Measurement-induced decoherence and Gaussian smoothing of the Wigner distribution function

International Nuclear Information System (INIS)

Chun, Yong-Jin; Lee, Hai-Woong

2003-01-01

We study the problem of measurement-induced decoherence using the phase-space approach employing the Gaussian-smoothed Wigner distribution function. Our investigation is based on the notion that measurement-induced decoherence is represented by the transition from the Wigner distribution to the Gaussian-smoothed Wigner distribution with the widths of the smoothing function identified as measurement errors. We also compare the smoothed Wigner distribution with the corresponding distribution resulting from the classical analysis. The distributions we computed are the phase-space distributions for simple one-dimensional dynamical systems such as a particle in a square-well potential and a particle moving under the influence of a step potential, and the time-frequency distributions for high-harmonic radiation emitted from an atom irradiated by short, intense laser pulses

Degeneracy of energy levels of pseudo-Gaussian oscillators

International Nuclear Information System (INIS)

Iacob, Theodor-Felix; Iacob, Felix; Lute, Marina

2015-01-01

We study the main features of the isotropic radial pseudo-Gaussian oscillators spectral properties. This study is made upon the energy levels degeneracy with respect to orbital angular momentum quantum number. In a previous work [6] we have shown that the pseudo-Gaussian oscillators belong to the class of quasi-exactly solvable models and an exact solution has been found

Hermite-Gaussian beams with self-forming spiral phase distribution

Science.gov (United States)

Zinchik, Alexander A.; Muzychenko, Yana B.

2014-05-01

Spiral laser beams is a family of laser beams that preserve the structural stability up to scale and rotate with the propagation. Properties of spiral beams are of practical interest for laser technology, medicine and biotechnology. Researchers use a spiral beams for movement and manipulation of microparticles. Spiral beams have a complicated phase distribution in cross section. This paper describes the results of analytical and computer simulation of Hermite-Gaussian beams with self-forming spiral phase distribution. In the simulation used a laser beam consisting of the sum of the two modes HG TEMnm and TEMn1m1. The coefficients n1, n, m1, m were varied. Additional phase depending from the coefficients n, m, m1, n1 imposed on the resulting beam. As a result, formed the Hermite Gaussian beam phase distribution which takes the form of a spiral in the process of distribution. For modeling was used VirtualLab 5.0 (manufacturer LightTrans GmbH).

IBS for non-gaussian distributions

International Nuclear Information System (INIS)

Fedotov, A.; Sidorin, A.O.; Smirnov, A.V.

2010-01-01

In many situations distribution can significantly deviate from Gaussian which requires accurate treatment of IBS. Our original interest in this problem was motivated by the need to have an accurate description of beam evolution due to IBS while distribution is strongly affected by the external electron cooling force. A variety of models with various degrees of approximation were developed and implemented in BETACOOL in the past to address this topic. A more complete treatment based on the friction coefficient and full 3-D diffusion tensor was introduced in BETACOOL at the end of 2007 under the name 'local IBS model'. Such a model allowed us calculation of IBS for an arbitrary beam distribution. The numerical benchmarking of this local IBS algorithm and its comparison with other models was reported before. In this paper, after briefly describing the model and its limitations, they present its comparison with available experimental data.

Nuclear collective flow from gaussian fits to triple differential distributions

International Nuclear Information System (INIS)

Gosset, J.; Babinet, R.; Cavata, C.; Marco, M. de; Demoulins, M.; Fanet, H.; Fodor, Z.; L'Hote, D.; Lucas, B.

1990-01-01

A simple characterization of triple differential cross sections is needed for a systematic study of the nuclear matter collective flow in relativistic nucleus-nucleus collisions. Our analysis is based upon a fitting procedure, so that the triple differential distributions need not be measured in the whole momentum space. If the detector acceptance eliminates most spectator particles or if it is artificially restricted for doing so, this method leads to a flow characterization of the participant nuclear matter. The center-of-mass triple-differential momentum distributions are fitted to a simple analytical shape, namely an anisotropic Gaussian distribution. The adjusted parameters (flow angle and aspect ratios) are corrected for uncertainty in the event-by-event determination of the reaction plane azimuth (finite-number effects). Results are presented for neon-nucleus and argon-nucleus collisions at incident energy between 400 and 800 MeV per nucleon. Flow is already significant for light systems, and depends clearly upon the impact parameter

A wavelet-based Gaussian method for energy dispersive X-ray fluorescence spectrum

Directory of Open Access Journals (Sweden)

Pan Liu

2017-05-01

Full Text Available This paper presents a wavelet-based Gaussian method (WGM for the peak intensity estimation of energy dispersive X-ray fluorescence (EDXRF. The relationship between the parameters of Gaussian curve and the wavelet coefficients of Gaussian peak point is firstly established based on the Mexican hat wavelet. It is found that the Gaussian parameters can be accurately calculated by any two wavelet coefficients at the peak point which has to be known. This fact leads to a local Gaussian estimation method for spectral peaks, which estimates the Gaussian parameters based on the detail wavelet coefficients of Gaussian peak point. The proposed method is tested via simulated and measured spectra from an energy X-ray spectrometer, and compared with some existing methods. The results prove that the proposed method can directly estimate the peak intensity of EDXRF free from the background information, and also effectively distinguish overlap peaks in EDXRF spectrum.

Scale-dependent bias from the reconstruction of non-Gaussian distributions

International Nuclear Information System (INIS)

Chongchitnan, Sirichai; Silk, Joseph

2011-01-01

Primordial non-Gaussianity introduces a scale-dependent variation in the clustering of density peaks corresponding to rare objects. This variation, parametrized by the bias, is investigated on scales where a linear perturbation theory is sufficiently accurate. The bias is obtained directly in real space by comparing the one- and two-point probability distributions of density fluctuations. We show that these distributions can be reconstructed using a bivariate Edgeworth series, presented here up to an arbitrarily high order. The Edgeworth formalism is shown to be well-suited for ''local'' cubic-order non-Gaussianity parametrized by g NL . We show that a strong scale dependence in the bias can be produced by g NL of order 10 5 , consistent with cosmic microwave background constraints. On a separation length of ∼100 Mpc, current constraints on g NL still allow the bias for the most massive clusters to be enhanced by 20-30% of the Gaussian value. We further examine the bias as a function of mass scale, and also explore the relationship between the clustering and the abundance of massive clusters in the presence of g NL . We explain why the Edgeworth formalism, though technically challenging, is a very powerful technique for constraining high-order non-Gaussianity with large-scale structures.

Exact Distributions of Intraclass Correlation and Cronbach's Alpha with Gaussian Data and General Covariance

Science.gov (United States)

Kistner, Emily O.; Muller, Keith E.

2004-01-01

Intraclass correlation and Cronbach's alpha are widely used to describe reliability of tests and measurements. Even with Gaussian data, exact distributions are known only for compound symmetric covariance (equal variances and equal correlations). Recently, large sample Gaussian approximations were derived for the distribution functions. New exact…

Extended q -Gaussian and q -exponential distributions from gamma random variables

Science.gov (United States)

Budini, Adrián A.

2015-05-01

The family of q -Gaussian and q -exponential probability densities fit the statistical behavior of diverse complex self-similar nonequilibrium systems. These distributions, independently of the underlying dynamics, can rigorously be obtained by maximizing Tsallis "nonextensive" entropy under appropriate constraints, as well as from superstatistical models. In this paper we provide an alternative and complementary scheme for deriving these objects. We show that q -Gaussian and q -exponential random variables can always be expressed as a function of two statistically independent gamma random variables with the same scale parameter. Their shape index determines the complexity q parameter. This result also allows us to define an extended family of asymmetric q -Gaussian and modified q -exponential densities, which reduce to the standard ones when the shape parameters are the same. Furthermore, we demonstrate that a simple change of variables always allows relating any of these distributions with a beta stochastic variable. The extended distributions are applied in the statistical description of different complex dynamics such as log-return signals in financial markets and motion of point defects in a fluid flow.

Image illumination enhancement with an objective no-reference measure of illumination assessment based on Gaussian distribution mapping

Directory of Open Access Journals (Sweden)

Gholamreza Anbarjafari

2015-12-01

Full Text Available Illumination problems have been an important concern in many image processing applications. The pattern of the histogram on an image introduces meaningful features; hence within the process of illumination enhancement, it is important not to destroy such information. In this paper we propose a method to enhance image illumination using Gaussian distribution mapping which also keeps the information laid on the pattern of the histogram on the original image. First a Gaussian distribution based on the mean and standard deviation of the input image will be calculated. Simultaneously a Gaussian distribution with the desired mean and standard deviation will be calculated. Then a cumulative distribution function of each of the Gaussian distributions will be calculated and used in order to map the old pixel value onto the new pixel value. Another important issue in the field of illumination enhancement is absence of a quantitative measure for the assessment of the illumination of an image. In this research work, a quantitative measure indicating the illumination state, i.e. contrast level and brightness of an image, is also proposed. The measure utilizes the estimated Gaussian distribution of the input image and the Kullback-Leibler Divergence (KLD between the estimated Gaussian and the desired Gaussian distributions to calculate the quantitative measure. The experimental results show the effectiveness and the reliability of the proposed illumination enhancement technique, as well as the proposed illumination assessment measure over conventional and state-of-the-art techniques.

Thermodynamics of noncommutative high-dimensional AdS black holes with non-Gaussian smeared matter distributions

CERN Document Server

Miao, Yan-Gang

2016-01-01

Considering non-Gaussian smeared matter distributions, we investigate thermodynamic behaviors of the noncommutative high-dimensional Schwarzschild-Tangherlini anti-de Sitter black hole, and obtain the condition for the existence of extreme black holes. We indicate that the Gaussian smeared matter distribution, which is a special case of non-Gaussian smeared matter distributions, is not applicable for the 6- and higher-dimensional black holes due to the hoop conjecture. In particular, the phase transition is analyzed in detail. Moreover, we point out that the Maxwell equal area law maintains for the noncommutative black hole with the Hawking temperature within a specific range, but fails with the Hawking temperature beyond this range.

Security of Continuous-Variable Quantum Key Distribution via a Gaussian de Finetti Reduction

Science.gov (United States)

Leverrier, Anthony

2017-05-01

Establishing the security of continuous-variable quantum key distribution against general attacks in a realistic finite-size regime is an outstanding open problem in the field of theoretical quantum cryptography if we restrict our attention to protocols that rely on the exchange of coherent states. Indeed, techniques based on the uncertainty principle are not known to work for such protocols, and the usual tools based on de Finetti reductions only provide security for unrealistically large block lengths. We address this problem here by considering a new type of Gaussian de Finetti reduction, that exploits the invariance of some continuous-variable protocols under the action of the unitary group U (n ) (instead of the symmetric group Sn as in usual de Finetti theorems), and by introducing generalized S U (2 ,2 ) coherent states. Crucially, combined with an energy test, this allows us to truncate the Hilbert space globally instead as at the single-mode level as in previous approaches that failed to provide security in realistic conditions. Our reduction shows that it is sufficient to prove the security of these protocols against Gaussian collective attacks in order to obtain security against general attacks, thereby confirming rigorously the widely held belief that Gaussian attacks are indeed optimal against such protocols.

American Option Pricing using GARCH models and the Normal Inverse Gaussian distribution

DEFF Research Database (Denmark)

Stentoft, Lars Peter

In this paper we propose a feasible way to price American options in a model with time varying volatility and conditional skewness and leptokurtosis using GARCH processes and the Normal Inverse Gaussian distribution. We show how the risk neutral dynamics can be obtained in this model, we interpret...... properties shows that there are important option pricing differences compared to the Gaussian case as well as to the symmetric special case. A large scale empirical examination shows that our model outperforms the Gaussian case for pricing options on three large US stocks as well as a major index...

Thermodynamics of noncommutative high-dimensional AdS black holes with non-Gaussian smeared matter distributions

Energy Technology Data Exchange (ETDEWEB)

Miao, Yan-Gang [Nankai University, School of Physics, Tianjin (China); Chinese Academy of Sciences, State Key Laboratory of Theoretical Physics, Institute of Theoretical Physics, P.O. Box 2735, Beijing (China); CERN, PH-TH Division, Geneva 23 (Switzerland); Xu, Zhen-Ming [Nankai University, School of Physics, Tianjin (China)

2016-04-15

Considering non-Gaussian smeared matter distributions, we investigate the thermodynamic behaviors of the noncommutative high-dimensional Schwarzschild-Tangherlini anti-de Sitter black hole, and we obtain the condition for the existence of extreme black holes. We indicate that the Gaussian smeared matter distribution, which is a special case of non-Gaussian smeared matter distributions, is not applicable for the six- and higher-dimensional black holes due to the hoop conjecture. In particular, the phase transition is analyzed in detail. Moreover, we point out that the Maxwell equal area law holds for the noncommutative black hole whose Hawking temperature is within a specific range, but fails for one whose the Hawking temperature is beyond this range. (orig.)

Coevolutionary particle swarm optimization using Gaussian distribution for solving constrained optimization problems.

Science.gov (United States)

Krohling, Renato A; Coelho, Leandro dos Santos

2006-12-01

In this correspondence, an approach based on coevolutionary particle swarm optimization to solve constrained optimization problems formulated as min-max problems is presented. In standard or canonical particle swarm optimization (PSO), a uniform probability distribution is used to generate random numbers for the accelerating coefficients of the local and global terms. We propose a Gaussian probability distribution to generate the accelerating coefficients of PSO. Two populations of PSO using Gaussian distribution are used on the optimization algorithm that is tested on a suite of well-known benchmark constrained optimization problems. Results have been compared with the canonical PSO (constriction factor) and with a coevolutionary genetic algorithm. Simulation results show the suitability of the proposed algorithm in terms of effectiveness and robustness.

Reconstruction of electrons with the Gaussian-sum filter in the CMS tracker at the LHC

International Nuclear Information System (INIS)

Adam, W; Fruehwirth, R; Strandlie, A; Todorov, T

2005-01-01

The bremsstrahlung energy loss distribution of electrons propagating in matter is highly non-Gaussian. Because the Kalman filter relies solely on Gaussian probability density functions, it is not necessarily the optimal reconstruction algorithm for electron tracks. A Gaussian-sum filter (GSF) algorithm for electron reconstruction in the CMS tracker has therefore been developed and implemented. The basic idea is to model the bremsstrahlung energy loss distribution by a Gaussian mixture rather than by a single Gaussian. It is shown that the GSF is able to improve the momentum resolution of electrons compared to the standard Kalman filter. The momentum resolution and the quality of the error estimate are studied both with a fast simulation, modelling the radiative energy loss in a simplified detector, and the full CMS tracker simulation. (research note from collaboration)

Reconstruction of Electrons with the Gaussian-Sum Filter in the CMS Tracker at the LHC

CERN Document Server

Adam, Wolfgang; Strandlie, Are; Todor, T

2005-01-01

The bremsstrahlung energy loss distribution of electrons propagating in matter is highly non-Gaussian. Because the Kalman filter relies solely on Gaussian probability density functions, it is not necessarily the optimal reconstruction algorithm for electron tracks. A Gaussian-sum filter (GSF) algorithm for electron reconstruction in the CMS tracker has therefore been developed and implemented. The basic idea is to model the bremsstrahlung energy loss distribution by a Gaussian mixture rather than by a single Gaussian. It is shown that the GSF is able to improve the momentum resolution of electrons compared to the standard Kalman filter. The momentum resolution and the quality of he error estimate are studied both with a fast simulation, modelling the radiative energy loss in a simplified detector, and the full CMS tracker simulation.

Probability distributions in conservative energy exchange models of multiple interacting agents

International Nuclear Information System (INIS)

Scafetta, Nicola; West, Bruce J

2007-01-01

Herein we study energy exchange models of multiple interacting agents that conserve energy in each interaction. The models differ regarding the rules that regulate the energy exchange and boundary effects. We find a variety of stochastic behaviours that manifest energy equilibrium probability distributions of different types and interaction rules that yield not only the exponential distributions such as the familiar Maxwell-Boltzmann-Gibbs distribution of an elastically colliding ideal particle gas, but also uniform distributions, truncated exponential distributions, Gaussian distributions, Gamma distributions, inverse power law distributions, mixed exponential and inverse power law distributions, and evolving distributions. This wide variety of distributions should be of value in determining the underlying mechanisms generating the statistical properties of complex phenomena including those to be found in complex chemical reactions

Monogamy inequality for distributed gaussian entanglement.

Science.gov (United States)

Hiroshima, Tohya; Adesso, Gerardo; Illuminati, Fabrizio

2007-02-02

We show that for all n-mode Gaussian states of continuous variable systems, the entanglement shared among n parties exhibits the fundamental monogamy property. The monogamy inequality is proven by introducing the Gaussian tangle, an entanglement monotone under Gaussian local operations and classical communication, which is defined in terms of the squared negativity in complete analogy with the case of n-qubit systems. Our results elucidate the structure of quantum correlations in many-body harmonic lattice systems.

A Fast Elitism Gaussian Estimation of Distribution Algorithm and Application for PID Optimization

Directory of Open Access Journals (Sweden)

Qingyang Xu

2014-01-01

Full Text Available Estimation of distribution algorithm (EDA is an intelligent optimization algorithm based on the probability statistics theory. A fast elitism Gaussian estimation of distribution algorithm (FEGEDA is proposed in this paper. The Gaussian probability model is used to model the solution distribution. The parameters of Gaussian come from the statistical information of the best individuals by fast learning rule. A fast learning rule is used to enhance the efficiency of the algorithm, and an elitism strategy is used to maintain the convergent performance. The performances of the algorithm are examined based upon several benchmarks. In the simulations, a one-dimensional benchmark is used to visualize the optimization process and probability model learning process during the evolution, and several two-dimensional and higher dimensional benchmarks are used to testify the performance of FEGEDA. The experimental results indicate the capability of FEGEDA, especially in the higher dimensional problems, and the FEGEDA exhibits a better performance than some other algorithms and EDAs. Finally, FEGEDA is used in PID controller optimization of PMSM and compared with the classical-PID and GA.

A fast elitism Gaussian estimation of distribution algorithm and application for PID optimization.

Science.gov (United States)

Xu, Qingyang; Zhang, Chengjin; Zhang, Li

2014-01-01

Estimation of distribution algorithm (EDA) is an intelligent optimization algorithm based on the probability statistics theory. A fast elitism Gaussian estimation of distribution algorithm (FEGEDA) is proposed in this paper. The Gaussian probability model is used to model the solution distribution. The parameters of Gaussian come from the statistical information of the best individuals by fast learning rule. A fast learning rule is used to enhance the efficiency of the algorithm, and an elitism strategy is used to maintain the convergent performance. The performances of the algorithm are examined based upon several benchmarks. In the simulations, a one-dimensional benchmark is used to visualize the optimization process and probability model learning process during the evolution, and several two-dimensional and higher dimensional benchmarks are used to testify the performance of FEGEDA. The experimental results indicate the capability of FEGEDA, especially in the higher dimensional problems, and the FEGEDA exhibits a better performance than some other algorithms and EDAs. Finally, FEGEDA is used in PID controller optimization of PMSM and compared with the classical-PID and GA.

Probability distribution for the Gaussian curvature of the zero level surface of a random function

Science.gov (United States)

Hannay, J. H.

2018-04-01

A rather natural construction for a smooth random surface in space is the level surface of value zero, or ‘nodal’ surface f(x,y,z)  =  0, of a (real) random function f; the interface between positive and negative regions of the function. A physically significant local attribute at a point of a curved surface is its Gaussian curvature (the product of its principal curvatures) because, when integrated over the surface it gives the Euler characteristic. Here the probability distribution for the Gaussian curvature at a random point on the nodal surface f  =  0 is calculated for a statistically homogeneous (‘stationary’) and isotropic zero mean Gaussian random function f. Capitalizing on the isotropy, a ‘fixer’ device for axes supplies the probability distribution directly as a multiple integral. Its evaluation yields an explicit algebraic function with a simple average. Indeed, this average Gaussian curvature has long been known. For a non-zero level surface instead of the nodal one, the probability distribution is not fully tractable, but is supplied as an integral expression.

Conformal Invariance, Dark Energy, and CMB Non-Gaussianity

CERN Document Server

Antoniadis, Ignatios; Mottola, Emil

2012-01-01

We show that in addition to simple scale invariance, a universe dominated by dark energy naturally gives rise to correlation functions possessing full conformal invariance. This is due to the mathematical isomorphism between the conformal group of certain three dimensional slices of de Sitter space and the de Sitter isometry group SO(4,1). In the standard homogeneous, isotropic cosmological model in which primordial density perturbations are generated during a long vacuum energy dominated de Sitter phase, the embedding of flat spatial R^3 sections in de Sitter space induces a conformal invariant perturbation spectrum and definite prediction for the shape of the non-Gaussian CMB bispectrum. In the case in which the density fluctuations are generated instead on the de Sitter horizon, conformal invariance of the S^2 horizon embedding implies a different but also quite definite prediction for the angular correlations of CMB non-Gaussianity on the sky. Each of these forms for the bispectrum is intrinsic to the sym...

Gaussian entanglement distribution via satellite

Science.gov (United States)

Hosseinidehaj, Nedasadat; Malaney, Robert

2015-02-01

In this work we analyze three quantum communication schemes for the generation of Gaussian entanglement between two ground stations. Communication occurs via a satellite over two independent atmospheric fading channels dominated by turbulence-induced beam wander. In our first scheme, the engineering complexity remains largely on the ground transceivers, with the satellite acting simply as a reflector. Although the channel state information of the two atmospheric channels remains unknown in this scheme, the Gaussian entanglement generation between the ground stations can still be determined. On the ground, distillation and Gaussification procedures can be applied, leading to a refined Gaussian entanglement generation rate between the ground stations. We compare the rates produced by this first scheme with two competing schemes in which quantum complexity is added to the satellite, thereby illustrating the tradeoff between space-based engineering complexity and the rate of ground-station entanglement generation.

The Gaussian atmospheric transport model and its sensitivity to the joint frequency distribution and parametric variability.

Science.gov (United States)

Hamby, D M

2002-01-01

Reconstructed meteorological data are often used in some form of long-term wind trajectory models for estimating the historical impacts of atmospheric emissions. Meteorological data for the straight-line Gaussian plume model are put into a joint frequency distribution, a three-dimensional array describing atmospheric wind direction, speed, and stability. Methods using the Gaussian model and joint frequency distribution inputs provide reasonable estimates of downwind concentration and have been shown to be accurate to within a factor of four. We have used multiple joint frequency distributions and probabilistic techniques to assess the Gaussian plume model and determine concentration-estimate uncertainty and model sensitivity. We examine the straight-line Gaussian model while calculating both sector-averaged and annual-averaged relative concentrations at various downwind distances. The sector-average concentration model was found to be most sensitive to wind speed, followed by horizontal dispersion (sigmaZ), the importance of which increases as stability increases. The Gaussian model is not sensitive to stack height uncertainty. Precision of the frequency data appears to be most important to meteorological inputs when calculations are made for near-field receptors, increasing as stack height increases.

Evaluation of geometrical contributions to the spread of the Compton-scatter energy distribution

International Nuclear Information System (INIS)

Hanson, A.L.; Gigante, G.E.; Dipartimento di Fisica, Universita degli Studi di Roma I, ''La Sapienza,'' Corso Vittorio Emanuele II, 244, 00186 Roma, Italy)

1989-01-01

The spectrum from Compton-scattered x rays is an inherently broad distribution. This distribution is the sum of several Gaussian-like distributions, which gives the sum its unique shape. The Gaussian-like distributions are the result of convoluting the so-called Compton profile, the spread in the scattered-x-ray energies due to the momentum distributions of the target electrons, with the detector response and the geometrical effects. The distribution is then further modified by the absorption within the sample. A formulation for both qualitatively and quantitatively determining the magnitude of the geometrical contributions is presented. This formulation is based on a recently devised approach to the scattering geometry [Hanson, Gigante, Meron, Phys. Rev. Lett. 61, 135 (1988)]. A methodology for determining the geometrical spread in the energy of the scattered x rays is presented. The results can be conveniently used to optimize scattering geometries for the reduction of the geometry-caused spread

Non-gaussian turbulence

Energy Technology Data Exchange (ETDEWEB)

Hoejstrup, J [NEG Micon Project Development A/S, Randers (Denmark); Hansen, K S [Denmarks Technical Univ., Dept. of Energy Engineering, Lyngby (Denmark); Pedersen, B J [VESTAS Wind Systems A/S, Lem (Denmark); Nielsen, M [Risoe National Lab., Wind Energy and Atmospheric Physics, Roskilde (Denmark)

1999-03-01

The pdf`s of atmospheric turbulence have somewhat wider tails than a Gaussian, especially regarding accelerations, whereas velocities are close to Gaussian. This behaviour is being investigated using data from a large WEB-database in order to quantify the amount of non-Gaussianity. Models for non-Gaussian turbulence have been developed, by which artificial turbulence can be generated with specified distributions, spectra and cross-correlations. The artificial time series will then be used in load models and the resulting loads in the Gaussian and the non-Gaussian cases will be compared. (au)

Distribution of Schmidt-like eigenvalues for Gaussian ensembles of the random matrix theory

Science.gov (United States)

Pato, Mauricio P.; Oshanin, Gleb

2013-03-01

We study the probability distribution function P(β)n(w) of the Schmidt-like random variable w = x21/(∑j = 1nx2j/n), where xj, (j = 1, 2, …, n), are unordered eigenvalues of a given n × n β-Gaussian random matrix, β being the Dyson symmetry index. This variable, by definition, can be considered as a measure of how any individual (randomly chosen) eigenvalue deviates from the arithmetic mean value of all eigenvalues of a given random matrix, and its distribution is calculated with respect to the ensemble of such β-Gaussian random matrices. We show that in the asymptotic limit n → ∞ and for arbitrary β the distribution P(β)n(w) converges to the Marčenko-Pastur form, i.e. is defined as P_{n}^{( \\beta )}(w) \\sim \\sqrt{(4 - w)/w} for w ∈ [0, 4] and equals zero outside of the support, despite the fact that formally w is defined on the interval [0, n]. Furthermore, for Gaussian unitary ensembles (β = 2) we present exact explicit expressions for P(β = 2)n(w) which are valid for arbitrary n and analyse their behaviour.

Distribution of Schmidt-like eigenvalues for Gaussian ensembles of the random matrix theory

International Nuclear Information System (INIS)

Pato, Mauricio P; Oshanin, Gleb

2013-01-01

We study the probability distribution function P (β) n (w) of the Schmidt-like random variable w = x 2 1 /(∑ j=1 n x 2 j /n), where x j , (j = 1, 2, …, n), are unordered eigenvalues of a given n × n β-Gaussian random matrix, β being the Dyson symmetry index. This variable, by definition, can be considered as a measure of how any individual (randomly chosen) eigenvalue deviates from the arithmetic mean value of all eigenvalues of a given random matrix, and its distribution is calculated with respect to the ensemble of such β-Gaussian random matrices. We show that in the asymptotic limit n → ∞ and for arbitrary β the distribution P (β) n (w) converges to the Marčenko–Pastur form, i.e. is defined as P n (β) (w)∼√((4 - w)/w) for w ∈ [0, 4] and equals zero outside of the support, despite the fact that formally w is defined on the interval [0, n]. Furthermore, for Gaussian unitary ensembles (β = 2) we present exact explicit expressions for P (β=2) n (w) which are valid for arbitrary n and analyse their behaviour. (paper)

Geometry of Gaussian quantum states

International Nuclear Information System (INIS)

Link, Valentin; Strunz, Walter T

2015-01-01

We study the Hilbert–Schmidt measure on the manifold of mixed Gaussian states in multi-mode continuous variable quantum systems. An analytical expression for the Hilbert–Schmidt volume element is derived. Its corresponding probability measure can be used to study typical properties of Gaussian states. It turns out that although the manifold of Gaussian states is unbounded, an ensemble of Gaussian states distributed according to this measure still has a normalizable distribution of symplectic eigenvalues, from which unitarily invariant properties can be obtained. By contrast, we find that for an ensemble of one-mode Gaussian states based on the Bures measure the corresponding distribution cannot be normalized. As important applications, we determine the distribution and the mean value of von Neumann entropy and purity for the Hilbert–Schmidt measure. (paper)

Nuclear collective flow from gaussian fits to triple differential distributions

International Nuclear Information System (INIS)

Gosset, J.; Demoulins, M.; Babinet, R.; Cavata, C.; Fanet, H.; L'Hote, D.; Lucas, B.; Poitou, J.; Valette, O.; Alard, J.P.; Augerat, J.; Bastid, N.; Charmensat, P.; Dupieux, P.; Fraysse, L.; Marroncle, J.; Montarou, G.; Parizet, M.J.; Qassoud, D.; Rahmani, A.; Brochard, F.; Gorodetzky, P.; Racca, C.

1990-01-01

In order to study the nuclear collective flow, the triple differential momentum distributions of charged baryons are fitted to a simple anisotropic gaussian distribution, within an acceptance which removes most of the spectator contribution. The adjusted flow angle and aspect ratios are corrected for systematic errors in the determination of the reaction plane. This method has been tested with Monte Carlo simulations and applied to experimental results and intranuclear cascade simulations of argon-nucleus collisions at 400 MeV per nucleon. (orig.)

q-Gaussian distributions of leverage returns, first stopping times, and default risk valuations

Science.gov (United States)

Katz, Yuri A.; Tian, Li

2013-10-01

We study the probability distributions of daily leverage returns of 520 North American industrial companies that survive de-listing during the financial crisis, 2006-2012. We provide evidence that distributions of unbiased leverage returns of all individual firms belong to the class of q-Gaussian distributions with the Tsallis entropic parameter within the interval 1distributions imply a much higher probability of extreme movements in a company’s leverage ratio than forecasted by the normal distribution (q=1). Motivated by these findings, we develop a q-Gaussian generalization of traditional structural models of default. Derived exact analytical expressions for the probability distribution of a first stopping time and its intensity forecast significantly higher probability of default and much wider credit spreads at short time-horizons. Our findings are broadly consistent with the results of empirical studies in equity markets and are essential for single-name default forecasting as well as valuations of portfolio credit risk and economic capital, which might be underestimated by a classic theory of diversified portfolio optimization.

Continuous-variable quantum key distribution with Gaussian source noise

International Nuclear Information System (INIS)

Shen Yujie; Peng Xiang; Yang Jian; Guo Hong

2011-01-01

Source noise affects the security of continuous-variable quantum key distribution (CV QKD) and is difficult to analyze. We propose a model to characterize Gaussian source noise through introducing a neutral party (Fred) who induces the noise with a general unitary transformation. Without knowing Fred's exact state, we derive the security bounds for both reverse and direct reconciliations and show that the bound for reverse reconciliation is tight.

GaussianCpG: a Gaussian model for detection of CpG island in human genome sequences.

Science.gov (United States)

Yu, Ning; Guo, Xuan; Zelikovsky, Alexander; Pan, Yi

2017-05-24

As crucial markers in identifying biological elements and processes in mammalian genomes, CpG islands (CGI) play important roles in DNA methylation, gene regulation, epigenetic inheritance, gene mutation, chromosome inactivation and nuclesome retention. The generally accepted criteria of CGI rely on: (a) %G+C content is ≥ 50%, (b) the ratio of the observed CpG content and the expected CpG content is ≥ 0.6, and (c) the general length of CGI is greater than 200 nucleotides. Most existing computational methods for the prediction of CpG island are programmed on these rules. However, many experimentally verified CpG islands deviate from these artificial criteria. Experiments indicate that in many cases %G+C is human genome. We analyze the energy distribution over genomic primary structure for each CpG site and adopt the parameters from statistics of Human genome. The evaluation results show that the new model can predict CpG islands efficiently by balancing both sensitivity and specificity over known human CGI data sets. Compared with other models, GaussianCpG can achieve better performance in CGI detection. Our Gaussian model aims to simplify the complex interaction between nucleotides. The model is computed not by the linear statistical method but by the Gaussian energy distribution and accumulation. The parameters of Gaussian function are not arbitrarily designated but deliberately chosen by optimizing the biological statistics. By using the pseudopotential analysis on CpG islands, the novel model is validated on both the real and artificial data sets.

Quantum key distribution using continuous-variable non-Gaussian states

Science.gov (United States)

Borelli, L. F. M.; Aguiar, L. S.; Roversi, J. A.; Vidiella-Barranco, A.

2016-02-01

In this work, we present a quantum key distribution protocol using continuous-variable non-Gaussian states, homodyne detection and post-selection. The employed signal states are the photon added then subtracted coherent states (PASCS) in which one photon is added and subsequently one photon is subtracted from the field. We analyze the performance of our protocol, compared with a coherent state-based protocol, for two different attacks that could be carried out by the eavesdropper (Eve). We calculate the secret key rate transmission in a lossy line for a superior channel (beam-splitter) attack, and we show that we may increase the secret key generation rate by using the non-Gaussian PASCS rather than coherent states. We also consider the simultaneous quadrature measurement (intercept-resend) attack, and we show that the efficiency of Eve's attack is substantially reduced if PASCS are used as signal states.

Wigner distribution function of Hermite-cosine-Gaussian beams through an apertured optical system.

Science.gov (United States)

Sun, Dong; Zhao, Daomu

2005-08-01

By introducing the hard-aperture function into a finite sum of complex Gaussian functions, the approximate analytical expressions of the Wigner distribution function for Hermite-cosine-Gaussian beams passing through an apertured paraxial ABCD optical system are obtained. The analytical results are compared with the numerically integrated ones, and the absolute errors are also given. It is shown that the analytical results are proper and that the calculation speed for them is much faster than for the numerical results.

Digital simulation of two-dimensional random fields with arbitrary power spectra and non-Gaussian probability distribution functions.

Science.gov (United States)

Yura, Harold T; Hanson, Steen G

2012-04-01

Methods for simulation of two-dimensional signals with arbitrary power spectral densities and signal amplitude probability density functions are disclosed. The method relies on initially transforming a white noise sample set of random Gaussian distributed numbers into a corresponding set with the desired spectral distribution, after which this colored Gaussian probability distribution is transformed via an inverse transform into the desired probability distribution. In most cases the method provides satisfactory results and can thus be considered an engineering approach. Several illustrative examples with relevance for optics are given.

Non-Gaussian Velocity Distributions in Solar Flares from Extreme Ultraviolet Lines: A Possible Diagnostic of Ion Acceleration

International Nuclear Information System (INIS)

Jeffrey, Natasha L. S.; Fletcher, Lyndsay; Labrosse, Nicolas

2017-01-01

In a solar flare, a large fraction of the magnetic energy released is converted rapidly to the kinetic energy of non-thermal particles and bulk plasma motion. This will likely result in non-equilibrium particle distributions and turbulent plasma conditions. We investigate this by analyzing the profiles of high temperature extreme ultraviolet emission lines from a major flare (SOL2014-03-29T17:44) observed by the EUV Imaging Spectrometer (EIS) on Hinode . We find that in many locations the line profiles are non-Gaussian, consistent with a kappa distribution of emitting ions with properties that vary in space and time. At the flare footpoints, close to sites of hard X-ray emission from non-thermal electrons, the κ index for the Fe xvi 262.976 Å line at 3 MK takes values of 3–5. In the corona, close to a low-energy HXR source, the Fe xxiii 263.760 Å line at 15 MK shows κ values of typically 4–7. The observed trends in the κ parameter show that we are most likely detecting the properties of the ion population rather than any instrumental effects. We calculate that a non-thermal ion population could exist if locally accelerated on timescales ≤0.1 s. However, observations of net redshifts in the lines also imply the presence of plasma downflows, which could lead to bulk turbulence, with increased non-Gaussianity in cooler regions. Both interpretations have important implications for theories of solar flare particle acceleration.

Replica Exchange Gaussian Accelerated Molecular Dynamics: Improved Enhanced Sampling and Free Energy Calculation.

Science.gov (United States)

Huang, Yu-Ming M; McCammon, J Andrew; Miao, Yinglong

2018-04-10

Through adding a harmonic boost potential to smooth the system potential energy surface, Gaussian accelerated molecular dynamics (GaMD) provides enhanced sampling and free energy calculation of biomolecules without the need of predefined reaction coordinates. This work continues to improve the acceleration power and energy reweighting of the GaMD by combining the GaMD with replica exchange algorithms. Two versions of replica exchange GaMD (rex-GaMD) are presented: force constant rex-GaMD and threshold energy rex-GaMD. During simulations of force constant rex-GaMD, the boost potential can be exchanged between replicas of different harmonic force constants with fixed threshold energy. However, the algorithm of threshold energy rex-GaMD tends to switch the threshold energy between lower and upper bounds for generating different levels of boost potential. Testing simulations on three model systems, including the alanine dipeptide, chignolin, and HIV protease, demonstrate that through continuous exchanges of the boost potential, the rex-GaMD simulations not only enhance the conformational transitions of the systems but also narrow down the distribution width of the applied boost potential for accurate energetic reweighting to recover biomolecular free energy profiles.

Treatment of non-Gaussian tails of multiple Coulomb scattering in track fitting with a Gaussian-sum filter

International Nuclear Information System (INIS)

Strandlie, A.; Wroldsen, J.

2006-01-01

If any of the probability densities involved in track fitting deviate from the Gaussian assumption, it is plausible that a non-linear estimator which better takes the actual shape of the distribution into account can do better. One such non-linear estimator is the Gaussian-sum filter, which is adequate if the distributions under consideration can be approximated by Gaussian mixtures. The main purpose of this paper is to present a Gaussian-sum filter for track fitting, based on a two-component approximation of the distribution of angular deflections due to multiple scattering. In a simulation study within a linear track model the Gaussian-sum filter is shown to be a competitive alternative to the Kalman filter. Scenarios at various momenta and with various maximum number of components in the Gaussian-sum filter are considered. Particularly at low momenta the Gaussian-sum filter yields a better estimate of the uncertainties than the Kalman filter, and it is also slightly more precise than the latter

On the joint distribution of excursion duration and amplitude of a narrow-band Gaussian process

DEFF Research Database (Denmark)

Ghane, Mahdi; Gao, Zhen; Blanke, Mogens

2018-01-01

of amplitude and period are limited to excursion through a mean-level or to describe the asymptotic behavior of high level excursions. This paper extends the knowledge by presenting a theoretical derivation of probability of wave exceedance amplitude and duration, for a narrow-band Gaussian process......The probability density of crest amplitude and of duration of exceeding a given level are used in many theoretical and practical problems in engineering. The joint density is essential for design of constructions that are subjected to waves and wind. The presently available joint distributions...... distribution, as expected, and that the marginal distribution of excursion duration works both for asymptotic and non-asymptotic cases. The suggested model is found to be a good replacement for the empirical distributions that are widely used. Results from simulations of narrow-band Gaussian processes, real...

Back to Normal! Gaussianizing posterior distributions for cosmological probes

Science.gov (United States)

Schuhmann, Robert L.; Joachimi, Benjamin; Peiris, Hiranya V.

2014-05-01

We present a method to map multivariate non-Gaussian posterior probability densities into Gaussian ones via nonlinear Box-Cox transformations, and generalizations thereof. This is analogous to the search for normal parameters in the CMB, but can in principle be applied to any probability density that is continuous and unimodal. The search for the optimally Gaussianizing transformation amongst the Box-Cox family is performed via a maximum likelihood formalism. We can judge the quality of the found transformation a posteriori: qualitatively via statistical tests of Gaussianity, and more illustratively by how well it reproduces the credible regions. The method permits an analytical reconstruction of the posterior from a sample, e.g. a Markov chain, and simplifies the subsequent joint analysis with other experiments. Furthermore, it permits the characterization of a non-Gaussian posterior in a compact and efficient way. The expression for the non-Gaussian posterior can be employed to find analytic formulae for the Bayesian evidence, and consequently be used for model comparison.

Improving the modelling of redshift-space distortions - I. A bivariate Gaussian description for the galaxy pairwise velocity distributions

Science.gov (United States)

Bianchi, Davide; Chiesa, Matteo; Guzzo, Luigi

2015-01-01

As a step towards a more accurate modelling of redshift-space distortions (RSD) in galaxy surveys, we develop a general description of the probability distribution function of galaxy pairwise velocities within the framework of the so-called streaming model. For a given galaxy separation r, such function can be described as a superposition of virtually infinite local distributions. We characterize these in terms of their moments and then consider the specific case in which they are Gaussian functions, each with its own mean μ and dispersion σ. Based on physical considerations, we make the further crucial assumption that these two parameters are in turn distributed according to a bivariate Gaussian, with its own mean and covariance matrix. Tests using numerical simulations explicitly show that with this compact description one can correctly model redshift-space distortions on all scales, fully capturing the overall linear and non-linear dynamics of the galaxy flow at different separations. In particular, we naturally obtain Gaussian/exponential, skewed/unskewed distribution functions, depending on separation as observed in simulations and data. Also, the recently proposed single-Gaussian description of RSD is included in this model as a limiting case, when the bivariate Gaussian is collapsed to a two-dimensional Dirac delta function. We also show how this description naturally allows for the Taylor expansion of 1 + ξS(s) around 1 + ξR(r), which leads to the Kaiser linear formula when truncated to second order, explicating its connection with the moments of the velocity distribution functions. More work is needed, but these results indicate a very promising path to make definitive progress in our programme to improve RSD estimators.

Thermal activation of current in an inhomogeneous Schottky diode with a Gaussian distribution of barrier height

International Nuclear Information System (INIS)

Guo-Ping, Ru; Rong, Yu; Yu-Long, Jiang; Gang, Ruan

2010-01-01

This paper investigates the thermal activation behaviour of current in an inhomogeneous Schottky diode with a Gaussian distribution of barrier height by numerical simulation. The analytical Gaussian distribution model predicted that the I-V-T curves may intersect with the possibility of the negative thermal activation of current, but may be contradictory to the thermionic emission mechanism in a Schottky diode. It shows that the cause of the unphysical phenomenon is related to the incorrect calculation of current across very low barriers. It proposes that junction voltage V j , excluding the voltage drop across series resistance from the external bias, is a crucial parameter for correct calculation of the current across very low barriers. For correctly employing the thermionic emission model, V j needs to be smaller than the barrier height ø. With proper scheme of series resistance connection where the condition of V j > ø is guaranteed, I-V-T curves of an inhomogeneous Schottky diode with a Gaussian distribution of barrier height have been simulated, which demonstrate normal thermal activation. Although the calculated results exclude the intersecting possibility of I-V-T curves with an assumption of temperature-independent series resistance, it shows that the intersecting is possible when the series resistance has a positive temperature coefficient. Finally, the comparison of our numerical and analytical results indicates that the analytical Gaussian distribution model is valid and accurate in analysing I-V-T curves only for small barrier height inhomogeneity. (condensed matter: electronic structure, electrical, magnetic, and optical properties)

Testing the mutual information expansion of entropy with multivariate Gaussian distributions.

Science.gov (United States)

Goethe, Martin; Fita, Ignacio; Rubi, J Miguel

2017-12-14

The mutual information expansion (MIE) represents an approximation of the configurational entropy in terms of low-dimensional integrals. It is frequently employed to compute entropies from simulation data of large systems, such as macromolecules, for which brute-force evaluation of the full configurational integral is intractable. Here, we test the validity of MIE for systems consisting of more than m = 100 degrees of freedom (dofs). The dofs are distributed according to multivariate Gaussian distributions which were generated from protein structures using a variant of the anisotropic network model. For the Gaussian distributions, we have semi-analytical access to the configurational entropy as well as to all contributions of MIE. This allows us to accurately assess the validity of MIE for different situations. We find that MIE diverges for systems containing long-range correlations which means that the error of consecutive MIE approximations grows with the truncation order n for all tractable n ≪ m. This fact implies severe limitations on the applicability of MIE, which are discussed in the article. For systems with correlations that decay exponentially with distance, MIE represents an asymptotic expansion of entropy, where the first successive MIE approximations approach the exact entropy, while MIE also diverges for larger orders. In this case, MIE serves as a useful entropy expansion when truncated up to a specific truncation order which depends on the correlation length of the system.

Super-resolving random-Gaussian apodized photon sieve.

Science.gov (United States)

Sabatyan, Arash; Roshaninejad, Parisa

2012-09-10

A novel apodized photon sieve is presented in which random dense Gaussian distribution is implemented to modulate the pinhole density in each zone. The random distribution in dense Gaussian distribution causes intrazone discontinuities. Also, the dense Gaussian distribution generates a substantial number of pinholes in order to form a large degree of overlap between the holes in a few innermost zones of the photon sieve; thereby, clear zones are formed. The role of the discontinuities on the focusing properties of the photon sieve is examined as well. Analysis shows that secondary maxima have evidently been suppressed, transmission has increased enormously, and the central maxima width is approximately unchanged in comparison to the dense Gaussian distribution. Theoretical results have been completely verified by experiment.

Entanglement of Gaussian states and the applicability to quantum key distribution over fading channels

International Nuclear Information System (INIS)

Usenko, Vladyslav C; Filip, Radim; Heim, Bettina; Peuntinger, Christian; Wittmann, Christoffer; Marquardt, Christoph; Leuchs, Gerd

2012-01-01

Entanglement properties of Gaussian states of light as well as the security of continuous variable quantum key distribution with Gaussian states in free-space fading channels are studied. These qualities are shown to be sensitive to the statistical properties of the transmittance distribution in the cases when entanglement is strong or when channel excess noise is present. Fading, i.e. transmission fluctuations, caused by beam wandering due to atmospheric turbulence, is a frequent challenge in free-space communication. We introduce a method of fading discrimination and subsequent post-selection of the corresponding sub-states and show that it can improve the entanglement resource and restore the security of the key distribution over a realistic fading link. Furthermore, the optimal post-selection strategy in combination with an optimized entangled resource is shown to drastically increase the protocol's robustness to excess noise, which is confirmed for experimentally measured fading channel characteristics. The stability of the result against finite data ensemble size and imperfect channel estimation is also addressed. (paper)

Comparison of Gaussian and non-Gaussian Atmospheric Profile Retrievals from Satellite Microwave Data

Science.gov (United States)

Kliewer, A.; Forsythe, J. M.; Fletcher, S. J.; Jones, A. S.

2017-12-01

The Cooperative Institute for Research in the Atmosphere at Colorado State University has recently developed two different versions of a mixed-distribution (lognormal combined with a Gaussian) based microwave temperature and mixing ratio retrieval system as well as the original Gaussian-based approach. These retrieval systems are based upon 1DVAR theory but have been adapted to use different descriptive statistics of the lognormal distribution to minimize the background errors. The input radiance data is from the AMSU-A and MHS instruments on the NOAA series of spacecraft. To help illustrate how the three retrievals are affected by the change in the distribution we are in the process of creating a new website to show the output from the different retrievals. Here we present initial results from different dynamical situations to show how the tool could be used by forecasters as well as for educators. However, as the new retrieved values are from a non-Gaussian based 1DVAR then they will display non-Gaussian behaviors that need to pass a quality control measure that is consistent with this distribution, and these new measures are presented here along with initial results for checking the retrievals.

Sn ion energy distributions of ns- and ps-laser produced plasmas

Science.gov (United States)

Bayerle, A.; Deuzeman, M. J.; van der Heijden, S.; Kurilovich, D.; de Faria Pinto, T.; Stodolna, A.; Witte, S.; Eikema, K. S. E.; Ubachs, W.; Hoekstra, R.; Versolato, O. O.

2018-04-01

Ion energy distributions arising from laser-produced plasmas of Sn are measured over a wide laser parameter space. Planar-solid and liquid-droplet targets are exposed to infrared laser pulses with energy densities between 1 J cm‑2 and 4 kJ cm‑2 and durations spanning 0.5 ps to 6 ns. The measured ion energy distributions are compared to two self-similar solutions of a hydrodynamic approach assuming isothermal expansion of the plasma plume into vacuum. For planar and droplet targets exposed to ps-long pulses, we find good agreement between the experimental results and the self-similar solution of a semi-infinite simple planar plasma configuration with an exponential density profile. The ion energy distributions resulting from solid Sn exposed to ns-pulses agrees with solutions of a limited-mass model that assumes a Gaussian-shaped initial density profile.

A method for atomic-level noncontact thermometry with electron energy distribution

Science.gov (United States)

Kinoshita, Ikuo; Tsukada, Chiharu; Ouchi, Kohei; Kobayashi, Eiichi; Ishii, Juntaro

2017-04-01

We devised a new method of determining the temperatures of materials with their electron-energy distributions. The Fermi-Dirac distribution convoluted with a linear combination of Gaussian and Lorentzian distributions was fitted to the photoelectron spectrum measured for the Au(110) single-crystal surface at liquid N2-cooled temperature. The fitting successfully determined the surface-local thermodynamic temperature and the energy resolution simultaneously from the photoelectron spectrum, without any preliminary results of other measurements. The determined thermodynamic temperature was 99 ± 2.1 K, which was in good agreement with the reference temperature of 98.5 ± 0.5 K measured using a silicon diode sensor attached to the sample holder.

Digital simulation of two-dimensional random fields with arbitrary power spectra and non-Gaussian probability distribution functions

DEFF Research Database (Denmark)

Yura, Harold; Hanson, Steen Grüner

2012-01-01

with the desired spectral distribution, after which this colored Gaussian probability distribution is transformed via an inverse transform into the desired probability distribution. In most cases the method provides satisfactory results and can thus be considered an engineering approach. Several illustrative...

Invariant measures on multimode quantum Gaussian states

Science.gov (United States)

Lupo, C.; Mancini, S.; De Pasquale, A.; Facchi, P.; Florio, G.; Pascazio, S.

2012-12-01

We derive the invariant measure on the manifold of multimode quantum Gaussian states, induced by the Haar measure on the group of Gaussian unitary transformations. To this end, by introducing a bipartition of the system in two disjoint subsystems, we use a parameterization highlighting the role of nonlocal degrees of freedom—the symplectic eigenvalues—which characterize quantum entanglement across the given bipartition. A finite measure is then obtained by imposing a physically motivated energy constraint. By averaging over the local degrees of freedom we finally derive the invariant distribution of the symplectic eigenvalues in some cases of particular interest for applications in quantum optics and quantum information.

Invariant measures on multimode quantum Gaussian states

International Nuclear Information System (INIS)

Lupo, C.; Mancini, S.; De Pasquale, A.; Facchi, P.; Florio, G.; Pascazio, S.

2012-01-01

We derive the invariant measure on the manifold of multimode quantum Gaussian states, induced by the Haar measure on the group of Gaussian unitary transformations. To this end, by introducing a bipartition of the system in two disjoint subsystems, we use a parameterization highlighting the role of nonlocal degrees of freedom—the symplectic eigenvalues—which characterize quantum entanglement across the given bipartition. A finite measure is then obtained by imposing a physically motivated energy constraint. By averaging over the local degrees of freedom we finally derive the invariant distribution of the symplectic eigenvalues in some cases of particular interest for applications in quantum optics and quantum information.

Invariant measures on multimode quantum Gaussian states

Energy Technology Data Exchange (ETDEWEB)

Lupo, C. [School of Science and Technology, Universita di Camerino, I-62032 Camerino (Italy); Mancini, S. [School of Science and Technology, Universita di Camerino, I-62032 Camerino (Italy); Istituto Nazionale di Fisica Nucleare, Sezione di Perugia, I-06123 Perugia (Italy); De Pasquale, A. [NEST, Scuola Normale Superiore and Istituto Nanoscienze-CNR, I-56126 Pisa (Italy); Facchi, P. [Dipartimento di Matematica and MECENAS, Universita di Bari, I-70125 Bari (Italy); Istituto Nazionale di Fisica Nucleare, Sezione di Bari, I-70126 Bari (Italy); Florio, G. [Istituto Nazionale di Fisica Nucleare, Sezione di Bari, I-70126 Bari (Italy); Museo Storico della Fisica e Centro Studi e Ricerche Enrico Fermi, Piazza del Viminale 1, I-00184 Roma (Italy); Dipartimento di Fisica and MECENAS, Universita di Bari, I-70126 Bari (Italy); Pascazio, S. [Istituto Nazionale di Fisica Nucleare, Sezione di Bari, I-70126 Bari (Italy); Dipartimento di Fisica and MECENAS, Universita di Bari, I-70126 Bari (Italy)

2012-12-15

We derive the invariant measure on the manifold of multimode quantum Gaussian states, induced by the Haar measure on the group of Gaussian unitary transformations. To this end, by introducing a bipartition of the system in two disjoint subsystems, we use a parameterization highlighting the role of nonlocal degrees of freedom-the symplectic eigenvalues-which characterize quantum entanglement across the given bipartition. A finite measure is then obtained by imposing a physically motivated energy constraint. By averaging over the local degrees of freedom we finally derive the invariant distribution of the symplectic eigenvalues in some cases of particular interest for applications in quantum optics and quantum information.

Energy optimized Gaussian basis sets for the atoms T1 - Rn

International Nuclear Information System (INIS)

Faegri, K. Jr.

1987-01-01

Energy optimized Gaussian basis sets have been derived for the atoms Tl-Rn. Two sets are presented - a (20,16,10,6) set and a (22,17,13,8) set. The smallest sets yield atomic energies 107 to 123 mH above the numerical Hartree-Fock values, while the larger sets give energies 11 mH above the numerical results. Energy trends from the smaller sets indicate that reduced shielding by p-electrons may place a greater demand on the flexibility of d- and f-orbital description for the lighter elements of the series

Non-gaussianity versus nonlinearity of cosmological perturbations.

Science.gov (United States)

Verde, L

2001-06-01

Following the discovery of the cosmic microwave background, the hot big-bang model has become the standard cosmological model. In this theory, small primordial fluctuations are subsequently amplified by gravity to form the large-scale structure seen today. Different theories for unified models of particle physics, lead to different predictions for the statistical properties of the primordial fluctuations, that can be divided in two classes: gaussian and non-gaussian. Convincing evidence against or for gaussian initial conditions would rule out many scenarios and point us toward a physical theory for the origin of structures. The statistical distribution of cosmological perturbations, as we observe them, can deviate from the gaussian distribution in several different ways. Even if perturbations start off gaussian, nonlinear gravitational evolution can introduce non-gaussian features. Additionally, our knowledge of the Universe comes principally from the study of luminous material such as galaxies, but galaxies might not be faithful tracers of the underlying mass distribution. The relationship between fluctuations in the mass and in the galaxies distribution (bias), is often assumed to be local, but could well be nonlinear. Moreover, galaxy catalogues use the redshift as third spatial coordinate: the resulting redshift-space map of the galaxy distribution is nonlinearly distorted by peculiar velocities. Nonlinear gravitational evolution, biasing, and redshift-space distortion introduce non-gaussianity, even in an initially gaussian fluctuation field. I investigate the statistical tools that allow us, in principle, to disentangle the above different effects, and the observational datasets we require to do so in practice.

Variational Gaussian approximation for Poisson data

Science.gov (United States)

Arridge, Simon R.; Ito, Kazufumi; Jin, Bangti; Zhang, Chen

2018-02-01

The Poisson model is frequently employed to describe count data, but in a Bayesian context it leads to an analytically intractable posterior probability distribution. In this work, we analyze a variational Gaussian approximation to the posterior distribution arising from the Poisson model with a Gaussian prior. This is achieved by seeking an optimal Gaussian distribution minimizing the Kullback-Leibler divergence from the posterior distribution to the approximation, or equivalently maximizing the lower bound for the model evidence. We derive an explicit expression for the lower bound, and show the existence and uniqueness of the optimal Gaussian approximation. The lower bound functional can be viewed as a variant of classical Tikhonov regularization that penalizes also the covariance. Then we develop an efficient alternating direction maximization algorithm for solving the optimization problem, and analyze its convergence. We discuss strategies for reducing the computational complexity via low rank structure of the forward operator and the sparsity of the covariance. Further, as an application of the lower bound, we discuss hierarchical Bayesian modeling for selecting the hyperparameter in the prior distribution, and propose a monotonically convergent algorithm for determining the hyperparameter. We present extensive numerical experiments to illustrate the Gaussian approximation and the algorithms.

Energy-Driven Image Interpolation Using Gaussian Process Regression

Directory of Open Access Journals (Sweden)

Lingling Zi

2012-01-01

Full Text Available Image interpolation, as a method of obtaining a high-resolution image from the corresponding low-resolution image, is a classical problem in image processing. In this paper, we propose a novel energy-driven interpolation algorithm employing Gaussian process regression. In our algorithm, each interpolated pixel is predicted by a combination of two information sources: first is a statistical model adopted to mine underlying information, and second is an energy computation technique used to acquire information on pixel properties. We further demonstrate that our algorithm can not only achieve image interpolation, but also reduce noise in the original image. Our experiments show that the proposed algorithm can achieve encouraging performance in terms of image visualization and quantitative measures.

Beam energy distribution influences on density modulation efficiency in seeded free-electron lasers

Directory of Open Access Journals (Sweden)

Guanglei Wang

2015-06-01

Full Text Available The beam energy spread at the entrance of an undulator system is of paramount importance for efficient density modulation in high-gain seeded free-electron lasers (FELs. In this paper, the dependences of high harmonic bunching efficiency in high-gain harmonic generation (HGHG, echo-enabled harmonic generation (EEHG and phase-merging enhanced harmonic generation (PEHG schemes on the electron beam energy spread distribution are studied. Theoretical investigations and multidimensional numerical simulations are applied to the cases of uniform and saddle beam energy distributions and compared to a traditional Gaussian distribution. It shows that the uniform and saddle electron energy distributions significantly enhance the bunching performance of HGHG FELs, while they almost have no influence on EEHG and PEHG schemes. A further start-to-end simulation example demonstrated that, with the saddle distribution of sliced beam energy spread controlled by a laser heater, the 30th harmonic can be directly generated by a single-stage HGHG scheme for a soft x-ray FEL facility.

Boltzmann-Gaussian transition under specific noise effect

International Nuclear Information System (INIS)

Anh, Chu Thuy; Lan, Nguyen Tri; Viet, Nguyen Ai

2014-01-01

It is observed that a short time data set of market returns presents almost symmetric Boltzmann distribution whereas a long time data set tends to show a Gaussian distribution. To understand this universal phenomenon, many hypotheses which are spreading in a wide range of interdisciplinary research were proposed. In current work, the effects of background fluctuations on symmetric Boltzmann distribution is investigated. The numerical calculation is performed to show that the Gaussian noise may cause the transition from initial Boltzmann distribution to Gaussian one. The obtained results would reflect non-dynamic nature of the transition under consideration.

Discrete Ziggurat: A time-memory trade-off for sampling from a Gaussian distribution over the integers

NARCIS (Netherlands)

Buchmann, J.; Cabarcas, D.; Göpfert, F.; Hülsing, A.T.; Weiden, P.; Lange, T.; Lauter, K.; Lisonek, P.

2014-01-01

Several lattice-based cryptosystems require to sample from a discrete Gaussian distribution over the integers. Existing methods to sample from such a distribution either need large amounts of memory or they are very slow. In this paper we explore a different method that allows for a flexible

Gaussian likelihood inference on data from trans-Gaussian random fields with Matérn covariance function

KAUST Repository

Yan, Yuan; Genton, Marc G.

2017-01-01

Gaussian likelihood inference has been studied and used extensively in both statistical theory and applications due to its simplicity. However, in practice, the assumption of Gaussianity is rarely met in the analysis of spatial data. In this paper, we study the effect of non-Gaussianity on Gaussian likelihood inference for the parameters of the Matérn covariance model. By using Monte Carlo simulations, we generate spatial data from a Tukey g-and-h random field, a flexible trans-Gaussian random field, with the Matérn covariance function, where g controls skewness and h controls tail heaviness. We use maximum likelihood based on the multivariate Gaussian distribution to estimate the parameters of the Matérn covariance function. We illustrate the effects of non-Gaussianity of the data on the estimated covariance function by means of functional boxplots. Thanks to our tailored simulation design, a comparison of the maximum likelihood estimator under both the increasing and fixed domain asymptotics for spatial data is performed. We find that the maximum likelihood estimator based on Gaussian likelihood is overall satisfying and preferable than the non-distribution-based weighted least squares estimator for data from the Tukey g-and-h random field. We also present the result for Gaussian kriging based on Matérn covariance estimates with data from the Tukey g-and-h random field and observe an overall satisfactory performance.

Gaussian likelihood inference on data from trans-Gaussian random fields with Matérn covariance function

KAUST Repository

Yan, Yuan

2017-07-13

Gaussian likelihood inference has been studied and used extensively in both statistical theory and applications due to its simplicity. However, in practice, the assumption of Gaussianity is rarely met in the analysis of spatial data. In this paper, we study the effect of non-Gaussianity on Gaussian likelihood inference for the parameters of the Matérn covariance model. By using Monte Carlo simulations, we generate spatial data from a Tukey g-and-h random field, a flexible trans-Gaussian random field, with the Matérn covariance function, where g controls skewness and h controls tail heaviness. We use maximum likelihood based on the multivariate Gaussian distribution to estimate the parameters of the Matérn covariance function. We illustrate the effects of non-Gaussianity of the data on the estimated covariance function by means of functional boxplots. Thanks to our tailored simulation design, a comparison of the maximum likelihood estimator under both the increasing and fixed domain asymptotics for spatial data is performed. We find that the maximum likelihood estimator based on Gaussian likelihood is overall satisfying and preferable than the non-distribution-based weighted least squares estimator for data from the Tukey g-and-h random field. We also present the result for Gaussian kriging based on Matérn covariance estimates with data from the Tukey g-and-h random field and observe an overall satisfactory performance.

Quantum steering of multimode Gaussian states by Gaussian measurements: monogamy relations and the Peres conjecture

International Nuclear Information System (INIS)

Ji, Se-Wan; Nha, Hyunchul; Kim, M S

2015-01-01

It is a topic of fundamental and practical importance how a quantum correlated state can be reliably distributed through a noisy channel for quantum information processing. The concept of quantum steering recently defined in a rigorous manner is relevant to study it under certain circumstances and here we address quantum steerability of Gaussian states to this aim. In particular, we attempt to reformulate the criterion for Gaussian steering in terms of local and global purities and show that it is sufficient and necessary for the case of steering a 1-mode system by an N-mode system. It subsequently enables us to reinforce a strong monogamy relation under which only one party can steer a local system of 1-mode. Moreover, we show that only a negative partial-transpose state can manifest quantum steerability by Gaussian measurements in relation to the Peres conjecture. We also discuss our formulation for the case of distributing a two-mode squeezed state via one-way quantum channels making dissipation and amplification effects, respectively. Finally, we extend our approach to include non-Gaussian measurements, more precisely, all orders of higher-order squeezing measurements, and find that this broad set of non-Gaussian measurements is not useful to demonstrate steering for Gaussian states beyond Gaussian measurements. (paper)

Gaussian basis functions for highly oscillatory scattering wavefunctions

Science.gov (United States)

Mant, B. P.; Law, M. M.

2018-04-01

We have applied a basis set of distributed Gaussian functions within the S-matrix version of the Kohn variational method to scattering problems involving deep potential energy wells. The Gaussian positions and widths are tailored to the potential using the procedure of Bačić and Light (1986 J. Chem. Phys. 85 4594) which has previously been applied to bound-state problems. The placement procedure is shown to be very efficient and gives scattering wavefunctions and observables in agreement with direct numerical solutions. We demonstrate the basis function placement method with applications to hydrogen atom–hydrogen atom scattering and antihydrogen atom–hydrogen atom scattering.

Gaussian statistics for palaeomagnetic vectors

Science.gov (United States)

Love, J.J.; Constable, C.G.

2003-01-01

With the aim of treating the statistics of palaeomagnetic directions and intensities jointly and consistently, we represent the mean and the variance of palaeomagnetic vectors, at a particular site and of a particular polarity, by a probability density function in a Cartesian three-space of orthogonal magnetic-field components consisting of a single (unimoda) non-zero mean, spherically-symmetrical (isotropic) Gaussian function. For palaeomagnetic data of mixed polarities, we consider a bimodal distribution consisting of a pair of such symmetrical Gaussian functions, with equal, but opposite, means and equal variances. For both the Gaussian and bi-Gaussian distributions, and in the spherical three-space of intensity, inclination, and declination, we obtain analytical expressions for the marginal density functions, the cumulative distributions, and the expected values and variances for each spherical coordinate (including the angle with respect to the axis of symmetry of the distributions). The mathematical expressions for the intensity and off-axis angle are closed-form and especially manageable, with the intensity distribution being Rayleigh-Rician. In the limit of small relative vectorial dispersion, the Gaussian (bi-Gaussian) directional distribution approaches a Fisher (Bingham) distribution and the intensity distribution approaches a normal distribution. In the opposite limit of large relative vectorial dispersion, the directional distributions approach a spherically-uniform distribution and the intensity distribution approaches a Maxwell distribution. We quantify biases in estimating the properties of the vector field resulting from the use of simple arithmetic averages, such as estimates of the intensity or the inclination of the mean vector, or the variances of these quantities. With the statistical framework developed here and using the maximum-likelihood method, which gives unbiased estimates in the limit of large data numbers, we demonstrate how to

Gaussian statistics for palaeomagnetic vectors

Science.gov (United States)

Love, J. J.; Constable, C. G.

2003-03-01

With the aim of treating the statistics of palaeomagnetic directions and intensities jointly and consistently, we represent the mean and the variance of palaeomagnetic vectors, at a particular site and of a particular polarity, by a probability density function in a Cartesian three-space of orthogonal magnetic-field components consisting of a single (unimodal) non-zero mean, spherically-symmetrical (isotropic) Gaussian function. For palaeomagnetic data of mixed polarities, we consider a bimodal distribution consisting of a pair of such symmetrical Gaussian functions, with equal, but opposite, means and equal variances. For both the Gaussian and bi-Gaussian distributions, and in the spherical three-space of intensity, inclination, and declination, we obtain analytical expressions for the marginal density functions, the cumulative distributions, and the expected values and variances for each spherical coordinate (including the angle with respect to the axis of symmetry of the distributions). The mathematical expressions for the intensity and off-axis angle are closed-form and especially manageable, with the intensity distribution being Rayleigh-Rician. In the limit of small relative vectorial dispersion, the Gaussian (bi-Gaussian) directional distribution approaches a Fisher (Bingham) distribution and the intensity distribution approaches a normal distribution. In the opposite limit of large relative vectorial dispersion, the directional distributions approach a spherically-uniform distribution and the intensity distribution approaches a Maxwell distribution. We quantify biases in estimating the properties of the vector field resulting from the use of simple arithmetic averages, such as estimates of the intensity or the inclination of the mean vector, or the variances of these quantities. With the statistical framework developed here and using the maximum-likelihood method, which gives unbiased estimates in the limit of large data numbers, we demonstrate how to

Centroid and full-width at half maximum uncertainties of histogrammed data with an underlying Gaussian distribution -- The moments method

International Nuclear Information System (INIS)

Valentine, J.D.; Rana, A.E.

1996-01-01

The effect of approximating a continuous Gaussian distribution with histogrammed data are studied. The expressions for theoretical uncertainties in centroid and full-width at half maximum (FWHM), as determined by calculation of moments, are derived using the error propagation method for a histogrammed Gaussian distribution. The results are compared with the corresponding pseudo-experimental uncertainties for computer-generated histogrammed Gaussian peaks to demonstrate the effect of binning the data. It is shown that increasing the number of bins in the histogram improves the continuous distribution approximation. For example, a FWHM ≥ 9 and FWHM ≥ 12 bins are needed to reduce the pseudo-experimental standard deviation of FWHM to within ≥5% and ≥1%, respectively, of the theoretical value for a peak containing 10,000 counts. In addition, the uncertainties in the centroid and FWHM as a function of peak area are studied. Finally, Sheppard's correction is applied to partially correct for the binning effect

Time-frequency analysis and harmonic Gaussian functions

International Nuclear Information System (INIS)

Ranaivoson, R.T.R; Raoelina Andriambololona; Hanitriarivo, R.

2013-01-01

A method for time-frequency analysis is given. The approach utilizes properties of Gaussian distribution, properties of Hermite polynomials and Fourier analysis. We begin by the definitions of a set of functions called Harmonic Gaussian Functions. Then these functions are used to define a set of transformations, noted Τ n , which associate to a function ψ, of the time variable t, a set of functions Ψ n which depend on time, frequency and frequency (or time) standard deviation. Some properties of the transformations Τ n and the functions Ψ n are given. It is proved in particular that the square of the modulus of each function Ψ n can be interpreted as a representation of the energy distribution of the signal, represented by the function ψ, in the time-frequency plane for a given value of the frequency (or time) standard deviation. It is also shown that the function ψ can be recovered from the functions Ψ n .

Mixed Platoon Flow Dispersion Model Based on Speed-Truncated Gaussian Mixture Distribution

Directory of Open Access Journals (Sweden)

Weitiao Wu

2013-01-01

Full Text Available A mixed traffic flow feature is presented on urban arterials in China due to a large amount of buses. Based on field data, a macroscopic mixed platoon flow dispersion model (MPFDM was proposed to simulate the platoon dispersion process along the road section between two adjacent intersections from the flow view. More close to field observation, truncated Gaussian mixture distribution was adopted as the speed density distribution for mixed platoon. Expectation maximum (EM algorithm was used for parameters estimation. The relationship between the arriving flow distribution at downstream intersection and the departing flow distribution at upstream intersection was investigated using the proposed model. Comparison analysis using virtual flow data was performed between the Robertson model and the MPFDM. The results confirmed the validity of the proposed model.

Superstatistical generalised Langevin equation: non-Gaussian viscoelastic anomalous diffusion

Science.gov (United States)

Ślęzak, Jakub; Metzler, Ralf; Magdziarz, Marcin

2018-02-01

Recent advances in single particle tracking and supercomputing techniques demonstrate the emergence of normal or anomalous, viscoelastic diffusion in conjunction with non-Gaussian distributions in soft, biological, and active matter systems. We here formulate a stochastic model based on a generalised Langevin equation in which non-Gaussian shapes of the probability density function and normal or anomalous diffusion have a common origin, namely a random parametrisation of the stochastic force. We perform a detailed analysis demonstrating how various types of parameter distributions for the memory kernel result in exponential, power law, or power-log law tails of the memory functions. The studied system is also shown to exhibit a further unusual property: the velocity has a Gaussian one point probability density but non-Gaussian joint distributions. This behaviour is reflected in the relaxation from a Gaussian to a non-Gaussian distribution observed for the position variable. We show that our theoretical results are in excellent agreement with stochastic simulations.

Ultrawide Bandwidth Receiver Based on a Multivariate Generalized Gaussian Distribution

KAUST Repository

Ahmed, Qasim Zeeshan

2015-04-01

Multivariate generalized Gaussian density (MGGD) is used to approximate the multiple access interference (MAI) and additive white Gaussian noise in pulse-based ultrawide bandwidth (UWB) system. The MGGD probability density function (pdf) is shown to be a better approximation of a UWB system as compared to multivariate Gaussian, multivariate Laplacian and multivariate Gaussian-Laplacian mixture (GLM). The similarity between the simulated and the approximated pdf is measured with the help of modified Kullback-Leibler distance (KLD). It is also shown that MGGD has the smallest KLD as compared to Gaussian, Laplacian and GLM densities. A receiver based on the principles of minimum bit error rate is designed for the MGGD pdf. As the requirement is stringent, the adaptive implementation of the receiver is also carried out in this paper. Training sequence of the desired user is the only requirement when implementing the detector adaptively. © 2002-2012 IEEE.

On signal design by the R/0/ criterion for non-white Gaussian noise channels

Science.gov (United States)

Bordelon, D. L.

1977-01-01

The use of the cut-off rate criterion for modulation system design is investigated for channels with non-white Gaussian noise. A signal space representation of the waveform channel is developed, and the cut-off rate for vector channels with additive non-white Gaussian noise and unquantized demodulation is derived. When the signal input to the channel is a continuous random vector, maximization of the cut-off rate with constrained average signal energy leads to a water-filling interpretation of optimal energy distribution in signal space. The necessary condition for a finite signal set to maximize the cut-off rate with constrained energy and an equally likely probability assignment of signal vectors is presented, and an algorithm is outlined for numerically computing the optimum signal set. As an example, the rectangular signal set which has the water-filling average energy distribution and the optimum rectangular set are compared.

Analysis of coals and biomass pyrolysis using the distributed activation energy model.

Science.gov (United States)

Li, Zhengqi; Liu, Chunlong; Chen, Zhichao; Qian, Juan; Zhao, Wei; Zhu, Qunyi

2009-01-01

The thermal decomposition of coals and biomass was studied using thermogravimetric analysis with the distributed activation energy model. The integral method resulted in Datong bituminous coal conversions of 3-73% at activation energies of 100-486 kJ/mol. The corresponding frequency factors were e(19.5)-e(59.0)s(-1). Jindongnan lean coal conversions were 8-52% at activation energies of 100-462 kJ/mol. Their corresponding frequency factors were e(13.0)-e(55.8)s(-1). The conversion of corn-stalk skins were 1-84% at activation energies of 62-169 kJ/mol with frequency factors of e(10.8)-e(26.5)s(-1). Datong bituminous coal, Jindongnan lean coal and corn-stalk skins had approximate Gaussian distribution functions with linear ln k(0) to E relationships.

Reproducing kernel Hilbert spaces of Gaussian priors

NARCIS (Netherlands)

Vaart, van der A.W.; Zanten, van J.H.; Clarke, B.; Ghosal, S.

2008-01-01

We review definitions and properties of reproducing kernel Hilbert spaces attached to Gaussian variables and processes, with a view to applications in nonparametric Bayesian statistics using Gaussian priors. The rate of contraction of posterior distributions based on Gaussian priors can be described

Upper bounds on the relative energy difference of pure and mixed Gaussian states with a fixed fidelity

International Nuclear Information System (INIS)

Dodonov, V V

2012-01-01

Exact and approximate formulas for the upper bound of the relative energy difference of two Gaussian states with a fixed fidelity between them are derived. The reciprocal formulas for the upper bound of the fidelity for the fixed value of the relative energy difference are also obtained. The bounds appear higher for pure states than for mixed ones, and their maximal values correspond to squeezed vacuum states. In particular, to guarantee the relative energy difference less than 10%, for quite arbitrary Gaussian states, the fidelity between them must exceed the level 0.998866. (fast track communication)

Energy and energy gradient matrix elements with N-particle explicitly correlated complex Gaussian basis functions with L =1

Science.gov (United States)

Bubin, Sergiy; Adamowicz, Ludwik

2008-03-01

In this work we consider explicitly correlated complex Gaussian basis functions for expanding the wave function of an N-particle system with the L =1 total orbital angular momentum. We derive analytical expressions for various matrix elements with these basis functions including the overlap, kinetic energy, and potential energy (Coulomb interaction) matrix elements, as well as matrix elements of other quantities. The derivatives of the overlap, kinetic, and potential energy integrals with respect to the Gaussian exponential parameters are also derived and used to calculate the energy gradient. All the derivations are performed using the formalism of the matrix differential calculus that facilitates a way of expressing the integrals in an elegant matrix form, which is convenient for the theoretical analysis and the computer implementation. The new method is tested in calculations of two systems: the lowest P state of the beryllium atom and the bound P state of the positronium molecule (with the negative parity). Both calculations yielded new, lowest-to-date, variational upper bounds, while the number of basis functions used was significantly smaller than in previous studies. It was possible to accomplish this due to the use of the analytic energy gradient in the minimization of the variational energy.

Energy and energy gradient matrix elements with N-particle explicitly correlated complex Gaussian basis functions with L=1.

Science.gov (United States)

Bubin, Sergiy; Adamowicz, Ludwik

2008-03-21

In this work we consider explicitly correlated complex Gaussian basis functions for expanding the wave function of an N-particle system with the L=1 total orbital angular momentum. We derive analytical expressions for various matrix elements with these basis functions including the overlap, kinetic energy, and potential energy (Coulomb interaction) matrix elements, as well as matrix elements of other quantities. The derivatives of the overlap, kinetic, and potential energy integrals with respect to the Gaussian exponential parameters are also derived and used to calculate the energy gradient. All the derivations are performed using the formalism of the matrix differential calculus that facilitates a way of expressing the integrals in an elegant matrix form, which is convenient for the theoretical analysis and the computer implementation. The new method is tested in calculations of two systems: the lowest P state of the beryllium atom and the bound P state of the positronium molecule (with the negative parity). Both calculations yielded new, lowest-to-date, variational upper bounds, while the number of basis functions used was significantly smaller than in previous studies. It was possible to accomplish this due to the use of the analytic energy gradient in the minimization of the variational energy.

Influence of atmospheric turbulence on the energy focusability of Gaussian beams with spherical aberration

International Nuclear Information System (INIS)

Deng, Jinping; Ji, Xiaoling

2014-01-01

By using the four-dimensional (4D) computer code of the time-dependent propagation of laser beams through atmospheric turbulence, the influence of atmospheric turbulence on the energy focusability of Gaussian beams with spherical aberration is studied in detail, where the mean-squared beam width, the power in the bucket (PIB), the β parameter and the energy Strehl ratio are taken as the characteristic parameters. It is shown that turbulence results in beam spreading, and the effect of spherical aberration on the beam spreading decreases due to turbulence. Gaussian beams with negative spherical aberration are more affected by turbulence than those with positive spherical aberration. For the negative spherical aberration case, the focus position moves to the source plane due to turbulence. It is mentioned that the influence of turbulence on the energy focusability defined by a certain energy (i.e. PIB = 63%) is very heavy when the negative spherical aberration is very heavy. On the other hand, the influence of turbulence on the energy focusability defined by the energy within a given bucket radius (i.e. mean-squared beam width) is heaviest when a certain negative spherical aberration coefficient is adopted. (papers)

Passivity and practical work extraction using Gaussian operations

International Nuclear Information System (INIS)

Brown, Eric G; Huber, Marcus; Friis, Nicolai

2016-01-01

Quantum states that can yield work in a cyclical Hamiltonian process form one of the primary resources in the context of quantum thermodynamics. Conversely, states whose average energy cannot be lowered by unitary transformations are called passive. However, while work may be extracted from non-passive states using arbitrary unitaries, the latter may be hard to realize in practice. It is therefore pertinent to consider the passivity of states under restricted classes of operations that can be feasibly implemented. Here, we ask how restrictive the class of Gaussian unitaries is for the task of work extraction. We investigate the notion of Gaussian passivity, that is, we present necessary and sufficient criteria identifying all states whose energy cannot be lowered by Gaussian unitaries. For all other states we give a prescription for the Gaussian operations that extract the maximal amount of energy. Finally, we show that the gap between passivity and Gaussian passivity is maximal, i.e., Gaussian-passive states may still have a maximal amount of energy that is extractable by arbitrary unitaries, even under entropy constraints. (paper)

On signal design by the R sub 0 criterion for non-white Gaussian noise channels

Science.gov (United States)

Bordelon, D. L.

1976-01-01

The use of the R sub 0 criterion for modulation system design is investigated for channels with non-white Gaussian noise. A signal space representation of the waveform channel is developed, and the cut-off rate R sub 0 for vector channels with additive nonwhite Gaussian noise and unquantized demodulation is derived. When the signal unput to the channel is a continuous random vector, maximization of R sub 0 with constrained average signal energy leads to a water-filling interpretation of optimal energy distribution in signal space. The necessary condition for a finite signal set to maximize R sub 0 with constrained energy and an equally likely probability assignment of signal vectors is presented, and an algorithm is outlined for numerically computing the optimum signal set. A necessary condition on a constrained energy, finite signal set is found which maximizes a Taylor series approximation of R sub 0. This signal set is compared with the finite signal set which has the water-filling average energy distribution.

The Gaussian cell two-point 'energy-like' equation : application to large-scale galaxy redshift and peculiar motion surveys

NARCIS (Netherlands)

Zaroubi, S; Branchini, E

2005-01-01

We introduce a simple linear equation relating the line-of-sight peculiar-velocity and density contrast correlation functions. The relation, which we call the Gaussian cell two-point 'energy-like' equation, is valid at the distant-observer limit and requires Gaussian smoothed fields. In the variance

Non-Gaussian power grid frequency fluctuations characterized by Lévy-stable laws and superstatistics

Science.gov (United States)

Schäfer, Benjamin; Beck, Christian; Aihara, Kazuyuki; Witthaut, Dirk; Timme, Marc

2018-02-01

Multiple types of fluctuations impact the collective dynamics of power grids and thus challenge their robust operation. Fluctuations result from processes as different as dynamically changing demands, energy trading and an increasing share of renewable power feed-in. Here we analyse principles underlying the dynamics and statistics of power grid frequency fluctuations. Considering frequency time series for a range of power grids, including grids in North America, Japan and Europe, we find a strong deviation from Gaussianity best described as Lévy-stable and q-Gaussian distributions. We present a coarse framework to analytically characterize the impact of arbitrary noise distributions, as well as a superstatistical approach that systematically interprets heavy tails and skewed distributions. We identify energy trading as a substantial contribution to today's frequency fluctuations and effective damping of the grid as a controlling factor enabling reduction of fluctuation risks, with enhanced effects for small power grids.

A Correction of Random Incidence Absorption Coefficients for the Angular Distribution of Acoustic Energy under Measurement Conditions

DEFF Research Database (Denmark)

Jeong, Cheol-Ho

2009-01-01

Most acoustic measurements are based on an assumption of ideal conditions. One such ideal condition is a diffuse and reverberant field. In practice, a perfectly diffuse sound field cannot be achieved in a reverberation chamber. Uneven incident energy density under measurement conditions can cause...... discrepancies between the measured value and the theoretical random incidence absorption coefficient. Therefore the angular distribution of the incident acoustic energy onto an absorber sample should be taken into account. The angular distribution of the incident energy density was simulated using the beam...... tracing method for various room shapes and source positions. The averaged angular distribution is found to be similar to a Gaussian distribution. As a result, an angle-weighted absorption coefficient was proposed by considering the angular energy distribution to improve the agreement between...

Crossover between the Gaussian orthogonal ensemble, the Gaussian unitary ensemble, and Poissonian statistics.

Science.gov (United States)

Schweiner, Frank; Laturner, Jeanine; Main, Jörg; Wunner, Günter

2017-11-01

Until now only for specific crossovers between Poissonian statistics (P), the statistics of a Gaussian orthogonal ensemble (GOE), or the statistics of a Gaussian unitary ensemble (GUE) have analytical formulas for the level spacing distribution function been derived within random matrix theory. We investigate arbitrary crossovers in the triangle between all three statistics. To this aim we propose an according formula for the level spacing distribution function depending on two parameters. Comparing the behavior of our formula for the special cases of P→GUE, P→GOE, and GOE→GUE with the results from random matrix theory, we prove that these crossovers are described reasonably. Recent investigations by F. Schweiner et al. [Phys. Rev. E 95, 062205 (2017)2470-004510.1103/PhysRevE.95.062205] have shown that the Hamiltonian of magnetoexcitons in cubic semiconductors can exhibit all three statistics in dependence on the system parameters. Evaluating the numerical results for magnetoexcitons in dependence on the excitation energy and on a parameter connected with the cubic valence band structure and comparing the results with the formula proposed allows us to distinguish between regular and chaotic behavior as well as between existent or broken antiunitary symmetries. Increasing one of the two parameters, transitions between different crossovers, e.g., from the P→GOE to the P→GUE crossover, are observed and discussed.

Enhancement of force patterns classification based on Gaussian distributions.

Science.gov (United States)

Ertelt, Thomas; Solomonovs, Ilja; Gronwald, Thomas

2018-01-23

Description of the patterns of ground reaction force is a standard method in areas such as medicine, biomechanics and robotics. The fundamental parameter is the time course of the force, which is classified visually in particular in the field of clinical diagnostics. Here, the knowledge and experience of the diagnostician is relevant for its assessment. For an objective and valid discrimination of the ground reaction force pattern, a generic method, especially in the medical field, is absolutely necessary to describe the qualities of the time-course. The aim of the presented method was to combine the approaches of two existing procedures from the fields of machine learning and the Gauss approximation in order to take advantages of both methods for the classification of ground reaction force patterns. The current limitations of both methods could be eliminated by an overarching method. Twenty-nine male athletes from different sports were examined. Each participant was given the task of performing a one-legged stopping maneuver on a force plate from the maximum possible starting speed. The individual time course of the ground reaction force of each subject was registered and approximated on the basis of eight Gaussian distributions. The descriptive coefficients were then classified using Bayesian regulated neural networks. The different sports served as the distinguishing feature. Although the athletes were all given the same task, all sports referred to a different quality in the time course of ground reaction force. Meanwhile within each sport, the athletes were homogeneous. With an overall prediction (R = 0.938) all subjects/sports were classified correctly with 94.29% accuracy. The combination of the two methods: the mathematical description of the time course of ground reaction forces on the basis of Gaussian distributions and their classification by means of Bayesian regulated neural networks, seems an adequate and promising method to discriminate the

The properties of the dark matter halo distribution in non-Gaussian scenarios

International Nuclear Information System (INIS)

Carbone, C.; Branchini, E.; Dolag, K.; Grossi, M.; Iannuzzi, F.; Matarrese, S.; Moscardini, L.; Verde, L.

2009-01-01

The description of halo abundance and clustering for non-Gaussian initial conditions has recently received renewed interest, motivated by the forthcoming large galaxy and cluster surveys, which can potentially detect primordial non-Gaussianity of the local form with a non-Gaussianity parameter |f NL | of order unity. This is particularly exciting because, while the simplest single-field slow-roll models of inflation predict a primordial |f NL | NL of large-scale structures that are expected to be above the predicted detection threshold [C. Carbone, L. Verde, and S. Matarrese, ApJL 684 (2008) L1]. We present tests on N-body simulations of analytical formulae describing the halo abundance and clustering for non-Gaussian initial conditions. In particular, when we calibrate the analytic non-Gaussian mass function of [S. Matarrese, L. Verde, L. and R. Jimenez, ApJL 541 (2000) 10] and [M. LoVerde, A. Miller, S. Shandera and L. Verde, JCAP 04 (2008) 014] and the analytic description of halo clustering for non-Gaussian initial conditions on N-body simulations, we find excellent agreement between the simulations and the analytic predictions if we make the substitutions δ c →δ c x√(q) and δ c →δ c xq where q≅0.75, in the density threshold for gravitational collapse and in the non-Gaussian fractional correction to the halo bias, respectively. We discuss the implications of these corrections on present and forecasted primordial non-Gaussianity constraints. We confirm that the non-Gaussian halo bias offers a robust and highly competitive test of primordial non-Gaussianity.

Football fever: goal distributions and non-Gaussian statistics

Science.gov (United States)

Bittner, E.; Nußbaumer, A.; Janke, W.; Weigel, M.

2009-02-01

Analyzing football score data with statistical techniques, we investigate how the not purely random, but highly co-operative nature of the game is reflected in averaged properties such as the probability distributions of scored goals for the home and away teams. As it turns out, especially the tails of the distributions are not well described by the Poissonian or binomial model resulting from the assumption of uncorrelated random events. Instead, a good effective description of the data is provided by less basic distributions such as the negative binomial one or the probability densities of extreme value statistics. To understand this behavior from a microscopical point of view, however, no waiting time problem or extremal process need be invoked. Instead, modifying the Bernoulli random process underlying the Poissonian model to include a simple component of self-affirmation seems to describe the data surprisingly well and allows to understand the observed deviation from Gaussian statistics. The phenomenological distributions used before can be understood as special cases within this framework. We analyzed historical football score data from many leagues in Europe as well as from international tournaments, including data from all past tournaments of the “FIFA World Cup” series, and found the proposed models to be applicable rather universally. In particular, here we analyze the results of the German women’s premier football league and consider the two separate German men’s premier leagues in the East and West during the cold war times as well as the unified league after 1990 to see how scoring in football and the component of self-affirmation depend on cultural and political circumstances.

Learning conditional Gaussian networks

DEFF Research Database (Denmark)

Bøttcher, Susanne Gammelgaard

This paper considers conditional Gaussian networks. The parameters in the network are learned by using conjugate Bayesian analysis. As conjugate local priors, we apply the Dirichlet distribution for discrete variables and the Gaussian-inverse gamma distribution for continuous variables, given...... a configuration of the discrete parents. We assume parameter independence and complete data. Further, to learn the structure of the network, the network score is deduced. We then develop a local master prior procedure, for deriving parameter priors in these networks. This procedure satisfies parameter...... independence, parameter modularity and likelihood equivalence. Bayes factors to be used in model search are introduced. Finally the methods derived are illustrated by a simple example....

Linking network usage patterns to traffic Gaussianity fit

NARCIS (Netherlands)

de Oliveira Schmidt, R.; Sadre, R.; Melnikov, Nikolay; Schönwälder, Jürgen; Pras, Aiko

Gaussian traffic models are widely used in the domain of network traffic modeling. The central assumption is that traffic aggregates are Gaussian distributed. Due to its importance, the Gaussian character of network traffic has been extensively assessed by researchers in the past years. In 2001,

Divergence of relative difference in Gaussian distribution function and stochastic resonance in a bistable system with frictionless state transition

Science.gov (United States)

Kasai, Seiya; Ichiki, Akihisa; Tadokoro, Yukihiro

2018-03-01

A bistable system efficiently detects a weak signal by adding noise, which is referred to as stochastic resonance. A previous theory deals with friction in state transition; however, this hypothesis is inadequate when friction force is negligible such as in nano- and molecular-scale systems. We show that, when the transition occurs without friction, the sensitivity of the bistable system to a Gaussian-noise-imposed weak signal becomes significantly high. The sensitivity is determined by the relative difference in noise distribution function. We find that the relative difference in Gaussian distribution function diverges in its tail edge, resulting in a high sensitivity in the present system.

Distributed Remote Vector Gaussian Source Coding for Wireless Acoustic Sensor Networks

DEFF Research Database (Denmark)

Zahedi, Adel; Østergaard, Jan; Jensen, Søren Holdt

2014-01-01

In this paper, we consider the problem of remote vector Gaussian source coding for a wireless acoustic sensor network. Each node receives messages from multiple nodes in the network and decodes these messages using its own measurement of the sound field as side information. The node’s measurement...... and the estimates of the source resulting from decoding the received messages are then jointly encoded and transmitted to a neighboring node in the network. We show that for this distributed source coding scenario, one can encode a so-called conditional sufficient statistic of the sources instead of jointly...

Scattering of 14. 0 MeV electrons. Fundamental study of the scattering foil. [Angular distribution, 14. 0 MeV, gaussian distribution

Energy Technology Data Exchange (ETDEWEB)

Takei, C [Kyushu Univ., Fukuoka (Japan). School of Health Sciences; Yoshimoto, S

1977-07-01

The angular distribution of 14.0 MeV electrons scattered by thin Al and Pb foils has been measured, since the beam flatness is important on the high energy electron therapy. These distributions measured were almost completely Gaussian. The root mean square scattering angles were obtained and were compared with the theories of Williams and Rossi. In our experiments the root mean square scattering angles obtained have the experimental errors of about 4% and 1% for 5/sup 0/ and 10/sup 0/, respectively. For Al foils of 0.5 mm to 3.0 mm the experimental values of the root mean square scattering angles are 5.49/sup 0/ and 12.43/sup 0/ and are 30% to 10% higher than those predicted by Williams. Although, these values are 4% to 9% lower than those calculated from the theory of Rossi. The root mean square scattering angles obtained with Pb foils of 0.1 mm to 0.3 mm are 9.62/sup 0/ to 18.05/sup 0/ and are 14% to 18% higher than Williams, and are 14% to 7% lower than those theoretically calculated by Rossi.

Partial summations of stationary sequences of non-Gaussian random variables

DEFF Research Database (Denmark)

Mohr, Gunnar; Ditlevsen, Ove Dalager

1996-01-01

The distribution of the sum of a finite number of identically distributed random variables is in many cases easily determined given that the variables are independent. The moments of any order of the sum can always be expressed by the moments of the single term without computational problems...... of convergence of the distribution of a sum (or an integral) of mutually dependent random variables to the Gaussian distribution. The paper is closely related to the work in Ditlevsen el al. [Ditlevsen, O., Mohr, G. & Hoffmeyer, P. Integration of non-Gaussian fields. Prob. Engng Mech 11 (1996) 15-23](2)....... lognormal variables or polynomials of standard Gaussian variables. The dependency structure is induced by specifying the autocorrelation structure of the sequence of standard Gaussian variables. Particularly useful polynomials are the Winterstein approximations that distributionally fit with non...

Time evolution of a Gaussian class of quasi-distribution functions under quadratic Hamiltonian.

Science.gov (United States)

Ginzburg, D; Mann, A

2014-03-10

A Lie algebraic method for propagation of the Wigner quasi-distribution function (QDF) under quadratic Hamiltonian was presented by Zoubi and Ben-Aryeh. We show that the same method can be used in order to propagate a rather general class of QDFs, which we call the "Gaussian class." This class contains as special cases the well-known Wigner, Husimi, Glauber, and Kirkwood-Rihaczek QDFs. We present some examples of the calculation of the time evolution of those functions.

Exploration, Sampling, And Reconstruction of Free Energy Surfaces with Gaussian Process Regression.

Science.gov (United States)

Mones, Letif; Bernstein, Noam; Csányi, Gábor

2016-10-11

Practical free energy reconstruction algorithms involve three separate tasks: biasing, measuring some observable, and finally reconstructing the free energy surface from those measurements. In more than one dimension, adaptive schemes make it possible to explore only relatively low lying regions of the landscape by progressively building up the bias toward the negative of the free energy surface so that free energy barriers are eliminated. Most schemes use the final bias as their best estimate of the free energy surface. We show that large gains in computational efficiency, as measured by the reduction of time to solution, can be obtained by separating the bias used for dynamics from the final free energy reconstruction itself. We find that biasing with metadynamics, measuring a free energy gradient estimator, and reconstructing using Gaussian process regression can give an order of magnitude reduction in computational cost.

Quantum beamstrahlung from gaussian bunches

International Nuclear Information System (INIS)

Chen, P.

1987-08-01

The method of Baier and Katkov is applied to calculate the correction terms to the Sokolov-Ternov radiation formula due to the variation of the magnetic field strength along the trajectory of a radiating particle. We carry the calculation up to the second order in the power expansion of B tau/B, where tau is the formation time of radiation. The expression is then used to estimate the quantum beamstrahlung average energy loss from e + e - bunches with gaussian distribution in bunch currents. We show that the effect of the field variation is to reduce the average energy loss from previous calculations based on the Sokolov-Ternov formula or its equivalent. Due to the limitation of our method, only an upper bound of the reduction is obtained. 18 refs

Investigation of non-Gaussian effects in the Brazilian option market

Science.gov (United States)

Sosa-Correa, William O.; Ramos, Antônio M. T.; Vasconcelos, Giovani L.

2018-04-01

An empirical study of the Brazilian option market is presented in light of three option pricing models, namely the Black-Scholes model, the exponential model, and a model based on a power law distribution, the so-called q-Gaussian distribution or Tsallis distribution. It is found that the q-Gaussian model performs better than the Black-Scholes model in about one third of the option chains analyzed. But among these cases, the exponential model performs better than the q-Gaussian model in 75% of the time. The superiority of the exponential model over the q-Gaussian model is particularly impressive for options close to the expiration date, where its success rate rises above ninety percent.

High-efficiency Gaussian key reconciliation in continuous variable quantum key distribution

Science.gov (United States)

Bai, ZengLiang; Wang, XuYang; Yang, ShenShen; Li, YongMin

2016-01-01

Efficient reconciliation is a crucial step in continuous variable quantum key distribution. The progressive-edge-growth (PEG) algorithm is an efficient method to construct relatively short block length low-density parity-check (LDPC) codes. The qua-sicyclic construction method can extend short block length codes and further eliminate the shortest cycle. In this paper, by combining the PEG algorithm and qua-si-cyclic construction method, we design long block length irregular LDPC codes with high error-correcting capacity. Based on these LDPC codes, we achieve high-efficiency Gaussian key reconciliation with slice recon-ciliation based on multilevel coding/multistage decoding with an efficiency of 93.7%.

Quantum key distribution using basis encoding of Gaussian-modulated coherent states

Science.gov (United States)

Huang, Peng; Huang, Jingzheng; Zhang, Zheshen; Zeng, Guihua

2018-04-01

The continuous-variable quantum key distribution (CVQKD) has been demonstrated to be available in practical secure quantum cryptography. However, its performance is restricted strongly by the channel excess noise and the reconciliation efficiency. In this paper, we present a quantum key distribution (QKD) protocol by encoding the secret keys on the random choices of two measurement bases: the conjugate quadratures X and P . The employed encoding method can dramatically weaken the effects of channel excess noise and reconciliation efficiency on the performance of the QKD protocol. Subsequently, the proposed scheme exhibits the capability to tolerate much higher excess noise and enables us to reach a much longer secure transmission distance even at lower reconciliation efficiency. The proposal can work alternatively to strengthen significantly the performance of the known Gaussian-modulated CVQKD protocol and serve as a multiplier for practical secure quantum cryptography with continuous variables.

Extreme Temperature Exceedances Change more Rapidly Under Future Warming in Regions of non-Gaussian Short Temperature Distribution Tails

Science.gov (United States)

Loikith, P. C.; Neelin, J. D.; Meyerson, J.

2017-12-01

Regions of shorter-than-Gaussian warm and cold side temperature distribution tails are shown to occur in spatially coherent patterns in the current climate. Under such conditions, warming may be manifested in more complex ways than if the underlying distribution were close to Gaussian. For example, under a uniform warm shift, the simplest prototype for future warming, a location with a short warm side tail would experience a greater increase in extreme warm exceedances compared to if the distribution were Gaussian. Similarly, for a location with a short cold side tail, a uniform warm shift would result in a rapid decrease in extreme cold exceedances. Both scenarios carry major societal and environmental implications including but not limited to negative impacts on human and ecosystem health, agriculture, and the economy. It is therefore important for climate models to be able to realistically reproduce short tails in simulations of historical climate in order to boost confidence in projections of future temperature extremes. Overall, climate models contributing to the fifth phase of the Coupled Model Intercomparison Project capture many of the principal observed regions of short tails. This suggests the underlying dynamics and physics occur on scales resolved by the models, and helps build confidence in model projections of extremes. Furthermore, most GCMs show more rapid changes in exceedances of extreme temperature thresholds in regions of short tails. Results therefore suggest that the shape of the tails of the underlying temperature distribution is an indicator of how rapidly a location will experience changes to extreme temperature occurrence under future warming.

Linear velocity fields in non-Gaussian models for large-scale structure

Science.gov (United States)

Scherrer, Robert J.

1992-01-01

Linear velocity fields in two types of physically motivated non-Gaussian models are examined for large-scale structure: seed models, in which the density field is a convolution of a density profile with a distribution of points, and local non-Gaussian fields, derived from a local nonlinear transformation on a Gaussian field. The distribution of a single component of the velocity is derived for seed models with randomly distributed seeds, and these results are applied to the seeded hot dark matter model and the global texture model with cold dark matter. An expression for the distribution of a single component of the velocity in arbitrary local non-Gaussian models is given, and these results are applied to such fields with chi-squared and lognormal distributions. It is shown that all seed models with randomly distributed seeds and all local non-Guassian models have single-component velocity distributions with positive kurtosis.

Reliability Implications in Wood Systems of a Bivariate Gaussian-Weibull Distribution and the Associated Univariate Pseudo-truncated Weibull

Science.gov (United States)

Steve P. Verrill; James W. Evans; David E. Kretschmann; Cherilyn A. Hatfield

2014-01-01

Two important wood properties are the modulus of elasticity (MOE) and the modulus of rupture (MOR). In the past, the statistical distribution of the MOE has often been modeled as Gaussian, and that of the MOR as lognormal or as a two- or three-parameter Weibull distribution. It is well known that MOE and MOR are positively correlated. To model the simultaneous behavior...

Analysis of Distributed Consensus Time Synchronization with Gaussian Delay over Wireless Sensor Networks

Directory of Open Access Journals (Sweden)

Xiong Gang

2009-01-01

Full Text Available This paper presents theoretical results on the convergence of the distributed consensus timing synchronization (DCTS algorithm for wireless sensor networks assuming general Gaussian delay between nodes. The asymptotic expectation and mean square of the global synchronization error are computed. The results lead to the definition of a time delay balanced network in which average timing consensus between nodes can be achieved despite random delays. Several structured network architectures are studied as examples, and their associated simulation results are used to validate analytical findings.

Equivalent non-Gaussian excitation method for response moment calculation of systems under non-Gaussian random excitation

International Nuclear Information System (INIS)

Tsuchida, Takahiro; Kimura, Koji

2015-01-01

Equivalent non-Gaussian excitation method is proposed to obtain the moments up to the fourth order of the response of systems under non-Gaussian random excitation. The excitation is prescribed by the probability density and power spectrum. Moment equations for the response can be derived from the stochastic differential equations for the excitation and the system. However, the moment equations are not closed due to the nonlinearity of the diffusion coefficient in the equation for the excitation. In the proposed method, the diffusion coefficient is replaced with the equivalent diffusion coefficient approximately to obtain a closed set of the moment equations. The square of the equivalent diffusion coefficient is expressed by the second-order polynomial. In order to demonstrate the validity of the method, a linear system to non-Gaussian excitation with generalized Gaussian distribution is analyzed. The results show the method is applicable to non-Gaussian excitation with the widely different kurtosis and bandwidth. (author)

Gaussian maximally multipartite-entangled states

Science.gov (United States)

Facchi, Paolo; Florio, Giuseppe; Lupo, Cosmo; Mancini, Stefano; Pascazio, Saverio

2009-12-01

We study maximally multipartite-entangled states in the context of Gaussian continuous variable quantum systems. By considering multimode Gaussian states with constrained energy, we show that perfect maximally multipartite-entangled states, which exhibit the maximum amount of bipartite entanglement for all bipartitions, only exist for systems containing n=2 or 3 modes. We further numerically investigate the structure of these states and their frustration for n≤7 .

Gaussian maximally multipartite-entangled states

International Nuclear Information System (INIS)

Facchi, Paolo; Florio, Giuseppe; Pascazio, Saverio; Lupo, Cosmo; Mancini, Stefano

2009-01-01

We study maximally multipartite-entangled states in the context of Gaussian continuous variable quantum systems. By considering multimode Gaussian states with constrained energy, we show that perfect maximally multipartite-entangled states, which exhibit the maximum amount of bipartite entanglement for all bipartitions, only exist for systems containing n=2 or 3 modes. We further numerically investigate the structure of these states and their frustration for n≤7.

Large-Scale Cubic-Scaling Random Phase Approximation Correlation Energy Calculations Using a Gaussian Basis.

Science.gov (United States)

Wilhelm, Jan; Seewald, Patrick; Del Ben, Mauro; Hutter, Jürg

2016-12-13

We present an algorithm for computing the correlation energy in the random phase approximation (RPA) in a Gaussian basis requiring [Formula: see text] operations and [Formula: see text] memory. The method is based on the resolution of the identity (RI) with the overlap metric, a reformulation of RI-RPA in the Gaussian basis, imaginary time, and imaginary frequency integration techniques, and the use of sparse linear algebra. Additional memory reduction without extra computations can be achieved by an iterative scheme that overcomes the memory bottleneck of canonical RPA implementations. We report a massively parallel implementation that is the key for the application to large systems. Finally, cubic-scaling RPA is applied to a thousand water molecules using a correlation-consistent triple-ζ quality basis.

Gaussian capacity of the quantum bosonic memory channel with additive correlated Gaussian noise

International Nuclear Information System (INIS)

Schaefer, Joachim; Karpov, Evgueni; Cerf, Nicolas J.

2011-01-01

We present an algorithm for calculation of the Gaussian classical capacity of a quantum bosonic memory channel with additive Gaussian noise. The algorithm, restricted to Gaussian input states, is applicable to all channels with noise correlations obeying certain conditions and works in the full input energy domain, beyond previous treatments of this problem. As an illustration, we study the optimal input states and capacity of a quantum memory channel with Gauss-Markov noise [J. Schaefer, Phys. Rev. A 80, 062313 (2009)]. We evaluate the enhancement of the transmission rate when using these optimal entangled input states by comparison with a product coherent-state encoding and find out that such a simple coherent-state encoding achieves not less than 90% of the capacity.

Monte Carlo simulation and gaussian broaden techniques for full energy peak of characteristic X-ray in EDXRF

International Nuclear Information System (INIS)

Li Zhe; Liu Min; Shi Rui; Wu Xuemei; Tuo Xianguo

2012-01-01

Background: Non-standard analysis (NSA) technique is one of the most important development directions of energy dispersive X-ray fluorescence (EDXRF). Purpose: This NSA technique is mainly based on Monte Carlo (MC) simulation and full energy peak broadening, which were studied preliminarily in this paper. Methods: A kind of MC model was established for Si-PIN based EDXRF setup, and the flux spectra were obtained for iron ore sample. Finally, the flux spectra were broadened by Gaussian broaden parameters calculated by a new method proposed in this paper, and the broadened spectra were compared with measured energy spectra. Results: MC method can be used to simulate EDXRF measurement, and can correct the matrix effects among elements automatically. Peak intensities can be obtained accurately by using the proposed Gaussian broaden technique. Conclusions: This study provided a key technique for EDXRF to achieve advanced NSA technology. (authors)

Inflation in random Gaussian landscapes

Energy Technology Data Exchange (ETDEWEB)

Masoumi, Ali; Vilenkin, Alexander; Yamada, Masaki, E-mail: ali@cosmos.phy.tufts.edu, E-mail: vilenkin@cosmos.phy.tufts.edu, E-mail: Masaki.Yamada@tufts.edu [Institute of Cosmology, Department of Physics and Astronomy, Tufts University, Medford, MA 02155 (United States)

2017-05-01

We develop analytic and numerical techniques for studying the statistics of slow-roll inflation in random Gaussian landscapes. As an illustration of these techniques, we analyze small-field inflation in a one-dimensional landscape. We calculate the probability distributions for the maximal number of e-folds and for the spectral index of density fluctuations n {sub s} and its running α {sub s} . These distributions have a universal form, insensitive to the correlation function of the Gaussian ensemble. We outline possible extensions of our methods to a large number of fields and to models of large-field inflation. These methods do not suffer from potential inconsistencies inherent in the Brownian motion technique, which has been used in most of the earlier treatments.

Response moments of dynamic systems under non-Gaussian random excitation by the equivalent non-Gaussian excitation method

International Nuclear Information System (INIS)

Tsuchida, Takahiro; Kimura, Koji

2016-01-01

Equivalent non-Gaussian excitation method is proposed to obtain the response moments up to the 4th order of dynamic systems under non-Gaussian random excitation. The non-Gaussian excitation is prescribed by the probability density and the power spectrum, and is described by an Ito stochastic differential equation. Generally, moment equations for the response, which are derived from the governing equations for the excitation and the system, are not closed due to the nonlinearity of the diffusion coefficient in the equation for the excitation even though the system is linear. In the equivalent non-Gaussian excitation method, the diffusion coefficient is replaced with the equivalent diffusion coefficient approximately to obtain a closed set of the moment equations. The square of the equivalent diffusion coefficient is expressed by a quadratic polynomial. In numerical examples, a linear system subjected to nonGaussian excitations with bimodal and Rayleigh distributions is analyzed by using the present method. The results show that the method yields the variance, skewness and kurtosis of the response with high accuracy for non-Gaussian excitation with the widely different probability densities and bandwidth. The statistical moments of the equivalent non-Gaussian excitation are also investigated to describe the feature of the method. (paper)

High-Order Local Pooling and Encoding Gaussians Over a Dictionary of Gaussians.

Science.gov (United States)

Li, Peihua; Zeng, Hui; Wang, Qilong; Shiu, Simon C K; Zhang, Lei

2017-07-01

Local pooling (LP) in configuration (feature) space proposed by Boureau et al. explicitly restricts similar features to be aggregated, which can preserve as much discriminative information as possible. At the time it appeared, this method combined with sparse coding achieved competitive classification results with only a small dictionary. However, its performance lags far behind the state-of-the-art results as only the zero-order information is exploited. Inspired by the success of high-order statistical information in existing advanced feature coding or pooling methods, we make an attempt to address the limitation of LP. To this end, we present a novel method called high-order LP (HO-LP) to leverage the information higher than the zero-order one. Our idea is intuitively simple: we compute the first- and second-order statistics per configuration bin and model them as a Gaussian. Accordingly, we employ a collection of Gaussians as visual words to represent the universal probability distribution of features from all classes. Our problem is naturally formulated as encoding Gaussians over a dictionary of Gaussians as visual words. This problem, however, is challenging since the space of Gaussians is not a Euclidean space but forms a Riemannian manifold. We address this challenge by mapping Gaussians into the Euclidean space, which enables us to perform coding with common Euclidean operations rather than complex and often expensive Riemannian operations. Our HO-LP preserves the advantages of the original LP: pooling only similar features and using a small dictionary. Meanwhile, it achieves very promising performance on standard benchmarks, with either conventional, hand-engineered features or deep learning-based features.

Non-Gaussianities in the topological charge distribution of the SU(3) Yang-Mills theory

Science.gov (United States)

Cè, Marco; Consonni, Cristian; Engel, Georg P.; Giusti, Leonardo

2015-10-01

We study the topological charge distribution of the SU(3) Yang-Mills theory with high precision in order to be able to detect deviations from Gaussianity. The computation is carried out on the lattice with high statistics Monte Carlo simulations by implementing a naive discretization of the topological charge evolved with the Yang-Mills gradient flow. This definition is far less demanding than the one suggested from Neuberger's fermions and, as shown in this paper, in the continuum limit its cumulants coincide with those of the universal definition appearing in the chiral Ward identities. Thanks to the range of lattice volumes and spacings considered, we can extrapolate the results for the second and fourth cumulant of the topological charge distribution to the continuum limit with confidence by keeping finite volume effects negligible with respect to the statistical errors. Our best results for the topological susceptibility is t02χ =6.67 (7 )×1 0-4 , where t0 is a standard reference scale, while for the ratio of the fourth cumulant over the second, we obtain R =0.233 (45 ). The latter is compatible with the expectations from the large Nc expansion, while it rules out the θ behavior of the vacuum energy predicted by the dilute instanton model. Its large distance from 1 implies that, in the ensemble of gauge configurations that dominate the path integral, the fluctuations of the topological charge are of quantum nonperturbative nature.

Nonclassicality by Local Gaussian Unitary Operations for Gaussian States

Directory of Open Access Journals (Sweden)

Yangyang Wang

2018-04-01

Full Text Available A measure of nonclassicality N in terms of local Gaussian unitary operations for bipartite Gaussian states is introduced. N is a faithful quantum correlation measure for Gaussian states as product states have no such correlation and every non product Gaussian state contains it. For any bipartite Gaussian state ρ A B , we always have 0 ≤ N ( ρ A B < 1 , where the upper bound 1 is sharp. An explicit formula of N for ( 1 + 1 -mode Gaussian states and an estimate of N for ( n + m -mode Gaussian states are presented. A criterion of entanglement is established in terms of this correlation. The quantum correlation N is also compared with entanglement, Gaussian discord and Gaussian geometric discord.

Toward the detection of gravitational waves under non-Gaussian noises I. Locally optimal statistic.

Science.gov (United States)

Yokoyama, Jun'ichi

2014-01-01

After reviewing the standard hypothesis test and the matched filter technique to identify gravitational waves under Gaussian noises, we introduce two methods to deal with non-Gaussian stationary noises. We formulate the likelihood ratio function under weakly non-Gaussian noises through the Edgeworth expansion and strongly non-Gaussian noises in terms of a new method we call Gaussian mapping where the observed marginal distribution and the two-body correlation function are fully taken into account. We then apply these two approaches to Student's t-distribution which has a larger tails than Gaussian. It is shown that while both methods work well in the case the non-Gaussianity is small, only the latter method works well for highly non-Gaussian case.

Gaussian quadrature and lattice discretization of the Fermi-Dirac distribution for graphene.

Science.gov (United States)

Oettinger, D; Mendoza, M; Herrmann, H J

2013-07-01

We construct a lattice kinetic scheme to study electronic flow in graphene. For this purpose, we first derive a basis of orthogonal polynomials, using as the weight function the ultrarelativistic Fermi-Dirac distribution at rest. Later, we use these polynomials to expand the respective distribution in a moving frame, for both cases, undoped and doped graphene. In order to discretize the Boltzmann equation and make feasible the numerical implementation, we reduce the number of discrete points in momentum space to 18 by applying a Gaussian quadrature, finding that the family of representative wave (2+1)-vectors, which satisfies the quadrature, reconstructs a honeycomb lattice. The procedure and discrete model are validated by solving the Riemann problem, finding excellent agreement with other numerical models. In addition, we have extended the Riemann problem to the case of different dopings, finding that by increasing the chemical potential the electronic fluid behaves as if it increases its effective viscosity.

Testing the lognormality of the galaxy and weak lensing convergence distributions from Dark Energy Survey maps

International Nuclear Information System (INIS)

Clerkin, L.; Kirk, D.; Manera, M.; Lahav, O.; Abdalla, F.

2016-01-01

It is well known that the probability distribution function (PDF) of galaxy density contrast is approximately lognormal; whether the PDF of mass fluctuations derived from weak lensing convergence (κWL) is lognormal is less well established. We derive PDFs of the galaxy and projected matter density distributions via the counts-in-cells (CiC) method. We use maps of galaxies and weak lensing convergence produced from the Dark Energy Survey Science Verification data over 139 deg"2. We test whether the underlying density contrast is well described by a lognormal distribution for the galaxies, the convergence and their joint PDF. We confirm that the galaxy density contrast distribution is well modelled by a lognormal PDF convolved with Poisson noise at angular scales from 10 to 40 arcmin (corresponding to physical scales of 3–10 Mpc). We note that as κWL is a weighted sum of the mass fluctuations along the line of sight, its PDF is expected to be only approximately lognormal. We find that the κWL distribution is well modelled by a lognormal PDF convolved with Gaussian shape noise at scales between 10 and 20 arcmin, with a best-fitting χ"2/dof of 1.11 compared to 1.84 for a Gaussian model, corresponding to p-values 0.35 and 0.07, respectively, at a scale of 10 arcmin. Above 20 arcmin a simple Gaussian model is sufficient. The joint PDF is also reasonably fitted by a bivariate lognormal. As a consistency check, we compare the variances derived from the lognormal modelling with those directly measured via CiC. Lastly, our methods are validated against maps from the MICE Grand Challenge N-body simulation.

Gaussian Process-Mixture Conditional Heteroscedasticity.

Science.gov (United States)

Platanios, Emmanouil A; Chatzis, Sotirios P

2014-05-01

Generalized autoregressive conditional heteroscedasticity (GARCH) models have long been considered as one of the most successful families of approaches for volatility modeling in financial return series. In this paper, we propose an alternative approach based on methodologies widely used in the field of statistical machine learning. Specifically, we propose a novel nonparametric Bayesian mixture of Gaussian process regression models, each component of which models the noise variance process that contaminates the observed data as a separate latent Gaussian process driven by the observed data. This way, we essentially obtain a Gaussian process-mixture conditional heteroscedasticity (GPMCH) model for volatility modeling in financial return series. We impose a nonparametric prior with power-law nature over the distribution of the model mixture components, namely the Pitman-Yor process prior, to allow for better capturing modeled data distributions with heavy tails and skewness. Finally, we provide a copula-based approach for obtaining a predictive posterior for the covariances over the asset returns modeled by means of a postulated GPMCH model. We evaluate the efficacy of our approach in a number of benchmark scenarios, and compare its performance to state-of-the-art methodologies.

Gaussian sum rules for optical functions

International Nuclear Information System (INIS)

Kimel, I.

1981-12-01

A new (Gaussian) type of sum rules (GSR) for several optical functions, is presented. The functions considered are: dielectric permeability, refractive index, energy loss function, rotatory power and ellipticity (circular dichroism). While reducing to the usual type of sum rules in a certain limit, the GSR contain in general, a Gaussian factor that serves to improve convergence. GSR might be useful in analysing experimental data. (Author) [pt

Scaled unscented transform Gaussian sum filter: Theory and application

KAUST Repository

Luo, Xiaodong

2010-05-01

In this work we consider the state estimation problem in nonlinear/non-Gaussian systems. We introduce a framework, called the scaled unscented transform Gaussian sum filter (SUT-GSF), which combines two ideas: the scaled unscented Kalman filter (SUKF) based on the concept of scaled unscented transform (SUT) (Julier and Uhlmann (2004) [16]), and the Gaussian mixture model (GMM). The SUT is used to approximate the mean and covariance of a Gaussian random variable which is transformed by a nonlinear function, while the GMM is adopted to approximate the probability density function (pdf) of a random variable through a set of Gaussian distributions. With these two tools, a framework can be set up to assimilate nonlinear systems in a recursive way. Within this framework, one can treat a nonlinear stochastic system as a mixture model of a set of sub-systems, each of which takes the form of a nonlinear system driven by a known Gaussian random process. Then, for each sub-system, one applies the SUKF to estimate the mean and covariance of the underlying Gaussian random variable transformed by the nonlinear governing equations of the sub-system. Incorporating the estimations of the sub-systems into the GMM gives an explicit (approximate) form of the pdf, which can be regarded as a "complete" solution to the state estimation problem, as all of the statistical information of interest can be obtained from the explicit form of the pdf (Arulampalam et al. (2002) [7]). In applications, a potential problem of a Gaussian sum filter is that the number of Gaussian distributions may increase very rapidly. To this end, we also propose an auxiliary algorithm to conduct pdf re-approximation so that the number of Gaussian distributions can be reduced. With the auxiliary algorithm, in principle the SUT-GSF can achieve almost the same computational speed as the SUKF if the SUT-GSF is implemented in parallel. As an example, we will use the SUT-GSF to assimilate a 40-dimensional system due to

Integration of non-Gaussian fields

DEFF Research Database (Denmark)

Ditlevsen, Ove Dalager; Mohr, Gunnar; Hoffmeyer, Pernille

1996-01-01

The limitations of the validity of the central limit theorem argument as applied to definite integrals of non-Gaussian random fields are empirically explored by way of examples. The purpose is to investigate in specific cases whether the asymptotic convergence to the Gaussian distribution is fast....... and Randrup-Thomsen, S. Reliability of silo ring under lognormal stochastic pressure using stochastic interpolation. Proc. IUTAM Symp., Probabilistic Structural Mechanics: Advances in Structural Reliability Methods, San Antonio, TX, USA, June 1993 (eds.: P. D. Spanos & Y.-T. Wu) pp. 134-162. Springer, Berlin...

A Concept for Measuring Electron Distribution Functions Using Collective Thomson Scattering

Science.gov (United States)

Milder, A. L.; Froula, D. H.

2017-10-01

A.B. Langdon proposed that stable non-Maxwellian distribution functions are realized in coronal inertial confinement fusion plasmas via inverse bremsstrahlung heating. For Zvosc2 Zvosc2 vth2 > 1 , vth2 > 1 , the inverse bremsstrahlung heating rate is sufficiently fast to compete with electron-electron collisions. This process preferentially heats the subthermal electrons leading to super-Gaussian distribution functions. A method to identify the super-Gaussian order of the distribution functions in these plasmas using collective Thomson scattering will be proposed. By measuring the collective Thomson spectra over a range of angles the density, temperature and super-Gaussian order can be determined. This is accomplished by fitting non-Maxwellian distribution data with a super-Gaussian model; in order to match the density and electron temperature to within 10%, the super-Gaussian order must be varied. This material is based upon work supported by the Department of Energy National Nuclear Security Administration under Award Number DE-NA0001944.

Broad distribution spectrum from Gaussian to power law appears in stochastic variations in RNA-seq data.

Science.gov (United States)

Awazu, Akinori; Tanabe, Takahiro; Kamitani, Mari; Tezuka, Ayumi; Nagano, Atsushi J

2018-05-29

Gene expression levels exhibit stochastic variations among genetically identical organisms under the same environmental conditions. In many recent transcriptome analyses based on RNA sequencing (RNA-seq), variations in gene expression levels among replicates were assumed to follow a negative binomial distribution, although the physiological basis of this assumption remains unclear. In this study, RNA-seq data were obtained from Arabidopsis thaliana under eight conditions (21-27 replicates), and the characteristics of gene-dependent empirical probability density function (ePDF) profiles of gene expression levels were analyzed. For A. thaliana and Saccharomyces cerevisiae, various types of ePDF of gene expression levels were obtained that were classified as Gaussian, power law-like containing a long tail, or intermediate. These ePDF profiles were well fitted with a Gauss-power mixing distribution function derived from a simple model of a stochastic transcriptional network containing a feedback loop. The fitting function suggested that gene expression levels with long-tailed ePDFs would be strongly influenced by feedback regulation. Furthermore, the features of gene expression levels are correlated with their functions, with the levels of essential genes tending to follow a Gaussian-like ePDF while those of genes encoding nucleic acid-binding proteins and transcription factors exhibit long-tailed ePDF.

Stable Lévy motion with inverse Gaussian subordinator

Science.gov (United States)

Kumar, A.; Wyłomańska, A.; Gajda, J.

2017-09-01

In this paper we study the stable Lévy motion subordinated by the so-called inverse Gaussian process. This process extends the well known normal inverse Gaussian (NIG) process introduced by Barndorff-Nielsen, which arises by subordinating ordinary Brownian motion (with drift) with inverse Gaussian process. The NIG process found many interesting applications, especially in financial data description. We discuss here the main features of the introduced subordinated process, such as distributional properties, existence of fractional order moments and asymptotic tail behavior. We show the connection of the process with continuous time random walk. Further, the governing fractional partial differential equations for the probability density function is also obtained. Moreover, we discuss the asymptotic distribution of sample mean square displacement, the main tool in detection of anomalous diffusion phenomena (Metzler et al., 2014). In order to apply the stable Lévy motion time-changed by inverse Gaussian subordinator we propose a step-by-step procedure of parameters estimation. At the end, we show how the examined process can be useful to model financial time series.

Initial conditions for inflation and the energy scale of SUSY-breaking from the (nearly) gaussian sky

CERN Document Server

Álvarez-Gaumé, Luis; Jimenez, Raul

We show how general initial conditions for small field inflation can be obtained in multi-field models. This is provided by non-linear angular friction terms in the inflaton that provide a phase of non-slow-roll inflation before the slow-roll inflation phase. This in turn provides a natural mechanism to star small-field slow-roll at nearly zero velocity for arbitrary initial conditions. We also show that there is a relation between the scale of SUSY breaking sqrt (f) and the amount of non-gaussian fluctuations generated by the inflaton. In particular, we show that in the local non-gaussian shape there exists the relation sqrt (f) = 10^{13} GeV sqrt (f_NL). With current observational limits from Planck, and adopting the minimum amount of non-gaussian fluctuations allowed by single-field inflation, this provides a very tight constraint for the SUSY breaking energy scale sqrt (f) = 3-7 x 10^{13} GeV at 95% confidence. Further limits, or detection, from next year's Planck polarisation data will further tighten th...

Validity of the assumption of Gaussian turbulence; Gyldighed af antagelsen om Gaussisk turbulence

Energy Technology Data Exchange (ETDEWEB)

Nielsen, M.; Hansen, K.S.; Juul Pedersen, B.

2000-07-01

Wind turbines are designed to withstand the impact of turbulent winds, which fluctuations usually are assumed of Gaussian probability distribution. Based on a large number of measurements from many sites, this seems a reasonable assumption in flat homogeneous terrain whereas it may fail in complex terrain. At these sites the wind speed often has a skew distribution with more frequent lulls than gusts. In order to simulate aerodynamic loads, a numerical turbulence simulation method was developed and implemented. This method may simulate multiple time series of variable not necessarily Gaussian distribution without distortion of the spectral distribution or spatial coherence. The simulated time series were used as input to the dynamic-response simulation program Vestas Turbine Simulator (VTS). In this way we simulated the dynamic response of systems exposed to turbulence of either Gaussian or extreme, yet realistic, non-Gaussian probability distribution. Certain loads on turbines with active pitch regulation were enhanced by up to 15% compared to pure Gaussian turbulence. It should, however, be said that the undesired effect depends on the dynamic system, and it might be mitigated by optimisation of the wind turbine regulation system after local turbulence characteristics. (au)

Generalization of the Gaussian electrostatic model: Extension to arbitrary angular momentum, distributed multipoles, and speedup with reciprocal space methods

Science.gov (United States)

Cisneros, G. Andrés; Piquemal, Jean-Philip; Darden, Thomas A.

2006-11-01

The simulation of biological systems by means of current empirical force fields presents shortcomings due to their lack of accuracy, especially in the description of the nonbonded terms. We have previously introduced a force field based on density fitting termed the Gaussian electrostatic model-0 (GEM-0) J.-P. Piquemal et al. [J. Chem. Phys. 124, 104101 (2006)] that improves the description of the nonbonded interactions. GEM-0 relies on density fitting methodology to reproduce each contribution of the constrained space orbital variation (CSOV) energy decomposition scheme, by expanding the electronic density of the molecule in s-type Gaussian functions centered at specific sites. In the present contribution we extend the Coulomb and exchange components of the force field to auxiliary basis sets of arbitrary angular momentum. Since the basis functions with higher angular momentum have directionality, a reference molecular frame (local frame) formalism is employed for the rotation of the fitted expansion coefficients. In all cases the intermolecular interaction energies are calculated by means of Hermite Gaussian functions using the McMurchie-Davidson [J. Comput. Phys. 26, 218 (1978)] recursion to calculate all the required integrals. Furthermore, the use of Hermite Gaussian functions allows a point multipole decomposition determination at each expansion site. Additionally, the issue of computational speed is investigated by reciprocal space based formalisms which include the particle mesh Ewald (PME) and fast Fourier-Poisson (FFP) methods. Frozen-core (Coulomb and exchange-repulsion) intermolecular interaction results for ten stationary points on the water dimer potential-energy surface, as well as a one-dimensional surface scan for the canonical water dimer, formamide, stacked benzene, and benzene water dimers, are presented. All results show reasonable agreement with the corresponding CSOV calculated reference contributions, around 0.1 and 0.15kcal/mol error for

Gaussian Process Interpolation for Uncertainty Estimation in Image Registration

Science.gov (United States)

Wachinger, Christian; Golland, Polina; Reuter, Martin; Wells, William

2014-01-01

Intensity-based image registration requires resampling images on a common grid to evaluate the similarity function. The uncertainty of interpolation varies across the image, depending on the location of resampled points relative to the base grid. We propose to perform Bayesian inference with Gaussian processes, where the covariance matrix of the Gaussian process posterior distribution estimates the uncertainty in interpolation. The Gaussian process replaces a single image with a distribution over images that we integrate into a generative model for registration. Marginalization over resampled images leads to a new similarity measure that includes the uncertainty of the interpolation. We demonstrate that our approach increases the registration accuracy and propose an efficient approximation scheme that enables seamless integration with existing registration methods. PMID:25333127

Effects of the Distributions of Energy or Charge Transfer Rates on Spectral Hole Burning in Pigment-Protein Complexes at Low Temperatures

Energy Technology Data Exchange (ETDEWEB)

Herascu, N.; Ahmouda, S.; Picorel, R.; Seibert, M.; Jankowiak, R.; Zazubovich, V.

2011-12-22

Effects of the distributions of excitation energy transfer (EET) rates (homogeneous line widths) on the nonphotochemical (resonant) spectral hole burning (SHB) processes in photosynthetic chlorophyll-protein complexes (reaction center [RC] and CP43 antenna of Photosystem II from spinach) are considered. It is demonstrated that inclusion of such a distribution results in somewhat more dispersive hole burning kinetics. More importantly, however, inclusion of the EET rate distributions strongly affects the dependence of the hole width on the fractional hole depth. Different types of line width distributions have been explored, including those resulting from Foerster type EET between weakly interacting pigments as well as Gaussian ones, which may be a reasonable approximation for those resulting, for instance, from so-called extended Foerster models. For Gaussian line width distributions, it is possible to determine the parameters of both line width and tunneling parameter distributions from SHB data without a priori knowledge of any of them. Concerning more realistic asymmetric distributions, we demonstrate, using the simple example of CP43 antenna, that one can use SHB modeling to estimate electrostatic couplings between pigments and support or exclude assignment of certain pigment(s) to a particular state.

Making tensor factorizations robust to non-gaussian noise.

Energy Technology Data Exchange (ETDEWEB)

Chi, Eric C. (Rice University, Houston, TX); Kolda, Tamara Gibson

2011-03-01

Tensors are multi-way arrays, and the CANDECOMP/PARAFAC (CP) tensor factorization has found application in many different domains. The CP model is typically fit using a least squares objective function, which is a maximum likelihood estimate under the assumption of independent and identically distributed (i.i.d.) Gaussian noise. We demonstrate that this loss function can be highly sensitive to non-Gaussian noise. Therefore, we propose a loss function based on the 1-norm because it can accommodate both Gaussian and grossly non-Gaussian perturbations. We also present an alternating majorization-minimization (MM) algorithm for fitting a CP model using our proposed loss function (CPAL1) and compare its performance to the workhorse algorithm for fitting CP models, CP alternating least squares (CPALS).

Geometry of perturbed Gaussian states and quantum estimation

International Nuclear Information System (INIS)

Genoni, Marco G; Giorda, Paolo; Paris, Matteo G A

2011-01-01

We address the non-Gaussianity (nG) of states obtained by weakly perturbing a Gaussian state and investigate the relationships with quantum estimation. For classical perturbations, i.e. perturbations to eigenvalues, we found that the nG of the perturbed state may be written as the quantum Fisher information (QFI) distance minus a term depending on the infinitesimal energy change, i.e. it provides a lower bound to statistical distinguishability. Upon moving on isoenergetic surfaces in a neighbourhood of a Gaussian state, nG thus coincides with a proper distance in the Hilbert space and exactly quantifies the statistical distinguishability of the perturbations. On the other hand, for perturbations leaving the covariance matrix unperturbed, we show that nG provides an upper bound to the QFI. Our results show that the geometry of non-Gaussian states in the neighbourhood of a Gaussian state is definitely not trivial and cannot be subsumed by a differential structure. Nevertheless, the analysis of perturbations to a Gaussian state reveals that nG may be a resource for quantum estimation. The nG of specific families of perturbed Gaussian states is analysed in some detail with the aim of finding the maximally non-Gaussian state obtainable from a given Gaussian one. (fast track communication)

Release the BEESTS: Bayesian Estimation of Ex-Gaussian STop-Signal Reaction Time Distributions

Directory of Open Access Journals (Sweden)

Dora eMatzke

2013-12-01

Full Text Available The stop-signal paradigm is frequently used to study response inhibition. Inthis paradigm, participants perform a two-choice response time task wherethe primary task is occasionally interrupted by a stop-signal that promptsparticipants to withhold their response. The primary goal is to estimatethe latency of the unobservable stop response (stop signal reaction timeor SSRT. Recently, Matzke, Dolan, Logan, Brown, and Wagenmakers (inpress have developed a Bayesian parametric approach that allows for theestimation of the entire distribution of SSRTs. The Bayesian parametricapproach assumes that SSRTs are ex-Gaussian distributed and uses Markovchain Monte Carlo sampling to estimate the parameters of the SSRT distri-bution. Here we present an efficient and user-friendly software implementa-tion of the Bayesian parametric approach —BEESTS— that can be appliedto individual as well as hierarchical stop-signal data. BEESTS comes withan easy-to-use graphical user interface and provides users with summarystatistics of the posterior distribution of the parameters as well various diag-nostic tools to assess the quality of the parameter estimates. The softwareis open source and runs on Windows and OS X operating systems. In sum,BEESTS allows experimental and clinical psychologists to estimate entiredistributions of SSRTs and hence facilitates the more rigorous analysis ofstop-signal data.

Performance assessment of density functional methods with Gaussian and Slater basis sets using 7σ orbital momentum distributions of N2O

Science.gov (United States)

Wang, Feng; Pang, Wenning; Duffy, Patrick

2012-12-01

Performance of a number of commonly used density functional methods in chemistry (B3LYP, Bhandh, BP86, PW91, VWN, LB94, PBe0, SAOP and X3LYP and the Hartree-Fock (HF) method) has been assessed using orbital momentum distributions of the 7σ orbital of nitrous oxide (NNO), which models electron behaviour in a chemically significant region. The density functional methods are combined with a number of Gaussian basis sets (Pople's 6-31G*, 6-311G**, DGauss TZVP and Dunning's aug-cc-pVTZ as well as even-tempered Slater basis sets, namely, et-DZPp, et-QZ3P, et-QZ+5P and et-pVQZ). Orbital momentum distributions of the 7σ orbital in the ground electronic state of NNO, which are obtained from a Fourier transform into momentum space from single point electronic calculations employing the above models, are compared with experimental measurement of the same orbital from electron momentum spectroscopy (EMS). The present study reveals information on performance of (a) the density functional methods, (b) Gaussian and Slater basis sets, (c) combinations of the density functional methods and basis sets, that is, the models, (d) orbital momentum distributions, rather than a group of specific molecular properties and (e) the entire region of chemical significance of the orbital. It is found that discrepancies of this orbital between the measured and the calculated occur in the small momentum region (i.e. large r region). In general, Slater basis sets achieve better overall performance than the Gaussian basis sets. Performance of the Gaussian basis sets varies noticeably when combining with different Vxc functionals, but Dunning's augcc-pVTZ basis set achieves the best performance for the momentum distributions of this orbital. The overall performance of the B3LYP and BP86 models is similar to newer models such as X3LYP and SAOP. The present study also demonstrates that the combinations of the density functional methods and the basis sets indeed make a difference in the quality of the

Interconversion of pure Gaussian states requiring non-Gaussian operations

Science.gov (United States)

Jabbour, Michael G.; García-Patrón, Raúl; Cerf, Nicolas J.

2015-01-01

We analyze the conditions under which local operations and classical communication enable entanglement transformations between bipartite pure Gaussian states. A set of necessary and sufficient conditions had been found [G. Giedke et al., Quant. Inf. Comput. 3, 211 (2003)] for the interconversion between such states that is restricted to Gaussian local operations and classical communication. Here, we exploit majorization theory in order to derive more general (sufficient) conditions for the interconversion between bipartite pure Gaussian states that goes beyond Gaussian local operations. While our technique is applicable to an arbitrary number of modes for each party, it allows us to exhibit surprisingly simple examples of 2 ×2 Gaussian states that necessarily require non-Gaussian local operations to be transformed into each other.

Deterministic models for energy-loss straggling

International Nuclear Information System (INIS)

Prinja, A.K.; Gleicher, F.; Dunham, G.; Morel, J.E.

1999-01-01

Inelastic ion interactions with target electrons are dominated by extremely small energy transfers that are difficult to resolve numerically. The continuous-slowing-down (CSD) approximation is then commonly employed, which, however, only preserves the mean energy loss per collision through the stopping power, S(E) = ∫ 0 ∞ dEprime (E minus Eprime) σ s (E → Eprime). To accommodate energy loss straggling, a Gaussian distribution with the correct mean-squared energy loss (akin to a Fokker-Planck approximation in energy) is commonly used in continuous-energy Monte Carlo codes. Although this model has the unphysical feature that ions can be upscattered, it nevertheless yields accurate results. A multigroup model for energy loss straggling was recently presented for use in multigroup Monte Carlo codes or in deterministic codes that use multigroup data. The method has the advantage that the mean and mean-squared energy loss are preserved without unphysical upscatter and hence is computationally efficient. Results for energy spectra compared extremely well with Gaussian distributions under the idealized conditions for which the Gaussian may be considered to be exact. Here, the authors present more consistent comparisons by extending the method to accommodate upscatter and, further, compare both methods with exact solutions obtained from an analog Monte Carlo simulation, for a straight-ahead transport problem

On the Distribution of Indefinite Quadratic Forms in Gaussian Random Variables

KAUST Repository

Al-Naffouri, Tareq Y.

2015-10-30

© 2015 IEEE. In this work, we propose a unified approach to evaluating the CDF and PDF of indefinite quadratic forms in Gaussian random variables. Such a quantity appears in many applications in communications, signal processing, information theory, and adaptive filtering. For example, this quantity appears in the mean-square-error (MSE) analysis of the normalized least-meansquare (NLMS) adaptive algorithm, and SINR associated with each beam in beam forming applications. The trick of the proposed approach is to replace inequalities that appear in the CDF calculation with unit step functions and to use complex integral representation of the the unit step function. Complex integration allows us then to evaluate the CDF in closed form for the zero mean case and as a single dimensional integral for the non-zero mean case. Utilizing the saddle point technique allows us to closely approximate such integrals in non zero mean case. We demonstrate how our approach can be extended to other scenarios such as the joint distribution of quadratic forms and ratios of such forms, and to characterize quadratic forms in isotropic distributed random variables.We also evaluate the outage probability in multiuser beamforming using our approach to provide an application of indefinite forms in communications.

Optimality of Gaussian attacks in continuous-variable quantum cryptography.

Science.gov (United States)

Navascués, Miguel; Grosshans, Frédéric; Acín, Antonio

2006-11-10

We analyze the asymptotic security of the family of Gaussian modulated quantum key distribution protocols for continuous-variables systems. We prove that the Gaussian unitary attack is optimal for all the considered bounds on the key rate when the first and second momenta of the canonical variables involved are known by the honest parties.

Detecting Non-Gaussian and Lognormal Characteristics of Temperature and Water Vapor Mixing Ratio

Science.gov (United States)

Kliewer, A.; Fletcher, S. J.; Jones, A. S.; Forsythe, J. M.

2017-12-01

Many operational data assimilation and retrieval systems assume that the errors and variables come from a Gaussian distribution. This study builds upon previous results that shows that positive definite variables, specifically water vapor mixing ratio and temperature, can follow a non-Gaussian distribution and moreover a lognormal distribution. Previously, statistical testing procedures which included the Jarque-Bera test, the Shapiro-Wilk test, the Chi-squared goodness-of-fit test, and a composite test which incorporated the results of the former tests were employed to determine locations and time spans where atmospheric variables assume a non-Gaussian distribution. These tests are now investigated in a "sliding window" fashion in order to extend the testing procedure to near real-time. The analyzed 1-degree resolution data comes from the National Oceanic and Atmospheric Administration (NOAA) Global Forecast System (GFS) six hour forecast from the 0Z analysis. These results indicate the necessity of a Data Assimilation (DA) system to be able to properly use the lognormally-distributed variables in an appropriate Bayesian analysis that does not assume the variables are Gaussian.

Analysis of piezoelectric energy harvester under modulated and filtered white Gaussian noise

Science.gov (United States)

Quaranta, Giuseppe; Trentadue, Francesco; Maruccio, Claudio; Marano, Giuseppe C.

2018-05-01

This paper proposes a comprehensive method for the electromechanical probabilistic analysis of piezoelectric energy harvesters subjected to modulated and filtered white Gaussian noise (WGN) at the base. Specifically, the dynamic excitation is simulated by means of an amplitude-modulated WGN, which is filtered through the Clough-Penzien filter. The considered piezoelectric harvester is a cantilever bimorph modeled as Euler-Bernoulli beam with a concentrated mass at the free-end, and its global behavior is approximated by the fundamental vibration mode (which is tuned with the dominant frequency of the dynamic input). A resistive electrical load is considered in the circuit. Once the Lyapunov equation of the coupled electromechanical problem has been formulated, an original and efficient semi-analytical procedure is proposed to estimate mean and standard deviation of the electrical energy extracted from the piezoelectric layers.

A Gaussian mixture copula model based localized Gaussian process regression approach for long-term wind speed prediction

International Nuclear Information System (INIS)

Yu, Jie; Chen, Kuilin; Mori, Junichi; Rashid, Mudassir M.

2013-01-01

Optimizing wind power generation and controlling the operation of wind turbines to efficiently harness the renewable wind energy is a challenging task due to the intermittency and unpredictable nature of wind speed, which has significant influence on wind power production. A new approach for long-term wind speed forecasting is developed in this study by integrating GMCM (Gaussian mixture copula model) and localized GPR (Gaussian process regression). The time series of wind speed is first classified into multiple non-Gaussian components through the Gaussian mixture copula model and then Bayesian inference strategy is employed to incorporate the various non-Gaussian components using the posterior probabilities. Further, the localized Gaussian process regression models corresponding to different non-Gaussian components are built to characterize the stochastic uncertainty and non-stationary seasonality of the wind speed data. The various localized GPR models are integrated through the posterior probabilities as the weightings so that a global predictive model is developed for the prediction of wind speed. The proposed GMCM–GPR approach is demonstrated using wind speed data from various wind farm locations and compared against the GMCM-based ARIMA (auto-regressive integrated moving average) and SVR (support vector regression) methods. In contrast to GMCM–ARIMA and GMCM–SVR methods, the proposed GMCM–GPR model is able to well characterize the multi-seasonality and uncertainty of wind speed series for accurate long-term prediction. - Highlights: • A novel predictive modeling method is proposed for long-term wind speed forecasting. • Gaussian mixture copula model is estimated to characterize the multi-seasonality. • Localized Gaussian process regression models can deal with the random uncertainty. • Multiple GPR models are integrated through Bayesian inference strategy. • The proposed approach shows higher prediction accuracy and reliability

Evaluation of the influence of double and triple Gaussian proton kernel models on accuracy of dose calculations for spot scanning technique.

Science.gov (United States)

Hirayama, Shusuke; Takayanagi, Taisuke; Fujii, Yusuke; Fujimoto, Rintaro; Fujitaka, Shinichiro; Umezawa, Masumi; Nagamine, Yoshihiko; Hosaka, Masahiro; Yasui, Keisuke; Omachi, Chihiro; Toshito, Toshiyuki

2016-03-01

The main purpose in this study was to present the results of beam modeling and how the authors systematically investigated the influence of double and triple Gaussian proton kernel models on the accuracy of dose calculations for spot scanning technique. The accuracy of calculations was important for treatment planning software (TPS) because the energy, spot position, and absolute dose had to be determined by TPS for the spot scanning technique. The dose distribution was calculated by convolving in-air fluence with the dose kernel. The dose kernel was the in-water 3D dose distribution of an infinitesimal pencil beam and consisted of an integral depth dose (IDD) and a lateral distribution. Accurate modeling of the low-dose region was important for spot scanning technique because the dose distribution was formed by cumulating hundreds or thousands of delivered beams. The authors employed a double Gaussian function as the in-air fluence model of an individual beam. Double and triple Gaussian kernel models were also prepared for comparison. The parameters of the kernel lateral model were derived by fitting a simulated in-water lateral dose profile induced by an infinitesimal proton beam, whose emittance was zero, at various depths using Monte Carlo (MC) simulation. The fitted parameters were interpolated as a function of depth in water and stored as a separate look-up table. These stored parameters for each energy and depth in water were acquired from the look-up table when incorporating them into the TPS. The modeling process for the in-air fluence and IDD was based on the method proposed in the literature. These were derived using MC simulation and measured data. The authors compared the measured and calculated absolute doses at the center of the spread-out Bragg peak (SOBP) under various volumetric irradiation conditions to systematically investigate the influence of the two types of kernel models on the dose calculations. The authors investigated the difference

Vibrational Energy Distribution Analysis (VEDA): Scopes and limitations

Science.gov (United States)

Jamróz, Michał H.

2013-10-01

The principle of operations of the VEDA program written by the author for Potential Energy Distribution (PED) analysis of theoretical vibrational spectra is described. Nowadays, the PED analysis is indispensible tool in serious analysis of the vibrational spectra. To perform the PED analysis it is necessary to define 3N-6 linearly independent local mode coordinates. Already for 20-atomic molecules it is a difficult task. The VEDA program reads the input data automatically from the Gaussian program output files. Then, VEDA automatically proposes an introductory set of local mode coordinates. Next, the more adequate coordinates are proposed by the program and optimized to obtain maximal elements of each column (internal coordinate) of the PED matrix (the EPM parameter). The possibility for an automatic optimization of PED contributions is a unique feature of the VEDA program absent in any other programs performing PED analysis.

Frequency Characteristics of Surface Wave Generated by Single-Line Pulsed Laser Beam with Two Kinds of Spatial Energy Profile Models: Gaussian and Square-Like

Energy Technology Data Exchange (ETDEWEB)

Seo, Ho Geon; Kim, Myung Hwan; Choi, Sung Ho; Kim, Chung Seok; Jhang, Kyung Young [Hanyang University, Seoul (Korea, Republic of)

2012-08-15

Using a single-line pulsed laser beam is well known as a useful noncontact method to generate a directional surface acoustic wave. In this method, different laser beam energy profiles produce different waveforms and frequency characteristics. In this paper, we considered two typical kinds of laser beam energy profiles, Gaussian and square-like, to find out a difference in the frequency characteristics. To achieve this, mathematical models were proposed first for Gaussian laser beam profile and square-like respectively, both of which depended on the laser beam width. To verify the theoretical models, experimental setups with a cylindrical lens and a line-slit mask were respectively designed to produce a line laser beam with Gaussian spatial energy profile and square-like. The frequency responses of the theoretical models showed good agreement with experimental results in terms of the existence of harmonic frequency components and the shift of the first peak frequencies to low.

Spectrophotometry of Wolf-Rayet stars. I - Continuum energy distributions

Science.gov (United States)

Morris, Patrick W.; Brownsberger, Kenneth R.; Conti, Peter S.; Massey, Philip; Vacca, William D.

1993-01-01

All available low-resolution IUE spectra are assembled for Galactic, LMC, and SMC W-R stars and are merged with ground-based optical and NIR spectra in order to collate in a systematic fashion the shapes of these energy distributions over the wavelength range 0.1-1 micron. They can be consistently fitted by a power law of the form F(lambda) is approximately equal to lambda exp -alpha over the range 1500-9000 A to derive color excesses E(B-V) and spectral indices by removing the 2175-A interstellar absorption feature. The WN star color excesses derived are found to be in good agreement with those of Schmutz and Vacca (1991) and Koesterke et al. (1991). Significant heterogeneity in spectral index values was generally seen with any given subtype, but the groups consisting of the combined set of Galactic and LMC W-R stars, the separate WN and WC sequences, and the Galactic and LMC W-R stars all showed a striking and consistent Gaussian-like frequency distribution of values.

A Gaussian quadrature method for total energy analysis in electronic state calculations

Science.gov (United States)

Fukushima, Kimichika

This article reports studies by Fukushima and coworkers since 1980 concerning their highly accurate numerical integral method using Gaussian quadratures to evaluate the total energy in electronic state calculations. Gauss-Legendre and Gauss-Laguerre quadratures were used for integrals in the finite and infinite regions, respectively. Our previous article showed that, for diatomic molecules such as CO and FeO, elliptic coordinates efficiently achieved high numerical integral accuracy even with a numerical basis set including transition metal atomic orbitals. This article will generalize straightforward details for multiatomic systems with direct integrals in each decomposed elliptic coordinate determined from the nuclear positions of picked-up atom pairs. Sample calculations were performed for the molecules O3 and H2O. This article will also try to present, in another coordinate, a numerical integral by partially using the Becke's decomposition published in 1988, but without the Becke's fuzzy cell generated by the polynomials of internuclear distance between the pair atoms. Instead, simple nuclear weights comprising exponential functions around nuclei are used. The one-center integral is performed with a Gaussian quadrature pack in a spherical coordinate, included in the author's original program in around 1980. As for this decomposition into one-center integrals, sample calculations are carried out for Li2.

Hybrid algorithm of ensemble transform and importance sampling for assimilation of non-Gaussian observations

Directory of Open Access Journals (Sweden)

Shin'ya Nakano

2014-05-01

Full Text Available A hybrid algorithm that combines the ensemble transform Kalman filter (ETKF and the importance sampling approach is proposed. Since the ETKF assumes a linear Gaussian observation model, the estimate obtained by the ETKF can be biased in cases with nonlinear or non-Gaussian observations. The particle filter (PF is based on the importance sampling technique, and is applicable to problems with nonlinear or non-Gaussian observations. However, the PF usually requires an unrealistically large sample size in order to achieve a good estimation, and thus it is computationally prohibitive. In the proposed hybrid algorithm, we obtain a proposal distribution similar to the posterior distribution by using the ETKF. A large number of samples are then drawn from the proposal distribution, and these samples are weighted to approximate the posterior distribution according to the importance sampling principle. Since the importance sampling provides an estimate of the probability density function (PDF without assuming linearity or Gaussianity, we can resolve the bias due to the nonlinear or non-Gaussian observations. Finally, in the next forecast step, we reduce the sample size to achieve computational efficiency based on the Gaussian assumption, while we use a relatively large number of samples in the importance sampling in order to consider the non-Gaussian features of the posterior PDF. The use of the ETKF is also beneficial in terms of the computational simplicity of generating a number of random samples from the proposal distribution and in weighting each of the samples. The proposed algorithm is not necessarily effective in case that the ensemble is located distant from the true state. However, monitoring the effective sample size and tuning the factor for covariance inflation could resolve this problem. In this paper, the proposed hybrid algorithm is introduced and its performance is evaluated through experiments with non-Gaussian observations.

A Gaussian Approximation Potential for Silicon

Science.gov (United States)

Bernstein, Noam; Bartók, Albert; Kermode, James; Csányi, Gábor

We present an interatomic potential for silicon using the Gaussian Approximation Potential (GAP) approach, which uses the Gaussian process regression method to approximate the reference potential energy surface as a sum of atomic energies. Each atomic energy is approximated as a function of the local environment around the atom, which is described with the smooth overlap of atomic environments (SOAP) descriptor. The potential is fit to a database of energies, forces, and stresses calculated using density functional theory (DFT) on a wide range of configurations from zero and finite temperature simulations. These include crystalline phases, liquid, amorphous, and low coordination structures, and diamond-structure point defects, dislocations, surfaces, and cracks. We compare the results of the potential to DFT calculations, as well as to previously published models including Stillinger-Weber, Tersoff, modified embedded atom method (MEAM), and ReaxFF. We show that it is very accurate as compared to the DFT reference results for a wide range of properties, including low energy bulk phases, liquid structure, as well as point, line, and plane defects in the diamond structure.

q-Gamow states for intermediate energies

Energy Technology Data Exchange (ETDEWEB)

Plastino, A. [La Plata National University and Argentina' s National Research Council, (IFLP-CCT-CONICET)-C. C. 727, 1900 La Plata (Argentina); Rocca, M.C., E-mail: mariocarlosrocca@gmail.com [La Plata National University and Argentina' s National Research Council, (IFLP-CCT-CONICET)-C. C. 727, 1900 La Plata (Argentina); Ferri, G.L. [Fac. de C. Exactas, National University La Pampa, Peru y Uruguay, Santa Rosa, La Pampa (Argentina); Zamora, D.J. [La Plata National University and Argentina' s National Research Council, (IFLP-CCT-CONICET)-C. C. 727, 1900 La Plata (Argentina)

2016-11-15

In a recent paper Plastino and Rocca (2016) [18] we have demonstrated the possible existence of Tsallis' q-Gamow states. Now, accelerators' experimental evidence for Tsallis' distributions has been ascertained only at very high energies. Here, instead, we develop a different set of q-Gamow states for which the associated q-Breit–Wigner distribution could easily be found at intermediate energies, for which accelerators are available at many locations. In this context, it should be strongly emphasized Vignat and Plastino (2009) [2] that, empirically, one never exactly and unambiguously “detects” pure Gaussians, but rather q-Gaussians. A prediction is made via Eq. (3.4).

Detection Performance of Signals in Dependent Noise From a Gaussian Mixture Uncertainty Class

National Research Council Canada - National Science Library

Gerlach, K

1998-01-01

... (correlated) multivariate noise from a Gaussian mixture uncertainty class. This uncertainty class is defined using upper and lower bounding functions on the univariate Gaussian mixing distribution function...

Non-Gaussian Methods for Causal Structure Learning.

Science.gov (United States)

Shimizu, Shohei

2018-05-22

Causal structure learning is one of the most exciting new topics in the fields of machine learning and statistics. In many empirical sciences including prevention science, the causal mechanisms underlying various phenomena need to be studied. Nevertheless, in many cases, classical methods for causal structure learning are not capable of estimating the causal structure of variables. This is because it explicitly or implicitly assumes Gaussianity of data and typically utilizes only the covariance structure. In many applications, however, non-Gaussian data are often obtained, which means that more information may be contained in the data distribution than the covariance matrix is capable of containing. Thus, many new methods have recently been proposed for using the non-Gaussian structure of data and inferring the causal structure of variables. This paper introduces prevention scientists to such causal structure learning methods, particularly those based on the linear, non-Gaussian, acyclic model known as LiNGAM. These non-Gaussian data analysis tools can fully estimate the underlying causal structures of variables under assumptions even in the presence of unobserved common causes. This feature is in contrast to other approaches. A simulated example is also provided.

Numerical modeling of macrodispersion in heterogeneous media: a comparison of multi-Gaussian and non-multi-Gaussian models

Science.gov (United States)

Wen, Xian-Huan; Gómez-Hernández, J. Jaime

1998-03-01

The macrodispersion of an inert solute in a 2-D heterogeneous porous media is estimated numerically in a series of fields of varying heterogeneity. Four different random function (RF) models are used to model log-transmissivity (ln T) spatial variability, and for each of these models, ln T variance is varied from 0.1 to 2.0. The four RF models share the same univariate Gaussian histogram and the same isotropic covariance, but differ from one another in terms of the spatial connectivity patterns at extreme transmissivity values. More specifically, model A is a multivariate Gaussian model for which, by definition, extreme values (both high and low) are spatially uncorrelated. The other three models are non-multi-Gaussian: model B with high connectivity of high extreme values, model C with high connectivity of low extreme values, and model D with high connectivities of both high and low extreme values. Residence time distributions (RTDs) and macrodispersivities (longitudinal and transverse) are computed on ln T fields corresponding to the different RF models, for two different flow directions and at several scales. They are compared with each other, as well as with predicted values based on first-order analytical results. Numerically derived RTDs and macrodispersivities for the multi-Gaussian model are in good agreement with analytically derived values using first-order theories for log-transmissivity variance up to 2.0. The results from the non-multi-Gaussian models differ from each other and deviate largely from the multi-Gaussian results even when ln T variance is small. RTDs in non-multi-Gaussian realizations with high connectivity at high extreme values display earlier breakthrough than in multi-Gaussian realizations, whereas later breakthrough and longer tails are observed for RTDs from non-multi-Gaussian realizations with high connectivity at low extreme values. Longitudinal macrodispersivities in the non-multi-Gaussian realizations are, in general, larger than

Gaussian vs non-Gaussian turbulence: impact on wind turbine loads

DEFF Research Database (Denmark)

Berg, Jacob; Natarajan, Anand; Mann, Jakob

2016-01-01

taking into account the safety factor for extreme moments. Other extreme load moments as well as the fatigue loads are not affected because of the use of non-Gaussian turbulent inflow. It is suggested that the turbine thus acts like a low-pass filter that averages out the non-Gaussian behaviour, which......From large-eddy simulations of atmospheric turbulence, a representation of Gaussian turbulence is constructed by randomizing the phases of the individual modes of variability. Time series of Gaussian turbulence are constructed and compared with its non-Gaussian counterpart. Time series from the two...

Legendre Duality of Spherical and Gaussian Spin Glasses

Energy Technology Data Exchange (ETDEWEB)

Genovese, Giuseppe, E-mail: giuseppe.genovese@math.uzh.ch [Universität Zürich, Institut für Mathematik (Switzerland); Tantari, Daniele, E-mail: daniele.tantari@sns.it [Scuola Normale Superiore di Pisa, Centro Ennio de Giorgi (Italy)

2015-12-15

The classical result of concentration of the Gaussian measure on the sphere in the limit of large dimension induces a natural duality between Gaussian and spherical models of spin glass. We analyse the Legendre variational structure linking the free energies of these two systems, in the spirit of the equivalence of ensembles of statistical mechanics. Our analysis, combined with the previous work (Barra et al., J. Phys. A: Math. Theor. 47, 155002, 2014), shows that such models are replica symmetric. Lastly, we briefly discuss an application of our result to the study of the Gaussian Hopfield model.

Legendre Duality of Spherical and Gaussian Spin Glasses

International Nuclear Information System (INIS)

Genovese, Giuseppe; Tantari, Daniele

2015-01-01

The classical result of concentration of the Gaussian measure on the sphere in the limit of large dimension induces a natural duality between Gaussian and spherical models of spin glass. We analyse the Legendre variational structure linking the free energies of these two systems, in the spirit of the equivalence of ensembles of statistical mechanics. Our analysis, combined with the previous work (Barra et al., J. Phys. A: Math. Theor. 47, 155002, 2014), shows that such models are replica symmetric. Lastly, we briefly discuss an application of our result to the study of the Gaussian Hopfield model

Emittance growth caused by nonuniform charge distribution of bunched beam in linac

International Nuclear Information System (INIS)

Chen Yinbao; Zhang Zhenhai

1993-09-01

The nonlinear space charge effect of bunched beam in linac is one of the important reasons that induces the emittance growth because of the conversion of the field energy to kinetic energy. The authors have worked out the internal field energies associated with some nonuniform space change distributions of a bunched beam, such as Gaussian distribution, waterbag distribution and parabolic distribution. And the emittance growths caused by these nonuniformities are obtained

EDITORIAL: Non-linear and non-Gaussian cosmological perturbations Non-linear and non-Gaussian cosmological perturbations

Science.gov (United States)

Sasaki, Misao; Wands, David

2010-06-01

In recent years there has been a resurgence of interest in the study of non-linear perturbations of cosmological models. This has been the result of both theoretical developments and observational advances. New theoretical challenges arise at second and higher order due to mode coupling and the need to develop new gauge-invariant variables beyond first order. In particular, non-linear interactions lead to deviations from a Gaussian distribution of primordial perturbations even if initial vacuum fluctuations are exactly Gaussian. These non-Gaussianities provide an important probe of models for the origin of structure in the very early universe. We now have a detailed picture of the primordial distribution of matter from surveys of the cosmic microwave background, notably NASA's WMAP satellite. The situation will continue to improve with future data from the ESA Planck satellite launched in 2009. To fully exploit these data cosmologists need to extend non-linear cosmological perturbation theory beyond the linear theory that has previously been sufficient on cosmological scales. Another recent development has been the realization that large-scale structure, revealed in high-redshift galaxy surveys, could also be sensitive to non-linearities in the primordial curvature perturbation. This focus section brings together a collection of invited papers which explore several topical issues in this subject. We hope it will be of interest to theoretical physicists and astrophysicists alike interested in understanding and interpreting recent developments in cosmological perturbation theory and models of the early universe. Of course it is only an incomplete snapshot of a rapidly developing field and we hope the reader will be inspired to read further work on the subject and, perhaps, fill in some of the missing pieces. This focus section is dedicated to the memory of Lev Kofman (1957-2009), an enthusiastic pioneer of inflationary cosmology and non-Gaussian perturbations.

Rotating quantum Gaussian packets

International Nuclear Information System (INIS)

Dodonov, V V

2015-01-01

We study two-dimensional quantum Gaussian packets with a fixed value of mean angular momentum. This value is the sum of two independent parts: the ‘external’ momentum related to the motion of the packet center and the ‘internal’ momentum due to quantum fluctuations. The packets minimizing the mean energy of an isotropic oscillator with the fixed mean angular momentum are found. They exist for ‘co-rotating’ external and internal motions, and they have nonzero correlation coefficients between coordinates and momenta, together with some (moderate) amount of quadrature squeezing. Variances of angular momentum and energy are calculated, too. Differences in the behavior of ‘co-rotating’ and ‘anti-rotating’ packets are shown. The time evolution of rotating Gaussian packets is analyzed, including the cases of a charge in a homogeneous magnetic field and a free particle. In the latter case, the effect of initial shrinking of packets with big enough coordinate-momentum correlation coefficients (followed by the well known expansion) is discovered. This happens due to a competition of ‘focusing’ and ‘de-focusing’ in the orthogonal directions. (paper)

Simple approximation for estimating centerline gamma absorbed dose rates due to a continuous Gaussian plume

International Nuclear Information System (INIS)

Overcamp, T.J.; Fjeld, R.A.

1987-01-01

A simple approximation for estimating the centerline gamma absorbed dose rates due to a continuous Gaussian plume was developed. To simplify the integration of the dose integral, this approach makes use of the Gaussian cloud concentration distribution. The solution is expressed in terms of the I1 and I2 integrals which were developed for estimating long-term dose due to a sector-averaged Gaussian plume. Estimates of tissue absorbed dose rates for the new approach and for the uniform cloud model were compared to numerical integration of the dose integral over a Gaussian plume distribution

Effects of a modulated vortex structure on the diffraction dynamics of ring Airy Gaussian beams.

Science.gov (United States)

Huang, Xianwei; Shi, Xiaohui; Deng, Zhixiang; Bai, Yanfeng; Fu, Xiquan

2017-09-01

The evolution of the ring Airy Gaussian beams with a modulated vortex in free space is numerically investigated. Compared with the unmodulated vortex, the unique property is that the beam spots first break up, and then gather. The evolution of the beams is influenced by the parameters of the vortex modulation, and the splitting phenomenon gets enhanced with multiple rings becoming light spots if the modulation depth increases. The symmetric branch pattern of the beam spots gets changed when the number of phase folds increases, and the initial modulation phase only impacts the angle of the beam spots. Moreover, a large distribution factor correlates to a hollow Gaussian vortex shape and weakens the splitting and gathering trend. By changing the initial parameters of the vortex modulation and the distribution factor, the peak intensity is greatly affected. In addition, the energy flow and the angular momentum are elucidated with the beam evolution features being confirmed.

Non-Gaussian signatures arising from warm inflation driven by geometric tachyon

International Nuclear Information System (INIS)

Bhattacharjee, Anindita; Deshamukhya, Atri

2014-01-01

In a warm inflationary scenario, the initial seeds of density perturbation arise from thermal fluctuations of the inflaton field. These fluctuations in principle have Gaussian distribution. In a Gaussian distribution the density perturbation can be expressed as the two point correlation function. Thus if in an inflationary model the density perturbation is expressed as correlation function of order higher than two, these fluctuations are non-Gaussian in nature. A simple inflationary model containing single scalar field, slow roll, canonical kinetic term and vacuum initial state can produce a tiny amount of non-Gaussianity which are very small to be detected by any experiment. Non-Gaussianity can also arise in inflationary models containing multiple scalar fields. For an inflationary scenario with single scalar field, non-Gaussianity can be expressed in terms of bi-spectrum however for multi field Inflation, it is expressed in terms of trispectrum etc. In this piece of work, the warm inflationary scenario, driven by a D3 brane due to the presence of a stack of k coincident NS 5 branes is considered and the non-Gaussian effects in such an inflationary scenario has been analysed by measuring the bispectrum of the gravitational field fluctuations generated during the warm inflation in strong dissipative regime. The bi-spectrum of the Inflation is expressed in terms of the parameter f NL and it is seen that the value of f NL parameter lies well within the limit observed by WMAP7

Modeling Non-Gaussian Time Series with Nonparametric Bayesian Model.

Science.gov (United States)

Xu, Zhiguang; MacEachern, Steven; Xu, Xinyi

2015-02-01

We present a class of Bayesian copula models whose major components are the marginal (limiting) distribution of a stationary time series and the internal dynamics of the series. We argue that these are the two features with which an analyst is typically most familiar, and hence that these are natural components with which to work. For the marginal distribution, we use a nonparametric Bayesian prior distribution along with a cdf-inverse cdf transformation to obtain large support. For the internal dynamics, we rely on the traditionally successful techniques of normal-theory time series. Coupling the two components gives us a family of (Gaussian) copula transformed autoregressive models. The models provide coherent adjustments of time scales and are compatible with many extensions, including changes in volatility of the series. We describe basic properties of the models, show their ability to recover non-Gaussian marginal distributions, and use a GARCH modification of the basic model to analyze stock index return series. The models are found to provide better fit and improved short-range and long-range predictions than Gaussian competitors. The models are extensible to a large variety of fields, including continuous time models, spatial models, models for multiple series, models driven by external covariate streams, and non-stationary models.

On the Shaker Simulation of Wind-Induced Non-Gaussian Random Vibration

Directory of Open Access Journals (Sweden)

Fei Xu

2016-01-01

Full Text Available Gaussian signal is produced by ordinary random vibration controllers to test the products in the laboratory, while the field data is usually non-Gaussian. Two methodologies are presented in this paper for shaker simulation of wind-induced non-Gaussian vibration. The first methodology synthesizes the non-Gaussian signal offline and replicates it on the shaker in the Time Waveform Replication (TWR mode. A new synthesis method is used to model the non-Gaussian signal as a Gaussian signal multiplied by an amplitude modulation function (AMF. A case study is presented to show that the synthesized non-Gaussian signal has the same power spectral density (PSD, probability density function (PDF, and loading cycle distribution (LCD as the field data. The second methodology derives a damage equivalent Gaussian signal from the non-Gaussian signal based on the fatigue damage spectrum (FDS and the extreme response spectrum (ERS and reproduces it on the shaker in the closed-loop frequency domain control mode. The PSD level and the duration time of the derived Gaussian signal can be manipulated for accelerated testing purpose. A case study is presented to show that the derived PSD matches the damage potential of the non-Gaussian environment for both fatigue and peak response.

Feasibility study on the least square method for fitting non-Gaussian noise data

Science.gov (United States)

Xu, Wei; Chen, Wen; Liang, Yingjie

2018-02-01

This study is to investigate the feasibility of least square method in fitting non-Gaussian noise data. We add different levels of the two typical non-Gaussian noises, Lévy and stretched Gaussian noises, to exact value of the selected functions including linear equations, polynomial and exponential equations, and the maximum absolute and the mean square errors are calculated for the different cases. Lévy and stretched Gaussian distributions have many applications in fractional and fractal calculus. It is observed that the non-Gaussian noises are less accurately fitted than the Gaussian noise, but the stretched Gaussian cases appear to perform better than the Lévy noise cases. It is stressed that the least-squares method is inapplicable to the non-Gaussian noise cases when the noise level is larger than 5%.

Fitting the Fractional Polynomial Model to Non-Gaussian Longitudinal Data

Directory of Open Access Journals (Sweden)

Ji Hoon Ryoo

2017-08-01

Full Text Available As in cross sectional studies, longitudinal studies involve non-Gaussian data such as binomial, Poisson, gamma, and inverse-Gaussian distributions, and multivariate exponential families. A number of statistical tools have thus been developed to deal with non-Gaussian longitudinal data, including analytic techniques to estimate parameters in both fixed and random effects models. However, as yet growth modeling with non-Gaussian data is somewhat limited when considering the transformed expectation of the response via a linear predictor as a functional form of explanatory variables. In this study, we introduce a fractional polynomial model (FPM that can be applied to model non-linear growth with non-Gaussian longitudinal data and demonstrate its use by fitting two empirical binary and count data models. The results clearly show the efficiency and flexibility of the FPM for such applications.

On Gaussian conditional independence structures

Czech Academy of Sciences Publication Activity Database

Lněnička, Radim; Matúš, František

2007-01-01

Roč. 43, č. 3 (2007), s. 327-342 ISSN 0023-5954 R&D Projects: GA AV ČR IAA100750603 Institutional research plan: CEZ:AV0Z10750506 Keywords : multivariate Gaussian distribution * positive definite matrices * determinants * gaussoids * covariance selection models * Markov perfectness Subject RIV: BA - General Mathematics Impact factor: 0.552, year: 2007

Photoelectron Energy Loss in Al(002) Revisited: Retrieval of the Single Plasmon Loss Energy Distribution by a Fourier Transform Method

Science.gov (United States)

Santana, Victor Mancir da Silva; David, Denis; de Almeida, Jailton Souza; Godet, Christian

2018-06-01

A Fourier transform (FT) algorithm is proposed to retrieve the energy loss function (ELF) of solid surfaces from experimental X-ray photoelectron spectra. The intensity measured over a broad energy range towards lower kinetic energies results from convolution of four spectral distributions: photoemission line shape, multiple plasmon loss probability, X-ray source line structure and Gaussian broadening of the photoelectron analyzer. The FT of the measured XPS spectrum, including the zero-loss peak and all inelastic scattering mechanisms, being a mathematical function of the respective FT of X-ray source, photoemission line shape, multiple plasmon loss function, and Gaussian broadening of the photoelectron analyzer, the proposed algorithm gives straightforward access to the bulk ELF and effective dielectric function of the solid, assuming identical ELF for intrinsic and extrinsic plasmon excitations. This method is applied to aluminum single crystal Al(002) where the photoemission line shape has been computed accurately beyond the Doniach-Sunjic approximation using the Mahan-Wertheim-Citrin approach which takes into account the density of states near the Fermi level; the only adjustable parameters are the singularity index and the broadening energy D (inverse hole lifetime). After correction for surface plasmon excitations, the q-averaged bulk loss function, q , of Al(002) differs from the optical value Im[- 1 / ɛ( E, q = 0)] and is well described by the Lindhard-Mermin dispersion relation. A quality criterion of the inversion algorithm is given by the capability of observing weak interband transitions close to the zero-loss peak, namely at 0.65 and 1.65 eV in ɛ( E, q) as found in optical spectra and ab initio calculations of aluminum.

Photoelectron Energy Loss in Al(002) Revisited: Retrieval of the Single Plasmon Loss Energy Distribution by a Fourier Transform Method

Science.gov (United States)

Santana, Victor Mancir da Silva; David, Denis; de Almeida, Jailton Souza; Godet, Christian

2018-04-01

A Fourier transform (FT) algorithm is proposed to retrieve the energy loss function (ELF) of solid surfaces from experimental X-ray photoelectron spectra. The intensity measured over a broad energy range towards lower kinetic energies results from convolution of four spectral distributions: photoemission line shape, multiple plasmon loss probability, X-ray source line structure and Gaussian broadening of the photoelectron analyzer. The FT of the measured XPS spectrum, including the zero-loss peak and all inelastic scattering mechanisms, being a mathematical function of the respective FT of X-ray source, photoemission line shape, multiple plasmon loss function, and Gaussian broadening of the photoelectron analyzer, the proposed algorithm gives straightforward access to the bulk ELF and effective dielectric function of the solid, assuming identical ELF for intrinsic and extrinsic plasmon excitations. This method is applied to aluminum single crystal Al(002) where the photoemission line shape has been computed accurately beyond the Doniach-Sunjic approximation using the Mahan-Wertheim-Citrin approach which takes into account the density of states near the Fermi level; the only adjustable parameters are the singularity index and the broadening energy D (inverse hole lifetime). After correction for surface plasmon excitations, the q-averaged bulk loss function, q , of Al(002) differs from the optical value Im[- 1 / ɛ(E, q = 0)] and is well described by the Lindhard-Mermin dispersion relation. A quality criterion of the inversion algorithm is given by the capability of observing weak interband transitions close to the zero-loss peak, namely at 0.65 and 1.65 eV in ɛ(E, q) as found in optical spectra and ab initio calculations of aluminum.

Non-Gaussian conductivity fluctuations in semiconductors

International Nuclear Information System (INIS)

Melkonyan, S.V.

2010-01-01

A theoretical study is presented on the statistical properties of conductivity fluctuations caused by concentration and mobility fluctuations of the current carriers. It is established that mobility fluctuations result from random deviations in the thermal equilibrium distribution of the carriers. It is shown that mobility fluctuations have generation-recombination and shot components which do not satisfy the requirements of the central limit theorem, in contrast to the current carrier's concentration fluctuation and intraband component of the mobility fluctuation. It is shown that in general the mobility fluctuation consist of thermal (or intraband) Gaussian and non-thermal (or generation-recombination, shot, etc.) non-Gaussian components. The analyses of theoretical results and experimental data from literature show that the statistical properties of mobility fluctuation and of 1/f-noise fully coincide. The deviation from Gaussian statistics of the mobility or 1/f fluctuations goes hand in hand with the magnitude of non-thermal noise (generation-recombination, shot, burst, pulse noises, etc.).

SU-E-T-327: Dosimetric Impact of Beam Energy for Intrabeam Breast IORT with Different Residual Cancer Cell Distributions After Surgery

Energy Technology Data Exchange (ETDEWEB)

Schwid, M; Zhang, H [Department of Radiation Oncology, Northwestern University Feinberg School of Medicine, Northwestern Memorial Hospital, Chicago, IL (United States)

2015-06-15

Purpose: The purpose of this study was to evaluate the dosimetric impact of beam energy to the IORT treatment of residual cancer cells with different cancer cell distributions after breast-conserving surgery. Methods: The three dimensional (3D) radiation doses of IORT using a 4-cm spherical applicator at the energy of 40 keV and 50 keV were separately calculated at different depths of the postsurgical tumor bed. The modified linear quadratic model (MLQ) was used to estimate the radiobiological response of the tumor cells assuming different radio-sensitivities and density distributions. The impact of radiation was evaluated for two types of breast cancer cell lines (α /β=10, and α /β =3.8) at 20 Gy dose prescribed at the applicator surface. Cancer cell distributions in the postsurgical tissue field were assumed to be a Gaussian with the standard deviations of 0.5, 1 and 2 mm respectively, namely the cancer cell infiltrations of 1.5, 3, and 6 mm respectively. The surface cancer cell percentage was assumed to be 0.01%, 0.1%, 1% and 10% separately. The equivalent uniform doses (EUD) for all the scenarios were calculated. Results: The EUDs were found to be dependent on the distributions of cancer cells, but independent of the cancer cell radio-sensitivities and the density at the surface. EUDs of 50 keV are 1% larger than that of 40 keV. For a prescription dose of 20 Gy, EUDs of 50 keV beam are 17.52, 16.21 and 13.14 Gy respectively for 0.5, 1.0 and 2.0 mm of the standard deviation of cancer cell Gaussian distributions. Conclusion: The impact by selected energies of IORT beams is very minimal. When energy is changed from 50 keV to 40 keV, the EUDs are almost the same for the same cancer cell distribution. 40 keV can be safely used as an alternative of 50 keV beam in IORT.

SU-E-T-327: Dosimetric Impact of Beam Energy for Intrabeam Breast IORT with Different Residual Cancer Cell Distributions After Surgery

International Nuclear Information System (INIS)

Schwid, M; Zhang, H

2015-01-01

Purpose: The purpose of this study was to evaluate the dosimetric impact of beam energy to the IORT treatment of residual cancer cells with different cancer cell distributions after breast-conserving surgery. Methods: The three dimensional (3D) radiation doses of IORT using a 4-cm spherical applicator at the energy of 40 keV and 50 keV were separately calculated at different depths of the postsurgical tumor bed. The modified linear quadratic model (MLQ) was used to estimate the radiobiological response of the tumor cells assuming different radio-sensitivities and density distributions. The impact of radiation was evaluated for two types of breast cancer cell lines (α /β=10, and α /β =3.8) at 20 Gy dose prescribed at the applicator surface. Cancer cell distributions in the postsurgical tissue field were assumed to be a Gaussian with the standard deviations of 0.5, 1 and 2 mm respectively, namely the cancer cell infiltrations of 1.5, 3, and 6 mm respectively. The surface cancer cell percentage was assumed to be 0.01%, 0.1%, 1% and 10% separately. The equivalent uniform doses (EUD) for all the scenarios were calculated. Results: The EUDs were found to be dependent on the distributions of cancer cells, but independent of the cancer cell radio-sensitivities and the density at the surface. EUDs of 50 keV are 1% larger than that of 40 keV. For a prescription dose of 20 Gy, EUDs of 50 keV beam are 17.52, 16.21 and 13.14 Gy respectively for 0.5, 1.0 and 2.0 mm of the standard deviation of cancer cell Gaussian distributions. Conclusion: The impact by selected energies of IORT beams is very minimal. When energy is changed from 50 keV to 40 keV, the EUDs are almost the same for the same cancer cell distribution. 40 keV can be safely used as an alternative of 50 keV beam in IORT

Gaussian entanglement revisited

Science.gov (United States)

Lami, Ludovico; Serafini, Alessio; Adesso, Gerardo

2018-02-01

We present a novel approach to the separability problem for Gaussian quantum states of bosonic continuous variable systems. We derive a simplified necessary and sufficient separability criterion for arbitrary Gaussian states of m versus n modes, which relies on convex optimisation over marginal covariance matrices on one subsystem only. We further revisit the currently known results stating the equivalence between separability and positive partial transposition (PPT) for specific classes of Gaussian states. Using techniques based on matrix analysis, such as Schur complements and matrix means, we then provide a unified treatment and compact proofs of all these results. In particular, we recover the PPT-separability equivalence for: (i) Gaussian states of 1 versus n modes; and (ii) isotropic Gaussian states. In passing, we also retrieve (iii) the recently established equivalence between separability of a Gaussian state and and its complete Gaussian extendability. Our techniques are then applied to progress beyond the state of the art. We prove that: (iv) Gaussian states that are invariant under partial transposition are necessarily separable; (v) the PPT criterion is necessary and sufficient for separability for Gaussian states of m versus n modes that are symmetric under the exchange of any two modes belonging to one of the parties; and (vi) Gaussian states which remain PPT under passive optical operations can not be entangled by them either. This is not a foregone conclusion per se (since Gaussian bound entangled states do exist) and settles a question that had been left unanswered in the existing literature on the subject. This paper, enjoyable by both the quantum optics and the matrix analysis communities, overall delivers technical and conceptual advances which are likely to be useful for further applications in continuous variable quantum information theory, beyond the separability problem.

A Monte Carlo simulation model for stationary non-Gaussian processes

DEFF Research Database (Denmark)

Grigoriu, M.; Ditlevsen, Ove Dalager; Arwade, S. R.

2003-01-01

includes translation processes and is useful for both Monte Carlo simulation and analytical studies. As for translation processes, the mixture of translation processes can have a wide range of marginal distributions and correlation functions. Moreover, these processes can match a broader range of second...... athe proposed Monte Carlo algorithm and compare features of translation processes and mixture of translation processes. Keywords: Monte Carlo simulation, non-Gaussian processes, sampling theorem, stochastic processes, translation processes......A class of stationary non-Gaussian processes, referred to as the class of mixtures of translation processes, is defined by their finite dimensional distributions consisting of mixtures of finite dimensional distributions of translation processes. The class of mixtures of translation processes...

Gaussian measures of entanglement versus negativities: Ordering of two-mode Gaussian states

International Nuclear Information System (INIS)

Adesso, Gerardo; Illuminati, Fabrizio

2005-01-01

We study the entanglement of general (pure or mixed) two-mode Gaussian states of continuous-variable systems by comparing the two available classes of computable measures of entanglement: entropy-inspired Gaussian convex-roof measures and positive partial transposition-inspired measures (negativity and logarithmic negativity). We first review the formalism of Gaussian measures of entanglement, adopting the framework introduced in M. M. Wolf et al., Phys. Rev. A 69, 052320 (2004), where the Gaussian entanglement of formation was defined. We compute explicitly Gaussian measures of entanglement for two important families of nonsymmetric two-mode Gaussian state: namely, the states of extremal (maximal and minimal) negativities at fixed global and local purities, introduced in G. Adesso et al., Phys. Rev. Lett. 92, 087901 (2004). This analysis allows us to compare the different orderings induced on the set of entangled two-mode Gaussian states by the negativities and by the Gaussian measures of entanglement. We find that in a certain range of values of the global and local purities (characterizing the covariance matrix of the corresponding extremal states), states of minimum negativity can have more Gaussian entanglement of formation than states of maximum negativity. Consequently, Gaussian measures and negativities are definitely inequivalent measures of entanglement on nonsymmetric two-mode Gaussian states, even when restricted to a class of extremal states. On the other hand, the two families of entanglement measures are completely equivalent on symmetric states, for which the Gaussian entanglement of formation coincides with the true entanglement of formation. Finally, we show that the inequivalence between the two families of continuous-variable entanglement measures is somehow limited. Namely, we rigorously prove that, at fixed negativities, the Gaussian measures of entanglement are bounded from below. Moreover, we provide some strong evidence suggesting that they

A non-Gaussian approach to risk measures

Science.gov (United States)

Bormetti, Giacomo; Cisana, Enrica; Montagna, Guido; Nicrosini, Oreste

2007-03-01

Reliable calculations of financial risk require that the fat-tailed nature of prices changes is included in risk measures. To this end, a non-Gaussian approach to financial risk management is presented, modelling the power-law tails of the returns distribution in terms of a Student- t distribution. Non-Gaussian closed-form solutions for value-at-risk and expected shortfall are obtained and standard formulae known in the literature under the normality assumption are recovered as a special case. The implications of the approach for risk management are demonstrated through an empirical analysis of financial time series from the Italian stock market and in comparison with the results of the most widely used procedures of quantitative finance. Particular attention is paid to quantify the size of the errors affecting the market risk measures obtained according to different methodologies, by employing a bootstrap technique.

Signed zeros of Gaussian vector fields - density, correlation functions and curvature

CERN Document Server

Foltin, G

2003-01-01

We calculate correlation functions of the (signed) density of zeros of Gaussian distributed vector fields. We are able to express correlation functions of arbitrary order through the curvature tensor of a certain abstract Riemann Cartan or Riemannian manifold. As an application, we discuss one- and two-point functions. The zeros of a two-dimensional Gaussian vector field model the distribution of topological defects in the high-temperature phase of two-dimensional systems with orientational degrees of freedom, such as superfluid films, thin superconductors and liquid crystals.

Gyrator transform of Gaussian beams with phase difference and generation of hollow beam

Science.gov (United States)

Xiao, Zhiyu; Xia, Hui; Yu, Tao; Xie, Ding; Xie, Wenke

2018-03-01

The optical expression of Gaussian beams with phase difference, which is caused by gyrator transform (GT), has been obtained. The intensity and phase distribution of transform Gaussian beams are analyzed. It is found that the circular hollow vortex beam can be obtained by overlapping two GT Gaussian beams with π phase difference. The effect of parameters on the intensity and phase distributions of the hollow vortex beam are discussed. The results show that the shape of intensity distribution is significantly influenced by GT angle α and propagation distance z. The size of the hollow vortex beam can be adjusted by waist width ω 0. Compared with previously reported results, the work shows that the hollow vortex beam can be obtained without any model conversion of the light source.

Gaussian-3 theory using density functional geometries and zero-point energies

International Nuclear Information System (INIS)

Baboul, A.G.; Curtiss, L.A.; Redfern, P.C.; Raghavachari, K.

1999-01-01

A variation of Gaussian-3 (G3) theory is presented in which the geometries and zero-point energies are obtained from B3LYP density functional theory [B3LYP/6-31G(d)] instead of geometries from second-order perturbation theory [MP2(FU)/6-31G(d)] and zero-point energies from Hartree - Fock theory [HF/6-31G(d)]. This variation, referred to as G3//B3LYP, is assessed on 299 energies (enthalpies of formation, ionization potentials, electron affinities, proton affinities) from the G2/97 test set [J. Chem. Phys. 109, 42 (1998)]. The G3//B3LYP average absolute deviation from experiment for the 299 energies is 0.99 kcal/mol compared to 1.01 kcal/mol for G3 theory. Generally, the results from the two methods are similar, with some exceptions. G3//B3LYP theory gives significantly improved results for several cases for which MP2 theory is deficient for optimized geometries, such as CN and O 2 + . However, G3//B3LYP does poorly for ionization potentials that involve a Jahn - Teller distortion in the cation (CH 4 + , BF 3 + , BCl 3 + ) because of the B3LYP/6-31G(d) geometries. The G3(MP2) method is also modified to use B3LYP/6-31G(d) geometries and zero-point energies. This variation, referred to as G3(MP2)//B3LYP, has an average absolute deviation of 1.25 kcal/mol compared to 1.30 kcal/mol for G3(MP2) theory. Thus, use of density functional geometries and zero-point energies in G3 and G3(MP2) theories is a useful alternative to MP2 geometries and HF zero-point energies. copyright 1999 American Institute of Physics

Distributed Energy Implementation Options

Energy Technology Data Exchange (ETDEWEB)

Shah, Chandralata N [National Renewable Energy Laboratory (NREL), Golden, CO (United States)

2017-09-13

This presentation covers the options for implementing distributed energy projects. It distinguishes between options available for distributed energy that is government owned versus privately owned, with a focus on the privately owned options including Energy Savings Performance Contract Energy Sales Agreements (ESPC ESAs). The presentation covers the new ESPC ESA Toolkit and other Federal Energy Management Program resources.

The Research of Indoor Positioning Based on Double-peak Gaussian Model

Directory of Open Access Journals (Sweden)

Lina Chen

2014-04-01

Full Text Available Location fingerprinting using Wi-Fi signals has been very popular and is a well accepted indoor positioning method. The key issue of the fingerprinting approach is generating the fingerprint radio map. Limited by the practical workload, only a few samples of the received signal strength are collected at each reference point. Unfortunately, fewer samples cannot accurately represent the actual distribution of the signal strength from each access point. This study finds most Wi- Fi signals have two peaks. According to the new finding, a double-peak Gaussian arithmetic is proposed to generate a fingerprint radio map. This approach requires little time to receive WiFi signals and it easy to estimate the parameters of the double-peak Gaussian function. Compared to the Gaussian function and histogram method to generate a fingerprint radio map, this method better approximates the occurrence signal distribution. This paper also compared the positioning accuracy using K-Nearest Neighbour theory for three radio maps, the test results show that the positioning distance error utilizing the double-peak Gaussian function is better than the other two methods.

A Distribution Family Bridging the Gaussian and the Laplace Laws, Gram–Charlier Expansions, Kurtosis Behaviour, and Entropy Features

Directory of Open Access Journals (Sweden)

Mario Faliva

2017-03-01

Full Text Available The paper devises a family of leptokurtic bell-shaped distributions which is based on the hyperbolic secant raised to a positive power, and bridges the Laplace and Gaussian laws on asymptotic arguments. Moment and cumulant generating functions are then derived and represented in terms of polygamma functions. The behaviour of shape parameters, namely kurtosis and entropy, is investigated. In addition, Gram–Charlier-type (GCT expansions, based on the aforementioned distributions and their orthogonal polynomials, are specified, and an operational criterion is provided to meet modelling requirements in a possibly severe kurtosis and skewness environment. The role played by entropy within the kurtosis ranges of GCT expansions is also examined.

Measurement of damping and temperature: Precision bounds in Gaussian dissipative channels

International Nuclear Information System (INIS)

Monras, Alex; Illuminati, Fabrizio

2011-01-01

We present a comprehensive analysis of the performance of different classes of Gaussian states in the estimation of Gaussian phase-insensitive dissipative channels. In particular, we investigate the optimal estimation of the damping constant and reservoir temperature. We show that, for two-mode squeezed vacuum probe states, the quantum-limited accuracy of both parameters can be achieved simultaneously. Moreover, we show that for both parameters two-mode squeezed vacuum states are more efficient than coherent, thermal, or single-mode squeezed states. This suggests that at high-energy regimes, two-mode squeezed vacuum states are optimal within the Gaussian setup. This optimality result indicates a stronger form of compatibility for the estimation of the two parameters. Indeed, not only the minimum variance can be achieved at fixed probe states, but also the optimal state is common to both parameters. Additionally, we explore numerically the performance of non-Gaussian states for particular parameter values to find that maximally entangled states within d-dimensional cutoff subspaces (d≤6) perform better than any randomly sampled states with similar energy. However, we also find that states with very similar performance and energy exist with much less entanglement than the maximally entangled ones.

Non-Gaussian diffusion in static disordered media

Science.gov (United States)

Luo, Liang; Yi, Ming

2018-04-01

Non-Gaussian diffusion is commonly considered as a result of fluctuating diffusivity, which is correlated in time or in space or both. In this work, we investigate the non-Gaussian diffusion in static disordered media via a quenched trap model, where the diffusivity is spatially correlated. Several unique effects due to quenched disorder are reported. We analytically estimate the diffusion coefficient Ddis and its fluctuation over samples of finite size. We show a mechanism of population splitting in the non-Gaussian diffusion. It results in a sharp peak in the distribution of displacement P (x ,t ) around x =0 , that has frequently been observed in experiments. We examine the fidelity of the coarse-grained diffusion map, which is reconstructed from particle trajectories. Finally, we propose a procedure to estimate the correlation length in static disordered environments, where the information stored in the sample-to-sample fluctuation has been utilized.

Application of the quasi-Gaussian entropy theory to the calculation of thermodynamic properties of water and methane in the liquid and gas phase

NARCIS (Netherlands)

Apol, M.E F; Amadei, A; Berendsen, H.J.C.

1996-01-01

In this article we investigate the applicability of the statistical Gamma state as following from the quasi-Gaussian entropy theory, where all thermodynamic properties at every temperature are obtained from the knowledge of the potential energy distribution at one temperature. We compared for a

Big bang nucleosynthesis with Gaussian inhomogeneous neutrino degeneracy

International Nuclear Information System (INIS)

Stirling, Spencer D.; Scherrer, Robert J.

2002-01-01

We consider the effect of inhomogeneous neutrino degeneracy on big bang nucleosynthesis for the case where the distribution of neutrino chemical potentials is given by a Gaussian. The chemical potential fluctuations are taken to be isocurvature, so that only inhomogeneities in the electron chemical potential are relevant. Then the final element abundances are a function only of the baryon-photon ratio η, the effective number of additional neutrinos ΔN ν , the mean electron neutrino degeneracy parameter ξ-bar, and the rms fluctuation of the degeneracy parameter, σ ξ . We find that for fixed η, ΔN ν , and ξ-bar, the abundances of 4 He, D, and 7 Li are, in general, increasing functions of σ ξ . Hence, the effect of adding a Gaussian distribution for the electron neutrino degeneracy parameter is to decrease the allowed range for η. We show that this result can be generalized to a wide variety of distributions for ξ

Identification and estimation of non-Gaussian structural vector autoregressions

DEFF Research Database (Denmark)

Lanne, Markku; Meitz, Mika; Saikkonen, Pentti

-Gaussian components is, without any additional restrictions, identified and leads to (essentially) unique impulse responses. We also introduce an identification scheme under which the maximum likelihood estimator of the non-Gaussian SVAR model is consistent and asymptotically normally distributed. As a consequence......, additional economic identifying restrictions can be tested. In an empirical application, we find a negative impact of a contractionary monetary policy shock on financial markets, and clearly reject the commonly employed recursive identifying restrictions....

Propagation of Gaussian Beams through Active GRIN Materials

International Nuclear Information System (INIS)

Gomez-Varela, A I; Flores-Arias, M T; Bao-Varela, C; Gomez-Reino, C; De la Fuente, X

2011-01-01

We discussed light propagation through an active GRIN material that exhibits loss or gain. Effects of gain or loss in GRIN materials can be phenomenologically taken into account by using a complex refractive index in the wave equation. This work examines the implication of using a complex refractive index on light propagation in an active GRIN material illuminated by a non-uniform monochromatic wave described by a Gaussian beam. We analyze how a Gaussian beam is propagated through the active material in order to characterize it by the beam parameters and the transverse irradiance distribution.

A path integral methodology for obtaining thermodynamic properties of nonadiabatic systems using Gaussian mixture distributions

Science.gov (United States)

Raymond, Neil; Iouchtchenko, Dmitri; Roy, Pierre-Nicholas; Nooijen, Marcel

2018-05-01

We introduce a new path integral Monte Carlo method for investigating nonadiabatic systems in thermal equilibrium and demonstrate an approach to reducing stochastic error. We derive a general path integral expression for the partition function in a product basis of continuous nuclear and discrete electronic degrees of freedom without the use of any mapping schemes. We separate our Hamiltonian into a harmonic portion and a coupling portion; the partition function can then be calculated as the product of a Monte Carlo estimator (of the coupling contribution to the partition function) and a normalization factor (that is evaluated analytically). A Gaussian mixture model is used to evaluate the Monte Carlo estimator in a computationally efficient manner. Using two model systems, we demonstrate our approach to reduce the stochastic error associated with the Monte Carlo estimator. We show that the selection of the harmonic oscillators comprising the sampling distribution directly affects the efficiency of the method. Our results demonstrate that our path integral Monte Carlo method's deviation from exact Trotter calculations is dominated by the choice of the sampling distribution. By improving the sampling distribution, we can drastically reduce the stochastic error leading to lower computational cost.

Gaussian random-matrix process and universal parametric correlations in complex systems

International Nuclear Information System (INIS)

Attias, H.; Alhassid, Y.

1995-01-01

We introduce the framework of the Gaussian random-matrix process as an extension of Dyson's Gaussian ensembles and use it to discuss the statistical properties of complex quantum systems that depend on an external parameter. We classify the Gaussian processes according to the short-distance diffusive behavior of their energy levels and demonstrate that all parametric correlation functions become universal upon the appropriate scaling of the parameter. The class of differentiable Gaussian processes is identified as the relevant one for most physical systems. We reproduce the known spectral correlators and compute eigenfunction correlators in their universal form. Numerical evidence from both a chaotic model and weakly disordered model confirms our predictions

Application of Gaussian cubature to model two-dimensional population balances

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Bałdyga Jerzy

2017-09-01

Full Text Available In many systems of engineering interest the moment transformation of population balance is applied. One of the methods to solve the transformed population balance equations is the quadrature method of moments. It is based on the approximation of the density function in the source term by the Gaussian quadrature so that it preserves the moments of the original distribution. In this work we propose another method to be applied to the multivariate population problem in chemical engineering, namely a Gaussian cubature (GC technique that applies linear programming for the approximation of the multivariate distribution. Examples of the application of the Gaussian cubature (GC are presented for four processes typical for chemical engineering applications. The first and second ones are devoted to crystallization modeling with direction-dependent two-dimensional and three-dimensional growth rates, the third one represents drop dispersion accompanied by mass transfer in liquid-liquid dispersions and finally the fourth case regards the aggregation and sintering of particle populations.

Cosmological information in Gaussianized weak lensing signals

Science.gov (United States)

Joachimi, B.; Taylor, A. N.; Kiessling, A.

2011-11-01

Gaussianizing the one-point distribution of the weak gravitational lensing convergence has recently been shown to increase the signal-to-noise ratio contained in two-point statistics. We investigate the information on cosmology that can be extracted from the transformed convergence fields. Employing Box-Cox transformations to determine optimal transformations to Gaussianity, we develop analytical models for the transformed power spectrum, including effects of noise and smoothing. We find that optimized Box-Cox transformations perform substantially better than an offset logarithmic transformation in Gaussianizing the convergence, but both yield very similar results for the signal-to-noise ratio. None of the transformations is capable of eliminating correlations of the power spectra between different angular frequencies, which we demonstrate to have a significant impact on the errors in cosmology. Analytic models of the Gaussianized power spectrum yield good fits to the simulations and produce unbiased parameter estimates in the majority of cases, where the exceptions can be traced back to the limitations in modelling the higher order correlations of the original convergence. In the ideal case, without galaxy shape noise, we find an increase in the cumulative signal-to-noise ratio by a factor of 2.6 for angular frequencies up to ℓ= 1500, and a decrease in the area of the confidence region in the Ωm-σ8 plane, measured in terms of q-values, by a factor of 4.4 for the best performing transformation. When adding a realistic level of shape noise, all transformations perform poorly with little decorrelation of angular frequencies, a maximum increase in signal-to-noise ratio of 34 per cent, and even slightly degraded errors on cosmological parameters. We argue that to find Gaussianizing transformations of practical use, it will be necessary to go beyond transformations of the one-point distribution of the convergence, extend the analysis deeper into the non

Adaptive Laguerre-Gaussian variant of the Gaussian beam expansion method.

Science.gov (United States)

Cagniot, Emmanuel; Fromager, Michael; Ait-Ameur, Kamel

2009-11-01

A variant of the Gaussian beam expansion method consists in expanding the Bessel function J0 appearing in the Fresnel-Kirchhoff integral into a finite sum of complex Gaussian functions to derive an analytical expression for a Laguerre-Gaussian beam diffracted through a hard-edge aperture. However, the validity range of the approximation depends on the number of expansion coefficients that are obtained by optimization-computation directly. We propose another solution consisting in expanding J0 onto a set of collimated Laguerre-Gaussian functions whose waist depends on their number and then, depending on its argument, predicting the suitable number of expansion functions to calculate the integral recursively.

Exploring super-gaussianity towards robust information-theoretical time delay estimation

DEFF Research Database (Denmark)

Petsatodis, Theodoros; Talantzis, Fotios; Boukis, Christos

2013-01-01

the effect upon TDE when modeling the source signal with different speech-based distributions. An information theoretical TDE method indirectly encapsulating higher order statistics (HOS) formed the basis of this work. The underlying assumption of Gaussian distributed source has been replaced...

Absorption Spectrum and Density of States of Square, Rectangular, and Triangular Frenkel Exciton Systems with Gaussian Diagonal Disorder

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Ibrahim Avgin

2017-01-01

Full Text Available Using the coherent potential approximation, we investigate the effects of disorder on the optical absorption and the density of states of Frenkel exciton systems on square, rectangular, and triangular lattices with nearest-neighbor interactions and a Gaussian distribution of transition energies. The analysis is based on an elliptic integral approach that gives results over the entire spectrum. The results for the square lattice are in good agreement with the finite-array calculations of Schreiber and Toyozawa. Our findings suggest that the coherent potential approximation can be useful in interpreting the optical properties of two-dimensional systems with dominant nearest-neighbor interactions and Gaussian diagonal disorder provided the optically active states are Frenkel excitons.

Assessment of the GPC Control Quality Using Non–Gaussian Statistical Measures

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Domański Paweł D.

2017-06-01

Full Text Available This paper presents an alternative approach to the task of control performance assessment. Various statistical measures based on Gaussian and non-Gaussian distribution functions are evaluated. The analysis starts with the review of control error histograms followed by their statistical analysis using probability distribution functions. Simulation results obtained for a control system with the generalized predictive controller algorithm are considered. The proposed approach using Cauchy and Lévy α-stable distributions shows robustness against disturbances and enables effective control loop quality evaluation. Tests of the predictive algorithm prove its ability to detect the impact of the main controller parameters, such as the model gain, the dynamics or the prediction horizon.

Polarization coupling of vector Bessel–Gaussian beams

International Nuclear Information System (INIS)

Takeuchi, Ryushi; Kozawa, Yuichi; Sato, Shunichi

2013-01-01

We report polarization coupling of radial and azimuthal electric field components of a vector light beam as predicted by the fact that the vector Helmholtz equation is expressed as coupled differential equations in cylindrical coordinates. To clearly observe the polarization variation of a beam as it propagates, higher order transverse modes of a vector Bessel–Gaussian beam were generated by a gain distribution modulation technique, which created a narrow ring-shaped gain region in a Nd:YVO 4 crystal. The polarization coupling was confirmed by the observation that the major polarization component of a vector Bessel–Gaussian beam alternates between radial and azimuthal components along with the propagation. (paper)

Distributed coordination of energy storage with distributed generators

NARCIS (Netherlands)

Yang, Tao; Wu, Di; Stoorvogel, Antonie Arij; Stoustrup, Jakob

2016-01-01

With a growing emphasis on energy efficiency and system flexibility, a great effort has been made recently in developing distributed energy resources (DER), including distributed generators and energy storage systems. This paper first formulates an optimal DER coordination problem considering

Mean intensity of the fundamental Bessel-Gaussian beam in turbulent atmosphere

Science.gov (United States)

Lukin, Igor P.

2017-11-01

In the given article mean intensity of a fundamental Bessel-Gaussian optical beam in turbulent atmosphere is studied. The problem analysis is based on the solution of the equation for the transverse second-order mutual coherence function of a fundamental Bessel-Gaussian beam of optical radiation. Distributions of mean intensity of a fundamental Bessel- Gaussian beam optical beam in longitudinal and transverse to a direction of propagation of optical radiation are investigated in detail. Influence of atmospheric turbulence on change of radius of the central part of a Bessel optical beam is estimated. Values of parameters at which it is possible to generate in turbulent atmosphere a nondiffracting pseudo-Bessel optical beam by means of a fundamental Bessel-Gaussian optical beam are established.

Colored non-gaussian noise driven open systems: generalization of Kramers' theory with a unified approach.

Science.gov (United States)

Baura, Alendu; Sen, Monoj Kumar; Goswami, Gurupada; Bag, Bidhan Chandra

2011-01-28

In this paper we have calculated escape rate from a meta stable state in the presence of both colored internal thermal and external nonthermal noises. For the internal noise we have considered usual gaussian distribution but the external noise may be gaussian or non-gaussian in characteristic. The calculated rate is valid for low noise strength of non-gaussian noise such that an effective gaussian approximation of non-gaussian noise wherein the higher order even cumulants of order "4" and higher are neglected. The rate expression we derived here reduces to the known results of the literature, as well as for purely external noise driven activated rate process. The latter exhibits how the rate changes if one switches from non-gaussian to gaussian character of the external noise.

Generation of Quasi-Gaussian Pulses Based on Correlation Techniques

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POHOATA, S.

2012-02-01

Full Text Available The Gaussian pulses have been mostly used within communications, where some applications can be emphasized: mobile telephony (GSM, where GMSK signals are used, as well as the UWB communications, where short-period pulses based on Gaussian waveform are generated. Since the Gaussian function signifies a theoretical concept, which cannot be accomplished from the physical point of view, this should be expressed by using various functions, able to determine physical implementations. New techniques of generating the Gaussian pulse responses of good precision are approached, proposed and researched in this paper. The second and third order derivatives with regard to the Gaussian pulse response are accurately generated. The third order derivates is composed of four individual rectangular pulses of fixed amplitudes, being easily to be generated by standard techniques. In order to generate pulses able to satisfy the spectral mask requirements, an adequate filter is necessary to be applied. This paper emphasizes a comparative analysis based on the relative error and the energy spectra of the proposed pulses.

Extension of filament propagation in water with Bessel-Gaussian beams

Energy Technology Data Exchange (ETDEWEB)

Kaya, G.; Sayrac, M.; Boran, Y.; Kolomenskii, A. A. [Department of Physics, Texas A& M University, College Station, Texas 77843 (United States); Kaya, N.; Schuessler, H. A. [Department of Physics, Texas A& M University, College Station, Texas 77843 (United States); Science and Petroleum, Texas A& M University at Qatar, Doha 23874 (Qatar); Strohaber, J. [Department of Physics, Texas A& M University, College Station, Texas 77843 (United States); Department of Physics, Florida A& M University, Tallahassee, Florida 32307 (United States); Amani, M. [Science and Petroleum, Texas A& M University at Qatar, Doha 23874 (Qatar)

2016-03-15

We experimentally studied intense femtosecond pulse filamentation and propagation in water for Bessel-Gaussian beams with different numbers of radial modal lobes. The transverse modes of the incident Bessel-Gaussian beam were created from a Gaussian beam of a Ti:sapphire laser system by using computer generated hologram techniques. We found that filament propagation length increased with increasing number of lobes under the conditions of the same peak intensity, pulse duration, and the size of the central peak of the incident beam, suggesting that the radial modal lobes may serve as an energy reservoir for the filaments formed by the central intensity peak.

Comparison of non-Gaussian and Gaussian diffusion models of diffusion weighted imaging of rectal cancer at 3.0 T MRI.

Science.gov (United States)

Zhang, Guangwen; Wang, Shuangshuang; Wen, Didi; Zhang, Jing; Wei, Xiaocheng; Ma, Wanling; Zhao, Weiwei; Wang, Mian; Wu, Guosheng; Zhang, Jinsong

2016-12-09

Water molecular diffusion in vivo tissue is much more complicated. We aimed to compare non-Gaussian diffusion models of diffusion-weighted imaging (DWI) including intra-voxel incoherent motion (IVIM), stretched-exponential model (SEM) and Gaussian diffusion model at 3.0 T MRI in patients with rectal cancer, and to determine the optimal model for investigating the water diffusion properties and characterization of rectal carcinoma. Fifty-nine consecutive patients with pathologically confirmed rectal adenocarcinoma underwent DWI with 16 b-values at a 3.0 T MRI system. DWI signals were fitted to the mono-exponential and non-Gaussian diffusion models (IVIM-mono, IVIM-bi and SEM) on primary tumor and adjacent normal rectal tissue. Parameters of standard apparent diffusion coefficient (ADC), slow- and fast-ADC, fraction of fast ADC (f), α value and distributed diffusion coefficient (DDC) were generated and compared between the tumor and normal tissues. The SEM exhibited the best fitting results of actual DWI signal in rectal cancer and the normal rectal wall (R 2  = 0.998, 0.999 respectively). The DDC achieved relatively high area under the curve (AUC = 0.980) in differentiating tumor from normal rectal wall. Non-Gaussian diffusion models could assess tissue properties more accurately than the ADC derived Gaussian diffusion model. SEM may be used as a potential optimal model for characterization of rectal cancer.

Resource theory of non-Gaussian operations

Science.gov (United States)

Zhuang, Quntao; Shor, Peter W.; Shapiro, Jeffrey H.

2018-05-01

Non-Gaussian states and operations are crucial for various continuous-variable quantum information processing tasks. To quantitatively understand non-Gaussianity beyond states, we establish a resource theory for non-Gaussian operations. In our framework, we consider Gaussian operations as free operations, and non-Gaussian operations as resources. We define entanglement-assisted non-Gaussianity generating power and show that it is a monotone that is nonincreasing under the set of free superoperations, i.e., concatenation and tensoring with Gaussian channels. For conditional unitary maps, this monotone can be analytically calculated. As examples, we show that the non-Gaussianity of ideal photon-number subtraction and photon-number addition equal the non-Gaussianity of the single-photon Fock state. Based on our non-Gaussianity monotone, we divide non-Gaussian operations into two classes: (i) the finite non-Gaussianity class, e.g., photon-number subtraction, photon-number addition, and all Gaussian-dilatable non-Gaussian channels; and (ii) the diverging non-Gaussianity class, e.g., the binary phase-shift channel and the Kerr nonlinearity. This classification also implies that not all non-Gaussian channels are exactly Gaussian dilatable. Our resource theory enables a quantitative characterization and a first classification of non-Gaussian operations, paving the way towards the full understanding of non-Gaussianity.

A model of non-Gaussian diffusion in heterogeneous media

Science.gov (United States)

Lanoiselée, Yann; Grebenkov, Denis S.

2018-04-01

Recent progress in single-particle tracking has shown evidence of the non-Gaussian distribution of displacements in living cells, both near the cellular membrane and inside the cytoskeleton. Similar behavior has also been observed in granular materials, turbulent flows, gels and colloidal suspensions, suggesting that this is a general feature of diffusion in complex media. A possible interpretation of this phenomenon is that a tracer explores a medium with spatio-temporal fluctuations which result in local changes of diffusivity. We propose and investigate an ergodic, easily interpretable model, which implements the concept of diffusing diffusivity. Depending on the parameters, the distribution of displacements can be either flat or peaked at small displacements with an exponential tail at large displacements. We show that the distribution converges slowly to a Gaussian one. We calculate statistical properties, derive the asymptotic behavior and discuss some implications and extensions.

Multi-variate joint PDF for non-Gaussianities: exact formulation and generic approximations

CERN Document Server

Verde, Licia; Heavens, Alan F; Jimenez, Raul; Matarrese, Sabino

2013-01-01

We provide an exact expression for the multi-variate joint probability distribution function of non-Gaussian fields primordially arising from local transformations of a Gaussian field. This kind of non-Gaussianity is generated in many models of inflation. We apply our expression to the non- Gaussianity estimation from Cosmic Microwave Background maps and the halo mass function where we obtain analytical expressions. We also provide analytic approximations and their range of validity. For the Cosmic Microwave Background we give a fast way to compute the PDF which is valid up to 7{\\sigma} for fNL values (both true and sampled) not ruled out by current observations, which consists of expressing the PDF as a combination of bispectrum and trispectrum of the temperature maps. The resulting expression is valid for any kind of non-Gaussianity and is not limited to the local type. The above results may serve as the basis for a fully Bayesian analysis of the non-Gaussianity parameter.

Mean anisotropy of homogeneous Gaussian random fields and anisotropic norms of linear translation-invariant operators on multidimensional integer lattices

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Phil Diamond

2003-01-01

Full Text Available Sensitivity of output of a linear operator to its input can be quantified in various ways. In Control Theory, the input is usually interpreted as disturbance and the output is to be minimized in some sense. In stochastic worst-case design settings, the disturbance is considered random with imprecisely known probability distribution. The prior set of probability measures can be chosen so as to quantify how far the disturbance deviates from the white-noise hypothesis of Linear Quadratic Gaussian control. Such deviation can be measured by the minimal Kullback-Leibler informational divergence from the Gaussian distributions with zero mean and scalar covariance matrices. The resulting anisotropy functional is defined for finite power random vectors. Originally, anisotropy was introduced for directionally generic random vectors as the relative entropy of the normalized vector with respect to the uniform distribution on the unit sphere. The associated a-anisotropic norm of a matrix is then its maximum root mean square or average energy gain with respect to finite power or directionally generic inputs whose anisotropy is bounded above by a≥0. We give a systematic comparison of the anisotropy functionals and the associated norms. These are considered for unboundedly growing fragments of homogeneous Gaussian random fields on multidimensional integer lattice to yield mean anisotropy. Correspondingly, the anisotropic norms of finite matrices are extended to bounded linear translation invariant operators over such fields.

Ultra-short FBG based distributed sensing using shifted optical Gaussian filters and microwave-network analysis.

Science.gov (United States)

Cheng, Rui; Xia, Li; Sima, Chaotan; Ran, Yanli; Rohollahnejad, Jalal; Zhou, Jiaao; Wen, Yongqiang; Yu, Can

2016-02-08

Ultrashort fiber Bragg gratings (US-FBGs) have significant potential as weak grating sensors for distributed sensing, but the exploitation have been limited by their inherent broad spectra that are undesirable for most traditional wavelength measurements. To address this, we have recently introduced a new interrogation concept using shifted optical Gaussian filters (SOGF) which is well suitable for US-FBG measurements. Here, we apply it to demonstrate, for the first time, an US-FBG-based self-referencing distributed optical sensing technique, with the advantages of adjustable sensitivity and range, high-speed and wide-range (potentially >14000 με) intensity-based detection, and resistance to disturbance by nonuniform parameter distribution. The entire system is essentially based on a microwave network, which incorporates the SOGF with a fiber delay-line between the two arms. Differential detections of the cascaded US-FBGs are performed individually in the network time-domain response which can be obtained by analyzing its complex frequency response. Experimental results are presented and discussed using eight cascaded US-FBGs. A comprehensive numerical analysis is also conducted to assess the system performance, which shows that the use of US-FBGs instead of conventional weak FBGs could significantly improve the power budget and capacity of the distributed sensing system while maintaining the crosstalk level and intensity decay rate, providing a promising route for future sensing applications.

A Nonlinear Framework of Delayed Particle Smoothing Method for Vehicle Localization under Non-Gaussian Environment

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Zhu Xiao

2016-05-01

Full Text Available In this paper, a novel nonlinear framework of smoothing method, non-Gaussian delayed particle smoother (nGDPS, is proposed, which enables vehicle state estimation (VSE with high accuracy taking into account the non-Gaussianity of the measurement and process noises. Within the proposed method, the multivariate Student’s t-distribution is adopted in order to compute the probability distribution function (PDF related to the process and measurement noises, which are assumed to be non-Gaussian distributed. A computation approach based on Ensemble Kalman Filter (EnKF is designed to cope with the mean and the covariance matrix of the proposal non-Gaussian distribution. A delayed Gibbs sampling algorithm, which incorporates smoothing of the sampled trajectories over a fixed-delay, is proposed to deal with the sample degeneracy of particles. The performance is investigated based on the real-world data, which is collected by low-cost on-board vehicle sensors. The comparison study based on the real-world experiments and the statistical analysis demonstrates that the proposed nGDPS has significant improvement on the vehicle state accuracy and outperforms the existing filtering and smoothing methods.

Relativistic effects and primordial non-Gaussianity in the galaxy bias

International Nuclear Information System (INIS)

Bartolo, Nicola; Matarrese, Sabino; Riotto, Antonio

2011-01-01

When dealing with observables, one needs to generalize the bias relation between the observed galaxy fluctuation field to the underlying matter distribution in a gauge-invariant way. We provide such relation at second-order in perturbation theory adopting the local Eulerian bias model and starting from the observationally motivated uniform-redshift gauge. Our computation includes the presence of primordial non-Gaussianity. We show that large scale-dependent relativistic effects in the Eulerian bias arise independently from the presence of some primordial non-Gaussianity. Furthermore, the Eulerian bias inherits from the primordial non-Gaussianity not only a scale-dependence, but also a modulation with the angle of observation when sources with different biases are correlated

Receiver design for SPAD-based VLC systems under Poisson-Gaussian mixed noise model.

Science.gov (United States)

Mao, Tianqi; Wang, Zhaocheng; Wang, Qi

2017-01-23

Single-photon avalanche diode (SPAD) is a promising photosensor because of its high sensitivity to optical signals in weak illuminance environment. Recently, it has drawn much attention from researchers in visible light communications (VLC). However, existing literature only deals with the simplified channel model, which only considers the effects of Poisson noise introduced by SPAD, but neglects other noise sources. Specifically, when an analog SPAD detector is applied, there exists Gaussian thermal noise generated by the transimpedance amplifier (TIA) and the digital-to-analog converter (D/A). Therefore, in this paper, we propose an SPAD-based VLC system with pulse-amplitude-modulation (PAM) under Poisson-Gaussian mixed noise model, where Gaussian-distributed thermal noise at the receiver is also investigated. The closed-form conditional likelihood of received signals is derived using the Laplace transform and the saddle-point approximation method, and the corresponding quasi-maximum-likelihood (quasi-ML) detector is proposed. Furthermore, the Poisson-Gaussian-distributed signals are converted to Gaussian variables with the aid of the generalized Anscombe transform (GAT), leading to an equivalent additive white Gaussian noise (AWGN) channel, and a hard-decision-based detector is invoked. Simulation results demonstrate that, the proposed GAT-based detector can reduce the computational complexity with marginal performance loss compared with the proposed quasi-ML detector, and both detectors are capable of accurately demodulating the SPAD-based PAM signals.

Gaussian fluctuation of the diffusion exponent of virus capsid in a living cell nucleus

Science.gov (United States)

Itto, Yuichi

2018-05-01

In their work [4], Bosse et al. experimentally showed that virus capsid exhibits not only normal diffusion but also anomalous diffusion in nucleus of a living cell. There, it was found that the distribution of fluctuations of the diffusion exponent characterizing them takes the Gaussian form, which is, quite remarkably, the same form for two different types of the virus. This suggests high robustness of such fluctuations. Here, the statistical property of local fluctuations of the diffusion exponent of the virus capsid in the nucleus is studied. A maximum-entropy-principle approach (originally proposed for a different virus in a different cell) is applied for obtaining the fluctuation distribution of the exponent. Largeness of the number of blocks identified with local areas of interchromatin corrals is also examined based on the experimental data. It is shown that the Gaussian distribution of the local fluctuations can be derived, in accordance with the above form. In addition, it is quantified how the fluctuation distribution on a long time scale is different from the Gaussian distribution.

The Dirac Equation in the algebraic approximation. VII. A comparison of molecular finite difference and finite basis set calculations using distributed Gaussian basis sets

NARCIS (Netherlands)

Quiney, H. M.; Glushkov, V. N.; Wilson, S.; Sabin,; Brandas, E

2001-01-01

A comparison is made of the accuracy achieved in finite difference and finite basis set approximations to the Dirac equation for the ground state of the hydrogen molecular ion. The finite basis set calculations are carried out using a distributed basis set of Gaussian functions the exponents and

Direct test of the Gaussian auxiliary field ansatz in nonconserved order parameter phase ordering dynamics

Science.gov (United States)

Yeung, Chuck

2018-06-01

The assumption that the local order parameter is related to an underlying spatially smooth auxiliary field, u (r ⃗,t ) , is a common feature in theoretical approaches to non-conserved order parameter phase separation dynamics. In particular, the ansatz that u (r ⃗,t ) is a Gaussian random field leads to predictions for the decay of the autocorrelation function which are consistent with observations, but distinct from predictions using alternative theoretical approaches. In this paper, the auxiliary field is obtained directly from simulations of the time-dependent Ginzburg-Landau equation in two and three dimensions. The results show that u (r ⃗,t ) is equivalent to the distance to the nearest interface. In two dimensions, the probability distribution, P (u ) , is well approximated as Gaussian except for small values of u /L (t ) , where L (t ) is the characteristic length-scale of the patterns. The behavior of P (u ) in three dimensions is more complicated; the non-Gaussian region for small u /L (t ) is much larger than that in two dimensions but the tails of P (u ) begin to approach a Gaussian form at intermediate times. However, at later times, the tails of the probability distribution appear to decay faster than a Gaussian distribution.

Off-Axis Gaussian Beams with Random Displacement in Atmospheric Turbulence

Directory of Open Access Journals (Sweden)

Yahya Baykal

2006-10-01

Full Text Available Our recent work in which we study the propagation of the general Hermite-sinusoidal-Gaussian laser beams in wireless broadband access telecommunication systems is elaborated in this paper to cover the special case of an off-axis Gaussian beam. We mainly investigate the propagation characteristics in atmospheric turbulence of an off-axis Gaussian beam possessing Gaussian distributed random displacement parameters. Our interest is to search for different types of laser beams that will improve the performance of a wireless broadband access system when atmospheric turbulence is considered. Our formulation is based on the basic solution of the second order mutual coherence function evaluated at the receiver plane. For fixed turbulence strength, the coherence length calculated at the receiver plane is found to decrease as the variance of the random displacement is increased. It is shown that as the turbulence becomes stronger, coherence lengths due to off-axis Gaussian beams tend to approach the same value, irrespective of the variance of the random displacement. As expected, the beam spreading is found to be pronounced for larger variance of displacement parameter. Average intensity profiles when atmospheric turbulence is present are plotted for different values of the variance of the random displacement parameter of the off-axis Gaussian beam.

Gaussian anamorphosis in the analysis step of the EnKF: a joint state-variable/observation approach

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Javier Amezcua

2014-09-01

Full Text Available The analysis step of the (ensemble Kalman filter is optimal when (1 the distribution of the background is Gaussian, (2 state variables and observations are related via a linear operator, and (3 the observational error is of additive nature and has Gaussian distribution. When these conditions are largely violated, a pre-processing step known as Gaussian anamorphosis (GA can be applied. The objective of this procedure is to obtain state variables and observations that better fulfil the Gaussianity conditions in some sense. In this work we analyse GA from a joint perspective, paying attention to the effects of transformations in the joint state-variable/observation space. First, we study transformations for state variables and observations that are independent from each other. Then, we introduce a targeted joint transformation with the objective to obtain joint Gaussianity in the transformed space. We focus primarily in the univariate case, and briefly comment on the multivariate one. A key point of this paper is that, when (1–(3 are violated, using the analysis step of the EnKF will not recover the exact posterior density in spite of any transformations one may perform. These transformations, however, provide approximations of different quality to the Bayesian solution of the problem. Using an example in which the Bayesian posterior can be analytically computed, we assess the quality of the analysis distributions generated after applying the EnKF analysis step in conjunction with different GA options. The value of the targeted joint transformation is particularly clear for the case when the prior is Gaussian, the marginal density for the observations is close to Gaussian, and the likelihood is a Gaussian mixture.

Extension of filament propagation in water with Bessel-Gaussian beams

Directory of Open Access Journals (Sweden)

G. Kaya

2016-03-01

Full Text Available We experimentally studied intense femtosecond pulse filamentation and propagation in water for Bessel-Gaussian beams with different numbers of radial modal lobes. The transverse modes of the incident Bessel-Gaussian beam were created from a Gaussian beam of a Ti:sapphire laser system by using computer generated hologram techniques. We found that filament propagation length increased with increasing number of lobes under the conditions of the same peak intensity, pulse duration, and the size of the central peak of the incident beam, suggesting that the radial modal lobes may serve as an energy reservoir for the filaments formed by the central intensity peak.

Modeling and forecasting foreign exchange daily closing prices with normal inverse Gaussian

Science.gov (United States)

Teneng, Dean

2013-09-01

We fit the normal inverse Gaussian(NIG) distribution to foreign exchange closing prices using the open software package R and select best models by Käärik and Umbleja (2011) proposed strategy. We observe that daily closing prices (12/04/2008 - 07/08/2012) of CHF/JPY, AUD/JPY, GBP/JPY, NZD/USD, QAR/CHF, QAR/EUR, SAR/CHF, SAR/EUR, TND/CHF and TND/EUR are excellent fits while EGP/EUR and EUR/GBP are good fits with a Kolmogorov-Smirnov test p-value of 0.062 and 0.08 respectively. It was impossible to estimate normal inverse Gaussian parameters (by maximum likelihood; computational problem) for JPY/CHF but CHF/JPY was an excellent fit. Thus, while the stochastic properties of an exchange rate can be completely modeled with a probability distribution in one direction, it may be impossible the other way around. We also demonstrate that foreign exchange closing prices can be forecasted with the normal inverse Gaussian (NIG) Lévy process, both in cases where the daily closing prices can and cannot be modeled by NIG distribution.

Evaluation of the non-Gaussianity of two-mode entangled states over a bosonic memory channel via cumulant theory and quadrature detection

Science.gov (United States)

Xiang, Shao-Hua; Wen, Wei; Zhao, Yu-Jing; Song, Ke-Hui

2018-04-01

We study the properties of the cumulants of multimode boson operators and introduce the phase-averaged quadrature cumulants as the measure of the non-Gaussianity of multimode quantum states. Using this measure, we investigate the non-Gaussianity of two classes of two-mode non-Gaussian states: photon-number entangled states and entangled coherent states traveling in a bosonic memory quantum channel. We show that such a channel can skew the distribution of two-mode quadrature variables, giving rise to a strongly non-Gaussian correlation. In addition, we provide a criterion to determine whether the distributions of these states are super- or sub-Gaussian.

Diffusion weighted imaging in patients with rectal cancer: Comparison between Gaussian and non-Gaussian models.

Directory of Open Access Journals (Sweden)

Georgios C Manikis

Full Text Available The purpose of this study was to compare the performance of four diffusion models, including mono and bi-exponential both Gaussian and non-Gaussian models, in diffusion weighted imaging of rectal cancer.Nineteen patients with rectal adenocarcinoma underwent MRI examination of the rectum before chemoradiation therapy including a 7 b-value diffusion sequence (0, 25, 50, 100, 500, 1000 and 2000 s/mm2 at a 1.5T scanner. Four different diffusion models including mono- and bi-exponential Gaussian (MG and BG and non-Gaussian (MNG and BNG were applied on whole tumor volumes of interest. Two different statistical criteria were recruited to assess their fitting performance, including the adjusted-R2 and Root Mean Square Error (RMSE. To decide which model better characterizes rectal cancer, model selection was relied on Akaike Information Criteria (AIC and F-ratio.All candidate models achieved a good fitting performance with the two most complex models, the BG and the BNG, exhibiting the best fitting performance. However, both criteria for model selection indicated that the MG model performed better than any other model. In particular, using AIC Weights and F-ratio, the pixel-based analysis demonstrated that tumor areas better described by the simplest MG model in an average area of 53% and 33%, respectively. Non-Gaussian behavior was illustrated in an average area of 37% according to the F-ratio, and 7% using AIC Weights. However, the distributions of the pixels best fitted by each of the four models suggest that MG failed to perform better than any other model in all patients, and the overall tumor area.No single diffusion model evaluated herein could accurately describe rectal tumours. These findings probably can be explained on the basis of increased tumour heterogeneity, where areas with high vascularity could be fitted better with bi-exponential models, and areas with necrosis would mostly follow mono-exponential behavior.

A novel Gaussian model based battery state estimation approach: State-of-Energy

International Nuclear Information System (INIS)

He, HongWen; Zhang, YongZhi; Xiong, Rui; Wang, Chun

2015-01-01

Highlights: • The Gaussian model is employed to construct a novel battery model. • The genetic algorithm is used to implement model parameter identification. • The AIC is used to decide the best hysteresis order of the battery model. • A novel battery SoE estimator is proposed and verified by two kinds of batteries. - Abstract: State-of-energy (SoE) is a very important index for battery management system (BMS) used in electric vehicles (EVs), it is indispensable for ensuring safety and reliable operation of batteries. For achieving battery SoE accurately, the main work can be summarized in three aspects. (1) In considering that different kinds of batteries show different open circuit voltage behaviors, the Gaussian model is employed to construct the battery model. What is more, the genetic algorithm is employed to locate the optimal parameter for the selecting battery model. (2) To determine an optimal tradeoff between battery model complexity and prediction precision, the Akaike information criterion (AIC) is used to determine the best hysteresis order of the combined battery model. Results from a comparative analysis show that the first-order hysteresis battery model is thought of being the best based on the AIC values. (3) The central difference Kalman filter (CDKF) is used to estimate the real-time SoE and an erroneous initial SoE is considered to evaluate the robustness of the SoE estimator. Lastly, two kinds of lithium-ion batteries are used to verify the proposed SoE estimation approach. The results show that the maximum SoE estimation error is within 1% for both LiFePO 4 and LiMn 2 O 4 battery datasets

Bootstrapping realized volatility and realized beta under a local Gaussianity assumption

DEFF Research Database (Denmark)

Hounyo, Ulrich

The main contribution of this paper is to propose a new bootstrap method for statistics based on high frequency returns. The new method exploits the local Gaussianity and the local constancy of volatility of high frequency returns, two assumptions that can simplify inference in the high frequency...... context, as recently explained by Mykland and Zhang (2009). Our main contributions are as follows. First, we show that the local Gaussian bootstrap is firstorder consistent when used to estimate the distributions of realized volatility and ealized betas. Second, we show that the local Gaussian bootstrap...... matches accurately the first four cumulants of realized volatility, implying that this method provides third-order refinements. This is in contrast with the wild bootstrap of Gonçalves and Meddahi (2009), which is only second-order correct. Third, we show that the local Gaussian bootstrap is able...

Modulation depth of Michelson interferometer with Gaussian beam.

Science.gov (United States)

Välikylä, Tuomas; Kauppinen, Jyrki

2011-12-20

Mirror misalignment or the tilt angle of the Michelson interferometer can be estimated from the modulation depth measured with collimated monochromatic light. The intensity of the light beam is usually assumed to be uniform, but, for example, with gas lasers it generally has a Gaussian distribution, which makes the modulation depth less sensitive to the tilt angle. With this assumption, the tilt angle may be underestimated by about 50%. We have derived a mathematical model for modulation depth with a circular aperture and Gaussian beam. The model reduces the error of the tilt angle estimate to below 1%. The results of the model have been verified experimentally.

Quantum information with Gaussian states

International Nuclear Information System (INIS)

Wang Xiangbin; Hiroshima, Tohya; Tomita, Akihisa; Hayashi, Masahito

2007-01-01

Quantum optical Gaussian states are a type of important robust quantum states which are manipulatable by the existing technologies. So far, most of the important quantum information experiments are done with such states, including bright Gaussian light and weak Gaussian light. Extending the existing results of quantum information with discrete quantum states to the case of continuous variable quantum states is an interesting theoretical job. The quantum Gaussian states play a central role in such a case. We review the properties and applications of Gaussian states in quantum information with emphasis on the fundamental concepts, the calculation techniques and the effects of imperfections of the real-life experimental setups. Topics here include the elementary properties of Gaussian states and relevant quantum information device, entanglement-based quantum tasks such as quantum teleportation, quantum cryptography with weak and strong Gaussian states and the quantum channel capacity, mathematical theory of quantum entanglement and state estimation for Gaussian states

Accounting for Non-Gaussian Sources of Spatial Correlation in Parametric Functional Magnetic Resonance Imaging Paradigms II: A Method to Obtain First-Level Analysis Residuals with Uniform and Gaussian Spatial Autocorrelation Function and Independent and Identically Distributed Time-Series.

Science.gov (United States)

Gopinath, Kaundinya; Krishnamurthy, Venkatagiri; Lacey, Simon; Sathian, K

2018-02-01

In a recent study Eklund et al. have shown that cluster-wise family-wise error (FWE) rate-corrected inferences made in parametric statistical method-based functional magnetic resonance imaging (fMRI) studies over the past couple of decades may have been invalid, particularly for cluster defining thresholds less stringent than p functions (sACFs) of fMRI data had been modeled incorrectly to follow a Gaussian form, whereas empirical data suggest otherwise. Hence, the residuals from general linear model (GLM)-based fMRI activation estimates in these studies may not have possessed a homogenously Gaussian sACF. Here we propose a method based on the assumption that heterogeneity and non-Gaussianity of the sACF of the first-level GLM analysis residuals, as well as temporal autocorrelations in the first-level voxel residual time-series, are caused by unmodeled MRI signal from neuronal and physiological processes as well as motion and other artifacts, which can be approximated by appropriate decompositions of the first-level residuals with principal component analysis (PCA), and removed. We show that application of this method yields GLM residuals with significantly reduced spatial correlation, nearly Gaussian sACF and uniform spatial smoothness across the brain, thereby allowing valid cluster-based FWE-corrected inferences based on assumption of Gaussian spatial noise. We further show that application of this method renders the voxel time-series of first-level GLM residuals independent, and identically distributed across time (which is a necessary condition for appropriate voxel-level GLM inference), without having to fit ad hoc stochastic colored noise models. Furthermore, the detection power of individual subject brain activation analysis is enhanced. This method will be especially useful for case studies, which rely on first-level GLM analysis inferences.

When non-Gaussian states are Gaussian: Generalization of nonseparability criterion for continuous variables

International Nuclear Information System (INIS)

McHugh, Derek; Buzek, Vladimir; Ziman, Mario

2006-01-01

We present a class of non-Gaussian two-mode continuous-variable states for which the separability criterion for Gaussian states can be employed to detect whether they are separable or not. These states reduce to the two-mode Gaussian states as a special case

Evaluation of Gaussian approximations for data assimilation in reservoir models

KAUST Repository

Iglesias, Marco A.

2013-07-14

The Bayesian framework is the standard approach for data assimilation in reservoir modeling. This framework involves characterizing the posterior distribution of geological parameters in terms of a given prior distribution and data from the reservoir dynamics, together with a forward model connecting the space of geological parameters to the data space. Since the posterior distribution quantifies the uncertainty in the geologic parameters of the reservoir, the characterization of the posterior is fundamental for the optimal management of reservoirs. Unfortunately, due to the large-scale highly nonlinear properties of standard reservoir models, characterizing the posterior is computationally prohibitive. Instead, more affordable ad hoc techniques, based on Gaussian approximations, are often used for characterizing the posterior distribution. Evaluating the performance of those Gaussian approximations is typically conducted by assessing their ability at reproducing the truth within the confidence interval provided by the ad hoc technique under consideration. This has the disadvantage of mixing up the approximation properties of the history matching algorithm employed with the information content of the particular observations used, making it hard to evaluate the effect of the ad hoc approximations alone. In this paper, we avoid this disadvantage by comparing the ad hoc techniques with a fully resolved state-of-the-art probing of the Bayesian posterior distribution. The ad hoc techniques whose performance we assess are based on (1) linearization around the maximum a posteriori estimate, (2) randomized maximum likelihood, and (3) ensemble Kalman filter-type methods. In order to fully resolve the posterior distribution, we implement a state-of-the art Markov chain Monte Carlo (MCMC) method that scales well with respect to the dimension of the parameter space, enabling us to study realistic forward models, in two space dimensions, at a high level of grid refinement. Our

Sums and Gaussian vectors

CERN Document Server

Yurinsky, Vadim Vladimirovich

1995-01-01

Surveys the methods currently applied to study sums of infinite-dimensional independent random vectors in situations where their distributions resemble Gaussian laws. Covers probabilities of large deviations, Chebyshev-type inequalities for seminorms of sums, a method of constructing Edgeworth-type expansions, estimates of characteristic functions for random vectors obtained by smooth mappings of infinite-dimensional sums to Euclidean spaces. A self-contained exposition of the modern research apparatus around CLT, the book is accessible to new graduate students, and can be a useful reference for researchers and teachers of the subject.

Gaussian model for emission rate measurement of heated plumes using hyperspectral data

Science.gov (United States)

Grauer, Samuel J.; Conrad, Bradley M.; Miguel, Rodrigo B.; Daun, Kyle J.

2018-02-01

This paper presents a novel model for measuring the emission rate of a heated gas plume using hyperspectral data from an FTIR imaging spectrometer. The radiative transfer equation (RTE) is used to relate the spectral intensity of a pixel to presumed Gaussian distributions of volume fraction and temperature within the plume, along a line-of-sight that corresponds to the pixel, whereas previous techniques exclusively presume uniform distributions for these parameters. Estimates of volume fraction and temperature are converted to a column density by integrating the local molecular density along each path. Image correlation velocimetry is then employed on raw spectral intensity images to estimate the volume-weighted normal velocity at each pixel. Finally, integrating the product of velocity and column density along a control surface yields an estimate of the instantaneous emission rate. For validation, emission rate estimates were derived from synthetic hyperspectral images of a heated methane plume, generated using data from a large-eddy simulation. Calculating the RTE with Gaussian distributions of volume fraction and temperature, instead of uniform distributions, improved the accuracy of column density measurement by 14%. Moreover, the mean methane emission rate measured using our approach was within 4% of the ground truth. These results support the use of Gaussian distributions of thermodynamic properties in calculation of the RTE for optical gas diagnostics.

Fault diagnosis of active magnetic bearings based on Gaussian GLRT detector

DEFF Research Database (Denmark)

Nagel, Leon; Galeazzi, Roberto; Voigt, Andreas Jauernik

2016-01-01

generalized likelihood ratio test is proposed for detecting faults striking the electromagnet. The detector is capable of detecting and isolating the occurrence of faults in e.g. the windings of bearing by tracking changes in the mean value of a Gaussian distribution. The statistical distribution...

Propagation of truncated modified Laguerre-Gaussian beams

Science.gov (United States)

Deng, D.; Li, J.; Guo, Q.

2010-01-01

By expanding the circ function into a finite sum of complex Gaussian functions and applying the Collins formula, the propagation of hard-edge diffracted modified Laguerre-Gaussian beams (MLGBs) through a paraxial ABCD system is studied, and the approximate closed-form propagation expression of hard-edge diffracted MLGBs is obtained. The transverse intensity distribution of the MLGB carrying finite power can be characterized by a single bright and symmetric ring during propagation when the aperture radius is very large. Starting from the definition of the generalized truncated second-order moments, the beam quality factor of MLGBs through a hard-edged circular aperture is investigated in a cylindrical coordinate system, which turns out to be dependent on the truncated radius and the beam orders.

Resting heart rate variability is associated with ex-Gaussian metrics of intra-individual reaction time variability.

Science.gov (United States)

Spangler, Derek P; Williams, DeWayne P; Speller, Lassiter F; Brooks, Justin R; Thayer, Julian F

2018-03-01

The relationships between vagally mediated heart rate variability (vmHRV) and the cognitive mechanisms underlying performance can be elucidated with ex-Gaussian modeling-an approach that quantifies two different forms of intra-individual variability (IIV) in reaction time (RT). To this end, the current study examined relations of resting vmHRV to whole-distribution and ex-Gaussian IIV. Subjects (N = 83) completed a 5-minute baseline while vmHRV (root mean square of successive differences; RMSSD) was measured. Ex-Gaussian (sigma, tau) and whole-distribution (standard deviation) estimates of IIV were derived from reaction times on a Stroop task. Resting vmHRV was found to be inversely related to tau (exponential IIV) but not to sigma (Gaussian IIV) or the whole-distribution standard deviation of RTs. Findings suggest that individuals with high vmHRV can better prevent attentional lapses but not difficulties with motor control. These findings inform the differential relationships of cardiac vagal control to the cognitive processes underlying human performance. Copyright © 2018 The Authors. Published by Elsevier B.V. All rights reserved.

Gate engineered heterostructure junctionless TFET with Gaussian doping profile for ambipolar suppression and electrical performance improvement

Science.gov (United States)

Aghandeh, Hadi; Sedigh Ziabari, Seyed Ali

2017-11-01

This study investigates a junctionless tunnel field-effect transistor with a dual material gate and a heterostructure channel/source interface (DMG-H-JLTFET). We find that using the heterostructure interface improves device behavior by reducing the tunneling barrier width at the channel/source interface. Simultaneously, the dual material gate structure decreases ambipolar current by increasing the tunneling barrier width at the drain/channel interface. The performance of the device is analyzed based on the energy band diagram at on, off, and ambipolar states. Numerical simulations demonstrate improvements in ION, IOFF, ION/IOFF, subthreshold slope (SS), transconductance and cut-off frequency and suppressed ambipolar behavior. Next, the workfunction optimization of dual material gate is studied. It is found that if appropriate workfunctions are selected for tunnel and auxiliary gates, the JLTFET exhibits considerably improved performance. We then study the influence of Gaussian doping distribution at the drain and the channel on the ambipolar performance of the device and find that a Gaussian doping profile and a dual material gate structure remarkably reduce ambipolar current. Gaussian doped DMG-H-JLTFET, also exhibits enhanced IOFF, ION/IOFF, SS and a low threshold voltage without degrading IOFF.

Energy Management of Smart Distribution Systems

Science.gov (United States)

Ansari, Bananeh

Electric power distribution systems interface the end-users of electricity with the power grid. Traditional distribution systems are operated in a centralized fashion with the distribution system owner or operator being the only decision maker. The management and control architecture of distribution systems needs to gradually transform to accommodate the emerging smart grid technologies, distributed energy resources, and active electricity end-users or prosumers. The content of this document concerns with developing multi-task multi-objective energy management schemes for: 1) commercial/large residential prosumers, and 2) distribution system operator of a smart distribution system. The first part of this document describes a method of distributed energy management of multiple commercial/ large residential prosumers. These prosumers not only consume electricity, but also generate electricity using their roof-top solar photovoltaics systems. When photovoltaics generation is larger than local consumption, excess electricity will be fed into the distribution system, creating a voltage rise along the feeder. Distribution system operator cannot tolerate a significant voltage rise. ES can help the prosumers manage their electricity exchanges with the distribution system such that minimal voltage fluctuation occurs. The proposed distributed energy management scheme sizes and schedules each prosumer's ES to reduce the electricity bill and mitigate voltage rise along the feeder. The second part of this document focuses on emergency energy management and resilience assessment of a distribution system. The developed emergency energy management system uses available resources and redundancy to restore the distribution system's functionality fully or partially. The success of the restoration maneuver depends on how resilient the distribution system is. Engineering resilience terminology is used to evaluate the resilience of distribution system. The proposed emergency energy

Topology in two dimensions. IV - CDM models with non-Gaussian initial conditions

Science.gov (United States)

Coles, Peter; Moscardini, Lauro; Plionis, Manolis; Lucchin, Francesco; Matarrese, Sabino; Messina, Antonio

1993-02-01

The results of N-body simulations with both Gaussian and non-Gaussian initial conditions are used here to generate projected galaxy catalogs with the same selection criteria as the Shane-Wirtanen counts of galaxies. The Euler-Poincare characteristic is used to compare the statistical nature of the projected galaxy clustering in these simulated data sets with that of the observed galaxy catalog. All the models produce a topology dominated by a meatball shift when normalized to the known small-scale clustering properties of galaxies. Models characterized by a positive skewness of the distribution of primordial density perturbations are inconsistent with the Lick data, suggesting problems in reconciling models based on cosmic textures with observations. Gaussian CDM models fit the distribution of cell counts only if they have a rather high normalization but possess too low a coherence length compared with the Lick counts. This suggests that a CDM model with extra large scale power would probably fit the available data.

Distribution of relaxation times in (KBr)/sub 0.5/(KCN)/sub 0.5/

International Nuclear Information System (INIS)

Birge, N.O.; Jeong, Y.H.; Nagel, S.R.; Bhattacharya, S.; Susman, S.

1984-01-01

Measurements of the dielectric response of (KBr)/sub 0.5/(KCN)/sub 0.5/ covering nine decades of frequency are reported. We have shown how the relaxation times proliferate as the temperature is lowered. The anomalously wide distribution of relaxation times can be generated from a Gaussian distribution of energy barriers. As temperature is decreased not only does the spread of relaxation times increase, but more importantly the width of the distribution of activation energies itself increases

Analyzing the effect of introducing a kurtosis parameter in Gaussian Bayesian networks

International Nuclear Information System (INIS)

Main, P.; Navarro, H.

2009-01-01

Gaussian Bayesian networks are graphical models that represent the dependence structure of a multivariate normal random variable with a directed acyclic graph (DAG). In Gaussian Bayesian networks the output is usually the conditional distribution of some unknown variables of interest given a set of evidential nodes whose values are known. The problem of uncertainty about the assumption of normality is very common in applications. Thus a sensitivity analysis of the non-normality effect in our conclusions could be necessary. The aspect of non-normality to be considered is the tail behavior. In this line, the multivariate exponential power distribution is a family depending on a kurtosis parameter that goes from a leptokurtic to a platykurtic distribution with the normal as a mesokurtic distribution. Therefore a more general model can be considered using the multivariate exponential power distribution to describe the joint distribution of a Bayesian network, with a kurtosis parameter reflecting deviations from the normal distribution. The sensitivity of the conclusions to this perturbation is analyzed using the Kullback-Leibler divergence measure that provides an interesting formula to evaluate the effect

Analyzing the effect of introducing a kurtosis parameter in Gaussian Bayesian networks

Energy Technology Data Exchange (ETDEWEB)

Main, P. [Dpto. Estadistica e I.O., Fac. Ciencias Matematicas, Univ. Complutense de Madrid, 28040 Madrid (Spain)], E-mail: pmain@mat.ucm.es; Navarro, H. [Dpto. de Estadistica, I.O. y Calc. Numerico, Fac. Ciencias, UNED, 28040 Madrid (Spain)

2009-05-15

Gaussian Bayesian networks are graphical models that represent the dependence structure of a multivariate normal random variable with a directed acyclic graph (DAG). In Gaussian Bayesian networks the output is usually the conditional distribution of some unknown variables of interest given a set of evidential nodes whose values are known. The problem of uncertainty about the assumption of normality is very common in applications. Thus a sensitivity analysis of the non-normality effect in our conclusions could be necessary. The aspect of non-normality to be considered is the tail behavior. In this line, the multivariate exponential power distribution is a family depending on a kurtosis parameter that goes from a leptokurtic to a platykurtic distribution with the normal as a mesokurtic distribution. Therefore a more general model can be considered using the multivariate exponential power distribution to describe the joint distribution of a Bayesian network, with a kurtosis parameter reflecting deviations from the normal distribution. The sensitivity of the conclusions to this perturbation is analyzed using the Kullback-Leibler divergence measure that provides an interesting formula to evaluate the effect.

A Note on Functional Averages over Gaussian Ensembles

Directory of Open Access Journals (Sweden)

Gabriel H. Tucci

2013-01-01

Full Text Available We find a new formula for matrix averages over the Gaussian ensemble. Let H be an n×n Gaussian random matrix with complex, independent, and identically distributed entries of zero mean and unit variance. Given an n×n positive definite matrix A and a continuous function f:ℝ+→ℝ such that ∫0∞‍e-αt|f(t|2dt0, we find a new formula for the expectation [Tr(f(HAH*]. Taking f(x=log(1+x gives another formula for the capacity of the MIMO communication channel, and taking f(x=(1+x-1 gives the MMSE achieved by a linear receiver.

Generation of dual-wavelength, synchronized, tunable, high energy, femtosecond laser pulses with nearly perfect gaussian spatial profile

Science.gov (United States)

Wang, J.-K.; Siegal, Y.; Lü, C.; Mazur, E.

1992-07-01

We use self-phase modulation in a single-mode fiber to produce broadband femtosecond laser pulses. Subsequent amplification through two Bethune cells yields high-energy, tunable, pulses synchronized with the output of an amplified colliding-pulse-modelocked (CPM) laser. We routinely obtain tunable 200 μJ pulses of 42 fs (fwhm) duration with a nearly perfect gaussian spatial profile. Although self-phase modulation in a single-mode fiber is widely used in femtosecond laser systems, amplification of a fiber-generated supercontinuum in a Bethune cell amplifier is a new feature which maintains the high-quality spatial profile while providing high gain. This laser system is particularly well suited for high energy dual-wavelength pump=probe experiments and time-resolved four-wave mixing spectroscopy.

DEM - distribution energy management

Energy Technology Data Exchange (ETDEWEB)

Seppaelae, A; Kekkonen, V; Koreneff, G [VTT Energy, Espoo (Finland); and others

1998-08-01

The electricity market was de-regulated in Finland at the end of 1995 and the customers can now freely choose their power suppliers. The national grid and local distribution network operators are now separated from the energy business. The network operators transmit the electric power to the customers on equal terms regardless from whom the power is purchased. The Finnish national grid is owned by one company Finnish Power Grid PLC (Fingrid). The major shareholders of Fingrid are the state of Finland, two major power companies and institutional investors. In addition there are about 100 local distribution utilities operating the local 110 kV, 20 kV and 0.4 kV networks. The distribution utilities are mostly owned by the municipalities and towns. In each network one energy supplier is always responsible for the hourly energy balance in the network (a `host`) and it also has the obligation to provide public energy prices accessible to any customer in the network`s area. The Finnish regulating authorities nominate such a supplier who has a dominant market share in the network`s area as the supplier responsible for the network`s energy balance. A regulating authority, called the Electricity Market Centre, ensures that the market is operating properly. The transmission prices and public energy prices are under the Electricity Market Centre`s control. For domestic and other small customers the cost of hourly metering (ca. 1000 US$) would be prohibitive and therefore the use of conventional energy metering and load models is under consideration by the authorities. Small customer trade with the load models (instead of the hourly energy recording) is scheduled to start in the first half of 1998. In this presentation, the problems of energy management from the standpoint of the energy trading and distributing companies in the new situation are first discussed. The topics covered are: the hourly load data management, the forecasting and estimation of hourly energy demands

EVOLUTION OF THE MAGNETIC FIELD LINE DIFFUSION COEFFICIENT AND NON-GAUSSIAN STATISTICS

Energy Technology Data Exchange (ETDEWEB)

Snodin, A. P. [Department of Mathematics, Faculty of Applied Science, King Mongkut’s University of Technology North Bangkok, Bangkok 10800 (Thailand); Ruffolo, D. [Department of Physics, Faculty of Science, Mahidol University, Bangkok 10400 (Thailand); Matthaeus, W. H. [Bartol Research Institute and Department of Physics and Astronomy, University of Delaware, Newark, DE 19716 (United States)

2016-08-20

The magnetic field line random walk (FLRW) plays an important role in the transport of energy and particles in turbulent plasmas. For magnetic fluctuations that are transverse or almost transverse to a large-scale mean magnetic field, theories describing the FLRW usually predict asymptotic diffusion of magnetic field lines perpendicular to the mean field. Such theories often depend on the assumption that one can relate the Lagrangian and Eulerian statistics of the magnetic field via Corrsin’s hypothesis, and additionally take the distribution of magnetic field line displacements to be Gaussian. Here we take an ordinary differential equation (ODE) model with these underlying assumptions and test how well it describes the evolution of the magnetic field line diffusion coefficient in 2D+slab magnetic turbulence, by comparisons to computer simulations that do not involve such assumptions. In addition, we directly test the accuracy of the Corrsin approximation to the Lagrangian correlation. Over much of the studied parameter space we find that the ODE model is in fairly good agreement with computer simulations, in terms of both the evolution and asymptotic values of the diffusion coefficient. When there is poor agreement, we show that this can be largely attributed to the failure of Corrsin’s hypothesis rather than the assumption of Gaussian statistics of field line displacements. The degree of non-Gaussianity, which we measure in terms of the kurtosis, appears to be an indicator of how well Corrsin’s approximation works.

Methods for Distributed Optimal Energy Management

DEFF Research Database (Denmark)

Brehm, Robert

The presented research deals with the fundamental underlying methods and concepts of how the growing number of distributed generation units based on renewable energy resources and distributed storage devices can be most efficiently integrated into the existing utility grid. In contrast to convent......The presented research deals with the fundamental underlying methods and concepts of how the growing number of distributed generation units based on renewable energy resources and distributed storage devices can be most efficiently integrated into the existing utility grid. In contrast...... to conventional centralised optimal energy flow management systems, here-in, focus is set on how optimal energy management can be achieved in a decentralised distributed architecture such as a multi-agent system. Distributed optimisation methods are introduced, targeting optimisation of energy flow in virtual......-consumption of renewable energy resources in low voltage grids. It can be shown that this method prevents mutual discharging of batteries and prevents peak loads, a supervisory control instance can dictate the level of autarchy from the utility grid. Further it is shown that the problem of optimal energy flow management...

Gaussian white noise as a resource for work extraction.

Science.gov (United States)

Dechant, Andreas; Baule, Adrian; Sasa, Shin-Ichi

2017-03-01

We show that uncorrelated Gaussian noise can drive a system out of equilibrium and can serve as a resource from which work can be extracted. We consider an overdamped particle in a periodic potential with an internal degree of freedom and a state-dependent friction, coupled to an equilibrium bath. Applying additional Gaussian white noise drives the system into a nonequilibrium steady state and causes a finite current if the potential is spatially asymmetric. The model thus operates as a Brownian ratchet, whose current we calculate explicitly in three complementary limits. Since the particle current is driven solely by additive Gaussian white noise, this shows that the latter can potentially perform work against an external load. By comparing the extracted power to the energy injection due to the noise, we discuss the efficiency of such a ratchet.

Non-Gaussian covariance of CMB B modes of polarization and parameter degradation

International Nuclear Information System (INIS)

Li Chao; Smith, Tristan L.; Cooray, Asantha

2007-01-01

The B-mode polarization lensing signal is a useful probe of the neutrino mass and to a lesser extent the dark energy equation of state as the signal depends on the integrated mass power spectrum between us and the last scattering surface. This lensing B-mode signal, however, is non-Gaussian and the resulting non-Gaussian covariance to the power spectrum could impact cosmological parameter measurements, as correlations between B-mode bins are at a level of 0.1. On the other hand, for temperature and E-mode polarization power spectra, the non-Gaussian covariance is not significant, where we find correlations at the 10 -5 level even for adjacent bins. When the power spectrum is estimated with roughly 5 uniformly spaced bins from l=5 to l=100 and 13 logarithmic uniformly spaced bins from l=100 to l=2000, the resulting degradation on neutrino mass and dark energy equation of state is about a factor of 2 to 3 when compared to the case where statistics are simply considered to be Gaussian. If we increase the total number of bins between l=5 and l=2000 to be about 100, we find that the non-Gaussianities only make a minor difference with less than a few percent correction to uncertainties of most cosmological parameters determined from the data. For Planck, the resulting constraints on the sum of the neutrino masses is σ Σm ν ∼0.2 eV and on the dark energy equation of state parameter we find that σ w ∼0.5. A post-Planck experiment can improve the neutrino mass measurement by a factor of 3 to 4

Computational Stimulation of the Basal Ganglia Neurons with Cost Effective Delayed Gaussian Waveforms.

Science.gov (United States)

Daneshzand, Mohammad; Faezipour, Miad; Barkana, Buket D

2017-01-01

Deep brain stimulation (DBS) has compelling results in the desynchronization of the basal ganglia neuronal activities and thus, is used in treating the motor symptoms of Parkinson's disease (PD). Accurate definition of DBS waveform parameters could avert tissue or electrode damage, increase the neuronal activity and reduce energy cost which will prolong the battery life, hence avoiding device replacement surgeries. This study considers the use of a charge balanced Gaussian waveform pattern as a method to disrupt the firing patterns of neuronal cell activity. A computational model was created to simulate ganglia cells and their interactions with thalamic neurons. From the model, we investigated the effects of modified DBS pulse shapes and proposed a delay period between the cathodic and anodic parts of the charge balanced Gaussian waveform to desynchronize the firing patterns of the GPe and GPi cells. The results of the proposed Gaussian waveform with delay outperformed that of rectangular DBS waveforms used in in-vivo experiments. The Gaussian Delay Gaussian (GDG) waveforms achieved lower number of misses in eliciting action potential while having a lower amplitude and shorter length of delay compared to numerous different pulse shapes. The amount of energy consumed in the basal ganglia network due to GDG waveforms was dropped by 22% in comparison with charge balanced Gaussian waveforms without any delay between the cathodic and anodic parts and was also 60% lower than a rectangular charged balanced pulse with a delay between the cathodic and anodic parts of the waveform. Furthermore, by defining a Synchronization Level metric, we observed that the GDG waveform was able to reduce the synchronization of GPi neurons more effectively than any other waveform. The promising results of GDG waveforms in terms of eliciting action potential, desynchronization of the basal ganglia neurons and reduction of energy consumption can potentially enhance the performance of DBS

Computational Stimulation of the Basal Ganglia Neurons with Cost Effective Delayed Gaussian Waveforms

Directory of Open Access Journals (Sweden)

Mohammad Daneshzand

2017-08-01

Full Text Available Deep brain stimulation (DBS has compelling results in the desynchronization of the basal ganglia neuronal activities and thus, is used in treating the motor symptoms of Parkinson's disease (PD. Accurate definition of DBS waveform parameters could avert tissue or electrode damage, increase the neuronal activity and reduce energy cost which will prolong the battery life, hence avoiding device replacement surgeries. This study considers the use of a charge balanced Gaussian waveform pattern as a method to disrupt the firing patterns of neuronal cell activity. A computational model was created to simulate ganglia cells and their interactions with thalamic neurons. From the model, we investigated the effects of modified DBS pulse shapes and proposed a delay period between the cathodic and anodic parts of the charge balanced Gaussian waveform to desynchronize the firing patterns of the GPe and GPi cells. The results of the proposed Gaussian waveform with delay outperformed that of rectangular DBS waveforms used in in-vivo experiments. The Gaussian Delay Gaussian (GDG waveforms achieved lower number of misses in eliciting action potential while having a lower amplitude and shorter length of delay compared to numerous different pulse shapes. The amount of energy consumed in the basal ganglia network due to GDG waveforms was dropped by 22% in comparison with charge balanced Gaussian waveforms without any delay between the cathodic and anodic parts and was also 60% lower than a rectangular charged balanced pulse with a delay between the cathodic and anodic parts of the waveform. Furthermore, by defining a Synchronization Level metric, we observed that the GDG waveform was able to reduce the synchronization of GPi neurons more effectively than any other waveform. The promising results of GDG waveforms in terms of eliciting action potential, desynchronization of the basal ganglia neurons and reduction of energy consumption can potentially enhance the

Autonomy-oriented mechanisms for efficient energy distribution

Energy Technology Data Exchange (ETDEWEB)

Liu, Jiming; Shi, Benyun

2010-09-15

Due to the uneven geographical availability of energy resources, it is essential for the energy suppliers and consumers in different countries/regions to most efficiently, economically, as well as reliably distribute energy resources. In this paper, starting from a specific energy distribution problem, we present a decentralized behavior-based paradigm that draws on the methodology of autonomy-oriented computing. The goal is twofold: (i) to characterize the underlying mechanism of the energy distribution systems, (ii) to provide scalable solutions for efficient energy distribution. We conjecture that efficient energy trading markets can emerge from appropriate behavior-based mechanisms, which can autonomously improve energy distribution efficiency.

First Passage Time Intervals of Gaussian Processes

Science.gov (United States)

Perez, Hector; Kawabata, Tsutomu; Mimaki, Tadashi

1987-08-01

The first passage time problem of a stationary Guassian process is theretically and experimentally studied. Renewal functions are derived for a time-dependent boundary and numerically calculated for a Gaussian process having a seventh-order Butterworth spectrum. The results show a multipeak property not only for the constant boundary but also for a linearly increasing boundary. The first passage time distribution densities were experimentally determined for a constant boundary. The renewal functions were shown to be a fairly good approximation to the distribution density over a limited range.

Measurement of Hubble constant: non-Gaussian errors in HST Key Project data

Energy Technology Data Exchange (ETDEWEB)

Singh, Meghendra [Dr. A.P.J. Abdul Kalam Technical University, Uttar Pradesh, Lucknow, 226021 India (India); Gupta, Shashikant; Pandey, Ashwini [Amity University Haryana, Gurgaon, Haryana, 122413 India (India); Sharma, Satendra, E-mail: meghendrasingh_db@yahoo.co.in, E-mail: shashikantgupta.astro@gmail.com, E-mail: satyamkashwini@gmail.com, E-mail: ssharma_phy@yahoo.co.uk [Yobe State University, Damaturu, Yobe State (Nigeria)

2016-08-01

Assuming the Central Limit Theorem, experimental uncertainties in any data set are expected to follow the Gaussian distribution with zero mean. We propose an elegant method based on Kolmogorov-Smirnov statistic to test the above; and apply it on the measurement of Hubble constant which determines the expansion rate of the Universe. The measurements were made using Hubble Space Telescope. Our analysis shows that the uncertainties in the above measurement are non-Gaussian.

Gaussian density matrices: Quantum analogs of classical states

International Nuclear Information System (INIS)

Mann, A.; Revzen, M.

1993-01-01

We study quantum analogs of clasical situations, i.e. quantum states possessing some specific classical attribute(s). These states seem quite generally, to have the form of gaussian density matrices. Such states can always be parametrized as thermal squeezed states (TSS). We consider the following specific cases: (a) Two beams that are built from initial beams which passed through a beam splitter cannot, classically, be distinguished from (appropriately prepared) two independent beams that did not go through a splitter. The only quantum states possessing this classical attribute are TSS. (b) The classical Cramer's theorem was shown to have a quantum version (Hegerfeldt). Again, the states here are Gaussian density matrices. (c) The special case in the study of the quantum version of Cramer's theorem, viz. when the state obtained after partial tracing is a pure state, leads to the conclusion that all states involved are zero temperature limit TSS. The classical analog here are gaussians of zero width, i.e. all distributions are δ functions in phase space. (orig.)

Interaction of Airy–Gaussian beams in saturable media

International Nuclear Information System (INIS)

Zhou Meiling; Peng Yulian; Chen Chidao; Chen Bo; Peng Xi; Deng Dongmei

2016-01-01

Based on the nonlinear Schrödinger equation, the interactions of the two Airy–Gaussian components in the incidence are analyzed in saturable media, under the circumstances of the same amplitude and different amplitudes, respectively. It is found that the interaction can be both attractive and repulsive depending on the relative phase. The smaller the interval between two Airy–Gaussian components in the incidence is, the stronger the intensity of the interaction. However, with the equal amplitude, the symmetry is shown and the change of quasi-breathers is opposite in the in-phase case and out-of-phase case. As the distribution factor is increased, the phenomena of the quasi-breather and the self-accelerating of the two Airy–Gaussian components are weakened. When the amplitude is not equal, the image does not have symmetry. The obvious phenomenon of the interaction always arises on the side of larger input power in the incidence. The maximum intensity image is also simulated. Many of the characteristics which are contained within other images can also be concluded in this figure. (paper)

A Novel Bearing Fault Diagnosis Method Based on Gaussian Restricted Boltzmann Machine

Directory of Open Access Journals (Sweden)

Xiao-hui He

2016-01-01

Full Text Available To realize the fault diagnosis of bearing effectively, this paper presents a novel bearing fault diagnosis method based on Gaussian restricted Boltzmann machine (Gaussian RBM. Vibration signals are firstly resampled to the same equivalent speed. Subsequently, the envelope spectrums of the resampled data are used directly as the feature vectors to represent the fault types of bearing. Finally, in order to deal with the high-dimensional feature vectors based on envelope spectrum, a classifier model based on Gaussian RBM is applied. Gaussian RBM has the ability to provide a closed-form representation of the distribution underlying the training data, and it is very convenient for modeling high-dimensional real-valued data. Experiments on 10 different data sets verify the performance of the proposed method. The superiority of Gaussian RBM classifier is also confirmed by comparing with other classifiers, such as extreme learning machine, support vector machine, and deep belief network. The robustness of the proposed method is also studied in this paper. It can be concluded that the proposed method can realize the bearing fault diagnosis accurately and effectively.

The accuracy of the Gaussian-and-finite-element-Coulomb (GFC) method for the calculation of Coulomb integrals.

Science.gov (United States)

Przybytek, Michal; Helgaker, Trygve

2013-08-07

We analyze the accuracy of the Coulomb energy calculated using the Gaussian-and-finite-element-Coulomb (GFC) method. In this approach, the electrostatic potential associated with the molecular electronic density is obtained by solving the Poisson equation and then used to calculate matrix elements of the Coulomb operator. The molecular electrostatic potential is expanded in a mixed Gaussian-finite-element (GF) basis set consisting of Gaussian functions of s symmetry centered on the nuclei (with exponents obtained from a full optimization of the atomic potentials generated by the atomic densities from symmetry-averaged restricted open-shell Hartree-Fock theory) and shape functions defined on uniform finite elements. The quality of the GF basis is controlled by means of a small set of parameters; for a given width of the finite elements d, the highest accuracy is achieved at smallest computational cost when tricubic (n = 3) elements are used in combination with two (γ(H) = 2) and eight (γ(1st) = 8) Gaussians on hydrogen and first-row atoms, respectively, with exponents greater than a given threshold (αmin (G)=0.5). The error in the calculated Coulomb energy divided by the number of atoms in the system depends on the system type but is independent of the system size or the orbital basis set, vanishing approximately like d(4) with decreasing d. If the boundary conditions for the Poisson equation are calculated in an approximate way, the GFC method may lose its variational character when the finite elements are too small; with larger elements, it is less sensitive to inaccuracies in the boundary values. As it is possible to obtain accurate boundary conditions in linear time, the overall scaling of the GFC method for large systems is governed by another computational step-namely, the generation of the three-center overlap integrals with three Gaussian orbitals. The most unfavorable (nearly quadratic) scaling is observed for compact, truly three-dimensional systems

Capacity and optimal collusion attack channels for Gaussian fingerprinting games

Science.gov (United States)

Wang, Ying; Moulin, Pierre

2007-02-01

In content fingerprinting, the same media covertext - image, video, audio, or text - is distributed to many users. A fingerprint, a mark unique to each user, is embedded into each copy of the distributed covertext. In a collusion attack, two or more users may combine their copies in an attempt to "remove" their fingerprints and forge a pirated copy. To trace the forgery back to members of the coalition, we need fingerprinting codes that can reliably identify the fingerprints of those members. Researchers have been focusing on designing or testing fingerprints for Gaussian host signals and the mean square error (MSE) distortion under some classes of collusion attacks, in terms of the detector's error probability in detecting collusion members. For example, under the assumptions of Gaussian fingerprints and Gaussian attacks (the fingerprinted signals are averaged and then the result is passed through a Gaussian test channel), Moulin and Briassouli1 derived optimal strategies in a game-theoretic framework that uses the detector's error probability as the performance measure for a binary decision problem (whether a user participates in the collusion attack or not); Stone2 and Zhao et al. 3 studied average and other non-linear collusion attacks for Gaussian-like fingerprints; Wang et al. 4 stated that the average collusion attack is the most efficient one for orthogonal fingerprints; Kiyavash and Moulin 5 derived a mathematical proof of the optimality of the average collusion attack under some assumptions. In this paper, we also consider Gaussian cover signals, the MSE distortion, and memoryless collusion attacks. We do not make any assumption about the fingerprinting codes used other than an embedding distortion constraint. Also, our only assumptions about the attack channel are an expected distortion constraint, a memoryless constraint, and a fairness constraint. That is, the colluders are allowed to use any arbitrary nonlinear strategy subject to the above

Panchromatic spectral energy distributions of Herschel sources

Science.gov (United States)

Berta, S.; Lutz, D.; Santini, P.; Wuyts, S.; Rosario, D.; Brisbin, D.; Cooray, A.; Franceschini, A.; Gruppioni, C.; Hatziminaoglou, E.; Hwang, H. S.; Le Floc'h, E.; Magnelli, B.; Nordon, R.; Oliver, S.; Page, M. J.; Popesso, P.; Pozzetti, L.; Pozzi, F.; Riguccini, L.; Rodighiero, G.; Roseboom, I.; Scott, D.; Symeonidis, M.; Valtchanov, I.; Viero, M.; Wang, L.

2013-03-01

Combining far-infrared Herschel photometry from the PACS Evolutionary Probe (PEP) and Herschel Multi-tiered Extragalactic Survey (HerMES) guaranteed time programs with ancillary datasets in the GOODS-N, GOODS-S, and COSMOS fields, it is possible to sample the 8-500 μm spectral energy distributions (SEDs) of galaxies with at least 7-10 bands. Extending to the UV, optical, and near-infrared, the number of bands increases up to 43. We reproduce the distribution of galaxies in a carefully selected restframe ten colors space, based on this rich data-set, using a superposition of multivariate Gaussian modes. We use this model to classify galaxies and build median SEDs of each class, which are then fitted with a modified version of the magphys code that combines stellar light, emission from dust heated by stars and a possible warm dust contribution heated by an active galactic nucleus (AGN). The color distribution of galaxies in each of the considered fields can be well described with the combination of 6-9 classes, spanning a large range of far- to near-infrared luminosity ratios, as well as different strength of the AGN contribution to bolometric luminosities. The defined Gaussian grouping is used to identify rare or odd sources. The zoology of outliers includes Herschel-detected ellipticals, very blue z ~ 1 Ly-break galaxies, quiescent spirals, and torus-dominated AGN with star formation. Out of these groups and outliers, a new template library is assembled, consisting of 32 SEDs describing the intrinsic scatter in the restframe UV-to-submm colors of infrared galaxies. This library is tested against L(IR) estimates with and without Herschel data included, and compared to eightother popular methods often adopted in the literature. When implementing Herschel photometry, these approaches produce L(IR) values consistent with each other within a median absolute deviation of 10-20%, the scatter being dominated more by fine tuning of the codes, rather than by the choice of

Distribution functions and thermodynamic functions of many particle systems

International Nuclear Information System (INIS)

Isihara, A.; Rosa Junior, S.G.

1976-01-01

A method is given of determining and upper bound of the entropy of a classical interacting system. A family of gaussian trial distribution functions is introduced for an electron gas. It was found that the ring diagram energy corresponds to the minimum free energy which the family produces. In contrast to the ring diagram method, the new approach is extremely simple and general [pt

Gaussianization for fast and accurate inference from cosmological data

Science.gov (United States)

Schuhmann, Robert L.; Joachimi, Benjamin; Peiris, Hiranya V.

2016-06-01

We present a method to transform multivariate unimodal non-Gaussian posterior probability densities into approximately Gaussian ones via non-linear mappings, such as Box-Cox transformations and generalizations thereof. This permits an analytical reconstruction of the posterior from a point sample, like a Markov chain, and simplifies the subsequent joint analysis with other experiments. This way, a multivariate posterior density can be reported efficiently, by compressing the information contained in Markov Chain Monte Carlo samples. Further, the model evidence integral (I.e. the marginal likelihood) can be computed analytically. This method is analogous to the search for normal parameters in the cosmic microwave background, but is more general. The search for the optimally Gaussianizing transformation is performed computationally through a maximum-likelihood formalism; its quality can be judged by how well the credible regions of the posterior are reproduced. We demonstrate that our method outperforms kernel density estimates in this objective. Further, we select marginal posterior samples from Planck data with several distinct strongly non-Gaussian features, and verify the reproduction of the marginal contours. To demonstrate evidence computation, we Gaussianize the joint distribution of data from weak lensing and baryon acoustic oscillations, for different cosmological models, and find a preference for flat Λcold dark matter. Comparing to values computed with the Savage-Dickey density ratio, and Population Monte Carlo, we find good agreement of our method within the spread of the other two.

Temporal and spatial distribution of high energy electrons at Jupiter

Science.gov (United States)

Jun, I.; Garrett, H. B.; Ratliff, J. M.

2003-04-01

Measurements of the high energy, omni-directional electron environment by the Galileo spacecraft Energetic Particle Detector (EPD) were used to study the high energy electron environment in the Jovian magnetosphere, especially in the region between 8 to 18 Rj (1 Rj = 1 Jovian radius = 71,400 km). 10-minute averages of the EPD data collected between Jupiter orbit insertion (JOI) in 1995 and the orbit number 33 (I33) in 2002 form an extensive dataset, which has been extremely useful to observe temporal and spatial variability of the Jovian high energy electron environment. The count rates of the EPD electron channels (0.174, 0.304, 0.527, 1.5, 2.0, and 11 MeV) were grouped into 0.5 Rj or 0.5 L bins and analyzed statistically. The results indicate that: (1) a log-normal Gaussian distribution well describes the statistics of the high energy electron environment (for example, electron differential fluxes) in the Jovian magnetosphere, in the region studied here; (2) the high energy electron environments inferred by the Galileo EPD measurements are in a close agreement with the data obtained using the Divine model, which was developed more than 30 years ago from Pioneer 10, 11 and Voyager 1, 2 data; (3) the data are better organized when plotted against magnetic radial parameter L than Rj; (4) the standard deviations of the 0.174, 0.304, 0.527 MeV channel count rates are larger than those of the 1.5, 2.0, 11 MeV count rates in 12 Rj. These observations are very helpful to understand short- and long-term, and local variability of the Jovian high energy electron environment, and are discussed in detail.

Tridiagonal realization of the antisymmetric Gaussian β-ensemble

International Nuclear Information System (INIS)

Dumitriu, Ioana; Forrester, Peter J.

2010-01-01

The Householder reduction of a member of the antisymmetric Gaussian unitary ensemble gives an antisymmetric tridiagonal matrix with all independent elements. The random variables permit the introduction of a positive parameter β, and the eigenvalue probability density function of the corresponding random matrices can be computed explicitly, as can the distribution of (q i ), the first components of the eigenvectors. Three proofs are given. One involves an inductive construction based on bordering of a family of random matrices which are shown to have the same distributions as the antisymmetric tridiagonal matrices. This proof uses the Dixon-Anderson integral from Selberg integral theory. A second proof involves the explicit computation of the Jacobian for the change of variables between real antisymmetric tridiagonal matrices, its eigenvalues, and (q i ). The third proof maps matrices from the antisymmetric Gaussian β-ensemble to those realizing particular examples of the Laguerre β-ensemble. In addition to these proofs, we note some simple properties of the shooting eigenvector and associated Pruefer phases of the random matrices.

Perturbative Gaussianizing transforms for cosmological fields

Science.gov (United States)

Hall, Alex; Mead, Alexander

2018-01-01

Constraints on cosmological parameters from large-scale structure have traditionally been obtained from two-point statistics. However, non-linear structure formation renders these statistics insufficient in capturing the full information content available, necessitating the measurement of higher order moments to recover information which would otherwise be lost. We construct quantities based on non-linear and non-local transformations of weakly non-Gaussian fields that Gaussianize the full multivariate distribution at a given order in perturbation theory. Our approach does not require a model of the fields themselves and takes as input only the first few polyspectra, which could be modelled or measured from simulations or data, making our method particularly suited to observables lacking a robust perturbative description such as the weak-lensing shear. We apply our method to simulated density fields, finding a significantly reduced bispectrum and an enhanced correlation with the initial field. We demonstrate that our method reconstructs a large proportion of the linear baryon acoustic oscillations, improving the information content over the raw field by 35 per cent. We apply the transform to toy 21 cm intensity maps, showing that our method still performs well in the presence of complications such as redshift-space distortions, beam smoothing, pixel noise and foreground subtraction. We discuss how this method might provide a route to constructing a perturbative model of the fully non-Gaussian multivariate likelihood function.

Energy Storage and Distributed Energy Generation Project, Final Project Report

Energy Technology Data Exchange (ETDEWEB)

Schwank, Johannes; Mader, Jerry; Chen, Xiaoyin; Mi, Chris; Linic, Suljo; Sastry, Ann Marie; Stefanopoulou, Anna; Thompson, Levi; Varde, Keshav

2008-03-31

This report serves as a Final Report under the “Energy Storage and Distribution Energy Generation Project” carried out by the Transportation Energy Center (TEC) at the University of Michigan (UM). An interdisciplinary research team has been working on fundamental and applied research on: -distributed power generation and microgrids, -power electronics, and -advanced energy storage. The long-term objective of the project was to provide a framework for identifying fundamental research solutions to technology challenges of transmission and distribution, with special emphasis on distributed power generation, energy storage, control methodologies, and power electronics for microgrids, and to develop enabling technologies for novel energy storage and harvesting concepts that can be simulated, tested, and scaled up to provide relief for both underserved and overstressed portions of the Nation’s grid. TEC’s research is closely associated with Sections 5.0 and 6.0 of the DOE "Five-year Program Plan for FY2008 to FY2012 for Electric Transmission and Distribution Programs, August 2006.”

Institutional distributed energy interconnection barriers

International Nuclear Information System (INIS)

Castelaz, S.A.

2002-01-01

This PowerPoint presentation provided an introduction to Encorp Inc., a leading provider of network technology and infrastructure management solutions for the distributed energy market. Encorp develops and markets software and hardware technology solutions for communications, control and networking of distributed energy. It is developing and implementing real-time, distributed energy-focused solutions for a wide variety of applications through new products and services which are technology neutral, and easily networked. Encorp controls more than 500 MW of distributed power with a total of 127 customers. This paper reviewed 3 barriers (regulatory, contractual/tariffs, and business practices) based on US experience. The challenge remaining is to determine if microgrids can be used effectively, and to determine the limitations of bi-directional power flows. The key issues regarding how end-users can share the costs and maximize on the benefits of distributed energy resources include: standby service charges, departing load charges, regulatory uncertainty, rate class degradation, lack of incentives for utility cost reduction, and lack of ability to create experimental tariffs. tabs., figs

Forecasts of non-Gaussian parameter spaces using Box-Cox transformations

Science.gov (United States)

Joachimi, B.; Taylor, A. N.

2011-09-01

Forecasts of statistical constraints on model parameters using the Fisher matrix abound in many fields of astrophysics. The Fisher matrix formalism involves the assumption of Gaussianity in parameter space and hence fails to predict complex features of posterior probability distributions. Combining the standard Fisher matrix with Box-Cox transformations, we propose a novel method that accurately predicts arbitrary posterior shapes. The Box-Cox transformations are applied to parameter space to render it approximately multivariate Gaussian, performing the Fisher matrix calculation on the transformed parameters. We demonstrate that, after the Box-Cox parameters have been determined from an initial likelihood evaluation, the method correctly predicts changes in the posterior when varying various parameters of the experimental setup and the data analysis, with marginally higher computational cost than a standard Fisher matrix calculation. We apply the Box-Cox-Fisher formalism to forecast cosmological parameter constraints by future weak gravitational lensing surveys. The characteristic non-linear degeneracy between matter density parameter and normalization of matter density fluctuations is reproduced for several cases, and the capabilities of breaking this degeneracy by weak-lensing three-point statistics is investigated. Possible applications of Box-Cox transformations of posterior distributions are discussed, including the prospects for performing statistical data analysis steps in the transformed Gaussianized parameter space.

Vortices in Gaussian beams

CSIR Research Space (South Africa)

Roux, FS

2009-01-01

Full Text Available , t0)} = P(du, dv) {FR{g(u, v, t0)}} Replacement: u→ du = t− t0 i2 ∂ ∂u′ v → dv = t− t0 i2 ∂ ∂v′ CSIR National Laser Centre – p.13/30 Differentiation i.s.o integration Evaluate the integral over the Gaussian beam (once and for all). Then, instead... . Gaussian beams with vortex dipoles CSIR National Laser Centre – p.2/30 Gaussian beam notation Gaussian beam in normalised coordinates: g(u, v, t) = exp ( −u 2 + v2 1− it ) u = xω0 v = yω0 t = zρ ρ = piω20 λ ω0 — 1/e2 beam waist radius; ρ— Rayleigh range ω ω...

Capacity Bounds for the Gaussian IM-DD Optical Multiple-Access Channel

KAUST Repository

Chaaban, Anas; Al-Ebraheemy, Omer M. S.; Al-Naffouri, Tareq Y.; Alouini, Mohamed-Slim

2017-01-01

Optical wireless communications (OWC) is a promising technology for closing the mismatch between the growing number of connected devices and the limited wireless network capabilities. Similar to downlink, uplink can also benefit from OWC for establishing connectivity between such devices and an optical access point. In this context, the incoherent intensitymodulation and direct-detection (IM-DD) scheme is desirable in practice. Hence, it is important to understand the fundamental limits of communication rates over an OWC uplink employing IM-DD, i.e., the channel capacity. This uplink, modeled as a Gaussian multiple-access channel (MAC) for indoors OWC, is studied in this paper, under the IM-DD constraints which form the main difference with the standard Gaussian MAC commonly studied in the radio-frequency context. Capacity region outer and inner bounds for this channel are derived. The bounds are fairly close at high signal-to-noise ratio (SNR), where a truncated- Gaussian input distribution achieves the capacity region within a constant gap. Furthermore, the bounds coincide at low SNR showing the optimality of on-off keying combined with successive cancellation decoding in this regime. At moderate SNR, an optimized uniformly-spaced discrete input distribution achieves fairly good performance.

Capacity Bounds for the Gaussian IM-DD Optical Multiple-Access Channel

KAUST Repository

Chaaban, Anas

2017-03-18

Optical wireless communications (OWC) is a promising technology for closing the mismatch between the growing number of connected devices and the limited wireless network capabilities. Similar to downlink, uplink can also benefit from OWC for establishing connectivity between such devices and an optical access point. In this context, the incoherent intensitymodulation and direct-detection (IM-DD) scheme is desirable in practice. Hence, it is important to understand the fundamental limits of communication rates over an OWC uplink employing IM-DD, i.e., the channel capacity. This uplink, modeled as a Gaussian multiple-access channel (MAC) for indoors OWC, is studied in this paper, under the IM-DD constraints which form the main difference with the standard Gaussian MAC commonly studied in the radio-frequency context. Capacity region outer and inner bounds for this channel are derived. The bounds are fairly close at high signal-to-noise ratio (SNR), where a truncated- Gaussian input distribution achieves the capacity region within a constant gap. Furthermore, the bounds coincide at low SNR showing the optimality of on-off keying combined with successive cancellation decoding in this regime. At moderate SNR, an optimized uniformly-spaced discrete input distribution achieves fairly good performance.

Evaluation of two typical distributed energy systems

Science.gov (United States)

Han, Miaomiao; Tan, Xiu

2018-03-01

According to the two-natural gas distributed energy system driven by gas engine driven and gas turbine, in this paper, the first and second laws of thermodynamics are used to measure the distributed energy system from the two parties of “quantity” and “quality”. The calculation results show that the internal combustion engine driven distributed energy station has a higher energy efficiency, but the energy efficiency is low; the gas turbine driven distributed energy station energy efficiency is high, but the primary energy utilization rate is relatively low. When configuring the system, we should determine the applicable natural gas distributed energy system technology plan and unit configuration plan according to the actual load factors of the project and the actual factors such as the location, background and environmental requirements of the project. “quality” measure, the utilization of waste heat energy efficiency index is proposed.

AUTONOMOUS GAUSSIAN DECOMPOSITION

International Nuclear Information System (INIS)

Lindner, Robert R.; Vera-Ciro, Carlos; Murray, Claire E.; Stanimirović, Snežana; Babler, Brian; Heiles, Carl; Hennebelle, Patrick; Goss, W. M.; Dickey, John

2015-01-01

We present a new algorithm, named Autonomous Gaussian Decomposition (AGD), for automatically decomposing spectra into Gaussian components. AGD uses derivative spectroscopy and machine learning to provide optimized guesses for the number of Gaussian components in the data, and also their locations, widths, and amplitudes. We test AGD and find that it produces results comparable to human-derived solutions on 21 cm absorption spectra from the 21 cm SPectral line Observations of Neutral Gas with the EVLA (21-SPONGE) survey. We use AGD with Monte Carlo methods to derive the H i line completeness as a function of peak optical depth and velocity width for the 21-SPONGE data, and also show that the results of AGD are stable against varying observational noise intensity. The autonomy and computational efficiency of the method over traditional manual Gaussian fits allow for truly unbiased comparisons between observations and simulations, and for the ability to scale up and interpret the very large data volumes from the upcoming Square Kilometer Array and pathfinder telescopes

AUTONOMOUS GAUSSIAN DECOMPOSITION

Energy Technology Data Exchange (ETDEWEB)

Lindner, Robert R.; Vera-Ciro, Carlos; Murray, Claire E.; Stanimirović, Snežana; Babler, Brian [Department of Astronomy, University of Wisconsin, 475 North Charter Street, Madison, WI 53706 (United States); Heiles, Carl [Radio Astronomy Lab, UC Berkeley, 601 Campbell Hall, Berkeley, CA 94720 (United States); Hennebelle, Patrick [Laboratoire AIM, Paris-Saclay, CEA/IRFU/SAp-CNRS-Université Paris Diderot, F-91191 Gif-sur Yvette Cedex (France); Goss, W. M. [National Radio Astronomy Observatory, P.O. Box O, 1003 Lopezville, Socorro, NM 87801 (United States); Dickey, John, E-mail: rlindner@astro.wisc.edu [University of Tasmania, School of Maths and Physics, Private Bag 37, Hobart, TAS 7001 (Australia)

2015-04-15

We present a new algorithm, named Autonomous Gaussian Decomposition (AGD), for automatically decomposing spectra into Gaussian components. AGD uses derivative spectroscopy and machine learning to provide optimized guesses for the number of Gaussian components in the data, and also their locations, widths, and amplitudes. We test AGD and find that it produces results comparable to human-derived solutions on 21 cm absorption spectra from the 21 cm SPectral line Observations of Neutral Gas with the EVLA (21-SPONGE) survey. We use AGD with Monte Carlo methods to derive the H i line completeness as a function of peak optical depth and velocity width for the 21-SPONGE data, and also show that the results of AGD are stable against varying observational noise intensity. The autonomy and computational efficiency of the method over traditional manual Gaussian fits allow for truly unbiased comparisons between observations and simulations, and for the ability to scale up and interpret the very large data volumes from the upcoming Square Kilometer Array and pathfinder telescopes.

A simple free energy for the isotropic-nematic phase transition of rods

NARCIS (Netherlands)

Tuinier, R.

2016-01-01

A free energy expression is proposed that describes the isotropic-nematic binodal concentrations of hard rods. A simple analytical form for this free energy was yet only available using a Gaussian trial function for the orientation distribution function (ODF), leading, however, to a significant

Detecting the presence of a magnetic field under Gaussian and non-Gaussian noise by adaptive measurement

Energy Technology Data Exchange (ETDEWEB)

Wang, Yuan-Mei; Li, Jun-Gang, E-mail: jungl@bit.edu.cn; Zou, Jian

2017-06-15

Highlights: • Adaptive measurement strategy is used to detect the presence of a magnetic field. • Gaussian Ornstein–Uhlenbeck noise and non-Gaussian noise have been considered. • Weaker magnetic fields may be more easily detected than some stronger ones. - Abstract: By using the adaptive measurement method we study how to detect whether a weak magnetic field is actually present or not under Gaussian noise and non-Gaussian noise. We find that the adaptive measurement method can effectively improve the detection accuracy. For the case of Gaussian noise, we find the stronger the magnetic field strength, the easier for us to detect the magnetic field. Counterintuitively, for non-Gaussian noise, some weaker magnetic fields are more likely to be detected rather than some stronger ones. Finally, we give a reasonable physical interpretation.

An Energy-Efficient Target Tracking Framework in Wireless Sensor Networks

Directory of Open Access Journals (Sweden)

Zhijun Yu

2009-01-01

Full Text Available This study devises and evaluates an energy-efficient distributed collaborative signal and information processing framework for acoustic target tracking in wireless sensor networks. The distributed processing algorithm is based on mobile agent computing paradigm and sequential Bayesian estimation. At each time step, the short detection reports of cluster members will be collected by cluster head, and a sensor node with the highest signal-to-noise ratio (SNR is chosen there as reference node for time difference of arrive (TDOA calculation. During the mobile agent migration, the target state belief is transmitted among nodes and updated using the TDOA measurement of these fusion nodes one by one. The computing and processing burden is evenly distributed in the sensor network. To decrease the wireless communications, we propose to represent the belief by parameterized methods such as Gaussian approximation or Gaussian mixture model approximation. Furthermore, we present an attraction force function to handle the mobile agent migration planning problem, which is a combination of the node residual energy, useful information, and communication cost. Simulation examples demonstrate the estimation effectiveness and energy efficiency of the proposed distributed collaborative target tracking framework.

The universal statistical distributions of the affinity, equilibrium constants, kinetics and specificity in biomolecular recognition.

Directory of Open Access Journals (Sweden)

Xiliang Zheng

2015-04-01

Full Text Available We uncovered the universal statistical laws for the biomolecular recognition/binding process. We quantified the statistical energy landscapes for binding, from which we can characterize the distributions of the binding free energy (affinity, the equilibrium constants, the kinetics and the specificity by exploring the different ligands binding with a particular receptor. The results of the analytical studies are confirmed by the microscopic flexible docking simulations. The distribution of binding affinity is Gaussian around the mean and becomes exponential near the tail. The equilibrium constants of the binding follow a log-normal distribution around the mean and a power law distribution in the tail. The intrinsic specificity for biomolecular recognition measures the degree of discrimination of native versus non-native binding and the optimization of which becomes the maximization of the ratio of the free energy gap between the native state and the average of non-native states versus the roughness measured by the variance of the free energy landscape around its mean. The intrinsic specificity obeys a Gaussian distribution near the mean and an exponential distribution near the tail. Furthermore, the kinetics of binding follows a log-normal distribution near the mean and a power law distribution at the tail. Our study provides new insights into the statistical nature of thermodynamics, kinetics and function from different ligands binding with a specific receptor or equivalently specific ligand binding with different receptors. The elucidation of distributions of the kinetics and free energy has guiding roles in studying biomolecular recognition and function through small-molecule evolution and chemical genetics.

Sufficient condition for a quantum state to be genuinely quantum non-Gaussian

Science.gov (United States)

Happ, L.; Efremov, M. A.; Nha, H.; Schleich, W. P.

2018-02-01

We show that the expectation value of the operator \\hat{{ \\mathcal O }}\\equiv \\exp (-c{\\hat{x}}2)+\\exp (-c{\\hat{p}}2) defined by the position and momentum operators \\hat{x} and \\hat{p} with a positive parameter c can serve as a tool to identify quantum non-Gaussian states, that is states that cannot be represented as a mixture of Gaussian states. Our condition can be readily tested employing a highly efficient homodyne detection which unlike quantum-state tomography requires the measurements of only two orthogonal quadratures. We demonstrate that our method is even able to detect quantum non-Gaussian states with positive–definite Wigner functions. This situation cannot be addressed in terms of the negativity of the phase-space distribution. Moreover, we demonstrate that our condition can characterize quantum non-Gaussianity for the class of superposition states consisting of a vacuum and integer multiples of four photons under more than 50 % signal attenuation.

Super-Gaussian transport theory and the field-generating thermal instability in laser–plasmas

International Nuclear Information System (INIS)

Bissell, J J; Ridgers, C P; Kingham, R J

2013-01-01

Inverse bremsstrahlung (IB) heating is known to distort the electron distribution function in laser–plasmas from a Gaussian towards a super-Gaussian, thereby modifying the equations of classical transport theory (Ridgers et al 2008 Phys. Plasmas 15 092311). Here we explore these modified equations, demonstrating that super-Gaussian effects both suppress traditional transport processes, while simultaneously introducing new effects, such as isothermal (anomalous Nernst) magnetic field advection up gradients in the electron number density n e , which we associate with a novel heat-flow q n ∝∇n e . Suppression of classical phenomena is shown to be most pronounced in the limit of low Hall-parameter χ, in which case the Nernst effect is reduced by a factor of five, the ∇T e × ∇n e field generation mechanism by ∼30% (where T e is the electron temperature), and the diffusive and Righi–Leduc heat-flows by ∼80 and ∼90% respectively. The new isothermal field advection phenomenon and associated density-gradient driven heat-flux q n are checked against kinetic simulation using the Vlasov–Fokker–Planck code impact, and interpreted in relation to the underlying super-Gaussian distribution through simplified kinetic analysis. Given such strong inhibition of transport at low χ, we consider the impact of IB on the seeding and evolution of magnetic fields (in otherwise un-magnetized conditions) by examining the well-known field-generating thermal instability in the light of super-Gaussian transport theory (Tidman and Shanny 1974 Phys. Fluids 12 1207). Estimates based on conditions in an inertial confinement fusion (ICF) hohlraum suggest that super-Gaussian effects can reduce the growth-rate of the instability by ≳80%. This result may be important for ICF experiments, since by increasing the strength of IB heating it would appear possible to inhibit the spontaneous generation of large magnetic fields. (paper)

Super-Gaussian transport theory and the field-generating thermal instability in laser-plasmas

Science.gov (United States)

Bissell, J. J.; Ridgers, C. P.; Kingham, R. J.

2013-02-01

Inverse bremsstrahlung (IB) heating is known to distort the electron distribution function in laser-plasmas from a Gaussian towards a super-Gaussian, thereby modifying the equations of classical transport theory (Ridgers et al 2008 Phys. Plasmas 15 092311). Here we explore these modified equations, demonstrating that super-Gaussian effects both suppress traditional transport processes, while simultaneously introducing new effects, such as isothermal (anomalous Nernst) magnetic field advection up gradients in the electron number density ne, which we associate with a novel heat-flow qn∝∇ne. Suppression of classical phenomena is shown to be most pronounced in the limit of low Hall-parameter χ, in which case the Nernst effect is reduced by a factor of five, the ∇Te × ∇ne field generation mechanism by ˜30% (where Te is the electron temperature), and the diffusive and Righi-Leduc heat-flows by ˜80 and ˜90% respectively. The new isothermal field advection phenomenon and associated density-gradient driven heat-flux qn are checked against kinetic simulation using the Vlasov-Fokker-Planck code impact, and interpreted in relation to the underlying super-Gaussian distribution through simplified kinetic analysis. Given such strong inhibition of transport at low χ, we consider the impact of IB on the seeding and evolution of magnetic fields (in otherwise un-magnetized conditions) by examining the well-known field-generating thermal instability in the light of super-Gaussian transport theory (Tidman and Shanny 1974 Phys. Fluids 12 1207). Estimates based on conditions in an inertial confinement fusion (ICF) hohlraum suggest that super-Gaussian effects can reduce the growth-rate of the instability by ≳80%. This result may be important for ICF experiments, since by increasing the strength of IB heating it would appear possible to inhibit the spontaneous generation of large magnetic fields.

On the insufficiency of arbitrarily precise covariance matrices: non-Gaussian weak-lensing likelihoods

Science.gov (United States)

Sellentin, Elena; Heavens, Alan F.

2018-01-01

We investigate whether a Gaussian likelihood, as routinely assumed in the analysis of cosmological data, is supported by simulated survey data. We define test statistics, based on a novel method that first destroys Gaussian correlations in a data set, and then measures the non-Gaussian correlations that remain. This procedure flags pairs of data points that depend on each other in a non-Gaussian fashion, and thereby identifies where the assumption of a Gaussian likelihood breaks down. Using this diagnosis, we find that non-Gaussian correlations in the CFHTLenS cosmic shear correlation functions are significant. With a simple exclusion of the most contaminated data points, the posterior for s8 is shifted without broadening, but we find no significant reduction in the tension with s8 derived from Planck cosmic microwave background data. However, we also show that the one-point distributions of the correlation statistics are noticeably skewed, such that sound weak-lensing data sets are intrinsically likely to lead to a systematically low lensing amplitude being inferred. The detected non-Gaussianities get larger with increasing angular scale such that for future wide-angle surveys such as Euclid or LSST, with their very small statistical errors, the large-scale modes are expected to be increasingly affected. The shifts in posteriors may then not be negligible and we recommend that these diagnostic tests be run as part of future analyses.

Speech Enhancement by MAP Spectral Amplitude Estimation Using a Super-Gaussian Speech Model

Directory of Open Access Journals (Sweden)

Lotter Thomas

2005-01-01

Full Text Available This contribution presents two spectral amplitude estimators for acoustical background noise suppression based on maximum a posteriori estimation and super-Gaussian statistical modelling of the speech DFT amplitudes. The probability density function of the speech spectral amplitude is modelled with a simple parametric function, which allows a high approximation accuracy for Laplace- or Gamma-distributed real and imaginary parts of the speech DFT coefficients. Also, the statistical model can be adapted to optimally fit the distribution of the speech spectral amplitudes for a specific noise reduction system. Based on the super-Gaussian statistical model, computationally efficient maximum a posteriori speech estimators are derived, which outperform the commonly applied Ephraim-Malah algorithm.

Nonparametric estimation of stochastic differential equations with sparse Gaussian processes.

Science.gov (United States)

García, Constantino A; Otero, Abraham; Félix, Paulo; Presedo, Jesús; Márquez, David G

2017-08-01

The application of stochastic differential equations (SDEs) to the analysis of temporal data has attracted increasing attention, due to their ability to describe complex dynamics with physically interpretable equations. In this paper, we introduce a nonparametric method for estimating the drift and diffusion terms of SDEs from a densely observed discrete time series. The use of Gaussian processes as priors permits working directly in a function-space view and thus the inference takes place directly in this space. To cope with the computational complexity that requires the use of Gaussian processes, a sparse Gaussian process approximation is provided. This approximation permits the efficient computation of predictions for the drift and diffusion terms by using a distribution over a small subset of pseudosamples. The proposed method has been validated using both simulated data and real data from economy and paleoclimatology. The application of the method to real data demonstrates its ability to capture the behavior of complex systems.

ExGUtils: A Python Package for Statistical Analysis With the ex-Gaussian Probability Density

Directory of Open Access Journals (Sweden)

Carmen Moret-Tatay

2018-05-01

Full Text Available The study of reaction times and their underlying cognitive processes is an important field in Psychology. Reaction times are often modeled through the ex-Gaussian distribution, because it provides a good fit to multiple empirical data. The complexity of this distribution makes the use of computational tools an essential element. Therefore, there is a strong need for efficient and versatile computational tools for the research in this area. In this manuscript we discuss some mathematical details of the ex-Gaussian distribution and apply the ExGUtils package, a set of functions and numerical tools, programmed for python, developed for numerical analysis of data involving the ex-Gaussian probability density. In order to validate the package, we present an extensive analysis of fits obtained with it, discuss advantages and differences between the least squares and maximum likelihood methods and quantitatively evaluate the goodness of the obtained fits (which is usually an overlooked point in most literature in the area. The analysis done allows one to identify outliers in the empirical datasets and criteriously determine if there is a need for data trimming and at which points it should be done.

Dynamic heterogeneity and conditional statistics of non-Gaussian temperature fluctuations in turbulent thermal convection

Science.gov (United States)

He, Xiaozhou; Wang, Yin; Tong, Penger

2018-05-01

Non-Gaussian fluctuations with an exponential tail in their probability density function (PDF) are often observed in nonequilibrium steady states (NESSs) and one does not understand why they appear so often. Turbulent Rayleigh-Bénard convection (RBC) is an example of such a NESS, in which the measured PDF P (δ T ) of temperature fluctuations δ T in the central region of the flow has a long exponential tail. Here we show that because of the dynamic heterogeneity in RBC, the exponential PDF is generated by a convolution of a set of dynamics modes conditioned on a constant local thermal dissipation rate ɛ . The conditional PDF G (δ T |ɛ ) of δ T under a constant ɛ is found to be of Gaussian form and its variance σT2 for different values of ɛ follows an exponential distribution. The convolution of the two distribution functions gives rise to the exponential PDF P (δ T ) . This work thus provides a physical mechanism of the observed exponential distribution of δ T in RBC and also sheds light on the origin of non-Gaussian fluctuations in other NESSs.

ExGUtils: A Python Package for Statistical Analysis With the ex-Gaussian Probability Density.

Science.gov (United States)

Moret-Tatay, Carmen; Gamermann, Daniel; Navarro-Pardo, Esperanza; Fernández de Córdoba Castellá, Pedro

2018-01-01

The study of reaction times and their underlying cognitive processes is an important field in Psychology. Reaction times are often modeled through the ex-Gaussian distribution, because it provides a good fit to multiple empirical data. The complexity of this distribution makes the use of computational tools an essential element. Therefore, there is a strong need for efficient and versatile computational tools for the research in this area. In this manuscript we discuss some mathematical details of the ex-Gaussian distribution and apply the ExGUtils package, a set of functions and numerical tools, programmed for python, developed for numerical analysis of data involving the ex-Gaussian probability density. In order to validate the package, we present an extensive analysis of fits obtained with it, discuss advantages and differences between the least squares and maximum likelihood methods and quantitatively evaluate the goodness of the obtained fits (which is usually an overlooked point in most literature in the area). The analysis done allows one to identify outliers in the empirical datasets and criteriously determine if there is a need for data trimming and at which points it should be done.

Research on the Orientation and Application of Distributed Energy Storage in Energy Internet

Science.gov (United States)

Zeng, Ming; Zhou, Pengcheng; Li, Ran; Zhou, Jingjing; Chen, Tao; Li, Zhe

2018-01-01

Energy storage is indispensable resources to achieve a high proportion of new energy power consumption in electric power system. As an important support to energy Internet, energy storage system can achieve a variety of energy integration operation to ensure maximum energy efficiency. In this paper, firstly, the SWOT analysis method is used to express the internal and external advantages and disadvantages of distributed energy storage participating in the energy Internet. Secondly, the function orientation of distributed energy storage in energy Internet is studied, based on which the application modes of distributed energy storage in virtual power plant, community energy storage and auxiliary services are deeply studied. Finally, this paper puts forward the development strategy of distributed energy storage which is suitable for the development of China’s energy Internet, and summarizes and prospects the application of distributed energy storage system.

Primordial Non-Gaussianity in the Large-Scale Structure of the Universe

Directory of Open Access Journals (Sweden)

Vincent Desjacques

2010-01-01

generated the cosmological fluctuations observed today. Any detection of significant non-Gaussianity would thus have profound implications for our understanding of cosmic structure formation. The large-scale mass distribution in the Universe is a sensitive probe of the nature of initial conditions. Recent theoretical progress together with rapid developments in observational techniques will enable us to critically confront predictions of inflationary scenarios and set constraints as competitive as those from the Cosmic Microwave Background. In this paper, we review past and current efforts in the search for primordial non-Gaussianity in the large-scale structure of the Universe.

TYPE Ia SUPERNOVA COLORS AND EJECTA VELOCITIES: HIERARCHICAL BAYESIAN REGRESSION WITH NON-GAUSSIAN DISTRIBUTIONS

International Nuclear Information System (INIS)

Mandel, Kaisey S.; Kirshner, Robert P.; Foley, Ryan J.

2014-01-01

We investigate the statistical dependence of the peak intrinsic colors of Type Ia supernovae (SNe Ia) on their expansion velocities at maximum light, measured from the Si II λ6355 spectral feature. We construct a new hierarchical Bayesian regression model, accounting for the random effects of intrinsic scatter, measurement error, and reddening by host galaxy dust, and implement a Gibbs sampler and deviance information criteria to estimate the correlation. The method is applied to the apparent colors from BVRI light curves and Si II velocity data for 79 nearby SNe Ia. The apparent color distributions of high-velocity (HV) and normal velocity (NV) supernovae exhibit significant discrepancies for B – V and B – R, but not other colors. Hence, they are likely due to intrinsic color differences originating in the B band, rather than dust reddening. The mean intrinsic B – V and B – R color differences between HV and NV groups are 0.06 ± 0.02 and 0.09 ± 0.02 mag, respectively. A linear model finds significant slopes of –0.021 ± 0.006 and –0.030 ± 0.009 mag (10 3 km s –1 ) –1 for intrinsic B – V and B – R colors versus velocity, respectively. Because the ejecta velocity distribution is skewed toward high velocities, these effects imply non-Gaussian intrinsic color distributions with skewness up to +0.3. Accounting for the intrinsic-color-velocity correlation results in corrections to A V extinction estimates as large as –0.12 mag for HV SNe Ia and +0.06 mag for NV events. Velocity measurements from SN Ia spectra have the potential to diminish systematic errors from the confounding of intrinsic colors and dust reddening affecting supernova distances

Breaking Gaussian incompatibility on continuous variable quantum systems

Energy Technology Data Exchange (ETDEWEB)

Heinosaari, Teiko, E-mail: teiko.heinosaari@utu.fi [Turku Centre for Quantum Physics, Department of Physics and Astronomy, University of Turku, FI-20014 Turku (Finland); Kiukas, Jukka, E-mail: jukka.kiukas@aber.ac.uk [Department of Mathematics, Aberystwyth University, Penglais, Aberystwyth, SY23 3BZ (United Kingdom); Schultz, Jussi, E-mail: jussi.schultz@gmail.com [Turku Centre for Quantum Physics, Department of Physics and Astronomy, University of Turku, FI-20014 Turku (Finland); Dipartimento di Matematica, Politecnico di Milano, Piazza Leonardo da Vinci 32, I-20133 Milano (Italy)

2015-08-15

We characterise Gaussian quantum channels that are Gaussian incompatibility breaking, that is, transform every set of Gaussian measurements into a set obtainable from a joint Gaussian observable via Gaussian postprocessing. Such channels represent local noise which renders measurements useless for Gaussian EPR-steering, providing the appropriate generalisation of entanglement breaking channels for this scenario. Understanding the structure of Gaussian incompatibility breaking channels contributes to the resource theory of noisy continuous variable quantum information protocols.

Continuous-variable entanglement distillation of non-Gaussian mixed states

International Nuclear Information System (INIS)

Dong Ruifang; Lassen, Mikael; Heersink, Joel; Marquardt, Christoph; Leuchs, Gerd; Filip, Radim; Andersen, Ulrik L.

2010-01-01

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

Poisson–Gaussian Noise Analysis and Estimation for Low-Dose X-ray Images in the NSCT Domain

Science.gov (United States)

Lee, Sangyoon; Lee, Min Seok; Kang, Moon Gi

2018-01-01

The noise distribution of images obtained by X-ray sensors in low-dosage situations can be analyzed using the Poisson and Gaussian mixture model. Multiscale conversion is one of the most popular noise reduction methods used in recent years. Estimation of the noise distribution of each subband in the multiscale domain is the most important factor in performing noise reduction, with non-subsampled contourlet transform (NSCT) representing an effective method for scale and direction decomposition. In this study, we use artificially generated noise to analyze and estimate the Poisson–Gaussian noise of low-dose X-ray images in the NSCT domain. The noise distribution of the subband coefficients is analyzed using the noiseless low-band coefficients and the variance of the noisy subband coefficients. The noise-after-transform also follows a Poisson–Gaussian distribution, and the relationship between the noise parameters of the subband and the full-band image is identified. We then analyze noise of actual images to validate the theoretical analysis. Comparison of the proposed noise estimation method with an existing noise reduction method confirms that the proposed method outperforms traditional methods. PMID:29596335

Poisson-Gaussian Noise Analysis and Estimation for Low-Dose X-ray Images in the NSCT Domain.

Science.gov (United States)

Lee, Sangyoon; Lee, Min Seok; Kang, Moon Gi

2018-03-29

The noise distribution of images obtained by X-ray sensors in low-dosage situations can be analyzed using the Poisson and Gaussian mixture model. Multiscale conversion is one of the most popular noise reduction methods used in recent years. Estimation of the noise distribution of each subband in the multiscale domain is the most important factor in performing noise reduction, with non-subsampled contourlet transform (NSCT) representing an effective method for scale and direction decomposition. In this study, we use artificially generated noise to analyze and estimate the Poisson-Gaussian noise of low-dose X-ray images in the NSCT domain. The noise distribution of the subband coefficients is analyzed using the noiseless low-band coefficients and the variance of the noisy subband coefficients. The noise-after-transform also follows a Poisson-Gaussian distribution, and the relationship between the noise parameters of the subband and the full-band image is identified. We then analyze noise of actual images to validate the theoretical analysis. Comparison of the proposed noise estimation method with an existing noise reduction method confirms that the proposed method outperforms traditional methods.

Propagation and spatiotemporal coupling characteristics of ultra-short Gaussian vortex pulse

Science.gov (United States)

Nie, Jianye; Liu, Guodong; Zhang, Rongzhu

2018-05-01

Based on Collins diffraction integral formula, the propagation equation of ultra-short Gaussian vortex pulse beam has been derived. Using the equation, the intensity distribution variations of vortex pulse in the propagation process are calculated. Specially, the spatiotemporal coupling characteristics of ultra-short vortex beams are discussed in detail. The results show that some key parameters, such as transverse distance, transmission distance, pulse width and topological charge number will influence the spatiotemporal coupling characteristics significantly. With the increasing of transverse distance, the waveforms of the pulses distort obviously. And when transmission distance is far than 50 mm, the distribution curve of transverse intensity gradually changes into a Gaussian type. In addition, initial pulse width will affect the distribution of light field, however, when initial pulse width is larger than 3 fs, the spatiotemporal coupling effect will be insignificant. Topological charge number does not affect the time delay characteristics, since with the increasing of topological charge number, the waveform of the pulse distorts gradually but the time delay does not occur.

Statistics of peaks of Gaussian random fields

International Nuclear Information System (INIS)

Bardeen, J.M.; Bond, J.R.; Kaiser, N.; Szalay, A.S.; Stanford Univ., CA; California Univ., Berkeley; Cambridge Univ., England; Fermi National Accelerator Lab., Batavia, IL)

1986-01-01

A set of new mathematical results on the theory of Gaussian random fields is presented, and the application of such calculations in cosmology to treat questions of structure formation from small-amplitude initial density fluctuations is addressed. The point process equation is discussed, giving the general formula for the average number density of peaks. The problem of the proper conditional probability constraints appropriate to maxima are examined using a one-dimensional illustration. The average density of maxima of a general three-dimensional Gaussian field is calculated as a function of heights of the maxima, and the average density of upcrossing points on density contour surfaces is computed. The number density of peaks subject to the constraint that the large-scale density field be fixed is determined and used to discuss the segregation of high peaks from the underlying mass distribution. The machinery to calculate n-point peak-peak correlation functions is determined, as are the shapes of the profiles about maxima. 67 references

Probabilistic wind power forecasting with online model selection and warped gaussian process

International Nuclear Information System (INIS)

Kou, Peng; Liang, Deliang; Gao, Feng; Gao, Lin

2014-01-01

Highlights: • A new online ensemble model for the probabilistic wind power forecasting. • Quantifying the non-Gaussian uncertainties in wind power. • Online model selection that tracks the time-varying characteristic of wind generation. • Dynamically altering the input features. • Recursive update of base models. - Abstract: Based on the online model selection and the warped Gaussian process (WGP), this paper presents an ensemble model for the probabilistic wind power forecasting. This model provides the non-Gaussian predictive distributions, which quantify the non-Gaussian uncertainties associated with wind power. In order to follow the time-varying characteristics of wind generation, multiple time dependent base forecasting models and an online model selection strategy are established, thus adaptively selecting the most probable base model for each prediction. WGP is employed as the base model, which handles the non-Gaussian uncertainties in wind power series. Furthermore, a regime switch strategy is designed to modify the input feature set dynamically, thereby enhancing the adaptiveness of the model. In an online learning framework, the base models should also be time adaptive. To achieve this, a recursive algorithm is introduced, thus permitting the online updating of WGP base models. The proposed model has been tested on the actual data collected from both single and aggregated wind farms

Learning non-Gaussian Time Series using the Box-Cox Gaussian Process

OpenAIRE

Rios, Gonzalo; Tobar, Felipe

2018-01-01

Gaussian processes (GPs) are Bayesian nonparametric generative models that provide interpretability of hyperparameters, admit closed-form expressions for training and inference, and are able to accurately represent uncertainty. To model general non-Gaussian data with complex correlation structure, GPs can be paired with an expressive covariance kernel and then fed into a nonlinear transformation (or warping). However, overparametrising the kernel and the warping is known to, respectively, hin...

Determination of Cross-Sectional Area of Focused Picosecond Gaussian Laser Beam

Science.gov (United States)

Ledesma, Rodolfo; Fitz-Gerald, James; Palmieri, Frank; Connell, John

2018-01-01

Measurement of the waist diameter of a focused Gaussian-beam at the 1/e(sup 2) intensity, also referred to as spot size, is key to determining the fluence in laser processing experiments. Spot size measurements are also helpful to calculate the threshold energy and threshold fluence of a given material. This work reports an application of a conventional method, by analyzing single laser ablated spots for different laser pulse energies, to determine the cross-sectional area of a focused Gaussian-beam, which has a nominal pulse width of approx. 10 ps. Polished tungsten was used as the target material, due to its low surface roughness and low ablation threshold, to measure the beam waist diameter. From the ablative spot measurements, the ablation threshold fluence of the tungsten substrate was also calculated.

Protection of Distribution Systems with Distributed Energy Resources

DEFF Research Database (Denmark)

Bak-Jensen, Birgitte; Browne, Matthew; Calone, Roberto

of 17 months of work of the Joint Working Group B5/C6.26/CIRED “Protection of Distribution Systems with Distributed Energy Resources”. The working group used the CIGRE report TB421 “The impact of Renewable Energy Sources and Distributed Generation on Substation Protection and Automation”, published...... by WG B5.34 as the entry document for the work on this report. In doing so, the group aligned the content and the scope of this report, the network structures considered, possible islanding, standardized communication and adaptive protection, interface protection, connection schemes and protection...... are listed (chapter 3). The first main part of the report starts with a summary of the backgrounds on DER and current practices in protection at the distribution level (chapter 4). This chapter contains an analysis of CIGRE TB421, protection relevant characteristics of DER, a review of current practices...

Non-Gaussian halo assembly bias

International Nuclear Information System (INIS)

Reid, Beth A.; Verde, Licia; Dolag, Klaus; Matarrese, Sabino; Moscardini, Lauro

2010-01-01

The strong dependence of the large-scale dark matter halo bias on the (local) non-Gaussianity parameter, f NL , offers a promising avenue towards constraining primordial non-Gaussianity with large-scale structure surveys. In this paper, we present the first detection of the dependence of the non-Gaussian halo bias on halo formation history using N-body simulations. We also present an analytic derivation of the expected signal based on the extended Press-Schechter formalism. In excellent agreement with our analytic prediction, we find that the halo formation history-dependent contribution to the non-Gaussian halo bias (which we call non-Gaussian halo assembly bias) can be factorized in a form approximately independent of redshift and halo mass. The correction to the non-Gaussian halo bias due to the halo formation history can be as large as 100%, with a suppression of the signal for recently formed halos and enhancement for old halos. This could in principle be a problem for realistic galaxy surveys if observational selection effects were to pick galaxies occupying only recently formed halos. Current semi-analytic galaxy formation models, for example, imply an enhancement in the expected signal of ∼ 23% and ∼ 48% for galaxies at z = 1 selected by stellar mass and star formation rate, respectively

Electricity End Uses, Energy Efficiency, and Distributed Energy Resources Baseline

Energy Technology Data Exchange (ETDEWEB)

Schwartz, Lisa [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Wei, Max [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Morrow, William [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Deason, Jeff [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Schiller, Steven R. [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Leventis, Greg [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Smith, Sarah [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Leow, Woei Ling [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Levin, Todd [Argonne National Lab. (ANL), Argonne, IL (United States); Plotkin, Steven [Argonne National Lab. (ANL), Argonne, IL (United States); Zhou, Yan [Oak Ridge Inst. for Science and Education (ORISE), Oak Ridge, TN (United States)

2017-01-01

This report was developed by a team of analysts at Lawrence Berkeley National Laboratory, with Argonne National Laboratory contributing the transportation section, and is a DOE EPSA product and part of a series of “baseline” reports intended to inform the second installment of the Quadrennial Energy Review (QER 1.2). QER 1.2 provides a comprehensive review of the nation’s electricity system and cover the current state and key trends related to the electricity system, including generation, transmission, distribution, grid operations and planning, and end use. The baseline reports provide an overview of elements of the electricity system. This report focuses on end uses, electricity consumption, electric energy efficiency, distributed energy resources (DERs) (such as demand response, distributed generation, and distributed storage), and evaluation, measurement, and verification (EM&V) methods for energy efficiency and DERs.

A User-Adaptive Algorithm for Activity Recognition Based on K-Means Clustering, Local Outlier Factor, and Multivariate Gaussian Distribution

Directory of Open Access Journals (Sweden)

Shizhen Zhao

2018-06-01

Full Text Available Mobile activity recognition is significant to the development of human-centric pervasive applications including elderly care, personalized recommendations, etc. Nevertheless, the distribution of inertial sensor data can be influenced to a great extent by varying users. This means that the performance of an activity recognition classifier trained by one user’s dataset will degenerate when transferred to others. In this study, we focus on building a personalized classifier to detect four categories of human activities: light intensity activity, moderate intensity activity, vigorous intensity activity, and fall. In order to solve the problem caused by different distributions of inertial sensor signals, a user-adaptive algorithm based on K-Means clustering, local outlier factor (LOF, and multivariate Gaussian distribution (MGD is proposed. To automatically cluster and annotate a specific user’s activity data, an improved K-Means algorithm with a novel initialization method is designed. By quantifying the samples’ informative degree in a labeled individual dataset, the most profitable samples can be selected for activity recognition model adaption. Through experiments, we conclude that our proposed models can adapt to new users with good recognition performance.

Energy efficiency optimization in distribution transformers considering Spanish distribution regulation policy

International Nuclear Information System (INIS)

Pezzini, Paola; Gomis-Bellmunt, Oriol; Frau-Valenti, Joan; Sudria-Andreu, Antoni

2010-01-01

In transmission and distribution systems, the high number of installed transformers, a loss source in networks, suggests a good potential for energy savings. This paper presents how the Spanish Distribution regulation policy, Royal Decree 222/2008, affects the overall energy efficiency in distribution transformers. The objective of a utility is the maximization of the benefit, and in case of failures, to install a chosen transformer in order to maximize the profit. Here, a novel method to optimize energy efficiency, considering the constraints set by the Spanish Distribution regulation policy, is presented; its aim is to achieve the objectives of the utility when installing new transformers. The overall energy efficiency increase is a clear result that can help in meeting the requirements of European environmental plans, such as the '20-20-20' action plan.

Area of isodensity contours in Gaussian and non-Gaussian fields

International Nuclear Information System (INIS)

Ryden, B.S.

1988-01-01

The area of isodensity contours in a smoothed density field can be measured by the contour-crossing statistic N1, the number of times per unit length that a line drawn through the density field pierces an isodensity contour. The contour-crossing statistic distinguishes between Gaussian and non-Gaussian fields and provides a measure of the effective slope of the power spectrum. The statistic is easy to apply and can be used on pencil beams and slices as well as on a three-dimensional field. 10 references

Energy Efficiency in Grocery Distribution in Denmark

DEFF Research Database (Denmark)

Jørgensen, Kaj

1997-01-01

Evaluation of the development of the energy efficiency of grocery distribution from 1960 to the present in Denmark, covering both the distribution to the shops and the shopping transport (distribution from shops to individual homes)......Evaluation of the development of the energy efficiency of grocery distribution from 1960 to the present in Denmark, covering both the distribution to the shops and the shopping transport (distribution from shops to individual homes)...

Theoretical analysis of non-Gaussian heterogeneity effects on subsurface flow and transport

Science.gov (United States)

Riva, Monica; Guadagnini, Alberto; Neuman, Shlomo P.

2017-04-01

Much of the stochastic groundwater literature is devoted to the analysis of flow and transport in Gaussian or multi-Gaussian log hydraulic conductivity (or transmissivity) fields, Y(x)=ln\\func K(x) (x being a position vector), characterized by one or (less frequently) a multiplicity of spatial correlation scales. Yet Y and many other variables and their (spatial or temporal) increments, ΔY, are known to be generally non-Gaussian. One common manifestation of non-Gaussianity is that whereas frequency distributions of Y often exhibit mild peaks and light tails, those of increments ΔY are generally symmetric with peaks that grow sharper, and tails that become heavier, as separation scale or lag between pairs of Y values decreases. A statistical model that captures these disparate, scale-dependent distributions of Y and ΔY in a unified and consistent manner has been recently proposed by us. This new "generalized sub-Gaussian (GSG)" model has the form Y(x)=U(x)G(x) where G(x) is (generally, but not necessarily) a multiscale Gaussian random field and U(x) is a nonnegative subordinator independent of G. The purpose of this paper is to explore analytically, in an elementary manner, lead-order effects that non-Gaussian heterogeneity described by the GSG model have on the stochastic description of flow and transport. Recognizing that perturbation expansion of hydraulic conductivity K=eY diverges when Y is sub-Gaussian, we render the expansion convergent by truncating Y's domain of definition. We then demonstrate theoretically and illustrate by way of numerical examples that, as the domain of truncation expands, (a) the variance of truncated Y (denoted by Yt) approaches that of Y and (b) the pdf (and thereby moments) of Yt increments approach those of Y increments and, as a consequence, the variogram of Yt approaches that of Y. This in turn guarantees that perturbing Kt=etY to second order in σYt (the standard deviation of Yt) yields results which approach those we obtain

From plane waves to local Gaussians for the simulation of correlated periodic systems

International Nuclear Information System (INIS)

Booth, George H.; Tsatsoulis, Theodoros; Grüneis, Andreas; Chan, Garnet Kin-Lic

2016-01-01

We present a simple, robust, and black-box approach to the implementation and use of local, periodic, atom-centered Gaussian basis functions within a plane wave code, in a computationally efficient manner. The procedure outlined is based on the representation of the Gaussians within a finite bandwidth by their underlying plane wave coefficients. The core region is handled within the projected augment wave framework, by pseudizing the Gaussian functions within a cutoff radius around each nucleus, smoothing the functions so that they are faithfully represented by a plane wave basis with only moderate kinetic energy cutoff. To mitigate the effects of the basis set superposition error and incompleteness at the mean-field level introduced by the Gaussian basis, we also propose a hybrid approach, whereby the complete occupied space is first converged within a large plane wave basis, and the Gaussian basis used to construct a complementary virtual space for the application of correlated methods. We demonstrate that these pseudized Gaussians yield compact and systematically improvable spaces with an accuracy comparable to their non-pseudized Gaussian counterparts. A key advantage of the described method is its ability to efficiently capture and describe electronic correlation effects of weakly bound and low-dimensional systems, where plane waves are not sufficiently compact or able to be truncated without unphysical artifacts. We investigate the accuracy of the pseudized Gaussians for the water dimer interaction, neon solid, and water adsorption on a LiH surface, at the level of second-order Møller–Plesset perturbation theory.

From plane waves to local Gaussians for the simulation of correlated periodic systems

Energy Technology Data Exchange (ETDEWEB)

Booth, George H., E-mail: george.booth@kcl.ac.uk [Department of Physics, King’s College London, Strand, London WC2R 2LS (United Kingdom); Tsatsoulis, Theodoros; Grüneis, Andreas, E-mail: a.grueneis@fkf.mpg.de [Max Planck Institute for Solid State Research, Heisenbergstraße 1, 70569 Stuttgart (Germany); Chan, Garnet Kin-Lic [Frick Laboratory, Department of Chemistry, Princeton University, Princeton, New Jersey 08544 (United States)

2016-08-28

We present a simple, robust, and black-box approach to the implementation and use of local, periodic, atom-centered Gaussian basis functions within a plane wave code, in a computationally efficient manner. The procedure outlined is based on the representation of the Gaussians within a finite bandwidth by their underlying plane wave coefficients. The core region is handled within the projected augment wave framework, by pseudizing the Gaussian functions within a cutoff radius around each nucleus, smoothing the functions so that they are faithfully represented by a plane wave basis with only moderate kinetic energy cutoff. To mitigate the effects of the basis set superposition error and incompleteness at the mean-field level introduced by the Gaussian basis, we also propose a hybrid approach, whereby the complete occupied space is first converged within a large plane wave basis, and the Gaussian basis used to construct a complementary virtual space for the application of correlated methods. We demonstrate that these pseudized Gaussians yield compact and systematically improvable spaces with an accuracy comparable to their non-pseudized Gaussian counterparts. A key advantage of the described method is its ability to efficiently capture and describe electronic correlation effects of weakly bound and low-dimensional systems, where plane waves are not sufficiently compact or able to be truncated without unphysical artifacts. We investigate the accuracy of the pseudized Gaussians for the water dimer interaction, neon solid, and water adsorption on a LiH surface, at the level of second-order Møller–Plesset perturbation theory.

Distributed Wind Energy in Idaho

Energy Technology Data Exchange (ETDEWEB)

Gardner, John [Boise State Univ., ID (United States); Johnson, Kathryn [Colorado School of Mines, Golden, CO (United States); Haynes, Todd [Boise State Univ., ID (United States); Seifert, Gary [Idaho National Lab. (INL), Idaho Falls, ID (United States)

2009-01-31

This project is a research and development program aimed at furthering distributed wind technology. In particular, this project addresses some of the barriers to distributed wind energy utilization in Idaho.

Charge state distributions for heavy ions in carbon stripper foils

International Nuclear Information System (INIS)

McMahan, M.A.; Lebed, R.F.; Feinberg, B.

1989-03-01

We have extended the database of measured charge state distributions available in the literature through measurements at the SuperHILAC using carbon stripper foils in the energy range 1.2--8.5 MeV/u. Modifying a semi-empirical model to include the effect of electronic shells, we are able to correctly predict the mean charge state to within 1/2 a charge state for 6≤Z≤92 and energies from 30 keV/u to 16 MeV/u. We have determined parameters for the widths of the distributions for each electronic shell. For distributions lying across a shell boundary, we join the two Gaussians of different widths to get an asymmetric distribution. 18 refs., 4 figs., 2 tabs

Energy efficiency optimization in distribution transformers considering Spanish distribution regulation policy

Energy Technology Data Exchange (ETDEWEB)

Pezzini, Paola [Centre d' Innovacio en Convertidors Estatics i Accionaments (CITCEA-UPC), E.T.S. Enginyeria Industrial Barcelona, Universitat Politecnica Catalunya, Diagonal, 647, Pl. 2, 08028 Barcelona (Spain); Gomis-Bellmunt, Oriol; Sudria-Andreu, Antoni [Centre d' Innovacio en Convertidors Estatics i Accionaments (CITCEA-UPC), E.T.S. Enginyeria Industrial Barcelona, Universitat Politecnica Catalunya, Diagonal, 647, Pl. 2, 08028 Barcelona (Spain); IREC Catalonia Institute for Energy Research, Josep Pla, B2, Pl. Baixa, 08019 Barcelona (Spain); Frau-Valenti, Joan [ENDESA, Carrer Joan Maragall, 16 07006 Palma (Spain)

2010-12-15

In transmission and distribution systems, the high number of installed transformers, a loss source in networks, suggests a good potential for energy savings. This paper presents how the Spanish Distribution regulation policy, Royal Decree 222/2008, affects the overall energy efficiency in distribution transformers. The objective of a utility is the maximization of the benefit, and in case of failures, to install a chosen transformer in order to maximize the profit. Here, a novel method to optimize energy efficiency, considering the constraints set by the Spanish Distribution regulation policy, is presented; its aim is to achieve the objectives of the utility when installing new transformers. The overall energy efficiency increase is a clear result that can help in meeting the requirements of European environmental plans, such as the '20-20-20' action plan. (author)

On the relationship between Gaussian stochastic blockmodels and label propagation algorithms

International Nuclear Information System (INIS)

Zhang, Junhao; Hu, Junfeng; Chen, Tongfei

2015-01-01

The problem of community detection has received great attention in recent years. Many methods have been proposed to discover communities in networks. In this paper, we propose a Gaussian stochastic blockmodel that uses Gaussian distributions to fit weight of edges in networks for non-overlapping community detection. The maximum likelihood estimation of this model has the same objective function as general label propagation with node preference. The node preference of a specific vertex turns out to be a value proportional to the intra-community eigenvector centrality (the corresponding entry in principal eigenvector of the adjacency matrix of the subgraph inside that vertex's community) under maximum likelihood estimation. Additionally, the maximum likelihood estimation of a constrained version of our model is highly related to another extension of the label propagation algorithm, namely, the label propagation algorithm under constraint. Experiments show that the proposed Gaussian stochastic blockmodel performs well on various benchmark networks. (paper)

Making the most of distributed energy

International Nuclear Information System (INIS)

Malkamaeki, M.

2004-01-01

Distributed energy production is on the threshold of a new area, and offers a growing number of options for meeting energy needs that cannot be met effectively by larger, base load-type infrastructure. Distributed energy generation can offer a more cost- effective approach, depending on things such as location, load requirements, and fuel availability. It can also make it possible to generate energy at times when grid power is not available or is likely to be overloaded, and in locations not covered by an existing grid net-work. Perhaps most interesting from a technological point of view is the fact that distributed power opens up the opportunity to use fuels that have not been utilised up until now, for a variety of reasons

Gas-Fired Distributed Energy Resource Technology Characterizations

Energy Technology Data Exchange (ETDEWEB)

Goldstein, L.; Hedman, B.; Knowles, D.; Freedman, S. I.; Woods, R.; Schweizer, T.

2003-11-01

The U. S. Department of Energy (DOE) Office of Energy Efficiency and Renewable Energy (EERE) is directing substantial programs in the development and encouragement of new energy technologies. Among them are renewable energy and distributed energy resource technologies. As part of its ongoing effort to document the status and potential of these technologies, DOE EERE directed the National Renewable Energy Laboratory to lead an effort to develop and publish Distributed Energy Technology Characterizations (TCs) that would provide both the department and energy community with a consistent and objective set of cost and performance data in prospective electric-power generation applications in the United States. Toward that goal, DOE/EERE - joined by the Electric Power Research Institute (EPRI) - published the Renewable Energy Technology Characterizations in December 1997.As a follow-up, DOE EERE - joined by the Gas Research Institute - is now publishing this document, Gas-Fired Distributed Energy Resource Technology Characterizations.

Crucial role of sidewalls in velocity distributions in quasi-two-dimensional granular gases

NARCIS (Netherlands)

van Zon, J.S.; Kreft, J.; Goldman, D.L.; Miracle, D.; Swift, J. B.; Swinney, H. L.

2004-01-01

The significance of sidewalls which yield velocity distributions with non-Gaussian tails and a peak near zero velocity in quasi-two-dimensional granular gases, was investigated. It was observed that the particles gained energy only through collisions with the bottom of the container, which was not

Modelling distributed energy resources in energy service networks

CERN Document Server

Acha, Salvador

2013-01-01

Focuses on modelling two key infrastructures (natural gas and electrical) in urban energy systems with embedded technologies (cogeneration and electric vehicles) to optimise the operation of natural gas and electrical infrastructures under the presence of distributed energy resources

Shell model test of the Porter-Thomas distribution

International Nuclear Information System (INIS)

Grimes, S.M.; Bloom, S.D.

1981-01-01

Eigenvectors have been calculated for the A=18, 19, 20, 21, and 26 nuclei in an sd shell basis. The decomposition of these states into their shell model components shows, in agreement with other recent work, that this distribution is not a single Gaussian. We find that the largest amplitudes are distributed approximately in a Gaussian fashion. Thus, many experimental measurements should be consistent with the Porter-Thomas predictions. We argue that the non-Gaussian form of the complete distribution can be simply related to the structure of the Hamiltonian

Implementation and application of the gaussian decomposition software for NaI gamma-ray spectrometry data

International Nuclear Information System (INIS)

Zeng Lihui; Wang Nanping; Tian Gui

2012-01-01

In order to extract the information of peaks in different energy from the data of overlapping peaks in environmental gamma spectrometer, a spectrum data Gaussian decomposition software was designed based on least-square Gaussian fitting method. The interface of this software is friendly, it can complete the decomposition of overlapping peaks in gamma spectrometer quickly by the way of man-machines interactive. The result of field measured data decomposed by this software indicates that the Gaussian decomposition software can efficiently extract 137 Cs spectra from over lapping peaks, which has significance to estimate the human nuclide contamination in the environment. (authors)

Implementation and application of the gaussian decomposition software for NaI gamma-ray spectrometry data

International Nuclear Information System (INIS)

Zeng Lihui; Wang Nanping Tian Gui

2011-01-01

In order to extract the information of peaks in different energy from the data of overlapping peaks in environmental gamma spectrometer, a spectrum data Gaussian decomposition soft is designed based on least- square Gaussian fitting method. The interface of this software is friendly, it can complete the decomposition of overlapping peaks in gamma spectrometer quickly by the way of man-machines interactive. The result that applied gamma spectrometry to data analysis in the field measurement indicates that the Gaussian decomposition soft can efficiently extract 137 Cs from overlapping peaks which has significance to assess the human nuclide contamination of environment. (authors)

Hawai‘i Distributed Energy Resource Technologies for Energy Security

Energy Technology Data Exchange (ETDEWEB)

None, None

2012-09-30

HNEI has conducted research to address a number of issues important to move Hawai‘i to greater use of intermittent renewable and distributed energy resource (DER) technologies in order to facilitate greater use of Hawai‘i's indigenous renewable energy resources. Efforts have been concentrated on the Islands of Hawai‘i, Maui, and O‘ahu, focusing in three areas of endeavor: 1) Energy Modeling and Scenario Analysis (previously called Energy Road mapping); 2) Research, Development, and Validation of Renewable DER and Microgrid Technologies; and 3) Analysis and Policy. These efforts focused on analysis of the island energy systems and development of specific candidate technologies for future insertion into an integrated energy system, which would lead to a more robust transmission and distribution system in the state of Hawai‘i and eventually elsewhere in the nation.

Damped least square based genetic algorithm with Gaussian distribution of damping factor for singularity-robust inverse kinematics

International Nuclear Information System (INIS)

Phuoc, Le Minh; Lee, Suk Han; Kim, Hun Mo; Martinet, Philippe

2008-01-01

Robot inverse kinematics based on Jacobian inversion encounters critical issues of kinematic singularities. In this paper, several techniques based on damped least squares are proposed to lead robot pass through kinematic singularities without excessive joint velocities. Unlike other work in which the same damping factor is used for all singular vectors, this paper proposes a different damping coefficient for each singular vector based on corresponding singular value of the Jacobian. Moreover, a continuous distribution of damping factor following Gaussian function guarantees the continuous in joint velocities. A genetic algorithm is utilized to search for the best maximum damping factor and singular region, which used to require ad hoc searching in other works. As a result, end effector tracking error, which is inherited from damped least squares by introducing damping factors, is minimized. The effectiveness of our approach is compared with other methods in both non-redundant robot and redundant robot

Damped least square based genetic algorithm with Gaussian distribution of damping factor for singularity-robust inverse kinematics

Energy Technology Data Exchange (ETDEWEB)

Phuoc, Le Minh; Lee, Suk Han; Kim, Hun Mo [Sungkyunkwan University, Suwon (Korea, Republic of); Martinet, Philippe [Blaise Pascal University, Clermont-Ferrand Cedex (France)

2008-07-15

Robot inverse kinematics based on Jacobian inversion encounters critical issues of kinematic singularities. In this paper, several techniques based on damped least squares are proposed to lead robot pass through kinematic singularities without excessive joint velocities. Unlike other work in which the same damping factor is used for all singular vectors, this paper proposes a different damping coefficient for each singular vector based on corresponding singular value of the Jacobian. Moreover, a continuous distribution of damping factor following Gaussian function guarantees the continuous in joint velocities. A genetic algorithm is utilized to search for the best maximum damping factor and singular region, which used to require ad hoc searching in other works. As a result, end effector tracking error, which is inherited from damped least squares by introducing damping factors, is minimized. The effectiveness of our approach is compared with other methods in both non-redundant robot and redundant robot

Analytic matrix elements with shifted correlated Gaussians

DEFF Research Database (Denmark)

Fedorov, D. V.

2017-01-01

Matrix elements between shifted correlated Gaussians of various potentials with several form-factors are calculated analytically. Analytic matrix elements are of importance for the correlated Gaussian method in quantum few-body physics.......Matrix elements between shifted correlated Gaussians of various potentials with several form-factors are calculated analytically. Analytic matrix elements are of importance for the correlated Gaussian method in quantum few-body physics....

Semiparametric inference on the fractal index of Gaussian and conditionally Gaussian time series data

DEFF Research Database (Denmark)

Bennedsen, Mikkel

Using theory on (conditionally) Gaussian processes with stationary increments developed in Barndorff-Nielsen et al. (2009, 2011), this paper presents a general semiparametric approach to conducting inference on the fractal index, α, of a time series. Our setup encompasses a large class of Gaussian...

Distributions of Conductance and Shot Noise and Associated Phase Transitions

International Nuclear Information System (INIS)

Vivo, Pierpaolo; Majumdar, Satya N.; Bohigas, Oriol

2008-01-01

For a chaotic cavity with two identical leads each supporting N channels, we compute analytically, for large N, the full distribution of the conductance and the shot noise power and show that in both cases there is a central Gaussian region flanked on both sides by non-Gaussian tails. The distribution is weakly singular at the junction of Gaussian and non-Gaussian regimes, a direct consequence of two phase transitions in an associated Coulomb gas problem

Probabilistic analysis and fatigue damage assessment of offshore mooring system due to non-Gaussian bimodal tension processes

Science.gov (United States)

Chang, Anteng; Li, Huajun; Wang, Shuqing; Du, Junfeng

2017-08-01

Both wave-frequency (WF) and low-frequency (LF) components of mooring tension are in principle non-Gaussian due to nonlinearities in the dynamic system. This paper conducts a comprehensive investigation of applicable probability density functions (PDFs) of mooring tension amplitudes used to assess mooring-line fatigue damage via the spectral method. Short-term statistical characteristics of mooring-line tension responses are firstly investigated, in which the discrepancy arising from Gaussian approximation is revealed by comparing kurtosis and skewness coefficients. Several distribution functions based on present analytical spectral methods are selected to express the statistical distribution of the mooring-line tension amplitudes. Results indicate that the Gamma-type distribution and a linear combination of Dirlik and Tovo-Benasciutti formulas are suitable for separate WF and LF mooring tension components. A novel parametric method based on nonlinear transformations and stochastic optimization is then proposed to increase the effectiveness of mooring-line fatigue assessment due to non-Gaussian bimodal tension responses. Using time domain simulation as a benchmark, its accuracy is further validated using a numerical case study of a moored semi-submersible platform.

Distributed Energy Planning for Climate Resilience

Energy Technology Data Exchange (ETDEWEB)

Stout, Sherry R [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Hotchkiss, Elizabeth L [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Day, Megan H [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Lee, Nathan [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Holm, Alison [National Renewable Energy Laboratory (NREL), Golden, CO (United States)

2018-05-01

At various levels of government across the United States and globally climate resilient solutions are being adopted and implemented. Solutions vary based on predicted hazards, community context, priorities, complexity, and available resources. Lessons are being learned through the implementation process, which can be replicated regardless of level or type of government entity carrying out the resiliency planning. Through a number of analyses and technical support across the world, NREL has learned key lessons related to resilience planning associated with power generation and water distribution. Distributed energy generation is a large factor in building resilience with clean energy technologies and solutions. The technical and policy solutions associated with distributed energy implementation for resilience fall into a few major categories, including spatial diversification, microgrids, water-energy nexus, policy, and redundancy.

Entanglement in Gaussian matrix-product states

International Nuclear Information System (INIS)

Adesso, Gerardo; Ericsson, Marie

2006-01-01

Gaussian matrix-product states are obtained as the outputs of projection operations from an ancillary space of M infinitely entangled bonds connecting neighboring sites, applied at each of N sites of a harmonic chain. Replacing the projections by associated Gaussian states, the building blocks, we show that the entanglement range in translationally invariant Gaussian matrix-product states depends on how entangled the building blocks are. In particular, infinite entanglement in the building blocks produces fully symmetric Gaussian states with maximum entanglement range. From their peculiar properties of entanglement sharing, a basic difference with spin chains is revealed: Gaussian matrix-product states can possess unlimited, long-range entanglement even with minimum number of ancillary bonds (M=1). Finally we discuss how these states can be experimentally engineered from N copies of a three-mode building block and N two-mode finitely squeezed states

Continuous variable tangle, monogamy inequality, and entanglement sharing in Gaussian states of continuous variable systems

International Nuclear Information System (INIS)

Adesso, Gerardo; Illuminati, Fabrizio

2006-01-01

For continuous-variable (CV) systems, we introduce a measure of entanglement, the CV tangle (contangle), with the purpose of quantifying the distributed (shared) entanglement in multimode, multipartite Gaussian states. This is achieved by a proper convex-roof extension of the squared logarithmic negativity. We prove that the contangle satisfies the Coffman-Kundu-Wootters monogamy inequality in all three-mode Gaussian states, and in all fully symmetric N-mode Gaussian states, for arbitrary N. For three-mode pure states, we prove that the residual entanglement is a genuine tripartite entanglement monotone under Gaussian local operations and classical communication. We show that pure, symmetric three-mode Gaussian states allow a promiscuous entanglement sharing, having both maximum tripartite residual entanglement and maximum couplewise entanglement between any pair of modes. These states are thus simultaneous CV analogues of both the GHZ and the W states of three qubits: in CV systems monogamy does not prevent promiscuity, and the inequivalence between different classes of maximally entangled states, holding for systems of three or more qubits, is removed

Continuous variable tangle, monogamy inequality, and entanglement sharing in Gaussian states of continuous variable systems

Energy Technology Data Exchange (ETDEWEB)

Adesso, Gerardo; Illuminati, Fabrizio [Dipartimento di Fisica ' E R Caianiello' , Universita degli Studi di Salerno (Italy); CNISM and CNR-Coherentia, Gruppo di Salerno (Italy); and INFN Sezione di Napoli-Gruppo Collegato di Salerno (Italy); Via S Allende, 84081 Baronissi, SA (Italy)

2006-01-15

For continuous-variable (CV) systems, we introduce a measure of entanglement, the CV tangle (contangle), with the purpose of quantifying the distributed (shared) entanglement in multimode, multipartite Gaussian states. This is achieved by a proper convex-roof extension of the squared logarithmic negativity. We prove that the contangle satisfies the Coffman-Kundu-Wootters monogamy inequality in all three-mode Gaussian states, and in all fully symmetric N-mode Gaussian states, for arbitrary N. For three-mode pure states, we prove that the residual entanglement is a genuine tripartite entanglement monotone under Gaussian local operations and classical communication. We show that pure, symmetric three-mode Gaussian states allow a promiscuous entanglement sharing, having both maximum tripartite residual entanglement and maximum couplewise entanglement between any pair of modes. These states are thus simultaneous CV analogues of both the GHZ and the W states of three qubits: in CV systems monogamy does not prevent promiscuity, and the inequivalence between different classes of maximally entangled states, holding for systems of three or more qubits, is removed.

Gaussian Quadrature is an efficient method for the back-transformation in estimating the usual intake distribution when assessing dietary exposure.

Science.gov (United States)

Dekkers, A L M; Slob, W

2012-10-01

In dietary exposure assessment, statistical methods exist for estimating the usual intake distribution from daily intake data. These methods transform the dietary intake data to normal observations, eliminate the within-person variance, and then back-transform the data to the original scale. We propose Gaussian Quadrature (GQ), a numerical integration method, as an efficient way of back-transformation. We compare GQ with six published methods. One method uses a log-transformation, while the other methods, including GQ, use a Box-Cox transformation. This study shows that, for various parameter choices, the methods with a Box-Cox transformation estimate the theoretical usual intake distributions quite well, although one method, a Taylor approximation, is less accurate. Two applications--on folate intake and fruit consumption--confirmed these results. In one extreme case, some methods, including GQ, could not be applied for low percentiles. We solved this problem by modifying GQ. One method is based on the assumption that the daily intakes are log-normally distributed. Even if this condition is not fulfilled, the log-transformation performs well as long as the within-individual variance is small compared to the mean. We conclude that the modified GQ is an efficient, fast and accurate method for estimating the usual intake distribution. Copyright © 2012 Elsevier Ltd. All rights reserved.

Distributed Energy Technology Laboratory

Data.gov (United States)

Federal Laboratory Consortium — The Distributed Energy Technologies Laboratory (DETL) is an extension of the power electronics testing capabilities of the Photovoltaic System Evaluation Laboratory...

Non-Gaussianity from isocurvature perturbations

Energy Technology Data Exchange (ETDEWEB)

Kawasaki, Masahiro; Nakayama, Kazunori; Sekiguchi, Toyokazu; Suyama, Teruaki [Institute for Cosmic Ray Research, University of Tokyo, Kashiwa 277-8582 (Japan); Takahashi, Fuminobu, E-mail: kawasaki@icrr.u-tokyo.ac.jp, E-mail: nakayama@icrr.u-tokyo.ac.jp, E-mail: sekiguti@icrr.u-tokyo.ac.jp, E-mail: suyama@icrr.u-tokyo.ac.jp, E-mail: fuminobu.takahashi@ipmu.jp [Institute for the Physics and Mathematics of the Universe, University of Tokyo, Kashiwa 277-8568 (Japan)

2008-11-15

We develop a formalism for studying non-Gaussianity in both curvature and isocurvature perturbations. It is shown that non-Gaussianity in the isocurvature perturbation between dark matter and photons leaves distinct signatures in the cosmic microwave background temperature fluctuations, which may be confirmed in future experiments, or possibly even in the currently available observational data. As an explicit example, we consider the quantum chromodynamics axion and show that it can actually induce sizable non-Gaussianity for the inflationary scale, H{sub inf} = O(10{sup 9}-10{sup 11}) GeV.

Handbook of Gaussian basis sets

International Nuclear Information System (INIS)

Poirier, R.; Kari, R.; Csizmadia, I.G.

1985-01-01

A collection of a large body of information is presented useful for chemists involved in molecular Gaussian computations. Every effort has been made by the authors to collect all available data for cartesian Gaussian as found in the literature up to July of 1984. The data in this text includes a large collection of polarization function exponents but in this case the collection is not complete. Exponents for Slater type orbitals (STO) were included for completeness. This text offers a collection of Gaussian exponents primarily without criticism. (Auth.)

Adaptive estimation of multivariate functions using conditionally Gaussian tensor-product spline priors

NARCIS (Netherlands)

Jonge, de R.; Zanten, van J.H.

2012-01-01

We investigate posterior contraction rates for priors on multivariate functions that are constructed using tensor-product B-spline expansions. We prove that using a hierarchical prior with an appropriate prior distribution on the partition size and Gaussian prior weights on the B-spline

The finite-temperature Gaussian effective potential from a variational principle

International Nuclear Information System (INIS)

Haugerud, H.; Ravndal, F.

1990-08-01

Writing the partition function for a scalar quantum field theory as a functional integral, it follows that the finite-temperature Gaussian effective potential is an upper limit to the free energy of the system. Explicit results are given for the anharmonic oscillator at finite temperature. 5 refs., 2 figs

Distributed energy store railguns experiment and analysis

International Nuclear Information System (INIS)

Holland, L.D.

1984-01-01

Electromagnetic acceleration of projectiles holds the potential for achieving higher velocities than yet achieved by any other means. A railgun is the simplest form of electromagnetic macroparticle accelerator and can generate the highest sustained accelerating force. The practical length of conventional railguns is limited by the impedance of the rails because current must be carried along the entire length of the rails. A railgun and power supply system called the distributed energy store railgun was proposed as a solution to this limitation. The distributed energy store railgun used multiple current sources connected to the rails of a railgun at points distributed along the bore. These current sources (energy stores) are turned on in sequence as the projectile moves down the bore so that current is fed to the railgun from behind the armature. In this system the length of the rails that carry the full armature current is less than the total length of the railgun. If a sufficient number of energy stores is used, this removes the limitation on the length of a railgun. An additional feature of distributed energy store type railguns is that they can be designed to maintain a constant pressure on the projectile being accelerated. A distributed energy store railgun was constructed and successfully operated. In addition to this first demonstration of the distributed energy store railgun principle, a theoretical model of the system was also constructed

Asymptotics of sums of lognormal random variables with Gaussian copula

DEFF Research Database (Denmark)

Asmussen, Søren; Rojas-Nandayapa, Leonardo

2008-01-01

Let (Y1, ..., Yn) have a joint n-dimensional Gaussian distribution with a general mean vector and a general covariance matrix, and let Xi = eYi, Sn = X1 + ⋯ + Xn. The asymptotics of P (Sn > x) as n → ∞ are shown to be the same as for the independent case with the same lognormal marginals. In part...

Error Rates of M-PAM and M-QAM in Generalized Fading and Generalized Gaussian Noise Environments

KAUST Repository

Soury, Hamza

2013-07-01

This letter investigates the average symbol error probability (ASEP) of pulse amplitude modulation and quadrature amplitude modulation coherent signaling over flat fading channels subject to additive white generalized Gaussian noise. The new ASEP results are derived in a generic closed-form in terms of the Fox H function and the bivariate Fox H function for the extended generalized-K fading case. The utility of this new general closed-form is that it includes some special fading distributions, like the Generalized-K, Nakagami-m, and Rayleigh fading and special noise distributions such as Gaussian and Laplacian. Some of these special cases are also treated and are shown to yield simplified results.

SURVEY DESIGN FOR SPECTRAL ENERGY DISTRIBUTION FITTING: A FISHER MATRIX APPROACH

International Nuclear Information System (INIS)

Acquaviva, Viviana; Gawiser, Eric; Bickerton, Steven J.; Grogin, Norman A.; Guo Yicheng; Lee, Seong-Kook

2012-01-01

The spectral energy distribution (SED) of a galaxy contains information on the galaxy's physical properties, and multi-wavelength observations are needed in order to measure these properties via SED fitting. In planning these surveys, optimization of the resources is essential. The Fisher Matrix (FM) formalism can be used to quickly determine the best possible experimental setup to achieve the desired constraints on the SED-fitting parameters. However, because it relies on the assumption of a Gaussian likelihood function, it is in general less accurate than other slower techniques that reconstruct the probability distribution function (PDF) from the direct comparison between models and data. We compare the uncertainties on SED-fitting parameters predicted by the FM to the ones obtained using the more thorough PDF-fitting techniques. We use both simulated spectra and real data, and consider a large variety of target galaxies differing in redshift, mass, age, star formation history, dust content, and wavelength coverage. We find that the uncertainties reported by the two methods agree within a factor of two in the vast majority (∼90%) of cases. If the age determination is uncertain, the top-hat prior in age used in PDF fitting to prevent each galaxy from being older than the universe needs to be incorporated in the FM, at least approximately, before the two methods can be properly compared. We conclude that the FM is a useful tool for astronomical survey design.

Overlay Spectrum Sharing using Improper Gaussian Signaling

KAUST Repository

Amin, Osama

2016-11-30

Improper Gaussian signaling (IGS) scheme has been recently shown to provide performance improvements in interference limited networks as opposed to the conventional proper Gaussian signaling (PGS) scheme. In this paper, we implement the IGS scheme in overlay cognitive radio system, where the secondary transmitter broadcasts a mixture of two different signals. The first signal is selected from the PGS scheme to match the primary message transmission. On the other hand, the second signal is chosen to be from the IGS scheme in order to reduce the interference effect on the primary receiver. We then optimally design the overlay cognitive radio to maximize the secondary link achievable rate while satisfying the primary network quality of service requirements. In particular, we consider full and partial channel knowledge scenarios and derive the feasibility conditions of operating the overlay cognitive radio systems. Moreover, we derive the superiority conditions of the IGS schemes over the PGS schemes supported with closed form expressions for the corresponding power distribution and the circularity coefficient and parameters. Simulation results are provided to support our theoretical derivations.

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

Science.gov (United States)

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

2017-12-01

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

Searching for non-Gaussianity in the WMAP data

International Nuclear Information System (INIS)

Bernui, A.; Reboucas, M. J.

2009-01-01

Some analyses of recent cosmic microwave background (CMB) data have provided hints that there are deviations from Gaussianity in the WMAP CMB temperature fluctuations. Given the far-reaching consequences of such a non-Gaussianity for our understanding of the physics of the early universe, it is important to employ alternative indicators in order to determine whether the reported non-Gaussianity is of cosmological origin, and/or extract further information that may be helpful for identifying its causes. We propose two new non-Gaussianity indicators, based on skewness and kurtosis of large-angle patches of CMB maps, which provide a measure of departure from Gaussianity on large angular scales. A distinctive feature of these indicators is that they provide sky maps of non-Gaussianity of the CMB temperature data, thus allowing a possible additional window into their origins. Using these indicators, we find no significant deviation from Gaussianity in the three and five-year WMAP Internal Linear Combination (ILC) map with KQ75 mask, while the ILC unmasked map exhibits deviation from Gaussianity, quantifying therefore the WMAP team recommendation to employ the new mask KQ75 for tests of Gaussianity. We also use our indicators to test for Gaussianity the single frequency foreground unremoved WMAP three and five-year maps, and show that the K and Ka maps exhibit a clear indication of deviation from Gaussianity even with the KQ75 mask. We show that our findings are robust with respect to the details of the method.

Continuous-variable quantum Gaussian process regression and quantum singular value decomposition of nonsparse low-rank matrices

Science.gov (United States)

Das, Siddhartha; Siopsis, George; Weedbrook, Christian

2018-02-01

With the significant advancement in quantum computation during the past couple of decades, the exploration of machine-learning subroutines using quantum strategies has become increasingly popular. Gaussian process regression is a widely used technique in supervised classical machine learning. Here we introduce an algorithm for Gaussian process regression using continuous-variable quantum systems that can be realized with technology based on photonic quantum computers under certain assumptions regarding distribution of data and availability of efficient quantum access. Our algorithm shows that by using a continuous-variable quantum computer a dramatic speedup in computing Gaussian process regression can be achieved, i.e., the possibility of exponentially reducing the time to compute. Furthermore, our results also include a continuous-variable quantum-assisted singular value decomposition method of nonsparse low rank matrices and forms an important subroutine in our Gaussian process regression algorithm.

Gaussian process regression analysis for functional data

CERN Document Server

Shi, Jian Qing

2011-01-01

Gaussian Process Regression Analysis for Functional Data presents nonparametric statistical methods for functional regression analysis, specifically the methods based on a Gaussian process prior in a functional space. The authors focus on problems involving functional response variables and mixed covariates of functional and scalar variables.Covering the basics of Gaussian process regression, the first several chapters discuss functional data analysis, theoretical aspects based on the asymptotic properties of Gaussian process regression models, and new methodological developments for high dime

Multimodal distribution of human cold pain thresholds.

Science.gov (United States)

Lötsch, Jörn; Dimova, Violeta; Lieb, Isabel; Zimmermann, Michael; Oertel, Bruno G; Ultsch, Alfred

2015-01-01

It is assumed that different pain phenotypes are based on varying molecular pathomechanisms. Distinct ion channels seem to be associated with the perception of cold pain, in particular TRPM8 and TRPA1 have been highlighted previously. The present study analyzed the distribution of cold pain thresholds with focus at describing the multimodality based on the hypothesis that it reflects a contribution of distinct ion channels. Cold pain thresholds (CPT) were available from 329 healthy volunteers (aged 18 - 37 years; 159 men) enrolled in previous studies. The distribution of the pooled and log-transformed threshold data was described using a kernel density estimation (Pareto Density Estimation (PDE)) and subsequently, the log data was modeled as a mixture of Gaussian distributions using the expectation maximization (EM) algorithm to optimize the fit. CPTs were clearly multi-modally distributed. Fitting a Gaussian Mixture Model (GMM) to the log-transformed threshold data revealed that the best fit is obtained when applying a three-model distribution pattern. The modes of the identified three Gaussian distributions, retransformed from the log domain to the mean stimulation temperatures at which the subjects had indicated pain thresholds, were obtained at 23.7 °C, 13.2 °C and 1.5 °C for Gaussian #1, #2 and #3, respectively. The localization of the first and second Gaussians was interpreted as reflecting the contribution of two different cold sensors. From the calculated localization of the modes of the first two Gaussians, the hypothesis of an involvement of TRPM8, sensing temperatures from 25 - 24 °C, and TRPA1, sensing cold from 17 °C can be derived. In that case, subjects belonging to either Gaussian would possess a dominance of the one or the other receptor at the skin area where the cold stimuli had been applied. The findings therefore support a suitability of complex analytical approaches to detect mechanistically determined patterns from pain phenotype data.

Quality of Gaussian basis sets: direct optimization of orbital exponents by the method of conjugate gradients

International Nuclear Information System (INIS)

Kari, R.E.; Mezey, P.G.; Csizmadia, I.G.

1975-01-01

Expressions are given for calculating the energy gradient vector in the exponent space of Gaussian basis sets and a technique to optimize orbital exponents using the method of conjugate gradients is described. The method is tested on the (9/sups/5/supp/) Gaussian basis space and optimum exponents are determined for the carbon atom. The analysis of the results shows that the calculated one-electron properties converge more slowly to their optimum values than the total energy converges to its optimum value. In addition, basis sets approximating the optimum total energy very well can still be markedly improved for the prediction of one-electron properties. For smaller basis sets, this improvement does not warrant the necessary expense

Performance of monitoring networks estimated from a Gaussian plume model

International Nuclear Information System (INIS)

Seebregts, A.J.; Hienen, J.F.A.

1990-10-01

In support of the ECN study on monitoring strategies after nuclear accidents, the present report describes the analysis of the performance of a monitoring network in a square grid. This network is used to estimate the distribution of the deposition pattern after a release of radioactivity into the atmosphere. The analysis is based upon a single release, a constant wind direction and an atmospheric dispersion according to a simplified Gaussian plume model. A technique is introduced to estimate the parameters in this Gaussian model based upon measurements at specific monitoring locations and linear regression, although this model is intrinsically non-linear. With these estimated parameters and the Gaussian model the distribution of the contamination due to deposition can be estimated. To investigate the relation between the network and the accuracy of the estimates for the deposition, deposition data have been generated by the Gaussian model, including a measurement error by a Monte Carlo simulation and this procedure has been repeated for several grid sizes, dispersion conditions, number of measurements per location, and errors per single measurement. The present technique has also been applied for the mesh sizes of two networks in the Netherlands, viz. the Landelijk Meetnet Radioaciviteit (National Measurement Network on Radioactivity, mesh size approx. 35 km) and the proposed Landelijk Meetnet Nucleaire Incidenten (National Measurement Network on Nuclear Incidents, mesh size approx. 15 km). The results show accuracies of 11 and 7 percent, respectively, if monitoring locations are used more than 10 km away from the postulated accident site. These figures are based upon 3 measurements per location and a dispersion during neutral weather with a wind velocity of 4 m/s. For stable weather conditions and low wind velocities, i.e. a small plume, the calculated accuracies are at least a factor 1.5 worse.The present type of analysis makes a cost-benefit approach to the

Gaussian operations and privacy

International Nuclear Information System (INIS)

Navascues, Miguel; Acin, Antonio

2005-01-01

We consider the possibilities offered by Gaussian states and operations for two honest parties, Alice and Bob, to obtain privacy against a third eavesdropping party, Eve. We first extend the security analysis of the protocol proposed in [Navascues et al. Phys. Rev. Lett. 94, 010502 (2005)]. Then, we prove that a generalized version of this protocol does not allow one to distill a secret key out of bound entangled Gaussian states

On the Performance Analysis of Digital Communication Systems Perturbed by Non-Gaussian Noise and Interference

KAUST Repository

Soury, Hamza

2016-06-29

The Gaussian distribution is typically used to model the additive noise affecting communication systems. However, in many cases the noise cannot be modeled by a Gaussian distribution. In this thesis, we investigate the performance of different communication systems perturbed by non-Gaussian noise. Three families of noise are considered in this work, namely the generalized Gaussian noise, the Laplace noise/interference, and the impulsive noise that is modeled by an α-stable distribution. More specifically, in the first part of this thesis, the impact of an additive generalized Gaussian noise is studied by computing the average symbol error rate (SER) of one dimensional and two dimensional constellations in fading environment. We begin by the simple case of two symbols, i.e. binary phase shift keying (BPSK) constellation. From the results of this constellation, we extended the work to the average SER of an M pulse amplitude modulation (PAM). The first 2 − D constellation is the M quadrature amplitude modulation (QAM) (studied for two geometric shapes, namely square and rectangular), which is the combination of two orthogonal PAM signals (in-phase and quadrature phase PAM). In the second part, the system performance of a circular constellation, namely M phase shift keying (MPSK) is studied in conjunction with a Laplace noise with independent noise components. A closed form and an asymptotic expansion of the SER are derived for two detectors, maximum likelihood and minimum distance detectors. Next, we look at the intra cell interference of a full duplex cellular network which is shown to follow a Laplacian distribution with dependent, but uncorrelated, complex components. The densities of that interference are expressed in a closed form in order to obtain the SER of several communication systems (BPSK, PAM, QAM, and MPSK). Finally, we study the statistics of the α-stable distribution. Those statistics are expressed in closed form in terms of the Fox H function and

Adaptive wiener filter based on Gaussian mixture distribution model for denoising chest X-ray CT image

International Nuclear Information System (INIS)

Tabuchi, Motohiro; Yamane, Nobumoto; Morikawa, Yoshitaka

2008-01-01

In recent decades, X-ray CT imaging has become more important as a result of its high-resolution performance. However, it is well known that the X-ray dose is insufficient in the techniques that use low-dose imaging in health screening or thin-slice imaging in work-up. Therefore, the degradation of CT images caused by the streak artifact frequently becomes problematic. In this study, we applied a Wiener filter (WF) using the universal Gaussian mixture distribution model (UNI-GMM) as a statistical model to remove streak artifact. In designing the WF, it is necessary to estimate the statistical model and the precise co-variances of the original image. In the proposed method, we obtained a variety of chest X-ray CT images using a phantom simulating a chest organ, and we estimated the statistical information using the images for training. The results of simulation showed that it is possible to fit the UNI-GMM to the chest X-ray CT images and reduce the specific noise. (author)

The Pearson IV distribution and its application to ion implanted depth profiles

International Nuclear Information System (INIS)

Wilson, R.G.

1980-01-01

The Pearson IV distribution system is analyzed to determine the regions of validity for the values of the moments that produce convex, concave, more pointed than Gaussian, and more flat-topped than Gaussian distributions; the limits beyond which no significant change in distribution is produced; and excluded regions. These regions are illustrated in a figure that can be used to facilitate the determination of the Pearson IV moments for experimental ion implanted depth distributions. Examples are given of Pearson IV distributions to illustrate the effects of the ranges of skewness, kurtosis, and standard deviation, for both more pointed and more flat-topped than Gaussian distributions. A procedure is described for matching experimental ion implanted depth distributions to computer plotted Pearson IV modified Gaussian distributions. A few experimental curves are given to illustrate the different types of Pearson IV curves, and accuracies of moments are discussed. (author)

Residual stress measurement by X-ray diffraction with the Gaussian curve method and its automation

International Nuclear Information System (INIS)

Kurita, M.

1987-01-01

X-ray technique with the Gaussian curve method and its automation are described for rapid and nondestructive measurement of residual stress. A simplified equation for measuring the stress by the Gaussian curve method is derived because in its previous form this method required laborious calculation. The residual stress can be measured in a few minutes, depending on materials, using an automated X-ray stress analyzer with a microcomputer which was developed in the laboratory. The residual stress distribution of a partially induction hardened and tempered (at 280 0 C) steel bar was measured with the Gaussian curve method. A sharp residual tensile stress peak of 182 MPa appeared right outside the hardened region at which fatigue failure is liable to occur

Versatile Gaussian probes for squeezing estimation

Science.gov (United States)

Rigovacca, Luca; Farace, Alessandro; Souza, Leonardo A. M.; De Pasquale, Antonella; Giovannetti, Vittorio; Adesso, Gerardo

2017-05-01

We consider an instance of "black-box" quantum metrology in the Gaussian framework, where we aim to estimate the amount of squeezing applied on an input probe, without previous knowledge on the phase of the applied squeezing. By taking the quantum Fisher information (QFI) as the figure of merit, we evaluate its average and variance with respect to this phase in order to identify probe states that yield good precision for many different squeezing directions. We first consider the case of single-mode Gaussian probes with the same energy, and find that pure squeezed states maximize the average quantum Fisher information (AvQFI) at the cost of a performance that oscillates strongly as the squeezing direction is changed. Although the variance can be brought to zero by correlating the probing system with a reference mode, the maximum AvQFI cannot be increased in the same way. A different scenario opens if one takes into account the effects of photon losses: coherent states represent the optimal single-mode choice when losses exceed a certain threshold and, moreover, correlated probes can now yield larger AvQFI values than all single-mode states, on top of having zero variance.

Non-Gaussian initial conditions in ΛCDM: Newtonian, relativistic, and primordial contributions

International Nuclear Information System (INIS)

Bruni, Marco; Hidalgo, Juan Carlos; Meures, Nikolai; Wands, David

2014-01-01

The goal of the present paper is to set initial conditions for structure formation at nonlinear order, consistent with general relativity, while also allowing for primordial non-Gaussianity. We use the nonlinear continuity and Raychaudhuri equations, which together with the nonlinear energy constraint, determine the evolution of the matter density fluctuation in general relativity. We solve this equations at first and second order in a perturbative expansion, recovering and extending previous results derived in the matter-dominated limit and in the Newtonian regime. We present a second-order solution for the comoving density contrast in a ΛCDM universe, identifying nonlinear contributions coming from the Newtonian growing mode, primordial non-Gaussianity and intrinsic non-Gaussianity, due to the essential nonlinearity of the relativistic constraint equations. We discuss the application of these results to initial conditions in N-body simulations, showing that relativistic corrections mimic a non-zero nonlinear parameter f NL

Single-quadrature continuous-variable quantum key distribution

DEFF Research Database (Denmark)

Gehring, Tobias; Jacobsen, Christian Scheffmann; Andersen, Ulrik Lund

2016-01-01

Most continuous-variable quantum key distribution schemes are based on the Gaussian modulation of coherent states followed by continuous quadrature detection using homodyne detectors. In all previous schemes, the Gaussian modulation has been carried out in conjugate quadratures thus requiring two...... commercialization of continuous-variable quantum key distribution, provided that the low noise requirement can be achieved....

Non-Gaussianity in island cosmology

International Nuclear Information System (INIS)

Piao Yunsong

2009-01-01

In this paper we fully calculate the non-Gaussianity of primordial curvature perturbation of the island universe by using the second order perturbation equation. We find that for the spectral index n s ≅0.96, which is favored by current observations, the non-Gaussianity level f NL seen in an island will generally lie between 30 and 60, which may be tested by the coming observations. In the landscape, the island universe is one of anthropically acceptable cosmological histories. Thus the results obtained in some sense mean the coming observations, especially the measurement of non-Gaussianity, will be significant to clarify how our position in the landscape is populated.

Laser-driven acceleration with Bessel and Gaussian beams

International Nuclear Information System (INIS)

Hafizi, B.; Esarey, E.; Sprangle, P.

1997-01-01

The possibility of enhancing the energy gain in laser-driven accelerators by using Bessel laser beams is examined. Scaling laws are derived for the propagation length, acceleration gradient, and energy gain in various accelerators for both Gaussian and Bessel beam drivers. For equal beam powers, the energy gain can be increased by a factor of N 1/2 by utilizing a Bessel beam with N lobes, provided that the acceleration gradient is linearly proportional to the laser field. This is the case in the inverse free electron laser and the inverse Cherenkov accelerators. If the acceleration gradient is proportional to the square of the laser field (e.g., the laser wakefield, plasma beat wave, and vacuum beat wave accelerators), the energy gain is comparable with either beam profile. copyright 1997 American Institute of Physics

Gaussian statistics of the cosmic microwave background: Correlation of temperature extrema in the COBE DMR two-year sky maps

Science.gov (United States)

Kogut, A.; Banday, A. J.; Bennett, C. L.; Hinshaw, G.; Lubin, P. M.; Smoot, G. F.

1995-01-01

We use the two-point correlation function of the extrema points (peaks and valleys) in the Cosmic Background Explorer (COBE) Differential Microwave Radiometers (DMR) 2 year sky maps as a test for non-Gaussian temperature distribution in the cosmic microwave background anisotropy. A maximum-likelihood analysis compares the DMR data to n = 1 toy models whose random-phase spherical harmonic components a(sub lm) are drawn from either Gaussian, chi-square, or log-normal parent populations. The likelihood of the 53 GHz (A+B)/2 data is greatest for the exact Gaussian model. There is less than 10% chance that the non-Gaussian models tested describe the DMR data, limited primarily by type II errors in the statistical inference. The extrema correlation function is a stronger test for this class of non-Gaussian models than topological statistics such as the genus.

Average bit error probability of binary coherent signaling over generalized fading channels subject to additive generalized gaussian noise

KAUST Repository

Soury, Hamza

2012-06-01

This letter considers the average bit error probability of binary coherent signaling over flat fading channels subject to additive generalized Gaussian noise. More specifically, a generic closed form expression in terms of the Fox\\'s H function is offered for the extended generalized-K fading case. Simplifications for some special fading distributions such as generalized-K fading and Nakagami-m fading and special additive noise distributions such as Gaussian and Laplacian noise are then presented. Finally, the mathematical formalism is illustrated by some numerical examples verified by computer based simulations for a variety of fading and additive noise parameters. © 2012 IEEE.

Inflation in random landscapes with two energy scales

Science.gov (United States)

Blanco-Pillado, Jose J.; Vilenkin, Alexander; Yamada, Masaki

2018-02-01

We investigate inflation in a multi-dimensional landscape with a hierarchy of energy scales, motivated by the string theory, where the energy scale of Kahler moduli is usually assumed to be much lower than that of complex structure moduli and dilaton field. We argue that in such a landscape, the dynamics of slow-roll inflation is governed by the low-energy potential, while the initial condition for inflation are determined by tunneling through high-energy barriers. We then use the scale factor cutoff measure to calculate the probability distribution for the number of inflationary e-folds and the amplitude of density fluctuations Q, assuming that the low-energy landscape is described by a random Gaussian potential with a correlation length much smaller than M pl. We find that the distribution for Q has a unique shape and a preferred domain, which depends on the parameters of the low-energy landscape. We discuss some observational implications of this distribution and the constraints it imposes on the landscape parameters.

Discretisation Schemes for Level Sets of Planar Gaussian Fields

Science.gov (United States)

Beliaev, D.; Muirhead, S.

2018-01-01

Smooth random Gaussian functions play an important role in mathematical physics, a main example being the random plane wave model conjectured by Berry to give a universal description of high-energy eigenfunctions of the Laplacian on generic compact manifolds. Our work is motivated by questions about the geometry of such random functions, in particular relating to the structure of their nodal and level sets. We study four discretisation schemes that extract information about level sets of planar Gaussian fields. Each scheme recovers information up to a different level of precision, and each requires a maximum mesh-size in order to be valid with high probability. The first two schemes are generalisations and enhancements of similar schemes that have appeared in the literature (Beffara and Gayet in Publ Math IHES, 2017. https://doi.org/10.1007/s10240-017-0093-0; Mischaikow and Wanner in Ann Appl Probab 17:980-1018, 2007); these give complete topological information about the level sets on either a local or global scale. As an application, we improve the results in Beffara and Gayet (2017) on Russo-Seymour-Welsh estimates for the nodal set of positively-correlated planar Gaussian fields. The third and fourth schemes are, to the best of our knowledge, completely new. The third scheme is specific to the nodal set of the random plane wave, and provides global topological information about the nodal set up to `visible ambiguities'. The fourth scheme gives a way to approximate the mean number of excursion domains of planar Gaussian fields.

Dynamics of double-well Bose–Einstein condensates subject to external Gaussian white noise

International Nuclear Information System (INIS)

Zheng Hanlei; Hao Yajiang; Gu Qiang

2013-01-01

Dynamical properties of the Bose–Einstein condensate in a double-well potential subject to Gaussian white noise are investigated by numerically solving the time-dependent Gross–Pitaevskii equation. The Gaussian white noise is used to describe influence of the random environmental disturbance on the double-well condensate. Dynamical evolutions from three different initial states, the Josephson oscillation state, the running phase and π-mode macroscopic quantum self-trapping states, are considered. It is shown that the system is rather robust with respect to the weak noise whose strength is small and change rate is high. If the evolution time is sufficiently long, the weak noise will finally drive the system to evolve from high-energy states to low-energy states, but in a manner rather different from the energy-dissipation effect. In the presence of strong noise with either large strength or slow change rate, the double-well condensate may exhibit very irregular dynamical behaviours. (paper)

Holographic non-Gaussianity

International Nuclear Information System (INIS)

McFadden, Paul; Skenderis, Kostas

2011-01-01

We investigate the non-Gaussianity of primordial cosmological perturbations within our recently proposed holographic description of inflationary universes. We derive a holographic formula that determines the bispectrum of cosmological curvature perturbations in terms of correlation functions of a holographically dual three-dimensional non-gravitational quantum field theory (QFT). This allows us to compute the primordial bispectrum for a universe which started in a non-geometric holographic phase, using perturbative QFT calculations. Strikingly, for a class of models specified by a three-dimensional super-renormalisable QFT, the primordial bispectrum is of exactly the factorisable equilateral form with f NL equil. = 5/36, irrespective of the details of the dual QFT. A by-product of this investigation is a holographic formula for the three-point function of the trace of the stress-energy tensor along general holographic RG flows, which should have applications outside the remit of this work

The chiral Gaussian two-matrix ensemble of real asymmetric matrices

International Nuclear Information System (INIS)

Akemann, G; Phillips, M J; Sommers, H-J

2010-01-01

We solve a family of Gaussian two-matrix models with rectangular N x (N + ν) matrices, having real asymmetric matrix elements and depending on a non-Hermiticity parameter μ. Our model can be thought of as the chiral extension of the real Ginibre ensemble, relevant for Dirac operators in the same symmetry class. It has the property that its eigenvalues are either real, purely imaginary or come in complex conjugate eigenvalue pairs. The eigenvalue joint probability distribution for our model is explicitly computed, leading to a non-Gaussian distribution including K-Bessel functions. All n-point density correlation functions are expressed for finite N in terms of a Pfaffian form. This contains a kernel involving Laguerre polynomials in the complex plane as a building block which was previously computed by the authors. This kernel can be expressed in terms of the kernel for complex non-Hermitian matrices, generalizing the known relation among ensembles of Hermitian random matrices. Compact expressions are given for the density at finite N as an example, as well as its microscopic large-N limits at the origin for fixed ν at strong and weak non-Hermiticity.

Non-Gaussianity from inflation: theory and observations

Science.gov (United States)

Bartolo, N.; Komatsu, E.; Matarrese, S.; Riotto, A.

2004-11-01

This is a review of models of inflation and of their predictions for the primordial non-Gaussianity in the density perturbations which are thought to be at the origin of structures in the Universe. Non-Gaussianity emerges as a key observable to discriminate among competing scenarios for the generation of cosmological perturbations and is one of the primary targets of present and future Cosmic Microwave Background satellite missions. We give a detailed presentation of the state-of-the-art of the subject of non-Gaussianity, both from the theoretical and the observational point of view, and provide all the tools necessary to compute at second order in perturbation theory the level of non-Gaussianity in any model of cosmological perturbations. We discuss the new wave of models of inflation, which are firmly rooted in modern particle physics theory and predict a significant amount of non-Gaussianity. The review is addressed to both astrophysicists and particle physicists and contains useful tables which summarize the theoretical and observational results regarding non-Gaussianity.

Energy evolution of the moments of the hadron distribution in QCD jets including NNLL resummation and NLO running-coupling corrections

CERN Document Server

Perez-Ramos, Redamy

2014-01-01

The moments of the single inclusive momentum distribution of hadrons in QCD jets, are studied in the next-to-modified-leading-log approximation (NMLLA) including next-to-leading-order (NLO) corrections to the alpha_s strong coupling. The evolution equations are solved using a distorted Gaussian parametrisation, which successfully reproduces the spectrum of charged hadrons of jets measured in e+e- collisions. The energy dependencies of the maximum peak, multiplicity, width, kurtosis and skewness of the jet hadron distribution are computed analytically. Comparisons of all the existing jet data measured in e+e- collisions in the range sqrt(s)~2-200 GeV to the NMLLA+NLO* predictions allow one to extract a value of the QCD parameter Lambda_QCD, and associated two-loop coupling constant at the Z resonance alpha_s(m_Z^2)= 0.1195 +/- 0.0022, in excellent numerical agreement with the current world average obtained using other methods.

Determination analysis of energy conservation standards for distribution transformers

Energy Technology Data Exchange (ETDEWEB)

Barnes, P.R.; Van Dyke, J.W.; McConnell, B.W.; Das, S.

1996-07-01

This report contains information for US DOE to use in making a determination on proposing energy conservation standards for distribution transformers as required by the Energy Policy Act of 1992. Potential for saving energy with more efficient liquid-immersed and dry-type distribution transformers could be significant because these transformers account for an estimated 140 billion kWh of the annual energy lost in the delivery of electricity. Objective was to determine whether energy conservation standards for distribution transformers would have the potential for significant energy savings, be technically feasible, and be economically justified from a national perspective. It was found that energy conservation for distribution transformers would be technically and economically feasible. Based on the energy conservation options analyzed, 3.6-13.7 quads of energy could be saved from 2000 to 2030.

Galaxy bias and primordial non-Gaussianity

Energy Technology Data Exchange (ETDEWEB)

Assassi, Valentin; Baumann, Daniel [DAMTP, Cambridge University, Wilberforce Road, Cambridge CB3 0WA (United Kingdom); Schmidt, Fabian, E-mail: assassi@ias.edu, E-mail: D.D.Baumann@uva.nl, E-mail: fabians@MPA-Garching.MPG.DE [Max-Planck-Institut für Astrophysik, Karl-Schwarzschild-Str. 1, 85748 Garching (Germany)

2015-12-01

We present a systematic study of galaxy biasing in the presence of primordial non-Gaussianity. For a large class of non-Gaussian initial conditions, we define a general bias expansion and prove that it is closed under renormalization, thereby showing that the basis of operators in the expansion is complete. We then study the effects of primordial non-Gaussianity on the statistics of galaxies. We show that the equivalence principle enforces a relation between the scale-dependent bias in the galaxy power spectrum and that in the dipolar part of the bispectrum. This provides a powerful consistency check to confirm the primordial origin of any observed scale-dependent bias. Finally, we also discuss the imprints of anisotropic non-Gaussianity as motivated by recent studies of higher-spin fields during inflation.

Optimal cloning of mixed Gaussian states

International Nuclear Information System (INIS)

Guta, Madalin; Matsumoto, Keiji

2006-01-01

We construct the optimal one to two cloning transformation for the family of displaced thermal equilibrium states of a harmonic oscillator, with a fixed and known temperature. The transformation is Gaussian and it is optimal with respect to the figure of merit based on the joint output state and norm distance. The proof of the result is based on the equivalence between the optimal cloning problem and that of optimal amplification of Gaussian states which is then reduced to an optimization problem for diagonal states of a quantum oscillator. A key concept in finding the optimum is that of stochastic ordering which plays a similar role in the purely classical problem of Gaussian cloning. The result is then extended to the case of n to m cloning of mixed Gaussian states

Galaxy bias and primordial non-Gaussianity

International Nuclear Information System (INIS)

Assassi, Valentin; Baumann, Daniel; Schmidt, Fabian

2015-01-01

We present a systematic study of galaxy biasing in the presence of primordial non-Gaussianity. For a large class of non-Gaussian initial conditions, we define a general bias expansion and prove that it is closed under renormalization, thereby showing that the basis of operators in the expansion is complete. We then study the effects of primordial non-Gaussianity on the statistics of galaxies. We show that the equivalence principle enforces a relation between the scale-dependent bias in the galaxy power spectrum and that in the dipolar part of the bispectrum. This provides a powerful consistency check to confirm the primordial origin of any observed scale-dependent bias. Finally, we also discuss the imprints of anisotropic non-Gaussianity as motivated by recent studies of higher-spin fields during inflation

Thermal Distribution System | Energy Systems Integration Facility | NREL

Science.gov (United States)

Thermal Distribution System Thermal Distribution System The Energy Systems Integration Facility's . Photo of the roof of the Energy Systems Integration Facility. The thermal distribution bus allows low as 10% of its full load level). The 60-ton chiller cools water with continuous thermal control

Spatio-Temporal Data Analysis at Scale Using Models Based on Gaussian Processes

Energy Technology Data Exchange (ETDEWEB)

Stein, Michael [Univ. of Chicago, IL (United States)

2017-03-13

Gaussian processes are the most commonly used statistical model for spatial and spatio-temporal processes that vary continuously. They are broadly applicable in the physical sciences and engineering and are also frequently used to approximate the output of complex computer models, deterministic or stochastic. We undertook research related to theory, computation, and applications of Gaussian processes as well as some work on estimating extremes of distributions for which a Gaussian process assumption might be inappropriate. Our theoretical contributions include the development of new classes of spatial-temporal covariance functions with desirable properties and new results showing that certain covariance models lead to predictions with undesirable properties. To understand how Gaussian process models behave when applied to deterministic computer models, we derived what we believe to be the first significant results on the large sample properties of estimators of parameters of Gaussian processes when the actual process is a simple deterministic function. Finally, we investigated some theoretical issues related to maxima of observations with varying upper bounds and found that, depending on the circumstances, standard large sample results for maxima may or may not hold. Our computational innovations include methods for analyzing large spatial datasets when observations fall on a partially observed grid and methods for estimating parameters of a Gaussian process model from observations taken by a polar-orbiting satellite. In our application of Gaussian process models to deterministic computer experiments, we carried out some matrix computations that would have been infeasible using even extended precision arithmetic by focusing on special cases in which all elements of the matrices under study are rational and using exact arithmetic. The applications we studied include total column ozone as measured from a polar-orbiting satellite, sea surface temperatures over the

Interaction of Airy-Gaussian beams in saturable media

Science.gov (United States)

Zhou, Meiling; Peng, Yulian; Chen, Chidao; Chen, Bo; Peng, Xi; Deng, Dongmei

2016-08-01

Based on the nonlinear Schrödinger equation, the interactions of the two Airy-Gaussian components in the incidence are analyzed in saturable media, under the circumstances of the same amplitude and different amplitudes, respectively. It is found that the interaction can be both attractive and repulsive depending on the relative phase. The smaller the interval between two Airy-Gaussian components in the incidence is, the stronger the intensity of the interaction. However, with the equal amplitude, the symmetry is shown and the change of quasi-breathers is opposite in the in-phase case and out-of-phase case. As the distribution factor is increased, the phenomena of the quasi-breather and the self-accelerating of the two Airy-Gaussian components are weakened. When the amplitude is not equal, the image does not have symmetry. The obvious phenomenon of the interaction always arises on the side of larger input power in the incidence. The maximum intensity image is also simulated. Many of the characteristics which are contained within other images can also be concluded in this figure. Project supported by the National Natural Science Foundation of China (Grant Nos. 11374108 and 10904041), the Foundation for the Author of Guangdong Province Excellent Doctoral Dissertation (Grant No. SYBZZXM201227), and the Foundation of Cultivating Outstanding Young Scholars (“Thousand, Hundred, Ten” Program) of Guangdong Province, China. CAS Key Laboratory of Geospace Environment, University of Science and Technology of China.

77 FR 10997 - Energy Conservation Program: Energy Conservation Standards for Distribution Transformers; Correction

Science.gov (United States)

2012-02-24

... Conservation Program: Energy Conservation Standards for Distribution Transformers; Correction AGENCY: Office of... standards for distribution transformers. It was recently discovered that values in certain tables of the...,'' including distribution transformers. The Energy Policy Act of 1992 (EPACT 1992), Public Law 102-486, amended...

Cost allocation model for distribution networks considering high penetration of distributed energy resources

DEFF Research Database (Denmark)

Soares, Tiago; Pereira, Fábio; Morais, Hugo

2015-01-01

The high penetration of distributed energy resources (DER) in distribution networks and the competitive environment of electricity markets impose the use of new approaches in several domains. The network cost allocation, traditionally used in transmission networks, should be adapted and used...... in the distribution networks considering the specifications of the connected resources. The main goal is to develop a fairer methodology trying to distribute the distribution network use costs to all players which are using the network in each period. In this paper, a model considering different type of costs (fixed......, losses, and congestion costs) is proposed comprising the use of a large set of DER, namely distributed generation (DG), demand response (DR) of direct load control type, energy storage systems (ESS), and electric vehicles with capability of discharging energy to the network, which is known as vehicle...

Electro-optic measurement of terahertz pulse energy distribution

NARCIS (Netherlands)

Sun, J.H.; Gallacher, J.G.; Brussaard, G.J.H.; Lemos, N.; Issac, R.; Huang, Z.X.; Dias, J.M.; Jaroszynski, D.A.

2009-01-01

An accurate and direct measurement of the energy distribution of a low repetition rate terahertz electromagnetic pulse is challenging because of the lack of sensitive detectors in this spectral range. In this paper, we show how the total energy and energy density distribution of a terahertz

Information geometry of Gaussian channels

International Nuclear Information System (INIS)

Monras, Alex; Illuminati, Fabrizio

2010-01-01

We define a local Riemannian metric tensor in the manifold of Gaussian channels and the distance that it induces. We adopt an information-geometric approach and define a metric derived from the Bures-Fisher metric for quantum states. The resulting metric inherits several desirable properties from the Bures-Fisher metric and is operationally motivated by distinguishability considerations: It serves as an upper bound to the attainable quantum Fisher information for the channel parameters using Gaussian states, under generic constraints on the physically available resources. Our approach naturally includes the use of entangled Gaussian probe states. We prove that the metric enjoys some desirable properties like stability and covariance. As a by-product, we also obtain some general results in Gaussian channel estimation that are the continuous-variable analogs of previously known results in finite dimensions. We prove that optimal probe states are always pure and bounded in the number of ancillary modes, even in the presence of constraints on the reduced state input in the channel. This has experimental and computational implications. It limits the complexity of optimal experimental setups for channel estimation and reduces the computational requirements for the evaluation of the metric: Indeed, we construct a converging algorithm for its computation. We provide explicit formulas for computing the multiparametric quantum Fisher information for dissipative channels probed with arbitrary Gaussian states and provide the optimal observables for the estimation of the channel parameters (e.g., bath couplings, squeezing, and temperature).

Effect of anaerobic digestion on sequential pyrolysis kinetics of organic solid wastes using thermogravimetric analysis and distributed activation energy model.

Science.gov (United States)

Li, Xiaowei; Mei, Qingqing; Dai, Xiaohu; Ding, Guoji

2017-03-01

Thermogravimetric analysis, Gaussian-fit-peak model (GFPM), and distributed activation energy model (DAEM) were firstly used to explore the effect of anaerobic digestion on sequential pyrolysis kinetic of four organic solid wastes (OSW). Results showed that the OSW weight loss mainly occurred in the second pyrolysis stage relating to organic matter decomposition. Compared with raw substrate, the weight loss of corresponding digestate was lower in the range of 180-550°C, but was higher in 550-900°C. GFPM analysis revealed that organic components volatized at peak temperatures of 188-263, 373-401 and 420-462°C had a faster degradation rate than those at 274-327°C during anaerobic digestion. DAEM analysis showed that anaerobic digestion had discrepant effects on activation energy for four OSW pyrolysis, possibly because of their different organic composition. It requires further investigation for the special organic matter, i.e., protein-like and carbohydrate-like groups, to confirm the assumption. Copyright © 2016 Elsevier Ltd. All rights reserved.

Gaussian elimination methods for calculating classical periodic trajectories in two dimensions

International Nuclear Information System (INIS)

Davies, K.T.R.

1991-08-01

A Gaussian-elimination method for calculating classical periodic trajectories is formulated for a two-dimensional system. Two variants of the theory are obtained, one assuming that the period of the motion is fixed and the other assuming that the total energy is fixed. Comparisons are made between various approaches. 14 refs

Small Distributed Renewable Energy Generation for Low Voltage Distribution Networks

Directory of Open Access Journals (Sweden)

Chindris M.

2016-08-01

Full Text Available Driven by the existing energy policies, the use of renewable energy has increased considerably all over the world in order to respond to the increasing energy consumption and to reduce the environmental impact of the electricity generation. Although most policy makers and companies are focusing on large applications, the use of cheap small generation units, based on local renewable resources, has become increasingly attractive for the general public, small farms and remote communities. The paper presents several results of a research project aiming to identify the power quality issues and the impact of RES based distributed generation (DG or other non-linear loads on low voltage (LV distribution networks in Romania; the final goal is to develop a Universal Power Quality Conditioner (UPQC able to diminish the existing disturbances. Basically, the work analyses the existing DG technologies and identifies possible solutions for their integration in Romania; taking into account the existent state of the art, the attention was paid on small systems, using wind and solar energy, and on possibility to integrate them into suburban and rural LV distribution networks. The presence of DG units at distribution voltage level means the transition from traditional passive to active distribution networks. In general, the relatively low penetration levels of DG does not produce problems; however, the nowadays massive increase of local power generation have led to new integration challenges in order to ensure the reliability and quality of the power supply. Power quality issues are identified and their assessment is the key element in the design of measures aiming to diminish all existing disturbances.

Laguerre Gaussian beam multiplexing through turbulence

CSIR Research Space (South Africa)

Trichili, A

2014-08-17

Full Text Available We analyze the effect of atmospheric turbulence on the propagation of multiplexed Laguerre Gaussian modes. We present a method to multiplex Laguerre Gaussian modes using digital holograms and decompose the resulting field after encountering a...

Efficient Kernel-Based Ensemble Gaussian Mixture Filtering

KAUST Repository

Liu, Bo

2015-11-11

We consider the Bayesian filtering problem for data assimilation following the kernel-based ensemble Gaussian-mixture filtering (EnGMF) approach introduced by Anderson and Anderson (1999). In this approach, the posterior distribution of the system state is propagated with the model using the ensemble Monte Carlo method, providing a forecast ensemble that is then used to construct a prior Gaussian-mixture (GM) based on the kernel density estimator. This results in two update steps: a Kalman filter (KF)-like update of the ensemble members and a particle filter (PF)-like update of the weights, followed by a resampling step to start a new forecast cycle. After formulating EnGMF for any observational operator, we analyze the influence of the bandwidth parameter of the kernel function on the covariance of the posterior distribution. We then focus on two aspects: i) the efficient implementation of EnGMF with (relatively) small ensembles, where we propose a new deterministic resampling strategy preserving the first two moments of the posterior GM to limit the sampling error; and ii) the analysis of the effect of the bandwidth parameter on contributions of KF and PF updates and on the weights variance. Numerical results using the Lorenz-96 model are presented to assess the behavior of EnGMF with deterministic resampling, study its sensitivity to different parameters and settings, and evaluate its performance against ensemble KFs. The proposed EnGMF approach with deterministic resampling suggests improved estimates in all tested scenarios, and is shown to require less localization and to be less sensitive to the choice of filtering parameters.

Phase statistics in non-Gaussian scattering

International Nuclear Information System (INIS)

Watson, Stephen M; Jakeman, Eric; Ridley, Kevin D

2006-01-01

Amplitude weighting can improve the accuracy of frequency measurements in signals corrupted by multiplicative speckle noise. When the speckle field constitutes a circular complex Gaussian process, the optimal function of amplitude weighting is provided by the field intensity, corresponding to the intensity-weighted phase derivative statistic. In this paper, we investigate the phase derivative and intensity-weighted phase derivative returned from a two-dimensional random walk, which constitutes a generic scattering model capable of producing both Gaussian and non-Gaussian fluctuations. Analytical results are developed for the correlation properties of the intensity-weighted phase derivative, as well as limiting probability densities of the scattered field. Numerical simulation is used to generate further probability densities and determine optimal weighting criteria from non-Gaussian fields. The results are relevant to frequency retrieval in radiation scattered from random media

On full duplex Gaussian relay channels with self-interference

KAUST Repository

Behboodi, Arash

2016-08-15

Self interference (SI) in full duplex (FD) systems is the interference caused by the transmission stream on the reception stream. Being one of the main restrictive factors for performance of practical full duplex systems, however, not too much is known about its effect on the fundamental limits of relaying systems. In this work, we consider the full duplex three-node relay channel with SI where SI is modeled as an additive Gaussian noise whose variance is dependent on instantaneous input power. The classical achievable rates and upper bounds for the single three-node relay channel no longer apply due to the structure of SI. Achievable rates for Decode-and-Forward (DF) and Compress-and-Forward (CF) and upper bounds on the capacity are derived assuming Gaussian inputs and SI. The deterministic model is also introduced and its capacity is characterized. The optimal joint source-relay distributions is discussed. Numerical results are provided comparing the achievable rates and upper bound. © 2016 IEEE.

Generalized Gaussian Error Calculus

CERN Document Server

Grabe, Michael

2010-01-01

For the first time in 200 years Generalized Gaussian Error Calculus addresses a rigorous, complete and self-consistent revision of the Gaussian error calculus. Since experimentalists realized that measurements in general are burdened by unknown systematic errors, the classical, widespread used evaluation procedures scrutinizing the consequences of random errors alone turned out to be obsolete. As a matter of course, the error calculus to-be, treating random and unknown systematic errors side by side, should ensure the consistency and traceability of physical units, physical constants and physical quantities at large. The generalized Gaussian error calculus considers unknown systematic errors to spawn biased estimators. Beyond, random errors are asked to conform to the idea of what the author calls well-defined measuring conditions. The approach features the properties of a building kit: any overall uncertainty turns out to be the sum of a contribution due to random errors, to be taken from a confidence inter...

Incorporating Skew into RMS Surface Roughness Probability Distribution

Science.gov (United States)

Stahl, Mark T.; Stahl, H. Philip.

2013-01-01

The standard treatment of RMS surface roughness data is the application of a Gaussian probability distribution. This handling of surface roughness ignores the skew present in the surface and overestimates the most probable RMS of the surface, the mode. Using experimental data we confirm the Gaussian distribution overestimates the mode and application of an asymmetric distribution provides a better fit. Implementing the proposed asymmetric distribution into the optical manufacturing process would reduce the polishing time required to meet surface roughness specifications.

Few-body problem in terms of correlated Gaussians

Science.gov (United States)

Silvestre-Brac, Bernard; Mathieu, Vincent

2007-10-01

In their textbook, Suzuki and Varga [Stochastic Variational Approach to Quantum-Mechanical Few-Body Problems (Springer, Berlin, 1998)] present the stochastic variational method with the correlated Gaussian basis in a very exhaustive way. However, the Fourier transform of these functions and their application to the management of a relativistic kinetic energy operator are missing and cannot be found in the literature. In this paper we present these interesting formulas. We also give a derivation for formulations concerning central potentials.

Distributed Prognostic Health Management with Gaussian Process Regression

Science.gov (United States)

Saha, Sankalita; Saha, Bhaskar; Saxena, Abhinav; Goebel, Kai Frank

2010-01-01

Distributed prognostics architecture design is an enabling step for efficient implementation of health management systems. A major challenge encountered in such design is formulation of optimal distributed prognostics algorithms. In this paper. we present a distributed GPR based prognostics algorithm whose target platform is a wireless sensor network. In addition to challenges encountered in a distributed implementation, a wireless network poses constraints on communication patterns, thereby making the problem more challenging. The prognostics application that was used to demonstrate our new algorithms is battery prognostics. In order to present trade-offs within different prognostic approaches, we present comparison with the distributed implementation of a particle filter based prognostics for the same battery data.

Comparing Approaches to Deal With Non-Gaussianity of Rainfall Data in Kriging-Based Radar-Gauge Rainfall Merging

Science.gov (United States)

Cecinati, F.; Wani, O.; Rico-Ramirez, M. A.

2017-11-01

Merging radar and rain gauge rainfall data is a technique used to improve the quality of spatial rainfall estimates and in particular the use of Kriging with External Drift (KED) is a very effective radar-rain gauge rainfall merging technique. However, kriging interpolations assume Gaussianity of the process. Rainfall has a strongly skewed, positive, probability distribution, characterized by a discontinuity due to intermittency. In KED rainfall residuals are used, implicitly calculated as the difference between rain gauge data and a linear function of the radar estimates. Rainfall residuals are non-Gaussian as well. The aim of this work is to evaluate the impact of applying KED to non-Gaussian rainfall residuals, and to assess the best techniques to improve Gaussianity. We compare Box-Cox transformations with λ parameters equal to 0.5, 0.25, and 0.1, Box-Cox with time-variant optimization of λ, normal score transformation, and a singularity analysis technique. The results suggest that Box-Cox with λ = 0.1 and the singularity analysis is not suitable for KED. Normal score transformation and Box-Cox with optimized λ, or λ = 0.25 produce satisfactory results in terms of Gaussianity of the residuals, probability distribution of the merged rainfall products, and rainfall estimate quality, when validated through cross-validation. However, it is observed that Box-Cox transformations are strongly dependent on the temporal and spatial variability of rainfall and on the units used for the rainfall intensity. Overall, applying transformations results in a quantitative improvement of the rainfall estimates only if the correct transformations for the specific data set are used.

A novel construction of complex-valued Gaussian processes with arbitrary spectral densities and its application to excitation energy transfer.

Science.gov (United States)

Chen, Xin; Cao, Jianshu; Silbey, Robert J

2013-06-14

The recent experimental discoveries about excitation energy transfer (EET) in light harvesting antenna (LHA) attract a lot of interest. As an open non-equilibrium quantum system, the EET demands more rigorous theoretical framework to understand the interaction between system and environment and therein the evolution of reduced density matrix. A phonon is often used to model the fluctuating environment and convolutes the reduced quantum system temporarily. In this paper, we propose a novel way to construct complex-valued Gaussian processes to describe thermal quantum phonon bath exactly by converting the convolution of influence functional into the time correlation of complex Gaussian random field. Based on the construction, we propose a rigorous and efficient computational method, the covariance decomposition and conditional propagation scheme, to simulate the temporarily entangled reduced system. The new method allows us to study the non-Markovian effect without perturbation under the influence of different spectral densities of the linear system-phonon coupling coefficients. Its application in the study of EET in the Fenna-Matthews-Olson model Hamiltonian under four different spectral densities is discussed. Since the scaling of our algorithm is linear due to its Monte Carlo nature, the future application of the method for large LHA systems is attractive. In addition, this method can be used to study the effect of correlated initial condition on the reduced dynamics in the future.

Novel active contour model based on multi-variate local Gaussian distribution for local segmentation of MR brain images

Science.gov (United States)

Zheng, Qiang; Li, Honglun; Fan, Baode; Wu, Shuanhu; Xu, Jindong

2017-12-01

Active contour model (ACM) has been one of the most widely utilized methods in magnetic resonance (MR) brain image segmentation because of its ability of capturing topology changes. However, most of the existing ACMs only consider single-slice information in MR brain image data, i.e., the information used in ACMs based segmentation method is extracted only from one slice of MR brain image, which cannot take full advantage of the adjacent slice images' information, and cannot satisfy the local segmentation of MR brain images. In this paper, a novel ACM is proposed to solve the problem discussed above, which is based on multi-variate local Gaussian distribution and combines the adjacent slice images' information in MR brain image data to satisfy segmentation. The segmentation is finally achieved through maximizing the likelihood estimation. Experiments demonstrate the advantages of the proposed ACM over the single-slice ACM in local segmentation of MR brain image series.

Fluctuation relations with intermittent non-Gaussian variables.

Science.gov (United States)

Budini, Adrián A

2011-12-01

Nonequilibrium stationary fluctuations may exhibit a special symmetry called fluctuation relations (FRs). Here, we show that this property is always satisfied by the subtraction of two random and independent variables related by a thermodynamiclike change of measure. Taking one of them as a modulated Poisson process, it is demonstrated that intermittence and FRs are compatible properties that may coexist naturally. Strong non-Gaussian features characterize the probability distribution and its generating function. Their associated large deviation functions develop a "kink" at the origin and a plateau regime respectively. Application of this model in different stationary nonequilibrium situations is discussed.

MCEM algorithm for the log-Gaussian Cox process

OpenAIRE

Delmas, Celine; Dubois-Peyrard, Nathalie; Sabbadin, Regis

2014-01-01

Log-Gaussian Cox processes are an important class of models for aggregated point patterns. They have been largely used in spatial epidemiology (Diggle et al., 2005), in agronomy (Bourgeois et al., 2012), in forestry (Moller et al.), in ecology (sightings of wild animals) or in environmental sciences (radioactivity counts). A log-Gaussian Cox process is a Poisson process with a stochastic intensity depending on a Gaussian random eld. We consider the case where this Gaussian random eld is ...

Studies of absorbed dose determinations and spatial dose distributions for high energy proton beams

International Nuclear Information System (INIS)

Hiraoka, Takeshi

1982-01-01

Absolute dose determinations were made with three types of ionization chamber and a Faraday cup. Methane based tissue equivalent (TE) gas, nitrogen, carbon dioxide, air were used as an ionizing gas with flow rate of 10 ml per minute. Measurements were made at the entrance position of unmodulated beams and for a beam of a spread out Bragg peak at a depth of 17.3 mm in water. For both positions, the mean value of dose determined by the ionization chambers was 0.993 +- 0.014 cGy for which the value of TE gas was taken as unity. The agreement between the doses estimated by the ionization chambers and the Faraday cup was within 5%. Total uncertainty estimated in the ionization chamber and the Faraday cup determinations is 6 and 4%, respectively. Common sources of error in calculating the dose from ionization chamber measurements are depend on the factors of ion recombination, W value, and mass stopping power ratio. These factors were studied by both experimentally and theoretically. The observed values for the factors show a good agreement to the predicted one. Proton beam dosimetry intercomparison between Japan and the United States was held. Good agreement was obtained with standard deviation of 1.6%. The value of the TE calorimeter is close to the mean value of all. In the proton spot scanning system, lateral dose distributions at any depth for one spot beam can be simulated by the Gaussian distribution. From the Gaussian distributions and the central axis depth doses for one spot beam, it is easy to calculate isodose distributions in the desired field by superposition of dose distribution for one spot beam. Calculated and observed isodose curves were agreed within 1 mm at any dose levels. (J.P.N.)

'The formula that killed Wall Street': the Gaussian copula and modelling practices in investment banking.

Science.gov (United States)

MacKenzie, Donald; Spears, Taylor

2014-06-01

Drawing on documentary sources and 114 interviews with market participants, this and a companion article discuss the development and use in finance of the Gaussian copula family of models, which are employed to estimate the probability distribution of losses on a pool of loans or bonds, and which were centrally involved in the credit crisis. This article, which explores how and why the Gaussian copula family developed in the way it did, employs the concept of 'evaluation culture', a set of practices, preferences and beliefs concerning how to determine the economic value of financial instruments that is shared by members of multiple organizations. We identify an evaluation culture, dominant within the derivatives departments of investment banks, which we call the 'culture of no-arbitrage modelling', and explore its relation to the development of Gaussian copula models. The article suggests that two themes from the science and technology studies literature on models (modelling as 'impure' bricolage, and modelling as articulating with heterogeneous objectives and constraints) help elucidate the history of Gaussian copula models in finance.

SNR Estimation in Linear Systems with Gaussian Matrices

KAUST Repository

Suliman, Mohamed Abdalla Elhag; Alrashdi, Ayed; Ballal, Tarig; Al-Naffouri, Tareq Y.

2017-01-01

This letter proposes a highly accurate algorithm to estimate the signal-to-noise ratio (SNR) for a linear system from a single realization of the received signal. We assume that the linear system has a Gaussian matrix with one sided left correlation. The unknown entries of the signal and the noise are assumed to be independent and identically distributed with zero mean and can be drawn from any distribution. We use the ridge regression function of this linear model in company with tools and techniques adapted from random matrix theory to achieve, in closed form, accurate estimation of the SNR without prior statistical knowledge on the signal or the noise. Simulation results show that the proposed method is very accurate.

SNR Estimation in Linear Systems with Gaussian Matrices

KAUST Repository

Suliman, Mohamed Abdalla Elhag

2017-09-27

This letter proposes a highly accurate algorithm to estimate the signal-to-noise ratio (SNR) for a linear system from a single realization of the received signal. We assume that the linear system has a Gaussian matrix with one sided left correlation. The unknown entries of the signal and the noise are assumed to be independent and identically distributed with zero mean and can be drawn from any distribution. We use the ridge regression function of this linear model in company with tools and techniques adapted from random matrix theory to achieve, in closed form, accurate estimation of the SNR without prior statistical knowledge on the signal or the noise. Simulation results show that the proposed method is very accurate.

Distributed Wireless Power Transfer With Energy Feedback

Science.gov (United States)

Lee, Seunghyun; Zhang, Rui

2017-04-01

Energy beamforming (EB) is a key technique for achieving efficient radio-frequency (RF) transmission enabled wireless energy transfer (WET). By optimally designing the waveforms from multiple energy transmitters (ETs) over the wireless channels, they can be constructively combined at the energy receiver (ER) to achieve an EB gain that scales with the number of ETs. However, the optimal design of EB waveforms requires accurate channel state information (CSI) at the ETs, which is challenging to obtain practically, especially in a distributed system with ETs at separate locations. In this paper, we study practical and efficient channel training methods to achieve optimal EB in a distributed WET system. We propose two protocols with and without centralized coordination, respectively, where distributed ETs either sequentially or in parallel adapt their transmit phases based on a low-complexity energy feedback from the ER. The energy feedback only depends on the received power level at the ER, where each feedback indicates one particular transmit phase that results in the maximum harvested power over a set of previously used phases. Simulation results show that the two proposed training protocols converge very fast in practical WET systems even with a large number of distributed ETs, while the protocol with sequential ET phase adaptation is also analytically shown to converge to the optimal EB design with perfect CSI by increasing the training time. Numerical results are also provided to evaluate the performance of the proposed distributed EB and training designs as compared to other benchmark schemes.

Fast pencil beam dose calculation for proton therapy using a double-Gaussian beam model

Directory of Open Access Journals (Sweden)

Joakim eda Silva

2015-12-01

Full Text Available The highly conformal dose distributions produced by scanned proton pencil beams are more sensitive to motion and anatomical changes than those produced by conventional radiotherapy. The ability to calculate the dose in real time as it is being delivered would enable, for example, online dose monitoring, and is therefore highly desirable. We have previously described an implementation of a pencil beam algorithm running on graphics processing units (GPUs intended specifically for online dose calculation. Here we present an extension to the dose calculation engine employing a double-Gaussian beam model to better account for the low-dose halo. To the best of our knowledge, it is the first such pencil beam algorithm for proton therapy running on a GPU. We employ two different parametrizations for the halo dose, one describing the distribution of secondary particles from nuclear interactions found in the literature and one relying on directly fitting the model to Monte Carlo simulations of pencil beams in water. Despite the large width of the halo contribution, we show how in either case the second Gaussian can be included whilst prolonging the calculation of the investigated plans by no more than 16%, or the calculation of the most time-consuming energy layers by about 25%. Further, the calculation time is relatively unaffected by the parametrization used, which suggests that these results should hold also for different systems. Finally, since the implementation is based on an algorithm employed by a commercial treatment planning system, it is expected that with adequate tuning, it should be able to reproduce the halo dose from a general beam line with sufficient accuracy.

Stable radiation pressure acceleration of ions by suppressing transverse Rayleigh-Taylor instability with multiple Gaussian pulses

Energy Technology Data Exchange (ETDEWEB)

Zhou, M. L.; Liu, B.; Hu, R. H.; Shou, Y. R.; Lin, C.; Lu, H. Y.; Lu, Y. R.; Ma, W. J., E-mail: wenjun.ma@pku.edu.cn [State Key Laboratory of Nuclear Physics and Technology, and Key Laboratory of HEDP of the Ministry of Education, CAPT, Peking University, Beijing 100871 (China); Gu, Y. Q. [Laser Fusion Research Center, China Academy of Engineering Physics, Mianyang, Sichuan 621900 (China); Yan, X. Q., E-mail: x.yan@pku.edu.cn [State Key Laboratory of Nuclear Physics and Technology, and Key Laboratory of HEDP of the Ministry of Education, CAPT, Peking University, Beijing 100871 (China); Collaborative Innovation Center of Extreme Optics, Shanxi University, Taiyuan, Shanxi 030006 (China)

2016-08-15

In the case of a thin plasma slab accelerated by the radiation pressure of an ultra-intense laser pulse, the development of Rayleigh-Taylor instability (RTI) will destroy the acceleration structure and terminate the acceleration process much sooner than theoretical limit. In this paper, a new scheme using multiple Gaussian pulses for ion acceleration in a radiation pressure acceleration regime is investigated with particle-in-cell simulation. We found that with multiple Gaussian pulses, the instability could be efficiently suppressed and the divergence of the ion bunch is greatly reduced, resulting in a longer acceleration time and much more collimated ion bunch with higher energy than using a single Gaussian pulse. An analytical model is developed to describe the suppression of RTI at the laser-plasma interface. The model shows that the suppression of RTI is due to the introduction of the long wavelength mode RTI by the multiple Gaussian pulses.

Characterisation of random Gaussian and non-Gaussian stress processes in terms of extreme responses

Directory of Open Access Journals (Sweden)

Colin Bruno

2015-01-01

Full Text Available In the field of military land vehicles, random vibration processes generated by all-terrain wheeled vehicles in motion are not classical stochastic processes with a stationary and Gaussian nature. Non-stationarity of processes induced by the variability of the vehicle speed does not form a major difficulty because the designer can have good control over the vehicle speed by characterising the histogram of instantaneous speed of the vehicle during an operational situation. Beyond this non-stationarity problem, the hard point clearly lies in the fact that the random processes are not Gaussian and are generated mainly by the non-linear behaviour of the undercarriage and the strong occurrence of shocks generated by roughness of the terrain. This non-Gaussian nature is expressed particularly by very high flattening levels that can affect the design of structures under extreme stresses conventionally acquired by spectral approaches, inherent to Gaussian processes and based essentially on spectral moments of stress processes. Due to these technical considerations, techniques for characterisation of random excitation processes generated by this type of carrier need to be changed, by proposing innovative characterisation methods based on time domain approaches as described in the body of the text rather than spectral domain approaches.

Stochastic differential calculus for Gaussian and non-Gaussian noises: A critical review

Science.gov (United States)

Falsone, G.

2018-03-01

In this paper a review of the literature works devoted to the study of stochastic differential equations (SDEs) subjected to Gaussian and non-Gaussian white noises and to fractional Brownian noises is given. In these cases, particular attention must be paid in treating the SDEs because the classical rules of the differential calculus, as the Newton-Leibnitz one, cannot be applied or are applicable with many difficulties. Here all the principal approaches solving the SDEs are reported for any kind of noise, highlighting the negative and positive properties of each one and making the comparisons, where it is possible.

Tailored ion energy distributions on plasma electrodes

International Nuclear Information System (INIS)

Economou, Demetre J.

2013-01-01

As microelectronic device features continue to shrink approaching atomic dimensions, control of the ion energy distribution on the substrate during plasma etching and deposition becomes increasingly critical. The ion energy should be high enough to drive ion-assisted etching, but not too high to cause substrate damage or loss of selectivity. In many cases, a nearly monoenergetic ion energy distribution (IED) is desired to achieve highly selective etching. In this work, the author briefly reviews: (1) the fundamentals of development of the ion energy distribution in the sheath and (2) methods to control the IED on plasma electrodes. Such methods include the application of “tailored” voltage waveforms on an electrode in continuous wave plasmas, or the application of synchronous bias on a “boundary electrode” during a specified time window in the afterglow of pulsed plasmas

Intra-individual response variability assessed by ex-gaussian analysis may be a new endophenotype for Attention Deficit / Hyperactivity Disorder

Directory of Open Access Journals (Sweden)

Marcela Patricia Henríquez-Henríquez

2015-01-01

Full Text Available Intra-individual variability of Response Times (RTisv is considered as potential endophenotype for Attentional Deficit/Hyperactivity Disorder (ADHD. Traditional methods for estimating RTisv lose information regarding Response Times (RTs distribution along the task, with eventual effects on statistical power. Ex-Gaussian analysis captures the dynamic nature of RTisv, estimating normal and exponential components for RT distribution, with specific phenomenological correlates. Here, we applied ex-Gaussian analysis to explore whether intra-individual variability of RTs agrees with criteria proposed by Gottesman and Gould for endophenotypes. Specifically, we evaluated if Normal and/or exponential components of RTs may a Present the stair-like distribution expected for endophenotypes (ADHD>Siblings>Typically Developing children (TD without familiar history of ADHD and b Represent a phenotypic correlate for previously described genetic risk variants. This is a pilot study including 55 subjects (20 ADHD-discordant sibling-pairs and 15 TD children, all aged between 8 and 13 years. Participants resolved a visual Go/Nogo with 10% Nogo probability. Ex-Gaussian distributions were fitted to individual RT data and compared among the three samples. In order to test whether intra-individual variability may represent a correlate for previously described genetic risk variants, VNTRs at DRD4 and SLC6A3 were identified in all sibling pairs following standard protocols. Groups were compared adjusting independent general linear models for the exponential and normal components from the ex-gaussian analysis. Identified trends were confirmed by the non-parametric Jonckheere-Terpstra test. Stair-like distributions were observed for μ (p=0.036 and σ (p=0.009. An additional DRD4-genotype X clinical status interaction was present for τ (p=0,014 reflecting a possible severity factor. Thus, Normal and exponential RTisv components are suitable as ADHD endophenotypes.

Distributed optimal coordination for distributed energy resources in power systems

DEFF Research Database (Denmark)

Wu, Di; Yang, Tao; Stoorvogel, A.

2017-01-01

Driven by smart grid technologies, distributed energy resources (DERs) have been rapidly developing in recent years for improving reliability and efficiency of distribution systems. Emerging DERs require effective and efficient coordination in order to reap their potential benefits. In this paper......, we consider an optimal DER coordination problem over multiple time periods subject to constraints at both system and device levels. Fully distributed algorithms are proposed to dynamically and automatically coordinate distributed generators with multiple/single storages. With the proposed algorithms...

Distributed Energy Resource (DER) Cybersecurity Standards

Energy Technology Data Exchange (ETDEWEB)

Saleem, Danish [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Johnson, Jay [Sandia National Laboratories

2017-11-08

This presentation covers the work that Sandia National Laboratories and National Renewable Energy Laboratory are doing for distributed energy resource cybersecurity standards, prepared for NREL's Annual Cybersecurity & Resilience Workshop on October 9-10, 2017.

Probabilistic behavior analysis of a sandwiched buckled beam under Gaussian white noise with energy harvesting perspectives

International Nuclear Information System (INIS)

Mokem Fokou, I.S.; Nono Dueyou Buckjohn, C.; Siewe Siewe, M.; Tchawoua, C.

2016-01-01

In this paper, a sandwiched buckled beam with axial compressive force under Gaussian white noise is considered as a piezoelectric energy harvester. A stochastic averaging method is proposed to analytically predict the system’s response, the stability and the estimation of system’s reliability. By using the generalized harmonic transformation, the Itô differential equations with respect to the mechanical and electrical amplitude are derived through this technique. From these differential equations, we construct the Fokker–Plank–Kolmogorov equation for the electrical and mechanical subsystem where the solution of each equation in the stationary state is a probability density. The mean first passage time (MFPT) is numerically provided in order to study the attractor stability(stable equilibrium point observed in the effective potential) which give rise to the noise-enhanced stability(NES) phenomenon. The mean square response and voltage are obtained for different white noise intensities and others system parameters. The effects of linear damping and noise intensity on the mean square voltage are investigated. We notice that harvested energy can be enhanced by suitable choice of noise intensity and others system parameters. In additional, by combining the random signal with harmonic excitation, the stochastic resonance(SR) phenomenon is observed via the mean residence time(TMR) which give rise to the large amplitude of vibrations and consequently, an optimization of harvested energy. The agreements between the analytical method and those obtained numerically validate the effectiveness of analytical investigations.

Loop corrections to primordial non-Gaussianity

Science.gov (United States)

Boran, Sibel; Kahya, E. O.

2018-02-01

We discuss quantum gravitational loop effects to observable quantities such as curvature power spectrum and primordial non-Gaussianity of cosmic microwave background (CMB) radiation. We first review the previously shown case where one gets a time dependence for zeta-zeta correlator due to loop corrections. Then we investigate the effect of loop corrections to primordial non-Gaussianity of CMB. We conclude that, even with a single scalar inflaton, one might get a huge value for non-Gaussianity which would exceed the observed value by at least 30 orders of magnitude. Finally we discuss the consequences of this result for scalar driven inflationary models.

Phase space structure of generalized Gaussian cat states

International Nuclear Information System (INIS)

Nicacio, Fernando; Maia, Raphael N.P.; Toscano, Fabricio; Vallejos, Raul O.

2010-01-01

We analyze generalized Gaussian cat states obtained by superposing arbitrary Gaussian states. The structure of the interference term of the Wigner function is always hyperbolic, surviving the action of a thermal reservoir. We also consider certain superpositions of mixed Gaussian states. An application to semiclassical dynamics is discussed.

Prediction and retrodiction with continuously monitored Gaussian states

DEFF Research Database (Denmark)

Zhang, Jinglei; Mølmer, Klaus

2017-01-01

Gaussian states of quantum oscillators are fully characterized by the mean values and the covariance matrix of their quadrature observables. We consider the dynamics of a system of oscillators subject to interactions, damping, and continuous probing which maintain their Gaussian state property......(t)$ to Gaussian states implies that the matrix $E(t)$ is also fully characterized by a vector of mean values and a covariance matrix. We derive the dynamical equations for these quantities and we illustrate their use in the retrodiction of measurements on Gaussian systems....

Distributed Energy Resources Test Facility

Data.gov (United States)