The literary uses of high-dimensional space

Directory of Open Access Journals (Sweden)

Ted Underwood

2015-12-01

Full Text Available Debates over “Big Data” shed more heat than light in the humanities, because the term ascribes new importance to statistical methods without explaining how those methods have changed. What we badly need instead is a conversation about the substantive innovations that have made statistical modeling useful for disciplines where, in the past, it truly wasn’t. These innovations are partly technical, but more fundamentally expressed in what Leo Breiman calls a new “culture” of statistical modeling. Where 20th-century methods often required humanists to squeeze our unstructured texts, sounds, or images into some special-purpose data model, new methods can handle unstructured evidence more directly by modeling it in a high-dimensional space. This opens a range of research opportunities that humanists have barely begun to discuss. To date, topic modeling has received most attention, but in the long run, supervised predictive models may be even more important. I sketch their potential by describing how Jordan Sellers and I have begun to model poetic distinction in the long 19th century—revealing an arc of gradual change much longer than received literary histories would lead us to expect.

SHOVAV-JUEL. A one dimensional space-time kinetic code for pebble-bed high-temperature reactors with temperature and Xenon feedback

International Nuclear Information System (INIS)

Nabbi, R.; Meister, G.; Finken, R.; Haben, M.

1982-09-01

The present report describes the modelling basis and the structure of the neutron kinetics-code SHOVAV-Juel. Information for users is given regarding the application of the code and the generation of the input data. SHOVAV-Juel is a one-dimensional space-time-code based on a multigroup diffusion approach for four energy groups and six groups of delayed neutrons. It has been developed for the analysis of the transient behaviour of high temperature reactors with pebble-bed core. The reactor core is modelled by horizontal segments to which different materials compositions can be assigned. The temperature dependence of the reactivity is taken into account by using temperature dependent neutron cross sections. For the simulation of transients in an extended time range the time dependence of the reactivity absorption by Xenon-135 is taken into account. (orig./RW)

Non-intrusive low-rank separated approximation of high-dimensional stochastic models

KAUST Repository

Doostan, Alireza; Validi, AbdoulAhad; Iaccarino, Gianluca

2013-01-01

This work proposes a sampling-based (non-intrusive) approach within the context of low-. rank separated representations to tackle the issue of curse-of-dimensionality associated with the solution of models, e.g., PDEs/ODEs, with high-dimensional random inputs. Under some conditions discussed in details, the number of random realizations of the solution, required for a successful approximation, grows linearly with respect to the number of random inputs. The construction of the separated representation is achieved via a regularized alternating least-squares regression, together with an error indicator to estimate model parameters. The computational complexity of such a construction is quadratic in the number of random inputs. The performance of the method is investigated through its application to three numerical examples including two ODE problems with high-dimensional random inputs. © 2013 Elsevier B.V.

Non-intrusive low-rank separated approximation of high-dimensional stochastic models

KAUST Repository

Doostan, Alireza

2013-08-01

This work proposes a sampling-based (non-intrusive) approach within the context of low-. rank separated representations to tackle the issue of curse-of-dimensionality associated with the solution of models, e.g., PDEs/ODEs, with high-dimensional random inputs. Under some conditions discussed in details, the number of random realizations of the solution, required for a successful approximation, grows linearly with respect to the number of random inputs. The construction of the separated representation is achieved via a regularized alternating least-squares regression, together with an error indicator to estimate model parameters. The computational complexity of such a construction is quadratic in the number of random inputs. The performance of the method is investigated through its application to three numerical examples including two ODE problems with high-dimensional random inputs. © 2013 Elsevier B.V.

On the space dimensionality based on metrics

International Nuclear Information System (INIS)

Gorelik, G.E.

1978-01-01

A new approach to space time dimensionality is suggested, which permits to take into account the possibility of altering dimensionality depending on the phenomenon scale. An attempt is made to give the definition of dimensionality, equivalent to a conventional definition for the Euclidean space and variety. The conventional definition of variety dimensionality is connected with the possibility of homeomorphic reflection of the Euclidean space on some region of each variety point

Variance inflation in high dimensional Support Vector Machines

DEFF Research Database (Denmark)

Abrahamsen, Trine Julie; Hansen, Lars Kai

2013-01-01

Many important machine learning models, supervised and unsupervised, are based on simple Euclidean distance or orthogonal projection in a high dimensional feature space. When estimating such models from small training sets we face the problem that the span of the training data set input vectors...... the case of Support Vector Machines (SVMS) and we propose a non-parametric scheme to restore proper generalizability. We illustrate the algorithm and its ability to restore performance on a wide range of benchmark data sets....... follow a different probability law with less variance. While the problem and basic means to reconstruct and deflate are well understood in unsupervised learning, the case of supervised learning is less well understood. We here investigate the effect of variance inflation in supervised learning including...

Four Dimensional Trace Space Measurement

Energy Technology Data Exchange (ETDEWEB)

Hernandez, M.

2005-02-10

Future high energy colliders and FELs (Free Electron Lasers) such as the proposed LCLS (Linac Coherent Light Source) at SLAC require high brightness electron beams. In general a high brightness electron beam will contain a large number of electrons that occupy a short longitudinal duration, can be focused to a small transverse area while having small transverse divergences. Therefore the beam must have a high peak current and occupy small areas in transverse phase space and so have small transverse emittances. Additionally the beam should propagate at high energy and have a low energy spread to reduce chromatic effects. The requirements of the LCLS for example are pulses which contain 10{sup 10} electrons in a temporal duration of 10 ps FWHM with projected normalized transverse emittances of 1{pi} mm mrad[1]. Currently the most promising method of producing such a beam is the RF photoinjector. The GTF (Gun Test Facility) at SLAC was constructed to produce and characterize laser and electron beams which fulfill the LCLS requirements. Emittance measurements of the electron beam at the GTF contain evidence of strong coupling between the transverse dimensions of the beam. This thesis explores the effects of this coupling on the determination of the projected emittances of the electron beam. In the presence of such a coupling the projected normalized emittance is no longer a conserved quantity. The conserved quantity is the normalized full four dimensional phase space occupied by the beam. A method to determine the presence and evaluate the strength of the coupling in emittance measurements made in the laboratory is developed. A method to calculate the four dimensional volume the beam occupies in phase space using quantities available in the laboratory environment is also developed. Results of measurements made of the electron beam at the GTF that demonstrate these concepts are presented and discussed.

Representations of space based on haptic input

NARCIS (Netherlands)

Zuidhoek, S.

2005-01-01

The present thesis focused on the representations of grasping space based on haptic input. We aimed at identifying their characteristics, and the underlying neurocognitive processes and mechanisms. To this end, we studied the systematic distortions in performance on several orientation perception

Gaussian processes with built-in dimensionality reduction: Applications to high-dimensional uncertainty propagation

International Nuclear Information System (INIS)

Tripathy, Rohit; Bilionis, Ilias; Gonzalez, Marcial

2016-01-01

Uncertainty quantification (UQ) tasks, such as model calibration, uncertainty propagation, and optimization under uncertainty, typically require several thousand evaluations of the underlying computer codes. To cope with the cost of simulations, one replaces the real response surface with a cheap surrogate based, e.g., on polynomial chaos expansions, neural networks, support vector machines, or Gaussian processes (GP). However, the number of simulations required to learn a generic multivariate response grows exponentially as the input dimension increases. This curse of dimensionality can only be addressed, if the response exhibits some special structure that can be discovered and exploited. A wide range of physical responses exhibit a special structure known as an active subspace (AS). An AS is a linear manifold of the stochastic space characterized by maximal response variation. The idea is that one should first identify this low dimensional manifold, project the high-dimensional input onto it, and then link the projection to the output. If the dimensionality of the AS is low enough, then learning the link function is a much easier problem than the original problem of learning a high-dimensional function. The classic approach to discovering the AS requires gradient information, a fact that severely limits its applicability. Furthermore, and partly because of its reliance to gradients, it is not able to handle noisy observations. The latter is an essential trait if one wants to be able to propagate uncertainty through stochastic simulators, e.g., through molecular dynamics codes. In this work, we develop a probabilistic version of AS which is gradient-free and robust to observational noise. Our approach relies on a novel Gaussian process regression with built-in dimensionality reduction. In particular, the AS is represented as an orthogonal projection matrix that serves as yet another covariance function hyper-parameter to be estimated from the data. To train the

Gaussian processes with built-in dimensionality reduction: Applications to high-dimensional uncertainty propagation

Science.gov (United States)

Tripathy, Rohit; Bilionis, Ilias; Gonzalez, Marcial

2016-09-01

Uncertainty quantification (UQ) tasks, such as model calibration, uncertainty propagation, and optimization under uncertainty, typically require several thousand evaluations of the underlying computer codes. To cope with the cost of simulations, one replaces the real response surface with a cheap surrogate based, e.g., on polynomial chaos expansions, neural networks, support vector machines, or Gaussian processes (GP). However, the number of simulations required to learn a generic multivariate response grows exponentially as the input dimension increases. This curse of dimensionality can only be addressed, if the response exhibits some special structure that can be discovered and exploited. A wide range of physical responses exhibit a special structure known as an active subspace (AS). An AS is a linear manifold of the stochastic space characterized by maximal response variation. The idea is that one should first identify this low dimensional manifold, project the high-dimensional input onto it, and then link the projection to the output. If the dimensionality of the AS is low enough, then learning the link function is a much easier problem than the original problem of learning a high-dimensional function. The classic approach to discovering the AS requires gradient information, a fact that severely limits its applicability. Furthermore, and partly because of its reliance to gradients, it is not able to handle noisy observations. The latter is an essential trait if one wants to be able to propagate uncertainty through stochastic simulators, e.g., through molecular dynamics codes. In this work, we develop a probabilistic version of AS which is gradient-free and robust to observational noise. Our approach relies on a novel Gaussian process regression with built-in dimensionality reduction. In particular, the AS is represented as an orthogonal projection matrix that serves as yet another covariance function hyper-parameter to be estimated from the data. To train the

Gaussian processes with built-in dimensionality reduction: Applications to high-dimensional uncertainty propagation

Energy Technology Data Exchange (ETDEWEB)

Tripathy, Rohit, E-mail: rtripath@purdue.edu; Bilionis, Ilias, E-mail: ibilion@purdue.edu; Gonzalez, Marcial, E-mail: marcial-gonzalez@purdue.edu

2016-09-15

Uncertainty quantification (UQ) tasks, such as model calibration, uncertainty propagation, and optimization under uncertainty, typically require several thousand evaluations of the underlying computer codes. To cope with the cost of simulations, one replaces the real response surface with a cheap surrogate based, e.g., on polynomial chaos expansions, neural networks, support vector machines, or Gaussian processes (GP). However, the number of simulations required to learn a generic multivariate response grows exponentially as the input dimension increases. This curse of dimensionality can only be addressed, if the response exhibits some special structure that can be discovered and exploited. A wide range of physical responses exhibit a special structure known as an active subspace (AS). An AS is a linear manifold of the stochastic space characterized by maximal response variation. The idea is that one should first identify this low dimensional manifold, project the high-dimensional input onto it, and then link the projection to the output. If the dimensionality of the AS is low enough, then learning the link function is a much easier problem than the original problem of learning a high-dimensional function. The classic approach to discovering the AS requires gradient information, a fact that severely limits its applicability. Furthermore, and partly because of its reliance to gradients, it is not able to handle noisy observations. The latter is an essential trait if one wants to be able to propagate uncertainty through stochastic simulators, e.g., through molecular dynamics codes. In this work, we develop a probabilistic version of AS which is gradient-free and robust to observational noise. Our approach relies on a novel Gaussian process regression with built-in dimensionality reduction. In particular, the AS is represented as an orthogonal projection matrix that serves as yet another covariance function hyper-parameter to be estimated from the data. To train the

Teleportation schemes in infinite dimensional Hilbert spaces

International Nuclear Information System (INIS)

Fichtner, Karl-Heinz; Freudenberg, Wolfgang; Ohya, Masanori

2005-01-01

The success of quantum mechanics is due to the discovery that nature is described in infinite dimension Hilbert spaces, so that it is desirable to demonstrate the quantum teleportation process in a certain infinite dimensional Hilbert space. We describe the teleportation process in an infinite dimensional Hilbert space by giving simple examples

Discrete symmetries and coset space dimensional reduction

International Nuclear Information System (INIS)

Kapetanakis, D.; Zoupanos, G.

1989-01-01

We consider the discrete symmetries of all the six-dimensional coset spaces and we apply them in gauge theories defined in ten dimensions which are dimensionally reduced over these homogeneous spaces. Particular emphasis is given in the consequences of the discrete symmetries on the particle content as well as on the symmetry breaking a la Hosotani of the resulting four-dimensional theory. (orig.)

A sparse grid based method for generative dimensionality reduction of high-dimensional data

Science.gov (United States)

Bohn, Bastian; Garcke, Jochen; Griebel, Michael

2016-03-01

Generative dimensionality reduction methods play an important role in machine learning applications because they construct an explicit mapping from a low-dimensional space to the high-dimensional data space. We discuss a general framework to describe generative dimensionality reduction methods, where the main focus lies on a regularized principal manifold learning variant. Since most generative dimensionality reduction algorithms exploit the representer theorem for reproducing kernel Hilbert spaces, their computational costs grow at least quadratically in the number n of data. Instead, we introduce a grid-based discretization approach which automatically scales just linearly in n. To circumvent the curse of dimensionality of full tensor product grids, we use the concept of sparse grids. Furthermore, in real-world applications, some embedding directions are usually more important than others and it is reasonable to refine the underlying discretization space only in these directions. To this end, we employ a dimension-adaptive algorithm which is based on the ANOVA (analysis of variance) decomposition of a function. In particular, the reconstruction error is used to measure the quality of an embedding. As an application, the study of large simulation data from an engineering application in the automotive industry (car crash simulation) is performed.

Coset space dimensional reduction of gauge theories

Energy Technology Data Exchange (ETDEWEB)

Kapetanakis, D. (Physik Dept., Technische Univ. Muenchen, Garching (Germany)); Zoupanos, G. (CERN, Geneva (Switzerland))

1992-10-01

We review the attempts to construct unified theories defined in higher dimensions which are dimensionally reduced over coset spaces. We employ the coset space dimensional reduction scheme, which permits the detailed study of the resulting four-dimensional gauge theories. In the context of this scheme we present the difficulties and the suggested ways out in the attempts to describe the observed interactions in a realistic way. (orig.).

Coset space dimensional reduction of gauge theories

International Nuclear Information System (INIS)

Kapetanakis, D.; Zoupanos, G.

1992-01-01

We review the attempts to construct unified theories defined in higher dimensions which are dimensionally reduced over coset spaces. We employ the coset space dimensional reduction scheme, which permits the detailed study of the resulting four-dimensional gauge theories. In the context of this scheme we present the difficulties and the suggested ways out in the attempts to describe the observed interactions in a realistic way. (orig.)

Fractal electrodynamics via non-integer dimensional space approach

Science.gov (United States)

Tarasov, Vasily E.

2015-09-01

Using the recently suggested vector calculus for non-integer dimensional space, we consider electrodynamics problems in isotropic case. This calculus allows us to describe fractal media in the framework of continuum models with non-integer dimensional space. We consider electric and magnetic fields of fractal media with charges and currents in the framework of continuum models with non-integer dimensional spaces. An application of the fractal Gauss's law, the fractal Ampere's circuital law, the fractal Poisson equation for electric potential, and equation for fractal stream of charges are suggested. Lorentz invariance and speed of light in fractal electrodynamics are discussed. An expression for effective refractive index of non-integer dimensional space is suggested.

On infinite-dimensional state spaces

International Nuclear Information System (INIS)

Fritz, Tobias

2013-01-01

It is well known that the canonical commutation relation [x, p]=i can be realized only on an infinite-dimensional Hilbert space. While any finite set of experimental data can also be explained in terms of a finite-dimensional Hilbert space by approximating the commutation relation, Occam's razor prefers the infinite-dimensional model in which [x, p]=i holds on the nose. This reasoning one will necessarily have to make in any approach which tries to detect the infinite-dimensionality. One drawback of using the canonical commutation relation for this purpose is that it has unclear operational meaning. Here, we identify an operationally well-defined context from which an analogous conclusion can be drawn: if two unitary transformations U, V on a quantum system satisfy the relation V −1 U 2 V=U 3 , then finite-dimensionality entails the relation UV −1 UV=V −1 UVU; this implication strongly fails in some infinite-dimensional realizations. This is a result from combinatorial group theory for which we give a new proof. This proof adapts to the consideration of cases where the assumed relation V −1 U 2 V=U 3 holds only up to ε and then yields a lower bound on the dimension.

On infinite-dimensional state spaces

Science.gov (United States)

Fritz, Tobias

2013-05-01

It is well known that the canonical commutation relation [x, p] = i can be realized only on an infinite-dimensional Hilbert space. While any finite set of experimental data can also be explained in terms of a finite-dimensional Hilbert space by approximating the commutation relation, Occam's razor prefers the infinite-dimensional model in which [x, p] = i holds on the nose. This reasoning one will necessarily have to make in any approach which tries to detect the infinite-dimensionality. One drawback of using the canonical commutation relation for this purpose is that it has unclear operational meaning. Here, we identify an operationally well-defined context from which an analogous conclusion can be drawn: if two unitary transformations U, V on a quantum system satisfy the relation V-1U2V = U3, then finite-dimensionality entails the relation UV-1UV = V-1UVU; this implication strongly fails in some infinite-dimensional realizations. This is a result from combinatorial group theory for which we give a new proof. This proof adapts to the consideration of cases where the assumed relation V-1U2V = U3 holds only up to ɛ and then yields a lower bound on the dimension.

TSAR: a program for automatic resonance assignment using 2D cross-sections of high dimensionality, high-resolution spectra

Energy Technology Data Exchange (ETDEWEB)

Zawadzka-Kazimierczuk, Anna; Kozminski, Wiktor [University of Warsaw, Faculty of Chemistry (Poland); Billeter, Martin, E-mail: martin.billeter@chem.gu.se [University of Gothenburg, Biophysics Group, Department of Chemistry and Molecular Biology (Sweden)

2012-09-15

While NMR studies of proteins typically aim at structure, dynamics or interactions, resonance assignments represent in almost all cases the initial step of the analysis. With increasing complexity of the NMR spectra, for example due to decreasing extent of ordered structure, this task often becomes both difficult and time-consuming, and the recording of high-dimensional data with high-resolution may be essential. Random sampling of the evolution time space, combined with sparse multidimensional Fourier transform (SMFT), allows for efficient recording of very high dimensional spectra ({>=}4 dimensions) while maintaining high resolution. However, the nature of this data demands for automation of the assignment process. Here we present the program TSAR (Tool for SMFT-based Assignment of Resonances), which exploits all advantages of SMFT input. Moreover, its flexibility allows to process data from any type of experiments that provide sequential connectivities. The algorithm was tested on several protein samples, including a disordered 81-residue fragment of the {delta} subunit of RNA polymerase from Bacillus subtilis containing various repetitive sequences. For our test examples, TSAR achieves a high percentage of assigned residues without any erroneous assignments.

High Input Voltage, Silicon Carbide Power Processing Unit Performance Demonstration

Science.gov (United States)

Bozak, Karin E.; Pinero, Luis R.; Scheidegger, Robert J.; Aulisio, Michael V.; Gonzalez, Marcelo C.; Birchenough, Arthur G.

2015-01-01

A silicon carbide brassboard power processing unit has been developed by the NASA Glenn Research Center in Cleveland, Ohio. The power processing unit operates from two sources: a nominal 300 Volt high voltage input bus and a nominal 28 Volt low voltage input bus. The design of the power processing unit includes four low voltage, low power auxiliary supplies, and two parallel 7.5 kilowatt (kW) discharge power supplies that are capable of providing up to 15 kilowatts of total power at 300 to 500 Volts (V) to the thruster. Additionally, the unit contains a housekeeping supply, high voltage input filter, low voltage input filter, and master control board, such that the complete brassboard unit is capable of operating a 12.5 kilowatt Hall effect thruster. The performance of the unit was characterized under both ambient and thermal vacuum test conditions, and the results demonstrate exceptional performance with full power efficiencies exceeding 97%. The unit was also tested with a 12.5kW Hall effect thruster to verify compatibility and output filter specifications. With space-qualified silicon carbide or similar high voltage, high efficiency power devices, this would provide a design solution to address the need for high power electric propulsion systems.

Individual-based models for adaptive diversification in high-dimensional phenotype spaces.

Science.gov (United States)

Ispolatov, Iaroslav; Madhok, Vaibhav; Doebeli, Michael

2016-02-07

Most theories of evolutionary diversification are based on equilibrium assumptions: they are either based on optimality arguments involving static fitness landscapes, or they assume that populations first evolve to an equilibrium state before diversification occurs, as exemplified by the concept of evolutionary branching points in adaptive dynamics theory. Recent results indicate that adaptive dynamics may often not converge to equilibrium points and instead generate complicated trajectories if evolution takes place in high-dimensional phenotype spaces. Even though some analytical results on diversification in complex phenotype spaces are available, to study this problem in general we need to reconstruct individual-based models from the adaptive dynamics generating the non-equilibrium dynamics. Here we first provide a method to construct individual-based models such that they faithfully reproduce the given adaptive dynamics attractor without diversification. We then show that a propensity to diversify can be introduced by adding Gaussian competition terms that generate frequency dependence while still preserving the same adaptive dynamics. For sufficiently strong competition, the disruptive selection generated by frequency-dependence overcomes the directional evolution along the selection gradient and leads to diversification in phenotypic directions that are orthogonal to the selection gradient. Copyright © 2015 Elsevier Ltd. All rights reserved.

High Resolution Modeling of the Thermospheric Response to Energy Inputs During the RENU-2 Rocket Flight

Science.gov (United States)

Walterscheid, R. L.; Brinkman, D. G.; Clemmons, J. H.; Hecht, J. H.; Lessard, M.; Fritz, B.; Hysell, D. L.; Clausen, L. B. N.; Moen, J.; Oksavik, K.; Yeoman, T. K.

2017-12-01

The Earth's magnetospheric cusp provides direct access of energetic particles to the thermosphere. These particles produce ionization and kinetic (particle) heating of the atmosphere. The increased ionization coupled with enhanced electric fields in the cusp produces increased Joule heating and ion drag forcing. These energy inputs cause large wind and temperature changes in the cusp region. The Rocket Experiment for Neutral Upwelling -2 (RENU-2) launched from Andoya, Norway at 0745UT on 13 December 2015 into the ionosphere-thermosphere beneath the magnetic cusp. It made measurements of the energy inputs (e.g., precipitating particles, electric fields) and the thermospheric response to these energy inputs (e.g., neutral density and temperature, neutral winds). Complementary ground based measurements were made. In this study, we use a high resolution two-dimensional time-dependent non hydrostatic nonlinear dynamical model driven by rocket and ground based measurements of the energy inputs to simulate the thermospheric response during the RENU-2 flight. Model simulations will be compared to the corresponding measurements of the thermosphere to see what they reveal about thermospheric structure and the nature of magnetosphere-ionosphere-thermosphere coupling in the cusp. Acknowledgements: This material is based upon work supported by the National Aeronautics and Space Administration under Grants: NNX16AH46G and NNX13AJ93G. This research was also supported by The Aerospace Corporation's Technical Investment program

High-Dimensional Function Approximation With Neural Networks for Large Volumes of Data.

Science.gov (United States)

Andras, Peter

2018-02-01

Approximation of high-dimensional functions is a challenge for neural networks due to the curse of dimensionality. Often the data for which the approximated function is defined resides on a low-dimensional manifold and in principle the approximation of the function over this manifold should improve the approximation performance. It has been show that projecting the data manifold into a lower dimensional space, followed by the neural network approximation of the function over this space, provides a more precise approximation of the function than the approximation of the function with neural networks in the original data space. However, if the data volume is very large, the projection into the low-dimensional space has to be based on a limited sample of the data. Here, we investigate the nature of the approximation error of neural networks trained over the projection space. We show that such neural networks should have better approximation performance than neural networks trained on high-dimensional data even if the projection is based on a relatively sparse sample of the data manifold. We also find that it is preferable to use a uniformly distributed sparse sample of the data for the purpose of the generation of the low-dimensional projection. We illustrate these results considering the practical neural network approximation of a set of functions defined on high-dimensional data including real world data as well.

Data analysis in high-dimensional sparse spaces

DEFF Research Database (Denmark)

Clemmensen, Line Katrine Harder

classification techniques for high-dimensional problems are presented: Sparse discriminant analysis, sparse mixture discriminant analysis and orthogonality constrained support vector machines. The first two introduces sparseness to the well known linear and mixture discriminant analysis and thereby provide low...... are applied to classifications of fish species, ear canal impressions used in the hearing aid industry, microbiological fungi species, and various cancerous tissues and healthy tissues. In addition, novel applications of sparse regressions (also called the elastic net) to the medical, concrete, and food...

Three-dimensional oscillator and Coulomb systems reduced from Kaehler spaces

International Nuclear Information System (INIS)

Nersessian, Armen; Yeranyan, Armen

2004-01-01

We define the oscillator and Coulomb systems on four-dimensional spaces with U(2)-invariant Kaehler metric and perform their Hamiltonian reduction to the three-dimensional oscillator and Coulomb systems specified by the presence of Dirac monopoles. We find the Kaehler spaces with conic singularity, where the oscillator and Coulomb systems on three-dimensional sphere and two-sheet hyperboloid originate. Then we construct the superintegrable oscillator system on three-dimensional sphere and hyperboloid, coupled to a monopole, and find their four-dimensional origins. In the latter case the metric of configuration space is a non-Kaehler one. Finally, we extend these results to the family of Kaehler spaces with conic singularities

On dimensional reduction over coset spaces

International Nuclear Information System (INIS)

Kapetanakis, D.; Zoupanos, G.

1990-01-01

Gauge theories defined in higher dimensions can be dimensionally reduced over coset spaces giving definite predictions for the resulting four-dimensional theory. We present the most interesting features of these theories as well as an attempt to construct a model with realistic low energy behaviour within this framework. (author)

Spinors and supersymmetry in four-dimensional Euclidean space

International Nuclear Information System (INIS)

McKeon, D.G.C.; Sherry, T.N.

2001-01-01

Spinors in four-dimensional Euclidean space are treated using the decomposition of the Euclidean space SO(4) symmetry group into SU(2)xSU(2). Both 2- and 4-spinor representations of this SO(4) symmetry group are shown to differ significantly from the corresponding spinor representations of the SO(3, 1) symmetry group in Minkowski space. The simplest self conjugate supersymmetry algebra allowed in four-dimensional Euclidean space is demonstrated to be an N=2 supersymmetry algebra which resembles the N=2 supersymmetry algebra in four-dimensional Minkowski space. The differences between the two supersymmetry algebras gives rise to different representations; in particular an analysis of the Clifford algebra structure shows that the momentum invariant is bounded above by the central charges in 4dE, while in 4dM the central charges bound the momentum invariant from below. Dimensional reduction of the N=1 SUSY algebra in six-dimensional Minkowski space (6dM) to 4dE reproduces our SUSY algebra in 4dE. This dimensional reduction can be used to introduce additional generators into the SUSY algebra in 4dE. Well known interpolating maps are used to relate the N=2 SUSY algebra in 4dE derived in this paper to the N=2 SUSY algebra in 4dM. The nature of the spinors in 4dE allows us to write an axially gauge invariant model which is shown to be both Hermitian and anomaly-free. No equivalent model exists in 4dM. Useful formulae in 4dE are collected together in two appendixes

High-Dimensional Intrinsic Interpolation Using Gaussian Process Regression and Diffusion Maps

International Nuclear Information System (INIS)

Thimmisetty, Charanraj A.; Ghanem, Roger G.; White, Joshua A.; Chen, Xiao

2017-01-01

This article considers the challenging task of estimating geologic properties of interest using a suite of proxy measurements. The current work recast this task as a manifold learning problem. In this process, this article introduces a novel regression procedure for intrinsic variables constrained onto a manifold embedded in an ambient space. The procedure is meant to sharpen high-dimensional interpolation by inferring non-linear correlations from the data being interpolated. The proposed approach augments manifold learning procedures with a Gaussian process regression. It first identifies, using diffusion maps, a low-dimensional manifold embedded in an ambient high-dimensional space associated with the data. It relies on the diffusion distance associated with this construction to define a distance function with which the data model is equipped. This distance metric function is then used to compute the correlation structure of a Gaussian process that describes the statistical dependence of quantities of interest in the high-dimensional ambient space. The proposed method is applicable to arbitrarily high-dimensional data sets. Here, it is applied to subsurface characterization using a suite of well log measurements. The predictions obtained in original, principal component, and diffusion space are compared using both qualitative and quantitative metrics. Considerable improvement in the prediction of the geological structural properties is observed with the proposed method.

Topology as fluid geometry two-dimensional spaces, volume 2

CERN Document Server

Cannon, James W

2017-01-01

This is the second of a three volume collection devoted to the geometry, topology, and curvature of 2-dimensional spaces. The collection provides a guided tour through a wide range of topics by one of the twentieth century's masters of geometric topology. The books are accessible to college and graduate students and provide perspective and insight to mathematicians at all levels who are interested in geometry and topology. The second volume deals with the topology of 2-dimensional spaces. The attempts encountered in Volume 1 to understand length and area in the plane lead to examples most easily described by the methods of topology (fluid geometry): finite curves of infinite length, 1-dimensional curves of positive area, space-filling curves (Peano curves), 0-dimensional subsets of the plane through which no straight path can pass (Cantor sets), etc. Volume 2 describes such sets. All of the standard topological results about 2-dimensional spaces are then proved, such as the Fundamental Theorem of Algebra (two...

Two-dimensional black holes and non-commutative spaces

International Nuclear Information System (INIS)

Sadeghi, J.

2008-01-01

We study the effects of non-commutative spaces on two-dimensional black hole. The event horizon of two-dimensional black hole is obtained in non-commutative space up to second order of perturbative calculations. A lower limit for the non-commutativity parameter is also obtained. The observer in that limit in contrast to commutative case see two horizon

Anisotropic fractal media by vector calculus in non-integer dimensional space

Energy Technology Data Exchange (ETDEWEB)

Tarasov, Vasily E., E-mail: tarasov@theory.sinp.msu.ru [Skobeltsyn Institute of Nuclear Physics, Lomonosov Moscow State University, Moscow 119991 (Russian Federation)

2014-08-15

A review of different approaches to describe anisotropic fractal media is proposed. In this paper, differentiation and integration non-integer dimensional and multi-fractional spaces are considered as tools to describe anisotropic fractal materials and media. We suggest a generalization of vector calculus for non-integer dimensional space by using a product measure method. The product of fractional and non-integer dimensional spaces allows us to take into account the anisotropy of the fractal media in the framework of continuum models. The integration over non-integer-dimensional spaces is considered. In this paper differential operators of first and second orders for fractional space and non-integer dimensional space are suggested. The differential operators are defined as inverse operations to integration in spaces with non-integer dimensions. Non-integer dimensional space that is product of spaces with different dimensions allows us to give continuum models for anisotropic type of the media. The Poisson's equation for fractal medium, the Euler-Bernoulli fractal beam, and the Timoshenko beam equations for fractal material are considered as examples of application of suggested generalization of vector calculus for anisotropic fractal materials and media.

Anisotropic fractal media by vector calculus in non-integer dimensional space

Science.gov (United States)

Tarasov, Vasily E.

2014-08-01

A review of different approaches to describe anisotropic fractal media is proposed. In this paper, differentiation and integration non-integer dimensional and multi-fractional spaces are considered as tools to describe anisotropic fractal materials and media. We suggest a generalization of vector calculus for non-integer dimensional space by using a product measure method. The product of fractional and non-integer dimensional spaces allows us to take into account the anisotropy of the fractal media in the framework of continuum models. The integration over non-integer-dimensional spaces is considered. In this paper differential operators of first and second orders for fractional space and non-integer dimensional space are suggested. The differential operators are defined as inverse operations to integration in spaces with non-integer dimensions. Non-integer dimensional space that is product of spaces with different dimensions allows us to give continuum models for anisotropic type of the media. The Poisson's equation for fractal medium, the Euler-Bernoulli fractal beam, and the Timoshenko beam equations for fractal material are considered as examples of application of suggested generalization of vector calculus for anisotropic fractal materials and media.

Anisotropic fractal media by vector calculus in non-integer dimensional space

International Nuclear Information System (INIS)

Tarasov, Vasily E.

2014-01-01

A review of different approaches to describe anisotropic fractal media is proposed. In this paper, differentiation and integration non-integer dimensional and multi-fractional spaces are considered as tools to describe anisotropic fractal materials and media. We suggest a generalization of vector calculus for non-integer dimensional space by using a product measure method. The product of fractional and non-integer dimensional spaces allows us to take into account the anisotropy of the fractal media in the framework of continuum models. The integration over non-integer-dimensional spaces is considered. In this paper differential operators of first and second orders for fractional space and non-integer dimensional space are suggested. The differential operators are defined as inverse operations to integration in spaces with non-integer dimensions. Non-integer dimensional space that is product of spaces with different dimensions allows us to give continuum models for anisotropic type of the media. The Poisson's equation for fractal medium, the Euler-Bernoulli fractal beam, and the Timoshenko beam equations for fractal material are considered as examples of application of suggested generalization of vector calculus for anisotropic fractal materials and media

Muscle synergies in neuroscience and robotics: from input-space to task-space perspectives

Directory of Open Access Journals (Sweden)

Cristiano eAlessandro

2013-04-01

Full Text Available In this paper we review the works related to muscle synergies that have been carried-out in neuroscience and control engineering. In particular, we refer to the hypothesis that the central nervous system (CNS generates desired muscle contractions by combining a small number of predefined modules, called muscle synergies. We provide an overview of the methods that have been employed to test the validity of this scheme, and we show how the concept of muscle synergy has been generalized for the control of artificial agents. The comparison between these two lines of research, in particular their different goals and approaches, is instrumental to explain the computational implications of the hypothesized modular organization. Moreover, it clarifies the importance of assessing the functional role of muscle synergies: although these basic modules are defined at the level of muscle activations (input-space, they should result in the effective accomplishment of the desired task. This requirement is not always explicitly considered in experimental neuroscience, as muscle synergies are often estimated solely by analyzing recorded muscle activities. We suggest that synergy extraction methods should explicitly take into account task execution variables, thus moving from a perspective purely based on input-space to one grounded on task-space as well.

Dimensional regularization in configuration space

International Nuclear Information System (INIS)

Bollini, C.G.; Giambiagi, J.J.

1995-09-01

Dimensional regularization is introduced in configuration space by Fourier transforming in D-dimensions the perturbative momentum space Green functions. For this transformation, Bochner theorem is used, no extra parameters, such as those of Feynman or Bogoliubov-Shirkov are needed for convolutions. The regularized causal functions in x-space have ν-dependent moderated singularities at the origin. They can be multiplied together and Fourier transformed (Bochner) without divergence problems. The usual ultraviolet divergences appear as poles of the resultant functions of ν. Several example are discussed. (author). 9 refs

The use of virtual reality to reimagine two-dimensional representations of three-dimensional spaces

Science.gov (United States)

Fath, Elaine

2015-03-01

A familiar realm in the world of two-dimensional art is the craft of taking a flat canvas and creating, through color, size, and perspective, the illusion of a three-dimensional space. Using well-explored tricks of logic and sight, impossible landscapes such as those by surrealists de Chirico or Salvador Dalí seem to be windows into new and incredible spaces which appear to be simultaneously feasible and utterly nonsensical. As real-time 3D imaging becomes increasingly prevalent as an artistic medium, this process takes on an additional layer of depth: no longer is two-dimensional space restricted to strategies of light, color, line and geometry to create the impression of a three-dimensional space. A digital interactive environment is a space laid out in three dimensions, allowing the user to explore impossible environments in a way that feels very real. In this project, surrealist two-dimensional art was researched and reimagined: what would stepping into a de Chirico or a Magritte look and feel like, if the depth and distance created by light and geometry were not simply single-perspective illusions, but fully formed and explorable spaces? 3D environment-building software is allowing us to step into these impossible spaces in ways that 2D representations leave us yearning for. This art project explores what we gain--and what gets left behind--when these impossible spaces become doors, rather than windows. Using sketching, Maya 3D rendering software, and the Unity Engine, surrealist art was reimagined as a fully navigable real-time digital environment. The surrealist movement and its key artists were researched for their use of color, geometry, texture, and space and how these elements contributed to their work as a whole, which often conveys feelings of unexpectedness or uneasiness. The end goal was to preserve these feelings while allowing the viewer to actively engage with the space.

High-dimensional structured light coding/decoding for free-space optical communications free of obstructions.

Science.gov (United States)

Du, Jing; Wang, Jian

2015-11-01

Bessel beams carrying orbital angular momentum (OAM) with helical phase fronts exp(ilφ)(l=0;±1;±2;…), where φ is the azimuthal angle and l corresponds to the topological number, are orthogonal with each other. This feature of Bessel beams provides a new dimension to code/decode data information on the OAM state of light, and the theoretical infinity of topological number enables possible high-dimensional structured light coding/decoding for free-space optical communications. Moreover, Bessel beams are nondiffracting beams having the ability to recover by themselves in the face of obstructions, which is important for free-space optical communications relying on line-of-sight operation. By utilizing the OAM and nondiffracting characteristics of Bessel beams, we experimentally demonstrate 12 m distance obstruction-free optical m-ary coding/decoding using visible Bessel beams in a free-space optical communication system. We also study the bit error rate (BER) performance of hexadecimal and 32-ary coding/decoding based on Bessel beams with different topological numbers. After receiving 500 symbols at the receiver side, a zero BER of hexadecimal coding/decoding is observed when the obstruction is placed along the propagation path of light.

We live in the quantum 4-dimensional Minkowski space-time

OpenAIRE

Hwang, W-Y. Pauchy

2015-01-01

We try to define "our world" by stating that "we live in the quantum 4-dimensional Minkowski space-time with the force-fields gauge group $SU_c(3) \\times SU_L(2) \\times U(1) \\times SU_f(3)$ built-in from the outset". We begin by explaining what "space" and "time" are meaning for us - the 4-dimensional Minkowski space-time, then proceeding to the quantum 4-dimensional Minkowski space-time. In our world, there are fields, or, point-like particles. Particle physics is described by the so-called ...

A non-linear dimension reduction methodology for generating data-driven stochastic input models

Science.gov (United States)

Ganapathysubramanian, Baskar; Zabaras, Nicholas

2008-06-01

Stochastic analysis of random heterogeneous media (polycrystalline materials, porous media, functionally graded materials) provides information of significance only if realistic input models of the topology and property variations are used. This paper proposes a framework to construct such input stochastic models for the topology and thermal diffusivity variations in heterogeneous media using a data-driven strategy. Given a set of microstructure realizations (input samples) generated from given statistical information about the medium topology, the framework constructs a reduced-order stochastic representation of the thermal diffusivity. This problem of constructing a low-dimensional stochastic representation of property variations is analogous to the problem of manifold learning and parametric fitting of hyper-surfaces encountered in image processing and psychology. Denote by M the set of microstructures that satisfy the given experimental statistics. A non-linear dimension reduction strategy is utilized to map M to a low-dimensional region, A. We first show that M is a compact manifold embedded in a high-dimensional input space Rn. An isometric mapping F from M to a low-dimensional, compact, connected set A⊂Rd(d≪n) is constructed. Given only a finite set of samples of the data, the methodology uses arguments from graph theory and differential geometry to construct the isometric transformation F:M→A. Asymptotic convergence of the representation of M by A is shown. This mapping F serves as an accurate, low-dimensional, data-driven representation of the property variations. The reduced-order model of the material topology and thermal diffusivity variations is subsequently used as an input in the solution of stochastic partial differential equations that describe the evolution of dependant variables. A sparse grid collocation strategy (Smolyak algorithm) is utilized to solve these stochastic equations efficiently. We showcase the methodology by constructing low-dimensional

A non-linear dimension reduction methodology for generating data-driven stochastic input models

International Nuclear Information System (INIS)

Ganapathysubramanian, Baskar; Zabaras, Nicholas

2008-01-01

Stochastic analysis of random heterogeneous media (polycrystalline materials, porous media, functionally graded materials) provides information of significance only if realistic input models of the topology and property variations are used. This paper proposes a framework to construct such input stochastic models for the topology and thermal diffusivity variations in heterogeneous media using a data-driven strategy. Given a set of microstructure realizations (input samples) generated from given statistical information about the medium topology, the framework constructs a reduced-order stochastic representation of the thermal diffusivity. This problem of constructing a low-dimensional stochastic representation of property variations is analogous to the problem of manifold learning and parametric fitting of hyper-surfaces encountered in image processing and psychology. Denote by M the set of microstructures that satisfy the given experimental statistics. A non-linear dimension reduction strategy is utilized to map M to a low-dimensional region, A. We first show that M is a compact manifold embedded in a high-dimensional input space R n . An isometric mapping F from M to a low-dimensional, compact, connected set A is contained in R d (d<< n) is constructed. Given only a finite set of samples of the data, the methodology uses arguments from graph theory and differential geometry to construct the isometric transformation F:M→A. Asymptotic convergence of the representation of M by A is shown. This mapping F serves as an accurate, low-dimensional, data-driven representation of the property variations. The reduced-order model of the material topology and thermal diffusivity variations is subsequently used as an input in the solution of stochastic partial differential equations that describe the evolution of dependant variables. A sparse grid collocation strategy (Smolyak algorithm) is utilized to solve these stochastic equations efficiently. We showcase the methodology

Quantum phase space points for Wigner functions in finite-dimensional spaces

OpenAIRE

Luis Aina, Alfredo

2004-01-01

We introduce quantum states associated with single phase space points in the Wigner formalism for finite-dimensional spaces. We consider both continuous and discrete Wigner functions. This analysis provides a procedure for a direct practical observation of the Wigner functions for states and transformations without inversion formulas.

Quantum phase space points for Wigner functions in finite-dimensional spaces

International Nuclear Information System (INIS)

Luis, Alfredo

2004-01-01

We introduce quantum states associated with single phase space points in the Wigner formalism for finite-dimensional spaces. We consider both continuous and discrete Wigner functions. This analysis provides a procedure for a direct practical observation of the Wigner functions for states and transformations without inversion formulas

Lip-reading aids word recognition most in moderate noise: a Bayesian explanation using high-dimensional feature space.

Science.gov (United States)

Ma, Wei Ji; Zhou, Xiang; Ross, Lars A; Foxe, John J; Parra, Lucas C

2009-01-01

Watching a speaker's facial movements can dramatically enhance our ability to comprehend words, especially in noisy environments. From a general doctrine of combining information from different sensory modalities (the principle of inverse effectiveness), one would expect that the visual signals would be most effective at the highest levels of auditory noise. In contrast, we find, in accord with a recent paper, that visual information improves performance more at intermediate levels of auditory noise than at the highest levels, and we show that a novel visual stimulus containing only temporal information does the same. We present a Bayesian model of optimal cue integration that can explain these conflicts. In this model, words are regarded as points in a multidimensional space and word recognition is a probabilistic inference process. When the dimensionality of the feature space is low, the Bayesian model predicts inverse effectiveness; when the dimensionality is high, the enhancement is maximal at intermediate auditory noise levels. When the auditory and visual stimuli differ slightly in high noise, the model makes a counterintuitive prediction: as sound quality increases, the proportion of reported words corresponding to the visual stimulus should first increase and then decrease. We confirm this prediction in a behavioral experiment. We conclude that auditory-visual speech perception obeys the same notion of optimality previously observed only for simple multisensory stimuli.

Lip-reading aids word recognition most in moderate noise: a Bayesian explanation using high-dimensional feature space.

Directory of Open Access Journals (Sweden)

Wei Ji Ma

Full Text Available Watching a speaker's facial movements can dramatically enhance our ability to comprehend words, especially in noisy environments. From a general doctrine of combining information from different sensory modalities (the principle of inverse effectiveness, one would expect that the visual signals would be most effective at the highest levels of auditory noise. In contrast, we find, in accord with a recent paper, that visual information improves performance more at intermediate levels of auditory noise than at the highest levels, and we show that a novel visual stimulus containing only temporal information does the same. We present a Bayesian model of optimal cue integration that can explain these conflicts. In this model, words are regarded as points in a multidimensional space and word recognition is a probabilistic inference process. When the dimensionality of the feature space is low, the Bayesian model predicts inverse effectiveness; when the dimensionality is high, the enhancement is maximal at intermediate auditory noise levels. When the auditory and visual stimuli differ slightly in high noise, the model makes a counterintuitive prediction: as sound quality increases, the proportion of reported words corresponding to the visual stimulus should first increase and then decrease. We confirm this prediction in a behavioral experiment. We conclude that auditory-visual speech perception obeys the same notion of optimality previously observed only for simple multisensory stimuli.

Detection of Subtle Context-Dependent Model Inaccuracies in High-Dimensional Robot Domains.

Science.gov (United States)

Mendoza, Juan Pablo; Simmons, Reid; Veloso, Manuela

2016-12-01

Autonomous robots often rely on models of their sensing and actions for intelligent decision making. However, when operating in unconstrained environments, the complexity of the world makes it infeasible to create models that are accurate in every situation. This article addresses the problem of using potentially large and high-dimensional sets of robot execution data to detect situations in which a robot model is inaccurate-that is, detecting context-dependent model inaccuracies in a high-dimensional context space. To find inaccuracies tractably, the robot conducts an informed search through low-dimensional projections of execution data to find parametric Regions of Inaccurate Modeling (RIMs). Empirical evidence from two robot domains shows that this approach significantly enhances the detection power of existing RIM-detection algorithms in high-dimensional spaces.

Electromagnetic-field equations in the six-dimensional space-time R6

International Nuclear Information System (INIS)

Teli, M.T.; Palaskar, D.

1984-01-01

Maxwell's equations (without monopoles) for electromagnetic fields are obtained in six-dimensional space-time. The equations possess structural symmetry in space and time, field and source densities. Space-time-symmetric conservation laws and field solutions are obtained. The results are successfully correlated with their four-dimensional space-time counterparts

High dimensional model representation method for fuzzy structural dynamics

Science.gov (United States)

Adhikari, S.; Chowdhury, R.; Friswell, M. I.

2011-03-01

Uncertainty propagation in multi-parameter complex structures possess significant computational challenges. This paper investigates the possibility of using the High Dimensional Model Representation (HDMR) approach when uncertain system parameters are modeled using fuzzy variables. In particular, the application of HDMR is proposed for fuzzy finite element analysis of linear dynamical systems. The HDMR expansion is an efficient formulation for high-dimensional mapping in complex systems if the higher order variable correlations are weak, thereby permitting the input-output relationship behavior to be captured by the terms of low-order. The computational effort to determine the expansion functions using the α-cut method scales polynomically with the number of variables rather than exponentially. This logic is based on the fundamental assumption underlying the HDMR representation that only low-order correlations among the input variables are likely to have significant impacts upon the outputs for most high-dimensional complex systems. The proposed method is first illustrated for multi-parameter nonlinear mathematical test functions with fuzzy variables. The method is then integrated with a commercial finite element software (ADINA). Modal analysis of a simplified aircraft wing with fuzzy parameters has been used to illustrate the generality of the proposed approach. In the numerical examples, triangular membership functions have been used and the results have been validated against direct Monte Carlo simulations. It is shown that using the proposed HDMR approach, the number of finite element function calls can be reduced without significantly compromising the accuracy.

Green functions and scattering amplitudes in many-dimensional space

International Nuclear Information System (INIS)

Fabre de la Ripelle, M.

1993-01-01

Methods for solving scattering are studied in many-dimensional space. Green function and scattering amplitudes are given in terms of the required asymptotic behaviour of the wave function. The Born approximation and the optical theorem are derived in many-dimensional space. Phase-shift analyses are performed for hypercentral potentials and for non-hypercentral potentials by use of the hyperspherical adiabatic approximation. (author)

Identification of Architectural Functions in A Four-Dimensional Space

Directory of Open Access Journals (Sweden)

Firza Utama

2012-06-01

Full Text Available This research has explored the possibilities and concept of architectural space in a virtual environment. The virtual environment exists as a different concept, and challenges the constraints of the physical world. One of the possibilities in a virtual environment is that it is able to extend the spatial dimension higher than the physical three-dimension. To take the advantage of this possibility, this research has applied some geometrical four-dimensional (4D methods to define virtual architectural space. The spatial characteristics of 4D space is established by analyzing the four-dimensional structure that can be comprehended by human participant for its spatial quality, and by developing a system to control the fourth axis of movement. Multiple three-dimensional spaces that fluidly change their volume have been defined as one of the possibilities of virtual architecturalspace concept in order to enrich our understanding of virtual spatial experience.

Generalized space-charge limited current and virtual cathode behaviors in one-dimensional drift space

International Nuclear Information System (INIS)

Yang, Zhanfeng; Liu, Guozhi; Shao, Hao; Chen, Changhua; Sun, Jun

2013-01-01

This paper reports the space-charge limited current (SLC) and virtual cathode behaviors in one-dimensional grounded drift space. A simple general analytical solution and an approximate solution for the planar diode are given. Through a semi-analytical method, a general solution for SLC in one-dimensional drift space is obtained. The behaviors of virtual cathode in the drift space, including dominant frequency, electron transit time, position, and transmitted current, are yielded analytically. The relationship between the frequency of the virtual cathode oscillation and the injected current presented may explain previously reported numerical works. Results are significant in facilitating estimations and further analytical studies

High-frequency matrix converter with square wave input

Science.gov (United States)

Carr, Joseph Alexander; Balda, Juan Carlos

2015-03-31

A device for producing an alternating current output voltage from a high-frequency, square-wave input voltage comprising, high-frequency, square-wave input a matrix converter and a control system. The matrix converter comprises a plurality of electrical switches. The high-frequency input and the matrix converter are electrically connected to each other. The control system is connected to each switch of the matrix converter. The control system is electrically connected to the input of the matrix converter. The control system is configured to operate each electrical switch of the matrix converter converting a high-frequency, square-wave input voltage across the first input port of the matrix converter and the second input port of the matrix converter to an alternating current output voltage at the output of the matrix converter.

Space Vector Modulation for an Indirect Matrix Converter with Improved Input Power Factor

Directory of Open Access Journals (Sweden)

Nguyen Dinh Tuyen

2017-04-01

Full Text Available Pulse width modulation strategies have been developed for indirect matrix converters (IMCs in order to improve their performance. In indirect matrix converters, the LC input filter is used to remove input current harmonics and electromagnetic interference problems. Unfortunately, due to the existence of the input filter, the input power factor is diminished, especially during operation at low voltage outputs. In this paper, a new space vector modulation (SVM is proposed to compensate for the input power factor of the indirect matrix converter. Both computer simulation and experimental studies through hardware implementation were performed to verify the effectiveness of the proposed modulation strategy.

Green function and scattering amplitudes in many dimensional space

International Nuclear Information System (INIS)

Fabre de la Ripelle, M.

1991-06-01

Methods for solving scattering are studied in many dimensional space. Green function and scattering amplitudes are given in terms of the requested asymptotic behaviour of the wave function. The Born approximation and the optical theorem are derived in many dimensional space. Phase-shift analysis are developed for hypercentral potentials and for non-hypercentral potentials with the hyperspherical adiabatic approximation. (author) 16 refs., 3 figs

The space-time model according to dimensional continuous space-time theory

International Nuclear Information System (INIS)

Martini, Luiz Cesar

2014-01-01

This article results from the Dimensional Continuous Space-Time Theory for which the introductory theoretician was presented in [1]. A theoretical model of the Continuous Space-Time is presented. The wave equation of time into absolutely stationary empty space referential will be described in detail. The complex time, that is the time fixed on the infinite phase time speed referential, is deduced from the New View of Relativity Theory that is being submitted simultaneously with this article in this congress. Finally considering the inseparable Space-Time is presented the duality equation wave-particle.

Few helium atoms in quasi two-dimensional space

International Nuclear Information System (INIS)

Kilic, Srecko; Vranjes, Leandra

2003-01-01

Two, three and four 3 He and 4 He atoms in quasi two-dimensional space above graphite and cesium surfaces and in 'harmonic' potential perpendicular to the surface have been studied. Using some previously examined variational wave functions and the Diffusion Monte Carlo procedure, it has been shown that all molecules: dimers, trimers and tetramers, are bound more strongly than in pure two- and three-dimensional space. The enhancement of binding with respect to unrestricted space is more pronounced on cesium than on graphite. Furthermore, for 3 He 3 ( 3 He 4 ) on all studied surfaces, there is an indication that the configuration of a dimer and a 'free' particle (two dimers) may be equivalently established

High-dimensional quantum cloning and applications to quantum hacking.

Science.gov (United States)

Bouchard, Frédéric; Fickler, Robert; Boyd, Robert W; Karimi, Ebrahim

2017-02-01

Attempts at cloning a quantum system result in the introduction of imperfections in the state of the copies. This is a consequence of the no-cloning theorem, which is a fundamental law of quantum physics and the backbone of security for quantum communications. Although perfect copies are prohibited, a quantum state may be copied with maximal accuracy via various optimal cloning schemes. Optimal quantum cloning, which lies at the border of the physical limit imposed by the no-signaling theorem and the Heisenberg uncertainty principle, has been experimentally realized for low-dimensional photonic states. However, an increase in the dimensionality of quantum systems is greatly beneficial to quantum computation and communication protocols. Nonetheless, no experimental demonstration of optimal cloning machines has hitherto been shown for high-dimensional quantum systems. We perform optimal cloning of high-dimensional photonic states by means of the symmetrization method. We show the universality of our technique by conducting cloning of numerous arbitrary input states and fully characterize our cloning machine by performing quantum state tomography on cloned photons. In addition, a cloning attack on a Bennett and Brassard (BB84) quantum key distribution protocol is experimentally demonstrated to reveal the robustness of high-dimensional states in quantum cryptography.

Motion of gas in highly rarefied space

Science.gov (United States)

Chirkunov, Yu A.

2017-10-01

A model describing a motion of gas in a highly rarefied space received an unlucky number 13 in the list of the basic models of the motion of gas in the three-dimensional space obtained by L.V. Ovsyannikov. For a given initial pressure distribution, a special choice of mass Lagrangian variables leads to the system describing this motion for which the number of independent variables is less by one. Hence, there is a foliation of a highly rarefied gas with respect to pressure. In a strongly rarefied space for each given initial pressure distribution, all gas particles are localized on a two-dimensional surface that moves with time in this space We found some exact solutions of the obtained system that describe the processes taking place inside of the tornado. For this system we found all nontrivial conservation laws of the first order. In addition to the classical conservation laws the system has another conservation law, which generalizes the energy conservation law. With the additional condition we found another one generalized energy conservation law.

A probabilistic graphical model based stochastic input model construction

International Nuclear Information System (INIS)

Wan, Jiang; Zabaras, Nicholas

2014-01-01

Model reduction techniques have been widely used in modeling of high-dimensional stochastic input in uncertainty quantification tasks. However, the probabilistic modeling of random variables projected into reduced-order spaces presents a number of computational challenges. Due to the curse of dimensionality, the underlying dependence relationships between these random variables are difficult to capture. In this work, a probabilistic graphical model based approach is employed to learn the dependence by running a number of conditional independence tests using observation data. Thus a probabilistic model of the joint PDF is obtained and the PDF is factorized into a set of conditional distributions based on the dependence structure of the variables. The estimation of the joint PDF from data is then transformed to estimating conditional distributions under reduced dimensions. To improve the computational efficiency, a polynomial chaos expansion is further applied to represent the random field in terms of a set of standard random variables. This technique is combined with both linear and nonlinear model reduction methods. Numerical examples are presented to demonstrate the accuracy and efficiency of the probabilistic graphical model based stochastic input models. - Highlights: • Data-driven stochastic input models without the assumption of independence of the reduced random variables. • The problem is transformed to a Bayesian network structure learning problem. • Examples are given in flows in random media

Lorentz covariant tempered distributions in two-dimensional space-time

International Nuclear Information System (INIS)

Zinov'ev, Yu.M.

1989-01-01

The problem of describing Lorentz covariant distributions without any spectral condition has hitherto remained unsolved even for two-dimensional space-time. Attempts to solve this problem have already been made. Zharinov obtained an integral representation for the Laplace transform of Lorentz invariant distributions with support in the product of two-dimensional future light cones. However, this integral representation does not make it possible to obtain a complete description of the corresponding Lorentz invariant distributions. In this paper the author gives a complete description of Lorentz covariant distributions for two-dimensional space-time. No spectral conditions is assumed

Mannheim Curves in Nonflat 3-Dimensional Space Forms

Directory of Open Access Journals (Sweden)

Wenjing Zhao

2015-01-01

Full Text Available We consider the Mannheim curves in nonflat 3-dimensional space forms (Riemannian or Lorentzian and we give the concept of Mannheim curves. In addition, we investigate the properties of nonnull Mannheim curves and their partner curves. We come to the conclusion that a necessary and sufficient condition is that a linear relationship with constant coefficients will exist between the curvature and the torsion of the given original curves. In the case of null curve, we reveal that there are no null Mannheim curves in the 3-dimensional de Sitter space.

An Unbiased Distance-based Outlier Detection Approach for High-dimensional Data

DEFF Research Database (Denmark)

Nguyen, Hoang Vu; Gopalkrishnan, Vivekanand; Assent, Ira

2011-01-01

than a global property. Different from existing approaches, it is not grid-based and dimensionality unbiased. Thus, its performance is impervious to grid resolution as well as the curse of dimensionality. In addition, our approach ranks the outliers, allowing users to select the number of desired...... outliers, thus mitigating the issue of high false alarm rate. Extensive empirical studies on real datasets show that our approach efficiently and effectively detects outliers, even in high-dimensional spaces....

Linear embeddings of finite-dimensional subsets of Banach spaces into Euclidean spaces

International Nuclear Information System (INIS)

Robinson, James C

2009-01-01

This paper treats the embedding of finite-dimensional subsets of a Banach space B into finite-dimensional Euclidean spaces. When the Hausdorff dimension of X − X is finite, d H (X − X) k are injective on X. The proof motivates the definition of the 'dual thickness exponent', which is the key to proving that a prevalent set of such linear maps have Hölder continuous inverse when the box-counting dimension of X is finite and k > 2d B (X). A related argument shows that if the Assouad dimension of X − X is finite and k > d A (X − X), a prevalent set of such maps are bi-Lipschitz with logarithmic corrections. This provides a new result for compact homogeneous metric spaces via the Kuratowksi embedding of (X, d) into L ∞ (X)

Superconductivity and the existence of Nambu's three-dimensional phase space mechanics

International Nuclear Information System (INIS)

Angulo, R.; Gonzalez-Bernardo, C.A.; Rodriguez-Gomez, J.; Kalnay, A.J.; Perez-M, F.; Tello-Llanos, R.A.

1984-01-01

Nambu proposed a generalization of hamiltonian mechanics such that three-dimensional phase space is allowed. Thanks to a recent paper by Holm and Kupershmidt we are able to show the existence of such three-dimensional phase space systems in superconductivity. (orig.)

Supersymmetric quantum mechanics in three-dimensional space, 1

International Nuclear Information System (INIS)

Ui, Haruo

1984-01-01

As a direct generalization of the model of supersymmetric quantum mechanics by Witten, which describes the motion of a spin one-half particle in the one-dimensional space, we construct a model of the supersymmetric quantum mechanics in the three-dimensional space, which describes the motion of a spin one-half particle in central and spin-orbit potentials in the context of the nonrelativistic quantum mechanics. With the simplest choice of the (super) potential, this model is shown to reduce to the model of the harmonic oscillator plus constant spin-orbit potential of unit strength of both positive and negative signs, which was studied in detail in our recent paper in connection with ''accidental degeneracy'' as well as the ''graded groups''. This simplest model is discussed in some detail as an example of the three-dimensional supersymmetric quantum mechanical system, where the supersymmetry is an exact symmetry of the system. More general choice of a polynomial superpotential is also discussed. It is shown that the supersymmetry cannot be spontaneously broken for any polynomial superpotential in our three-dimensional model; this result is contrasted to the corresponding one in the one-dimensional model. (author)

Sensory Synergy as Environmental Input Integration

Directory of Open Access Journals (Sweden)

Fady eAlnajjar

2015-01-01

Full Text Available The development of a method to feed proper environmental inputs back to the central nervous system (CNS remains one of the challenges in achieving natural movement when part of the body is replaced with an artificial device. Muscle synergies are widely accepted as a biologically plausible interpretation of the neural dynamics between the CNS and the muscular system. Yet the sensorineural dynamics of environmental feedback to the CNS has not been investigated in detail. In this study, we address this issue by exploring the concept of sensory synergy. In contrast to muscle synergy, we hypothesize that sensory synergy plays an essential role in integrating the overall environmental inputs to provide low-dimensional information to the CNS. We assume that sensor synergy and muscle synergy communicate using these low-dimensional signals. To examine our hypothesis, we conducted posture control experiments involving lateral disturbance with 9 healthy participants. Proprioceptive information represented by the changes on muscle lengths were estimated by using the musculoskeletal model analysis software SIMM. Changes on muscles lengths were then used to compute sensory synergies. The experimental results indicate that the environmental inputs were translated into the two dimensional signals and used to move the upper limb to the desired position immediately after the lateral disturbance. Participants who showed high skill in posture control were found to be likely to have a strong correlation between sensory and muscle signaling as well as high coordination between the utilized sensory synergies. These results suggest the importance of integrating environmental inputs into suitable low-dimensional signals before providing them to the CNS. This mechanism should be essential when designing the prosthesis’ sensory system to make the controller simpler

Sensory synergy as environmental input integration.

Science.gov (United States)

Alnajjar, Fady; Itkonen, Matti; Berenz, Vincent; Tournier, Maxime; Nagai, Chikara; Shimoda, Shingo

2014-01-01

The development of a method to feed proper environmental inputs back to the central nervous system (CNS) remains one of the challenges in achieving natural movement when part of the body is replaced with an artificial device. Muscle synergies are widely accepted as a biologically plausible interpretation of the neural dynamics between the CNS and the muscular system. Yet the sensorineural dynamics of environmental feedback to the CNS has not been investigated in detail. In this study, we address this issue by exploring the concept of sensory synergy. In contrast to muscle synergy, we hypothesize that sensory synergy plays an essential role in integrating the overall environmental inputs to provide low-dimensional information to the CNS. We assume that sensor synergy and muscle synergy communicate using these low-dimensional signals. To examine our hypothesis, we conducted posture control experiments involving lateral disturbance with nine healthy participants. Proprioceptive information represented by the changes on muscle lengths were estimated by using the musculoskeletal model analysis software SIMM. Changes on muscles lengths were then used to compute sensory synergies. The experimental results indicate that the environmental inputs were translated into the two dimensional signals and used to move the upper limb to the desired position immediately after the lateral disturbance. Participants who showed high skill in posture control were found to be likely to have a strong correlation between sensory and muscle signaling as well as high coordination between the utilized sensory synergies. These results suggest the importance of integrating environmental inputs into suitable low-dimensional signals before providing them to the CNS. This mechanism should be essential when designing the prosthesis' sensory system to make the controller simpler.

Faithful representation of similarities among three-dimensional shapes in human vision.

Science.gov (United States)

Cutzu, F; Edelman, S

1996-01-01

Efficient and reliable classification of visual stimuli requires that their representations reside a low-dimensional and, therefore, computationally manageable feature space. We investigated the ability of the human visual system to derive such representations from the sensory input-a highly nontrivial task, given the million or so dimensions of the visual signal at its entry point to the cortex. In a series of experiments, subjects were presented with sets of parametrically defined shapes; the points in the common high-dimensional parameter space corresponding to the individual shapes formed regular planar (two-dimensional) patterns such as a triangle, a square, etc. We then used multidimensional scaling to arrange the shapes in planar configurations, dictated by their experimentally determined perceived similarities. The resulting configurations closely resembled the original arrangements of the stimuli in the parameter space. This achievement of the human visual system was replicated by a computational model derived from a theory of object representation in the brain, according to which similarities between objects, and not the geometry of each object, need to be faithfully represented. Images Fig. 3 PMID:8876260

Visualising very large phylogenetic trees in three dimensional hyperbolic space

Directory of Open Access Journals (Sweden)

Liberles David A

2004-04-01

Full Text Available Abstract Background Common existing phylogenetic tree visualisation tools are not able to display readable trees with more than a few thousand nodes. These existing methodologies are based in two dimensional space. Results We introduce the idea of visualising phylogenetic trees in three dimensional hyperbolic space with the Walrus graph visualisation tool and have developed a conversion tool that enables the conversion of standard phylogenetic tree formats to Walrus' format. With Walrus, it becomes possible to visualise and navigate phylogenetic trees with more than 100,000 nodes. Conclusion Walrus enables desktop visualisation of very large phylogenetic trees in 3 dimensional hyperbolic space. This application is potentially useful for visualisation of the tree of life and for functional genomics derivatives, like The Adaptive Evolution Database (TAED.

High-dimensional orbital angular momentum entanglement concentration based on Laguerre–Gaussian mode selection

International Nuclear Information System (INIS)

Zhang, Wuhong; Su, Ming; Wu, Ziwen; Lu, Meng; Huang, Bingwei; Chen, Lixiang

2013-01-01

Twisted photons enable the definition of a Hilbert space beyond two dimensions by orbital angular momentum (OAM) eigenstates. Here we propose a feasible entanglement concentration experiment, to enhance the quality of high-dimensional entanglement shared by twisted photon pairs. Our approach is started from the full characterization of entangled spiral bandwidth, and is then based on the careful selection of the Laguerre–Gaussian (LG) modes with specific radial and azimuthal indices p and ℓ. In particular, we demonstrate the possibility of high-dimensional entanglement concentration residing in the OAM subspace of up to 21 dimensions. By means of LabVIEW simulations with spatial light modulators, we show that the Shannon dimensionality could be employed to quantify the quality of the present concentration. Our scheme holds promise in quantum information applications defined in high-dimensional Hilbert space. (letter)

Extending the Generalised Pareto Distribution for Novelty Detection in High-Dimensional Spaces.

Science.gov (United States)

Clifton, David A; Clifton, Lei; Hugueny, Samuel; Tarassenko, Lionel

2014-01-01

Novelty detection involves the construction of a "model of normality", and then classifies test data as being either "normal" or "abnormal" with respect to that model. For this reason, it is often termed one-class classification. The approach is suitable for cases in which examples of "normal" behaviour are commonly available, but in which cases of "abnormal" data are comparatively rare. When performing novelty detection, we are typically most interested in the tails of the normal model, because it is in these tails that a decision boundary between "normal" and "abnormal" areas of data space usually lies. Extreme value statistics provides an appropriate theoretical framework for modelling the tails of univariate (or low-dimensional) distributions, using the generalised Pareto distribution (GPD), which can be demonstrated to be the limiting distribution for data occurring within the tails of most practically-encountered probability distributions. This paper provides an extension of the GPD, allowing the modelling of probability distributions of arbitrarily high dimension, such as occurs when using complex, multimodel, multivariate distributions for performing novelty detection in most real-life cases. We demonstrate our extension to the GPD using examples from patient physiological monitoring, in which we have acquired data from hospital patients in large clinical studies of high-acuity wards, and in which we wish to determine "abnormal" patient data, such that early warning of patient physiological deterioration may be provided.

Modeling extreme (Carrington-type) space weather events using three-dimensional MHD code simulations

Science.gov (United States)

Ngwira, C. M.; Pulkkinen, A. A.; Kuznetsova, M. M.; Glocer, A.

2013-12-01

There is growing concern over possible severe societal consequences related to adverse space weather impacts on man-made technological infrastructure and systems. In the last two decades, significant progress has been made towards the modeling of space weather events. Three-dimensional (3-D) global magnetohydrodynamics (MHD) models have been at the forefront of this transition, and have played a critical role in advancing our understanding of space weather. However, the modeling of extreme space weather events is still a major challenge even for existing global MHD models. In this study, we introduce a specially adapted University of Michigan 3-D global MHD model for simulating extreme space weather events that have a ground footprint comparable (or larger) to the Carrington superstorm. Results are presented for an initial simulation run with ``very extreme'' constructed/idealized solar wind boundary conditions driving the magnetosphere. In particular, we describe the reaction of the magnetosphere-ionosphere system and the associated ground induced geoelectric field to such extreme driving conditions. We also discuss the results and what they might mean for the accuracy of the simulations. The model is further tested using input data for an observed space weather event to verify the MHD model consistence and to draw guidance for future work. This extreme space weather MHD model is designed specifically for practical application to the modeling of extreme geomagnetically induced electric fields, which can drive large currents in earth conductors such as power transmission grids.

Mappings with closed range and finite dimensional linear spaces

International Nuclear Information System (INIS)

Iyahen, S.O.

1984-09-01

This paper looks at two settings, each of continuous linear mappings of linear topological spaces. In one setting, the domain space is fixed while the range space varies over a class of linear topological spaces. In the second setting, the range space is fixed while the domain space similarly varies. The interest is in when the requirement that the mappings have a closed range implies that the domain or range space is finite dimensional. Positive results are obtained for metrizable spaces. (author)

On the Zeeman Effect in highly excited atoms: 2. Three-dimensional case

International Nuclear Information System (INIS)

Baseia, B.; Medeiros e Silva Filho, J.

1984-01-01

A previous result, found in two-dimensional hydrogen-atoms, is extended to the three-dimensional case. A mapping of a four-dimensional space R 4 onto R 3 , that establishes an equivalence between Coulomb and harmonic potentials, is used to show that the exact solution of the Zeeman effect in highly excited atoms, cannot be reached. (Author) [pt

Embedding of attitude determination in n-dimensional spaces

Science.gov (United States)

Bar-Itzhack, Itzhack Y.; Markley, F. Landis

1988-01-01

The problem of attitude determination in n-dimensional spaces is addressed. The proper parameters are found, and it is shown that not all three-dimensional methods have useful extensions to higher dimensions. It is demonstrated that Rodriguez parameters are conveniently extendable to other dimensions. An algorithm for using these parameters in the general n-dimensional case is developed and tested with a four-dimensional example. The correct mathematical description of angular velocities is addressed, showing that angular velocity in n dimensions cannot be represented by a vector but rather by a tensor of the second rank. Only in three dimensions can the angular velocity be described by a vector.

Charged fluid distribution in higher dimensional spheroidal space-time

Indian Academy of Sciences (India)

A general solution of Einstein field equations corresponding to a charged fluid distribution on the background of higher dimensional spheroidal space-time is obtained. The solution generates several known solutions for superdense star having spheroidal space-time geometry.

Approximating high-dimensional dynamics by barycentric coordinates with linear programming

Energy Technology Data Exchange (ETDEWEB)

Hirata, Yoshito, E-mail: yoshito@sat.t.u-tokyo.ac.jp; Aihara, Kazuyuki; Suzuki, Hideyuki [Institute of Industrial Science, The University of Tokyo, 4-6-1 Komaba, Meguro-ku, Tokyo 153-8505 (Japan); Department of Mathematical Informatics, The University of Tokyo, Bunkyo-ku, Tokyo 113-8656 (Japan); CREST, JST, 4-1-8 Honcho, Kawaguchi, Saitama 332-0012 (Japan); Shiro, Masanori [Department of Mathematical Informatics, The University of Tokyo, Bunkyo-ku, Tokyo 113-8656 (Japan); Mathematical Neuroinformatics Group, Advanced Industrial Science and Technology, Tsukuba, Ibaraki 305-8568 (Japan); Takahashi, Nozomu; Mas, Paloma [Center for Research in Agricultural Genomics (CRAG), Consorci CSIC-IRTA-UAB-UB, Barcelona 08193 (Spain)

2015-01-15

The increasing development of novel methods and techniques facilitates the measurement of high-dimensional time series but challenges our ability for accurate modeling and predictions. The use of a general mathematical model requires the inclusion of many parameters, which are difficult to be fitted for relatively short high-dimensional time series observed. Here, we propose a novel method to accurately model a high-dimensional time series. Our method extends the barycentric coordinates to high-dimensional phase space by employing linear programming, and allowing the approximation errors explicitly. The extension helps to produce free-running time-series predictions that preserve typical topological, dynamical, and/or geometric characteristics of the underlying attractors more accurately than the radial basis function model that is widely used. The method can be broadly applied, from helping to improve weather forecasting, to creating electronic instruments that sound more natural, and to comprehensively understanding complex biological data.

Approximating high-dimensional dynamics by barycentric coordinates with linear programming.

Science.gov (United States)

Hirata, Yoshito; Shiro, Masanori; Takahashi, Nozomu; Aihara, Kazuyuki; Suzuki, Hideyuki; Mas, Paloma

2015-01-01

The increasing development of novel methods and techniques facilitates the measurement of high-dimensional time series but challenges our ability for accurate modeling and predictions. The use of a general mathematical model requires the inclusion of many parameters, which are difficult to be fitted for relatively short high-dimensional time series observed. Here, we propose a novel method to accurately model a high-dimensional time series. Our method extends the barycentric coordinates to high-dimensional phase space by employing linear programming, and allowing the approximation errors explicitly. The extension helps to produce free-running time-series predictions that preserve typical topological, dynamical, and/or geometric characteristics of the underlying attractors more accurately than the radial basis function model that is widely used. The method can be broadly applied, from helping to improve weather forecasting, to creating electronic instruments that sound more natural, and to comprehensively understanding complex biological data.

Approximating high-dimensional dynamics by barycentric coordinates with linear programming

International Nuclear Information System (INIS)

Hirata, Yoshito; Aihara, Kazuyuki; Suzuki, Hideyuki; Shiro, Masanori; Takahashi, Nozomu; Mas, Paloma

2015-01-01

The increasing development of novel methods and techniques facilitates the measurement of high-dimensional time series but challenges our ability for accurate modeling and predictions. The use of a general mathematical model requires the inclusion of many parameters, which are difficult to be fitted for relatively short high-dimensional time series observed. Here, we propose a novel method to accurately model a high-dimensional time series. Our method extends the barycentric coordinates to high-dimensional phase space by employing linear programming, and allowing the approximation errors explicitly. The extension helps to produce free-running time-series predictions that preserve typical topological, dynamical, and/or geometric characteristics of the underlying attractors more accurately than the radial basis function model that is widely used. The method can be broadly applied, from helping to improve weather forecasting, to creating electronic instruments that sound more natural, and to comprehensively understanding complex biological data

Characterization of discontinuities in high-dimensional stochastic problems on adaptive sparse grids

International Nuclear Information System (INIS)

Jakeman, John D.; Archibald, Richard; Xiu Dongbin

2011-01-01

In this paper we present a set of efficient algorithms for detection and identification of discontinuities in high dimensional space. The method is based on extension of polynomial annihilation for discontinuity detection in low dimensions. Compared to the earlier work, the present method poses significant improvements for high dimensional problems. The core of the algorithms relies on adaptive refinement of sparse grids. It is demonstrated that in the commonly encountered cases where a discontinuity resides on a small subset of the dimensions, the present method becomes 'optimal', in the sense that the total number of points required for function evaluations depends linearly on the dimensionality of the space. The details of the algorithms will be presented and various numerical examples are utilized to demonstrate the efficacy of the method.

High-Voltage-Input Level Translator Using Standard CMOS

Science.gov (United States)

Yager, Jeremy A.; Mojarradi, Mohammad M.; Vo, Tuan A.; Blalock, Benjamin J.

2011-01-01

proposed integrated circuit would translate (1) a pair of input signals having a low differential potential and a possibly high common-mode potential into (2) a pair of output signals having the same low differential potential and a low common-mode potential. As used here, "low" and "high" refer to potentials that are, respectively, below or above the nominal supply potential (3.3 V) at which standard complementary metal oxide/semiconductor (CMOS) integrated circuits are designed to operate. The input common-mode potential could lie between 0 and 10 V; the output common-mode potential would be 2 V. This translation would make it possible to process the pair of signals by use of standard 3.3-V CMOS analog and/or mixed-signal (analog and digital) circuitry on the same integrated-circuit chip. A schematic of the circuit is shown in the figure. Standard 3.3-V CMOS circuitry cannot withstand input potentials greater than about 4 V. However, there are many applications that involve low-differential-potential, high-common-mode-potential input signal pairs and in which standard 3.3-V CMOS circuitry, which is relatively inexpensive, would be the most appropriate circuitry for performing other functions on the integrated-circuit chip that handles the high-potential input signals. Thus, there is a need to combine high-voltage input circuitry with standard low-voltage CMOS circuitry on the same integrated-circuit chip. The proposed circuit would satisfy this need. In the proposed circuit, the input signals would be coupled into both a level-shifting pair and a common-mode-sensing pair of CMOS transistors. The output of the level-shifting pair would be fed as input to a differential pair of transistors. The resulting differential current output would pass through six standoff transistors to be mirrored into an output branch by four heterojunction bipolar transistors. The mirrored differential current would be converted back to potential by a pair of diode-connected transistors

State-space dimensionality in short-memory hidden-variable theories

International Nuclear Information System (INIS)

Montina, Alberto

2011-01-01

Recently we have presented a hidden-variable model of measurements for a qubit where the hidden-variable state-space dimension is one-half the quantum-state manifold dimension. The absence of a short memory (Markov) dynamics is the price paid for this dimensional reduction. The conflict between having the Markov property and achieving the dimensional reduction was proved by Montina [A. Montina, Phys. Rev. A 77, 022104 (2008)] using an additional hypothesis of trajectory relaxation. Here we analyze in more detail this hypothesis introducing the concept of invertible process and report a proof that makes clearer the role played by the topology of the hidden-variable space. This is accomplished by requiring suitable properties of regularity of the conditional probability governing the dynamics. In the case of minimal dimension the set of continuous hidden variables is identified with an object living an N-dimensional Hilbert space whose dynamics is described by the Schroedinger equation. A method for generating the economical non-Markovian model for the qubit is also presented.

Three-dimensional space charge calculation method

International Nuclear Information System (INIS)

Lysenko, W.P.; Wadlinger, E.A.

1981-01-01

A method is presented for calculating space-charge forces suitable for use in a particle tracing code. Poisson's equation is solved in three dimensions with boundary conditions specified on an arbitrary surface by using a weighted residual method. Using a discrete particle distribution as our source input, examples are shown of off-axis, bunched beams of noncircular crosssection in radio-frequency quadrupole (RFQ) and drift-tube linac geometries

Three-Dimensional Terahertz Coded-Aperture Imaging Based on Single Input Multiple Output Technology

Directory of Open Access Journals (Sweden)

Shuo Chen

2018-01-01

Full Text Available As a promising radar imaging technique, terahertz coded-aperture imaging (TCAI can achieve high-resolution, forward-looking, and staring imaging by producing spatiotemporal independent signals with coded apertures. In this paper, we propose a three-dimensional (3D TCAI architecture based on single input multiple output (SIMO technology, which can reduce the coding and sampling times sharply. The coded aperture applied in the proposed TCAI architecture loads either purposive or random phase modulation factor. In the transmitting process, the purposive phase modulation factor drives the terahertz beam to scan the divided 3D imaging cells. In the receiving process, the random phase modulation factor is adopted to modulate the terahertz wave to be spatiotemporally independent for high resolution. Considering human-scale targets, images of each 3D imaging cell are reconstructed one by one to decompose the global computational complexity, and then are synthesized together to obtain the complete high-resolution image. As for each imaging cell, the multi-resolution imaging method helps to reduce the computational burden on a large-scale reference-signal matrix. The experimental results demonstrate that the proposed architecture can achieve high-resolution imaging with much less time for 3D targets and has great potential in applications such as security screening, nondestructive detection, medical diagnosis, etc.

hdm: High-dimensional metrics

OpenAIRE

Chernozhukov, Victor; Hansen, Christian; Spindler, Martin

2016-01-01

In this article the package High-dimensional Metrics (\\texttt{hdm}) is introduced. It is a collection of statistical methods for estimation and quantification of uncertainty in high-dimensional approximately sparse models. It focuses on providing confidence intervals and significance testing for (possibly many) low-dimensional subcomponents of the high-dimensional parameter vector. Efficient estimators and uniformly valid confidence intervals for regression coefficients on target variables (e...

Similarity-dissimilarity plot for visualization of high dimensional data in biomedical pattern classification.

Science.gov (United States)

Arif, Muhammad

2012-06-01

In pattern classification problems, feature extraction is an important step. Quality of features in discriminating different classes plays an important role in pattern classification problems. In real life, pattern classification may require high dimensional feature space and it is impossible to visualize the feature space if the dimension of feature space is greater than four. In this paper, we have proposed a Similarity-Dissimilarity plot which can project high dimensional space to a two dimensional space while retaining important characteristics required to assess the discrimination quality of the features. Similarity-dissimilarity plot can reveal information about the amount of overlap of features of different classes. Separable data points of different classes will also be visible on the plot which can be classified correctly using appropriate classifier. Hence, approximate classification accuracy can be predicted. Moreover, it is possible to know about whom class the misclassified data points will be confused by the classifier. Outlier data points can also be located on the similarity-dissimilarity plot. Various examples of synthetic data are used to highlight important characteristics of the proposed plot. Some real life examples from biomedical data are also used for the analysis. The proposed plot is independent of number of dimensions of the feature space.

High Dimensional Classification Using Features Annealed Independence Rules.

Science.gov (United States)

Fan, Jianqing; Fan, Yingying

2008-01-01

Classification using high-dimensional features arises frequently in many contemporary statistical studies such as tumor classification using microarray or other high-throughput data. The impact of dimensionality on classifications is largely poorly understood. In a seminal paper, Bickel and Levina (2004) show that the Fisher discriminant performs poorly due to diverging spectra and they propose to use the independence rule to overcome the problem. We first demonstrate that even for the independence classification rule, classification using all the features can be as bad as the random guessing due to noise accumulation in estimating population centroids in high-dimensional feature space. In fact, we demonstrate further that almost all linear discriminants can perform as bad as the random guessing. Thus, it is paramountly important to select a subset of important features for high-dimensional classification, resulting in Features Annealed Independence Rules (FAIR). The conditions under which all the important features can be selected by the two-sample t-statistic are established. The choice of the optimal number of features, or equivalently, the threshold value of the test statistics are proposed based on an upper bound of the classification error. Simulation studies and real data analysis support our theoretical results and demonstrate convincingly the advantage of our new classification procedure.

A Hybrid Semi-Supervised Anomaly Detection Model for High-Dimensional Data

Directory of Open Access Journals (Sweden)

Hongchao Song

2017-01-01

Full Text Available Anomaly detection, which aims to identify observations that deviate from a nominal sample, is a challenging task for high-dimensional data. Traditional distance-based anomaly detection methods compute the neighborhood distance between each observation and suffer from the curse of dimensionality in high-dimensional space; for example, the distances between any pair of samples are similar and each sample may perform like an outlier. In this paper, we propose a hybrid semi-supervised anomaly detection model for high-dimensional data that consists of two parts: a deep autoencoder (DAE and an ensemble k-nearest neighbor graphs- (K-NNG- based anomaly detector. Benefiting from the ability of nonlinear mapping, the DAE is first trained to learn the intrinsic features of a high-dimensional dataset to represent the high-dimensional data in a more compact subspace. Several nonparametric KNN-based anomaly detectors are then built from different subsets that are randomly sampled from the whole dataset. The final prediction is made by all the anomaly detectors. The performance of the proposed method is evaluated on several real-life datasets, and the results confirm that the proposed hybrid model improves the detection accuracy and reduces the computational complexity.

Vector calculus in non-integer dimensional space and its applications to fractal media

Science.gov (United States)

Tarasov, Vasily E.

2015-02-01

We suggest a generalization of vector calculus for the case of non-integer dimensional space. The first and second orders operations such as gradient, divergence, the scalar and vector Laplace operators for non-integer dimensional space are defined. For simplification we consider scalar and vector fields that are independent of angles. We formulate a generalization of vector calculus for rotationally covariant scalar and vector functions. This generalization allows us to describe fractal media and materials in the framework of continuum models with non-integer dimensional space. As examples of application of the suggested calculus, we consider elasticity of fractal materials (fractal hollow ball and fractal cylindrical pipe with pressure inside and outside), steady distribution of heat in fractal media, electric field of fractal charged cylinder. We solve the correspondent equations for non-integer dimensional space models.

Mars 2.2 code manual: input requirements

International Nuclear Information System (INIS)

Chung, Bub Dong; Lee, Won Jae; Jeong, Jae Jun; Lee, Young Jin; Hwang, Moon Kyu; Kim, Kyung Doo; Lee, Seung Wook; Bae, Sung Won

2003-07-01

Korea Advanced Energy Research Institute (KAERI) conceived and started the development of MARS code with the main objective of producing a state-of-the-art realistic thermal hydraulic systems analysis code with multi-dimensional analysis capability. MARS achieves this objective by very tightly integrating the one dimensional RELAP5/MOD3 with the multi-dimensional COBRA-TF codes. The method of integration of the two codes is based on the dynamic link library techniques, and the system pressure equation matrices of both codes are implicitly integrated and solved simultaneously. In addition, the Equation-of-State (EOS) for the light water was unified by replacing the EOS of COBRA-TF by that of the RELAP5. This input manual provides a complete list of input required to run MARS. The manual is divided largely into two parts, namely, the one-dimensional part and the multi-dimensional part. The inputs for auxiliary parts such as minor edit requests and graph formatting inputs are shared by the two parts and as such mixed input is possible. The overall structure of the input is modeled on the structure of the RELAP5 and as such the layout of the manual is very similar to that of the RELAP. This similitude to RELAP5 input is intentional as this input scheme will allow minimum modification between the inputs of RELAP5 and MARS. MARS development team would like to express its appreciation to the RELAP5 Development Team and the USNRC for making this manual possible

MARS code manual volume II: input requirements

International Nuclear Information System (INIS)

Chung, Bub Dong; Kim, Kyung Doo; Bae, Sung Won; Jeong, Jae Jun; Lee, Seung Wook; Hwang, Moon Kyu

2010-02-01

Korea Advanced Energy Research Institute (KAERI) conceived and started the development of MARS code with the main objective of producing a state-of-the-art realistic thermal hydraulic systems analysis code with multi-dimensional analysis capability. MARS achieves this objective by very tightly integrating the one dimensional RELAP5/MOD3 with the multi-dimensional COBRA-TF codes. The method of integration of the two codes is based on the dynamic link library techniques, and the system pressure equation matrices of both codes are implicitly integrated and solved simultaneously. In addition, the Equation-Of-State (EOS) for the light water was unified by replacing the EOS of COBRA-TF by that of the RELAP5. This input manual provides a complete list of input required to run MARS. The manual is divided largely into two parts, namely, the one-dimensional part and the multi-dimensional part. The inputs for auxiliary parts such as minor edit requests and graph formatting inputs are shared by the two parts and as such mixed input is possible. The overall structure of the input is modeled on the structure of the RELAP5 and as such the layout of the manual is very similar to that of the RELAP. This similitude to RELAP5 input is intentional as this input scheme will allow minimum modification between the inputs of RELAP5 and MARS3.1. MARS3.1 development team would like to express its appreciation to the RELAP5 Development Team and the USNRC for making this manual possible

DataHigh: Graphical user interface for visualizing and interacting with high-dimensional neural activity

OpenAIRE

Cowley, Benjamin R.; Kaufman, Matthew T.; Churchland, Mark M.; Ryu, Stephen I.; Shenoy, Krishna V.; Yu, Byron M.

2012-01-01

The activity of tens to hundreds of neurons can be succinctly summarized by a smaller number of latent variables extracted using dimensionality reduction methods. These latent variables define a reduced-dimensional space in which we can study how population activity varies over time, across trials, and across experimental conditions. Ideally, we would like to visualize the population activity directly in the reduced-dimensional space, whose optimal dimensionality (as determined from the data)...

Six-dimensional real and reciprocal space small-angle X-ray scattering tomography.

Science.gov (United States)

Schaff, Florian; Bech, Martin; Zaslansky, Paul; Jud, Christoph; Liebi, Marianne; Guizar-Sicairos, Manuel; Pfeiffer, Franz

2015-11-19

When used in combination with raster scanning, small-angle X-ray scattering (SAXS) has proven to be a valuable imaging technique of the nanoscale, for example of bone, teeth and brain matter. Although two-dimensional projection imaging has been used to characterize various materials successfully, its three-dimensional extension, SAXS computed tomography, poses substantial challenges, which have yet to be overcome. Previous work using SAXS computed tomography was unable to preserve oriented SAXS signals during reconstruction. Here we present a solution to this problem and obtain a complete SAXS computed tomography, which preserves oriented scattering information. By introducing virtual tomography axes, we take advantage of the two-dimensional SAXS information recorded on an area detector and use it to reconstruct the full three-dimensional scattering distribution in reciprocal space for each voxel of the three-dimensional object in real space. The presented method could be of interest for a combined six-dimensional real and reciprocal space characterization of mesoscopic materials with hierarchically structured features with length scales ranging from a few nanometres to a few millimetres--for example, biomaterials such as bone or teeth, or functional materials such as fuel-cell or battery components.

Model-based Clustering of High-Dimensional Data in Astrophysics

Science.gov (United States)

Bouveyron, C.

2016-05-01

The nature of data in Astrophysics has changed, as in other scientific fields, in the past decades due to the increase of the measurement capabilities. As a consequence, data are nowadays frequently of high dimensionality and available in mass or stream. Model-based techniques for clustering are popular tools which are renowned for their probabilistic foundations and their flexibility. However, classical model-based techniques show a disappointing behavior in high-dimensional spaces which is mainly due to their dramatical over-parametrization. The recent developments in model-based classification overcome these drawbacks and allow to efficiently classify high-dimensional data, even in the "small n / large p" situation. This work presents a comprehensive review of these recent approaches, including regularization-based techniques, parsimonious modeling, subspace classification methods and classification methods based on variable selection. The use of these model-based methods is also illustrated on real-world classification problems in Astrophysics using R packages.

Modeling extreme "Carrington-type" space weather events using three-dimensional global MHD simulations

Science.gov (United States)

Ngwira, Chigomezyo M.; Pulkkinen, Antti; Kuznetsova, Maria M.; Glocer, Alex

2014-06-01

There is a growing concern over possible severe societal consequences related to adverse space weather impacts on man-made technological infrastructure. In the last two decades, significant progress has been made toward the first-principles modeling of space weather events, and three-dimensional (3-D) global magnetohydrodynamics (MHD) models have been at the forefront of this transition, thereby playing a critical role in advancing our understanding of space weather. However, the modeling of extreme space weather events is still a major challenge even for the modern global MHD models. In this study, we introduce a specially adapted University of Michigan 3-D global MHD model for simulating extreme space weather events with a Dst footprint comparable to the Carrington superstorm of September 1859 based on the estimate by Tsurutani et. al. (2003). Results are presented for a simulation run with "very extreme" constructed/idealized solar wind boundary conditions driving the magnetosphere. In particular, we describe the reaction of the magnetosphere-ionosphere system and the associated induced geoelectric field on the ground to such extreme driving conditions. The model setup is further tested using input data for an observed space weather event of Halloween storm October 2003 to verify the MHD model consistence and to draw additional guidance for future work. This extreme space weather MHD model setup is designed specifically for practical application to the modeling of extreme geomagnetically induced electric fields, which can drive large currents in ground-based conductor systems such as power transmission grids. Therefore, our ultimate goal is to explore the level of geoelectric fields that can be induced from an assumed storm of the reported magnitude, i.e., Dst˜=-1600 nT.

Elucidating high-dimensional cancer hallmark annotation via enriched ontology.

Science.gov (United States)

Yan, Shankai; Wong, Ka-Chun

2017-09-01

Cancer hallmark annotation is a promising technique that could discover novel knowledge about cancer from the biomedical literature. The automated annotation of cancer hallmarks could reveal relevant cancer transformation processes in the literature or extract the articles that correspond to the cancer hallmark of interest. It acts as a complementary approach that can retrieve knowledge from massive text information, advancing numerous focused studies in cancer research. Nonetheless, the high-dimensional nature of cancer hallmark annotation imposes a unique challenge. To address the curse of dimensionality, we compared multiple cancer hallmark annotation methods on 1580 PubMed abstracts. Based on the insights, a novel approach, UDT-RF, which makes use of ontological features is proposed. It expands the feature space via the Medical Subject Headings (MeSH) ontology graph and utilizes novel feature selections for elucidating the high-dimensional cancer hallmark annotation space. To demonstrate its effectiveness, state-of-the-art methods are compared and evaluated by a multitude of performance metrics, revealing the full performance spectrum on the full set of cancer hallmarks. Several case studies are conducted, demonstrating how the proposed approach could reveal novel insights into cancers. https://github.com/cskyan/chmannot. Copyright © 2017 Elsevier Inc. All rights reserved.

Preventing Out-of-Sequence for Multicast Input-Queued Space-Memory-Memory Clos-Network

DEFF Research Database (Denmark)

Yu, Hao; Ruepp, Sarah Renée; Berger, Michael Stübert

2011-01-01

This paper proposes an out-of-sequence (OOS) preventative cell dispatching algorithm, the multicast flow-based round robin (MFRR), for multicast input-queued space-memory-memory (IQ-SMM) Clos-network architecture. Independently treating each incoming cell, such as the desynchronized static round...

Topological properties of function spaces $C_k(X,2)$ over zero-dimensional metric spaces $X$

OpenAIRE

Gabriyelyan, S.

2015-01-01

Let $X$ be a zero-dimensional metric space and $X'$ its derived set. We prove the following assertions: (1) the space $C_k(X,2)$ is an Ascoli space iff $C_k(X,2)$ is $k_\\mathbb{R}$-space iff either $X$ is locally compact or $X$ is not locally compact but $X'$ is compact, (2) $C_k(X,2)$ is a $k$-space iff either $X$ is a topological sum of a Polish locally compact space and a discrete space or $X$ is not locally compact but $X'$ is compact, (3) $C_k(X,2)$ is a sequential space iff $X$ is a Pol...

Addressing Curse of Dimensionality in Sensitivity Analysis: How Can We Handle High-Dimensional Problems?

Science.gov (United States)

Safaei, S.; Haghnegahdar, A.; Razavi, S.

2016-12-01

Complex environmental models are now the primary tool to inform decision makers for the current or future management of environmental resources under the climate and environmental changes. These complex models often contain a large number of parameters that need to be determined by a computationally intensive calibration procedure. Sensitivity analysis (SA) is a very useful tool that not only allows for understanding the model behavior, but also helps in reducing the number of calibration parameters by identifying unimportant ones. The issue is that most global sensitivity techniques are highly computationally demanding themselves for generating robust and stable sensitivity metrics over the entire model response surface. Recently, a novel global sensitivity analysis method, Variogram Analysis of Response Surfaces (VARS), is introduced that can efficiently provide a comprehensive assessment of global sensitivity using the Variogram concept. In this work, we aim to evaluate the effectiveness of this highly efficient GSA method in saving computational burden, when applied to systems with extra-large number of input factors ( 100). We use a test function and a hydrological modelling case study to demonstrate the capability of VARS method in reducing problem dimensionality by identifying important vs unimportant input factors.

An Integrated Approach to Parameter Learning in Infinite-Dimensional Space

Energy Technology Data Exchange (ETDEWEB)

Boyd, Zachary M. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Wendelberger, Joanne Roth [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

2017-09-14

The availability of sophisticated modern physics codes has greatly extended the ability of domain scientists to understand the processes underlying their observations of complicated processes, but it has also introduced the curse of dimensionality via the many user-set parameters available to tune. Many of these parameters are naturally expressed as functional data, such as initial temperature distributions, equations of state, and controls. Thus, when attempting to find parameters that match observed data, being able to navigate parameter-space becomes highly non-trivial, especially considering that accurate simulations can be expensive both in terms of time and money. Existing solutions include batch-parallel simulations, high-dimensional, derivative-free optimization, and expert guessing, all of which make some contribution to solving the problem but do not completely resolve the issue. In this work, we explore the possibility of coupling together all three of the techniques just described by designing user-guided, batch-parallel optimization schemes. Our motivating example is a neutron diffusion partial differential equation where the time-varying multiplication factor serves as the unknown control parameter to be learned. We find that a simple, batch-parallelizable, random-walk scheme is able to make some progress on the problem but does not by itself produce satisfactory results. After reducing the dimensionality of the problem using functional principal component analysis (fPCA), we are able to track the progress of the solver in a visually simple way as well as viewing the associated principle components. This allows a human to make reasonable guesses about which points in the state space the random walker should try next. Thus, by combining the random walker's ability to find descent directions with the human's understanding of the underlying physics, it is possible to use expensive simulations more efficiently and more quickly arrive at the

Convergent-beam electron diffraction study of incommensurately modulated crystals. Pt. 2. (3 + 1)-dimensional space groups

International Nuclear Information System (INIS)

Terauchi, Masami; Takahashi, Mariko; Tanaka, Michiyoshi

1994-01-01

The convergent-beam electron diffraction (CBED) method for determining three-dimensional space groups is extended to the determination of the (3 + 1)-dimensional space groups for one-dimensional incommensurately modulated crystals. It is clarified than an approximate dynamical extinction line appears in the CBED discs of the reflections caused by an incommensurate modulation. The extinction enables the space-group determination of the (3 + 1)-dimensional crystals or the one-dimensional incommensurately modulated crystals. An example of the dynamical extinction line is shown using an incommensurately modulated crystal of Sr 2 Nb 2 O 7 . Tables of the dynamical extinction lines appearing in CBED patterns are given for all the (3 + 1)-dimensional space groups of the incommensurately modulated crystal. (orig.)

Three-dimensional space: locomotory style explains memory differences in rats and hummingbirds.

Science.gov (United States)

Flores-Abreu, I Nuri; Hurly, T Andrew; Ainge, James A; Healy, Susan D

2014-06-07

While most animals live in a three-dimensional world, they move through it to different extents depending on their mode of locomotion: terrestrial animals move vertically less than do swimming and flying animals. As nearly everything we know about how animals learn and remember locations in space comes from two-dimensional experiments in the horizontal plane, here we determined whether the use of three-dimensional space by a terrestrial and a flying animal was correlated with memory for a rewarded location. In the cubic mazes in which we trained and tested rats and hummingbirds, rats moved more vertically than horizontally, whereas hummingbirds moved equally in the three dimensions. Consistent with their movement preferences, rats were more accurate in relocating the horizontal component of a rewarded location than they were in the vertical component. Hummingbirds, however, were more accurate in the vertical dimension than they were in the horizontal, a result that cannot be explained by their use of space. Either as a result of evolution or ontogeny, it appears that birds and rats prioritize horizontal versus vertical components differently when they remember three-dimensional space.

Dirac equation in 5- and 6-dimensional curved space-time manifolds

International Nuclear Information System (INIS)

Vladimirov, Yu.S.; Popov, A.D.

1984-01-01

The program of plotting unified multidimensional theory of gravitation, electromagnetism and electrically charged matter with transition from 5-dimensional variants to 6-dimensional theory possessing signature (+----+) is developed. For recording the Dirac equation in 5- and 6-dimensional curved space-time manifolds the tetrad formalism and γ-matrix formulation of the General Relativity Theory are used. It is shown that the 6-dimensional theory case unifies the two private cases of 5-dimensional theory and corresponds to two possibilities of the theory developed by Kadyshevski

Clustering high dimensional data

DEFF Research Database (Denmark)

Assent, Ira

2012-01-01

High-dimensional data, i.e., data described by a large number of attributes, pose specific challenges to clustering. The so-called ‘curse of dimensionality’, coined originally to describe the general increase in complexity of various computational problems as dimensionality increases, is known...... to render traditional clustering algorithms ineffective. The curse of dimensionality, among other effects, means that with increasing number of dimensions, a loss of meaningful differentiation between similar and dissimilar objects is observed. As high-dimensional objects appear almost alike, new approaches...... for clustering are required. Consequently, recent research has focused on developing techniques and clustering algorithms specifically for high-dimensional data. Still, open research issues remain. Clustering is a data mining task devoted to the automatic grouping of data based on mutual similarity. Each cluster...

To quantum averages through asymptotic expansion of classical averages on infinite-dimensional space

International Nuclear Information System (INIS)

Khrennikov, Andrei

2007-01-01

We study asymptotic expansions of Gaussian integrals of analytic functionals on infinite-dimensional spaces (Hilbert and nuclear Frechet). We obtain an asymptotic equality coupling the Gaussian integral and the trace of the composition of scaling of the covariation operator of a Gaussian measure and the second (Frechet) derivative of a functional. In this way we couple classical average (given by an infinite-dimensional Gaussian integral) and quantum average (given by the von Neumann trace formula). We can interpret this mathematical construction as a procedure of 'dequantization' of quantum mechanics. We represent quantum mechanics as an asymptotic projection of classical statistical mechanics with infinite-dimensional phase space. This space can be represented as the space of classical fields, so quantum mechanics is represented as a projection of 'prequantum classical statistical field theory'

Construction of high-dimensional universal quantum logic gates using a Λ system coupled with a whispering-gallery-mode microresonator.

Science.gov (United States)

He, Ling Yan; Wang, Tie-Jun; Wang, Chuan

2016-07-11

High-dimensional quantum system provides a higher capacity of quantum channel, which exhibits potential applications in quantum information processing. However, high-dimensional universal quantum logic gates is difficult to achieve directly with only high-dimensional interaction between two quantum systems and requires a large number of two-dimensional gates to build even a small high-dimensional quantum circuits. In this paper, we propose a scheme to implement a general controlled-flip (CF) gate where the high-dimensional single photon serve as the target qudit and stationary qubits work as the control logic qudit, by employing a three-level Λ-type system coupled with a whispering-gallery-mode microresonator. In our scheme, the required number of interaction times between the photon and solid state system reduce greatly compared with the traditional method which decomposes the high-dimensional Hilbert space into 2-dimensional quantum space, and it is on a shorter temporal scale for the experimental realization. Moreover, we discuss the performance and feasibility of our hybrid CF gate, concluding that it can be easily extended to a 2n-dimensional case and it is feasible with current technology.

High-Dimensional Metrics in R

OpenAIRE

Chernozhukov, Victor; Hansen, Chris; Spindler, Martin

2016-01-01

The package High-dimensional Metrics (\\Rpackage{hdm}) is an evolving collection of statistical methods for estimation and quantification of uncertainty in high-dimensional approximately sparse models. It focuses on providing confidence intervals and significance testing for (possibly many) low-dimensional subcomponents of the high-dimensional parameter vector. Efficient estimators and uniformly valid confidence intervals for regression coefficients on target variables (e.g., treatment or poli...

Out-of-Sequence Prevention for Multicast Input-Queuing Space-Memory-Memory Clos-Network

DEFF Research Database (Denmark)

Yu, Hao; Ruepp, Sarah; Berger, Michael Stübert

2011-01-01

This paper proposes two cell dispatching algorithms for the input-queuing space-memory-memory (IQ-SMM) Closnetwork to reduce out-of-sequence (OOS) for multicast traffic. The frequent connection pattern change of DSRR results in a severe OOS problem. Based on the principle of DSRR, MFDSRR is able ...

Application of data mining in three-dimensional space time reactor model

International Nuclear Information System (INIS)

Jiang Botao; Zhao Fuyu

2011-01-01

A high-fidelity three-dimensional space time nodal method has been developed to simulate the dynamics of the reactor core for real time simulation. This three-dimensional reactor core mathematical model can be composed of six sub-models, neutron kinetics model, cay heat model, fuel conduction model, thermal hydraulics model, lower plenum model, and core flow distribution model. During simulation of each sub-model some operation data will be produced and lots of valuable, important information reflecting the reactor core operation status could be hidden in, so how to discovery these information becomes the primary mission people concern. Under this background, data mining (DM) is just created and developed to solve this problem, no matter what engineering aspects or business fields. Generally speaking, data mining is a process of finding some useful and interested information from huge data pool. Support Vector Machine (SVM) is a new technique of data mining appeared in recent years, and SVR is a transformed method of SVM which is applied in regression cases. This paper presents only two significant sub-models of three-dimensional reactor core mathematical model, the nodal space time neutron kinetics model and the thermal hydraulics model, based on which the neutron flux and enthalpy distributions of the core are obtained by solving the three-dimensional nodal space time kinetics equations and energy equations for both single and two-phase flows respectively. Moreover, it describes that the three-dimensional reactor core model can also be used to calculate and determine the reactivity effects of the moderator temperature, boron concentration, fuel temperature, coolant void, xenon worth, samarium worth, control element positions (CEAs) and core burnup status. Besides these, the main mathematic theory of SVR is introduced briefly next, on the basis of which SVR is applied to dealing with the data generated by two sample calculation, rod ejection transient and axial

Naked singularities in higher dimensional Vaidya space-times

International Nuclear Information System (INIS)

Ghosh, S. G.; Dadhich, Naresh

2001-01-01

We investigate the end state of the gravitational collapse of a null fluid in higher-dimensional space-times. Both naked singularities and black holes are shown to be developing as the final outcome of the collapse. The naked singularity spectrum in a collapsing Vaidya region (4D) gets covered with the increase in dimensions and hence higher dimensions favor a black hole in comparison to a naked singularity. The cosmic censorship conjecture will be fully respected for a space of infinite dimension

Quantum vacuum energy in two dimensional space-times

International Nuclear Information System (INIS)

Davies, P.C.W.; Fulling, S.A.

1977-01-01

The paper presents in detail the renormalization theory of the energy-momentum tensor of a two dimensional massless scalar field which has been used elsewhere to study the local physics in a model of black hole evaporation. The treatment is generalized to include the Casimir effect occurring in spatially finite models. The essence of the method is evaluation of the field products in the tensor as functions of two points, followed by covariant subtraction of the discontinuous terms arising as the points coalesce. In two dimensional massless theories, conformal transformations permit exact calculations to be performed. The results are applied here to some special cases, primarily space-times of constant curvature, with emphasis on the existence of distinct 'vacuum' states associated naturally with different conformal coordinate systems. The relevance of the work to the general problems of defining observables and of classifying and interpreting states in curved-space quantum field theory is discussed. (author)

Quantum vacuum energy in two dimensional space-times

Energy Technology Data Exchange (ETDEWEB)

Davies, P C.W.; Fulling, S A [King' s Coll., London (UK). Dept. of Mathematics

1977-04-21

The paper presents in detail the renormalization theory of the energy-momentum tensor of a two dimensional massless scalar field which has been used elsewhere to study the local physics in a model of black hole evaporation. The treatment is generalized to include the Casimir effect occurring in spatially finite models. The essence of the method is evaluation of the field products in the tensor as functions of two points, followed by covariant subtraction of the discontinuous terms arising as the points coalesce. In two dimensional massless theories, conformal transformations permit exact calculations to be performed. The results are applied here to some special cases, primarily space-times of constant curvature, with emphasis on the existence of distinct 'vacuum' states associated naturally with different conformal coordinate systems. The relevance of the work to the general problems of defining observables and of classifying and interpreting states in curved-space quantum field theory is discussed.

High-Resolution Reciprocal Space Mapping for Characterizing Deformation Structures

DEFF Research Database (Denmark)

Pantleon, Wolfgang; Wejdemann, Christian; Jakobsen, Bo

2014-01-01

With high-angular resolution three-dimensional X-ray diffraction (3DXRD), quantitative information is gained about dislocation structures in individual grains in the bulk of a macroscopic specimen by acquiring reciprocal space maps. In high-resolution 3D reciprocal space maps of tensile......-deformed copper, individual, almost dislocation-free subgrains are identified from high-intensity peaks and distinguished by their unique combination of orientation and elastic strain; dislocation walls manifest themselves as a smooth cloud of lower intensity. The elastic strain shows only minor variations within...... dynamics is followed in situ during varying loading conditions by reciprocal space mapping: during uninterrupted tensile deformation, formation of subgrains is observed concurrently with broadening of Bragg reflections shortly after the onset of plastic deformation. When the traction is terminated, stress...

How the flip target behaves in four-dimensional space

International Nuclear Information System (INIS)

Antillon, A.; Kats, J.

1985-01-01

We use available coupling theory for understanding how a flip target in a 4-dimensional phase space reduces a gaussian beam of particles. Experimental evidence at the AGS can be qualitatively explained by this theory

Quantum interest in (3+1)-dimensional Minkowski space

International Nuclear Information System (INIS)

Abreu, Gabriel; Visser, Matt

2009-01-01

The so-called 'quantum inequalities', and the 'quantum interest conjecture', use quantum field theory to impose significant restrictions on the temporal distribution of the energy density measured by a timelike observer, potentially preventing the existence of exotic phenomena such as 'Alcubierre warp drives' or 'traversable wormholes'. Both the quantum inequalities and the quantum interest conjecture can be reduced to statements concerning the existence or nonexistence of bound states for a certain one-dimensional quantum mechanical pseudo-Hamiltonian. Using this approach, we shall provide a simple variational proof of one version of the quantum interest conjecture in (3+1)-dimensional Minkowski space.

On High Dimensional Searching Spaces and Learning Methods

DEFF Research Database (Denmark)

Yazdani, Hossein; Ortiz-Arroyo, Daniel; Choros, Kazimierz

2017-01-01

, and similarity functions and discuss the pros and cons of using each of them. Conventional similarity functions evaluate objects in the vector space. Contrarily, Weighted Feature Distance (WFD) functions compare data objects in both feature and vector spaces, preventing the system from being affected by some...

Method of solving conformal models in D-dimensional space I

International Nuclear Information System (INIS)

Fradkin, E.S.; Palchik, M.Y.

1996-01-01

We study the Hilbert space of conformal field theory in D-dimensional space. The latter is shown to have model-independent structure. The states of matter fields and gauge fields form orthogonal subspaces. The dynamical principle fixing the choice of model may be formulated either in each of these subspaces or in their direct sum. In the latter case, gauge interactions are necessarily present in the model. We formulate the conditions specifying the class of models where gauge interactions are being neglected. The anomalous Ward identities are derived. Different values of anomalous parameters (D-dimensional analogs of a central charge, including operator ones) correspond to different models. The structure of these models is analogous to that of 2-dimensional conformal theories. Each model is specified by D-dimensional analog of null vector. The exact solutions of the simplest models of this type are examined. It is shown that these models are equivalent to Lagrangian models of scalar fields with a triple interaction. The values of dimensions of such fields are calculated, and the closed sets of differential equations for higher Green functions are derived. Copyright copyright 1996 Academic Press, Inc

Hyper dimensional phase-space solver and its application to laser-matter

Energy Technology Data Exchange (ETDEWEB)

Kondoh, Yoshiaki; Nakamura, Takashi; Yabe, Takashi [Department of Energy Sciences, Tokyo Institute of Technology, Yokohama, Kanagawa (Japan)

2000-03-01

A new numerical scheme for solving the hyper-dimensional Vlasov-Poisson equation in phase space is described. At each time step, the distribution function and its first derivatives are advected in phase space by the Cubic Interpolated Propagation (CIP) scheme. Although a cell within grid points is interpolated by a cubic-polynomial, any matrix solutions are not required. The scheme guarantees the exact conservation of the mass. The numerical results show good agreement with the theory. Even if we reduce the number of grid points in the v-direction, the scheme still gives stable, accurate and reasonable results with memory storage comparable to particle simulations. Owing to this fact, the scheme has succeeded to be generalized in a straightforward way to deal with the six-dimensional, or full-dimensional problems. (author)

Hyper dimensional phase-space solver and its application to laser-matter

International Nuclear Information System (INIS)

Kondoh, Yoshiaki; Nakamura, Takashi; Yabe, Takashi

2000-01-01

A new numerical scheme for solving the hyper-dimensional Vlasov-Poisson equation in phase space is described. At each time step, the distribution function and its first derivatives are advected in phase space by the Cubic Interpolated Propagation (CIP) scheme. Although a cell within grid points is interpolated by a cubic-polynomial, any matrix solutions are not required. The scheme guarantees the exact conservation of the mass. The numerical results show good agreement with the theory. Even if we reduce the number of grid points in the v-direction, the scheme still gives stable, accurate and reasonable results with memory storage comparable to particle simulations. Owing to this fact, the scheme has succeeded to be generalized in a straightforward way to deal with the six-dimensional, or full-dimensional problems. (author)

Numerical Resolution of N-dimensional Fokker-Planck stochastic equations; Resolucion Numerica de Ecuaciones Estocasticas de tipo Fokker-Planck en Varias Dimensiones

Energy Technology Data Exchange (ETDEWEB)

Garcia-Olivares, R A; Munoz Roldan, A

1992-07-01

This document describes the use of a library of programs able to solve stochastic Fokker-Planck equations in a N-dimensional space. The input data are essentially: (i) the initial distribution of the stochastic variable, (ii) the drift and fluctuation coefficients as a function of the state (which can be obtained from the transition probabilities between neighboring states) and (iii) some parameters controlling the run. A last version of the library accepts sources and sinks defined in the states space. The output is the temporal evolution of the probability distribution in the space defined by a N-dimensional grid. Some applications and readings in Synergetic, Self-Organization, transport phenomena, Ecology and other fields are suggested. If the probability distribution is interpreted as a distribution of particles then the codes can be used to solve the N-dimensional problem of advection-diffusion. (Author) 16 refs.

Elasticity of fractal materials using the continuum model with non-integer dimensional space

Science.gov (United States)

Tarasov, Vasily E.

2015-01-01

Using a generalization of vector calculus for space with non-integer dimension, we consider elastic properties of fractal materials. Fractal materials are described by continuum models with non-integer dimensional space. A generalization of elasticity equations for non-integer dimensional space, and its solutions for the equilibrium case of fractal materials are suggested. Elasticity problems for fractal hollow ball and cylindrical fractal elastic pipe with inside and outside pressures, for rotating cylindrical fractal pipe, for gradient elasticity and thermoelasticity of fractal materials are solved.

Possibilities of identifying cyber attack in noisy space of n-dimensional abstract system

Energy Technology Data Exchange (ETDEWEB)

Jašek, Roman; Dvořák, Jiří; Janková, Martina; Sedláček, Michal [Tomas Bata University in Zlin Nad Stranemi 4511, 760 05 Zlin, Czech republic jasek@fai.utb.cz, dvorakj@aconte.cz, martina.jankova@email.cz, michal.sedlacek@email.cz (Czech Republic)

2016-06-08

This article briefly mentions some selected options of current concept for identifying cyber attacks from the perspective of the new cyberspace of real system. In the cyberspace, there is defined n-dimensional abstract system containing elements of the spatial arrangement of partial system elements such as micro-environment of cyber systems surrounded by other suitably arranged corresponding noise space. This space is also gradually supplemented by a new image of dynamic processes in a discreet environment, and corresponding again to n-dimensional expression of time space defining existence and also the prediction for expected cyber attacksin the noise space. Noises are seen here as useful and necessary for modern information and communication technologies (e.g. in processes of applied cryptography in ICT) and then the so-called useless noises designed for initial (necessary) filtering of this highly aggressive environment and in future expectedly offensive background in cyber war (e.g. the destruction of unmanned means of an electromagnetic pulse, or for destruction of new safety barriers created on principles of electrostatic field or on other principles of modern physics, etc.). The key to these new options is the expression of abstract systems based on the models of microelements of cyber systems and their hierarchical concept in structure of n-dimensional system in given cyberspace. The aim of this article is to highlight the possible systemic expression of cyberspace of abstract system and possible identification in time-spatial expression of real environment (on microelements of cyber systems and their surroundings with noise characteristics and time dimension in dynamic of microelements’ own time and externaltime defined by real environment). The article was based on a partial task of faculty specific research.

Possibilities of identifying cyber attack in noisy space of n-dimensional abstract system

International Nuclear Information System (INIS)

Jašek, Roman; Dvořák, Jiří; Janková, Martina; Sedláček, Michal

2016-01-01

This article briefly mentions some selected options of current concept for identifying cyber attacks from the perspective of the new cyberspace of real system. In the cyberspace, there is defined n-dimensional abstract system containing elements of the spatial arrangement of partial system elements such as micro-environment of cyber systems surrounded by other suitably arranged corresponding noise space. This space is also gradually supplemented by a new image of dynamic processes in a discreet environment, and corresponding again to n-dimensional expression of time space defining existence and also the prediction for expected cyber attacksin the noise space. Noises are seen here as useful and necessary for modern information and communication technologies (e.g. in processes of applied cryptography in ICT) and then the so-called useless noises designed for initial (necessary) filtering of this highly aggressive environment and in future expectedly offensive background in cyber war (e.g. the destruction of unmanned means of an electromagnetic pulse, or for destruction of new safety barriers created on principles of electrostatic field or on other principles of modern physics, etc.). The key to these new options is the expression of abstract systems based on the models of microelements of cyber systems and their hierarchical concept in structure of n-dimensional system in given cyberspace. The aim of this article is to highlight the possible systemic expression of cyberspace of abstract system and possible identification in time-spatial expression of real environment (on microelements of cyber systems and their surroundings with noise characteristics and time dimension in dynamic of microelements’ own time and externaltime defined by real environment). The article was based on a partial task of faculty specific research.

Possibilities of identifying cyber attack in noisy space of n-dimensional abstract system

Science.gov (United States)

Jašek, Roman; Dvořák, Jiří; Janková, Martina; Sedláček, Michal

2016-06-01

This article briefly mentions some selected options of current concept for identifying cyber attacks from the perspective of the new cyberspace of real system. In the cyberspace, there is defined n-dimensional abstract system containing elements of the spatial arrangement of partial system elements such as micro-environment of cyber systems surrounded by other suitably arranged corresponding noise space. This space is also gradually supplemented by a new image of dynamic processes in a discreet environment, and corresponding again to n-dimensional expression of time space defining existence and also the prediction for expected cyber attacksin the noise space. Noises are seen here as useful and necessary for modern information and communication technologies (e.g. in processes of applied cryptography in ICT) and then the so-called useless noises designed for initial (necessary) filtering of this highly aggressive environment and in future expectedly offensive background in cyber war (e.g. the destruction of unmanned means of an electromagnetic pulse, or for destruction of new safety barriers created on principles of electrostatic field or on other principles of modern physics, etc.). The key to these new options is the expression of abstract systems based on the models of microelements of cyber systems and their hierarchical concept in structure of n-dimensional system in given cyberspace. The aim of this article is to highlight the possible systemic expression of cyberspace of abstract system and possible identification in time-spatial expression of real environment (on microelements of cyber systems and their surroundings with noise characteristics and time dimension in dynamic of microelements' own time and externaltime defined by real environment). The article was based on a partial task of faculty specific research.

Adaptive observer for the joint estimation of parameters and input for a coupled wave PDE and infinite dimensional ODE system

KAUST Repository

Belkhatir, Zehor; Mechhoud, Sarra; Laleg-Kirati, Taous-Meriem

2016-01-01

This paper deals with joint parameters and input estimation for coupled PDE-ODE system. The system consists of a damped wave equation and an infinite dimensional ODE. This model describes the spatiotemporal hemodynamic response in the brain

Multi-dimensional analysis of high resolution γ-ray data

International Nuclear Information System (INIS)

Flibotte, S.; Huttmeier, U.J.; France, G. de; Haas, B.; Romain, P.; Theisen, Ch.; Vivien, J.P.; Zen, J.; Bednarczyk, P.

1992-01-01

High resolution γ-ray multi-detectors capable of measuring high-fold coincidences with a large efficiency are presently under construction (EUROGAM, GASP, GAMMASPHERE). The future experimental progress in our understanding of nuclear structure at high spin critically depends on our ability to analyze the data in a multi-dimensional space and to resolve small photopeaks of interest from the generally large background. Development of programs to process such high-fold events is still in its infancy and only the 3-fold case has been treated so far. As a contribution to the software development associated with the EUROGAM spectrometer, we have written and tested the performances of computer codes designed to select multi-dimensional gates from 3-, 4- and 5-fold coincidence databases. The tests were performed on events generated with a Monte Carlo simulation and also on experimental data (triples) recorded with the 8π spectrometer and with a preliminary version of the EUROGAM array. (author). 7 refs., 3 tabs., 1 fig

Multi-dimensional analysis of high resolution {gamma}-ray data

Energy Technology Data Exchange (ETDEWEB)

Flibotte, S; Huttmeier, U J; France, G de; Haas, B; Romain, P; Theisen, Ch; Vivien, J P; Zen, J [Centre National de la Recherche Scientifique (CNRS), 67 - Strasbourg (France); Bednarczyk, P [Institute of Nuclear Physics, Cracow (Poland)

1992-08-01

High resolution {gamma}-ray multi-detectors capable of measuring high-fold coincidences with a large efficiency are presently under construction (EUROGAM, GASP, GAMMASPHERE). The future experimental progress in our understanding of nuclear structure at high spin critically depends on our ability to analyze the data in a multi-dimensional space and to resolve small photopeaks of interest from the generally large background. Development of programs to process such high-fold events is still in its infancy and only the 3-fold case has been treated so far. As a contribution to the software development associated with the EUROGAM spectrometer, we have written and tested the performances of computer codes designed to select multi-dimensional gates from 3-, 4- and 5-fold coincidence databases. The tests were performed on events generated with a Monte Carlo simulation and also on experimental data (triples) recorded with the 8{pi} spectrometer and with a preliminary version of the EUROGAM array. (author). 7 refs., 3 tabs., 1 fig.

A covariant form of the Maxwell's equations in four-dimensional spaces with an arbitrary signature

International Nuclear Information System (INIS)

Lukac, I.

1991-01-01

The concept of duality in the four-dimensional spaces with the arbitrary constant metric is strictly mathematically formulated. A covariant model for covariant and contravariant bivectors in this space based on three four-dimensional vectors is proposed. 14 refs

High-dimensional atom localization via spontaneously generated coherence in a microwave-driven atomic system.

Science.gov (United States)

Wang, Zhiping; Chen, Jinyu; Yu, Benli

2017-02-20

We investigate the two-dimensional (2D) and three-dimensional (3D) atom localization behaviors via spontaneously generated coherence in a microwave-driven four-level atomic system. Owing to the space-dependent atom-field interaction, it is found that the detecting probability and precision of 2D and 3D atom localization behaviors can be significantly improved via adjusting the system parameters, the phase, amplitude, and initial population distribution. Interestingly, the atom can be localized in volumes that are substantially smaller than a cubic optical wavelength. Our scheme opens a promising way to achieve high-precision and high-efficiency atom localization, which provides some potential applications in high-dimensional atom nanolithography.

Spinorial characterizations of surfaces into 3-dimensional psuedo-Riemannian space forms

OpenAIRE

Lawn , Marie-Amélie; Roth , Julien

2011-01-01

9 pages; We give a spinorial characterization of isometrically immersed surfaces of arbitrary signature into 3-dimensional pseudo-Riemannian space forms. For Lorentzian surfaces, this generalizes a recent work of the first author in $\\mathbb{R}^{2,1}$ to other Lorentzian space forms. We also characterize immersions of Riemannian surfaces in these spaces. From this we can deduce analogous results for timelike immersions of Lorentzian surfaces in space forms of corresponding signature, as well ...

Three-dimensional studies on resorption spaces and developing osteons.

Science.gov (United States)

Tappen, N C

1977-07-01

Resorption spaces and their continuations as developing osteons were traced in serial cross sections from decalcified long bones of dogs, baboons and a man, and from a human rib. Processes of formation of osteons and transverse (Volkmann's) canals can be inferred from three-dimensional studies. Deposits of new osseous tissue begin to line the walls of the spaces soon after termination of resorption. The first deposits are osteoid, usually stained very darkly by the silver nitrate procedure utilized, but a lighter osteoid zone adjacent to the canals occurs frequently. Osteoid linings continue to be produced as lamellar bone forms around them; the large canals of immature osteons usually narrow very gradually. Frequently they terminate both proximally and distally as resorption spaces, indicating that osteons often advance in opposite directions as they develop. Osteoclasts of resorption spaces tunnel preferentially into highly mineralized bone, and usually do not use previously existing canals as templates for their advance. Osteons evidently originate by localized resorption of one side of the wall of an existing vascular channel in bone, with subsequent orientation of the resorption front along the axis of the shaft. Advancing resorption spaces also apparently stimulate the formation of numerous additional transverse canal connections to neighboring longitudinal canals. Serial tracing and silver nitrate differential staining combine to reveal many of the processes of bone remodeling at work, and facilitate quantitative treatment of the data. Further uses in studies of bone tissue and associated cells are recommended.

Asymptotic analysis of fundamental solutions of Dirac operators on even dimensional Euclidean spaces

International Nuclear Information System (INIS)

Arai, A.

1985-01-01

We analyze the short distance asymptotic behavior of some quantities formed out of fundamental solutions of Dirac operators on even dimensional Euclidean spaces with finite dimensional matrix-valued potentials. (orig.)

Non-Euclidean geometry and curvature two-dimensional spaces, volume 3

CERN Document Server

Cannon, James W

2017-01-01

This is the final volume of a three volume collection devoted to the geometry, topology, and curvature of 2-dimensional spaces. The collection provides a guided tour through a wide range of topics by one of the twentieth century's masters of geometric topology. The books are accessible to college and graduate students and provide perspective and insight to mathematicians at all levels who are interested in geometry and topology. Einstein showed how to interpret gravity as the dynamic response to the curvature of space-time. Bill Thurston showed us that non-Euclidean geometries and curvature are essential to the understanding of low-dimensional spaces. This third and final volume aims to give the reader a firm intuitive understanding of these concepts in dimension 2. The volume first demonstrates a number of the most important properties of non-Euclidean geometry by means of simple infinite graphs that approximate that geometry. This is followed by a long chapter taken from lectures the author gave at MSRI, wh...

Three-dimensional space charge distribution measurement in electron beam irradiated PMMA

International Nuclear Information System (INIS)

Imaizumi, Yoichi; Suzuki, Ken; Tanaka, Yasuhiro; Takada, Tatsuo

1996-01-01

The localized space charge distribution in electron beam irradiated PMMA was investigated using pulsed electroacoustic method. Using a conventional space charge measurement system, the distribution only in the depth direction (Z) can be measured assuming the charges distributed uniformly in the horizontal (X-Y) plane. However, it is difficult to measure the distribution of space charge accumulated in small area. Therefore, we have developed the new system to measure the three-dimensional space charge distribution using pulsed electroacoustic method. The system has a small electrode with a diameter of 1mm and a motor-drive X-Y stage to move the sample. Using the data measured at many points, the three-dimensional distribution were obtained. To estimate the system performance, the electron beam irradiated PMMA was used. The electron beam was irradiated from transmission electron microscope (TEM). The depth of injected electron was controlled using the various metal masks. The measurement results were compared with theoretically calculated values of electron range. (author)

Summary of astronaut inputs on automation and robotics for Space Station Freedom

Science.gov (United States)

Weeks, David J.

1990-01-01

Astronauts and payload specialists present specific recommendations in the form of an overview that relate to the use of automation and robotics on the Space Station Freedom. The inputs are based on on-orbit operations experience, time requirements for crews, and similar crew-specific knowledge that address the impacts of automation and robotics on productivity. Interview techniques and specific questionnaire results are listed, and the majority of the responses indicate that incorporating automation and robotics to some extent and with human backup can improve productivity. Specific support is found for the use of advanced automation and EVA robotics on the Space Station Freedom and for the use of advanced automation on ground-based stations. Ground-based control of in-flight robotics is required, and Space Station activities and crew tasks should be analyzed to assess the systems engineering approach for incorporating automation and robotics.

Self-dual phase space for (3 +1 )-dimensional lattice Yang-Mills theory

Science.gov (United States)

Riello, Aldo

2018-01-01

I propose a self-dual deformation of the classical phase space of lattice Yang-Mills theory, in which both the electric and magnetic fluxes take value in the compact gauge Lie group. A local construction of the deformed phase space requires the machinery of "quasi-Hamiltonian spaces" by Alekseev et al., which is reviewed here. The results is a full-fledged finite-dimensional and gauge-invariant phase space, the self-duality properties of which are largely enhanced in (3 +1 ) spacetime dimensions. This enhancement is due to a correspondence with the moduli space of an auxiliary noncommutative flat connection living on a Riemann surface defined from the lattice itself, which in turn equips the duality between electric and magnetic fluxes with a neat geometrical interpretation in terms of a Heegaard splitting of the space manifold. Finally, I discuss the consequences of the proposed deformation on the quantization of the phase space, its quantum gravitational interpretation, as well as its relevance for the construction of (3 +1 )-dimensional topological field theories with defects.

Four dimensional magnetic resonance imaging with retrospective k-space reordering: A feasibility study

International Nuclear Information System (INIS)

Liu, Yilin; Yin, Fang-Fang; Cai, Jing; Chen, Nan-kuei; Chu, Mei-Lan

2015-01-01

Purpose: Current four dimensional magnetic resonance imaging (4D-MRI) techniques lack sufficient temporal/spatial resolution and consistent tumor contrast. To overcome these limitations, this study presents the development and initial evaluation of a new strategy for 4D-MRI which is based on retrospective k-space reordering. Methods: We simulated a k-space reordered 4D-MRI on a 4D digital extended cardiac-torso (XCAT) human phantom. A 2D echo planar imaging MRI sequence [frame rate (F) = 0.448 Hz; image resolution (R) = 256 × 256; number of k-space segments (N KS ) = 4] with sequential image acquisition mode was assumed for the simulation. Image quality of the simulated “4D-MRI” acquired from the XCAT phantom was qualitatively evaluated, and tumor motion trajectories were compared to input signals. In particular, mean absolute amplitude differences (D) and cross correlation coefficients (CC) were calculated. Furthermore, to evaluate the data sufficient condition for the new 4D-MRI technique, a comprehensive simulation study was performed using 30 cancer patients’ respiratory profiles to study the relationships between data completeness (C p ) and a number of impacting factors: the number of repeated scans (N R ), number of slices (N S ), number of respiratory phase bins (N P ), N KS , F, R, and initial respiratory phase at image acquisition (P 0 ). As a proof-of-concept, we implemented the proposed k-space reordering 4D-MRI technique on a T2-weighted fast spin echo MR sequence and tested it on a healthy volunteer. Results: The simulated 4D-MRI acquired from the XCAT phantom matched closely to the original XCAT images. Tumor motion trajectories measured from the simulated 4D-MRI matched well with input signals (D = 0.83 and 0.83 mm, and CC = 0.998 and 0.992 in superior–inferior and anterior–posterior directions, respectively). The relationship between C p and N R was found best represented by an exponential function (C P =100(1−e −0.18N R ), when N S

A qualitative numerical study of high dimensional dynamical systems

Science.gov (United States)

Albers, David James

Since Poincare, the father of modern mathematical dynamical systems, much effort has been exerted to achieve a qualitative understanding of the physical world via a qualitative understanding of the functions we use to model the physical world. In this thesis, we construct a numerical framework suitable for a qualitative, statistical study of dynamical systems using the space of artificial neural networks. We analyze the dynamics along intervals in parameter space, separating the set of neural networks into roughly four regions: the fixed point to the first bifurcation; the route to chaos; the chaotic region; and a transition region between chaos and finite-state neural networks. The study is primarily with respect to high-dimensional dynamical systems. We make the following general conclusions as the dimension of the dynamical system is increased: the probability of the first bifurcation being of type Neimark-Sacker is greater than ninety-percent; the most probable route to chaos is via a cascade of bifurcations of high-period periodic orbits, quasi-periodic orbits, and 2-tori; there exists an interval of parameter space such that hyperbolicity is violated on a countable, Lebesgue measure 0, "increasingly dense" subset; chaos is much more likely to persist with respect to parameter perturbation in the chaotic region of parameter space as the dimension is increased; moreover, as the number of positive Lyapunov exponents is increased, the likelihood that any significant portion of these positive exponents can be perturbed away decreases with increasing dimension. The maximum Kaplan-Yorke dimension and the maximum number of positive Lyapunov exponents increases linearly with dimension. The probability of a dynamical system being chaotic increases exponentially with dimension. The results with respect to the first bifurcation and the route to chaos comment on previous results of Newhouse, Ruelle, Takens, Broer, Chenciner, and Iooss. Moreover, results regarding the high-dimensional

Numerical resolution of N-dimensional Fokker-Plank stochastic equations

International Nuclear Information System (INIS)

Garcia-Olivares, A.; Muoz, A.

1992-01-01

This document describes the use of a library of programs able to solve stochastic Fokker-Planck equations in a N-dimensional space. the input data are essentially: (i) the initial distribution of the stochastic variable, (ii) the drift and fluctuation coefficients as a function of the state (which can be obtained from the transition probabilities between neighboring states) and (iii) some parameters controlling the run. A last version of the library accepts sources and sinks defined in the states space. The output is the temporal evolution of the probability distribution in the space defined by a N-dimensional grid. Some applications and readings in Synergetics, Self-Organization, transport phenomena, Ecology and other fields are suggested. If the probability distribution is interpreted as a distribution of particles then the codes can be used to solve the N-dimensional problem of advection-diffusion. (author) 21 fig. 16 ref

Numerical Resolution of N-dimensional Fokker-Planck stochastic equations

International Nuclear Information System (INIS)

Garcia-Olivares, R. A.; Munoz Roldan, A.

1992-01-01

This document describes the use of a library of programs able to solve stochastic Fokker-Planck equations in a N-dimensional space. The input data are essentially: (i) the initial distribution of the stochastic variable, (ii) the drift and fluctuation coefficients as a function of the state (which can be obtained from the transition probabilities between neighboring states) and (iii) some parameters controlling the run. A last version of the library accepts sources and sinks defined in the states space. The output is the temporal evolution of the probability distribution in the space defined by a N-dimensional grid. Some applications and readings in Synergetic, Self-Organization, transport phenomena, Ecology and other fields are suggested. If the probability distribution is interpreted as a distribution of particles then the codes can be used to solve the N-dimensional problem of advection-diffusion. (Author) 16 refs

Geodesics on a hot plate: an example of a two-dimensional curved space

International Nuclear Information System (INIS)

Erkal, Cahit

2006-01-01

The equation of the geodesics on a hot plate with a radially symmetric temperature profile is derived using the Lagrangian approach. Numerical solutions are presented with an eye towards (a) teaching two-dimensional curved space and the metric used to determine the geodesics (b) revealing some characteristics of two-dimensional curved spacetime and (c) providing insight into understanding the curved space which emerges in teaching relativity. In order to provide a deeper insight, we also present the analytical solutions and show that they represent circles whose characteristics depend on curvature of the space, conductivity and the coefficient of thermal expansion

Geodesics on a hot plate: an example of a two-dimensional curved space

Energy Technology Data Exchange (ETDEWEB)

Erkal, Cahit [Department of Geology, Geography, and Physics, University of Tennessee, Martin, TN 38238 (United States)

2006-07-01

The equation of the geodesics on a hot plate with a radially symmetric temperature profile is derived using the Lagrangian approach. Numerical solutions are presented with an eye towards (a) teaching two-dimensional curved space and the metric used to determine the geodesics (b) revealing some characteristics of two-dimensional curved spacetime and (c) providing insight into understanding the curved space which emerges in teaching relativity. In order to provide a deeper insight, we also present the analytical solutions and show that they represent circles whose characteristics depend on curvature of the space, conductivity and the coefficient of thermal expansion.

Absolute continuity of autophage measures on finite-dimensional vector spaces

Energy Technology Data Exchange (ETDEWEB)

Raja, C R.E. [Stat-Math Unit, Indian Statistical Institute, Bangalore (India); [Abdus Salam International Centre for Theoretical Physics, Trieste (Italy)]. E-mail: creraja@isibang.ac.in

2002-06-01

We consider a class of measures called autophage which was introduced and studied by Szekely for measures on the real line. We show that the autophage measures on finite-dimensional vector spaces over real or Q{sub p} are infinitely divisible without idempotent factors and are absolutely continuous with bounded continuous density. We also show that certain semistable measures on such vector spaces are absolutely continuous. (author)

Intertwined Hamiltonians in two-dimensional curved spaces

International Nuclear Information System (INIS)

Aghababaei Samani, Keivan; Zarei, Mina

2005-01-01

The problem of intertwined Hamiltonians in two-dimensional curved spaces is investigated. Explicit results are obtained for Euclidean plane, Minkowski plane, Poincare half plane (AdS 2 ), de Sitter plane (dS 2 ), sphere, and torus. It is shown that the intertwining operator is related to the Killing vector fields and the isometry group of corresponding space. It is shown that the intertwined potentials are closely connected to the integral curves of the Killing vector fields. Two problems are considered as applications of the formalism presented in the paper. The first one is the problem of Hamiltonians with equispaced energy levels and the second one is the problem of Hamiltonians whose spectrum is like the spectrum of a free particle

Numerical relativity for D dimensional space-times: Head-on collisions of black holes and gravitational wave extraction

International Nuclear Information System (INIS)

Witek, Helvi; Nerozzi, Andrea; Zilhao, Miguel; Herdeiro, Carlos; Gualtieri, Leonardo; Cardoso, Vitor; Sperhake, Ulrich

2010-01-01

Higher dimensional black holes play an exciting role in fundamental physics, such as high energy physics. In this paper, we use the formalism and numerical code reported in [1] to study the head-on collision of two black holes. For this purpose we provide a detailed treatment of gravitational wave extraction in generic D dimensional space-times, which uses the Kodama-Ishibashi formalism. For the first time, we present the results of numerical simulations of the head-on collision in five space-time dimensions, together with the relevant physical quantities. We show that the total radiated energy, when two black holes collide from rest at infinity, is approximately (0.089±0.006)% of the center of mass energy, slightly larger than the 0.055% obtained in the four-dimensional case, and that the ringdown signal at late time is in very good agreement with perturbative calculations.

Introducing the Dimensional Continuous Space-Time Theory

International Nuclear Information System (INIS)

Martini, Luiz Cesar

2013-01-01

This article is an introduction to a new theory. The name of the theory is justified by the dimensional description of the continuous space-time of the matter, energy and empty space, that gathers all the real things that exists in the universe. The theory presents itself as the consolidation of the classical, quantum and relativity theories. A basic equation that describes the formation of the Universe, relating time, space, matter, energy and movement, is deduced. The four fundamentals physics constants, light speed in empty space, gravitational constant, Boltzmann's constant and Planck's constant and also the fundamentals particles mass, the electrical charges, the energies, the empty space and time are also obtained from this basic equation. This theory provides a new vision of the Big-Bang and how the galaxies, stars, black holes and planets were formed. Based on it, is possible to have a perfect comprehension of the duality between wave-particle, which is an intrinsic characteristic of the matter and energy. It will be possible to comprehend the formation of orbitals and get the equationing of atomics orbits. It presents a singular comprehension of the mass relativity, length and time. It is demonstrated that the continuous space-time is tridimensional, inelastic and temporally instantaneous, eliminating the possibility of spatial fold, slot space, worm hole, time travels and parallel universes. It is shown that many concepts, like dark matter and strong forces, that hypothetically keep the cohesion of the atomics nucleons, are without sense.

Three-dimensional reciprocal space x-ray coherent scattering tomography of two-dimensional object.

Science.gov (United States)

Zhu, Zheyuan; Pang, Shuo

2018-04-01

X-ray coherent scattering tomography is a powerful tool in discriminating biological tissues and bio-compatible materials. Conventional x-ray scattering tomography framework can only resolve isotropic scattering profile under the assumption that the material is amorphous or in powder form, which is not true especially for biological samples with orientation-dependent structure. Previous tomography schemes based on x-ray coherent scattering failed to preserve the scattering pattern from samples with preferred orientations, or required elaborated data acquisition scheme, which could limit its application in practical settings. Here, we demonstrate a simple imaging modality to preserve the anisotropic scattering signal in three-dimensional reciprocal (momentum transfer) space of a two-dimensional sample layer. By incorporating detector movement along the direction of x-ray beam, combined with a tomographic data acquisition scheme, we match the five dimensions of the measurements with the five dimensions (three in momentum transfer domain, and two in spatial domain) of the object. We employed a collimated pencil beam of a table-top copper-anode x-ray tube, along with a panel detector to investigate the feasibility of our method. We have demonstrated x-ray coherent scattering tomographic imaging at a spatial resolution ~2 mm and momentum transfer resolution 0.01 Å -1 for the rotation-invariant scattering direction. For any arbitrary, non-rotation-invariant direction, the same spatial and momentum transfer resolution can be achieved based on the spatial information from the rotation-invariant direction. The reconstructed scattering profile of each pixel from the experiment is consistent with the x-ray diffraction profile of each material. The three-dimensional scattering pattern recovered from the measurement reveals the partially ordered molecular structure of Teflon wrap in our sample. We extend the applicability of conventional x-ray coherent scattering tomography to

High-dimensional quantum key distribution based on multicore fiber using silicon photonic integrated circuits

DEFF Research Database (Denmark)

Ding, Yunhong; Bacco, Davide; Dalgaard, Kjeld

2017-01-01

is intrinsically limited to 1 bit/photon. Here we propose and experimentally demonstrate, for the first time, a high-dimensional quantum key distribution protocol based on space division multiplexing in multicore fiber using silicon photonic integrated lightwave circuits. We successfully realized three mutually......-dimensional quantum states, and enables breaking the information efficiency limit of traditional quantum key distribution protocols. In addition, the silicon photonic circuits used in our work integrate variable optical attenuators, highly efficient multicore fiber couplers, and Mach-Zehnder interferometers, enabling...

Numerical relativity for D dimensional axially symmetric space-times: Formalism and code tests

International Nuclear Information System (INIS)

Zilhao, Miguel; Herdeiro, Carlos; Witek, Helvi; Nerozzi, Andrea; Sperhake, Ulrich; Cardoso, Vitor; Gualtieri, Leonardo

2010-01-01

The numerical evolution of Einstein's field equations in a generic background has the potential to answer a variety of important questions in physics: from applications to the gauge-gravity duality, to modeling black hole production in TeV gravity scenarios, to analysis of the stability of exact solutions, and to tests of cosmic censorship. In order to investigate these questions, we extend numerical relativity to more general space-times than those investigated hitherto, by developing a framework to study the numerical evolution of D dimensional vacuum space-times with an SO(D-2) isometry group for D≥5, or SO(D-3) for D≥6. Performing a dimensional reduction on a (D-4) sphere, the D dimensional vacuum Einstein equations are rewritten as a 3+1 dimensional system with source terms, and presented in the Baumgarte, Shapiro, Shibata, and Nakamura formulation. This allows the use of existing 3+1 dimensional numerical codes with small adaptations. Brill-Lindquist initial data are constructed in D dimensions and a procedure to match them to our 3+1 dimensional evolution equations is given. We have implemented our framework by adapting the Lean code and perform a variety of simulations of nonspinning black hole space-times. Specifically, we present a modified moving puncture gauge, which facilitates long-term stable simulations in D=5. We further demonstrate the internal consistency of the code by studying convergence and comparing numerical versus analytic results in the case of geodesic slicing for D=5, 6.

Nonrenormalizable quantum field models in four-dimensional space-time

International Nuclear Information System (INIS)

Raczka, R.

1978-01-01

The construction of no-cutoff Euclidean Green's functions for nonrenormalizable interactions L/sub I/(phi) = lambda∫ddelta (epsilon): expepsilonphi: in four-dimensional space-time is carried out. It is shown that all axioms for the generating functional of the Euclidean Green's function are satisfied except perhaps SO(4) invariance

The dimensionality of stellar chemical space using spectra from the Apache Point Observatory Galactic Evolution Experiment

Science.gov (United States)

Price-Jones, Natalie; Bovy, Jo

2018-03-01

Chemical tagging of stars based on their similar compositions can offer new insights about the star formation and dynamical history of the Milky Way. We investigate the feasibility of identifying groups of stars in chemical space by forgoing the use of model derived abundances in favour of direct analysis of spectra. This facilitates the propagation of measurement uncertainties and does not pre-suppose knowledge of which elements are important for distinguishing stars in chemical space. We use ˜16 000 red giant and red clump H-band spectra from the Apache Point Observatory Galactic Evolution Experiment (APOGEE) and perform polynomial fits to remove trends not due to abundance-ratio variations. Using expectation maximized principal component analysis, we find principal components with high signal in the wavelength regions most important for distinguishing between stars. Different subsamples of red giant and red clump stars are all consistent with needing about 10 principal components to accurately model the spectra above the level of the measurement uncertainties. The dimensionality of stellar chemical space that can be investigated in the H band is therefore ≲10. For APOGEE observations with typical signal-to-noise ratios of 100, the number of chemical space cells within which stars cannot be distinguished is approximately 1010±2 × (5 ± 2)n - 10 with n the number of principal components. This high dimensionality and the fine-grained sampling of chemical space are a promising first step towards chemical tagging based on spectra alone.

FLUTAN input specifications

International Nuclear Information System (INIS)

Borgwaldt, H.; Baumann, W.; Willerding, G.

1991-05-01

FLUTAN is a highly vectorized computer code for 3-D fluiddynamic and thermal-hydraulic analyses in cartesian and cylinder coordinates. It is related to the family of COMMIX codes originally developed at Argonne National Laboratory, USA. To a large extent, FLUTAN relies on basic concepts and structures imported from COMMIX-1B and COMMIX-2 which were made available to KfK in the frame of cooperation contracts in the fast reactor safety field. While on the one hand not all features of the original COMMIX versions have been implemented in FLUTAN, the code on the other hand includes some essential innovative options like CRESOR solution algorithm, general 3-dimensional rebalacing scheme for solving the pressure equation, and LECUSSO-QUICK-FRAM techniques suitable for reducing 'numerical diffusion' in both the enthalphy and momentum equations. This report provides users with detailed input instructions, presents formulations of the various model options, and explains by means of comprehensive sample input, how to use the code. (orig.) [de

Dimensionality analysis of multiparticle production at high energies

International Nuclear Information System (INIS)

Chilingaryan, A.A.

1989-01-01

An algorithm of analysis of multiparticle final states is offered. By the Renyi dimensionalities, which were calculated according to experimental data, though it were hadron distribution over the rapidity intervals or particle distribution in an N-dimensional momentum space, we can judge about the degree of correlation of particles, separate the momentum space projections and areas where the probability measure singularities are observed. The method is tested in a series of calculations with samples of fractal object points and with samples obtained by means of different generators of pseudo- and quasi-random numbers. 27 refs.; 11 figs

Geometry of quantum dynamics in infinite-dimensional Hilbert space

Science.gov (United States)

Grabowski, Janusz; Kuś, Marek; Marmo, Giuseppe; Shulman, Tatiana

2018-04-01

We develop a geometric approach to quantum mechanics based on the concept of the Tulczyjew triple. Our approach is genuinely infinite-dimensional, i.e. we do not restrict considerations to finite-dimensional Hilbert spaces, contrary to many other works on the geometry of quantum mechanics, and include a Lagrangian formalism in which self-adjoint (Schrödinger) operators are obtained as Lagrangian submanifolds associated with the Lagrangian. As a byproduct we also obtain results concerning coadjoint orbits of the unitary group in infinite dimensions, embedding of pure states in the unitary group, and self-adjoint extensions of symmetric relations.

Influence of cusps and intersections on the Wilson loop in ν-dimensional space

International Nuclear Information System (INIS)

Bezerra, V.B.

1984-01-01

A discussion is given about the influence of cusps and intersections on the calculation of the Wilson loop in ν-dimensional space. In particular, for the two-dimensional case, it is shown that there are no divergences. (Author) [pt

Dimensional Analysis with space discrimination applied to Fickian difussion phenomena

International Nuclear Information System (INIS)

Diaz Sanchidrian, C.; Castans, M.

1989-01-01

Dimensional Analysis with space discrimination is applied to Fickian difussion phenomena in order to transform its partial differen-tial equations into ordinary ones, and also to obtain in a dimensionl-ess fom the Ficks second law. (Author)

Reducing the Complexity of Genetic Fuzzy Classifiers in Highly-Dimensional Classification Problems

Directory of Open Access Journals (Sweden)

DimitrisG. Stavrakoudis

2012-04-01

Full Text Available This paper introduces the Fast Iterative Rule-based Linguistic Classifier (FaIRLiC, a Genetic Fuzzy Rule-Based Classification System (GFRBCS which targets at reducing the structural complexity of the resulting rule base, as well as its learning algorithm's computational requirements, especially when dealing with high-dimensional feature spaces. The proposed methodology follows the principles of the iterative rule learning (IRL approach, whereby a rule extraction algorithm (REA is invoked in an iterative fashion, producing one fuzzy rule at a time. The REA is performed in two successive steps: the first one selects the relevant features of the currently extracted rule, whereas the second one decides the antecedent part of the fuzzy rule, using the previously selected subset of features. The performance of the classifier is finally optimized through a genetic tuning post-processing stage. Comparative results in a hyperspectral remote sensing classification as well as in 12 real-world classification datasets indicate the effectiveness of the proposed methodology in generating high-performing and compact fuzzy rule-based classifiers, even for very high-dimensional feature spaces.

Small high cooling power space cooler

Energy Technology Data Exchange (ETDEWEB)

Nguyen, T. V.; Raab, J.; Durand, D.; Tward, E. [Northrop Grumman Aerospace Systems Redondo Beach, Ca, 90278 (United States)

2014-01-29

The small High Efficiency pulse tube Cooler (HEC) cooler, that has been produced and flown on a number of space infrared instruments, was originally designed to provide cooling of 10 W @ 95 K. It achieved its goal with >50% margin when limited by the 180 W output ac power of its flight electronics. It has also been produced in 2 stage configurations, typically for simultaneously cooling of focal planes to temperatures as low as 35 K and optics at higher temperatures. The need for even higher cooling power in such a low mass cryocooler is motivated by the advent of large focal plane arrays. With the current availability at NGAS of much larger power cryocooler flight electronics, reliable long term operation in space with much larger cooling powers is now possible with the flight proven 4 kg HEC mechanical cooler. Even though the single stage cooler design can be re-qualified for those larger input powers without design change, we redesigned both the linear and coaxial version passive pulse tube cold heads to re-optimize them for high power cooling at temperatures above 130 K while rejecting heat to 300 K. Small changes to the regenerator packing, the re-optimization of the tuned inertance and no change to the compressor resulted in the increased performance at 150 K. The cooler operating at 290 W input power achieves 35 W@ 150 K corresponding to a specific cooling power at 150 K of 8.25 W/W and a very high specific power of 72.5 W/Kg. At these powers the cooler still maintains large stroke, thermal and current margins. In this paper we will present the measured data and the changes to this flight proven cooler that were made to achieve this increased performance.

Explorations on High Dimensional Landscapes: Spin Glasses and Deep Learning

Science.gov (United States)

Sagun, Levent

This thesis deals with understanding the structure of high-dimensional and non-convex energy landscapes. In particular, its focus is on the optimization of two classes of functions: homogeneous polynomials and loss functions that arise in machine learning. In the first part, the notion of complexity of a smooth, real-valued function is studied through its critical points. Existing theoretical results predict that certain random functions that are defined on high dimensional domains have a narrow band of values whose pre-image contains the bulk of its critical points. This section provides empirical evidence for convergence of gradient descent to local minima whose energies are near the predicted threshold justifying the existing asymptotic theory. Moreover, it is empirically shown that a similar phenomenon may hold for deep learning loss functions. Furthermore, there is a comparative analysis of gradient descent and its stochastic version showing that in high dimensional regimes the latter is a mere speedup. The next study focuses on the halting time of an algorithm at a given stopping condition. Given an algorithm, the normalized fluctuations of the halting time follow a distribution that remains unchanged even when the input data is sampled from a new distribution. Two qualitative classes are observed: a Gumbel-like distribution that appears in Google searches, human decision times, and spin glasses and a Gaussian-like distribution that appears in conjugate gradient method, deep learning with MNIST and random input data. Following the universality phenomenon, the Hessian of the loss functions of deep learning is studied. The spectrum is seen to be composed of two parts, the bulk which is concentrated around zero, and the edges which are scattered away from zero. Empirical evidence is presented for the bulk indicating how over-parametrized the system is, and for the edges that depend on the input data. Furthermore, an algorithm is proposed such that it would

Out-of-Sequence Preventative Cell Dispatching for Multicast Input-Queued Space-Memory-Memory Clos-Network

DEFF Research Database (Denmark)

Yu, Hao; Ruepp, Sarah Renée; Berger, Michael Stübert

2011-01-01

This paper proposes two out-of-sequence (OOS) preventative cell dispatching algorithms for the multicast input-queued space-memory-memory (IQ-SMM) Clos-network switch architecture, i.e. the multicast flow-based DSRR (MF-DSRR) and the multicast flow-based round-robin (MFRR). Treating each cell...

An Autonomous Sensor Tasking Approach for Large Scale Space Object Cataloging

Science.gov (United States)

Linares, R.; Furfaro, R.

The field of Space Situational Awareness (SSA) has progressed over the last few decades with new sensors coming online, the development of new approaches for making observations, and new algorithms for processing them. Although there has been success in the development of new approaches, a missing piece is the translation of SSA goals to sensors and resource allocation; otherwise known as the Sensor Management Problem (SMP). This work solves the SMP using an artificial intelligence approach called Deep Reinforcement Learning (DRL). Stable methods for training DRL approaches based on neural networks exist, but most of these approaches are not suitable for high dimensional systems. The Asynchronous Advantage Actor-Critic (A3C) method is a recently developed and effective approach for high dimensional systems, and this work leverages these results and applies this approach to decision making in SSA. The decision space for the SSA problems can be high dimensional, even for tasking of a single telescope. Since the number of SOs in space is relatively high, each sensor will have a large number of possible actions at a given time. Therefore, efficient DRL approaches are required when solving the SMP for SSA. This work develops a A3C based method for DRL applied to SSA sensor tasking. One of the key benefits of DRL approaches is the ability to handle high dimensional data. For example DRL methods have been applied to image processing for the autonomous car application. For example, a 256x256 RGB image has 196608 parameters (256*256*3=196608) which is very high dimensional, and deep learning approaches routinely take images like this as inputs. Therefore, when applied to the whole catalog the DRL approach offers the ability to solve this high dimensional problem. This work has the potential to, for the first time, solve the non-myopic sensor tasking problem for the whole SO catalog (over 22,000 objects) providing a truly revolutionary result.

The new Big Bang Theory according to dimensional continuous space-time theory

International Nuclear Information System (INIS)

Martini, Luiz Cesar

2014-01-01

This New View of the Big Bang Theory results from the Dimensional Continuous Space-Time Theory, for which the introduction was presented in [1]. This theory is based on the concept that the primitive Universe before the Big Bang was constituted only from elementary cells of potential energy disposed side by side. In the primitive Universe there were no particles, charges, movement and the Universe temperature was absolute zero Kelvin. The time was always present, even in the primitive Universe, time is the integral part of the empty space, it is the dynamic energy of space and it is responsible for the movement of matter and energy inside the Universe. The empty space is totally stationary; the primitive Universe was infinite and totally occupied by elementary cells of potential energy. In its event, the Big Bang started a production of matter, charges, energy liberation, dynamic movement, temperature increase and the conformation of galaxies respecting a specific formation law. This article presents the theoretical formation of the Galaxies starting from a basic equation of the Dimensional Continuous Space-time Theory.

The New Big Bang Theory according to Dimensional Continuous Space-Time Theory

Science.gov (United States)

Martini, Luiz Cesar

2014-04-01

This New View of the Big Bang Theory results from the Dimensional Continuous Space-Time Theory, for which the introduction was presented in [1]. This theory is based on the concept that the primitive Universe before the Big Bang was constituted only from elementary cells of potential energy disposed side by side. In the primitive Universe there were no particles, charges, movement and the Universe temperature was absolute zero Kelvin. The time was always present, even in the primitive Universe, time is the integral part of the empty space, it is the dynamic energy of space and it is responsible for the movement of matter and energy inside the Universe. The empty space is totally stationary; the primitive Universe was infinite and totally occupied by elementary cells of potential energy. In its event, the Big Bang started a production of matter, charges, energy liberation, dynamic movement, temperature increase and the conformation of galaxies respecting a specific formation law. This article presents the theoretical formation of the Galaxies starting from a basic equation of the Dimensional Continuous Space-time Theory.

Can We Train Machine Learning Methods to Outperform the High-dimensional Propensity Score Algorithm?

Science.gov (United States)

Karim, Mohammad Ehsanul; Pang, Menglan; Platt, Robert W

2018-03-01

The use of retrospective health care claims datasets is frequently criticized for the lack of complete information on potential confounders. Utilizing patient's health status-related information from claims datasets as surrogates or proxies for mismeasured and unobserved confounders, the high-dimensional propensity score algorithm enables us to reduce bias. Using a previously published cohort study of postmyocardial infarction statin use (1998-2012), we compare the performance of the algorithm with a number of popular machine learning approaches for confounder selection in high-dimensional covariate spaces: random forest, least absolute shrinkage and selection operator, and elastic net. Our results suggest that, when the data analysis is done with epidemiologic principles in mind, machine learning methods perform as well as the high-dimensional propensity score algorithm. Using a plasmode framework that mimicked the empirical data, we also showed that a hybrid of machine learning and high-dimensional propensity score algorithms generally perform slightly better than both in terms of mean squared error, when a bias-based analysis is used.

On construction of two-dimensional Riemannian manifolds embedded into enveloping Euclidean (pseudo-Euclidean) space

International Nuclear Information System (INIS)

Saveliev, M.V.

1983-01-01

In the framework of the algebraic approach a construction of exactly integrable two-dimensional Riemannian manifolds embedded into enveloping Euclidean (pseudo-Euclidean) space Rsub(N) of an arbitrary dimension is presented. The construction is based on a reformulation of the Gauss, Peterson-Codazzi and Ricci equations in the form of a Lax-type representation in two-dimensional space. Here the Lax pair operators take the values in algebra SO(N)

Modeling high dimensional multichannel brain signals

KAUST Repository

Hu, Lechuan

2017-03-27

In this paper, our goal is to model functional and effective (directional) connectivity in network of multichannel brain physiological signals (e.g., electroencephalograms, local field potentials). The primary challenges here are twofold: first, there are major statistical and computational difficulties for modeling and analyzing high dimensional multichannel brain signals; second, there is no set of universally-agreed measures for characterizing connectivity. To model multichannel brain signals, our approach is to fit a vector autoregressive (VAR) model with sufficiently high order so that complex lead-lag temporal dynamics between the channels can be accurately characterized. However, such a model contains a large number of parameters. Thus, we will estimate the high dimensional VAR parameter space by our proposed hybrid LASSLE method (LASSO+LSE) which is imposes regularization on the first step (to control for sparsity) and constrained least squares estimation on the second step (to improve bias and mean-squared error of the estimator). Then to characterize connectivity between channels in a brain network, we will use various measures but put an emphasis on partial directed coherence (PDC) in order to capture directional connectivity between channels. PDC is a directed frequency-specific measure that explains the extent to which the present oscillatory activity in a sender channel influences the future oscillatory activity in a specific receiver channel relative all possible receivers in the network. Using the proposed modeling approach, we have achieved some insights on learning in a rat engaged in a non-spatial memory task.

Modeling high dimensional multichannel brain signals

KAUST Repository

Hu, Lechuan; Fortin, Norbert; Ombao, Hernando

2017-01-01

In this paper, our goal is to model functional and effective (directional) connectivity in network of multichannel brain physiological signals (e.g., electroencephalograms, local field potentials). The primary challenges here are twofold: first, there are major statistical and computational difficulties for modeling and analyzing high dimensional multichannel brain signals; second, there is no set of universally-agreed measures for characterizing connectivity. To model multichannel brain signals, our approach is to fit a vector autoregressive (VAR) model with sufficiently high order so that complex lead-lag temporal dynamics between the channels can be accurately characterized. However, such a model contains a large number of parameters. Thus, we will estimate the high dimensional VAR parameter space by our proposed hybrid LASSLE method (LASSO+LSE) which is imposes regularization on the first step (to control for sparsity) and constrained least squares estimation on the second step (to improve bias and mean-squared error of the estimator). Then to characterize connectivity between channels in a brain network, we will use various measures but put an emphasis on partial directed coherence (PDC) in order to capture directional connectivity between channels. PDC is a directed frequency-specific measure that explains the extent to which the present oscillatory activity in a sender channel influences the future oscillatory activity in a specific receiver channel relative all possible receivers in the network. Using the proposed modeling approach, we have achieved some insights on learning in a rat engaged in a non-spatial memory task.

Time-dependent gravitating solitons in five dimensional warped space-times

CERN Document Server

Giovannini, Massimo

2007-01-01

Time-dependent soliton solutions are explicitly derived in a five-dimensional theory endowed with one (warped) extra-dimension. Some of the obtained geometries, everywhere well defined and technically regular, smoothly interpolate between two five-dimensional anti-de Sitter space-times for fixed value of the conformal time coordinate. Time dependent solutions containing both topological and non-topological sectors are also obtained. Supplementary degrees of freedom can be also included and, in this case, the resulting multi-soliton solutions may describe time-dependent kink-antikink systems.

The additive hazards model with high-dimensional regressors

DEFF Research Database (Denmark)

Martinussen, Torben; Scheike, Thomas

2009-01-01

This paper considers estimation and prediction in the Aalen additive hazards model in the case where the covariate vector is high-dimensional such as gene expression measurements. Some form of dimension reduction of the covariate space is needed to obtain useful statistical analyses. We study...... model. A standard PLS algorithm can also be constructed, but it turns out that the resulting predictor can only be related to the original covariates via time-dependent coefficients. The methods are applied to a breast cancer data set with gene expression recordings and to the well known primary biliary...

A study on the multi-dimensional spectral analysis for response of a piping model with two-seismic inputs

International Nuclear Information System (INIS)

Suzuki, K.; Sato, H.

1975-01-01

The power and the cross power spectrum analysis by which the vibration characteristic of structures, such as natural frequency, mode of vibration and damping ratio, can be identified would be effective for the confirmation of the characteristics after the construction is completed by using the response for small earthquakes or the micro-tremor under the operating condition. This method of analysis previously utilized only from the view point of systems with single input so far, is extensively applied for the analysis of a medium scale model of a piping system subjected to two seismic inputs. The piping system attached to a three storied concrete structure model which is constructed on a shaking table was excited due to earthquake motions. The inputs to the piping system were recorded at the second floor and the ceiling of the third floor where the system was attached to. The output, the response of the piping system, was instrumented at a middle point on the system. As a result, the multi-dimensional power spectrum analysis is effective for a more reliable identification of the vibration characteristics of the multi-input structure system

Development of the three dimensional flow model in the SPACE code

International Nuclear Information System (INIS)

Oh, Myung Taek; Park, Chan Eok; Kim, Shin Whan

2014-01-01

SPACE (Safety and Performance Analysis CodE) is a nuclear plant safety analysis code, which has been developed in the Republic of Korea through a joint research between the Korean nuclear industry and research institutes. The SPACE code has been developed with multi-dimensional capabilities as a requirement of the next generation safety code. It allows users to more accurately model the multi-dimensional flow behavior that can be exhibited in components such as the core, lower plenum, upper plenum and downcomer region. Based on generalized models, the code can model any configuration or type of fluid system. All the geometric quantities of mesh are described in terms of cell volume, centroid, face area, and face center, so that it can naturally represent not only the one dimensional (1D) or three dimensional (3D) Cartesian system, but also the cylindrical mesh system. It is possible to simulate large and complex domains by modelling the complex parts with a 3D approach and the rest of the system with a 1D approach. By 1D/3D co-simulation, more realistic conditions and component models can be obtained, providing a deeper understanding of complex systems, and it is expected to overcome the shortcomings of 1D system codes. (author)

Adaptive observer for the joint estimation of parameters and input for a coupled wave PDE and infinite dimensional ODE system

KAUST Repository

Belkhatir, Zehor

2016-08-05

This paper deals with joint parameters and input estimation for coupled PDE-ODE system. The system consists of a damped wave equation and an infinite dimensional ODE. This model describes the spatiotemporal hemodynamic response in the brain and the objective is to characterize brain regions using functional Magnetic Resonance Imaging (fMRI) data. For this reason, we propose an adaptive estimator and prove the asymptotic convergence of the state, the unknown input and the unknown parameters. The proof is based on a Lyapunov approach combined with a priori identifiability assumptions. The performance of the proposed observer is illustrated through some simulation results.

Spinorial Characterizations of Surfaces into 3-dimensional Pseudo-Riemannian Space Forms

International Nuclear Information System (INIS)

Lawn, Marie-Amélie; Roth, Julien

2011-01-01

We give a spinorial characterization of isometrically immersed surfaces of arbitrary signature into 3-dimensional pseudo-Riemannian space forms. This generalizes a recent work of the first author for spacelike immersed Lorentzian surfaces in ℝ 2,1 to other Lorentzian space forms. We also characterize immersions of Riemannian surfaces in these spaces. From this we can deduce analogous results for timelike immersions of Lorentzian surfaces in space forms of corresponding signature, as well as for spacelike and timelike immersions of surfaces of signature (0, 2), hence achieving a complete spinorial description for this class of pseudo-Riemannian immersions.

A high-order integral solver for scalar problems of diffraction by screens and apertures in three-dimensional space

Energy Technology Data Exchange (ETDEWEB)

Bruno, Oscar P., E-mail: obruno@caltech.edu; Lintner, Stéphane K.

2013-11-01

We present a novel methodology for the numerical solution of problems of diffraction by infinitely thin screens in three-dimensional space. Our approach relies on new integral formulations as well as associated high-order quadrature rules. The new integral formulations involve weighted versions of the classical integral operators related to the thin-screen Dirichlet and Neumann problems as well as a generalization to the open-surface problem of the classical Calderón formulae. The high-order quadrature rules we introduce for these operators, in turn, resolve the multiple Green function and edge singularities (which occur at arbitrarily close distances from each other, and which include weakly singular as well as hypersingular kernels) and thus give rise to super-algebraically fast convergence as the discretization sizes are increased. When used in conjunction with Krylov-subspace linear algebra solvers such as GMRES, the resulting solvers produce results of high accuracy in small numbers of iterations for low and high frequencies alike. We demonstrate our methodology with a variety of numerical results for screen and aperture problems at high frequencies—including simulation of classical experiments such as the diffraction by a circular disc (featuring in particular the famous Poisson spot), evaluation of interference fringes resulting from diffraction across two nearby circular apertures, as well as solution of problems of scattering by more complex geometries consisting of multiple scatterers and cavities.

Three-Dimensional, Transgenic Cell Models to Quantify Space Genotoxic Effects

Science.gov (United States)

Gonda, S. R.; Sognier, M. A.; Wu, H.; Pingerelli, P. L.; Glickman, B. W.; Dawson, David L. (Technical Monitor)

1999-01-01

The space environment contains radiation and chemical agents known to be mutagenic and carcinogenic to humans. Additionally, microgravity is a complicating factor that may modify or synergize induced genotoxic effects. Most in vitro models fail to use human cells (making risk extrapolation to humans more difficult), overlook the dynamic effect of tissue intercellular interactions on genotoxic damage, and lack the sensitivity required to measure low-dose effects. Currently a need exists for a model test system that simulates cellular interactions present in tissue, and can be used to quantify genotoxic damage induced by low levels of radiation and chemicals, and extrapolate assessed risk to humans. A state-of-the-art, three-dimensional, multicellular tissue equivalent cell culture model will be presented. It consists of mammalian cells genetically engineered to contain multiple copies of defined target genes for genotoxic assessment,. NASA-designed bioreactors were used to coculture mammalian cells into spheroids, The cells used were human mammary epithelial cells (H184135) and Stratagene's (Austin, Texas) Big Blue(TM) Rat 2 lambda fibroblasts. The fibroblasts were genetically engineered to contain -a high-density target gene for mutagenesis (60 copies of lacl/LacZ per cell). Tissue equivalent spheroids were routinely produced by inoculation of 2 to 7 X 10(exp 5) fibroblasts with Cytodex 3 beads (150 micrometers in diameter). at a 20:1 cell:bead ratio, into 50-ml HARV bioreactors (Synthecon, Inc.). Fibroblasts were cultured for 5 days, an equivalent number of epithelial cells added, and the fibroblast/epithelial cell coculture continued for 21 days. Three-dimensional spheroids with diameters ranging from 400 to 600 micrometers were obtained. Histological and immunohistochemical Characterization revealed i) both cell types present in the spheroids, with fibroblasts located primarily in the center, surrounded by epithelial cells; ii) synthesis of extracellular matrix

Quantum theory of spinor field in four-dimensional Riemannian space-time

International Nuclear Information System (INIS)

Shavokhina, N.S.

1996-01-01

The review deals with the spinor field in the four-dimensional Riemannian space-time. The field beys the Dirac-Fock-Ivanenko equation. Principles of quantization of the spinor field in the Riemannian space-time are formulated which in a particular case of the plane space-time are equivalent to the canonical rules of quantization. The formulated principles are exemplified by the De Sitter space-time. The study of quantum field theory in the De Sitter space-time is interesting because it itself leads to a method of an invariant well for plane space-time. However, the study of the quantum spinor field theory in an arbitrary Riemannian space-time allows one to take into account the influence of the external gravitational field on the quantized spinor field. 60 refs

Quantization of coset space σ-models coupled to two-dimensional gravity

International Nuclear Information System (INIS)

Korotkin, D.; Samtleben, H.

1996-07-01

The mathematical framework for an exact quantization of the two-dimensional coset space σ-models coupled to dilaton gravity, that arise from dimensional reduction of gravity and supergravity theories, is presented. The two-time Hamiltonian formulation is obtained, which describes the complete phase space of the model in the whole isomonodromic sector. The Dirac brackets arising from the coset constraints are calculated. Their quantization allows to relate exact solutions of the corresponding Wheeler-DeWitt equations to solutions of a modified (Coset) Knizhnik-Zamolodchikov system. On the classical level, a set of observables is identified, that is complete for essential sectors of the theory. Quantum counterparts of these observables and their algebraic structure are investigated. Their status in alternative quantization procedures is discussed, employing the link with Hamiltonian Chern-Simons theory. (orig.)

A comprehensive analysis of earthquake damage patterns using high dimensional model representation feature selection

Science.gov (United States)

Taşkin Kaya, Gülşen

2013-10-01

Recently, earthquake damage assessment using satellite images has been a very popular ongoing research direction. Especially with the availability of very high resolution (VHR) satellite images, a quite detailed damage map based on building scale has been produced, and various studies have also been conducted in the literature. As the spatial resolution of satellite images increases, distinguishability of damage patterns becomes more cruel especially in case of using only the spectral information during classification. In order to overcome this difficulty, textural information needs to be involved to the classification to improve the visual quality and reliability of damage map. There are many kinds of textural information which can be derived from VHR satellite images depending on the algorithm used. However, extraction of textural information and evaluation of them have been generally a time consuming process especially for the large areas affected from the earthquake due to the size of VHR image. Therefore, in order to provide a quick damage map, the most useful features describing damage patterns needs to be known in advance as well as the redundant features. In this study, a very high resolution satellite image after Iran, Bam earthquake was used to identify the earthquake damage. Not only the spectral information, textural information was also used during the classification. For textural information, second order Haralick features were extracted from the panchromatic image for the area of interest using gray level co-occurrence matrix with different size of windows and directions. In addition to using spatial features in classification, the most useful features representing the damage characteristic were selected with a novel feature selection method based on high dimensional model representation (HDMR) giving sensitivity of each feature during classification. The method called HDMR was recently proposed as an efficient tool to capture the input

Three-dimensional theory for interaction between atomic ensembles and free-space light

International Nuclear Information System (INIS)

Duan, L.-M.; Cirac, J.I.; Zoller, P.

2002-01-01

Atomic ensembles have shown to be a promising candidate for implementations of quantum information processing by many recently discovered schemes. All these schemes are based on the interaction between optical beams and atomic ensembles. For description of these interactions, one assumed either a cavity-QED model or a one-dimensional light propagation model, which is still inadequate for a full prediction and understanding of most of the current experimental efforts that are actually taken in the three-dimensional free space. Here, we propose a perturbative theory to describe the three-dimensional effects in interaction between atomic ensembles and free-space light with a level configuration important for several applications. The calculations reveal some significant effects that were not known before from the other approaches, such as the inherent mode-mismatching noise and the optimal mode-matching conditions. The three-dimensional theory confirms the collective enhancement of the signal-to-noise ratio which is believed to be one of the main advantages of the ensemble-based quantum information processing schemes, however, it also shows that this enhancement needs to be understood in a more subtle way with an appropriate mode-matching method

Gauge fields in nonlinear group realizations involving two-dimensional space-time symmetry

International Nuclear Information System (INIS)

Machacek, M.E.; McCliment, E.R.

1975-01-01

It is shown that gauge fields may be consistently introduced into a model Lagrangian previously considered by the authors. The model is suggested by the spontaneous breaking of a Lorentz-type group into a quasiphysical two-dimensional space-time and one internal degree of freedom, loosely associated with charge. The introduction of zero-mass gauge fields makes possible the absorption via the Higgs mechanism of the Goldstone fields that appear in the model despite the fact that the Goldstone fields do not transform as scalars. Specifically, gauge invariance of the Yang-Mills type requires the introduction of two sets of massless gauge fields. The transformation properties in two-dimensional space-time suggest that one set is analogous to a charge doublet that behaves like a second-rank tensor in real four-dimensional space time. The other set suggests a spin-one-like charge triplet. Via the Higgs mechanism, the first set absorbs the Goldstone fields and acquires mass. The second set remains massless. If massive gauge fields are introduced, the associated currents are not conserved and the Higgs mechanism is no longer fully operative. The Goldstone fields are not eliminated, but coupling between the Goldstone fields and the gauge fields does shift the mass of the antisymmetric second-rank-tensor gauge field components

Execution spaces for simple higher dimensional automata

DEFF Research Database (Denmark)

Raussen, Martin

2012-01-01

Higher dimensional automata (HDA) are highly expressive models for concurrency in Computer Science, cf van Glabbeek (Theor Comput Sci 368(1–2): 168–194, 2006). For a topologist, they are attractive since they can be modeled as cubical complexes—with an inbuilt restriction for directions of allowa......Higher dimensional automata (HDA) are highly expressive models for concurrency in Computer Science, cf van Glabbeek (Theor Comput Sci 368(1–2): 168–194, 2006). For a topologist, they are attractive since they can be modeled as cubical complexes—with an inbuilt restriction for directions...

Training astronauts using three-dimensional visualisations of the International Space Station.

Science.gov (United States)

Rycroft, M; Houston, A; Barker, A; Dahlstron, E; Lewis, N; Maris, N; Nelles, D; Bagaoutdinov, R; Bodrikov, G; Borodin, Y; Cheburkov, M; Ivanov, D; Karpunin, P; Katargin, R; Kiselyev, A; Kotlayarevsky, Y; Schetinnikov, A; Tylerov, F

1999-03-01

Recent advances in personal computer technology have led to the development of relatively low-cost software to generate high-resolution three-dimensional images. The capability both to rotate and zoom in on these images superposed on appropriate background images enables high-quality movies to be created. These developments have been used to produce realistic simulations of the International Space Station on CD-ROM. This product is described and its potentialities demonstrated. With successive launches, the ISS is gradually built up, and visualised over a rotating Earth against the star background. It is anticipated that this product's capability will be useful when training astronauts to carry out EVAs around the ISS. Simulations inside the ISS are also very realistic. These should prove invaluable when familiarising the ISS crew with their future workplace and home. Operating procedures can be taught and perfected. "What if" scenario models can be explored and this facility should be useful when training the crew to deal with emergency situations which might arise. This CD-ROM product will also be used to make the general public more aware of, and hence enthusiastic about, the International Space Station programme.

Quantum scattering theory of a single-photon Fock state in three-dimensional spaces.

Science.gov (United States)

Liu, Jingfeng; Zhou, Ming; Yu, Zongfu

2016-09-15

A quantum scattering theory is developed for Fock states scattered by two-level systems in three-dimensional free space. It is built upon the one-dimensional scattering theory developed in waveguide quantum electrodynamics. The theory fully quantizes the incident light as Fock states and uses a non-perturbative method to calculate the scattering matrix.

Three dimensional monocular human motion analysis in end-effector space

DEFF Research Database (Denmark)

Hauberg, Søren; Lapuyade, Jerome; Engell-Nørregård, Morten Pol

2009-01-01

In this paper, we present a novel approach to three dimensional human motion estimation from monocular video data. We employ a particle filter to perform the motion estimation. The novelty of the method lies in the choice of state space for the particle filter. Using a non-linear inverse kinemati...

A video of Mixed Interaction Space video

DEFF Research Database (Denmark)

Lykke, Olesen, Andreas; Hansen, Thomas Riisgaard; Eriksson, Eva

Mixed Interaction Space is a new concept that uses the mobile phone to interact with either applications on the phone or in the environment by tracking the position and rotation with the camera in 4 dimmension. Most mobile devices today has a camera onboard. In the project about Mixed Interaction...... Spaces we use image processing algorithms to track the movement of the mobile phone according to a fixed point and use this information as input to different applications. We are able to track the movement of the device in 3D plus the rotation of the device and uses these information as a kind of four...... dimensional input device. As a fixed point we use a circle in the first version of Mixis. By tracking the circle we have developed a number of applications that uses this technique as input. Above is three examples....

Representing high-dimensional data to intelligent prostheses and other wearable assistive robots: A first comparison of tile coding and selective Kanerva coding.

Science.gov (United States)

Travnik, Jaden B; Pilarski, Patrick M

2017-07-01

Prosthetic devices have advanced in their capabilities and in the number and type of sensors included in their design. As the space of sensorimotor data available to a conventional or machine learning prosthetic control system increases in dimensionality and complexity, it becomes increasingly important that this data be represented in a useful and computationally efficient way. Well structured sensory data allows prosthetic control systems to make informed, appropriate control decisions. In this study, we explore the impact that increased sensorimotor information has on current machine learning prosthetic control approaches. Specifically, we examine the effect that high-dimensional sensory data has on the computation time and prediction performance of a true-online temporal-difference learning prediction method as embedded within a resource-limited upper-limb prosthesis control system. We present results comparing tile coding, the dominant linear representation for real-time prosthetic machine learning, with a newly proposed modification to Kanerva coding that we call selective Kanerva coding. In addition to showing promising results for selective Kanerva coding, our results confirm potential limitations to tile coding as the number of sensory input dimensions increases. To our knowledge, this study is the first to explicitly examine representations for realtime machine learning prosthetic devices in general terms. This work therefore provides an important step towards forming an efficient prosthesis-eye view of the world, wherein prompt and accurate representations of high-dimensional data may be provided to machine learning control systems within artificial limbs and other assistive rehabilitation technologies.

Dimensionality reduction of collective motion by principal manifolds

Science.gov (United States)

Gajamannage, Kelum; Butail, Sachit; Porfiri, Maurizio; Bollt, Erik M.

2015-01-01

While the existence of low-dimensional embedding manifolds has been shown in patterns of collective motion, the current battery of nonlinear dimensionality reduction methods is not amenable to the analysis of such manifolds. This is mainly due to the necessary spectral decomposition step, which limits control over the mapping from the original high-dimensional space to the embedding space. Here, we propose an alternative approach that demands a two-dimensional embedding which topologically summarizes the high-dimensional data. In this sense, our approach is closely related to the construction of one-dimensional principal curves that minimize orthogonal error to data points subject to smoothness constraints. Specifically, we construct a two-dimensional principal manifold directly in the high-dimensional space using cubic smoothing splines, and define the embedding coordinates in terms of geodesic distances. Thus, the mapping from the high-dimensional data to the manifold is defined in terms of local coordinates. Through representative examples, we show that compared to existing nonlinear dimensionality reduction methods, the principal manifold retains the original structure even in noisy and sparse datasets. The principal manifold finding algorithm is applied to configurations obtained from a dynamical system of multiple agents simulating a complex maneuver called predator mobbing, and the resulting two-dimensional embedding is compared with that of a well-established nonlinear dimensionality reduction method.

Coherent states on horospheric three-dimensional Lobachevsky space

Energy Technology Data Exchange (ETDEWEB)

Kurochkin, Yu., E-mail: y.kurochkin@ifanbel.bas-net.by; Shoukavy, Dz., E-mail: shoukavy@ifanbel.bas-net.by [Institute of Physics, National Academy of Sciences of Belarus, 68 Nezalezhnasci Ave., Minsk 220072 (Belarus); Rybak, I., E-mail: Ivan.Rybak@astro.up.pt [Institute of Physics, National Academy of Sciences of Belarus, 68 Nezalezhnasci Ave., Minsk 220072 (Belarus); Instituto de Astrofísica e Ciências do Espaço, CAUP, Rua das Estrelas, 4150-762 Porto (Portugal); Faculdade de Ciências, Universidade do Porto, Rua do Campo Alegre 687, 4169-007 Porto (Portugal)

2016-08-15

In the paper it is shown that due to separation of variables in the Laplace-Beltrami operator (Hamiltonian of a free quantum particle) in horospheric and quasi-Cartesian coordinates of three dimensional Lobachevsky space, it is possible to introduce standard (“conventional” according to Perelomov [Generalized Coherent States and Their Applications (Springer-Verlag, 1986), p. 320]) coherent states. Some problems (oscillator on horosphere, charged particle in analogy of constant uniform magnetic field) where coherent states are suitable for treating were considered.

Aspects of high-dimensional theories in embedding spaces

International Nuclear Information System (INIS)

Maia, M.D.; Mecklenburg, W.

1983-01-01

The question of whether physical meaning may be attributed to the extra dimensions provided by embedding procedures as applied to physical space-times is discussed. The similarities and differences of the present picture to that of conventional Kaluza-Klein pictures are commented. (Author) [pt

Mixed Interaction Spaces

DEFF Research Database (Denmark)

Lykke-Olesen, Andreas; Eriksson, E.; Hansen, T.R.

In this paper, we describe a new interaction technique for mobile devices named Mixed Interaction Space that uses the camera of the mobile device to track the position, size and rotation of a fixed-point. In this demonstration we will present a system that uses a hand-drawn circle, colored object...... or a person’s face as a fixed-point to determine the location of the device. We use these features as a 4 dimensional input vector to a set of different applications....

Single-phase multi-dimensional thermohydraulics direct numerical simulation code DINUS-3. Input data description

Energy Technology Data Exchange (ETDEWEB)

Muramatsu, Toshiharu [Power Reactor and Nuclear Fuel Development Corp., Oarai, Ibaraki (Japan). Oarai Engineering Center

1998-08-01

This report explains the numerical methods and the set-up method of input data for a single-phase multi-dimensional thermohydraulics direct numerical simulation code DINUS-3 (Direct Numerical Simulation using a 3rd-order upwind scheme). The code was developed to simulate non-stationary temperature fluctuation phenomena related to thermal striping phenomena, developed at Power Reactor and Nuclear Fuel Development Corporation (PNC). The DINUS-3 code was characterized by the use of a third-order upwind scheme for convection terms in instantaneous Navier-Stokes and energy equations, and an adaptive control system based on the Fuzzy theory to control time step sizes. Author expect this report is very useful to utilize the DINUS-3 code for the evaluation of various non-stationary thermohydraulic phenomena in reactor applications. (author)

Machine learning for toxicity characterization of organic chemical emissions using USEtox database: Learning the structure of the input space.

Science.gov (United States)

Marvuglia, Antonino; Kanevski, Mikhail; Benetto, Enrico

2015-10-01

Toxicity characterization of chemical emissions in Life Cycle Assessment (LCA) is a complex task which usually proceeds via multimedia (fate, exposure and effect) models attached to models of dose-response relationships to assess the effects on target. Different models and approaches do exist, but all require a vast amount of data on the properties of the chemical compounds being assessed, which are hard to collect or hardly publicly available (especially for thousands of less common or newly developed chemicals), therefore hampering in practice the assessment in LCA. An example is USEtox, a consensual model for the characterization of human toxicity and freshwater ecotoxicity. This paper places itself in a line of research aiming at providing a methodology to reduce the number of input parameters necessary to run multimedia fate models, focusing in particular to the application of the USEtox toxicity model. By focusing on USEtox, in this paper two main goals are pursued: 1) performing an extensive exploratory analysis (using dimensionality reduction techniques) of the input space constituted by the substance-specific properties at the aim of detecting particular patterns in the data manifold and estimating the dimension of the subspace in which the data manifold actually lies; and 2) exploring the application of a set of linear models, based on partial least squares (PLS) regression, as well as a nonlinear model (general regression neural network--GRNN) in the seek for an automatic selection strategy of the most informative variables according to the modelled output (USEtox factor). After extensive analysis, the intrinsic dimension of the input manifold has been identified between three and four. The variables selected as most informative may vary according to the output modelled and the model used, but for the toxicity factors modelled in this paper the input variables selected as most informative are coherent with prior expectations based on scientific knowledge

High-resolution two-dimensional and three-dimensional modeling of wire grid polarizers and micropolarizer arrays

Science.gov (United States)

Vorobiev, Dmitry; Ninkov, Zoran

2017-11-01

Recent advances in photolithography allowed the fabrication of high-quality wire grid polarizers for the visible and near-infrared regimes. In turn, micropolarizer arrays (MPAs) based on wire grid polarizers have been developed and used to construct compact, versatile imaging polarimeters. However, the contrast and throughput of these polarimeters are significantly worse than one might expect based on the performance of large area wire grid polarizers or MPAs, alone. We investigate the parameters that affect the performance of wire grid polarizers and MPAs, using high-resolution two-dimensional and three-dimensional (3-D) finite-difference time-domain simulations. We pay special attention to numerical errors and other challenges that arise in models of these and other subwavelength optical devices. Our tests show that simulations of these structures in the visible and near-IR begin to converge numerically when the mesh size is smaller than ˜4 nm. The performance of wire grid polarizers is very sensitive to the shape, spacing, and conductivity of the metal wires. Using 3-D simulations of micropolarizer "superpixels," we directly study the cross talk due to diffraction at the edges of each micropolarizer, which decreases the contrast of MPAs to ˜200∶1.

A Shell Multi-dimensional Hierarchical Cubing Approach for High-Dimensional Cube

Science.gov (United States)

Zou, Shuzhi; Zhao, Li; Hu, Kongfa

The pre-computation of data cubes is critical for improving the response time of OLAP systems and accelerating data mining tasks in large data warehouses. However, as the sizes of data warehouses grow, the time it takes to perform this pre-computation becomes a significant performance bottleneck. In a high dimensional data warehouse, it might not be practical to build all these cuboids and their indices. In this paper, we propose a shell multi-dimensional hierarchical cubing algorithm, based on an extension of the previous minimal cubing approach. This method partitions the high dimensional data cube into low multi-dimensional hierarchical cube. Experimental results show that the proposed method is significantly more efficient than other existing cubing methods.

Solution of the two-dimensional space-time reactor kinetics equation by a locally one-dimensional method

International Nuclear Information System (INIS)

Chen, G.S.; Christenson, J.M.

1985-01-01

In this paper, the authors present some initial results from an investigation of the application of a locally one-dimensional (LOD) finite difference method to the solution of the two-dimensional, two-group reactor kinetics equations. Although the LOD method is relatively well known, it apparently has not been previously applied to the space-time kinetics equations. In this investigation, the LOD results were benchmarked against similar computational results (using the same computing environment, the same programming structure, and the same sample problems) obtained by the TWIGL program. For all of the problems considered, the LOD method provided accurate results in one-half to one-eight of the time required by the TWIGL program

Optical asymmetric cryptography using a three-dimensional space-based model

International Nuclear Information System (INIS)

Chen, Wen; Chen, Xudong

2011-01-01

In this paper, we present optical asymmetric cryptography combined with a three-dimensional (3D) space-based model. An optical multiple-random-phase-mask encoding system is developed in the Fresnel domain, and one random phase-only mask and the plaintext are combined as a series of particles. Subsequently, the series of particles is translated along an axial direction, and is distributed in a 3D space. During image decryption, the robustness and security of the proposed method are further analyzed. Numerical simulation results are presented to show the feasibility and effectiveness of the proposed optical image encryption method

Dynamics of a neuron model in different two-dimensional parameter-spaces

Science.gov (United States)

Rech, Paulo C.

2011-03-01

We report some two-dimensional parameter-space diagrams numerically obtained for the multi-parameter Hindmarsh-Rose neuron model. Several different parameter planes are considered, and we show that regardless of the combination of parameters, a typical scenario is preserved: for all choice of two parameters, the parameter-space presents a comb-shaped chaotic region immersed in a large periodic region. We also show that exist regions close these chaotic region, separated by the comb teeth, organized themselves in period-adding bifurcation cascades.

The curvature and the algebra of Killing vectors in five-dimensional space

International Nuclear Information System (INIS)

Rcheulishvili, G.

1990-12-01

This paper presents the Killing vectors for a five-dimensional space with the line element. The algebras which are formed by these vectors are written down. The curvature two-forms are described. (author). 10 refs

High-dimensional covariance estimation with high-dimensional data

CERN Document Server

Pourahmadi, Mohsen

2013-01-01

Methods for estimating sparse and large covariance matrices Covariance and correlation matrices play fundamental roles in every aspect of the analysis of multivariate data collected from a variety of fields including business and economics, health care, engineering, and environmental and physical sciences. High-Dimensional Covariance Estimation provides accessible and comprehensive coverage of the classical and modern approaches for estimating covariance matrices as well as their applications to the rapidly developing areas lying at the intersection of statistics and mac

A three-dimensional phase space dynamical model of the Earth's radiation belt

International Nuclear Information System (INIS)

Boscher, D. M.; Beutier, T.; Bourdarie, S.

1996-01-01

A three dimensional phase space model of the Earth's radiation belt is presented. We have taken into account the magnetic and electric radial diffusions, the pitch angle diffusions due to Coulomb interactions and interactions with the plasmaspheric hiss, and the Coulomb drag. First, a steady state of the belt is presented. Two main maxima are obtained, corresponding to the inner and outer parts of the belt. Then, we have modelled a simple injection at the external boundary. The particle transport seems like what was measured aboard satellites. A high energy particle loss is found, by comparing the model results and the measurements. It remains to be explained

Canonical Groups for Quantization on the Two-Dimensional Sphere and One-Dimensional Complex Projective Space

International Nuclear Information System (INIS)

Sumadi A H A; H, Zainuddin

2014-01-01

Using Isham's group-theoretic quantization scheme, we construct the canonical groups of the systems on the two-dimensional sphere and one-dimensional complex projective space, which are homeomorphic. In the first case, we take SO(3) as the natural canonical Lie group of rotations of the two-sphere and find all the possible Hamiltonian vector fields, and followed by verifying the commutator and Poisson bracket algebra correspondences with the Lie algebra of the group. In the second case, the same technique is resumed to define the Lie group, in this case SU (2), of CP'.We show that one can simply use a coordinate transformation from S 2 to CP 1 to obtain all the Hamiltonian vector fields of CP 1 . We explicitly show that the Lie algebra structures of both canonical groups are locally homomorphic. On the other hand, globally their corresponding canonical groups are acting on different geometries, the latter of which is almost complex. Thus the canonical group for CP 1 is the double-covering group of SO(3), namely SU(2). The relevance of the proposed formalism is to understand the idea of CP 1 as a space of where the qubit lives which is known as a Bloch sphere

Gauge constructs and immersions of four-dimensional spacetimes in (4 + k)-dimensional flat spaces: algebraic evaluation of gravity fields

International Nuclear Information System (INIS)

Edelen, Dominic G B

2003-01-01

Local action of the fundamental group SO(a, 4 + k - a) is used to show that any solution of an algebraically closed differential system, that is generated from matrix Lie algebra valued 1-forms on a four-dimensional parameter space, will generate families of immersions of four-dimensional spacetimes R 4 in flat (4 + k)-dimensional spaces M 4+k with compatible signature. The algorithm is shown to work with local action of SO(a, 4 + k - a) replaced by local action of GL(4 + k). Immersions generated by local action of the Poincare group on the target spacetime are also obtained. Evaluations of the line elements, immersion loci and connection and curvature forms of these immersions are algebraic. Families of immersions that depend on one or more arbitrary functions are calculated for 1 ≤ k ≤ 4. Appropriate sections of graphs of the conformal factor for two and three interacting line singularities immersed in M 6 are given in appendix A. The local immersion theorem given in appendix B shows that all local solutions of the immersion problem are obtained by use of this method and an algebraic extension in exceptional cases

Ghosts in high dimensional non-linear dynamical systems: The example of the hypercycle

International Nuclear Information System (INIS)

Sardanyes, Josep

2009-01-01

Ghost-induced delayed transitions are analyzed in high dimensional non-linear dynamical systems by means of the hypercycle model. The hypercycle is a network of catalytically-coupled self-replicating RNA-like macromolecules, and has been suggested to be involved in the transition from non-living to living matter in the context of earlier prebiotic evolution. It is demonstrated that, in the vicinity of the saddle-node bifurcation for symmetric hypercycles, the persistence time before extinction, T ε , tends to infinity as n→∞ (being n the number of units of the hypercycle), thus suggesting that the increase in the number of hypercycle units involves a longer resilient time before extinction because of the ghost. Furthermore, by means of numerical analysis the dynamics of three large hypercycle networks is also studied, focusing in their extinction dynamics associated to the ghosts. Such networks allow to explore the properties of the ghosts living in high dimensional phase space with n = 5, n = 10 and n = 15 dimensions. These hypercyclic networks, in agreement with other works, are shown to exhibit self-maintained oscillations governed by stable limit cycles. The bifurcation scenarios for these hypercycles are analyzed, as well as the effect of the phase space dimensionality in the delayed transition phenomena and in the scaling properties of the ghosts near bifurcation threshold

Longitudinal Phase Space Tomography with Space Charge

CERN Document Server

Hancock, S; Lindroos, M

2000-01-01

Tomography is now a very broad topic with a wealth of algorithms for the reconstruction of both qualitative and quantitative images. In an extension in the domain of particle accelerators, one of the simplest algorithms has been modified to take into account the non-linearity of large-amplitude synchrotron motion. This permits the accurate reconstruction of longitudinal phase space density from one-dimensional bunch profile data. The method is a hybrid one which incorporates particle tracking. Hitherto, a very simple tracking algorithm has been employed because only a brief span of measured profile data is required to build a snapshot of phase space. This is one of the strengths of the method, as tracking for relatively few turns relaxes the precision to which input machine parameters need to be known. The recent addition of longitudinal space charge considerations as an optional refinement of the code is described. Simplicity suggested an approach based on the derivative of bunch shape with the properties of...

On renormalisation of the quantum stress tensor in curved space-time by dimensional regularisation

International Nuclear Information System (INIS)

Bunch, T.S.

1979-01-01

Using dimensional regularisation, a prescription is given for obtaining a finite renormalised stress tensor in curved space-time. Renormalisation is carried out by renormalising coupling constants in the n-dimensional Einstein equation generalised to include tensors which are fourth order in derivatives of the metric. Except for the special case of a massless conformal field in a conformally flat space-time, this procedure is not unique. There exists an infinite one-parameter family of renormalisation ansatze differing from each other in the finite renormalisation that takes place. Nevertheless, the renormalised stress tensor for a conformally invariant field theory acquires a nonzero trace which is independent of the renormalisation ansatz used and which has a value in agreement with that obtained by other methods. A comparison is made with some earlier work using dimensional regularisation which is shown to be in error. (author)

Quadcopter control in three-dimensional space using a noninvasive motor imagery based brain-computer interface

Science.gov (United States)

LaFleur, Karl; Cassady, Kaitlin; Doud, Alexander; Shades, Kaleb; Rogin, Eitan; He, Bin

2013-01-01

Objective At the balanced intersection of human and machine adaptation is found the optimally functioning brain-computer interface (BCI). In this study, we report a novel experiment of BCI controlling a robotic quadcopter in three-dimensional physical space using noninvasive scalp EEG in human subjects. We then quantify the performance of this system using metrics suitable for asynchronous BCI. Lastly, we examine the impact that operation of a real world device has on subjects’ control with comparison to a two-dimensional virtual cursor task. Approach Five human subjects were trained to modulate their sensorimotor rhythms to control an AR Drone navigating a three-dimensional physical space. Visual feedback was provided via a forward facing camera on the hull of the drone. Individual subjects were able to accurately acquire up to 90.5% of all valid targets presented while travelling at an average straight-line speed of 0.69 m/s. Significance Freely exploring and interacting with the world around us is a crucial element of autonomy that is lost in the context of neurodegenerative disease. Brain-computer interfaces are systems that aim to restore or enhance a user’s ability to interact with the environment via a computer and through the use of only thought. We demonstrate for the first time the ability to control a flying robot in the three-dimensional physical space using noninvasive scalp recorded EEG in humans. Our work indicates the potential of noninvasive EEG based BCI systems to accomplish complex control in three-dimensional physical space. The present study may serve as a framework for the investigation of multidimensional non-invasive brain-computer interface control in a physical environment using telepresence robotics. PMID:23735712

Finding and Visualizing Relevant Subspaces for Clustering High-Dimensional Astronomical Data Using Connected Morphological Operators

NARCIS (Netherlands)

Ferdosi, Bilkis J.; Buddelmeijer, Hugo; Trager, Scott; Wilkinson, Michael H.F.; Roerdink, Jos B.T.M.

2010-01-01

Data sets in astronomy are growing to enormous sizes. Modern astronomical surveys provide not only image data but also catalogues of millions of objects (stars, galaxies), each object with hundreds of associated parameters. Exploration of this very high-dimensional data space poses a huge challenge.

N-Dimensional LLL Reduction Algorithm with Pivoted Reflection

Directory of Open Access Journals (Sweden)

Zhongliang Deng

2018-01-01

Full Text Available The Lenstra-Lenstra-Lovász (LLL lattice reduction algorithm and many of its variants have been widely used by cryptography, multiple-input-multiple-output (MIMO communication systems and carrier phase positioning in global navigation satellite system (GNSS to solve the integer least squares (ILS problem. In this paper, we propose an n-dimensional LLL reduction algorithm (n-LLL, expanding the Lovász condition in LLL algorithm to n-dimensional space in order to obtain a further reduced basis. We also introduce pivoted Householder reflection into the algorithm to optimize the reduction time. For an m-order positive definite matrix, analysis shows that the n-LLL reduction algorithm will converge within finite steps and always produce better results than the original LLL reduction algorithm with n > 2. The simulations clearly prove that n-LLL is better than the original LLL in reducing the condition number of an ill-conditioned input matrix with 39% improvement on average for typical cases, which can significantly reduce the searching space for solving ILS problem. The simulation results also show that the pivoted reflection has significantly declined the number of swaps in the algorithm by 57%, making n-LLL a more practical reduction algorithm.

Quantum theory of string in the four-dimensional space-time

International Nuclear Information System (INIS)

Pron'ko, G.P.

1986-01-01

The Lorentz invariant quantum theory of string is constructed in four-dimensional space-time. Unlike the traditional approach whose result was breaking of Lorentz invariance, our method is based on the usage of other variables for description of string configurations. The method of an auxiliary spectral problem for periodic potentials is the main tool in construction of these new variables

Evaluation of a new high-dimensional miRNA profiling platform

Directory of Open Access Journals (Sweden)

Lamblin Anne-Francoise

2009-08-01

Full Text Available Abstract Background MicroRNAs (miRNAs are a class of approximately 22 nucleotide long, widely expressed RNA molecules that play important regulatory roles in eukaryotes. To investigate miRNA function, it is essential that methods to quantify their expression levels be available. Methods We evaluated a new miRNA profiling platform that utilizes Illumina's existing robust DASL chemistry as the basis for the assay. Using total RNA from five colon cancer patients and four cell lines, we evaluated the reproducibility of miRNA expression levels across replicates and with varying amounts of input RNA. The beta test version was comprised of 735 miRNA targets of Illumina's miRNA profiling application. Results Reproducibility between sample replicates within a plate was good (Spearman's correlation 0.91 to 0.98 as was the plate-to-plate reproducibility replicates run on different days (Spearman's correlation 0.84 to 0.98. To determine whether quality data could be obtained from a broad range of input RNA, data obtained from amounts ranging from 25 ng to 800 ng were compared to those obtained at 200 ng. No effect across the range of RNA input was observed. Conclusion These results indicate that very small amounts of starting material are sufficient to allow sensitive miRNA profiling using the Illumina miRNA high-dimensional platform. Nonlinear biases were observed between replicates, indicating the need for abundance-dependent normalization. Overall, the performance characteristics of the Illumina miRNA profiling system were excellent.

Input-output analysis of high-speed turbulent jet noise

Science.gov (United States)

Jeun, Jinah; Nichols, Joseph W.

2015-11-01

We apply input-output analysis to predict and understand the aeroacoustics of high-speed isothermal turbulent jets. We consider axisymmetric linear perturbations about Reynolds-averaged Navier-Stokes solutions of ideally expanded turbulent jets with Mach numbers 0 . 6 parabolized stability equations (PSE), and this mode dominates the response. For subsonic jets, however, the singular values indicate that the contributions of suboptimal modes to noise generation are nearly equal to that of the optimal mode, explaining why PSE misses some of the farfield sound in this case. Finally, high-fidelity large eddy simulation (LES) is used to assess the prevalence of suboptimal modes in the unsteady data. By projecting LES data onto the corresponding input modes, the weighted gain of each mode is examined.

Feature Augmentation via Nonparametrics and Selection (FANS) in High-Dimensional Classification.

Science.gov (United States)

Fan, Jianqing; Feng, Yang; Jiang, Jiancheng; Tong, Xin

We propose a high dimensional classification method that involves nonparametric feature augmentation. Knowing that marginal density ratios are the most powerful univariate classifiers, we use the ratio estimates to transform the original feature measurements. Subsequently, penalized logistic regression is invoked, taking as input the newly transformed or augmented features. This procedure trains models equipped with local complexity and global simplicity, thereby avoiding the curse of dimensionality while creating a flexible nonlinear decision boundary. The resulting method is called Feature Augmentation via Nonparametrics and Selection (FANS). We motivate FANS by generalizing the Naive Bayes model, writing the log ratio of joint densities as a linear combination of those of marginal densities. It is related to generalized additive models, but has better interpretability and computability. Risk bounds are developed for FANS. In numerical analysis, FANS is compared with competing methods, so as to provide a guideline on its best application domain. Real data analysis demonstrates that FANS performs very competitively on benchmark email spam and gene expression data sets. Moreover, FANS is implemented by an extremely fast algorithm through parallel computing.

Enhancement of regional wet deposition estimates based on modeled precipitation inputs

Science.gov (United States)

James A. Lynch; Jeffery W. Grimm; Edward S. Corbett

1996-01-01

Application of a variety of two-dimensional interpolation algorithms to precipitation chemistry data gathered at scattered monitoring sites for the purpose of estimating precipitation- born ionic inputs for specific points or regions have failed to produce accurate estimates. The accuracy of these estimates is particularly poor in areas of high topographic relief....

On Kubo-Martin-Schwinger states of classical dynamical systems with the infinite-dimensional phase space

International Nuclear Information System (INIS)

Arsen'ev, A.A.

1979-01-01

Example of a classical dynamical system with the infinite-dimensional phase space, satisfying the analogue of the Kubo-Martin-Schwinger conditions for classical dynamics, is constructed explicitly. Connection between the system constructed and the Fock space dynamics is pointed out

Highly conducting one-dimensional solids

CERN Document Server

Evrard, Roger; Doren, Victor

1979-01-01

Although the problem of a metal in one dimension has long been known to solid-state physicists, it was not until the synthesis of real one-dimensional or quasi-one-dimensional systems that this subject began to attract considerable attention. This has been due in part to the search for high­ temperature superconductivity and the possibility of reaching this goal with quasi-one-dimensional substances. A period of intense activity began in 1973 with the report of a measurement of an apparently divergent conduc­ tivity peak in TfF-TCNQ. Since then a great deal has been learned about quasi-one-dimensional conductors. The emphasis now has shifted from trying to find materials of very high conductivity to the many interesting problems of physics and chemistry involved. But many questions remain open and are still under active investigation. This book gives a review of the experimental as well as theoretical progress made in this field over the last years. All the chapters have been written by scientists who have ...

Inferring biological tasks using Pareto analysis of high-dimensional data.

Science.gov (United States)

Hart, Yuval; Sheftel, Hila; Hausser, Jean; Szekely, Pablo; Ben-Moshe, Noa Bossel; Korem, Yael; Tendler, Avichai; Mayo, Avraham E; Alon, Uri

2015-03-01

We present the Pareto task inference method (ParTI; http://www.weizmann.ac.il/mcb/UriAlon/download/ParTI) for inferring biological tasks from high-dimensional biological data. Data are described as a polytope, and features maximally enriched closest to the vertices (or archetypes) allow identification of the tasks the vertices represent. We demonstrate that human breast tumors and mouse tissues are well described by tetrahedrons in gene expression space, with specific tumor types and biological functions enriched at each of the vertices, suggesting four key tasks.

A New Ensemble of Perturbed-Input-Parameter Simulations by the Community Atmosphere Model

Energy Technology Data Exchange (ETDEWEB)

Covey, C; Brandon, S; Bremer, P T; Domyancis, D; Garaizar, X; Johannesson, G; Klein, R; Klein, S A; Lucas, D D; Tannahill, J; Zhang, Y

2011-10-27

Uncertainty quantification (UQ) is a fundamental challenge in the numerical simulation of Earth's weather and climate, and other complex systems. It entails much more than attaching defensible error bars to predictions: in particular it includes assessing low-probability but high-consequence events. To achieve these goals with models containing a large number of uncertain input parameters, structural uncertainties, etc., raw computational power is needed. An automated, self-adapting search of the possible model configurations is also useful. Our UQ initiative at the Lawrence Livermore National Laboratory has produced the most extensive set to date of simulations from the US Community Atmosphere Model. We are examining output from about 3,000 twelve-year climate simulations generated with a specialized UQ software framework, and assessing the model's accuracy as a function of 21 to 28 uncertain input parameter values. Most of the input parameters we vary are related to the boundary layer, clouds, and other sub-grid scale processes. Our simulations prescribe surface boundary conditions (sea surface temperatures and sea ice amounts) to match recent observations. Fully searching this 21+ dimensional space is impossible, but sensitivity and ranking algorithms can identify input parameters having relatively little effect on a variety of output fields, either individually or in nonlinear combination. Bayesian statistical constraints, employing a variety of climate observations as metrics, also seem promising. Observational constraints will be important in the next step of our project, which will compute sea surface temperatures and sea ice interactively, and will study climate change due to increasing atmospheric carbon dioxide.

An adaptive ANOVA-based PCKF for high-dimensional nonlinear inverse modeling

Science.gov (United States)

Li, Weixuan; Lin, Guang; Zhang, Dongxiao

2014-02-01

The probabilistic collocation-based Kalman filter (PCKF) is a recently developed approach for solving inverse problems. It resembles the ensemble Kalman filter (EnKF) in every aspect-except that it represents and propagates model uncertainty by polynomial chaos expansion (PCE) instead of an ensemble of model realizations. Previous studies have shown PCKF is a more efficient alternative to EnKF for many data assimilation problems. However, the accuracy and efficiency of PCKF depends on an appropriate truncation of the PCE series. Having more polynomial chaos basis functions in the expansion helps to capture uncertainty more accurately but increases computational cost. Selection of basis functions is particularly important for high-dimensional stochastic problems because the number of polynomial chaos basis functions required to represent model uncertainty grows dramatically as the number of input parameters (random dimensions) increases. In classic PCKF algorithms, the PCE basis functions are pre-set based on users' experience. Also, for sequential data assimilation problems, the basis functions kept in PCE expression remain unchanged in different Kalman filter loops, which could limit the accuracy and computational efficiency of classic PCKF algorithms. To address this issue, we present a new algorithm that adaptively selects PCE basis functions for different problems and automatically adjusts the number of basis functions in different Kalman filter loops. The algorithm is based on adaptive functional ANOVA (analysis of variance) decomposition, which approximates a high-dimensional function with the summation of a set of low-dimensional functions. Thus, instead of expanding the original model into PCE, we implement the PCE expansion on these low-dimensional functions, which is much less costly. We also propose a new adaptive criterion for ANOVA that is more suited for solving inverse problems. The new algorithm was tested with different examples and demonstrated

Influence of cusps and intersections on the calculation of the Wilson loop in ν-dimensional space

International Nuclear Information System (INIS)

Bezerra, V.B.

1984-01-01

A discussion is given about the influence of cusps and intersections on the calculation of the Wilson Loop in ν-dimensional space. In particular, for the two-dimensional case, it is shown that there are no divergences. (Author) [pt

Three-Dimensional Navier-Stokes Calculations Using the Modified Space-Time CESE Method

Science.gov (United States)

Chang, Chau-lyan

2007-01-01

The space-time conservation element solution element (CESE) method is modified to address the robustness issues of high-aspect-ratio, viscous, near-wall meshes. In this new approach, the dependent variable gradients are evaluated using element edges and the corresponding neighboring solution elements while keeping the original flux integration procedure intact. As such, the excellent flux conservation property is retained and the new edge-based gradients evaluation significantly improves the robustness for high-aspect ratio meshes frequently encountered in three-dimensional, Navier-Stokes calculations. The order of accuracy of the proposed method is demonstrated for oblique acoustic wave propagation, shock-wave interaction, and hypersonic flows over a blunt body. The confirmed second-order convergence along with the enhanced robustness in handling hypersonic blunt body flow calculations makes the proposed approach a very competitive CFD framework for 3D Navier-Stokes simulations.

Neutrino stress tensor regularization in two-dimensional space-time

International Nuclear Information System (INIS)

Davies, P.C.W.; Unruh, W.G.

1977-01-01

The method of covariant point-splitting is used to regularize the stress tensor for a massless spin 1/2 (neutrino) quantum field in an arbitrary two-dimensional space-time. A thermodynamic argument is used as a consistency check. The result shows that the physical part of the stress tensor is identical with that of the massless scalar field (in the absence of Casimir-type terms) even though the formally divergent expression is equal to the negative of the scalar case. (author)

Coset Space Dimensional Reduction approach to the Standard Model

International Nuclear Information System (INIS)

Farakos, K.; Kapetanakis, D.; Koutsoumbas, G.; Zoupanos, G.

1988-01-01

We present a unified theory in ten dimensions based on the gauge group E 8 , which is dimensionally reduced to the Standard Mode SU 3c xSU 2 -LxU 1 , which breaks further spontaneously to SU 3L xU 1em . The model gives similar predictions for sin 2 θ w and proton decay as the minimal SU 5 G.U.T., while a natural choice of the coset space radii predicts light Higgs masses a la Coleman-Weinberg

Highly-Expressive Spaces of Well-Behaved Transformations: Keeping It Simple

DEFF Research Database (Denmark)

Freifeld, Oren; Hauberg, Søren; Batmanghelich, Kayhan

We propose novel finite-dimensional spaces of Rn → Rn transformations, n ∈ {1, 2, 3}, derived from (continuously-defined) parametric stationary velocity fields. Particularly, we obtain these transformations, which are diffeomorphisms, by fast and highly-accurate integration of continuous piecewise...... transformations). Its applications include, but are not limited to: unconstrained optimization over monotonic functions; modeling cumulative distribution functions or histograms; time warping; image registration; landmark-based warping; real-time diffeomorphic image editing....

The role of extreme orbits in the global organization of periodic regions in parameter space for one dimensional maps

Energy Technology Data Exchange (ETDEWEB)

Costa, Diogo Ricardo da, E-mail: diogo_cost@hotmail.com [Departamento de Física, UNESP – Universidade Estadual Paulista, Av. 24A, 1515, Bela Vista, 13506-900, Rio Claro, SP (Brazil); Hansen, Matheus [Departamento de Física, UNESP – Universidade Estadual Paulista, Av. 24A, 1515, Bela Vista, 13506-900, Rio Claro, SP (Brazil); Instituto de Física, Univ. São Paulo, Rua do Matão, Cidade Universitária, 05314-970, São Paulo – SP (Brazil); Guarise, Gustavo [Departamento de Física, UNESP – Universidade Estadual Paulista, Av. 24A, 1515, Bela Vista, 13506-900, Rio Claro, SP (Brazil); Medrano-T, Rene O. [Departamento de Ciências Exatas e da Terra, UNIFESP – Universidade Federal de São Paulo, Rua São Nicolau, 210, Centro, 09913-030, Diadema, SP (Brazil); Department of Mathematics, Imperial College London, London SW7 2AZ (United Kingdom); Leonel, Edson D. [Departamento de Física, UNESP – Universidade Estadual Paulista, Av. 24A, 1515, Bela Vista, 13506-900, Rio Claro, SP (Brazil); Abdus Salam International Center for Theoretical Physics, Strada Costiera 11, 34151 Trieste (Italy)

2016-04-22

We show that extreme orbits, trajectories that connect local maximum and minimum values of one dimensional maps, play a major role in the parameter space of dissipative systems dictating the organization for the windows of periodicity, hence producing sets of shrimp-like structures. Here we solve three fundamental problems regarding the distribution of these sets and give: (i) their precise localization in the parameter space, even for sets of very high periods; (ii) their local and global distributions along cascades; and (iii) the association of these cascades to complicate sets of periodicity. The extreme orbits are proved to be a powerful indicator to investigate the organization of windows of periodicity in parameter planes. As applications of the theory, we obtain some results for the circle map and perturbed logistic map. The formalism presented here can be extended to many other different nonlinear and dissipative systems. - Highlights: • Extreme orbits and the organization of periodic regions in parameter space. • One-dimensional dissipative mappings. • The circle map and also a time perturbed logistic map were studied.

The role of extreme orbits in the global organization of periodic regions in parameter space for one dimensional maps

International Nuclear Information System (INIS)

Costa, Diogo Ricardo da; Hansen, Matheus; Guarise, Gustavo; Medrano-T, Rene O.; Leonel, Edson D.

2016-01-01

We show that extreme orbits, trajectories that connect local maximum and minimum values of one dimensional maps, play a major role in the parameter space of dissipative systems dictating the organization for the windows of periodicity, hence producing sets of shrimp-like structures. Here we solve three fundamental problems regarding the distribution of these sets and give: (i) their precise localization in the parameter space, even for sets of very high periods; (ii) their local and global distributions along cascades; and (iii) the association of these cascades to complicate sets of periodicity. The extreme orbits are proved to be a powerful indicator to investigate the organization of windows of periodicity in parameter planes. As applications of the theory, we obtain some results for the circle map and perturbed logistic map. The formalism presented here can be extended to many other different nonlinear and dissipative systems. - Highlights: • Extreme orbits and the organization of periodic regions in parameter space. • One-dimensional dissipative mappings. • The circle map and also a time perturbed logistic map were studied.

High-resolution Self-Organizing Maps for advanced visualization and dimension reduction.

Science.gov (United States)

Saraswati, Ayu; Nguyen, Van Tuc; Hagenbuchner, Markus; Tsoi, Ah Chung

2018-05-04

Kohonen's Self Organizing feature Map (SOM) provides an effective way to project high dimensional input features onto a low dimensional display space while preserving the topological relationships among the input features. Recent advances in algorithms that take advantages of modern computing hardware introduced the concept of high resolution SOMs (HRSOMs). This paper investigates the capabilities and applicability of the HRSOM as a visualization tool for cluster analysis and its suitabilities to serve as a pre-processor in ensemble learning models. The evaluation is conducted on a number of established benchmarks and real-world learning problems, namely, the policeman benchmark, two web spam detection problems, a network intrusion detection problem, and a malware detection problem. It is found that the visualization resulted from an HRSOM provides new insights concerning these learning problems. It is furthermore shown empirically that broad benefits from the use of HRSOMs in both clustering and classification problems can be expected. Copyright © 2018 Elsevier Ltd. All rights reserved.

3-dimensional interactive space (3DIS)

International Nuclear Information System (INIS)

Veitch, S.; Veitch, J.; West, S.J.

1991-01-01

This paper reports on the 3DIS security system which uses standard CCTV cameras to create 3-Dimensional detection zones around valuable assets within protected areas. An intrusion into a zone changes light values and triggers an alarm that is annunciated, while images from multiple cameras are recorded. 3DIS lowers nuisance alarm rates and provides superior automated surveillance capability. Performance is improved over 2-D systems because activity around, above or below the zone does to cause an alarm. Invisible 3-D zones protect assets as small as a pin or as large as a 747 jetliner. Detection zones are created by excising subspaces from the overlapping fields of view of two or more video cameras. Hundred of zones may co-exist, operating simultaneously. Intrusion into any 3-D zone will cause a coincidental change in light values, triggering an alarm specific to that space

High-Dimensional Quantum Information Processing with Linear Optics

Science.gov (United States)

Fitzpatrick, Casey A.

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

Modeling Dispersion of Chemical-Biological Agents in Three Dimensional Living Space

International Nuclear Information System (INIS)

William S. Winters

2002-01-01

This report documents a series of calculations designed to demonstrate Sandia's capability in modeling the dispersal of chemical and biological agents in complex three-dimensional spaces. The transport of particles representing biological agents is modeled in a single room and in several connected rooms. The influence of particle size, particle weight and injection method are studied

Eigenmodes of three-dimensional spherical spaces and their application to cosmology

International Nuclear Information System (INIS)

Lehoucq, Roland; Weeks, Jeffrey; Uzan, Jean-Philippe; Gausmann, Evelise; Luminet, Jean-Pierre

2002-01-01

This paper investigates the computation of the eigenmodes of the Laplacian operator in multi-connected three-dimensional spherical spaces. General mathematical results and analytical solutions for lens and prism spaces are presented. Three complementary numerical methods are developed and compared with our analytic results and previous investigations. The cosmological applications of these results are discussed, focusing on the cosmic microwave background (CMB) anisotropies. In particular, whereas in the Euclidean case too-small universes are excluded by present CMB data, in the spherical case, candidate topologies will always exist even if the total energy density parameter of the universe is very close to unity

Eigenmodes of three-dimensional spherical spaces and their application to cosmology

Energy Technology Data Exchange (ETDEWEB)

Lehoucq, Roland [CE-Saclay, DSM/DAPNIA/Service d' Astrophysique, F-91191 Gif sur Yvette (France); Weeks, Jeffrey [15 Farmer St, Canton, NY 13617-1120 (United States); Uzan, Jean-Philippe [Institut d' Astrophysique de Paris, GReCO, CNRS-FRE 2435, 98 bis, Bd Arago, 75014 Paris (France); Gausmann, Evelise [Instituto de Fisica Teorica, Rua Pamplona, 145 Bela Vista - Sao Paulo - SP, CEP 01405-900 (Brazil); Luminet, Jean-Pierre [Laboratoire Univers et Theories, CNRS-FRE 2462, Observatoire de Paris, F-92195 Meudon (France)

2002-09-21

This paper investigates the computation of the eigenmodes of the Laplacian operator in multi-connected three-dimensional spherical spaces. General mathematical results and analytical solutions for lens and prism spaces are presented. Three complementary numerical methods are developed and compared with our analytic results and previous investigations. The cosmological applications of these results are discussed, focusing on the cosmic microwave background (CMB) anisotropies. In particular, whereas in the Euclidean case too-small universes are excluded by present CMB data, in the spherical case, candidate topologies will always exist even if the total energy density parameter of the universe is very close to unity.

Application and optimization of input parameter spaces in mass flow modelling: a case study with r.randomwalk and r.ranger

Science.gov (United States)

Krenn, Julia; Zangerl, Christian; Mergili, Martin

2017-04-01

r.randomwalk is a GIS-based, multi-functional, conceptual open source model application for forward and backward analyses of the propagation of mass flows. It relies on a set of empirically derived, uncertain input parameters. In contrast to many other tools, r.randomwalk accepts input parameter ranges (or, in case of two or more parameters, spaces) in order to directly account for these uncertainties. Parameter spaces represent a possibility to withdraw from discrete input values which in most cases are likely to be off target. r.randomwalk automatically performs multiple calculations with various parameter combinations in a given parameter space, resulting in the impact indicator index (III) which denotes the fraction of parameter value combinations predicting an impact on a given pixel. Still, there is a need to constrain the parameter space used for a certain process type or magnitude prior to performing forward calculations. This can be done by optimizing the parameter space in terms of bringing the model results in line with well-documented past events. As most existing parameter optimization algorithms are designed for discrete values rather than for ranges or spaces, the necessity for a new and innovative technique arises. The present study aims at developing such a technique and at applying it to derive guiding parameter spaces for the forward calculation of rock avalanches through back-calculation of multiple events. In order to automatize the work flow we have designed r.ranger, an optimization and sensitivity analysis tool for parameter spaces which can be directly coupled to r.randomwalk. With r.ranger we apply a nested approach where the total value range of each parameter is divided into various levels of subranges. All possible combinations of subranges of all parameters are tested for the performance of the associated pattern of III. Performance indicators are the area under the ROC curve (AUROC) and the factor of conservativeness (FoC). This

Room Scanner representation and measurement of three-dimensional spaces using a smartphone

International Nuclear Information System (INIS)

Bejarano Rodriguez, Mauricio

2013-01-01

An algorithm was designed to measure and represent three-dimensional spaces using the resources available on a smartphone. The implementation of the fusion sensor has enabled to use basic trigonometry to calculate the lengths of the walls and the corners of the room. The OpenGL library was used to create and visualize the three-dimensional model of the measured internal space. A library was created to export the represented model to other commercial formats. A certain level of degradation is obtained once an attempt is made to measure long distances because the algorithm depends on the degree of inclination of the smarthphone to perform the measurements. For this reason, at higher elevations are obtained more accurate measurements. The capture process was changed in order to correct the margin of error to measure soccer field. The algorithm has recorded measurements less than 3% margin of error through the process of subdividing the measurement area. (author) [es

LABAN-PEL: a two-dimensional, multigroup diffusion, high-order response matrix code

International Nuclear Information System (INIS)

Mueller, E.Z.

1991-06-01

The capabilities of LABAN-PEL is described. LABAN-PEL is a modified version of the two-dimensional, high-order response matrix code, LABAN, written by Lindahl. The new version extends the capabilities of the original code with regard to the treatment of neutron migration by including an option to utilize full group-to-group diffusion coefficient matrices. In addition, the code has been converted from single to double precision and the necessary routines added to activate its multigroup capability. The coding has also been converted to standard FORTRAN-77 to enhance the portability of the code. Details regarding the input data requirements and calculational options of LABAN-PEL are provided. 13 refs

Nonlinear dynamics of the magnetosphere and space weather

Science.gov (United States)

Sharma, A. Surjalal

1996-01-01

The solar wind-magnetosphere system exhibits coherence on the global scale and such behavior can arise from nonlinearity on the dynamics. The observational time series data were used together with phase space reconstruction techniques to analyze the magnetospheric dynamics. Analysis of the solar wind, auroral electrojet and Dst indices showed low dimensionality of the dynamics and accurate prediction can be made with an input/output model. The predictability of the magnetosphere in spite of the apparent complexity arises from its dynamical synchronism with the solar wind. The electrodynamic coupling between different regions of the magnetosphere yields its coherent, low dimensional behavior. The data from multiple satellites and ground stations can be used to develop a spatio-temporal model that identifies the coupling between different regions. These nonlinear dynamical models provide space weather forecasting capabilities.

Faster exact algorithms for computing Steiner trees in higher dimensional Euclidean spaces

DEFF Research Database (Denmark)

Fonseca, Rasmus; Brazil, Marcus; Winter, Pawel

The Euclidean Steiner tree problem asks for a network of minimum total length interconnecting a finite set of points in d-dimensional space. For d ≥ 3, only one practical algorithmic approach exists for this problem --- proposed by Smith in 1992. A number of refinements of Smith's algorithm have...

Ergodic channel capacity of spatial correlated multiple-input multiple-output free space optical links using multipulse pulse-position modulation

Science.gov (United States)

Wang, Huiqin; Wang, Xue; Cao, Minghua

2017-02-01

The spatial correlation extensively exists in the multiple-input multiple-output (MIMO) free space optical (FSO) communication systems due to the channel fading and the antenna space limitation. Wilkinson's method was utilized to investigate the impact of spatial correlation on the MIMO FSO communication system employing multipulse pulse-position modulation. Simulation results show that the existence of spatial correlation reduces the ergodic channel capacity, and the reception diversity is more competent to resist this kind of performance degradation.

Dynamics of a neuron model in different two-dimensional parameter-spaces

International Nuclear Information System (INIS)

Rech, Paulo C.

2011-01-01

We report some two-dimensional parameter-space diagrams numerically obtained for the multi-parameter Hindmarsh-Rose neuron model. Several different parameter planes are considered, and we show that regardless of the combination of parameters, a typical scenario is preserved: for all choice of two parameters, the parameter-space presents a comb-shaped chaotic region immersed in a large periodic region. We also show that exist regions close these chaotic region, separated by the comb teeth, organized themselves in period-adding bifurcation cascades. - Research highlights: → We report parameter-spaces obtained for the Hindmarsh-Rose neuron model. → Regardless of the combination of parameters, a typical scenario is preserved. → The scenario presents a comb-shaped chaotic region immersed in a periodic region. → Periodic regions near the chaotic region are in period-adding bifurcation cascades.

On spinless null propagation in five-dimensional space-times with approximate space-like Killing symmetry

Energy Technology Data Exchange (ETDEWEB)

Breban, Romulus [Institut Pasteur, Paris Cedex 15 (France)

2016-09-15

Five-dimensional (5D) space-time symmetry greatly facilitates how a 4D observer perceives the propagation of a single spinless particle in a 5D space-time. In particular, if the 5D geometry is independent of the fifth coordinate then the 5D physics may be interpreted as 4D quantum mechanics. In this work we address the case where the symmetry is approximate, focusing on the case where the 5D geometry depends weakly on the fifth coordinate. We show that concepts developed for the case of exact symmetry approximately hold when other concepts such as decaying quantum states, resonant quantum scattering, and Stokes drag are adopted, as well. We briefly comment on the optical model of the nuclear interactions and Millikan's oil drop experiment. (orig.)

Pair production of Dirac particles in a d + 1-dimensional noncommutative space-time

Energy Technology Data Exchange (ETDEWEB)

Ousmane Samary, Dine [Perimeter Institute for Theoretical Physics, Waterloo, ON (Canada); University of Abomey-Calavi, International Chair in Mathematical Physics and Applications (ICMPA-UNESCO Chair), Cotonou (Benin); N' Dolo, Emanonfi Elias; Hounkonnou, Mahouton Norbert [University of Abomey-Calavi, International Chair in Mathematical Physics and Applications (ICMPA-UNESCO Chair), Cotonou (Benin)

2014-11-15

This work addresses the computation of the probability of fermionic particle pair production in d + 1-dimensional noncommutative Moyal space. Using Seiberg-Witten maps, which establish relations between noncommutative and commutative field variables, up to the first order in the noncommutative parameter θ, we derive the probability density of vacuum-vacuum pair production of Dirac particles. The cases of constant electromagnetic, alternating time-dependent, and space-dependent electric fields are considered and discussed. (orig.)

Cooperative simulation of lithography and topography for three-dimensional high-aspect-ratio etching

Science.gov (United States)

Ichikawa, Takashi; Yagisawa, Takashi; Furukawa, Shinichi; Taguchi, Takafumi; Nojima, Shigeki; Murakami, Sadatoshi; Tamaoki, Naoki

2018-06-01

A topography simulation of high-aspect-ratio etching considering transports of ions and neutrals is performed, and the mechanism of reactive ion etching (RIE) residues in three-dimensional corner patterns is revealed. Limited ion flux and CF2 diffusion from the wide space of the corner is found to have an effect on the RIE residues. Cooperative simulation of lithography and topography is used to solve the RIE residue problem.

High-dimensional change-point estimation: Combining filtering with convex optimization

OpenAIRE

Soh, Yong Sheng; Chandrasekaran, Venkat

2017-01-01

We consider change-point estimation in a sequence of high-dimensional signals given noisy observations. Classical approaches to this problem such as the filtered derivative method are useful for sequences of scalar-valued signals, but they have undesirable scaling behavior in the high-dimensional setting. However, many high-dimensional signals encountered in practice frequently possess latent low-dimensional structure. Motivated by this observation, we propose a technique for high-dimensional...

Irreducible quantum group modules with finite dimensional weight spaces

DEFF Research Database (Denmark)

Pedersen, Dennis Hasselstrøm

a finitely generated U q -module which has finite dimensional weight spaces and is a sum of those. Our approach follows the procedures used by S. Fernando and O. Mathieu to solve the corresponding problem for semisimple complex Lie algebra modules. To achieve this we have to overcome a number of obstacles...... not present in the classical case. In the process we also construct twisting functors rigerously for quantum group modules, study twisted Verma modules and show that these admit a Jantzen filtration with corresponding Jantzen sum formula....

Modeling and simulation of high dimensional stochastic multiscale PDE systems at the exascale

Energy Technology Data Exchange (ETDEWEB)

Zabaras, Nicolas J. [Cornell Univ., Ithaca, NY (United States)

2016-11-08

Predictive Modeling of multiscale and Multiphysics systems requires accurate data driven characterization of the input uncertainties, and understanding of how they propagate across scales and alter the final solution. This project develops a rigorous mathematical framework and scalable uncertainty quantification algorithms to efficiently construct realistic low dimensional input models, and surrogate low complexity systems for the analysis, design, and control of physical systems represented by multiscale stochastic PDEs. The work can be applied to many areas including physical and biological processes, from climate modeling to systems biology.

Three-dimensional labeling program for elucidation of the geometric properties of biological particles in three-dimensional space.

Science.gov (United States)

Nomura, A; Yamazaki, Y; Tsuji, T; Kawasaki, Y; Tanaka, S

1996-09-15

For all biological particles such as cells or cellular organelles, there are three-dimensional coordinates representing the centroid or center of gravity. These coordinates and other numerical parameters such as volume, fluorescence intensity, surface area, and shape are referred to in this paper as geometric properties, which may provide critical information for the clarification of in situ mechanisms of molecular and cellular functions in living organisms. We have established a method for the elucidation of these properties, designated the three-dimensional labeling program (3DLP). Algorithms of 3DLP are so simple that this method can be carried out through the use of software combinations in image analysis on a personal computer. To evaluate 3DLP, it was applied to a 32-cell-stage sea urchin embryo, double stained with FITC for cellular protein of blastomeres and propidium iodide for nuclear DNA. A stack of optical serial section images was obtained by confocal laser scanning microscopy. The method was found effective for determining geometric properties and should prove applicable to the study of many different kinds of biological particles in three-dimensional space.

Three-body problem in d-dimensional space: Ground state, (quasi)-exact-solvability

Science.gov (United States)

Turbiner, Alexander V.; Miller, Willard; Escobar-Ruiz, M. A.

2018-02-01

As a straightforward generalization and extension of our previous paper [A. V. Turbiner et al., "Three-body problem in 3D space: Ground state, (quasi)-exact-solvability," J. Phys. A: Math. Theor. 50, 215201 (2017)], we study the aspects of the quantum and classical dynamics of a 3-body system with equal masses, each body with d degrees of freedom, with interaction depending only on mutual (relative) distances. The study is restricted to solutions in the space of relative motion which are functions of mutual (relative) distances only. It is shown that the ground state (and some other states) in the quantum case and the planar trajectories (which are in the interaction plane) in the classical case are of this type. The quantum (and classical) Hamiltonian for which these states are eigenfunctions is derived. It corresponds to a three-dimensional quantum particle moving in a curved space with special d-dimension-independent metric in a certain d-dependent singular potential, while at d = 1, it elegantly degenerates to a two-dimensional particle moving in flat space. It admits a description in terms of pure geometrical characteristics of the interaction triangle which is defined by the three relative distances. The kinetic energy of the system is d-independent; it has a hidden sl(4, R) Lie (Poisson) algebra structure, alternatively, the hidden algebra h(3) typical for the H3 Calogero model as in the d = 3 case. We find an exactly solvable three-body S3-permutationally invariant, generalized harmonic oscillator-type potential as well as a quasi-exactly solvable three-body sextic polynomial type potential with singular terms. For both models, an extra first order integral exists. For d = 1, the whole family of 3-body (two-dimensional) Calogero-Moser-Sutherland systems as well as the Tremblay-Turbiner-Winternitz model is reproduced. It is shown that a straightforward generalization of the 3-body (rational) Calogero model to d > 1 leads to two primitive quasi

Execution spaces for simple higher dimensional automata

DEFF Research Database (Denmark)

Raussen, Martin

Higher Dimensional Automata (HDA) are highly expressive models for concurrency in Computer Science, cf van Glabbeek [26]. For a topologist, they are attractive since they can be modeled as cubical complexes - with an inbuilt restriction for directions´of allowable (d-)paths. In Raussen [25], we...

Filaments of Meaning in Word Space

OpenAIRE

Karlgren, Jussi; Holst, Anders; Sahlgren, Magnus

2008-01-01

Word space models, in the sense of vector space models built on distributional data taken from texts, are used to model semantic relations between words. We argue that the high dimensionality of typical vector space models lead to unintuitive effects on modeling likeness of meaning and that the local structure of word spaces is where interesting semantic relations reside. We show that the local structure of word spaces has substantially different dimensionality and character than the global s...

Multivariate statistics high-dimensional and large-sample approximations

CERN Document Server

Fujikoshi, Yasunori; Shimizu, Ryoichi

2010-01-01

A comprehensive examination of high-dimensional analysis of multivariate methods and their real-world applications Multivariate Statistics: High-Dimensional and Large-Sample Approximations is the first book of its kind to explore how classical multivariate methods can be revised and used in place of conventional statistical tools. Written by prominent researchers in the field, the book focuses on high-dimensional and large-scale approximations and details the many basic multivariate methods used to achieve high levels of accuracy. The authors begin with a fundamental presentation of the basic

High dimensional neurocomputing growth, appraisal and applications

CERN Document Server

Tripathi, Bipin Kumar

2015-01-01

The book presents a coherent understanding of computational intelligence from the perspective of what is known as "intelligent computing" with high-dimensional parameters. It critically discusses the central issue of high-dimensional neurocomputing, such as quantitative representation of signals, extending the dimensionality of neuron, supervised and unsupervised learning and design of higher order neurons. The strong point of the book is its clarity and ability of the underlying theory to unify our understanding of high-dimensional computing where conventional methods fail. The plenty of application oriented problems are presented for evaluating, monitoring and maintaining the stability of adaptive learning machine. Author has taken care to cover the breadth and depth of the subject, both in the qualitative as well as quantitative way. The book is intended to enlighten the scientific community, ranging from advanced undergraduates to engineers, scientists and seasoned researchers in computational intelligenc...

Quantifying multi-dimensional functional trait spaces of trees: empirical versus theoretical approaches

Science.gov (United States)

Ogle, K.; Fell, M.; Barber, J. J.

2016-12-01

Empirical, field studies of plant functional traits have revealed important trade-offs among pairs or triplets of traits, such as the leaf (LES) and wood (WES) economics spectra. Trade-offs include correlations between leaf longevity (LL) vs specific leaf area (SLA), LL vs mass-specific leaf respiration rate (RmL), SLA vs RmL, and resistance to breakage vs wood density. Ordination analyses (e.g., PCA) show groupings of traits that tend to align with different life-history strategies or taxonomic groups. It is unclear, however, what underlies such trade-offs and emergent spectra. Do they arise from inherent physiological constraints on growth, or are they more reflective of environmental filtering? The relative importance of these mechanisms has implications for predicting biogeochemical cycling, which is influenced by trait distributions of the plant community. We address this question using an individual-based model of tree growth (ACGCA) to quantify the theoretical trait space of trees that emerges from physiological constraints. ACGCA's inputs include 32 physiological, anatomical, and allometric traits, many of which are related to the LES and WES. We fit ACGCA to 1.6 million USFS FIA observations of tree diameters and heights to obtain vectors of trait values that produce realistic growth, and we explored the structure of this trait space. No notable correlations emerged among the 496 trait pairs, but stepwise regressions revealed complicated multi-variate structure: e.g., relationships between pairs of traits (e.g., RmL and SLA) are governed by other traits (e.g., LL, radiation-use efficiency [RUE]). We also simulated growth under various canopy gap scenarios that impose varying degrees of environmental filtering to explore the multi-dimensional trait space (hypervolume) of trees that died vs survived. The centroid and volume of the hypervolumes differed among dead and live trees, especially under gap conditions leading to low mortality. Traits most predictive

Superintegrability in two-dimensional Euclidean space and associated polynomial solutions

International Nuclear Information System (INIS)

Kalnins, E.G.; Miller, W. Jr; Pogosyan, G.S.

1996-01-01

In this work we examine the basis functions for those classical and quantum mechanical systems in two dimensions which admit separation of variables in at least two coordinate systems. We do this for the corresponding systems defined in Euclidean space and on the two dimensional sphere. We present all of these cases from a unified point of view. In particular, all of the spectral functions that arise via variable separation have their essential features expressed in terms of their zeros. The principal new results are the details of the polynomial base for each of the nonsubgroup base, not just the subgroup cartesian and polar coordinate case, and the details of the structure of the quadratic algebras. We also study the polynomial eigenfunctions in elliptic coordinates of the N-dimensional isotropic quantum oscillator. 28 refs., 1 tab

Multiple-canister flow and transport code in 2-dimensional space. MCFT2D: user's manual

International Nuclear Information System (INIS)

Lim, Doo-Hyun

2006-03-01

A two-dimensional numerical code, MCFT2D (Multiple-Canister Flow and Transport code in 2-Dimensional space), has been developed for groundwater flow and radionuclide transport analyses in a water-saturated high-level radioactive waste (HLW) repository with multiple canisters. A multiple-canister configuration and a non-uniform flow field of the host rock are incorporated in the MCFT2D code. Effects of heterogeneous flow field of the host rock on migration of nuclides can be investigated using MCFT2D. The MCFT2D enables to take into account the various degrees of the dependency of canister configuration for nuclide migration in a water-saturated HLW repository, while the dependency was assumed to be either independent or perfectly dependent in previous studies. This report presents features of the MCFT2D code, numerical simulation using MCFT2D code, and graphical representation of the numerical results. (author)

Supplementary High-Input Impedance Voltage-Mode Universal Biquadratic Filter Using DVCCs

Directory of Open Access Journals (Sweden)

Jitendra Mohan

2012-01-01

Full Text Available To further extend the existing knowledge on voltage-mode universal biquadratic filter, in this paper, a new biquadratic filter circuit with single input and multiple outputs is proposed, employing three differential voltage current conveyors (DVCCs, three resistors, and two grounded capacitors. The proposed circuit realizes all the standard filter functions, that is, high-pass, band-pass, low-pass, notch, and all-pass filters simultaneously. The circuit enjoys the feature of high-input impedance, orthogonal control of resonance angular frequency (o, and quality factor (Q via grounded resistor and the use of grounded capacitors which is ideal for IC implementation.

Frequency Preference Response to Oscillatory Inputs in Two-dimensional Neural Models: A Geometric Approach to Subthreshold Amplitude and Phase Resonance.

Science.gov (United States)

Rotstein, Horacio G

2014-01-01

We investigate the dynamic mechanisms of generation of subthreshold and phase resonance in two-dimensional linear and linearized biophysical (conductance-based) models, and we extend our analysis to account for the effect of simple, but not necessarily weak, types of nonlinearities. Subthreshold resonance refers to the ability of neurons to exhibit a peak in their voltage amplitude response to oscillatory input currents at a preferred non-zero (resonant) frequency. Phase-resonance refers to the ability of neurons to exhibit a zero-phase (or zero-phase-shift) response to oscillatory input currents at a non-zero (phase-resonant) frequency. We adapt the classical phase-plane analysis approach to account for the dynamic effects of oscillatory inputs and develop a tool, the envelope-plane diagrams, that captures the role that conductances and time scales play in amplifying the voltage response at the resonant frequency band as compared to smaller and larger frequencies. We use envelope-plane diagrams in our analysis. We explain why the resonance phenomena do not necessarily arise from the presence of imaginary eigenvalues at rest, but rather they emerge from the interplay of the intrinsic and input time scales. We further explain why an increase in the time-scale separation causes an amplification of the voltage response in addition to shifting the resonant and phase-resonant frequencies. This is of fundamental importance for neural models since neurons typically exhibit a strong separation of time scales. We extend this approach to explain the effects of nonlinearities on both resonance and phase-resonance. We demonstrate that nonlinearities in the voltage equation cause amplifications of the voltage response and shifts in the resonant and phase-resonant frequencies that are not predicted by the corresponding linearized model. The differences between the nonlinear response and the linear prediction increase with increasing levels of the time scale separation between

Research on the development of space target detecting system and three-dimensional reconstruction technology

Science.gov (United States)

Li, Dong; Wei, Zhen; Song, Dawei; Sun, Wenfeng; Fan, Xiaoyan

2016-11-01

With the development of space technology, the number of spacecrafts and debris are increasing year by year. The demand for detecting and identification of spacecraft is growing strongly, which provides support to the cataloguing, crash warning and protection of aerospace vehicles. The majority of existing approaches for three-dimensional reconstruction is scattering centres correlation, which is based on the radar high resolution range profile (HRRP). This paper proposes a novel method to reconstruct the threedimensional scattering centre structure of target from a sequence of radar ISAR images, which mainly consists of three steps. First is the azimuth scaling of consecutive ISAR images based on fractional Fourier transform (FrFT). The later is the extraction of scattering centres and matching between adjacent ISAR images using grid method. Finally, according to the coordinate matrix of scattering centres, the three-dimensional scattering centre structure is reconstructed using improved factorization method. The three-dimensional structure is featured with stable and intuitive characteristic, which provides a new way to improve the identification probability and reduce the complexity of the model matching library. A satellite model is reconstructed using the proposed method from four consecutive ISAR images. The simulation results prove that the method has gotten a satisfied consistency and accuracy.

Stargate GTM: Bridging Descriptor and Activity Spaces.

Science.gov (United States)

Gaspar, Héléna A; Baskin, Igor I; Marcou, Gilles; Horvath, Dragos; Varnek, Alexandre

2015-11-23

Predicting the activity profile of a molecule or discovering structures possessing a specific activity profile are two important goals in chemoinformatics, which could be achieved by bridging activity and molecular descriptor spaces. In this paper, we introduce the "Stargate" version of the Generative Topographic Mapping approach (S-GTM) in which two different multidimensional spaces (e.g., structural descriptor space and activity space) are linked through a common 2D latent space. In the S-GTM algorithm, the manifolds are trained simultaneously in two initial spaces using the probabilities in the 2D latent space calculated as a weighted geometric mean of probability distributions in both spaces. S-GTM has the following interesting features: (1) activities are involved during the training procedure; therefore, the method is supervised, unlike conventional GTM; (2) using molecular descriptors of a given compound as input, the model predicts a whole activity profile, and (3) using an activity profile as input, areas populated by relevant chemical structures can be detected. To assess the performance of S-GTM prediction models, a descriptor space (ISIDA descriptors) of a set of 1325 GPCR ligands was related to a B-dimensional (B = 1 or 8) activity space corresponding to pKi values for eight different targets. S-GTM outperforms conventional GTM for individual activities and performs similarly to the Lasso multitask learning algorithm, although it is still slightly less accurate than the Random Forest method.

Search of wormholes in different dimensional non-commutative inspired space-times with Lorentzian distribution

Energy Technology Data Exchange (ETDEWEB)

Bhar, Piyali; Rahaman, Farook [Jadavpur University, Department of Mathematics, Kolkata, West Bengal (India)

2014-12-01

In this paper we ask whether the wormhole solutions exist in different dimensional noncommutativity-inspired spacetimes. It is well known that the noncommutativity of the space is an outcome of string theory and it replaced the usual point-like object by a smeared object. Here we have chosen the Lorentzian distribution as the density function in the noncommutativity-inspired spacetime. We have observed that the wormhole solutions exist only in four and five dimensions; however, in higher than five dimensions no wormhole exists. For five dimensional spacetime, we get a wormhole for a restricted region. In the usual four dimensional spacetime, we get a stable wormhole which is asymptotically flat. (orig.)

Genetic algorithm based input selection for a neural network function approximator with applications to SSME health monitoring

Science.gov (United States)

Peck, Charles C.; Dhawan, Atam P.; Meyer, Claudia M.

1991-01-01

A genetic algorithm is used to select the inputs to a neural network function approximator. In the application considered, modeling critical parameters of the space shuttle main engine (SSME), the functional relationship between measured parameters is unknown and complex. Furthermore, the number of possible input parameters is quite large. Many approaches have been used for input selection, but they are either subjective or do not consider the complex multivariate relationships between parameters. Due to the optimization and space searching capabilities of genetic algorithms they were employed to systematize the input selection process. The results suggest that the genetic algorithm can generate parameter lists of high quality without the explicit use of problem domain knowledge. Suggestions for improving the performance of the input selection process are also provided.

Horizontal biases in rats’ use of three-dimensional space

Science.gov (United States)

Jovalekic, Aleksandar; Hayman, Robin; Becares, Natalia; Reid, Harry; Thomas, George; Wilson, Jonathan; Jeffery, Kate

2011-01-01

Rodent spatial cognition studies allow links to be made between neural and behavioural phenomena, and much is now known about the encoding and use of horizontal space. However, the real world is three dimensional, providing cognitive challenges that have yet to be explored. Motivated by neural findings suggesting weaker encoding of vertical than horizontal space, we examined whether rats show a similar behavioural anisotropy when distributing their time freely between vertical and horizontal movements. We found that in two- or three-dimensional environments with a vertical dimension, rats showed a prioritization of horizontal over vertical movements in both foraging and detour tasks. In the foraging tasks, the animals executed more horizontal than vertical movements and adopted a “layer strategy” in which food was collected from one horizontal level before moving to the next. In the detour tasks, rats preferred the routes that allowed them to execute the horizontal leg first. We suggest three possible reasons for this behavioural bias. First, as suggested by Grobety and Schenk [5], it allows minimisation of energy expenditure, inasmuch as costly vertical movements are minimised. Second, it may be a manifestation of the temporal discounting of effort, in which animals value delayed effort as less costly than immediate effort. Finally, it may be that at the neural level rats encode the vertical dimension less precisely, and thus prefer to bias their movements in the more accurately encoded horizontal dimension. We suggest that all three factors are related, and all play a part. PMID:21419172

A High Fidelity Approach to Data Simulation for Space Situational Awareness Missions

Science.gov (United States)

Hagerty, S.; Ellis, H., Jr.

2016-09-01

Space Situational Awareness (SSA) is vital to maintaining our Space Superiority. A high fidelity, time-based simulation tool, PROXOR™ (Proximity Operations and Rendering), supports SSA by generating realistic mission scenarios including sensor frame data with corresponding truth. This is a unique and critical tool for supporting mission architecture studies, new capability (algorithm) development, current/future capability performance analysis, and mission performance prediction. PROXOR™ provides a flexible architecture for sensor and resident space object (RSO) orbital motion and attitude control that simulates SSA, rendezvous and proximity operations scenarios. The major elements of interest are based on the ability to accurately simulate all aspects of the RSO model, viewing geometry, imaging optics, sensor detector, and environmental conditions. These capabilities enhance the realism of mission scenario models and generated mission image data. As an input, PROXOR™ uses a library of 3-D satellite models containing 10+ satellites, including low-earth orbit (e.g., DMSP) and geostationary (e.g., Intelsat) spacecraft, where the spacecraft surface properties are those of actual materials and include Phong and Maxwell-Beard bidirectional reflectance distribution function (BRDF) coefficients for accurate radiometric modeling. We calculate the inertial attitude, the changing solar and Earth illumination angles of the satellite, and the viewing angles from the sensor as we propagate the RSO in its orbit. The synthetic satellite image is rendered at high resolution and aggregated to the focal plane resolution resulting in accurate radiometry even when the RSO is a point source. The sensor model includes optical effects from the imaging system [point spread function (PSF) includes aberrations, obscurations, support structures, defocus], detector effects (CCD blooming, left/right bias, fixed pattern noise, image persistence, shot noise, read noise, and quantization

Unconscious integration of multisensory bodily inputs in the peripersonal space shapes bodily self-consciousness.

Science.gov (United States)

Salomon, Roy; Noel, Jean-Paul; Łukowska, Marta; Faivre, Nathan; Metzinger, Thomas; Serino, Andrea; Blanke, Olaf

2017-09-01

Recent studies have highlighted the role of multisensory integration as a key mechanism of self-consciousness. In particular, integration of bodily signals within the peripersonal space (PPS) underlies the experience of the self in a body we own (self-identification) and that is experienced as occupying a specific location in space (self-location), two main components of bodily self-consciousness (BSC). Experiments investigating the effects of multisensory integration on BSC have typically employed supra-threshold sensory stimuli, neglecting the role of unconscious sensory signals in BSC, as tested in other consciousness research. Here, we used psychophysical techniques to test whether multisensory integration of bodily stimuli underlying BSC also occurs for multisensory inputs presented below the threshold of conscious perception. Our results indicate that visual stimuli rendered invisible through continuous flash suppression boost processing of tactile stimuli on the body (Exp. 1), and enhance the perception of near-threshold tactile stimuli (Exp. 2), only once they entered PPS. We then employed unconscious multisensory stimulation to manipulate BSC. Participants were presented with tactile stimulation on their body and with visual stimuli on a virtual body, seen at a distance, which were either visible or rendered invisible. We found that participants reported higher self-identification with the virtual body in the synchronous visuo-tactile stimulation (as compared to asynchronous stimulation; Exp. 3), and shifted their self-location toward the virtual body (Exp.4), even if stimuli were fully invisible. Our results indicate that multisensory inputs, even outside of awareness, are integrated and affect the phenomenological content of self-consciousness, grounding BSC firmly in the field of psychophysical consciousness studies. Copyright © 2017 Elsevier B.V. All rights reserved.

DataHigh: graphical user interface for visualizing and interacting with high-dimensional neural activity

Science.gov (United States)

Cowley, Benjamin R.; Kaufman, Matthew T.; Butler, Zachary S.; Churchland, Mark M.; Ryu, Stephen I.; Shenoy, Krishna V.; Yu, Byron M.

2013-12-01

Objective. Analyzing and interpreting the activity of a heterogeneous population of neurons can be challenging, especially as the number of neurons, experimental trials, and experimental conditions increases. One approach is to extract a set of latent variables that succinctly captures the prominent co-fluctuation patterns across the neural population. A key problem is that the number of latent variables needed to adequately describe the population activity is often greater than 3, thereby preventing direct visualization of the latent space. By visualizing a small number of 2-d projections of the latent space or each latent variable individually, it is easy to miss salient features of the population activity. Approach. To address this limitation, we developed a Matlab graphical user interface (called DataHigh) that allows the user to quickly and smoothly navigate through a continuum of different 2-d projections of the latent space. We also implemented a suite of additional visualization tools (including playing out population activity timecourses as a movie and displaying summary statistics, such as covariance ellipses and average timecourses) and an optional tool for performing dimensionality reduction. Main results. To demonstrate the utility and versatility of DataHigh, we used it to analyze single-trial spike count and single-trial timecourse population activity recorded using a multi-electrode array, as well as trial-averaged population activity recorded using single electrodes. Significance. DataHigh was developed to fulfil a need for visualization in exploratory neural data analysis, which can provide intuition that is critical for building scientific hypotheses and models of population activity.

DataHigh: graphical user interface for visualizing and interacting with high-dimensional neural activity.

Science.gov (United States)

Cowley, Benjamin R; Kaufman, Matthew T; Butler, Zachary S; Churchland, Mark M; Ryu, Stephen I; Shenoy, Krishna V; Yu, Byron M

2013-12-01

Analyzing and interpreting the activity of a heterogeneous population of neurons can be challenging, especially as the number of neurons, experimental trials, and experimental conditions increases. One approach is to extract a set of latent variables that succinctly captures the prominent co-fluctuation patterns across the neural population. A key problem is that the number of latent variables needed to adequately describe the population activity is often greater than 3, thereby preventing direct visualization of the latent space. By visualizing a small number of 2-d projections of the latent space or each latent variable individually, it is easy to miss salient features of the population activity. To address this limitation, we developed a Matlab graphical user interface (called DataHigh) that allows the user to quickly and smoothly navigate through a continuum of different 2-d projections of the latent space. We also implemented a suite of additional visualization tools (including playing out population activity timecourses as a movie and displaying summary statistics, such as covariance ellipses and average timecourses) and an optional tool for performing dimensionality reduction. To demonstrate the utility and versatility of DataHigh, we used it to analyze single-trial spike count and single-trial timecourse population activity recorded using a multi-electrode array, as well as trial-averaged population activity recorded using single electrodes. DataHigh was developed to fulfil a need for visualization in exploratory neural data analysis, which can provide intuition that is critical for building scientific hypotheses and models of population activity.

DataHigh: Graphical user interface for visualizing and interacting with high-dimensional neural activity

Science.gov (United States)

Cowley, Benjamin R.; Kaufman, Matthew T.; Butler, Zachary S.; Churchland, Mark M.; Ryu, Stephen I.; Shenoy, Krishna V.; Yu, Byron M.

2014-01-01

Objective Analyzing and interpreting the activity of a heterogeneous population of neurons can be challenging, especially as the number of neurons, experimental trials, and experimental conditions increases. One approach is to extract a set of latent variables that succinctly captures the prominent co-fluctuation patterns across the neural population. A key problem is that the number of latent variables needed to adequately describe the population activity is often greater than three, thereby preventing direct visualization of the latent space. By visualizing a small number of 2-d projections of the latent space or each latent variable individually, it is easy to miss salient features of the population activity. Approach To address this limitation, we developed a Matlab graphical user interface (called DataHigh) that allows the user to quickly and smoothly navigate through a continuum of different 2-d projections of the latent space. We also implemented a suite of additional visualization tools (including playing out population activity timecourses as a movie and displaying summary statistics, such as covariance ellipses and average timecourses) and an optional tool for performing dimensionality reduction. Main results To demonstrate the utility and versatility of DataHigh, we used it to analyze single-trial spike count and single-trial timecourse population activity recorded using a multi-electrode array, as well as trial-averaged population activity recorded using single electrodes. Significance DataHigh was developed to fulfill a need for visualization in exploratory neural data analysis, which can provide intuition that is critical for building scientific hypotheses and models of population activity. PMID:24216250

Self-Structured Organizing Single-Input CMAC Control for Robot Manipulator

Directory of Open Access Journals (Sweden)

ThanhQuyen Ngo

2011-09-01

Full Text Available This paper represents a self-structured organizing single-input control system based on differentiable cerebellar model articulation controller (CMAC for an n-link robot manipulator to achieve the high-precision position tracking. In the proposed scheme, the single-input CMAC controller is solely used to control the plant, so the input space dimension of CMAC can be simplified and no conventional controller is needed. The structure of single-input CMAC will also be self-organized; that is, the layers of single-input CMAC will grow or prune systematically and their receptive functions can be automatically adjusted. The online tuning laws of single-input CMAC parameters are derived in gradient-descent learning method and the discrete-type Lyapunov function is applied to determine the learning rates of proposed control system so that the stability of the system can be guaranteed. The simulation results of robot manipulator are provided to verify the effectiveness of the proposed control methodology.

High Temperature Test Facility Preliminary RELAP5-3D Input Model Description

Energy Technology Data Exchange (ETDEWEB)

Bayless, Paul David [Idaho National Lab. (INL), Idaho Falls, ID (United States)

2015-12-01

A RELAP5-3D input model is being developed for the High Temperature Test Facility at Oregon State University. The current model is described in detail. Further refinements will be made to the model as final as-built drawings are released and when system characterization data are available for benchmarking the input model.

Workflow Optimization for Tuning Prostheses with High Input Channel

Science.gov (United States)

2017-10-01

of Specific Aim 1 by driving a commercially available two DoF wrist and single DoF hand. The high -level control system will provide analog signals...AWARD NUMBER: W81XWH-16-1-0767 TITLE: Workflow Optimization for Tuning Prostheses with High Input Channel PRINCIPAL INVESTIGATOR: Daniel Merrill...Unlimited The views, opinions and/or findings contained in this report are those of the author(s) and should not be construed as an official Department

Collapsing perfect fluid in self-similar five dimensional space-time and cosmic censorship

International Nuclear Information System (INIS)

Ghosh, S.G.; Sarwe, S.B.; Saraykar, R.V.

2002-01-01

We investigate the occurrence and nature of naked singularities in the gravitational collapse of a self-similar adiabatic perfect fluid in a five dimensional space-time. The naked singularities are found to be gravitationally strong in the sense of Tipler and thus violate the cosmic censorship conjecture

A non-Abelian SO(8) monopole as generalization of Dirac-Yang monopoles for a 9-dimensional space

International Nuclear Information System (INIS)

Le, Van-Hoang; Nguyen, Thanh-Son

2011-01-01

We establish an explicit form of a non-Abelian SO(8) monopole in a 9-dimensional space and show that it is indeed a direct generalization of Dirac and Yang monopoles. Using the generalized Hurwitz transformation, we have found a connection between a 16-dimensional harmonic oscillator and a 9-dimensional hydrogenlike atom in the field of the SO(8) monopole (MICZ-Kepler problem). Using the built connection the group of dynamical symmetry of the 9-dimensional MICZ-Kepler problem is found as SO(10, 2).

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

Science.gov (United States)

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

2018-05-01

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

High-T /SUB c/ Superconducting integrated circuit: a dc SQUID with input coil

International Nuclear Information System (INIS)

Di Iorio, M.S.; Beasley, M.R.

1985-01-01

We have fabricated a high transition temperature superconducting integrated circuit consisting of a dc SQUID and an input coupling coil. The purpose is to ascertain the generic problems associated with constructing a high-T /SUB c/ circuit as well as to fabricate a high performance dc SQUID. The superconductor used for both the SQUID and the input coil is Nb 3 Sn which must be deposited at 800 0 C. Importantly, the insulator separating SQUID and input coil maintains its integrity at this elevated temperature. A hole in the insulator permits contact to the innermost winding of the coil. This contact has been achieved without significant degradation of the superconductivity. Consequently, the device operates over a wide temperature range, from below 4.2 K to near T /SUB c/

Parametric analysis of diffuser requirements for high expansion ratio space engine

Science.gov (United States)

Wojciechowski, C. J.; Anderson, P. G.

1981-01-01

A supersonic diffuser ejector design computer program was developed. Using empirically modified one dimensional flow methods the diffuser ejector geometry is specified by the code. The design code results for calculations up to the end of the diffuser second throat were verified. Diffuser requirements for sea level testing of high expansion ratio space engines were defined. The feasibility of an ejector system using two commonly available turbojet engines feeding two variable area ratio ejectors was demonstrated.

Two-dimensional effects in the problem of tearing modes control by electron cyclotron current drive

International Nuclear Information System (INIS)

Comisso, L.; Lazzaro, E.

2010-01-01

The design of means to counteract robustly the classical and neoclassical tearing modes in a tokamak by localized injection of an external control current requires an ever growing understanding of the physical process, beyond the Rutherford-type zero-dimensional models. Here a set of extended magnetohydrodynamic nonlinear equations for four continuum fields is used to investigate the two-dimensional effects in the response of the reconnecting modes to specific inputs of the localized external current. New information is gained on the space- and time-dependent effects of the external action on the two-dimensional structure of magnetic islands, which is very important to formulate applicable control strategies.

Hierarchical low-rank approximation for high dimensional approximation

KAUST Repository

Nouy, Anthony

2016-01-07

Tensor methods are among the most prominent tools for the numerical solution of high-dimensional problems where functions of multiple variables have to be approximated. Such high-dimensional approximation problems naturally arise in stochastic analysis and uncertainty quantification. In many practical situations, the approximation of high-dimensional functions is made computationally tractable by using rank-structured approximations. In this talk, we present algorithms for the approximation in hierarchical tensor format using statistical methods. Sparse representations in a given tensor format are obtained with adaptive or convex relaxation methods, with a selection of parameters using crossvalidation methods.

Hierarchical low-rank approximation for high dimensional approximation

KAUST Repository

Nouy, Anthony

2016-01-01

Tensor methods are among the most prominent tools for the numerical solution of high-dimensional problems where functions of multiple variables have to be approximated. Such high-dimensional approximation problems naturally arise in stochastic analysis and uncertainty quantification. In many practical situations, the approximation of high-dimensional functions is made computationally tractable by using rank-structured approximations. In this talk, we present algorithms for the approximation in hierarchical tensor format using statistical methods. Sparse representations in a given tensor format are obtained with adaptive or convex relaxation methods, with a selection of parameters using crossvalidation methods.

Input-output analysis of high-speed axisymmetric isothermal jet noise

Science.gov (United States)

Jeun, Jinah; Nichols, Joseph W.; Jovanović, Mihailo R.

2016-04-01

We use input-output analysis to predict and understand the aeroacoustics of high-speed isothermal turbulent jets. We consider axisymmetric linear perturbations about Reynolds-averaged Navier-Stokes solutions of ideally expanded turbulent jets with jet Mach numbers 0.6 parabolized stability equations (PSE), and this mode dominates the response. For subsonic jets, however, the singular values indicate that the contributions of sub-optimal modes to noise generation are nearly equal to that of the optimal mode, explaining why the PSE do not fully capture the far-field sound in this case. Furthermore, high-fidelity large eddy simulation (LES) is used to assess the prevalence of sub-optimal modes in the unsteady data. By projecting LES source term data onto input modes and the LES acoustic far-field onto output modes, we demonstrate that sub-optimal modes of both types are physically relevant.

A high-speed computerized tomography image reconstruction using direct two-dimensional Fourier transform method

International Nuclear Information System (INIS)

Niki, Noboru; Mizutani, Toshio; Takahashi, Yoshizo; Inouye, Tamon.

1983-01-01

The nescessity for developing real-time computerized tomography (CT) aiming at the dynamic observation of organs such as hearts has lately been advocated. It is necessary for its realization to reconstruct the images which are markedly faster than present CTs. Although various reconstructing methods have been proposed so far, the method practically employed at present is the filtered backprojection (FBP) method only, which can give high quality image reconstruction, but takes much computing time. In the past, the two-dimensional Fourier transform (TFT) method was regarded as unsuitable to practical use because the quality of images obtained was not good, in spite of the promising method for high speed reconstruction because of its less computing time. However, since it was revealed that the image quality by TFT method depended greatly on interpolation accuracy in two-dimensional Fourier space, the authors have developed a high-speed calculation algorithm that can obtain high quality images by pursuing the relationship between the image quality and the interpolation method. In this case, radial data sampling points in Fourier space are increased to β-th power of 2 times, and the linear or spline interpolation is used. Comparison of this method with the present FBP method resulted in the conclusion that the image quality is almost the same in practical image matrix, the computational time by TFT method becomes about 1/10 of FBP method, and the memory capacity also reduces by about 20 %. (Wakatsuki, Y.)

Harnessing high-dimensional hyperentanglement through a biphoton frequency comb

Science.gov (United States)

Xie, Zhenda; Zhong, Tian; Shrestha, Sajan; Xu, Xinan; Liang, Junlin; Gong, Yan-Xiao; Bienfang, Joshua C.; Restelli, Alessandro; Shapiro, Jeffrey H.; Wong, Franco N. C.; Wei Wong, Chee

2015-08-01

Quantum entanglement is a fundamental resource for secure information processing and communications, and hyperentanglement or high-dimensional entanglement has been separately proposed for its high data capacity and error resilience. The continuous-variable nature of the energy-time entanglement makes it an ideal candidate for efficient high-dimensional coding with minimal limitations. Here, we demonstrate the first simultaneous high-dimensional hyperentanglement using a biphoton frequency comb to harness the full potential in both the energy and time domain. Long-postulated Hong-Ou-Mandel quantum revival is exhibited, with up to 19 time-bins and 96.5% visibilities. We further witness the high-dimensional energy-time entanglement through Franson revivals, observed periodically at integer time-bins, with 97.8% visibility. This qudit state is observed to simultaneously violate the generalized Bell inequality by up to 10.95 standard deviations while observing recurrent Clauser-Horne-Shimony-Holt S-parameters up to 2.76. Our biphoton frequency comb provides a platform for photon-efficient quantum communications towards the ultimate channel capacity through energy-time-polarization high-dimensional encoding.

Feed and manure use in low-N-input and high-N-input dairy cattle production systems

Science.gov (United States)

Powell, J. Mark

2014-11-01

In most parts of Sub-Saharan Africa fertilizers and feeds are costly, not readily available and used sparingly in agricultural production. In many parts of Western Europe, North America, and Oceania fertilizers and feeds are relatively inexpensive, readily available and used abundantly to maximize profitable agricultural production. A case study, dairy systems approach was used to illustrate how differences in feed and manure management in a low-N-input dairy cattle system (Niger, West Africa) and a high-N-input dairy production system (Wisconsin, USA) impact agricultural production and environmental N loss. In Niger, an additional daily feed N intake of 114 g per dairy animal unit (AU, 1000 kg live weight) could increase annual milk production from 560 to 1320 kg AU-1, and the additional manure N could greatly increase millet production. In Wisconsin, reductions in daily feed N intake of 100 g AU-1 would not greatly impact milk production but decrease urinary N excretion by 25% and ammonia and nitrous oxide emissions from manure by 18% to 30%. In Niger, compared to the practice of housing livestock and applying dung only onto fields, corralling cattle or sheep on cropland (to capture urinary N) increased millet yields by 25% to 95%. The additional millet grain due to dung applications or corralling would satisfy the annual food grain requirements of 2-5 persons; the additional forage would provide 120-300 more days of feed for a typical head of cattle; and 850 to 1600 kg ha-1 more biomass would be available for soil conservation. In Wisconsin, compared to application of barn manure only, corralling heifers in fields increased forage production by only 8% to 11%. The application of barn manure or corralling increased forage production by 20% to 70%. This additional forage would provide 350-580 more days of feed for a typical dairy heifer. Study results demonstrate how different approaches to feed and manure management in low-N-input and high-N-input dairy cattle

Covariance Method of the Tunneling Radiation from High Dimensional Rotating Black Holes

Science.gov (United States)

Li, Hui-Ling; Han, Yi-Wen; Chen, Shuai-Ru; Ding, Cong

2018-04-01

In this paper, Angheben-Nadalini-Vanzo-Zerbini (ANVZ) covariance method is used to study the tunneling radiation from the Kerr-Gödel black hole and Myers-Perry black hole with two independent angular momentum. By solving the Hamilton-Jacobi equation and separating the variables, the radial motion equation of a tunneling particle is obtained. Using near horizon approximation and the distance of the proper pure space, we calculate the tunneling rate and the temperature of Hawking radiation. Thus, the method of ANVZ covariance is extended to the research of high dimensional black hole tunneling radiation.

Achievable Information Rates on Linear Interference Channels with Discrete Input

DEFF Research Database (Denmark)

Yankov, Metodi Plamenov; Forchhammer, Søren

2015-01-01

In this paper lower bound on the capacity of multi-dimensional linear interference channels is derived, when the input is taken from a finite size alphabet. The bounds are based on the QR decomposition of the channel matrix, and hold for any input distribution that is independent across dimensions...

Numerical Study of Three Dimensional Effects in Longitudinal Space-Charge Impedance

Energy Technology Data Exchange (ETDEWEB)

Halavanau, A. [NICADD, DeKalb; Piot, P. [NICADD, DeKalb

2015-06-01

Longitudinal space-charge (LSC) effects are generally considered as detrimental in free-electron lasers as they can seed instabilities. Such “microbunching instabilities” were recently shown to be potentially useful to support the generation of broadband coherent radiation pulses [1, 2]. Therefore there has been an increasing interest in devising accelerator beamlines capable of sustaining this LSC instability as a mechanism to produce a coherent light source. To date most of these studies have been carried out with a one-dimensional impedance model for the LSC. In this paper we use a N-body “Barnes-Hut” algorithm [3] to simulate the 3D space charge force in the beam combined with elegant [4] and explore the limitation of the 1D model often used

State-space representation of instationary two-dimensional airfoil aerodynamics

Energy Technology Data Exchange (ETDEWEB)

Meyer, Marcus; Matthies, Hermann G. [Institute of Scientific Computing, Technical University Braunschweig, Hans-Sommer-Str. 65, Braunschweig 38106 (Germany)

2004-03-01

In the aero-elastic analysis of wind turbines the need to include a model of the local, two-dimensional instationary aerodynamic loads, commonly referred to as dynamic stall model, has become obvious in the last years. In this contribution an alternative choice for such a model is described, based on the DLR model. Its derivation is governed by the flow physics, thus enabling interpolation between different profile geometries. An advantage of the proposed model is its state-space form, i.e. a system of differential equations, which facilitates the important tasks of aeroelastic stability and sensitivity investigations. The model is validated with numerical calculations.

The dimensional reduction in a multi-dimensional cosmology

International Nuclear Information System (INIS)

Demianski, M.; Golda, Z.A.; Heller, M.; Szydlowski, M.

1986-01-01

Einstein's field equations are solved for the case of the eleven-dimensional vacuum spacetime which is the product R x Bianchi V x T 7 , where T 7 is a seven-dimensional torus. Among all possible solutions, the authors identify those in which the macroscopic space expands and the microscopic space contracts to a finite size. The solutions with this property are 'typical' within the considered class. They implement the idea of a purely dynamical dimensional reduction. (author)

The Euclidean scalar Green function in the five-dimensional Kaluza-Klein magnetic monopole space-time

International Nuclear Information System (INIS)

Bezerra de Mello, E.R.

2006-01-01

In this paper we present, in a integral form, the Euclidean Green function associated with a massless scalar field in the five-dimensional Kaluza-Klein magnetic monopole superposed to a global monopole, admitting a nontrivial coupling between the field with the geometry. This Green function is expressed as the sum of two contributions: the first one related with uncharged component of the field, is similar to the Green function associated with a scalar field in a four-dimensional global monopole space-time. The second contains the information of all the other components. Using this Green function it is possible to study the vacuum polarization effects on this space-time. Explicitly we calculate the renormalized vacuum expectation value * (x)Φ(x)> Ren , which by its turn is also expressed as the sum of two contributions

Engineering two-photon high-dimensional states through quantum interference

Science.gov (United States)

Zhang, Yingwen; Roux, Filippus S.; Konrad, Thomas; Agnew, Megan; Leach, Jonathan; Forbes, Andrew

2016-01-01

Many protocols in quantum science, for example, linear optical quantum computing, require access to large-scale entangled quantum states. Such systems can be realized through many-particle qubits, but this approach often suffers from scalability problems. An alternative strategy is to consider a lesser number of particles that exist in high-dimensional states. The spatial modes of light are one such candidate that provides access to high-dimensional quantum states, and thus they increase the storage and processing potential of quantum information systems. We demonstrate the controlled engineering of two-photon high-dimensional states entangled in their orbital angular momentum through Hong-Ou-Mandel interference. We prepare a large range of high-dimensional entangled states and implement precise quantum state filtering. We characterize the full quantum state before and after the filter, and are thus able to determine that only the antisymmetric component of the initial state remains. This work paves the way for high-dimensional processing and communication of multiphoton quantum states, for example, in teleportation beyond qubits. PMID:26933685

Unified Theoretical Frame of a Joint Transmitter-Receiver Reduced Dimensional STAP Method for an Airborne MIMO Radar

Directory of Open Access Journals (Sweden)

Guo Yiduo

2016-10-01

Full Text Available The unified theoretical frame of a joint transmitter-receiver reduced dimensional Space-Time Adaptive Processing (STAP method is studied for an airborne Multiple-Input Multiple-Output (MIMO radar. First, based on the transmitted waveform diverse characteristics of the transmitted waveform of the airborne MIMO radar, a uniform theoretical frame structure for the reduced dimensional joint adaptive STAP is constructed. Based on it, three reduced dimensional STAP fixed structures are established. Finally, three reduced rank STAP algorithms, which are suitable for a MIMO system, are presented corresponding to the three reduced dimensional STAP fixed structures. The simulations indicate that the joint adaptive algorithms have preferable clutter suppression and anti-interference performance.

Scattering of three-dimensional plane waves in a self-reinforced half-space lying over a triclinic half-space

Science.gov (United States)

Gupta, Shishir; Pramanik, Abhijit; Smita; Pramanik, Snehamoy

2018-06-01

The phenomenon of plane waves at the intersecting plane of a triclinic half-space and a self-reinforced half-space is discussed with possible applications during wave propagation. Analytical expressions of the phase velocities of reflection and refraction for quasi-compressional and quasi-shear waves under initial stress are discussed carefully. The closest form of amplitude proportions on reflection and refraction factors of three quasi-plane waves are developed mathematically by applying appropriate boundary conditions. Graphics are sketched to exhibit the consequences of initial stress in the three-dimensional plane wave on reflection and refraction coefficients. Some special cases that coincide with the fundamental properties of several layers are designed to express the reflection and refraction coefficients.

Estimation Methods for Infinite-Dimensional Systems Applied to the Hemodynamic Response in the Brain

KAUST Repository

Belkhatir, Zehor

2018-05-01

Infinite-Dimensional Systems (IDSs) which have been made possible by recent advances in mathematical and computational tools can be used to model complex real phenomena. However, due to physical, economic, or stringent non-invasive constraints on real systems, the underlying characteristics for mathematical models in general (and IDSs in particular) are often missing or subject to uncertainty. Therefore, developing efficient estimation techniques to extract missing pieces of information from available measurements is essential. The human brain is an example of IDSs with severe constraints on information collection from controlled experiments and invasive sensors. Investigating the intriguing modeling potential of the brain is, in fact, the main motivation for this work. Here, we will characterize the hemodynamic behavior of the brain using functional magnetic resonance imaging data. In this regard, we propose efficient estimation methods for two classes of IDSs, namely Partial Differential Equations (PDEs) and Fractional Differential Equations (FDEs). This work is divided into two parts. The first part addresses the joint estimation problem of the state, parameters, and input for a coupled second-order hyperbolic PDE and an infinite-dimensional ordinary differential equation using sampled-in-space measurements. Two estimation techniques are proposed: a Kalman-based algorithm that relies on a reduced finite-dimensional model of the IDS, and an infinite-dimensional adaptive estimator whose convergence proof is based on the Lyapunov approach. We study and discuss the identifiability of the unknown variables for both cases. The second part contributes to the development of estimation methods for FDEs where major challenges arise in estimating fractional differentiation orders and non-smooth pointwise inputs. First, we propose a fractional high-order sliding mode observer to jointly estimate the pseudo-state and input of commensurate FDEs. Second, we propose a

Quantum limits to information about states for finite dimensional Hilbert space

International Nuclear Information System (INIS)

Jones, K.R.W.

1990-01-01

A refined bound for the correlation information of an N-trial apparatus is developed via an heuristic argument for Hilbert spaces of arbitrary finite dimensionality. Conditional upon the proof of an easily motivated inequality it was possible to find the optimal apparatus for large ensemble quantum Inference, thereby solving the asymptotic optimal state determination problem. In this way an alternative inferential uncertainty principle, is defined which is then contrasted with the usual Heisenberg uncertainty principle. 6 refs

Supporting Dynamic Quantization for High-Dimensional Data Analytics.

Science.gov (United States)

Guzun, Gheorghi; Canahuate, Guadalupe

2017-05-01

Similarity searches are at the heart of exploratory data analysis tasks. Distance metrics are typically used to characterize the similarity between data objects represented as feature vectors. However, when the dimensionality of the data increases and the number of features is large, traditional distance metrics fail to distinguish between the closest and furthest data points. Localized distance functions have been proposed as an alternative to traditional distance metrics. These functions only consider dimensions close to query to compute the distance/similarity. Furthermore, in order to enable interactive explorations of high-dimensional data, indexing support for ad-hoc queries is needed. In this work we set up to investigate whether bit-sliced indices can be used for exploratory analytics such as similarity searches and data clustering for high-dimensional big-data. We also propose a novel dynamic quantization called Query dependent Equi-Depth (QED) quantization and show its effectiveness on characterizing high-dimensional similarity. When applying QED we observe improvements in kNN classification accuracy over traditional distance functions. Gheorghi Guzun and Guadalupe Canahuate. 2017. Supporting Dynamic Quantization for High-Dimensional Data Analytics. In Proceedings of Ex-ploreDB'17, Chicago, IL, USA, May 14-19, 2017, 6 pages. https://doi.org/http://dx.doi.org/10.1145/3077331.3077336.

Quality and efficiency in high dimensional Nearest neighbor search

KAUST Repository

Tao, Yufei; Yi, Ke; Sheng, Cheng; Kalnis, Panos

2009-01-01

Nearest neighbor (NN) search in high dimensional space is an important problem in many applications. Ideally, a practical solution (i) should be implementable in a relational database, and (ii) its query cost should grow sub-linearly with the dataset size, regardless of the data and query distributions. Despite the bulk of NN literature, no solution fulfills both requirements, except locality sensitive hashing (LSH). The existing LSH implementations are either rigorous or adhoc. Rigorous-LSH ensures good quality of query results, but requires expensive space and query cost. Although adhoc-LSH is more efficient, it abandons quality control, i.e., the neighbor it outputs can be arbitrarily bad. As a result, currently no method is able to ensure both quality and efficiency simultaneously in practice. Motivated by this, we propose a new access method called the locality sensitive B-tree (LSB-tree) that enables fast highdimensional NN search with excellent quality. The combination of several LSB-trees leads to a structure called the LSB-forest that ensures the same result quality as rigorous-LSH, but reduces its space and query cost dramatically. The LSB-forest also outperforms adhoc-LSH, even though the latter has no quality guarantee. Besides its appealing theoretical properties, the LSB-tree itself also serves as an effective index that consumes linear space, and supports efficient updates. Our extensive experiments confirm that the LSB-tree is faster than (i) the state of the art of exact NN search by two orders of magnitude, and (ii) the best (linear-space) method of approximate retrieval by an order of magnitude, and at the same time, returns neighbors with much better quality. © 2009 ACM.

A preliminary feasibility study of passive in-core thermionic reactors for highly compact space nuclear power systems

International Nuclear Information System (INIS)

Parlos, A.G.; Khan, E.U.; Frymire, R.; Negron, S.; Thomas, J.K.; Peddicord, K.L.

1991-01-01

Results of a preliminary feasibility study on a new concept for a highly compact space reactor power systems are presented. Notwithstanding the preliminary nature of the present study, the results which include a new space reactor configuration and its associated technologies indicate promising avenues for the devleopment of highly compact space reactors. The calculations reported in this study include a neutronic design trade-off study using a two-dimensioinal neutron transport model, as well as a simplified one-dimensional thermal analysis of the reactor core. In arriving at the most desirable configuration, various options have been considered and analyzed, and their advantages/disadvantages have been compared. However, because of space limitation, only the most favorable reactor configuration is presented in this summary

Fast metabolite identification with Input Output Kernel Regression

Science.gov (United States)

Brouard, Céline; Shen, Huibin; Dührkop, Kai; d'Alché-Buc, Florence; Böcker, Sebastian; Rousu, Juho

2016-01-01

Motivation: An important problematic of metabolomics is to identify metabolites using tandem mass spectrometry data. Machine learning methods have been proposed recently to solve this problem by predicting molecular fingerprint vectors and matching these fingerprints against existing molecular structure databases. In this work we propose to address the metabolite identification problem using a structured output prediction approach. This type of approach is not limited to vector output space and can handle structured output space such as the molecule space. Results: We use the Input Output Kernel Regression method to learn the mapping between tandem mass spectra and molecular structures. The principle of this method is to encode the similarities in the input (spectra) space and the similarities in the output (molecule) space using two kernel functions. This method approximates the spectra-molecule mapping in two phases. The first phase corresponds to a regression problem from the input space to the feature space associated to the output kernel. The second phase is a preimage problem, consisting in mapping back the predicted output feature vectors to the molecule space. We show that our approach achieves state-of-the-art accuracy in metabolite identification. Moreover, our method has the advantage of decreasing the running times for the training step and the test step by several orders of magnitude over the preceding methods. Availability and implementation: Contact: celine.brouard@aalto.fi Supplementary information: Supplementary data are available at Bioinformatics online. PMID:27307628

A Dissimilarity Measure for Clustering High- and Infinite Dimensional Data that Satisfies the Triangle Inequality

Science.gov (United States)

Socolovsky, Eduardo A.; Bushnell, Dennis M. (Technical Monitor)

2002-01-01

The cosine or correlation measures of similarity used to cluster high dimensional data are interpreted as projections, and the orthogonal components are used to define a complementary dissimilarity measure to form a similarity-dissimilarity measure pair. Using a geometrical approach, a number of properties of this pair is established. This approach is also extended to general inner-product spaces of any dimension. These properties include the triangle inequality for the defined dissimilarity measure, error estimates for the triangle inequality and bounds on both measures that can be obtained with a few floating-point operations from previously computed values of the measures. The bounds and error estimates for the similarity and dissimilarity measures can be used to reduce the computational complexity of clustering algorithms and enhance their scalability, and the triangle inequality allows the design of clustering algorithms for high dimensional distributed data.

Tracking in Object Action Space

DEFF Research Database (Denmark)

Krüger, Volker; Herzog, Dennis

2013-01-01

the space of the object affordances, i.e., the space of possible actions that are applied on a given object. This way, 3D body tracking reduces to action tracking in the object (and context) primed parameter space of the object affordances. This reduces the high-dimensional joint-space to a low...

Application of space-angle synthesis to two-dimensional neutral-particle transport problems of weapon physics

International Nuclear Information System (INIS)

Roberds, R.M.

1975-01-01

A space-angle synthesis (SAS) method has been developed for treating the steady-state, two-dimensional transport of neutrons and gamma rays from a point source of simulated nuclear weapon radiation in air. The method was validated by applying it to the problem of neutron transport from a point source in air over a ground interface, and then comparing the results to those obtained by DOT, a state-of-the-art, discrete-ordinates code. In the SAS method, the energy dependence of the Boltzmann transport equation was treated in the standard multigroup manner. The angular dependence was treated by expanding the flux in specially tailored trial functions and applying the method of weighted residuals which analytically integrated the transport equation over all angles. The weighted-residual approach was analogous to the conventional spherical-harmonics (P/sub N/) method with the exception that the tailored expansion allowed for more rapid convergence than a spherical-harmonics P 1 expansion and resulted in a greater degree of accuracy. The trial functions used in the expansion were odd and even combinations of selected trial solutions, the trial solutions being shaped ellipsoids which approximated the angular distribution of the neutron flux in one-dimensional space. The parameters which described the shape of the ellipsoid varied with energy group and the spatial medium, only, and were obtained from a one-dimensional discrete-ordinates calculation. Thus, approximate transport solutions were made available for all two-dimensional problems of a certain class by using tabulated parameters obtained from a single, one-dimensional calculation

High dimensional entanglement

CSIR Research Space (South Africa)

Mc

2012-07-01

Full Text Available stream_source_info McLaren_2012.pdf.txt stream_content_type text/plain stream_size 2190 Content-Encoding ISO-8859-1 stream_name McLaren_2012.pdf.txt Content-Type text/plain; charset=ISO-8859-1 High dimensional... entanglement M. McLAREN1,2, F.S. ROUX1 & A. FORBES1,2,3 1. CSIR National Laser Centre, PO Box 395, Pretoria 0001 2. School of Physics, University of the Stellenbosch, Private Bag X1, 7602, Matieland 3. School of Physics, University of Kwazulu...

Life cycle assessment of small-scale high-input Jatropha biodiesel production in India

International Nuclear Information System (INIS)

Pandey, Krishan K.; Pragya, Namita; Sahoo, P.K.

2011-01-01

Highlights: → NEB and NER of high input Jatropha biodiesel system was higher than those of low input. → These values further increase on including the energy content of the co-products, and in the further years. → Maximum energy use was during oil extraction, followed by oil processing and fertilizer use. → Allocation of resources at right time and with proper care increase the overall system productivity. -- Abstract: In the current scenario of depleting energy resources, increasing food insecurity and global warming, Jatropha has emerged as a promising energy crop for India. The aim of this study is to examine the life cycle energy balance for Jatropha biodiesel production and greenhouse gas emissions from post-energy use and end combustion of biodiesel, over a period of 5 years. It's a case specific study for a small scale, high input Jatropha biodiesel system. Most of the existing studies have considered low input Jatropha biodiesel system and have used NEB (Net energy balance i.e. difference of energy output and energy input) and NER (Net energy ratio i.e. ratio of energy output to energy input) as indicators for estimating the viability of the systems. Although, many of them have shown these indicators to be positive, yet the values are very less. The results of this study, when compared with two previous studies of Jatropha, show that the values for these indicators can be increased to a much greater extent, if we use a high input Jatropha biodiesel system. Further, when compared to a study done on palm oil and Coconut oil, it was found even if the NEB and NER of biodiesel from Jatropha were lesser in comparison to those of Palm oil and Coconut oil, yet, when energy content of the co-products were also considered, Jatropha had the highest value for both the indicators in comparison to the rest two.

Low dimensionality semiconductors: modelling of excitons via a fractional-dimensional space

Science.gov (United States)

Christol, P.; Lefebvre, P.; Mathieu, H.

1993-09-01

An interaction space with a fractionnal dimension is used to calculate in a simple way the binding energies of excitons confined in quantum wells, superlattices and quantum well wires. A very simple formulation provides this energy versus the non-integer dimensionality of the physical environment of the electron-hole pair. The problem then comes to determining the dimensionality α. We show that the latter can be expressed from the characteristics of the microstructure. α continuously varies from 3 (bulk material) to 2 for quantum wells and superlattices, and from 3 to 1 for quantum well wires. Quite a fair agreement is obtained with other theoretical calculations and experimental data, and this model coherently describes both three-dimensional limiting cases for quantum wells (L_wrightarrow 0 and L_wrightarrow infty) and the whole range of periods of the superlattice. Such a simple model presents a great interest for spectroscopists though it does not aim to compete with accurate but often tedious variational calculations. Nous utilisons un espace des interactions doté d'une dimension fractionnaire pour calculer simplement l'énergie de liaison des excitons confinés dans les puits quantiques, superréseaux et fils quantiques. Une formulation très simple donne cette énergie en fonction de la dimensionalité non-entière de l'environnement physique de la paire électron-trou. Le problème revient alors à déterminer cette dimensionalité α, dont nous montrons qu'une expression peut être déduite des caractéristiques de la microstructure. α varie continûment de 3 (matériau massif) à 2 pour un puits quantique ou un superréseau, et de 3 à 1 pour un fil quantique, selon le confinement du mouvement des porteurs. Les comparaisons avec d'autres calculs théoriques et données expérimentales sont toujours très convenables, et cette théorie décrit d'une façon cohérente les limites tridimensionnelles du puits quantique (L_wrightarrow 0 et L

The N=4 supersymmetric E8 gauge theory and coset space dimensional reduction

International Nuclear Information System (INIS)

Olive, D.; West, P.

1983-01-01

Reasons are given to suggest that the N=4 supersymmetric E 8 gauge theory be considered as a serious candidate for a physical theory. The symmetries of this theory are broken by a scheme based on coset space dimensional reduction. The resulting theory possesses four conventional generations of low-mass fermions together with their mirror particles. (orig.)

Large parallel volumes of finite and compact sets in d-dimensional Euclidean space

DEFF Research Database (Denmark)

Kampf, Jürgen; Kiderlen, Markus

The r-parallel volume V (Cr) of a compact subset C in d-dimensional Euclidean space is the volume of the set Cr of all points of Euclidean distance at most r > 0 from C. According to Steiner’s formula, V (Cr) is a polynomial in r when C is convex. For finite sets C satisfying a certain geometric...

Using High-Dimensional Image Models to Perform Highly Undetectable Steganography

Science.gov (United States)

Pevný, Tomáš; Filler, Tomáš; Bas, Patrick

This paper presents a complete methodology for designing practical and highly-undetectable stegosystems for real digital media. The main design principle is to minimize a suitably-defined distortion by means of efficient coding algorithm. The distortion is defined as a weighted difference of extended state-of-the-art feature vectors already used in steganalysis. This allows us to "preserve" the model used by steganalyst and thus be undetectable even for large payloads. This framework can be efficiently implemented even when the dimensionality of the feature set used by the embedder is larger than 107. The high dimensional model is necessary to avoid known security weaknesses. Although high-dimensional models might be problem in steganalysis, we explain, why they are acceptable in steganography. As an example, we introduce HUGO, a new embedding algorithm for spatial-domain digital images and we contrast its performance with LSB matching. On the BOWS2 image database and in contrast with LSB matching, HUGO allows the embedder to hide 7× longer message with the same level of security level.

Holography in three-dimensional Kerr-de Sitter space with a gravitational Chern-Simons term

International Nuclear Information System (INIS)

Park, Mu-In

2008-01-01

The holographic description of the three-dimensional Kerr-de Sitter space with a gravitational Chern-Simons term is studied, in the context of dS/CFT correspondence. The space has only one (cosmological) event horizon and its mass and angular momentum are identified from the holographic energy-momentum tensor at the asymptotic infinity. The thermodynamic entropy of the cosmological horizon is computed directly from the first law of thermodynamics, with the conventional Hawking temperature, and it is found that the usual Gibbons-Hawking entropy is modified. It is remarked that, due to the gravitational Chern-Simons term, (a) the results go beyond the analytic continuation from AdS, (b) the maximum-mass/N-bound conjecture may be violated and (c) the three-dimensional cosmology is chiral. A statistical mechanical computation of the entropy, from a Cardy-like formula for a dual CFT at the asymptotic boundary, is discussed. Some remarks on the technical differences in the Chern-Simons energy-momentum tensor, from the literature, are also made

Direct observation of strain in bulk subgrains and dislocation walls by high angular resolution three-dimensional X-ray diffraction

DEFF Research Database (Denmark)

Jakobsen, Bo; Lienert, U.; Almer, J.

2008-01-01

The X-ray diffraction (XRD) method "high angular resolution 3DXRD" is briefly introduced, and results are presented for a single bulk grain in a polycrystalline copper sample deformed in tension. It is found that the three-dimensional reciprocal-space intensity distribution of a 400 reflection...

Three-directional motion compensation-based novel-look-up-table for video hologram generation of three-dimensional objects freely maneuvering in space.

Science.gov (United States)

Dong, Xiao-Bin; Kim, Seung-Cheol; Kim, Eun-Soo

2014-07-14

A new three-directional motion compensation-based novel-look-up-table (3DMC-NLUT) based on its shift-invariance and thin-lens properties, is proposed for video hologram generation of three-dimensional (3-D) objects moving with large depth variations in space. The input 3-D video frames are grouped into a set of eight in sequence, where the first and remaining seven frames in each set become the reference frame (RF) and general frames (GFs), respectively. Hence, each 3-D video frame is segmented into a set of depth-sliced object images (DOIs). Then x, y, and z-directional motion vectors are estimated from blocks and DOIs between the RF and each of the GFs, respectively. With these motion vectors, object motions in space are compensated. Then, only the difference images between the 3-directionally motion-compensated RF and each of the GFs are applied to the NLUT for hologram calculation. Experimental results reveal that the average number of calculated object points and the average calculation time of the proposed method have been reduced compared to those of the conventional NLUT, TR-NLUT and MPEG-NLUT by 38.14%, 69.48%, and 67.41% and 35.30%, 66.39%, and 64.46%, respectively.

A Kronecker product splitting preconditioner for two-dimensional space-fractional diffusion equations

Science.gov (United States)

Chen, Hao; Lv, Wen; Zhang, Tongtong

2018-05-01

We study preconditioned iterative methods for the linear system arising in the numerical discretization of a two-dimensional space-fractional diffusion equation. Our approach is based on a formulation of the discrete problem that is shown to be the sum of two Kronecker products. By making use of an alternating Kronecker product splitting iteration technique we establish a class of fixed-point iteration methods. Theoretical analysis shows that the new method converges to the unique solution of the linear system. Moreover, the optimal choice of the involved iteration parameters and the corresponding asymptotic convergence rate are computed exactly when the eigenvalues of the system matrix are all real. The basic iteration is accelerated by a Krylov subspace method like GMRES. The corresponding preconditioner is in a form of a Kronecker product structure and requires at each iteration the solution of a set of discrete one-dimensional fractional diffusion equations. We use structure preserving approximations to the discrete one-dimensional fractional diffusion operators in the action of the preconditioning matrix. Numerical examples are presented to illustrate the effectiveness of this approach.

Quantum trajectories in complex space: One-dimensional stationary scattering problems

International Nuclear Information System (INIS)

Chou, C.-C.; Wyatt, Robert E.

2008-01-01

One-dimensional time-independent scattering problems are investigated in the framework of the quantum Hamilton-Jacobi formalism. The equation for the local approximate quantum trajectories near the stagnation point of the quantum momentum function is derived, and the first derivative of the quantum momentum function is related to the local structure of quantum trajectories. Exact complex quantum trajectories are determined for two examples by numerically integrating the equations of motion. For the soft potential step, some particles penetrate into the nonclassical region, and then turn back to the reflection region. For the barrier scattering problem, quantum trajectories may spiral into the attractors or from the repellers in the barrier region. Although the classical potentials extended to complex space show different pole structures for each problem, the quantum potentials present the same second-order pole structure in the reflection region. This paper not only analyzes complex quantum trajectories and the total potentials for these examples but also demonstrates general properties and similar structures of the complex quantum trajectories and the quantum potentials for one-dimensional time-independent scattering problems

Entanglement of arbitrary superpositions of modes within two-dimensional orbital angular momentum state spaces

International Nuclear Information System (INIS)

Jack, B.; Leach, J.; Franke-Arnold, S.; Ireland, D. G.; Padgett, M. J.; Yao, A. M.; Barnett, S. M.; Romero, J.

2010-01-01

We use spatial light modulators (SLMs) to measure correlations between arbitrary superpositions of orbital angular momentum (OAM) states generated by spontaneous parametric down-conversion. Our technique allows us to fully access a two-dimensional OAM subspace described by a Bloch sphere, within the higher-dimensional OAM Hilbert space. We quantify the entanglement through violations of a Bell-type inequality for pairs of modal superpositions that lie on equatorial, polar, and arbitrary great circles of the Bloch sphere. Our work shows that SLMs can be used to measure arbitrary spatial states with a fidelity sufficient for appropriate quantum information processing systems.

Clustering high dimensional data using RIA

Energy Technology Data Exchange (ETDEWEB)

Aziz, Nazrina [School of Quantitative Sciences, College of Arts and Sciences, Universiti Utara Malaysia, 06010 Sintok, Kedah (Malaysia)

2015-05-15

Clustering may simply represent a convenient method for organizing a large data set so that it can easily be understood and information can efficiently be retrieved. However, identifying cluster in high dimensionality data sets is a difficult task because of the curse of dimensionality. Another challenge in clustering is some traditional functions cannot capture the pattern dissimilarity among objects. In this article, we used an alternative dissimilarity measurement called Robust Influence Angle (RIA) in the partitioning method. RIA is developed using eigenstructure of the covariance matrix and robust principal component score. We notice that, it can obtain cluster easily and hence avoid the curse of dimensionality. It is also manage to cluster large data sets with mixed numeric and categorical value.

Asymptotically Honest Confidence Regions for High Dimensional

DEFF Research Database (Denmark)

Caner, Mehmet; Kock, Anders Bredahl

While variable selection and oracle inequalities for the estimation and prediction error have received considerable attention in the literature on high-dimensional models, very little work has been done in the area of testing and construction of confidence bands in high-dimensional models. However...... develop an oracle inequality for the conservative Lasso only assuming the existence of a certain number of moments. This is done by means of the Marcinkiewicz-Zygmund inequality which in our context provides sharper bounds than Nemirovski's inequality. As opposed to van de Geer et al. (2014) we allow...

Classical testing particles and (4 + N)-dimensional theories of space-time

International Nuclear Information System (INIS)

Nieto-Garcia, J.A.

1986-01-01

The Lagrangian theory of a classical relativistic spinning test particle (top) developed by Hanson and Regge and by Hojman is briefly reviewed. Special attention is devoted to the constraints imposed on the dynamical variables associated with the system of this theory. The equations for a relativistic top are formulated in a way suitable for use in the study of geometrical properties of the 4 + N-dimensional Kaluza-Klein background. It is shown that the equations of motion of a top in five dimensions reduce to the Hanson-Regge generalization of the Bargmann-Michel-Telegdi equations of motion in four dimensions when suitable conditions on the spin tensor are imposed. The classical bosonic relativistic string theory is discussed and the connection of this theory with the top theory is examined. It is found that the relation between the string and the top leads naturally to the consideration of a 3-dimensional extended system (called terron) which sweeps out a 4-dimensional surface as it evolves in a space-time. By using a square root procedure based on ideas by Teitelboim a theory of a supersymmetric top is developed. The quantization of the new supersymmetric system is discussed. Conclusions and suggestions for further research are given

Convergence rates and finite-dimensional approximations for nonlinear ill-posed problems involving monotone operators in Banach spaces

International Nuclear Information System (INIS)

Nguyen Buong.

1992-11-01

The purpose of this paper is to investigate convergence rates for an operator version of Tikhonov regularization constructed by dual mapping for nonlinear ill-posed problems involving monotone operators in real reflective Banach spaces. The obtained results are considered in combination with finite-dimensional approximations for the space. An example is considered for illustration. (author). 15 refs

Evaluating Clustering in Subspace Projections of High Dimensional Data

DEFF Research Database (Denmark)

Müller, Emmanuel; Günnemann, Stephan; Assent, Ira

2009-01-01

Clustering high dimensional data is an emerging research field. Subspace clustering or projected clustering group similar objects in subspaces, i.e. projections, of the full space. In the past decade, several clustering paradigms have been developed in parallel, without thorough evaluation...... and comparison between these paradigms on a common basis. Conclusive evaluation and comparison is challenged by three major issues. First, there is no ground truth that describes the "true" clusters in real world data. Second, a large variety of evaluation measures have been used that reflect different aspects...... of the clustering result. Finally, in typical publications authors have limited their analysis to their favored paradigm only, while paying other paradigms little or no attention. In this paper, we take a systematic approach to evaluate the major paradigms in a common framework. We study representative clustering...

Fusion rule estimation using vector space methods

International Nuclear Information System (INIS)

Rao, N.S.V.

1997-01-01

In a system of N sensors, the sensor S j , j = 1, 2 .... N, outputs Y (j) element-of Re, according to an unknown probability distribution P (Y(j) /X) , corresponding to input X element-of [0, 1]. A training n-sample (X 1 , Y 1 ), (X 2 , Y 2 ), ..., (X n , Y n ) is given where Y i = (Y i (1) , Y i (2) , . . . , Y i N ) such that Y i (j) is the output of S j in response to input X i . The problem is to estimate a fusion rule f : Re N → [0, 1], based on the sample, such that the expected square error is minimized over a family of functions Y that constitute a vector space. The function f* that minimizes the expected error cannot be computed since the underlying densities are unknown, and only an approximation f to f* is feasible. We estimate the sample size sufficient to ensure that f provides a close approximation to f* with a high probability. The advantages of vector space methods are two-fold: (a) the sample size estimate is a simple function of the dimensionality of F, and (b) the estimate f can be easily computed by well-known least square methods in polynomial time. The results are applicable to the classical potential function methods and also (to a recently proposed) special class of sigmoidal feedforward neural networks

The influence of high heat input and inclusions control for rare earth on welding in low alloy high strength steel

Science.gov (United States)

Chu, Rensheng; Mu, Shukun; Liu, Jingang; Li, Zhanjun

2017-09-01

In the current paper, it is analyzed for the influence of high heat input and inclusions control for rare earth on welding in low alloy high strength steel. It is observed for the structure for different heat input of the coarse-grained area. It is finest for the coarse grain with the high heat input of 200 kJ / cm and the coarse grain area with 400 kJ / cm is the largest. The performance with the heat input of 200 kJ / cm for -20 °C V-shaped notch oscillatory power is better than the heat input of 400 kJ / cm. The grain structure is the ferrite and bainite for different holding time. The grain structure for 5s holding time has a grain size of 82.9 μm with heat input of 200 kJ/cm and grain size of 97.9 μm for 10s holding time. For the inclusions for HSLA steel with adding rare earth, they are Al2O3-CaS inclusions in the Al2O3-CaS-CaO ternary phase diagram. At the same time, it can not be found for low melting calcium aluminate inclusions compared to the inclusions for the HSLA steel without rare earth. Most of the size for the inclusions is between 1 ~ 10μm. The overall grain structure is smaller and the welding performance is more excellent for adding rare earth.

Multiple Input - Multiple Output (MIMO) SAR

Data.gov (United States)

National Aeronautics and Space Administration — This effort will research and implement advanced Multiple-Input Multiple-Output (MIMO) Synthetic Aperture Radar (SAR) techniques which have the potential to improve...

Positioning with stationary emitters in a two-dimensional space-time

International Nuclear Information System (INIS)

Coll, Bartolome; Ferrando, Joan Josep; Morales, Juan Antonio

2006-01-01

The basic elements of the relativistic positioning systems in a two-dimensional space-time have been introduced in a previous work [Phys. Rev. D 73, 084017 (2006)] where geodesic positioning systems, constituted by two geodesic emitters, have been considered in a flat space-time. Here, we want to show in what precise senses positioning systems allow to make relativistic gravimetry. For this purpose, we consider stationary positioning systems, constituted by two uniformly accelerated emitters separated by a constant distance, in two different situations: absence of gravitational field (Minkowski plane) and presence of a gravitational mass (Schwarzschild plane). The physical coordinate system constituted by the electromagnetic signals broadcasting the proper time of the emitters are the so called emission coordinates, and we show that, in such emission coordinates, the trajectories of the emitters in both situations, the absence and presence of a gravitational field, are identical. The interesting point is that, in spite of this fact, particular additional information on the system or on the user allows us not only to distinguish both space-times, but also to complete the dynamical description of emitters and user and even to measure the mass of the gravitational field. The precise information under which these dynamical and gravimetric results may be obtained is carefully pointed out

Three-dimensionality of space and the quantum bit: an information-theoretic approach

International Nuclear Information System (INIS)

Müller, Markus P; Masanes, Lluís

2013-01-01

It is sometimes pointed out as a curiosity that the state space of quantum two-level systems, i.e. the qubit, and actual physical space are both three-dimensional and Euclidean. In this paper, we suggest an information-theoretic analysis of this relationship, by proving a particular mathematical result: suppose that physics takes place in d spatial dimensions, and that some events happen probabilistically (not assuming quantum theory in any way). Furthermore, suppose there are systems that carry ‘minimal amounts of direction information’, interacting via some continuous reversible time evolution. We prove that this uniquely determines spatial dimension d = 3 and quantum theory on two qubits (including entanglement and unitary time evolution), and that it allows observers to infer local spatial geometry from probability measurements. (paper)

Euclidean scalar Green function in a higher dimensional global monopole space-time

International Nuclear Information System (INIS)

Bezerra de Mello, E.R.

2002-01-01

We construct the explicit Euclidean scalar Green function associated with a massless field in a higher dimensional global monopole space-time, i.e., a (1+d)-space-time with d≥3 which presents a solid angle deficit. Our result is expressed in terms of an infinite sum of products of Legendre functions with Gegenbauer polynomials. Although this Green function cannot be expressed in a closed form, for the specific case where the solid angle deficit is very small, it is possible to develop the sum and obtain the Green function in a more workable expression. Having this expression it is possible to calculate the vacuum expectation value of some relevant operators. As an application of this formalism, we calculate the renormalized vacuum expectation value of the square of the scalar field, 2 (x)> Ren , and the energy-momentum tensor, μν (x)> Ren , for the global monopole space-time with spatial dimensions d=4 and d=5

Influence of the input database in detecting fire space-time clusters

Science.gov (United States)

Pereira, Mário; Costa, Ricardo; Tonini, Marj; Vega Orozco, Carmen; Parente, Joana

2015-04-01

Fire incidence variability is influenced by local environmental variables such as topography, land use, vegetation and weather conditions. These induce a cluster pattern of the fire events distribution. The space-time permutation scan statistics (STPSS) method developed by Kulldorff et al. (2005) and implemented in the SaTScanTM software (http://www.satscan.org/) proves to be able to detect space-time clusters in many different fields, even when using incomplete and/or inaccurate input data. Nevertheless, the dependence of the STPSS method on the different characteristics of different datasets describing the same environmental phenomenon has not been studied yet. In this sense, the objective of this study is to assess the robustness of the STPSS for detecting real clusters using different input datasets and to justify the obtained results. This study takes advantage of the existence of two very different official fire datasets currently available for Portugal, both provided by the Institute for the Conservation of Nature and Forests. The first one is the aggregated Portuguese Rural Fire Database PRFD (Pereira et al., 2011), which is based on ground measurements and provides detailed information about the ignition and extinction date/time and the area burnt by each fire in forest, scrubs and agricultural areas. However, in the PRFD, the fire location of each fire is indicated by the name of smallest administrative unit (the parish) where the ignition occurred. Consequently, since the application of the STPSS requires the geographic coordinates of the events, the centroid of the parishes was considered. The second fire dataset is the national mapping burnt areas (NMBA), which is based on satellite measurements and delivered in shape file format. The NMBA provides a detailed spatial information (shape and size of each fire) but the temporal information is restricted to the year of occurrence. Besides these differences, the two datasets cover different periods, they

Diffraction limited focusing with controllable arbitrary three-dimensional polarization

International Nuclear Information System (INIS)

Chen, Weibin; Zhan, Qiwen

2010-01-01

We propose a new approach that enables full control over the three-dimensional state of polarization and the field distribution near the focus of a high numerical aperture objective lens. By combining the electric dipole radiation and a vectorial diffraction method, the input field at the pupil plane for generating arbitrary three-dimensionally oriented linear polarization at the focal point with a diffraction limited spot size is found analytically by solving the inverse problem. Arbitrary three-dimensional elliptical polarization can be obtained by introducing a second electric dipole oriented in the orthogonal plane with appropriate amplitude and phase differences

Calculating the sensitivity of wind turbine loads to wind inputs using response surfaces

DEFF Research Database (Denmark)

Rinker, Jennifer M.

2016-01-01

at a low computational cost. Sobol sensitivity indices (SIs) can then be calculated with relative ease using the calibrated response surface. The proposed methodology is demonstrated by calculating the total sensitivity of the maximum blade root bending moment of the WindPACT 5 MW reference model to four......This paper presents a methodology to calculate wind turbine load sensitivities to turbulence parameters through the use of response surfaces. A response surface is a high-dimensional polynomial surface that can be calibrated to any set of input/output data and then used to generate synthetic data...... turbulence input parameters: a reference mean wind speed, a reference turbulence intensity, the Kaimal length scale, and a novel parameter reflecting the nonstationarity present in the inflow turbulence. The input/output data used to calibrate the response surface were generated for a previous project...

Modeling High-Dimensional Multichannel Brain Signals

KAUST Repository

Hu, Lechuan; Fortin, Norbert J.; Ombao, Hernando

2017-01-01

aspects: first, there are major statistical and computational challenges for modeling and analyzing high-dimensional multichannel brain signals; second, there is no set of universally agreed measures for characterizing connectivity. To model multichannel

Three-dimensional volume rendering of tibiofibular joint space and quantitative analysis of change in volume due to tibiofibular syndesmosis diastases

International Nuclear Information System (INIS)

Taser, F.; Shafiq, Q.; Ebraheim, N.A.

2006-01-01

The diagnosis of ankle syndesmosis injuries is made by various imaging techniques. The present study was undertaken to examine whether the three-dimensional reconstruction of axial CT images and calculation of the volume of tibiofibular joint space enhances the sensitivity of diastases diagnoses or not. Six adult cadaveric ankle specimens were used for spiral CT-scan assessment of tibiofibular syndesmosis. After the specimens were dissected, external fixation was performed and diastases of 1, 2, and 3 mm was simulated by a precalibrated device. Helical CT scans were obtained with 1.0-mm slice thickness. The data was transferred to the computer software AcquariusNET. Then the contours of the tibiofibular syndesmosis joint space were outlined on each axial CT slice and the collection of these slices were stacked using the computer software AutoCAD 2005, according to the spatial arrangement and geometrical coordinates between each slice, to produce a three-dimensional reconstruction of the joint space. The area of each slice and the volume of the entire tibiofibular joint space were calculated. The tibiofibular joint space at the 10th-mm slice level was also measured on axial CT scan images at normal, 1, 2 and 3-mm joint space diastases. The three-dimensional volume-rendering of the tibiofibular syndesmosis joint space from the spiral CT data demonstrated the shape of the joint space and has been found to be a sensitive method for calculating joint space volume. We found that, from normal to 1 mm, a 1-mm diastasis increases approximately 43% of the joint space volume, while from 1 to 3 mm, there is about a 20% increase for each 1-mm increase. Volume calculation using this method can be performed in cases of syndesmotic instability after ankle injuries and for preoperative and postoperative evaluation of the integrity of the tibiofibular syndesmosis. (orig.)

Free-space optical communications with peak and average constraints: High SNR capacity approximation

KAUST Repository

Chaaban, Anas

2015-09-07

The capacity of the intensity-modulation direct-detection (IM-DD) free-space optical channel with both average and peak intensity constraints is studied. A new capacity lower bound is derived by using a truncated-Gaussian input distribution. Numerical evaluation shows that this capacity lower bound is nearly tight at high signal-to-noise ratio (SNR), while it is shown analytically that the gap to capacity upper bounds is a small constant at high SNR. In particular, the gap to the high-SNR asymptotic capacity of the channel under either a peak or an average constraint is small. This leads to a simple approximation of the high SNR capacity. Additionally, a new capacity upper bound is derived using sphere-packing arguments. This bound is tight at high SNR for a channel with a dominant peak constraint.

Families of null surfaces in the Minkowski tri dimensional space-time and its associated differential equations

International Nuclear Information System (INIS)

Silva O, G.; Garcia G, P.

2004-01-01

In this work we describe the procedure to obtain all the family of third order ordinary differential equations connected by a contact transformation such that in their spaces of solutions is defined a conformal three dimensional Minkowski metric. (Author)

Small-angle X-ray scattering tensor tomography: model of the three-dimensional reciprocal-space map, reconstruction algorithm and angular sampling requirements.

Science.gov (United States)

Liebi, Marianne; Georgiadis, Marios; Kohlbrecher, Joachim; Holler, Mirko; Raabe, Jörg; Usov, Ivan; Menzel, Andreas; Schneider, Philipp; Bunk, Oliver; Guizar-Sicairos, Manuel

2018-01-01

Small-angle X-ray scattering tensor tomography, which allows reconstruction of the local three-dimensional reciprocal-space map within a three-dimensional sample as introduced by Liebi et al. [Nature (2015), 527, 349-352], is described in more detail with regard to the mathematical framework and the optimization algorithm. For the case of trabecular bone samples from vertebrae it is shown that the model of the three-dimensional reciprocal-space map using spherical harmonics can adequately describe the measured data. The method enables the determination of nanostructure orientation and degree of orientation as demonstrated previously in a single momentum transfer q range. This article presents a reconstruction of the complete reciprocal-space map for the case of bone over extended ranges of q. In addition, it is shown that uniform angular sampling and advanced regularization strategies help to reduce the amount of data required.

On the average complexity of sphere decoding in lattice space-time coded multiple-input multiple-output channel

KAUST Repository

Abediseid, Walid

2012-12-21

The exact average complexity analysis of the basic sphere decoder for general space-time codes applied to multiple-input multiple-output (MIMO) wireless channel is known to be difficult. In this work, we shed the light on the computational complexity of sphere decoding for the quasi- static, lattice space-time (LAST) coded MIMO channel. Specifically, we drive an upper bound of the tail distribution of the decoder\\'s computational complexity. We show that when the computational complexity exceeds a certain limit, this upper bound becomes dominated by the outage probability achieved by LAST coding and sphere decoding schemes. We then calculate the minimum average computational complexity that is required by the decoder to achieve near optimal performance in terms of the system parameters. Our results indicate that there exists a cut-off rate (multiplexing gain) for which the average complexity remains bounded. Copyright © 2012 John Wiley & Sons, Ltd.

Modeling the ionosphere-thermosphere response to a geomagnetic storm using physics-based magnetospheric energy input: OpenGGCM-CTIM results

Directory of Open Access Journals (Sweden)

Connor Hyunju Kim

2016-01-01

Full Text Available The magnetosphere is a major source of energy for the Earth’s ionosphere and thermosphere (IT system. Current IT models drive the upper atmosphere using empirically calculated magnetospheric energy input. Thus, they do not sufficiently capture the storm-time dynamics, particularly at high latitudes. To improve the prediction capability of IT models, a physics-based magnetospheric input is necessary. Here, we use the Open Global General Circulation Model (OpenGGCM coupled with the Coupled Thermosphere Ionosphere Model (CTIM. OpenGGCM calculates a three-dimensional global magnetosphere and a two-dimensional high-latitude ionosphere by solving resistive magnetohydrodynamic (MHD equations with solar wind input. CTIM calculates a global thermosphere and a high-latitude ionosphere in three dimensions using realistic magnetospheric inputs from the OpenGGCM. We investigate whether the coupled model improves the storm-time IT responses by simulating a geomagnetic storm that is preceded by a strong solar wind pressure front on August 24, 2005. We compare the OpenGGCM-CTIM results with low-earth-orbit satellite observations and with the model results of Coupled Thermosphere-Ionosphere-Plasmasphere electrodynamics (CTIPe. CTIPe is an up-to-date version of CTIM that incorporates more IT dynamics such as a low-latitude ionosphere and a plasmasphere, but uses empirical magnetospheric input. OpenGGCM-CTIM reproduces localized neutral density peaks at ~ 400 km altitude in the high-latitude dayside regions in agreement with in situ observations during the pressure shock and the early phase of the storm. Although CTIPe is in some sense a much superior model than CTIM, it misses these localized enhancements. Unlike the CTIPe empirical input models, OpenGGCM-CTIM more faithfully produces localized increases of both auroral precipitation and ionospheric electric fields near the high-latitude dayside region after the pressure shock and after the storm onset

Estimate of the largest Lyapunov characteristic exponent of a high dimensional atmospheric global circulation model: a sensitivity analysis

International Nuclear Information System (INIS)

Guerrieri, A.

2009-01-01

In this report the largest Lyapunov characteristic exponent of a high dimensional atmospheric global circulation model of intermediate complexity has been estimated numerically. A sensitivity analysis has been carried out by varying the equator-to-pole temperature difference, the space resolution and the value of some parameters employed by the model. Chaotic and non-chaotic regimes of circulation have been found. [it

High-order sliding mode observer for fractional commensurate linear systems with unknown input

KAUST Repository

Belkhatir, Zehor; Laleg-Kirati, Taous-Meriem

2017-01-01

In this paper, a high-order sliding mode observer (HOSMO) is proposed for the joint estimation of the pseudo-state and the unknown input of fractional commensurate linear systems with single unknown input and a single output. The convergence of the proposed observer is proved using a Lyapunov-based approach. In addition, an enhanced variant of the proposed fractional-HOSMO is introduced to avoid the peaking phenomenon and thus to improve the estimation results in the transient phase. Simulation results are provided to illustrate the performance of the proposed fractional observer in both noise-free and noisy cases. The effect of the observer’s gains on the estimated pseudo-state and unknown input is also discussed.

High-order sliding mode observer for fractional commensurate linear systems with unknown input

KAUST Repository

Belkhatir, Zehor

2017-05-20

In this paper, a high-order sliding mode observer (HOSMO) is proposed for the joint estimation of the pseudo-state and the unknown input of fractional commensurate linear systems with single unknown input and a single output. The convergence of the proposed observer is proved using a Lyapunov-based approach. In addition, an enhanced variant of the proposed fractional-HOSMO is introduced to avoid the peaking phenomenon and thus to improve the estimation results in the transient phase. Simulation results are provided to illustrate the performance of the proposed fractional observer in both noise-free and noisy cases. The effect of the observer’s gains on the estimated pseudo-state and unknown input is also discussed.

High-dimensional model estimation and model selection

CERN Multimedia

CERN. Geneva

2015-01-01

I will review concepts and algorithms from high-dimensional statistics for linear model estimation and model selection. I will particularly focus on the so-called p>>n setting where the number of variables p is much larger than the number of samples n. I will focus mostly on regularized statistical estimators that produce sparse models. Important examples include the LASSO and its matrix extension, the Graphical LASSO, and more recent non-convex methods such as the TREX. I will show the applicability of these estimators in a diverse range of scientific applications, such as sparse interaction graph recovery and high-dimensional classification and regression problems in genomics.

Joint High-Dimensional Bayesian Variable and Covariance Selection with an Application to eQTL Analysis

KAUST Repository

Bhadra, Anindya

2013-04-22

We describe a Bayesian technique to (a) perform a sparse joint selection of significant predictor variables and significant inverse covariance matrix elements of the response variables in a high-dimensional linear Gaussian sparse seemingly unrelated regression (SSUR) setting and (b) perform an association analysis between the high-dimensional sets of predictors and responses in such a setting. To search the high-dimensional model space, where both the number of predictors and the number of possibly correlated responses can be larger than the sample size, we demonstrate that a marginalization-based collapsed Gibbs sampler, in combination with spike and slab type of priors, offers a computationally feasible and efficient solution. As an example, we apply our method to an expression quantitative trait loci (eQTL) analysis on publicly available single nucleotide polymorphism (SNP) and gene expression data for humans where the primary interest lies in finding the significant associations between the sets of SNPs and possibly correlated genetic transcripts. Our method also allows for inference on the sparse interaction network of the transcripts (response variables) after accounting for the effect of the SNPs (predictor variables). We exploit properties of Gaussian graphical models to make statements concerning conditional independence of the responses. Our method compares favorably to existing Bayesian approaches developed for this purpose. © 2013, The International Biometric Society.

Visualization of virtual slave manipulator using the master input device

International Nuclear Information System (INIS)

Kim, S. H.; Song, T. K.; Lee, J. Y.; Yoon, J. S.

2003-01-01

To handle the high level radioactive materials such a spent fuel, the Master-Slave Manipulators (MSM) are widely used as a remote handling device in nuclear facilities such as the hot cell with sealed and shielded space. In this paper, the Digital Mockup which simulates the remote operation of the Advanced Conditioning Process(ACP) is developed. Also, the workspace and the motion of the slave manipulator, as well as, the remote operation task should be analyzed. The process equipment of ACP and Maintenance/Handling Device are drawn in 3D CAD models using IGRIP. Modeling device of manipulator is assigned with various mobiles attributes such as a relative position, kinematics constraints, and a range of mobility. The 3D graphic simulator using the external input device of space ball displays the movement of manipulator. To connect the external input device to the graphic simulator, the interface program of external input device with 6 DOF is deigned using the Low Level Tele-operation Interface (LLTI). The experimental result shows that the developed simulation system gives much-improved human interface characteristics and shows satisfactory response characteristics in terms of synchronization speed. This should be useful for the development of work's education system in the virtual environment

MOSRA-Light; high speed three-dimensional nodal diffusion code for vector computers

Energy Technology Data Exchange (ETDEWEB)

Okumura, Keisuke [Japan Atomic Energy Research Inst., Tokai, Ibaraki (Japan). Tokai Research Establishment

1998-10-01

MOSRA-Light is a three-dimensional neutron diffusion calculation code for X-Y-Z geometry. It is based on the 4th order polynomial nodal expansion method (NEM). As the 4th order NEM is not sensitive to mesh sizes, accurate calculation is possible by the use of coarse meshes of about 20 cm. The drastic decrease of number of unknowns in a 3-dimensional problem results in very fast computation. Furthermore, it employs newly developed computation algorithm `boundary separated checkerboard sweep method` appropriate to vector computers. This method is very efficient because the speedup factor by vectorization increases, as a scale of problem becomes larger. Speed-up factor compared to the scalar calculation is from 20 to 40 in the case of PWR core calculation. Considering the both effects by the vectorization and the coarse mesh method, total speedup factor is more than 1000 as compared with conventional scalar code with the finite difference method. MOSRA-Light can be available on most of vector or scalar computers with the UNIX or it`s similar operating systems (e.g. freeware like Linux). Users can easily install it by the help of the conversation style installer. This report contains the general theory of NEM, the fast computation algorithm, benchmark calculation results and detailed information for usage of this code including input data instructions and sample input data. (author)

MOSRA-Light; high speed three-dimensional nodal diffusion code for vector computers

International Nuclear Information System (INIS)

Okumura, Keisuke

1998-10-01

MOSRA-Light is a three-dimensional neutron diffusion calculation code for X-Y-Z geometry. It is based on the 4th order polynomial nodal expansion method (NEM). As the 4th order NEM is not sensitive to mesh sizes, accurate calculation is possible by the use of coarse meshes of about 20 cm. The drastic decrease of number of unknowns in a 3-dimensional problem results in very fast computation. Furthermore, it employs newly developed computation algorithm 'boundary separated checkerboard sweep method' appropriate to vector computers. This method is very efficient because the speedup factor by vectorization increases, as a scale of problem becomes larger. Speed-up factor compared to the scalar calculation is from 20 to 40 in the case of PWR core calculation. Considering the both effects by the vectorization and the coarse mesh method, total speedup factor is more than 1000 as compared with conventional scalar code with the finite difference method. MOSRA-Light can be available on most of vector or scalar computers with the UNIX or it's similar operating systems (e.g. freeware like Linux). Users can easily install it by the help of the conversation style installer. This report contains the general theory of NEM, the fast computation algorithm, benchmark calculation results and detailed information for usage of this code including input data instructions and sample input data. (author)

State Estimation of International Space Station Centrifuge Rotor With Incomplete Knowledge of Disturbance Inputs

Science.gov (United States)

Sullivan, Michael J.

2005-01-01

This thesis develops a state estimation algorithm for the Centrifuge Rotor (CR) system where only relative measurements are available with limited knowledge of both rotor imbalance disturbances and International Space Station (ISS) thruster disturbances. A Kalman filter is applied to a plant model augmented with sinusoidal disturbance states used to model both the effect of the rotor imbalance and the 155 thrusters on the CR relative motion measurement. The sinusoidal disturbance states compensate for the lack of the availability of plant inputs for use in the Kalman filter. Testing confirms that complete disturbance modeling is necessary to ensure reliable estimation. Further testing goes on to show that increased estimator operational bandwidth can be achieved through the expansion of the disturbance model within the filter dynamics. In addition, Monte Carlo analysis shows the varying levels of robustness against defined plant/filter uncertainty variations.

Coupled multiview autoencoders with locality sensitivity for three-dimensional human pose estimation

Science.gov (United States)

Yu, Jialin; Sun, Jifeng; Luo, Shasha; Duan, Bichao

2017-09-01

Estimating three-dimensional (3D) human poses from a single camera is usually implemented by searching pose candidates with image descriptors. Existing methods usually suppose that the mapping from feature space to pose space is linear, but in fact, their mapping relationship is highly nonlinear, which heavily degrades the performance of 3D pose estimation. We propose a method to recover 3D pose from a silhouette image. It is based on the multiview feature embedding (MFE) and the locality-sensitive autoencoders (LSAEs). On the one hand, we first depict the manifold regularized sparse low-rank approximation for MFE and then the input image is characterized by a fused feature descriptor. On the other hand, both the fused feature and its corresponding 3D pose are separately encoded by LSAEs. A two-layer back-propagation neural network is trained by parameter fine-tuning and then used to map the encoded 2D features to encoded 3D poses. Our LSAE ensures a good preservation of the local topology of data points. Experimental results demonstrate the effectiveness of our proposed method.

Approximation of Quantities of Interest in Stochastic PDEs by the Random Discrete L^2 Projection on Polynomial Spaces

KAUST Repository

Migliorati, G.

2013-05-30

In this work we consider the random discrete L^2 projection on polynomial spaces (hereafter RDP) for the approximation of scalar quantities of interest (QOIs) related to the solution of a partial differential equation model with random input parameters. In the RDP technique the QOI is first computed for independent samples of the random input parameters, as in a standard Monte Carlo approach, and then the QOI is approximated by a multivariate polynomial function of the input parameters using a discrete least squares approach. We consider several examples including the Darcy equations with random permeability, the linear elasticity equations with random elastic coefficient, and the Navier--Stokes equations in random geometries and with random fluid viscosity. We show that the RDP technique is well suited to QOIs that depend smoothly on a moderate number of random parameters. Our numerical tests confirm the theoretical findings in [G. Migliorati, F. Nobile, E. von Schwerin, and R. Tempone, Analysis of the Discrete $L^2$ Projection on Polynomial Spaces with Random Evaluations, MOX report 46-2011, Politecnico di Milano, Milano, Italy, submitted], which have shown that, in the case of a single uniformly distributed random parameter, the RDP technique is stable and optimally convergent if the number of sampling points is proportional to the square of the dimension of the polynomial space. Here optimality means that the weighted $L^2$ norm of the RDP error is bounded from above by the best $L^\\\\infty$ error achievable in the given polynomial space, up to logarithmic factors. In the case of several random input parameters, the numerical evidence indicates that the condition on quadratic growth of the number of sampling points could be relaxed to a linear growth and still achieve stable and optimal convergence. This makes the RDP technique very promising for moderately high dimensional uncertainty quantification.

Underwater striling engine design with modified one-dimensional model

Directory of Open Access Journals (Sweden)

Daijin Li

2015-05-01

Full Text Available Stirling engines are regarded as an efficient and promising power system for underwater devices. Currently, many researches on one-dimensional model is used to evaluate thermodynamic performance of Stirling engine, but in which there are still some aspects which cannot be modeled with proper mathematical models such as mechanical loss or auxiliary power. In this paper, a four-cylinder double-acting Stirling engine for Unmanned Underwater Vehicles (UUVs is discussed. And a one-dimensional model incorporated with empirical equations of mechanical loss and auxiliary power obtained from experiments is derived while referring to the Stirling engine computer model of National Aeronautics and Space Administration (NASA. The P-40 Stirling engine with sufficient testing results from NASA is utilized to validate the accuracy of this one-dimensional model. It shows that the maximum error of output power of theoretical analysis results is less than 18% over testing results, and the maximum error of input power is no more than 9%. Finally, a Stirling engine for UUVs is designed with Schmidt analysis method and the modified one-dimensional model, and the results indicate this designed engine is capable of showing desired output power.

Linearized fermion-gravitation system in a (2+1)-dimensional space-time with Chern-Simons data

International Nuclear Information System (INIS)

Mello, E.R.B. de.

1990-01-01

The fermion-graviton system at linearized level in a (2+1)-dimensional space-time with the gravitational Chern-Simons term is studied. In this approximation it is shown that this system presents anomalous rotational properties and spin, in analogy with the gauge field-matter system. (A.C.A.S.) [pt

Free massless fermionic fields of arbitrary spin in d-dimensional anti-de Sitter space

Energy Technology Data Exchange (ETDEWEB)

Vasiliev, M A

1988-04-25

Free massless fermionic fields of arbitrary spins, corresponding to fully symmetric tensor-spinor irreducible representations of the flat little group SO(d-2), are described in d-dimensional anti-de Sitter space in terms of differential forms. Appropriate linearized higher-spin curvature 2-forms are found. Explicitly gauge invariant higher-spin actions are constructed in terms of these linearized curvatures.

Multisymplectic Structure-Preserving in Simple Finite Element Method in High Dimensional Case

Institute of Scientific and Technical Information of China (English)

BAI Yong-Qiang; LIU Zhen; PEI Ming; ZHENG Zhu-Jun

2003-01-01

In this paper, we study a finite element scheme of some semi-linear elliptic boundary value problems inhigh-dimensional space. With uniform mesh, we find that, the numerical scheme derived from finite element method cankeep a preserved multisymplectic structure.

Matrix correlations for high-dimensional data: The modified RV-coefficient

NARCIS (Netherlands)

Smilde, A.K.; Kiers, H.A.L.; Bijlsma, S.; Rubingh, C.M.; Erk, M.J. van

2009-01-01

Motivation: Modern functional genomics generates high-dimensional datasets. It is often convenient to have a single simple number characterizing the relationship between pairs of such high-dimensional datasets in a comprehensive way. Matrix correlations are such numbers and are appealing since they

Development of High Heat Input Welding Offshore Steel as Normalized Condition

Science.gov (United States)

Deng, Wei; Qin, Xiaomei

The heavy plate used for offshore structure is one of the important strategic products. In recent years, there is an increasing demand for heavy shipbuilding steel plate with excellent weldability in high heat input welding. During the thermal cycle, the microstructure of the heat affected zone (HAZ) of plates was damaged, and this markedly reduced toughness of HAZ. So, how to improve the toughness of HAZ has been a key subject in the fields of steel research. Oxide metallurgy is considered as an effective way to improve toughness of HAZ, because it could be used to retard grain growth by fine particles, which are stable at the high temperature.The high strength steel plate, which satisfies the low temperature specification, has been applied to offshore structure. Excellent properties of the plates and welded joints were obtained by oxide metallurgy technology, latest controlled rolling and accelerated cooling technology using Ultra-Fast Cooling (an on-line accelerated cooling system). The 355MPa-grade high strength steel plates with normalizing condition were obtained, and the steels have excellent weldability with heat input energy of 79 287kJ/cm, and the nil ductility transition (NDT) temperature was -70°C, which can satisfy the construction of offshore structure in cold regions.

Massive quantum field theory in two-dimensional Robertson-Walker space-time

International Nuclear Information System (INIS)

Bunch, T.S.; Christensen, S.M.; Fulling, S.A.

1978-01-01

The stress tensor of a massive scalar field, as an integral over normal modes (which are not mere plane waves), is regularized by covariant point separation. When the expectation value in a Parker-Fulling adiabatic vacuum state is expanded in the limit of small curvature-to-mass ratios, the series coincides in each order with the Schwinger-DeWitt-Christensen proper-time expansion. The renormalization ansatz suggested by these expansions (which applies to arbitrary curvature-to-mass ratios and arbitrary quantum state) can be implemented at the integrand level for practical computations. The renormalized tensor (1) passes in the massless limit, for appropriate choice of state, to the known vacuum stress of a massless field, (2) agrees with the explicit results of Bernard and Duncan for a special model, and (3) has a nonzero vacuum expectation value in the two-dimensional ''Milne universe'' (flat space in hyperbolic coordinates). Following Wald, we prove that the renormalized tensor is conserved and point out that there is no arbitrariness in the renormalization procedure. The general approach of this paper is applicable to four-dimensional models

Three-dimensional growth of human endothelial cells in an automated cell culture experiment container during the SpaceX CRS-8 ISS space mission - The SPHEROIDS project.

Science.gov (United States)

Pietsch, Jessica; Gass, Samuel; Nebuloni, Stefano; Echegoyen, David; Riwaldt, Stefan; Baake, Christin; Bauer, Johann; Corydon, Thomas J; Egli, Marcel; Infanger, Manfred; Grimm, Daniela

2017-04-01

Human endothelial cells (ECs) were sent to the International Space Station (ISS) to determine the impact of microgravity on the formation of three-dimensional structures. For this project, an automatic experiment unit (EU) was designed allowing cell culture in space. In order to enable a safe cell culture, cell nourishment and fixation after a pre-programmed timeframe, the materials used for construction of the EUs were tested in regard to their biocompatibility. These tests revealed a high biocompatibility for all parts of the EUs, which were in contact with the cells or the medium used. Most importantly, we found polyether ether ketones for surrounding the incubation chamber, which kept cellular viability above 80% and allowed the cells to adhere as long as they were exposed to normal gravity. After assembling the EU the ECs were cultured therein, where they showed good cell viability at least for 14 days. In addition, the functionality of the automatic medium exchange, and fixation procedures were confirmed. Two days before launch, the ECs were cultured in the EUs, which were afterwards mounted on the SpaceX CRS-8 rocket. 5 and 12 days after launch the cells were fixed. Subsequent analyses revealed a scaffold-free formation of spheroids in space. Copyright © 2017 Elsevier Ltd. All rights reserved.

Two-Dimensional Space-Time Dependent Multi-group Diffusion Equation with SLOR Method

International Nuclear Information System (INIS)

Yulianti, Y.; Su'ud, Z.; Waris, A.; Khotimah, S. N.

2010-01-01

The research of two-dimensional space-time diffusion equations with SLOR (Successive-Line Over Relaxation) has been done. SLOR method is chosen because this method is one of iterative methods that does not required to defined whole element matrix. The research is divided in two cases, homogeneous case and heterogeneous case. Homogeneous case has been inserted by step reactivity. Heterogeneous case has been inserted by step reactivity and ramp reactivity. In general, the results of simulations are agreement, even in some points there are differences.

Reactive scattering with row-orthonormal hyperspherical coordinates. 4. Four-dimensional-space Wigner rotation function for pentaatomic systems.

Science.gov (United States)

Kuppermann, Aron

2011-05-14

The row-orthonormal hyperspherical coordinate (ROHC) approach to calculating state-to-state reaction cross sections and bound state levels of N-atom systems requires the use of angular momentum tensors and Wigner rotation functions in a space of dimension N - 1. The properties of those tensors and functions are discussed for arbitrary N and determined for N = 5 in terms of the 6 Euler angles involved in 4-dimensional space.

Large Break LOCA Analysis with New downcomer Nodalizaion and Multi-Dimensional Model and Effect of Cross flow option in MARS code

Energy Technology Data Exchange (ETDEWEB)

Jang, Hyung-wook; Lee, Sang-yong; Oh, Seung-jong; Kim, Woong-bae [KEPCO International Nuclear Graduate School, Ulsan (Korea, Republic of)

2016-10-15

The phenomena of LOCA have been investigated for long time. The most extensive research project for LOCA was the 2D/3D program experiments. The results of the 2D/3D experiments show flow conditions in the downcomer during end-of-blowdown were highly multi-dimensional at full-scale. In this paper, the authors modified the nodalization of MARS code LBLOCA input deck and performed LBLOCA analysis with new input deck. An LBLOCA analysis for APR1400 with new downcomer input deck was conducted using KREM with MARS-KS 1.4 Version code. Analysis was processed under LBCOCA of 100% break size of cold leg case. The authors developed input deck with new downcomer nodalizaion and Multi-Dimensional downcomer model, then implemented LOCA analysis with new input decks and compared with existing analysis results. PCT from new input and multi-dimensional input deck shows similar PCT trend from original input deck. There occurred more rapid drop of PCT from new and multidimensional input deck than original input deck. PCT from new and multidimensional input deck are satisfied with PCT design limit. It can be concluded that there occurs no acceptance criteria issue even though new and multidimensional input deck are applied to LBLOCA analysis. In future study, comparative analysis with experiment results will be implemented.

A Recurrent Probabilistic Neural Network with Dimensionality Reduction Based on Time-series Discriminant Component Analysis.

Science.gov (United States)

Hayashi, Hideaki; Shibanoki, Taro; Shima, Keisuke; Kurita, Yuichi; Tsuji, Toshio

2015-12-01

This paper proposes a probabilistic neural network (NN) developed on the basis of time-series discriminant component analysis (TSDCA) that can be used to classify high-dimensional time-series patterns. TSDCA involves the compression of high-dimensional time series into a lower dimensional space using a set of orthogonal transformations and the calculation of posterior probabilities based on a continuous-density hidden Markov model with a Gaussian mixture model expressed in the reduced-dimensional space. The analysis can be incorporated into an NN, which is named a time-series discriminant component network (TSDCN), so that parameters of dimensionality reduction and classification can be obtained simultaneously as network coefficients according to a backpropagation through time-based learning algorithm with the Lagrange multiplier method. The TSDCN is considered to enable high-accuracy classification of high-dimensional time-series patterns and to reduce the computation time taken for network training. The validity of the TSDCN is demonstrated for high-dimensional artificial data and electroencephalogram signals in the experiments conducted during the study.

Non-commutative phase space and its space-time symmetry

International Nuclear Information System (INIS)

Li Kang; Dulat Sayipjamal

2010-01-01

First a description of 2+1 dimensional non-commutative (NC) phase space is presented, and then we find that in this formulation the generalized Bopp's shift has a symmetric representation and one can easily and straightforwardly define the star product on NC phase space. Then we define non-commutative Lorentz transformations both on NC space and NC phase space. We also discuss the Poincare symmetry. Finally we point out that our NC phase space formulation and the NC Lorentz transformations are applicable to any even dimensional NC space and NC phase space. (authors)

Theoretical formulation of finite-dimensional discrete phase spaces: I. Algebraic structures and uncertainty principles

International Nuclear Information System (INIS)

Marchiolli, M.A.; Ruzzi, M.

2012-01-01

We propose a self-consistent theoretical framework for a wide class of physical systems characterized by a finite space of states which allows us, within several mathematical virtues, to construct a discrete version of the Weyl–Wigner–Moyal (WWM) formalism for finite-dimensional discrete phase spaces with toroidal topology. As a first and important application from this ab initio approach, we initially investigate the Robertson–Schrödinger (RS) uncertainty principle related to the discrete coordinate and momentum operators, as well as its implications for physical systems with periodic boundary conditions. The second interesting application is associated with a particular uncertainty principle inherent to the unitary operators, which is based on the Wiener–Khinchin theorem for signal processing. Furthermore, we also establish a modified discrete version for the well-known Heisenberg–Kennard–Robertson (HKR) uncertainty principle, which exhibits additional terms (or corrections) that resemble the generalized uncertainty principle (GUP) into the context of quantum gravity. The results obtained from this new algebraic approach touch on some fundamental questions inherent to quantum mechanics and certainly represent an object of future investigations in physics. - Highlights: ► We construct a discrete version of the Weyl–Wigner–Moyal formalism. ► Coherent states for finite-dimensional discrete phase spaces are established. ► Discrete coordinate and momentum operators are properly defined. ► Uncertainty principles depend on the topology of finite physical systems. ► Corrections for the discrete Heisenberg uncertainty relation are also obtained.

Hypergraph-based anomaly detection of high-dimensional co-occurrences.

Science.gov (United States)

Silva, Jorge; Willett, Rebecca

2009-03-01

This paper addresses the problem of detecting anomalous multivariate co-occurrences using a limited number of unlabeled training observations. A novel method based on using a hypergraph representation of the data is proposed to deal with this very high-dimensional problem. Hypergraphs constitute an important extension of graphs which allow edges to connect more than two vertices simultaneously. A variational Expectation-Maximization algorithm for detecting anomalies directly on the hypergraph domain without any feature selection or dimensionality reduction is presented. The resulting estimate can be used to calculate a measure of anomalousness based on the False Discovery Rate. The algorithm has O(np) computational complexity, where n is the number of training observations and p is the number of potential participants in each co-occurrence event. This efficiency makes the method ideally suited for very high-dimensional settings, and requires no tuning, bandwidth or regularization parameters. The proposed approach is validated on both high-dimensional synthetic data and the Enron email database, where p > 75,000, and it is shown that it can outperform other state-of-the-art methods.

Characterization of 3-dimensional superconductive thin film components for gravitational experiments in space

Energy Technology Data Exchange (ETDEWEB)

Hechler, S.; Nawrodt, R.; Nietzsche, S.; Vodel, W.; Seidel, P. [Friedrich-Schiller-Univ. Jena (Germany). Inst. fuer Festkoerperphysik; Dittus, H. [ZARM, Univ. Bremen (Germany); Loeffler, F. [Physikalisch-Technische Bundesanstalt, Braunschweig (Germany)

2007-07-01

Superconducting quantum interference devices (SQUIDs) are used for high precise gravitational experiments. One of the most impressive experiments is the satellite test of the equivalence principle (STEP) of NASA/ESA. The STEP mission aims to prove a possible violation of Einstein's equivalence principle at an extreme level of accuracy of 1 part in 10{sup 18} in space. In this contribution we present an automatically working measurement equipment to characterize 3-dimensional superconducting thin film components like i.e. pick-up coils and test masses for STEP. The characterization is done by measurements of the transition temperature between the normal and the superconducting state using a special built anti-cryostat. Above all the setup was designed for use in normal LHe transport Dewars. The sample chamber has a volume of 150 cm{sup 3} and can be fully temperature controlled over a range from 4.2 K to 300 K with a resolution of better then 100 mK. (orig.)

Rare event simulation in finite-infinite dimensional space

International Nuclear Information System (INIS)

Au, Siu-Kui; Patelli, Edoardo

2016-01-01

Modern engineering systems are becoming increasingly complex. Assessing their risk by simulation is intimately related to the efficient generation of rare failure events. Subset Simulation is an advanced Monte Carlo method for risk assessment and it has been applied in different disciplines. Pivotal to its success is the efficient generation of conditional failure samples, which is generally non-trivial. Conventionally an independent-component Markov Chain Monte Carlo (MCMC) algorithm is used, which is applicable to high dimensional problems (i.e., a large number of random variables) without suffering from ‘curse of dimension’. Experience suggests that the algorithm may perform even better for high dimensional problems. Motivated by this, for any given problem we construct an equivalent problem where each random variable is represented by an arbitrary (hence possibly infinite) number of ‘hidden’ variables. We study analytically the limiting behavior of the algorithm as the number of hidden variables increases indefinitely. This leads to a new algorithm that is more generic and offers greater flexibility and control. It coincides with an algorithm recently suggested by independent researchers, where a joint Gaussian distribution is imposed between the current sample and the candidate. The present work provides theoretical reasoning and insights into the algorithm.

Solute transport with periodic input point source in one-dimensional ...

African Journals Online (AJOL)

JOY

groundwater flow velocity is considered proportional to multiple of temporal function and ζ th ... One-dimensional solute transport through porous media with or without .... solute free. ... the periodic concentration at source of the boundary i.e.,. 0.

On spectral distribution of high dimensional covariation matrices

DEFF Research Database (Denmark)

Heinrich, Claudio; Podolskij, Mark

In this paper we present the asymptotic theory for spectral distributions of high dimensional covariation matrices of Brownian diffusions. More specifically, we consider N-dimensional Itô integrals with time varying matrix-valued integrands. We observe n equidistant high frequency data points...... of the underlying Brownian diffusion and we assume that N/n -> c in (0,oo). We show that under a certain mixed spectral moment condition the spectral distribution of the empirical covariation matrix converges in distribution almost surely. Our proof relies on method of moments and applications of graph theory....

Pseudo inputs for pairwise learning with Gaussian processes

DEFF Research Database (Denmark)

Nielsen, Jens Brehm; Jensen, Bjørn Sand; Larsen, Jan

2012-01-01

We consider learning and prediction of pairwise comparisons between instances. The problem is motivated from a perceptual view point, where pairwise comparisons serve as an effective and extensively used paradigm. A state-of-the-art method for modeling pairwise data in high dimensional domains...... is based on a classical pairwise probit likelihood imposed with a Gaussian process prior. While extremely flexible, this non-parametric method struggles with an inconvenient O(n3) scaling in terms of the n input instances which limits the method only to smaller problems. To overcome this, we derive...... to other similar approximations that have been applied in standard Gaussian process regression and classification problems such as FI(T)C and PI(T)C....

HSM: Heterogeneous Subspace Mining in High Dimensional Data

DEFF Research Database (Denmark)

Müller, Emmanuel; Assent, Ira; Seidl, Thomas

2009-01-01

Heterogeneous data, i.e. data with both categorical and continuous values, is common in many databases. However, most data mining algorithms assume either continuous or categorical attributes, but not both. In high dimensional data, phenomena due to the "curse of dimensionality" pose additional...... challenges. Usually, due to locally varying relevance of attributes, patterns do not show across the full set of attributes. In this paper we propose HSM, which defines a new pattern model for heterogeneous high dimensional data. It allows data mining in arbitrary subsets of the attributes that are relevant...... for the respective patterns. Based on this model we propose an efficient algorithm, which is aware of the heterogeneity of the attributes. We extend an indexing structure for continuous attributes such that HSM indexing adapts to different attribute types. In our experiments we show that HSM efficiently mines...

Fast Estimation Method of Space-Time Two-Dimensional Positioning Parameters Based on Hadamard Product

Directory of Open Access Journals (Sweden)

Haiwen Li

2018-01-01

Full Text Available The estimation speed of positioning parameters determines the effectiveness of the positioning system. The time of arrival (TOA and direction of arrival (DOA parameters can be estimated by the space-time two-dimensional multiple signal classification (2D-MUSIC algorithm for array antenna. However, this algorithm needs much time to complete the two-dimensional pseudo spectral peak search, which makes it difficult to apply in practice. Aiming at solving this problem, a fast estimation method of space-time two-dimensional positioning parameters based on Hadamard product is proposed in orthogonal frequency division multiplexing (OFDM system, and the Cramer-Rao bound (CRB is also presented. Firstly, according to the channel frequency domain response vector of each array, the channel frequency domain estimation vector is constructed using the Hadamard product form containing location information. Then, the autocorrelation matrix of the channel response vector for the extended array element in frequency domain and the noise subspace are calculated successively. Finally, by combining the closed-form solution and parameter pairing, the fast joint estimation for time delay and arrival direction is accomplished. The theoretical analysis and simulation results show that the proposed algorithm can significantly reduce the computational complexity and guarantee that the estimation accuracy is not only better than estimating signal parameters via rotational invariance techniques (ESPRIT algorithm and 2D matrix pencil (MP algorithm but also close to 2D-MUSIC algorithm. Moreover, the proposed algorithm also has certain adaptability to multipath environment and effectively improves the ability of fast acquisition of location parameters.

Investigating Hydrocarbon Seep Environments with High-Resolution, Three-Dimensional Geographic Visualizations.

Science.gov (United States)

Doolittle, D. F.; Gharib, J. J.; Mitchell, G. A.

2015-12-01

Detailed photographic imagery and bathymetric maps of the seafloor acquired by deep submergence vehicles such as Autonomous Underwater Vehicles (AUV) and Remotely Operated Vehicles (ROV) are expanding how scientists and the public view and ultimately understand the seafloor and the processes that modify it. Several recently acquired optical and acoustic datasets, collected during ECOGIG (Ecosystem Impacts of Oil and Gas Inputs to the Gulf) and other Gulf of Mexico expeditions using the National Institute for Undersea Science Technology (NIUST) Eagle Ray, and Mola Mola AUVs, have been fused with lower resolution data to create unique three-dimensional geovisualizations. Included in these data are multi-scale and multi-resolution visualizations over hydrocarbon seeps and seep related features. Resolution of the data range from 10s of mm to 10s of m. When multi-resolution data is integrated into a single three-dimensional visual environment, new insights into seafloor and seep processes can be obtained from the intuitive nature of three-dimensional data exploration. We provide examples and demonstrate how integration of multibeam bathymetry, seafloor backscatter data, sub-bottom profiler data, textured photomosaics, and hull-mounted multibeam acoustic midwater imagery are made into a series a three-dimensional geovisualizations of actively seeping sites and associated chemosynthetic communities. From these combined and merged datasets, insights on seep community structure, morphology, ecology, fluid migration dynamics, and process geomorphology can be investigated from new spatial perspectives. Such datasets also promote valuable inter-comparisons of sensor resolution and performance.

Space-by-time manifold representation of dynamic facial expressions for emotion categorization

Science.gov (United States)

Delis, Ioannis; Chen, Chaona; Jack, Rachael E.; Garrod, Oliver G. B.; Panzeri, Stefano; Schyns, Philippe G.

2016-01-01

Visual categorization is the brain computation that reduces high-dimensional information in the visual environment into a smaller set of meaningful categories. An important problem in visual neuroscience is to identify the visual information that the brain must represent and then use to categorize visual inputs. Here we introduce a new mathematical formalism—termed space-by-time manifold decomposition—that describes this information as a low-dimensional manifold separable in space and time. We use this decomposition to characterize the representations used by observers to categorize the six classic facial expressions of emotion (happy, surprise, fear, disgust, anger, and sad). By means of a Generative Face Grammar, we presented random dynamic facial movements on each experimental trial and used subjective human perception to identify the facial movements that correlate with each emotion category. When the random movements projected onto the categorization manifold region corresponding to one of the emotion categories, observers categorized the stimulus accordingly; otherwise they selected “other.” Using this information, we determined both the Action Unit and temporal components whose linear combinations lead to reliable categorization of each emotion. In a validation experiment, we confirmed the psychological validity of the resulting space-by-time manifold representation. Finally, we demonstrated the importance of temporal sequencing for accurate emotion categorization and identified the temporal dynamics of Action Unit components that cause typical confusions between specific emotions (e.g., fear and surprise) as well as those resolving these confusions. PMID:27305521

Three-dimensional space changes after premature loss of a maxillary primary first molar.

Science.gov (United States)

Park, Kitae; Jung, Da-Woon; Kim, Ji-Yeon

2009-11-01

A space maintainer is generally preferred when a primary first molar is lost before or during active eruption of the first permanent molars in order to prevent space loss. However, controversy prevails regarding the space loss after eruption of the permanent first molars. The purpose of this study was to examine spatial changes subsequent to premature loss of a maxillary primary first molar after the eruption of the permanent first molars. Thirteen children, five girls and eight boys, expecting premature extraction of a maxillary primary first molar because of caries and/or failed pulp therapy, were selected. Spatial changes were investigated using a three-dimensional laser scanner by comparing the primary molar space, arch width, arch length, and arch perimeter before and after the extraction of a maxillary primary first molar. Also, the inclination and angulation changes in the maxillary primary canines, primary second molars, and permanent first molars adjacent to the extraction site were investigated before and after the extraction of the maxillary primary first molar in order to examine the source of space loss. There was no statistically significant space loss on the extraction side compared to the control side (P = 0.33). No consistent findings were seen on the inclination and angulation changes on the extraction side. The premature loss of a maxillary primary first molar, in cases with class I molar relationship, has limited influence on the space in permanent dentition.

COGEDIF - automatic TORT and DORT input generation from MORSE combinatorial geometry models

International Nuclear Information System (INIS)

Castelli, R.A.; Barnett, D.A.

1992-01-01

COGEDIF is an interactive utility which was developed to automate the preparation of two and three dimensional geometrical inputs for the ORNL-TORT and DORT discrete ordinates programs from complex three dimensional models described using the MORSE combinatorial geometry input description. The program creates either continuous or disjoint mesh input based upon the intersections of user defined meshing planes and the MORSE body definitions. The composition overlay of the combinatorial geometry is used to create the composition mapping of the discretized geometry based upon the composition found at the centroid of each of the mesh cells. This program simplifies the process of using discrete orthogonal mesh cells to represent non-orthogonal geometries in large models which require mesh sizes of the order of a million cells or more. The program was specifically written to take advantage of the new TORT disjoint mesh option which was developed at ORNL

Three-Dimensional Triplet Tracking for LHC and Future High Rate Experiments

CERN Document Server

Schöning, Andre

2014-10-20

The hit combinatorial problem is a main challenge for track reconstruction and triggering at high rate experiments. At hadron colliders the dominant fraction of hits is due to low momentum tracks for which multiple scattering (MS) effects dominate the hit resolution. MS is also the dominating source for hit confusion and track uncertainties in low energy precision experiments. In all such environments, where MS dominates, track reconstruction and fitting can be largely simplified by using three-dimensional (3D) hit-triplets as provided by pixel detectors. This simplification is possible since track uncertainties are solely determined by MS if high precision spatial information is provided. Fitting of hit-triplets is especially simple for tracking detectors in solenoidal magnetic fields. The over-constrained 3D-triplet method provides a complete set of track parameters and is robust against fake hit combinations. The triplet method is ideally suited for pixel detectors where hits can be treated as 3D-space poi...

Intracranial cerebrospinal fluid spaces imaging using a pulse-triggered three-dimensional turbo spin echo MR sequence with variable flip-angle distribution

International Nuclear Information System (INIS)

Hodel, Jerome; Silvera, Jonathan; Bekaert, Olivier; Decq, Philippe; Rahmouni, Alain; Bastuji-Garin, Sylvie; Vignaud, Alexandre; Petit, Eric; Durning, Bruno

2011-01-01

To assess the three-dimensional turbo spin echo with variable flip-angle distribution magnetic resonance sequence (SPACE: Sampling Perfection with Application optimised Contrast using different flip-angle Evolution) for the imaging of intracranial cerebrospinal fluid (CSF) spaces. We prospectively investigated 18 healthy volunteers and 25 patients, 20 with communicating hydrocephalus (CH), five with non-communicating hydrocephalus (NCH), using the SPACE sequence at 1.5T. Volume rendering views of both intracranial and ventricular CSF were obtained for all patients and volunteers. The subarachnoid CSF distribution was qualitatively evaluated on volume rendering views using a four-point scale. The CSF volumes within total, ventricular and subarachnoid spaces were calculated as well as the ratio between ventricular and subarachnoid CSF volumes. Three different patterns of subarachnoid CSF distribution were observed. In healthy volunteers we found narrowed CSF spaces within the occipital aera. A diffuse narrowing of the subarachnoid CSF spaces was observed in patients with NCH whereas patients with CH exhibited narrowed CSF spaces within the high midline convexity. The ratios between ventricular and subarachnoid CSF volumes were significantly different among the volunteers, patients with CH and patients with NCH. The assessment of CSF spaces volume and distribution may help to characterise hydrocephalus. (orig.)

Intracranial cerebrospinal fluid spaces imaging using a pulse-triggered three-dimensional turbo spin echo MR sequence with variable flip-angle distribution

Energy Technology Data Exchange (ETDEWEB)

Hodel, Jerome [Unite Analyse et Restauration du Mouvement, UMR-CNRS, 8005 LBM ParisTech Ensam, Paris (France); University Paris Est Creteil (UPEC), Creteil (France); Assistance Publique-Hopitaux de Paris, Paris (France); Hopital Henri Mondor, Department of Neuroradiology, Creteil (France); Hopital Henri Mondor, Creteil (France); Silvera, Jonathan [University Paris Est Creteil (UPEC), Creteil (France); Assistance Publique-Hopitaux de Paris, Paris (France); Hopital Henri Mondor, Department of Neuroradiology, Creteil (France); Bekaert, Olivier; Decq, Philippe [Unite Analyse et Restauration du Mouvement, UMR-CNRS, 8005 LBM ParisTech Ensam, Paris (France); University Paris Est Creteil (UPEC), Creteil (France); Assistance Publique-Hopitaux de Paris, Paris (France); Hopital Henri Mondor, Department of Neurosurgery, Creteil (France); Rahmouni, Alain [University Paris Est Creteil (UPEC), Creteil (France); Assistance Publique-Hopitaux de Paris, Paris (France); Hopital Henri Mondor, Department of Radiology, Creteil (France); Bastuji-Garin, Sylvie [University Paris Est Creteil (UPEC), Creteil (France); Assistance Publique-Hopitaux de Paris, Paris (France); Hopital Henri Mondor, Department of Public Health, Creteil (France); Vignaud, Alexandre [Siemens Healthcare, Saint Denis (France); Petit, Eric; Durning, Bruno [Laboratoire Images Signaux et Systemes Intelligents, UPEC, Creteil (France)

2011-02-15

To assess the three-dimensional turbo spin echo with variable flip-angle distribution magnetic resonance sequence (SPACE: Sampling Perfection with Application optimised Contrast using different flip-angle Evolution) for the imaging of intracranial cerebrospinal fluid (CSF) spaces. We prospectively investigated 18 healthy volunteers and 25 patients, 20 with communicating hydrocephalus (CH), five with non-communicating hydrocephalus (NCH), using the SPACE sequence at 1.5T. Volume rendering views of both intracranial and ventricular CSF were obtained for all patients and volunteers. The subarachnoid CSF distribution was qualitatively evaluated on volume rendering views using a four-point scale. The CSF volumes within total, ventricular and subarachnoid spaces were calculated as well as the ratio between ventricular and subarachnoid CSF volumes. Three different patterns of subarachnoid CSF distribution were observed. In healthy volunteers we found narrowed CSF spaces within the occipital aera. A diffuse narrowing of the subarachnoid CSF spaces was observed in patients with NCH whereas patients with CH exhibited narrowed CSF spaces within the high midline convexity. The ratios between ventricular and subarachnoid CSF volumes were significantly different among the volunteers, patients with CH and patients with NCH. The assessment of CSF spaces volume and distribution may help to characterise hydrocephalus. (orig.)

Restoring the Generalizability of SVM Based Decoding in High Dimensional Neuroimage Data

DEFF Research Database (Denmark)

Abrahamsen, Trine Julie; Hansen, Lars Kai

2011-01-01

Variance inflation is caused by a mismatch between linear projections of test and training data when projections are estimated on training sets smaller than the dimensionality of the feature space. We demonstrate that variance inflation can lead to an increased neuroimage decoding error rate...

On higher-dimensional loop algebras, pseudodifferential operators and Fock space realizations

International Nuclear Information System (INIS)

Westerberg, A.

1997-01-01

We discuss a previously discovered extension of the infinite-dimensional Lie algebra map(M,g) which generalizes the Kac-Moody algebras in 1+1 dimensions and the Mickelsson-Faddeev algebras in 3+1 dimensions to manifolds M of general dimensions. Furthermore, we review the method of regularizing current algebras in higher dimensions using pseudodifferential operator (PSDO) symbol calculus. In particular, we discuss the issue of Lie algebra cohomology of PSDOs and its relation to the Schwinger terms arising in the quantization process. Finally, we apply this regularization method to the algebra with partial success, and discuss the remaining obstacles to the construction of a Fock space representation. (orig.)

Conformal symmetry in two-dimensional space: recursion representation of conformal block

International Nuclear Information System (INIS)

Zamolodchikov, A.B.

1988-01-01

The four-point conformal block plays an important part in the analysis of the conformally invariant operator algebra in two-dimensional space. The behavior of the conformal block is calculated in the present paper in the limit in which the dimension Δ of the intermediate operator tends to infinity. This makes it possible to construct a recursion relation for this function that connects the conformal block at arbitrary Δ to the blocks corresponding to the dimensions of the zero vectors in the degenerate representations of the Virasoro algebra. The relation is convenient for calculating the expansion of the conformal block in powers of the uniformizing parameters q = i π tau

Secondary beam line phase space measurement and modeling at LAMPF

International Nuclear Information System (INIS)

Floyd, R.; Harrison, J.; Macek, R.; Sanders, G.

1979-01-01

Hardware and software have been developed for precision on-line measurement and fitting of secondary beam line phase space parameters. A system consisting of three MWPC planes for measuring particle trajectories, in coincidence with a time-of-flight telescope and a range telescope for particle identification, has been interfaced to a computer. Software has been developed for on-line track reconstruction, application of experimental cuts, and fitting of two-dimensional phase space ellipses for each particle species. The measured distributions have been found to agree well with the predictions of the Monte Carlo program DECAY TURTLE. The fitted phase space ellipses are a useful input to optimization routines, such as TRANSPORT, used to search for superior tunes. Application of this system to the LAMPF Stopped Muon Channel is described

Analysing spatially extended high-dimensional dynamics by recurrence plots

Energy Technology Data Exchange (ETDEWEB)

Marwan, Norbert, E-mail: marwan@pik-potsdam.de [Potsdam Institute for Climate Impact Research, 14412 Potsdam (Germany); Kurths, Jürgen [Potsdam Institute for Climate Impact Research, 14412 Potsdam (Germany); Humboldt Universität zu Berlin, Institut für Physik (Germany); Nizhny Novgorod State University, Department of Control Theory, Nizhny Novgorod (Russian Federation); Foerster, Saskia [GFZ German Research Centre for Geosciences, Section 1.4 Remote Sensing, Telegrafenberg, 14473 Potsdam (Germany)

2015-05-08

Recurrence plot based measures of complexity are capable tools for characterizing complex dynamics. In this letter we show the potential of selected recurrence plot measures for the investigation of even high-dimensional dynamics. We apply this method on spatially extended chaos, such as derived from the Lorenz96 model and show that the recurrence plot based measures can qualitatively characterize typical dynamical properties such as chaotic or periodic dynamics. Moreover, we demonstrate its power by analysing satellite image time series of vegetation cover with contrasting dynamics as a spatially extended and potentially high-dimensional example from the real world. - Highlights: • We use recurrence plots for analysing partially extended dynamics. • We investigate the high-dimensional chaos of the Lorenz96 model. • The approach distinguishes different spatio-temporal dynamics. • We use the method for studying vegetation cover time series.

Accelerating solutions of one-dimensional unsteady PDEs with GPU-based swept time-space decomposition

Science.gov (United States)

Magee, Daniel J.; Niemeyer, Kyle E.

2018-03-01

The expedient design of precision components in aerospace and other high-tech industries requires simulations of physical phenomena often described by partial differential equations (PDEs) without exact solutions. Modern design problems require simulations with a level of resolution difficult to achieve in reasonable amounts of time-even in effectively parallelized solvers. Though the scale of the problem relative to available computing power is the greatest impediment to accelerating these applications, significant performance gains can be achieved through careful attention to the details of memory communication and access. The swept time-space decomposition rule reduces communication between sub-domains by exhausting the domain of influence before communicating boundary values. Here we present a GPU implementation of the swept rule, which modifies the algorithm for improved performance on this processing architecture by prioritizing use of private (shared) memory, avoiding interblock communication, and overwriting unnecessary values. It shows significant improvement in the execution time of finite-difference solvers for one-dimensional unsteady PDEs, producing speedups of 2 - 9 × for a range of problem sizes, respectively, compared with simple GPU versions and 7 - 300 × compared with parallel CPU versions. However, for a more sophisticated one-dimensional system of equations discretized with a second-order finite-volume scheme, the swept rule performs 1.2 - 1.9 × worse than a standard implementation for all problem sizes.

Method of solving conformal models in D-dimensional space 2: A family of exactly solvable models in D > 2

International Nuclear Information System (INIS)

Fradkin, E.S.; Palchik, M.Ya.

1996-02-01

We study a family of exactly solvable models of conformally-invariant quantum field theory in D-dimensional space. We demonstrate the existence of D-dimensional analogs of primary and secondary fields. Under the action of energy-momentum tensor and conserved currents, the primary fields creates an infinite set of (tensor) secondary fields of different generations. The commutators of secondary fields with zero components of current and energy-momentum tensor include anomalous operator terms. We show that the Hilbert space of conformal theory has a special sector which structure is solely defined by the Ward identities independently on the choice of dynamical model. The states of this sector are constructed from secondary fields. Definite self-consistent conditions on the states of the latter sector fix the choice of the field model uniquely. In particular, Lagrangian models do belong to this class of models. The above self-consistent conditions are formulated as follows. Special superpositions Q s , s = 1,2,... of secondary fields are constructed. Each superposition is determined by the requirement that the form of its commutators with energy-momentum tensor and current (i.e. transformation properties) should be identical to that of a primary field. Each equation Q s (x) = 0 is consistent, and defines an exactly solvable model for D ≥ 3. The structure of these models are analogous to that of well-known two dimensional conformal models. The states Q s (x) modul 0> are analogous to the null-vectors of two dimensional theory. In each of these models one can obtain a closed set of differential equations for all the higher Green functions, as well as algebraic equations relating the scale dimension of fundamental field to the D-dimensional analog of a central charge. As an example, we present a detailed discussion of a pair of exactly solvable models in even-dimensional space D ≥ 4. (author). 28 refs

Axes of resistance for tooth movement: does the center of resistance exist in 3-dimensional space?

Science.gov (United States)

Viecilli, Rodrigo F; Budiman, Amanda; Burstone, Charles J

2013-02-01

The center of resistance is considered the most important reference point for tooth movement. It is often stated that forces through this point will result in tooth translation. The purpose of this article is to report the results of numeric experiments testing the hypothesis that centers of resistance do not exist in space as 3-dimensional points, primarily because of the geometric asymmetry of the periodontal ligament. As an alternative theory, we propose that, for an arbitrary tooth, translation references can be determined by 2-dimensional projection intersections of 3-dimensional axes of resistance. Finite element analyses were conducted on a maxillary first molar model to determine the position of the axes of rotation generated by 3-dimensional couples. Translation tests were performed to compare tooth movement by using different combinations of axes of resistance as references. The couple-generated axes of rotation did not intersect in 3 dimensions; therefore, they do not determine a 3-dimensional center of resistance. Translation was obtained by using projection intersections of the 2 axes of resistance perpendicular to the force direction. Three-dimensional axes of resistance, or their 2-dimensional projection intersections, should be used to plan movement of an arbitrary tooth. Clinical approximations to a small 3-dimensional "center of resistance volume" might be adequate in nearly symmetric periodontal ligament cases. Copyright © 2013 American Association of Orthodontists. Published by Mosby, Inc. All rights reserved.

Three-Dimensional Messages for Interstellar Communication

Science.gov (United States)

Vakoch, Douglas A.

One of the challenges facing independently evolved civilizations separated by interstellar distances is to communicate information unique to one civilization. One commonly proposed solution is to begin with two-dimensional pictorial representations of mathematical concepts and physical objects, in the hope that this will provide a foundation for overcoming linguistic barriers. However, significant aspects of such representations are highly conventional, and may not be readily intelligible to a civilization with different conventions. The process of teaching conventions of representation may be facilitated by the use of three-dimensional representations redundantly encoded in multiple formats (e.g., as both vectors and as rasters). After having illustrated specific conventions for representing mathematical objects in a three-dimensional space, this method can be used to describe a physical environment shared by transmitter and receiver: a three-dimensional space defined by the transmitter--receiver axis, and containing stars within that space. This method can be extended to show three-dimensional representations varying over time. Having clarified conventions for representing objects potentially familiar to both sender and receiver, novel objects can subsequently be depicted. This is illustrated through sequences showing interactions between human beings, which provide information about human behavior and personality. Extensions of this method may allow the communication of such culture-specific features as aesthetic judgments and religious beliefs. Limitations of this approach will be noted, with specific reference to ETI who are not primarily visual.

Nonperturbative construction of nonrenormalizable models of quantum field theory in four-dimensional space-time

International Nuclear Information System (INIS)

Raczka, R.

1979-01-01

Construction of non-cutoff Euclidean Green's functions for nonrenormalizable interactions Lsub(I)(phi)=lambda∫dσ(epsilon):expepsilonphi: in four-dimensional space-time is presented. It is shown that all axioms for the generating functional of E.G.F. are satisfied except perhaps the SO(4) invariance. It is shown that the singularities of E.G.F. for coinciding points are not worse than those of the free theory. (author)

An angle-based subspace anomaly detection approach to high-dimensional data: With an application to industrial fault detection

International Nuclear Information System (INIS)

Zhang, Liangwei; Lin, Jing; Karim, Ramin

2015-01-01

The accuracy of traditional anomaly detection techniques implemented on full-dimensional spaces degrades significantly as dimensionality increases, thereby hampering many real-world applications. This work proposes an approach to selecting meaningful feature subspace and conducting anomaly detection in the corresponding subspace projection. The aim is to maintain the detection accuracy in high-dimensional circumstances. The suggested approach assesses the angle between all pairs of two lines for one specific anomaly candidate: the first line is connected by the relevant data point and the center of its adjacent points; the other line is one of the axis-parallel lines. Those dimensions which have a relatively small angle with the first line are then chosen to constitute the axis-parallel subspace for the candidate. Next, a normalized Mahalanobis distance is introduced to measure the local outlier-ness of an object in the subspace projection. To comprehensively compare the proposed algorithm with several existing anomaly detection techniques, we constructed artificial datasets with various high-dimensional settings and found the algorithm displayed superior accuracy. A further experiment on an industrial dataset demonstrated the applicability of the proposed algorithm in fault detection tasks and highlighted another of its merits, namely, to provide preliminary interpretation of abnormality through feature ordering in relevant subspaces. - Highlights: • An anomaly detection approach for high-dimensional reliability data is proposed. • The approach selects relevant subspaces by assessing vectorial angles. • The novel ABSAD approach displays superior accuracy over other alternatives. • Numerical illustration approves its efficacy in fault detection applications

Reconstruction of neuronal input through modeling single-neuron dynamics and computations

International Nuclear Information System (INIS)

Qin, Qing; Wang, Jiang; Yu, Haitao; Deng, Bin; Chan, Wai-lok

2016-01-01

Mathematical models provide a mathematical description of neuron activity, which can better understand and quantify neural computations and corresponding biophysical mechanisms evoked by stimulus. In this paper, based on the output spike train evoked by the acupuncture mechanical stimulus, we present two different levels of models to describe the input-output system to achieve the reconstruction of neuronal input. The reconstruction process is divided into two steps: First, considering the neuronal spiking event as a Gamma stochastic process. The scale parameter and the shape parameter of Gamma process are, respectively, defined as two spiking characteristics, which are estimated by a state-space method. Then, leaky integrate-and-fire (LIF) model is used to mimic the response system and the estimated spiking characteristics are transformed into two temporal input parameters of LIF model, through two conversion formulas. We test this reconstruction method by three different groups of simulation data. All three groups of estimates reconstruct input parameters with fairly high accuracy. We then use this reconstruction method to estimate the non-measurable acupuncture input parameters. Results show that under three different frequencies of acupuncture stimulus conditions, estimated input parameters have an obvious difference. The higher the frequency of the acupuncture stimulus is, the higher the accuracy of reconstruction is.

Reconstruction of neuronal input through modeling single-neuron dynamics and computations

Energy Technology Data Exchange (ETDEWEB)

Qin, Qing; Wang, Jiang; Yu, Haitao; Deng, Bin, E-mail: dengbin@tju.edu.cn; Chan, Wai-lok [School of Electrical Engineering and Automation, Tianjin University, Tianjin 300072 (China)

2016-06-15

Mathematical models provide a mathematical description of neuron activity, which can better understand and quantify neural computations and corresponding biophysical mechanisms evoked by stimulus. In this paper, based on the output spike train evoked by the acupuncture mechanical stimulus, we present two different levels of models to describe the input-output system to achieve the reconstruction of neuronal input. The reconstruction process is divided into two steps: First, considering the neuronal spiking event as a Gamma stochastic process. The scale parameter and the shape parameter of Gamma process are, respectively, defined as two spiking characteristics, which are estimated by a state-space method. Then, leaky integrate-and-fire (LIF) model is used to mimic the response system and the estimated spiking characteristics are transformed into two temporal input parameters of LIF model, through two conversion formulas. We test this reconstruction method by three different groups of simulation data. All three groups of estimates reconstruct input parameters with fairly high accuracy. We then use this reconstruction method to estimate the non-measurable acupuncture input parameters. Results show that under three different frequencies of acupuncture stimulus conditions, estimated input parameters have an obvious difference. The higher the frequency of the acupuncture stimulus is, the higher the accuracy of reconstruction is.

A two dimensional fibre reinforced micropolar thermoelastic problem for a half-space subjected to mechanical force

Directory of Open Access Journals (Sweden)

Ailawalia Praveen

2015-01-01

Full Text Available The purpose of this paper is to study the two dimensional deformation of fibre reinforced micropolar thermoelastic medium in the context of Green-Lindsay theory of thermoelasticity. A mechanical force is applied along the interface of fluid half space and fibre reinforced micropolar thermoelastic half space. The normal mode analysis has been applied to obtain the exact expressions for displacement component, force stress, temperature distribution and tangential couple stress. The effect of anisotropy and micropolarity on the displacement component, force stress, temperature distribution and tangential couple stress has been depicted graphically.

ETFOD: a point model physics code with arbitrary input

International Nuclear Information System (INIS)

Rothe, K.E.; Attenberger, S.E.

1980-06-01

ETFOD is a zero-dimensional code which solves a set of physics equations by minimization. The technique used is different than normally used, in that the input is arbitrary. The user is supplied with a set of variables from which he specifies which variables are input (unchanging). The remaining variables become the output. Presently the code is being used for ETF reactor design studies. The code was written in a manner to allow easy modificaton of equations, variables, and physics calculations. The solution technique is presented along with hints for using the code

All ASD complex and real 4-dimensional Einstein spaces with Λ≠0 admitting a nonnull Killing vector

Science.gov (United States)

Chudecki, Adam

2016-12-01

Anti-self-dual (ASD) 4-dimensional complex Einstein spaces with nonzero cosmological constant Λ equipped with a nonnull Killing vector are considered. It is shown that any conformally nonflat metric of such spaces can be always brought to a special form and the Einstein field equations can be reduced to the Boyer-Finley-Plebański equation (Toda field equation). Some alternative forms of the metric are discussed. All possible real slices (neutral, Euclidean and Lorentzian) of ASD complex Einstein spaces with Λ≠0 admitting a nonnull Killing vector are found.

The metric on field space, functional renormalization, and metric–torsion quantum gravity

International Nuclear Information System (INIS)

Reuter, Martin; Schollmeyer, Gregor M.

2016-01-01

Searching for new non-perturbatively renormalizable quantum gravity theories, functional renormalization group (RG) flows are studied on a theory space of action functionals depending on the metric and the torsion tensor, the latter parameterized by three irreducible component fields. A detailed comparison with Quantum Einstein–Cartan Gravity (QECG), Quantum Einstein Gravity (QEG), and “tetrad-only” gravity, all based on different theory spaces, is performed. It is demonstrated that, over a generic theory space, the construction of a functional RG equation (FRGE) for the effective average action requires the specification of a metric on the infinite-dimensional field manifold as an additional input. A modified FRGE is obtained if this metric is scale-dependent, as it happens in the metric–torsion system considered.

New efficient five-input majority gate for quantum-dot cellular automata

International Nuclear Information System (INIS)

Farazkish, Razieh; Navi, Keivan

2012-01-01

A novel fault-tolerant five-input majority gate for quantum-dot cellular automata is presented. Quantum-dot cellular automata (QCA) is an emerging technology which is considered to be presented in future computers. Two principle logic elements in QCA are “majority gate” and “inverter.” In this paper, we propose a new approach to the design of fault-tolerant five-input majority gate by considering two-dimensional arrays of QCA cells. We analyze fault tolerance properties of such block five-input majority gate in terms of misalignment, missing, and dislocation cells. Some physical proofs are used for verifying five-input majority gate circuit layout and functionality. Our results clearly demonstrate that the redundant version of the block five-input majority gate is more robust than the standard style for this gate.

The Group Evacuation Behavior Based on Fire Effect in the Complicated Three-Dimensional Space

Directory of Open Access Journals (Sweden)

Jun Hu

2014-01-01

Full Text Available In order to effectively depict the group evacuation behavior in the complicated three-dimensional space, a novel pedestrian flow model is proposed with three-dimensional cellular automata. In this model the calculation methods of floor field and fire gain are elaborated at first, and the transition gain of target position at the next moment is defined. Then, in consideration of pedestrian intimacy and velocity change, the group evacuation strategy and evolution rules are given. Finally, the experiments were conducted with the simulation platform to study the relationships of evacuation time, pedestrian density, average system velocity, and smoke spreading velocity. The results had shown that large-scale group evacuation should be avoided, and in case of large pedestrian density, the shortest route of evacuation strategy would extend system evacuation time.

High Input Voltage Hall Thruster Discharge Converter, Phase I

Data.gov (United States)

National Aeronautics and Space Administration — The overall scope of this Phase I/II effort is the development of a high efficiency 15kW (nominal) Hall thruster discharge converter. In Phase I, Busek Co. Inc. will...

Rotation-type input-output relationships for Wigner distribution moments in fractional Fourier transform systems

NARCIS (Netherlands)

Bastiaans, M.J.; Alieva, T.

2002-01-01

It is shown how all global Wigner distribution moments of arbitrary order in the output plane of a (generally anamorphic) two-dimensional fractional Fourier transform system can be expressed in terms of the moments in the input plane. This general input-output relationship is then broken down into a

Stability and Existence Results for Quasimonotone Quasivariational Inequalities in Finite Dimensional Spaces

Energy Technology Data Exchange (ETDEWEB)

Castellani, Marco; Giuli, Massimiliano, E-mail: massimiliano.giuli@univaq.it [University of L’Aquila, Department of Information Engineering, Computer Science and Mathematics (Italy)

2016-02-15

We study pseudomonotone and quasimonotone quasivariational inequalities in a finite dimensional space. In particular we focus our attention on the closedness of some solution maps associated to a parametric quasivariational inequality. From this study we derive two results on the existence of solutions of the quasivariational inequality. On the one hand, assuming the pseudomonotonicity of the operator, we get the nonemptiness of the set of the classical solutions. On the other hand, we show that the quasimonoticity of the operator implies the nonemptiness of the set of nonzero solutions. An application to traffic network is also considered.

Stability and Existence Results for Quasimonotone Quasivariational Inequalities in Finite Dimensional Spaces

International Nuclear Information System (INIS)

Castellani, Marco; Giuli, Massimiliano

2016-01-01

We study pseudomonotone and quasimonotone quasivariational inequalities in a finite dimensional space. In particular we focus our attention on the closedness of some solution maps associated to a parametric quasivariational inequality. From this study we derive two results on the existence of solutions of the quasivariational inequality. On the one hand, assuming the pseudomonotonicity of the operator, we get the nonemptiness of the set of the classical solutions. On the other hand, we show that the quasimonoticity of the operator implies the nonemptiness of the set of nonzero solutions. An application to traffic network is also considered

A High-power Electric Propulsion Test Platform in Space

Science.gov (United States)

Petro, Andrew J.; Reed, Brian; Chavers, D. Greg; Sarmiento, Charles; Cenci, Susanna; Lemmons, Neil

2005-01-01

This paper will describe the results of the preliminary phase of a NASA design study for a facility to test high-power electric propulsion systems in space. The results of this design study are intended to provide a firm foundation for subsequent detailed design and development activities leading to the deployment of a valuable space facility. The NASA Exploration Systems Mission Directorate is sponsoring this design project. A team from the NASA Johnson Space Center, Glenn Research Center, the Marshall Space Flight Center and the International Space Station Program Office is conducting the project. The test facility is intended for a broad range of users including government, industry and universities. International participation is encouraged. The objectives for human and robotic exploration of space can be accomplished affordably, safely and effectively with high-power electric propulsion systems. But, as thruster power levels rise to the hundreds of kilowatts and up to megawatts, their testing will pose stringent and expensive demands on existing Earth-based vacuum facilities. These considerations and the human access to near-Earth space provided by the International Space Station (ISS) have led to a renewed interest in space testing. The ISS could provide an excellent platform for a space-based test facility with the continuous vacuum conditions of the natural space environment and no chamber walls to modify the open boundary conditions of the propulsion system exhaust. The test platform could take advantage of the continuous vacuum conditions of the natural space environment. Space testing would provide open boundary conditions without walls, micro-gravity and a realistic thermal environment. Testing on the ISS would allow for direct observation of the test unit, exhaust plume and space-plasma interactions. When necessary, intervention by on-board personnel and post-test inspection would be possible. The ISS can provide electrical power, a location for

Evaluation of Reduced Power Spectra from Three-Dimensional k-Space

Science.gov (United States)

Saur, J.; von Papen, M.

2014-12-01

We present a new tool to evaluate one dimensional reduced power spectral densities (PSD) from arbitrary energy distributions in kk-space. This enables us to calculate the power spectra as they are measured in spacecraft frame for any given measurement geometry assuming Taylor's frozen-in approximation. It is possible to seperately calculate the diagonal elements of the spectral tensor and also to insert additional, non-turbulent energy in kk-space (e.g. mirror mode waves). Given a critically balanced turbulent cascade with k∥˜kα⊥k_\\|sim k_perp^alpha, we explore the implications on the spectral form of the PSD and the functional dependence of the spectral index κkappa on the field-to-flow angle θtheta between plasma flow and background magnetic field. We show that critically balanced turbulence develops a θtheta-independent cascade with the spectral slope of the perpendicular cascade κ(θ=90∘)kappa(theta{=}90^circ). This happens at frequencies f>fmaxf>f_mathrm{max}, where fmax(L,α,θ)f_mathrm{max}(L,alpha,theta) is a function of outer scale LL, critical balance exponent αalpha and field-to-flow angle θtheta. We also discuss potential damping terms acting on the kk-space distribution of energy and their effect on the PSD. Further, we show that the functional dependence κ(θ)kappa(theta) as found by textit{Horbury et al.} (2008) and textit{Chen et al.} (2010) can be explained with a damped critically balanced turbulence model.

OSCIL: one-dimensional spring-mass system simulator for seismic analysis of high temperature gas cooled reactor core

International Nuclear Information System (INIS)

Lasker, L.

1976-01-01

OSCIL is a program to predict the effects of seismic input on a HTGR core. The present model is a one-dimensional array of blocks with appropriate spring constants, inter-elemental and ground damping, and clearances. It can be used more generally for systems of moving masses separated by nonlinear springs and dampers

OSCIL: one-dimensional spring-mass system simulator for seismic analysis of high temperature gas cooled reactor core

Energy Technology Data Exchange (ETDEWEB)

Lasker, L. (ed.)

1976-01-01

OSCIL is a program to predict the effects of seismic input on a HTGR core. The present model is a one-dimensional array of blocks with appropriate spring constants, inter-elemental and ground damping, and clearances. It can be used more generally for systems of moving masses separated by nonlinear springs and dampers.

CMOS single-stage input-powered bridge rectifier with boost switch and duty cycle control

Science.gov (United States)

Radzuan, Roskhatijah; Mohd Salleh, Mohd Khairul; Hamzah, Mustafar Kamal; Ab Wahab, Norfishah

2017-06-01

This paper presents a single-stage input-powered bridge rectifier with boost switch for wireless-powered devices such as biomedical implants and wireless sensor nodes. Realised using CMOS process technology, it employs a duty cycle switch control to achieve high output voltage using boost technique, leading to a high output power conversion. It has only six external connections with the boost inductance. The input frequency of the bridge rectifier is set at 50 Hz, while the switching frequency is 100 kHz. The proposed circuit is fabricated on a single 0.18-micron CMOS die with a space area of 0.024 mm2. The simulated and measured results show good agreement.

Relativistic three-dimensional Lippmann-Schwinger cross sections for space radiation applications

Science.gov (United States)

Werneth, C. M.; Xu, X.; Norman, R. B.; Maung, K. M.

2017-12-01

Radiation transport codes require accurate nuclear cross sections to compute particle fluences inside shielding materials. The Tripathi semi-empirical reaction cross section, which includes over 60 parameters tuned to nucleon-nucleus (NA) and nucleus-nucleus (AA) data, has been used in many of the world's best-known transport codes. Although this parameterization fits well to reaction cross section data, the predictive capability of any parameterization is questionable when it is used beyond the range of the data to which it was tuned. Using uncertainty analysis, it is shown that a relativistic three-dimensional Lippmann-Schwinger (LS3D) equation model based on Multiple Scattering Theory (MST) that uses 5 parameterizations-3 fundamental parameterizations to nucleon-nucleon (NN) data and 2 nuclear charge density parameterizations-predicts NA and AA reaction cross sections as well as the Tripathi cross section parameterization for reactions in which the kinetic energy of the projectile in the laboratory frame (TLab) is greater than 220 MeV/n. The relativistic LS3D model has the additional advantage of being able to predict highly accurate total and elastic cross sections. Consequently, it is recommended that the relativistic LS3D model be used for space radiation applications in which TLab > 220MeV /n .

The role of extreme orbits in the global organization of periodic regions in parameter space for one dimensional maps

Science.gov (United States)

da Costa, Diogo Ricardo; Hansen, Matheus; Guarise, Gustavo; Medrano-T, Rene O.; Leonel, Edson D.

2016-04-01

We show that extreme orbits, trajectories that connect local maximum and minimum values of one dimensional maps, play a major role in the parameter space of dissipative systems dictating the organization for the windows of periodicity, hence producing sets of shrimp-like structures. Here we solve three fundamental problems regarding the distribution of these sets and give: (i) their precise localization in the parameter space, even for sets of very high periods; (ii) their local and global distributions along cascades; and (iii) the association of these cascades to complicate sets of periodicity. The extreme orbits are proved to be a powerful indicator to investigate the organization of windows of periodicity in parameter planes. As applications of the theory, we obtain some results for the circle map and perturbed logistic map. The formalism presented here can be extended to many other different nonlinear and dissipative systems.

Analysis of chaos in high-dimensional wind power system.

Science.gov (United States)

Wang, Cong; Zhang, Hongli; Fan, Wenhui; Ma, Ping

2018-01-01

A comprehensive analysis on the chaos of a high-dimensional wind power system is performed in this study. A high-dimensional wind power system is more complex than most power systems. An 11-dimensional wind power system proposed by Huang, which has not been analyzed in previous studies, is investigated. When the systems are affected by external disturbances including single parameter and periodic disturbance, or its parameters changed, chaotic dynamics of the wind power system is analyzed and chaotic parameters ranges are obtained. Chaos existence is confirmed by calculation and analysis of all state variables' Lyapunov exponents and the state variable sequence diagram. Theoretical analysis and numerical simulations show that the wind power system chaos will occur when parameter variations and external disturbances change to a certain degree.

Higher-dimensional Bianchi type-VIh cosmologies

Science.gov (United States)

Lorenz-Petzold, D.

1985-09-01

The higher-dimensional perfect fluid equations of a generalization of the (1 + 3)-dimensional Bianchi type-VIh space-time are discussed. Bianchi type-V and Bianchi type-III space-times are also included as special cases. It is shown that the Chodos-Detweiler (1980) mechanism of cosmological dimensional-reduction is possible in these cases.

Two-dimensional computer simulation of high intensity proton beams

CERN Document Server

Lapostolle, Pierre M

1972-01-01

A computer program has been developed which simulates the two- dimensional transverse behaviour of a proton beam in a focusing channel. The model is represented by an assembly of a few thousand 'superparticles' acted upon by their own self-consistent electric field and an external focusing force. The evolution of the system is computed stepwise in time by successively solving Poisson's equation and Newton's law of motion. Fast Fourier transform techniques are used for speed in the solution of Poisson's equation, while extensive area weighting is utilized for the accurate evaluation of electric field components. A computer experiment has been performed on the CERN CDC 6600 computer to study the nonlinear behaviour of an intense beam in phase space, showing under certain circumstances a filamentation due to space charge and an apparent emittance growth. (14 refs).

Design and implementation of space physics multi-model application integration based on web

Science.gov (United States)

Jiang, Wenping; Zou, Ziming

With the development of research on space environment and space science, how to develop network online computing environment of space weather, space environment and space physics models for Chinese scientific community is becoming more and more important in recent years. Currently, There are two software modes on space physics multi-model application integrated system (SPMAIS) such as C/S and B/S. the C/S mode which is traditional and stand-alone, demands a team or workshop from many disciplines and specialties to build their own multi-model application integrated system, that requires the client must be deployed in different physical regions when user visits the integrated system. Thus, this requirement brings two shortcomings: reducing the efficiency of researchers who use the models to compute; inconvenience of accessing the data. Therefore, it is necessary to create a shared network resource access environment which could help users to visit the computing resources of space physics models through the terminal quickly for conducting space science research and forecasting spatial environment. The SPMAIS develops high-performance, first-principles in B/S mode based on computational models of the space environment and uses these models to predict "Space Weather", to understand space mission data and to further our understanding of the solar system. the main goal of space physics multi-model application integration system (SPMAIS) is to provide an easily and convenient user-driven online models operating environment. up to now, the SPMAIS have contained dozens of space environment models , including international AP8/AE8 IGRF T96 models and solar proton prediction model geomagnetic transmission model etc. which are developed by Chinese scientists. another function of SPMAIS is to integrate space observation data sets which offers input data for models online high-speed computing. In this paper, service-oriented architecture (SOA) concept that divides system into

Three dimensional range geometry and texture data compression with space-filling curves.

Science.gov (United States)

Chen, Xia; Zhang, Song

2017-10-16

This paper presents a novel method to effectively store three-dimensional (3D) data and 2D texture data into a regular 24-bit image. The proposed method uses the Hilbert space-filling curve to map the normalized unwrapped phase map to two 8-bit color channels, and saves the third color channel for 2D texture storage. By further leveraging existing 2D image and video compression techniques, the proposed method can achieve high compression ratios while effectively preserving data quality. Since the encoding and decoding processes can be applied to most of the current 2D media platforms, this proposed compression method can make 3D data storage and transmission available for many electrical devices without requiring special hardware changes. Experiments demonstrate that if a lossless 2D image/video format is used, both original 3D geometry and 2D color texture can be accurately recovered; if lossy image/video compression is used, only black-and-white or grayscale texture can be properly recovered, but much higher compression ratios (e.g., 1543:1 against the ASCII OBJ format) are achieved with slight loss of 3D geometry quality.

Three-dimensional seismic analysis for spent fuel storage rack

International Nuclear Information System (INIS)

Lee, Gyu Mahn; Kim, Kang Soo; Park, Keun Bae; Park, Jong Kyun

1998-01-01

Time history analysis is usually performed to characterize the nonlinear seismic behavior of a spent fuel storage rack (SFSR). In the past, the seismic analyses of the SFSR were performed with two-dimensional planar models, which could not account for torsional response and simultaneous multi-directional seismic input. In this study, three-dimensional seismic analysis methodology is developed for the single SFSR using the ANSY code. The 3-D model can be used to determine the nonlinear behavior of the rack, i.e., sliding, uplifting, and impact evaluation between the fuel assembly and rack, and rack and the pool wall. This paper also reviews the 3-D modeling of the SFSR and the adequacy of the ANSYS for the seismic analysis. As a result of the adequacy study, the method of ANSYS transient analysis with acceleration time history is suitable for the seismic analysis of highly nonlinear structure such as an SFSR but it isn't appropriate to use displacement time history of seismic input. (author)

Three-dimensional Locomotion and Drilling Microrobot Using Electromagnetic Actuation System

International Nuclear Information System (INIS)

Li, Girl; Choi, Hyun Chul; Cha, Kyoung Rae; Jeong, Se Mi; Park, Jong Oh; Park, Suk Ho

2011-01-01

In this study, a novel electromagnetic microrobot system with locomotion and drilling functions in three dimensional space was developed. Because of size limitations, the microrobot does not have actuator, battery, and controller. Therefore, an electromagnetic actuation (EMA) system was used to drive the robot. The proposed EMA system consists of three rectangular Helmholtz coil pairs in x-, y- and z-axes and a Maxwell coil pair in the z-axis. The magnetic field generated in the EMA coil system could be controlled by the input current of the EMA coil. Finally, through various experiments, the locomotion and drilling performances of the proposed EMA microrobot system were verified

Three-dimensional Locomotion and Drilling Microrobot Using Electromagnetic Actuation System

Energy Technology Data Exchange (ETDEWEB)

Li, Girl; Choi, Hyun Chul; Cha, Kyoung Rae; Jeong, Se Mi; Park, Jong Oh; Park, Suk Ho [Chonnam National University, Gwangju (Korea, Republic of)

2011-12-15

In this study, a novel electromagnetic microrobot system with locomotion and drilling functions in three dimensional space was developed. Because of size limitations, the microrobot does not have actuator, battery, and controller. Therefore, an electromagnetic actuation (EMA) system was used to drive the robot. The proposed EMA system consists of three rectangular Helmholtz coil pairs in x-, y- and z-axes and a Maxwell coil pair in the z-axis. The magnetic field generated in the EMA coil system could be controlled by the input current of the EMA coil. Finally, through various experiments, the locomotion and drilling performances of the proposed EMA microrobot system were verified.

The Application of a Three-Dimensional Printed Product to Fill the Space After Organ Removal.

Science.gov (United States)

Weng, Jui-Yu; Wang, Che-Chuna; Chen, Pei-Jar; Lim, Sher-Wei; Kuo, Jinn-Rung

2017-11-01

Maintaining body integrity, especially in Asian societies, is an independent predictor of organ donation. Herein, we report the case of an 18-year-old man who suffered a traumatic brain injury with ensuing brain death caused by a car accident. According to the family's wishes, we used a 3-dimensional printer to create simulated heart, kidneys, and liver to fill the spaces after the patient's organs were removed. This is the first case report to introduce this new clinical application of 3-dimensional printed products during transplantation surgery. This new clinical application may have supportive psychological effects on the family and caregivers; however, given the varied responses to our procedure, this ethical issue is worth discussing. Copyright © 2017 Elsevier Inc. All rights reserved.

Input and Intake in Language Acquisition

Science.gov (United States)

Gagliardi, Ann C.

2012-01-01

This dissertation presents an approach for a productive way forward in the study of language acquisition, sealing the rift between claims of an innate linguistic hypothesis space and powerful domain general statistical inference. This approach breaks language acquisition into its component parts, distinguishing the input in the environment from…

High-dimensional data in economics and their (robust) analysis

Czech Academy of Sciences Publication Activity Database

Kalina, Jan

2017-01-01

Roč. 12, č. 1 (2017), s. 171-183 ISSN 1452-4864 R&D Projects: GA ČR GA17-07384S Institutional support: RVO:67985556 Keywords : econometrics * high-dimensional data * dimensionality reduction * linear regression * classification analysis * robustness Subject RIV: BA - General Mathematics OBOR OECD: Business and management http://library.utia.cas.cz/separaty/2017/SI/kalina-0474076.pdf

Adaptive distributed parameter and input estimation in linear parabolic PDEs

KAUST Repository

Mechhoud, Sarra

2016-01-01

First, new sufficient identifiability conditions of the input and the parameter simultaneous estimation are stated. Then, by means of Lyapunov-based design, an adaptive estimator is derived in the infinite-dimensional framework. It consists of a state observer and gradient-based parameter and input adaptation laws. The parameter convergence depends on the plant signal richness assumption, whereas the state convergence is established using a Lyapunov approach. The results of the paper are illustrated by simulation on tokamak plasma heat transport model using simulated data.

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

Science.gov (United States)

Beauchard, Karine; Marbach, Frédéric

2018-03-01

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

Logarithmic corrections to the Bekenstein-Hawking entropy for five-dimensional black holes and de Sitter spaces

International Nuclear Information System (INIS)

Myung, Y.S.

2003-01-01

We calculate corrections to the Bekenstein-Hawking entropy formula for the five-dimensional topological AdS (TAdS)-black holes and topological de Sitter (TdS) spaces due to thermal fluctuations. We can derive all thermal properties of the TdS spaces from those of the TAdS black holes by replacing k by -k. Also we obtain the same correction to the Cardy-Verlinde formula for TAdS and TdS cases including the cosmological horizon of the Schwarzschild-de Sitter (SdS) black hole. Finally we discuss the AdS/CFT and dS/CFT correspondences and their dynamic correspondences

Black objects and hoop conjecture in five-dimensional space-time

Energy Technology Data Exchange (ETDEWEB)

Yamada, Yuta; Shinkai, Hisa-aki, E-mail: m1m08a26@info.oit.ac.j, E-mail: shinkai@is.oit.ac.j [Faculty of Information Science and Technology, Osaka Institute of Technology, 1-79-1 Kitayama, Hirakata, Osaka 573-0196 (Japan)

2010-02-21

We numerically investigated the sequences of initial data of a thin spindle and a thin ring in five-dimensional space-time in the context of the cosmic censorship conjecture. We modeled the matter in non-rotating homogeneous spheroidal or toroidal configurations under the momentarily static assumption, solved the Hamiltonian constraint equation and searched the apparent horizons. We discussed when S{sup 3} (black-hole) or S{sup 1} x S{sup 2} (black-ring) horizons ('black objects') are formed. By monitoring the location of the maximum Kretchmann invariant, an appearance of 'naked singularity' or 'naked ring' under special situations is suggested. We also discuss the validity of the hyper-hoop conjecture using a minimum area around the object, and show that the appearance of the ring horizon does not match with this hoop.

Emotion-based Music Rretrieval on a Well-reduced Audio Feature Space

DEFF Research Database (Denmark)

Ruxanda, Maria Magdalena; Chua, Bee Yong; Nanopoulos, Alexandros

2009-01-01

-emotion. However, the real-time systems that retrieve music over large music databases, can achieve order of magnitude performance increase, if applying multidimensional indexing over a dimensionally reduced audio feature space. To meet this performance achievement, in this paper, extensive studies are conducted......Music expresses emotion. A number of audio extracted features have influence on the perceived emotional expression of music. These audio features generate a high-dimensional space, on which music similarity retrieval can be performed effectively, with respect to human perception of the music...... on a number of dimensionality reduction algorithms, including both classic and novel approaches. The paper clearly envisages which dimensionality reduction techniques on the considered audio feature space, can preserve in average the accuracy of the emotion-based music retrieval....

Impact of high-latitude energy input on the mid- and low-latitude ionosphere and thermosphere

Science.gov (United States)

Lu, G.; Sheng, C.

2017-12-01

High-latitude energy input has a profound impact on the ionosphere and thermosphere especially during geomagnetic storms. Intense auroral particle precipitation ionizes neutral gases and modifies ionospheric conductivity; collisions between neutrals and fast-moving ions accelerate the neutral winds and produce Joule frictional heating; and the excess Joule and particle heating causes atmospheric upwelling and changes neutral composition due to the rising of the heavier, molecular-rich air. In addition, impulsive Joule heating launches large-scale gravity waves that propagate equatorward toward middle and low latitudes and even into the opposite hemisphere, altering the mean global circulation of the thermosphere. Furthermore, high-latitude electric field can also directly penetrate to lower latitudes under rapidly changing external conditions, causing prompt ionospheric variations in the mid- and low-latitude regions. To study the effects of high-latitude energy input, we apply the different convection and auroral precipitation patterns based on both empirical models and the AMIE outputs. We investigate how the mid- and low-latitude regions respond to the different specifications of high-latitude energy input. The main purpose of the study is to delineate the various dynamical, electrodynamical, and chemical processes and to determine their relative importance in the resulting ionospheric and thermospheric properties at mid and low latitudes.

High-dimensional Data in Economics and their (Robust) Analysis

Czech Academy of Sciences Publication Activity Database

Kalina, Jan

2017-01-01

Roč. 12, č. 1 (2017), s. 171-183 ISSN 1452-4864 R&D Projects: GA ČR GA17-07384S Grant - others:GA ČR(CZ) GA13-01930S Institutional support: RVO:67985807 Keywords : econometrics * high-dimensional data * dimensionality reduction * linear regression * classification analysis * robustness Subject RIV: BB - Applied Statistics, Operational Research OBOR OECD: Statistics and probability

Nebula: reconstruction and visualization of scattering data in reciprocal space.

Science.gov (United States)

Reiten, Andreas; Chernyshov, Dmitry; Mathiesen, Ragnvald H

2015-04-01

Two-dimensional solid-state X-ray detectors can now operate at considerable data throughput rates that allow full three-dimensional sampling of scattering data from extended volumes of reciprocal space within second to minute time-scales. For such experiments, simultaneous analysis and visualization allows for remeasurements and a more dynamic measurement strategy. A new software, Nebula , is presented. It efficiently reconstructs X-ray scattering data, generates three-dimensional reciprocal space data sets that can be visualized interactively, and aims to enable real-time processing in high-throughput measurements by employing parallel computing on commodity hardware.