dimension d goes to infinity is investigated for the standard 12-6 Lennard-Jones fluid. This is done by computer simulations for d = 2, 3, 4 going from the critical point along the critical isotherm/isochore to higher density/temperature. In both cases the virial potential-energy correlation coefficient increases significantly. For a given density and temperature relative to the critical point, with increasing number of dimension the Lennard-Jones system conforms better to the hidden-scale-invariance property characterized bymore » high virial potential-energy correlations (a property that leads to the existence of isomorphs in the thermodynamic phase diagram, implying that it becomes effectively one-dimensional in regard to structure and dynamics). The present paper also gives the first numerical demonstration of isomorph invariance of structure and dynamics in four dimensions. Our findings emphasize the need for a universally applicable 1/d expansion in liquid-state theory; we conjecture that the systems known to obey hidden scale invariance in three dimensions are those for which the yet-to-be-developed 1/d expansion converges rapidly.« less

Solvable two-dimensional time-dependent non-Hermitian quantum systems with infinite dimensional Hilbert space in the broken PT-regime

NASA Astrophysics Data System (ADS)

Fring, Andreas; Frith, Thomas

2018-06-01

We provide exact analytical solutions for a two-dimensional explicitly time-dependent non-Hermitian quantum system. While the time-independent variant of the model studied is in the broken PT-symmetric phase for the entire range of the model parameters, and has therefore a partially complex energy eigenspectrum, its time-dependent version has real energy expectation values at all times. In our solution procedure we compare the two equivalent approaches of directly solving the time-dependent Dyson equation with one employing the Lewis–Riesenfeld method of invariants. We conclude that the latter approach simplifies the solution procedure due to the fact that the invariants of the non-Hermitian and Hermitian system are related to each other in a pseudo-Hermitian fashion, which in turn does not hold for their corresponding time-dependent Hamiltonians. Thus constructing invariants and subsequently using the pseudo-Hermiticity relation between them allows to compute the Dyson map and to solve the Dyson equation indirectly. In this way one can bypass to solve nonlinear differential equations, such as the dissipative Ermakov–Pinney equation emerging in our and many other systems.

A Comparison of Linking Methods for Estimating National Trends in International Comparative Large-Scale Assessments in the Presence of Cross-national DIF

ERIC Educational Resources Information Center

Sachse, Karoline A.; Roppelt, Alexander; Haag, Nicole

2016-01-01

Trend estimation in international comparative large-scale assessments relies on measurement invariance between countries. However, cross-national differential item functioning (DIF) has been repeatedly documented. We ran a simulation study using national item parameters, which required trends to be computed separately for each country, to compare…

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.

RESULTS OF COMPUTATIONS MADE FOR DASA-USNRDL FALLOUT SYMPOSIUM

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

Read, R.; Wagner, L.; Moorehead, E.

1962-11-01

The regression techniques introduced by the Civil Defense Research Project for estimating fallout particle deposition coordinates, their standard ellipses, and isointensity contours have been applied to some of the homework problems assigned for the DASA-USNRDL Fallout Symposium. The results are reported and the estimates are contrasted with estimates based on the assumption that winds are invariant with time. (auth).

A Neural Network Model of the Effects of Entrenchment and Memory Development on Grammatical Gender Learning

ERIC Educational Resources Information Center

Monner, Derek; Vatz, Karen; Morini, Giovanna; Hwang, So-One; DeKeyser, Robert

2013-01-01

To investigate potential causes of L2 performance deficits that correlate with age of onset, we use a computational model to explore the individual contributions of L1 entrenchment and aspects of memory development. Since development and L1 entrenchment almost invariably coincide, studying them independently is seldom possible in humans. To avoid…

Short assessment of the Big Five: robust across survey methods except telephone interviewing.

PubMed

Lang, Frieder R; John, Dennis; Lüdtke, Oliver; Schupp, Jürgen; Wagner, Gert G

2011-06-01

We examined measurement invariance and age-related robustness of a short 15-item Big Five Inventory (BFI-S) of personality dimensions, which is well suited for applications in large-scale multidisciplinary surveys. The BFI-S was assessed in three different interviewing conditions: computer-assisted or paper-assisted face-to-face interviewing, computer-assisted telephone interviewing, and a self-administered questionnaire. Randomized probability samples from a large-scale German panel survey and a related probability telephone study were used in order to test method effects on self-report measures of personality characteristics across early, middle, and late adulthood. Exploratory structural equation modeling was used in order to test for measurement invariance of the five-factor model of personality trait domains across different assessment methods. For the short inventory, findings suggest strong robustness of self-report measures of personality dimensions among young and middle-aged adults. In old age, telephone interviewing was associated with greater distortions in reliable personality assessment. It is concluded that the greater mental workload of telephone interviewing limits the reliability of self-report personality assessment. Face-to-face surveys and self-administrated questionnaire completion are clearly better suited than phone surveys when personality traits in age-heterogeneous samples are assessed.

Percolation critical polynomial as a graph invariant

DOE PAGES

Scullard, Christian R.

2012-10-18

Every lattice for which the bond percolation critical probability can be found exactly possesses a critical polynomial, with the root in [0; 1] providing the threshold. Recent work has demonstrated that this polynomial may be generalized through a definition that can be applied on any periodic lattice. The polynomial depends on the lattice and on its decomposition into identical finite subgraphs, but once these are specified, the polynomial is essentially unique. On lattices for which the exact percolation threshold is unknown, the polynomials provide approximations for the critical probability with the estimates appearing to converge to the exact answer withmore » increasing subgraph size. In this paper, I show how the critical polynomial can be viewed as a graph invariant like the Tutte polynomial. In particular, the critical polynomial is computed on a finite graph and may be found using the deletion-contraction algorithm. This allows calculation on a computer, and I present such results for the kagome lattice using subgraphs of up to 36 bonds. For one of these, I find the prediction p c = 0:52440572:::, which differs from the numerical value, p c = 0:52440503(5), by only 6:9 X 10 -7.« less

Approximate Joint Diagonalization and Geometric Mean of Symmetric Positive Definite Matrices

PubMed Central

Congedo, Marco; Afsari, Bijan; Barachant, Alexandre; Moakher, Maher

2015-01-01

We explore the connection between two problems that have arisen independently in the signal processing and related fields: the estimation of the geometric mean of a set of symmetric positive definite (SPD) matrices and their approximate joint diagonalization (AJD). Today there is a considerable interest in estimating the geometric mean of a SPD matrix set in the manifold of SPD matrices endowed with the Fisher information metric. The resulting mean has several important invariance properties and has proven very useful in diverse engineering applications such as biomedical and image data processing. While for two SPD matrices the mean has an algebraic closed form solution, for a set of more than two SPD matrices it can only be estimated by iterative algorithms. However, none of the existing iterative algorithms feature at the same time fast convergence, low computational complexity per iteration and guarantee of convergence. For this reason, recently other definitions of geometric mean based on symmetric divergence measures, such as the Bhattacharyya divergence, have been considered. The resulting means, although possibly useful in practice, do not satisfy all desirable invariance properties. In this paper we consider geometric means of covariance matrices estimated on high-dimensional time-series, assuming that the data is generated according to an instantaneous mixing model, which is very common in signal processing. We show that in these circumstances we can approximate the Fisher information geometric mean by employing an efficient AJD algorithm. Our approximation is in general much closer to the Fisher information geometric mean as compared to its competitors and verifies many invariance properties. Furthermore, convergence is guaranteed, the computational complexity is low and the convergence rate is quadratic. The accuracy of this new geometric mean approximation is demonstrated by means of simulations. PMID:25919667

Quantum phase transition and protected ideal transport in a Kondo chain

DOE PAGES

Tsvelik, A. M.; Yevtushenko, O. M.

2015-11-30

We study the low energy physics of a Kondo chain where electrons from a one-dimensional band interact with magnetic moments via an anisotropic exchange interaction. It is demonstrated that the anisotropy gives rise to two different phases which are separated by a quantum phase transition. In the phase with easy plane anisotropy, Z2 symmetry between sectors with different helicity of the electrons is broken. As a result, localization effects are suppressed and the dc transport acquires (partial) symmetry protection. This effect is similar to the protection of the edge transport in time-reversal invariant topological insulators. The phase with easy axismore » anisotropy corresponds to the Tomonaga-Luttinger liquid with a pronounced spin-charge separation. The slow charge density wave modes have no protection against localizatioin.« less

Systematics of constant roll inflation

NASA Astrophysics Data System (ADS)

Anguelova, Lilia; Suranyi, Peter; Wijewardhana, L. C. R.

2018-02-01

We study constant roll inflation systematically. This is a regime, in which the slow roll approximation can be violated. It has long been thought that this approximation is necessary for agreement with observations. However, recently it was understood that there can be inflationary models with a constant, and not necessarily small, rate of roll that are both stable and compatible with the observational constraint ns ≈ 1. We investigate systematically the condition for such a constant-roll regime. In the process, we find a whole new class of inflationary models, in addition to the known solutions. We show that the new models are stable under scalar perturbations. Finally, we find a part of their parameter space, in which they produce a nearly scale-invariant scalar power spectrum, as needed for observational viability.

Adiabatic regularization of the power spectrum in nonminimally coupled general single-field inflation

NASA Astrophysics Data System (ADS)

Alinea, Allan L.; Kubota, Takahiro

2018-03-01

We perform adiabatic regularization of power spectrum in nonminimally coupled general single-field inflation with varying speed of sound. The subtraction is performed within the framework of earlier study by Urakawa and Starobinsky dealing with the canonical inflation. Inspired by Fakir and Unruh's model on nonminimally coupled chaotic inflation, we find upon imposing near scale-invariant condition, that the subtraction term exponentially decays with the number of e -folds. As in the result for the canonical inflation, the regularized power spectrum tends to the "bare" power spectrum as the Universe expands during (and even after) inflation. This work justifies the use of the "bare" power spectrum in standard calculation in the most general context of slow-roll single-field inflation involving nonminimal coupling and varying speed of sound.

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

Wu, Fuke, E-mail: wufuke@mail.hust.edu.cn; Tian, Tianhai, E-mail: tianhai.tian@sci.monash.edu.au; Rawlings, James B., E-mail: james.rawlings@wisc.edu

The frequently used reduction technique is based on the chemical master equation for stochastic chemical kinetics with two-time scales, which yields the modified stochastic simulation algorithm (SSA). For the chemical reaction processes involving a large number of molecular species and reactions, the collection of slow reactions may still include a large number of molecular species and reactions. Consequently, the SSA is still computationally expensive. Because the chemical Langevin equations (CLEs) can effectively work for a large number of molecular species and reactions, this paper develops a reduction method based on the CLE by the stochastic averaging principle developed in themore » work of Khasminskii and Yin [SIAM J. Appl. Math. 56, 1766–1793 (1996); ibid. 56, 1794–1819 (1996)] to average out the fast-reacting variables. This reduction method leads to a limit averaging system, which is an approximation of the slow reactions. Because in the stochastic chemical kinetics, the CLE is seen as the approximation of the SSA, the limit averaging system can be treated as the approximation of the slow reactions. As an application, we examine the reduction of computation complexity for the gene regulatory networks with two-time scales driven by intrinsic noise. For linear and nonlinear protein production functions, the simulations show that the sample average (expectation) of the limit averaging system is close to that of the slow-reaction process based on the SSA. It demonstrates that the limit averaging system is an efficient approximation of the slow-reaction process in the sense of the weak convergence.« less

Analytical approach to Eigen-emittance evolution in storage rings

NASA Astrophysics Data System (ADS)

Nash, Boaz

This dissertation develops the subject of beam evolution in storage rings with nearly uncoupled symplectic linear dynamics. Linear coupling and dissipative/diffusive processes are treated perturbatively. The beam distribution is assumed Gaussian and a function of the invariants. The development requires two pieces: the global invariants and the local stochastic processes which change the emittances, or averages of the invariants. A map based perturbation theory is described, providing explicit expressions for the invariants near each linear resonance, where small perturbations can have a large effect. Emittance evolution is determined by the damping and diffusion coefficients. The discussion is divided into the cases of uniform and non-uniform stochasticity, synchrotron radiation an example of the former and intrabeam scattering the latter. For the uniform case, the beam dynamics is captured by a global diffusion coefficent and damping decrement for each eigen-invariant. Explicit expressions for these quantities near coupling resonances are given. In many cases, they are simply related to the uncoupled values. Near a sum resonance, it is found that one of the damping decrements becomes negative, indicating an anti-damping instability. The formalism is applied to a number of examples, including synchrobetatron coupling caused by a crab cavity, a case of current interest where there is concern about operation near half integer betatron tune. In the non-uniform case, the moment evolution is computed directly, which is illustrated through the example of intrabeam scattering. Our approach to intrabeam scattering damping and diffusion has the advantage of not requiring a loosely-defined Coulomb Logarithm. It is found that in some situations there is a small difference between our results and the standard approaches such as Bjorken-Mtingwa, which is illustrated by comparison of the two approaches and with a measurement of Au evolution in RHIC. Finally, in combining IBS with the global invariants some general statements about IBS equilibrium can be made. Specifically, it is emphasized that no such equilibrium is possible in a non-smooth lattice, even below transition. Near enough to a synchrobetatron coupling resonance, it is found that even for a smooth ring, no IBS equilibrium occurs.

A pictorial study of an invariant torus in phase space of four dimensions.

NASA Technical Reports Server (NTRS)

Baxter, R.; Eiserike, H.; Stokes, A.

1972-01-01

An investigation was conducted with the aid of a computer graphics device at Goddard Space Flight Center to study the behavior of the invariant manifolds of a particular fourth-order equation, as a parameter in the equation is varied over the interval from 0 to 1. The equation consists of two coupled Van der Pol equations. For a small parameter value, the manifold is an asymptotically stable torus, where the flow on the torus is simply a rotation. As the value of the parameter is increased, the only thing that changes is the nature of the flow on the torus, which itself persists throughout the parameter variation. It is shown that ultimately the four periodic cycles which appear play a more significant part in the phase profile of the system than does the torus itself.

Optimization of wavefront coding imaging system using heuristic algorithms

NASA Astrophysics Data System (ADS)

González-Amador, E.; Padilla-Vivanco, A.; Toxqui-Quitl, C.; Zermeño-Loreto, O.

2017-08-01

Wavefront Coding (WFC) systems make use of an aspheric Phase-Mask (PM) and digital image processing to extend the Depth of Field (EDoF) of computational imaging systems. For years, several kinds of PM have been designed to produce a point spread function (PSF) near defocus-invariant. In this paper, the optimization of the phase deviation parameter is done by means of genetic algorithms (GAs). In this, the merit function minimizes the mean square error (MSE) between the diffraction limited Modulated Transfer Function (MTF) and the MTF of the system that is wavefront coded with different misfocus. WFC systems were simulated using the cubic, trefoil, and 4 Zernike polynomials phase-masks. Numerical results show defocus invariance aberration in all cases. Nevertheless, the best results are obtained by using the trefoil phase-mask, because the decoded image is almost free of artifacts.

Adiabatic invariants in stellar dynamics. 1: Basic concepts

NASA Technical Reports Server (NTRS)

Weinberg, Martin D.

1994-01-01

The adiabatic criterion, widely used in astronomical dynamics, is based on the harmonic oscillator. It asserts that the change in action under a slowly varying perturbation is exponentially small. Recent mathematical results that precisely define the conditions for invariance show that this model does not apply in general. In particular, a slowly varying perturbation may cause significant evolution stellar dynamical systems even if its time scale is longer than any internal orbital time scale. This additional 'heating' may have serious implications for the evolution of star clusters and dwarf galaxies which are subject to long-term environmental forces. The mathematical developments leading to these results are reviewed, and the conditions for applicability to and further implications for stellar systems are discussed. Companion papers present a computational method for a general time-dependent disturbance and detailed example.

Global symmetries and renormalizability of Lee-Wick theories

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

Chivukula, R. Sekhar; Farzinnia, Arsham; Foadi, Roshan

2010-08-01

In this paper we discuss the global symmetries and the renormalizability of Lee-Wick (LW) scalar QED. In particular, in the ''auxiliary-field'' formalism we identify softly broken SO(1,1) global symmetries of the theory. We introduce SO(1,1) invariant gauge-fixing conditions that allow us to show in the auxiliary-field formalism directly that the number of superficially divergent amplitudes in a LW Abelian gauge theory is finite. To illustrate the renormalizability of the theory, we explicitly carry out the one-loop renormalization program in LW scalar QED and demonstrate how the counterterms required are constrained by the joint conditions of gauge and SO(1,1) invariance. Wemore » also compute the one-loop beta functions in LW scalar QED and contrast them with those of ordinary scalar QED.« less

Gravity Duals of Lifshitz-Like Fixed Points

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

Kachru, Shamit; /Stanford U., Phys. Dept. /SLAC; Liu, Xiao

2008-11-05

We find candidate macroscopic gravity duals for scale-invariant but non-Lorentz invariant fixed points, which do not have particle number as a conserved quantity. We compute two-point correlation functions which exhibit novel behavior relative to their AdS counterparts, and find holographic renormalization group flows to conformal field theories. Our theories are characterized by a dynamical critical exponent z, which governs the anisotropy between spatial and temporal scaling t {yields} {lambda}{sup z}t, x {yields} {lambda}x; we focus on the case with z = 2. Such theories describe multicritical points in certain magnetic materials and liquid crystals, and have been shown to arisemore » at quantum critical points in toy models of the cuprate superconductors. This work can be considered a small step towards making useful dual descriptions of such critical points.« less

HoDOr: histogram of differential orientations for rigid landmark tracking in medical images

NASA Astrophysics Data System (ADS)

Tiwari, Abhishek; Patwardhan, Kedar Anil

2018-03-01

Feature extraction plays a pivotal role in pattern recognition and matching. An ideal feature should be invariant to image transformations such as translation, rotation, scaling, etc. In this work, we present a novel rotation-invariant feature, which is based on Histogram of Oriented Gradients (HOG). We compare performance of the proposed approach with the HOG feature on 2D phantom data, as well as 3D medical imaging data. We have used traditional histogram comparison measures such as Bhattacharyya distance and Normalized Correlation Coefficient (NCC) to assess efficacy of the proposed approach under effects of image rotation. In our experiments, the proposed feature performs 40%, 20%, and 28% better than the HOG feature on phantom (2D), Computed Tomography (CT-3D), and Ultrasound (US-3D) data for image matching, and landmark tracking tasks respectively.

Emergent Topological order from Spin-Orbit Density wave

NASA Astrophysics Data System (ADS)

Gupta, Gaurav; Das, Tanmoy

We study the emergence of a Z2 -type topological order because of Landau type symmetry breaking order parameter. When two Rashba type SOC bands of different chirality become nested by a magic wavevector [(0, ∖pi) or (∖pi,0)], it introduces the inversion of chirality between different lattice sites. Such a density wave state is known as spin-orbit density wave. The resulting quantum order is associated with the topological order which is classified by a Z2 invariant. So, this system can simultaneously be classified by both a symmetry breaking order parameter and the associated Z2 topological invariant. This order parameter can be realized or engineered in two- or quasi-two-dimensional fermionic lattices, quantum wires, with tunable RSOC and correlation strength. The work is facilitated by the computer cluster facility at Department of Physics, Indian Institute of Science.

Topological mirror superconductivity.

PubMed

Zhang, Fan; Kane, C L; Mele, E J

2013-08-02

We demonstrate the existence of topological superconductors (SCs) protected by mirror and time-reversal symmetries. D-dimensional (D=1, 2, 3) crystalline SCs are characterized by 2(D-1) independent integer topological invariants, which take the form of mirror Berry phases. These invariants determine the distribution of Majorana modes on a mirror symmetric boundary. The parity of total mirror Berry phase is the Z(2) index of a class DIII SC, implying that a DIII topological SC with a mirror line must also be a topological mirror SC but not vice versa and that a DIII SC with a mirror plane is always time-reversal trivial but can be mirror topological. We introduce representative models and suggest experimental signatures in feasible systems. Advances in quantum computing, the case for nodal SCs, the case for class D, and topological SCs protected by rotational symmetries are pointed out.

A robust rotation-invariance displacement measurement method for a micro-/nano-positioning system

NASA Astrophysics Data System (ADS)

Zhang, Xiang; Zhang, Xianmin; Wu, Heng; Li, Hai; Gan, Jinqiang

2018-05-01

A robust and high-precision displacement measurement method for a compliant mechanism-based micro-/nano-positioning system is proposed. The method is composed of an integer-pixel and a sub-pixel matching procedure. In the proposed algorithm (Pro-A), an improved ring projection transform (IRPT) and gradient information are used as features for approximating the coarse candidates and fine locations, respectively. Simulations are conducted and the results show that the Pro-A has the ability of rotation-invariance and strong robustness, with a theoretical accuracy of 0.01 pixel. To validate the practical performance, a series of experiments are carried out using a computer micro-vision and laser interferometer system (LIMS). The results demonstrate that both the LIMS and Pro-A can achieve high precision, while the Pro-A has better stability and adaptability.

Onboard Image Registration from Invariant Features

NASA Technical Reports Server (NTRS)

Wang, Yi; Ng, Justin; Garay, Michael J.; Burl, Michael C

2008-01-01

This paper describes a feature-based image registration technique that is potentially well-suited for onboard deployment. The overall goal is to provide a fast, robust method for dynamically combining observations from multiple platforms into sensors webs that respond quickly to short-lived events and provide rich observations of objects that evolve in space and time. The approach, which has enjoyed considerable success in mainstream computer vision applications, uses invariant SIFT descriptors extracted at image interest points together with the RANSAC algorithm to robustly estimate transformation parameters that relate one image to another. Experimental results for two satellite image registration tasks are presented: (1) automatic registration of images from the MODIS instrument on Terra to the MODIS instrument on Aqua and (2) automatic stabilization of a multi-day sequence of GOES-West images collected during the October 2007 Southern California wildfires.

Microstructure Evolution and the Resulted Influence on Localized Corrosion in Al-Zn-Mg-Cu Alloy during Non-Isothermal Ageing

PubMed Central

Chen, Jun-Zhou; Li, Guo-Ai; Cai, Xin; Jiang, Jian-Tang; Shao, Wen-Zhu; Yang, Li; Zhen, Liang

2018-01-01

A non-isothermal ageing process was proposed for an Al-Zn-Mg-Cu alloy aiming to accommodate the slow heating/cooling procedure during the ageing of large components. The evolution of microstructure and microchemistry was analyzed by using transmission electron microscopy, high-angle annular dark field imaging, and energy dispersive spectrometry. The age-hardening of the alloy was examined to evaluate the strengthening behavior during the non-isothermal process. The corrosion behavior was investigated via observing the specimens immersed in EXCO solution (solution for Exfoliation Corrosion Susceptibility test in 2xxx and 7xxx series aluminum alloys, referring ASTM G34-01). Secondary precipitation was observed during the cooling stage, leading to increased precipitate number density. The distribution of grain boundary precipitates transits from discontinuous to continuous at the cooling stage, due to the secondary precipitation’s linking-up effect. The solutes’ enrichment on grain boundary precipitates and the depletion in precipitate-free zones develops during the heating procedure, but remains invariable during the cooling procedure. The corrosion in NIA (Non-isothermal Ageing) treated specimens initiates from pitting and then transits to intergranular corrosion and exfoliation corrosion. The transition from pitting to intergranular corrosion is very slow for specimens heated to 190 °C, but accelerates slightly as the cooling procedure proceeds. The transition to exfoliation corrosion is observed to be quite slow in all specimens in non-isothermal aged to over-aged condition, suggesting a corrosion resistance comparable to that of RRA condition. PMID:29751493

Microstructure Evolution and the Resulted Influence on Localized Corrosion in Al-Zn-Mg-Cu Alloy during Non-Isothermal Ageing.

PubMed

Chen, Jun-Zhou; Li, Guo-Ai; Cai, Xin; Jiang, Jian-Tang; Shao, Wen-Zhu; Yang, Li; Zhen, Liang

2018-05-03

A non-isothermal ageing process was proposed for an Al-Zn-Mg-Cu alloy aiming to accommodate the slow heating/cooling procedure during the ageing of large components. The evolution of microstructure and microchemistry was analyzed by using transmission electron microscopy, high-angle annular dark field imaging, and energy dispersive spectrometry. The age-hardening of the alloy was examined to evaluate the strengthening behavior during the non-isothermal process. The corrosion behavior was investigated via observing the specimens immersed in EXCO solution (solution for Exfoliation Corrosion Susceptibility test in 2xxx and 7xxx series aluminum alloys, referring ASTM G34-01). Secondary precipitation was observed during the cooling stage, leading to increased precipitate number density. The distribution of grain boundary precipitates transits from discontinuous to continuous at the cooling stage, due to the secondary precipitation’s linking-up effect. The solutes’ enrichment on grain boundary precipitates and the depletion in precipitate-free zones develops during the heating procedure, but remains invariable during the cooling procedure. The corrosion in NIA (Non-isothermal Ageing) treated specimens initiates from pitting and then transits to intergranular corrosion and exfoliation corrosion. The transition from pitting to intergranular corrosion is very slow for specimens heated to 190 °C, but accelerates slightly as the cooling procedure proceeds. The transition to exfoliation corrosion is observed to be quite slow in all specimens in non-isothermal aged to over-aged condition, suggesting a corrosion resistance comparable to that of RRA condition.

Towards a predictive thermal explosion model for energetic materials

NASA Astrophysics Data System (ADS)

Yoh, Jack J.; McClelland, Matthew A.; Maienschein, Jon L.; Wardell, Jeffrey F.

2005-01-01

We present an overview of models and computational strategies for simulating the thermal response of high explosives using a multi-physics hydrodynamics code, ALE3D. Recent improvements to the code have aided our computational capability in modeling the behavior of energetic materials systems exposed to strong thermal environments such as fires. We apply these models and computational techniques to a thermal explosion experiment involving the slow heating of a confined explosive. The model includes the transition from slow heating to rapid deflagration in which the time scale decreases from days to hundreds of microseconds. Thermal, mechanical, and chemical effects are modeled during all phases of this process. The heating stage involves thermal expansion and decomposition according to an Arrhenius kinetics model while a pressure-dependent burn model is employed during the explosive phase. We describe and demonstrate the numerical strategies employed to make the transition from slow to fast dynamics. In addition, we investigate the sensitivity of wall expansion rates to numerical strategies and parameters. Results from a one-dimensional model show that violence is influenced by the presence of a gap between the explosive and container. In addition, a comparison is made between 2D model and measured results for the explosion temperature and tube wall expansion profiles.

Spectral method for a kinetic swarming model

DOE PAGES

Gamba, Irene M.; Haack, Jeffrey R.; Motsch, Sebastien

2015-04-28

Here we present the first numerical method for a kinetic description of the Vicsek swarming model. The kinetic model poses a unique challenge, as there is a distribution dependent collision invariant to satisfy when computing the interaction term. We use a spectral representation linked with a discrete constrained optimization to compute these interactions. To test the numerical scheme we investigate the kinetic model at different scales and compare the solution with the microscopic and macroscopic descriptions of the Vicsek model. Lastly, we observe that the kinetic model captures key features such as vortex formation and traveling waves.

A Computational Behaviorist Takes Turing's Test

NASA Astrophysics Data System (ADS)

Whalen, Thomas E.

Behaviorism is a school of thought in experimental psychology that has given rise to powerful techniques for managing behavior. Because the Turing Test is a test of linguistic behavior rather than mental processes, approaching the test from a behavioristic perspective is worth examining. A behavioral approach begins by observing the kinds of questions that judges ask, then links the invariant features of those questions to pre-written answers. Because this approach is simple and powerful, it has been more successful in Turing competitions than the more ambitious linguistic approaches. Computational behaviorism may prove successful in other areas of Artificial Intelligence.

Computational neural learning formalisms for manipulator inverse kinematics

NASA Technical Reports Server (NTRS)

Gulati, Sandeep; Barhen, Jacob; Iyengar, S. Sitharama

1989-01-01

An efficient, adaptive neural learning paradigm for addressing the inverse kinematics of redundant manipulators is presented. The proposed methodology exploits the infinite local stability of terminal attractors - a new class of mathematical constructs which provide unique information processing capabilities to artificial neural systems. For robotic applications, synaptic elements of such networks can rapidly acquire the kinematic invariances embedded within the presented samples. Subsequently, joint-space configurations, required to follow arbitrary end-effector trajectories, can readily be computed. In a significant departure from prior neuromorphic learning algorithms, this methodology provides mechanisms for incorporating an in-training skew to handle kinematics and environmental constraints.

CHAMPION: Intelligent Hierarchical Reasoning Agents for Enhanced Decision Support

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

Hohimer, Ryan E.; Greitzer, Frank L.; Noonan, Christine F.

2011-11-15

We describe the design and development of an advanced reasoning framework employing semantic technologies, organized within a hierarchy of computational reasoning agents that interpret domain specific information. Designed based on an inspirational metaphor of the pattern recognition functions performed by the human neocortex, the CHAMPION reasoning framework represents a new computational modeling approach that derives invariant knowledge representations through memory-prediction belief propagation processes that are driven by formal ontological language specification and semantic technologies. The CHAMPION framework shows promise for enhancing complex decision making in diverse problem domains including cyber security, nonproliferation and energy consumption analysis.

Broad Search for Unstable Resonant Orbits in the Planar Circular Restricted Three-Body Problem

NASA Technical Reports Server (NTRS)

Anderson, Rodney L.; Campagnola, Stefano; Lantoine, Gregory

2013-01-01

Unstable resonant orbits in the circular restricted three-body problem have increasingly been used for trajectory design using optimization and invariant manifold techniques.In this study, several methods for computing these unstable resonant orbits are explored including flyby maps, continuation from two-body models, and grid searches. Families of orbits are computed focusing on the Jupiter-Europa system, and their characteristics are explored. Different parameters such as period and stability are examined for each set of resonantor bits, and the continuation of several specific orbits is explored in more detail.

Exponential Methods for the Time Integration of Schroedinger Equation

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

Cano, B.; Gonzalez-Pachon, A.

2010-09-30

We consider exponential methods of second order in time in order to integrate the cubic nonlinear Schroedinger equation. We are interested in taking profit of the special structure of this equation. Therefore, we look at symmetry, symplecticity and approximation of invariants of the proposed methods. That will allow to integrate till long times with reasonable accuracy. Computational efficiency is also our aim. Therefore, we make numerical computations in order to compare the methods considered and so as to conclude that explicit Lawson schemes projected on the norm of the solution are an efficient tool to integrate this equation.

Removal of inactivation causes time-invariant sodium current decays

PubMed Central

1988-01-01

The kinetic properties of the closing of Na channels were studied in frog skeletal muscle to obtain information about the dependence of channel closing on the past history of the channel. Channel closing was studied in normal and modified channels. Chloramine-T was used to modify the channels so that inactivation was virtually removed. A series of depolarizing prepulse potentials was used to activate Na channels, and a -140-mV postpulse was used to monitor the closing of the channels. Unmodified channels decay via a biexponential process with time constants of 72 and 534 microseconds at 12 degrees C. The observed time constants do not depend upon the potential used to activate the channels. The contribution of the slow component to the total decay increases as the activating prepulse is lengthened. After inactivation is removed, the biexponential character of the decay is retained, with no change in the magnitude of the time constants. However, increases in the duration of the activating prepulse over the range where the current is maximal 1-75 ms) produce identical biexponential decays. The presence of biexponential decays suggests that either two subtypes of Na channels are found in muscle, or Na channels can exist in one of two equally conductive states. The time- invariant decays observed suggest that channel closure does not depend upon their past history. PMID:2852208

Coherence Conversion for Optimized Resolution in Optical Measurements - Example of Femtosecond Time Resolution Using the Transverse Coherence of 100-Picosecond X-Rays

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

Adams, Bernhard W.

2015-01-01

A way is proposed to obtain a femtosecond time resolution over a picosecond range in x-ray spectroscopic measurements where the light source and the detector are much slower than that. It is based on the invariance of the modulus of the Fourier transform to object translations. The method geometrically correlates time in the sample with x-ray amplitudes over a spatial coordinate, and then takes the optical Fourier transform through far-field diffraction. Thus, explicitly time-invariant intensities that encode the time evolution of the sample can be measured with a slow detector. This corresponds to a phase-space transformation that converts the transversemore » coherence to become effective in the longitudinal direction. Because synchrotron-radiation sources have highly anisotropic coherence properties with about $10^5$ longitudinal electromagnetic-field modes at 1 eV bandwidth, but only tens to hundreds transverse modes, coherence conversion can drastically improve the time resolution. Reconstruction of the femtosecond time evolution in the sample from the Fourier intensities is subject to a phase ambiguity that is well-known in crystallography. However, a way is presented to resolve it that is not available in that discipline. Finally, data from a demonstration experiment are presented. The same concept can be used to obtain attosecond time resolution with an x-ray free-electron laser.« less

Computational Aeroacoustics: An Overview

NASA Technical Reports Server (NTRS)

Tam, Christopher K. W.

2003-01-01

An overview of recent advances in computational aeroacoustics (CAA) is presented. CAA algorithms must not be dispersive and dissipative. It should propagate waves supported by the Euler equations with the correct group velocities. Computation domains are inevitably finite in size. To avoid the reflection of acoustic and other outgoing waves at the boundaries of the computation domain, it is required that special boundary conditions be imposed at the boundary region. These boundary conditions either absorb all the outgoing waves without reflection or allow the waves to exit smoothly. High-order schemes, invariably, supports spurious short waves. These spurious waves tend to pollute the numerical solution. They must be selectively damped or filtered out. All these issues and relevant computation methods are briefly reviewed. Jet screech tones are known to have caused structural fatigue in military combat aircrafts. Numerical simulation of the jet screech phenomenon is presented as an example of a successful application of CAA.

Physical models and primary design of reactor based slow positron source at CMRR

NASA Astrophysics Data System (ADS)

Wang, Guanbo; Li, Rundong; Qian, Dazhi; Yang, Xin

2018-07-01

Slow positron facilities are widely used in material science. A high intensity slow positron source is now at the design stage based on the China Mianyang Research Reactor (CMRR). This paper describes the physical models and our primary design. We use different computer programs or mathematical formula to simulate different physical process, and validate them by proper experiments. Considering the feasibility, we propose a primary design, containing a cadmium shield, a honeycomb arranged W tubes assembly, electrical lenses, and a solenoid. It is planned to be vertically inserted in the Si-doping channel. And the beam intensity is expected to be 5 ×109

Next Generation Distributed Computing for Cancer Research

PubMed Central

Agarwal, Pankaj; Owzar, Kouros

2014-01-01

Advances in next generation sequencing (NGS) and mass spectrometry (MS) technologies have provided many new opportunities and angles for extending the scope of translational cancer research while creating tremendous challenges in data management and analysis. The resulting informatics challenge is invariably not amenable to the use of traditional computing models. Recent advances in scalable computing and associated infrastructure, particularly distributed computing for Big Data, can provide solutions for addressing these challenges. In this review, the next generation of distributed computing technologies that can address these informatics problems is described from the perspective of three key components of a computational platform, namely computing, data storage and management, and networking. A broad overview of scalable computing is provided to set the context for a detailed description of Hadoop, a technology that is being rapidly adopted for large-scale distributed computing. A proof-of-concept Hadoop cluster, set up for performance benchmarking of NGS read alignment, is described as an example of how to work with Hadoop. Finally, Hadoop is compared with a number of other current technologies for distributed computing. PMID:25983539

Next generation distributed computing for cancer research.

PubMed

Agarwal, Pankaj; Owzar, Kouros

2014-01-01

Advances in next generation sequencing (NGS) and mass spectrometry (MS) technologies have provided many new opportunities and angles for extending the scope of translational cancer research while creating tremendous challenges in data management and analysis. The resulting informatics challenge is invariably not amenable to the use of traditional computing models. Recent advances in scalable computing and associated infrastructure, particularly distributed computing for Big Data, can provide solutions for addressing these challenges. In this review, the next generation of distributed computing technologies that can address these informatics problems is described from the perspective of three key components of a computational platform, namely computing, data storage and management, and networking. A broad overview of scalable computing is provided to set the context for a detailed description of Hadoop, a technology that is being rapidly adopted for large-scale distributed computing. A proof-of-concept Hadoop cluster, set up for performance benchmarking of NGS read alignment, is described as an example of how to work with Hadoop. Finally, Hadoop is compared with a number of other current technologies for distributed computing.

Bridging Quantum, Classical and Stochastic Shortcuts to Adiabaticity

NASA Astrophysics Data System (ADS)

Patra, Ayoti

Adiabatic invariants - quantities that are preserved under the slow driving of a system's external parameters - are important in classical mechanics, quantum mechanics and thermodynamics. Adiabatic processes allow a system to be guided to evolve to a desired final state. However, the slow driving of a quantum system makes it vulnerable to environmental decoherence, and for both quantum and classical systems, it is often desirable and time-efficient to speed up a process. Shortcuts to adiabaticity are strategies for preserving adiabatic invariants under rapid driving, typically by means of an auxiliary field that suppresses excitations, otherwise generated during rapid driving. Several theoretical approaches have been developed to construct such shortcuts. In this dissertation we focus on two different approaches, namely counterdiabatic driving and fast-forward driving, which were originally developed for quantum systems. The counterdiabatic approach introduced independently by Dermirplak and Rice [J. Phys. Chem. A, 107:9937, 2003], and Berry [J. Phys. A: Math. Theor., 42:365303, 2009] formally provides an exact expression for the auxiliary Hamiltonian, which however is abstract and difficult to translate into an experimentally implementable form. By contrast, the fast-forward approach developed by Masuda and Nakamura [Proc. R. Soc. A, 466(2116):1135, 2010] provides an auxiliary potential that may be experimentally implementable but generally applies only to ground states. The central theme of this dissertation is that classical shortcuts to adiabaticity can provide useful physical insights and lead to experimentally implementable shortcuts for analogous quantum systems. We start by studying a model system of a tilted piston to provide a proof of principle that quantum shortcuts can successfully be constructed from their classical counterparts. In the remainder of the dissertation, we develop a general approach based on flow-fields which produces simple expressions for auxiliary terms required for both counterdiabatic and fast-forward driving. We demonstrate the applicability of this approach for classical, quantum as well as stochastic systems. We establish strong connections between counterdiabatic and fast-forward approaches, and also between shortcut protocols required for classical, quantum and stochastic systems. In particular, we show how the fast-forward approach can be extended to highly excited states of quantum systems.

Lack of synchronization between iron uptake and cell growth leads to iron overload in Saccharomyces cerevisiae during post-exponential growth modes

PubMed Central

Park, Jinkyu; McCormick, Sean P.; Chakrabarti, Mrinmoy; Lindahl, Paul A.

2014-01-01

Fermenting cells growing exponentially on rich (YPAD) medium transitioned to a slow-growing state as glucose levels declined and their metabolism shifted to respiration. During exponential growth, Fe import and cell growth rates were matched, affording an approximately invariant cellular Fe concentration. During the transitionary period, the high-affinity Fe import rate declined slower than the cell growth rate declined, causing Fe to accumulate, initially as FeIII oxyhydroxide nanoparticles but eventually as mitochondrial and vacuolar Fe. Once in slow-growth mode, Fe import and cell growth rates were again matched, and the cellular Fe concentration was again approximately invariant. Fermenting cells grown on minimal medium (MM) grew more slowly during exponential phase and transitioned to a true stationary state as glucose levels declined. The Fe concentration of MM cells that just entered stationary state was similar to that of YPAD cells, but MM cells continued to accumulate Fe in stationary state. Fe initially accumulated as nanoparticles and high-spin FeII species, but vacuolar FeIII also eventually accumulated. Surprisingly, Fe-packed 5-day-old MM cells suffered no more ROS damage than younger cells, suggesting that Fe concentration alone does not accurately predict the extent of ROS damage. The mode and rate of growth at the time of harvesting dramatically affected cellular Fe content. A mathematical model of Fe metabolism in a growing cell was developed. The model included Fe import via a regulated high-affinity pathway and an unregulated low-affinity pathway. Fe import from the cytosol into vacuoles and mitochondria, and nanoparticle formation were also included. The model captured essential trafficking behavior, demonstrating that cells regulate Fe import in accordance with their overall growth rate and that they misregulate Fe import when nanoparticles accumulate. The lack of regulation of Fe in yeast is perhaps unique compared to the tight regulation of other cellular metabolites. This phenomenon likely derives from the unique chemistry associated with Fe nanoparticle formation. PMID:24344915

A Bayesian Analysis of Scale-Invariant Processes

DTIC Science & Technology

2012-01-01

Earth Grid (EASE- Grid). The NED raster elevation data of one arc-second resolution (30 m) over the continental US are derived from multiple satellites ...instructions, searching existing data sources, gathering and maintaining the data needed, and completing and reviewing the collection of information. Send...empirical and ME distributions, yet ensuring computational efficiency. Instead of com- puting empirical histograms from large amount of data , only some

Classification of Magneto-Optic Images using Neural Networks

NASA Technical Reports Server (NTRS)

Nath, Shridhar; Wincheski, Buzz; Fulton, Jim; Namkung, Min

1994-01-01

A real time imaging system with a neural network classifier has been incorporated on a Macintosh computer in conjunction with an MOI system. This system images rivets on aircraft aluminium structures using eddy currents and magnetic imaging. Moment invariant functions from the image of a rivet is used to train a multilayer perceptron neural network to classify the rivets as good or bad (rivets with cracks).

Group analysis of dynamics equations of self-gravitating polytropic gas

NASA Astrophysics Data System (ADS)

Klebanov, I.; Panov, A.; Ivanov, S.; Maslova, O.

2018-06-01

The Lie algebras admitted by the dynamics equations of self-gravitating gas for an arbitrary equation of state and a polytropic gas are calculated. A spherically symmetric submodel is constructed for the case of a polytropic gas. The Lie algebras and the optimal system of subalgebras for a spherically symmetric submodel are computed. An invariant solution describing the steady motion is obtained.

Noncommutative Wilson lines in higher-spin theory and correlation functions of conserved currents for free conformal fields

NASA Astrophysics Data System (ADS)

Bonezzi, Roberto; Boulanger, Nicolas; De Filippi, David; Sundell, Per

2017-11-01

We first prove that, in Vasiliev’s theory, the zero-form charges studied in Sezgin E and Sundell P 2011 (arXiv:1103.2360 [hep-th]) and Colombo N and Sundell P 20 (arXiv:1208.3880 [hep-th]) are twisted open Wilson lines in the noncommutative Z space. This is shown by mapping Vasiliev’s higher-spin model on noncommutative Yang-Mills theory. We then prove that, prior to Bose-symmetrising, the cyclically-symmetric higher-spin invariants given by the leading order of these n-point zero-form charges are equal to corresponding cyclically-invariant building blocks of n-point correlation functions of bilinear operators in free conformal field theories (CFT) in three dimensions. On the higher spin gravity side, our computation reproduces the results of Didenko V and Skvortsov E 2013 J. High Energy Phys. JHEP04(2013)158 using an alternative method amenable to the computation of subleading corrections obtained by perturbation theory in normal order. On the free CFT side, our proof involves the explicit computation of the separate cyclic building blocks of the correlation functions of n conserved currents in arbitrary dimension d>2 using polarization vectors, which is an original result. It is shown to agree, for d=3 , with the results obtained in Gelfond O A and Vasiliev M A 2013 Nucl. Phys. B 876 871-917 in various dimensions and where polarization spinors were used.

Nonrelativistic Conformed Symmetry in 2 + 1 Dimensional Field Theory.

NASA Astrophysics Data System (ADS)

Bergman, Oren

This thesis is devoted to the study of conformal invariance and its breaking in non-relativistic field theories. It is a well known feature of relativistic field theory that theories which are conformally invariant at the classical level can acquire a conformal anomaly upon quantization and renormalization. The anomaly appears through the introduction of an arbitrary, but dimensionful, renormalization scale. One does not usually associate the concepts of renormalization and anomaly with nonrelativistic quantum mechanics, but there are a few examples where these concepts are useful. The most well known case is the two-dimensional delta -function potential. In two dimensions the delta-function scales like the kinetic term of the Hamiltonian, and therefore the problem is classically conformally invariant. Another example of classical conformal invariance is the famous Aharonov-Bohm (AB) problem. In that case each partial wave sees a 1/r^2 potential. We use the second quantized formulation of these problems, namely the nonrelativistic field theories, to compute Green's functions and derive the conformal anomaly. In the case of the AB problem we also solve an old puzzle, namely how to reproduce the result of Aharonov and Bohm in perturbation theory. The thesis is organized in the following manner. Chapter 1 is an introduction to nonrelativistic field theory, nonrelativistic conformal invariance, contact interactions and the AB problem. In Chapter 2 we discuss nonrelativistic scalar field theory, and how its quantization produces the anomaly. Chapter 3 is devoted to the AB problem, and the resolution of the perturbation puzzle. In Chapter 4 we generalize the discussion of Chapter 3 to particles carrying nonabelian charges. The structure of the nonabelian theory is much richer, and deserves a separate discussion. We also comment on the issues of forward scattering and single -valuedness of wavefunctions, which are important for Chapter 3 as well. (Copies available exclusively from MIT Libraries, Rm. 14-0551, Cambridge, MA 02139-4307. Ph. 617-253-5668; Fax 617-253-1690.).

Fierz bilinear formulation of the Maxwell–Dirac equations and symmetry reductions

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

Inglis, Shaun, E-mail: sminglis@utas.edu.au; Jarvis, Peter, E-mail: Peter.Jarvis@utas.edu.au

We study the Maxwell–Dirac equations in a manifestly gauge invariant presentation using only the spinor bilinear scalar and pseudoscalar densities, and the vector and pseudovector currents, together with their quadratic Fierz relations. The internally produced vector potential is expressed via algebraic manipulation of the Dirac equation, as a rational function of the Fierz bilinears and first derivatives (valid on the support of the scalar density), which allows a gauge invariant vector potential to be defined. This leads to a Fierz bilinear formulation of the Maxwell tensor and of the Maxwell–Dirac equations, without any reference to gauge dependent quantities. We showmore » how demanding invariance of tensor fields under the action of a fixed (but arbitrary) Lie subgroup of the Poincaré group leads to symmetry reduced equations. The procedure is illustrated, and the reduced equations worked out explicitly for standard spherical and cylindrical cases, which are coupled third order nonlinear PDEs. Spherical symmetry necessitates the existence of magnetic monopoles, which do not affect the coupled Maxwell–Dirac system due to magnetic terms cancelling. In this paper we do not take up numerical computations. As a demonstration of the power of our approach, we also work out the symmetry reduced equations for two distinct classes of dimension 4 one-parameter families of Poincaré subgroups, one splitting and one non-splitting. The splitting class yields no solutions, whereas for the non-splitting class we find a family of formal exact solutions in closed form. - Highlights: • Maxwell–Dirac equations derived in manifestly gauge invariant tensor form. • Invariant scalar and four vector fields for four Poincaré subgroups derived, including two unusual cases. • Symmetry reduction imposed on Maxwell–Dirac equations under example subgroups. • Magnetic monopole arises for spherically symmetric case, consistent with charge quantization condition.« less

Male body dissatisfaction scale (MBDS): proposal for a reduced model.

PubMed

da Silva, Wanderson Roberto; Marôco, João; Ochner, Christopher N; Campos, Juliana Alvares Duarte Bonini

2017-09-01

To evaluate the psychometric properties of the male body dissatisfaction scale (MBDS) in Brazilian and Portuguese university students; to present a reduced model of the scale; to compare two methods of computing global scores for participants' body dissatisfaction; and to estimate the prevalence of participants' body dissatisfaction. A total of 932 male students participated in this study. A confirmatory factor analysis (CFA) was used to assess the scale's psychometric properties. Multi-group analysis was used to test transnational invariance and invariance in independent samples. The body dissatisfaction score was calculated using two methods (mean and matrix of weights in the CFA), which were compared. Finally, individuals were classified according to level of body dissatisfaction, using the best method. The MBDS model did not show adequate fit for the sample and was, therefore, refined. Thirteen items were excluded and two factors were combined. A reduced model of 12 items and 2 factors was proposed and shown to have adequate psychometric properties. There was a significant difference (p < 0.001) between the methods for calculating the score for body dissatisfaction, since the mean overestimated the scores. Among student participants, the prevalence of body dissatisfaction with musculature and general appearance was 11.2 and 5.3%, respectively. The reduced bi-factorial model of the MBDS showed adequate validity, reliability, and transnational invariance and invariance in independent samples for Brazilian and Portuguese students. The new proposal for calculating the global score was able to more accurately show their body dissatisfaction. No level of evidence Basic Science.

Trial-Level Regressor Modulation for Functional Magnetic Resonance Imaging Designs Requiring Strict Periodicity of Stimulus Presentations: Illustrated Using a Go/No-Go Task

PubMed Central

Motes, Michael A; Rao, Neena K; Shokri-Kojori, Ehsan; Chiang, Hsueh-Sheng; Kraut, Michael A; Hart, John

2017-01-01

Computer-based assessment of many cognitive processes (eg, anticipatory and response readiness processes) requires the use of invariant stimulus display times (SDT) and intertrial intervals (ITI). Although designs with invariant SDTs and ITIs have been used in functional magnetic resonance imaging (fMRI) research, such designs are problematic for fMRI studies because of collinearity issues. This study examined regressor modulation with trial-level reaction times (RT) as a method for improving signal detection in a go/no-go task with invariant SDTs and ITIs. The effects of modulating the go regressor were evaluated with respect to the detection of BOLD signal-change for the no-go condition. BOLD signal-change to no-go stimuli was examined when the go regressor was based on a (a) canonical hemodynamic response function (HRF), (b) RT-based amplitude-modulated (AM) HRF, and (c) RT-based amplitude and duration modulated (A&DM) HRF. Reaction time–based modulation reduced the collinearity between the go and no-go regressors, with A&DM producing the greatest reductions in correlations between the regressors, and greater reductions in the correlations between regressors were associated with longer mean RTs and greater RT variability. Reaction time–based modulation increased statistical power for detecting group-level no-go BOLD signal-change across a broad set of brain regions. The findings show the efficacy of using regressor modulation to increase power in detecting BOLD signal-change in fMRI studies in which circumstances dictate the use of temporally invariant stimulus presentations. PMID:29276390

Trial-Level Regressor Modulation for Functional Magnetic Resonance Imaging Designs Requiring Strict Periodicity of Stimulus Presentations: Illustrated Using a Go/No-Go Task.

PubMed

Motes, Michael A; Rao, Neena K; Shokri-Kojori, Ehsan; Chiang, Hsueh-Sheng; Kraut, Michael A; Hart, John

2017-01-01

Computer-based assessment of many cognitive processes (eg, anticipatory and response readiness processes) requires the use of invariant stimulus display times (SDT) and intertrial intervals (ITI). Although designs with invariant SDTs and ITIs have been used in functional magnetic resonance imaging (fMRI) research, such designs are problematic for fMRI studies because of collinearity issues. This study examined regressor modulation with trial-level reaction times (RT) as a method for improving signal detection in a go / no-go task with invariant SDTs and ITIs. The effects of modulating the go regressor were evaluated with respect to the detection of BOLD signal-change for the no-go condition. BOLD signal-change to no-go stimuli was examined when the go regressor was based on a (a) canonical hemodynamic response function (HRF), (b) RT-based amplitude-modulated (AM) HRF, and (c) RT-based amplitude and duration modulated (A&DM) HRF. Reaction time-based modulation reduced the collinearity between the go and no-go regressors, with A&DM producing the greatest reductions in correlations between the regressors, and greater reductions in the correlations between regressors were associated with longer mean RTs and greater RT variability. Reaction time-based modulation increased statistical power for detecting group-level no-go BOLD signal-change across a broad set of brain regions. The findings show the efficacy of using regressor modulation to increase power in detecting BOLD signal-change in fMRI studies in which circumstances dictate the use of temporally invariant stimulus presentations.

Tectonic Tremor and the Collective Behavior of Low-Frequency Earthquakes

NASA Astrophysics Data System (ADS)

Frank, W.; Shapiro, N.; Husker, A. L.; Kostoglodov, V.; Campillo, M.; Gusev, A. A.

2015-12-01

Tectonic tremor, a long duration, emergent seismic signal observed along the deep roots of plate interfaces, is thought to be the superposition of repetitive shear events called low-frequency earthquakes (LFE) [e.g. Shelly et al., Nature, 2007]. We use a catalog of more than 1.8 million LFEs regrouped into more than 1000 families observed over 2 years in the Guerrero subduction zone in Mexico, considering each family as an individual repetitive source or asperity. We develop a statistical analysis to determine whether the subcatalogs corresponding to different sources represent random Poisson processes or if they exhibit scale-invariant clustering in time, which we interpret as a manifestation of collective behavior. For each individual LFE source, we compare their level of collective behavior during two time periods: during the six-month-long 2006 Mw 7.5 slow-slip event and during a calm period with no observed slow slip. We find that the collective behavior of LFEs depends on distance from the trench and increases when the subduction interface is slowly slipping. Our results suggest that the occurrence of strong episodes of tectonic tremors cannot be simply explained by increased rates of low frequency earthquakes at every individual LFE source but correspond to an enhanced collective behavior of the ensemble of LFE asperities.

New type of hill-top inflation

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

Barvinsky, A.O.; Department of Physics, Tomsk State University,Lenin Ave. 36, Tomsk 634050; Department of Physics and Astronomy, Pacific Institue for Theoretical Physics,University of British Columbia, 6224 Agricultural Road, Vancouver, BC V6T 1Z1

2016-01-20

We suggest a new type of hill-top inflation originating from the initial conditions in the form of the microcanonical density matrix for the cosmological model with a large number of quantum fields conformally coupled to gravity. Initial conditions for inflation are set up by cosmological instantons describing underbarrier oscillations in the vicinity of the inflaton potential maximum. These periodic oscillations of the inflaton field and cosmological scale factor are obtained within the approximation of two coupled oscillators subject to the slow roll regime in the Euclidean time. This regime is characterized by rapid oscillations of the scale factor on themore » background of a slowly varying inflaton, which guarantees smallness of slow roll parameters ϵ and η of the following inflation stage. A hill-like shape of the inflaton potential is shown to be generated by logarithmic loop corrections to the tree-level asymptotically shift-invariant potential in the non-minimal Higgs inflation model and R{sup 2}-gravity. The solution to the problem of hierarchy between the Planckian scale and the inflation scale is discussed within the concept of conformal higher spin fields, which also suggests the mechanism bringing the model below the gravitational cutoff and, thus, protecting it from large graviton loop corrections.« less

New type of hill-top inflation

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

Barvinsky, A.O.; Nesterov, D.V.; Kamenshchik, A.Yu., E-mail: barvin@td.lpi.ru, E-mail: Alexander.Kamenshchik@bo.infn.it, E-mail: nesterov@td.lpi.ru

2016-01-01

We suggest a new type of hill-top inflation originating from the initial conditions in the form of the microcanonical density matrix for the cosmological model with a large number of quantum fields conformally coupled to gravity. Initial conditions for inflation are set up by cosmological instantons describing underbarrier oscillations in the vicinity of the inflaton potential maximum. These periodic oscillations of the inflaton field and cosmological scale factor are obtained within the approximation of two coupled oscillators subject to the slow roll regime in the Euclidean time. This regime is characterized by rapid oscillations of the scale factor on themore » background of a slowly varying inflaton, which guarantees smallness of slow roll parameters ε and η of the following inflation stage. A hill-like shape of the inflaton potential is shown to be generated by logarithmic loop corrections to the tree-level asymptotically shift-invariant potential in the non-minimal Higgs inflation model and R{sup 2}-gravity. The solution to the problem of hierarchy between the Planckian scale and the inflation scale is discussed within the concept of conformal higher spin fields, which also suggests the mechanism bringing the model below the gravitational cutoff and, thus, protecting it from large graviton loop corrections.« less

Metasurface optics for full-color computational imaging.

PubMed

Colburn, Shane; Zhan, Alan; Majumdar, Arka

2018-02-01

Conventional imaging systems comprise large and expensive optical components that successively mitigate aberrations. Metasurface optics offers a route to miniaturize imaging systems by replacing bulky components with flat and compact implementations. The diffractive nature of these devices, however, induces severe chromatic aberrations, and current multiwavelength and narrowband achromatic metasurfaces cannot support full visible spectrum imaging (400 to 700 nm). We combine principles of both computational imaging and metasurface optics to build a system with a single metalens of numerical aperture ~0.45, which generates in-focus images under white light illumination. Our metalens exhibits a spectrally invariant point spread function that enables computational reconstruction of captured images with a single digital filter. This work connects computational imaging and metasurface optics and demonstrates the capabilities of combining these disciplines by simultaneously reducing aberrations and downsizing imaging systems using simpler optics.

Scale Space for Camera Invariant Features.

PubMed

Puig, Luis; Guerrero, José J; Daniilidis, Kostas

2014-09-01

In this paper we propose a new approach to compute the scale space of any central projection system, such as catadioptric, fisheye or conventional cameras. Since these systems can be explained using a unified model, the single parameter that defines each type of system is used to automatically compute the corresponding Riemannian metric. This metric, is combined with the partial differential equations framework on manifolds, allows us to compute the Laplace-Beltrami (LB) operator, enabling the computation of the scale space of any central projection system. Scale space is essential for the intrinsic scale selection and neighborhood description in features like SIFT. We perform experiments with synthetic and real images to validate the generalization of our approach to any central projection system. We compare our approach with the best-existing methods showing competitive results in all type of cameras: catadioptric, fisheye, and perspective.

View synthesis using parallax invariance

NASA Astrophysics Data System (ADS)

Dornaika, Fadi

2001-06-01

View synthesis becomes a focus of attention of both the computer vision and computer graphics communities. It consists of creating novel images of a scene as it would appear from novel viewpoints. View synthesis can be used in a wide variety of applications such as video compression, graphics generation, virtual reality and entertainment. This paper addresses the following problem. Given a dense disparity map between two reference images, we would like to synthesize a novel view of the same scene associated with a novel viewpoint. Most of the existing work is relying on building a set of 3D meshes which are then projected onto the new image (the rendering process is performed using texture mapping). The advantages of our view synthesis approach are as follows. First, the novel view is specified by a rotation and a translation which are the most natural way to express the virtual location of the camera. Second, the approach is able to synthesize highly realistic images whose viewing position is significantly far away from the reference viewpoints. Third, the approach is able to handle the visibility problem during the synthesis process. Our developed framework has two main steps. The first step (analysis step) consists of computing the homography at infinity, the epipoles, and thus the parallax field associated with the reference images. The second step (synthesis step) consists of warping the reference image into a new one, which is based on the invariance of the computed parallax field. The analysis step is working directly on the reference views, and only need to be performed once. Examples of synthesizing novel views using either feature correspondences or dense disparity map have demonstrated the feasibility of the proposed approach.

Introducing the Microcomputer into Undergraduate Tax Courses.

ERIC Educational Resources Information Center

Dillaway, Manson P.; Savage, Allan H.

Although accountants have used computers for tax planning and tax return preparation for many years, tax education has been slow to reflect the increasing role of computers in tax accounting. The following are only some of the tasks that a business education department offering undergraduate tax courses for accounting majors should perform when…

Introduction to Reactor Statics Modules, RS-1. Nuclear Engineering Computer Modules.

ERIC Educational Resources Information Center

Edlund, Milton C.

The nine Reactor Statics Modules are designed to introduce students to the use of numerical methods and digital computers for calculation of neutron flux distributions in space and energy which are needed to calculate criticality, power distribution, and fuel burn-up for both slow neutron and fast neutron fission reactors. The diffusion…

Learning Together: Micro-Computers in Crosby, Texas, Schools.

ERIC Educational Resources Information Center

McNeil, Linda M.

The Crosby Independent School District near Houston, Texas, planned to introduce microcomputer instruction to its nearly 3,000 students in slow stages that had teachers and students learning at the same time. The initial impetus for computers came from an administrator who found useful information at a Regional Service Center of the State…

Quantum-like model for the adaptive dynamics of the genetic regulation of E. coli's metabolism of glucose/lactose.

PubMed

Asano, Masanari; Basieva, Irina; Khrennikov, Andrei; Ohya, Masanori; Tanaka, Yoshiharu; Yamato, Ichiro

2012-06-01

We developed a quantum-like model describing the gene regulation of glucose/lactose metabolism in a bacterium, Escherichia coli. Our quantum-like model can be considered as a kind of the operational formalism for microbiology and genetics. Instead of trying to describe processes in a cell in the very detail, we propose a formal operator description. Such a description may be very useful in situation in which the detailed description of processes is impossible or extremely complicated. We analyze statistical data obtained from experiments, and we compute the degree of E. coli's preference within adaptive dynamics. It is known that there are several types of E. coli characterized by the metabolic system. We demonstrate that the same type of E. coli can be described by the well determined operators; we find invariant operator quantities characterizing each type. Such invariant quantities can be calculated from the obtained statistical data.

A pseudo energy-invariant method for relativistic wave equations with Riesz space-fractional derivatives

NASA Astrophysics Data System (ADS)

Macías-Díaz, J. E.; Hendy, A. S.; De Staelen, R. H.

2018-03-01

In this work, we investigate a general nonlinear wave equation with Riesz space-fractional derivatives that generalizes various classical hyperbolic models, including the sine-Gordon and the Klein-Gordon equations from relativistic quantum mechanics. A finite-difference discretization of the model is provided using fractional centered differences. The method is a technique that is capable of preserving an energy-like quantity at each iteration. Some computational comparisons against solutions available in the literature are performed in order to assess the capability of the method to preserve the invariant. Our experiments confirm that the technique yields good approximations to the solutions considered. As an application of our scheme, we provide simulations that confirm, for the first time in the literature, the presence of the phenomenon of nonlinear supratransmission in Riesz space-fractional Klein-Gordon equations driven by a harmonic perturbation at the boundary.

Polarizability tensor invariants of H2, HD, and D2

NASA Astrophysics Data System (ADS)

Raj, Ankit; Hamaguchi, Hiro-o.; Witek, Henryk A.

2018-03-01

We report an exhaustive compilation of wavelength-dependent matrix elements over the mean polarizability (α ¯ ) and polarizability anisotropy (γ) operators for the rovibrational states of the H2, HD, and D2 molecules together with an accompanying computer program for their evaluation. The matrix elements can be readily evaluated using the provided codes for rovibrational states with J = 0-15 and v = 0-4 and for any laser wavelengths in the interval 182.25-1320.6 nm corresponding to popular, commercially available lasers. The presented results substantially extend the scope of the data available in the literature, both in respect of the rovibrational transitions analyzed and the range of covered laser frequencies. The presented detailed tabulation of accurate polarizability tensor invariants is essential for successful realization of our main long-term goal: developing a universal standard for determining absolute Raman cross sections and absolute Raman intensities in experimental Rayleigh and Raman scattering studies of molecules.

Nonlinear model identification and spectral submanifolds for multi-degree-of-freedom mechanical vibrations

NASA Astrophysics Data System (ADS)

Szalai, Robert; Ehrhardt, David; Haller, George

2017-06-01

In a nonlinear oscillatory system, spectral submanifolds (SSMs) are the smoothest invariant manifolds tangent to linear modal subspaces of an equilibrium. Amplitude-frequency plots of the dynamics on SSMs provide the classic backbone curves sought in experimental nonlinear model identification. We develop here, a methodology to compute analytically both the shape of SSMs and their corresponding backbone curves from a data-assimilating model fitted to experimental vibration signals. This model identification utilizes Taken's delay-embedding theorem, as well as a least square fit to the Taylor expansion of the sampling map associated with that embedding. The SSMs are then constructed for the sampling map using the parametrization method for invariant manifolds, which assumes that the manifold is an embedding of, rather than a graph over, a spectral subspace. Using examples of both synthetic and real experimental data, we demonstrate that this approach reproduces backbone curves with high accuracy.

An exact algebraic solution of the infimum in H-infinity optimization with output feedback

NASA Technical Reports Server (NTRS)

Chen, Ben M.; Saberi, Ali; Ly, Uy-Loi

1991-01-01

This paper presents a simple and noniterative procedure for the computation of the exact value of the infimum in the standard H-infinity-optimal control with output feedback. The problem formulation is general and does not place any restrictions on the direct feedthrough terms between the control input and the controlled output variables, and between the disturbance input and the measurement output variables. The method is applicable to systems that satisfy (1) the transfer function from the control input to the controlled output is right-invertible and has no invariant zeros on the j(w) axis and, (2) the transfer function from the disturbance to the measurement output is left-invertible and has no invariant zeros on the j(w) axis. A set of necessary and sufficient conditions for the solvability of H-infinity-almost disturbance decoupling problem via measurement feedback with internal stability is also given.

Numerical study of the geometry of the phase space of the Augmented Hill Three-Body problem

NASA Astrophysics Data System (ADS)

Farrés, Ariadna; Jorba, Àngel; Mondelo, Josep-Maria

2017-09-01

The Augmented Hill Three-Body problem is an extension of the classical Hill problem that, among other applications, has been used to model the motion of a solar sail around an asteroid. This model is a 3 degrees of freedom (3DoF) Hamiltonian system that depends on four parameters. This paper describes the bounded motions (periodic orbits and invariant tori) in an extended neighbourhood of some of the equilibrium points of the model. An interesting feature is the existence of equilibrium points with a 1:1 resonance, whose neighbourhood we also describe. The main tools used are the computation of periodic orbits (including their stability and bifurcations), the reduction of the Hamiltonian to centre manifolds at equilibria, and the numerical approximation of invariant tori. It is remarkable how the combination of these techniques allows the description of the dynamics of a 3DoF Hamiltonian system.

Arnold Diffusion of Charged Particles in ABC Magnetic Fields

NASA Astrophysics Data System (ADS)

Luque, Alejandro; Peralta-Salas, Daniel

2017-06-01

We prove the existence of diffusing solutions in the motion of a charged particle in the presence of ABC magnetic fields. The equations of motion are modeled by a 3DOF Hamiltonian system depending on two parameters. For small values of these parameters, we obtain a normally hyperbolic invariant manifold and we apply the so-called geometric methods for a priori unstable systems developed by A. Delshams, R. de la Llave and T.M. Seara. We characterize explicitly sufficient conditions for the existence of a transition chain of invariant tori having heteroclinic connections, thus obtaining global instability (Arnold diffusion). We also check the obtained conditions in a computer-assisted proof. ABC magnetic fields are the simplest force-free-type solutions of the magnetohydrodynamics equations with periodic boundary conditions, and can be considered as an elementary model for the motion of plasma-charged particles in a tokamak.

Invariant classification of second-order conformally flat superintegrable systems

NASA Astrophysics Data System (ADS)

Capel, J. J.; Kress, J. M.

2014-12-01

In this paper we continue the work of Kalnins et al in classifying all second-order conformally-superintegrable (Laplace-type) systems over conformally flat spaces, using tools from algebraic geometry and classical invariant theory. The results obtained show, through Stäckel equivalence, that the list of known nondegenerate superintegrable systems over three-dimensional conformally flat spaces is complete. In particular, a seven-dimensional manifold is determined such that each point corresponds to a conformal class of superintegrable systems. This manifold is foliated by the nonlinear action of the conformal group in three dimensions. Two systems lie in the same conformal class if and only if they lie in the same leaf of the foliation. This foliation is explicitly described using algebraic varieties formed from representations of the conformal group. The proof of these results rely heavily on Gröbner basis calculations using the computer algebra software packages Maple and Singular.

Global point signature for shape analysis of carpal bones

NASA Astrophysics Data System (ADS)

Chaudhari, Abhijit J.; Leahy, Richard M.; Wise, Barton L.; Lane, Nancy E.; Badawi, Ramsey D.; Joshi, Anand A.

2014-02-01

We present a method based on spectral theory for the shape analysis of carpal bones of the human wrist. We represent the cortical surface of the carpal bone in a coordinate system based on the eigensystem of the two-dimensional Helmholtz equation. We employ a metric—global point signature (GPS)—that exploits the scale and isometric invariance of eigenfunctions to quantify overall bone shape. We use a fast finite-element-method to compute the GPS metric. We capitalize upon the properties of GPS representation—such as stability, a standard Euclidean (ℓ2) metric definition, and invariance to scaling, translation and rotation—to perform shape analysis of the carpal bones of ten women and ten men from a publicly-available database. We demonstrate the utility of the proposed GPS representation to provide a means for comparing shapes of the carpal bones across populations.

Neural-network-based system for recognition of partially occluded shapes and patterns

NASA Astrophysics Data System (ADS)

Mital, Dinesh P.; Teoh, Eam-Khwang; Amarasinghe, S. K.; Suganthan, P. N.

1996-10-01

The purpose of this paper is to demonstrate how a structural matching approach can be used to perfonn effective rotational invariant fingerprint identification. In this approach, each of the exiracted features is correlated with Live of its nearest neighbouring features to form a local feature gmup for a first-stage matching. After that, the feature with the highest match is used as a central feature whereby all the other features are correlated to form a global feature group for a second.stage matching. The correlation between the features is in terms of distance and relative angle. This approach actually make the matching method rotational invariant A substantial amount of testing was carried out and it shows that this matching technique is capable of matching the four basic fingerprint patterns with an average matching time of4 seconds on a 66Mhz, 486 DX personal computer.

Iris recognition using possibilistic fuzzy matching on local features.

PubMed

Tsai, Chung-Chih; Lin, Heng-Yi; Taur, Jinshiuh; Tao, Chin-Wang

2012-02-01

In this paper, we propose a novel possibilistic fuzzy matching strategy with invariant properties, which can provide a robust and effective matching scheme for two sets of iris feature points. In addition, the nonlinear normalization model is adopted to provide more accurate position before matching. Moreover, an effective iris segmentation method is proposed to refine the detected inner and outer boundaries to smooth curves. For feature extraction, the Gabor filters are adopted to detect the local feature points from the segmented iris image in the Cartesian coordinate system and to generate a rotation-invariant descriptor for each detected point. After that, the proposed matching algorithm is used to compute a similarity score for two sets of feature points from a pair of iris images. The experimental results show that the performance of our system is better than those of the systems based on the local features and is comparable to those of the typical systems.

Molecular-dynamics simulations of crosslinking and confinement effects on structure, segmental mobility and mechanics of filled elastomers

NASA Astrophysics Data System (ADS)

Davris, Theodoros; Lyulin, Alexey V.

2016-05-01

The significant drop of the storage modulus under uniaxial deformation (Payne effect) restrains the performance of the elastomer-based composites and the development of possible new applications. In this paper molecular-dynamics (MD) computer simulations using LAMMPS MD package have been performed to study the mechanical properties of a coarse-grained model of this family of nanocomposite materials. Our goal is to provide simulational insights into the viscoelastic properties of filled elastomers, and try to connect the macroscopic mechanics with composite microstructure, the strength of the polymer-filler interactions and the polymer mobility at different scales. To this end we simulate random copolymer films capped between two infinite solid (filler aggregate) walls. We systematically vary the strength of the polymer-substrate adhesion interactions, degree of polymer confinement (film thickness), polymer crosslinking density, and study their influence on the equilibrium and non-equilibrium structure, segmental dynamics, and the mechanical properties of the simulated systems. The glass-transition temperature increases once the mesh size became smaller than the chain radius of gyration; otherwise it remained invariant to mesh-size variations. This increase in the glass-transition temperature was accompanied by a monotonic slowing-down of segmental dynamics on all studied length scales. This observation is attributed to the correspondingly decreased width of the bulk density layer that was obtained in films whose thickness was larger than the end-to-end distance of the bulk polymer chains. To test this hypothesis additional simulations were performed in which the crystalline walls were replaced with amorphous or rough walls.

Spin-dependent post-Newtonian parameters from EMRI computation in Kerr background

NASA Astrophysics Data System (ADS)

Friedman, John; Le Tiec, Alexandre; Shah, Abhay

2013-04-01

Because the extreme mass-ratio inspiral (EMRI) approximation is accurate to all orders in v/c, it can be used to find high order post-Newtonian parameters that are not yet analytically accessible. We report here on progress in computing spin-dependent, conservative, post-Newtonian parameters from a radiation-gauge computation for a particle in circular orbit in a family of Kerr geometries. For a particle with 4-velocity u^α= U k^α, with k^α the helical Killing vector of the perturbed spacetime, the renormalized perturbation δU, when written as a function of the particle's angular velocity, is invariant under gauge transformations generated by helically symmetric vectors. The EMRI computations are done in a modified radiation gauge. Extracted parameters are compared to previously known and newly computed spin-dependent post-Newtonian terms. This work is modeled on earlier computations by Blanchet, Detweiler, Le Tiec and Whiting of spin-independent terms for a particle in circular orbit in a Schwarzschild geometry.

Computational complexities and storage requirements of some Riccati equation solvers

NASA Technical Reports Server (NTRS)

Utku, Senol; Garba, John A.; Ramesh, A. V.

1989-01-01

The linear optimal control problem of an nth-order time-invariant dynamic system with a quadratic performance functional is usually solved by the Hamilton-Jacobi approach. This leads to the solution of the differential matrix Riccati equation with a terminal condition. The bulk of the computation for the optimal control problem is related to the solution of this equation. There are various algorithms in the literature for solving the matrix Riccati equation. However, computational complexities and storage requirements as a function of numbers of state variables, control variables, and sensors are not available for all these algorithms. In this work, the computational complexities and storage requirements for some of these algorithms are given. These expressions show the immensity of the computational requirements of the algorithms in solving the Riccati equation for large-order systems such as the control of highly flexible space structures. The expressions are also needed to compute the speedup and efficiency of any implementation of these algorithms on concurrent machines.

Two-nucleon S10 amplitude zero in chiral effective field theory

NASA Astrophysics Data System (ADS)

Sánchez, M. Sánchez; Yang, C.-J.; Long, Bingwei; van Kolck, U.

2018-02-01

We present a new rearrangement of short-range interactions in the S10 nucleon-nucleon channel within chiral effective field theory. This is intended to address the slow convergence of Weinberg's scheme, which we attribute to its failure to reproduce the amplitude zero (scattering momentum ≃340 MeV) at leading order. After the power counting scheme is modified to accommodate the zero at leading order, it includes subleading corrections perturbatively in a way that is consistent with renormalization-group invariance. Systematic improvement is shown at next-to-leading order, and we obtain results that fit empirical phase shifts remarkably well all the way up to the pion-production threshold. An approach in which pions have been integrated out is included, which allows us to derive analytic results that also fit phenomenology surprisingly well.

Abiotic synthesis of fatty acids

NASA Technical Reports Server (NTRS)

Leach, W. W.; Nooner, D. W.; Oro, J.

1978-01-01

The formation of fatty acids by Fischer-Tropsch-type synthesis was investigated with ferric oxide, ammonium carbonate, potassium carbonate, powdered Pueblito de Allende carbonaceous chondrite, and filings from the Canyon Diablo meteorite used as catalysts. Products were separated and identified by gas chromatography and mass spectrometry. Iron oxide, Pueblito de Allende chondrite, and Canyon Diablo filings in an oxidized catalyst form yielded no fatty acids. Canyon Diablo filings heated overnight at 500 C while undergoing slow purging by deuterium produced fatty acids only when potassium carbonate was admixed; potassium carbonate alone also produced these compounds. The active catalytic combinations gave relatively high yields of aliphatic and aromatic hydrocarbons; substantial amounts of n-alkenes were almost invariably observed when fatty acids were produced; the latter were in the range C6 to C18, with maximum yield in C9 or 10.

Unified presentation of four fundamental inequalities

NASA Astrophysics Data System (ADS)

Lajzerowicz, Joseph; Lehoucq, Roland; Graner, François

2018-03-01

We suggest an unified presentation to teach fundamental constants to graduate students, by introducing four lower limits to observed phenomena. The reduced Planck constant ℏ is the lowest classically definable action. The inverse of invariant speed, s, is the lowest observable slowness. The Planck time, {t}{{P}}, is the lowest observable time scale. The Boltzmann constant, k, determines the lowest coherent degree of freedom; we recall an Einstein criterion on the fluctuations of small thermal systems and show that it has far-reaching implications, such as demonstrating the relations between critical exponents. Each of these four fundamental limits enters in an inequality, which marks a horizon of the Universe we can perceive. This compact presentation can resolve some difficulties encountered when trying to defining the epistemologic status of these constants, and emphasizes their useful role in shaping our intuitive vision of the Universe.

Narayanaswamy’s 1971 aging theory and material time

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

Dyre, Jeppe C., E-mail: dyre@ruc.dk

2015-09-21

The Bochkov-Kuzovlev nonlinear fluctuation-dissipation theorem is used to derive Narayanaswamy’s phenomenological theory of physical aging, in which this highly nonlinear phenomenon is described by a linear material-time convolution integral. A characteristic property of the Narayanaswamy aging description is material-time translational invariance, which is here taken as the basic assumption of the derivation. It is shown that only one possible definition of the material time obeys this invariance, namely, the square of the distance travelled from a configuration of the system far back in time. The paper concludes with suggestions for computer simulations that test for consequences of material-time translational invariance.more » One of these is the “unique-triangles property” according to which any three points on the system’s path form a triangle such that two side lengths determine the third; this is equivalent to the well-known triangular relation for time-autocorrelation functions of aging spin glasses [L. F. Cugliandolo and J. Kurchan, J. Phys. A: Math. Gen. 27, 5749 (1994)]. The unique-triangles property implies a simple geometric interpretation of out-of-equilibrium time-autocorrelation functions, which extends to aging a previously proposed framework for such functions in equilibrium [J. C. Dyre, e-print arXiv:cond-mat/9712222 (1997)].« less

Scale invariance of temporal order discrimination using complex, naturalistic events

PubMed Central

Kwok, Sze Chai; Macaluso, Emiliano

2015-01-01

Recent demonstrations of scale invariance in cognitive domains prompted us to investigate whether a scale-free pattern might exist in retrieving the temporal order of events from episodic memory. We present four experiments using an encoding-retrieval paradigm with naturalistic stimuli (movies or video clips). Our studies show that temporal order judgement retrieval times were negatively correlated with the temporal separation between two events in the movie. This relation held, irrespective of whether temporal distances were on the order of tens of minutes (Exp 1−2) or just a few seconds (Exp 3−4). Using the SIMPLE model, we factored in the retention delays between encoding and retrieval (delays of 24 h, 15 min, 1.5–2.5 s, and 0.5 s for Exp 1–4, respectively) and computed a temporal similarity score for each trial. We found a positive relation between similarity and retrieval times; that is, the more temporally similar two events, the slower the retrieval of their temporal order. Using Bayesian analysis, we confirmed the equivalence of the RT/similarity relation across all experiments, which included a vast range of temporal distances and retention delays. These results provide evidence for scale invariance during the retrieval of temporal order of episodic memories. PMID:25909581

A novel image registration approach via combining local features and geometric invariants

PubMed Central

Lu, Yan; Gao, Kun; Zhang, Tinghua; Xu, Tingfa

2018-01-01

Image registration is widely used in many fields, but the adaptability of the existing methods is limited. This work proposes a novel image registration method with high precision for various complex applications. In this framework, the registration problem is divided into two stages. First, we detect and describe scale-invariant feature points using modified computer vision-oriented fast and rotated brief (ORB) algorithm, and a simple method to increase the performance of feature points matching is proposed. Second, we develop a new local constraint of rough selection according to the feature distances. Evidence shows that the existing matching techniques based on image features are insufficient for the images with sparse image details. Then, we propose a novel matching algorithm via geometric constraints, and establish local feature descriptions based on geometric invariances for the selected feature points. Subsequently, a new price function is constructed to evaluate the similarities between points and obtain exact matching pairs. Finally, we employ the progressive sample consensus method to remove wrong matches and calculate the space transform parameters. Experimental results on various complex image datasets verify that the proposed method is more robust and significantly reduces the rate of false matches while retaining more high-quality feature points. PMID:29293595

Ship detection based on rotation-invariant HOG descriptors for airborne infrared images

NASA Astrophysics Data System (ADS)

Xu, Guojing; Wang, Jinyan; Qi, Shengxiang

2018-03-01

Infrared thermal imagery is widely used in various kinds of aircraft because of its all-time application. Meanwhile, detecting ships from infrared images attract lots of research interests in recent years. In the case of downward-looking infrared imagery, in order to overcome the uncertainty of target imaging attitude due to the unknown position relationship between the aircraft and the target, we propose a new infrared ship detection method which integrates rotation invariant gradient direction histogram (Circle Histogram of Oriented Gradient, C-HOG) descriptors and the support vector machine (SVM) classifier. In details, the proposed method uses HOG descriptors to express the local feature of infrared images to adapt to changes in illumination and to overcome sea clutter effects. Different from traditional computation of HOG descriptor, we subdivide the image into annular spatial bins instead of rectangle sub-regions, and then Radial Gradient Transform (RGT) on the gradient is applied to achieve rotation invariant histogram information. Considering the engineering application of airborne and real-time requirements, we use SVM for training ship target and non-target background infrared sample images to discriminate real ships from false targets. Experimental results show that the proposed method has good performance in both the robustness and run-time for infrared ship target detection with different rotation angles.

Target recognition of log-polar ladar range images using moment invariants

NASA Astrophysics Data System (ADS)

Xia, Wenze; Han, Shaokun; Cao, Jie; Yu, Haoyong

2017-01-01

The ladar range image has received considerable attentions in the automatic target recognition field. However, previous research does not cover target recognition using log-polar ladar range images. Therefore, we construct a target recognition system based on log-polar ladar range images in this paper. In this system combined moment invariants and backpropagation neural network are selected as shape descriptor and shape classifier, respectively. In order to fully analyze the effect of log-polar sampling pattern on recognition result, several comparative experiments based on simulated and real range images are carried out. Eventually, several important conclusions are drawn: (i) if combined moments are computed directly by log-polar range images, translation, rotation and scaling invariant properties of combined moments will be invalid (ii) when object is located in the center of field of view, recognition rate of log-polar range images is less sensitive to the changing of field of view (iii) as object position changes from center to edge of field of view, recognition performance of log-polar range images will decline dramatically (iv) log-polar range images has a better noise robustness than Cartesian range images. Finally, we give a suggestion that it is better to divide field of view into recognition area and searching area in the real application.

A rodent model for the study of invariant visual object recognition

PubMed Central

Zoccolan, Davide; Oertelt, Nadja; DiCarlo, James J.; Cox, David D.

2009-01-01

The human visual system is able to recognize objects despite tremendous variation in their appearance on the retina resulting from variation in view, size, lighting, etc. This ability—known as “invariant” object recognition—is central to visual perception, yet its computational underpinnings are poorly understood. Traditionally, nonhuman primates have been the animal model-of-choice for investigating the neuronal substrates of invariant recognition, because their visual systems closely mirror our own. Meanwhile, simpler and more accessible animal models such as rodents have been largely overlooked as possible models of higher-level visual functions, because their brains are often assumed to lack advanced visual processing machinery. As a result, little is known about rodents' ability to process complex visual stimuli in the face of real-world image variation. In the present work, we show that rats possess more advanced visual abilities than previously appreciated. Specifically, we trained pigmented rats to perform a visual task that required them to recognize objects despite substantial variation in their appearance, due to changes in size, view, and lighting. Critically, rats were able to spontaneously generalize to previously unseen transformations of learned objects. These results provide the first systematic evidence for invariant object recognition in rats and argue for an increased focus on rodents as models for studying high-level visual processing. PMID:19429704

Communication: Studies of the Lennard-Jones fluid in 2, 3, and 4 dimensions highlight the need for a liquid-state 1/d expansion.

PubMed

Costigliola, Lorenzo; Schrøder, Thomas B; Dyre, Jeppe C

2016-06-21

The recent theoretical prediction by Maimbourg and Kurchan [e-print arXiv:1603.05023 (2016)] that for regular pair-potential systems the virial potential-energy correlation coefficient increases towards unity as the dimension d goes to infinity is investigated for the standard 12-6 Lennard-Jones fluid. This is done by computer simulations for d = 2, 3, 4 going from the critical point along the critical isotherm/isochore to higher density/temperature. In both cases the virial potential-energy correlation coefficient increases significantly. For a given density and temperature relative to the critical point, with increasing number of dimension the Lennard-Jones system conforms better to the hidden-scale-invariance property characterized by high virial potential-energy correlations (a property that leads to the existence of isomorphs in the thermodynamic phase diagram, implying that it becomes effectively one-dimensional in regard to structure and dynamics). The present paper also gives the first numerical demonstration of isomorph invariance of structure and dynamics in four dimensions. Our findings emphasize the need for a universally applicable 1/d expansion in liquid-state theory; we conjecture that the systems known to obey hidden scale invariance in three dimensions are those for which the yet-to-be-developed 1/d expansion converges rapidly.

SALSA3D: A Tomographic Model of Compressional Wave Slowness in the Earth’s Mantle for Improved Travel-Time Prediction and Travel-Time Prediction Uncertainty

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

Ballard, Sanford; Hipp, James R.; Begnaud, Michael L.

The task of monitoring the Earth for nuclear explosions relies heavily on seismic data to detect, locate, and characterize suspected nuclear tests. In this study, motivated by the need to locate suspected explosions as accurately and precisely as possible, we developed a tomographic model of the compressional wave slowness in the Earth’s mantle with primary focus on the accuracy and precision of travel-time predictions for P and Pn ray paths through the model. Path-dependent travel-time prediction uncertainties are obtained by computing the full 3D model covariance matrix and then integrating slowness variance and covariance along ray paths from source tomore » receiver. Path-dependent travel-time prediction uncertainties reflect the amount of seismic data that was used in tomography with very low values for paths represented by abundant data in the tomographic data set and very high values for paths through portions of the model that were poorly sampled by the tomography data set. The pattern of travel-time prediction uncertainty is a direct result of the off-diagonal terms of the model covariance matrix and underscores the importance of incorporating the full model covariance matrix in the determination of travel-time prediction uncertainty. In addition, the computed pattern of uncertainty differs significantly from that of 1D distance-dependent travel-time uncertainties computed using traditional methods, which are only appropriate for use with travel times computed through 1D velocity models.« less

SALSA3D: A Tomographic Model of Compressional Wave Slowness in the Earth’s Mantle for Improved Travel-Time Prediction and Travel-Time Prediction Uncertainty

DOE PAGES

Ballard, Sanford; Hipp, James R.; Begnaud, Michael L.; ...

2016-10-11

The task of monitoring the Earth for nuclear explosions relies heavily on seismic data to detect, locate, and characterize suspected nuclear tests. In this study, motivated by the need to locate suspected explosions as accurately and precisely as possible, we developed a tomographic model of the compressional wave slowness in the Earth’s mantle with primary focus on the accuracy and precision of travel-time predictions for P and Pn ray paths through the model. Path-dependent travel-time prediction uncertainties are obtained by computing the full 3D model covariance matrix and then integrating slowness variance and covariance along ray paths from source tomore » receiver. Path-dependent travel-time prediction uncertainties reflect the amount of seismic data that was used in tomography with very low values for paths represented by abundant data in the tomographic data set and very high values for paths through portions of the model that were poorly sampled by the tomography data set. The pattern of travel-time prediction uncertainty is a direct result of the off-diagonal terms of the model covariance matrix and underscores the importance of incorporating the full model covariance matrix in the determination of travel-time prediction uncertainty. In addition, the computed pattern of uncertainty differs significantly from that of 1D distance-dependent travel-time uncertainties computed using traditional methods, which are only appropriate for use with travel times computed through 1D velocity models.« less

Observing and modeling the spectrum of a slow slip event: Constraints on the scaling of slow slip and tremor

NASA Astrophysics Data System (ADS)

Hawthorne, J. C.; Bartlow, N. M.; Ghosh, A.

2017-12-01

We estimate the normalized moment rate spectrum of a slow slip event in Cascadia and then attempt to reproduce it. Our goal is to further assess whether a single physical mechanism could govern slow slip and tremor events, with durations that span 6 orders of magnitude, so we construct the spectrum by parameterizing a large slow slip event as the sum of a number of subevents with various durations. The spectrum estimate uses data from three sources: the GPS-based slip inversion of Bartlow et al (2011), PBO borehole strain measurements, and beamforming-based tremor moment estimates of Ghosh et al (2009). We find that at periods shorter than 1 day, the moment rate power spectrum decays as frequencyn, where n is between 0.7 and 1.4 when measured from strain and between 1.2 and 1.4 when inferred from tremor. The spectrum appears roughly flat at periods of 1 to 10 days, as both the 1-day-period strain and tremor data and the 6-day-period slip inversion data imply a moment rate power of 0.02 times the the total moment squared. We demonstrate one way to reproduce this spectrum: by constructing the large-scale slow slip event as the sum of a series of subevents. The shortest of these subevents could be interpreted as VLFEs or even LFEs, while longer subevents might represent the aseismic slip that drives rapid tremor reverals, streaks, or rapid tremor migrations. We pick the subevent magnitudes from a Gutenberg-Richter distribution and place the events randomly throughout a 30-day interval. Then we assign each subevent a duration that scales with its moment to a specified power. Finally, we create a moment rate function for each subevent and sum all of the moment rates. We compute the summed slow slip moment rate spectra with two approaches: a time-domain numerical computation and a frequency-domain analytical summation. Several sets of subevent parameters can allow the constructed slow slip event to match the observed spectrum. One allowable set of parameters is of particular interest: a b-value of 1 coupled with subevent durations that scale linearly with their moments, as suggested by previous observations of slow earthquakes (Ide et al, 2007). Our work thus lends further plausibility to the existence of a single family of slow earthquakes, possibly governed by a single physical mechanism.

Methods for Assessing Item, Step, and Threshold Invariance in Polytomous Items Following the Partial Credit Model

ERIC Educational Resources Information Center

Penfield, Randall D.; Myers, Nicholas D.; Wolfe, Edward W.

2008-01-01

Measurement invariance in the partial credit model (PCM) can be conceptualized in several different but compatible ways. In this article the authors distinguish between three forms of measurement invariance in the PCM: step invariance, item invariance, and threshold invariance. Approaches for modeling these three forms of invariance are proposed,…

Noncommutative Jackiw-Pi model: One-loop renormalization

NASA Astrophysics Data System (ADS)

Bufalo, R.; Ghasemkhani, M.; Alipour, M.

2018-06-01

In this paper, we study the quantum behavior of the noncommutative Jackiw-Pi model. After establishing the Becchi-Rouet-Store-Tyutin (BRST) invariant action, the perturbative renormalizability is discussed, allowing us to introduce the renormalized mass and gauge coupling. We then proceed to compute the one-loop correction to the basic 1PI functions, necessary to determine the renormalized parameters (mass and charge), next we discuss the physical behavior of these parameters.

Pattern recognition neural-net by spatial mapping of biology visual field

NASA Astrophysics Data System (ADS)

Lin, Xin; Mori, Masahiko

2000-05-01

The method of spatial mapping in biology vision field is applied to artificial neural networks for pattern recognition. By the coordinate transform that is called the complex-logarithm mapping and Fourier transform, the input images are transformed into scale- rotation- and shift- invariant patterns, and then fed into a multilayer neural network for learning and recognition. The results of computer simulation and an optical experimental system are described.

A Reduced Dimension Static, Linearized Kalman Filter and Smoother

NASA Technical Reports Server (NTRS)

Fukumori, I.

1995-01-01

An approximate Kalman filter and smoother, based on approximations of the state estimation error covariance matrix, is described. Approximations include a reduction of the effective state dimension, use of a static asymptotic error limit, and a time-invariant linearization of the dynamic model for error integration. The approximations lead to dramatic computational savings in applying estimation theory to large complex systems. Examples of use come from TOPEX/POSEIDON.

Addressing Security Challenges in Pervasive Computing Applications

DTIC Science & Technology

2010-10-10

Personalized Privacy for Location - Based Services ", Transactions on Data Privacy, 2(1), 2009. 22. Indrakshi Ray, Indrajit Ray and Sudip Chakraborty, "An...Dewri, Indrakshi Ray, Indrajit Ray and Darrell Whitley, "Query m-Invariance: Pre- venting Query Disclosures in Continuous Location - Based Services ", Proceedings...location information is used to provide better services. Often such applications need continuous location - based services (LBS) where the mobile object must

The Butterfly and the Photon:. New Perspectives on Unpredictability, and the Notion of Casual Reality, in Quantum Physics

NASA Astrophysics Data System (ADS)

Palmer, T. N.

2012-12-01

This essay discusses a proposal that draws together the three great revolutionary theories of 20th Century physics: quantum theory, relativity theory and chaos theory. Motivated by the Bohmian notion of implicate order, and what in chaos theory would be described as a strange attractor, the proposal attributes special ontological significance to certain non-computable, dynamically invariant state-space geometries for the universe as a whole. Studying the phenomenon of quantum interference, it is proposed to understand quantum wave-particle duality, and indeed classical electromagnetism, in terms of particles in space time and waves on this state space geometry. Studying the EPR experiment, the acausal constraints that this invariant geometry provides on spatially distant degrees of freedom, provides a way for the underlying dynamics to be consistent with the Bell theorem, yet be relativistically covariant ("nonlocality without nonlocality"). It is suggested that the physical basis for such non-computable geometries lies in properties of gravity with the information irreversibility implied by black hole no-hair theorems being crucial. In conclusion it is proposed that quantum theory may be emergent from an extended theory of gravity which is geometric not only in space time, but also in state space. Such a notion would undermine most current attempts to "quantise gravity".

Black hole meiosis

NASA Astrophysics Data System (ADS)

van Herck, Walter; Wyder, Thomas

2010-04-01

The enumeration of BPS bound states in string theory needs refinement. Studying partition functions of particles made from D-branes wrapped on algebraic Calabi-Yau 3-folds, and classifying states using split attractor flow trees, we extend the method for computing a refined BPS index, [1]. For certain D-particles, a finite number of microstates, namely polar states, exclusively realized as bound states, determine an entire partition function (elliptic genus). This underlines their crucial importance: one might call them the ‘chromosomes’ of a D-particle or a black hole. As polar states also can be affected by our refinement, previous predictions on elliptic genera are modified. This can be metaphorically interpreted as ‘crossing-over in the meiosis of a D-particle’. Our results improve on [2], provide non-trivial evidence for a strong split attractor flow tree conjecture, and thus suggest that we indeed exhaust the BPS spectrum. In the D-brane description of a bound state, the necessity for refinement results from the fact that tachyonic strings split up constituent states into ‘generic’ and ‘special’ states. These are enumerated separately by topological invariants, which turn out to be partitions of Donaldson-Thomas invariants. As modular predictions provide a check on many of our results, we have compelling evidence that our computations are correct.

Topological strings on singular elliptic Calabi-Yau 3-folds and minimal 6d SCFTs

NASA Astrophysics Data System (ADS)

Del Zotto, Michele; Gu, Jie; Huang, Min-xin; Kashani-Poor, Amir-Kian; Klemm, Albrecht; Lockhart, Guglielmo

2018-03-01

We apply the modular approach to computing the topological string partition function on non-compact elliptically fibered Calabi-Yau 3-folds with higher Kodaira singularities in the fiber. The approach consists in making an ansatz for the partition function at given base degree, exact in all fiber classes to arbitrary order and to all genus, in terms of a rational function of weak Jacobi forms. Our results yield, at given base degree, the elliptic genus of the corresponding non-critical 6d string, and thus the associated BPS invariants of the 6d theory. The required elliptic indices are determined from the chiral anomaly 4-form of the 2d worldsheet theories, or the 8-form of the corresponding 6d theories, and completely fix the holomorphic anomaly equation constraining the partition function. We introduce subrings of the known rings of Weyl invariant Jacobi forms which are adapted to the additional symmetries of the partition function, making its computation feasible to low base wrapping number. In contradistinction to the case of simpler singularities, generic vanishing conditions on BPS numbers are no longer sufficient to fix the modular ansatz at arbitrary base wrapping degree. We show that to low degree, imposing exact vanishing conditions does suffice, and conjecture this to be the case generally.